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HomeMy Public PortalAboutVol_3_CanyonSpringsFEIR_AppB_RDEIRCommentLettersCanyon Springs Final EIR October 2015 | Prepared For: Town of Truckee Technical Appendices | Volume 3 of 4 Canyon Springs Final EIR October 2015 | Prepared For: Town of Truckee Technical Appendices | Volume 3 of 4 Orange County • Northern California • Los Angeles/Downtown • Los Angeles/West • Inland Empire • San Diego 1625 Shattuck Avenue, Suite 300 | Berkeley, California 94709 | 510.848.3815 | 510.848.4315 (f)www.placeworks.com ........................................................................................................................ A PPENDIX B C OMMENT L ETTERS ON THE R EVISED D RAFT EIR ........................................................................................................................ APPENDIX B LIST OF COMMENTERS Comments on the Revised Draft EIR were received from the following agencies and service providers, and private individuals and organizations. Each comment letter has been assigned a number, as indicated below. A. Agencies and Service Providers A10 Raymond Brown, District Engineer, Truckee Sanitary District. October 6, 2014 A11 Sanna Schlosser, Electrical Engineer, Truckee Donner Public Utility District. October 13, 2014 A12 Jason A. Parker, Engineering Department Manager, Tahoe-Truckee Sanitation Agency, November 11, 2014. A13 Tina Bartlett, Regional Manager, California Department of Fish and Wildlife, November 20, 2014 A14 Steve Castleberry, County of Nevada Community Development Agency, Department of Public Works, November 21, 2014 A15 Scott Morgan, Governor's Office of Planning and Research, State Clearinghouse and Planning Unit, November 21, 2014 B. Private Individuals and Organizations B68 Maxine Rix. October 11, 2014 B69 Martha L. Janer. October 13, 2014 B70 Katherine Hayes Rodriguez. October 15, 2014 B71 Kelly Romer. October 20, 2014 B72 Ted Thompson. October 23, 2014 B73 Michael McNab. October 27, 2014 B74 Karen LaFarge-Unrein. October 28, 2014 B75 Janet R. Phillips. October 28, 2014 B76 Jean Brooks. October 30, 2014 B77 John Black. November 1, 2014 B78 Pamela Stock. November 8, 2014 B79 Greg Brooks. November 10, 2014 B80 Brigitte Kaneda. November 11, 2014 B81 Pamela Eisele. November 11, 2014 B82 Janet Atkinson. November 11, 2014 B83 Mike Starrett. November 14, 2014 B84 Barbara Sullivan. November 14, 2014 B85 Eva Stramer Nichols. November 17, 2014 B86 Karen A. Foster. November 17, 2014 B87 Mary-Anne Carley. November 17, 2014 B88 Miriam Hoffman. November 17, 2014 B89 Ursula Riina. November 17, 2014 B90 Sky Rondenet. November 17, 2014 APPENDIX B LIST OF COMMENTERS B91 Charles and Dale Timinsky, et al. November 17, 2014 B92 Caryn Dombroski. November 17, 2014 B93 Steve and Diana Yale. November 18, 2014 B94 Mike Kreton. November 18, 2014 B95 Mary Rondenet-Vieth. November 18, 2014 B96 Jim Vieth. November 18, 2014 B97 Sara Taddo Jones. November 19, 2014 B98 Jennifer Bloomfield. November 19, 2014 B99 Nedra Benites. November 19, 2014 B100 Ken Weakley, Mike Sabarese and Dave Giacomini, The Meadows Homeowners Association. November 19, 2014 B101 John and Carol Pratt. November 19, 2014 B102 Jason S. Adams. November 19, 2014 B103 Robert H. Moore Jr. November 19, 2014 B104 Jennifer Goldberg. November 20, 2014 B105 Leigh Golden. November 20, 2014 B106 Ellison Folk and Carmen J. Borg, Mountain Area Preservation Foundation and Saving Open Space around Glenshire. November 20, 2014 B107 Brendan Riley. November 19, 2014 B108 Brendan Riley. November 20, 2014 B109 Martha Frantz. November 20, 2014 B110 Josh and Gina Evans. November 20, 2014 B111 Nikki Riley, Mountain Area Preservation. November 20, 2014 B112 Linda Stoner. November 20, 2014 B113 Mark Bunge and Tanja Hester. November 20, 2014 B114 Kathy Echols. November 20, 2014 B115 Glenshire Devonshire Residents Association. November 20, 2014 B116 Sandy Korth. November 20, 2014 B117 Dale Creighton, Martin D. Wood, John Heal, Greg C. Gatto, Whit Manley and Christopher Huck. November 20, 2014 B118 John Heal. November 20, 2014 B119 Ray Butler. November 20, 2014 B120 Kris Kuyper. November 20, 2014 B121 Neil Pankler. November 20, 2014 B122 Jan Zabriskie. November 20, 2014 B123 Lori Kelley. November 20, 2014 B124 Lisa Wallace. November 20, 2014 B125 George Lake. November 20, 2014 APPENDIX B LIST OF COMMENTERS B126 Lisa Holan. November 21, 2014 B127 John Eisele. November 21, 2014 B128 Allison Pedley. November 21, 2014 B129 Lisa Holan. November 21, 2014 B130 Jacqui Zink. November 21, 2014 B131 Adrian Juncosa. November 21, 2014 B132 Peter Bowers and Martha Janer. November 21, 2014 B133 Marianne Ryan. November 21, 2014 B134 Joshua Dubansky, M.D. October 14, 2014 February 20, 2013 Ms. Carmen Borg, AICP Shute, Mihaly & Weinberger LLP 396 Hayes Street San Francisco, California 94102 Subject: Review of Transportation and Traffic Impact Analysis Draft Environmental Impact Report – Canyon Springs, Truckee, California Dear Ms. Borg: As requested, MRO Engineers, Inc., has completed a review of the “Transportation and Traffic” analysis completed with respect to the proposed Canyon Springs project in Truckee, California. The proposed project is the subject of a Draft Environmental Impact Report (DEIR) prepared by The Planning Center/DCE in December 2012. The DEIR incorporates (as Appendix I) a traffic impact analysis prepared by LSC Transportation Consultants, Inc. [Reference: LSC Transportation Consultants, Inc., Canyon Springs Traffic Impact Analysis, August 27, 2012.] Our review focused on the adequacy of the “Transportation and Traffic” section of the DEIR, including the detailed procedures and conclusions documented in the LSC report. Transportation and Traffic Impact Analysis Review Our review of the project’s traffic impact analysis revealed a number of significant traffic impacts that were not disclosed or mitigated in the DEIR and that should be addressed prior to certification of the environmental document by the Town of Truckee. These issues are summarized below. 1. No Analysis of Potential Freeway System Impacts – The Canyon Springs traffic impact analysis addresses conditions at eight intersections (including one future intersection) and eleven roadway segments. Among the intersections included in the analysis are I-80 Eastbound Ramps/Hirschdale Road and I-80 Westbound Ramps/Hirschdale Road. DEIR Figure 4.14-4 (p. 4.14-32) illustrates the “2011 Project Generated PM Traffic Volumes.” Review of that figure reveals that a total of 91 PM peak-hour project-generated trips were assigned to/from the west on I-80 at the Hirschdale Road ramps. Those 91 trips represent 35 percent of the total project trip generation in the PM peak hour. In that same PM peak-hour period, 64 project-related trips (25 percent of the project-generated total) were assigned to/from the east on I-80 at the Hirschdale Road ramps. DEIR Figure 4.14-5 (p. 4.14-33) illustrates similar information for the year 2031. A total of 101 project-related trips (39 percent of the total) were assigned to/from west on I-80 in the PM peak hour, and 47 project trips (18 percent of the total) were assigned to/from the east. Despite the fact that I-80 was projected to carry a substantial portion of the traffic generated by the proposed project, no analysis was conducted to assess potential project-related traffic impacts at any of the on- or off-ramps or the merge/diverge points where the ramps meet the freeway mainline. Further, no analysis of project-related impacts on the I-80 mainline was performed. M R O ENGINEERS 2202 Plaza Drive Rocklin, California 95765-4404 PHONE (916) 783-3838 FAX (916) 783-5003 Ms. Carmen Borg February 20, 2013 Page 2 Consequently, it is impossible to determine whether the proposed project will adversely impact traffic operations on the freeway facilities. To ensure a thorough analysis of potential traffic impacts, it is essential that these analyses be performed and documented in a revised DEIR. 2. Level of Service Calculation Methodology – Town of Truckee General Plan Policy CIR-P3.1 requires that, “. . . level of service shall be computed according to the planning methodology documented in Special Report 209: Highway Capacity Manual, published by the Transportation Research Board in 2000, or as amended in subsequent updates.” [DEIR p. 4.14-6] The reference to “subsequent updates” is important, in that the year 2010 version of the Highway Capacity Manual (HCM 2010) was released on April 11, 2011. In this regard, the LSC report (p. 32) states: “The 2010 Highway Capacity Manual was released subsequent to commencement of this traffic analysis. The HCM 2010 methodology was used in the evaluation of the Donner Pass Road/Glenshire Drive intersection, as applied in the Highway Capacity Software 2010 (HCS 2010) software package developed by McTrans Center at the University of Florida.” This raises the obvious question: If HCM 2010 could be used for the Donner Pass Road/Glenshire Drive intersection, why could it not be used for the other locations included in the traffic analysis? We also note that data collection for the study occurred at the I-80/Hirschdale Road interchange on July 8, 2011, which is about three months after the HCM 2010 release date. (See LSC report, p. 7) Also, delay counts were performed at Glenshire Drive/Donner Pass Road on Friday, August 5, 2011. Clearly, the 2010 update to the Highway Capacity Manual was available at the time that the analysis was initiated (or, certainly, in the earliest stages of the analysis, prior to the conduct of any level of service calculations). The failure to use the latest version of the Highway Capacity Manual represents a violation of the Town of Truckee General Plan. The level of service calculations must be redone using the current methodology, and the results must be provided for public review in a revised DEIR. 3. Analysis Periods – The analysis largely focuses on traffic operations in the PM peak hour, although AM peak-hour analyses were performed at four of the eight study intersections. AM peak hour impacts were only analyzed at Glenshire Drive/Donner Pass Road, as well as three intersections (Glenshire Drive at Dorchester (West), Somerset, and Whitehorse/Martis Peak) where traffic patterns were judged to be influenced by activity at the nearby Glenshire Elementary School. Although it might be true that, in general, PM peak hour volumes are greater than AM peak hour volumes, this does not eliminate the possibility that additional significant impacts will be found in the AM. Directional traffic patterns are different in the two peak-hour periods, so that problems that may not be apparent in the PM peak hour are revealed in the AM peak hour. For example, left turns are often the critical consideration in intersection operations. Project- generated traffic will be added to different left-turn movements in the AM and PM peak hours. By analyzing only the PM peak hour, any related AM peak hour impacts will be missed. M R O ENGINEERS Ms. Carmen Borg February 20, 2013 Page 3 DEIR Table 4.14-6 summarizes the volume of traffic that the project will generate in the AM and PM peak hours. While it is true that the number of PM peak-hour trips exceeds the AM peak-hour value, the volume of project-related trips in the AM peak hour is substantial – 194 total trips. Of those trips, 148 will be outbound from the project site. In comparison, the peak direction trip number in the PM peak hour is 164 (inbound) trips, which is only 16 trips greater than the peak directional trip value in the AM peak hour. Although we recognize that the Town of Truckee has adopted a policy requiring that only the PM peak hour impacts be evaluated, CEQA requires that all significant impacts associated with the proposed project be revealed in the DEIR. Given that the AM and PM peak-hour trip generation values for the project are not substantially different and that different traffic flow patterns exist in the AM and PM peak hours, we believe there is a reasonable likelihood that significant impacts might be found in the AM peak hour that differ from those identified in the PM peak hour. The only way to verify this, of course, is to perform AM peak hour analyses and document the results of those analyses in a revised DEIR. 4. Peak Hour Traffic Volume Data – Pages 5 - 7 of the LSC Transportation Consultants report describe the derivation of the “existing” conditions traffic volumes. (This information is not provided in the DEIR.) Page 6 of the LSC report says, “Year 2011 peak-hour intersection turning movement volumes were estimated at the study intersections as described below.” That estimation process is summarized here: • At three locations (Glenshire Drive/Donner Pass Road, Glenshire Drive/Dorchester Drive (West), and Glenshire Drive/Whitehorse Road/Martis Peak Road) PM peak-hour counts performed in 2009 were increased using a two percent per year growth factor to estimate values for 2011. • At Glenshire Drive/Somerset Drive and Glenshire Drive/Hirschdale Road, the year 2011 volumes were based on counts conducted in March 2004. Those old counts were first adjusted to approximate Summer 2004 values, then were further manipulated to represent estimated Summer 2009 traffic volumes. A two percent per year growth factor was then applied to those fabricated numbers to estimate 2011 traffic volumes. • The AM peak-hour volumes at the Glenshire Drive/Donner Pass Road intersection were based on counts conducted in July 2004. Those volumes were adjusted upward to represent estimated 2009 values, which were subsequently increased further using the two percent per year growth factor. Only the intersections that were judged to be affected by school traffic patterns were actually counted at the time the study was initiated. In every other case, the “existing conditions” traffic volumes were fabricated from data as much as seven years old when the study began. The traffic analysis claims that the resulting traffic volume estimates are “conservative,” but there is no way to know if this is actually the case. DEIR p. 4.14-17 says: “These volumes are considered to be conservative, given that a comparison of the 2006 to 2009 PM peak-hour traffic volumes through the Donner Pass Road/Glenshire Drive intersection indicates no growth in the total intersection volume.” Of course, the 2011 volumes used in the analysis were not based on 2006 volumes; they were based M R O ENGINEERS Ms. Carmen Borg February 20, 2013 Page 4 on either 2004 or 2009 volumes. The comparison of 2009 volumes to 2006 volumes obviously ignores what might have happened between 2004 and 2006, as well as from 2009 to 2011. Also, we note that this conclusion is based on traffic volumes at one location at the extreme west end of the study area, which might not be representative of what has happened elsewhere within the study area. With regard to the Town’s policy calling for analysis of the tenth-highest summer PM peak hour, we would suggest that a better approach for this study would have been to perform Summer 2011 counts and adjust those as necessary to represent the tenth-highest hour. This is vastly superior to basing the Summer 2011 volumes on counts conducted in the spring or summer of 2004. In short, it is a substantial concern that the bulk of the “existing” intersection traffic volumes were estimated, rather than based on recent data collection. This is quite unusual, and the resulting estimates may not accurately represent current conditions in Truckee. Moreover, because these estimated traffic volumes represent the most critical input parameter in the intersection level of service calculation process, any inaccuracies in those values directly affects the validity of the level of service results. In short, to the extent that the estimated peak- hour traffic volumes are inaccurate, the corresponding level of service results reported in the DEIR are invalid, and a misleading representation of the environmental setting is provided.. 5. Daily Traffic Volume Data – The daily traffic volumes used in the analysis of roadway segments were also estimated, rather than counted. In this case, the margin of error associated with the daily traffic volumes is potentially even greater, given that the daily volume estimates are based on estimates of peak-hour traffic. That is, the estimates were estimated based on other estimates. Specifically, the “existing” daily traffic volumes were estimated from the peak-hour volumes (derived as described above) by applying a factor ranging from 9.5 to 10.6. This is somewhat puzzling, as the study apparently began in the spring or summer of 2011, since counts were performed at the I-80/Hirschdale Road interchange in July 2011. Consequently, summer counts could have been conducted as part of this study. [See LSC report, p. 6 – 7] Again, we must question the validity of the fabricated “existing” traffic volumes. 6. Cumulative Conditions Traffic Volume Estimates – The cumulative conditions analysis presented in the DEIR addresses projected traffic operations in the year 2031. However, as described on p. 4.14-20 of the DEIR, the year 2031 traffic volumes are actually year 2025 traffic volume projections. That is, the Town of Truckee’s TransCAD travel demand forecasting model was used to create estimates of traffic in the year 2025, and “[n]o further growth in traffic is assumed between 2025 and 2031.” [DEIR, p. 4.14-20] Thus, zero traffic growth was assumed for six of the twenty years included in the cumulative conditions analysis. Even though the year 2025 traffic projections represent buildout of the Truckee General Plan [DEIR, p. 4.14-20], the approach employed in the analysis fails to account for General Plan amendments that might be approved in the next twelve years. Similarly, it fails to reflect traffic increases associated with growth beyond Truckee’s boundaries, which would not be reflected in the General Plan land use. M R O ENGINEERS Ms. Carmen Borg February 20, 2013 Page 5 The use of 2025 traffic volume projections is inappropriate unless the analysis is described as being for that year. To suggest that the analysis covers a twenty-year time period when it actually considers only fourteen years is misleading. The cumulative conditions analysis must be revised using valid estimates of year 2031 traffic volumes, then recirculated for public review. 7. Safety Analysis – DEIR Table 4.14-5 (p. 4.14-26) and the related text provide “Historical Accident Data” (including accident rates per million-vehicle-miles for roadway segments and million-vehicle-movements for intersections) for the seven locations (three intersections and four roadway segments) included in the safety analysis. The DEIR, though, provides no assessment of whether the derived accident rates indicate an existing safety problem. On the other hand, the LSC report (pp. 7 – 12) supplements the historical accident data with a comparison to California and Nevada County average accident rates for similar roads. In six of the seven cases, the historical accident rates are substantially higher than those averages, as summarized in Table 1 below. It is substantial concern that the DEIR failed to include this important information, which directly indicates that a considerable safety problem exists in the study area today. The failure to include this information in the body of the DEIR effectively defeats the purpose of the report as an informational document. Although we acknowledge that the information was presented in an appendix to the DEIR, we believe that a finding directly relating to the safety of the residents of the study area should be afforded greater prominence. Moreover, given the existence of this safety issue, a greater effort should have been made to address the potential impacts of the proposed project. Will the additional traffic generated by the project exacerbate this existing deficiency? Specifically, will the residents of the area be subject to a greater likelihood of being involved in a potentially injury-causing collision as a result of implementation of the proposed project? The DEIR must be revised to include a detailed analysis of project-related safety impacts and to identify needed mitigation measures. M R O ENGINEERS M R O ENGINEERS Ms. Carmen Borg February 20, 2013 Page 6 Table 1 Study Area Accident Experience (2006 – 2010)1 Location Actual Accident Rate2 Caltrans Average Accident Rate2 Does Actual Rate Exceed Caltrans Average? Nevada County Average Accident Rate2 Does Actual Rate Exceed Nevada County Average? Intersections Glenshire Dr./Donner Pass Rd.3 0.52 0.20 Yes N.A.4 N.A. Glenshire Dr./Dorchester Dr. 0.38 0.20 Yes N.A. N.A. Glenshire Dr./Martis Peak Rd./Whitehorse Rd. 0.0 0.20 No N.A. N.A. Roadways Glenshire Dr. through residential subdivision5 1.11 0.97 Yes 1.04 Yes Glenshire Dr. between Martis Peak Rd. and Hirschdale Rd.6 1.98 0.97 Yes 1.04 Yes Hirschdale Rd. between Glenshire Dr. and I-807 2.61 0.97 Yes 1.04 Yes Edinburgh Dr./Regency Cir./ Courtenay Ln./Somerset Dr. 1.54 0.97 Yes 1.04 Yes Notes: 1 Source: LSC Transportation Consultants, Inc., Canyon Springs Traffic Impact Analysis, August 27, 2012, Table 2, p. 11. 2 Accidents per million-vehicle-movements for intersections and accidents per million- vehicle-miles for roadways. 3 Of the twelve accidents reported, five (42%) resulted in injuries to a total of eight individuals. 4 Not applicable; no Nevada County average accident rates were presented for intersections. 5 Six of the sixteen accidents reported resulted in injuries, with a total of nine people being hurt. 6 Accident rate is approximately double the State and County averages and one-third of the accidents (i.e., three of nine) resulted in injuries. 7 Actual rate is 2.7 times the State average and 2.5 times the County average. 8. Donner Pass Road Extension Project – The analysis of cumulative conditions is based on a number of assumptions regarding land use and the transportation system that will exist in the study’s horizon year. One of the key roadway system assumptions is that the Donner Pass Road Extension will be complete by the year 2031. In fact, it is primarily due to this assumption that acceptable levels of service are reported at certain study locations for cumulative conditions. For example, operations at the study intersection of Glenshire Drive/Donner Pass Road will be M R O ENGINEERS Ms. Carmen Borg February 20, 2013 Page 7 substantially improved when the Donner Pass Road Extension project is completed, as the left- turn volume from Glenshire Drive onto Donner Pass Road will be greatly reduced. However, this critical roadway system improvement project is beyond the control of the Canyon Springs project. In fact, it is beyond the control of the Town of Truckee, as the Donner Pass Road Extension project is directly tied to the private sector Railyard Master Plan project. Consequently, there is simply no guarantee that the road improvement will occur. The Town has committed only a small portion of the total cost of the extension project. If, therefore, the developer of the Railyard Master Plan project fails to act on that development (due to a failure to obtain project financing, for example), the Donner Pass Road Extension will not be completed. If that occurs, the entire cumulative conditions traffic analysis presented in the DEIR will be inaccurate, presenting an overly-optimistic view of traffic operations in the year 2031. Consequently, additional cumulative conditions traffic impacts are likely to be found. In short, the finding of acceptable cumulative conditions LOS is dependent upon completion of the Donner Pass Road Extension, and there can be no assurance that the extension project will actually be constructed. Ultimately, whether this improvement occurs is dependent upon whether the railyard developer proceeds with the development project and funds its substantial portion of the road improvement. To ensure consideration of a reasonable “worst case” scenario, the revised DEIR must include a cumulative conditions analysis to reveal traffic impacts and related mitigation measures if the Donner Pass Road Extension project is not completed. CONCLUSION Our review of the Draft Environmental Impact Report prepared for the proposed Canyon Springs project in Truckee, California revealed several issues potentially affecting the validity of the conclusions and recommendations presented in that document. Further, our review indicates that the proposed project may have additional significant impacts on the environment beyond those identified in the DEIR, particularly with respect to intersection and roadway level of service, freeway system operations, and safety. These issues should be addressed prior to approval of the proposed project and its related environmental documentation. We hope this information is useful. If you have questions concerning anything presented here, please feel free to contact me at (916) 783-3838. Sincerely, MRO ENGINEERS, INC. Neal K. Liddicoat, P.E. Traffic Engineering Manager M R O ENGINEERS    5900 Hollis Street, Suite D, Emeryville, CA 94608 | P: (510) 420-8686 | F: (510) 420-1707 | www.baseline-env.com   21 February 2013  13302‐00.2006      Ms. Carmen Borg  Shute, Mihaly, and Weinberger  396 Hayes Street  San Francisco, CA 94102  Subject: Canyon Springs Project, Town of Truckee, Draft Environmental Impact Report  Dear Ms. Borg:  At your request, BASELINE Environmental Consulting (“BASELINE”) has reviewed the Hydrology and  Water Quality section (and related technical documentation) of the Canyon Springs Project, Draft  Environmental Impact Report (“DEIR”), dated January 2013, prepared for the Town of Truckee  Planning Division.  In order to provide a meaningful context for the analyses in the Hydrology and  Water Quality section, we also reviewed the Project Description. Our comments are presented below.  COMMENTS ON DEIR  Project Description  On page 3‐5 of the Project Description, the DEIR states that “Juniper Creek, a tributary of the  Truckee River, flows through the site from east to west and serves as a wildlife corridor.”  Juniper Creek does not cross the project site, but flows to the north of Martis Peak Road, more  than 1,000 feet northeast of the project site.  In accordance with current National Pollution Discharge Elimination System (“NPDES”)  regulations, the project would be required to incorporate Low Impact Development (“LID”)  principles into sitewide drainage design. The goal of LID is to reduce runoff and mimic a site’s  predevelopment hydrology by minimizing disturbed areas and impervious cover and then  infiltrating, storing, detaining, evapotranspiring, and/or biotreating stormwater runoff close to  its source. Practices used to adhere to these LID principles include measures such as rain  barrels and cisterns, green roofs, permeable pavement, preserving undeveloped open space,  and biotreatment through rain gardens, bioretention units, bioswales, and planter/tree boxes.  The DEIR Project Description indicates that the project would comply with LID requirements  (DEIR page 3‐31 as follows):  Surface drainage from impervious surfaces, such as residential roofs and driveways  located within the proposed restricted building envelopes, will be collected, treated, and  contained on‐site using low impact development (LID) methods of drainage treatment.  Infiltration trenches, rainwater gardens and small retention, or subsurface structures    Ms. Carmen Borg  21 February 2013  Page 2  13302‐00.2006‐2/21/13  would be utilized. Figure 3‐11 shows the location of proposed drainage ditches and  retention ponds.  The first two sentences quoted above from the DEIR refer to accepted LID drainage features.  However, the third sentence refers the reader to a drainage plan that shows only drainage  ditches and centralized retention ponds (referred elsewhere in the DEIR as “detention basins”),  which are not LID features. Based on our review of the DEIR (Project Description, Hydrology  and Water Quality section, and the Hydrology and Hydraulics Report included in Appendix K), it  appears that the actual drainage plan for the site was prepared and completed in 2003,1 prior  to the inclusion of LID requirements in NPDES permits (and the widespread recognition of their  benefits). The first two sentences from the DEIR excerpt above are describing some other  drainage plan that is not presented in the DEIR.  Without a clear, consistent, and detailed  description of the proposed drainage plan, the reader of the DEIR cannot understand what the  project is proposing and cannot effectively evaluate potential environmental impacts.  Hydrology and Water Quality   Much of the discussion of “existing conditions” related to hydrology and drainage appear to be  based on work done approximately ten years ago, including a site reconnaissance conducted by  Geocon2 in 2004 (DEIR page 4.9‐15) and the previously mentioned 2003 Hydrology and  Hydraulics Report.3  It is unclear whether conditions observed 9‐10 years ago are still  representative of existing conditions. The DEIR should be revised to, at minimum, include  documentation of a more recent site reconnaissance and an updated drainage plan.   The DEIR states that “for the two main ephemeral drainages on the project site, 100‐year  floodplain limits and 50‐foot setbacks are shown on Figure 3‐6” (DEIR page 4.9‐16).  Neither the  100‐year floodplain nor the 50‐foot setback limits are shown on Figure 3‐6 (or on any other  figure in the Hydrology and Water Quality section). Figure 3‐6 appears to show the area of  encroachment into the 50‐foot setback from the floodplain, but does not actually show the  floodplain limits (or even all the creek alignments). Without this information, the reader cannot  verify compliance with specified setbacks and encroachment related to bridge foundations.  On page 4.9‐16, the DEIR states:  Prior to initiation of construction, the project proponent would need to demonstrate  that the post development design storm hydrograph leaving the project is not changed  from pre‐project conditions such that downstream drainage structures (culverts,                                                            1 CFA, 2003, Preliminary Hydrology and Hydraulics Report, Tahoe Boca, October 3.   2 Geocon, Inc is a geotechnical and environmental engineering firm, but their role in this development plan is  not clearly explained in the DEIR, nor are any reports or supporting documentation prepared by them included in the  DEIR attachments.  3 The DEIR refers to a 2007 Geocon report, but this document is not included in the DEIR and was not available  for review.    Ms. Carmen Borg  21 February 2013  Page 3  13302‐00.2006‐2/21/13  bridges, etc.) remain adequate post‐development. To this end, soil infiltration rates,  pond detention times, and other suggested revisions from the 2007 technical review by  Geocon would also need to be incorporated into the construction plans to illustrate the  feasibility of the proposed drainage design.  The above excerpt from the DEIR appears to indicate that Geocon reviewed the project and  suggested revisions to the drainage plan. Yet this Geocon report has not been included in the  DEIR, nor has a summary of the suggested project revisions been described.  Once again, the  Project Description and the Hydrology and Water Quality section provide incomplete and  potentially conflicting descriptions of the project.  How is the reader of the DEIR supposed to  understand what the drainage plan is if it is being revised by reports that are not included in  the public record?  Similarly, the DEIR (page 4.9‐16) indicates that “a revised site/drainage plan  was prepared in April 2011, reflecting 37 fewer building lots than the original 2003 plan.”  This  revised plan was not included as part of the DEIR and was not available for this review.    Page 4.9‐18 of the DEIR states that “the project would include construction of vegetated,  earthen swales on both sides of the site’s crowned, paved roads to convey flows to  decentralized treatment and infiltration facilities.” Collection and conveyance of stormwater to  centralized treatment facilities is exactly the opposite of LID principles.  The DEIR is internally  contradictory and the 2003 drainage plan that was included in the DEIR appendix has not been  designed to be fully compliant with an LID approach, as required under the current NPDES  permits.  The project drainage plan (and to the extent the LID drainage requirements affect the  site plan and layout) should be redesigned.  The Hydrology and Water Quality section of the DEIR has failed to demonstrate that an LID‐ type drainage approach is feasible at this site.  For example, do the on‐site soils have an  adequate infiltration capacity (since LID focuses on keeping runoff on‐site and infiltrating it)?   The recently adopted Phase II General Permit4 specifies that any proposed LID treatment  facilities be at least as effective as a bioretention system with: 1) a maximum surface loading  rate of 5 inches per hour, based on the flow rates calculated (a sizing factor of 4 percent of  tributary impervious area may be used); and 2) minimum surface reservoir volume equal to  surface area times a depth of 6 inches (General Permit, page 110). It is unclear whether the  drainage plan as proposed meets these criteria.  The Hydrology and Water Quality section fails to address potential impacts to stormwater and  snowmelt runoff water quality related to application of road salt.  When snow and ice melts,  the applied salt goes with it, potentially entering surface receiving waters (in this case  Glenshire Pond) and/or underlying groundwater. Water quality degradation and related stress                                                            4 State Water Resources Control Board, 2013, WDRs for Storm Water Discharges from Small Municipal Separate  Storm Sewer Systems General Permit, adopted February 5.    Ms. Carmen Borg  21 February 2013  Page 4  13302‐00.2006‐2/21/13  and mortality to flora and fauna is an established result of road salt application.5,6  The DEIR  makes no mention of this potential impact, which is particularly surprising since the project  proposes to collect and convey road drainage to centralized detentions basins where the water  would be infiltrated.  This practice, of concentrating runoff into a few locations would increase  the pollutant loading at those locations and increase the risk to groundwater quality  degradation.    Similarly, the DEIR fails to analyze potential construction period (e.g., sedimentation) water  quality impacts to Glenshire Pond in the Hydrology and Water Quality section (Glenshire Pond  is located approximately 4,000 feet west of the project site).  Since most of the runoff from the  site would drain to this pond, it is puzzling that the DEIR does not discuss potential impacts to  this receiving water body in any way. The setting should provide all the relevant information  that is needed for the reader of the DEIR to understand the current water quality conditions of  this water body and its potential sensitivity to a new pollutant load, which would include  sediment, nutrients (e.g. fertilizers), oil and grease, pesticides, and road salt.   Overall, the DEIR fails to demonstrate that the proposed mitigation measures provided to  address project construction and operation period water quality impacts would be effective.  Mitigation measures HYDRO‐1 and HYDRO‐2 provide no specific performance standards by  which to measure the effectiveness of the BMPs that the applicant might select.  This is  unacceptable under CEQA because it leaves for later critical decision‐making that could affect  the effectiveness of the water quality measures, with no performance standard to ensure or  gauge success.    The DEIR acknowledges the uncertainty of the feasibility of adequately treating runoff by  infiltration (which is touted as the primary treatment approach throughout the discussion) at  this site by stating “other control measures may be considered if site constraints are such that  construction of infiltration features is not feasible (DEIR page 4.9‐31). Relying on infiltration  throughout the mitigation measures, and then indicating that it may not be feasible leaves the  reader of the DEIR to wonder what types of measures will be used if infiltration is not feasible.   Deferment of this feasibility analysis is unacceptable under CEQA. The feasibility analysis  should be conducted now and the DEIR recirculated so that the reader of the DEIR has a clear,  concise, and feasible drainage and stormwater treatment plan to review and comment upon.   The DEIR states (page 4.9‐15) that “one well was observed on the site during the field  reconnaissance, the well appeared to be capped and not in service.” The DEIR fails to provide  any information about the location of the well relative to proposed grading and development is  provided. During grading and construction, wells are frequently unnoticed and the wellhead                                                            5 USEPA, 2013, The Influence of Road Salts on Water Quality in a Restored Urban Stream, website accessed 2‐ 12‐13:  http://www.epa.gov/ada/eco/pdfs/road_salts.pdf  6 Cooper, C.A., P.M. Mayer, and B.R. Faulkner, (2008), The Influence of Road Salts on Water Quality in a  Restored Urban Stream, in 16th National Nonpoint Source Monitoring Workshop. Edited by J. D'Ambrosio.    Ms. Carmen Borg  21 February 2013  Page 5  13302‐00.2006‐2/21/13  sheared off or damaged. This can provide a preferential flowpath for contaminants at the  surface to be introduced to groundwater, thereby degrading water quality.  This potential  should be identified as a significant impact and measures required to either properly abandon  (i.e., seal) the well, or protect it during grading and construction.    Should you have any questions or comments, please contact us at your convenience.  Sincerely,    Bruce Abelli‐Amen  Senior Hydrogeologist  Cert. Hydrogeologist No. 96    BAA:km  Canyon Springs SierraBluffsSF Flycasters TDLT/CDFW Tru c k e e R i v e r J u n i p e r C r e e k Gray C r e e k Ma r t i s C r e e k We s t F o r k G r a y C r e e k Bronco Creek We s t J u n i p e r C r e e k Prosser Creek Rivers & Streams Lakes & Reservoirs Town of Truckee Nevada Co. Parcels Nevada Co. Boundary Legend 0 0.5 1 1.5 20.25 Miles TDLT/TTAD Ü Canyon Springs Hydrology Map by: S. Taddo Jones 2/25/2013Sources: Nevada County, State of CA, USGS 1 INTERSTATE DEER PROJECT Loyalton-Truckee Deer Herd Report and Management Plan Update (Habitat Sections Only) 2010 Table of Contents Introduction …………………………………………………………………………. 2 Land Ownership …………………………………………………………..….……. 3 Vegetation/Land Cover ………………………………………….………….…...… 5 Grazing …………………………………………………………………………..…. 7 Fire History ………………………………………………………………….…….… 8 Seasonal Ranges …………………………………………………………….……. 10 Human Population Change ……………………………………………………..… 14 Exurban Growth ………………………….………………………………………… 15 Land Use Planning …..………………………………………………………..…… 18 Telemetry Studies ……………………………………………….…………..…...... 19 Resident versus Migratory Deer …………………………………………………. 28 Summary …………………………………………………………………….……… 29 Literature Cited …………………………………………………………..……….… 31 2 Introduction In April of 2009 the Interstate Deer Herd Committee of California and Nevada met to establish 2009 tag allocations for the interstate deer herds, and to discuss a project to identify areas of concern within interstate deer herds. The purpose of this project is to produce habitat related information to guide interactions with land management agencies, planning commissions, etc., in regards to mule deer, and possibly other species (sage grouse, antelope). Attending this meeting were California Department of Fish and Game (CDFG) staff from the Deer Management Program in Sacramento: Craig Stowers, Mary Sommer, and David Casady; CDFG Regional biologists: Richard Callas, Terri Weist, Sara Holm, and Tim Taylor: and Nevada Department of Wildlife (NDOW) biologists Mike Cox, Jason Salisbury, Chris Hampson, and Carl Lackey. The discussions about the project revolved around the need to document and quantify what habitat we have now as compared to what we used to have, and identifying the most obvious threats on summer and winter range. This project was initiated in 2007, but little work was accomplished due to work loads and other agency priorities. To get the project (now called the Interstate Deer Project) going, Mary Sommer was designated as the lead. The long term goal of the Interstate Project is to investigate all the interstate deer herds, however the Loyalton-Truckee Deer Herd was chosen as a pilot project due to the belief that development, especially in the Nevada portion of the herd range and in the Truckee, California area, and other issues have led to a critical situation in this herd. These concerns are shared by biologists from CDFG and NDOW. The Loyalton-Truckee deer herd is an interstate herd with winter ranges in both California and Nevada, and summer ranges in California. This herd comprises the bulk of California’s deer zones X7a and X7b, two highly sought after deer hunting areas. A secondary goal of this document is to update habitat related sections in the 1982 Loyalton-Truckee Deer Herd Management Plan. The plan contains information about the herd and its environment that was current in 1982, but much has changed in the years since its writing. While the main elements of vegetation, grazing, fire, seasonal ranges, and land ownership have remained of interest, the details and importance of each has changed over time. Other topics such as human population change, exurban growth, land use, and results of telemetry studies have been added to this report to supplement the original topics. The following sections are intended to accomplish two things: 1. Describe various habitat related issues and their progression over the past 20-30 years. 2. Update sections of the original Loyalton-Truckee Deer Herd Plan relating to habitat and migration patterns of the deer herd. 3 Land Ownership The states of California and Nevada share the land that comprises the Loyalton-Truckee Deer Herd, with approximately 77% within California and 23% Nevada. In California the vast majority is owned by the US Forest Service (50%) and private landowners (44%). Nevada’s portion of the Loyalton-Truckee Deer Herd range consists primarily of Private (38%), BLM (32%), and US Forest Service (29%). Land ownership is shown in Table 1 and the map in Figure 1. CALIFORNIA OWNERSHIP ACRES PERCENTAGE Bureau of Land Management 17,027.76 2.71% CA Dept. of Fish and Game 16,896.64 2.69% CA Dept. of Parks and Rec 3,164.17 0.50% Department of Defense 47.43 0.01% CA State Lands Commission 996.29 0.16% Private 277,164.72 44.05% USDA Forest Service 313,902.27 49.89% 629,199.27 100.00% NEVADA OWNERSHIP Bureau of Land Management 61,274.26 32.23% Department of Defense 1,732.33 0.91% Forest Service 54,773.46 28.81% Private 72,298.15 38.03% Regional Park 37.75 0.02% 190,115.95 100.00% CA & NV COMBINED Private 349,462.87 42.65% USDA Forest Service 368,675.72 45.00% Bureau of Land Management 78,302.03 9.56% Department of Defense 1,779.75 0.22% Regional Park (Nevada) 37.75 0.00% CA Dept. of Fish and Game 16,896.64 2.06% CA Dept. of Parks and Rec 3,164.17 0.39% CA State Lands Commission 996.29 0.12% 819,315.21 100.00% 76.80% CA 23.20% NV Table 1. Land Ownership within the Loyalton-Truckee Deer Herd Boundary Data sources California: Public and Conservation Lands, California Resources Agency Legacy Project, data relevant up to 2003. Nevada: Land Status Nevada, U.S. Dept. of the Interior – BLM - Nevada State Office – Mapping Sciences, data relevant for 1998-2007. 4 Figure 1. Land ownership of the Loyalton-Truckee Deer Herd. 5 Vegetation/Land Cover The general land cover types that characterize the habitat of the Loyalton-Truckee Deer Herd are listed in Table 2 below, and illustrated in Figure 2. The shrub/scrub classification is the most extensive, covering approximately 47% of the range mostly in the northeastern section, and dominating the Nevada portion. The next most common land cover type is the Evergreen Forest (36%), occurring in the south and central part of the range, as well as all along the western border. The Herbaceous type occupies approximately 10% of the herd range, mostly in the area of Sierra Valley. Land Cover for the Loyalton-Truckee Deer Herd LANDCOVER TYPE ACRES PERCENTAGEOpen Water 6,941.97 0.84%Developed, Open Space 10,593.53 1.29%Developed, Low Intensity 12,827.38 1.56%Developed, Medium Intensity 4,183.34 0.51%Developed, High Intensity 980.73 0.12%Barren Land 3,541.36 0.43%Deciduous Forest 106.07 0.01%Evergreen Forest 298,325.42 36.31%Shrub/Scrub 385,249.04 46.88%Herbaceous 85,728.00 10.43%Hay/Pasture 6,070.80 0.74%Cultivated Crops 1,490.63 0.18%Emergent Herbaceous Wetlands 5,679.43 0.69% 821,717.70 100.00% Developed 28,584.99 3.48%Agriculture (Hay/Pasture/Crops) 7,561.42 0.92% Data Source: Multi-Resolution Land Characteristics Consortium (MRLC)2001 National Land Cover Database Source data 2001 remote sensing imageryPublication_Date: 20030901 Table 2. Vegetation/land cover types of the Loyalton-Truckee Deer Herd 6 Figure 2. Land Cover types within the Loyalton-Truckee Deer Herd boundary. 7 Grazing When the 1982 Loyalton-Truckee Deer Herd Plan was written, livestock grazing on USFS and BLM grazing allotments had improved from a historical high level of overuse to a more moderate level of grazing. Since that time the numbers of livestock grazed has continued to decrease within the Loyalton-Truckee Deer Herd boundary. According to Roberta Lim, East Zone Range Management Specialist for the Tahoe National Forest, this is due in large part to the implementation of the National Environmental Policy Act (NEPA) in 1970, and the resulting assessment of the effects of grazing on Federal lands. Standards that were set at NEPA’s inception have been modified over the years and are continually changing, with the trend being more stringent grazing standards. In the 1990’s the health of each individual grazing allotment was evaluated to see if standards were being met, and action was taken to ensure compliance to the latest grazing requirements (personal communication, 4 June 2010). The majority of grazing allotments within the Loyalton-Truckee Deer Herd area lie within the Tahoe National Forest. Reports generated by Roberta Lim, East Zone Range Management Specialist, Tahoe National Forest, 4 June 2010, show that there are currently 14 active allotments for a total of 7,849 AUM’s. The 1982 Loyalton-Truckee Deer Herd Plan lists 24 active allotments for the Tahoe National Forest with 14,257 AUM’s. This represents a substantial reduction in grazing over a large portion of the Loyalton-Truckee Deer Herd range. Of the grazing allotments on the Toiyabe National Forest that were listed in the 1982 plan, it has been confirmed by Courtney Priess, Range Management Specialist, Humboldt-Toiyabe National Forest, that all are currently in vacant status and most have not been grazed since the 1990’s. Two other allotments that used to be BLM allotments (Peavine Watershed S&G and Peavine/Blacksprings S&G) have been permanently closed to grazing (personal communication, 3 June 2010). BLM grazing allotments also show a decline from a total of 16,294 AUM’s (from the 1982 Loyalton-Truckee Deer Herd Plan) to a current number of 13,095 AUM’s (Katrina Leavitt, BLM Carson City District, personal communication, June 2010). While grazing trends on private property are largely unknown, the decrease in competition from livestock grazing on public lands is most likely of benefit to the Loyalton-Truckee Deer Herd. 8 Fire History Despite active fire suppression efforts, fire is a common occurrence on the landscape of the Loyalton-Truckee Deer Herd. The majority of the winter range is composed of sagebrush and bitterbrush communities that are vital to deer populations. The East Side Pine community is an intermediate habitat type that includes conifers with sagebrush and mountain mahogany understory. Deer use this habitat type primarily in the summer. While a cool/light fire can rejuvenate vegetation, particularly in the conifer forest, fire on the shrub dominated winter range tends to burn hot and destroy habitat that recovers slowly at best. Figure 3 shows the locations of fires that burned in the years 1980-2008. Cheatgrass invasion Fire in sagebrush plant communities not only destroys brush forage species that deer depend on, but also opens the way for invasive plants such as cheatgrass (Bromus tectorum) to become established. Cheatgrass is an exceptionally competitive annual grass due to its early germination in the fall and winter, well developed root system for water uptake, abundant seed production, and extended seed dormancy. This grass takes over after fire and outcompetes brush and other grasses. Cheatgrass also provides a fine textured, early maturing fuel that increases the incidence of fire (deVos et al. 2003). Cheatgrass has typically become established following fires in the sagebrush dominated plant communities of the Loyalton-Truckee Deer Herd range. A relatively small portion of the Hallelujah Junction Wildlife Area burned in the Chilcoot fire of 2003, leaving an area of pure cheatgrass (Figure 4). In 2007 the Balls Canyon fire burned a much larger area of HJWLA, destroying 4,400 acres of prime deer habitat. This fire prompted extensive re-vegetation efforts, but it will still be decades before the range has anywhere near the value to deer that it did historically. Cheatgrass appears to be a relatively new addition to the landscape of the Loyalton-Truckee Deer Herd, as there is no mention of it in the 1982 Deer Herd Plan but it is now considered a serious invasive plant problem. 9 Figure 3. Fire perimeters recorded for 1980 – 2008. Data sources: Fire Perimeters (fire08_2), frap.cdf.ca.gov; Nevada Fire History, USDOI BLM Nevada State Office Geographic Sciences (NV_firehistory). 10 Figure 4. Photo of Hallelujah Junction Wildlife Area showing cheatgrass invasion after fire. Fire area is on the left, unburned area on the right. Seasonal Ranges The 1982 Loyalton-Truckee Deer Herd Plan lists 3 well defined, geographically separate winter ranges used (5,000 – 6,000 ft. elevation) All of these winter ranges are dominated by bitterbrush-sagebrush habitat types: 1) Verdi Basin – 5 key ranges: 1)Sunrise basin, 2)Guest Ranch (Donner Trails), 3)Peavine Mtn, 4)Garson, 5)Belli 2) Sierra Valley 3) South Petersen Mtn, including Sand Hills Verdi Basin The Verdi Basin is an important wintering area for deer in the southern portion of this deer herd. The Verdi Basin winter ranges are located mostly in Nevada, and have been impacted extensively by development. 11 Sara Holm, CDFG Associate Wildlife Biologist describes impacts to these key areas: Garson Road is the present day Cabela's exit and runs mostly parallel to Hwy 80. The area is built up but deer are seen there. Beli Ranch is now a series of ranchettes on the south side of Hwy 80 but it does abut the open land as you go up the hill towards the Mt. Rose Wilderness Area. There is lots of use on the hillside but the ability for deer to get water from the Truckee River is very impacted with all the homes, streets and activity along the river. Peavine Mountain is mostly what you see to the north of Hwy 80 and is what we fly for comp counts. We see a lot of deer there but considering it also runs down into Somerset, which is a huge development, it has been highly impacted. This is also the site of the Verdi fire and a lot of habitat was wiped out from that too (personal communication, 14 September 2010). Mike Cox of NDOW estimates the percent loss of winter range in Nevada compared to historic in the following: Development has destroyed 40% (most critical because it was the lowest elevation and key during the killing winters), and severely comprised another 10%, with wildfires destroying 30% and another 10% having severely limited value due to older fires with ever-so-slight vegetation recovery (causing only a handful of deer to survive in it vs. several hundred), leaving only 10% intact winter range left (that could be generous). Some historic deer migrations most likely were all the way into Reno wrapping around to the southeast, but much of that is severed by development (personal communication, 14 September 2010). According to Carl Lackey of NDOW, the herd used to migrate all the way into the Truckee Meadows and east of Reno into the Virginia Range (personal communication, 17 September 2010). The 1982 Loyalton-Truckee Deer Herd Plan mentions that the construction of Hwy 80 in the 1960’s created a barrier to intermingling deer populations on the north and south sides of the Truckee River. There have been no deer collaring projects on the Verdi Basin deer since the 1982 Deer Herd Plan, and no movement studies since the 1970’s. However, a study was initiated in the fall of 2009, which is designed to answer questions regarding the movements of the deer that use the Verdi Basin. Preliminary data show that at least two of the collared does cross Highway 80 to travel between their summer and winter ranges. For more information on this study, see “Telemetry Studies” in this report. The Truckee River Wildlife Area is a complex of CDFG owned units totaling 3,880 acres in Nevada, Placer and Sierra counties, approximately 2 to 7 miles east of Truckee. While these units are located along the Truckee River and were mainly acquired for fisheries values, some provide valuable habitat for deer. The Canyon Unit and Union Ice Unit are the largest and most useful to deer. Recent collaring data show the Union Ice Unit to be a summer concentration and fawning area. 12 Sierra Valley There are two CDFG owned Wildlife Areas that provide important winter habitat to the deer in the Sierra Valley area. These are the Antelope Valley Wildlife Area and the Smithneck Creek Wildlife Area, both located in Sierra County near Loyalton, south of Highway 49. These Wildlife Areas were designated after the 1982 Loyalton-Truckee Deer Herd Plan was written. The Antelope Valley Wildlife Area is 5,616 acres largely covered by sagebrush interspersed with rabbit brush and bitterbrush at the lower elevations. The upper slopes are populated by Jeffrey pine, juniper, mountain mahogany, and chaparral plants. It is considered prime deer winter range, and was acquired to preserve critical deer winter range and migration corridors from development. The wildlife area is considered by sportsmen and the Department as a premier hunting area in California (California Department of Fish and Game, 2008). The Smithneck Creek Wildlife Area consists of 1,395 acres of a variety of habitats typical of the east side of the Sierra. The sagebrush-bitterbrush habitat is a critical deer winter-range area for migratory deer. Limited stands of yellow pine, mountain mahogany and juniper provide additional habitat for resident deer. Wet and dry meadows are found along Bear Valley Creek. Riparian habitat consisting of alders, willows and aspen provide cover along Bear Valley, Smithneck and Badenaugh Creeks. South Petersen Mountain The 1982 Loyalton-Truckee Deer Herd Plan lists South Petersen Mountain in Nevada as a winter range area, although it also stated that during mild winters deer may not cross 395 into Nevada, and instead winter in the Balls Canyon, Evans Canyon, and Coulee Canyon of Sierra County, California. At that time the NDOW fall composition counts in November and December showed large numbers of deer on top of Petersen Mountain. Chris Hampson, the NDOW biologist for the Petersen Mountain area, describes current conditions: “We have a much smaller resident herd now than what we had back in the early 80's. Continued human disturbance and encroachment, plus numerous wildfires have really impacted the Petersen's and surrounding areas. I do see mule deer in the fall but it certainly would not be large numbers by any means, and numbers are generally pretty low as far as the resident herd. Habitat changes on the ground along with the warmer/drier climate have hurt most deer herds in western Nevada.” Chris also points out that fire has been prevalent on the Petersen Mountains, with close to 10,000 acres lost in 2009. Some of the area that burned had been burned previously, but some good unburned habitat was also lost. There is “some important winter range on the SW corner still intact that is keeping some deer alive through the winter and some on 13 the Northern 1/3 of the range as well. Most in between has burned” (personal communication, 26 September 2010). The Hallelujah Junction Wildlife Area is owned and managed by the CDFG, and is an important locale for wintering deer. This Wildlife Area covers 13,394 acres, is located in Lassen and Sierra Counties, and includes part of Balls Canyon and Evans Canyon. The habitat is a mosaic of sagebrush scrub, bitterbrush, Juniper woodlands, wet meadows and wetland habitats. The primary purpose of this land acquisition was the preservation of critical deer winter range and migration corridors from development (California Department of Fish and Game, 2009). This property was acquired after the 1982 Loyalton-Truckee Deer Herd Plan was written. Intermediate and Summer Ranges According to the 1982 Loyalton-Truckee Deer Herd Plan, intermediate and summer ranges cover 67% of the total range, of which 47% is publicly owned. Elevations range between 6,000 and 9,000 feet, and are typically dominated by sagebrush and Jeffrey pine vegetation types. Primary forage species are perennial grasses, green leaf manzanita, sagebrush, bitterbrush, and various species of Ceanothus (California Department of Fish and Game, 1982). While the area of intermediate and summer range is larger than that of the winter range, the quality of much of the habitat is thought to be degraded to a point where all summer range is important and can be considered essential to this deer herd. Patches of relatively rare habitat types such as meadows and aspen are critical as they are often used in summer for fawning. There have been land acquisitions and conservation easements within the summer range negotiated by the Truckee Donner Land Trust, a nonprofit organization that works to preserve and protect important historic, recreational, and scenic open spaces in the greater Truckee Donner region. To date, the Truckee Donner Land Trust has protected 16,296 acres, including 2,000 acres surrounding Independence Lake and 983 acres in Perrazo Meadows. In summary, while many habitats have been severely degraded by development and fire, there have been steps taken to preserve blocks of important deer range. 14 Human Population Change Growth of the human population is an important factor to consider due to the need for resources that an ever-growing population requires. Impacts from various aspects of human population growth, from residential development to recreational use, can influence wildlife populations. Human encroachment on deer habitat can impact habitat suitability in three ways: displacing deer through habitat occupation, reducing habitat suitability by altering the physical characteristics of that habitat, and displacing deer through disturbance, such as noise and activity (Sommer et al. 2007). Deer are displaced when their habitat is occupied by the construction of buildings, roads and other related development, or habitat is converted to another use such as agriculture. With these changes may come additional concerns to deer such as fences, livestock, and dogs. Increased roads can limit access to important habitats and increase mortality by vehicle collisions. Habitat suitability may be decreased when the physical characteristics of that habitat are altered. Unregulated off-highway vehicle (OHV) use can alter habitat characteristics through destruction of vegetation, soil compaction, and increased erosion. Excessive livestock grazing may alter habitat suitability by removing forage and cover species that deer rely on. Other land uses such as mining, energy developments, and landfills can alter habitat suitability by changing vegetation composition and new road installation. Deer are also displaced through disturbance, such as noise and activity. The U.S. Forest Service estimated that OHV use increased 7-fold during a recent 20 year period (Wisdom et al. 2005). Hiking, mountain biking, and ATV use are examples of other disturbances that are common on deer ranges. Recreational use, especially on public lands, occurs primarily in critical summer months, during fawning and lactation periods. Recreational use continues to grow as human populations expand. Table 3 shows the human population change by decade in each county that is part of the Loyalton-Truckee Deer Herd area. While much of the growth in California counties has occurred outside the boundaries of the deer herd (closer to the Sacramento area), local growth such as in the Truckee area and that of Washoe County near Reno has expanded into important habitats of the Loyalton-Truckee Deer Herd. 15 California 2000 1990 1980 1970 1960 Lassen County 33,828 27,598 21,661 16,796 13,597Nevada County 92,033 78,510 51,645 26,346 20,911Placer County 248,399 172,796 117,247 77,632 56,998Plumas County 20,824 19,739 17,340 11,707 11,620Sierra County 3,555 3,318 3,073 2,365 2,247 NevadaWashoe County 339,486 254,667 193,623 121,068 84,743 California 1990 to 2000 1980 to 1990 1970 to 1980 Total 30 year change Lassen County 22.60 27.40 29.00 79.00Nevada County 17.20 52.00 96.00 165.20Placer County 43.80 47.40 51.00 142.20Plumas County 5.50 13.80 48.10 67.40Sierra County 7.10 8.00 29.90 45.00 NevadaWashoe County 33.30 31.50 59.90 124.70 Source: U.S. Census Bureau, Census 2000 Percent Change of Population HUMAN POPULATION CHANGE FOR COUNTIES OF THE LOYALTON-TRUCKEE DEER HERD Population Table 3. Census data comparison by County. Exurban Growth Residential development beyond the urban fringe, sometimes called exurban sprawl or rural residential development, has resulted in extensive and widespread changes to the landscape across the United States. Theobald, 2005, describes this trend: “the general notion of urban sprawl is that the spatial spread of development proceeds at a greater rate than population growth, resulting in dispersed, low-density development”. As undeveloped rural areas are converted to exurban or possibly urban/suburban land use, natural resource values rapidly diminish. Theobald’s work has shown that nationwide, exurban land use occupies five to ten times more area than urban and suburban densities, and has been growing at a rate of about 10–15% per year, which exceeds the rate of urban development. These exurban areas are often located adjacent to or nearby protected lands, which may expose these lands to growth related impacts. 16 Theobald has produced a nationwide, fine-grained database of historical, current, and forecasted housing density, which can be used to quantify changes in growth patterns to infer possible ecological effects (Theobald, 2005). This database was used to quantify habitat altered by development on the privately owned land within the Loyalton-Truckee Deer Herd from 1960 to 2000 (Table 4). Within the deer herd boundary, undeveloped private land has decreased from 73% in 1960 to 46% in 2000. This represents a loss or conversion of 90,986 acres (26%) of undeveloped private land. This acreage has been redistributed among the other three classes shown in the table below. The greatest increase by percentage however, is in the exurban/urban/built-up classification which includes development of up to 10 acres per housing unit, plus commercial, industrial, and transportation. This is the most intensive type of development of the classes listed, and is the most detrimental to the deer herd. CLASS 2000 Percentage 1980 Percentage 1960 Percentage Undeveloped private 46%55%73%40 acres and above per unit 32%28%21%10 - 40 acres per unit 6%9%3%Exurban/urban & Urban/built-up 15%8%3% Exurban/urban/built-up = Up to 10 acres per housing unit, plus commercial, industrial, and transportation. Table 4. Percentages of development classes for selected years on privately owned land of the Loyalton-Truckee Deer Herd. The extent and growth of exurban sprawl within the Loyalton-Truckee Deer Herd area is striking. Figure 5 maps the spatial distribution of the changes in development class that have occurred from 1960 to the year 2000. In addition, the model used by Theobald to forecast future development shows an increasing trend in all development for the Loyalton-Truckee Deer Herd in 2010 (Table 5). Roads and sprawling neighborhoods are replacing and altering deer habitat, putting the survival and reproduction of portions of this deer herd at risk. Habitats have shrunk, fragmented, and in some cases disappeared altogether. Extensive and widespread land-use changes have occurred and are likely to continue. Class Name 2010 Acreage Percentage Undeveloped private Rural 1 111,961 32%40 acres and above per unit Rural 1 142,691 41%10 - 40 acres per unit Rural 2 15,177 4%Exurban/urban & Urban/built-up Exurban/urban/built-up 80,030 23% TOTAL 349,859 100% Table 5. Forcasted pattern of development classes for 2010. 17 Figure 5. Levels of development on privately owned land within the boundaries of the Loyalton-Truckee Deer Herd from 1960 to 2010. Blank areas (in white) are public lands. 18 Land Use Planning The California Environmental Quality Act (CEQA) is a statute passed in 1970 that requires California state and local agencies to follow a protocol of analysis and public disclosure of the potential environmental impacts of development projects. Because CEQA makes environmental protection a mandatory part of every California state and local agency's decision making process, it has been somewhat effective in protecting the environment from some development issues. Nevada, unfortunately, does not have the same type of environmental protection. Each county within the Loyalton-Truckee Deer Herd boundary was contacted in an effort to obtain GIS data that could be used to map general plans and/or zoning for the herd area. Due to differences in classification systems between counties, and the absence of current GIS data for some areas, mapping proved to be problematic. However the information collected provides an overview of the trends in land use planning for each county. Following is a summarization of that information. The portion of the Loyalton-Truckee Deer Herd that lies within Washoe County Nevada is heavily impacted by development. Virtually all private property within that area is either under development or there are plans for it in the future. The land within the city limits of Reno is no exception. The City of Reno Master Plan Land Use shows the vast majority of property within the city to be slated for development incompatible with deer use. Plumas County in the northwest corner of the herd area has been zoned for various development levels up to 160 acre lots. Most of the area is zoned for lots of 20 – 160 acres, with some smaller areas zoned for lots less than 20 acres. To the east of Plumas County is a small area of Lassen County within the herd area. The best data available shows this to all be assigned lot size of less than 20 acres, however the reliability of the data are unknown. The Sierra County portion of the deer herd is comprised primarily of public lands and open space, with smaller localized areas zoned for 20 acres or less around Loyalton, Sierraville, Sattley, Calpine, and just west of Verdi. Nevada County has a good amount of public land and open space north of Truckee, however within the city limits of Truckee zoning is all parcels of 20 acres and less, and to the east and west of the city limits are areas of planned development. Placer County in the southern end of this deer herd includes the north and west shore of Lake Tahoe. The Lake Tahoe area, the southern half of Martis Valley, and several ski resorts along highways 89 and 267 comprise the bulk of the development in this county. USFS land is interspersed with private property which is zoned mostly for 20-160 acre parcels, with localized areas of smaller than 20 acre parcels. 19 Telemetry Studies There have been 3 deer telemetry collaring studies conducted on the Loyalton-Truckee Deer Herd since the writing of the 1982 Herd Plan; one in 1992-94, another in 2002-05, and the latest beginning in 2006 and is ongoing. CDFG Associate Wildlife Biologist Syd Kahre conducted the 1992-94 study in an effort to define migration corridors and seasonal use areas for the deer herd. 25 deer were captured at the Hallelujah Junction Wildlife Area and fitted with VHS collars. Aerial surveys were used to track the collared deer, and locations were recorded using GPS. The resulting location information is shown in Figure 6. Jim Lidberg followed Syd Kahre as the next CDFG Associate Wildlife Biologist that worked with the Loyalton-Truckee Deer Herd. The collaring effort Jim conducted during 2002-2005 was a joint effort between the CDFG Sacramento Valley and Central Sierra Region (Region 2) and the Wildlife Programs Branch. The purpose of the study was three fold: 1) provide “markers” for locating individuals in the herd prior to conducting helicopter composition counts in December and March of each year; 2) collect data on distribution of the deer herd at various times of the year; and 3) determine habitat use by the herd. Deer were captured by a net gun fired from a helicopter and by herding deer with the helicopter into linear drive-nets. Deer were captured and fitted with VHS collars made by Telonics, which have a design life of up to 4 years. In 2002 there were 29 deer with collars, in 2003 there were 50, in 2004 there were 42, and in 2005 there were 18 deer with collars. Data were collected on flights conducted regularly over the period of the study. Location information collected for all collars is illustrated in Figure 7. 20 Figure 6. Deer locations from 1992-94 telemetry study. Locations were recorded by GPS during aerial flights. 21 Figure 7. Deer locations from 2002-05 telemetry study. 22 CDFG Associate Wildlife Biologist Sara Holm was the next biologist to study the Loyalton-Truckee Deer Herd with the Hwy 89 Stewardship Team telemetry study, initiated in 2006. This project is an ongoing effort by the Highway 89 Stewardship Team to identify crossing, migration corridor, summer and winter range boundary, and fawning areas. Through a series of grants the Team has completed the first of several anticipated mitigation underpass structures on Hwy 89 between Truckee and Sierraville, and will complete fencing to ensure safe passage across the highway for mule deer in the Loyalton-Truckee Deer Herd as well as other wildlife species. The overall 20-year plan for the Team includes research, mitigation and outreach. The collaring of 15 deer each year has helped to identify priority areas along the highway for crossing structures. The movement seen by these deer will impact land acquisition choices, habitat connectivity and restoration, tag quotas for the draw zones and interstate decisions about the herd. For this project deer were captured on the Hallelujah Junction Wildlife Area, the Antelope Valley Wildlife Area, and a small number on summer ranges, beginning in 2006. Deer were captured by darting from the ground, and immobilized using the drugs telazole and zylazine. All but two of the collared deer were does, and each deer was fitted with a GPS collar. Collars were set to collect data every hour for a month and a half during migration (November and May) and once a day the rest of the year. Deer locations from 2006 through January of 2010 are shown in Figure 8. Using the location data collected in this study, seasonal use areas were delineated using Hawths Tools in ArcGIS. First the fixed kernel density estimator was used to calculate a grid of kernel density, and then 95% volume contours were created for summer and winter use areas. The 95% volume contour contain on average 95% of the points that were used to generate the kernel density estimate. Figures 9 and 10 illustrate summer and winter use areas for the portion of the herd covered by this study. 23 Figure 8. Locations collected by GPS collars 24 Figure 9. Summer contours – 95% of collar locations in July, August, and September occurred within the areas in red. 25 Figure 10. Winter contours – 95% of collar locations in January, February, and March occurred within the areas in blue. 26 Analysis of the telemetry data from 2006 – January 2010 also revealed information regarding the number of deer that did and did not migrate. In 2006, 1 of the 4 collared deer did not migrate (25%), and stayed at Antelope Valley Wildlife Area (AVWLA) near Palen Reservoir. This doe was captured and collared at AVWLA on 5/10/06. All locations recorded for this doe were within approximately 550 meters of each other. In 2007, 4 of the 7 collared deer did not migrate (57%), and all stayed at AVWLA where they were captured and collared. The 3 deer that migrated were captured at locations other than AVWLA. The 4 deer from AVWLA stayed within a 4-5 mile area. In 2008, 2 of the 10 collared deer did not migrate (20%), and stayed at Hallelujah Junction WLA and the private land just south of the WLA, all within 8 miles. Records show both were captured on 3/28/08 at EHJ Guz1 (East Hallelujah Junction, Guzzler 1?). In 2009, all 10 collared deer migrated. These data show that some deer do not migrate in the spring, and remain on what we have considered winter range all year. The data also show that for this sample of collared animals, all that did not migrate stayed in the area where they were captured. Verdi sub-unit The 1982 Loyalton-Truckee Deer Herd Plan describes two sub-units of the herd, the Sierra Valley sub-unit in the north and the Verdi sub-unit in the south. The studies mentioned so far in this report focused on the Sierra Valley sub-unit. A supplemental collaring project was initiated in October of 2009, which intends to track the movements of deer in the Verdi sub-unit. Specific movement related issues will be analyzed such as: 1) how the two sub-units interact, if at all; 2) how much deer movement occurs across hwy 80: and 3) How much movement into Nevada occurs. Initially the captures were conducted by CDFG wildlife staff on the Truckee Wildlife Area, plus a small number captured in the Glenshire area. NDOW has added at least 6 collared deer that were captured by helicopter. Figure 11 illustrates location information collected by 5 satellite collars as of summer 2010. These preliminary data show that the collared deer summer and give birth to their fawns along the Truckee River east of the town of Truckee, and use the Truckee River Wildlife Area extensively. In winter they migrate approximately 10 miles north and east to areas near Verdi. Two of the does cross Hwy 80 to move back and forth between their summer and winter ranges. Further data will be needed to determine where these deer cross the freeway, and where their specific migration routes are. Fall migration occurred in late November through December, and spring movements occurred in May for these collared does. 27 Figure 11. Location information from 5 satellite collared does. 28 Resident versus Migratory Deer There are both migratory and resident deer within the Loyalton-Truckee deer herd, with the resident population generally occupying portions of the winter ranges. Varying proportions of migratory and resident deer within a herd have been observed by researchers studying seasonal movements of deer (Stephenson et al., 2009, Kufeld et al., 1989; Loft et al., 1984). There are a variety of factors involved in determining if migration is advantageous. Migration typically provides access to habitats of higher quality which in turn results in increased nutrition, and often better resting and escape cover. Deer under these conditions potentially would be in better condition, leading to healthier fawns and increased reproductive success (Nicholson et al., 1997). However the possible drawbacks involved with migration may include increased predation, increased energetic costs, and disruption to migration corridors by human disturbance and barriers such as roads, residential development, and recreational use. For migration to be beneficial the costs of making the migration to and from the summer range must be outweighed by the gains associated with using that range. This balance often changes over time, as is illustrated by the following description of the Round Valley Deer study. Deer that winter in Round Valley (Mono and Inyo Counties) have undergone a substantial change in the proportion of deer that migrate over the past 20-25 years. Some of these deer travel over the Sierra Crest to summer on the west slope of the Sierra Nevada range, and the rest remain on the east side all year long. The west side summer ranges are much more mesic and forested compared to the sagebrush dominated habitats on the east side. In 1987 it was determined that >85% of the mule deer wintering in Round Valley migrated to occupy summer ranges west of the Sierra Crest, however by 2009 the proportion of does occupying summer range on either side of the Sierras had shifted to approximately 50:50 (Stephenson et al., 2009). In a long term study of Round Valley deer spanning 1997 – 2009, it was found that does summering on the east side of the Sierras have significantly higher fawn recruitment than the does summering on the west side. The same study revealed that causes of fawn mortality differ between the east and west side, with a large percentage (67%) of fawn mortality due to bear predation on the west side, and only 8% by bears on the east side. The main mortality factor on the east side was coyote predation (25%). In this instance, increased predation on the west side outweighed the benefits of the better habitat conditions, resulting in fewer fawns recruited to the population. The report points out that while bear control on the west side may result in improved fawn recruitment, the increased number of deer on the winter range would only serve to exacerbate the effects of an already forage limited winter range (Stephenson et al., 2009). 29 Each deer population has its own unique set of factors that influence migration. In some areas resident deer appear to be on the increase, and have the potential to severely impact winter range that is already overstocked with deer. During harsh winters the range may not be able to support all deer present, leading to high levels of winter mortality. Increased densities of malnourished deer also provide an environment that invites the spread of disease. Meanwhile summer range may be under-utilized by deer. Lack of deer in the forest in summer and fall is recognized by hunters as well as those that value deer for their intrinsic significance. Summary The Loyalton-Truckee Deer Herd has experienced various changes since the writing of the 1982 deer herd plan, not all of which have been detrimental to deer. Land acquisitions targeting deer habitat have conserved and protected prime deer range. Of particular note are three areas that are used extensively by this deer herd; the Hallelujah Junction and Antelope Valley Wildlife Areas in the north and the Truckee River Wildlife Area in the south. In addition, decreased livestock grazing on US Forest Service and Bureau of Land Management property may be of benefit to the deer herd. Nevertheless, issues remain that have significant negative consequences to this deer herd. The 1982 Loyalton-Truckee Deer Herd Plan described a severe decline in deer numbers during the late 1960’s and early 1970’s, and cited “a combination of factors including, but not limited to, loss of habitat through human encroachment, significant mortality on highways and railroads, reduced habitat productivity resulting from natural vegetational changes, and harassment caused by greatly increased human recreational use.” These issues still exist today, although in some cases in a slightly modified form. Fire continues to be an issue, especially in brush dominated habitats which are vital to the Loyalton-Truckee Deer Herd. A relatively new complication in the fire regime is the introduction of the invasive annual cheatgrass, which often takes over after fire and out-competes native vegetation. Once established, cheatgrass is prone to burning, decreasing the time between fires and preventing establishment of shrub species. Mortality due to highways and railroads may have decreased as the size of the deer herd has declined, however it is still a significant problem in certain areas. The Highway 89 Stewardship Project is addressing this problem in a particularly lethal stretch of Highway 89 that lies across the herd’s migration route in Sierra County. Climate has always been of concern in the context of too little or too much precipitation, and/or excessively cold winter conditions. Current views are also recognizing the issue of climate change and its possible affects on wildlife. For 30 the Loyalton-Truckee Deer Herd, there is speculation that migration into Nevada is decreasing due to warmer, drier winters. It is believed that the more severe the winter, the farther into Nevada these deer travel to reach suitable winter habitat. Habitat changes resulting from residential development and recreational use are currently the biggest concern for the future of this deer herd. Approximately 43% of the land supporting the Loyalton-Truckee Deer Herd is privately owned. A significant issue impacting this herd today involves changes in land use on private land. While changes due to development are most visible around the Reno, Nevada and Truckee, California areas, there are many areas subject to less obvious changes that nonetheless impact deer. The concept of exurban growth (rural residential development) is relatively new, and this type of development has been expanding even more quickly than human population growth. It is fortunate that there exists a large amount of US Forest Service owned land located along the main migration route to and from seasonal ranges in the northern portion of the area. This will help prevent habitat fragmentation, such is occurring in the southern part of the range, and allow migration of a major portion of this deer herd. The Verdi sub-unit of the herd appears to be in trouble, and the future of these migratory deer is not as hopeful. While there are numerous concerns regarding the health of the Loyalton-Truckee Deer Herd, there is significant work being done to ensure the long term viability of the herd. Telemetry studies are essential to expand our knowledge regarding current migration routes and seasonal use areas. Identification of areas used by deer on both public and private property will help to focus conservation efforts efficiently to support this deer herd. Within the Habitat Element of the 1982 Loyalton-Truckee Deer Herd plan the main objective is to “improve fawning success and summer range habitat capacity through habitat alteration and improvement. Protect critical winter ranges from further encroachment due to human activities; improve the capacity of winter habitats wherever possible.” These objectives are still valid, and should continue to guide acquisition and habitat improvement projects. Specific recommendations will need to be coordinated with agency biologists for the project areas. 31 Literature Cited California Department of Fish and Game. 2009. Hallelujah Junction Wildlife Area Land Management Plan. California Department of Fish and Game, Sacramento, USA. California Department of Fish and Game. 2008. Antelope Valley and Smithneck Creek Wildlife Areas Final Land Management Plan, California Department of Fish and Game, Sacramento, USA. California Department of Fish and Game. 1982. Loyalton-Truckee Deer Herd Plan. California Department of Fish and Game, Sacramento, USA. deVos, Jr. J. C, M. R. Conover, and N. E. Headrick. 2003. Mule Deer Conservation: Issues and management Strategies. Berryman Institute Press, Utah State University, Logan, USA. Kufeld, R. C., D. C. Bowden, and D. L. Schrupp. 1989. Distribution and movements of female mule deer in the Rocky Mountain foothills. The Journal of Wildlife Management, 53:871-877. Loft, E. R., J. W. Menke, and T. S. Burton. 1984. Seasonal movements and summer habitats of female black-tailed deer. The Journal of Wildlife Management, 48:1317-1325. Nicholson, M. C., R. T. Bowyer and J. G. Kie. 1997. Habitat Selection and Survival of Mule Deer: Tradeoffs Associated with Migration. Journal of Mammalogy, Vol. 78, No. 2. (May, 1997), pp. 483-504. Sommer, M. L., R. L. Barboza, R. A. Botta, E. B. Kleinfelter, M. E. Schauss and J. R. Thompson. 2007. Habitat Guidelines for Mule Deer: California Woodland Chaparral Ecoregion. Mule Deer Working Group, Western Association of Fish and Wildlife Agencies. Stephenson, T. R. and K. L. Monteith. 2009. Form 872 Post-Project Evaluation Report for Project #608.08 Population Dynamics of an Eastern Sierra Deer Herd, and Assessment of Impacts Associated with Development. Deer Herd Management Plan Implementation Program, California Department of Fish and Game. Theobald, D. 2005. Landscape patterns of exurban growth in the USA from 1980 to 2020. Ecology and Society 10(1): 32. [online] URL: http://www.ecologyandsociety.org/vol10/iss1/art32/ Wisdom, M. J., A. A. Ager, H. K. Preisler, N. J. Cimon, and B. K. Johnson. 2005. Effects of off-road recreation on mule deer and elk. Pages 67-80 in M. J. 32 Wisdom, technical editor. The Starkey Project: a synthesis of long-term studies of elk and mule deer. Reprinted from 2004 Transactions of the North American Wildlife and Natural Resources Conference, Alliance Communications Group, Lawrence, Kansas, USA. Environmental Health Perspectives • v o l u m e 120 | n u m b e r 6 | June 2012 831 Research Tropospheric ozone and black carbon (BC), a component of fine particulate matter (PM ≤ 2.5 µm in aerodynamic diameter; PM2.5), have been associated with deleterious effects on human health (e.g., Jerrett et al. 2009; Laden et al. 2006; Pope et al. 2002), agriculture (e.g., Ashmore 2005), and climate (e.g., Ramanathan and Carmichael 2008). Methane, a relatively short-lived greenhouse gas (residence time 8–10 years), is an ozone precursor that affects background ozone concentrations. Controlling methane emissions may be a promising means of simultaneously mitigating climate change and reducing global ozone concentrations, compared with controlling shorter-lived ozone precursors [nitrogen oxides (NOx), carbon monoxide (CO), and non-methane volatile organic compounds (NMVOCs)] (West et al. 2006, 2007). The latter may have larger and more immediate air quality and health benefits near the areas with emission reductions but smaller benefits (CO, NMVOC) or net disbenefits (NOx) for climate. Major anthropogenic sources of methane include fossil fuel production and distribution, landfills, livestock, rice cultivation, and wastewater treatment. BC is a product of incomplete combustion from sources such as biomass burning, transportation (mainly diesel vehicles), residential combustion, and industry, and is coemitted with other pollutants, including NOx, NMVOCs, CO, sulfur dioxide (SO2), and organic carbon. Climate benefits of reducing BC may be partially offset by associated reductions of coemitted pollutants that may have a net cooling effect on climate (and a net warming effect when reduced), either directly (organic carbon) or after chemical transformation in the atmosphere (organic carbon, SO2, and NOx). However, all emission reductions leading to reduced ozone and PM2.5 concentrations would be expected to have health benefits. Mitigating ozone and BC may ben- efit climate and health simultaneously (e.g., Jacobson 2002; Smith et al. 2009; West et al. 2006); because methane and BC are short- lived relative to the long-lived greenhouse gases [e.g., carbon dioxide (CO2)], mitigation would reduce the rate of climate change in the near-term (Jackson 2009; Ramanathan and Carmichael 2008). Although a recent series of studies has examined the ancillary health benefits of greenhouse gas mitigation (Haines et al. 2009), the health benefits of mitigating ozone and BC as climate forcers have been studied less extensively. Studies examining the health impacts of all fossil fuel and biofuel emissions (Jacobson 2010), percentage reduc- tions in ozone precursors (West et al. 2006) and BC (Anenberg et al. 2011), and adoption of European vehicle emission standards in the Address correspondence to S.C. Anenberg, U.S. Environmental Protection Agency, 1200 Pennsylvania Ave. NW, MC-6301A, Washington, DC 20460 USA. Telephone: (202) 564-2065. Fax: (202) 564-1543. E-mail: anenberg.susan@epa.gov *Current address: Eurasia Institute of Earth Sciences, Istanbul Technical University, Istanbul, Turkey. Supplemental Material is available online (http:// dx.doi.org/10.1289/ehp.1104301). We thank the United Nations Environment Programme (UNEP) and the World Meteorological Organization (WMO) for making this work pos- sible. We also thank the many coauthors and review- ers of the UNEP/WMO Integrated Assessment of Black Carbon and Tropospheric Ozone for their con- tributions along the way. The opinions expressed in this article are the authors’ and do not necessarily represent those of their employers, including the U.S. Environmental Protection Agency. The authors declare they have no actual or potential competing financial interests. Received 4 August 2011; accepted 14 March 2012. Global Air Quality and Health Co-benefits of Mitigating Near-Term Climate Change through Methane and Black Carbon Emission Controls Susan C. Anenberg,1 Joel Schwartz,2 Drew Shindell,3 Markus Amann,4 Greg Faluvegi,3 Zbigniew Klimont,4 Greet Janssens-Maenhout,5 Luca Pozzoli,5* Rita Van Dingenen,5 Elisabetta Vignati,5 Lisa Emberson,6 Nicholas Z. Muller,7 J. Jason West,8 Martin Williams,9 Volodymyr Demkine,10 W. Kevin Hicks,6 Johan Kuylenstierna,6 Frank Raes,5 and Veerabhadran Ramanathan11 1U.S. Environmental Protection Agency, Washington, DC, USA; 2Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA; 3NASA Goddard Institute for Space Studies and Columbia Earth Institute, Columbia University, New York, New York, USA; 4International Institute for Applied Systems Analysis, Laxenburg, Austria; 5European Commission, Joint Research Centre, Ispra, Italy; 6Stockholm Environment Institute, Environment Department, University of York, York, United Kingdom; 7Department of Economics, Middlebury College, Middlebury, Vermont, USA; 8Environmental Sciences and Engineering Department, Gillings School of Global Public Health, University of North Carolina–Chapel Hill, Chapel Hill, North Carolina, USA; 9Environmental Research Group, King’s College London, London, United Kingdom; 10United Nations Environment Programme, Nairobi, Kenya; 11Scripps Institution of Oceanography, University of California–San Diego, San Diego, California, USA Ba c k g r o u n d : Tropospheric ozone and black carbon (BC), a component of fine particulate matter (PM ≤ 2.5 µm in aerodynamic diameter; PM2.5), are associated with premature mortality and they disrupt global and regional climate. oB jectives : We examined the air quality and health benefits of 14 specific emission control measures targeting BC and methane, an ozone precursor, that were selected because of their potential to reduce the rate of climate change over the next 20–40 years. Me t h o d s : We simulated the impacts of mitigation measures on outdoor concentrations of PM2.5 and ozone using two composition-climate models, and calculated associated changes in premature PM2.5- and ozone-related deaths using epidemiologically derived concentration–response functions. re s u l t s : We estimated that, for PM2.5 and ozone, respectively, fully implementing these measures could reduce global population-weighted average surface concentrations by 23–34% and 7–17% and avoid 0.6–4.4 and 0.04–0.52 million annual premature deaths globally in 2030. More than 80% of the health benefits are estimated to occur in Asia. We estimated that BC mitigation mea- sures would achieve approximately 98% of the deaths that would be avoided if all BC and methane mitigation measures were implemented, due to reduced BC and associated reductions of non- methane ozone precursor and organic carbon emissions as well as stronger mortality relationships for PM2.5 relative to ozone. Although subject to large uncertainty, these estimates and conclusions are not strongly dependent on assumptions for the concentration–response function. co n c l u s i o n s : In addition to climate benefits, our findings indicate that the methane and BC emission control measures would have substantial co-benefits for air quality and public health worldwide, potentially reversing trends of increasing air pollution concentrations and mortality in Africa and South, West, and Central Asia. These projected benefits are independent of carbon dioxide mitigation measures. Benefits of BC measures are underestimated because we did not account for benefits from reduced indoor exposures and because outdoor exposure estimates were limited by model spatial resolution. key w o r d s : air quality, climate change, health impact analysis, outdoor air, particulate matter. Environ Health Perspect 120:831–839 (2012). http://dx.doi.org/10.1289/ehp.1104301 [Online 14 March 2012] Anenberg et al. 832 v o l u m e 120 | n u m b e r 6 | June 2012 • Environmental Health Perspectives developing world (Shindell et al. 2011) sug- gest that controlling methane and BC emis- sions may substantially benefit global public health, particularly in Asia where large popu- lations are exposed to high PM2.5 and ozone concentrations (Ramanathan et al. 2008). The United Nations Environment Programme (UNEP) and the World Meteorological Organization (WMO) there- fore initiated an integrated assessment of the potential climate, health, agricultural, and economic benefits that would be achieved by further implementing methane and BC mitigation measures already employed in vari- ous parts of the world (UNEP 2011). In the present study, we used emissions scenarios developed for the UNEP/WMO assessment to examine the potential air quality and health benefits of methane and BC mitigation mea- sures in more detail. Methods Emission scenarios and modeling. We used five emissions scenarios developed for the UNEP/ WMO assessment to examine methane and BC mitigation impacts on air quality and health globally and in five world regions [see Supplemental Material, Figure 1 (http://dx.doi. org/10.1289/ehp.1104301)]. These scenarios include a present-day (2005) reference case, a 2030 reference scenario that incorporates International Energy Agency energy projec- tions (International Energy Agency 2009) and all presently agreed upon (but no additional) policies affecting emissions (see Supplemental Material, Table 2 and Figure 2), and three dif- ferent policy scenarios in which varying degrees of additional emission controls are imple- mented by 2030. To isolate the impacts of anthropogenic emission changes, all scenarios assume identical meteorology and natural emissions [including open biomass burning (i.e., wildfires); year 2000]. The emission sce- narios and their projected effects on climate are detailed by Shindell et al. (2012) and are sum- marized in Supplemental Material, pp. 4–9. We selected the three policy scenarios based on an evaluation of the potential cli- mate impacts of approximately 2,000 mitiga- tion measures defined in the International Institute for Applied Systems Analysis (IIASA) Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS) model (Amann et al. 2011). Climate impacts of each measure were classified according to CO2 equivalence, which was calculated based on global warm- ing potential (GWP) over a 100-year time horizon for predicted methane, CO, SO2, NOx, NMVOCs, BC, organic carbon, and CO2 emission changes following implemen- tation of the control measure (Shindell et al. 2012). Based on this evaluation, we identified 14 individual methane and BC control mea- sures that would achieve approximately 90% of the climate benefits feasible for all of the evaluated measures combined (according to the CO2 equivalence metric). The 14 measures were grouped into three increasingly strin- gent policy scenarios for 2030 [Table 1; see also Supplemental Material, pp. 4–8 (http:// dx.doi.org/10.1289/ehp.1104301)]. The first scenario includes seven technological mea- sures for controlling methane emissions. The second adds four technological measures (BC group 1) for reducing emissions of incomplete combustion, including implementation of Euro 6 and Euro VI equivalent vehicle emis- sion standards (requiring installation of diesel particulate filters) (European Union 2010, 2011) and improving traditional biomass cook stoves in developing countries. We assumed that emission factors for cook stoves would decline in all regions to levels consistent with emissions from rocket stoves, resulting in a 25% decrease in BC and 80–90% decreases in other species, including organic matter, CO, NMVOC, methane, and direct PM2.5, relative to emissions from traditional stoves (MacCarty et al. 2008). Realistically, emission reductions from cookstoves could be lower depending on stove adoption and use; however, other stove technologies may also be more effec- tive at lowering emissions. Finally, the third and most stringent policy scenario adds three regulatory measures (BC group 2) to eliminate high-emitting vehicles, biomass cook stoves (in developing countries), and agricultural waste burning. We simulated ozone and PM2.5 concen- trations using two global composition-cli- mate models, the NASA Goddard Institute for Space Studies (GISS) model for Physical Understanding of Composition-Climate INteractions and Impacts (GISS-PUCCINI; Shindell et al. 2006), and the ECHAM- HAMMOZ model (Pozzoli et al. 2008), referred to here as GISS and ECHAM. We assumed that mitigation measures would be fully implemented and their impacts on con- centrations fully realized by 2030. Methane concentrations (accounting for chemical and biological loss processes) were averaged over years 15–19 of each simulation to realize the steady-state effects of methane reductions, although additional minor impacts may occur beyond this period. GISS has a horizontal res- olution of 2° latitude × 2.5° longitude with 40 vertical layers from the surface to 0.1 hec- topascal (hPa). ECHAM has a horizontal reso- lution of 2.8° × 2.8° and 31 vertical layers up to 10 hPa. Both models simulate BC, organic carbon, SO4, sea salt, and dust. GISS also includes nitrate (NO3). We multiplied simu- lated organic carbon concentrations by 1.4 to estimate total organic matter concentrations (Cooke et al. 1999). Using a different conver- sion factor would affect organic matter concen- trations proportionally. Because these coarse model resolutions cannot capture fine con- centration gradients, particularly for primary PM2.5 species (BC and organic carbon) around urban areas, we allocated BC and organic carbon to 0.5° × 0.5° resolution according to population density, following Shindell et al. (2011; see their Supplemental Information). All other species, including ozone, SO4, and NO3, were simply regridded to 0.5° × 0.5° resolution, because secondary pollutants are generally more spatially homogeneous. For the main results, we excluded dust and sea salt (which are assumed to be natural) and use the health impact function described below. We also examined the sensitivity of mortality results to inclusion of dust and sea salt and to Table 1. Description of the 14 methane and BC mitigation measures included in the three increasingly stringent policy scenarios for 2030. Scenario Mitigation measure Methane measures: technical measures for methane emissions Extended pre-mine degasification and recovery and oxidation of methane from ventilation air from coal mines Extended recovery and use—rather than venting—of associated gas and improved control of unintended fugitive emissions from the production of oil and natural gas Reduced gas leakage from long-distance transmission pipelines Separation and treatment of biodegradable municipal waste through recycling, composting, and anaerobic digestion as well as landfill gas collection with combustion/utilization Upgrading primary wastewater treatment to secondary/tertiary treatment with gas recovery and overflow control Control of methane emissions from livestock, mainly through farm-scale anaerobic digestion of manure from cattle and pigs Intermittent aeration of continuously flooded rice paddies BC group 1: technical measures for reducing emissions of incomplete combustion Diesel particle filters as part of a Euro VI package for road and off-road diesel vehicles Introduction of clean-burning stoves for cooking and heating in developing countries Replacing traditional brick kilns with vertical shaft kilns and Hoffman kilns Replacing traditional coke ovens with modern recovery ovens, including the improvement of end-of-pipe abatement measures in developing countries BC group 2: nontechnical measures to eliminate the most polluting activities Elimination of high-emitting vehicles in road and off-road transport (excluding shipping) Ban of open field burning of agricultural waste Substitution of clean-burning cook stoves using modern fuels for traditional biomass cook stoves in developing countries Health impacts of black carbon and methane controls Environmental Health Perspectives • v o l u m e 120 | n u m b e r 6 | June 2012 833 different magnitudes and shapes of the health impact function. Health impact assessment. We used epidemiologically derived health impact functions to estimate changes in premature PM2.5- and ozone-related mortality between the 2030 reference scenario and 2005, and between the 2030 reference scenario and the three policy scenarios individually, using 2030 population projections for all scenario comparisons to isolate the impacts of simulated concentration changes. We assumed log-linear relationships between PM2.5 or ozone concentrations and relative risks (RR), following Anenberg et al. (2010), and calculated the fraction of baseline deaths attributable to a given change in concentration (attributable fraction; AF) as AF = (RR – 1)/RR = 1 – exp–β∆X, [1] where β is the concentration–response factor (CRF, the estimated slope of the log-linear relation between PM2.5 or ozone concentra- tion and mortality) and ∆X is the change in pollutant concentration. We multiplied AF by the baseline mortality rate (y0) and population size (Pop) to estimate the change in premature deaths (∆Mort) that would result from a given change in concentration (∆X): ∆Mort = y0 × Pop × (1 – exp–β∆X). [2] Because disease survival times vary among populations, we estimated the change in years of life lost (∆YLL) due to a change in prema- ture deaths using the baseline YLL (YLL0) per death: ∆YLL = ∆Mort × YLL0/y0. [3] We applied Equations 2 and 3 in each 0.5° × 0.5° grid cell using corresponding population sizes, baseline mortality and YLL rates, and the simulated changes in PM2.5 and ozone concentrations. We calculated CRFs for PM2.5 based on long-term RR estimates starting from the American Cancer Society (ACS) cohort study (Pope et al. 2002). Specifically, for a 10-µg/m3 increase in annual average PM2.5, RRs for all-cause, cardiopulmonary disease, and lung cancer mortality were 1.06 [95% confidence interval (CI): 1.02, 1.11), 1.09 (95% CI: 1.03, 1.16), and 1.14 (95% CI: 1.04, 1.23), respectively, when averaged based on data for 1979–1983 and 1999–2000. Although the ACS cohort was large compared with other PM2.5 cohort studies [e.g., the Harvard Six Cities Study (Laden et al. 2006)], results may underestimate the PM2.5–mortality relationship because well-educated affluent populations are overrepresented in the cohort and because exposure was measured with greater error than in other studies. A 2008 expert elicitation (including ACS authors) produced a mean all-cause mortality CRF estimate [approximately 1.1% mortality increase per 1-µg/m3 increase in PM2.5 (Roman et al. 2008)] that was between the CRFs calculated from the ACS (~ 0.6%) and Harvard Six Cities Study (~ 1.6%) RR estimates. The expert elicitation (Roman et al. 2008), however, did not estimate cause- specific RRs, which may be more applicable globally than all-cause mortality. We therefore multiplied the cause-specific CRFs calculated from the Pope et al. (2002) RR estimates by 1.8, the factor difference between the all-cause CRFs from the expert elicitation mean and Pope et al. (2002). A newer ACS reanalysis reported 40% higher cardiopulmonary effect estimates with tighter confidence intervals for all RR estimates (Krewski et al. 2009), but Figure 1. Estimated changes in annual average PM2.5 (µg/m3) and seasonal (6‑month) average 1‑hr daily maximum ozone (ppb) concentration for the 2030 reference scenario relative to 2005, based on the GISS and the ECHAM models. GISS, PM2.5 GISS, ozone ppbµg/m3 ECHAM, PM2.5 ECHAM, ozone –5 50 010–10 Anenberg et al. 834 v o l u m e 120 | n u m b e r 6 | June 2012 • Environmental Health Perspectives these results were not available for the expert elicitation. Therefore, we examined the effect of these RRs in a sensitivity analysis only. Other recent cohort studies have reported considerably larger estimated effect sizes than the expert mean judgment (e.g., Miller et al. 2007; Puett et al. 2009), suggesting that our approach is conservative. Although some BC-rich PM2.5 mixtures may be more toxic than other mixtures (Maynard et al. 2007; Smith et al. 2009), we assumed that all PM2.5 components and mixtures are equally toxic because evidence for differential toxicity is currently inconclusive. For ozone, we used long-term RR esti- mates from the ACS cohort (Jerrett et al. 2009) based on a two-pollutant model that controlled for PM2.5, in which ozone was sig- nificantly associated only with death from respiratory causes. For a 10-ppb increase in the seasonal (6-month) average of 1-hr daily maximum ozone, the RR of respiratory dis- ease was 1.04 (95% CI: 1.010, 1.067). The study by Jerrett et al. (2009) was the first major study to find a significant positive rela- tionship between chronic ozone exposure and mortality in a general population; biologi- cal plausibility for this result is supported by evidence from toxicology and human expo- sure studies showing that ozone affects air- way inflammation, pulmonary function, and asthma induction and exacerbation (National Resource Council 2008). Global extrapolation of U.S.-based RR estimates for both PM2.5 and ozone is supported by generally consis- tent short-term PM2.5 and ozone mortality relationships around the world (e.g., Health Effects Institute 2010). We used simulated concentrations in the first model layer for surface concentrations, and used annual average concentrations for PM2.5 and the maximum 6-month average of the 1-hr daily maximum for ozone, consistent with the epidemiology studies. We projected population growth (global population is pro- jected to increase to 8.4 billion in 2030) based on the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios (SRES) B2 scenario, which is near the center of projected population growth estimates for the different SRES scenarios (Intergovernmental Panel on Climate Change 2000). We esti- mated mortality only for the fraction of the population ≥ 30 years of age to be consistent with the age range of the ACS cohort, and we used present-day baseline mortality and YLL rates from the World Health Organization as described previously by Anenberg et al. (2010). Results Impacts of the future reference scenario. Both the GISS and ECHAM models indicated that PM2.5 and ozone concentrations would change dramatically, and with great spatial variability around the world, in the 2030 reference sce- nario relative to baseline estimates for 2005 (Figure 1). Projected concentration changes are solely due to emission changes because meteorology was held constant. Changes in climate would also impact concentrations to a lesser degree (e.g., Jacobson 2008). We estimated that these concentration changes would substantially affect air pollution- related mortality around the world. Unless otherwise specified, ranges reported for expected changes in mortality and YLL represent the lowest and highest 95% CI bounds estimated using either the GISS or the ECHAM model, where the 95% CIs reflect uncertainty in the CRF. We expect that regulations that are currently in place or planned in North America and Europe will reduce PM2.5 and ozone concentrations substantially, resulting in 0.1–0.8 million avoided PM2.5-related deaths per year (0.5–4.8 million YLL) in 2030, with the majority of avoided deaths in Europe [Figure 2; see also Supplemental Material, Figures 4 and 5 (http://dx.doi.org/10.1289/ ehp.1104301)]. Regulations are also expected to reduce PM2.5 concentrations in East Asia, Southeast Asia, and the Pacific, resulting in 0.1–1.1 million avoided PM2.5-related deaths (0.4–7.7 million YLL) annually, based on 2030 population projections. However, we estimated Table 2. Global simple and population‑weighted (Pop‑wt) average reductions in annual average PM2.5 (µg/m3) and maximum 6‑month average 1‑hr daily maxi‑ mum ozone (ppb) concentrations, avoided PM2.5 cardiopulmonary and lung cancer deaths and ozone respiratory deaths (millions), and avoided YLL (millions) based on 2030 population projections for increasingly stringent mitigation policies relative to the baseline scenario for 2030. Methane measures Methane and BC group 1 measures Methane, BC group 1, and BC group 2 measures Result PM2.5 Ozone PM2.5 Ozone PM2.5 Ozone Simple average GISS –0.01 3.08 0.15 5.34 0.22 5.66 ECHAM –0.03 3.60 0.18 4.00 0.27 3.92 Pop-wt average GISS –0.03 2.82 2.90 9.95 3.98 11.0 ECHAM –0.12 4.09 3.59 4.96 4.92 4.71 Avoided deaths GISS –0.02 (–0.01, –0.03)0.07 (0.02, 0.11)1.39 (0.46, 2.47)0.28 (0.09, 0.47)1.93 (0.63, 3.48)0.31 (0.10, 0.52) ECHAM –0.06 (–0.02, –0.11)0.10 (0.03, 0.17)1.74 (0.57, 3.12)0.13 (0.04, 0.21)2.42 (0.78, 4.40)0.12 (0.04, 0.20) Avoided YLL GISS –0.12 (–0.04, –0.21)0.61 (0.20, 1.01)11.8 (3.85, 21.0)2.54 (0.82, 4.28)16.2 (5.25, 29.3)2.81 (0.90, 4.74) ECHAM –0.59 (–0.20, –1.01)0.94 (0.31, 1.56)14.9 (4.86, 26.6)1.15 (0.38, 1.92)20.5 (6.63, 37.4)1.06 (0.35, 1.76) 95% CIs (shown in parentheses) reflect uncertainty in the CRFs for PM2.5‑ and ozone‑related mortality only. Estimates are based on simulations using the GISS and ECHAM models. Figure 2. Estimated changes in premature PM2.5‑related mortality (cardiopulmonary and lung cancer deaths) and ozone‑related mortality (respiratory deaths) for the 2030 reference scenario and assuming implementation of methane plus BC group 1 and BC group 2 (all) measures relative to 2005, based on 2030 population projections. 95% CIs reflect uncertainty in the CRF only. 2 1 0 –1 –2 –3 Pr e m a t u r e d e a t h s ( m i l l i o n s ) Africa Latin America and Carribean North America and Europe South, West, and Central Asia East Asia, Southeast Asia, and Pacific 2030 reference, GISS 2030 reference, ECHAM All measures, GISS All measures, ECHAM Health impacts of black carbon and methane controls Environmental Health Perspectives • v o l u m e 120 | n u m b e r 6 | June 2012 835 that increased ozone concentrations in East Asia, Southeast Asia, and the Pacific would cause 0–0.2 million additional premature ozone-related deaths (0.1–1.4 million YLL) per year. In addition, increased PM2.5 and ozone concentrations in South, West, and Central Asia resulting from rapid emissions growth would cause an estimated 0.1–1.8 million (1.2– 15.9 million YLL) additional PM2.5-related premature deaths and 0–0.2 million (0.1–2.4 million YLL) additional ozone-related premature deaths annually. Benefits of the mitigation measures. Relative to the 2030 reference scenario, implement- ing the methane measures (Table 1) would decrease seasonal (6-month) average 1-hr daily maximum ozone concentrations by 3–4 ppb (Table 2 and Figure 3). Projected ozone con- centrations decreased fairly evenly across the globe due to the relatively longer lifetime of methane compared with other ozone precur- sors (e.g., NOx, VOCs). However, simulated annual average PM2.5 concentrations increased slightly from northern Africa to the Indian subcontinent in response to the methane mea- sures due to particle formation resulting from changes in oxidant concentrations (Table 2 and Figure 4), as demonstrated previously by West et al. (2006). However, when BC and methane measures were applied together, these increases Figure 3. Estimated changes in seasonal (6‑month) average 1‑hr daily maximum ozone concentration (ppb) in 2030 for successive implementation of methane measures, methane plus BC group 1 measures, and methane plus BC group 1 and BC group 2 (all) measures, relative to the 2030 reference scenario, based on the GISS and the ECHAM models. GISS, methane measures ECHAM, methane measures GISS, and BC group 1 measures GISS, all measures –30 300 ECHAM, all measures ECHAM, and BC group 1 measures ppb Anenberg et al. 836 v o l u m e 120 | n u m b e r 6 | June 2012 • Environmental Health Perspectives were projected only by the ECHAM model and were limited to a small area off the coast of eastern Africa and India. Adding the BC measures would reduce population-weighted PM2.5 concentrations by 4–5 µg/m3 compared with the 2030 reference scenario. Adding BC measures would also decrease ozone concen- trations due to reductions in coemitted ozone precursors, but GISS projected larger reduc- tions (11 ppb reduction when methane and BC measures were applied together) than did ECHAM (5 ppb reduction). Projected reduc- tions in ozone concentrations resulting from the BC measures were localized near the emis- sions sources (primarily in South and East Asia where emissions are largest) because of the short atmospheric lifetime of the ozone precur- sors that are affected by the BC measures [NOx and CO; see Supplemental Material, Figure 3 (http://dx.doi.org/10.1289/ehp.1104301)]. Spatial patterns of simulated concentration changes were similar for both models, but GISS projections for ozone were more sensi- tive to precursors that would be affected by BC measures, whereas ECHAM projected greater reductions in ozone in response to the methane measures and greater reductions in PM2.5 in response to BC measures. We estimated that implementing all mea- sures would avoid 0.6–4.4 million PM2.5- related deaths (5.3–37.4 million YLL) and 0.04–0.52 million ozone-related deaths (0.35–4.7 million YLL) in 2030 [Table 2; see also Supplemental Material, Figures 6–9 (http://dx.doi.org/10.1289/ehp.1104301)]. For both models, > 80% of the estimated mortality benefits from implementation of all three groups of measures would occur in Asia, where large populations are exposed to high Figure 4. Estimated changes in annual average PM2.5 concentration (µg/m3) in 2030 for successive implementation of methane measures, methane plus BC group 1 measures, and methane plus BC group 1 and BC group 2 (all) measures, relative to the 2030 reference scenario, based on the GISS and the ECHAM models. GISS, methane measures ECHAM, methane measures GISS, methane and BC group 1 measures GISS, all measures –5 50 ECHAM, all measures ECHAM, methane and BC group 1 measures µg/m3 Health impacts of black carbon and methane controls Environmental Health Perspectives • v o l u m e 120 | n u m b e r 6 | June 2012 837 concentrations (Table 3). BC groups 1 and 2 measures (four technological measures for reducing emissions of incomplete combustion and three nontechnical measures to reduce the most polluting activities, respectively) would account for 72% and 26% of avoided deaths globally for either model. In contrast, estimated global mortality benefits of the methane mea- sures were an order of magnitude smaller than those of the BC measures (approximately 2%), because of reductions of non-methane ozone precursor and organic carbon emissions associ- ated with implementation of the BC measures and because of stronger relationships of PM2.5 with mortality. The estimated contribution of each policy measure to the total mortality benefit in each region generally followed the global contributions. When low-carbon CO2 measures (decrease in use of fossil fuel) were included in both the reference and policy sce- narios, estimates showed approximately 10% fewer avoided deaths in East Asia, Southeast Asia, and the Pacific and in South, West, and Central Asia [see Supplemental Material, Figure 10 (http://dx.doi.org/10.1289/ ehp.1104301)]. Implementing the methane and BC measures would reduce mortality sub- stantially in all regions, and in some regions (Africa and South, West, and Central Asia) would reverse trends of increasing mortality due to air pollution (Figure 2). Sensitivity analysis. We examined the effect of varying CRF assumptions on esti- mated avoided deaths from implementing all methane and BC measures (Figure 5). In the main results (case 1), we excluded dust and sea salt because evidence for toxicity of these components is weaker than that for particulate products of incomplete combustion. Including dust and sea salt would have increased esti- mated PM2.5 concentrations from a maximum of 62–73 µg/m3 (in the main results) to a max- imum of 269–451 µg/m3. Whereas linearity of the CRF has been demonstrated up to 30 µg/ m3 in the ACS study (Krewski et al. 2009) and up to 40 µg/m3 in the Harvard Six Cities study (Laden et al. 2006), some evidence sug- gests that the PM2.5 mortality relationship may flatten at high concentrations (e.g., Pope et al. 2009). We therefore examined several sensitivity cases in which the shape of the CRF was varied. Case 1 represented our baseline assumptions of linear CRFs from Pope et al. (2002) multiplied by 1.8 to scale up to the mean of the expert elicitation (Roman et al. 2008), that is, that cardiopulmonary and lung cancer mortality would increase by 1.6% and 2.4% with each 1-µg/m3 increase in PM2.5, as in the main results (case 1). For case 2 we used log CRFs from Pope et al. (2002), multiplied by 1.8, such that the slopes of the relation between log-transformed PM2.5 concentra- tion and cardiopulmonary and lung cancer mortality, respectively, were 0.2794 and 0.4180 (0.1552 and 0.2322 prior to scaling, as reported by Cohen et al. 2004). Case 3 was identical to case 2, except the log CRFs were modified to be linear below 7 µg/m3. Cases 4 and 5 were identical to cases 2 and 3 except they included dust and sea salt in estimated total PM2.5 concentrations. Because dust and sea salt were not significantly affected by the mitigation measures, using linear functions with dust and sea salt produced results that were similar to case 1. Two additional sensitiv- ity cases examined the effect of using linear CRFs from the latest ACS reanalysis in which cardiopulmonary and lung cancer mortality increased by 1.3% and 1.4%, respectively, with each 1-µg/m3 increase in PM2.5 (Krewski et al. 2009; case 6) and linear CRFs from the latest Harvard Six Cities reanalysis in which cardiopulmonary and lung cancer mortal- ity increased by 2.8% and 2.7% with each 1-µg/m3 increase in PM2.5 (Laden et al. 2006; case 7). The significantly higher RR estimates reported by Laden et al. (2006) are still lower than estimates from other studies with less exposure error (e.g., Puett et al. 2009). Compared with regional avoided deaths estimated using a linear function, those esti- mated using log functions without dust and sea Table 3. Distributions of estimated numbers of avoided premature deaths according to policy measures and world regions, relative to the 2030 reference scenario. Percent of avoided deaths attributed to each group of policy measuresa Percent of all avoided deaths resulting from implementation of policy measuresb Region Methane BC Group 1 BC Group 2 Methane Methane and BC Group 1 Methane, BC Group 1 and BC Group 2 Global GISS 2.36 72.09 25.55 ECHAM 1.62 72.09 26.29 Africa GISS 3.62 74.36 22.01 12.77 8.71 8.32 ECHAM 2.78 72.88 24.34 17.84 10.68 10.40 East Asia, Southeast Asia, and Pacific GISS 2.22 68.52 29.26 38.14 38.48 40.50 ECHAM 6.29 64.27 29.45 130.84 32.34 33.79 Latin America and Caribbean GISS 9.67 64.36 25.96 7.37 1.79 1.80 ECHAM 12.0 54.71 33.26 13.72 1.68 1.85 North America and Europe GISS 6.53 68.76 24.70 11.94 4.36 4.31 ECHAM 3.81 60.63 35.56 12.29 4.58 5.24 South, West, and Central Asia GISS 1.56 75.50 22.94 29.78 46.66 45.08 ECHAM –2.49 79.23 23.26 –74.69 50.73 48.72 aThe individual impact of each group of policy measures is estimated based on the difference in mortality with the imple‑ mentation of the increasingly stringent policy scenarios; the total for each row equals 100%. bProportions of avoided deaths associated with the successive implementation of the policy scenarios; column totals for each model (GISS or ECHAM) equal 100%. Figure 5. Estimated annual PM2.5‑related cardiopulmonary and lung cancer deaths assuming implementa‑ tion of methane plus BC group 1 and BC group 2 (all) measures relative to the 2030 reference scenario using concentrations simulated by the GISS model and different assumptions for the CRF, based on 2030 population projections. Africa Latin America and Carribean North America and Europe South, West, and Central Asia East Asia, Southeast Asia, and Pacific 3.0 2.5 2.0 1.5 1.0 0.5 0 Av o i d e d d e a t h s ( m i l l i o n s ) Case 1: Pope et al. (2002) × 1.8, linear Case 2: Pope et al. (2002) × 1.8, log Case 3: Pope et al. (2002) × 1.8, log with linear modification Case 4: case 2 with dust and sea salt Case 5: case 3 with dust and sea salt Case 6: Krewski et al. (2009), linear Case 7: Laden et al. (2006), linear Anenberg et al. 838 v o l u m e 120 | n u m b e r 6 | June 2012 • Environmental Health Perspectives salt (case 2) were 1.2–8.3 times higher and had larger differences in the least polluted regions due to a higher marginal impact of PM2.5 on mortality for the log functions at low concen- trations. When dust and sea salt were included in PM2.5 concentrations (case 4), estimates were 12–29% lower in Asia (where PM2.5 concentrations are high) and 1.4–4.6 times higher in less-polluted regions. Modifying the functions to be linear at low concentrations (cases 3 and 5) reduced the inflated estimates that occurred in relatively unpolluted regions when log functions were used. Using RR estimates from Krewski et al. (2009; case 6) reduced estimated deaths by approximately 25% relative to the main results. Although RR estimates by Krewski et al. (2009) are higher than those reported by Pope et al. (2002), we multiplied CRFs from Pope et al. (2002) by 1.8 for the main results. Using RR estimates from the Harvard Six Cities cohort (case 7) increased estimates by approximately 60%. Uncertainty ranges were large for each case, with the exception of case 6, because Krewski et al. (2009) estimated more precise RRs than the other studies. However, confidence inter- vals overlapped among estimates from all of the sensitivity analyses. Discussion and Conclusion We estimated the potential future air qual- ity and health benefits resulting from imple- menting 14 specific methane and BC emission control measures selected for their near-term climate benefits (Table 1). We estimate that these measures could reduce global population- weighted average surface PM2.5 and ozone con- centrations by 3.98–4.92 µg/m3 (23.0–33.7%) and 4.71–11.0 ppb (6.5–17.0%), respectively, and avoid 0.6–4.4 and 0.04–0.52 million annual premature deaths globally in 2030. More than 80% of the health benefits of these measures are estimated to occur in Asia. Based on our estimates, avoided deaths would repre- sent 1–8% of cardiopulmonary and lung can- cer deaths among those ≥ 30 years of age and 1–7% of all deaths for all ages, assuming con- stant baseline mortality rates. BC mitigation measures would account for approximately 98% of the estimated deaths avoided, because BC mitigation would also reduce emissions of non-methane ozone precursors and organic carbon and because concentration–response relationships are stronger for PM2.5 than for ozone. Our estimates are consistent with pre- vious health impact assessments of BC and methane reductions (Anenberg et al. 2011; Shindell et al. 2011; West et al. 2006) after accounting for methodological differences [see Supplemental Material, p. 16 (http://dx.doi. org/10.1289/ehp.1104301)]. We used two global composition-climate models (GISS and ECHAM) to improve con- fidence in our results, and sensitivity analysis indicated that our results and conclusions are not strongly dependent on assumptions for the CRF. However, we were unable to quantify other uncertainties associated with estimating air pollution mortality on a global scale, including uncertainties in the atmospheric model assumptions and inputs (e.g., emissions) and in estimates of popula- tion growth and baseline mortality rates. We applied U.S.-based CRFs globally, despite differences in concentrations, air pollutant mixtures, and exposure and population sus- ceptibility characteristics. We assumed that all PM2.5 mixtures are equally toxic, despite some evidence that BC-rich mixtures are more toxic than the average (e.g., Smith et al. 2009). These uncertainties may cause under- or over- estimation in the results. The benefits of implementing BC mea- sures are likely to have been underestimated because we did not account for health benefits of reduced indoor exposure from the burning of solid fuel, which has been estimated to cause 1.6 million premature deaths annually (Smith et al. 2004). In addition, while we downscaled modeled BC and organic carbon concentra- tions to a finer resolution grid, observed BC concentrations near highly populated regions that rely on biomass combustion for cooking and heating are orders of magnitude higher than the grid mean values used here (Rehman et al. 2011). We also did not consider ben- efits from reductions in noncarbonaceous pri- mary PM2.5 components (e.g., fly ash) that may result from the BC mitigation measures. We estimate that including noncarbonaceous primary PM2.5 components would reduce total PM2.5 emissions by an additional 18% [see Supplemental Material, Figure 3 (http:// dx.doi.org/10.1289/ehp.1104301)] but would have a smaller effect on PM2.5 concentration changes (and associated mortality changes), because some PM2.5 components included in the PM2.5 definition are not emitted directly but are formed in the atmosphere. We did not estimate effects of air pollution on morbidity or infant mortality because of concerns about the quality and availability of concentration– response functions and baseline incidence data globally. We also did not consider health effects of climate change (e.g., direct effects of temperature), which vary across locations and are poorly understood. Finally, we held present-day baseline mortality rates constant to 2030, although economic development around the world is reducing mortality from infectious disease and increasing mortality due to chronic diseases that are more affected by air pollution. Hence the overall health benefits of these interventions are likely to be understated. The UNEP/WMO assessment demonstrated that further implementation of methane and BC emissions control measures currently employed in some parts of the world can slow the rate of climate change in the decades following implementation (Shindell et al. 2012; UNEP 2011). We conclude that these measures can also substantially benefit global public health, potentially reversing trends of increasing concentrations and air pollution-related mortality in Africa and South, West, and Central Asia. These estimated benefits are independent of CO2 mitigation measures. Future research should include both indoor and outdoor concentration changes to quantify the full health and climate benefits of cook stove replacement, and should quantify the benefits and costs of each measure in individual countries or regions to support national-scale policy decisions. Refe R ences Amann M, Bertok I, Borken‑Kleefeld J, Cofala J, Heyes C, Hoglund‑Isaksson L, et al. 2011. Cost‑effective control of air quality and greenhouse gases in Europe: modeling and policy applications. Environ Modelling Software 26:1489–1501. Anenberg SC, Horowitz LW, Tong DQ, West JJ. 2010. An estimate of the global burden of anthropogenic ozone and fine par‑ ticulate matter on premature human mortality using atmo‑ spheric modeling. Environ Health Perspect 118:1189–1195. Anenberg SC, Talgo K, Arunachalam S, Dolwick P, Jang C, West JJ. 2011. Impacts of global, regional, and sectoral black carbon emission reductions on surface air quality and human mortality. Atmos Chem Phys 11:7253–7267. Ashmore MR. 2005. Assessing the future global impacts of ozone on vegetation. Plant Cell Environ 28:949–964. Cohen AJ, Anderson HR, Ostro B, Pandey KD, Krzyzanowski M, Künzli N, et al. 2004. Urban air pollution. In: Comparative Quantification of Health Risks: Global and Regional Burden of Disease due to Selected Major Risk Factors (Ezzati M, Lopez AD, Rodgers A, Murray CJL, eds). Geneva:World Health Organization, 1353–1434. Available: http://www.who. int/healthinfo/global_burden_disease/cra/en/ [accessed 24 April 2012]. Cooke WF, Liouss C, Cachier H, Feichter J. 1999. Construction of a 1x1 fossil fuel emission data set for carbonaceous aerosol and implementation and radiative impact in the ECHAM4 model. J Geophys Res 104:22137–22162. European Union. 2010. Emissions from Heavy Duty Vehicles (Euro VI): Certification Rules. Available: http://europa.eu/ legislation_summaries/environment/air_pollution/mi0029_ en.htm [accessed 25 April 2012]. European Union. 2011. Reduction of Pollutant Emissions from Light Vehicles. Available: http://europa.eu/legislation_ summaries/environment/air_pollution/l28186_en.htm [accessed 25 April 2012]. Haines A, McMichael AJ, Smith KR, Roberts I, Woodcock J, Markandya A, et al. 2009. Public health benefits of strate‑ gies to reduce greenhouse‑gas emissions: overview and implications for policy makers. Lancet 374:2104–2114. Health Effects Institute. 2010. Public Health and Air Pollution in Asia (PAPA): Coordinated Studies of Short‑Term Exposure to Air Pollution and Daily Mortality in Four Cities. HEI Research Report 154. Boston:Health Effects Institute. Intergovernmental Panel on Climate Change. 2000. Special Report on Emissions Scenarios: A Special Report of Working Group III of the Intergovernmental Panel on Climate Change. Cambridge, UK:Cambridge University Press. International Energy Agency. 2009. World Energy Outlook 2009. Paris:International Energy Agency. Jackson SC. 2009. Parallel pursuit of near‑term and long‑term climate mitigation. Science 326:526–527. Jacobson MZ. 2002. Control of fossil‑fuel particulate black carbon and organic matter, possibly the most effective method of slowing global warming. J Geophys Res 107:4410; doi:10.1029/2001JD001376 [Online 15 October 2002]. Jacobson MZ. 2008. On the causal link between carbon dioxide and air pollution mortality. Geophys Res Lett 35:L03809; doi:10.1029/2007GL031101 [Online 12 February 2008]. Jacobson MZ. 2010. Short‑term effects of controlling fossil‑fuel Health impacts of black carbon and methane controls Environmental Health Perspectives • v o l u m e 120 | n u m b e r 6 | June 2012 839 soot, biofuel soot and gases, and methane on climate, Arctic ice, and air pollution health. J Geophys Res 115:D14209: doi:10.1029/2009JD013795 [Online 29 July 2010]. Jerrett M, Burnett RT, Pope CA III, Ito K, Thurston G, Krewski D, et al. 2009. Long‑term ozone exposure and mortality. N Engl J Med 360:1085–1095. Krewski D, Jerrett M, Burnett RT, Ma R, Hughes E, Shi Y, et al. 2009. Extended Follow‑up and Spatial Analysis of the American Cancer Society Study Linking Particulate Air Pollution and Mortality. Boston:Health Effects Institute. Laden F, Schwartz J, Speizer FE, Dockery DW. 2006. Reduction in fine particulate air pollution and mortality: extended follow‑up of the Harvard Six Cities study. Am J Resp Crit Care Med 173:667–672. MacCarty N, Ogle D, Still D, Bond T, Roden C. 2008. A laboratory comparison of the global warming impact of five major types of biomass cooking stoves. Energy Sustainable Dev 12:56–65. Maynard D, Coull BA, Gryparis A, Schwartz J. 2007. Mortality risk associated with short‑term exposure to traffic particles and sulfates. Environ Health Perspect 115:751–755. Miller KA, Siscovick DS, Sheppard L, Shepherd K, Sullivan JH, Anderson GL, et al. 2007. Long‑term exposure to air pollution and incidence of cardiovascular events in women. N Engl J Med 356:447–458. National Research Council. 2008. Estimating Mortality Risk Reduction and Economic Benefits from Controlling Ozone Air Pollution. Washington, DC:National Academies Press. Pope CA III, Burnett RT, Krewski D, Jerrett M, Shi Y, Calle EE, et al. 2009. Cardiovascular mortality and exposure to air‑ borne fine particulate matter and cigarette smoke: shape of the exposure‑response relationship. Circulation 120:941–948. Pope CA III, Burnett RT, Thun MJ, Calle EE, Krewski D, Ito K, et al. 2002. Lung cancer, cardiopulmonary mortality, and long‑term exposure to fine particulate air pollution. JAMA 287:1132–1141. Pozzoli L, Bey I, Rast S, Schultz MG, Stier P, Feichter J. 2008. Trace gas and aerosol interactions in the fully coupled model of aerosol‑chemistry‑climate ECHAM5‑HAMMOZ: 1. Model description and insights from the spring 2001 TRACE‑P experiment. J Geophys Res 113:D07308; doi:10.1029/2007JD009007 [Online 15 April 2008]. Puett RC, Hart J, Yanosky JD, Paciorek C, Schwartz J, Suh H, et al. 2009. Chronic fine and coarse particulate exposure, mortality, and coronary heart disease in the Nurses’ Health Study. Environ Health Perspect 117:1702–1706. Ramanathan V, Agrawal M, Akimoto H, Aufhammer M, Devotta S, Emberson L, et al. 2008. Atmospheric Brown Clouds: Regional Assessment Report with Focus on Asia. Nairobi, Kenya:United Nations Environment Programme. Ramanathan V, Carmichael G. 2008. Global and regional climate changes due to black carbon. Nat Geosci 1:221–227. Rehman IH, Ahmed T, Praveen PS, Kar A, Ramanathan V. 2011. Black carbon emissions from biomass and fossil fuels in rural India. Atmos Chem Phys 11:7289–7299. Roman HA, Walker KD, Walsh TL, Conner L, Richmond HM, Hubbell BJ, et al. 2008. Expert judgment assessment of the mortality impact of changes in ambient fine particulate matter in the U.S. Environ Sci Technol 42:2268–2274. Shindell DT, Faluvegi G, Unger N, Aguilar E, Schmidt GA, Koch DM, et al. 2006. Simulations of preindustrial, present‑ day, and 2100 conditions in the NASA GISS composition and climate model G‑PUCCINI. Atmos Chem Phys 6:4427–4459. Shindell D, Faluvegi G, Walsh M, Anenberg SC, Van Dingenen R, Muller NZ, et al. 2011. Climate, health, agricultural and economic impacts of tighter vehicle‑emission standards. Nat Clim Change 1:59–66. Shindell D, Kuylenstierna JCI, Vignati E, Van Dingenen R, Amann M, Klimont Z, et al. 2012. Simultaneously mitigating near‑term climate change and improving human health and food security. Science 335:183–189. Smith KR, Jerrett M, Anderson HR, Burnett RT, Stone V, Derwent R, et al. 2009. Public health benefits of strategies to reduce greenhouse‑gas emissions: health implications of short‑lived greenhouse pollutants. Lancet 374:2091–2103. Smith KR, Mehta S, Maeusezahl‑Feuz M. 2004. Indoor air pol‑ lution from household use of solid fuels. In: Comparative Quantification of Health Risks: Global and Regional Burden of Disease Attribution to Selected Major Risk Factors (Ezzati M, Lopez AD, Rodgers A, Murray CJL, eds). Geneva:World Health Organization, 1435–1493. UNEP (United Nations Environment Programme). 2011. Opportunities to Limit Near‑Term Climate Change: An Integrated Assessment of Black Carbon and Tropospheric Ozone and Its Precursors. Nairobi, Kenya:United Nations Environment Programme and World Meteorological Organization. West JJ, Fiore AM, Horowitz LW, Mauzerall DL. 2006. Global health benefits of mitigating ozone pollution with methane emission controls. Proc Natl Acad Sci USA 103:3988–3993. West JJ, Szopa S, Hauglustaine DA. 2007. Human mortality effects of future concentrations of tropospheric ozone. C R Geosci 339:775–783. Report to Congress on Black Carbon March 2012 Department of the Interior, Environment, and Related Agencies Appropriations Act, 2010 United States Environmental Protection Agency iiiReport to Congress on Black Carbon Highlights y Black carbon (BC) is the most strongly light- absorbing component of particulate matter (PM), and is formed by the incomplete combustion of fossil fuels, biofuels, and biomass. y BC is emitted directly into the atmosphere in the form of fine particles (PM2.5). The United States contributes about 8% of the global emissions of BC. Within the United States, BC is estimated to account for approximately 12% of all direct PM2.5 emissions in 2005. y BC contributes to the adverse impacts on human health, ecosystems, and visibility associated with PM2.5. y BC influences climate by: 1) directly absorbing light, 2) reducing the reflectivity (“albedo”) of snow and ice through deposition, and 3) interacting with clouds. y The direct and snow/ice albedo effects of BC are widely understood to lead to climate warming. However, the globally averaged net climate effect of BC also includes the effects associated with cloud interactions, which are not well quantified and may cause either warming or cooling. Therefore, though most estimates indicate that BC has a net warming influence, a net cooling effect cannot be ruled out. y Sensitive regions such as the Arctic and the Himalayas are particularly vulnerable to the warming and melting effects of BC. y BC is emitted with other particles and gases, many of which exert a cooling influence on climate. Therefore, estimates of the net effect of BC emissions sources on climate should include the offsetting effects of these co-emitted pollutants. This is particularly important for evaluating mitigation options. y BC’s short atmospheric lifetime (days to weeks), combined with its strong warming potential, means that targeted strategies to reduce BC emissions can be expected to provide climate benefits within the next several decades. y The different climate attributes of BC and long-lived greenhouse gases make it difficult to interpret comparisons of their relative climate impacts based on common metrics. y Based on recent emissions inventories, the majority of global BC emissions come from Asia, Latin America, and Africa. Emissions patterns and trends across regions, countries and sources vary significantly. y Control technologies are available to reduce BC emissions from a number of source categories. y BC mitigation strategies, which lead to reductions in PM2.5, can provide substantial public health and environmental benefits. y Considering the location and timing of emissions and accounting for co-emissions will improve the likelihood that mitigation strategies will be properly guided by the balance of climate and public health objectives. y Achieving further BC reductions, both domestically and globally, will require adding a specific focus on reducing direct PM2.5 emissions to overarching fine particle control programs. y The most promising mitigation options identified in this report for reducing BC (and related “soot”) emissions are consistent with control opportunities emphasized in other recent assessments. –United States: The United States will achieve substantial BC emissions reductions by 2030, largely due to controls on new mobile diesel engines. Other source categories in the United States, including stationary sources, residential wood combustion, and open biomass burning also offer potential opportunities. –Global: The most important BC emissions reduction opportunities globally include residential cookstoves in all regions; brick kilns and coke ovens in Asia; and mobile diesels in all regions. –Sensitive Regions: To address impacts in the Arctic, other assessments have identified the transportation sector; residential heating; and forest, grassland and agricultural burning as primary mitigation opportunities. In the Himalayas, studies have focused on residential cooking; industrial sources; and transportation, primarily on-road and off-road diesel engines. y A variety of other options may also be suitable and cost-effective for reducing BC emissions, but these can only be identified with a tailored assessment that accounts for individual countries’ resources and needs. y Despite some remaining uncertainties about BC that require further research, currently available scientific and technical information provides a strong foundation for making mitigation decisions to achieve lasting benefits for public health, the environment, and climate. iv Highlights Report to Congress on Black Carbon United States Environmental Protection Agency Health Assessment Document For Diesel Engine Exhaust CONTENTS LIST OF TABLES ........................................................... viii LIST OF FIGURES ........................................................... xi FOREWORD ............................................................... xiv PREFACE ................................................................. xvi AUTHORS, CONTRIBUTORS, AND REVIEWERS .............................. xvii ACKNOWLEDGMENTS .................................................... xxii 1. EXECUTIVE SUMMARY ................................................. 1-1 1.1. INTRODUCTION .....................................................1-1 1.2. COMPOSITION OF DIESEL EXHAUST .................................. 1-1 1.3. DIESEL EXHAUST AS A COMPONENT OF AMBIENT PARTICULATE MATTER ............................................................ 1-2 1.4. ATMOSPHERIC TRANSFORMATION OF DIESEL EXHAUST ............... 1-2 1.5. EXPOSURE TO DIESEL EXHAUST ..................................... 1-3 1.6. HEALTH EFFECTS OF DIESEL EXHAUST ...............................1-3 1.6.1. Acute (Short-Term Exposure) Effects ................................ 1-4 1.6.2. Chronic (Long-Term Exposure) Noncancer Respiratory Effects ............ 1-4 1.6.3. Chronic (Long-Term Exposure) Carcinogenic Effects .................... 1-4 1.7. SOURCES OF UNCERTAINTY ......................................... 1-6 2. DIESEL EXHAUST EMISSIONS CHARACTERIZATION, ATMOSPHERIC TRANSFORMATION, AND EXPOSURES .................................... 2-1 2.1. INTRODUCTION .....................................................2-1 2.2. PRIMARY DIESEL EXHAUST EMISSIONS .............................. 2-3 2.2.1. History of Dieselization ........................................... 2-3 2.2.2. Diesel Combustion and Formation of Primary Emissions ................. 2-9 2.2.3. Diesel Emission Standards and Emission Trends Inventory .............. 2-15 2.2.4. Historical Trends in Diesel Fuel Use and Impact of Fuel Properties on Emissions .......................................... 2-25 2.2.5. Chronological Assessment of Emission Factors ........................ 2-29 2.2.6. Engine Technology Description and Chronology ...................... 2-43 2.2.7. Air Toxic Emissions ............................................. 2-53 2.2.8. Physical and Chemical Composition of Diesel Exhaust Particles .......... 2-59 2.3. ATMOSPHERIC TRANSFORMATION OF DIESEL EXHAUST .............. 2-84 2.3.1. Gas-Phase Diesel Exhaust ........................................ 2-84 2.3.2. Particle-Phase Diesel Exhaust ..................................... 2-90 2.3.3. Diesel Exhaust Aging ............................................ 2-93 2.4. AMBIENT DIESEL EXHAUST CONCENTRATIONS AND EXPOSURES ..... 2-94 2.4.1. Diesel Exhaust Gases in the Ambient Atmosphere ..................... 2-94 2.4.2. Ambient Concentrations of DPM .................................. 2-95 2.4.3. Exposures to Diesel Exhaust ..................................... 2-106 2.5. SUMMARY AND DISCUSSION ...................................... 2-118 2.5.1. History of Diesel Engine Use, Standards, and Technology .............. 2-119 2.5.2. Physical and Chemical Composition of Diesel Exhaust ................ 2-120 iii CONTENTS (continued) 2.5.3. Atmospheric Transformation of Diesel Exhaust ...................... 2-123 2.5.4. Ambient Concentrations and Exposure to Diesel Exhaust .............. 2-124 REFERENCES FOR CHAPTER 2 ............................................ 2-126 3. DOSIMETRY OF DIESEL PARTICULATE MATTER ........................... 3-1 3.1. INTRODUCTION ..................................................... 3-1 3.2. CHARACTERISTICS OF INHALED DIESEL PARTICULATE MATTER ....... 3-2 3.3. REGIONAL DEPOSITION OF INHALED DIESEL PARTICULATE MATTER . . . 3-2 3.3.1. Deposition Mechanisms ........................................... 3-3 3.3.2. Particle Clearance and Translocation Mechanisms ...................... 3-9 3.3.3. Translocations of Particles to Extra-Alveolar Macrophage Compartment Sites .......................................................... 3-22 3.4. PARTICLE “OVERLOAD” ............................................ 3-26 3.4.1. Introduction .................................................... 3-26 3.4.2. Relevance to Humans ............................................ 3-28 3.4.3. Potential Mechanisms for an AM Sequestration Compartment for Particles During Particle Overload ............................... 3-30 3.5. BIOAVAILABILITY OF ORGANIC CONSTITUENTS PRESENT ON DIESEL EXHAUST PARTICLES ....................................... 3-31 3.5.1. In Vivo Studies ................................................. 3-32 3.5.2. In Vitro Studies ................................................. 3-34 3.5.3. Modeling Studies ............................................... 3-36 3.5.4. Summary and Bioavailability ...................................... 3-37 3.6. MODELING THE DEPOSITION AND CLEARANCE OF PARTICLES IN THE RESPIRATORY TRACT .......................................... 3-38 3.6.1. Introduction .................................................... 3-38 3.6.2. Dosimetry Models for DPM ....................................... 3-38 3.7. SUMMARY AND DISCUSSION ........................................ 3-54 REFERENCES FOR CHAPTER 3 ............................................. 3-56 4. MUTAGENICITY ........................................................ 4-1 4.1. GENE MUTATIONS .................................................. 4-2 4.2. CHROMOSOME EFFECTS ............................................. 4-5 4.3. OTHER GENOTOXIC EFFECTS ........................................ 4-7 4.4. SUMMARY AND DISCUSSION ......................................... 4-8 REFERENCES FOR CHAPTER 4 .............................................. 4-9 5. NONCANCER HEALTH EFFECTS OF DIESEL EXHAUST ...................... 5-1 5.1. HEALTH EFFECTS OF WHOLE DIESEL EXHAUST ....................... 5-2 5.1.1. Human Studies .................................................. 5-2 5.1.2. Traffic Studies .................................................. 5-23 5.1.3. Laboratory Animal Studies ........................................5-24 5.2. MODE OF ACTION OF DIESEL EXHAUST-INDUCED NONCANCER EFFECTS ........................................................... 5-82 5.2.1. Comparison of Health Effects of Filtered and Unfiltered Diesel Exhaust .... 5-82 iv CONTENTS (continued) 5.2.2. Mode of Action for the Noncarcinogenic Effects of DPM ................ 5-89 5.3. INTERACTIVE EFFECTS OF DIESEL EXHAUST ......................... 5-90 5.4. COMPARATIVE RESPONSIVENESS AMONG SPECIES TO THE HISTOPATHOLOGIC EFFECTS OF DIESEL EXHAUST ................... 5-92 5.5. DOSE-RATE AND PARTICULATE CAUSATIVE ISSUES .................. 5-93 5.6. SUMMARY AND DISCUSSION ........................................ 5-97 5.6.1. Effects of Diesel Exhaust on Humans ............................... 5-97 5.6.2. Effects of Diesel Exhaust on Laboratory Animals ...................... 5-99 5.6.3. Comparison of Filtered and Unfiltered Diesel Exhaust .................. 5-102 5.6.4. Interactive Effects of Diesel Exhaust ............................... 5-103 5.6.5. Conclusions ................................................... 5-103 REFERENCES FOR CHAPTER 5 ............................................ 5-104 6. ESTIMATING HUMAN NONCANCER HEALTH RISKS OF DIESEL EXHAUST . . . 6-1 6.1. INTRODUCTION .................................................... 6-1 6.2. THE INHALATION REFERENCE CONCENTRATION APPROACH .......... 6-3 6.3. CHRONIC REFERENCE CONCENTRATION FOR DIESEL EXHAUST ........ 6-5 6.3.1. Principal Studies for Dose-Response Analysis: Chronic, Multiple-Dose Level Rat Studies .................................... 6-6 6.3.2. Derivation of Human Continuous Equivalent Concentrations, HECs ........ 6-9 6.3.3. Dose-Response Analysis—Choice of an Effect Level .................. 6-11 6.3.4. Uncertainty Factors (UF) for the RFC—A Composite Factor of 30 ........ 6-14 6.3.5. Derivation of the RfC for Diesel Exhaust ............................ 6-16 6.4. EPIDEMIOLOGICAL EVIDENCE AND NAAQS FOR FINE PM ............. 6-17 6.4.1. Epidemiological Evidence for Fine PM .............................. 6-18 6.4.2. NAAQS for Fine PM ............................................ 6-25 6.4.3. DPM as a Component of Fine PM .................................. 6-30 6.5. CHARACTERIZATION OF THE NONCANCER ASSESSMENT FOR DIESEL EXHAUST ......................................................... 6-30 6.6. SUMMARY ........................................................ 6-32 REFERENCES FOR CHAPTER 6 ............................................. 6-33 7. CARCINOGENICITY OF DIESEL EXHAUST ................................. 7-1 7.1. INTRODUCTION .................................................... 7-1 7.1.1. Overview ...................................................... 7-1 7.1.2. Ambient PM-Lung Cancer Relationships ............................. 7-1 7.2. EPIDEMIOLOGIC STUDIES OF THE CARCINOGENICITY OF EXPOSURE TO DIESEL EXHAUST ................................................ 7-3 7.2.1. Cohort Studies .................................................. 7-6 7.2.2. Case-Control Studies of Lung Cancer ............................... 7-32 7.2.3. Summaries of Studies and Meta-Analyses of Lung Cancer .............. 7-61 7.2.4. Summary and Discussion ......................................... 7-66 v CONTENTS (continued) 7.3. CARCINOGENICITY OF DIESEL EXHAUST IN LABORATORY ANIMALS ......................................................... 7-83 7.3.1. Inhalation Studies (Whole Diesel Exhaust) ........................... 7-84 7.3.2. Inhalation Studies (Filtered Diesel Exhaust) ......................... 7-108 7.3.3. Inhalation Studies (DE Plus Cocarcinogens).........................7-109 7.3.4. Lung Implantation or Intratracheal Instillation Studies ................. 7-111 7.3.5. Subcutaneous and Intraperitoneal Injection Studies ................... 7-117 7.3.6. Dermal Studies ................................................ 7-119 7.3.7. Summary and Conclusions of Laboratory Animal Carcinogenicity Studies . 7-121 7.4. MODE OF ACTION OF DIESEL EXHAUST-INDUCED CARCINOGENESIS ................................................ 7-128 7.4.1. Potential Role of Organic Exhaust Components in Lung Cancer Induction . 7-129 7.4.2. Role of Inflammatory Cytokines and Proteolytic Enzymes in the Induction of Lung Cancer in Rats by Diesel Exhaust .................. 7-132 7.4.3. Role of Reactive Oxygen Species in Lung Cancer Induction by Diesel Exhaust ..................................................... 7-133 7.4.4. Relationship of Physical Characteristics of Particles to Cancer Induction . . 7-136 7.4.5. Integrative Hypothesis for Diesel-Induced Lung Cancer ............... 7-137 7.4.6. Summary .................................................... 7-139 7.5. WEIGHT-OF-EVIDENCE EVALUATION FOR POTENTIAL HUMAN CARCINOGENICITY ....................................... 7-140 7.5.1. Human Evidence .............................................. 7-141 7.5.2. Animal Evidence .............................................. 7-142 7.5.3. Other Key Data ............................................... 7-143 7.5.4. Mode of Action ............................................... 7-143 7.5.5. Characterization of Overall Weight of Evidence: EPA’s 1986 Guidelines for Carcinogen Risk Assessment .................................. 7-144 7.5.6. Weight-of-Evidence Hazard Narrative: EPA’s Proposed Guidelines for Carcinogen Risk Assessment (1996b, 1999) ...................... 7-144 7.6. EVALUATIONS BY OTHER ORGANIZATIONS ........................ 7-146 7.7. CONCLUSION ..................................................... 7-147 REFERENCES FOR CHAPTER 7 ............................................ 7-148 8. DOSE-RESPONSE ASSESSMENT: CARCINOGENIC EFFECTS ................. 8-1 8.1. INTRODUCTION .................................................... 8-1 8.2. MODE OF ACTION AND DOSE-RESPONSE APPROACH .................. 8-2 8.3. USE OF EPIDEMIOLOGIC STUDIES FOR QUANTITATIVE RISK ASSESSMENT .................................................. 8-4 8.3.1. Sources of Uncertainty ............................................ 8-4 8.3.2. Evaluation of Key Epidemiologic Studies for Potential Use in Quantitative Risk Estimates .......................... 8-5 8.3.3. Conclusion .................................................... 8-11 8.4. PERSPECTIVES ON CANCER RISK ................................... 8-11 8.5. SUMMARY AND DISCUSSION ....................................... 8-16 REFERENCES FOR CHAPTER 8 ............................................. 8-17 vi Additionally, several cities had passed laws barring steam locomotives within the city limits because the large quantities of smoke obscured visibility, creating a safety hazard. The first prototype diesel locomotive was completed in 1917. By 1924 General Electric (GE) was producing a standard line of switching locomotives on a production basis. Electro-Motive Corporation was founded the same year to produce diesel locomotives in competition with GE. This company was purchased in 1929 by General Motors (GM) and became the Electro-Motive Division. After this acquisition, GM began to develop the two-stroke engine for this application. Up to this time, all locomotive diesel engines were four-stroke. Two-strokes offered a much higher power-to-weight ratio, and GM’s strategy was to get a large increase in power by moving to the two-stroke cycle. The first true high-speed, two-stroke, diesel-electric locomotives were produced by GM in 1935. However, because of the economic climate of the Great Depression, few of these were sold until after the Second World War. At the end of the war, most locomotives were still steam-driven but were more than 15 years old, and the railroads were ready to replace the entire locomotive fleet. Few, if any, steam locomotives were sold after 1945 because the entire fleet was converted to diesel (Coifman, 1994). The locomotive fleet has included significant percentages of both two- and four-stroke engines. The four-stroke diesel engines were naturally aspirated in the 1940s and 1950s. It is unlikely that any of the two-stroke engines used in locomotive applications were strictly naturally aspirated. Nearly all two-stroke diesel locomotive engines are uniflow scavenged, with a positive-displacement blower for scavenging assistance. In 1975, it was estimated that 75% of the locomotives in service were two-stroke, of which about one-half used one or more turbochargers in addition to the existing positive-displacement blower for additional intake boost pressure. Almost all of the four-stroke locomotive engines were naturally aspirated in 1975. Electronic fuel injection for locomotive engines was first offered in the 1994 model year (U.S. EPA, 1998b). All locomotive engines manufactured in recent years are turbocharged, aftercooled or intercooled four-stroke engines. In part, this is because of the somewhat greater durability of four-strokes, although impending emissions regulations may have also been a factor in this shift. The typical lifespan of a locomotive has been estimated to be more than 40 years (U.S. EPA, 1998b). Many of the smaller railroads are still using engines built in the 1940s, although the engines may have been rebuilt several times since their original manufacture. 2.2.2. Diesel Combustion and Formation of Primary Emissions A basic understanding of diesel combustion processes can assist in understanding the complex factors that influence the formation of DPM and other DE emissions. Unlike SI combustion, diesel combustion is a fairly nonhomogenous process. Fuel is sprayed at high 2-9 Figure 2-6. HD diesel truck engines. these applications by the early 1980s. A comparison of IDI (A) and DI (B) combustion systems of high-speed DI engines almost completely replaced IDI engines for pressure into the compressed cylinder contents (primarily air with some residual combustion products) as the piston nears the top of the compression stroke. The turbulent mixing of fuel and air that takes place is enhanced by injection pressure, the orientation of the intake ports (inducement of intake-swirl tangential to the cylinder wall), piston motion, and piston bowl shape. In some cases, fuel and air mixing is induced via injection of the fuel into a turbulence- generating pre-chamber or swirl chamber located adjacent to the main chamber (primarily in older, higher speed engines and some LD diesels). Examples of typical direct injection and indirect injection combustion systems are compared in Figure 2-6. Diesel combustion can be considered to consist of the following phases (Heywood, 1988; Watson and Janota, 1982): Figure 2-6. A comparison of IDI (A) and DI (B) combustion systems of high-speed HD diesel truck engines. DI engines almost completely replaced IDI engines for these applications by the early 1980s. (IDI = indirect injection, DI=direct injection) 2-10 " An ignition delay period, which starts after the initial injection of fuel and continues until the initiation of combustion. The delay period is governed by the rate of fuel and air mixing, diffusion, turbulence, heat transfer, chemical kinetics, fuel vaporization, and fuel composition. Fuel cetane rating is an indication of ignition delay. " Rapid, premixed burning of the fuel and air mixture from the ignition delay period. " Diffusion-controlled burning, where the fuel burns as it is injected and diffuses into the cylinder. " A very small amount of rate-controlled burning during the expansion stroke, after the end of injection. Engine speed and load are controlled by the quantity of fuel injected. Thus, the overall fuel-to-air ratio varies greatly as engine speed and load vary. On a macro scale, the cylinder contents are always fuel-lean. Depending on the time available for combustion and the proximity of oxygen, the fuel droplets are either completely or partially oxidized. At temperatures above 1,300 K, much of the unburned fuel that is not oxidized is pyrolized (stripped of hydrogen) to form EC (Dec and Espey, 1995). In addition to EC, other carbonaceous matter is present, largely from unburned fuel. The agglomeration of elemental and OC forms particles that are frequently referred to as  soot particles. In this document, the terms  EC and  OC are used to refer to the carbon-containing components of DPM, and collectively, they are referred to as the carbonaceous fraction of a diesel particle. Carbonaceous particle formation occurs primarily during the diffusion-burn phase of combustion, and is highest during high load and other conditions consistent with high fuel-air ratios. Most of the carbonaceous matter formed (80% to 98%) is oxidized during combustion, most likely by hydroxyl radicals (Kittelson et al., 1986; Foster and Tree, 1994). DPM is defined by the measurement procedures summarized in the Code of Federal Regulations, Title 40 CFR, Part 86, Subpart N (CFR 40:86.N). These procedures define DPM emissions as the mass of material collected on a filter at a temperature of 52 �C or less after dilution of the exhaust with air. DPM is formed by a number of physical processes acting in concert as the exhaust is cooled and diluted. These are nucleation, coagulation, condensation, and adsorption. The core DE particles are formed by nucleation and coagulation from primary spherical particles consisting of solid carbonaceous (EC) material and ash (trace metals and other elements). To these, through coagulation, adsorption, and condensation, are added organic and sulfur compounds (sulfate) combined with other condensed material (Figure 2-7). Because of 2-11 Solid Carbonaceous/Ash Particle with adsorbed hydrocarbon/sulfate layer Sulfuric Acid Particles Hydrocarbon/Sulfate Particles 0.2 µm Figure 2-7. Schematic diagram of diesel engine exhaust particles. Source: Modified from Kittelson, 1998. their size, <0.5 mm, these particles have a very large surface area per gram of mass, which makes them able to adsorb large quantities of ash, organic compounds, and sulfate. The specific surface area of the EC core has been measured to be approximately 30–50 m2/g (Frey and Corn, 1967). Pierson and Brachaczek (1976) report that after the extraction of adsorbed organic material, the surface area of the diesel particle core is approximately 90 m2/g. The organic material associated with diesel particles originates from unburned fuel, engine lubrication oil, and small quantities of partial combustion and pyrolysis products. This is frequently quantified as the SOF, which is discussed in much more detail in Section 2.2.7. The formation of sulfate in DE depends primarily on fuel sulfur content. During combustion, sulfur compounds present in the fuel are oxidized to sulfur dioxide (SO2). Approximately 1% to 4% of fuel sulfur is oxidized to form sulfuric acid (H2SO4) (Wall et al., 1987; Khatri et al., 1978; Baranescu, 1988; Barry et al., 1985). Upon cooling, sulfuric acid and water condense into an aerosol that is nonvolatile under ambient conditions. The mass of sulfuric acid DPM is more than doubled by the mass of water associated with the sulfuric acid under typical DPM measurement conditions (50% relative humidity, 20–25 °C) (Wall et al., 1987). 2-12 Emissions from combustion engines produce oxide of nitrogen (NOx) primarily (at least initially) as of NO. High combustion temperatures cause reactions between oxygen and nitrogen to form NO and some NO2. Most NO2 formed during combustion is rapidly decomposed. NO can also decompose to N2 and O2, but the rate of decomposition is very slow (Heywood, 1988; Watson and Janota, 1982). Thus, almost all of the NOx emitted is NO. Some organic compounds from unburned fuel and from lubricating oil consumed by the engine can be trapped in crevices or cool spots within the cylinder and thus are not sufficiently available to conditions that would lead to their oxidation or pyrolysis. These compounds are emitted from the engine and either contribute to gas-phase organic emissions or to DPM emissions, depending on their volatility. Within the exhaust system, temperatures are sufficiently high that these compounds are entirely present within the gas phase (Johnson and Kittelson, 1996). Upon cooling and mixing with ambient air in the exhaust plume, some of the less volatile organic compounds can adsorb to the surfaces of the EC agglomerate particles. Lacking sufficient EC adsorption sites, the organic compounds may condense on sulfuric acid nuclei to form a heterogeneously nucleated organic aerosol (Abdul-Khalek et al., 1999). Although not unique to DE, the high content of EC associated with typical DPM emissions has long been used by some investigators to distinguish diesel engine sources of this particle from other combustion aerosols. Diesel particles from newer HD engines are typically composed of ~75% EC (EC can range from 33% to 90%), ~20% OC (OC can range from 7% to 49%), and small amounts of sulfate, nitrate, trace elements, water, and unidentified components (Figure 2-8). Metallic compounds from engine component wear, and from compounds in the fuel and lubricant, contribute to DPM mass. Ash from oil combustion also contributes trace amounts. Ambient PM2.5 measured in the eastern United States is dominated by sulfate (34%), whereas ambient PM2.5 in the western United States is dominated by OC (39%) (Table 2-3) (U.S. EPA, 1999a). Many sources contribute to ambient PM2.5, and these sources and their relative contribution to ambient PM2.5 can be identified on the basis of the chemical species present. The OC fraction of DPM is increasingly being used to assist investigators in identifying the contribution of diesel engine emissions to ambient PM2.5. In particular, hopane and sterane compounds (aromatic compounds, >C30) have been used in addition to other polycyclic aromatic hydrocarbons (PAHs) and long-chain alkanes to distinguish DPM from other mobile source PM and from ambient PM (Schauer et al., 1996; Fujita et al., 1998). Although PAH compounds make up 1% or less of DPM mass, diesel emissions have been observed to have elevated concentrations of methylated naphthalenes and methylated phenanthrene isomers compared to other combustion aerosols (Benner et al., 1989; Lowenthal et al., 1994; Rogge et al., 1993). Enrichment of benzo[a]anthracene and benzo[a]pyrene (B[a]P) in DPM has also been 2-13 Figure 2-8. Typical chemical composition for diesel particulate matter (PM2.5) from new (post-1990) HD diesel vehicle exhaust. Table 2-3. Typical chemical composition of fine particulate matter Eastern U.S. Western U.S. Diesel PM2.5 Elemental carbon 4% 15% 75% OC 21% 39% 19% Sulfate, nitrate, ammonium 48% 35% 1% Minerals 4% 15% 2% Unknown 23% – 3% Source: U.S. EPA, 1999a. 2-14 observed under some conditions and has been used to assess the relative contribution of DE to ambient PM. Although specific OC species are being used to help distinguish DPM aerosols from other combustion aerosols, up to 90% of the organic fraction associated with DPM is currently classified as unresolvable complex material. Ultrafine DPM (5–50 nm) accounts for the majority (50% to 90%) of the number of particles but only 1% to 20% of the mass of DPM. A study conducted by Gertler (1999) in the Tuscarora Mountain tunnel demonstrated an increase in 20 nm diameter particles as the fraction of diesel vehicles in the tunnel increased from 13% to 78%. The contribution of nuclei-mode particles from a freeway on an ambient aerosol size distribution was reported by Whitby and Sverdrup (1980). In summary, four main characteristics of DPM are (1) the high proportion of EC, (2) the large surface area associated with the carbonaceous particles in the 0.2 :m size range, (3) enrichment of certain polycyclic organic compounds, and (4) 50%–90% of the number of DPM particles in diesel engine exhaust are in the nuclei-mode size range, with a mode of 20 nm. 2.2.3. Diesel Emission Standards and Emission Trends Inventory EPA set a smoke standard for on-road HD diesel engines beginning with the 1970 model year and added a carbon monoxide (CO) standard and a combined hydrocarbon (HC) and NOx standard for the 1974 model year (Table 2-4). Beginning in the 1979 model year, EPA added a HC standard while retaining the combined HC and NOx standard. All of the testing for HC, CO, and NOx was completed using a steady-state test procedure. Beginning in the 1985 model year,EPA added a NOx standard (10.7 g/bhp-hr), dropped the combined HC and NOx standard, and converted from steady-state to transient testing for HC, CO, and NOx emissions. EPA introduced a particulate standard for 1988 model year diesel engines using the transient test (0.6 g/bhp-hr). Transient testing involves running an engine on a dynamometer over a range of load and speed set points. Since the 1985 model year, only the NOx and particulate standards have been tightened for on-road diesel engines. For truck and bus engines, the particulate standard was reduced to 0.25 g/bhp-hr in 1991, and it was reduced again in 1994 for truck engines to 0.1 g/bhp-hr. For urban bus engines, the particulate standard was reduced in 1994 to 0.07 g/bhp-hr and again in 1996 to 0.05 g/bhp-hr. The NOx standard was reduced to 4.0 g/bhp-hr in 1998 for all on-road diesel engines (bus and truck engines). The standards for nonmethane hydrocarbon (NMHC) and NOx combined were further lowered in a 1997 rulemaking, to take effect in 2004. EPA has recently finalized a regulation that will further reduce NOx, NMHC, and PM emissions from diesel engines starting in 2007. 2-15 Showcasinga120-acreregional multi-purposepublicpark,pedestri- an-friendlydesign,anda1500+acre wetlandsystem,theBuckwalterPUD andtheBuckwalterPlaceurbancen- terinBluffton,SouthCarolinapro- motemultipleaspectsofsustainable development. Ma t t G r e e n Understanding Planned Unit Development A planned unit development (PUD) is a large, integrated development adhering to a comprehensive plan and located on a single tract of land or on two or more tracts of land that may be separated only by a street of other right-of-way. PUD is a form of development that, although conceived decades ago, can be used today to advance a number of important smart growth and sustainability objectives. PUD has a number of distinct advantages over conventional lot-by-lot development. Properly written and administered, PUD can offer a degree of flexibility that allows creativity in land planning, site design, and the protection of environmentally sensitive lands not possible with conventional subdivision and land development practices. Moreover, properly applied, PUD is capable of mixing residential and nonresidential land uses, providing broader housing choices, allowing more compact development, permanently preserving common open space, reducing vehicle trips, and providing pedestrian and bicycle facilities. In exchange for design flexibility, developers are better able to provide amenities and infrastructure improvements, and find it easier to accommodate environmental and scenic attributes. PUD is particularly useful when applied to large developments approved in phases over a number of years, such as master planned communities. PUDs are typically approved by the local legislative body (city council, board of supervisors, county commissioners) after a comprehensive review and recommendation by the planning board or commission, which normally includes a public hearing. Communities considering adoption of a PUD ordinance should be mindful that while planning boards and commissions are given a good deal of discretionary power in acting on PUDs, appropriate standards are essential. Moreover, a delicate balance must be found between the desire to be flexible in order to take into account unique site characteristics and the need to spell out concrete standards and criteria. WHY PLANNED UNIT DEVELOPMENT IS POPULAR PUD has grown increasingly popular, in part because standard subdivision and zoning ordinances have serious limitations. Many older vintage zoning ordinances prohibit mixed use. Single family, multifamily, and nonresidential uses are often not allowed in the same zoning district. Older conventional ordinances also contain uniform site development standards that tend to produce monotonous outcomes. Subdivision control ordinances deal with narrow concerns, such as street, curb, and sidewalk standards and lot and block layout.The lack of meaningful amounts of well- placed, accessible open space and recreational amenities is another shortfall of conventional development controls. TYPES OF PLANNED UNIT DEVELOPMENT Planned unit developments can take many forms, ranging from modest residential developments where housing units are clustered and open space is provided, to mixed use master planned communities that cover thousands of acres. Simple Residential Cluster.Simple cluster subdivisions allow smaller lots on some parts of the site in exchange for permanently preserved common open space elsewhere on the site. Planning boards or commissions normally require the open space to be configured in a manner to protect sensitive natural features such as streams and riparian areas, vernal pools, ponds, and lakes, and to take into account hazard areas and areas of steep slope. Communities may either limit the gross density of the tract to what would be permitted under conventional zoning, or may choose to offer a density bonus allowing more units than would other- Planningfundamentals forpublicofficialsand engagedcitizens A Publication of the American Planning Association |PASQuickNotesNo.22 OUICKNOTES ThisPASQuickNoteswaspreparedby APAresearchstaffwithcontributions fromnationalplanninglawexperts. wise be allowed. By allowing a bonus, the community can require a greater percentage of the tract as common open space.Theoretically, communities can choose to allow any residential type (or combination of types) on a parcel in the cluster plan—single-family houses, attached houses, town houses, garden apartments, or high rises. As a practical matter, however, cluster subdivisions are developed mostly for single-family homes on individual lots. Mixed Uses.PUD builds on the simple residential cluster idea by allowing nonresidential uses, often at higher densities. Retail and service establishments, restaurants, schools, libraries, churches, recreation facilities, offices, and even industrial uses can be included in PUDs. Downtown or village center development with apartments above shops and live-work arrangements are also possible. The extreme case is the master planned community, which usually involves substantial acreage and combines employment, office, retail, and entertainment centers with associated self-contained neighborhoods.This can include diverse housing types as well as retail, entertainment and office centers. WHICH ORDINANCE,WHICH AGENCY? Individual state planning statutes control how communities handle the deliberative process leading to a decision about a PUD. In most states a PUD provision can be made part of the zoning ordinance or it may be written as a stand-alone ordinance. In either case, the decision to approve, approve with conditions, or disapprove a PUD falls to the legislative branch of local government. Some communities permit a PUD through a discretionary review process, such as a conditional or special use permit. These permits can be approved by the legislative body, planning commission, or board of adjustment, depending on the state enabling legislation and local policies. Some communities provide for the administrative approval of mixed use developments that normally require a discretionary PUD process. The zoning ordinance is the most appropriate place to locate planned unit development regulations. Basic legislative decisions on use and density are normally the responsibility of the legislative body. Street design and infrastructure could also be resolved through PUD approval, though these considerations are normally built into a unified development ordinance. Decisions about plan details can be left to the planning board or commission and planning staff. ZONING FOR PUD Communities face a number of questions when deciding how to fit planned unit development regulations into their zoning ordinances. One alternative is to provide for planned unit development as-of-right. Under this guideline the ordinance would specify the requirements for a planned unit development, and discretionary review and approval procedures would not be necessary. Stand-alone PUD ordinances are now fairly common. Although there are variations, a typical ordinance will include a purpose clause; a statement of the type or types of PUD that are authorized; zoning procedures; and standards for approval.The ordinance may contain definitions. CONSISTENCYWITHTHE COMPREHENSIVE PLAN Consistency with the comprehensive plan should be required, especially if the PUD has a major effect on growth and development in the community and on public facilities.This will be true of master planned communities. Many statutes now require zoning to be consistent with a comprehensive plan, and consistency can be required by ordinance even if there is no statutory mandate.☐ PASQuickNotesisapublicationoftheAmericanPlanningAssociation'sPlanningAdvisoryService(PAS).Copyright©2009. VisitPASonlineatwww.planning.org/pastofindouthowPAScanworkforyou.AmericanPlanningAssociationstaff: W.PaulFarmer,FAICP,ExecutiveDirectorandCEO;WilliamR.Klein,AICP,DirectorofResearchandAdvisoryServices; TreJerdon,QuickNotesEditor;TimMennel,SeniorEditor;JulieVonBergen,AssistantEditor;SusanDeegan, SeniorGraphicDesigner. A Publication of the American Planning Association |PASQuickNotesNo.22 REFERENCES 1. Published by American Planning Association Mandelker, Daniel R. 2007. Planned Unit Developments. Planning Advisory Service Report no. 545. Chicago: American Planning Association. Mandelker, Daniel R. 2007.“Planned Unit Developments and Master Planned Communities: Review and Approval Process.”Zoning Practice, March. 2. Other Resources American Planning Association. 2006. “Legal Foundations: Planned Unit Development.”Pp. 599–601 in Part 6: ImplementationTechniques, in Planning and Urban Design Standards. 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T h e r e a n u m b e r t f p c t e n t i a l l y s i g n i f i c a n t i m p a c t s t o w a t e r q u a l l t y a n d w a t e r r e s Ð u r c e s t h a t m u s t b e a d e q u a t e l y a r J c i r e s s e d i n t h e e n v i r o n m e n t a l r e v i e w , W i t h o u t a d e q u a t e m i t i g a t i o n , P r o j e c t i m p l e n r e n t a t i c n c c u l d r e s u l t i r r s i g n i f i c a * i a d v e r s e i m p a c t s t o r ¡ ¡ a t e r q u a l i t y a n d r î a y r e s u l t i n c u m u l a t i v e i m p a c l s t h a t h a v e t h e p o t e n t i a l t o p e r r n a n e n t l y a l t e r t h * h y d r c l o g i c a l a n d e c e l o g i c a l f u n c t i q n o f t h e a q u a t i c w ã l ê r r s s o u r c e $ w í t h i n i h e P r ç J e c t a r e a . t h e r e b y a d v e r s e i y a f f e c t i r t g b e n e î ' i c i a l u s e s o f w a t e r s o f t h e S t a t e . C * l í f o r n i r E * v i r o n m e n t c l f ' r n t e c l ì a n Á g m q v 7 6 7 1 F l ì t n ¡ ) F h o . r å f r a x r { g r ¡ ¡ " ) ¿ f a { þ t f c . t t r * ! P e p a ì t r 5 . r l i , ' : u . i ! L F - , : : l ; ' l ! J 3 n i , I ! ' 2 2 7 : L å H t r . l l " É 1 1 ' l P Ê I G E r r - t ' ; : ¡ 1 . ! D e n y e l l e N i s h i m o r i - ¿ ^ A U T H O R I T Y $ t a l e l a w a s s i g n s r e s p o n s i b i l i t y f o r p r o t e c t i o n o f w a t e r q u a l i t y i ¡ t t h e L a h o n t a ¡ r r e . q r ô n t o t h e L a h o n t a n W a t e r B o a r d . T h e B a s i n P l a n c o n t a i n s p o l i c i e s t h a t t h e W a t e r B o a r d u e e s w i l h o t h e r l a w r a n d r e g u l a t i o r t s t o p r o t e c t v , , a t e r q u a l i t y t ¡ ¡ i t h i n t h e r e g t o n . A l l E u r l a c e w a t e r s a n d g r o u n d l v a t e r s a r e * o n s i d e r e d w a t e r s o f t h e $ t a t e . S u r f a c e w â t e r e i ¡ t c l u d e , t r u t a r e n c t l i m i t e d t o , d r a ì n a g e s , g t r e a m s , W â s h â s , p o n d s , p o o l s , o r w e t l a n d s , a n d m a y b e p e r r r r a n e n t o r i n t e r m i t t e n t . A i l w a t e r e o f t h e $ t a l e a r e p l o t e c i t e d f o r b e n e f i c i a l u s e s u n d e r t a l i f o r n i s ! a w . A d d i t i o n a l p r o t e c { i o n m a y b e B r o v i d e d f o r w a t e r s s f t h e U n ì t e d S i a t e s { U . S , ) u n d e r t h e F e d e r a l Õ l e a n l  J a t e r A c t { C W A ) i f t h e w a t e r s i n t l i e a r e ; t a r e f e d e r a i l y j u r i r d i c t i o r r a l . B a s e d c n o u r r e v i e w o f t h e N C I P , p r o j e c t c o m p c n e n t s t T ã y i n v o l v e a l t e r a t i o n , d r e d g i n g , f i l l i n g , a n d l o r e x c a . v â t ¡ n g a c t i v i t i e s i n w a t e r s o f t h e $ t a t e . S r . r c h a o t i v i t i e s c s n E t i t u t e a d i s c h a r g e o f w o s t e ' , a s d e f i n e d i n C a l i f c r n i a W a t ç r O o d e { C W C ) , s e c t i o n 1 3 0 5 0 , a n c l c c u l d a f f e c t t h e q u a l i t y o f w a t e r s o f t h e $ t a t e . l ' h e $ t a t e W a t e r R e s o u r c e s C o n t r i ¡ l B o a r c í ( S t a t e W a t e r B o a r d ) a n d t h e L a h o n t a n W a t e r B o e r d r e g u l a t e d i e c h a r g e s i n o r d e r t o p r o t e c t t h e w a t e r q u * f i $ f o r þ e n e f i c i i a l u s e s o f w a t e ¡ s o f i h s . $ t a t e . T h e B a s i f l P l a n p r o v i d e s g u i e l a n c e r e g a r d i n g v ¿ a t e r q u a l i i y a n d h o w t h e L a h o n t a n ' r  / a t e r B o a r d m a y r e g u l a t e a c i i v i t i e c t l ¡ a t h a v e t h e p c t e r r t i s l t a a f f e c t w a t e r i r i , - ' r t - ! - - i r - - - - - ! - . ^ f i ^ ^ n - - : * ñ l - . . : - - 1 , . J ^ - - - ^ L : L : a l - - - . . . ^ ! - e - . . - l i : . ^ ¿ - - - l - - J ^ q u a l l r y w t l n l n I n e r e g t ç n . ! i l e Ì : 1 4 $ ! f I r t a l l l t ì r J t u u Ë i ' p t u ! ! t [ J ! u u ! r ì i t w i á r E ! q u i á u 1 ] r Þ r , á f r L ¡ L 1 f u * , a n d p o l i c i e s f o r i m p l e m e n t a t i o n o f s t a n d a r d e . T h e B a s i n P l a n c a n b e a e c e s s e d v i a t h e V l a t e r B o a r d ' s w e b s i t e a t h t t p ' Í w r ¿ r w , W - a t g r þ p Ê { d å . C å g g { l g b g g l 3 n i w a t e r - i F s u S s l o r o g r a * i g ¿ b å q 3 ¡ - i i - l g U t e j g r e q n i r ! . W e r e q u e s t t h s t t h e e n v i r o r r m e n t a l d o c u m e n t * n a l y z e c o m p l i a n c e w i t h p o l i c i e s i n t h e Ë a s i n P l a n i n t h e h y d r o l o g y , b i o l o g i c a l r e s o u r c e s , a n d w a t e r q u a l i t y a n a [ y s e s a n d r c q u i r e f h a t t h e P r o j e c t p r o p o n Ë n l c o n r ¡ . r l y w i t h a l l a p p l i c a b i e w a t e r . q u a r l i l y r t a n d a r d s a n d p r o h i b i t i o n s , i n c l u d i n g p r o v i s i o n s c l t h + B * s i n F l a n c o n c e r n i n g i n d u s t r i a l r , v a s t e s , w e t l a n d s , f l o o d p l a i n s , c c n s t r u c t i o n a d i v i t i e s , a n c l l a n d r i e v e l c p m e n t . P E R M I T S A n u m b e r o f a e t i v i t i e s a f j s s c i a t e d w l t h t h e F r a j e c i r n a y r e q u í r e p e r m i t s o r o t i r ê r o r ç e r s i s s u e d b y e i t h e r t h e S t a l e W a t e r E e a r d o r L a h o n t a n W a t e r B o e r d þ e ç a u s e t h e y h a v e t h e p o t e n t i a l t o i m p a c t w a t e r s o f t h * $ t a t e . T h e r e q u i r e m e n t s m a y i n c l u d * t h e f o l k : w i n g : D i s c h a r g e o f f i l l o r d r e d g e m a t e r i a l t a a s r . ¡ r f a c e w ä t e r m a y r e q u i r e ¿ c C W A s e c t i o n 4 0 1 w a t e r q u a l i t y E : c r t i f i c a t i o n f f V A C ¡ o r c l e r f o r i m p a c t s t o f e d e r a l w a t * r s ( r r , r a t e r s o f t h e U $ , ) , o r d r e d g e a n d f i l l W a s t e Ð i s c h a r g e R e q u i r e m e n t s ( W Þ R s ) f o r ¡ m p a c t $ t r . ¡ n o n - f e d e r a I w a t e r s . - t l * ' å â l ¡ ¡ " i s { t c f ì n e c J ! r t h e B å s i n P l å ñ t o i n c l þ d e a t y u ' ü s l f o r d Ê ' e t Ê r i o u s t î E : e , ì ; ¡ r i n c l u d l n g . b u t n o l : i r , } ' ! e ¡ J i ó . w â $ i e e a d h e n f i ¿ t e r ì a h * ( s u c t r a s s í i l , s í l l . s a r x ¡ , c l ã y , r ¡ c k . o r o t h e r o r g a n i c ç ¡ n r i n e ¡ e I r ì å t e r i ð l ) n n c a n y o t h e r w e r $ t e â - 3 d e f i n e d i n t h e t a l i f r v n i a l V a l e r C o d e , s e c i i r : ¡ r 1 S t t C I { d } . { a I i f o n t i ø E t t v i r ç w r ? e n t s . l P r ç t e $ i o r t Å g e n c } t t $ I { r c . : z r r l P a ¡ e r ú 5 , 1 1 , ' ! t 3 L l ' 1 t : ? ' j 5 . J ü t 4 ' : ? ? ? ¡ l J e n y e l l e N i s h í r n c j r i I l - A r - i L { . r T A þ l F å { : i E U i ¡ ' i I - 3 t D i s c h a r g e o f ð n y w â s t e f i ì a t e f i a l a n d i û r F e r m â n ê n t o r ì e r n p o r a r y d i s t u r b a n c e w i t h i n t h e 1 0 O - y e a r f l o o d p l a i n a f t h e T r r . ¡ c k e e R i v e L o r Í n y t r i f l u t å r y t o t h e T r u c k e * R i v e r m a y r e q u i r e a r r e x e m p t i o n r o t h e 1 0 t - y e a r f l o o c l ¡ l a i n d i s c h a r g e p r o l r i b i t i o n i n t h e B s s i n P l a n ( p r o j e c t r n u s t m e e t a l l e x e m p t i o n c r i t , : r i å s p e c i f i e c l ì n t h e B a s i n P l a n ) . S e e s e c t i o n I b e l o w f o r a d d i t i o n a l c o m l n e n t s , l - a n d ( u p l a n d ) d i s t u r b a n Ê e o f o n e a c r ê o r r n o r e m a y n ; q u i r e a C V V A , s e c t i ç n a 0 2 ( p ) s t o r m w a t e r p e r m i t , i n c l u d i n g a N a t i o n a l P o l l u t t r n t D i s c h a r g e E l i m i n a t i o n $ y s t e n r ( N F D E S ) G e n e r a l Ç o n s t r u c t i o n S t o r m y ¡ a t e r l - ' e r m l t o b t a i n e d f r o m t h e S t a t e W a t e r B o a r d , o r a n i n d i v i d u a l s i o r m w a t ê r p e r m ' t q þ t a i n e d f r s m t h e l - a h o n t a n W a t e r B o a r d . C u v e r a g e u n c l e r t h e L a h o n t a n W a t e r B o a r d ' s S m a i l ' l o n s t n ¡ c t i o n F e r r n i t O r d e r N o . R 6 T - 2 t 0 3 - 0 0 0 4 m a y b e r e q u i r e d i f u p l a n d d i s t u ¡ b a n c e i s L : e t w e e n ' 1 û , l J 0 t s q u a r e f e e t a n d o n e a c r e . $ e e h t t S t : / / y u q n i l - . w a t - ë - r þ g g ¡ d s . c g . a a y / l a h ó n t a n H g y 3 t þ . þ l è * C s - c . w n e $ g [ g [ - ? " 8 0 ? - * Q ! ! 4 _ a t A e h É þ 1 m ! f o r a c c p y o f t h i s O r d e r a n ¡ l i t s a t t a c h m e n t s . N o t e , t h i s p e r m i t m a y b e u s e d t o a u t h s r i z e t w o k i n d s o f a c t i v i t ' ¿ s : ( 1 ) u p l a n c l i r n p a c t s b e t w e e n 1 0 , 0 0 0 $ q u ä r e f e e t a n d o n e s c r e , ( 2 ) d r e d r ¡ e a n d f i l l a c t i v i t í e s t c w e t e r s o f t h e S t a t e t h a t a r e n s t a l s o w a t e r s o f t h e U . 8 . D i s c h a r g e o f l o w t h r e a t w a $ i e s t o a s u r f a c e w a t e r , i n c f u d i n g , b u t n o l l i n r i t e r J t o . d i v e r t e d s t r e a m f l o w s , c o n s t r u c l i o n a n d l o r d r e d g e s p o i l , $ d e v l a t e r i n g , a n d w e l l c o n s t r u c t i o n a n d h y d r o s t a t i c t e s t i r r g d i s c h a r g e , m a y r e q u i i e a n N P I J E $ p e m i t f o r L i m l t e d T h r e a t D i s c h a r g e s t o $ u r f a c e W a t e r s i s s u e d t r y t h e W a t e r B o a r ¡ l . r D i s c h a r g e o f l o w t h r e a t w a s t e s t o l a n d , i n c l u d i n g c l e a r w a t e r d i s c h a r g e s , s m a l l d e w a t e r i n g p r ö j e Ç t s , a n d i n e Ë w a s t e s , m a y r e q u i r e Ê e r r e r a l W a s t e Þ i s c h a r g t : R e q u l r e m e n t s { W D R s } f o r Ð i s c h a r g e s t o L a n d w i t h a l . o w T h r e a t t a W a t e r Q u a l i t y i r e s u e d b y t h e W a t e r B o a r d . $ o m e ' " v a t e r s o f t h e S t a t e a r e " í s o l a t e c Í " f r o n r w a t e r s o f t h e U . $ . ; d e t e r r n i n a t i o r t s o { t h s j u r i s d i c t i o n a l e x t e n t o f t h e w a t e r s o f t h e U , $ . a r e m a d e b y t h e U n i t e d $ i a t e e A r r n y C o r p s o f E n g i n e e r s ( I J S A C E ) . P r o j e c t s t h a t h a v e t h e p o t e n t i a l t o i r r p a c t s u r f a c e v ¡ a t e r e w i l l r e q u i r e t h e a p p r c p r i a ' t e j u r i * d i c i i ç n a l c i e t e i m i n a t i o n s . W a t e r 3 c ¡ a r d a n a l y s e s t y p i c a l l y f o l l c w o n d e t e r m i n a t i o n s b y t h e U S A C E a n d / s r s s m e t i r r e e t h e C a l i - f r r r n i a D e p a * m s r r t o f F i s h a n d G a n t e ( C D F G ) c o n c e r n i n g a q u a t i c h a b i t a t s . T h e s e d e t e r m i n a t i o n s â r e n ê c e s c ä r y t o d i s c e r n i f t h e p r a p o s e d s u d a c e w a l e r i m p a e t s l v r l l b e r e g u i a t e d u n d e r s e c t i o n 4 0 1 o f t h e C W A o r t h r o u g h W D R s i s s u e d b y t h e W a t ; r B o a r d . T h e L a h o n t * n W a t e r B o a r d r n a y r e q u í r e h y d r o l o g i c a n a l y s i s t o d e t e r m l n e 1 3 0 - y e a r f l o o d p l a i n b o u t r d a r i e s i n w a l e r s h e d s w h e r e f l o o d p l a i n r n â p s a r e n o t a v a i i a þ l e ( e . 9 . , f o r f e d e r a l Í l ç o d i n s u r a n c e ) . W e t e q u e s t t h a t P r o j e c t p r C I p ç r ì e n t c o r i s u l t w i t h t h e U S A C E L n d G Ð F G a n d p e r f r : r n r t h e n e c e $ s â r y j u r i s c l i c t i o n a l d e t e r ¡ n i n a t i o n g T o r s u r f a c e w a t e r s v r . n i n t h e P r o j e c t a r e a . l n t a f t f o r n i a E n v i r t t n n r c n t * I P r a I e c I í ç n t l . " c t t c ) : ' f r Ê a 4 v b d f u p e r * 5 . ' ' 1 i l ! e ' l t 1 Ë : ? ' l 5 . l e r 1 4 d ? ? 7 i . Ð e n y e l l e N i s h i m o r i L A H ü { T A I . I - 4 - C a I i f o r n i d E r w i y o n t n e t ú * I P m I e e t i o t t f - å r i E . l l ¿ , i 1 1 a d d i t i o n , w e r e q u e s i : t h a t t h e e n v i r o n m e n t a l d o c u r n e r . ¿ l i s t t h e p e r m i t s t h a t r n a y b e r e q u i r e d . a s o u t l i n e d a þ o v e , a n d i d e n t i f f t h e s p e c i f ì r . o p e r a t i o n s , n r a i n t e n a n r e , â n d / o r m i n o r c o n s t r u c t i û n a c t i v i t ¡ e s a r r r J t i r * Í r i m p a c t m i t i g l t i o n m ê â s u r e s t h a t w i l l b e e m p l o y e e l u n d e r t h e s e p e r m i t t i n g a c t i o n s i n t h e a p p r o p r i a t e s e c t i o n s o f t l r e e n v i r e n m e n t â l d o c u n e n t . I n f o m a t i o n r e g a r d i n g t h e s e p e r m i t s i n c l u d i n g a p p l i c a t i o n f o r r n s , c a n b e d o w n l o a d e d f r o n ' ; o u ¡ w e b s i t e a t h t t p : i l v 4 U r , v , W - i g r _ þ s g l ü q , ç a . ç r g v / l â h o n t a n . P O T E N T I A L I I J I P A C T S T O S U R F A C E W A T E R S S u r l a c e t v a t e r s p e r f o r m a v a r i e t y o i i n r p o r t a n t h y d r o l o g i 6 a n d b i o g e o ê h e m i ô ä l f u n c t i o n s t h a t a f f e c t l r ' ¿ t e r q u a l i t y . l n p a d i c u l a r . s i r e a m e h a n n e l c o r r i e l o r s a n d r i p a r i a n â r € ä s a s s o c i a t e r J w i t h b o t h p e r e n n i ä l s t r e a r n s a n d e p h e m e r a l d r a i n a g e s p r o v i d e a n ä t u r a l h u f f e i a n d h e l p m i t i g a t e a n d c o n t r o l r ' â t L 5 r q u a l i t y i m p a o t s b y r e m o v i n g p o l l r " r t a n t s a r r d s e d i r n e n t f r o r n s u r f a c e r u n o f f . 4 ¡ 1 ¡ s : , g i 1 t h e p r o p o s e d r . l e v e l o p m e n t l a y o u t a p p e a r s t o a v o i c l w e t l a n e l s a n d d r a i n a g e s ( e x c e l , t f o r o n e r o a d c r o s s i n g a n d s e v e r a l l r a i l e r o s s i n g s ) a n i n c r e a s e i n ì m p e r v i o u E s u r f a c e r , . * t h t h e d e v e l o p m e n t o f r o a d s a n d s t r u c l u r e s c o u l c i c h a n g e t h e h y d r o l o g y o f l h e s e n e a r b y w a t e r r e s o u r c ê s b y i n c r e a s i n g w a t e r f l o r . r v a l o c i t y , w h i c h i n t u r n l e a d s t o i n c r e a s e c r n t h a s e v e r i t y o f p e a k d i s c h a r g e s . T h e s e h y r . l r o l o g i c c h a n g e s t e n d l o e x a c e r b a t e f r c d i n g , e r û s i o n , s c o u i l n g , s e d i m e n t a t í o ¡ t a n d l o g s o f ñ , f + r r t s â l { ¡ r n ¡ l i n n a a n J t ¡ a h ¡ a e . ' { ^ . - - L - a , ¡ ¡ ! r ¡ r * + l a s . . l + ' f L ^ ã ¡ E - . . - ¿ - l J - - ^ - ¡ L ^ ^ ! . . . , - . t ¡ s r u r q . ¡ u t r ì ¡ r r v r l e q ! l v Y q l u ç e v r ( / t ç ç ¡ l ê ã l ¡ r J V v ç l l ø l l \ J C r , I l ! E f . ; l I \ l l l U ù L a t l . ¡ L l l t : ü ¡ t t l ç A l , ¡ { . l v q , - c i t e d p o t e n t i a l i m p a c t s . w h l c h a r e c o n s i d e r e d s i g n i f i c a n t . B E N E F I C I A L U $ E S O i , W A T E R t s e n e f l c i a l u s e s a s s r c i a t e d w i t h H y d r o f o g i c A r e a o f J u n i p e r C r e e k , l n w h i c h t h e P r e j e c t i s l o c a l e d , i n c l u d e m u n i c i p â l a n d d o m e s t i c s u p p l y ( M U N ) ; a g r i c u l t u r a l s u p p l y ( A G R ) ; g r o u n d l t a t e r r e e r t a r g e ( G W R ) ; w a t e r e c ' n t â c t r e c r e a t i o n { R E C - 1 ) ; n o n - c o n t a c , t w a t e r r e e i e a t i o n l R E C - z ) ; c o m m a r c i e l a n c l s p o r t 4 í s h i n g ( C C M M ) ; c o l d f r e s h w a t e r h a b i t a t ( C O L D ) ; w i l ¡ ¡ ¡ ¡ E h a b i t a t f l ¡ v l L D ) ; r a r e . t h r s a t e n e d , o r e n d a n g e r e d s p e c i e s ( R A R F ) ; a n c l s p a v r n i n g r e p r o d u c t i o n , a n d d e v e l o p m e n t ( $ P W N ) . T h c E I R m u s t i d è n t i f y t h e p r e s c r i b " J b e n e f i c i a l u s e s a f s u r f a c e w a t e r s w i t h i n t h e P r o j e c t a r e a , e v a l u a t e t h e P r o j e c t ' : , Þ * t e n t l â l i m p a c t s t o w a t e r q u a l i t y w i t h r e s p e c t t o i h o s e b e n e f i c i a l u s e $ , a n d p r o v l d , : a l t c r n e t i v e s t o a v o i d t h o s e i m p a c t s o r d e s c r i b e s p e c i f ì c m i t i g a t i o n r i l e a s u r e s t h a t , , v h e h i m p l e m e n t e d , w i l l m i n i m i z e i . ¡ ¡ n a v c i d a b l e i m p a c t s t o a í e s s t h a n s i g n i f i c a r r t l e v ¿ , 1 . S r ' . o p Ê a n d L e v e l o f A n a l y s e s N e e d e d . U r b a n d e v e t o p m e n t d e g r a d e s w ã t ê r q u a f i t y t l , r o u g h a c o m p l e x o f i n t e n e l a t e d c a u s e s a n d e f f e c l s , w h i c h i f u n n r a n a g e d , u l t i m a t e l y n a - r d e s t r o y t h e p h y s l c a l , c h e r n i c a l , a n d b i o l o g i c a l r r r t e g r i t y o f t h e w a t e i e h e d s i n w h i c h i þ r 1 o Ç Ë u r . T h e p r i m a r y a d v e r s e i m p a c t s o í p ó a r þ p l a n n e à d e v e l o p r n e n t p r o j e c t s o n w a t e r q u a l i t y a r e : ' T h e { i t ç q t p h y s i c a l i m p a c t s t o a q u a t i c , } o ¡ e t l a n d , n n d r i p a r i a n h a b i t a l a n d o t h e r þ e n e f i c i a l u s e s ; ' G e n e r a t i o n o f c o n s t r u c t i o n - r e l a t e d a n c i p o s t - c o n s t r { . ¡ c t i o n u r b a n p o l l u t a n t * ; " A l t e r a t i o n o f f l o w r e g i m e e a n d g r o u n d w a t Ê r r e e h a r g e a s a r e s u l l o f i r n p e r v í o u s s l ¡ r f a c e s a n d s t ç r r n d r a i n c a l l e c t o r s y s t e r n s ; $ R * q t t a d r a V a - , Å g e n r y $ 5 r i : i 2 i j 1 I 1 ï ¡ : t 3 5 ? 9 5 4 4 2 2 7 i L ¡ I H ü { T ¿ \ I , ¡ D e n y e l l e þ , l i * h i n l o r i D i s r u p t i o r r o f w a t e r s h e d l e v e l a q u a t ¡ c f u n c l i o n s , i n c l u d i n g p o l l l r t å t ì t r e r ì 1 o v a ì , f i o o d w a t e r r e t e n t i a n , a n d h a b i { a t c o n n e c t i v i t y . J " h r : s e f a c t o r s h a v e h i s t o r i c a l l y r e s u l t e d i n a c y ö i e o f d e s t a b i l i z e d s t r e a m c h a t t n e l e , p o o r w a t e r q u a l í t y , a n d e n g i n e e r e c l s o l u t i o n s t o d i s r u p t e d f l o w p a t t e r n $ , c u l n t i r t a t i n g i n l o s s o f n a t u r a l f u n c t i o n s a n d s o c i e t a l v a k " r e s i n t h e a f f e c t e d b a s i n s . T h c n u m þ e r ê n d v a r i a b i l i t y o f t h e f ) l î t h w a y s f h r Õ u g h w h i c h w a . t e r q u a l i t y d e g r a d a t i o n c ' å n æ c i l r c o m p l i c a t e s a n a f y s i s , b u t u n d e r s t a n d i n g h o w t h e s e p a t h w a y s o p e r a t e w i t f i i n t h e s p e c i f i c c i r c u r n s t a n c e s o f t h i s p r a j e c t i s e s s e n t i a l t o e f f e c t i v e l y m i t i g a t i n g t h e a d v e r s e e f f e c t s , F o r t u n a t e l y , a v o i d a n c e o r m l n i r n i z a t l o n o f a n y c a u s a l l l n k w i l l o b v l a t e o r r e d u c e s u b s e q u e n t e f f e o i s a n d n e e d e d a n a l y s e s , ã n d ã r e l a t i v e l y s m a l l n u r n b e r o f k e y v a i ' í a b l e s r n e d i a t s m o s t r ¡ f t h e p a t h w a y s c a u s i n g w a t ç r q u a l i t y d e g r a d a t i o n . T o f t r l f i l l Õ u r $ t ã t u t s r y r e s p o n $ i b i l i t i e s , t h e W a t e r B o a r d n e e d s t o u n d e r s t a n d h o w t h i s p r o J e c t w i l l a v C I i d o r m i n i m i z e e a c h p o t e n t i a l c a u s ç o i w a t e r q u a l i t y d e g r a d a t i o n , w h a t e f f e c t s w i l l r e r ¡ r a i n u n m i t i g a t e d t h r o u g h p r o j e c t d e * i g n , a n d t h e m a g n i t u d e c ¡ f i h e r e m a i n i n g a d v e r s e e f f e c t $ . Q u a n t i f i c a t i o n s h o u l d b e a s d e f i n i t i v e a s p o s s i b l e , u s i n g a p p r o p r i a t e m o d e l i n g a n d a d e q u a t e d a t a . M o d e l i n g a p p r o a c h e s s h o u l d b e d o c u r n e r r t e d a n i l d a t a d e f i c i e n c i e e o r o t h e r f a c t o r $ a f f e c t i n g t h e r e l i a b i l i t y o f t h e r e s u l t s i d e n t i f i e d s n d c h a r a c t e r i z e d . C u r n u l a t i v e i m p a c l s m u s t E l s p b e a d d r e s s e d , $ g e t r i f i c - o m m e n t Ð 1 . L o w l m p a c t l . l e v e l o p ¡ n e n t : R e d u c l n g h y d r c l o g i c d i s r u p t i o n t î o m i a n d d e v e l o p m e n t o r r e d e v e l o p m e n t i s o f t e n r e f e i r e d t o a s " L o w l m p a c t D e v e l o p m e n t " ( L l D ) . l t r s ç u l t s i n l e s s s u r f a c e r u n o f f a n d l e s s p o l l u t i o n r o u t e d t o r e c e i v i n g w a t e r s . P r i n c i p l e s o f L I D i n c l u d e : [ / l a i n t a i n i n g n a t u r a l d r a i n a g e p a t h s a n c J l a n d s c a p e f e a t u r e $ t ù s l t w a n c i f i l l e r r u n o f f a n d m a x i r n i z e g r o u n d w a t e r r e c h a r g e , R e d u c i n g a n d d i s c o n n e c t i n g t h e i m p e r v i q r u s c o v e r c r e a t e d b y d e v e l o p m e n t a n d t h e a s s o c i a t e d t r a n s p o r l a t i o n r r e t w c r k , a n d M a n a g i n g r u n o f f a s c l o s e t o t h e s ô u r c e a s p c s e i b l e . L I D d e v e l o p m e n t p r a ç t i r ; e s t h a t w o u l r l r n a l n t a i n a q u a t i c v a h ; e s c e u l d a l s o r e d u c e l o c a l i n f r a s t r u c t u r e r e q u i r e , t r e n t s a n d c o u l d b e n e f i l e r ì ê r g y c r ¡ n s e r v a t i o n , a i r q u a l i t y . o p e n s p a c e , a n d h a b i t a t , M a n y p l a n n i n g t o o l s e x i s t t o i m p l e m e n t t h e a b ¿ t v e p r i n c i ¡ t l * s , a n d a n u m b e r o f r e c e n t r e p o r t s a r r d m â n u a l c p r o v i d e s p e c i f r c g u i r l a n c e r e g a r d i n g L l D . W a t e r B o a r d s t a f f r e c o m m e n d t h e u s e o f L I D c l e v e l o p n t e n t p r a c t ì c e s . a n d m a n y o f o u r ç o m r n e n t s a r e b a s e C c n t h i s p r i n c i p l e . A d d i t i o n a l r e s o u r c Ê i n f a i ' n r a t l o r t m a y b e c r b t a i n e d f r o r n t h e L c w l m p a c t D e v e l o p m e n t C e n i e r ' s w e þ s i t e k : c a t e r l s t w v / w . l i ç L g l g f u l r c l e l n e ! . 2 . l d e n t i f i . r a t i s n s f A f f e c t e d W a t e r s : M a p a i l w a t e r ß p ô t e n t r â l l y a f f e c t e d b y t h i s p r o j e c i a n d l i s t t h e r n ¡ n a p p r o p r i a t e t a b u l a r f o r m a t , o r g a n ì z e d b y w a t e t l r o c ] y t y p e a n d Ç ø I i f o r n i a E n v í r a n n t t ¡ t t n I P r a k : c l i o n , 4 g e t r c ¡ t F A 6 [ u 5 . t I ¡ 5 a ¡ a a d å r k ¡ ; ' c i e t l P o r ¿ r 6 5 , / 1 ã / : ü . L l i t s : 2 . 1 5 3 8 5 4 . i 2 2 ; ' 1 L A H L I ' l l , : ' ' l ' ¡ F A í J F þ F . , ' ] - 1 D e n y e l l e N i s h i m û r i s u þ - þ a s i n . F o r e a c h v r a t e r b o d y d i r e c t l y a f f e c t e d , f o t e x a m p l € 1 ' o r p r o p o s e d d r e c l g e a n d f i l l a e t i v i t y , i d e n t i i y t h e a c r e a g e ã n d ( f o r d r a l n a g e f e a t u r e s ) i h e n u r n b e r o f l i n e a r f e e t d i r e c t l y i m p a c t e d . $ u r n t h e t b t a l a f f e c t e d a d r e s , a n d l i n e a r f e e t b y w a t e r þ ô d y t y p e , w i t h i ñ W a t e r B o a r d j u r i s d i c t i o n , â n t 1 a s p r o i e o t t o t a l . l d e n t i f y a n y " i s o l a t e d " r , v e t l a n d s ô r o t h e r w a t e r s n o t s u b i e c t t o f e d e r a l j u r i s d i c t i o n . 3 , A v o i d a n c e , M i n i ¡ r r i r e t i o n , a n d f l l l i t i g a t i s n : T h b P r o j e c t h a s t h e p ô t e n 1 i ä l f o r m a i o r w â t e r q u â l i t y i m p a c t s . H o w e v e r , i t a l s o h a s t h e p o s s i b i l i t y o f i m p l e r n e n t ì n g a n i n t e g r a t e d w â t e r s h e d p l a n n l n g a p p r o a c h u s i n g L o w l r n p a c t D e v e l o p m e n t ( L i D ) p r i n ð i p t e s t o m l n l m l z e t h o s e l n r p a r , ' t s . l v l o s t c c n û t r u c t i o n - r e l a t e d d Í r e c t i m p a c l s t o s u r f a c e w a t e r s w i l l l i k e l y r e q u i r e e i t h e r ï n d i v i c i u a l W D R s o r c c v e r a g e u n r i ç r G e n e r a l \ ¡ V Ð R s f o r l m p a c ' t s t o w a t e r s o f t h e S t a t e , a n r i / c r r C W Á $ 4 0 1 w a f e r q u a l i t y c e r t i f i c a t i o n f r o m t h e W â t ê r B o a r d a n d C W A $ 4 0 4 p e r m i t e l r o m t h e U . $ . A r m y C c t r p s o f ã n g i n e e r s ( U S A C E ) i f t h e w a t e r s o f t h e S t a t e a r e a l s c ¡ w a t e r s q f t h e U . $ . T h e p r o j e c t p r o p o n e n t i s a d v i s e d t o c a n d u c t a n a l t e r n a t i v e s a n a l y s i s c o n s i s t e n t w i t h t h e r e q u i r e m e n t e ö f t h e f e d e r a l C l \ ¡ { \ S 4 0 4 i b X 1 } G ¡ J t d e l i n e s . W h i l e t h e s e G u ¡ c j s l i n e s n r e n r o ç t d i r e c t l y i n c u m b e n t ü n t h ê U $ A C Ë , t h e p r i n b l p a l s s f a v o i d a n c e , w h i c h t h e y a r t i c u l a t e , a r e d i r e c t l y r e l e v a n l t o t h e W a t e r B o a r d ' s m a n d a t e t o p r a t e c t w a t e r q u a l i t y l n c l u r l e a C W A S , 4 0 4 ( b X 1 ) G ¿ ¡ i d a / i n e s - l i k e a l t e r n a t i v e a n a l ' y s i s i n t h e E l R . T h e $ l a t e r B o a r d r e g u Ì a t e s a l l w e t l a n d â r e â $ i r r e l t r d i n g , b u t n o t l i m i t e d t o , s e a s o n a l a l p i n e l v e t l a n d s . A l l w e t l a r r d s ( d e f i n e d b y U . S , A r m y C o t p s o f Ë n g l n e e r s 1 9 8 7 W e t l a n d s D e l i n e a t i o n M a n u a l ) a r e w a t e r s o f i h e S t a t e a s w e l l a s w a t e r s o f t h e U . . Ê . , a n c l t h e W a t e r B ç a r d ' s B a s i n P l a n p r o h i b i t s a n y , d i s c h a r g e o f v ¡ a s t e e â r t h e n m a t e r i a l s o r o t h e r p r o j e c t - r e l a t e d p o l l u t â n t $ t o ê l l s u $ a c e w a t e r E ( i n c l u d i n g i s o l a t e d r v e t l a n d s ) . V i o l a t i n g t h i s p r o l ' l i b i t i o n w o u l d c r e a t e a s i g n i f i c a n t w a t e r q u a l i t y i r n p a c { . l t s l : o t ¡ l d b e n o t e d t h a t w a t e r q u a l i t y i m p a c t s a s s o . r i a t e d r , v i l h a v o i d l r i g r v e t l a n d i r n p a c t s a r e s u b s t a n t i a l l y d l f f e r e n t t h a n t h o s e a e s c c i a t e d ' w i t h m i n i m i z i n g i m p a c t s . T h e f i n a l Ë l R d o c . u r n e r r t s h o u l d i n c l u d e a n â p p r o v e d w e t l â n d d e t i n e a t i o n ( w i t h d ä t a s h e e t s . a r : d ã ô c t r n p a n y i n g m a p o f d a t a p o i n t s ) a n d m u s t i d é n t l f u m e a s u r e s t o p r e v e n t t h e c J i s c h a t g e o f p o l l u t a n t s t o w e t l a n d a r e å s p r l o r t o d e t e r m i n i n g t h e l e v e l o f i m p a c t t h a t w i l l b e ç i e a t E d b y t h e p r o p o s e d p r o j e e t . A n y p r ó p o s e d w e t l a n d e n c r o a c h n r e n t r n u s t b a i d e n t i f i e r l i r ¡ t h e f i n a l E I R a n d m u s t b e a c c o m p a n l e d w i t h a p p r o p r i a t e i n f o r n r a t i o n f o r t h e W a t s r B o a r c l t o e v a i : . ¡ a t e w h e t h e ! " o r n o t g u c h a n i m p a c t w o u l d q u a f i f y f o r a n e x e m p { i o n i c a p r o h i b i t i o n . I t m a y b e n e c e s s a r y t o o b t a i n a t í e a n W a t e r A c t S e c t i o n 4 0 4 p e r m i t f r o m t h e A r n r y C o r ¡ r s o f E n g i n e e r c { A r m y C a r p s i f o r p r o p o s e e l d i s c h a r g e s o f d r e d g e d a n d f i l l t n a i e r i a l $ 1 o w a t a r s o f t h e U n i t e c J S i a t e s " l f t h e A r m y C o r p s d e t e n n i n e s t h a t i i i s . n e t e s $ a r y t c r e g u l a t e l h e p r o . l e c t u n d e r $ e c t ì o n 4 0 4 , t h e n l h e p r o j e * t a p p t i c a n i m a y b e r e q u i r e d t o o b t a i n C l e a n W a t e r A c t S E c t i o n 4 0 1 W a t e r Q u a l i t y C e r i i f i e a l i o n { 4 0 i W A C ) f r o m t l " r e R e g i o n a l B o a r d . T h e p t o J e c t a p p l i c a n t s h o u l d c o n t a c t t h e A r n r y C o r p s ' $ a c r a n r e n t o D i s t r i c i Õ f r i c e a n c l d ç t e r m i n a i f t h e p r o j e c t i s s u b j e c t t o C l e a n \ l a t e r A c t S e c t i o n 4 0 4 a n t l i f s o , u n d e r w h i c h $ e c t i o n 4 0 4 p e r r n i t . T h e Þ r c j e c t p r o p o n e n t s h o u l d c o n t a c t f / a t e r B o a r d s t a f f t o d e t e r r n i n e l f f t i s n e c e s $ * r y t o r r b t a i n C l e a n W a t e r A c t S e c t i o n 4 0 1 W a t e r Q u a t i t y C e r t i f i c a t i o n f r o r ¡ t h e W a t e r B o a r d , C a t i f o r n i a E n $ r o n ¡ n e t t t ø | . P r o t e c t î a n o - ß e q t l i t l P r 4 x t , l g z t t c ¡ * ' _ i ¡ 1 r " ' { , / ' : [ r . ¡ . 1 l 6 ; : - : 3 5 3 8 5 4 4 ? ? ì r ' : L A H ü ' l T A t . l F ¡ i ( : L - L l r / r L Þ e n y e l l e N i s h i m o r i - 7 - T h e P r o j e c t w i l l n e e d t o í n c l u d e a p p r o p r i â i e L l D . f e a t u r e s ä n d / o r b e s t n t a n a g ê m ê n l p r a c t i c e s ( B M P s ) t h a t a t a m i n i m u m t r e a t o r r e t a i n s t o r m v t ä t È r r u n o f f f r Ô m i r n p e r v i o u s s u r f ä c e s g e n e r ã t e d b y l h e 2 0 - y e a r , l - h o u r s t ü r m e v e n t ( 0 . 7 i n c h e s o f i a i n ) . B t u l F s d e s l g n e r l t o r e t a i n s t o r n ¡ w ¿ : l t e r i u n b f f a r e i n i e n d a d t o a v o i d c r r e t l u c e a d v e r s e e f f ê c t s l o s u r f a c e w a t e r h y d r o l o g y ( e . 9 . i n c r e a s i n g p e a k f l o w s , i n c r e a s i n g f t o w v e t * c i t i e s , f l o o d i n g , ê i e , ) , w h i c h g e n e r a ¡ l y l e a d t o a d v e r e e e f l e c t s o n v " ¡ a t e r q u a l i t y a n d t h e a q u a t í c e n v i r o n m e n t ( e . g . i r i c r e a s e d c h a n t r e l i r r s t a b i l i t y , b a n k e r o s i o r t , c h a n n e i s c Ð u Í , i n c r e a s e d s e d i m e n t a t i o n , i n c r e a s e d p o l l u t a n t l o a d i n g , e t c . ) . S u c h B M P s r n a y i n c l u c l e , b u t n o t b e l i m i t e d t o , i n f i l t r a t i o n t r e n c h e s , i n f i l t r a t i o n g a l l e t i e s . a n d i n ; ¡ l t r a t i o n b a s i n s . l n a d c i ; i i o n t o m a n a g i n g t h e s t o n n w å t e r r u n o { f v o l u r n e g e n e r a t e c l b y t l t e a b o v e - r e t ' e r e r r r : e ' C s t o r m , i t i s e q u a l l y i r n p o r t a n t t o e n s u r e t h a i t h e $ t 6 r m v / ã t Ð i i s a d e q u a t e l y t r e a t e ' J p r i o r t o d i s p o s a l . $ t o r m w a l e r r u n o f f c o n t a í n s s e C i m e n t , p e i r a l e u r r 6 r r " o d u c t s â n d Õ t : t e r . ¡ e h i c r ¡ l a r f l u i d s , m e t a t s , n u t ¡ i e n l s f r o n ¡ f e r t i i i z e r s a n d o i n È r s ô u r c e s , p e a t i c r d e s , a n d r s a d w a y d e i c i n g a n d t r a c t i o n p r o d u c t s . T h e s e p r o d u c i s c a r ' r C a l í , f o r n ì c E ¡ t v b a i l m s i l t u l P r e ¡ I s c I í o n ' 4 g e n t . v 4 . l - { y d r o l o g i c D i s r u p t l o n : B e c a u s e i n c r e s s e d r u n o f f f r o m s l e v e l o p e d a r e a * i s t h e k e y v ã r i a b l e ã i l v i n g a n u m b e r o f o t h e r a d v e r s e e f f e c t s , a t t e n t i o n t o m a i n t a i n i n g t h e p r e - p r o j e c t h y d r o g - r a p h w i l l p r e v e n t o r m i n i r n i z e o t h e r p r o b l e n r s a n d w i l l l i m i t t h e n e e d f o r b t n b r a n å t y s * s a n O m i t i þ a { o n t o b e i n c l u r j e d i n t h e E l R . W e s t r o n g l y e n c o u t a g e t h e u s e o f l - l D p r i n c i p l e s a n d p r a c i i c e s t s e e l l t g l l y r ¡ ¡ ¡ r y ¡ ' e 1 e { þ g a d - : g a , . g l ¿ y A r y a l g t i s Ë l & g l a t ç g r a n r g l ] q f l i E r p a c t d e v e l o o m F n t / i n Ë Ë & $ h l ) A N a t i o n a i P o l l u t a n t D i s c h a r g e E l i r r r i n a t i o n S y s t e m ( N P Ð E S ) g e n e Í d l p e r r n i t f o r s t ç n n w ä t ê r d i o c h a r g e s w i l l b e r e q u i r e c l d u e t o c b n $ t r u Ë t ¡ q n a c t i ' ¡ i t í e s r e s u l t i n g i n a l a n d d i s t u r b a n c e o f ó n e ä c r e Õ r m o r e . T h e a p p l í c a n t c a n o b i a i n a N o t i c e o f l n t e n t i N p l l Ë S g e n e r a l p e r m i t a p p l i c a t i o n ) f o r s t o m w ä t e r d i g c h a r g e s a s s o c i s t e d w i t h c o n s t r u c i i o n s c t l v i t i e s o n t h e w e b a t U t B { ¡ y l t ¡ g l f l g l e È _ o a r d L q g . g o d w a t e r r å q u a - g / Þ C t i g l r , g l l ! 0 ! ' A s p a r t o f t h e N P D Ë $ P e r m i t , t h e a p p l i c a n t i s r e q u i r e c l t o d e v e l o p a n d i n t p l e r n e n l a $ t o i r n W a t e r P o l l u t i o n P r e v e n t i o n P I a n ( S W P P P j . T h e S U { P P P i s s r r b l e c t t o r e v i e l v b y t h e W a t e r B o a n 1 . T h e W a t e r B o a r d w i l l r e q u i r e ( i u b m i t t a l o f g r a d i n g l d r a i n a g e a n d e i o s i o n c c r n t r o l p l â n Ë a s p a r t o f t h e S V ü P P P , i n â d d i t i c n t o t h e o t h e r r e q u i r e d S W P P P e l e m e r ì t s . l n r : l u d e m ê a s u r e s t o r n a i n t a i n t h e p r e - p r o j e c t h y d r o g r a p h i n t h e a l t e r r r a t l v e s a n a l y s e s i n t h e E I R ( s e e b e l o w ) . A l s o , t h e d r a f f E I R m u s t c j o c u m e n t p o t e r . r t i a l c u m u l a i i v e i m p a c t s t o w a t e r s h e d h y d r o l o g y f r a m e x i s t i n g a r r d a n y Ô t h e r p l a n n e d d e v e l o p m e n t i n t h e a r e a . A t i e n l i s r ì L o n r a i n t a i n i n g t h e p r e ç r o j e g t l r y r i r o g r a p h i s a l s o r e q u i r e d u n d e r t h e $ t a t e B o a r d ' s G e n e r a l P e r r n i l f o r D i s c h a r g e s o i S t o r m W a t e r f r o m $ r n a l l M $ 4 s ( W Q û r d e r N o . 2 0 0 3 - 0 0 0 S - D W O ) a n d u n d e r t h e $ t a t e B o a r d ' s G e n e r a l P e r m i t f o r Ð i ç c h a r g e s o f $ i o r m W a t e r A s e o c i a t e d w i t h C o n s t r u c t i o n A c t i v i t y ( W 8 O r d e r N s . 2 0 0 9 - 0 0 0 9 - D W A ) ; t h e p r a j e c t w i l l b e r e q u i r e d 1 o o b t a ¡ n c û v e r â g e u n d e r t h e t a t t e r Q r d e r . A g a i n , c r ¡ m u l a t í v e i r n p a c t s m u e t a l s o b e a d d r e s s e d . { $ t l e q ' ; t t < t P d p e t r s \ / L ? , t 2 ú i 1 1 € , : ' J 3 ç 3 8 ã 4 1 ? ? f 1 L . A H I : $ I T A N D e n y e l l e N i s h i t n o r i - 8 - a d v e r s e l y a f f e c t b o t h s u r f a c e a n d g r o u n r J w a t e r q u a f i t y , $ t a f f r e c o r l r n Ê n d s l h a t a c ö m b i n a i l o n t f å o u r o g o o i l t r û l a n d t r e a t m e n t B M P s b e u s e d d u r i n g a n d f o l l o r r y i n g c o n s t r u c t i s n . $ u c l ¡ B M P s i n c l u d e d b u t a r e n o t l i m i t e d t o : ç ç n g t r u t c m i P e r m a n e n t t r a p s s u c l r a s a r e â $ o f u n s t a b l e s o i l c r ¡ n c l i t i o n s s u m p â r e a $ w i t l r i n d r o P i n l o t ' * , b a s i n s M i n i m i z i n g t h e a r e a t $ t a l U s ì n g a b s o r t r i n g P r o d u c t * F A S E I ] 8 / 1 7 t I t Å d i s t u r b â n c e $ t e b i l í e e d â r e a e o f i n g r e s s a n d ë g f e s 3 C o n s t r i : e t i a n I ' l i a s t e M a n a g e m e n t P l a n ( c o n c r e t e w a s t e , t r a s h , c 0 n s t r u c t ¡ ê n e q u i p i l t ê n t w a s t e w l t h i n s t s r m w â t e r a t r n e n t a n d i m p l e r n e n t a R e v e g e t a t i o n P l a n t h a t f p t i l i t a t e s e f f e c t i v e s o i l s t a þ i l i z a t i o n w i t h ¡ l ^ . r ^ t ¡ n * ¡ . n l a r ¡ I ^ . , ; ^ { . i ^ ^ â . ' F ¡ - Å ^ l J l t V E l \ J p l I l ç l t L a r l l L ¡ ! ; r \ 1 ì ' t l l l L , â u l l f l r . ' Ë w a t e r s m s n t t r a p s a $ D e v e l o p i n g a n d i r n p a I s i i t a t i o n f e n c i n g , f i b e r r o l l s , g r a v e l Ê h e m i c a l / l r r i g a t i o n M a n a ç ¡ e r n e n t P l a n b b e r m g d a m g f o r i m p l e m e n t a t M a i n t a i n a ) T h e p r o p o s e d p r s j e c t s l r o u f d p r o v i d e Þ o t h a d e q u a t e ç t o r m w a t e r t r e â t r n e r l t å n r l r e t e n t i o n . T h e D r a f t Ë l R s h o u l d i d e n t i f u t h e p r o b a b l e t r e a t n ' r e n t a n d r e t e n t i o n B M P s a n d d i s c u s s t h e p o l l u t a n t * t h a t t h e i d e n t i f i e d B M P s w i l l a d d r e ç s . T h e f , i r a f t Ë l R e h c u l d q l s c ¡ i n c l u d e a d i s c u s s i c n r e g a r d i n g t h e q u a n t i t y o f s t o r m w a t e r r u n o f f t h e s e B M P s w i l l n e e c j t o a c c o r n m o d a t e . $ u c l t i n f o r m a t i o n c o u l c l þ e i n c l u c l e d i n a " G o n c e p t u a f " $ W P P P , T h e C o n c e p t u a l S W P P P w o u l d a l s o p r o v i d e s d d i t i o n a l i n f o r m a l i o n c . ) n o t h e r e i * r n e n t s { e . 9 , o o n s t i ' u c t i o n w a s t E m ä n Ë g s r n s n t . Ê h i P m a i n t e n a n c e , { r a i n i n g , d e w e t e r i n g o p e r a t i o r r s , p o l l u t a n i s o u r c a i d e n t i { i c a i i o n ) t h a t t h e N P D E S S t o r m W a t e r C o n $ t r u c t i o n G e n e r a l P e r m ? t r e q u i r e t b e i n g i n s l u d e d i n a S W P P P . S u c h i n f c n n a t i o n w i l l a * ç l s t s t e f f i n d e t e r r n i n i n g l f w a t e r q u a l i t y w i l i l r e a d e q u a l e l y p r e t e c t e d , b ) T i r e D E I R s h o u k l i n c l ¡ . l d e a n y s t o r m w a t e r r u n o f f c t n v e y a n r e o r d r a i n a g e a n a l y s i s r e p o r t s t l r a . t l ' ¡ a v e l " r e e n ç r a r e r e q u i r e d t o b e p r e p a r e d p r i o r t o i m p l e m e n t i n g t h e p r o j e c t . c ) T h e L t F I R s h o u l d d í s c u ç s i f f e ¡ t i l i z e i s ä n d o t h e r e h e m i c a l s w i l l L l e u s e d o n l a n c l s c a p e d a r e ı s . l f c h * m i c a l s w i l l b e u s e c J t p n l e i n t a i n l a n d s c a p e d a r e a a , t h e D Ë l R s h o u l d i d e n t i f y i h e r n e ä $ u r e s ( ê . 9 . i r i g a t i o n p r a c t i e e s , e h e m i e a l a p p l i c a t i r : r r p r a c t i c e s i t þ a t w i l l b e i m p l e m e n t e d t o p r â v e n t l a n c l s c a p e r r a í r r t e n e r r c e . r c t i v i l i c ; e f r c n r a d v e r s e i y a f f e c " i i n g w a t e r q u a l i t y . t a I | þ r n i a E n r ì r t ) f i ; ' t è n î a { I ' r * I e e t í t x , " l g t n c ¡ , i ß å . . : c r . ¿ t : s ' i r r r F . x , p : , l l ¡ , ' ? r ! 1 t 1 Ë : ! 3 5 3 8 - î 4 4 ' - ? ? 7 . ' . D e n y e l l e N i s h i m o r i L Ê r H ü ' { ï f n ' ¡ " . 9 . - C n l í þ r n i n f i n v * t n m e n I a l F r o \ e c | í o n . Å g e n c a ' P å r l r - ù 9 . r 1 . 1 5 d ) l f i h e p r C I j e ç " t w i l l b e r e l y i n g u p o n a r e v s g e i a t i o n e f f ( r t t o r e s t a b i l i e e â r e a s o f ' d i s t u r b e d s o i l , t h e p É l R e h o u l c l d i s c u s s w h a t m e a s L r r e s i s e e d i n g , F l a n l i n g , . i á * p o r a r y s o i t s t ã b i l i z a t i o n s u c h a s m u l s h ì n g , t e m ' . r o r a r y i r r i g a t i o n , m o n i t o r i n g ' ¡ n t e i i m a n d t ¡ n a l u r . c e s s c r i t e r i a ) w i l l b e i m p l e r n o n t e d t o e n s u r e t h a t v e g e t a t i o n i s r e e s t a þ t i s t r e d i ¡ r a m a n n e r t h a t e f f e c t i v e l y a n c l p e r r n å n e n t l y s t a b i l i z e s d i s t u r b e d s o ¡ l s . C l e a n W a t e r Å c t s e c t i o n 3 t l 3 { d } L i s t : C l o s e l y r e l l r t e d t o s t O r m r ¡ r a t e r c o n t r o l / t r e a l m e n t i s e r o s i o n c o n t i o i . l - h e T r u c k e e r { i v e r h a s b e e n p l a q e d o n t h e c l e a n w a t e r A c t s e c t i o r r 3 C I 3 ( d ) L i s l , a s b e i n g w a ! + r q u a t i t y i m p a i r e d c l u e t o . e x c e g g i v e e e d i m e n t ã t i o n . W a t e r B o a r d s l a f f c o n r i d e r s i n c r e a s e s i n * e d l m e n t l i a d i n g t o t h e T r u c k e e R i v e r a n d i t s t r i b u t a r í e s ã i a p o t e n t i a l l y s i g n i f i w n t i r n p a c t , T h e D Ë l R s h o u l d i d e n t i t y p r o b a b l e e r o s i o n c c n t r a l B M P s a n d l o c ¿ r t i o n * w i 1 e r e t h e y * o g f O l i i e l y b e d e p l o y e d . T h e C o n c e p t u a l S W P P P c o u l d b e u e e d t ' o p r a v i d e s u c h i l r f o r n r a t i o n a s t h e f i n â l S W P P P w i l l n e e d t o i d e r r t t f y t h e s p e c i f i c e r o s i o r l ç o n t r Ú i B * ¡ 1 p s t h a t w i l l b e u e e d ã t t h e p r o j e c t g i t e a n d t h e i r l o c a t i o n s . S t a f f r e c û r n l ï e n { s t h a t t h e e r o s i o n c o n t r o l B M P ç f o c u s û n s Õ u r c e c o n t r o l w i t h t r e a t m e n þ b s g e r l B M P s p r o v i d i r r g a s e c o n d l i n e o f d e f e n s e . M i n i r n i a i n g a n d s t a b i l i z i n g a r e a s o f d ¡ s t u r b è d ä o i t , r t o o - t p i l e r r r a n a g a m e n t / p r o t e c t i o n , d u s t s u p p r e $ s i o n , t e m p e l r a r y a n d p e r m a n e n t s t a b i l i z e d s t o r m w a t é r c o n v e y a n c e f e a l u r e s , a n d s e d i m e n t t r a c k i n g c o n t r o l s . a r e . ç o m e o f t h e s û u r c e - , : o n t r o l m e a s r ¡ r e s t h a l c a n b e i n c o r p o r a t e c t i n t o p r o j e c t d e s i g n a n d c o n s t r u c t l o n . l f p r c p o s e d c l u s t c o n t r o l r n e a s l ¡ r e s i n o l u d e t h e u s e o f d u s t p à l t i . t i u * * i n a d d i t i o n t o o r i n l i e u o f w a t e r , t h e n s t a f f l e c o m m è n d s t h a t t h e t l E l R i n c l u d e s h t a t ç r i a l S a f e t y D a t a S l r e e t s f o r e e l e c t e d s l u s t p a l l i a l i v e s s o t h a t s t a f f c a n b e t i e r e v a l u a t e i f t h e p r o p o s e d p r o d u c t s p r e s e n t p o i e n t ¡ å l w a t e r q u a l i t y t h r e a t s . S t a f f s e x p e r i e n o e s l n d i c a t e t h a t i t i s r ¡ o r e e f f e c l i v e t o k r : ê Þ t h e E o i l i n p l a c e . ( s o u r c e c o n t r o t ) , i a t h e r t h a n t r y i n g t o r e m o v a i t b y t r e a t m e n t o r . : e i t h a s b e e n r n o þ i l i z e d b y S t o r m w a t e r r u n o f f o r s n o w m e l t . T h i e i s w h y s t â f f r ê c ' ; t n ¡ n e n d s u s i n g L I D a n d s o u r c è - c o n t r o l r n e a s u r e s â s t h e p r i m a r y l i n e o f d e f e n ¡ e w i t h t r e a t m e n t t n å a s u t e s i r r r e d u n d a n c y a s t h e s e c o n d l i n e o f d e f e r t s e . g n o w S t o r a g e A r e a s : T h e i n f o r m a t i o n p r o v i d e d d o e ' ; n o t i t l q l i u a t e p o t e n t i a l l o c a l i o r r . t f o r f ¡ n o w s t O r a g e . S n o w r e m o v e d f r q r n a r s e s a s s o c i a t e d w i t h d e v e l o p m a n t s o f t h e p r o þ o s e c l p r o j e c t s n a t u r e o f t e , t c o n t a i n s s e c l i m e n t s , o i l - q , g r e a s e i , p e t r o l e r r m ¡ r r o d u c t s , a n , i o t h e r " o n . 1 ¡ l u e r r t s t h a t w o u l d n o r n r a l l y b e o o t l e c t e d a r r d t r e a t e d t h r o u g h v a r i o u s B f r / i P s . T h e D E I R s h o u l d d i s c u s s p r o b a b l e r n e t h o d s t ' r a t w i l l b e e m ¡ r l o y e d t o p r o l e c t b o t h s u d a c e a n d g r o u n d w a t e r q u a l i i y f r o r n p o l i u t ' . n t t s a s s c c l a t e t i w i t h s n o w r e t n o v a l a n d d l s p o s a l a c t i i i t i e s . T t r e O Ë l R s h o u i d a i s o C , s c u s s p r o p o s e d d e i c i n g m e t h r : d s f o r r o a d a n d p a r k i n g a r e g 3 , d e i c i n g m a t e r i a l ' , t o l Ë r g ê a n d h a n d l i ¡ t g a r e a s , a n d a s s ç c ¡ a t e c l B M P g . 6 ' $ . . , ? * . 1 , ; / e d f o p e " [ r 5 . j l l r , ' t ¡ l 1 I 1 å r ? i g 3 É ] Í 4 ¿ ? ' : 7 1 L - i e n ' y e l l e N i s l r i m o r i L A H T Í I T A I . I l 3 å L i f " b " l l , - 1 0 . 7 . H a l ¡ i t a t C o t r n e c t i v i t y : T , i e P r o j e c t i * p r o p o s e d f o r a n o p e n s p a c È a r e a a n d m a y p o $ e â s i g n i f i c a n t d i s r u p : r c n t o h a b i l ¿ r l c o n n e c t i v i t y , R i p a r i a n c q r r i d o r s a n d c t h e r w a t e r s w i t h i n t h e r e g u l r i t t ¡ . i p r l a , / i e w o f t h e W a t e r B o a r d c a n p l a y i r n p o r l a n t r o l e s i ¡ r r n a i n t a i n i r r g h a b i t a t c o r n e ( t i v i t y , Ë n c l o s u r e 3 , T e n e s t r i a l H a þ í t a t Ç o n n e c t i v i $ R e / a f e d T a W e t l a n d , R ì p a í a n a n r l A t h e r A q u a t i c R e s a u ¡ c e s , p r o v i d e s i n f o r m a t i o r i a n c l r e f e r e n Ë e s o n t i , i s s u ' r j e c t . A q u a t i c h a h ' i l a t r n a y a l s o b e f r a g n r e n t e c l b y i n r p a c t s t o s t r e â n ì $ o r o t h e r w ¡ t e ' o o r . { i e s , T h e E I B s h o u t d a n a l y z e t h e r e g i o n a l i r r i ¡ : u r t a n c e o f m o v e m e n t c o r r i d o r s i n a ¡ r d a l u n g v ¡ a t e r þ o c l i e s , t h e p o t e n . r a l r i f e c t o f d i s n i p t i n g s u e h c o r r i d o r s , a n d t h e p o t e n t i a l f o r e n h å n c , r t g s l . ¡ c h r ç o n r c l o ¡ " s l . ; p r o v i d € p r o j e c t m i t i g a l i o n . l n c l t t d e i n f o r m a t i o n r e g a r d i n c ¡ a r r y s e n s i t i v e p l a n r e , 1 d ä n m a l e p e c i e ç i h a t l i k e l y u t i l i z e t h e c o r r i d o r s . t r d e n t i f y a n y p r o j e e t i m p a c t s r ¡ r " ' p a r i a i l , : r o t h e r v ¿ a t e r s t h a t c o u l d c o n r p r o m i s e f i t t u r e ¡ e m e d i a t i * n o f e x i s t i n g c o n : r e c i i v i t y b a ¡ r i e r * . T o f u r t h e r i n f o r m i h e s e a n a l y s e s , c o n s i d e r t h e i n f o r m a t i o n a ' r d l i t e r a t u r e r e f e r e n c e d i n Ë n c l o s u r e 2 . i n c l u d i n g d a t a o ¡ ¡ t h e r o l e o f r i p a r i a n c ç r r d ç r s â s r n o v e m e n t c c r r i d o r s i n C a l i f c l n i a . B . 1 0 0 - y e a i ' F l o o d p l a i n P r o h i b i t i c n : l " h e L a h o n t a n W a t e r B c ¡ a r d p r o h i b i t s w a s t e d i $ e h s g e * ; d u e t o i f l s t u r b a n c e o t s u i l a c e w a t Ê r s a n d t h ê i r 1 0 û - y e a i f l o c , d p l a i n s i i i r - 1 . . - + . - - - 1 . - - ñ : - . ^ . - l l . . J - ^ l - - l - ¡ l * : ¿ ? L - - , . - - - L : l - ! r : - - . : - , i : . ^ ¿ L - i  l - ¡ ^ - I I i e ! U ç K e e 1 1 ! v e ! r l y i l l s l ç U l c r . ! l ¡ ! . . I t r $ $ S F ) t O f l l l J l l l t l l l $ ä l e C Ð f - r I - ã l t { ] ç A l t ! t l l l ? V ì J ë L t i ¡ E l t l r ¡ c l ' s B ; r s i ¡ r P l a n a n d c a n b e v i e w e d r n o u r w e b s i t e l o c s t e d a t h r - , 8 ' J $ ¡ S Þ . , W a t g l b j â r d g . _ 0 9 * g g g l þ h ç f ! 9 i l , u n d e r C h a p t e r 4 . 1 o f t h e B a s i n P l a n Ï h e r ¡ a $ i ñ P l a n p r o h i b i t i o n s a p p l y i n p a r t t o d r a i n a g e s w a l e s a n d w e t l a n d s , i n a d d i t i o n t o l a r g e r s u r f a c e w a t e l s . T l r e Ë l a s i n P l a n a l s < ¡ c o n t e i n s e x e n r p t i o n c r i t e r i a f o r p r o h i b i t i o n 4 ( c ) a d d r e s s i n g w a s t e d i s e h a r y e s t o t h e 1 0 0 - y e a r f l o a c l p l a i n o f t h e T r u c k e e R i v e r a n d i t s t r i b u t Ê r i * s . T h e p r o j e c t p r o p o n e n t w i i l h a v e t o r l t : m o n s t r â t e t h å i å ì n y p r o p o s e c l d i s t u r þ a n c e t o ç u r f a c e w a t e r s a n d l o r t h e i r 1 0 ü - y e * r f l o o d p l a i n u e a t i s l ¡ t h + e x e m p t i o n c r l t e r i a . H o $ r ê v e r , n o e x e m p t i o n c r i t e r i a e x i s t s f o r i * o l a t e d s u d a c e w a l e r s ( i n c f u d i n g i s o l a t e d w e t l a n d s ) , l f t h e p r o p o e e d p r o j e c l i n c l u e l e s d i s c h a r g e s o f r v ä s t e , i n c l u d i n g b u t n o t l i m i t e c l t o e a r t h ç n m a t e r i a l e , t o l s o l a t e d s u r f a c e w ê t e r s , r r e n n l c ' r e t h a n l i k e l y , g u c h a d i * c h a r g e w i l l þ e p r o h i b i t e d a r ¡ c l i h e p r o j e c t w i l l n e e d t o - , : r e d e s i g n e d t o a v o i d s u * h S i s c h ã r g o $ . . , s i m p o r t a n t t t r u t i h e Ð Ë l R i d e n t i f i e s a i l s u r f a c e w â t e r s ( e p í r e m e r a l a n c i p e r e n r r i a i : h a n n e l s / c r e e k s l s t r e a m e , w e t l a n d s , p o n d s , l a k e s , e t c . ) a n d a s s o c i a t e d ' 1 0 O - y e a r t o Ó d p l a i n s l C I æ t e d Õ n t h ê p r o B o s e d p r o j e c t s i t e . l t i s a l s o i r ï p e r a t i v e t h e t t h e D E I F i e n t i f y e a * h k n o w n s u r f a c e w â t e i a s " i ç q l a t e i f ' ' e r " t r i b u t a r y t o t h e T r u c l c e e R i v e r . ' l f t h e p r o j e c t p r o p o s a l i n c l u c l e s d i s c h a r g * o f w a s t e , i n c l u d i n g b u t n c t l i ¡ n i t e d t o e a r t h e n r n a t g r i a l s , t o a s u r f a c è w â t e r t h a t i E a t r i b u t a r y o f t h e T r u c k a e R i ! , , ê r , t h e n t h e Ð E l R n e e r J s t o i n c f u d e i n f o r m a t i o n d e m o n s t r a t i n g h o w t h e p r o p o s e r l p r o j e c t { r r l r n p l i e s l v i t h t h e ¡ * r o h i b i t i o n e x e m p t i o n c r i t e r i a c o n l a i n e d l n t h e B a s i n P l a n . l f g u c r r i n f o ' r n a t i o n i E n o t p r o v i c , l e d i n t h e Ð Ë l R , i t w i l l b e d i f f i c u l t a i b e s t t o i J e t e r r r i n e i f t h e ¡ : t o p o s e d p r o l e c t c o m p l i e s w i t h t h e B a s i n P l a n . P l e a s e b e ã w ' â r e t h a l a B a s i n P t a r r v i o l a t i o n i s c o n ç k i ç l e d a s i g n i f i c a n t i m p a c t . Ç a l i t ' o r n i * E n v i r ç n ¡ * e t r t a I P r ç t e e I ì . o n , 4 g e n c ¡ , $ Å c g r t c o ' P a p e t l ; i , ¡ l : , ' i ' l j l l 1 t ; 3 . i 5 ? B : d 4 : : ; f " : D * n y e l l e N i s h i m o r i L A H [ , ¡ ' I T å I ' ¡ P å r 3 8 . : l . ' 1 l . 1 1 - 9 . l ¿ V a t e r S u p p l y : T h e p r a p c s e d p r o j e c t w i l l c i e a t e a d d i t l o n a l d e m a n d u p û n t i r Ê e x i a t i n g w a t e r s u p p f y s y s l e m " P u n r p i n g g r o l n d w a t e r p r o v i d e s t h e r n a j o r i g o f w a l e r s u p p l y w i l h i n t i r e T r u c k e e a r e a . S t a f f i s c o n c e r n e r J t h a t i n c r e a s e s i n g r o u n d u , ¡ a t e r p u r n p i n g f r o n r t h i t P r o i e c t m a y b e g i n t o a d v e r s e l y a f f e c t s u d a c e w a t ê r r e s o u r È e $ a n d t h e b * n e f i c i a l r e s o u r ü e s a s s o c i a t e d w i t h t h o s e r ë s o u r c e s . $ l a f f w o u l d c r : n s ì d e r i t t o b e a s i g n i f i c a n t i m p a c t i f g r o u n d w a l e r r v i t h d r a w a l s b e g a n t o d e c r e a s e s u r f a c e v v a t e r r e å o u r c e s d u e t o i n d i r e c t i m p a c t s s u c h a s d e s i c c a t i n g w e t k : n c l s . T h e I J E I R s h o u l c l p r o v i d e i n f o r m a t i o n t h a t d a r n o n s t r a t e s t h a t t h e p r o p o s e c l p r o j e c t , i n c i i v i d t - t * l l y a n d c u m u l a t i v e l y w i t h o t h e r e x r s t i n g a n d p r o p o e ; e d d e v e l o p m e i i i w i l l n * t a d ' ; e r s e l y i m p a c l s u f a c e w â t ê r r e t ç u r c e s . l f t h e i n f o r m a t i o n a n d c o r r c l u È i o n s f , r r o v i d e d í n t h e D Ë l R r e l y u p o n r e g i o n a l c i r o u n d w a t e r s l u d i e s , t h e n e t s f f r e q i l e s l å t h a t s i t e - s p e c i Í i c i n f o r m a t i o n ì s a l r o p r o v i d e d t o s r . r p p o r t a n y r e g i o n e l - b a s e d c o n c f u s i o n s t h a t t h e t l E l f ì r e l i e s u p o n . A g a i n , t h a n k y o u f c r r t h i s o p p c r t u n i t y t o c o r n n r e n t . A t t e r n p t s i o n l a n a g ê t h e t r c l v e r s e e f f e c t s o f u r b a n d e v e l o p m e n t f o r r n a l a r q ¡ e p a r f , o f t h e w o r k l a a d o f t h e S t a t e a n r J L a h o n t a n W a t e r E o a r d n o n - p o i n t s o u r c e , s t c r n w a t e r ' , a n d l v a t e r q u a f i t y c e r t i T i ç a t i o n p r o g r a r n s , a s w * l l å 3 û u r e f f o r t s t ö e s t a b l i s h t o t â l n r a x ¡ r n r . r m d a i l y l o a d s f o r i r n p a i r e d w a t e r l ¡ o c l i e s . l v l a n y o f t h e w a t e r b o d i e s c u r r e n t l y o n t h e S t a i e ' s l i s t o f i m p a i r e d v ¿ a t e r l r Õ d i e s e r e a f t e c t e d b y c o n d i t i o n s w i t h i n i h e p u r v i e w o f l o c a l a g e n c y p l a n n i n g . H o w e v e r , a f i e r - t h e - f a c t r e g u l ä t e r y c o n t r o l i s a t b e * t a p a r t i a l s ¡ - l þ s t i t u t e f o r p l a n n i n g w h i c h a v o i d s w a t e r q u a l i t y d e g r a d a t i o n . W e t h e r e f o r e w e l c o r r r e t h e o p p o r l u n i t y t o w o r k w i t h t h e T o w n o f T r u c k e e t o m a k e t h e P r o j e c t d e v e l o p m e n i a n e x a m p l e o f e n v i r o n m e n t a l l y - a p p r o p r i a t e p l a n n i n g i n C s l i f o r n í a . W e l o o k f o r w a r d t c r w o r k í n g w i t h y o u l r r y o u r e t T o r t s t o p r ç 1 6 6 ¡ w a t e r q u a l i t y . l f y o u h a v e a n y q u e s t i o n s , p l e a s e c o n t a c t " l o b i T y l e r a t ( 5 å 0 ) S 4 Z - ä / r 3 5 . ¡ \ ! a n M i l l e r , P . Ë , C t r ¡ e f , N r : r t h B a ¡ ; i n R e g u l a t o r y U n i t Ë n c l o s r ¡ r e : T e r r e s t r i a l H a b i t a t C o n n e c i i v i i y R e i å t e d t o W e t l a n c l , R i p a r : i a n a n d . $ i h * r A q u a t i c R e s o u r c e s r Ç : $ t a t e Ç l e a r l n g h o u s e - ñ , T l Õ e r y o n $ p r i n g s l - i l i : P ê ¡ 1 l i r g / N t ! + r d ã S ù b r t ì v l s l o r r N O P c o r ¡ . n e n l s 5 - ' i å - i l T r d + c C ô u n t y , 1 C * n y q n S ! r n g s $ u t l d i v i s l ¡ ¡ r p ¡ r i j e r : ! C t l i þ r n i a E n ú r o n n t e t i s I F r o t e c l i o n , 4 9 * n c r - November 5, 2014 Ms. Carmen Borg, AICP Shute, Mihaly & Weinberger LLP 396 Hayes Street San Francisco, California 94102 Subject: Review of Transportation and Traffic Impact Analysis Revised Draft Environmental Impact Report – Canyon Springs, Truckee, California Dear Ms. Borg: As requested, MRO Engineers, Inc., (MRO) has reviewed the traffic impact analysis addendum completed with respect to the proposed Canyon Springs project in Truckee, California. The revised traffic impact analysis was prepared by LSC Transportation Consultants, Inc., and was documented in a letter report dated January 17, 2014. The traffic impact analysis addendum report has been incorporated into a Revised Draft Environmental Impact Report (RDEIR) prepared by Placeworks (formerly The Planning Center/DCE) on September 29, 2014. Background On February 20, 2013, MRO completed a letter report documenting the results of our review of the “Transportation and Traffic” section of the Draft Environmental Impact Report (DEIR) for the proposed Canyon Springs project. That review focused on the adequacy of the DEIR’s transportation and traffic analysis, including the detailed procedures and conclusions documented in the LSC Transportation Consultants report, which formed the basis for that section of the DEIR. Our letter report documented eight areas of concern with respect to the DEIR traffic analysis. Based on that, we concluded that the DEIR was deficient and needed to be revised, then recirculated for further public comment. The introduction to the January 2014 traffic impact analysis addendum states that certain additional or revised traffic analyses were undertaken, “. . . in response to comments received during the DEIR public review period.” We initially assumed that the addendum report would fully address the eight deficient areas that we identified in our February 2013 letter. Unfortunately, however, that was not the case. In fact, only one of the problem areas was addressed, while ignoring the remaining seven. The following section summarizes the results of our review of the traffic impact analysis addendum that was incorporated into the RDEIR. Following that, we present several additional comments resulting from our review of the RDEIR. Traffic Impact Analysis Addendum/RDEIR Review As indicated above, the traffic impact analysis addendum failed to address a number of deficiencies that we identified within the DEIR. Those deficiencies included significant traffic impacts that were not disclosed or mitigated in the DEIR, which should be addressed prior to certification of the environmental document by the Town of Truckee. The status of these issues is summarized below. M R O ENGINEERS 660 Auburn Folsom Rd. Suite 201B Auburn, California 95603 PHONE (916) 783-3838 FAX (916) 783-5003 Ms. Carmen Borg November 5, 2014 Page 2 1. No Analysis of Potential Freeway System Impacts – In our February 20, 2013 letter, we noted the following: • Thirty-five percent of the Canyon Springs-generated traffic was assigned to/from the west on I-80 at the Hirschdale Road ramps in the PM peak hour. • Twenty-five percent of the project-generated trips were assigned to/from the east on I-80 at the Hirschdale Road ramps in the PM peak hour. • Under year 2031 conditions, 39 percent of the project-generated trips were assigned to/from west on I-80 in the PM peak hour, and 18 percent of the total were assigned to/from the east. Despite this, no analysis was conducted to assess potential project-related traffic impacts on the freeway mainline or at any of the on- or off-ramps or the merge/diverge points where the ramps meet the freeway mainline. Consequently, no determination could be made as to whether the proposed project will adversely impact traffic operations on the freeway facilities. The RDEIR continues to ignore the proposed project’s potential impacts on the freeway system. 2. Level of Service Calculation Methodology – The DEIR traffic analysis failed to employ the latest (year 2010) version of the Highway Capacity Manual, in violation of the Town of Truckee General Plan Policy CIR-P3.1. The traffic impact analysis addendum report presents revised level of service results, based on application of the current edition of the Highway Capacity Manual. As such, no further comment is presented with respect to this issue. 3. Analysis Periods – The DEIR traffic analysis largely focused on traffic operations in the PM peak hour, although AM peak-hour analyses were performed at four of the eight study intersections. We pointed out that, although it might be true that PM peak hour volumes are greater than AM peak hour volumes, because directional traffic patterns are different in the two peak-hour periods, problems that may not be apparent in the PM peak hour are sometimes revealed in the AM peak hour. Further, the volume of project-related trips in the AM peak hour is substantial – 194 total trips, 148 of which will be outbound from the project site (which is only 16 trips fewer than the peak direction volume in the PM peak hour). In short, by analyzing only the PM peak hour, any AM peak hour impacts will be missed. Although CEQA requires that all significant impacts associated with the proposed project be revealed in the DEIR, the RDEIR failed to address the possibility of AM peak-hour traffic impacts. We believe there is a reasonable likelihood that significant impacts might be found in the AM peak hour that are in addition to those identified in the PM peak hour. 4. Peak Hour Traffic Volume Data – In our February 2013 letter, we summarized the circuitous process used to estimate the year 2011 (i.e., existing) traffic volumes used in the analysis. At certain locations, this process consisted of manipulation of traffic count data from the year 2004, a full ten years ago. Despite this, the DEIR makes the dubious assertion that the traffic volumes used in the analysis are conservative. Of course, the standard approach to developing “existing conditions” traffic volume information is simply to perform counts at the study locations. Given the almost one-year interval between submittal of our February 20, 2013 comment letter and completion of the January 17, 2014 M R O ENGINEERS M R O ENGINEERS M R O ENGINEERS Ms. Carmen Borg November 5, 2014 Page 3 traffic impact analysis addendum, there was clearly sufficient time to collect data that would satisfy the Town’s policy calling for analysis of the tenth-highest summer PM peak hour. It is unclear, therefore, why no counts were performed in the summer of 2013. Those counts could have then been adjusted as necessary to represent the tenth-highest hour. As we noted in our February 2013 letter, this approach is vastly superior to basing the existing conditions volumes on counts conducted in the spring or summer of 2004. Because no effort was expended to obtain valid, up to date traffic volume data, we remain concerned that the estimated traffic volumes used in the RDEIR analysis may not accurately represent current conditions in Truckee. 5. Daily Traffic Volume Data – The daily traffic volumes used in the analysis of roadway segments were also estimated, based on estimates of peak-hour traffic. The process of developing daily traffic estimates based on estimated peak-hour values results in a substantial margin of error for those daily traffic figures. Again considering the one-year interval between the DEIR comment period and completion of the RDEIR traffic analysis, it is puzzling that no counts were conducted in the summer of 2013. Because the RDEIR failed to address this deficiency in the most basic information employed in the traffic analysis, we continue to question the validity of the fabricated “existing” traffic volumes. 6. Cumulative Conditions Traffic Volume Estimates – Although the cumulative conditions analysis presented in the RDEIR claims to address projected traffic operations in the year 2031, it actually employs year 2025 traffic volume projections. (The Town of Truckee’s TransCAD travel demand forecasting model provides traffic estimates for the year 2025 and no further traffic growth was assumed between 2025 and 2031.) It is simply misleading and inappropriate to suggest that the analysis covers a twenty-year time period when it actually considers only fourteen years. The RDEIR does include a limited evaluation of the updated (June 2011) Truckee model, which has higher trip generation projections in the Glenshire area near the proposed project, as well as a revised trip distribution. Based on consideration of two study intersections, the RDEIR concludes that it is unnecessary to update the analysis for the entire study area. We believe that this is insufficient justification for the use of an obsolete traffic model. Given the complexity of any transportation system, it is simply not possible to make a reasonable judgement of this sort without additional consideration. At a minimum, the RDEIR should document a comparison of the traffic volumes at each study location using each version of the model. A reasonable recommendation could then be documented with respect to the need for additional analysis. 7. Safety Analysis – Our February 2013 letter documented the failure of the DEIR to provide information regarding safety problems in the vicinity of the proposed project. Although the DEIR presented a table and related text describing historical accident rates at seven locations, it neglected the fact that six of those seven locations have accident rates that are substantially higher than California and Nevada County averages for similar roads. Although this information was buried in the LSC traffic report (which was provided as DEIR Appendix I), it is disturbing that such an obvious safety issue was not presented in a more transparent fashion. In addition to the possibility that this could be viewed as a failure to meet the DEIR’s obligations as an informational document, we are concerned that no effort was made to evaluate the potential M R O ENGINEERS M R O ENGINEERS M R O ENGINEERS Ms. Carmen Borg November 5, 2014 Page 4 impacts of the proposed project with respect to the safety of nearby residents. The RDEIR includes no effort to rectify this substantial deficiency. 8. Donner Pass Road Extension Project – As presented in our February 2013 comment letter, the finding of acceptable levels of service under cumulative conditions is dependent upon the assumed completion of the Donner Pass Road Extension. Unfortunately, completion of that critical roadway system improvement project is beyond the control of not only the Canyon Springs project, but also the Town of Truckee. In fact, the Donner Pass Road Extension project is directly tied to the private sector Railyard Master Plan project, and whether this roadway system improvement occurs is dependent upon whether the railyard developer proceeds with the development project and funds its substantial portion of the road improvement. If the developer of the Railyard Master Plan project fails to implement that development for any reason, the Donner Pass Road Extension will not be completed. If that occurs, the entire cumulative conditions traffic analysis presented in the DEIR will be inaccurate, presenting an overly-optimistic view of traffic operations in the year 2031. Consequently, additional cumulative conditions traffic impacts are likely to be found. As with the other issues discussed above, the RDEIR includes no revisions aimed at correcting this deficiency in the environmental documentation. We believe that an enhanced cumulative conditions analysis is necessary, which would reveal the traffic impacts and needed mitigation measures if the Donner Pass Road Extension project is not completed. ADDITIONAL COMMENTS In addition to the comments summarized above, further review of the environmental documentation has revealed several more issues. These are presented below. 9. Glenshire Drive/Donner Pass Road Intersection Mitigation – To offset excessive intersection delay at Glenshire Drive/Donner Pass Road, Mitigation Measure TRANS-1 (RDEIR p. 4.14-68) calls for implementation of a center refuge/acceleration lane for vehicles turning left from Glenshire Drive to westbound Donner Pass Road, in combination with other actions (including limitation of the development to 84 units until other requirements are met). The RDEIR concludes that construction of this physical improvement, combined with the various development limitations, will reduce the impact to Less Than Significant. However, several issues affect the feasibility of this recommended mitigation measure, primarily relating to funding, safety, and effectiveness of the proposed improvement. With regard to funding of the center refuge/acceleration lane, Mitigation Measure TRANS-1 states that: “. . . the project applicant shall pay its fair share portion of the cost.” No information is provided with respect to how the remaining portion of the improvement cost (i.e., the portion in excess of the project’s fair share) would be funded. Payment of a fair share contribution toward an improvement provides no mitigation unless the full cost of the measure is M R O ENGINEERS Ms. Carmen Borg November 5, 2014 Page 5 guaranteed. Because the mitigation measure described in the RDEIR gives no indication that the improvement project is fully funded, no mitigation exists. The second issue relating to the proposed mitigation measure concerns its feasibility and effectiveness. Construction of this lane would allow left-turning vehicles to perform a “two-stage” movement: first, a left-turn from Glenshire Drive to the refuge/acceleration lane and, second, acceleration into westbound Donner Pass Road traffic. Unfortunately, sufficient distance is not available between Glenshire Drive and Keiser Avenue to construct an adequate acceleration lane that would allow vehicles to move safely into the westbound traffic stream on Donner Pass Road. Specifically, the conceptual design illustrated on RDEIR Figure 4.14-7 (RDEIR p. 4.14-42) shows an acceleration lane that is approximately 120 feet long. This is far less than the acceleration lane length recommended in the 2010 National Cooperative Highway Research Program (NCHRP) Report 650, Median Intersection Design for Rural High-Speed Divided Highways. Table 35 in that document describes the “Desirable Length of Full-Width MAL” [Median Acceleration Lane] for a roadway with a 45 MPH posted speed limit as 820 feet. (Note that introduction of the center refuge/acceleration lane effectively turns the pertinent section of Donner Pass Road into a divided highway with a painted median.) With respect to the length of median acceleration lanes, the Caltrans Highway Design Manual generally defers to the document entitled, A Policy on Geometric Design of Highways and Streets (American Association of State Highway and Transportation Officials (AASHTO), 2011). Specifically, the May 7, 2012 version of the Caltrans document states the following (pp. 400-22 – 400-23): “Acceleration Lanes for Turning Moves onto State Highways. At rural intersections, with “STOP” control on the local cross road, acceleration lanes for left and right turns onto the State facility should be considered. . . . For additional information and guidance, refer to AASHTO, A Policy on Geometric Design of Highways and Streets. . .” Exhibit 10-70 of the AASHTO document shows the minimum acceleration lengths for “entrance terminals.” For a roadway having a 45 MPH design speed with vehicles entering from a “stop condition,” the recommended acceleration length is 560 feet. We should note that this value applies to a facility with a “flat grade of two percent or less,” and Donner Pass Road at Glenshire Drive is on a downgrade that exceeds two percent. Consequently, a substantial portion of the westbound vehicles on Donner Pass Road were observed to be traveling in excess of 45 MPH, which would increase the needed acceleration length. Referring back to the Caltrans Highway Design Manual (p. 200-30): “Figure 405.9 shows the standard taper to be used for dropping an acceleration lane at a signalized intersection. This taper can also be used when transitioning median acceleration lanes.” The taper referred to above is equal to the width of the acceleration lane multiplied by the velocity of the vehicles (for speeds greater than or equal to 45 MPH). Thus, for the 15-foot-wide M R O ENGINEERS Ms. Carmen Borg November 5, 2014 Page 6 acceleration lane shown on RDEIR Figure 4.14-7, a taper of 675 feet would be required (15 X 45 = 675). Even if the lane were only the standard width of twelve feet, the taper would need to be 540 feet (12 X 45 = 540). Combining the required acceleration lane length (560 feet) and the taper length needed to blend the lane back into the two-lane road (at least 540 feet and as much as 675 feet) indicates a need for a total length of 1,100 – 1,235 feet. In comparison, RDEIR Figure 4.14-7 shows a 120-foot acceleration lane length combined with a taper or transition section of approximately 65 feet, for a total length of about 185 feet. Therefore, to construct this “mitigation measure” would potentially induce a significant safety issue at the Glenshire Drive/Donner Pass Road intersection, as drivers attempting to merge into the flow of traffic on westbound Donner Pass Road would have insufficient distance to accelerate to anything close to 45 MPH before being forced to merge with that high-speed traffic. An additional safety issue concerns the likely possibility that vehicles turning left from Keiser Avenue to eastbound Donner Pass Road will also use the refuge/acceleration lane. In this regard, the RDEIR (p. 4.14-41) says the following: “The pavement markings associated with the left turn lane would be designed to discourage drivers making left turns from Keiser Avenue onto Donner Pass Road from pulling into the painted median area, in order to minimize the potential for traffic accidents.” We note the use of the word “discourage,” rather than the more certain “prohibit.” We believe it is a relative certainty that drivers turning from Keiser Avenue will drive over the painted pavement markings to use the refuge area, leading to confusion, conflicts, and collisions. Furthermore, RDEIR Table 4.17-10 (p. 4.14-43) shows that, even with implementation of the median acceleration lane, the “with project” delay on the worst movement at this intersection would be 5.6 vehicle-hours. The LSC addendum report (p. 4) further states: “Table 5 summarizes the LOS and delay on the worst movement (the left-turn movement from Glenshire Drive) under 2011 conditions with the new center lane. . . However, with full buildout of Canyon Springs, the LOS would degrade to an unacceptable level, with approximately 5.6 to 7.0 vehicle-hours of delay on the worst movement, depending on which site access alternative is selected.” LSC’s Table 5 shows that the value of 5.6 vehicle-hours of delay is associated with the proposed project, while the 7.0 vehicle-hours of delay result relates to the Edinburgh Drive Access alternative. In short, even with implementation of the recommended mitigation measure, the intersection fails to operate acceptably under full project buildout. Moreover, as described above, the proposed mitigation measure will create a significant safety issue at the intersection. It simply M R O ENGINEERS Ms. Carmen Borg November 5, 2014 Page 7 makes no sense to induce a potentially significant safety problem by constructing an “improvement” that provides insufficient operational benefit. The RDEIR analysis dismisses the possibility of installing a traffic signal at this location, with only the briefest consideration. According to RDEIR p. 4.14-40, a traffic signal was considered infeasible, “due to the existing steep grades.” We note that the traffic volumes at this intersection are sufficient to meet the “Peak Hour” traffic signal warrant, as presented on Figure 4C-3 of the California Manual on Uniform Traffic Control Devices (Caltrans, January 12, 2012), and provided here as Attachment A. We believe that it is not sufficient to claim that this intersection cannot be signalized because of the grades on Donner Pass Road at Glenshire Drive. Many jurisdictions have constructed signals in similar locations, with snowy conditions. Features such as advance signal heads, flashing beacons, high-friction pavement, advance detector loops, etc., may be necessary to ensure safety but, with judicious design, a traffic signal is potentially feasible at this location, and needs to be considered. With specific regard to the use of high-friction pavement, we note that neighboring Placer County has recently announced that it will be installing “high friction surface treatment” at 26 locations throughout the county. According to a public notice distributed by the Placer County Public Information Office (“Placer County E-News,” October 24, 2014): “The treatments are effective in reducing accidents by dramatically increasing the friction between vehicle tires and the roadway. This helps vehicles stop faster and drivers maintain better control without skidding. The treatment is especially effective around curves, on downhills, or approaching an intersection. The treatment places a thin layer of specially engineered aggregates as a topping on a coat of resin binder. The resin binder then locks the aggregate firmly in place, creating an extremely rough and durable surface capable of withstanding everyday roadway demands.” In conclusion, the proposed mitigation measure not only has limited beneficial effect with respect to traffic operations, but it will create a significant safety hazard on Donner Pass Road. Installation of a carefully designed traffic signal would appear to be the safest and most effective means of moving traffic through this intersection. More detailed consideration needs to be given to this option to mitigate the project’s significant impact at this location. 10. School-Related Traffic Impacts – To assess the impacts of the project on school-related traffic, the environmental documents evaluated three intersections at which traffic patterns were judged to be influenced by activity at the nearby Glenshire Elementary School: • Glenshire Drive/Dorchester Drive (West), • Glenshire Drive/Somerset, and • Glenshire Drive/Whitehorse Road/Martis Peak Road. Unfortunately, these study intersections do not encompass the entire area that will be affected by project-related traffic impacts. Particularly significant is the exclusion of the Glenshire Drive/Dorchester Drive (East) intersection, as that will provide the primary access to the school from the project site (via Martis Peak Road to Glenshire Drive). In addition, the Glenshire M R O ENGINEERS Ms. Carmen Borg November 5, 2014 Page 8 Drive/Rolands Way intersection should be evaluated, as it is likely to be used for outbound trips from the school. To ensure a thorough analysis of potential school-related traffic impacts, it is essential that these two additional intersections be evaluated for project-related impacts. 11. Edinburgh Drive Access Analysis – Section 5 of the RDEIR documents the analysis of project alternatives. One of those alternatives, designated Alternative B, considers a project circulation plan that includes vehicular access by way of Edinburgh Drive on the west side of the project site (in addition to the access location on the east side of the site that would be provided as part of the proposed project). According to RDEIR Table 5-1 (RDEIR p. 5-5), that alternative would have traffic impacts that are “similar to the proposed project.” This finding is simply not credible, however, as will be demonstrated below. Inclusion of the Edinburgh Drive access point will alter the geographic distribution of the project-related trips. The environmental documents, however, present inconsistent information with respect to the specific magnitude of this change. For example, p. 50 of the August 2012 report by LSC Transportation Consultants, Inc. (which was incorporated into the DEIR) says: “A key difference between this [Edinburgh Drive] alternative and the proposed alternative is that the majority (60 percent) of project-generated traffic would use the Edinburgh Drive/Glenshire Drive route instead of the Hirschdale Road/I-80 route for trips made to/from points west of the Glenshire area.” In contrast to this, page 48 of the same LSC report states the following: “Based on the layout of the development, it is assumed that 85 percent of trips made to/from points west of Glenshire would use the Edinburgh Drive access, and the remaining 15 percent of these trips would use Martis Peak Road.” Thus, there seems to be some confusion on the part of the traffic analyst as to the trip distribution for project-generated trips under the Edinburgh Drive access alternative. In any event, the RDEIR has apparently employed the latter (85 percent west/15 percent east) distribution, as described on p. 5-11 of that document, which contains a statement that is almost identical to the second excerpt from the LSC report presented above (differing only in substitution of the word “site” for “development”). We should note that, based on field investigations and evaluation of the study area road system, we would generally support the “85 percent west/15 percent east” distribution of traffic under this alternative. In concluding that the Edinburgh Drive Access alternative’s traffic impacts are similar to those of the proposed project, the RDEIR goes on to say (RDEIR p. 5-18): “With the Edinburgh Drive connection open to general traffic, the Alternative B is expected to result in an increase of up to approximately 89 PM peak-hour one-way trips and 840 average daily traffic (ADT) in 2011, and 91 PM peak-hour trips and 860 ADT in 2031 on the local roadway segments in the project study area. As this increase is less than 1,000 ADT, Alternative B would meet the Town’s adopted M R O ENGINEERS M R O ENGINEERS Ms. Carmen Borg November 5, 2014 Page 9 standard for impacts on local residential roadways, so long as the provisions of Circulation Element Policy P2.4 can be met.” Unfortunately, the arithmetic performed in deriving the values presented above is apparently faulty, as those values reflect no more than about 35 percent of the project-generated trips, which is obviously far less than 85 percent. Table 1 summarizes the actual volume of traffic that would be expected on the residential streets upon implementation of this alternative. Table 1 Alternative B: Edinburgh Drive Access Local Roadway Traffic Assignment Daily Trips AM Peak Hour PM Peak Hour In Out Total In Out Total Total Project Trip Generation1 2,578 46 148 194 164 93 257 RDEIR 2011 Local Roadway Trips2 840 --3 -- -- -- -- 89 32.6% -- -- -- -- -- 34.6% RDEIR 2031 Local Roadway Trips2 860 -- -- -- -- -- 91 33.4% -- -- -- -- -- 35.4% Corrected Local Roadway Trips4 2,191 39 126 165 139 79 218 85.0% 85.0% 85.0% 85.0% 85.0% 85.0% 85.0% Notes: 1 RDEIR Table 4.14-6, p. 4.14-29. 2 RDEIR p. 5-18, as cited above. 3 No figure presented in the RDEIR. 4 Based on the 85 percent westerly trip assumption presented in the RDEIR. Clearly, the volume of project-related traffic on the local roadways that would be affected by implementation of the Edinburgh Drive Access alternative is grossly underestimated in the RDEIR. The number of PM peak hour project trips on the local residential streets will be over 200, not 89 or 91. More importantly, rather than 840 or 860 daily trips added to those roadways, the actual number will be almost 2,200, based on the trip distribution presented in the RDEIR. Further, every single one of these trips will occur on Edinburgh Drive and Regency Circle north of Edinburgh Drive, with the bulk of the trips also using major portions of Courtenay Lane and Somerset Drive. In short, given that 2,200 daily trips is substantially more than the 1,000 trips per day that the Town uses as a standard for residential streets, this alternative would clearly result in a significant impact. Table 21 (p. 61) in the August 2012 LSC traffic impact analysis report summarizes the project- related effects on the local roadways. As noted above, however, the volume of project-generated trips derived for that analysis is incorrect. Table 2 presents a corrected version of that table. M R O ENGINEERS Ms. Carmen Borg November 5, 2014 Page 10 Table 2 Local Road Impacts - Corrected Edinburgh Access Alternative Roadway Segment ADT Exceeds Town Standard for Allowable ADT? Without Project Project Impact With Project Year 2011 Somerset Dr. – Glenshire Dr. to Courtenay Ln. 1,430 2,190 3,620 Yes Courtenay Ln. – Somerset Dr. to Regency Circle 530 2,190 2,720 Yes Regency Circle 510 2,190 2,700 Yes Edinburgh Dr. 130 2,190 2,320 Yes Year 2031 Somerset Dr. – Glenshire Dr. to Courtenay Ln. 2,060 2,190 4,250 Yes Courtenay Ln. – Somerset Dr. to Regency Circle 590 2,190 2,780 Yes Regency Circle 570 2,190 2,760 Yes Edinburgh Dr. 150 2,190 2,340 Yes All four local roads represented in the table would exceed the 1,000 trips per day standard employed by Truckee, in both 2011 and 2031. Traffic on Edinburgh Drive in 2011 would be almost 18 times greater with completion of the project, representing an increase of 1,685 percent). On Regency Circle, an increase of over 400 percent is projected for the year 2011, with lesser, but still significant increases on the other residential streets. Because the RDEIR analysis of project alternatives includes no detailed level of service analyses and the LSC report presents only very limited information of this type, it is impossible to discern the exact impact to the intersections and roadways in the neighborhood to the west of the proposed project (with the exception of the Glenshire Drive/Somerset intersection). Clearly, the facilities that would be impacted with the Edinburgh Drive connection are drastically different from those affected by the proposed project. If the Edinburgh Drive Access alternative is to be given serious consideration, at a minimum, the following locations should be examined: Roadways • Edinburgh Drive, • Regency Drive, • Courtenay Lane, • Somerset Drive, M R O ENGINEERS Ms. Carmen Borg November 5, 2014 Page 11 • Wiltshire Lane, and • Wellington Way. Intersections • Regency Circle/Courtenay Lane, • Somerset Drive/Courtenay Lane, • Wellington Way/Courtenay Lane, • Wellington Way/Glenshire Drive, and • Wiltshire Lane/Glenshire Drive. 12. Potentially Unfunded Transportation Projects Assumed – In addition to the Donner Pass Road Extension Project, which was discussed in our February 2013 letter, the cumulative conditions (year 2031) analysis in the RDEIR assumes completion of two other road system improvements: the Pioneer Trail Extension and the Bridge Street Extension. According to the RDEIR, these projects will provide additional connections between Downtown Truckee, Tahoe Donner, and Pioneer Trail. However, no information is presented with respect to the source(s) of funding to construct these projects (if any). It is, therefore, unclear whether there is a reasonable certainty that the roadway system improvements will actually be built in the cumulative conditions timeframe. If they are not completed, the level of service at certain locations could be worse than stated in the RDEIR, potentially resulting in additional significant impacts. To ensure consideration of a reasonable “worst case” scenario, the RDEIR must be modified to include a cumulative conditions analysis that would reveal traffic impacts and related mitigation measures if the Pioneer Trail Extension, Bridge Street Extension, and Donner Pass Road Extension projects are not completed. 13. Bicycle Safety – The RDEIR fails to address issues related to bicycle safety in the study area. Of particular concern is the two-mile section of Glenshire Drive between Martis Peak Road and Hirschdale Road, which is commonly known as the Hirschdale Hill. Bicyclists commonly use this facility, which is steep, curvy, and relatively narrow (particularly with respect to the width that would be necessary to provide two standard travel lanes in combination with standard bike lanes on each side). Project-related increases in traffic volumes on Glenshire Drive will exacerbate existing bike safety deficiencies, potentially leading to a significant impact. This must be evaluated in detail in the environmental documents. CONCLUSION Our review of the Revised Draft Environmental Impact Report prepared for the proposed Canyon Springs project in Truckee, California revealed continued deficiencies in the document. Several issues that we identified in our February 20, 2013 comment letter were simply ignored in the RDEIR. Moreover, we have identified several additional deficiencies in the environmental documentation, which are presented in this letter. Of particular concern is the inaccurate analysis of the impacts of the Edinburgh Drive Access alternative, particularly with respect to the residential streets in the existing neighborhood immediately to the west of the project. That analysis incorrectly M R O ENGINEERS M R O ENGINEERS M R O ENGINEERS M R O ENGINEERS M R O ENGINEERS Ms. Carmen Borg November 5, 2014 Page 12 concludes that this alternative would have no significant impacts on the neighborhood. We have presented information demonstrating that this conclusion is faulty. Consequently, the validity of the conclusions and recommendations presented in the environmental documents remains questionable, and the proposed project may have additional significant impacts on the environment beyond those identified in the RDEIR. These issues must be fully addressed prior to approval of the proposed project and its related environmental documentation. We hope this information is useful. If you have questions concerning anything presented here, please feel free to contact me at (916) 783-3838. Sincerely, MRO ENGINEERS, INC. Neal K. Liddicoat, P.E. Ann C. Olson, C.E., T.E., P.T.O.E. Traffic Engineering Manager President M R O ENGINEERS ATTACHMENT A Warrant 3 - Peak Hour Signal Warrant Glenshire Drive/Donner Pass Road M R O ENGINEERS Conservation Biology Institute 1 November 18, 2014 Conservation Biology Institute 136 SW Washington Avenue Suite 202 Corvallis, Oregon 97333 www.consbio.org November 18, 2014 Ms. Carmen Borg, AICP Shute, Mihaly & Weinberger LLP 396 Hayes Street San Francisco, CA 94102 Subject: Review of Biological Section of Canyon Springs Revised Draft Environmental Impact Report Dear Ms. Borg: This comment letter on the Canyon Springs Revised Draft Environmental Impact Report (RDEIR) (Placeworks 2014) is submitted by the Conservation Biology Institute (CBI) on behalf of the Mountain Area Preservation Foundation (MAPF) and Saving Open Space Around Glenshire (SOSG). CBI is a non-profit conservation science organization whose mission is providing scientific expertise to support conservation and recovery of biological divers ity in its natural state through applied research, education, planning, and community service. I have confined my review primarily to the Biological Resources section s of the RDEIR and Draft Environmental Impact Report (DEIR), and appendices to these documents. Other relevant documents or data reviewed are included in the reference section of this letter. I also reviewed Shute, Mihaly and Weinberger’s prior comment letter on the DEIR (SMW 2013) and concur with statements in that letter regarding biol ogical issues, particularly the failure of the DEIR to adequately address the biological setting, impacts, and mitigation. Those issues were not adequately addressed in the RDEIR. This letter expands on those and other biological issues. Conservation Biology Institute 2 November 18, 2014 In general, I find the RDEIR inadequate for the following reasons:  The description of existing biological resources is outdated and it is questionable whether it accurately describes current conditions onsite.  Project does not adequately address direct or indirect impacts to biological resources.  Project does not address impacts in a regional context.  Project does not adequately address cumulative impacts to biological resources .  Mitigation for habitat impacts is insufficient . These inadequacies affect the findings presented in the RDEIR. In some cases, the proposed project may result in impacts not addressed in the RDEIR. In other cases, the RDEIR underestimates the proposed project’s impacts and/or additional surveys/analyses are required to support the findings presented in the document. Major areas of concern are addressed below. Inadequate Description of Existing Biological Resource Conditions Setting, p. 4.4-18. The RDEIR relies on outdated information to describe the existing setting on the project site. Specifically, the RDEIR states that since 2011 reconnaissance level surveys determined that site conditions were predominantly unchanged from previous analyses, the existing setting discussion is based largely on previous findings (Placeworks 2014). However, the RDEIR provides very little documentation to support this finding. Descriptions of plant communities are based on surveys conducted at least 10 years ago (Foothill Associates 2004), and updated species lists are not provided to demonstrate that species use of the site is unchanged over the last decade. The project setting discussion and vegetation mapping should reflect current (not past) conditions and analyses. Refer to the earlier letter from Shute, Mihaly and Weinberger (SMW 2013) regarding additional comments on the description of existing biological resource conditions that were not addressed in the RDEIR. Setting, Plant Communities, p. 4.4-19. Vegetation mapping is used to identify sensitive or unique vegetation communities, wildlife habitat, and site biodiversity and thus, is a critical component of biological analyses. At the site (or property) level, vegetation mapping is achieved through field mapping and use of a vegetation classification system t hat is appropriately detailed to achieve the mapping objectives. Mapping that uses an overly broad classification system that does not recognize all habitats onsite will underesti mate impacts to these habitats. Vegetation mapping used to characterize the Canyon Springs project site follows older classification systems (RDEIR, p. 4.4.-19) rather than the most recent (and detailed) system of classification and nomenclature presented in A Manual of California Vegetation (MCV) (Sawyer et al. 2009). The MCV is the standard reference for vegetation mapping in California. It has been adopted by state and federal agencies and conforms to the National Vegetation Classification System (Sawyer et al. 2009, FGDC 2008). The 2009 MCV is a complete revision of the 1995 version cited in the RDEIR (p. 4.4-19), and includes updated and original vegetation Conservation Biology Institute 3 November 18, 2014 descriptions based on additional sampling and analysis. This additional level of detail is important for identifying sensitive or unique vegetation communities (e.g., wetlands), wildlife habitat (e.g., mule deer habitat), and biodiversity. As an example, the RDEIR (p. 4.4-19) identifies a Jeffrey pine community, which likely corresponds to the MCV-identified Jeffrey pine alliance (Pinus jeffreyi Forest Alliance). Within this alliance, the MCV identifies 45 associations, including one association with mountain sagebrush (Artemisia tridentata ssp. vaseyana) as a co-dominant species and four associations with bitterbrush (Purshia tridentata) as a co-dominant species. Both mountain sagebrush and bitterbrush occur onsite, but information provided in the RDEIR is not sufficient to relate (or cross-walk) mapped vegetation to MCV association-level vegetation. In addition, the site- specific vegetation descriptions do not provide sufficient detail with regard to species composition and cover. Both ponderosa pine (Pinus ponderosa) and white fir (Abies concolor) were identified onsite in the wetland delineation (DEIR, Appendix D, Chapter 4, pg. 4-12) and earlier reports (e.g., Foothills Associates 2004), yet neither species is mentioned in the site- specific vegetation descriptions within the RDEIR. Co-dominance of either species with Jeffrey pine would result in mapping of additional vegetation types onsite, increased site biodiversity, and possibly, additional niche habitat for wildlife species. Failure to identify all vegetation associations onsite may result in underestimating impacts due to loss of habitat. The RDEIR (p. 4.4-20) identifies one sagebrush community dominated by mountain sagebrush , with bitterbrush, low sagebrush (Artemisia arbuscula), and rabbitbrush (Ericameria nauseosus) as associated species. Based on species composition, the mapped sagebrush community appears to correspond to one MCV vegetation alliance (Artemisia tridentata ssp. vaseyana shrubland alliance), but could fall into three to four different vegetation associations. Bitterbrush is considered a particularly important browse species for mule deer (DEIR, Appendix E, pg. 3.2), yet the RDEIR does not adequately describe how prevalent this shrub is onsite. Failure to identify habitat dominated or co-dominated by bitterbrush would result in underestimating impacts both to this vegetation type and to foraging habitat for mule deer. The vegetation map identifies some areas of low tree cover as sagebrush scrub and other areas with similar tree cover as Jeffrey pine forest. The RDEIR fails to explain the basis for these determinations. The document should include a description of mapping methodology, including (1) minimum mapping units for upland habitats, (2) degree of delineation from aerial imagery (if any) versus field-verification, (3) percent cover of tree species used to delineate forest versus shrub habitats, and (4) vegetation mapping date(s) (year/month). Failure to classify vegetation correctly could result in underestimating impacts to wildlife habitat. Meadow habitats (p. 4.4-23 – 4.4-24) should also be mapped according to MCV mapping standards. The RDEIR identified two meadow types: wet meadows and pebble meadows. The MCV (Sawyer et al. 2009) includes at least five different vegetation alliances that potentially Conservation Biology Institute 4 November 18, 2014 correspond to the wet meadow habitat onsite. Failure to identify all wet meadow vegetation types onsite could result in underestimating both impacts and appropriate mitigation. The description of pebble meadows in the RDEIR identifies biotic (vegetation) attributes of this habitat, but no abiotic attributes (e.g., soils, hydrology). The habitat description should include abiotic features that support this habitat and which may be adversely impacted by project implementation. Failure to include this information precludes a comprehensive analysis of project impacts and appropriate mitigation (e.g., buffers) for this habitat. Wetland Delineation. The wetland delineation (RDEIR, p. 4.4-35) identified 5.94 acres of wetlands onsite and indicated that t he wetland-upland boundary was ‘demarked by an abrupt shift in the plant community from those species that are hydrophytes to those t hat are associated with uplands.’ Based on a cursory review of recent (2010) aerial imagery of the site, there appears to be a shift between potential wetland and adjacent upland associations in Intermittent Drainage 1 (ID-1) (DEIR, Appendix D [HEC 2011b], Delineation map), as well as apparent wetland hydrology (channel). However, there is no indication that ID-1 was sampled for the presence of wetland vegetation during the wetland delineation. The westernmost portion of ID-1 (along with other drainages onsite) is designated by the U.S. Forest Service as a Sierra Nevada Riparian Conservation Area (USFS 2006). Riparian conservation areas are ‘land allocations that are managed to maintain or restore the structure and function of aquatic, riparian and meadow ecosystems. The intent of management direction for RCAs is to (1) preserve, enhance, and restore habitat for riparian - and aquatic-dependent species; (2) ensure that water quality is maintained or restored; (3) enhance habita t conservation for species associated with the transition zone between upslope and riparian areas; and (4) provide greater connectivity within the watershed’ (USFS 2006). Inclusion of ID-1 in a RCA further suggests that this area should be assessed for the presence of wetlands. At a minimum, the RDEIR should indicate why this area is not considered a wetland. The wetland delineation was conducted in late August and early September 2010 under conditions of very little recent rain, and direct observation of hydrology on the site was not possible because very little rain had recently occurred (DEIR, Appendix D, p. 4-13). If wetland hydrology and some wetland species (e.g., herbaceous plan ts) could not be identified during the survey period, the wetland delineation may have underestimated the wetland acreage onsite. As discussed earlier, the RDEIR (Section 4.4, Biological Resources, p. 4.4-18) indicates that site conditions in 2011 were ‘predominantly unchanged from the conditions reported in the previous analysis prepared for the project site,’ thus providing justification for including descriptions of vegetation derived largely from a 10-year old report (Foothill Associates 2004). However, the 2004 report identified several wetland species, including at least two obligate wetland species (Mimulus primuloides, Stachys ajugoides) and three facultative wetland species (Hypericum scouleri, Ranunculus occidentalis, Salix drummondii), not detected in the recent wetland Conservation Biology Institute 5 November 18, 2014 delineation (DEIR, Appendix D). This suggests that either site conditions have changed since earlier surveys or the recent wetland delineation was conducted at a time of year that was not optimal for detection of these wetland species. Failure to provide current descriptions of wetland habitats or conduct appropriately-timed wetland delineations could result in underestimating wetland impacts from the proposed project. The wetland delineation indicates that a number of plant species were difficult to identify due to the season (DEIR, Appendix D, p. 4-12), but fails to name which plants are in question. This is important because at least two wetland species are also potentially-occurring sensitive species onsite: Carex davyi and Juncus luciensis. If any Carex or Juncus were identified only to generic level during either the wetland delineation or rare plant surveys, then the potential exists for these sensitive taxa to occur onsite. This would warrant either additional surveys to verify identification or consideration of these species in the impact analysis. Special Status Wildlife, p.4.4-25 – 4.4-29 and Table 4.4-2. The RDEIR, DEIR, and appendices indicate that general wildlife surveys and focused deer surveys were conducted on the project site. It is not clear, however, whether focused surveys were conducted for potentially-occurring sensitive wildlife species other than mule deer. Where sensitive wildlife species have a potential for occurrence onsite, focused surveys should be conducted prior to project approval to determine use onsite, particularly if these species are expected to utilize habitat that will be directly or indirectly impacted by the proposed project. The project site is not an historic location for the federally endangered and state threatened Sierra Nevada yellow-legged frog, nor does the site occur within proposed Critical Habitat for this species. However, the applicant should survey specifically for Sierra Nevada yellow-legged frog in upstream reaches of drainages onsite at the appropriate time of year (May-June) to assess whether these areas provide habitat components necessary for the frog to complete its life history. The RDEIR (p. 4.4-23) indicates that the meadow systems onsite are generally dry by mid-summer except in upstream areas directly influenced by off -site perennial springs. While persistence of water is crucial to the survival and recruitment of this spec ies, active-season habitat (feeding, refuge) encompasses all types of aquatic habitats (Brown et al. 2014). Further, studies indicate that this species can move across the landscape, at least on a local level (Brown et al. 2014). Thus, there may be some potential for the species to use selected areas of the site as part of a larger home range. The RDEIR discussion of Special Status Wildlife should include black-backed woodpecker (p. 4.4-25). Although the CDFW recently determined that an endangered or threatened designation is not warranted for this species (CDFW 2013b; California Regulatory Notice Register 2013), t he U.S. Fish and Wildlife Service (USFWS) has ruled that they will review the status of this species when funding becomes available to determin e if listing is warranted (USFWS 2013). Because of the ongoing potential for this species to be listed at the federal level, it should be included for consideration under Special Status Wildlife. Conservation Biology Institute 6 November 18, 2014 The discussion of mule deer should be updated with the most recent data from CDFW (2014) regarding use of the project site by this species (p. 4.4-31). The RDEIR notes that ‘there is a high potential for mule deer to utilize the project site and surrounding area for foraging, movement, and migration.’ However, based on reports and CDFW data, deer are actively use the project site (DEIR, Appendix E [RMT, Inc. 2009, HEC 2011a], CDFW 2014). The RDEIR does not mention that fawns have been observed onsite on several occasi ons (DEIR, Appendix E), and considers the potential for onsite fawning habitat to be low based on distance to designated critical fawning habitat . The RDEIR should assess whether the presence of fawns onsite is due to suitable fawning habitat onsite or in proximity to the site, or a function of migration from critical fawning habitat. Special Status Plants, p. 4.4-32 and Table 4.4-2. The CDFW rare plant survey protocols (CDFG 2009) indicate that rare plant surveys should be floristic in nature, i.e., every ‘plant taxon onsite should be identified to the taxonomic level necessary to determine rarity and listing status .’ The RDEIR should include a list of plant species detected onsite during the most recent rare plant surveys to document that these survey objectives were met. The CDFW protocols specifically state that floristic inventories are necessary when prior inventories or special status plant surveys have been conducted but are not current. The RDEIR should indicate the suitability of the survey year(s) for detection of sensitive plant species. Climatic conditions (e.g., low rainfall) affect flowering for many plant species and thus, the ability to detect those species where flowers or seed are diagnostic characteristics . The RDEIR does not describe the climatic conditions during the survey period. Therefore, it is not possible to evaluate whether conditions were suitable for detecting the presence or flowering of sensitive plant species (particularly, herbaceous perennial species). If adverse conditions are present during the survey period (e.g., drought), negative survey results may not provide reliable evidence that the target species does not occur onsite (CDFG 2009). Jurisdictional Waters, p. 4.4-33, 4.4-35. The RDEIR indicates that wetlands and non -wetland waters would be subject to regulation by the Army Corp of Engineers and/or the Regional Water Quality Control Board under the Clean Water Act (sectio ns 404 and 401, respectively) and that these areas and associated riparian areas may be subject to regulation by the CDFW pursuant to Sections 1600-1616 of the California Code of Regulations (CCR). The RDEIR should include discussion of a Minor Use Permit (Truckee Municipal Code Chapter 18.30, General Property Development Standards, Section 18.30.050.F.3), which would be required for ‘projects resulting in the disturbance of land or located within 200 feet of any wetland area , unless the Director finds that the topographic conditions of the surrounding area will clearly preclude any disturbance of wetland areas and will ensure that any runoff from the project will not result in any water quality impacts to a wetland area.’ Conservation Biology Institute 7 November 18, 2014 The RDEIR’s Impact Analysis Underestimates Significant Impacts to Biological Resources Impacts to Sensitive Plant Communities and Federally Protected Wetlands, p. 4.4-38 – 4.4-42. The RDEIR states that all proposed building envelopes would be outside of the Town -required 50-foot setback from designated 100-year floodplains for the two blue line waterways (RDEIR, p. 4.4-38) and that ‘the project includes a 100-foot setback from private housing lots to the main drainage…with the exception of ten housing lots (122 to 131), which woul d have a minimum 50- foot setback from the building envelopes to Buck Spring’ (RDEIR, p. 4-4-38 and p. 4.4-41). The RDEIR concludes that the proposed setbacks and project design features would result in less than significant impacts to sensitive habitats f rom direct and indirect impacts and thus, no mitigation measures are required. It is important to note that the reduced setback (ten housing lots, 122 - 131) is adjacent to the most extensive wet meadow habitat onsite. Further, a review of edge effect literature indicated that buffer widths of 80 -100 feet were only moderately likely to be effective at reducing impacts from invasive plants, vegetation clearing, trampling, and increased water supply, whereas buffer widths of 200 feet or greater were highly likely to be effective at reducing these same impacts (CBI 2000). Thus, buffer widths of 50 feet adjacent to sensitive habitat are not likely to reduce indirect impacts to a level of less than significant. Indirect impacts are discussed in additional detail below. The RDEIR (p. 4.4-42) indicates that the proposed project could indirectly impact sensitive plant communities (wet meadow, pebble meadow) and federally protected wetlands through modification of the hydrology that supports these areas. The RDEIR further concludes that project design features that will limit runoff from impervious surfaces will result in less than significant impacts to these habitats and, thus, no mitigation will be required. However, there is no quantification of expected runoff or runoff capture to support this statement. The RDEIR does not consider indirect impacts to habitat areas resulting from the project such as proliferation of invasive species, trampling (the larger pebble meadow is located 50 feet from a building envelope, road, and trail), or loss or reduction of pollinators within the larger pebble meadow due to fragmentation, which may affect long-term function and viability of this habitat. The RDEIR states that project design features would minimize edge effects such as habitat fragmentation (p. 4.4-47), but it is not clear how these design features offset invasive species or fragmentation-related impacts. As discussed above, the 50-foot setback from the pebble meadow is not sufficient to reduce indirect impacts to this habitat to a level of less than significant . The RDEIR analysis ignores the importance of the project site in the context of the hydrologica l sub-basin. For example, meadows reduce peak water flow after storms and during runoff, recharge groundwater supplies, provide wildlife habitat, filter sediments, and help provide clean water (Weixelman et al. 2011). The RDEIR (p. 4.4-35) indicates that non-wetland waters ‘convey mostly surface runoff and snow melt, but also include some groundwater recharge.’ The impact analysis must consider the effects of the proposed project on the filtering and Conservation Biology Institute 8 November 18, 2014 groundwater recharge functions of wetlands onsite, as well as impacts to the long-term viability of wetlands onsite from groundwater drawdown associated with project implementation. Impacts to Potentially Occurring Sensitive Wildlife Species . The impact analysis does not consider loss of snag or forest habitat for the black-backed woodpecker, which is a potentially occurring species onsite and under review by the USFWS for federal listing. In addition, black- backed woodpecker is considered a management indicator species for snags within burned forests by the U.S. Forest Service (USFS 2008). Direct Loss of Habitat for Movement, Foraging, and Migration . Loss of snags and Jeffrey pine and sagebrush scrub onsite are considered significant impacts (RDEIR, p. 4.4 -43); however, no mitigation is provided for loss of these habitats. Some restoration is proposed to replace native perennial grasses and bitterbrush; however, the extent of this effort (acres) is not specified. Open Space Configuration. The RDEIR indicates that 176.17 acres of habitat would be preserved as public open space and would serve as a wildlife habitat and movement corridor. While the open space configuration captures the maj ority of the wetlands and ‘other waters of the U.S.,’ it is distributed throughout the development and is bisected by roads in several locations; thus, it is inconsistent with the Truckee General Plan Policy (COS-P1.1) and with general conservation principles of preserving open space that is in large blocks, contiguous, and connected (RDEIR, Table 4.4-1, p. 4.4-6). Nor will the open space serve as an effective movement corridor for some species, including mule deer . The RDEIR (p. 4.4-44) acknowledges the project will result in potentially significant im pacts to the Loyalton-Truckee mule deer herd, but considers public open space and project design features sufficient to mitigate impacts to less than significant (p. 4.4.-45, 4.4-47). However, the open space design is not conducive to continued mule deer use, as discussed below, and proposed mitigation measures will not sufficiently offset habitat losses for this species. Mule deer movement and migration have been documented through the northern and southeastern portions of the project site (CDFW 2014); however, building envelopes extend into both areas. In the southeast corner of the project site, individual lot lines occur within 400 feet of the property boundary. The CDFW (Bentrup 2008 in CDFW 2013a) noted that edge effects may influence mammal behavior and reproductive success an average of 300 feet from altered habitat; thus, the proposed project would severely restrict mule deer migration through the project site. In addition, mule deer migration through the project site generally occurs in a northeast to southwest direction, while much of the designated open space is oriented in the opposite direction, situated between clustered housing, and bisected by roads, trails, and bridges. These open space features will inhibit use of the open space by mule deer. Because mule deer show high site fidelity (CDFW 2013a), project development that impacts known mule deer migration and foraging habitat will result in significant impacts. Conservation Biology Institute 9 November 18, 2014 As mentioned above, the presence of roads within open space diminishes the value of that open space as wildlife habitat. In addition to fragmenting habitat and increasing wildlife mortality (Beier et al. 2008), roads increase the spread of invasive plants, while roadway chemi cals contribute to wetland pollution (Forman et al. 2003). The RDEIR should include an assessment of all indirect impacts and provide mitigation for significant impacts. It is unclear whether roads within the open space (including rights-of-way and additional easements) or fuel management zones are included in the total open space acreage. The RDEIR should clarify permitted activities within open space and adjust open space acrea ge (if necessary) to reflect the area that will remain undisturbed and/or restored to a natural state. It is also unclear whether other infrastructure (sewer main, drainage ditch) will occur within the open space (DEIR, Figure 3-11A) versus existing roadway rights-of-way and public utilities easements (DEIR, p. 3-29), and whether infrastructure footprints (e.g., retention ponds) within open space are counted in the total open space acreage. The RDEIR should clarify direct and indirect impacts within open space from infrastructure install ation, and indicate whether impacts will be temporary (e.g., installation only) or long-term (clearing, utility maintenance). In addition, the RDEIR should indicate how direct and indirect impacts will be mitigated. Loss of Loyalton-Truckee Deer Herd Habitat for Movement, Foraging, and Migration. The RDEIR indicates that project design features (including open space, see above) would result in less than significant impacts from both direct and indirect impacts to wildlife species, including mule deer, and concludes that no mitigation is required for habitat losses. Contrary to the RDEIR’s conclusion, the CDFW indicates that development in both Nevada and the Truckee, California area is a concern for the Loyalton-Truckee deer herd (Sommer 2010). Mule deer use of much of the Canyon Springs site has been documented by the CDFW and others (CDFW 2014; CDFW 2013a; DEIR, Appendix E), and loss of this site for individuals that show high site fidelity will result in impacts to a deer herd that is already a source of concern due to habitat loss in the region. In addition, the project may further impact mule deer or mule deer habitat through increased mortality along roads and project-associated increases in noise, lighting, dust, water pollution, invasive species, fire frequency, and recreational activities. While some of these impacts are addressed in project design features (p. 4.4 -46), others have not been considered sufficiently or at all; thus, the impact analysis is incomplete and mitigation is inadequate. Relationship to Other Conserved Lands. The RDEIR does not consider the value of the project site in a regional context, particularly its role in connecting conserved lands to the northeast and the southwest in support of the overall conservation vision for the region. The property is located between the state-owned Truckee River Wildlife Area, which lies 0.6 mile to the northeast, and the Martis Valley Conservation Area, which lies 0.5 -0.75 mile to the southwest. Two units of the Truckee River Wildlife Area, including the unit closest to the proj ect site (Union Ice Unit), are important for deer. Recent collaring data show the Union Ice Unit to be a summer concentration and fawning area for the Verdi sub -herd of the Loyalton-Truckee deer Conservation Biology Institute 10 November 18, 2014 herd (Sommer 2010), and fawning grounds also occur in the Ma rtis Valley. A map depicting the project site in relation to the Martis Valley Priority Conservation Area and other conserved lands in the region is included with this letter. This map supplements Figure 4.3-2 (Public and Permanently Protected Open Space) of the Town of Truckee’s 2025 General Plan EIR , which also depicts conserved lands in the region. The impact analysis should assess the effects of the proposed project on landscape-level conservation values and connectivity. Development that impedes or blocks deer movement along migration corridors linking winter range and fawning habitats would affect the long-term viability of the herd and constitute a significant impact. The project site is included in or adjacent to high priority lands targeted for acquisition in the Sierra Valley Conceptual Area Protection Plan (CAPP) Amendment (CDFW 2012). This amendment, referred to as the Sierra Valley-Truckee Basin CAPP, would expand the original Sierra Valley CAPP. The purpose of land acquisition in the amended CAPP is to consolidate conservation efforts within the Sierra -Cascade region and expand protection for the Loyalton- Truckee deer herd (CDFW 2012). While the objectives of the original Sierra Valley CAPP were to protect wetland, wet meadow, riparian, bitterbrush and sagebrush habitats for the Loyalton - Truckee deer herd and other wildlife species, the amended CAPP would additionally include important migratory corridors, critical fawning habitat and winter range (CDFW 2012). Land ownership within the amended CAPP is variable, but much of the land scape is owned by the U.S. Forest Service or private timberlands. Portions of the project site (Assessor Parcel Numbers 49-020-17, 49-020-18, and 49-020-19) have been designated high priorities for acquisition under the Sierra Valley-Truckee Basin CAPP, along with adjacent lands to the east (CDFW 2012). These designations reinforce the value of these areas to the Loyalton -Truckee deer herd. Cumulative Impacts. The proposed project will result in loss of mule deer habitat and impacts to a deer migration corridor. The CDFW indicates that ‘the quality of much of the mule deer habitat (in the region) is degraded to the point where all summer range is important and can be considered essential to this deer herd’ (Sommer 2010). The loss of habitat on the project site constitutes a significant, cumulative impact that requires mitigation to offset these losses. The proposed project may result in significant, cumulative impacts to other wildlife species, such as black-backed woodpecker or Sierra Nevada yellow-legged frog. However, the RDEIR does not assess potential impacts for these species. The RDEIR does not consider the effects of climate change on deer migration , migration routes, or deer habitat. Deer migration is influenced by climate and plant phenology (Monteith et al. 2011), and predicted warmer temperatures and reduced snow depth (Kershner 2014) may result in deer staying on summer grounds longer. While mule deer may adjust to these changes, shifts in migration patterns will increase pressure on summer ranges. Thus, summer range habitat may take on additional importance to support viable deer populations. The RDEIR should address the cumulative impact of the loss of foraging and migration habitat on future deer population viability under changing conditions, and provide mitigation to offset significant impacts. Conservation Biology Institute 11 November 18, 2014 Climate change scenarios also predict that fire seasons will be increasingly longer and hotter, and characterized by larger and more frequent fires than in the past (Westerling 2006). Altered fire regimes may be further exacerbated by invasive species and an increase in anthropogenic fire ignitions due to increasing human populations near wildland areas (Pauseas and Keeley 2014). Altered fire regimes may result in habitat type conversions, with shrub habitats replaced by invasive species such as cheatgrass (Bromus tectorum). Cheatgrass has been documented on the Canyon Springs site. (DEIR, Appendix D). As discussed earlier, development of roadways and other project elements will increase the spread of invasive plants, including cheatgrass. Cheatgrass contributes to increased fire frequency in sagebrush communities (Baker 2006), and already has altered the fire season in some areas of the eastern Sierra Nevada (Slaton and Stone 2013). Conversion of scrub habitats to cheatgrass-dominated grasslands would reduce cover and browse opportunities for mule deer. The RDEIR fails to assess the potential for the project site to contribute cumulatively to impacts to deer habitat in the region from increased fire ignitions and invasive species. Alternatives Analysis. The analysis of alternatives is based on findings from the impact analyses, which are incomplete. Nonetheless, alternatives (including the no project alternative) that reduce the development footprint, increase setbacks to sensitive habitat (wetlands, meadows, deer migration routes), increase open space in t he southeast portion of the site, and decrease direct and indirect impacts in open space areas are preferable to the current project design. Conclusion The description of biological resources onsite is outdated, while methods and survey results are not sufficiently detailed to determine the adequacy of biological surveys. Further, the RDEIR does not consider or adequately address all direct, indirect, or cumulative impacts to biological resources that may occur from project implementation. As a result, proposed mitigation measures are incomplete and inadequate to compensate for project impacts. It is CBI’s recommendation that these deficiencies are addressed prior to certifying the document. Sincerely, Patricia Gordon-Reedy Vegetation Ecologist/Conservation Biologist Map: Conserved Lands in the Vicinity of the Canyon Springs Project Site, including the Martis Valley Priority Conservation Area (Priority Conservation Area) Conservation Biology Institute 12 November 18, 2014 Conserved Lands in the Vicinity of the Canyon Springs Project Site, including the Martis Valley Priority Conservation Area (Priority Conservation Area) Conservation Biology Institute 13 November 18, 2014 References Baker, W.L. 2006. Fire and restoration of sagebrush ecosystems. Wildlife Society Bulletin 34(1):177-185. Beier, P., D. Majka, S. Newell, and E. Garding. 2008. Best management practices for wildlife corridors. Northern Arizona University. 14 pp. Bentrup, G. 2008. Conservation buffers: design guidelines for buffers, corridors, and greenways. Gen. Tech. Rep. SRS-109. Asheville, NC: USDA, Forest Service, Southern Research Station. http://nac.unl.edu/bufferguidelines/guidelines/2_bodiversity/10.html . In California Department of Fish and Wildlife (CDFW). 2013a. Com ment letter, DEIR for the Canyon Springs subdivision (SCH# 2004052060), County of Nevada, CA. March 1. Brown, C., M.P. Hayes, G.A. Green, and D.C. Macfarlane, technical coordinators. 2014. Mountain yellow-legged frog conservation assessment for the Sierra Nevada Mountains of California, USA. A collaborative inter-Agency project by USDA Forest Service, California Department of Fish and Wildlife, National Park Service, and U.S. Fish and Wildlife Service. R5-TP-038. July. California Department of Fish and Game (CDFG). 2009. Protocols for surveying and evaluating impacts to special status native plant populations and natural communities. State of California, Natural Resources Agency. November 24. https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=18959&inline=1 California Department of Fish and Wildlife (CDFW). 2012. Land acquisition proposal: Sierra Valley-Truckee Basin Conceptual Area Protection Plan (CAPP) expansion. August 24. California Department of Fish and Wildlife (CDFW). 2013a. Comment letter, DEIR for the Canyon Springs subdivision (SCH# 2004052060), County of Nevada, CA. March 1. California Department of Fish and Wildlife (CDFW). 2013 b. Memorandum: black-backed woodpecker; proposed California Fish and Game Commission findings of fact (Fish and Game Code, 2075.5(1).). October 17. California Department of Fish and Wildlife (CDFW). 2014. GIS mule deer shapefile data in relation to Canyon Springs development (combined shapefile). California Regulatory Notice Register. 2013. Fish and Game Commission, notice of findings, black-backed woodpecker (Picoides arcticus). 47-Z:1837-1846. http://www.oal.ca.gov/res/docs/pdf/notice/47z -2013.pdf#page=45 Conservation Biology Institute (CBI). 2000. Review of potential edge effects on the San Fernando Valley spineflower (Chorizanthe parryi var. fernandina). Prepared for Ahmanson Land Company and Beveridge and Diamond, LLP. March 21. Conservation Biology Institute 14 November 18, 2014 Federal Geographic Data Committee (FGDC). 2008. National vegetation classification standard, version 2. FGDC -STD-005-2008. Federal Geographic Data Committee, FGDC Secretariat, U.S. Geological Survey, Reston, VA. Foothill Associates. 2004. Biological resource analysis for the Tahoe Boca Estates project site. Prepared for Quad Knopf. August 6. Forman, R.T.T., D. Sperling, J.A. Bissonette, A.P. Cleve nger, C.D. Cutshall, V.H. Hale, L. Fahrig, R. France, C.R. Goldman, K. Heanue, J.A. Jones, F.J. Swanson, T. Turrentine, and T.C. Winter. 2003. Road ecology: science and solutions. Island Press, Washington, DC. Heal Environmental Consulting (HEC). 2011a. CEQA significance of mule deer at the Canyon springs site, Truckee, California. Prepared for Canyon Springs Joint Venture. July 28. Heal Environmental Consulting (HEC). 2011b. Final delineation of waters of the U.S. Canyon Springs, Town of Truckee, #200300655. Prepared for Canyon Springs Joint Venture. October 17. Kahre, K.S., and G.S. Fowler. 1982. Loyalton-Truckee deer herd management plan. California Department of Fish and Game in cooperation with the Tahoe National Forest, Plumas National Forest, Toiyabe National Forest, U.S. Forest Service Lake Tahoe Basin Management Unit, Nevada Department of Wildlife, and U.S. Bureau of La nd Management, Carson City District. 83 pp. Kershner, J.M., editor. 2014. A climate change vulnerability assessment for focal resources of the Sierra Nevada. Version1.0. EcoAdapt, Bainbridge Island,WA. Monteith, K.L., V.C. Bleich, T.R. Stephenson, B.M. Pierce, M.M. Conner, R.W. Klaver, and R.T. Bowyer. 2011. Timing of seasonal migration in mule deer: effects of climate, plant phenology, and life-history characteristics. Ecosphere 2(4):1-34. Article 47. Pausas, J.G., and J.E. Keeley. 2014. Abrupt climate-independent fire regime changes. Ecosystems DOI: 10.1007/s10021 -014-9773-5. Placeworks. 2004. Canyon Springs revised draft EIR. Prepared for Town of Truckee. September 29. RMT, Inc. 2009. Movement and migration of mule deer at the Canyon Springs site, Truckee, California. October 20. Sawyer, J.O., T. Keeler-Wolf, and J.M. Evens. 2009. A manual of California vegetation, second edition. California Native Plant Society in collaboration with California Department of Fish and Game. California Native Plant Society Press, Sacramento, CA. 1300 pp. Shute, Mihaly and Weinberger LLP. 2013. Comment letter: Canyon Springs project draft environmental impact report. Prepared by Ellison Folk and Carmen Borg on behalf of Mountain Area Preservation Foundation ("MAPF") and Saving Open Space around Glenshire ("SOSG"). March 5. Conservation Biology Institute 15 November 18, 2014 Slaton, M.R., and H.E. Stone. 2013. Natural range of variation (NRV) for pinyon -juniper in the bioregional assessment area, including the Sierra Nevada, southern Cascades, and Modoc and Inyo National Forests. U.S. Department of Agriculture, Forest Service, Pacific Southwest region, Vallejo, CA. Sommer, M. 2010. Interstate deer project. Loyalton -Truckee deer herd report and management plan update. Habitat sections only. In partial fulfillment of PR Grant W-83-R-1. California Department of Fish and Wildlife. U.S. Fish and Wildlife Service (USFWS). 2013. Endangered and threatened wildlife and plants; 90-day finding on a petition to list two populations of black -backed woodpecker as endangered or threatened. Federal Register 78(68):21086 -21097. U.S. Forest Service (USFS). 2006. Sierra Nevada riparian conservation areas. U.S. Department of Agriculture, Forest Service, Pacific Southwest Region, Remote Sensing Lab. http://www.fs.fed.us/r5/rsl/projects/frdb/layers/rcas.html U.S. Forest Service (USFS). 2008. Sierra Nevada Forests bioregional management indicator species (MIS) report: life history and analysis of management indicator species of the 10 Sierra Nevada National Forests: Eldorado, Inyo, Lassen, Modoc, Plumas, Sequoia, Sierra, Stanislaus, and Tahoe National Forests and the Lake Tahoe Basin Management Unit. Pacific Southwest Region, Va llejo, CA. January. Weixelman, D.A., B. Hill, D.J. Cooper, E.L. Berlow, J.H. Viers, S.E. Purdy, A.G. Merrill, and S.E. Gross. 2011. A field key to meadow hydrogeomorphic types for the Sierra Nevada and southern Cascade Ranges in California. U.S. Depart ment of Agriculture, Forest Service, Pacific Southwest Region, Vallejo, CA. General technical report R5 -TP-034. 34 pp. Westerling, A.L., H.G. Hidalgo, D.R. Cayan, and T.W. Swetnam. 2006. Increases in western U.S. forest wildfire associated with warming and advances in the timing of spring. Science 313:940–943.