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# Policy Assessment for the Review of the 7 

# Secondary National Ambient Air Quality 8 

# Standards for NO x 

# and SO x 9

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# First External Review Draft 12

13EPA-452/P-10-006 1 March 2010 2 3 4 5 6 7 

## Policy Assessment for the Review of the 8 

## Secondary National Ambient Air Quality Standards 9 

## for NO x 

## and SO x 

## : 10
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## First External Review Draft 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 U.S. Environmental Protection Agency 37 Office of Air and Radiation 38 Office of Air Quality Planning and Standards 39 Health and Environmental Impacts Division 40 Research Triangle Park, North Carolina 27711 41 42 43 44DISCLAIMER 1 2 3 This document has been reviewed by the Office of Air Quality Planning and Standards, 4 U.S. Environmental Protection Agency (EPA ), and approved for publication. This draft 5 document has been prepared by staff from the Office of Air Quality Planning and Standards, 6 U.S. Environmental Protection Agency. Any opinions, findings, conclusions, or 7
recommendations are those of the authors and do not necessarily reflect the views of the EPA. 8 Mention of trade names or commercial products is not intended to constitute endorsement or 9 recommendation for use. This document is being provided to the Clean Ai r Scientific Advisory 10 Committee for their review, and made available to the public for commen t. Any questions or 11 comments concerning this document should be addressed to Dr. Bryan Hubbell, U.S. 12 Environmental Protection Agency, Office of Air Quality Planning and Standards, C504-02, 13 Research Triangle Park, North Caro lina 27711 (email: hubbell.bryan@epa.gov ). 14
15March 2010 i Draft – Do Not Quote or Cite 

### TABLE OF CONTENTS 1
List of Figures ............................................................................................................... ................. iv 2 List of Tables ................................................................................................................ ................ vii 3 List of Acronyms and Abbreviations ............................................................................................ . ix 4 List of Key Terms ............................................................................................................. ............ xii 5 1. Introduction .................................................................................................................. ............. 1 6 1.1 Definitions of NO x and SO x for this Assessment ............................................................. 3 7 1.2 Policy Objectives ............................................................................................................. 4 8 1.3 Critical Policy Elements .................................................................................................. 6 9 1.4 Historical Context ............................................................................................................ 8 10 1.4.1 History of NO x and SO x NAAQS Review ........................................................... 8 11 1.4.2 History of Related Assessments and Agency Actions ....................................... 10 12 1.5 Proposed Conceptual Framework for Combined NO x SO x Standards .......................... 13 13 1.6 Policy Relevant Questions ............................................................................................. 16 14
2. Known or anticipated ecological effects ................................................................................. 22 15 2.1 Acidification: Evidence of effects on st ructure and function of terrestrial and 16 freshwater ecosystems ................................................................................................... 23 17 2.1.1 What is the nature of acidificat ion related ecosystem responses to 18 reactive nitrogen and/ su lfur deposition? ........................................................... 24 19 2.1.2 What types of ecosystems are sensitive to such effects? In which ways 20 are these responses affected by at mospheric, ecological, and landscape 21 factors? ............................................................................................................... 26 22 2.1.3 What is the magnitude of ecosystem re sponses to acidifying deposition? ........ 26 23 2.1.4 What are the key uncertainties a ssociated with acidification? ........................... 35 24 2.2 Nitrogen enrichment: Evidence of effects on structure and function of terrestrial 25 and freshwater ecosystems ............................................................................................. 37 26 2.2.1 What is the nature of terrestrial a nd freshwater ecosystem responses to 27 reactive nitrogen and/ su lfur deposition? ........................................................... 37 28 2.2.2 What types of ecosystems are sensitiv e to such effects? How are these 29 responses affected by atmospheric, ecological, and landscape factors .............. 39 30 2.2.3 What is the magnitude of ecosystem responses to nitrogen deposition? ........... 40 31 2.2.4 What are the key uncertainties associ ated with nutrient enrichment? ............... 48 32 2.3 What Ecological effects are a ssociated with gas-phase NO x and SO x ? ......................... 49 33 2.3.1 What is the nature of ecosystem responses to gas-phase nitrogen and 34 sulfur? ................................................................................................................ 50 35 2.3.2 What types of ecosystems are sensitiv e to such effects? How are these 36 responses affected by atmospheric, ec ological, and landscape factors? ............ 50 37 2.3.3 What is the magnitude of ecosystem responses to gas phase effects of 38 NO x and SO x ? .................................................................................................... 51 39 2.4 Summary ....................................................................................................................... . 51 40 2.5 References .................................................................................................................... .. 52 41March 2010 ii Draft – Do No Quote or Cite 3. Considerations of Adversity to Public Welfare ...................................................................... 62 1 3.1 How do we characterize adversity to pub lic welfare? What are the relevant 2 factors and how are they addr essed in this document? .................................................. 62 3 3.1.1 What are the benchmarks for adversity from other sources? ............................. 62 4 3.1.2 Other EPA Programs and Federal Agencies ...................................................... 65 5 3.2 What are ecosystem services and how does this concept relate to public 6 welfare? ...................................................................................................................... .... 69 7 3.3 What is the role of economics? ...................................................................................... 75 8 3.4 What is the evidence for effects on ecosystem services? How do we link 9 ecological indicators to services? .................................................................................. 78 10 3.5 References .................................................................................................................... .. 89 11
4 Addressing the Adequacy of the Current Standards ............................................................. 101 12 4.1 Are the structures of the current NO x and SO x secondary standards based on 13 relevant ecological indicators such that they are adequate to determine and 14 protect public welfare against a dverse effects on ecosystems? ................................... 101 15 4.2 To what extent are the structures of the current NO x and SO x secondary 16 standards meaningfully related to rele vant ecological indicators of public 17 welfare effects? ............................................................................................................ 1 03 18 4.3 To what extent do current monitoring networks provide a sufficient basis for 19 determining the adequacy of current secondary NO x and SO x standards? .................. 106 20 4.3.1 What does the NADP monitoring netw ork provide and what are the 21 major limitations? ............................................................................................ 111 22 4.3.2 How do we characterize deposition through Monitoring and Models? ........... 112 23 4.4 What is our best charac terization of atmospheri c concentrations of NO y and 24 SO x , and deposition of N and S?.................................................................................. 114 25 4.4.1 What are the current atmospheric concentrations of reactive nitrogen, 26 NO y , reduced nitrogen, NH x , sulfur dioxide, SO 2 , and sulfate, SO 4 ? .............. 115 27 4.5 Are adverse effects on the public welfar e occurring under current air quality 28 conditions for NO 2 and So 2 and would they occur if the nation met the current 29 secondary standards? ................................................................................................... 130 30 4.5.1 To what extent do the current NO x and SO x secondary standards provide 31 protection from adverse effects a ssociated with deposition of 32 atmospheric NO x , and SO x which results in acidification in sensitive 33 aquatic and terrestrial ecosystems? .................................................................. 133 34 4.5.2 To what extent does the current NO x secondary standard provide 35 protection from adverse effects a ssociated with deposition of 36 atmospheric NO x , which results in nutrient enrichment effects in 37 sensitive aquatic and terrestrial ecosystems? ................................................... 138 38 4.5.3 Aquatic Nutrient Enrichment ........................................................................... 139 39 4.5.4 Terrestrial Nutrient Enrichment ....................................................................... 141 40 4.6 To what extent do the current NO x and/or SO x secondary stan dards provide 41 protection from other ecological effects (e.g., mercury methylation) associated 42 with the deposition of atmospheric NO x , and/or SO x ? ................................................ 142 43 4.7 References .................................................................................................................... 143 44
5. Conceptual Design of an Ecologically Re levant Multi-pollutant Standard .......................... 145 45 5.1 Components of the design ............................................................................................ 145 46March 2010 iii Draft – Do No Quote or Cite 5.1.1 For which effects is there suffici ent information to support setting 1 standards?......................................................................................................... 146 2 5.2 Ecological Components of the Stan dard: Aquatic Acidification ................................. 147 3 5.2.1 Conceptual design considerations from the ISA and REA .............................. 149 4 5.2.2 Design options for aquatic acidification .......................................................... 157 5 5.3 Ecological Components of the Standard: Terrestrial Acidific ation, Terrestrial 6 Nutrient Enrichment and Surface water Nutrient Enrichment ..................................... 167 7 5.3.1 Terrestrial Acidification ................................................................................... 167 8 5.3.2 Terrestrial and surface water nutrient enrichment ........................................... 168 9 5.3.3 Summary .......................................................................................................... 169 10 5.4 Linking Deposition to Atmospheric Concentration ..................................................... 169 11 5.4.1 Background ...................................................................................................... 169 12 5.4.2 Aggregation Issues ........................................................................................... 170 13 5.4.3 Air Quality Simulation Models ........................................................................ 171 14 5.4.4 Oxidized Sulfur and Nitr ogen Pollutant Species ............................................. 172 15 5.4.5 Example Calculations ...................................................................................... 173 16 5.5 Example calculation for the conceptual design and derivation of AAPI ..................... 177 17 5.5.1 Example calculation for the conceptual design ............................................... 177 18 5.5.2 Derivation of the Atmospheric Acidif ication Potential Index (AAPI): ........... 185 19 5.6 References .................................................................................................................... 188 20
6. Options for Elements of the Standard ................................................................................... 190 21 6.1 What atmospheric indicators of oxidized nitrogen and sulfur are appropriate for 22 use in a secondary NAAQS that provid es protection for public welfare from 23 exposure related to deposition of N and S? What averaging times and statistics 24 for such indicators are appr opriate to consider? .......................................................... 191 25 6.2 What is the appropriate averaging ti me for the air quality indicators NO y and 26 SO x to provide protection of public we lfare from adverse effects from 27 acidification? ................................................................................................................ 193 28 6.3 What form(s) of the standard are most appropriate to pr ovide protection of 29 sensitive ecosystems from the effects of acidifying deposition related to ambient 30 NO x and SO x concentrations? ...................................................................................... 194 31 6.4 What are the appropriate spatial extent s of the boundaries for evaluating AAPI? 32 Within those boundaries, what are the appropr iate statistics to use in calculating 33 the parameters of the AAPI, e.g. G, V NOy , V S , and NH x ? Within those 34 boundaries, what s the appropriate spatial averaging for the air quality indicators 35 NO y and SO x to provide protection of public we lfare from adverse effects from 36 acidification? ................................................................................................................ 203 37 6.5 What are the options for specifying the targets for the ecological indicator for 38 aquatic acidification? ................................................................................................... 203 39 6.5.1 What levels of impairment are relate d to alternative levels of ANC? ............. 204 40 6.6 What are the appropriate ambient air monitoring methods to consider in 41 developing the standards? ............................................................................................ 208 42 6.6.1 What measurements would be used to characterize NO y and SO x 43 ambient air concentrations for the purposes of the AAPI based standard? ..... 208 44 6.6.2 What sampling frequency would be required? ................................................ 208 45March 2010 iv Draft – Do No Quote or Cite 6.6.3 What are the spatial scale issues associated with monitoring for 1 compliance, and how should these be addressed? ........................................... 209 2 6.7 Taking into consideration information about ecosystem services and other 3 factors related to characterizing adve rsity for the ecological effects being 4 assessed in this review, what is an appr opriate range of alternative standards for 5 the Agency to consider? ............................................................................................... 210 6
7. Co-protection for Other Effects Using Standa rds to Protect Against Acidification ............. 213 7 7.1 To what extent would a standard specifi cally defined to protect against aquatic 8 acidification likely provide protection from terrestrial acidification? ......................... 213 9 7.2 To what extent would a standard specifi cally defined to protect against aquatic 10 acidification likely provide protection from terrestrial nutrient enrichment? .............. 214 11 7.3 To what extent would a standard specifi cally defined to protect against aquatic 12 acidification likely provide protection from aquatic nutrient enrichment? ................. 215 13
8. Consideration of Issues Regarding Redu ced and Oxidized Forms of Nitrogen ................... 216 14 9.1 Conclusions .................................................................................................................. 219 15 9.2 Summary of key uncertainties and resear ch recommendations related to setting 16 a secondary standard for NO x and SO x ........................................................................ 223 17 9.2.1 Research Needs to Reduce Uncertainty in the Next Review (focused on 18 aquatic acidification) ........................................................................................ 223 19 9.2.2 Data Needs to Reduce Uncertainty in the Next Review (focused on 20 aquatic acidification) ........................................................................................ 223 21 22


### LIST OF FIGURES 23 Figure 1-1. Framework of an alte rnative secondary standard. ...................................................... 16 24 Figure 2-1. Ecological Effects A ssociated with Alternative Le vels of Acid Neutralizing 25 Capacity (ANC) .................................................................................................. 28 26 Figure 2-2. Average NO 3 - concentrations (orange), SO 4 2- concentrations (red), and ANC 27 (blue) across the 44 lakes in the Adirondack Case Study Area modeled 28 using MAGIC for the period 1850 to 2050. ....................................................... 29 29 Figure 2-3. ANC concentrations of preacidif ication (1860) and current (2006) conditions 30 based on hindcasts of 44 lakes in the Adirondack Case Study Area 31 modeled using MAGIC. [Note: in this map, the symbol for red is 32 reversed and should be < 0. The figure will be revised in the next draft.] ......... 30 33 Figure 2-4. Critical loads of acidifying depos ition that each surface water location can 34 receive in the Adirondack Case Study Area while maintaining or 35 exceeding an ANC concentration of 50 μ eq/L based on 2002 data. 36 Watersheds with critical load values <100 meq/m 2 /yr (red and orange 37 circles) are most sensitive to su rface water acidification, whereas 38 watersheds with values >100 meq/m 2 /yr (yellow and green circles) are 39 the least sensitive sites. ....................................................................................... 31 40 Figure 2-5. Average NO 3 - concentrations orange), SO 4 2- concentrations (red), and ANC 41 (blue) levels for the 60 streams in the Shenandoah Case Study Area 42 modeled using MAGIC for the period 1850 to 2050. ........................................ 32 43March 2010 v Draft – Do No Quote or Cite Figure 2-6. ANC levels of 1860 (preacidifica tion) and 2006 (current) conditions based on 1 hindcasts of 60 streams in the Shenandoah Case Study Area modeled 2 using MAGIC. .................................................................................................... 33 3 Figure 2-7. Critical loads of surface water acidity for an ANC of 50 μ eq/L for 4 Shenandoah Case Study Area streams. Each dot represents an estimated 5 amount of acidifying deposition (i.e., critical load) that each stream’s 6 watershed can receive and still maintain a surface water ANC >50 μ eq/L. 7 Watersheds with critical load values <100 meq/m 2 /yr (red and orange 8 circles) are most sensitive to su rface water acidification, whereas 9 watersheds with values >100 meq/m 2 /yr (yellow and green circles) are 10 the least sensitive sites. ....................................................................................... 34 11 Figure 2-8. Benchmarks of atmospheric ni trogen deposition for several ecosystem 12 indicators with the inclusion of the diatom changes in the Rocky 13 Mountain lakes (REA 5.3.1.2) ............................................................................ 42 14 Figure 2-9 (from REA figure 5.3-9). Observed effects from ambient and experimental 15 atmospheric nitrogen deposition load s in relation to using CMAQ 2002 16 modeling results and NADP monitoring data. Citations for effect results 17 are from the ISA, Table 4.4 (U.S. EPA, 2008). .................................................. 43 18 Figure 3-1. Common anthropogenic stressors and the essential ecological attributes they 19 affect. Modified from Young and Sanzone (2002) ............................................ 64 20 Figure 3-2. Representation of the benefits assessment process indicating where some 21 ecological benefits may remain unrecognized, unquantified, or 22 unmonetized. (Source: EBASP USEPA 2006). ................................................. 71 23 Figure 3-3. Conceptual model showing the relationships among ambient air quality 24 indicators and exposure pathways and the resulting impacts on 25 ecosystems, ecological responses, eff ects and benefits to characterize 26 known or anticipated adverse effects to public welfare. [This figure to be 27 revised for Second Draft Policy Assessment Document] ................................... 73 28 Figure 3-4. Locations of Eastern U.S. Nationa l Parks (Class I areas) relative to deposition 29 of Nitrogen and Sulfur in sensitive aquatic areas ............................................... 74 30 Figure 3-5. Location of Western U.S. National Parks (Class I areas) relative to deposition 31 of Nitrogen and Sulfur ........................................................................................ 75 32 Figure 3-6. Conceptual model linking ecological indicator (ANC) to affected ecosystem 33 services. .............................................................................................................. 79 34 Figure 4-1. Routinely operating surface m onitoring stations measuring forms of 35 atmospheric nitrogen. ....................................................................................... 107 36 Figure 4-2. Routinely operating surface m onitoring stations measuring forms of 37 atmospheric sulfur. ........................................................................................... 108 38 Figure 4-3. Anticipated network of surface based NO y stations based on 2009 network 39 design plans. The NCore stations are scheduled to be operating by 40 January, 2011. ................................................................................................... 110 41 Figure 4-4. Location of approximately 250 Na tional Atmospheric Deposition Monitoring 42 (NADP) National Trends Network (NTN) sites illustrating annual 43 ammonium deposition for 2005. Weekly values of precipitation based 44 nitrate, sulfate and ammonium are provided by NADP. .................................. 112 45March 2010 vi Draft – Do No Quote or Cite Figure 4-5. 2005 CMAQ modeled annual average NO y (ppb). These maps will be 1 replaced with full CONUS maps in the next draft. .......................................... 117 2 Figure 4-6. 2005 CMAQ modeled annual av erage total reduced nitrogen (NH x ) (as μ g/m 3 3 nitrogen) ........................................................................................................... 118 4 Figure 4-7. 2005 CMAQ modeled annual average ammonia, NH 3 , (as μ g/m 3 N) ..................... 119 5 Figure 4-8. 2005 CMAQ modeled annual average ammonia, NH4, (as μ g/m 3 N) .................... 120 6 Figure 4-9. 2005 CMAQ modeled annual average SO x , (as μ g/m 3 S from SO 2 and SO 4 ). ........ 121 7 Figure 4-10. 2005 CMAQ modeled annual average SO 2 (as μ g/m 3 S) ...................................... 122 8 Figure 4-11. 2005 CMAQ modeled annual average SO 4 (as μ g/m 3 S). ..................................... 123 9 Figure 4-12. 2005 annual average sulfur di oxide concentrations based on CASTNET 10 generated by the Visibility Information Exchange Web Sysytem 11 (VIEWS). .......................................................................................................... 124 12 Figure 4-13. 2005 annual average sulfate con centrations based on CASTNET generated 13 by the Visibility Information Exch ange Web Sysytem (VIEWS). ................... 124 14 Figure 4-14. Annual average 2005 NO y concentrations from reporting stations in AQS. ......... 125 15 Figure 4-15. 2005 CMAQ modeled Oxidized Nitrogen Deposition (kgN/Ha/Yr) ..................... 126 16 Figure 4-16. 2005 CMAQ modeled Oxidized Sulfur Deposition (kgS/Ha/Yr) .......................... 127 17 Figure 4-17. Three hour average maximum 2005 SO 2 concentrations based on the 18 SLAMS reporting to EPA’s Air Quality System (AQS) data base. The 19 current SO 2 secondary standard based on a the maximum 3 hour average 20 value is 500 ppb, a value not exceeded. While there are obvious spatial 21 gaps, the majority of these stations are located to capture maximum 22 values generally in proximity to major sources and high populations. 23 Lower relative values are expected in more remote acid sensitive areas ......... 128 24 Figure 4-18. Annual average 2005 NO 2 concentrations based on the SLAMS reporting to 25 EPA’s Air Quality System (AQS) data base. The current NO 2 secondary 26 standard is 53 ppb, a value well a bove those observed. While there are 27 obvious spatial gaps, the stations are located in areas of relatively high 28 concentrations in highly populated areas. Lower relative values are 29 expected in more remote acid sensitive areas. .................................................. 129 30 Figure 4-19. 2005 CMAQ derived annual average ratio of (NO y – NO 2 )/NO y . The 31 fraction of NO 2 contributing to total NO y generally is less than 50% in 32 the Adirondack and Shenandoah case st udy areas. The ratio reflects the 33 relative air mass aging associated with transformation of oxidized 34 nitrogen beyond NO and NO 2 as one moves from urban to rural 35 locations. ........................................................................................................... 130 36 Figure 4-20. National map highlighting the 9 case study areas evaluated in the REA. .............. 133 37 Fig 5-1. Schematic diagram of the conceptual design of the standard ....................................... 146 38 Fig 5-2. Schematic diagram of the conceptual design of the standard based on aquatic 39 acidification. From left to right, if a desired le vel of ANC is known, then 40 the concentration of the atmospheric i ndicators that will cause that level 41 may be calculated. From right to left, if the if the concentration of the air 42 quality indicators are known than the ANC that will be caused may be 43 calculated. ......................................................................................................... 148 44March 2010 vii Draft – Do No Quote or Cite Figure 5-3. The depositional load function. ................................................................................ 15 8 1 Fig 5-4. A map of acid sensitive areas of th e Eastern U.S. developed from a lithology2 based five-unit geologic classification system after methods in Sullivan 3 et al. (2007). ...................................................................................................... 163 4 Figure 5-5. V S/N values for each grid cell in the east ern (right) and western (left) U.S. 5 domains. The top maps are for sulfur and the bottom are for nitrogen. ........... 174 6 Figure 5-6. Schematic Diagram illustrating the procedure for converting deposition 7 tradeoff curves of sulfur and nitroge n to atmospheric concentrations of 8 SO x and NO x . .................................................................................................... 175 9 Figure 5-7. Inter-annual coeffici ents of variation (CV) of a) nitrogen and b) sulfur V S/N 10 values, based on a series of 2002-2005 CMAQ v4.7 simulation. .................... 176 11 Figure 5-8. Tradeoff curve for S and N deposition to protect from aquatic acidification in 12 the Adirondacks using N eco equation 2 ............................................................. 181 13 Figure 5-9. Tradeoff curve for S and N deposition to protect from aquatic acidification in 14 the Adirondacks using N eco equation 3 ............................................................. 181 15 Figure 5-10. Tradeoff curve for S and NO y deposition to protect from aquatic 16 acidification in the Adirondacks using N eco equation 2 .................................... 183 17 Figure 5-11. Tradeoff curve for S and NO y deposition to protect from aquatic 18 acidification in the Adirondacks using N eco equation 3 .................................... 183 19 Figure 5-12. Tradeoff curve for at mospheric concentration of SO x and NO y to protect 20 from aquatic acidification in the Adirondacks using N eco equation 2 .............. 184 21 Figure 5-13. Tradeoff curve for at mospheric concentration of SO x and NO y to protect 22 from aquatic acidification in the Adirondacks using N eco equation 3 .............. 185 23 Figure 6-1. Ecosystems sensitive to acidifying deposition in the Eastern U.S. (Note that 24 Florida represents a special cas e where high levels of natural 25 acidification exist unrelated to depo sition) This map does not include all 26 sensitive areas in the U.S. Certai n mountainous areas of the Western 27 U.S. are also sensitive to acidifying deposition. ............................................... 202 28 Figure 6-2. Number of fish sp ecies per lake or stream versus ANC level and aquatic 29 status category (colored regions) for lakes in the Adirondack Case Study 30 Area (Sullivan et al., 2006). .............................................................................. 206 31 32


### LIST OF TABLES 33 Table 3-1. Crosswalk between Ecosystem Se rvices and Public Welfare Effects ......................... 70 34 Table 5-1. Illustration of how selected models and water chemistry data were used to 35 calculate critical lo ads in the REA. .................................................................. 151 36 Table 5-2. Summary of the ecological components of design option 1. ..................................... 166 37 Table 5-3. Oxidized sulfur and nitrogen species currently available in CMAQ 38 simulations. Note that PNA concentrat ions are not avai lable in current 39 CMAQ extractions. ........................................................................................... 174 40 Table 5-4. Example Calculations for Determin ing the Percent of Wa ter Bodies Achieving 41 Target ANC Levels ........................................................................................... 180 42March 2010 viii Draft – Do No Quote or Cite Table 5-5. Values for N and S deposition tr adeoff curves for ANC = 50, protecting 32 1 and 50% of the population, in Adirondacks case study area as illustrated 2 on Fig 5-8 and Fig 5-9. Units are in me q/m2/yr unless noted otherwise. ........ 180 3 Table 5-6. Values for NO y and S deposition tradeoff curves for ANC = 50, protecting 32 4 and 50% of the population in Adirondacks case study area as illustrated 5 on Fig 5.10 and Fig 5.11. Units are in meq/ m2/yr unless noted otherwise. ..... 182 6 Table 7-1. Results of comparing aquatic ANC 50 critical loads to average terrestrial 7 watershed area Bc:Al ratios. Left numbers in each column are the 8 number of lakes or streams that ha d a lower critical load than the 9 terrestrial calculated critical load. Right numbers in each column are the 10 number of lakes that had a higher critical load than the watershed 11 calculated terrestrial critical loads. ................................................................... 214 12 13 14 15March 2010 ix Draft – Do No Quote or Cite 

### LIST OF ACRONYMS AND ABBREVIATIONS 1 AAPI Atmospheric Acidification Potential Index 2 ADR Adirondack Mountains of New York 3 Al 3+ aluminum 4 ANC acid neutralizing capacity 5 AQCD Air Quality Criteria Document 6 AQRV air quality related values 7 ASSETS EI Assessment of Estuarine Trophic Status eutrophication index 8 Bc/Al Base cation to aluminum ratio, also Bc:Al 9 C carbon 10 Ca/Al calcium to aluminum ratio 11 Ca 2+ calcium 12 CAA Clean Air Act 13 CASAC Clean Air Scientific Advisory Committee 14 CASTNet Clean Air Status and Trends Network 15 CCS coastal sage scrub 16 Chl a chlorophyll a 17 CLE critical load exceedance 18 CMAQ Community Multisc ale Air Quality model 19 CSS coastal sage scrub 20 CWA Clean Water Act 21 DIN dissolved inorganic nitrogen 22 DO dissolved oxygen 23 DOI U.S. Department of Interior 24 EMAP Environmental Monito ring and Assessment Program 25 EPA U.S. Environmental Protection Agency 26 FHWAR fishing, hunting and wildlife associated recreation survey 27 FIA Forest Inventory and Analysis National Program 28 FWS Fish and Wildlife Service 29 GIS geographic information systems 30 GPP gross primary productivity 31 H + hydrogen ion 32 H 2 O water vapor 33 H 2 SO 4 sulfuric acid 34 ha hectare 35 HAB harmful algal bloom 36 HFC hydrofluorocarbon 37 Hg +2 reactive mercury 38 Hg 0 elemental mercury 39 HNO 3 nitric acid 40 HONO nitrous acid 41 HUC hydrologic unit code 42 IMPROVE Interagency Monitoring of Protected Visual Environments 43 ISA Integrated Science Assessment 44 K + potassium 45March 2010 x Draft – Do No Quote or Cite kg/ha/yr kilograms per hectare per year 1 km kilometer 2 LRMP Land and Resource Management Plan 3 LTER Long Term Ecological Monitoring and Research 4 LTM Long-Term Monitoring 5 MAGIC Model of Acidification of Groundwater in Catchments 6 MCF Mixed Conifer Forest 7 MEA Millennium Ecosystem Assessment 8 Mg 2+ magnesium 9 N nitrogen 10 N 2 gaseous nitrogen 11 N 2 O nitrous oxide 12 N 2 O 3 nitrogen trioxide 13 N 2 O 4 nitrogen tetroxide 14 N 2 O 5 dinitrogen pentoxide 15 Na + sodium 16 NAAQS National Ambient Air Quality Standards 17 NADP National Atmospheric Deposition Program 18 NAPAP National Acid Precipitation Assessment Program 19 NAWQA National Water Quality Assessment 20 NEEA National Estuarine Eutrophication Assessment 21 NEP net ecosystem productivity 22 NH 3 ammonia gas 23 NH 4 + ammonium ion 24 (NH 4 ) 2 SO 4 ammonium sulfate 25 NH x category label for NH 3 plus NH 4 + 26 NO nitric oxide 27 NO 2 nitrogen dioxide 28 NO 2 - reduced nitrite 29 NO 3 - reduced nitrate 30 NOAA National Oceanic and A tmospheric Administration 31 NO x nitrogen oxides 32 NO y total oxidi zed nitrogen 33 NPP net primary productivity 34 NPS National Park Service 35 NRC National Research Council 36 NSWS National Surface Water Survey 37 NTN National Trends Network 38 NTR organic nitrate 39 O 3 ozone 40 OAQPS Office of Air Qualit y Planning and Standards 41 OW Office of Water 42 PAN peroxyacyl nitrates 43 PFC perfluorocarbons 44 pH relative acidity 45 ppb parts per billion 46 ppm parts per million 47March 2010 xi Draft – Do No Quote or Cite ppt parts per trillion 1 PSD prevention of signi ficant deterioration 2 REA Risk and Exposure Assessment 3 REMAP Regional Environmental Mon itoring and Assessment Program 4 S sulfur 5 S 2 O 3 thiosulfate 6 S 2 O 7 heptoxide 7 SAV submerged aquatic vegetation 8 SF 6 sulfur hexafluoride 9 SMP Simple Mass Balance 10 SO sulfur monoxide 11 SO 2 sulfur dioxide 12 SO 3 sulfur trioxide 13 SO 3 2- sulfite 14 SO 4 wet sulfate 15 SO 4 2- sulfate ion 16 SOM soil organic matter 17 SO x sulfur oxides 18 SPARROW SPAtially Referenced Regressions on Watershed Attributes 19 SRB sulfate-reducing bacteria 20 STORET STORage and RETrieval 21 TIME Temporally Integrated Monitoring of Ecosystems 22 TMDL total maximum daily load 23 TP total phosphorus 24 USFS U.S. Forest Service 25 USGS U.S. Geological Survey 26 μ eq/L microequivalents per liter 27 μ g/m 3 micrograms per cubic meter 28 29
30March 2010 xii Draft – Do No Quote or Cite 

### LIST OF KEY TERMS 1

Acidification: The process of increasing th e acidity of a system (e.g., la ke, stream, forest soil). 2 Atmospheric deposition of aci dic or acidifying compounds can acidify lakes, streams, 3 and forest soils. 4 Air Quality Indicator: The substance or set of substances (e.g., PM 2.5 , NO 2 , SO 2 ) occurring in 5 the ambient air for which the National Ambient Air Quality Standards set a standard level 6 and monitoring occurs. 7 Alpine: The biogeographic zone made up of slopes above the tree line, characterized by the 8 presence of rosette-forming herbaceous plants and low, shrubby, slow-growing woody 9 plants. 10 Acid Neutralizing Capacity: A key indicator of the ability of water to neutralize the acid or 11 acidifying inputs it receives. This ability de pends largely on associated biogeophysical 12 characteristics, such as underlying geology, base cation concentra tions, and weathering 13 rates. 14 Arid Region: A land region of low rainfall, where “low ” is widely accepted to be less than 250 15 mm precipitation per year. 16 Base Cation Saturation: The degree to which soil cation excha nge sites are occupied with base 17 cations (e.g., Ca 2+ , Mg 2+ , K + ) as opposed to Al 3+ and H + . Base cation saturation is a 18 measure of soil acidification, w ith lower values being more acidic. There is a threshold 19 whereby soils with base saturations less than 20% (especially between 10%–20%) are 20 extremely sensitive to change. 21 Ecologically Relevant Indicator: A physical, chemical, or bi ological entity/feature that 22 demonstrates a consistent degree of respons e to a given level of stressor exposure and 23 that is easily measured/quantified to make it a useful predictor of ecological risk. 24 Critical Load: A quantitative estimate of an exposure to one or more pollutants, below which 25 significant (as defined by the analyst or decision maker) harmful effects on specified 26 sensitive elements of the environment do not occur, according to present knowledge. 27 Denitrification: The anaerobic reduction of oxidized nitroge n (e.g., nitrate or ni trite) to gaseous 28 nitrogen (e.g., N 2 O or N 2 ) by denitrifying bacteria. 29 Dry Deposition: The removal of gases and particles from the atmosphere to surfaces in the 30 absence of precipitation (e.g., rain, snow) or occu lt deposition (e.g., fog). 31 Ecological Risk: The likelihood that advers e ecological effects may occur or are occurring as a 32 result of exposure to one or more stressors (U.S. EPA, 1992). 33 Ecological Risk Assessment: A process that evaluates the likelihood that adverse ecological 34 effects may occur or are occurr ing as a result of exposure to one or more stressors (U.S. 35 EPA, 1992). 36 Ecosystem: The interactive system formed from a ll living organisms and their abiotic (i.e., 37 physical and chemical) environment within a gi ven area. Ecosystems cover a hierarchy of 38 spatial scales and can comprise the entire globe, biomes at the continental scale, or small, 39 well-circumscribed systems such as a small pond. 40 Ecosystem Benefit: The value, expressed qualitatively, quan titatively, and/or in economic terms, 41 where possible, associated with changes in eco system services that result either directly 42 or indirectly in improved human health and/or welfare. Examples of ecosystem benefits 43 that derive from improved air quality incl ude improvements in habitats for sport fish 44 species, the quality of drinking water and recreational areas, and visibility. 45March 2010 xiii Draft – Do No Quote or Cite Ecosystem Function: The processes and interactions that operate within an ecosystem. 1 Ecosystem Services: The ecological processes or functions having monetary or non-monetary 2 value to individuals or soci ety at large. These are (1) supporting services, such as 3 productivity or biodiversity main tenance; (2) provisioning servi ces, such as food, fiber, or 4 fish; (3) regulating services, such as climat e regulation or carbon sequestration; and (4) 5 cultural services, such as tourism or spiritual and aesthetic appreciation. 6 Eutrophication: The process by which nitrogen additions stimulate the growth of autotrophic 7 biota, usually resulting in the depletion of dissolved oxygen. 8 Nitrogen Enrichment: The process by which a terrestrial system becomes enhanced by nutrient 9 additions to a degree that stimulates the growth of plant or other terre strial biota, usually 10 resulting in an increase in productivity. 11 Nitrogen Saturation: The point at which nitrogen inputs from atmospheric deposition and other 12 sources exceed the biological requirements of the ecosystem; a le vel beyond nitrogen 13 enrichment. 14 Occult Deposition: The removal of gases and particles fr om the atmosphere to surfaces by fog 15 or mist. 16 Semi-arid Regions: Regions of moderately low rainfall, which are not highly productive and are 17 usually classified as rangelands. “Moderatel y low” is widely accepted as between 100- 18 and 250-mm precipitation per year. 19 Sensitivity: The degree to which a system is affecte d, either adversely or beneficially, by NO x 20 and/or SO x pollution (e.g., acidificati on, nutrient enrichment). The effect may be direct 21 (e.g., a change in growth in response to a ch ange in the mean, range, or variability of 22 nitrogen deposition) or indirect (e.g., change s in growth due to th e direct effect of 23 nitrogen consequently altering competitiv e dynamics between species and decreased 24 biodiversity). 25 Total Reactive Nitrogen: This includes all biologically, ch emically, and radiatively active 26 nitrogen compounds in the atmos phere and biosphere, such as NH 3 , NH 4 + , NO, NO 2 , 27 HNO 3 , N 2 O, NO3–, and organic compounds (e.g. , urea, amines, nucleic acids). 28 Valuation: The economic or non-economic process of determining either the value of 29 maintaining a given ecosystem type, state, or condition, or the value of a change in an 30 ecosystem, its components, or the services it provides. 31 Variable Factors: Influences which by themselves or in combination with other factors may 32 alter the effects on public welfare of an air polluta nt (section 108 (a)(2)) 33 (a) Atmospheric Factors: Atmospheric c onditions that may influence transformation, 34 conversion, transport, and deposition, and th ereby, the effects of an air pollutant on 35 public welfare, such as preci pitation, relative humid ity, oxidation state, and co-pollutants 36 present in the atmosphere. 37 (b) Ecological Factors: Ecological conditions that may influence the effects of an air 38 pollutant on public welfare once it is introduced into an ecosystem, such as soil base 39 saturation, soil thickness, runoff rate, la nd use conditions, bedrock geology, and 40 weathering rates. 41 Vulnerability: The degree to which a system is suscep tible to, and unable to cope with, the 42 adverse effects of NO x and/or SO x air pollution. 43 Welfare Effects: The effects on soils, water, crops, vegetation, man-ma de materials, animals, 44 wildlife, weather, visibility, and climate; as well as damage to and deterioration of 45 property, hazards to transpor tation, and the effects on econom ic values and on personal 46March 2010 xiv Draft – Do No Quote or Cite comfort and well-being, whether caused by tr ansformation, conversion, or combination 1 with other air pollu tants (Clean Air Ac t Section 302[h]). 2 Wet Deposition: The removal of gases and particles from the atmosphere to surfaces by rain or 3 other precipitation. 4 5 6 7Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

February, 2010 Draft – Do Not Quote or Cite 1 . 

### 1. INTRODUCTION 1
The U.S. Environmental Protection Agency (EPA) is presently conducting a review of 2 the secondary National Ambient Air Quality St andards (NAAQS) for oxides of nitrogen (NO x ) 3 and oxides of sulfur (SO x ). The EPA’s overall plan and schedu le for this review were presented 4 in the Integrated Review Plan for the Seconda ry National Ambient Air Quality Standards for 5 Nitrogen Dioxide and Sulfur Dioxide (US EPA, 2007). The Integrated Review Plan (IRP) 6 outlined the Clean Air Act (CAA or the Act) re quirements related to the establishment and 7 reviews of the NAAQS, the process and schedule for conducting the current review, and the key 8 components in the NAAQS review process: an In tegrated Science Assessment (ISA), Risk and 9 Exposure Assessment (REA), and policy assess ment/rulemaking. It presented key policy10
relevant issues to be addressed in this revi ew as a series of que stions that frames our 11
consideration of whether the current secondary (welfare-based) NAAQS for NO x and SO x should 12
be retained or revised. 13 As part of this review, staff in the U.S. Environmental Protection Agency’s (EPA) Office 14 of Air Quality Planning and Standards (OAQPS) prepared this first draft Policy Assessment. 1 15 The objective of this assessment is to evaluate the policy implications of the key scientific 16
information contained in the document Integrated Science Assessment for Oxides of Nitrogen 17 and Sulfur-Ecological Criteria (USEPA, 2008; henceforth referred to as the ISA), prepared by 18
EPA’s National Center for Environmental Assessme nt (NCEA) and the results from the analyses 19
contained in the Risk and Exposure Assessment for Review of the Secondary National Ambient 20 Air Quality Standards for Oxides of Nitrogen and Oxides of Sulfur (U.S. EPA, 2009; henceforth 21 referred to as the REA). This first draft also pres ents preliminary staff conclusions on a range of 22 policy options that we believe are appropriate for the Administ rator to consider concerning 23 whether, and if so how, to revise the secondary (welfare-based) NO x and SO x NAAQS. 24

1 Preparation of a PA by OAQPS staff reflects Administrator Jackson’s decision to modify the NAAQS review process that was presented in the IRP. See http://www.e pa.gov/ttn/naaqs/review.html for more information on the current NAAQS review process.Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 2 This policy assessment is intended to help “bridge the gap” between the scientific 1 assessment contained in the ISA and the judgmen ts required of the EPA Administrator in 2 determining whether it is appropriate to retain or revise the secondary NAAQS for NO x and SO x . 3 This policy assessment considers the available sc ientific evidence and quantitative risk-based 4 analyses, together with related limitations and un certainties, and focuses on the basic elements of 5 air quality standards: indicators 2 , averaging times, forms 3 , and levels. These elements, which 6 serve to define each standard, must be cons idered collectively in evaluating the welfare 7 protection afforded by the secondary NO x and SO x NAAQS. Our development of this policy 8 assessment is based on the assessment and integra tive synthesis of inform ation presented in the 9 ISA and on staff analyses and evaluations presente d in this document, and is further informed by 10 comments and advice received from an independen t scientific review committee, the Clean Air 11 Scientific Advisory Committee (CASAC), in their review of the prev ious integrated science and 12 risk and exposure assessments. The Policy Assessment is further informed by comments 13 submitted by the public 4 . To view related documents developed as part of the planning, science, 14 and risk assessment phases of this review see 15 http://www.epa.gov/ttn/naaqs/standards/no2so2sec/index.html. 16 This document is organized around a conceptual framework for a combined NO x and SO x 17 secondary NAAQS and is focused on answer ing key policy questions related to the 18 implementation of that conceptual framework. Chapter 2 provides a summary of ecological 19 effects from the deposition of ambient NO x and SO x to sensitive ecosystems, drawing from the 20 ISA and REA. Chapter 3 places those ecological e ffects within the context of “public welfare” 21 by linking effects to ecosystem services or ot her benchmarks of public welfare. Chapter 4 22 addresses the adequacy of the current NO x and SO x secondary NAAQS in addressing the impacts 23 on public welfare from ecological effects. Ch apter 5 develops the conceptual design for 24 ecologically relevant multi-polluta nt standards. Chapter 6 presents options for developing critical 25 elements of a secondary NAAQS necessary to implement the conceptual design. Chapter 7 26 describes how secondary NAAQS designed to prot ect a specific ecologi cal endpoint may also 27 provide protection for other ecol ogical endpoints. Chapter 8 provide s a consideration of issues 28

2 The “indicator” of a standard define s the chemical species or mixture that is to be measured in determining whether an area attains the standard. 3 The “form” of a standard defines the ai r quality statistic that is to be compared to the level of the standard in determining whether an area attains the standard. 4 Summary information on public comments will be provided in a later draft of the policy assessmentPolicy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 3 regarding reduced and oxidized forms of nitroge n. Chapter 9 concludes with preliminary staff 1 conclusions regarding ranges of options for pollutant indicators, averaging times, forms, and 2 levels for the secondary NO x and SO x NAAQS, including a discussion of staff initial conclusions 3 on what levels of the secondary NAAQS might be requisite to protect public welfare. 4
In this document we consider how the available scientific evidence and quantitative risk5 based analyses, together with related limitations and uncertainties, info rm the review of each 6 element of the NAAQS: indicator, averaging times, forms, and levels. These elements must be 7 considered collectively in evaluating the welf are protection afforded by the secondary NAAQS 8
standards. This draft document does not contain fi nal staff conclusions as to all the necessary 9 components of an alternativ e secondary standard for NO x and/or SO x but rather describes the 10 current state of thinking with regard to poten tial policy options and provides an appropriate 11
context of information for the Administrator to consider in making decisions regarding the 12
standards. 13 While this policy assessment should be of use to all parties interest ed in the secondary 14
NO x and SO x NAAQS review, it is written with an e xpectation that the reader has some 15 familiarity with the technical discu ssions contained in the ISA and REA. 16 EPA will be preparing a second draft Policy Assessment subsequent to receiving advice 17 from the CASAC. The second draft will incorp orate responses to comments received from 18 CASAC, as well as comments submitted by the pub lic. The second draft will also provide a more 19 complete development of the conceptual model, and will provide a more complete set of staff 20
conclusions on critical elements of the standa rds. EPA’s final Policy Assessment will address 21 additional CASAC comments on the second draft, and will include sufficient information to 22
inform the Administrator on critical elements of the standards, and staff conclusions regarding 23
alternative levels of the standards. 24



### 1.1 DEFINITIONS OF NO X 

### AND SO X 

### FOR THIS ASSESSMENT 25 As discussed in detail in the REA ( REA 1.3.1 ), in the atmospheric science community 26
NO x is typically referred to as the sum of nitrogen dioxide (NO 2 ), and nitric oxide (NO). From a 27 Clean Air Act perspective, the family of NO x includes any gaseous combination of nitrogen and 28 oxygen (e.g., NO 2 , NO, nitrous oxide [N 2 O], nitrogen trioxide [N 2 O 3 ], nitrogen tetroxide [N 2 O 4 ], 29 and dinitrogen pentoxide [N 2 O 5 ]). The term used by the scientific community to represent the 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 4 complete set of oxidized nitr ogen compounds, includi ng those listed in CAA Section 108(c), is 1 total oxidized nitrogen (NO y ). NO y includes all nitrogen oxides, including e.g. total reactive 2 oxidized atmospheric n itrogen, defined as NO x (NO and NO 2 ) and all oxidized NO x products: 3
NO y = NO 2 + NO + HNO 3 + PAN +2N 2 O 5 + HONO+ NO 3 + organic nitrates + particulate NO 3 4 (Finlayson-Pitts and Pitts, 2000). In this document, unless otherwise indicated, we use the term 5
NO x interchangeably with NO y to refer to the complete set of oxidized nitrogen compounds. 6 For this assessment, SO x is defined to include all oxides of sulfur, including multiple 7 gaseous substances (e.g., SO 2 , sulfur monoxide [SO], sulfur trioxide [SO 3 ], thiosulfate [S 2 O 3 ], 8 and heptoxide [S 2 O 7 ], as well as particulate species, such as ammonium sulfate [(NH 4 ) 2 SO 4 ]). 9 Throughout this text we refer to sulfate as SO 4 and nitrate as NO 3 , recognizing that they have 10 charges of -2 for sulfat e and -1 for nitrate. 11



### 1.2 POLICY OBJECTIVES 12 In conducting this periodic review of the NO x and SO x secondary NAAQS, EPA has 13 decided to jointly assess the scie ntific information, associated ri sks, and standards relevant to 14 protecting the public welfare from adverse effects associated with oxides of nitrogen and sulfur. 15 Although EPA has historically adopted separate secondary standards for oxides of nitrogen 16 (NO x ) and oxides of sulfur (SO x ), EPA is conducting a joint seconda ry review of these standards 17
because NO x , SO x , and their associated transformation pr oducts are linked from an atmospheric 18 chemistry perspective, as well as from an e nvironmental effects perspective. The National 19 Research Council (NRC) has recommended that EPA consider multiple pollutants, as 20 appropriate, in forming the scientific basis fo r the NAAQS (NRC, 2004). There is a strong basis 21 for considering these pollutants together, bui lding upon EPA’s and CASAC’s past recognition of 22 the interactions of these polluta nts and on the growing body of scien tific information that is now 23
available related to these interactions and associated ecological effects. 24 EPA sets secondary standards for tw o criteria pollutants related to NO x and SO x : ozone 25 and particulate matter (PM). NO x is a precursor to the formation of ozone in the atmosphere, and 26 under certain conditions, can combine with atmos pheric ammonia to form ammonium nitrate, a 27 component of fine PM. SO x is a precursor to the formation of particulate sulfate, which is a 28 significant component of fine PM in many parts of the U.S. While there are a number of welfare 29 effects associated with ozone and fine PM, incl uding ozone damage to vegetation, and visibility 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 5 degradation related to PM, protec tion against those effects is pr ovided by the ozone and fine PM 1
standards. This review focuses on eval uation of the protection provided by NO x and SO x 2 secondary standards for effects associated wi th direct atmospheric concentrations of NO x and 3
SO x , and effects associated with deposition of NO x and SO x to ecosystems, including deposition 4 in the form of particulate nitrate an d sulfate in their component forms. 5 The ISA highlights the ecological effects as sociated with deposition of ambient NO x and 6
SO x to ecosystems other than commercially mana ged forests and agricultural lands. This 7 assessment evaluates information on gas-phase effects of NO x and SO x via stomatal exposure on 8 vegetation, but primarily focuses on the effects of gas-phase NO x and SO x exposure via 9 deposition on multiple ecological receptors. Highli ghted effects include those associated with 10 acidification and nitrogen nutrien t enrichment. Based on these highlighted effects, EPA’s policy 11 objective is to develop a framework for NO x and SO x standards that incorporate factors that will 12 lead to standards that are ecologically relevant, and that recognizes the in teractions between the 13 two pollutants as they deposit to sensitive ecosystem s, with an ultimate goal of setting standards 14 that, based on the ecological criteria described in the ISA, and consistent with the requirements 15 of the Clean Air Act, “are requisite to protec t the public welfare from any known or anticipated 16 adverse effects associated with the presence of such air pollutant in the ambient air.” 17 In presenting policy options fo r the Administrator’s consider ation, we note that the final 18 decision on retaining or revising the current secondary standards for NO x and SO x is largely a 19 public welfare policy judgment based on the Ad ministrator’s informed assessment of what 20 constitutes requisite protection against adverse ef fects to public welfare. A final decision should 21 draw upon scientific information and analyses about welfare effects, exposure and risks, as well 22 as judgments about the appropriate response to the range of uncertain ties that are inherent in the 23 scientific evidence and analyses. The ultimate determination as to what level of damage to 24 ecosystems and the services provided by those ecos ystems is adverse to public welfare is not 25 wholly a scientific question, al though it is informed by scien tific studies linking ecosystem 26 damage to losses in ecosystem services, and econo mic information on the value of those losses in 27 ecosystem services. Our approach to informi ng these judgments, as discussed below, is 28 consistent with the requiremen ts of the NAAQS provisions of th e Clean Air Act and with how 29 EPA and the courts have historically interp reted the Act. These provisions require the 30
Administrator to establish seconda ry NAAQS that, in the Administ rator’s judgment, are requisite 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 6 to protect public welfar e from any known or anticipated a dverse effects associated with the 1 presence of NO x and SO x in the ambient air. In so doing, th e Administrator seeks to establish 2
standards that are neither more nor less st ringent than necessary for this purpose. 3 For this first draft policy assessment, we have chosen to focus much of our discussion on 4
the effects of ambient NO x and SO x on ecological impacts associat ed with acidifying deposition 5 of nitrogen and sulfur, which is a transformation product of ambient NO x and SO x . We have the 6 greatest confidence in the causal linkages between NO x and SO x and aquatic acidification effects, 7 and we have the most complete information av ailable with which to develop an ecologically 8 meaningful structure for the standards. In future drafts, we expect to be able to explore whether 9 and how the standards can be expanded to direct ly address effects of aci dification on terrestrial 10 ecosystems, and to address the effects of nut rient enrichment in terrestrial and aquatic 11 ecosystems. 12



### 1.3 CRITICAL POLICY ELEMENTS 13 Our policy objective is guided by the informa tion in the ISA and REA, framed within the 14 legislative requirements of the CAA. This frami ng leads us to focus on critical policy elements 15 (CPE) consistent with elements of Clean Air Act language. 16 Sections 108 and 109 of the CAA govern the establishment and periodic review of the 17 NAAQS and of the air quality criteria upon whic h the standards are based. The NAAQS are 18 established for pollutants that are listed unde r section 108, based on th ree criteria, including 19 whether emissions of the air pollutant cause or contribute to air pollu tion which may reasonably 20 be anticipated to endanger public health or welfare and whose presence in the ambient air results 21
from numerous or diverse mobile or stationa ry sources. The NAAQS are based on air quality 22
criteria that reflect the latest scientific knowledge, useful in in dicating the types and extent of 23 identifiable effects on public health or welfare th at may be expected from the presence of the 24 pollutant in ambient air. The criteria refer to cr iteria issued pursuant to §108 of the Clean Air 25 Act, which include “(A) those variable factors (including at mospheric conditions) which of 26
themselves or in combination with other factors may alter the effects on public health or welfare 27 of such air pollutant; (B) the t ypes of air pollutants which, when present in the atmosphere, may 28 interact with such pollutant to produce an adverse effect on public health of welfare; and (C) any 29 known or anticipated adve rse effects on welfare.” 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 7 The following critical policy elements for th e design of ecologically relevant secondary 1
standards for NO x and SO x are identified: 2 (CPE 1) An evaluation of the effects of ambient NO x and SO x on ecosystems, and the 3 relationship between those effects and the measure of dose in the ecosystem, 4 indicated by the depositional loadings of N and S. 5 (CPE 1.1) Evaluation of the relationship be tween response of ecological receptors, e.g. 6 changes in diversity of fish species, and the response related to public welfare, 7 e.g. loss in recreationa l fishing services. 8 (CPE 1.2) Evaluation of the extent to which identified effects are occurring under recent 9 conditions, and the extent to which meeting the current standards would 10 provide protection against these effects. 11 (CPE 2) An assessment of how best to ch aracterize, in defining the standards, the 12 variable ecosystem factors that affect the relationship between ecological 13 effects and depositional loadings of N and S. 14 (CPE 2.1) Specification of potential indi cators of ecological effects, e.g. acid 15 neutralizing capacity (ANC) th at incorporates variability in ecosystem factors. 16 (CPE 3) Characterization of the comp lex atmospheric transformations between 17
ambient concentrations of NO x and SO x and deposition of N and S in the 18 specification of a standard. 19 (CPE 4) Specification of those factors, such as precipitation, which interact with 20
ambient NO x and SO x to produce adverse effects on welfare, by affecting 21 deposition of N and S. 22 (CPE 5) Specification of the form for th e standard(s), including ambient atmospheric 23
indicators for NO x and SO x , with consideration of averaging times, and 24 options for levels of the standard(s). 25 The development of the conceptual framework for the NO x and SO x standards described 26 in Section 1.4 will be motivated by these critical policy elements. However, in order to provide a 27
historical context for this new framework, the next section provide s a brief history of previous 28
reviews of the NO x and SO x secondary NAAQS, as well as other relevant historical reviews of 29 welfare effects associated with these pollutants. 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 8 

### 1.4 HISTORICAL CONTEXT 1

1.4.1 History of NO x and SO x NAAQS Review 2

1.4.1.1 NO x NAAQS 3 EPA began the most recent previous review of the NO x secondary standards in 1987 and 4 in November 1991, EPA released an updated dr aft AQCD for CASAC and public review and 5 comment (56 FR 59285). This draft document pr ovided a comprehensive assessment of the 6
available scientific and technical information on health and welfare eff ects associated with NO 2 7
and other NO x . CASAC reviewed the draf t document at a meeting held on July 1, 1993, and 8
concluded in a closure letter to the Administrator that the document “provides a scientifically 9 balanced and defensible summary of current kno wledge of the effects of this pollutant and 10 provides an adequate basis for EPA to make a decision as to the appropriate NAAQS for NO 2 ” 11 (Wolff, 1993). The AQCD Air Quality Criteria for Oxides of Nitrogen was then finalized (U.S. 12 EPA, 1993). EPA also prepared a Staff Paper that summarized and integrat ed the key studies and 13
scientific evidence contained in the revised NO x AQCD and identified the critical elements to be 14
considered in the review of the NO 2 NAAQS. CASAC reviewed two drafts of the Staff Paper and 15
concluded in a closure letter to the Administrator that the docu ment provided a “scientifically 16 adequate basis for regulatory decisions on nitr ogen dioxide” (Wolff, 1995). In October 1995, the 17 Administrator announced her proposed decision not to revise eith er the primary or secondary 18 NAAQS for NO 2 (60 FR 52874; October 11, 1995). A year la ter, the Administrator made a final 19 determination not to revise the NAAQS for NO 2 after careful evaluation of the comments 20 received on the proposal (61 FR 52852; October 8, 1996). The level for both the existing primary 21 and secondary NAAQS for NO 2 is 0.053 ppm (100 micrograms per cubic meter [ μ g/m 3 ] of air), 22 annual arithmetic average, calculated as the arithmetic mean of the 1-hour NO 2 concentrations. 23

1.4.1.2 SO x NAAQS 24
Based on the 1970 SO x criteria document (DHEW, 1970), EPA promulgated primary and 25 secondary NAAQS for SO 2 on April 30, 1971 (36 FR 8186). The secondary standards included a 26 standard at 0.02 ppm in an annual arithmetic m ean and a 3-hour average of 0.5 ppm, not to be 27 exceeded more than once per year. These secondary standards were established solely on the 28 basis of evidence of adverse effects on vege tation. In 1973, revisions made to Chapter 5 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 9 (“Effects of Sulfur Oxide in th e Atmosphere on Vegetation”) of Air Quality Criteria for Sulfur 1
Oxides (U.S. EPA, 1973) indicated that it could not properly be c oncluded that the vegetation 2 injury reported resulted from the average SO 2 exposure over the growi ng season, rather than 3 from short-term peak concentrations. Therefor e, EPA proposed (38 FR 11355) and then finalized 4 (38 FR 25678) a revocation of the annual mean sec ondary standard. At that time, EPA was aware 5
that SO x have other public welfare eff ects, including effects on mate rials, visibility, soils, and 6 water. However, the available data were cons idered insufficient to establish a quantitative 7 relationship between specific ambient SO x concentrations and effects (38 FR 25679). 8 In 1979, EPA announced that it was revising th e Air Quality Criteri a Document (AQCD) 9 for sulfur oxides concurrently with that for particulate matter and w ould produce a combined 10 particulate matter and sulfur oxi des criteria document. Following its review of a draft revised 11 criteria document in August 1980, CASAC conc luded that acid deposition was a topic of 12 extreme scientific complexity because of the difficulty in establishing firm quantitative 13 relationships among (1) emissions of relevant pollutants (e.g., SO 2 and oxides of nitrogen), (2) 14 formation of acidic wet and dry deposition products, and (3) eff ects on terrestrial and aquatic 15 ecosystems. CASAC also noted th at acid deposition involves, at a minimum, several different 16 criteria pollutants: oxides of sulfur, oxides of nitrogen, and the fine particulate fraction of 17 suspended particles. CASAC felt that any documen t on this subject should address both wet and 18 dry deposition, since dry deposition was believed to account for at least one ha lf of the total acid 19 deposition problem. 20 For these reasons, CASAC recommended that a separate, comprehensive document on 21 acid deposition be prepared prior to any cons ideration of using the NAAQS as a regulatory 22 mechanism for the control of acid deposition. CASA C also suggested that a discussion of acid 23 deposition be included in the AQCDs for nitrogen oxides and PM and SO x . Following CASAC 24 closure on the AQCD for SO 2 in December 1981, EPA’s Office of Air Quality Planning and 25 Standards published a Staff Paper in November 1982, but the paper did not directly assess the 26 issue of acid deposition. Instead, EPA subse quently prepared the following documents: The 27 Acidic Deposition Phenomenon and Its Effects: Cr itical Assessment Review Papers, Volumes I 28
and II (U.S. EPA, 1984a, b), and The Acidic Deposition Phenom enon and Its Effects: Critical 29
Assessment Document (U.S. EPA, 1985) (53 FR 14935 -14936). These documents, though they 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 10 were not considered criteria documents and did not undergo CASAC review, represented the 1 most comprehensive summary of relevant scientif ic information completed by EPA at that point. 2 On April 26, 1988 (53 FR 14926), EPA proposed not to revise the existing primary and 3 secondary standards for SO 2 . This proposal regarding the secondary SO 2 NAAQS was due to the 4
Administrator’s conclusions that (1) based upon the then-current scientific understanding of the 5 acid deposition problem, it would be premature and unwise to pr escribe any regulatory control 6 program at that time, and (2) when the fundament al scientific uncertain ties had been reduced 7 through ongoing research efforts, EPA would draf t and support an appropriate set of control 8

measures. 9

1.4.2 History of Related Assessments and Agency Actions 10 In 1980, the Congress created the National Acid Precip itation Assessment Program 11 (NAPAP) in response to growing concern a bout acidic deposition. The NAPAP was given a 12 broad 10-year mandate to examine the causes an d effects of acidic de position and to explore 13 alternative control options to al leviate acidic deposition and its e ffects. During the course of the 14 program, the NAPAP issued a series of publicly av ailable interim reports prior to the completion 15 of a final report in 1990 (NAPAP, 1990). 16 In spite of the complexities and significan t remaining uncertainties associated with the 17 acid deposition problem, it soon became clear th at a program to address acid deposition was 18
needed. The Clean Air Act Amendments of 1990 included numerous separa te provisions related 19 to the acid deposition problem. The primary and most important of the provisions, the 20 amendments to Title IV of the Act, establishe d the Acid Rain Program to reduce emissions of 21
SO 2 by 10 million tons and NO x emissions by 2 million tons from 1980 emission levels in order 22 to achieve reductions over broad geographic re gions. In this provision, Congress included a 23 statement of findings that led them to take ac tion, concluding that (1) the presence of acid 24 compounds and their precursors in the atmosphere and in deposition from the atmosphere 25 represents a threat to natural resources, ecosyst ems, materials, visibil ity, and public health; (2) 26 the problem of acid deposition is of national and international significance; and (3) current and 27 future generations of Americans will be adversely affected by delaying measures to remedy the 28 problem. 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 11 Second, Congress authorized the continuation of the NAPAP in order to assure that the 1 research and monitoring efforts already undertaken would continue to be coordinated and would 2 provide the basis for an impartial assessment of the effectiveness of the Title IV program. 3 Third, Congress considered that further acti on might be necessary in the long term to 4 address any problems remaining after implementa tion of the Title IV program and, reserving 5 judgment on the form that action could take , included Section 404 of the 1990 Amendments 6 (Clean Air Act Amendments of 1990, Pub. L. 101-549, § 404) requiring EPA to conduct a study 7 on the feasibility and effectiveness of an acid deposition standard or standards to protect 8 “sensitive and critically sensitiv e aquatic and terrestrial resources .” At the conclusion of the 9 study, EPA was to submit a report to Congress. Five years later, EPA submitted its report, 10
entitled Acid Deposition Standard Feasibilit y Study: Report to Congress (U.S. EPA, 1995) in 11 fulfillment of this requirement. The Report conc luded that establishing acid deposition standards 12 for sulfur and nitrogen deposition may at some point in the future be technically feasible, 13 although appropriate deposition loads for these acidi fying chemicals could not be defined with 14 reasonable certainty at that time. 15 Fourth, the 1990 Amendments also added new language to sections of the CAA 16 pertaining to the scope and app lication of the secondary NAAQS designed to protect the public 17 welfare. Specifically, the definition of “effect s on welfare” in Section 302(h) was expanded to 18
state that the welfare effects include effects “...whet her caused by transformation, conversion, or 19 combination with other air pollutants.” 20 In 1999, seven Northeastern states cited this amended language in Section 302(h) in a 21 petition asking EPA to use its authority under the NAAQS program to promulgate secondary 22 NAAQS for the criteria pollutants as sociated with the formation of acid rain. The petition stated 23 that this language “clearly references the transf ormation of pollutants resulting in the inevitable 24 formation of sulfate and nitrate aerosols and/or their ultimate environmental impacts as wet and 25 dry deposition, clearly signaling Congressional intent that th e welfare damage occasioned by 26 sulfur and nitrogen oxides be addressed through the secondary standard provisions of Section 27 109 of the Act.” The petition fu rther stated that “recent fede ral studies, including the NAPAP 28 Biennial Report to Congress: An Integrated Assessment, documen t the continued-and increasing29 damage being inflicted by acid deposition to th e lakes and forests of New York, New England 30 and other parts of our nation, de monstrating that the Title IV program had proven insufficient.” 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 12 The petition also listed other a dverse welfare effects associated with the transformation of these 1 criteria pollutants, including im paired visibility, eutrophicati on of coastal estuaries, global 2 warming, and tropospheric ozone and stratospheric ozone depletion. 3 In a related matter, the Office of the Secret ary of the U.S. Department of Interior 4 requested in 2000 that EPA initiate a rulemaki ng proceeding to enhance the air quality in 5 national parks and wilderness areas in order to protect resources and values that are being 6 adversely affected by air pollution. Included among the effects of concern identified in the 7 request were the acidification of streams, surface waters, and/or soils; eutrophication of coastal 8 waters; visibility impairment; and foliar injury from ozone. 9 In a Federal Register notice in 2001, EPA a nnounced receipt of these requests and asked 10
for comment on the issues raised in them. EPA stated that it would consider any relevant 11 comments and information submitted, along with the information provided by the petitioners and 12 DOI, before making any decision concerning a response to these requests for rulemaking (65 FR 13 48699). 14 The most recent 2005 NAPAP report states that “... scientific studies indicate that the 15 emission reductions achieved by Title IV are not sufficient to allo w recovery of acid-sensitive 16 ecosystems. Estimates from the literature of the scope of additional emi ssion reductions that are 17 necessary in order to protect acid-sensitive ecosystems range from approximately 40-80% 18 beyond full implementation of Title IV.... The results of the modeling presente d in this Report to 19 Congress indicate that broader r ecovery is not predicted without additional emission reductions” 20 (NAPAP, 2005). 5 21
Given the state of the science as described in the ISA and in other recent reports, such as 22 the NAPAP’s above, EPA believes it is appropriate, in the context of eval uating the adequacy of 23
the current NO 2 and SO 2 secondary standards in this revi ew, to revisit the question of the 24 appropriateness and the feasibility of setti ng a secondary NAAQS to address remaining known 25 or anticipated adverse public we lfare effects resulting from the acidic and nutrient deposition of 26 these criteria pollutants 27

5 Note that a new NAPAP report is exp ected to be released later in 2010. The findings of that report will be considered in the final policy assessment.Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 13 

### 1.5 PROPOSED CONCEPTUAL FRAMEWORK FOR COMBINED NO X 1 

### SO X 

### STANDARDS 2 There is a strong basis for considering NO x and SO x together at this time, building upon 3 EPA’s and CASAC’s past recognition of the intera ctions of these polluta nts and on the growing 4 body of scientific information that is now availabl e related to these intera ctions and associated 5 ecological effects. The REA introduced a concep tual framework for ecologically meaningful 6 secondary standards that recognized the complex processes by which ecosystems are exposed to 7
ambient NO x and SO x . That framework provided a flow from ambient concentrations exposures 8 via deposition to ecological indicators and e ffects (see Figure ES-2 in the REA Executive 9 Summary). This sequence represents the process by which we can determine the risks associated 10
with ambient concentrations of NO x and SO x . However, for the purposes of discussing a 11 conceptual framework for design of standards to protect against those risks, a modified version 12
of the risk framework is needed. 13 Figure 1-1 depicts the framework by which we are considering the structure of an 14 ecologically meaningful secondary standard. It is a conceptual diagram that illustrates how a 15 level of protection related to an indicator of ecological effect(s) equates to atmospheric 16
concentrations of NO x and SO x indicators. This conceptual diagram illustrates the linkages 17
between ambient air concentratio ns and resulting deposition metr ics, and between the deposition 18 metric and the ecological indicator of con cern. The Atmospheric Deposition Transformation 19
Function translates ambient atmo spheric concentrations of NO x and SO x to nitrogen and sulfur 20 deposition metrics, while the Ecological Effect Function transforms the deposition metric into 21 the ecological indicator. 22 Development of a form for the standard that refl ects this structure is a critical step in the 23 overall standard setting process. The atmospheric levels of NO x and SO x that satisfy a particular 24 level of ecosystem protection are those levels that result in an amount of deposition that is less 25 than the amount of deposition that a given ecosy stem can accept without excessive degradation 26 of the ecological indicator for a targeted effect. 27 The details of this conceptual framew ork are discussed in Chapter 5, including 28 discussions of modifying fact ors that alter the relationshi p between ambient atmospheric 29
concentrations of NO x and SO x and depositional loads of nitrogen and sulfur, and those that 30 modify the relationship between depositi on loads and the ecological indicator. 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 14 In setting NAAQS to protect public health a nd welfare, EPA has historically established 1 standards which require the compar ison of monitored concentrations of an air pollutant against a 2 numerical metric of atmospheric concentration that does not vary geographically. This approach 3 has appropriately protected public health as at -risk populations are wide ly distributed throughout 4
the nation. As more is learned about the effects of pollutants such as NO x and SO x and the 5 environment, however, such an approach may not be appropriate to provide the requisite level of 6 protection to public welfare from effects on sens itive ecosystems. EPA is considering in this 7
review of the seconda ry standard for NO x and SO x whether a standard th at takes into account 8 variable factors, such as atmospheric variables and ecosystem sensitivities, is the appropriate 9 approach to protect the public welfare from th e effects associated with the presence of these 10 pollutants in the ambient air. 11 EPA must undertake a thorough revi ew of the air quality criteria for the pollutant at issue 12 in reviewing a secondary NAAQS, and determine whether a current standa rd is requisite to 13 protect the public welfare. Unde r section 108 of the CAA, air quali ty criteria are to “reflect the 14 latest scientific knowledge useful in indicating the kind and extent of all identifiable effects” 15 associated with the presence of the pollutant in th e ambient air. It is clear from the language of 16 the CAA that where the state of the science provi des a basis for considering such effects, the 17 review of the air quality crit eria should encompass a broa d analysis of “any” known or 18 anticipated adverse effects, as well as the ways in which variable conditions such as atmospheric 19 conditions may impact the effect of a pollutant and the ways in which other air pollutants may 20 interact with the criteria pollutant to produce ad verse effects. Specifically, section 108(a)(2) of 21 the CAA provides that: 22 Air quality criteria for an air pollutant sh all accurately reflect the latest scientific 23 knowledge useful in indicating the kind and extent of all identifiable eff ects on public health or 24 welfare which may be expected from the presence of such pollutant in the ambient air, in varying 25 quantities. The criteria for an air pollutant to th e extent practicable, sha ll include information on: 26

 (A) those variable factors (including atmos pheric conditions) which of themselves or 27
in combination with other fact ors may alter the effects on public health or welfare of such 28 air pollutants; 29

 (B) the types of air pollutants which, when present in the atmosphere, may interact 30 with such pollutants to produ ce an adverse effect on public health or welfare; and 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 15  (C) any known or anticipated adverse effects on welfare. 1
Based on this extensive review of the air quality criteria for an air pollutant, the 2 Administrator is required to review and to revi se, as appropriate, the secondary standard to 3
ensure that the standard “is re quisite to protect pub lic welfare from any known or anticipated 4 adverse effects associated with the presence of such air pollutant in the ambient air.” CAA § 5 109(b) & (d). “Effects on welfare,” in turn, is defined to include a broad array of effects, 6 including effects on soil, water, crops, vegeta tion, and manmade materials, “whether caused by 7 transformation, conversion, or combination with other air pollutants.” CAA § 302(h). Thus, as 8
with the sections of the CAA describing the issuance of air qu ality criteria, the CAA uses 9 expansive language in describing th e scope of EPA’s responsibility and the range of effects that 10 EPA should take into account in setting a standard that is requisite to protect public welfare. The 11 term “requisite,” however, indicates that sec tion 109 is not open-ende d. In considering the 12 meaning of the term “requisite” in the context of the primary standards, the Supreme Court has 13 agreed with EPA that such a standard is one that is “sufficient, but not more than necessary” to 14 protect public health. Whitman v. American Trucking, 531 U.S. 457, 473 (2001). 15
While EPA has most often considered the results of direct exposure to an air pollutant in 16 the ambient air in assessing effects on public hea lth and welfare, such as the health effects on 17 humans when breathing in an air pollutant or the effects on vegetation through the uptake of air 18 pollutants from the ambient air through leaves, EP A has also considered, where appropriate, the 19 effects of exposure to air pollutants through more indirect mechanisms. For example, both in 20 1978 and in 2008, EPA established a NAAQS for lead that addressed the health effects of 21 ambient lead whether the lead particles were in haled or were ingested after deposition on the 22 ground or other surfaces. 73 FR 66964 (November 12, 2008), Lead Industries v. EPA, 647 F.2d 23 1130 (DC Cir. 1980) (1978 NAAQS). The deposition of ambient NO x and SO x to terrestrial and 24 aquatic environments can impact ecosystems th rough both direct and indirect mechanisms, as 25
discussed in the REA and this document. Given C ongress’ instruction to set a standard that “is 26 requisite to protect the public welfare from “any known or anticipat ed adverse effects associated 27 with the presence of such air pollutant in the ambient air,” 42 U.S.C. § 109 (b)(2) (emphasis 28 added), this review appropriately attempts to take into consideration widely acknowledged 29 effects, such as acidification and nutrient enrichme nt, which are associated with the presence of 30
ambient SO x and NO x . 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 16 In this review, EPA is also attempting to de velop a standard that takes into account the 1 variability in effects from ambient levels of SO x and NO x . The CAA requires EPA to establish 2 “national” standards, based on the air quality cr iteria, that provide the requisite degree of 3 protection, but does not clearly a ddress how to do so under the ci rcumstances present here. One 4 approach is to develop a secondary standard such as the one discussed in this Policy Assessment 5 Document. Such a standard is designed to pr ovide a generally uniform degree of protection 6 throughout the country by allowing for varyi ng concentrations of allowable ambient NO x and 7
SO x , depending on atmospheric conditions and other variabilities, to ach ieve that degree of 8 protection. Such a standard protects sensitive ecosystems wherever such ecosystems are found. 9 This approach recognizes that setting a standard that is sufficient to protect the public welfare but 10 not more than is necessary calls for consideration of a standard such as the one discussed in this 11
document. 12 

# Structure of an Ecol ogically-based Standard

Air Quality Indicator(s ) Measured over a specified averaging time ; expressed in terms of a specified

statistic (form ) Ecological Indicator Ecological

Effect Function Atmospheric Deposition
Transformation

Function Deposition Metric Variable/Fixed Factors: Ecological Variable/Fixed Factors: Atmospheric Landscape

Form of the Standard

Level of the Standard 13 Figure 1-1. Framework of an alterna tive secondary standard. 14 

### 1.6 POLICY RELEVANT QUESTIONS 15 In this policy assessment, a series of genera l questions frames our approach to identifying 16 a range of policy options for consideration by the Administrator rega rding secondary NAAQS 17
for NO x and SO x . These questions are drawn from our Integrated Review Plan with 18Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 17 modifications based on further considerati on by staff and comments from CASAC and the 1 public. Our policy assessment begins by characteri zing “known or anticipated adverse effects” 2 on public welfare within our concep tual model (CPE 1). As noted earlier, this review is focusing 3 on effects in unmanaged ecosystems (not co mmercial forests or agricultural lands 6 ) resulting 4
from ambient concentrations of NO x and SO x through deposition of N and S. In Chapter 2, we 5 draw from the information and conclusions pr esented in the ISA and REA to address the 6 following questions: 7 1. What are the nature and magnitude of eco system responses to reactive nitrogen and 8 sulfur deposition? 9 a. How are these responses a ffected by landscape factors? 10 b. What types of ecosystems are sensitive to such responses? 11 2. To what extent can ecosystem responses to nitrogen deposition be separated into 12 responses related to oxidized and reduced forms of reactive nitrogen compounds? 13 In Chapter 3, we address the following questions related to linking e ffects to measures of 14 adversity (CPE 1.1): 15 1. How do we characterize adversity to pub lic welfare? What are the sources of 16 potentially relevant characteriza tion for this policy assessment? 17 2. What is the evidence of effects on ecosys tem services, and how can those ecosystem 18 services be linked to ecological indicators? 19 3. To what extent are identified ecosystem effects important from a public welfare 20 perspective, and what are the important uncer tainties associated with estimating such 21
effects? 22 Once we have described ecological effects, we then provide an assessment of the 23 adequacy of the existing NO x and SO x standards (CPE 1.2). We begin this assessment by 24 drawing from the information and conclusions presented in the ISA and REA to address in 25 Chapter 4 the following questions, which allow us to identify whether the st ructure of the current 26 standards is appropriate relativ e to the key ecological effects assessed in the ISA and REA, 27

6 The decision to focus on unmanaged ecosystems is based on the weight of evidence of effects in those ecosystems. The majority of the scientific evidence regarding acidifi cation and nutrient enrichment is based on studies in unmanaged ecosystems. Non-managed terrestrial ecosystems tend to have a higher fraction of N deposition resulting from atmospheric N ( ISA 3.3.2.5 ). In addition, the ISA notes that agricultural and commercial forest lands are routinely fertilized with amounts of N (100 to 300 kg N/ha) that exceed air pollutant inputs even in the most polluted areas ( ISA 3.3.9 )Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 18 including acidification and excess nutrient enrichment and whether there is adequate information 1 and analyses available at this time to assess th e extent to which potenti ally adverse effects on 2 aquatic and terrestrial ecosystems can be associat ed with current levels of atmospheric reactive 3 nitrogen, accounting for the contributions of oxidized and reduced forms, and SO x and with 4
levels that are at or below th e current seconda ry standards: 5
1. To what extent are effects that could r easonably be judged to be adverse to public 6 welfare occurring under current conditions and would such effects occur if the nation 7
met the current standards? To what extent do the current NO x and SO x secondary 8 standards provide protection from eff ects associated with deposition of: 9
a. Sulfur and oxidized nitr ogen from atmospheric NO x , and SO x which results in 10 acidification in sensitive aqua tic and terrestrial ecosystems? 11 b. Oxidized nitrogen from atmospheric NO x , which results in nutrient enrichment 12 effects in sensitive aquatic and terrestrial ecosystems? 13
c. Sulfur and oxidized nitr ogen from atmospheric NO x and SO x which results in 14 other ecological effects (e .g. mercury methylation)? 15 2. In what way are the structures of the current NO x and SO x secondary standards 16 inadequate to protect agai nst public welfare effects? 17 In Chapter 5, we follow our adequacy assessment by developing in greater detail the 18 conceptual framework for the design of ecologically relevant multi-pollutant standards 19
introduced in Section 1.4 above. To the extent th at the available informa tion calls into question 20 the adequacy of protection afforded by the curr ent standards and/or th e appropriateness of the 21 structure of the standards, we explore the ex tent to which available information supports 22
consideration of alternative sta ndards, in terms of atmospheri c and ecological indicators and 23 related averaging times, forms, and levels. This conceptual framework is designed to focus on 24 resolving the following questions: 25 1. (CPE 2.1) Does the available informati on provide support for th e use of ecological 26 indicators to characterize the responses of aquatic and terrestrial ecosystems to 27 oxidized nitrogen and sulfur deposition? 28 2. (CPE 1) Does the available informati on provide support for the development of 29 appropriate ecological response to deposition relationship(s) that meaningfully relates 30 oxidized nitrogen and sulfur deposition to relevant ecological indicators? Does a 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 19 quantified relationship exist between the leve l of a relevant ecological indicator and 1 an amount of nitrogen and sulfur deposition? 2 3. (CPE 2) What are the important variable s in the ecological response to deposition 3 relationship(s)? Are these relationships applicable nationally? What are the 4 appropriate temporal scales for these relationships? 5 a. How does ecological response to depos ition relationship(s) depend upon spatially 6 heterogeneous geologic factors (e.g. bedroc k type, weathering rates) that govern 7 sensitivity? 8 b. How do we consider areas with high natural background acidi fication or nutrient 9 loadings? 10 4. (CPE 3) Does the available informati on provide support for the development of 11 appropriate functions that characterize the relationshi ps between atmospheric NO x 12
and SO x and the wet and dry deposition of total reactive nitrogen a nd sulfur? (CPE 4) 13 How do these relationships depend upon rele vant atmospheric factors (e.g., reduced 14 forms of nitrogen, meteorological fa ctors) and landscape factors? 15 a. What deposition function is appropriat e to use for the purpose of relating an 16 amount of nitrogen and/or sulfur deposition in sensitive ecosystems to ambient 17 concentrations of atmospheric reactiv e nitrogen, including oxides and reduced 18 forms, and/or sulfur? What are the importa nt variables in such a function? What 19 are appropriate spatial and temporal scales to use in specifying such variables? 20 Based on the conceptual framework for the st ructure of the ecologi cally relevant multi21 pollutant standards, we then address in Chapter 6 the elements of the standard needed to develop 22 options for consideration by the Administrator. Development of these options will focus on 23 addressing the following questions: 24 1. (CPE 2.1) What ecological indicators ar e appropriate to use for the purpose of 25 developing an alternative standard for the va rious ecological effects assessed in this 26
review? 27 2. (CPE 5) What indicators of oxides of nitr ogen and sulfur are a ppropriate to use for 28 the purpose of determining whether the resultan t deposition is within the target values 29 needed to achieve the desired degree of pr otection? What averaging times and forms 30 are appropriate to consider? 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 20 3. (CPE 4) What approaches are available to specify non-atmospheric elements of the 1 standard, e.g. weathering ra tes? Are there approaches that can simplify the structure 2 of the standard by using disc rete representations (bins) of continuous variables? 3 4. What are the available approaches for account ing for reduced N in the structure of the 4
standard? 5 5. What is the most appropriate form for the standards to reflect the relationships 6
between ambient NO x and SO x , acidifying deposition, and th e ecological indicator for 7
acidification? 8 Several follow-up questions derive from our assessment of options for specifying the 9 elements of a multipollutant standard. In Chapter 7, we address the questions: 10
1. To what extent would a sta ndard specifically defined to protect against one ecological 11 effect (i.e., aquatic acidifi cation) likely provide protect ion from other relevant 12 ecological effects? 13 2. What are the available approaches for combining multiple indicators into a single 14 standard, e.g. using nitrogen eff ects to bound the tradeoff curve for NO x /SO x for 15 aquatic acidification effects 16 3. What are the available approaches to in tegrate potential standards for aquatic and 17 terrestrial acidification and/or aquatic and terrestrial N enrichment? 18 In Chapter 8, we plan to address in the second draft policy assessment issues regarding 19 the adequacy of the current definitions of oxide s of nitrogen and sulfur in specifying standards 20 for protection against effects associated with de position of nitrogen and sulfur. This discussion 21 will be focused on the following questions: 22
1. To what extent are effects associated w ith atmospheric nitrogen deposition reduced 23
when NO x related deposition is reduced? 24 2. To what extent can appropriate protec tion from relevant ecological effects be 25 achieved by specifying indicators of atmo spheric reactive nitrogen and sulfur 26 compounds in terms of gas- and particle-pha se nitrogen oxides and/ or sulfur oxides? 27
3. To what extent does the available inform ation on welfare effects provide a basis for 28 considering expanding the list of criteria pollutants to include all reactive nitrogen or 29 gas-phase ammonia? What are the relative merits of listing total reactive nitrogen 30 versus gas phase ammonia for protection of public welfare effects? 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 21 We conclude with a discussion of a range of options to consider in selecting pollutant 1 indicators, averaging times, forms, and levels for the secondary NO x and SO x standards, 2 including a discussion of staff initial conclusions on what levels of the standard for NO x and SO x 3 would be requisite to protect pub lic welfare against adverse ecologi cal effects. This discussion is 4 informed by a consideration of the role of ecosy stem services in helping to characterize what 5 adversity to public welfare, fo cused on the following questions: 6 1. (CPE 5) What are the risks of ecosystem service impairment under alternative levels 7 of potential standards for NO x and SO x ? 8 2. (CPE 5) To what extent can information about ecosystem services be used to help 9 characterize the extent to which differing le vels of relevant ecological indicators 10 reflect impacts that can reasonably be j udged to be adverse from a public welfare 11 perspective? 12 3. (CPE 5) Are there relevant benchmarks fo r adversity to public welfare that can be 13
derived from other sources? 14 4. (CPE 5) Taking into consideration inform ation about ecosystem services and other 15 factors related to characterizing adversity to public welfare for the ecological effects 16 being assessed in this review, what is an appropriate range of levels of protection to 17 be achieved by alternat ive standards for the Agency to consider? 18

19Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 22 

### 2. KNOWN OR ANTICIPATED ECOLOGICAL EFFECTS 1
This chapter addresses Critical Policy Elem ent 1, evaluation of th e effects of ambient 2
NO x and SO x on ecosystems, and the relationship between those effects and the measure of dose 3 in the ecosystem, indicated by the depositional lo adings of N and S. In section 302(h) of the 4 Clean Air Act, welfare effects addressed by a secondary NAAQS include, but are not limited to, 5 “effects on soils, water, crops, vegetation, man-ma de materials, animals, wildlife, weather, 6 visibility and climate, damage to and deteriorat ion of property, and hazard s to transportation, as 7 well as effects on economic values and on person al comfort and well-being”. Of these welfare 8 effects categories, the effects of NO x and SO x on aquatic and terrestrial ecosystems, which 9 encompass soils, water, vegetation, wildlife, an d contribute to economic value and well-being, 10 are of most concern at concentrations typically occurring in the U.S. Direct effects of NO x and 11
SO x on vegetation are also discussed in this chap ter, and have been the focus of previous 12 reviews. However, for this review, the focus of this chapter is on th e known and anticipated 13 effects to ecosystems caused by exposure to NO x and SO x through deposition. 14 The information presented here is a concis e summary of conclusions from the ISA and 15 the REA. This chapter focuses on effects on sp ecific ecosystems with a brief discussion on 16
critical uncertainties associated with acidifica tion and nutrient enrichment; Chapter 3 evaluates 17
those effects within the context of alternative definitions of, including a ssessments of potential 18 impacts on ecosystem services. Effects are broadl y categorized into acidification and nutrient19 enrichment in the proceeding sections. This is background information intended to support new 20 approaches for the design of eco logically relevant secondary NO x and SO x standards which are 21 protective of U.S. ecosystems. More detailed information on the conceptual design and specific 22 options for the proposed standards are presented in Chapters 5 and 6 of this policy assessment 23 document. While we provide a summary of effects for all four of the primary effects categories, 24
we reiterate that the focus of this first draft policy assessment is on effects related to aquatic 25 acidification, without downplayi ng the potential significance of effects in other categories. 26Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 23 

### 2.1 ACIDIFICATION: EVIDENCE OF EFFECTS ON STRUCTURE AND 1 

### FUNCTION OF TERRESTR IAL AND FRESHWATER 2 

### ECOSYSTEMS 3 Sulfur oxides (SO x ) and nitrogen oxides (NO x ) compounds in the atmosphere undergo a 4 complex mix of reactions and thermodynamic pro cesses in gaseous, liquid, and solid phases to 5 form various acidic compounds. These acidic compounds are removed from the atmosphere 6 through deposition: either wet (e.g., rain, snow), fog or cloud, or dry (e.g., gases, particles). 7 Deposition of these acidic compounds leads to ecosystem exposure and effects on ecosystem 8 structure and function. Following de position, these compounds can, in some instances, leach out 9 of the soils in the form of sulfate (SO 4 2- ) and nitrate (NO 3 - ), leading to the acidification of surface 10 waters. The effects on ecosystems depend on the magnitude of deposition, as well as a host of 11 biogeochemical processes occurring in the soils and waterbodies ( REA 2.1 ). The chemical forms 12 of nitrogen that may contribute to acidifyi ng deposition include bot h oxidized and reduced 13 species. 14 When sulfur or nitrogen leaches from so ils to surface waters in the form of SO 4 2- or NO 3 - , 15 an equivalent amount of positive ca tions, or countercharge, is also transported. This maintains 16 electroneutrality. If the countercharge is pr ovided by base cations, such as calcium (Ca 2+ ), 17 magnesium (Mg 2+ ), sodium (Na + ), or potassium (K + ), rather than hydrogen (H + ) and dissolved 18 inorganic aluminum, the acidity of the soil water is neutralized, but the base saturation of the soil 19
is reduced. Continued SO 4 2

- or NO 3 - leaching can deplete the base cation supply of the soil. As 20 the base cations are removed, con tinued deposition and leaching of SO 4 2- and/or NO 3 - (with 21
H + and Al 3+ ) leads to acidification of soil water, an d by connection, surface water. A watershed’s 22 ability to neutralize acidic deposition is determined by a host of biogeophysical factors, including 23 base cation concentrations, weathering rates, up take by vegetation, rate of surface water flow, 24 soil depth, and bedrock. ( REA 2.1 ) Some of these factors such as vegetation and soil depth are 25 highly variable over small spatial scales, but othe rs vary over larger spa tial scales like geology. 26 For the purpose of a national secondary standard, th e most relevant characteristics are those that 27
are less variable over small scales. 28 Acidifying deposition of NO x and SO x and the chemical and biological responses 29 associated with these inputs vary temporally. Ch ronic or long-term deposi tion processes result in 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 24 increases of N and S and the associated effects of acidifying deposition in the time scale of years 1 to decades. Episodic or short term (i.e., hours or days) deposition refers to events in which the 2 level of the acid neutralizing cap acity (ANC) of a lake or str eam is temporarily lowered. In 3 aquatic ecosystems, short-term (i.e., hours or days ) episodic changes in water chemistry can have 4 significant biological effects. Episodic chemistry refers to conditions du ring precipitation or 5 snowmelt events when proportionately more draina ge water is routed th rough upper soil horizons 6 that tend to provide less acid neutralizing than was passing through deeper soil horizons ( REA 7
4.2 ). Some streams and lakes may have chronic or ba se flow chemistry that is suitable for aquatic 8 biota, but may be subject to occasional acidic episodes with lethal consequences. 9 The following summary is a concise overview of the known or anticipated effects caused 10 by acidification to ecosystems within the United St ates. Acidification aff ects both terrestrial and 11 freshwater aquatic ecosystems. Terrestrial and aquatic processes are often linked; therefore 12 responses to the following questions address bo th types of ecosystems unless otherwise noted. 13

2.1.1 What is the nature of acidification related ecosystem responses to reactive 14 nitrogen and/ sulfur deposition? 15 The ISA concluded that deposition of SO x , NO x , and NH x leads to the acidification of 16 ecosystems (EPA 2008). In the process of acidifi cation, geochemical com ponents of terrestrial 17 and freshwater aquatic ecosystems are altered in a way that leads to effects on biological 18 organisms. Deposition to terrestrial ecosystem s often moves through th e soil and eventually 19 leaches into adjacent water bodies, moreover depo sition to the land effects the water as well. 20
The scientific evidence is sufficient to infer a causal relationship between acidifying 21 deposition and effects on biogeochemist ry and biota in aquatic ecosystems (ISA 4.2.2 ). The 22 strongest evidence comes from studies of surface water chemistry in which acidic deposition is 23
observed to alter sulfate and nitr ate concentrations in surface wa ters, sum and surplus of base 24 cations, acid, ANC, inorganic aluminum, calcium, and surface water pH (ISA 3.2.3.2)

. 25
Consistent and coherent documentation from mul tiple studies on various species from all major 26 trophic levels of aquatic systems shows that geochemical alteration caused by acidification can 27 result in the loss of acid-sensitive biological species ( ISA 3.2.3.3 ). For example, in the 28 Adirondacks, of the 53 fish species recorded in Adirondack lakes about half (26 species) were 29 absent from lakes with pH below 6.0 (Baker et al., 1990b). Biological effects are linked to 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 25 changes in water chemistry in cluding ANC, inorganic Al, and pH. Decreases in ANC and pH 1 and increases in inorganic Al concentration c ontribute to declines in taxonomic richness of 2 zooplankton, macroinvertebrates, and fish, which often are sources of food for birds and other 3 animal species in the ecosystem, as well as se rving as a source of food and recreation for 4 humans. Acidification of ecosystems has been shown to disrupt food web dynamics causing 5 alteration to the diet, breedi ng distribution and re production of certain species of birds (ISA 6 4.2.2.2. and Table 3-9) . For example, breeding distribution of the common goldeneye 7 (Bucephala clangula) an insectivorous duck, may be affected by changes in acidifying deposition 8 (Longcore and Gill, 1993). Similarly, reduced prey diversity and quantity have been observed to 9 create feeding problems for nesting pairs of l oons on low-pH lakes in the Adirondacks (Parker 10 1988). 11 In terrestrial ecosystems, the evidence is sufficient to infer a causal relationship between 12 acidifying deposition and changes in biogeochemistry (ISA 4.2.1.1). The strongest evidence 13 comes from studies of forested ecosystems, with supportive information on other plant 14 communities, including shrubs and lichens ( ISA 3.2.2.1. ). Three useful indicators of chemical 15 changes and acidification effects on terrestrial ecosystems, showing consistency and coherence 16 among multiple studies: soil base saturation, Al con centrations in soil water and soil C:N ratio 17 ( ISA 3.2.2.2 ). 18
In soils with base saturati on less than about 15 to 20% exchange ion chemistry is 19 dominated by Al (Reuss, 1983). Under this conditi on, responses to inputs of sulfuric acid and 20 nitric acid largely involve the release and mob ilization of inorganic Al through cation exchange. 21 The effect can be neutralized by weathering fr om geologic parent material or base cation 22 exchange. The Ca 2+ and Al in soils are strongly influenced by soil acidification and both have 23 been shown to have quantita tive links to tree health, including Al interference with Ca 2+ uptake 24 and Al toxicity to roots (Par ker et al., 1989; U.S. EPA, 2009) . Effects of n itrification and 25
associated acidification and cati on leaching have been consistently shown to occur only in soils 26
with a C:N ratio below about 20 to 25 (Aber et al., 2003; Ross et al., 2004). 27
Acidification has been shown to cause decreas ed growth and increase d susceptibility to 28 disease and injury in sensitive tree species. Red spruce ( Picea rubens ) dieback or decline has 29 been observed across high elevation areas in the Adirondack, Green and White mountains 30 (DeHayes et al., 1999). The frequency of freezing in jury to red spruce needles has increased over 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 26 the past 40 years, a period that coincided w ith increased emissions of S and N oxides and 1 increased acidifying deposition (DeHayes et al., 1999). Acidifying deposition may be 2 contributing to episodic dieback in Sugar maple ( Acer saccharum ) through depletion of nutrient 3 cations from marginal soils (Hor sley et al., 2000; Bailey et al., 2004). Grasslands are likely less 4
sensitive to acidification than forests (Blake et al ., 1999; Kocky and Wilson 2001). 5

2.1.2 What types of ecosystems are sensitive to such effects? In which ways are 6 these responses affected by atmospheric, ecological, and landscape factors? 7
The intersection between curre nt deposition loading, historic loading, and sensitivity 8 defines the ecological vulnerability to the e ffects of acidification. Fr eshwater aquatic and 9 terrestrial ecosystems are the ecosystem types whic h are most sensitive to acidification. The ISA 10 reports that the principal factor governing the se nsitivity of terrestrial a nd aquatic ecosystems to 11 acidification from sulfur and nitrogen deposit ion is geology (particularly surficial geology). 12 Geologic formations having low base cation supply generally unde rlie the watersheds of acid13
sensitive lakes and streams. Other factors that contribute to the sensitivity of so ils and surface 14 waters to acidifying depositi on include topography, soil chem istry, land use, and hydrologic 15 flowpath. Episodic and chronic acidi fication tends to occur at rela tively high elevation in areas 16 that have base-poor bedrock, hi gh relief, and shallow soils ( ISA 3.2.4.1 ). 17

2.1.3 What is the magnitude of ecosystem responses to acidifying deposition? 18 Terrestrial and aquatic ecosystems differ in their response to acidifying deposition. 19 Therefore the magnitude of ecosystem response is described separately for aquatic and terrestrial 20 ecosystems in the following sections. The magnitude of response refers to both the severity of 21 effects and the spatial extent of the U.S. which is affected. 22

2.1.3.1 Aquatic 23 Freshwater ecosystem surveys and monitoring in the eastern United States have been 24 conducted by many programs since the mid-1980s, including EPA’s Environmental Monitoring 25 and Assessment Program (EMAP), National Surface Water Survey (NSWS), Temporally 26 Integrated Monitoring of Ecosystems (TIME) (Stoddard, 1990), and Long-term Monitoring 27 (LTM) (Ford et al., 1993; Stoddard et al., 1996) programs. Based on analyses of surface water 28 data from these programs, New England, the Ad irondack Mountains, the Appalachian Mountains 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 27 (northern Appalachian Plateau and Ridge/Blue Ridge region), and the Upper Midwest contain 1 the most sensitive lakes and streams (i.e., ANC less than about 50 μ eq/L) since the 1980s. 2
Portions of northern Florida also contain ma ny acidic and low-ANC lakes and streams, although 3 the role of acidifying deposition in these areas is less clear. The western U.S. contains many of 4 the surface waters most sensitive to potential acid ification effects, but wi th the exception of the 5 Los Angeles Basin and surrounding areas, the levels of acidifyi ng deposition are low in most 6
areas. Therefore acidic surface waters are uncomm on in the western U.S., and the extent of 7
chronic surface water acidif ication that has occurred in that re gion to date has likely been very 8
limited (ISA 3.2.4.2 and REA 4.2.2). 9 There are a number of species including fis h, aquatic insects, other invertebrates and 10 algae that are sensitive to acidification and can not survive, compete, or reproduce in acidic 11 waters ( ISA 3.2.3.3 ). Decreases in ANC and pH have been shown to contribute to declines in 12 species richness and abundance of zooplankton, macroinvertebrate s, and fish (Keller and Gunn 13 1995; Schindler et al., 1985). Reduced growth rate s have been attributed to acid stress in a 14 number of fish species including Atlantic salmon ( Salmo salar ), Chinook salmon ( Oncorhynchus 15 tshawytscha ), lake trout ( Salvelinus namaycush ), rainbow trout ( Oncorhynchis mykiss ), brook 16 trout ( Salvelinus Fontinalis ), and brown trout (Salmo trutta ) (Baker et al., 1990). In response to 17 small to moderate changes in acidity, acid-sens itive species are often replaced by other more 18 acid-tolerant species, resulting in changes in community composition and richness. The effects of 19 acidification are continuous, with more species being affected at higher degrees of acidification. 20 At a point, typically a pH <4.5 and an ANC <0 μ eq/L, complete to near-complete loss of many 21 classes of organisms occur, including fish a nd aquatic insect populati ons, whereas others are 22 reduced to only a few acidophilic forms. These ch anges in species integrity are because energy 23 cost in maintaining physiologi cal homeostasis, growth, and reproduction is hi gh at low ANC 24 levels (Schreck, 1981, 1982; Wedemeger et al., 1990; REA appendix 2.3 ). Decreases in species 25
richness related to acidification have been obs erved in the Adirondack Mountains and Catskill 26 Mountains of New York (Baker et al., 1996), New England and Pe nnsylvania (Haines and Baker, 27 1986), and Virginia (Bulger et al., 2000). 28 From the sensitive areas identified by the ISA, further “case study” analyses on aquatic 29 ecosystems in the Adirondack Mountains and Shenandoah National Park were conducted to 30 better characterize ecological risk associated with acidification ( REA Chapter 4 ). 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 28 In the literature, ANC is the most widely used indicator of acid se nsitivity and has been 1 found in various studies to be the best single in dicator of the biological response and health of 2 aquatic communities in acid-sensi tive systems (Lien et al., 1992; Sullivan et al., 2006; ISA). In 3 the REA, surface water trends in SO 4 2- and NO 3 - concentrations and ANC levels were analyzed 4 to affirm the understanding that reductions in de position could influence th e risk of acidification. 5 ANC values were categorized according to thei r effects on biota, as shown in Figure 2-1. 6 Monitoring data from the EPA-administered TI ME/LTM and EMAP programs were assessed for 7 the years 1990 to 2006, and past, present, and futu re water quality levels were estimated by both 8 steady-state and dynamic biogeochemical models. 9
10

11 Figure 2-1. Ecological Effects Asso ciated with Alternative Levels of Acid 12 Neutralizing Capacity (ANC) 13 The analyses of the Adirondack Case Study Area indicated that although wet deposition 14
rates for SO 2 and NO x have been reduced since the mid-1990s , current concentrations are still 15 well above pre-acidification (1860) conditions. Modeling predicts NO 3 - and SO 4 2- are 17- and 5- 16Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 29 fold higher today, respectively. The estimated average ANC across the 44 lakes in the 1 Adirondack Case Study Area is 62.1 μ eq/L (± 15.7 μ eq/L); 78 % of all monitored lakes in the 2 Adirondack Case Study Area ha ve a current risk of Elevated , Severe , or Acute . Of the 78%, 31% 3 experience episodic acidification, and 18% are chronically acidic today ( REA 4.2.4.2 ). 4 Based on a deposition scenario that mainta ins current emission levels to 2020 and 2050, 5 the simulation forecast indicates no improvement in water quality in the Adirondack Case Study 6 Area. The percentage of lakes within the Elevated to Acute Concern classes remains the same in 7
2020 and 2050. 8

0 20 40 60 80 100 120 140

1850 1900 1950 2000 2050ANC Concentration(μeq/L)

9 Figure 2-2. Average NO 3 - concentrations (orange), SO 4 2- concentrations (red), 10 and ANC (blue) across the 44 lakes in the Adirondack Case Study Area modeled 11 using MAGIC for the period 1850 to 2050. 12Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 30 1 Figure 2-3 . ANC concentrations of preacidif ication (1860) and current (2006) 2 conditions based on hindcasts of 44 la kes in the Adirondack Case Study Area 3 modeled using MAGIC. [Note: in this ma p, the symbol for red is reversed and 4 should be < 0. The figure will be revised in the next draft.] 5

6Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 31 1 Figure 2-4. Critical loads of acidifying depositio n that each surface water location 2 can receive in the Adirondack Case Study Area while maintaining or exceeding 3 an ANC concentration of 50 μ eq/L based on 2002 data. Watersheds with critical 4 load values <100 meq/m 2 /yr (red and orange circles) are most sensitive to surface 5 water acidification, whereas wate rsheds with values >100 meq/m 2 /yr (yellow and 6 green circles) are the least sensitive sites. 7 It is important to note that st udies on fish species richness in the Adirondacks Case Study 8 Area demonstrated the effect of acidification; of the 53 fish species recorded in Adirondack Case 9 Study Area lakes, only 27 species were found in lakes with a pH <6.0. The 26 species missing 10 from lakes with a pH <6.0 include important recr eational species, such as Atlantic salmon, tiger 11 trout ( Salmo trutta X Salvelinus fontinalis ), redbreast sunfish ( Lepomis auritus ), bluegill 12 ( Lepomis macrochirus ), tiger musky ( Esox masquinongy X lucius ), walleye ( Sander vitreus ), 13 alewife ( Alosa pseudoharengus ), and kokanee ( Oncorhynchus nerka ) (Kretser et al., 1989), as 14 well as ecologically important minnows that ar e commonly eaten by sport fish. A survey of 15 1,469 lakes in the late 1980s found 346 lakes to be devoid of fish. Among lakes with fish, there 16 was a relationship between the number of fish species and lake pH, ranging from about one 17 species per lake for lakes having a pH <4.5 to a bout six species per lake for lakes having a pH 18Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 32 >6.5 (Driscoll et al., 2001; Kretser et al., 1989). In the Adirondacks, a positive relationship exists 1 between the pH and ANC in lakes and the numbe r of fish species present in those lakes ( ISA 2
3.2.3.4 ). 3 Since the mid-1990s, streams in the Shenandoah Case Study Area have shown slight 4
declines in NO 3 - and SO 4 2- concentrations in surface waters. Current concentrations are still 5 above pre-acidification (1860) conditions . MAGIC modeling predicts surface water 6
concentrations of NO 3 - and SO 4 2- are10- and 32-fold higher today, respectively. The estimated 7 average ANC across 60 streams in th e Shenandoah Case Study Area is 57.9 μ eq/L (± 4.5 μ eq/L). 8 55% of all monitored streams in the Shena ndoah Case Study Area have a current risk of 9
Elevated , Severe , or Acute . Of the 55%, 18% experience epis odic acidification, and 18% are 10 chronically acidic today ( REA 4.2.4.3 ) 11 Based on a deposition scenario that mainta ins current emission levels to 2020 and 2050, 12
the simulation forecast indicates that a large number of streams still have Elevated to Acute 13 problems with acidity. In f act, from 2006 to 2050, the percentage of streams with Acute Concern 14 increases by 5%, while the percentage of st reams in Moderate Concern decreases by 5%. 15 Biological effects of increased acidification documented in the Shenandoah Case Study 16
Area include a reduction in the condition fact or in Blacknose Dace (Dennis and Bulgar 1995, 17 Bulgar et al., 1999) and a decrea se in fish biodiversity associat ed with decreasing stream ANC 18 (Bulger et al., 1995; Dennis and Bulger, 1995; Dennis et al., 1995; MacAvoy and Bulger, 1995, 19 Bulgar et al., 1999). On average, the fish species richness is lo wer by one fish species for every 20
21 μ eq/L decrease in ANC in Shenandoah National Park streams ( ISA 3.2.3.4 ). 21

0 20 40 60 80 100 120

1850 1900 1950 2000 205 0
YearsANC Concentration(μeq/L)

2050

22 Figure 2-5. Average NO 3 - concentrations orange), SO 4 2- concentrations (red), and 23 ANC (blue) levels for the 60 stream s in the Shenandoah Case Study Area 24 modeled using MAGIC for the period 1850 to 2050. 25Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 33 1

2 Figure 2-6. ANC levels of 1860 (preacidification) and 2006 (current) conditions 3 based on hindcasts of 60 streams in the Shenandoah Case Study Area modeled 4 using MAGIC. 5Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 34 1 Figure 2-7. Critical loads of surface wate r acidity for an ANC of 50 μ eq/L for 2 Shenandoah Case Study Area streams. Each dot represents an estimated amount 3 of acidifying deposition (i.e., critical lo ad) that each stream’s watershed can 4 receive and still maintain a surface water ANC >50 μ eq/L. Watersheds with 5 critical load values <100 meq/m 2 /yr (red and orange circles) are most sensitive to 6 surface water acidification, whereas wa tersheds with values >100 meq/m 2 /yr 7 (yellow and green circles) ar e the least sensitive sites. 8 2.1.3.2 Terrestrial Acidification 9 The ISA identified a variety of indicators that can be used to measure the effects of 10
acidification in soils. Tree health has been linked to base cations (Bc) in soil (such as Ca 2+ , Mg 2+ 11 and potassium), as well as soil Al content. Tree species show similar sens itivities to Ca/Al and 12 Bc/Al soil solution ratios, theref ore these are good chemical indi cators because they directly 13 relate to the biological effects. Critical Bc/A l ratios for a large variet y of tree species ranged 14 from 0.2 to 0.8 (Sverdrup and Warfvinge, 1993, a me ta-data analysis of laboratory and field 15 studies). This range is similar to critical ratio s of Ca/Al. Plant toxic ity or nutrient antagonism 16 was reported to occur at Ca/Al ratios ranging from 0.2 to 2.5 (Cronan and Grigal, 1995; meta17 data assessment) ( REA pg 4-54, REA Appendix 5 ). 18Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 35 There has been no systematic national survey of terrestrial ecosystems to determine the 1 extent and distribution of terrestrial ecosystem sensitivity to the effects of acidifying deposition. 2 However, one preliminary national evaluation esti mated that ~15% of forest ecosystems in the 3
U.S. exceeds the estimated critical load base d on soil chemistry for S and N deposition by >250 4 eq ha -1 yr -1 (McNulty et al., 2007). Forests of the Adirondack Mountains of New York, Green 5 Mountains of Vermont, White Mountains of New Hampshire, the Allegheny Plateau of 6 Pennsylvania, and high-elevation forest ecosystems in the southern Appalachians are the regions 7
most sensitive to terrestrial acidifi cation effects from acidifying deposition (ISA 3.2.4.2). While 8 studies show some recovery of surface waters , there are widespread measurements of ongoing 9 depletion of exchangeable base ca tions in forest soils in the northeastern U.S. despite recent 10 decreases in acidifying deposition, indicating a slow recovery time. 11 In the REA, a critical load analysis was pe rformed for sugar maple and red spruce forests 12 in the eastern United States by using Bc/Al ratio in acidified forest soils as an indicator to assess 13 the impact of nitrogen and sulfur deposition on tree health. These are the two most commonly 14 studied species in North America for effects of acidification. At a Bc/Al ratio of 1.2, red spruce 15 growth can be reduced by 20%. Sugar maple grow th can be reduced by 20% at a Bc/Al ratio of 16 0.6. The REA analysis determined the health of at least a portion of the sugar maple and red 17 spruce growing in the United States may have be en compromised with acidifying total nitrogen 18 and sulfur deposition in 2002. Specifically, total n itrogen and sulfur deposition levels exceeded 19 three selected critical loads for tree growth in 3% to 75% of all s ugar maple plots across 24 20 states. For Red Spruce, total nitrog en and sulfur deposition levels ex ceeded three selected critical 21 loads in 3% to 36% of all red spruce plots across eight states. 22

2.1.4 What are the key uncertainties associated with acidification? 23 There are different levels of uncertainty asso ciated with relationships between deposition, 24 ecological effects and ecological indicators. In Chapter 7 of the REA, key uncertainties are 25 characterized as follows to evaluate the strength of the scientific basi s for setting a national 26 standard to protect ag ainst a given effect ( REA 7.0 ): 27

 Data Availability: high, medium or low quality. This criterion is based on the availability 28 and robustness of data sets, monitoring networ ks, availability of data that allows for 29 extrapolation to larger assessment areas , and input parameters for modeling and 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 36 developing the ecological effect function. The sc ientific basis for th e ecological indicator 1 selected is also incorporated into this criterion. 2

 Modeling Approach: high, fairly high, intermediate, or low confidence. This value is 3 based on the strengths and limitations of the models used in the analysis and how accepted 4 they are by the scientific community fo r their application in this analysis. 5

 Ecological Effect Function: high, fairly high, intermediate, or low confidence. This 6 ranking is based on how well th e ecological effect function describes the relationship 7 between atmospheric deposition and the ecological indicator of an effect. 8

2.1.4.1 Aquatic Acidification 9
The REA concludes that the availabl e data are robust and considered high quality . There 10 is high confidence about the use of these data and their value for extr apolating to a larger 11 regional population of lakes. The EPA TIME/LTM network represents a source of long-term, 12 representative sampling. Data on sulfate concentr ations, nitrate concentrations and ANC from 13 1990 to 2006 used for this analysis as well as EPA EMAP and REMAP surveys, provide 14
considerable data on surface water trends. 15
There is fairly high confidence associated with modeli ng and input parameters. 16 Uncertainties in water quality estimates (.i.e. ANC) from MAGIC was derived from multiple site 17 calibrations. The 95% confidence interval for pre-acidification of lakes was an average of 15 18

μ eq/L difference in ANC concentrations or 10% and 8 μ eq/L or 5% for streams ( REA 7.1.2 ) The 19
use of the critical load model used to estimate aquatic critical load s is limited by the uncertainties 20 associated with runoff and surface water measurements and in estimating the catchment supply 21 of base cations from the weathering of bedroc k and soils (McNulty et al., 2007). To propagate 22 uncertainty in the model parameters, Monte Carl o methods were employed to develop an inverse 23
function of exceedences. There is high confidence associated with the ecological effect function 24 developed for aquatic acidification. In calculati ng the ANC function, the depositional load for N 25 or S is fixed by the deposition of the other, so deposition for either will never be zero ( Figure 26
7.1-6 REA ). 27

Terrestrial Acidification 28 The available data used to qua ntify the targeted effect of terrestrial acidification are 29
robust and considered high quality . The USFS-Kane experimental forest and significant amounts 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 37 of research work in the Allegheny Plateau have produced extensive, p eer-reviewed datasets. A 1 meta-analysis of laboratory studies showed that tree growth was reduced by 20% relative to 2
controls for BC/Al ratios (ISA 7.2.1 and Figure 7.2-1 ). Sugar maple and red spruce were the 3 focus of the REA since they are demonstr ated to be negatively affected by Ca2 + depletion and 4 high concentrations of available Al, and occur in areas that receive high acidifying deposition, 5 There is high confidence about the use of the RE A terrestrial acidificati on data and their value 6 for extrapolating to a larger regional population of forests. 7
There is high confidence associated with the models, i nput parameters, and assessment of 8 uncertainty used in the case study for terrestr ial acidification. The Si mple Mass Balance (SMB) 9 model, a commonly used and widely applied approach for estimating critical loads, was used in 10 the REA analysis ( ISA 7.2.2 ). There is fairly high confidence associated with the ecological 11 effect function developed for terrestrial acidification ( REA 7.2.3 ). 12



### 2.2 NITROGEN ENRICHMENT: EVIDENCE OF EFFECTS ON 13 

### STRUCTURE AND FUNCTION OF TERRESTRIAL AND 14 

### FRESHWATER ECOSYSTEMS 15 The following summary is a concise overview of the known or anticipated effects caused 16 by nitrogen nutrient enrichment to ecosystems within the United States. Nutrient-enrichment 17 affects terrestrial, freshwater and estuarine ecosystems. Nitrogen deposition is often the main 18 source of anthropogenic nitrogen in terrestrial and freshwater ecos ystems. In contrast, nitrogen 19 deposition often contributes to nitrogen-enrichmen t effects in estuaries, but does not drive the 20 effects. Both oxides of nitrogen a nd reduced forms of nitrogen, e.g. NH x , contribute to nitrogen 21 deposition. For the most part, nitrogen eff ects on ecosystems do not depend on whether the 22 nitrogen is in oxidized or reduced form. Thus, this summary focuses on the effects of nitrogen 23 deposition in total. We address the issue of incorporating the re lative contributions of oxidized 24 and reduced nitrogen into the st andards in Chapters 5, 6, and 8. 25

2.2.1 What is the nature of terrestrial and freshwater ecosystem responses to 26 reactive nitrogen and/ sulfur deposition? 27 The ISA found that deposition of nitrogen, including NO x and NH x leads to the nitrogen 28 enrichment of ecosystems (EPA 2008). In the process of nitrogen enrichment, geochemical 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 38 components of terrestrial and freshwater aquatic ecosystems are altered in a way that leads to 1 effects on biological organisms. 2
The evidence is sufficient to infer a causal relationship between N deposition and the 3 alteration of biogeochemical cycl ing in terrestrial ecosystems ( ISA 4.3.1.1 and 3.3.2.1 ). This is 4 supported by numerous observational, depositio n gradient and field addition experiments. 5 Stoddard (1994) identified the leaching of NO 3 - in soil drainage wate rs and the export of NO 3 - in 6 steam water as two of the primary indictors of N enrichment. Several N-addition studies indicate 7
that NO 3 - leaching is induced by chronic additional of N (Edwards et al., 2002b; Kahl et al., 8 1999; Peterjohn et al., 1996; Nort on et al., 1999). Aber et al. (2003) found that surface water 9
NO 3 - concentrations exceeded 1 μ eq/L in watersheds receiving about 9 to 13 kg N/ha/yr of 10 atmospheric N deposition. N deposition disrupts the nutrient balance of ecosystems with 11 numerous biogeochemical effects. The chemical i ndicators that are typi cally measured include 12
NO 3 − leaching, C:N ratio, N mineralization, nitrifi cation, denitrification, foliar N concentration, 13
and soil water NO 3 − and NH 4 + concentrations. Note that N saturation (N leaching from 14 ecosystems) does not need to occur to cau se effects. Substantial leaching of NO 3 − from forest 15 soils to stream water can acidify downstream waters , leading to effects desc ribed in the previous 16 section on aquatic acidification. Due to the comp lexity of interactions between the N and C 17 cycling, the effects of N on C budge ts (quantified input and output of C to the ecosystem) are 18 variable. Regional trends in net ecosystem pr oductivity (NEP) of forests (not managed for 19 silviculture) have been estimat ed through models based on gradie nt studies and meta-analysis. 20 Atmospheric N deposition has been shown to cause increased litter accumulation and carbon 21 storage in above-ground woody biomass. In the West, this has lead to increased su sceptibility to 22 more severe fires. Less is known regarding the effects of N deposition on C budgets of non23 forest ecosystems. 24
The evidence is sufficient to infer a causal relationship between N deposition on the 25 alteration of species richness, species composition and biodiversit y in terrestrial ecosystems ( ISA 26
4.3.1.2 ). The most sensitive terrestrial taxa are lich ens. Empirical evidence indicates that lichens 27 in the U.S. are affected by deposition levels as low as 3 kg N/ha/yr. Alpine ecosystems are also 28 sensitive to N deposition, changes in an individual species (Carex rupestris) were estimated to 29 occur at deposition levels near 4 kg /ha/yr and modeling indicates that deposition levels near 10 30 kg N/ha/yr alter plant community assemblages. In several grassland ecosystems, reduced species 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 39 diversity and an increase in non-na tive, invasive species are associ ated with N deposition (Clark 1 and Tillman, 2008; Schwinning et al., 2005). 2 In freshwater ecosystems, the evidence is sufficient to infer a causal relationship between 3 N deposition and the alteration of biogeochemical cycling in freshwater aquatic ecosystems ( ISA 4
3.3.2.3 ). N deposition is the main source of N enri chment to headwater streams, lower order 5 streams and high elevation lakes. The most co mmon chemical indicators that were studied 6
included NO 3 − and dissolved inorganic nitrogen (DIN) con centration in surface waters as well as 7
Chl a :total P ratio. Elevated surface water NO 3 − concentrations occur in both the eastern and 8 western U.S. Bergstrom and Jansson (2006) report a significant correla tion between N deposition 9 and lake biogeochemistry by identifying a correl ation between wet deposi tion and [DIN] and Chl 10

a : Total P. Recent evidence provides examples of lakes and streams that are limited by N and 11 show signs of eutrophication in response to N addition. 12
The evidence is sufficient to infer a causal relationship between N deposition and the 13 alteration of species richness, species composition and biodiversity in freshwater aquatic 14 ecosystems ( ISA 3.3.5.3 ). Increased N deposition can cause a shift in community composition 15 and reduce algal biodiversit y, especially in sensitive oligotrophic lakes. 16

2.2.2 What types of ecosystems are sensit ive to such effect s? How are these 17 responses affected by atmospheric, ecological, and landscape factors 18 The numerous ecosystem types that occur ac ross the U.S. have a broad range of 19 sensitivity to N deposition. Organisms in their natural environment are commonly adapted to a 20 specific regime of nutrient availabi lity. Change in the availability of one important nutrient, such 21 as N, may result in imbalance in ecological stoi chiometry, with effects on ecosystem processes, 22 structure and function (Sterner and Elser, 2002). In general, N deposition to terrestrial 23 ecosystems causes accelerated gr owth rates in some species, which may lead to altered 24 competitive interactions among species and nut rient imbalances, ultimately affecting 25 biodiversity. The onset of these effects occurs wi th N deposition levels as low as 3 kg N/ha/yr in 26 sensitive terrestrial ecosystems. In aquatic ecosy stems, N that is both leached from the soil and 27 directly deposited can pollute surface water. Th is causes alteration of the diatom community at 28 levels as low as 1.5 kg N/ha/yr in sensitive freshwater ecosystems. 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 40 The degree of ecosystem effects lies at the intersection of N loading and N-sensitivity. N1 sensitivity is predominately driven by the de gree to which growth is limited by nitrogen 2 availability. Grasslands in the western United States are typically N-limited ecosystems 3 dominated by a diverse mix of perennial forb s and grass species (Clark and Tilman, 2008; 4 Suding et al., 2005). A meta-a nalysis by Lebauer and Tresed er (2008) indicated that N 5 fertilization increased aboveground growth in all non-forest ecosys tems except for deserts. In 6 other words, almost all terrestrial ecosystems are N-limited and will be altered by the addition of 7 anthropogenic nitrogen. Likewise, a fr eshwater lake or stream must be N-limited to be sensitive 8 to N-mediated eutrophication. There are many exampl es of fresh waters that are N-limited or N 9 and P co-limited ( ISA 3.3.3.2 ). In a meta-analysis that includ ed 653 datasets, Elser et al. (2007) 10 found that N-limitation occurred as frequently as P-limitation in freshwater ecosystems. 11 Additional factors that govern the sensitivity of ecosystems to nutrient enrichment from N 12 deposition include rates and form of N depos ition, elevation, climate, species composition, 13 length of growing season, a nd soil N retention capacity. ( ISA 4.3 ). Less is known about the 14
extent and distribution of the terr estrial ecosystems in the U.S. that are most sensitive to the 15
effects of nutrient enrichment from atmos pheric N deposition compared to acidification. 16

2.2.3 What is the magnitude of ecosystem responses to nitrogen deposition? 17

2.2.3.1 Terrestrial 18
Little is known about the full extent and dist ribution of the terrestrial ecosystems in the 19 U.S. that are most sensitive to impacts cau sed by nutrient enrichment from atmospheric N 20 deposition. As previously state d, most terrestrial ecosystems ar e N-limited, therefore they are 21 sensitive to perturbation cause d by N additions (LeBauer and Tr eseder, 2008). Effects are most 22 likely to occur where areas of relatively high atmospheric N deposition intersect with N-limited 23 plant communities. The alpine eco systems of the Colorado Front Range, chaparral watersheds of 24 the Sierra Nevada, lichen and vascular plant communities in the San Bernardino Mountains and 25 the Pacific Northwest, and the southern Calif ornia coastal sage scrub (CSS) community are 26 among the most sensitive terrestrial ecosystem s. There is growing evidence that existing 27 grassland ecosystems in the western United Stat es are being altered by elevated levels of N 28 inputs, including inputs from atmospheric depos ition (Clark and Tilman, 2008; Suding et al., 29 2005). 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 41 In the eastern U.S., the degree of N satura tion of the terrestrial ecosystem is often 1 assessed in terms of the degree of NO 3 − leaching from watershed soils into ground water or 2 surface water. Stoddard (1994) estimated the number of surface waters at different stages of 3 saturation across several regions in the eastern U.S. Of the 85 nor theastern watersheds examined 4 60% were in Stage 1 or Stage 2 of N saturation on a scale of 0 (background or pretreatment) to 3 5 (visible decline). Of the northeastern sites for wh ich adequate data were available for assessment, 6 those in Stage 1 or 2 were most prevalent in the Adirondack and Catskill Mountains. Effects on 7 individual plant species have not been well st udied in the U.S. More is known about the 8 sensitivity of particular plant communities. Base d largely on results obtained in more extensive 9 studies conducted in Europe, it is expected that the more sensitive terrestrial ecosystems include 10 hardwood forests, alpine meadows, arid a nd semi-arid lands, and grassland ecosystems ( ISA 11
3.8.2 ). 12 The REA used published research results ( REA 5.3.1 and ISA Table 4.4 ) to identify 13 meaningful ecological benchmarks associated wi th different levels of atmospheric nitrogen 14 deposition. These are given by figure 2-8. The sensit ive areas and ecological indicators identified 15 by the ISA were analyzed further in the REA to create a national map that illustrates effects 16 observed from ambient and experimental atmosp heric nitrogen deposition loads in relation to 17 CMAQ 2002 modeling results and NADP monitoring data. This map, reproduced in Figure 2-9, 18 depicts the sites where empirical effects of terrestrial nutrient en richment have been observed 19 and site proximity to elevated atmospheric N deposition. 20
21Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 42 1 Figure 2-8. Benchmarks of atmospheric nitrogen deposition for several 2 ecosystem indicators with the inclusion of the diatom changes in the Rocky 3 Mountain lakes (REA 5.3.1.2) 4Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 43 1. Nitrogen enrichment or eutrophication of lakes (Loc h Vale, CO: 0.5 to1.5 kg/ha/yr; Niwot Ridge, CO: 4.71 kg/ha/yr) 2. Alpine lakes increase shift in diatom species (Rocky Mountains, CO: 2 kg/ha/yr) 3. Alpine meadows’ elevated NO 3 - levels in runoff (Colorado Front Range: 20, 40, 60 kg/ha/yr) 4. Alpine meadows’ shift toward hairgrass (Niwot Ridge, CO: 25 kg/ha/yr) 5. Nitrogen enrichment or nitrogen saturation (e.g., soil and foliar nitrogen concentration) (eastern slope of Rocky Mountains: 1.2, 3.6 kg/ha/yr; Fraser Forest, CO: 3.2 to 5.5 kg/ha/yr) 6. Increased nitrogen mineralization rates and nitrif ication (Loch Vale, CO (spruce): 1.7 kg/ha/yr) 7. Alpine tundra with increased plant foliage and decr eased species richness (Niwot Ridge, CO: 50 kg/ha/yr) 8. Nitrogen saturation, high NO 3 - in streamwater, soil, leaves; high nitric oxide (NO) emissions (Los Angeles, CA, air basin: saturation at 24 to 25 kg/ha/yr (dry) and at 0.8 to 45 kg/ha/yr (wet); northeastern U.S.: 3.3 to 12.7 kg/ha/yr) 9. Nitrogen saturation, high NO 3 - in streamwater (San Bernardino Mountains , CA (coniferous): 2.9 and 18.8 kg/ha/yr) 10. NO 3 - leaching (New England; Adirondack lakes: 8 to10 kg/ha/yr) 11. Nitrogen saturation, high dissolved inorganic nitrogen (San Bernardino Mountains, San Gabriel Mountains, CA, chaparral, hardwood, coniferous): 11 to 40 kg/ha/yr) 12. Increased tree mortality and beetle activity (San Be rnardino Mountains, CA (Ponderosa): 8 and 82 kg/ha/yr) 13. Enhanced growth of black cherry and yellow poplar; po ssible decline in red maple vigor; increased foliar nitrogen (Fernow Forest, WV: 35.5 kg/ha/yr) 14. Impacts on lichen communities (California MCF: 3. 1 kg/ha/yr; Columbia R. Gorge, OR/WA: 11/5 to 25.4) 15. Evidence that threatened and endangered species impacted San Francisco Bay, CA (checkerspot butterfly and serpentinitic grass invasion: 10 to15 kg/ha/yr; Jasper Ridge, CA: 70 kg/ha/yr) 16. Decreased diversity of mycorrhizal comm unities (Southern California: ~10 kg/ha/yr) 17. Decreased abundance of CSS (Southern California: 3.3 kg/ha/yr) 18. Loss of grasslands (Cedar Creek, MN: 5.3 [1.3 to 9.8] kg/ha/yr) 19. Decrease in abundance of desert creosote bush, incr ease in nonnative grasses (Mojave Desert and Chihuahuan Desert, CA: 1.7 kg/ha/yr and up) 20. Decrease in pitcher plant population growth rate (Hawley Bog, MA and Molly Bog, VA: 10 to14 kg/ha/yr) Figure 2-9 (from REA figure 5.3-9). Observed effects from ambient and 1 experimental atmospheric nitrogen depos ition loads in relation to using CMAQ 2 2002 modeling results and NADP monitoring da ta. Citations for effect results are 3 from the ISA, Table 4.4 (U.S. EPA, 2008). 4Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 44 Based on information in the ISA and initial analysis in the REA, further case study 1 analyses on terrestrial nutrie nt enrichment of ecosystems were developed for the CCS 2 community and Mixed Conifer Forest (MCF) (EPA 2009). Geographic information systems 3 (GIS) analysis supported a qualita tive review of past field re search to identify ecological 4 benchmarks associated with CSS and mycorrh izal communities, as well as MCF’s nutrient5 sensitive acidophyte lichen communities, fine-ro ot biomass in Ponderosa pine, and leached 6 nitrate in receiving waters. 7 The ecological benchmarks that were identified for the CSS and the MCF are included in 8 the suite of benchmarks identified in the ISA ( ISA 3.3 ). There are sufficient data to confidently 9 relate the ecological effect to a loading of atmospheric nitr ogen. For the CSS community, the 10 following ecological benchmarks were identified: 11

 3.3 kg N/ha/yr – the amount of nitrogen uptake by a vigorous stand of CSS; above this 12 level, nitrogen may no longer be limiting 13

 10 kg N/ha/yr – mycorrhizal community changes 14 For the MCF community, the following ecological benchmarks were identified: 15

 3.1 kg N/ha/yr – shift from sensitiv e to tolerant lichen species 16

 5.2 kg N/ha/yr – dominance of the tolerant lichen species 17

 10.2 kg N/ha/yr – loss of sensitive lichen species 18

 17 kg N/ha/yr – leaching of nitrate into streams. 19 These benchmarks, ranging from 3.1 to 17 kg N/ha/yr, were compared to 2002 20 CMAQ/NADP data to discern a ny associations between atmos pheric deposition and changing 21 communities. Evidence supports the finding that nitrogen alters CSS and MCF. Key findings 22 include the following: 2002 CMAQ/NADP nitrogen de position data show that the 3.3 kg N/ha/yr 23
benchmark has been exceeded in more than 93% of CSS areas (654,048 ha). These deposition 24 levels are a driving force in the degradati on of CSS communities. Although CSS decline has 25 been observed in the absence of fire, the contri butions of deposition and fire to the CSS decline 26 require further research. CSS is fragment ed into many small parcels, and the 2002 27 CMAQ/NADP 12-km grid data are not fine eno ugh to fully validate th e relationship between 28 CSS distribution, nitrogen deposition, and fi re. 2002 CMAQ/NADP nitrogen deposition data 29 exceeds the 3.1 kg N/ha/yr benchmark in more than 38% (1,099,133 ha) of MCF areas, and 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 45 nitrate leaching has been observed in surface wa ters. Ozone effects confound nitrogen effects on 1 MCF acidophyte lichen, and the inte rrelationship between fire and nitrogen cycling requires 2
additional research. 3

2.2.3.2 Freshwater 4 The magnitude of ecosystem response may be thought of on two time scales, current 5 conditions and how ecosystems have been altere d since the onset of an thropogenic N deposition. 6 As noted previously, Elser et al. (2008) found that N-limitation occurs as frequently as P7 limitation in freshwater ecosystems ( ISA 3.3.3.2 ). Recently, a comprehensive study of available 8 data from the northern hemisphere surveys of lakes along gradients of N deposition show 9 increased inorganic N concentration and producti vity to be correlated with atmospheric N 10 deposition (Bergström and Jansson 2006). The results are unequivocal evidence of N limitation 11 in lakes with low ambient inputs of N, and in creased N concentrations in lakes receiving N 12 solely from atmospheric N deposition (Bergström and Jansson, 2006). These authors suggested 13 that most lakes in the northern hemisphere may have originally been N-limited, and that 14 atmospheric N deposition has changed the balance of N and P in lakes. 15 Available data suggest that th e increases in total N deposition do not have to be large to 16 elicit an ecological effect. For ex ample, a hindcasting exercise determined that the change in 17 Rocky Mountain National Park lake algae that occurred betw een 1850 and 1964 was associated 18 with an increase in wet N deposition that was only about 1.5 kg N/ha (Baron, 2006). Similar 19 changes inferred from lake sediment cores of the Beartooth Mountains of Wyoming also 20 occurred at about 1.5 kg N/ha deposition (Sar os et al., 2003). Pre- industrial inorganic N 21 deposition is estimated to have been only 0.1 to 0.7 kg N/ha based on measurements from remote 22 parts of the world (Galloway et al., 1995; Holland et al., 1999) . In the western U.S., pre23 industrial, or background, inorganic N depositio n was estimated by (Holland et al., 1999) to 24 range from 0.4 to 0.7 kg/ha/yr. 25 Eutrophication effects from N deposition are most likely to be manifested in undisturbed, 26
low nutrient surface waters such as those found in the higher elevat ion areas of the western U.S. 27 The most severe eutrophication from N deposition effects is expected downwind of major urban 28 and agricultural centers. High concentr ations of lake or streamwater NO3

− , indicative of 29 ecosystem saturation, have been found at a variet y of locations throughout the U.S., including the 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 46 San Bernardino and San Gabriel Mo untains within the Los Angeles Air Basin (Fenn et al., 1996), 1 the Front Range of Colorado (Baron et al., 1994 ; Williams et al., 1996), the Allegheny mountains 2 of West Virginia (Gilliam et al., 1996), the Catskill Mountains of New York (Murdoch and 3 Stoddard, 1992; Stoddard, 1994), the Adirondack M ountains of New York (Wigington et al., 4 1996), and the Great Smoky Mountains in Tennessee (Cook et al., 1994) ( ISA 3.3.8 ). 5

2.2.3.3 Nitrogen Enrichment: Evidence of Effects on Estuaries 6
In contrast to terrestrial and freshwater systems, atmospheric N load to estuaries 7
contributes to the total load but does not necessar ily drive the effects. In estuaries, N-loading 8 from multiple anthropogenic and non-anthropogenic pathways leads to water quality 9 deterioration, resulting in numerous effects including hypoxic zones, species mortality, changes 10 in community composition and harmful algal bloo ms that are indicative of eutrophication. The 11 following summary is a concise overview of th e known or anticipated effects of nitrogen 12
enrichment on estuaries within the United States. 13
2.2.3.3.1 What is the nature of estuary responses to reactive nitrogen andsulfur 14 deposition? 15 In the ISA, the evidence is sufficient to infer a causal relationship between Nr deposition 16 and the biogeochemical cycling of N and C in estuaries ( ISA 4.3.4.1 and 3.3.2.3 ). In general, 17 estuaries tend to be nitrogen-limited, and many cu rrently receive high levels of nitrogen input 18 from human activities ( REA 5.1.1 ). It is unknown if atmospheric deposition alone is sufficient to 19 cause eutrophication, however, th e contribution of atmospheric nitrogen deposition to total 20 nitrogen load is calculated for some estuaries an d can be >40% ( REA 5.1.1 ). 21
The evidence is sufficient to infer a causal relationship between N deposition and the 22 alteration of species richness, species composition and biodiversity in estuarine ecosystems ( ISA 23
4.3.4.2 and 3.3.5.4 ). Atmospheric and non-atmospheric sour ces of N contribute to increased 24 phytoplankton and algal productivity, leading to eutrophication. Sh ifts in community 25 composition, reduced hypolimnetic DO, reduced biodiversity, and mortality of submerged 26 aquatic vegetation are associated with incr eased N deposition in estuarine systems. 27Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 47 2.2.3.3.2 What types of ecosystems are sensit ive to such effects? How are these 1 responses affected by atmospheric, ecological, and landscape factors? 2 Because the productivity of estuarine and near shore marine ecosystems is generally 3 limited by the availability of N, they are susceptible to the eutr ophication effect of N deposition 4 ( ISA 4.3.4.1 ). A recent national assessment of eutrophi c conditions in estuaries found the most 5 eutrophic estuaries were generally those that ha d large watershed-to-estuarine surface area, high 6 human population density, high rain fall and runoff, low dilution, and low flushing rates (Bricker 7 et al., 2007). In the REA, the National Oceanic and Atmospheric Administration’s (NOAA) 8 National Estuarine Eutrophication Assessmen t (NEEA) assessment tool, Assessment of 9 Estuarine Tropic Status (ASSETS) categorical Eu trophication Index (EI) (Bricker et al., 2007) 10 was used to evaluate eutrophication due to atmos pheric loading of nitrog en. ASSETS EI is an 11 estimation of the likelihood that an estuary is experiencing eutrophicat ion or will experience 12 eutrophication based on five eco logical indicators: chlorophyll a , macroalgae, dissolved oxygen, 13 nuisance/toxic algal blooms and submerged aqua tic vegetation (SAV) (Bricker et al., 2007). 14 In the REA, two regions were selected fo r case study analysis using ASSETS EI, the 15 Chesapeake Bay and Pamlico Sound. Both regi ons received an ASSETS EI rating of Bad 16 indicating that the estuary had m oderate to high pressure due to overall human influence and a 17 moderate high to high eutrophic condition ( REA 5.2.4.1 and 5.2.4.2 ). These results were then 18 considered with SPAtially Referenced Regre ssion (SPARROW) modeling to develop a response 19 curve to examine the role of atmospheric nitroge n deposition in achieving desired reduction load. 20 To change the Neuse River Estuary’s EI score from Bad to Poor not only must 100% of the total 21 atmospheric nitrogen deposition be eliminated, but considerably more nitrogen from other 22 sources as well must be reduced (REA secti on 5.2.7.2). In the Potomac River estuary, a 78% 23 reduction of total nitrogen could move the EI score from Bad to Poor ( REA 5.2.7.1 ). The results 24 of this analysis indicated reductions in atmospheric deposition alone could not solve coastal 25 eutrophication problems due to multip le non-atmospheric nitrogen inputs ( REA 7.3.3 ). However, 26 by reducing atmospheric contributions, it may help avoid the need for more costly controls on 27 nitrogen from other sources. 28 In general, estuaries tend to be N-limited (Elser et al., 2008), and many currently receive 29 high levels of N input from human activities to cause eutrophication (H owarth et al., 1996; 30 Vitousek and Howarth, 1991). Atmospheric N loads to estuaries in the U.S. are estimated to 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 48 range from 2-8% for Guadalupe Bay, TX on the lo west end to as high as 72% for St Catherines1 Sapelo estuary, GA (Castro et al., 2003). The Chesapeake Bay is an example of a large, well2 studied and severely eutrophic estuar y that is calculated to receive as much as 30% of its total N 3 load from the atmosphere. 4
2.2.3.3.3 What is the magnitude of ecosyst em responses to eutrophication? 5 There is a scientific consensus that nitrogen-driven eutrophication in shallow estuaries 6 has increased over the past several decades and that the environmental degradation of coastal 7 ecosystems due to nitrogen, phosphorus, and other i nputs is now a widespr ead occurrence (Paerl 8 et al., 2001). For example, the frequency of phytopl ankton blooms and the ex tent and severity of 9 hypoxia have increased in the Chesapeake Bay (Off icer et al., 1984) and Pamlico estuaries in 10 North Carolina (Paerl et al., 1998) and along the c ontinental shelf adjacent to the Mississippi and 11 Atchafalaya rivers’ discharges to the Gulf of Mexico (E adie et al., 1994). 12 A recent national assessment of eutrophic cond itions in estuaries found that 65% of the 13 assessed systems had moderate to high overall eutrophic conditions and generally received the 14 greatest N loads from all sources, including atmos pheric and land-based sour ces (Bricker et al., 15 2007). Most eutrophic estuaries o ccurred in the mid-Atlantic regi on and the estuaries with the 16 lowest degree of eutrophication were in the Nort h Atlantic (Bricker et al., 2007). Other regions 17 had mixtures of low, moderate, and high degree of eutrophication ( ISA 4.3.4.3 ). 18 The mid-Atlantic region is the most heavily im pacted area in terms of moderate or high 19 loss of submerged aquatic vege tation due to eutrophication ( ISA 4.3.4.2 ). Submerged aquatic 20 vegetation is important to the qua lity of estuarine ecosystem hab itats because it provides habitat 21 for a variety of aquatic organisms, absorb s excess nutrients, and traps sediments ( ISA 4.3.4.2). It 22 is partly because many estuaries and near-coa stal marine waters are degraded by nutrient 23 enrichment that they are highly sensitive to potential negative impact s from nitrogen addition 24 from atmospheric deposition. 25

2.2.4 What are the key uncertainties as sociated with nutrient enrichment? 26 There are different levels of uncertainty asso ciated with relationships between deposition, 27 ecological effects and ecological in dicators. The criteria used in the REA to evaluate the degree 28 of confidence in the data, modeli ng and ecological effect function ar e detailed in Chapter 7 of the 29 REA and summarized in section 2.1.4 of this chapter ( REA 7.0 ). 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 49 Aquatic 1 The approach for assessing atmospheric contri butions to total nitrogen loading in the 2 REA, was to consider the main-stem river to an estuary (including the estuary) rather than an 3 entire estuary system or bay. The biological in dicators used in the NOAA ASSETS EI required 4 the evaluation of many national databases including the USGS NAWQA files, EPA’s STORET 5 database, NOAA’s Estuarine Drainage Areas data , and EPA’s water quality standards nutrient 6 criteria for rivers and lakes ( REA Appendix 6, Table 1.2.-1 ). Both the SPARROW modeling for 7 nitrogen loads and assessment of estuar y conditions under NOAA ASSETS EI, have been 8 applied on a national scale. The REA c oncludes that the available data are medium quality with 9 intermediate confidence about the use of these da ta and their values for ex trapolating to a larger 10 regional area ( REA 7.3.1 ). Intermediate confidence is associated with the modeling approach 11 using ASSETS EI and SPARROW. The REA states there is low confidence with the ecological 12 effect function due to the results of the analysis which indicated that re ductions in atmospheric 13 deposition alone could not solve coastal eu trophication problems due to multiple non14 atmospheric nitrogen inputs ( REA 7.3.3 ). 15

Terrestrial 16 Ecological thresholds are identified for CSS a nd MCF and these data are considered to be 17
of high quality , however, the ability to extrapolate these data to larger regional areas is limited 18 ( REA 7.4.1 ). No quantitative modeling was conducted or ecological effect function developed 19 for terrestrial nutrient enrichment reflecting the uncertainties associated with these depositional 20
effects. 21



### 2.3 WHAT ECOLOGICAL EFFECTS ARE ASSO CIATED WITH GAS22 

### PHASE NO X 

### AND SO X 

### ? 23 Acidifying deposition and nitrogen enrichme nt are the main focus of this policy 24 assessment; however, there are other known ecologi cal effects are attri buted to gas-phase NO x 25
and SO x . Acute and chronic exposures to gaseous pollutants such as sulfur dioxide (SO 2 ), 26 nitrogen dioxide (NO 2 ), nitric oxide (NO), nitric acid (HNO 3 ) and peroxyacetyl nitrite (PAN) are 27 associated with negative impacts to vegeta tion. The current secondary NAAQS were set to 28 protect against direct damage to vegetation by exposure to gas-phase NO x or SO x , such as foliar 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 50 injury, decreased photosynthesis, and decreased growth. The fo llowing summary is a concise 1 overview of the known or anticipated effects to vegetation caused by gas phase N and S. 2

2.3.1 What is the nature of ecosystem resp onses to gas-phase nitrogen and sulfur? 3 The 2008 ISA found that gas phase N and S are associated with direct phytotoxic effects 4 ( ISA 4.4 ). The evidence is sufficient to infer a causal relationship between exposure to SO 2 and 5 injury to vegetation ( ISA 4.4.1 and 3.4.2.1 ). Acute foliar injury to vegetation from SO 2 may 6 occur at levels above the current secondary standard (3-h average of 0.50 ppm). Effects on 7 growth, reduced photosynthesis and decreased yi eld of vegetation are al so associated with 8
increased SO 2 exposure concentration and time of exposure. 9 The evidence is sufficient to infer a causal relationship between exposure to NO, NO 2 10 and PAN and injury to vegetation ( ISA 4.4.2 and 3.4.2.2 ). In sufficient concentrations, NO, NO 2 11 and PAN can decrease photosynthesis and induce visible foliar injury to plants. Evidence is also 12 sufficient to infer a causal relationship between exposure to HNO 3 and changes to vegetation 13 ( ISA 4.4.3 and 3.4.2.3 ). Phytotoxic effects of this pollutant include damage to the leaf cuticle in 14 vascular plants and disappearance of some sensitive lichen species. 15

2.3.2 What types of ecosystems are sensit ive to such effect s? How are these 16 responses affected by atmospheric, ecological, and landscape factors? 17 Vegetation in ecosystems near sources of gaseous NO x and SO x or where ambient 18
concentrations of SO 2 , NO, NO 2 , PAN and HNO 3 are higher are more likely to be impacted by 19 these pollutants. Uptake of th ese pollutants in a plant canopy is a complex process involving 20 adsorption to surfaces (leaves, stems and soil) and absorption into leaves ( ISA 3.4.2 ). The 21 functional relationship between ambien t concentrations of gas phase NO x and SO x and specific 22 plant response are impacted by internal factors su ch as rate of stomatal conductance and plant 23 detoxtification mechanisms, and external factors including plant water stat us, light, temperature, 24 humidity, and pollutant exposure regime ( ISA 3.4.2 ). 25 Entry of gases into a leaf is dependent upon physical and chemical processes of gas phase 26 as well as to stomatal aperature. The aperat ure of the stomata is controlled largely by the 27 prevailing environmental conditions, such as humi dity, temperature, and light intensity. When 28 the stomata are closed, resistance to gas uptake is high and the plant has a very low degree of 29 susceptibility to injury. Mosses and lichens do no t have a protective cuti cle barrier to gaseous 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 51 pollutants or stomata and are generally more se nsitive to gaseous sulf ur and nitrogen than 1 vascular plants ( ISA 3.4.2 ). 2 The appearance of foliar injury can vary significantly across species and growth 3 conditions affecting stomatal c onductance in vascular plants ( REA 6.4.1 ). For example, damage 4
to lichens from SO 2 exposure includes reduced photosynt hesis and respiration, damage to the 5 algal component of the lichen, leak age of electrolytes, inhibition of nitrogen fixation, reduced K + 6 absorption, and structural changes (Belnap et al., 1993; Farmer et al., 1992, Hutchinson et al., 7 1996). 8

2.3.3 What is the magnitude of ecosystem responses to gas phase effects of NO x 9
and SO x ? 10 The phytotoxic effects of gas phase NO x and SO x are dependent on the exposure 11 concentration and duration and sp ecies sensitivity to these pollu tants. Effects to vegetation 12
associated with NO x and SO x , are therefore, variable across the U.S. and tend to be higher near 13 sources of photochemical smog. For example, SO 2 is considered to be the primary factor 14 contributing to the death of lichens in many urba n and industrial areas, with fruticose lichens 15 being more susceptible to SO 2 than many foliose and crustose sp ecies (Hutchinson et al., 1996). 16 The ISA states there is very limited ne w research on phytotoxic effects of NO, NO 2 , PAN 17
and HNO 3 at concentrations currently observed in th e United States with the exception of some 18 lichen species ( ISA 4.4 ). Past and current HNO 3 concentrations may be contributing to the 19 decline in lichen species in the Los Angeles basin (Boonpragob and Nash 1991; Nash and Sigal, 20 1999; Riddell et al., 2008). PAN is a very small co mponent of nitrogen depos ition in most areas 21 of the United States ( REA 6.4.2 ). Current deposition of HNO 3 is contributing to N saturation of 22 some ecosystems close to sources of photochemical smog (Fenn et al., 1998) such as the MCF’s 23 of the Los Angeles basin mountai n (Bytnerowicz et al., 1999). 24



### 2.4 SUMMARY 25 In summary, NO x and SO x in the atmosphere contribute to effects on individual species 26 and ecosystems through direct contact with vege tation, and more significan tly through deposition 27 to sensitive ecosystems. The ISA concludes that the evidence is sufficient to conclude causal 28 relationships between acidifyi ng deposition of N and S and ef fects on freshwater aquatic 29 ecosystems and terrestrial ecosystems, and between nitrogen nutrient enrichment and effects on 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 52 sensitive terrestrial and freshwater aquatic ecosy stems. The ISA also concludes that a causal 1 relationship is supported betw een nitrogen nutrient enrichment and effects on estuarine 2 ecosystems; however, the contribut ion of atmospheric oxidized nitrogen relative to reduced 3 nitrogen and non-atmospheric nitrogen is more difficult to determine. 4 The REA provides additional support that unde r recent conditions, deposition levels have 5 exceeded benchmarks for ecologica l indicators of acidification and nutrient enrichment that 6 indicate that effects are likely to be occurring in significant numb ers of lakes and streams within 7 sensitive ecosystems. 8



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March 2010 Draft – Do Not Quote or Cite 55 sensitive habitats. Project fina l report, Volume IV: Stream bioassays, aluminum toxicity, 1 species richness and stream ch emistry, and models of suscep tibility to acidification. 2 Chapter 6B. Project completion report to the National Park Service. Charlottesville, VA; 3 Department of Environmental Scie nces, University of Virginia. 4

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Edwards PJ; Kochenderfer JN; Coble DW; Adams MB. (2002). Soil leachate responses during 12 10 years of induced whole-watershed acidi fication. Water Air Soil Pollut, 140, 99-118. 13

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Farmer AM; Bates JW; Bell JNB. (1992). Ecophys iological effects of acid rain on bryophytes 18 and lichens. In: Bates JW; Farmer AM (Eds .), Bryophytes and liche ns in a changing 19 environment. Oxford, UK: Claredon Press. 20

Fenn ME; Poth MA; Johnson DW. (1996). Evid ence for nitrogen saturation in the San 21
Bernardino Mountains in southern Ca lifornia. For Ecol Manage, 82, 211-230. 22

Ford J; Stoddard JL; Powers CF. (1993). Pers pectives in environm ental monitoring: an 23 introduction to the U.S. EPA long-term m onitonring (LTM) project. Water Air Soil 24 Pollut, 67, 247-255. 25Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 56 Galloway JN; Schlesinger WH; Levy H; Michaels AF; Schnoor JL. (1995). Nitrogen-fixation: 1 anthropogenic enhancement, environmental response. Glob Biogeochem Cycles, 9, 235- 2
252. 3

Gilliam FS; Adams MB; Yurish BM. (1996). Ecos ystem nutrient responses to chronic nutrient 4 inputs at Fernow Experimental Forest, West Virginia. Can J For Res, 26, 196-205. 5

Haines TA; Baker JP. (1986). Evidence of fish population responses to acidification in the 6 eastern United States. Water Air Soil Pollut, 31, 605-629. 7

Holland EA; Dentener FJ; Braswell BH; Sulzma n JM. (1999). Contemporary and pre-industrial 8 global reactive nitrogen budge ts. Biogeochemistry, 46, 7-43. 9

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March 2010 Draft – Do Not Quote or Cite 57 Kochy M; Wilson SD. (2001). Nitrogen deposition a nd forest expansion in the northern Great 1 Plains. J Ecol, 89, 807-817. 2

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Lien L; Raddum GG; Fjellheim A. (1992). Critical loads for surface waters: invertebrates and 8 fish. (Acid rain research report no 21). Os lo, Norway: Norwegian Institute for Water 9
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McNulty SG; Cohen EC; Myers JAM; Sullivan TJ; Li H. (2007). Estimates of critical acid loads 16 and exceedances for forest soils across the conterminous United States. Environ Pollut, 17 149, 281-292. 18

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montane forests of southern California: A case study of the San Bernardino mountains. 23 Ecological Studies, 134, (pp. 223-234). New York, NY: Springer-Verlag. 24Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 58 Norton S; Kahl J; Fernandez I. (1999). Altered soil-soil water interactions inferred from stream 1 water chemistry at an artificially acidif ied watershed at Bear Brook Watershed, Maine 2 USA. Environ Monit Assess, 55, 97-111. 3

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Paerl H; Pinckney J; Fear J; Pe ierls B. (1998). Ecosystem respons es to internal and watershed 12 organic matter loading: Consequences for hypoxia in the eutrophying Neusse River 13 Estuary, NC, USA. Mar Ecol Prog Ser, 166, 17-25. 14

Parker KE. (1988). Common loon reproduction and chick feeding on acidified lakes in the 15 Adirondack Park, New York. Cana dian Journal of Zoology, 66, 804-810. 16

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March 2010 Draft – Do Not Quote or Cite 59 Ross DS; Lawrence GB; Fredriksen G. (2004). Minera lization and nitrificati on patterns at eight 1
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Stoddard JL. (1990). Plan for converting the NAPAP aquatic effects long-term monitoring 18 (LTM) project to the temporally integrated monitoring of ecosystems (TIME) project. 19 (International Report). Corvallis, OR; U.S. Environmental Protection Agency. 20

Stoddard JL. (1994). Long-term changes in wate rshed retention of nitrogen: its causes and 21 aquatic consequences. In Ba ker LA (Ed.), Environmental chemistry of lakes and 22 reservoirs. (pp. 223-284). Washington, D. C.: American Chemical Society. 23

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March 2010 Draft – Do Not Quote or Cite 60 Suding KN; Collins SL; Gough L; Clark C; Clela nd EE; Gross KL; Milchunas DG; Pennings S. 1 (2005). Functional- and abundance-based mech anisms explain diversity loss due to N 2 fertlization. Proc Natl Acad Sci USA, 102, 4387-4392. 3

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Sverdrup H; Warfvinge P. (1993). The effect of soil acidification on the growth of trees, grass 11 and herbs as expressed by the (Ca+ Mg + K)/Al ratio. Rep in Ecol & Eng, 2, 1993. 12

US EPA (2008) U.S. EPA. Integrated Science Assessment (ISA) for Oxides of Nitrogen and 13 Sulfur Ecological Criteria (Final Report) . U.S. Environmental Protection Agency, 14 Washington, D.C., EPA/600/R-08/082F, 2008. 15

US EPA (2009) Risk and Exposure Assessment fo r Review of the Sec ondary National Ambient 16 Air Quality Standards for Oxides of Nitrogen and Oxides of Sulfur-Main Content - Final 17 Report. U.S. Environmental Protection Ag ency, Washington, D.C., EPA-452/R-09-008a 18

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Wigington PJ Jr; DeWalle DR; Murdoch PS; Kretse r WA; Simonin HA; Van Sickle J; Baker JP. 23 (1996b). Episodic acidification of small streams in the northeastern United States: Ionic 24 controls of episodes. Ecol Appl, 6, 389-407. 25Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 61 Wedemeyer GA; Barton BA; MeLeay DJ. (1990) . Stress and acclimation. In: Schreck CB, 1 Moyle PB (Eds.), Methods for fish biol ogy (pp. 178-196). Bethesda, MD: American 2 Fisheries Society. 3

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March 2010 Draft – Do Not Quote or Cite 62 

## 3. CONSIDERATIONS OF ADVERSITY TO PUBLIC 1 

## WELFARE 2



### 3.1 HOW DO WE CHARACTER IZE ADVERSITY TO PUBLIC 3 

### WELFARE? WHAT ARE THE RE LEVANT FACTORS AND HOW 4 

### ARE THEY ADDRESSED IN THIS DOCUMENT? 5 The paradigm of looking at adversity to public welfare as deriving from disruptions in 6 ecosystem structure and function has been used broadly by EPA to categorize effects from the 7 cellular to the ecosystem level. An evaluation of adversity to public welfare might consider the 8 type, intensity, and scale of the effect as well as the potential for recovery. 9 Similar concepts were used in past revi ews of secondary NAAQS for ozone, PM relating 10 to visibility as well as in itial reviews of effects from lead deposition. Because NO x and SO x are 11 deposited from ambient sources into ecosystem s where they affect changes to organisms, 12 populations and ecosystems, the concept of adversity to public welfare as related to impacts on 13 the public from alterations in stru cture and function of ecosystems is appropriate for this review. 14 Other information that may be helpful to cons ider includes the role of critical loads and 15 ecosystem service impacts as benchmarks or meas ures of impacts on ecosystems that may affect 16 public welfare. Ecosystem services can be relate d directly to concepts of public welfare to 17 inform discussions of societal adverse impacts. Subsequent sections will discuss each of these 18 concepts as they relate to adversity. 19

3.1.1 What are the benchmarks for adversity from other sources? 20

3.1.1.1 Ozone and PM NAAQS Reviews 21 The evaluation of adversity from a public welf are perspective in the context of ozone and 22 particulate matter (PM) are relevant to this cu rrent review. Both ozone and PM have documented 23 effects on ecological receptors. These criteria pol lutants are being reviewed on a schedule as part 24 of the NAAQS process. The ozone secondary sta ndard is currently under reconsideration from 25 the 2008 ruling with a proposal due on January 6, 2010. A draft Policy Assessment for PM is 26 being developed for CASAC and public consultation. 27Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 63 3.1.1.1.1 Ozone 1 Welfare effects of ozone are primarily limite d to vegetation. These effects begin at the 2
level of the individual cell and a ccumulate up to the level of whol e leaves and plants. If effects 3 occur on enough individual plants within the population, communities and ecosystems may be 4 impacted. Prior to the 2008 ozone review, Ozone vegetation effects were classified as either 5 “injury” or “damage” (FR 72 37889). “Injury” was defined as; encompassing all plant reactions, 6 including reversible changes or changes in plant metabolism, quali ty or reduced growth that does 7 not impair the intended use of the plant while “damage” includes those injury effects that reach 8 sufficient magnitude as to reduce or impair the intended use of the plant (FR 72 37890). The 9 “intended use” of the plant was imbedded with the concept of adversity to public welfare. 10 Ozone-associated “damage” was considered adve rse if the intended use of the plant was 11 compromised (i.e. crops, ornamental s, plants located in Class I ar eas). Effects of ozone on single 12 plants or species grown in monocultures such as agricultural crops and managed forests were 13
evaluated without consideration of potential effects on natural forests or entir e ecosystems. 14 In the 2008 rulemaking, EPA expanded the char acterization of adversity to go beyond the 15 individual plant level and this language is co ntinued in the 2010 ozone reconsideration. The 2008 16 final rule and 2010 proposal conclude that a dete rmination of what constitutes an “adverse” 17
welfare effect in the context of secondar y NAAQS review can appropriately occur by 18 considering effects at higher ecological leve ls (populations, communities, ecosystems) as 19 supported by recent literature. The ozone review us es the example of the construct presented in 20 Hogsett et al. (1997) as a model for assessing risk s to forests. This study suggests that adverse 21
effects could be classified into one or more of the following categories: (1) economic production, 22 (2) ecological structure, (3) genetic resources , and (4) cultural values”. Another recent 23 publication, “A Framework for Assessing and Reporting on Ecological Condition: an SAB 24 report” (Young and Sanzone, 2002) provides additio nal support for expanding the consideration 25 of adversity beyond the species level and at hi gher levels by making explicit the linkages 26
between stress-related effects at the species level and at higher levels within an ecosystem 27 hierarchy (See Figure 3.1.1). 28Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 64 1 Figure 3-1. Common anthropogenic stressors and the essential ecological 2 attributes they affect. Modified from Young and Sanzone (2002) 3
In the 2008 ozone NAAQS review a nd current ozone NAAQS proposal, the 4 interpretation of what constitute s an adverse effect on public we lfare can vary depending on the 5
location and intended use of the plant. The degree to which O 3 -related effects are considered 6 adverse to public welfare depends on the intended use of the ve getation and its significance to 7 public welfare (73 FR 16496). Therefore, effects on vegetation (e.g., biomass loss, foliar injury, 8 impairment of intended use) may be judged to have a different degree of impact on public 9 welfare depending, for example, on whether that e ffect occurs in a Cla ss I area, a city park, 10 commercial cropland or private land. 11 In the proposed ozone reconsideration in 2010 the Administrator has found that the types 12 of information most useful in informing the select ion of an appropriate ra nge of protective levels 13Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 65 is appropriately focused on information regardin g exposures and responses of sensitive trees and 1 other native species known or antic ipated to occur in protected areas such as Class I areas or on 2 lands set aside by States, Tribes and public interest groups to pr ovide similar benefits to the 3 public welfare, for residents on those lands, as well as visitors to those ar eas. She further notes 4
that while direct links between O 3 induced visible foliar injury symptoms and other adverse 5 effects ( e.g., biomass loss) are not always found, visible fo liar injury in itself is considered by the 6 National Park Service (NPS) to affect adversely air quality related values (AQRV) in Class I 7

areas. W hile the Administrator recognizes that uncerta inty remains as to what level of annual tree 8 seedling biomass loss when compounded over multiple years should be judged adverse to the 9 public welfare, she believes that the potential for such anticipated effects should be considered in 10 judging to what degree a standard should be precautionary (73 FR 16496). The range of 11 proposed levels from 7 – 15 ppb includes at the maximum level of 15 ppb protection of 12 approximately 75% of seedlings fr om more than 10% biomass loss. 13

3.1.1.1.2 PM 14 [To be added in the second draft policy assessment based on the draft PM policy 15 assessment] 16

3.1.2 Other EPA Programs and Federal Agencies 17 Various federal laws and policies exist to protect ecosystem health. How other federal 18 agencies and EPA offices consider ecosystem e ffects in carrying out their programs can help 19
inform the Administrator when she evaluates the adversity of ecosy stem impacts on public 20 welfare. For example, an effect may be consider ed adverse to public welf are if it contributes to 21 the inability of areas to meet water quality obj ectives as defined by the Clean Water Act. The 22 following federal statutes and policie s may prove helpful to consider. 23

EPA Office of Water 24
Section 101 of the Clean Water Act (CWA) (Declaration of Goal s and Policy) states that 25 the objective of the CWA is to restore and main tain the chemical, physical, and biological 26 integrity of the Nation’s waters and to attain, where possible, water quality that protects fish, 27 shellfish, wildlife and provides for water-based recreation. 28Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 66 The CWA also authorizes EPA to develop wate r quality criteria as a guide for the states 1 to set water quality standards to protect aquatic life. In consideration of acidification effects, 2 EPA’s Redbook, Quality Criteria for Water , published originally in 1976, recommends that 3 alkalinity be 20 mg/l or more as CaCO3 for freshwater aquatic life except where natural 4 concentrations are less. Alkalinity is the sum total of components in the water that tend to elevate 5 the pH of the water abov e a value of about 4.5. 6 As mentioned in the Redbook, alkalinity is expressed as CaCO3 in mg/l. Alkalinity 7 differs slightly from ANC in that ANC include s other buffering compounds (Na, Mg, and K) as 8 well and includes buffering capacity of particulates in the water sample. Since alkalinity is 9 expressed as mg/l and ANC is expressed as μ eq/l, alkalinity must be multiplied by 20 to be 10
converted to μ eq/l. Thus a recommended criterion of 20 mg/l alkalinity is roughly equivalent to 11
an ANC of 400 μ eq/l. 12
The Clean Air Act’s Prevention of Significant Deterioration (PSD) program (42 13 U.S.C. 7470) purposes include to “p reserve, protect and enhance the air quality in national parks, 14 wilderness areas and other areas of natural, recreati onal, scenic or historic value . . . .” Also, the 15 PSD program charges the Federal Land Managers, in cluding the NPS, with “. . . an affirmative 16 responsibility to protect the air qu ality related values . . . “within federal Class I lands. (42 U.S.C. 17 7475(d)(2)(B)). 18

National Park Service 19 The National Park Service (NPS) is responsible for the protec tion of all resources within 20 the national park system. These resources include those that are related to and/or dependent upon 21 good air quality, such as whole ecosystems and ecosy stem components. The NPS, in its Organic 22 Act (16 U.S.C. 1), is directed to conserve th e scenery, natural and hist oric objects and wildlife 23 and to provide for the enjoyment of these resources unimpaired for current and future 24 generations. 25
The Wilderness Act of 1964 asserts wilderness areas will be administered in such a 26 manner as to leave them unimpaired and preserve them for the enjoyment of future generations. 27 NPS Management Policies (2006) guide all NPS actions including natural resources 28 management. In general, the NPS Management Po licies reiterate the NPS Organic Act’s mandate 29 to manage the resources “unimpaired.” 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 67 U.S. Fish and Wildlife Service 1 On endangered species, Title 16 USC Chapter 35 Section 1531 states “The Congress 2 finds and declares that— these species of fish, wildlife, and plants are of esthetic, ecological, 3 educational, historical, recreationa l, and scientific value to the Nation and its people and that all 4 Federal departments and agencies will use thei r authorities to conserve threatened and 5 endangered species. 6
The United States Fish and Wildlife Serv ice (FWS) manages the National Wildlife 7 Refuge System lands to “...ensure that the biol ogical integrity, dive rsity, and environmental 8 health of the Systems are maintained for the benefit of present and future generations of 9 Americans.” 16 U.S.C. Section 668dd(a)(4)(B)(1997). 10

U.S. Forest Service 11 The National Forest units are managed consis tent with Land and Resource Management 12 Plans (LRMPs) under the provisions of the Na tional Forest Management Act (NFMA). 16 13 §U.S.C. 1604 (1997). LRMPs are, in part, specif ically based on recognition that the National 14 Forests are ecosystems and their management fo r goods and services requ ires an awareness and 15 consideration of the interrelationships among pl ants, animals, soil, water, air, and other 16
environmental factors within such ecosystems. 36 C.F.R. §219.1(b)(3) 17 Any measures addressing Air Quality Re lated Values (AQRV) on National Forest 18 System lands will be implemented through, and be consistent with, the provisions of an 19 applicable LRMP or its revision (16 U.S.C. §1604(i)). Additionall y, the Secretary of Agriculture 20 must prepare a Renewable Resource Program th at recognizes the need to protect and, if 21 necessary, improve the quality of ai r resources. 16 U.S.C. §1602(5)(C). 22 AQRVs in Wilderness areas may receive furthe r protection by the previously mentioned 23
1964 Wilderness Act. For Wilderness Areas in the National Forest System, the Act's 24 implementing regulations are found at 36 C.F.R. §293 requiring these Wilderness Areas be 25 administered to preserve and prot ect [their] wilderness character. 26

Chesapeake Bay Total Maximum Daily Loads 27 Under section 303(d) of the Clean Water Act, st ates, territories, and authorized tribes are 28 required to develop lists of impa ired waters. These are waters th at are too polluted or otherwise 29 degraded to meet the water quality standards set by states, territories, or authorized tribes. The 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 68 law requires that these jurisdictions establish prio rity rankings for waters on the lists and develop 1 TMDLs for these waters. A Total Maximum Daily Load, or TMDL, is a calculation of the 2 maximum amount of a pollutant that a waterbody can receive and still safely meet water quality 3 standards. EPA is developing a TMDL for th e Chesapeake Bay and its tributaries. The 4 Chesapeake Bay Program has modeled the level of nitrogen that can reach the Bay and still meet 5 the Bay’s water quality standards. The TMDL, with full public pa rticipation, will set waste load 6 allocations for point source discharges and load allocations for nonpoint sources of nitrogen. Air 7 deposition to the Bay and its watershed, as a s ource category, will have a specific allocation. The 8
allocation can be used to calculate the level of ambient air concentrations of reactive nitrogen 9 that are likely to meet the de position allocation. To find the NO x portion of the allocation one 10
would subtract the reduced forms fr om the total allocation. If the total load to the Bay of nitrogen 11 from all the allocated source categories remains be low the allocations, then the Bay is expected 12 to meet the water quality standards, which are set to protect the designated uses of the Bay. Since 13 the designated uses are set by the states with public input, not meeting the designated uses can be 14 seen as having an adverse effect. 15

United Nations Economic Commission for Europe (UNECE) 16 [This information will be in cluded in the second draft.] 17

Critical Loads 18
The term critical load is used to describe the threshold of air pollution deposition that 19 causes a specified level of harm to sensitive re sources in an ecosystem. A critical load is 20 technically defined as “the quant itative estimate of an exposure to one or more pollutants below 21 which significant harmful effects on specified sensitive elements of the environment are not 22 expected to occur according to present know ledge” (Nilsson and Grennfelt, 1988). The 23
determination of when a harmful effect becomes “s ignificant” may be in th e view of a researcher 24 or through a policy development process. Research ers often use the term “critical loads” to 25 describe when particular detrimental effects ar e realized, as is the cas e in Figure 2-1. In many 26 European countries a critical loads framework is used to determine a level of damages to 27 ecosystem services from pollution that are legall y allowed. These critical loads are determined 28 through a policy process. 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 69 Harmful effects due to acidific ation have been defined here as those that occur below a 1 given ANC for aquatic systems and below a given Bc:Al ratio for terrestrial systems. However, 2
the level at which an effect becomes harmful in that it causes adverse e ffects on public welfare is 3 determined by the Administrator. 4



### 3.2 WHAT ARE ECOSYSTEM SE RVICES AND HOW DOES THIS 5 

### CONCEPT RELATE TO PUBLIC WELFARE? 6 An additional concept that may be useful in considering the issue of adversity to public 7 welfare is ecosystem services. In the next se ction the concept of eco system services, its 8 relationship to adversity and public welfare within the context of this review are explained. 9 Characterizing a known or anticipated adverse effect to public welfare is an important 10 component of developing any secondary NAAQS. According to the Clean Air Act, welfare 11
effects include: 12 effects on soils, water, crops, vegetation, manmade materials, animals, wildlife, 13 weather, visibility, and climate, damage to and deterioration of property, and 14 hazards to transportation, as well as effect on economic values and on personal 15 comfort and well-being, whether cause d by transformation, conversion, or 16 combination with other air pol lutants (CAA, Section 302(h)). 17 While the text above lists a number of welfare effects, these effects are not an effect on 18 public welfare in and of themselves. 19 Ecosystem services can be generally defined as the benefits individua ls and organizations 20 obtain from ecosystems. Ecosystem services can be classified as provisioning (food and water), 21 regulating (control of climate and disease), cultural (recreational), and supporting (nutrient 22 cycling) (MEA 2005). Conceptually, changes in ecosystem services may be used to aid in 23 characterizing a known or anticipate d adverse effect to public welf are. In the context of this 24 review, ecosystem services may also aid in assessing the magnitude and significance to the 25 public of a resource and in assessing how NO x and SO x concentrations and deposition may 26 impact that resource. The relationship between ec osystem services and pub lic welfare effects is 27
illustrated in Table 3.2.1. 28Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 70 Table 3-1. Crosswalk between Ecosystem Serv ices and Public Welfare Effects

Public Welfare Effect Ecosystem Service Service Category Soils Nutrient Cycling Supporting Water Drinking water, Recreation, Aesthetic Provisioning, Cultural

Crops Food, Fuel Production Provisioning Vegetation Food, Recreation, Aesthetic, Nonuse Provisioning, Cultural

Wildlife Recreation, Food, Nonuse Cultural, Provisioning Climate Climate Control Regulating *Personal Comfort and Wellbeing *All ecosystem services contribute to personal comfort and wellbeing. 1 EPA has defined ecological goods and services for the purposes of a Regulatory Impact 2 Analysis as the “outputs of ecologi cal functions or processes that di rectly or indirectly contribute 3 to social welfare or have the potential to do so in the future. Some outputs may be bought and 4 sold, but most are not marketed” (US EPA 2006). Though this is not a definition specifically for 5 use in the NAAQS process it may be a useful one in considering the scope of ecosystem services 6 and the effects of air pollut ants upon those services. Es pecially important is the 7 acknowledgement that most of the goods and serv ices supplied by ecosystems cannot be fully 8 measured or monetized. Valuing ecological benefits, or the contributions to social welfare 9 derived from ecosystems, can be challenging as noted in EPA’s Ecological Benefits Assessment 10 Strategic Plan (US EPA 2006) and the Science A dvisory Board report “Valuing the Protection of 11 Ecological Systems and Services” (US EPA, 2009) . It can be informative in characterizing 12 adversity to public welfare to attempt to plac e an economic valuation on the set of goods and 13
services that have been identifie d with respect to a change in policy however it must be noted 14 that this valuation will be incomplete and illust rative only. The stepwise concept leading to the 15 valuation of ecosystem services is gr aphically depicted in Figure 3-2. 16Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 71 1 Figure 3-2. Representation of the benefits a ssessment process indicating where 2 some ecological benefits may remain unrecognized, unquantified, or 3 unmonetized. (Source: EBASP USEPA 2006). 4 A conceptual model integrating the role of ecosystem services in characterizing known or 5 anticipated adverse effects to public welfare is shown in Figur e 3-3. Under Section 109 of the 6 CAA, the secondary standard is to specify a level of air quality th at is requisite to protect public 7 welfare. For this review, the relevant air qua lity indicator is interpreted as ambient NO x and SO x 8
concentrations that can be linked to levels of deposition for which there are ecological effects 9 that are adverse to public welfar e. The case study analyses (describ ed in Chapters 4 and 5 of the 10 REA and summarized in Chapter 2 of this doc ument) link deposition in sensitive ecosystems 11 (e.g., the exposure pathway) to changes in a given ecological indicator (e.g., for aquatic 12 acidification, changes in acid ne utralizing capacity [ANC]) and then to changes in ecosystems 13 and the services they provide (e.g., fish speci es richness and its infl uence on recreational 14 fishing). To the extent possible for each targeted effect area, ambient c oncentrations of nitrogen 15 and sulfur (i.e., ambient air quali ty indicators) were linked to de position in sensitive ecosystems 16 (i.e., exposure pathways), and then deposition wa s linked to system response as measured by a 17 given ecological indicator (e.g., lake and stream acidification as measured by ANC). The 18Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 72 ecological effect (e.g., changes in fish species ric hness, etc.) was then, wher e possible, associated 1 with changes in ecosystem servi ces and their public welfare eff ects (e.g., recreational fishing). 2 Knowledge about the relationships linking ambient concentrations and ecosystem 3
services can be used to info rm a policy judgment on a known or anticipated adverse public 4 welfare effect. The conceptual model outlined fo r aquatic acidification in Figure 3-3 can be 5 modified for any targeted effect area where sufficient data and models are available. For 6 example, a change in an ecosystem structure and process, such as foliar injury, would be 7 classified as an ecological effect, with the asso ciated changes in ecosystem services, such as 8 primary productivity, food availability, and aesthetic s (e.g., scenic viewing), classified as public 9 welfare effects. Additionally, changes in biodivers ity would be classified as an ecological effect, 10 and the associated changes in ecosystem se rvices—productivity, recr eational viewing and 11
aesthetics—would be classified as public welfare effects. This information can then be used by 12
the Administrator to determine whether or not the changes described are adverse to public 13 welfare. In subsequent sections these concepts ar e applied to characterize the ecosystem services 14 potentially affected by nitrogen and/or sulfur for each of the effect areas assessed in the REA. 15Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 73 1 Figure 3-3. Conceptual model showing the re lationships among ambient air 2 quality indicators and exposure pa thways and the resulting impacts on 3 ecosystems, ecological responses, effects and benefits to ch aracterize known or 4 anticipated adverse effects to public welfare. [This figur e to be revised for Second 5 Draft Policy Assessment Document] 6 These concepts can also be applied to th e programs described in section 3.1. National 7 parks represent areas of nationa lly recognized ecological and public welfare significance, which 8 are afforded a higher level of protection. Theref ore, staff has also focused on air quality and 9 deposition in the subset of national park sites and important natural ar eas. Figures 3-4 and 3-5 10 illustrate the spatial relationships between se nsitive regions, Class 1 areas and nitrogen 11 deposition levels. 12Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 74 1 Figure 3-4. Locations of Eastern U.S. National Parks (Class I areas) relative to 2 deposition of Nitrogen and Sulfur in sensitive aquatic areas 3Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 75 1 Figure 3-5. Location of Western U.S. National Parks (Class I areas) relative to 2 deposition of Nitrogen and Sulfur 3 [Figures 3-4 and 3-5 will be revised for Second Draft policy Assessment Document] 4



### 3.3 WHAT IS THE ROLE OF ECONOMICS? 5
As discussed earlier in this document, a s econdary NAAQS is required to be set at the 6 “level(s) of air quality necessary to protect th e public welfare from any known or anticipated 7 adverse effects”. As part of the effort to dete rmine the standard, EPA linked the changes in the 8
ambient air concentrations of NO x and SO x to the changes in ecosystem services and ultimately 9 to changes in public welfare (U.S. EPA, 2009) . As previously mentioned most ecosystem 10Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 76 services are not amenable to monetization a small subset of changes in services can be described 1 by economic valuation methods. And although ec onomics on its own cannot determine which 2 impact on public welfare is “adverse”, economics c ould be helpful in the context of a secondary 3 NAAQS for determining the degree to which impr ovements are beneficial to public welfare and 4 illustrating and aggregating those impacts. 7 5 The Role of Economics in Defining “Adversity” There is neither an economic definition 6 of how much loss in public welfar e is adverse nor an economic definition of adversity. While an 7 economist might consider a particular scenario adverse because it might imply some harm or 8 potential for improvement, there is no specific thre shold level when a loss in welfare (e.g. loss in 9 dollars) becomes adverse. An individual might be willing to give up some of their resources to 10 avoid a threat or negative outcome (i.e., willing to pay to avoid a particular outcome). According 11 to economic theory, if an individual is willing to give up something to avoid the outcome, then 12 imposing the outcome on the individual must make them worse off, at which point an economist 13 might colloquially describe the outcome as advers e. However, the amount they would have been 14 willing to pay to avoid the outcome might be quite small, and might not rise to a level of harm 15 that the Administrator interprets as “adverse” to public welfare. In summary, economics provides 16 little guidance as to how the Administrator should interpret the word “adverse” in the context of 17 public welfare. 18 Ecosystem Services and Li nks to Public Welfare An ecosystem service framework 19 provides a structure to measure changes in public welfare from changes in ecosystem functions 20 affected by air pollution. EPA’s Risk Assessment for this rulemaking defines ecosystem services 21 as “the ecological processes or functions having monetary or non monetary value to individuals 22 or society at large” (EPA 2009.) The discipline of economics provides a useful approach for 23 summarizing how the public values changes in the services provided by the environment. An 24 ecosystem services framework (with or without va luation) can provide measures of changes in 25 public welfare. 26

7 Section 109 of the Clean Air Act forbids consideration of the compliance costs of reducing pollution when setting a NAAQS. However, there is no prohibition regarding the consideration of the monetized impacts of welfare effects occurring due to levels of pollu tion above alternative standards in eval uating the adversity of the impacts to public welfare. Ecosystem services can be characterized as a method of monetizing the impacts of the air pollution. Although a separate regulatory document quantifying the co sts and benefits of attain ing a NAAQS is prepared simultaneously, this document is not considered when selecting a standard.Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 77 Economics as a Framework to Illust rate Changes in Public Welfare Economics can 1 provide a framework to illustrate how public welfare 8 changes in response to changes in 2 environmental quality by quantitatively linking ch anges in ecosystem services to preferences. 3
Economics assumes that the choices that individu als make reflect their preferences over certain 4 outcomes and that, generally speaking, they will make choices that, in expectation, will make 5 them as well off as possible given their resour ces. In economics revealed and stated preference 6
methods are used to observe the choices individuals make to understand the outcomes 7 individuals prefer. What individu als are willing to give up for an outcome is their willingness-to8 pay (WTP) for that outcome. An example of an outcome is an improvement in an ecosystem 9 service. Often, to provide comparability to other goods and services , in economics these 10
tradeoffs are framed relative to dollars for convenience. 9 11 Economics could inform the Administrator by valuing and characterizing the changes in 12 public welfare from changes in the quantity and quality of ecosystem services. Overall, this 13 assessment intends to characterize changes in ecos ystem services from a scientific perspective 14 using effects on ecosystem structures and func tions or ecosystem integrity. Economics then 15 estimates the effect on public welfare of these ch anges in the quantity and quality of ecosystem 16 services. For example, a decrease in a particular bird species can be characterized by its effect on 17 the ecosystem’s structure and function, while from an economic perspective, the effects would 18 be based on the impact on public welfare or the value the public places on that species. A simple 19 example is a comparison between a decrease in a bird species that is relatively unknown 20 compared to a decrease in a very prominent sp ecies (e.g. Bald Eagle). The public is likely to 21 have a higher WTP to avoid the latter, and thus the decrease would affect the public welfare 22

more. 23 There are important complications with usi ng preferences to unde rstand the effect of 24 pollution on public welfare. For example, while th e field of economics generally assumes that 25 public preferences are the paramount considera tion; these preferences may change when the 26 public receives new information. Therefore, if individuals do not unde rstand how pollution will 27

8 [A discussion of economic interpretation of “Public Welfare” will be included in the second draft] 9 Often groups collectively make choices to engage in activ ities that improve the collective welfare of the group. For example, a community around an acidified lake might purchase lime and use it to reduce the acidity of the lake. The collective decisions can also be used to understand how people value improvements to ecosystem services. [Additional discussion will be included in the second draft related to collective actions that reveal preferences for improvements in relevant ecosystem services and how thes e collective actions, and the absence of these actions, can be interpreted.]Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 78 affect ecosystem services, or even how those ecosyst em services affect their quality of life, then 1 they will have a difficult time valuing changes in those services. Similarly, it may be very costly 2
for individuals to learn and unders tand how changes in particular ecosystem services may affect 3 them, in part because typically there are sign ificant interdependencies within an ecosystem. 4 Because of this complexity, individuals may imp licitly value a species, or habitat, or ecosystem 5 function because it supports an ecosystem service that they do clearly value. Furthermore, the 6 public also has limited understand ing regarding irrevers ibilities, tipping points, and other more 7 complex aspects of ecosystems, which limits the ability to adequately value these ecosystems. 10 8 In addition, where and when a change in an ecosy stem takes places is crucial for characterizing 9 the associated change in an ecosystem service, and will also affect the value the public places on 10 that change. 11



### 3.4 WHAT IS THE EVIDENCE FOR EFFECTS ON ECOSYSTEM 12 

### SERVICES? HOW DO WE LINK ECOLOGICAL INDICATORS TO 13 

### SERVICES? 14 The process used to link ecological indicat ors to ecosystem services is discussed 15 extensively in Appendix 8 of the REA. In brie f, for each effect area assessed the ecological 16 indicators were linked to an ecological response that was subsequently linked, to the extent 17 possible, to associated services. For example in the case study for aquatic acidification the 18 chosen ecological indicator is ANC which can be linked to the ecosystem service of recreational 19 fishing as illustrated in the conceptual model shown in Figure 3-6. Alt hough recreational fishing 20 losses are the only service effects that can be quan tified or monetized at this time, there are, as 21 can be seen in the Figure, numerous other ec osystem services that may be related to the 22 ecological effects of acidification. 23

10 While the public may not fully appreciate the interdependencies within ecosystems, they can learn them, but again it may be costly to do so. It is possible for individuals to value outcomes that are irreversible or result in discrete changes (i.e., tipping points) in the quality and quantity of ecosystem services. Avoiding irreversible outcomes should be and are more valued by individuals than outcomes that are not irreversible (Arrow and Fischer, 1974).Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 79 1 Figure 3-6. Conceptual model linking ecological indicator (ANC) to affected 2 ecosystem services. 3

The next four sections summarize the current levels of certain ecosystem services for 4 each of the effect areas analyzed in the REA and present results of analyses that have attempted 5 to quantify and monetize the harms to public welf are, as represented by ecosystem services, due 6 to nitrogen and sulfur deposition. 7 Evidence for Adversity Related to Aquatic Acidification 8 Acidification primarily affects the ecosystem services that are derived from the fish and 9 other aquatic life found in these surface waters ( REA, Section 5.2.1.3 ). Food is generally the 10 most important provisioning services provided by inland surface waters (MEA, 2005). In the 11 northeastern United States, the surface waters affect ed by acidification are not a major source of 12 commercially raised or caught fish; however, they are a source of food for some recreational and 13
subsistence fishers and for other consumers. Although data and models are available for 14 examining the effects on recreational fishing, relativ ely little data are available for measuring the 15
effects on subsistence and other consumers. For ex ample, although there is evidence that certain 16 population subgroups in the Northeas tern United States, such as the Hmong and Chippewa ethnic 17 groups, have particularly high ra tes of self-caught fish consum ption (Hutchison and Kraft, 1994; 18 Peterson et al., 1994), it is not known if and how their consumption patterns are affected by the 19 reductions in available fish populations caused by surface water acidification. 20 Inland surface waters support several cultural se rvices, such as aesthetic and educational 21 services; however, the type of se rvice that is likely to be most widely and significantly affected 22Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 80 by aquatic acidification is recreational fishing 11 . Recreational fishing in lakes and streams is 1 among the most popular outdoor recr eational activitie s in the northeastern United States. Data 2 from the 2006 National Survey of Fishing, H unting, and Wildlife A ssociated Recreation 3 (FHWAR) indicate that more than 9% of adults in this part of the country participate annually in 4 freshwater fishing with 140 million freshwater fishing days. Based on studies conducted in the 5 northeastern United States, Kaval and Loomis (2003) estimated aver age consumer surplus values 6 per day of $35 for recreational fishing (in 2007 dolla rs). Therefore, the im plied total annual value 7 of freshwater fishing in the northeast ern United States was $5 billion in 2006. 8 In general, inland surface waters such as la kes, rivers, and streams provide a number of 9 regulating services, such as hydrol ogical regime regulation and clim ate regulation. There is little 10
evidence that acidification of fr eshwaters in the northeastern United States has significantly 11 degraded these specific services ; however, freshwater ecosystems also provide biol ogical control 12 services by providing environments that sustain delicate aquatic food chains. 13
The toxic effects of acidification on fish and other aquatic life impair these services by 14 disrupting the trophic structure of surface waters (Driscoll et al., 2001). Although it is difficult to 15 quantify these services and how th ey are affected by acidification, it is worth noting that some of 16 these services may be captured through measures of provisioning and cultural services. For 17 example, these biological control services may serve as “intermediate” inputs that support the 18 production of “final” recreational fish ing and other cultural services. 19 What is the value of the impaire d recreational fishing services? 20 The previous section describes the ecosystem se rvices that are most likely to be affected 21 by N and S deposition, and it summarizes evidence regarding the current magnitude and values 22 of recreational fishing services; however, it does not measure the degree to which these services 23 are impaired by existing NO x /SO x levels. 24 To address this limitation, the REA (Appendix 8) provides insights into the magnitude of 25 ecosystem service impairments. 26 Specifically, the REA focuses on measuring the benefits of ecosystem service 27 enhancements resulting from the elim ination of anthropogenic sources of NO x /SO x . Rather than 28 asking how much public welfare is currently adve rsely affected relative to a scenario without 29

11 Banzhaf et al (2006) has shown that non-use services are arguably a more significant source of benefits from reduced acidification than recreational fishing.Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 81 anthropogenic NO x /SO x , it asks a similar question of how mu ch public welfare would improve if 1 the emissions were eliminated. The REA provides quantitative estimates of selected ecosystem 2 services impairments or enhancements for three main categories of ecosystem effects – aquatic 3 acidification, terrestrial acidifica tion, and aquatic nutrient enrichment 12 . Within these three 4 categories, the selection of specific ecosystem services for more in-depth analysis depended 5 primarily on the expected magnitude of impairme nts and on the availability of appropriate data 6 and modeling tools. 7 The analysis of ecosystem service impairments due to aquatic acidification builds on the 8 case study analysis of lakes in the New York Ad irondacks. It estimates changes in recreational 9 fishing services, as well as ch anges more broadly in “cultural ” ecosystem services (including 10 recreational, aesthetic, and nonuse services). First, the MAGI C model was applied to 44 lakes to 11 predict what ANC levels would be under both “bus iness as usual” conditions (i.e., allowing for 12 some decline in deposition due to existing regulati ons) and pre-emission (i.e., background) 13
conditions. When these model runs were initiated staff were intere sted in a prospe ctive analysis 14 of conditions assuming a 2010 implementation of “ zero-out” emissions with a projected lag time 15 to improvement of 10 years thus results were calculated for the year 2020. These predictions 16 were then extrapolated to the full universe of Adirondack lakes. Second, to estimate the 17 recreational fishing impacts of aquatic acidification in these lakes, an existing model of 18 recreational fishing demand and si te choice was applied. This m odel predicts how recreational 19 fishing patterns in the Adirond acks would differ and how much higher the average annual value 20 of recreational fishing services would be fo r New York residents if lake ANC levels 21 corresponded to background (rather than business as usual) conditions. Aggregating these values 22 across all NY residents implies that acidifica tion of Adirondack lakes due to anthropogenic 23
sources of NO x /SO x would impair annual recreational fi shing services of NY residents by $6 24 million to $11 million in 2020. Current annual impairments are most likely of a similar 25 magnitude because, although current NO x /SO x levels are somewhat highe r than those expected in 26 2020 (under business as usual – give n expected emissions controls associated with Title IV 27 regulations but no additional nitr ogen or sulfur controls), the affected NY population is also 28 somewhat smaller (based on U.S. Census Bureau projections). 29

12 Estimates for terrestrial nutrient enri chments were not generated due to the limited availability of necessary data and models for this effect category.Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 82 Third, to estimate impacts on a broader cate gory of cultural ecosystem services, results 1 from an existing valuation survey of NY residents were adapted a nd applied to this context. The 2 survey used a contingent valuation approach to estimate the average annual household WTP for 3 future reductions (20% and 45%) in the percent of Adirondack lakes impaired by acidification. 4 These WTP estimates were then (1) rescaled to reflect predicted cha nges between business-as5 usual and background conditions in 2020 (MAGIC lake modeling results indicate that the 6 percentage of impaired lakes would be 22 to 31 points lower under background conditions), and 7 (2) aggregated across NY households. The aggreg ate annual value to NY residents in 2010 for a 8
reduction in lake acidification to background levels by 2020 was estimated to range $4 million to 9 $300 million in 2007 dollars. For comparison the pr evious section estimated the value of 10 recreational fishing in the North eastern states at approximately $5 billion in 2006. These results 11 suggest that the value of avoi ding current impairments to ecosystem services from Adirondack 12 lakes are even higher than the estimate, because they occur t oday rather than in 2020 (i.e., no 13 delayed effect) and because the perc ent of impaired lakes is slight ly higher today than expected 14 in 2020 under business-as-usual. These results imply significant value to the public derived from 15 recreational fishing services. The analysis especi ally illustrates what may be the scale of all 16 impacts to public welfare when viewed as a subs et of all services im pacted by acidification. 17 Evidence for Terrestrial Acidification 18 A similar model to Figure 3-6 can be drawn fo r terrestrial acidification that links Bc:Al 19 ratio to reduced tree growth to decreases in timber harvest although we have less confidence in 20 the significance of this linkage than we do for aquatic acidification. There are numerous services 21 expected to be affected, but the means to adequate ly describe those losses does not as yet exist. 22
These services include effects to forest healt h, water quality, and habita t, including decline in 23 habitat for threatened and endange red species, decline in forest aesthetics, decline in forest 24 productivity, increases in forest soil erosion and decreases in water retention (ISA, 2009; REA, 25 2009; Krieger, 2001). 26
Forests in the Northeastern United States provide several important and valuable 27 provisioning services, which are reflected in the production and sales of tree products. 28 Sugar maples are a particularly important commercial hardwood tree species in the 29 United States, producing wood products like timber and maple syrup that provide hundreds of 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 83 millions of dollars in economic value annually (NASS, 2008). Red spruce is also used in a 1 variety of wood products and provides up to $100 million in economic value annually. 2
Forests in the Northeastern United States are also an important source of cultural 3 ecosystem services, including nonuse (existence va lue for threatened a nd endangered species), 4 recreational, and aesthetic serv ices (ISA, 2009; REA, 2009). Red sp ruce forests are home to two 5 federally listed species. 6 Although we do not have the data to link ac idification damages directly to economic 7 values of lost recreational services in forests, these resources are valuable to the public. A recent 8 study suggests that the total annual value of off-road driving recr eation was more than $9 billion, 9 total and value of hunting and wildlife viewing was more than $4 billion each in the Northeastern 10 United States in 2006(Kaval and Loomis, 2003). In addition, fall color view ing is a recreational 11 activity that is directly depe ndent on forest conditions. Sugar maple trees, in particular, are 12 known for their bright colors and are, therefore, an essential aesthetic component of most fall 13 color landscapes. Statistics on fall color viewi ng are much less available than for the other 14 recreational and tourism activities; however, a few studies have documented the extent and 15 significance of this activity. For example, Spen cer and Holecek (2007) found that roughly 30% 16 of residents reported at least one trip in the previous year in volving fall color viewing. In a 17 separate study conducted in Vermont, Brown (2002) reported that more than 22% of households 18 visiting Vermont in 2001 made the trip primarily for the purpose of viewing fall colors. 19 Two studies that have estimated values for pr otecting high-elevation sp ruce forests in the 20 Southern Appalachians. Kramer et al. (2003) co nducted a contingent valuation study estimating 21 households’ WTP for programs to protect remaining high-elevati on spruce forests from damages 22 associated with air pollution and insect infest ation (Haefele et al., 1991 ; Holmes and Kramer, 23 1995). Median household WTP was estimated to be roughly $29 (in 2007 dollars) for the 24 minimal program and $44 for the more extens ive program. Another study by Jenkins, Sullivan, 25 and Amacher (2002) estimated an aggregate an nual value of $3.4 bill ion for avoiding a 26 significant decline in the health of high-elevation spruce forest s in the Southern Appalachian 27 region. 28
Forests in the Northeastern United States al so support and provide a wide variety of 29 valuable regulating services, including soil stab ilization and erosion co ntrol, water regulation, 30 and climate regulation (Krieger, 200 1). Forest vegetation plays an important role in maintaining 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 84 soils in order to reduce erosion, runoff, and se dimentation that can adversely impact surface 1 waters. In addition to protecting the quality of water in this wa y, forests also help store and 2 regulate the quantity and flows of water in watersheds. Finally, forests help regulate climate 3 locally by trapping moisture and globally by sequestering carbon. The total value of these 4 ecosystem services is very difficult to quantify and the magnitude of thes e impacts is currently 5 very uncertain. 6 What is the value of current ecosystem service impairments? 7 The analysis of ecosystem service impairments associated with terrestrial acidification 8 specifically addresses impacts on the forest product provisioning services from two 9 commercially important tree species – sugar maple a nd red spruce--that are particularly sensitive 10 to the effects of acidification. Using data from the USFS Forest Inventory and Analysis (FIA) 11 database, an exposure-response relationship wa s estimated for each species to measure the 12 average negative effect of criti cal load exceedances (CLEs) of n itrogen and sulfur deposition on 13 annual tree growth. These estimate d relationships were then a pplied to sugar maple and red 14 spruce stocks in the Northeast and North central regions to estimate the average percent increase 15 in annual tree growth that would occur if all CLEs were eliminated. To estimate the aggregate16 level forest market impacts of eliminating CLEs starting in the year 2000, the tree-level growth 17 adjustments were applied using the Forest and Agricultural Sect or Optimization Model 18 (FASOM), which is a dynamic optimization model of the U.S. forest and agricultural sectors. 19 The public welfare gains linked to these markets from eliminating CLEs was estimated to be 20 $0.69 million per year. These estimates can also be interpreted as the current value of 21 impairments to forest provisioning services due to forest acidification effects from nitrogen and 22 sulfur deposition. 23
Nutrient Enrichment 24 For the purposes of the following sections nutri ent enrichment refers only to that due to 25
NO y deposition. Additionally these sections focus on the detrimental effects of that deposition. 26 Staff acknowledges that a certain amount of NO x deposition in managed terrestrial ecosystems 27 may have a beneficial effect. However no attemp t has been made to quantify those beneficial 28
effects. 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 85 Evidence for Aquatic Nutrient Enrichment 1
Estuaries in the eastern United States are an important source of food production, in 2 particular fish and shellfish production. The estu aries are capable of s upporting large stocks of 3 resident commercial species, a nd they serve as the breeding grounds and interim habitat for 4 several migratory species (U.S. EPA, 2009). To provide an indication of the magnitude of 5 provisioning services associated with coastal fisheries, from 2005 to 2007, the average value of 6 total catch was $1.5 billion per year in 15 East Coast states. It is not known, however, what 7 percentage of this value is dire ctly attributable to or dependent upon the estuaries in these states. 8 Based on commercial landings in Maryland and Virg inia, the values for three key species—blue 9 crab, striped bass, and menhaden- totaled ne arly $69 million in 2007 in the Chesapeake Bay 10
alone. 11 Assessing how eutrophication in estuaries aff ects fishery resources requires bioeconomic 12 models (i.e., models that comb ine biological models of fish population dynamics with economic 13 models describing fish harvesting and consumpti on decisions), but relativ ely few exist (Knowler, 14 2002). Kahn and Kemp (1985) estimated that a 50% reduction in SAV from levels would 15 decrease the net social benefits from stripe d bass by $16 million (in 2007 do llars). In a separate 16 analysis, Anderson (1989) modeled blue crab harvests under baseline conditions and under 17
conditions with “full restoration” of SAV. In equilibrium, the increase in annual producer surplus 18 and consumer surplus with full restoration of SAV was estimated to be $7.9 million (in 2007 19 dollars). Mistiaen, Strand, and Lipton (2003) f ound that reductions in DO cause a statistically 20 significant reduction in commercial harvest and re venues crab harvests. For the Patuxent River 21 alone, a simulated reduction of DO from 5.6 to 4.0 mg/L was estimated to reduce crab harvests 22 by 49% and reduce total annual earnings in the fishery by $275,000 (in 2007 dollars). 23 In addition, eutrophication in estuaries may also affect the demand for seafood. For 24 example, a well-publicized toxic pfiesteria bloom in the Maryla nd Eastern Shore in 1997 led to 25 an estimated $56 million (in 2007 dollars) in lost seafood sales for 360 seafood firms in 26 Maryland in the months following the outbrea k (Lipton, 1999). Surveys by Whitehead, Haab, 27 and Parsons (2003) and Parsons et al. (2006) indicated a reducti on in consumer surplus due to 28 eutrophication-related fish kills ra nging from $2 to $5 per seafood meal. 13 As a result, they 29

13 Surprisingly, these estimates were not sensitive to whether the fish kill was de scribed as major or minor or to the different types of information included in the survey.Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 86 estimated aggregate consumer surplus losses of $43 million to $84 million (in 2007 dollars) in 1
the month after a fish kill. 2
As mentioned in the REA (5.2.1.3) , estuaries in the eastern United States also provide an 3 important and substantial variety of cultura l ecosystem services, including water-based 4
recreational and aesthetic serv ices. For example, FHWAR data indicate that 4.8% of the 5 population in coastal states from North Carolina to Massachusetts participated in saltwater 6 fishing, in 26 million saltwater fishing days in 2006 (U.S. DOI, 2007). Based on estimates in 7
Section 5.2.1.3 of the REA , total recreational consumer surplus value from these saltwater 8 fishing days was approximately $1.3 billion (i n 2007 dollars). Recreat ional participation 9
estimates for several other coastal recreationa l activities are also available for 1999–2000 from 10
the NSRE. Almost 6 million individu als participated in motorboating in coastal states from North 11 Carolina to Massachusetts. Again, based on analysis in the REA, the aggregate value of these 12 coastal motorboating outings was $2billion per year. Almost 7 million participated in 13 birdwatching, for a total of almost 175 million days per year, and more than 3 million 14 participated in visits to nonbeach coastal watersid e areas, for a total of more than 35 million days 15

per year. 16 Estuaries and marshes have the potential to support a wide range of regulating services, 17 including climate, biological, a nd water regulation; pollution det oxification; erosion prevention; 18 and protection against natural hazards (MEA, 2005c). The relative lack of empirical models and 19 valuation studies imposes obstacles to the estimati on of ecosystem services affected by nitrogen 20 deposition. While atmospheric deposition contribute s to eutrophication there is uncertainty in 21 separating the effects of atmospheric nitroge n from nitrogen reaching the estuaries from many 22
other sources. 23 What is the value of current ecosystem service impairments? 24 The aquatic nutrient enrich ment case study relied on the NOAA Eutrophication Index as 25 the indicator, which includes dissolved oxygen, HAB s, loss of SAV and loss of water clarity. 26
There are methods available to link some of the components to ecosystem services, most notably 27 loss of SAV and reductions in DO. The REA analys is estimates the change in several ecosystem 28 services including recreational fishing, boating, beach use, aesthetic services and nonuse 29 services. The REA focuses on two major East Co ast estuaries – the Chesapeake Bay and the 30 Neuse River. Both estuaries receive between 20% -30% percent of their annual nitrogen loadings 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 87 through air deposition and both are showing sympto ms of eutrophication. The analysis uses and 1 adapts results from several existing studies to approximate effects on several ecosystem services, 2 including commercial fishing, re creation, aesthetic enjoyment, and nonuse values. For example, 3 it is estimated that atmospheric nitrogen reduc es the annual benefits of recreational fishing, 4 boating, and beach use in the Chesapeake Bay by $43-$217 million, $3-8 million, and $124 5 million respectively, and reduces annual aesthetic benefits to nearshore residents by $39-102 6 million. In the Neuse River, the value of annua l commercial crab fishing services would be 7 between $0.1-1 million higher without the contribu tion of atmospheric nitrogen, and recreation 8 fishing services in the larger Albermarle Pa mlico Sound estuary system (which includes the 9 Neuse) would be $1-8 million greater per year. 10 Evidence for Terrestrial Nutrient Enrichment 11 The ecosystem service impacts of terrestrial nutrient enrichment include primarily 12 cultural and regulating services. In CSS areas, concerns focus on a decline in CSS and an 13 increase in nonnative grasses and other specie s, impacts on the viability of threatened and 14 endangered species associated with CSS, and an increase in fire frequency. Changes in MCF 15 include changes in habitat suitab ility and increased tree mortality, increased fire intensity, and a 16 change in the forest’s nutrient cycling that may affect surface water quality through nitrate 17 leaching (EPA, 2008). 18
The value that California residents and the U.S. population as a whole place on CSS and 19 MCF habitats is reflected in the various federal, state, and local government measures that have 20 been put in place to protect th ese habitats. Threatened and endangered species are protected by 21 the Endangered Species Act. The State of California passed the Natural Communities 22 Conservation Planning Program (NCCP) in 1991, and CSS was the first habitat identified for 23 protection under the program (see www.dfg.ca.gov/ha bcon/nccp). Private organizations such as 24 The Nature Conservancy, the Audubon Society, and local land trusts also protect and restore 25
CSS and MCF habitat. 26
CSS and MCF are found in numerous recreation areas in California. Three national parks 27 and monuments in California contain CSS, in cluding Cabrillo National Monument, Channel 28 Islands National Park, and Santa Monica Nationa l Recreation Area. All three parks showcase 29 CSS habitat with educational programs and inform ation provided to visitors, guided hikes, and 30 research projects focused on understanding and pres erving CSS. Over a million visitors traveled 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 88 through these three parks in 2008. MCF is highl ighted in Sequoia and Kings Canyon National 1 Park, Yosemite National Park, and Lassen Volcan ic National Park, where more than 5 million 2 people visited in 2008. 3 The 2006 FHWAR for California (DOI, 2007) reports on the number of individuals 4 involved in fishing, hunting, and w ildlife viewing in Calif ornia. Millions of people are involved 5 in just these three activities each year. The quality of these trips de pends in part on the health of 6 the ecosystems and their ability to support the dive rsity of plants and animals found in important 7 habitats found in CSS or MCF ecosystems and th e parks associated with those ecosystems. 8 Based on analyses in Section 5.3.1.3 of the REA (U.S.EPA, 2009), average values of the total 9 benefits in 2006 from fishing, hunting, and wildlif e viewing away from home in California were 10 approximately $947 million, $169 million, and $3.59 bill ion, respectively. In addition, data from 11 California State Parks (2003) indicat e that in 2002, 68.7% of adult re sidents participated in trail 12 hiking for an average of 24.1 days per year. The analyses in the REA (U.S.EPA, 2009) indicate 13 that the aggregate annual be nefit for California residents from trail hiking in 2007 was $11.59 14
billion. 15 CSS and MCF are home to a number of important and rare species a nd habitat types. CSS 16 displays richness in biodiversity with more than 550 herbaceous annual and perennial species. Of 17 these herbs, nearly half are endangered, sensitiv e, or of special status (Burger et al., 2003). 18 Additionally, avian, arthropod, herp etofauna, and mammalian species live in CSS habitat or use 19 the habitat for breeding or fora ging. Communities of CSS are home to three important federally 20 endangered species. MCF is home to one federa lly endangered species and a number of state21 level sensitive species. The Audubon Society lists 28 important bird areas in CSS habitat and at 22 least 5 in MCF in California (h ttp://ca.audubon.org/ib a/index.shtml). 14 23 The terrestrial enrichment case study in Section 5.3.1.3 of the REA and Section 3.3.5 of 24 the ISA identified fire regulation as a service that could be affected by nutrient enrichment of the 25 CSS and MCF ecosystems by encouraging growth of more flammable grasses, increasing fuel 26 loads, and altering the fire cycle. Over the 5-year period from 2004 to 2008, Southern California 27 experienced, on average, over 4,000 fires per ye ar burning, on average, over 400,000 acres per 28 year (National Association of State Foresters [ NASF], 2009). It is not po ssible at this time to 29 quantify the contribution of nitrogen depositio, am ong many other factors, to increased fire risk. 30

14 Important Bird Areas are sites that provide essential habitat for one or more species of bird.Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 89 The CSS and MCF were selected as case studie s for terrestrial enrichment because of the 1 potential that these areas coul d be adversely affected by exce ssive N deposition. To date, the 2 detailed studies needed to identify the magnitude of the adverse impacts due to N deposition 3 have not been completed. Based on available data, this report provides a qualitative discussion of 4 the services offered by CSS and MCF and a sense of the scale of benefits associated with these 5
services. California is famous for its recr eational opportunities and b eautiful landscapes. CSS 6 and MCF are an integral part of the Californi a landscape, and together the ranges of these 7 habitats include the densely populated and valu able coastline and the mountain areas. Through 8 recreation and scenic value, these habitats affect the lives of millions of California residents and 9 tourists. Numerous threatened and endangered speci es at both the state and federal levels reside 10 in CSS and MCF. Both habitats may play an im portant role in wildfire frequency and intensity, 11 an extremely important problem for California. The potentially high value of the ecosystem 12 services provided by CSS and MCF justify carefu l attention to the long-term viability of these 13
habitats. 14
The terrestrial nutrient enrichment case st udy relies on benchmark deposition levels for 15 various species and ecosystems as indicators of ecosystem response. While it would be expected 16 that deposition above those levels would have deleterious effects on th e provision of ecosystem 17 services in those areas, at this time it is possibl e only to describe the magnitude of the some of 18 the services currently being pr ovided. Methods are not yet ava ilable to allow estimation of 19 changes in services due to nitrogen deposition. 20



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R.E.Turner. 2001. Nitrogen Loading in Coastal Water Bodies: An Atmospheric 26 Perspective .Washington, DC: American Geophysical Union. 27Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 100 Van Houtven, G. and A. Sommer. December 2002. Recreational Fishing Benefits: A Case Study 1
of Reductions in Nutrient Loads to the Al bemarle-Pamlico Sounds Estuary. Final Report. 2 Prepared for the U.S. Environmental Pr otection Agency. Research Triangle Park, 3
NC:RTI International. 4

Van Houtven, G.L., J. Powers, and S.K. Pattanayak. 2007. “Valuing Water Quality 5 Improvements Using Meta-Analysis: Is the Gl ass Half-Full or Half-Empty for National 6 Policy Analysis?” Resource and Energy Economics 29:206-228. 7

Vaughan, W.J. 1986. “The Water Quality Ladder.” In cluded as Appendix B in R.C. Mitchell, 8 and R.T. Carson, eds. The Use of Contingent Valuation Da ta for Benefit/Cost Analysis in 9
Water Pollution Control . CR-810224-02. Prepared for the U.S. Environmental Protection 10 Agency, Office of Policy, Planning, and Evaluation. 11

Virginia Department of Conservation and Recreation. 2007. “2006 Virginia Outdoors 12 Survey.”Available at 13 http://www.dcr.virginia.gov/recreati onal_planning/documents/vopsurvey06.pdf. 14

Wallace, K.J. 2007. “Classification of Ecosys tem Services: Problems and Solutions.” Ecological 15
Conservation 139:235-246. 16

Whitehead, J.C., T.C. Haab, and G.R. Pars ons. 2003. “Economic Effects of Pfiesteria.” Ocean & 17 Coastal Management 46(9-10):845-858. 18

19Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 101 

### 4 ADDRESSING THE ADEQUACY OF THE CURRENT STANDARDS 1
Based on the information in Chapters 2 and 3, we conclude that th ere is support in the 2
available effects-based evidence for cons ideration of seconda ry standards for NO x and SO x that 3 are protective against adverse ecological effects associated with deposition of NO x and SO x to 4 sensitive ecosystems. Having reached this genera l conclusion, we then to the extent possible 5 evaluate the adequacy of the current NO x and SO x secondary standards by considering to what 6 degree risks to sensitivity ecosyst ems would be expected to occur in areas that meet the current 7
standards. Staff conclusions re garding the adequacy of the cu rrent standards are based on the 8 available ecological effects, expos ure and risk-based ev idence. In evaluating the strength of this 9 information, staff have taken into account the uncertainties and limitations in the scientific 10 evidence. This chapter addresses key policy rele vant questions that inform our determination 11 regarding the adequacy of the structure and levels of the cu rrent secondary standards. The 12 chapter begins with a discussion of the stru cture of the current standards, followed by a 13 presentation of information on recent air quality relative to the existing standards, recent NO x 14
and SO x deposition levels, evaluation of recent depositi on levels relative to levels where adverse 15 ecological effects have been observed, and a set of conclusions regarding the adequacy of the 16
current structure and leve ls of the standards. 17 It is also appropriate in this review to consider whether th e current standards are adequate 18 to protect against the direct effects on vegetation resulting from ambient NO 2 and SO 2 which 19 were the basis for the current secondary standards. We will include a discussion of this issue in 20 the second draft policy assessment. 21



### 4.1 ARE THE STRUCTURES OF THE CURRENT NO X 

### AND SO X 22 

### SECONDARY STANDARDS BASED ON RELEVANT 23 

### ECOLOGICAL INDICATORS SUCH THAT THEY ARE 24 

### ADEQUATE TO DETERMINE AN D PROTECT PU BLIC WELFARE 25 

### AGAINST ADVERSE EFFECTS ON ECOSYSTEMS? 26 The current secondary NO x and SO x standards are intended to protect against adverse 27 effects to public welfare. For NO x , the current secondary standa rd was set identical to the 28Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 102 primary standard 15 , e.g. an annual standard set for NO 2 to protect against adverse effects on 1 vegetation from direct exposure to ambient NO x . For SO x , the current secondary standard is a 3- 2 hour standard intended to provide protection for plants from the di rect foliar damage associated 3 with atmospheric c oncentrations of SO 2 . 4 The ISA has established that the major eff ects of concern for this review of the NO x and 5
SO x standards are associated with deposition of N and S associated with atmospheric 6
concentrations of NO x and SO x (see Chapter 2). As such, the cu rrent secondary standards do not 7 reflect the conclusions of the ISA in the major ar eas of indicator, form, or averaging times. By 8 using atmospheric NO 2 and SO 2 , concentrations as indicators th e current standards address only 9 a fraction of total atmospheric NO x and SO x , and do not take into account the effects from 10 deposition of total atmospheric NO x and SO x . By addressing short-term concentrations of SO 2 , 11
the current SO 2 standard, while protective against di rect foliar effects from gaseous SO x , does 12 not take into account the findings of effects in the ISA, whic h notes the relationship between 13 annual deposition of S and acidification effects which are likely to be more severe and 14 widespread than phytotoxic effects under curren t ambient conditions. Acidification is a process 15 which occurs over time, as the abil ity of an aquatic system to c ounteract acidic inputs is reduced 16 as natural buffers are used more rapidly than they can be replaced through geologic weathering. 17 The relevant period of exposure for ecosystems is therefore not the exposures captured in the 18 short averaging time of the current SO 2 standard. In addition, the ISA has concluded that NO x 19
and SO x and their deposition products jointly affect eco systems, and as such the current separate 20
structure of the NO x and SO x secondary standards does not take into account the joint ecological 21 effects of the two pollutants. 22 Current standards are specified as allowable single atmospheric concentration levels for 23
NO 2 or SO 2 . This type of structure does not take in to account variability in the atmospheric and 24 ecological factors that may alter the effects of NO x and SO x on public welfare. Consistent with 25 section 108, the ISA includes in th e air quality criteria consider ation of how these variable 26 factors impact the effects of ambient NO x and SO x on public welfare. Se condary standards are 27
intended to address a wide variet y of effects occurring in differe nt types of environments and 28 ecosystems. Ecosystems are not uniformly distribu ted either spatially or temporally in their 29

15 The current primary NO 2 standard has recently been change d to the 3 year average of the 98 th percentile of the annual distribution of the 1 hour daily maximum of the concentration of NO 2 . The current secondary standard remains as it was set in 1971.Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 103 sensitivity to air pollution. Therefore, failure to account for the major determinants of variability, 1 especially geologic conditions related to sensi tivity to acidification a nd atmospheric conditions 2 which govern rates of deposition, may lead to standa rds that do not provide appropriate levels of 3 protection across ecosystems. We can state with confidence the current standards were not 4 designed to be protective agai nst those welfare effects tied to deposition of ambient NO x and SO x 5 and thus are not likely to be ad equate to protect public welfar e against known or anticipated 6 adverse effects from deposition. 7
Because most areas of the U.S. are in attainment with the current NO 2 and SO x standards, 8 it is possible to evaluate curre nt conditions, and evaluate the impact on public welfare from the 9 current effects on ecosystems from NO x and SO x deposition in areas th at attain the current 10
standards that use NO 2 and SO 2 as indicators. In addition, this chapter qualitativ ely addresses the 11 adequacy of the structures of the existing standa rds relative to ecologically relevant standards for 12
NO x and SO x , and sets up arguments for developing an ecologically relevant structure for the 13 standards as described in Chapter 5. 14



### 4.2 TO WHAT EXTENT ARE TH E STRUCTURES OF THE CURRENT 15 

### NO X 

### AND SO X 

### SECONDARY STANDARDS MEANINGFULLY 16 

### RELATED TO RELEVANT ECOL OGICAL INDICATORS OF 17 

### PUBLIC WELFARE EFFECTS? 18 The current secondary standard for NO x , set in 1971, using NO 2 as the atmospheric 19 indicator, is 0.053 parts per million (ppm) (100 micrograms per cubic meter of air [ μ g/m3]), 20 annual arithmetic average, calculated as the arithmetic mean of the 1-hour NO 2 concentrations. 21 This standard was selected to provide protecti on to the public welfare against acute injury to 22 vegetation from direct exposure and resulting phy toxicity. During the la st review of the NO x 23 standards, impacts associated with chroni c acidification and eutrophication from NO x deposition 24 were acknowledged, but the relationships be tween atmospheric concentrations of NO x and levels 25 of acidification and eutrophication and associated welfare impacts were determined to be too 26
uncertain to be useful as a basis for setti ng a national secondary standard (USEPA 1995). 27 The current secondary standard for SO x , set in 1971, uses SO 2 as the atmospheric 28 indicator, is a 3-hour average of 0.5 ppm, not to be exceeded more than once per year. This 29 standard was selected to provi de protection to the public welf are against acute injury to 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 104 vegetation. In the last review of the SO x secondary standard, impact s associated with chronic 1 acidification were acknowledged, but the relationships between at mospheric concentrations of 2
SO x and levels of acidification, along with the complex interactions between SO x and NO x in 3 acidification processes, were cite d as critical uncertainties whic h made the setting of secondary 4 NAAQS to protect against acidification inappropriate at that time (USEPA 1982). 5 In the previous indepe ndent reviews of the NO x and SO x secondary standards, each 6 review acknowledged the additional impacts of NO x and SO x on public welfare through the 7 longer term impact of the pollutants once depos ited to ecosystems. However, the previous 8
reviews cited numerous uncertainties as the basi s for not addressing those impacts in the setting 9 of the standards. In addition, these previous re views did not consider the common pathways of 10 impact for the two pollutants acti ng on the same ecosystem endpoints. 11 Three issues arise that call into question the ecological relevance of the current structure 12 of the secondary standards for NO x and SO x . One issue is the exposure period that is relevant for 13 ecosystem impacts. The majority of deposition related impacts are associated with depositional 14 loads that occur over periods of months to years. This diffe rs significantly from exposures 15 associated with hourly concentrations of NO 2 and SO 2 as measured by the current standards. 16 Even though the NO 2 standard uses an annual average of NO 2 , it is focused on the annual 17 average of 1-hour NO 2 concentrations, rather than a cumulative metric or an averaging metric 18 based on daily or monthly averag es. A second issue is the choice of atmospheric indicators. NO 2 19
and SO 2 are used as the component of oxides of nitr ogen and sulfur that are measured, but they 20 do not provide a complete link to the direct effects on ecosystems from deposition of NO x and 21
SO x as they do not capture all re levant species of oxidized nitr ogen and oxidized sulfur that 22 contribute to deposition. The ISA provides eviden ce that deposition related effects are linked 23 with total nitrogen and total sulf ur, and thus all forms of oxidi zed nitrogen and oxidized sulfur 24 that are deposited will contribute to eff ects on ecosystems. This suggests that more 25 comprehensive atmospheric indicators should be considered in designing ecologically relevant 26
standards. Further discussions of the need for mo re ecologically relevant atmospheric indicators 27
as well as the relative contributions to deposition from various species of NO x and SO x can be in 28 found in Chapters 5 and 6. The third issue is that the current standards reflect separate 29 assessments of the two individual pollutants, NO 2 and SO 2 , rather than assessing the joint 30 impacts of deposition of NO x and SO x to ecosystems, recognizing the role that each pollutant 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 105 plays in jointly affecting ecosystem indicators, functions, and services. Th e clearest example of 1 this interaction is in assessment of the impacts of acidifying deposition on aquatic ecosystems. 2 Acidification in an aquatic ecosystem depe nds on the total acidifying potential of the 3 deposition of both N and S from both atmospheric deposition of NO x and SO x as well as the 4 inputs from other sources of N and S such as re duced nitrogen and non-atmospheric sources. It is 5 the joint impact of the two pollutants that determ ines the ultimate effect on organisms within the 6 ecosystem, and critical ecosystem functions such as habitat provision and biodiversity. Standards 7 that are set independently are less able to account for the contribution of the other pollutant. This 8 suggests that interactions between NO x and SO x should be a critical el ement of the conceptual 9 framework for ecologically relevant standards. There are also important interactions between 10
NO x and SO x and reduced forms of nitrogen, which also contributes to acid ification and nutrient 11
enrichment. While the standards do not address redu ced forms of nitrogen in the atmosphere, it is 12 important that the struct ure of the standards address the role of reduced nitrogen in determining 13 the ecological effects resulting fr om deposition of atmospheric NO x and SO x . Consideration will 14 also have to be given to account for loadi ngs coming from non-atmospheric sources as 15 ecosystems will respond to these sources as well. 16
In addition to the fundamental issues disc ussed above, the current structures of the 17
standards do not address the co mplexities in the responses of ecosystems to deposition of NO x 18
and SO x . Ecosystems contain complex grouping of organi sms that respond in various ways to the 19
alterations of soil and water that result from deposition of nitrogen and sulfur compounds. 20 Different ecosystems therefore respond in diffe rent ways depending on a multitude of factors 21 that control how deposition is integrated into the system. For example, the same levels of 22 deposition falling on limestone dominated soils have a very different eff ect than those falling on 23 shallow glaciated soils underline with granite. One syst em may over time display no obvious 24 detriment while the other may expe rience a catastrophic loss in fish communities. This degree of 25 sensitivity is a function of many atmospheric fact ors which control rates of deposition as well as 26 ecological factors which control how an ecosyst em responds to that deposition. The current 27
standards do not take into acc ount spatial and seasonal variat ions not only in depositional 28 loadings but also in sensitivity of ecosystems exposed to those loadings. 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 106 

### 4.3 TO WHAT EXTENT DO CU RRENT MONITORING NETWORKS 1 

### PROVIDE A SUFFICIENT BA SIS FOR DETERMINING THE 2 

### ADEQUACY OF CURR ENT SECONDARY NO X 

### AND SO X 3 

### STANDARDS? 4 There are over 1000 ground level monitoring plat forms (Figures 4-1 and 4-2) that provide 5 measurements of some form of atmospheric ni trogen or sulfur. The key pollutants for this 6 assessment are total oxidized nitrogen (NO y ), total reduced nitrogen (NH x ), and total sulfur (ST). 7 Total reactive oxidized atmospheric nitrogen, NO y , is defined as NO x (NO and NO 2 ) and all 8
oxidized NO x products: NO y = NO 2 + NO + HNO 3 + PAN +2N 2 O 5 + HONO+ NO 3 + organic 9 nitrates + particulate NO 3 (Finlayson-Pitts and Pitts, 2000). This definition of NO y reflects the 10 operational principles of standard measurement te chniques in which all oxid ized nitrogen species 11 are converted to nitrogen oxide (NO) through catalytic reduction and the resulting NO is detected 12 through luminescence. Thus, NO y is truly defined as total oxidi zed nitrogen as converted to NO. 13
NO y is not a strict representation of the all moles of oxidized nitrogen as the diatomic nitrogen 14 species such as N 2 O 5 yield 2 moles of NO. This definition is consistent with the relationship 15 between atmospheric nitrogen and acidi fication processes as the reported NO y provides a direct 16 estimate of the potential equivalents availabl e for acidification. Total reduced nitrogen (NH x ) 17 includes ammonia, NH 3 , plus ammonium, NH4 (EPA, 2008). Reduced nitrogen plus oxidized 18 nitrogen is referred to as total reacti ve nitrogen. Total sulfur (ST) includes SO 2 gas and 19 particulate sulfate, SO 4 . Ammonium and sulfate are compone nts of atmospheric particulate 20 matter as well as directly m easured and modeled in precip itation as direct deposition 21 components. As discussed in this section, there are only very limited routine measurements of 22 total oxidized and reduced nitrogen. In additi on, existing monitoring networks do not provide 23 adequate geographic coverage to fully assess co ncentrations and deposition of reactive nitrogen 24 and sulfur in and near sensitive ecosystems. 25
26Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 107 1 Figure 4-1. Routinely operating surface monitori ng stations measuring forms of 2 atmospheric nitrogen. 3Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 108 1 Figure 4-2. Routinely operating surface monitori ng stations measuring forms of 2 atmospheric sulfur. 3 The principal monitoring networks include the regulatory based State and Local Air 4 Monitoring Stations (SLAMS) pr oviding mostly urban-based SO 2 , NO and NO x , the PM 2.5 5 chemical speciation networks Interagency M onitoring of Protected visual Environments 6 (IMPROVE) and EPA’s Chemical Speciation Netw ork (CSN) providing pa rticle bound sulfate 7 and nitrate, and the Clean Ai r Status and Trends Networ k (CASTNET) providing weekly 8 averaged values of SO 2 , nitric acid, and particle bound su lfate, nitrate and ammonium. The 9 private sector supported SouthEastern Aerosol Research and Characterization (SEARCH) Study 10
network of 4-8 sites in the southeast provides the only rout inely operating source of true 11
continuous NO 2 , ammonia, and nitric acid measurements. SEARCH also provides PM 2.5 size 12
fractions of nitrate and su lfate. Collectively, the SLAM S, Photochemical Assessment 13 Measurement Stations (PAMS), SEARCH and NCore networks will provide over 100 sites 14 measuring NO y (Figure 4-3). The NCore network (Sche ffe et al., 2009) is a multiple pollutant 15Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 109 network with co-located measurem ents of key trace gases (CO, SO 2 , O 3 , NO and NO y ), PM 2.5 1 and PM(10-2.5) mass and PM 2.5 chemical speciation. Additional air pollutants, particularly 2 volatile organic compounds (VOCs), will be measured at those sites that are part of the existing 3 PAMS and National Air Toxics Trends (NATTS ) platforms. The NATTS (EPA, 2008) include 4
27 stations across the U.S. that monitor for a vari ety of hazardous air pollut ants and are intended 5 to remain in place to provide a longe term r ecord. Additional measurements of ammonia and 6 possibly true NO 2 are under consideration. True NO 2 is noted to differentiate from the NO 2 7 determined through routine regulatory networks that have known variable positive bias for NO 2 . 8 The network currently is being de ployed and expected to be operational with nearly 75 sites by 9 January, 2011. The sites are inte nded to serve as central site monitors capturing broadly 10 representative (e.g., not strongly in fluenced by nearby sources) air qua lity in a suite of major and 11 mid size cities, and approximately 20 s ites are located in rural locations. 12Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 110 1 Figure 4-3. Anticipated network of surface based NO y stations based on 2009 2 network design plans. The NCore stati ons are scheduled to be operating by 3 January, 2011. 4 There are significant measurement gaps for characterizing NO y , NH x and SO 2 in the 5 nations ambient air observation networks (EPA, 2008) that lead to greate r reliance on air quality 6 modeling simulations to describe current cond itions. National design of routinely operating 7 ambient air monitoring networks is driven most ly by data uses associated with implementing 8 primary NAAQS, with noted exceptions of the CASTNET and IMPROVE networks In addition 9 to significant spatial gaps in sensitive ecosystem areas that arise from a population oriented 10 network design, the current measurements for primary and secondary nitrogen are markedly 11 different and in some instances of negligible value for secondary NO x and SO x standards. For 12 example, a true NO x (NO plus NO 2 ) measurement typically would capture less than 50% (see 13 discussion below) of the total regional NO y mass in rural locations as the more aged air masses 14 contain significant ox idized nitrogen products in addition to NO x . Note that the NO x monitors 15Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 111 used for NAAQS primary compliance purposes do capture varying amounts of transformed 1 nitrogen species; however, the method provides biased low estimates wi th significant airshed 2 induced variability relative to true NO y . With the exception of the SEARCH network in the 3 southeast, there are virtually no routine netw orks that measure ammonia, although EPA is 4 considering options for ammonia sampling in CASTNET and NCORE networks. Ammonium is 5 reported in EPA chemical speciati on networks, although th e values are believed to be biased low 6
due to ammonia volatization. 7 CASTNET provides mostly ru ral measurements of SO 2 , total nitrate, and ammonium, and 8 affords an existing infrastructure useful for future monitoring in support of a NO x and SO x 9 secondary standard. However, the lack of NO y , SO x and NH x measurements in sensitive 10 ecosystems will require attention in th e N/S secondary standard proposal. 11 As a result of the limited monitoring networks for NO y and SO x in sensitive ecosystems, 12 we are unable to use current monitoring data to fully assess whether the current standards have 13
resulted in levels of NO y and SO x in sensitive ecosystems that would result in deposition levels 14 that are or are not causing eco logical effects adverse to public welfare. We supplement the 15 available monitoring data with the use of s ophisticated atmospheric modeling conducted using 16 EPA’s CMAQ model. 17

4.3.1 What does the NADP monitoring network provide and what are the major 18
limitations? 19 The National Atmospheric Deposition Progr am (NADP) includes approximately 250 20 sites (Figure 4-4) across the U.S. providing annual total wet deposition based on weekly 21 averaged measures of wet deposition of nitr ate, ammonium and sulf ate ions based on the 22
concentrations of these ions in precipitation samples. Meteorologi cal models have difficulty in 23 capturing the correct spatial and temporal features of precipitation events, raising the importance 24 of the NADP as a principal source of precipi tation chemistry. The NADP has enabled several 25 organizations to participate in a measurement program with a centralized laboratory affording 26 measurement and analysis protocol consistency nationwide. Virtually every CASTNET site is 27
located at an NADP site and the combined NADP/ CASTNET infrastructure is a starting point for 28 discussions addressing future N/ S monitoring needs. The Organic bound nitrogen is not analyzed 29 routinely in NADP samples. Consideration might be given to adding NADP sites in locations 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 112 where ambient air monitoring is conducted to assess compliance with a secondary NO x /SO x 1
standard. 2

3 Figure 4-4. Location of approximately 250 Na tional Atmospheric Deposition 4 Monitoring (NADP) National Trends Netw ork (NTN) sites illustrating annual 5 ammonium deposition for 2005. Weekly valu es of precipitation based nitrate, 6 sulfate and ammonium are provided by NADP. 7
4.3.2 How do we characterize depositi on through Monitoring and Models? 8 Routinely available directly measured precip itation to quantify wet deposition of sulfur 9 and nitrogen species are provide d through the NADP. Dry deposition is not a directly measured 10 variable in routine monitoring efforts and, fo r all practical purposes, largely will remain a 11 research endeavor that supports the parameterizations used for estimating dry deposition, as 12 opposed to striving to develop operational methods. Estimates of dry deposition based on 13 observations are provided through the CASTNE T program. However, dry deposition is a 14 calculated value represented as the product of ambient concentrati on (either observed or 15 estimated through air quality modeling) and deposition velocity, Amb i Dry i Dry i C v Dep

⋅ =
. 16Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 113 Deposition velocity is modeled as a mass tr ansfer process through resistance layers 1 associated with the canopy, uptake by vegeta tion, water and soil which collectively are 2 influenced by micrometeorology, land surf ace and vegetation types and species specific 3 solubility and reactivity. Dry deposition is calculated thr ough deposition velocity models 4 capturing these features and using species specifi c ambient air concentrations. This approach 5 conceptually is similar using either observed or modeled air concentrations. Dry deposition 6 estimates from the Community Multi-scale Air Quality (CMAQ) model (EPA, 1999) have been 7 used in this assessment to provide spatially more resolved and extensive estimates of dry 8 deposition for sulfur and all reactive nitrogen (oxidized and reduced) species (CASTNET does 9 not capture important gases such as nitrogen dioxide and peroxyacetyl nitrate). All of the 10 relevant meteorological, land use, vegetation and elevation data required to estimate deposition 11 velocities are generated or acce ssible in the CMAQ and/or meteorological pre-processors. 12

4.3.2.1 Why are we using CMAQ to model depos ition? How are we using it? Why is 13 CMAQ the right model to use? What is the spatial and temporal resolution of 14 CMAQ? What are the model years? Wh at are the limitations to CMAQ? 15 CMAQ provides a platform that allows for a consistent mass accounting approach across 16 ambient concentrations and dry and wet depos ition values. Recognizing the limitations of 17 ambient air networks, CMAQ was used to estim ate dry deposition to complement NADP wet 18 deposition for MAGIC modeling and for the FA B critical load modeling. CMAQ promotes 19 analytical consistency and efficiency across anal yses of multiple pollutants. EPA’s Office of 20 Research and Development continues to enha nce the underlying deposition science in CMAQ. 21 For the purposes of this policy assessment, CMAQ provides a consistent platform incorporating 22 the atmospheric and deposition species of interest over the entire United States. The caveats and 23 limitations of the use of model predictions are largely associated with the general reliance on 24 calculated values, rather than measurements. Model evaluation addressing the comparison of 25 predictions with observed values is addressed in the REA. Current ly, there are efforts to improve 26 a number of nitrogen re lated processes in CMAQ, recognizi ng comparatively less uncertainty 27
with the treatment of sulfur. Active areas of m odel process improvement are in the treatment of 28 lightning generated NO x and the transference of nitrogen be tween atmospheric and terrestrial and 29 aquatic media, often referred to as bi-directional flux. Lightning NO x potentially provides a 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 114 significant contribution to wet deposition as the resulting NO x is rapidly entrained into aqueous 1 cloud processes. Both the thermodynamics of so il processes and mass tr ansfer of nitrogen 2 species across the surface-atmosphe re interface is governed by an assortment of temperature, 3 moisture, advection and concentr ation patterns. These processes and mass transfer relationships 4 are coupled within the emissions, meteorologi cal, and chemical simulation processes and 5 associated surface/vegetation and terrain informa tion incorporated in or accessed by the CMAQ. 6 In addition to research activities to improve the characterization of nitrog en-related processes in 7 CMAQ, efforts are also underway to improve th e general characterizati on of ammonia emissions 8
which remains as an area of large uncertainty due to limited source data and the ubiquitous 9 nature of these emissions. Another challenge for regional/national air quality modeling is 10 properly representing the effects on pollutant concentrations, precipitation and therefore 11 deposition of variable terrain features, particularly steep m ountain-valley gradients and the 12 interfaces to wide open basins encountered in the Western United States. 13 The CMAQ was used in this assessment becau se it is the state of science model for 14 treating simulating sources, formation, and fate of nitrogen and sulfur species. In addition to 15 undergoing periodic independent scientific pe er review, CMAQ bridges the scientific and 16 regulatory communities as it is used extensivel y by EPA for regulatory air quality assessments 17 and rules. CMAQ provides hourly estimates of the important precursor, intermediate and 18 secondarily formed species associated with atmospheric chemistry and deposition processes 19 influencing ozone, particulate matter concentr ations and sulfur and nitrogen deposition. 20 Simulations based on horizontal spatial scale resolu tions of 12 km and 36 km were used in this 21
PAD for 2002 – 2005. 22



### 4.4 WHAT IS OUR BEST CHARAC TERIZATION OF ATMOSPHERIC 23 

### CONCENTRATIONS OF NO Y 

### AND SO X 

### , AND DEPOSITION OF N 24 

### AND S? 25 Air quality models and blending of mode l results and observations are used to 26
characterize current environmental state conditions due to the relative sparseness of monitoring 27 coverage in sensitive ecosystems as well as gaps in coverage for specific atmospheric species of 28 N and S most relevant to deposition, such as NO y , in available monitoring platforms. 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 115 4.4.1 What are the current atmospheric con centrations of reactive nitrogen, NO y , 1 reduced nitrogen, NH x , sulfur dioxide, SO 2 , and sulfate, SO 4 ? 2 To provide information for use in characteriz ing the adequacy of the current standards, 3 we assess the best available data for estimating the ambient concentrations of the major sources 4 of atmospheric nitrogen and su lfur across the U.S. Acidifi cation and nutrient enrichment 5 processes are largely dependent on the cycling of total nitrogen and su lfur species. From an 6 atmospheric perspective, it is convenient and co nsistent with current measurement and modeling 7
frameworks to consider the reduced and oxidized forms of atmospheric nitrogen. Virtually all 8 atmospheric sulfur is considered oxidized sulf ur in the forms of particulate bound sulfate and 9 gaseous sulfur dioxide. In order to assess curren t concentrations of react ive nitrogen and sulfur 10 we evaluated data available from monitoring th e existing networks as well as from the CMAQ 11 model. Regarding the monitoring data, there are a number of important issues in understanding 12
the measurements of NO y provided by different monitoring ne tworks. In principle, measured 13
NO y is based on catalytic conversion of all oxidized species to NO followed by 14 chemiluminescence NO detection. We recognize the caveats associated with instrument 15 conversion efficiency and possible inlet losses. The CMAQ treats the dominant NO y species as 16 explicit species while the minor contributing non-PAN or ganic nitrogen compounds are 17 aggregated. Atmospheric nitrogen a nd sulfur are largely viewed as regional air quality issues due 18 to the importance of chemical conversion of prim ary emissions into secondarily formed species; 19 a combination of ubiquitous sources, part icularly mobile s ource emissions of NO x , and elevated 20
emissions of NO x and SO 2 that aid pollutant mass dispersal and broader physical transport over 21 large distances. In effect, the regional nature is due to both transport pr ocesses as well as the 22 relatively ubiquitous nature of sources combined with chemical processes that tend to form more 23 stable species with extended atmospheric lifetimes. This regi onalized effect, particularly 24 throughout the Eastern United St ates, dominates the overall pa tterns discussed below of 25 secondarily formed species such as sulfate or NO y , which is an aggregate of species where the 26 more aged air masses consisting largely of chemi cally processed air is dominated by secondarily 27 formed peroxyacetyl nitrate (PAN), pa rticulate nitrate and nitric acid. 28 Nationwide maps of CMAQ-predicted 2005 annual average NO y , NH x (NH 3 and NH4), 29
NH 3 , NH 4 , S T , SO 4 , and SO 2 are provided in figures 4-5 th rough 4-11 respectively. Given the 30 considerable gaps in air quality observation ne tworks as discussed in the REA and ISA (2008), 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 116 modeled concentration patterns are used here to illustrate national representations of current air 1 quality conditions for nitrogen and sulfur. The 2005 model year reflec ts the most recent available 2 simulation for inclusion in this policy assessm ent. In addition, figures 4-12 and 4-13 provide 3 maps of 2005 annual average SO 2 and SO 4 , respectively based on CASTNET observations. Site 4 specific annual average 2005 NO y measured concentrations at SLAMS (Figure 4-14) are 5 typically are less than 40 ppb., The spatial pa tterns for the 2005 modeled and observed NO y and 6
SO 2 concentrations are similar to the 2002 CMAQ -based maps provided in the REA., largely 7 capturing the influence of major source regi ons throughout the nation. A spreading of the 8 oxidized sulfur fields (Figures 4-5 and 4-6), relative to SO 2 , is consistent with sulfate 9 transformation and associated air mass agi ng and transport. Ammonia and ammonium 10 concentration patterns (Figure 4-4) are in fluenced strongly by the ammonia emissions 11 distribution, with marginal spreading associated with the addition of NH 4 . The NH x fields are 12 more strongly influenced by source location, rela tive to sulfur, based on the fast removal of 13 atmospheric ammonia through deposition. Total depos ition for nitrogen and sulfur (Figures 4-15 14 and 4-16) basically follow the patterns of ambient air concentrations. 15
Current conditions indicate that the current SO 2 and NO 2 secondary standards are not 16 exceeded (Figures 4-17 and 4-18) in locations wh ere ecological effects have been observed, and 17 where critical loads of nitrogen a nd sulfur are exceeded. This is c onsistent with the fact that NO 2 18 accounts for only a fraction of NO y , and thus reductions in NO 2 emissions would not be expected 19 to fully address concentrations of NO y . The map in Figure 4-19 furthe r illustrates this point by 20 showing that the contribution of NO 2 to NO y is often less than 50% in rural areas. 21Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 117 1 Figure 4-5. 2005 CMAQ modeled annual average NO y (ppb). These maps will be 2 replaced with full CONUS maps in the next draft. 3

4Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 118 1 Figure 4-6. 2005 CMAQ modeled annual average total reduced nitrogen (NH x ) 2 (as μ g/m 3 nitrogen) 3

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March 2010 Draft – Do Not Quote or Cite 119 1 Figure 4-7. 2005 CMAQ modeled annual average ammonia, NH 3 , (as μ g/m 3 N) 2

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March 2010 Draft – Do Not Quote or Cite 120 1 Figure 4-8. 2005 CMAQ modeled annual average ammonia, NH4, (as μ g/m 3 N) 2

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March 2010 Draft – Do Not Quote or Cite 121 1 Figure 4-9. 2005 CMAQ modeled annual average SO x , (as μ g/m 3 S from SO 2 and 2 SO 4 ). 3

4 5Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 122 1 Figure 4-10. 2005 CMAQ modeled annual average SO 2 (as μ g/m 3 S) 2

3Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 123 1 Figure 4-11. 2005 CMAQ modeled annual average SO 4 (as μ g/m 3 S). 2

3Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 124 1 Figure 4-12. 2005 annual average sulfur dioxide concentrations based on 2 CASTNET generated by the Visibility Information Exchange Web Sysytem 3 (VIEWS). 4

5 Figure 4-13. 2005 annual average sulfate concentrations based on CASTNET 6 generated by the Visibility Informat ion Exchange Web Sysytem (VIEWS). 7

8Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 125 1 Figure 4-14. Annual average 2005 NO y concentrations from reporting stations in 2 AQS. 3

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March 2010 Draft – Do Not Quote or Cite 126 1 Figure 4-15. 2005 CMAQ modeled Oxidized Nitrogen Deposition (kgN/Ha/Yr). 2

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March 2010 Draft – Do Not Quote or Cite 127 1 Figure 4-16. 2005 CMAQ modeled Oxidized Sulf ur Deposition (kgS/Ha/Yr). 2

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March 2010 Draft – Do Not Quote or Cite 128 1 Figure 4-17. Three hour average maximum 2005 SO 2 concentrations based on the 2 SLAMS reporting to EPA’s Air Quality System (AQS) data base. The current 3 SO 2 secondary standard based on the ma ximum 3 hour average value is 500 ppb, 4 a value not exceeded. While there are obvious spatial gaps, the majority of these 5 stations are located to ca pture maximum values generally in proximity to major 6 sources and high populations. Lower relative values are expected in more remote 7 acid sensitive areas. 8

9Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 129 1 Figure 4-18. Annual average 2005 NO 2 concentrations based on the SLAMS 2 reporting to EPA’s Air Quality System (AQS) data base. The current NO 2 3 secondary standard is 53 ppb, a value we ll above those observed. While there are 4 obvious spatial gaps, the stations are located in areas of relatively high 5 concentrations in highly populated areas. Lower relative values are expected in 6 more remote acid sensitive areas. 7

8Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 130 1 Figure 4-19. 2005 CMAQ derived annual average ratio of (NO y – NO 2 )/NO y . The 2 fraction of NO 2 contributing to total NO y generally is less than 50% in the 3 Adirondack and Shenandoah case study areas. The ratio reflects the relative air 4 mass aging associated with transforma tion of oxidized nitrogen beyond NO and 5 NO 2 as one moves from urban to rural locations. 6


### 4.5 ARE ADVERSE EFFECTS ON THE PUBLIC WELFARE 7 

### OCCURRING UNDER CURRENT AIR QUALITY CONDITIONS 8 

### FOR NO 2 

### AND SO 2 

### AND WOULD THEY OCCUR IF THE NATION 9 

### MET THE CURRENT SECONDARY STANDARDS? 10 The previous sections have established that almost all areas of the U.S. were at 11
concentrations of SO 2 and NO 2 below the levels of the current standards. In many locations, SO 2 12
and NO 2 concentrations are substantially below the le vels of the standards. This suggests that 13 levels of deposition and any effects on ecosystems due to deposition of NO x and SO x under 14Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 131 recent conditions are occurring even though areas m eet or are below current standards. This 1 section focuses on summarizing the evidence of e ffects occurring at depos ition levels consistent 2
with recent conditions. 3
The ISA summarizes the available studies of relative nitrogen contribution and finds that 4 in much of the U.S., NO x contributes from 50 to 75 percen t of total atmospheric deposition [ ISA 5
Section 2.8.4 ]. While the proportion of total nitrogen loadings asso ciated with atmospheric 6 deposition of nitrogen varies across locations (N deposition in the Eastern U.S. includes 7 locations with greater than 9 kg N/ha/year, and in the central U. S. high deposition locations with 8 values on the order of 6 to 7 kg N/ha/year), the ISA indicates th at atmospheric N deposition is 9 the main source of new anthropogenic N to most headwater streams, high elevation lakes, and 10 low-order streams. Atmospheric N deposition cont ributes to the total N load in terrestrial, 11 wetland, freshwater, and estuarine ecosystems th at receive N through multiple pathways. In 12 several large estuarine systems, including th e Chesapeake Bay, atmospheric deposition accounts 13 for between 10 and 40 percent of total nitrogen loadings. 14 Atmospheric concentrations of SO x account for nearly all S deposition in the US. For the 15 period 2004–2006, mean S deposition in the U.S. was greatest east of the Mi ssissippi River with 16 the highest deposition amount, 21.3 kg S/ha/yr, in the Ohio River Valley where most recording 17 stations reported 3 year averages >10 kg S/ha/yr. Numerous other stations in the East reported S 18 deposition >5 kg S/ha/yr. Total S deposition in the U.S. west of the 100th meridian was 19 relatively low, with all recording stations reporting <2 kg S/ha/yr and many reporting <1 kg 20 S/ha/yr. S was primarily deposited in the form of wet SO 4 2

− followed in decreasing order by a 21 smaller proportion of dry SO 2 and a much smaller proportion of deposition as dry SO 4 2

−

. 22
New scientific evidence exists to address each of the areas of uncer tainty raised in the 23 previous reviews (summarized above). Based on the new evidence, the current ISA concludes 24
that: 25 (1) The evidence is sufficient to infer a ca usal relationship betwee n acidifying deposition 26 (to which both NO x and SO x contribute) and effects on biogeochemistry related to 27 terrestrial and aquatic ecosys tems; and biota in terrestri al and aquatic ecosystems. 28 (2) The evidence is sufficient to infer a causal relationship between N deposition, to 29
which NO x and NH x contribute, and the alteration of A) biogeochemical cycling of N 30 and carbon in terrestrial, wetland, freshwater aquatic, and coastal marine ecosystems; 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 132 B) biogenic flux of methane (CH4), and N 2 O in terrestrial and wetland ecosystems; 1 and C) species richness, species compositi on, and biodiversity in terrestrial, wetland, 2 freshwater aquatic and co astal marine ecosystems. 3 (3) The evidence is sufficient to infer a causal relationship between S deposition and 4 increased Hg methylation in we tlands and aquatic environments. 5 Subsequent to the previous review of the NO x secondary standard, a great deal of 6 information on the contribution of atmosphe ric deposition associated with ambient NO x has 7 become available. Chapter 3 of the REA provi des a thorough assessment of the contribution of 8
NO x to nitrogen deposition throughout the U.S., and the relative contributions of ambient NO x 9 and reduced forms of nitrogen. Staff conclude s that based on that analysis, ambient NO x is a 10 significant component of atmosphe ric nitrogen deposition, even in areas with relatively high 11 rates of deposition of reduced nitrogen. In addi tion, staff initially concludes that atmospheric 12 deposition of oxidized nitrogen co ntributes significantly to total nitrogen loadings in nitrogen 13 sensitive ecosystems. 14 As discussed throughout the ri sk and exposure assessment document, there are several 15 key areas of risk that are associated with ambient concentrations of NO x and SO x . In previous 16
reviews of the NO x and SO x secondary standards, th e standards were designed to protect against 17 direct exposure of plants to ambient concentrat ions of the pollutants. A significant shift in 18 understanding of the effects of NO x and SO x has occurred since the la st reviews, reflecting the 19 large amount of research that has been conducte d on the effects of depos ition of nitrogen and 20 sulfur to ecosystems. The most significant risks of adverse effects to public welfare are those 21 related to deposition of NO x and SO x to both terrestrial and aquatic ecosystems. These risks fall 22 into two categories: acidification and nutrient enrichment. These made up the emphasis of the 23 REA, and are most relevant to evaluating the ad equacy of the existing standards in protecting 24 public welfare from adverse ecological effects. 25Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 133 4.5.1 To what extent do the current NO x and SO x secondary standards provide 1 protection from adverse effects associated with deposition of atmospheric 2
NO x , and SO x which results in acidification in sensitive aquatic and 3 terrestrial ecosystems? 4
The focus of the REA case studies was on dete rmining whether deposition of sulfur and 5 oxidized nitrogen in locations where ambient NO x and SO x was at or below the current standards 6 was resulting in acidification and related eff ects. This review has focused on identifying 7 ecological indicators that can link atmospheric de position to ecological effects associated with 8
acidification. NO x and SO x contribute to acidific ation in both aquatic and terrestrial ecosystems, 9 although the indicators of effects differ. While there are some geographic areas with both 10 terrestrial and aquatic ecosyste ms that are vulnerable to acidi fication, the case study areas do not 11 fully overlap. Figure 4-20 shows the locations of the case studies evaluated in the REA. 12

13 Figure 4-20. National map highlighting the 9 cas e study areas evaluated in the 14 REA. 15Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 134 4.5.1.1 Aquatic Acidification 1
Based on the case studies conducted for la kes in the Adirondacks and streams in 2 Shenandoah National Park, staff conc ludes that there is significant risk to acid sensitive aquatic 3 ecosystems at atmospheric concentrations of NO x and SO x at or below the current standards. 4 This conclusion is based on application of the MAGIC model to estimate the effects of 5 deposition at levels consistent with atmospheric NO x and SO x concentrations that are at or below 6 the current standards. An important ecological in dicator for aquatic acidification effects is ANC, 7 measuring the acid buffering capacity of a wa terbody, and the case study focused on evaluating 8 whether locations were likely to be below cr itical values of ANC given deposition levels 9
associated with NO x and SO x concentrations that meet the curr ent standards. In addition, the case 10 studies assessed the ecological effects and some of the known ecosystem services that are 11
associated with different levels of ANC in order to associat e the ecological indicator with 12 measures of public welfare that may be adversel y affected by deposition levels consistent with 13
concentrations of NO x and SO x that meet the current standards. 14
Staff concludes that the evidence and risk assessment support strongly a relationship 15 between atmospheric deposition of NO x and SO x and ANC, and that ANC is an excellent 16 indicator of aquatic acidification. St aff also concludes that at levels of deposition associated with 17
NO x and SO x concentrations at or below the current st andards, ANC levels are expected to be 18 below benchmark values that are associated with significant losses in fish species richness ( REA 19 Section 4)

. 20 Many locations in sensitive ar eas of the U.S. have ANC levels below benchmark levels 21 for ANC classified as severe, elevated, or moderate concern (see Figure 2-1). The average 22
current ANC levels across 44 lakes in the Adirondack case study area is 62.1 (moderate 23 concern), however, 44 percent of lakes had depos ition levels exceeding the critical load for an 24 ANC of 50, and 28 percent of lakes had deposition levels exceeding the critical load for an ANC 25 of 20 μeq/L ( REA Section 4.2.4.2 ). This indicates that almost half of the 44 lakes in the 26 Adirondacks case study area are at an elevated concern levels, and al most a third are at a severe 27
concern level. These levels are associated with greatly reduced fish species diversity, and losses 28 in the health and reproductive capacity of remaining populations . Based on assessments of the 29 relationship between number of fish species and ANC leve l in both the Adirondacks and 30 Shenandoah areas, the number of fi sh species is decreased by ove r half at an ANC level of 20 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 135 μeq/L relative to an ANC level at 100 μeq/L ( REA Figure 4.2-1 ). At levels below 20 μeq/L, 1 populations of sensitive species, such as brook tr out, may decline significantly during episodic 2 acidification events. When extrapolated to the full population of lakes in the Adirondacks area 3 using weights based on the EMAP probability survey ( REA 4.2.6.1) , 36 percent of lakes 4 exceeded the critical load for an ANC of 50 μeq/ L and 13 percent of lakes exceeded the critical 5 load for an ANC of 20 μeq/L. 6 Many streams in the Shenandoah case study area also have levels of deposition that are 7
associated with ANC levels classified as seve re, elevated, or moderate concern. The average 8
ANC under recent conditions for the 60 streams ev aluated in the Shenandoah case study area is 9 57.9, indicating moderate concern. However, 85 percent of streams had recent deposition 10 exceeding the critical load for an ANC of 50 μeq/L, and 72 percent exceeded the critical load for 11 an ANC of 20 μeq/L. As with the Adirondacks area, this suggests that significant numbers of 12
sensitive streams in the Shenandoah area are at risk of adverse impacts on fish populations under 13 recent conditions. Many other streams in the Shena ndoah area are likely to experience conditions 14 of elevated to severe concern based on the pr evalence in the area of bedrock geology associated 15 with increased sensitivity to acidification suggesti ng that effects due to stream acidification could 16 be widespread in the Shenandoah area ( REA 4.2.6.2 ). 17 The ISA notes that large portions of the Easter n U.S. are acid sensitiv e, and that current 18 deposition levels exceed those that would allow r ecovery of the most acid sensitive lakes in the 19 Adirondacks ( ISA ES ). In addition, because of past lo adings, areas of the Shenandoah are 20 sensitive to current deposition levels ( ISA ES ). Much of the West is naturally less sensitive to 21 acidification, and as such, less focus is placed on the adequacy of the existing standards in these 22 areas, with the exception of the mountainous areas of the West, whic h experience episodic 23 acidification due to deposition. 24 While most (99 percent) of stream kilometers in the U.S. are not chronically acidified 25 under current conditions, a recent survey found sens itive streams in many locations in the U.S., 26 including the Appalachian mountains, the Co astal Plain, and the Mountainous West ( ISA 27
Section 4.2.2.3 ). In these sensitive areas , between 1 and 6 percent of stream kilometers are 28 chronically acidified. 29 The ISA notes that “consideration of episodi c acidification greatly increases the extent 30 and degree of estimated effects for acidifying deposition on surface waters.” ( ISA Section 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 136 3.2.1.6 ) Some studies show that the number of lakes th at could be classified as acidified based on 1 episodic acidification is 2 to 3 times the number of lakes classified as acidified based on chronic 2 ANC. These episodic acidification events can ha ve long term effects on fish populations ( ISA 3
Section 3.2.1.6 ). Under recent conditions, episodic acidif ication has been observed in locations 4 in the Eastern U.S. and in the Mountainous Western U.S. ( ISA Section 3.2.1.6 ). 5
It can therefore be conclude d that recent levels of NO x and SO x are associated with 6 deposition that leads to ANC values below benc hmark values known to cause ecological harm in 7 sensitive aquatic systems, incl uding lakes and streams in multiple areas of the U.S. These 8 changes are known to have impacts on ecosystem services such as reductions in recreational 9 fishing. While other ecosystem services (e.g. habitat provisioning, s ubsistence fishing, and 10 biological control as well as many others) are potentially a ffected by reductions in ANC, 11 confidence in the specific translation of ANC values to these additional ecosystem services is 12
much lower. 13

4.5.1.2 Terrestrial Acidification 14 Based on the case studies on sugar maple and red spruce habitat, staff concludes that 15 there is significant risk to terrestrial ecosystems from acidification at atmospheric concentrations 16
of NO x and SO x at or below the current standards. This conclusion is based on application of the 17 simple mass balance model to depo sition levels associated with NO x and SO x concentrations at 18 or below the current standards. The ecological indicat or selected for terrestrial acidification is the 19 base cation to aluminum ratio (BC:Al), which has been linked to tree health and growth. The 20 results of the REA strongly support a relatio nship between atmospheric deposition of NO x and 21
SO x and BC:Al, and that BC:Al is a good indicator of terrestrial acidifi cation. At levels of 22 deposition associated with NO x and SO x concentrations at or below the current standards, BC:Al 23 levels are expected to be belo w benchmark values that are associated with significant losses in 24 tree health and growth. Such de gradation of terrestrial ecosy stems could affect ecosystem 25 services such as habitat provisioning, endange red species, goods production (timber, syrup, etc.) 26 and many others. 27 Many locations in sensitive areas of the U.S. have Bc/Al levels below benchmark levels 28 classified as providing low to intermediate levels of protection to tree hea lth. At a Bc/Al ratio of 29 1.2 (intermediate level of protect ion), red spruce growth can be reduced by 20 percent. At a 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 137 Bc/Al ratio of 0.6 (low level of protection), s ugar maple growth can be reduced by 20 percent. 1 The REA did not evaluate broad sensitive regions. However, in the sugar maple case study area 2 (Kane Experimental Forest), recent deposition leve ls are associated with a Bc/Al ratio below 1.2, 3 indicating between intermediate and low level of protection, which would indicate the potential 4 for a greater than 20 percent reduction in grow th. In the red spruce case study area (Hubbard 5 Brook Experimental Forest), recent deposition levels are associated with a Bc/Al ratio slightly 6 above 1.2, indicating slightly better than an intermediate level of protection ( REA Section 7
4.3.5.1 ). 8 Over the full range of sugar maple, 12 per cent of evaluated forest plots exceeded the 9 critical load for a Bc/AL ratio of 1.2, and 3 percen t exceeded the critical lo ad for a Bc/Al ratio of 10 0.6. However, there was large variability across states. In New Jersey, 67 percent of plots 11
exceeded the critical load for a Bc/Al ratio of 1.2, while in severa l states on the outskirts of the 12 range for sugar maple, e.g. Arkansas, Illinois, no pl ots exceeded the critical load for a Bc/Al ratio 13 of 1.2. For red spruce, overall 5 percent of plots exceeded the critical load for a Bc/Al ratio of 14 1.2, and 3 percent exceeded the critical load fo r a Bc/Al ratio of 0.6. In the major red spruce 15 producing states (Maine, New Hampshire, and Verm ont), critical loads fo r a Bc/AL ratio of 1.2 16 were exceeded in 0.5, 38, and 6 percent of plots. 17 The ISA reported one study that estimated 15 percent of U.S. forest ecosystems exceeded 18 the critical loads for acidity for N and S depos ition by >250 eq/ha/year under current conditions 19 ( ISA Section 4.2.1.3 ). Staff believes that this represents a significant portion of sensitive 20 terrestrial ecosystems. 21
It can therefore be conclude d that recent levels of NO x and SO x are associated with 22 deposition that leads to BC:Al values below be nchmark values that cause ecological harm in 23 some sensitive terrestrial ecosystems. While eff ects are more widespread for sugar maple, there 24
are locations with low to intermediate levels of protection from effects on both sugar maple and 25 red spruce. While there are many other ecosyst em services, including timber production, natural 26 habitat provision, and regulation of water, c limate, and erosion, potentially affected by 27 reductions in BC:Al, linkages of BC:Al values to these additional ecosystem services is on the 28
whole not well understood. 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 138 4.5.2 To what extent does the current NO x secondary standard provide protection 1
from adverse effects associated wi th deposition of atmospheric NO x , which 2
results in nutrient enrich ment effects in sensitiv e aquatic and terrestrial 3 ecosystems? 4
Nutrient enrichment effects are due to nitr ogen loadings from bot h atmospheric and non5 atmospheric sources. Evaluation of nutrient enri chment effects requires an understanding that 6 nutrient inputs are essential to ecosystem health. The specific long term levels of nutrients in a 7 system affect the types of species that occur ov er long periods of time. Short term additions of 8 nutrients can affect species competition, and even small additions of nitr ogen in areas that are 9 traditionally nutrient poor can have significant impacts. In certain limited situations, additions of 10 nitrogen can increase rates of gr owth, and these increases can have short term benefits in certain 11 managed ecosystems. As noted earlier, this re view of the standards is focused on unmanaged 12 ecosystems. As a result, in assessing adequacy of the current standards, we are focusing on the 13
adverse effects of nutrient enrichment in unm anaged ecosystems. However, the following 14 discussion provides a brief assessment of effects in managed ecosystems. 15 Impacts of nutrient enrichment in mana ged ecosystems may be positive or negative 16 depending on the levels of nutrients from other s ources in those areas. Positive effects can occur 17 when crops or commercial fo rests are not receiving enough nitrogen nutrients. Nutrients 18 deposited on crops from atmospheric sources ar e often referred to as passive fertilization. 19 Nitrogen is a fundamental nut rient for primary production in both managed and unmanaged 20 ecosystems. Most productive agricult ural systems require external so urces of nitrogen in order to 21 satisfy nutrient requirements. Nitr ogen uptake by crops varies, but typical requirements for wheat 22 and corn are approximately 150 kg/ha/yr and 300 kg/ha/yr, respectivel y (NAPAP, 1990). These 23 rates compare to estimated rates of passive nitrog en fertilization in the range of 0 to 5.5 kg/ha/yr 24 (NAPAP, 1991). 25 Information on the effects of changes in pa ssive nitrogen deposition on forestlands and 26 other terrestrial ecosystems is very limited. The mu ltiplicity of factors affecting forests, including 27 other potential stressors such as ozone, and limiting factors such as moisture and other nutrients, 28 confound assessments of marginal changes in any one stressor or nutrient in forest ecosystems. 29 The ISA notes that only a fraction of the deposited nitrogen is taken up by the forests, most of 30 the nitrogen is retained in the soils ( ISA 3.3.2.1 ). In addition, the ISA indicates that forest 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 139 management practices can significan tly affect the nitrogen cycling within a forest ecosystem, and 1 as such, the response of managed forests to NO x deposition will be variable depending on the 2 forest management practices employed in a given forest ecosystem ( ISA Annex C C.6.3 ) 3 Increases in the availability of nitrogen in N-limited forests via atmospheric deposition could 4 increase forest production over large non-managed areas, but the evidence is mixed, with some 5 studies showing increased pr oduction and other showing li ttle effect on wood production (ISA 6 3.3.9) . Because leaching of nitrate can promote cation losses, which in some cases create nutrient 7 imbalances, slower growth and lessened disease a nd freezing tolerances for forest trees, the net 8
effect of increased N on forest s in the U.S. is uncertain (ISA 3.3.9). 9 In managed agricultural ecosystems, n itrogen inputs from atmospheric NO x comprise a 10 small fraction (less than 3 percen t) of total nitrogen inputs, whic h include commercially applied 11 fertilizers as well as applications of composted manure. And because of the temporal and spatial 12 variability in atmospheric deposition of NO x , it is unlikely that farmers would alter their 13
fertilization decisions based on expected nitrogen inputs from NO x . And, in some locations, 14 farmers need less nitrogen inputs due to producti on of excess nitrogen th rough livestock. In some 15 locations, nitrogen production thro ugh livestock waste exceeds the absorptive capacity of the 16 surrounding land, and as such, excess nitrogen from deposition of NO x in those locations reduces 17 the capacity of the system to dispose of excess nitrogen, potentially increa sing the costs of waste 18 management from livestock operations (Letson and Gollehon, 1996). A USDA Economic 19 Research Service report found that in 1997, 68 counties with high le vels of confined livestock 20 production had manure nitrogen levels that excee d the assimilative capacit y of all the county’s 21 crop and pasture land (Gollehon et al, 2001). In t hose locations, additional nitrogen inputs from 22
NO x deposition will result in excess nitrogen, leading to nitrogen leaching and associated effects. 23

4.5.3 Aquatic Nutrient Enrichment 24
The REA case studies focused on coastal estuaries and revealed that while current 25 ambient loadings of atmospheric NO x are contributing to the overall depositional loading of 26 coastal estuaries, other non-atmospheric sources ar e contributing in far greater amounts in total, 27 although atmospheric contributions are as large as some othe r individual source types. The 28 ability of current data and models to characterize the increm ental adverse impacts of nitrogen 29 deposition is limited, both by the av ailable ecological indicators, a nd by the inability to attribute 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 140 specific effects to atmospheric sources of nitr ogen. The REA case studies used as the ecological 1 indicator for aquatic nutrient enrichment, an in dex of eutrophication known as the Assessment of 2 Estuarine Trophic Status Eutrophication Index (ASS ETS EI). This index is a six level index 3 characterizing overall eutrophicatio n risk in a waterbody. This i ndictor is not sensitive to 4 relatively large changes in nitrog en deposition. In addition, this t ype of indicator does not reflect 5 the impact of nitrogen deposition in conj unction with other s ources of nitrogen. 6 For example, if NO x deposition is contributing nine tenths of the nitrogen loading 7 required to move a waterbody from an ASSETS EI category of “moderate” to a category of 8 “poor”, zeroing out NO x deposition will have no impact on the ASSETS EI value. However, if 9 an area were to decide to put in place decreases in nitrogen loadings to move that waterbody 10 from “poor” to “moderate,” the area would have to reduce the full am ount of the loadings 11 through other sources if atmospheri c deposition were not considere d. Thus, the adverse impact of 12 atmospheric nitrogen is in its contribution to the overall loading, and reductions in NO x will 13
decrease the amount of reductions from other sour ces of nitrogen loadings that would be required 14
to move from a lower ASSETS EI category to a higher category. NO x deposition can also be 15 characterized as reducing the risk of a waterbody moving from a higher ASSETS EI category to 16 a lower category, by reducing the vu lnerability of that waterbody to increased loadings from 17 non-atmospheric sources. 18 Based on the above considerations, staff prelim inarily concludes that the ASSETS EI is 19 not an appropriate ecological indicator for estuarine aquatic eutrophication. Staff further 20
concludes that additional analysis is required to develop an appropriate indicator for determining 21 the appropriate levels of protec tion from N nutrient enrichment effects in estuaries related to 22 deposition of NO x . As a result, staff is unable to make a determination as to the adequacy of the 23 existing secondary NO x standard in protecting public welfar e from N nutrient enrichment effects 24 in estuarine aquatic ecosystems. 25 Additionally, nitrogen deposition can alter species com position and cause eutrophication 26 in freshwater systems. In the Rocky Mountai ns, for example, deposition loads of 1.5 to 2 27 kg/ha/yr which are well within current ambient levels are know n to cause changes in species 28 composition in diatom communities i ndicating impaired water quality ( ISA Section 3.3.5.3 ). It 29 then seems apparent then that th e existing secondary standard for NO x does not protect such 30 ecosystems and their resulting services from impairment. 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 141 4.5.4 Terrestrial Nutrient Enrichment 1 The scientific literature has many examples of the deleterious effects caused by excessive 2 nitrogen loadings to terrestrial systems. Several studies have set benchmark values for levels of 3 N deposition at which scientifically adverse eff ects are known to occur. These benchmarks are 4 discussed more thoroughly in Chapter 5 of the RE A. Large areas of the country appear to be 5 experiencing deposition above these benchmarks for example, Fenn et al. (2008) found that at 6 3.1 kg N/ha/yr, the community of lichens begins to change from acidophytic to tolerant species; 7 at 5.2 kg N/ha/yr, the typical dominance by acid ophytic species no longer occurs; and at 10.2 kg 8 N/ha/yr, acidophytic lichens are totally lost fr om the community. Additional studies in the 9 Colorado Front Range of the Rocky Mountain National Park support th ese findings and are 10 summarized in Chapter 6.0 of the Risk and Exposure Assessment . These three values (3.1, 5.2, 11 and 10.2 kg/ha/yr) are one set of ecologically meaningful benchmarks for the mixed conifer 12 forest (MCF) of the pacific coast regions. Nearly all of the known sensitive communities receive 13 total nitrogen deposition levels above the 3.1 N kg/ha/yr ecological be nchmark according to 14 the12 km, 2002 CMAQ/NADP data, with the excep tion of the easternmost Sierra Nevadas. 15 MCFs in the southern portion of the Sierra Ne vada forests and nearly all MCF communities in 16 the San Bernardino forests receive total nitrog en deposition levels above the 5.2 N kg/ha/yr 17 ecological benchmark. 18 Coastal Sage Scrub communities (CSS) are al so known to be sensitive to community 19 shifts caused by excess nitrogen lo adings. Wood et al. (2006) inve stigated the amount of nitrogen 20 utilized by healthy and degraded CSS systems. In healthy stands, the au thors estimated that 3.3 21 kg N/ha/yr was used for CSS plant growth (Wood et al., 2006). It is assumed that 3.3 kg N/ha/yr 22 is near the point where nitrogen is no longe r limiting in the CSS community. Therefore, this 23 amount can be considered an ecological benchmar k for the CSS community. The majority of the 24 known CSS range is currently r eceiving deposition in excess of this benchmark. Thus, staff 25
concludes that recent conditions where NO x ambient concentrations ar e at or below the current 26
NO x secondary standards are not adequate to prot ect against anticipated adverse impacts from N 27 nutrient enrichment in sensitive ecosystems (systems where N is not limiting). 28Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 142 

### 4.6 TO WHAT EXTENT DO THE CURRENT NO X 

### AND/OR SO X 1 

### SECONDARY STANDARDS PROV IDE PROTECTION FROM 2 

### OTHER ECOLOGICAL EFFE CTS (E.G., MERCURY 3 

### METHYLATION) ASSOCIATED WITH THE DEPOSITION OF 4 

### ATMOSPHERIC NO X 

### , AND/OR SO X 

### ? 5 It is stated in the ISA ( ISA Sections 3.4.1 and 4.5 ) that mercury is a highly neurotoxic 6
contaminant that enters the food web as a methylated compound, methylmercury. Mercury is 7 principally methylated by sulfur-reducing bact eria and can be taken up by microorganisms, 8 zooplankton and macroinvertebrates. The contamin ant is concentrated in higher trophic levels, 9 including fish eaten by humans. Experimental ev idence has established th at only inconsequential 10 amounts of methylmercury can be produced in th e absence of sulfate. Once methylmercury is 11 present, other variables influence how much accumu lates in fish, but elevated mercury levels in 12 fish can only occur where substantial amounts of methylmercury are present. Current evidence 13
indicates that in watersheds wher e mercury is present, increased SO x deposition very likely 14 results in additional production of methylmercur y which leads to greater accumulation of MeHg 15 concentrations in fish (Munthe et al, 2007; Drevnick et al., 2007). 16 The production of meaningful amounts of me thylmercury (MeHg) requires the presence 17
of SO 4 2- and mercury, and where mercury is pr esent, increased availability of SO 4 2- results in 18 increased production of MeHg. Th ere is increasing evidence on th e relationship between sulfur 19 deposition and increased methylatio n of mercury in aquatic environm ents; this effect occurs only 20 where other factors are present at levels within a range to a llow methylation. The production of 21 methylmercury requires the presen ce of sulfate and mercury, but the amount of methylmercury 22 produced varies with oxygen content, temperatur e, pH, and supply of labile organic carbon ( ISA 23
Section 3.4 ). In watersheds where changes in sulfate deposition did not produce an effect, one or 24 several of those interacting factor s were not in the range required for meaningful methylation to 25 occur ( ISA Section 3.4 ). Watersheds with conditions know n to be conducive to mercury 26 methylation can be found in the northeastern United States and southeastern Canada. The 27 relationship between sulfur and methylmercury pr oduction is addressed qual itatively in Chapter 28 6 of the Risk and Exposure Assessment. 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 143 With respect to sulfur deposition and merc ury methylation, the final ISA determined: The 1 evidence is sufficient to infer a causal rela tionship between sulfur deposition and increased 2 mercury methylation in wetl ands and aquatic environments. However, staff did not conduct a 3 quantitative assessment of the risks associated w ith increased mercury me thylation under current 4 conditions. As such, staff are unabl e to make a determination as to the adequacy of the existing 5
SO 2 standards in protecting against welfare e ffects associated with increased mercury 6 methylation. 7

4.7 REFERENCES 8 B.J. Finlayson-Pitts and J.N. Pitts, 2000, Chemistry of the Upper and Lower Troposhere, 9 Academic Press, San Diego, CA 10

Drevnick, P.E., D.E. Canfield, P.R. Gorski, A. L.C. Shinneman, D.R. Engstrom, D.C.G. Muir, 11 G.R. Smith, P.J. Garrison, L.B. Cleckner, J.P. Hurley, R.B. Noble, R.R. Otter, and J.T. 12 Oris. 2007. Deposition and cycling of sulfur controls mercury accumulation in Isle 13 Royale fish. Environmental Science and Technology 41 (21):7266–7272. 14

Fenn, M.E., S. Jovan, F. Yuan, L. Geiser, T. Meixner, and B.S. Gimeno. 2008. Empirical and 15 simulated critical loads for nitrogen deposit ion in California mixed conifer forests. 16
Environmental Pollution 155 (3):492–511. 17

Munthe, J., R.A. Bodaly, B.A. Br anfireun, C.T. Driscoll, C.C. Gilm our, R. Harris, M. Horvat, M. 18 Lucotte, and O. Malm. 2007. Recovery of mercury-contaminated fisheries. Ambio 36 :33– 19
44. 20

Scheffe, R.D., P. A. Solomon, R. Husar, T. Ha nley, M. Schmidt, M. Koerber, M. Gilroy, J. 21 Hemby, N. Watkins, M. Papp, J. Rice, J. Tikvart and R. Valentinetti, The National 22 Ambient Air Monitoring Strategy: Rethinking the Role of National Networks, JAWMA, 23
ISSN:1047-3289 J. Air & Waste Manage. Assoc. 2009, 59:579–590 DOI:10.3155/1047- 24
3289.59.5.579 25

U.S. EPA (Environmental Protection Agency). 1982. Review of the National Ambient Air Quality 26 Standards for Sulfur Oxides: Assessment of Scientific and Tec hnical Information

. 27Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 144 OAQPS Staff Paper. EPA-450/5-82-007. U.S. E nvironmental Protection Agency, Office 1 of Air Quality Planning and Standard s, Research Triangle Park, NC. 2

U.S. EPA (Environmental Protection Agency). 1995. Review of the National Ambient Air Quality 3 Standards for Nitrogen Dioxide: Assessment of Scientific and T echnical Information

. 4 OAQPS Staff Paper. EPA-452/R- 95-005. U.S. Environmental Protection Agency, Office 5 of Air Quality Planning and Standards, Research Triangle Park, NC. September. 6

U.S. EPA (Environmental Protection Agency). 2008. Integrated Science Assessment (ISA) for 7 Oxides of Nitrogen and Sulfur–Ecolog ical Criteria (Final Report). EPA/600/R8 08/082F. U.S. Environmental Protection Agen cy, National Center for Environmental 9 Assessment–RTP Division, Office of Research and Development, Research Triangle 10 Park, NC. Available at http://cfpub.epa .gov/ncea/cfm/recordisplay.cfm?deid=201485. 11

Wood, Y., T. Meixner, P.J. Shouse, and E. B. Allen. 2006. Altered Ecohydrologic response 12 drives native shrub loss under conditions of elevated N-deposition. Journal of 13 Environmental Quality 35 :76–92. 14

15Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 145 

### 5. CONCEPTUAL DESIGN OF 

## AN ECOLOGICALLY RELEVANT 1


### MULTI-POLLUTANT STANDARD 2
The objective of this chapter is to describe the conceptual design for a national ambient 3 air quality standard that links ecological indicators of concern to ambient air indicators of NO x 4
and SO x . In Chapter 4 of this policy assessment, th e limitations of the design of the current 5 secondary standards are described as they a pply to protection of sensitive ecosystems. The 6 conceptual design described in this chapter a ddresses those limitations . The overall concept for 7 the standards starts by recognizing that the fundamental welfare e ffects associated with ambient 8
NO x and SO x occur through the process of deposition to sensitive ecosystems. As detailed in 9 Chapter 4, previous NO x and SO x NAAQS reviews only considered effects to vegetation via 10 stomatal exposure. There is now sufficient data to link atmospheric con centrations to adverse 11 effects in ecosystems that are caused by expos ure via deposition to soils and surface waters. 12 Deposition is a direct consequence of atmospheric concentration; however it is also modified by 13 factors that vary across the landscape (e.g. el evation and groundcover). Likewise, ecological 14 response to deposition can vary according to eco system sensitivity and the ecological indicator 15 of concern. This is the first time a secondarystandard for deposition effects related to NO x and 16
SO x has been developed; therefore the conceptual de sign of a potential standa rd is described here 17 prior to the specific details on the indicator, leve l, form and averaging time for such a potential 18 standard that are presented in chapter 6. 19



### 5.1 COMPONENTS OF THE DESIGN 20 There are four main components to the con ceptual design of the standard: atmospheric 21 and ecological indicators, deposition metrics, f unctions that relate i ndicators to deposition 22 metrics and factors that modify the functions. These components of the design are illustrated in 23 Figure 5-1. The squares represent indicators. Ecological indicator s are chemical or biological 24 components of the ecosystem that can be linke d to N and S deposition based on scientific 25 evidence. Air quality indicators are the chemical sp ecies of the criteria air pollutants that best 26 represent the atmospheric pollutants that caus e ecological harm in the criteria pollutant 27 categories of oxides of nitrogen and oxides of su lfur. Triangles indicate functions in which two 28 variables are related. The ecologi cal effect function is the rela tionship between the ecological 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 146 indicator and deposition over a range of values. The atmosphe ric deposition transformation 1 function is the relationship betw een deposition and the atmosphe ric concentration of an air 2 quality indicator. The circles represent factor s which will modify the functions. Modifying 3 factors can vary across the landscape. The spatia l heterogeneity of modifying factors can be 4 challenging to characterize, and therefore in some cases we present multiple options for how to 5 incorporate them into the design. 6

7 Fig 5-1. Schematic diagram of the conceptual design of the standard. 8

5.1.1 For which effects is there sufficient in formation to support setting standards? 9 After review of the ISA and REA, CASAC conc luded that aquatic ac idification should be 10 the focus for developing a multi-pollutant standa rd, based on the quantity and quality of data. 11 CASAC also recommended that, in addition to aquatic acidifi cation, the EPA should consider 12 multiple ecological indicators and made the fo llowing statement in thei r letter to the EPA on 13 August 28, 2009: 14
“...the Panel finds the information in the current REA sufficient to inform setting 15 separate standards for terre strial acidification, eutrophi cation of western alpine 16 lakes and terrestrial nutrient enrichment. However, the Panel believes that setting 17 a standard for coastal nutrient enrich ment would be difficult because of the 18 substantial inputs of non-atmospheric sources of N to these systems.” 19 The following sections describe the concep tual design for standards based on aquatic 20 acidification, terrestrial acid ification, eutrophica tion of high elevation western lakes and 21 Air Quality Indicator(s) Ecological Indicator Ecological Response to Deposition Function Atmospheric Deposition Transformation Function Deposition

Metric Variable/Fixed Modifying

Factors Variable/Fixed Modifying

FactorsPolicy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 147 terrestrial nutrient enri chment. The focus of the first draf t will be on aquatic acidification , but 1 this general conceptual framework will appl y to a broader set of potential endpoints. 2



### 5.2 ECOLOGICAL COMPONENTS OF THE STANDARD: AQUATIC 3 

### ACIDIFICATION 4 Details of the concep tual design of the NO x and SO x NAAQS based on aquatic 5
acidification effects are presented in this section. A summary of our over all approach is given 6 here to help provide context and support for the more detailed discussions that follow. 7 At the catchment scale, ambient NO y and SO x add to the total deposition of N and S that 8 lead to aquatic acidification. NH x is often another big componen t of the total N deposition. The 9 load of deposition that causes a desired level of ANC will vary depending on the characteristics 10 of the ecosystem. The level of ANC is tied to th e degree of biological harm to the system from 11 aquatic acidification. 12 The components of the standard are modified for application to aquatic acidification and 13 presented in Fig 5-2. The bidirectional arrows emphasize that the order in which one considers 14
the links between ANC and atmo spheric concentrations of NO x and SO x is conceptually 15 important to the standard design. Moreover, di fferent questions may be answered by working 16 through Fig 5-2 from the left to the right versus the right to the left. Fo r example, working from 17 left to right, when a level of ANC is specified the deposition lo adings of N and S that would 18 cause the specified level of ANC can be calculated; in essence this would be a critical load for a 19 specified ANC limit. A comparison between the to tal amount of deposited N and S to the critical 20 load would determine whether the specified level of ANC is achieved for a catchment. Let’s now 21 work through the equation from right to left. If the amount of N and S deposited to a given 22 catchment is known, you could calculate the leve l of ANC that would result. The calculated 23 ANC could then be compared to a benchmark va lue of ANC. In both of these approaches the 24
amount of reduced N would be subtracted from the total N deposition to calculate deposition 25
from NO y . The atmospheric concentrations of NO y and SO x would be calculated from the 26 deposition of NO y and S according to the methods presented in section 5.4. To determine the 27 appropriate conceptual design from the ecological components of the standard, the analysis from 28
the REA is evaluated in which critical loads were calculated for a target value of ANC, thereby 29 working from left to right on Fig 5-2. 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 148 1 Fig 5-2. Schematic diagram of the conceptual design of the standard based on 2 aquatic acidification. From left to right, if a desired level of ANC is known, then 3 the concentration of the atmospheric indica tors that will cause that level may be 4 calculated. From right to left, if the if the concentration of the air quality 5 indicators are known than the ANC that will be caused may be calculated. 6 The secondary NAAQS would apply to all areas of the country. It is not practical to 7 evaluate each catchment individually, and that is not the appropriate approach for a national 8 standard. Here, EPA staff proposes to categorize landscape features na tionally, such that within a 9 category there are generally similar characteristics as far as the relationship of total deposited N 10 and S to the ANC. Every part of the country woul d be assigned into one of these bins/ landscape 11 categories. 12 The secondary NAAQS would be based on a judg ment as to a specified level of ANC. 13 For each national acid-sensitivity bin/ landscape cate gory there would be a range of critical loads 14 for a specified ANC limit from the individual ca tchments within the total population aggregated 15 to an acid-sensitivity category. Given that, th e EPA would develop a deposition metric and 16 associated tradeoff curve that represented the pe rcentage of the catchments that would achieve 17 the ANC (DL %ECO ). Therefore a judgment would also need to be made to determine the 18 Concentration of the Air Quality Indicator(s) Level of ANC related to biological effects Ecosystem Acidification

Model that relates ANC to

depositionat catchmentscale Atmospheric Deposition Transformation Function Deposition Loading of N +S which represent national

scale landscape categories Modifying

Factors Modifying Factors

Relationship between the amount of deposition and the effect on the selected ecological indicator, ANC (described in 5.2) Relationship between the amount of deposition and the concentration of NOx and SOx (described in 5.4)Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 149 percentage of ecosystems that would be targeted to achieve a specified ANC level that applies to 1 a bin/category. 2 The following discussions in this section focus on the ecological components of the 3 standard (ecological indicator, the deposition me tric, the ecological response function and its 4 modifiers). Questions that are re levant to the design of the sta ndard are used to organize these 5
discussions. The first series of questions (section 5.2.1) consider s information presented in the 6 ISA and REA relevant to the conceptual design, while the second series of questions (section 7 5.2.2) presents the proposed conceptual design in more detail with an example calculation based 8 on the Adirondacks case study presented in section 5.5. 9

5.2.1 Conceptual design considerations from the ISA and REA 10 This section presents discussion of the eco logical components of the design based on 11
information in the ISA and REA. The informa tion presented here is considered in the 12 development of the design options that are proposed (section 5.2.2). 13

5.2.1.1 Does the available information prov ide support for the use of ecological 14 indicators to characterize the responses of aquatic ecosystems to nitrogen and 15 sulfur deposition? 16 Ecological indicators of acidi fication in aquatic ecosystems can be chemical or 17 biological components of the ecosystem that are demonstrated to be altered by the acidifying 18 effects of N and S deposition base d on scientific evidence. A de sirable ecological indicator for 19 aquatic acidification will be one that is measurable or estimable, linked causally to deposition of 20 N and S, and linked causally to ecological effects known or anticipated to adversely affect public 21
welfare. 22 As summarized in Chapter 2, aquatic acidifica tion is indicated by changes in the surface 23 water chemistry of ecosystems. In turn, the alte ration of surface water chemistry has been linked 24 to negative effects on the biotic integrity of fres hwater ecosystems. There are a suite of chemical 25
indicators that can be used to assess the effects of acidifying de position on lake or stream acid26 base chemistry. These indicators include acid ne utralizing capacity (ANC), surface water pH and 27
concentrations of SO 4 2- , NO 3 - , Al, and Ca 2+ ; the sum of base cations; and the recently developed 28 base cation surplus. ANC is the most widely used chemical indicator of acid sensitivity and has 29 been found in various studies to be the best singl e indicator of the biological response and health 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 150 of aquatic communities in acid-sensitive systems (Lien et al., 1992; Sullivan et al., 2006). The 1 utility of the ANC criterion lies in the a ssociation between ANC and the surface water 2 constituents that directly contri bute to or ameliorate acidity-relat ed stress, in particular pH, Ca 2+

, 3
and Al. ANC is also used because it integrates overall acid status ( ISA 3.2.3 and REA 5.2.1 ) and 4
the acid-related stress for biota th at occupies the water that can be directly relate d to biological 5 impairment, specifically the number of fish species ( ISA 3.2.3 ). 6
EPA staff thus concludes that the available information pr ovides support for the use of 7 ecological indicators to characteri ze the responses of aquatic ecosy stems to nitrogen and sulfur 8 deposition, and that ANC is th e most supportable indicator. 9

5.2.1.2 Does the available information pr ovide support for the development of a 10 function that relates total nitrogen and sulfur deposition to ecological 11
indicators? 12 There is evidence to support the link between deposition of N and S, water chemistry and 13 biota. Atmospheric deposition of NO x and SO x causes aquatic acidifica tion through the input of 14 acid anions (e.g. NO 3 - and SO 4 2- ). The anions are deposited e ither directly to the aquatic 15 ecosystem, or indirectly vi a terrestrial ecosystems. In other words, when the anions are mobile in 16 the terrestrial soil, they can l each into adjacent waterbodies. Acidification of ecosystems is 17 reflected in a robust relationship between ANC of water and the deposition of NO x and SO x . 18 In the REA, the relationship between deposit ion and ANC was investigated using models 19 of ecosystem acidification ( REA Chapter 4 and REA Appendix 4 ). These models characterize 20 the relationship between deposition N and S and the ability of an ecosystem to counterbalance or 21 buffer the deposition. The utility of the ecosystem acidification models is for simulating a variety 22 of water and soil acidification responses at the laboratory, plot, hillslope, and catchment scales. 23 For example, the ANC value caused by the current amount of deposition could be calculated, or, 24 the level of deposition that causes a specified le vel of an ecosystem endpoint could be calculated 25 (i.e. a critical load for ANC=50) ( ISA appendix A ). 26 The models used in the REA were the Steady State Water Chemistry model (SSWC), the 27 First-order Acid Balance model (FAB) and th e Model of Acidifica tion of Groundwater in 28 Catchment (MAGIC). The SSWC and FAB models we re used to calculate critical loads for 29 specified ANC levels in the case study areas. M AGIC was used to develop weathering rates that 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 151 were needed for the Shenandoah critical load s calculation and the F-factor was used for 1 weathering rates in the in the Adirondacks. MAGIC was also used to show long-term trends 2 between anthropogenic N and S deposition on ANC dating back to pre-industrial times. It is 3 important to note that acidification models are data intensive. Water chemistry data from the 4 TIME and LTM programs, which are part of the Environmental Monitoring and Assessment 5 Program (EMAP), were input to the acidifcation models. An abbreviated summary of 6
acidification models and data i nputs is given in Table 5.2-1, a co mplete list is in Appendix A. 7

Table 5-1. Illustration of how selected models and wa ter chemistry data were used to calculate critical loads in the REA.
Weathering rate

as input to CL model Water chemistry data input to CL model CL calculation: single value CL calculation: critical load

function Adirondack F-factor EMAP SSWC FAB Shenandoah MAGIC EMAP SSWC FAB 8 In summary, the EPA staff concludes that the available information supports using the 9
acidification models to characterize the relations hip between total nitroge n and sulfur deposition 10 and the ANC ecological indicator. 11

5.2.1.3 Does a quantified relationship exist betw een the level of a relevant ecological 12 indicator to an amount of n itrogen and sulfur deposition? 13 A quantified relationship exists between th e level of ANC and nitrogen and sulfur 14 deposition. This relationship was analyzed to dete rmine current risk for tw o case study areas, the 15 Adirondacks and Shenandoahs, in the REA using a time series analysis and a critical load 16 approach. The time series analysis was conducte d using MAGIC and recent monitoring data. The 17 critical loads analysis used water chemistry data from the Temporally Integrated Monitoring of 18 Ecosystems ( TIME) program and Long-term Monitoring ( LTM) to calculate critical loads with the 19
SSWC and FAB models. 20 Long-term trends in surface water nitrate, sulfate and ANC were modeled using MAGIC 21 for the two case study areas. This data was used to compare current surface water conditions 22 (2006) with preindustrial conditi ons (i.e. preacidification or 1860). The results showed a 23Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 152 dramatic increase in the number of acidified lakes, characterized as a decrease in ANC levels, 1
since the onset of anthro pogenic N and S deposition ( REA Appendix 4 Section 5 ) 2 More recent trends in ANC, over the time pe riod from 1990 to 2006, were assessed using 3 monitoring data collected at the two case study areas. In both case study areas, nitrate and sulfate 4 deposition decreased over this time period. In the Adirondack s, this corresponded to a decreased 5
concentration of nitrate and sulfate in th e surface waters and an increase in ANC ( REA 4.2.4.2 ). 6 In the Shenandoahs, there was a s light decrease in nitrate and su lfate concentration in surface 7 waters corresponding to modest increase in ANC from 50 μ eq/L in 1990 to 67 μ eq/L in 2006 8 ( REA 4.2.4.3 and REA Appendix 4 Section 3.4 ). 9
A critical load for ANC is the amount (or load per year) of N and S deposition above 10
which a selected level of ANC will be exceeded for individual water bodies. In the REA case 11 study analyses, critical loads and their exceedances were calculated for four values of ANC (i.e., 12 ANC of 0, 20, 50, and 100 μ eq/L) for 169 lakes in the Adirondacks and 60 streams in the 13 Shenandoahs. Those four ANC values correspond to important points along the ANC response 14
curve that are associated with le vels of ecosystem impairment. Th e case studies used steady-state 15
critical loads models and focus on the combined load of sulfur and nitrogen deposition, below 16 which the ANC level would still support hea lthy aquatic ecosystems. For each waterbody, the 17 total deposition in the year 2002 was compared with the estimated critical loads for the four 18
critical limit thresholds to determine which si tes exceed their critical limit of deposition and 19 biological protection level. Estimates of depos ition were based on the sum of measured wet 20 deposition values from the year 2002 NADP netw ork and modeled dry deposition values based 21 on the year 2002 emissions and meteorology usi ng the Community Multiscale Air Quality 22 (CMAQ) model, respectively ( REA 4.2 ). It is important to note th at a single level of ANC may 23 be caused by a range of deposition values due to heterogeneous sensitivity among watersheds. 24 In summary, EPA staff concl udes that a quantified relationship exists between the level 25 of surface water ANC and an amount of nitrogen and sulfur deposition. This relationship is 26 demonstrated by long-term trends going back to preindustrial conditions in the 1860s, recent 27
trends since the 1990s and critical loads modeli ng based on 2002 deposition data. Models are the 28 best way to evaluate how multiple environm ental factors alter the relationship ANC and 29 deposition. 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 153 5.2.1.4 What are the important variables in the ecological response to deposition 1 relationship(s)? 2 There are numerous variables that modify the ANC to deposition relationship. The effects 3
of these modifiers are described by models that parameterize ecosy stems to simulate the process 4 of acidification. The steady-state models used fo r critical loads analys is in the REA required 5 input data for between 17 and 20 environmental parameters. 6 The basic principle of the steady-state appro ach is to determine the maximum acid input 7 that will balance the system at a biogeochemical safe-limit. Safe-limit is a subjective term that 8 relates to a particular benchmark (e.g. ANC = 20, 50, 100), representing protection against 9 specific types and magnitudes of aquatic ecosyste m response. The steady-state models that were 10 used in the REA relate an aquatic ecosystem’s cri tical load to the weatheri ng rate of its drainage 11 basin expressed in terms of the base cation flux. W eathering rate of geologic parent material is 12 the main source of base cations to an ecosystem. It is considered one of the governing factors to 13 ecosystem critical loads, and therefore an im portant variable in th e ecological response to 14 deposition relationship. Landscape features that are correlated to ecosystem acid-sensitivity 15 include lithology, elevation, percen t forested watershed, and watershed area (Sullivan et al. 16 2007). A more detailed summary of the models and the environmental va riables incorporated 17
into the models that were used in the REA is presented in Appendix A. 18
Numerous environmental variables affect th e acidification process. Therefore the input 19 data required to run acidificati on models is rather extensive. For example, MAGIC, a dynamic 20 process based model of acidifica tion, requires atmospheric deposition fluxes for the base cations 21 and strong acid anions as inputs to the model. The volume discharge for the catchment must also 22 be provided to the model. Values for soil and surface water temperature, partial pressure of 23 carbon dioxide and organic acid concentrations must also be provided at the appropriate 24 temporal resolution. The aggregated nature of the model requires that it be calibrated to 25 observational data from a system before it can be used to examine potential system response. The 26 calibration procedure requires that stream water quality, soil chemical and physical 27 characteristics, and atmospheric deposition data be available for each catchment. The water 28 quality data needed for calibrati on are the concentrations of the individual ba se cations (Ca, Mg, 29 Na, and K) and acid anions (Cl, SO 4 2- , and NO 3 - ) and the pH. The soil data used in the model 30 include soil depth and bulk density, soil pH, so il cation-exchange capacity, and exchangeable 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 154 bases in the soil (Ca, Mg, Na, and K). The atmo spheric deposition inputs to the model must be 1 estimates of total deposition (wet and dry). 2 In summary, the EPA staff concludes there are numerous variables which modify the 3 ANC to deposition relationship. Th e relationships between envir onmental factors are described 4 by models that parameterize ecosystems to simula te the process of acidi fication. Weathering rate 5 of geologic parent material is th e main source of base cations to an ecosystem, and it is therefore 6 considered one of the governing factors of ecosyst em critical loads. Landscape features that are 7 correlated to ecosystem acid-sensitivity include lithology, elevation, percen t forested watershed, 8
and watershed area. Consideration of the effect s of environmental variables on the relationship 9
between environmental variables is extensive in ecosystem acidification models. The calibration 10 procedure requires that stream water quality, soil chemical a nd physical characteristics, and 11 atmospheric deposition data be available for each catchment. 12

5.2.1.5 Are these relationships applicable regionally? 13 The relationship between ANC and N + S de position based on catchment- scale modeling 14 is applicable regionally. Response to N and S deposition will vary ca tchment by catchment. 15 However, modeling every catchment in a regi on (i.e. a spatial area that includes a large 16 population of individual catchments) is implausible due to the ex tensive data requirements to 17 inform the simulations. A method to extrapolat e watershed-scale anal ysis to a region was 18 developed in the REA. In that method, the critic al loads (combined N+S load) developed for the 19 case study sites were applied over a region using water quality data . Critical load exceedance 20 (i.e., the amount of actual deposition above the cr itical load, if any) was calculated for each 21 waterbody in the region to quantify the number of la kes or streams that recei ve harmful levels of 22 deposition. Lakes and streams with positive ex ceedance values, where actual deposition was 23 above its critical load, were not protected at that critical limit (e.g. ANC= 20, 50, 100; REA 24 appendix 4). 25 In the Adirondack case study conducted in th e REA, critical load exceedances were 26 extrapolated to lakes defined by the New E ngland EMAP probability survey. The EMAP 27 probability survey was designed to estimate, with known confidence, the status, extent, change, 28 and trends in condition of the nation’s ecological resources, such as surface water quality. For 29 the Adirondack Case Study Area, the regional EMAP probability survey of 117 lakes were used 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 155 to infer the number of lakes and percentage of lakes that receive acidifying deposition above 1
their critical load of a population of 1,842 lakes. ANC limits of 20, 50, and 100 μ eq/L were 2
examined. 3 In the Shenandoah case study, critical load ex ceedances were extrapolated using the 4 SWAS-VTSSS LTM quarterly monito red sites to the population of brook trout streams that do 5
not lie on limestone bedrock and/ or are not significantly affected by human activity within the 6
watershed. The total number of brook trout streams represented by the SWAS-VTSSS LTM 7 quarterly monitored sites is approximately 310 streams out of 440 mountain headwater streams 8 known to support reproducing brook trout. ANC limits of 20, 50, and 100 μ eq/L were examined. 9 (REA Appendix 4.3.1). 10 In summary, approaches were developed in the REA to extrapolate the ANC-deposition 11 relationship across a region. The da ta requirements for these appro aches include (1) calculation 12
of critical loads of ANC using a catchment-scale model (2) stream chemistry data across the 13 region of concern, and (3) depos ition loads across the region. With this information the 14 deposition load that would cause the stream to ex ceed the critical limit of ANC was calculated as 15
the critical load exceedance. 16

5.2.1.6 Are these relationships applicable nationally? 17 The relationship between ANC and N + S depos ition is applicable nationally. Areas that 18 have similar geologic underpinni ngs and weathering rates should show similar sensitivity to NO x 19
and SO x deposition. The critical load modeling that was used in the REA case studies requires 20 parameterization to each catchment. The spatial scal e is small (e.g. catchment level) and the data 21 requirements are great (17+ environmental variab les for each catchment) to use this method to 22 determine critical loads across all sensitive regions of the U.S. at this time. It is important to note 23 that acid-sensitivity often varies from catchment to catchment. Even if we did calculate critical 24 loads data for each catchment, aggregation of the catchment-scale data is appropriate for a 25
national standard. 26 The technique developed in the REA for extr apolating catchment-specific results to a 27 regional area determines the number of streams in a given area that show critical load (CL) 28 exceedances based on a selected value of ANC and deposition values for 2002. The approach 29 developed in the case study for extr apolating catchment-specific re sults to a regional area is not 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 156 immediately applicable across the U.S. because data for surface water chemistry and data for 1 other input parameters is not av ailable at a national scale. 2 To summarize, the relationship between ANC and N + S deposition is applicable 3 nationally. However the data requi red for critical loads analysis and extrapolation that is 4 available on the regional scale is not available at the national scale. Considering this current data 5 limitation the utility of the extrapolation approach developed in the REA to the national-scale is 6 limited. Additional national-scale appro aches are discussed in section 5.2.3. 7

5.2.1.7 Summary 8 In summary, EPA staff concl udes that the available information from the ISA and REA 9 supports the following characteriza tion of aquatic acidification. Fi rst, there is sufficient support 10 for the use of ecological indica tors to characterize the res ponses of aquatic ecosystems to 11 nitrogen and sulfur deposition, and that ANC is the most supportable indicator. The available 12 information supports using the acid ification models to characteri ze the ecological response, using 13 ANC as the indicator, to nitrogen and sulfur deposition. Models ar e the best way to evaluate how 14 multiple environmental factors alter the relationship ANC and deposition. 15 Heterogeneous sensitivity among watersheds is due in part to landscape features. 16 Weathering rate of geologic parent material is the main source of base cations to an ecosystem, 17 and is therefore considered one of the governing factors of ecosystem critical loads. Landscape 18 features that are correlated to ecosystem acid- sensitivity include lithology, elevation, percent 19 forested watershed, and watershed area. 20 Modeling every catchment in a region is implausible due to the extensive data 21 requirements. The relationship between ANC an d N + S deposition is applicable regionally. A 22 method to extrapolate watershed-sc ale analysis to a region was developed in the REA. In that 23 method, the critical loads (combined N+S load) de veloped for the case study sites were applied 24 over a region using water quality data. The da ta requirements for the regional extrapolation 25 include (1) calculation of cri tical loads for ANC using a catchment-scale model (2) stream 26 chemistry data across the regi on of concern, and (3) depositio n loads across the region. The 27 approach developed in the case st udy areas is not immediately app licable across the U.S. because 28 data for critical loads modeling and surface water chemistry is not available at a national scale. 29 However, it is important to note that the re lationship between ANC and N + S deposition is 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 157 applicable nationally. Areas that have simila r geologic underpinnings should show similar 1 sensitivity to NO x and SO x deposition. 2

5.2.2 Design options for aquatic acidification 3 The following design options describe the c onceptual approach to integrating the 4 ecological components of the standard outlined in section 5.1: ecological indicator, modifying 5 factors, ecological response function and deposition metric. The goal is to illustrate how levels of 6
NO x and SO x can be set to protect areas of the U.S. from acidic deposition. 7

5.2.2.1 Is it appropriate to use ANC as the eco logical indicator for the conceptual 8 design of the NO x and SO x standard based on aquatic acidification? 9 There is strong evidence supporting that ANC is an appropriate ecol ogical indicator for 10 aquatic acidification as discussed in Chapter 2 and Section 5.1.1 (as well as ISA 3.2.3 and REA 11
5.2.1 ). Options for the level of the indicator are di scussed in Chapter 6. The options for the levels 12 are derived from experimental and observed evid ence in the scientific literature showing the 13 biological effects over a range of ANC values. 14

5.2.2.2 What is the appropriate ecosystem ac idification model(s) to represent the 15 ecological response function? 16 In the REA, critical loads were calculated for specified ANC levels using the SSWC and 17 FAB models, these are referred to as acidification models, acid bala nce models or critical loads 18 models. The different assumptions of each modeli ng approach have implications that should be 19 considered in the conceptual design of a deposition-based NO x and SO x standard. Most notably, 20 biogeochemical pathways of N and S deposition are c onsidered differently in the two models. In the 21 SSWC model, sulfate is assumed to be a mobile an ion (i.e. S leaching = S deposition), while nitrogen is 22 retained in the catchment by various processes. This assumption that all N is retained by the ecosystem 23
and does not contribute to acidification is incorrect in many instances because nitrate leaching is 24 observed. If nitrogen is leaching out of an ecosystem , obviously it has not been retained. Nitrate leaching 25
is determined from the sum of the measured concentr ations of nitrate and ammonia in the runoff. The 26 critical load for sulfur that is calculated by SSWC can be corrected for the amount of nitrogen that 27
contributes to acidification. When an exceedence value fo r the critical load is calculated, the critical load 28 is subtracted from S deposition plus the amount of ni trate leaching, as it represents the difference between 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 158 N deposition and N retention by the ecosystem. N leachi ng data used in this calculation is considered 1
robust. 2 In contrast to the SSWC approach, the FAB model includes more explicit modeling of N 3 processes including soil immobilization, denitr ification, and wood removal, in-lake retention of N 4 and S, as well as lake size. A lthough N cycling is more detailed in the FAB model, there is 5 greater uncertainty in the input data needed to char acterize the components of the N cycle. The 6 FAB model yields a deposition load function for a specified level of an endpoint. This function is 7 characterized by three nodes that are illustrated on Figure 5-3: 1) the maximum of amount of N 8 deposition when S deposition equals zero (DLmax (N)), 2) the amount of N deposition that will 9 be captured by the ecosystem before it leaches (DLmin(N)) and 3) the maximum amount of S 10 sulfur deposition considering the N captured by the ecosystem (DLmax (S)). The function 11 represents many unique pairs of N and S deposition that will equal the critical load for acidifying 12 deposition. The slope portion of th e function will vary according to attributes of the water body 13 that is modeled, including lake size and in-lake retention. 14

15 Figure 5-3. The depositional load function. 16 A third modeling approach, which synthesizes components of each model used in the 17 REA, is suggested by staff for catchment scale modeling in deve loping the NAAQS. The 18 foundation of the proposed approach is the SSWC model because there is high confidence in the 19 input data required. The SSWC model for aqua tic acidification is expressed as equation 1. 20 

## ( ) 

## [ ] [ ] Q ANC BC S N DL O ANC ) ( lim * lim − = + (1) 21

where, 22Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 159 DL ANClim (N+S) = depositional load of S and N that does not cause the ecosystems to exceed a 1 given ANC lim 2 [BC] 0 * = the preindustrial concentrati on of base cations (equ/L) 3
ANC limit = a “target” ANC level (equ/L) 4 Q= surface water runoff (m/yr) (this is typically equal to precipitati on –evapotranspiration 5
6 This model could be further constrained by a quantity of N which would which would be 7 taken up, immobilized or denitrified by ecosystems a nd adjust the quantity of deposition required 8 to meet a specified critical load. This term is represented as DLmin(N) in the FAB model and 9 illustrated in Fig. 5-3. For application in the NAAQS and in the following discussion, the 10 parameter is designated with the abbreviation N ECO . The acid-base model constrained by N ECO is 11 expressed by equation 2. 12 

## ( ) 

## [ ] [ ]

eco O ANC N Q ANC BC S N DL +

− = + ) ( lim * lim (2) 13

14 where, 15
N eco = nitrogen retention and denitrif ication by terrestrial catchment and nitrogen retention in the 16
lake 17
18
The term N eco could be derived multiple ways, each yielding different ultimate results. 19 The first is by taking the mean value calculate d to represent the long-term amount of N an 20 ecosystem can immobilize and denitrify before leach ing (i.e. N saturation) that is derived from 21 the FAB model [denoted as DLmin(N) in the FA B model]. This approach requires the input of 22 multiple ecosystem parameters. Its components are expressed by eq 3. 23 

## ( ) ( ) den imm ret eco N N r N fNupt N +

− + + = 1 (3) 24

where, 25
N upt = nitrogen uptake by the catchment 26
N imm = nitrogen immobilization by the catchment 27
N den =denitrification of nitrogen in the catchment, 28Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 160 N ret = in-lake retention of nitrogen 1
f =forest cover in the catchm ent (dimensionless parameter) 2
r = fraction lake/catchment ra tio (dimensionless parameter) 3
4 The second approach for estimating N eco is to take the difference between N deposition 5 and measured N leaching in a catchment as expressed by eq 4. 6

leach eco N N DL N

− = ) ( (4) 7

It is unclear which approach for calculating N ECO should be used in developing the 8 NAAQS. The two equations can re sult in quite different values (See section 5.4 for an example 9 calculation). 10 To summarize, the SSWC model assumes N deposited to the ecosystem is retained by the 11 ecosystem, while also assuming that all S depos ition is leached and c ontributes to aquatic 12
acidification. The critical load is calculated for S deposition, and the N that contributes to 13 acidification is incorporated into the exceed ance calculation. The FAB model considers a 14 detailed accounting of the N cycl e; however confidence in the input data to the model is more 15 uncertain. The FAB approach yields a function which may be solved by many unique pairs of N 16 and S deposition. A minimum amount of N depos ition that will be captured by the ecosystem 17
before it leaches is included in the calculation of the maximum amount of S deposition. A third 18 approach is suggested by staff as the most appropriate approach fo r informing the structure of the 19
NO x and SO x secondary standard. This a pproach constrains the critic al load calculated from a 20 SSWC method by a value of N ECO [previously defined as DL min(N)] which accounts for the 21 amount of N deposition that would be taken up by the ecosystem and, therefore, would not 22
contribute to acidification. 23

5.2.2.3 How are results of acidification mode ls aggregated to adequately represent a 24 larger spatial area and inform a deposition metric? 25 So far in this section, the ecological indicator would be established as ANC. Acidification 26
models are considered the best way to describe the relations hip between ANC and deposition and 27 to describe how this relationship is altered by modifying factors. If deposition is known the 28 model may be run to calculate th e resultant ANC. If a target ANC level is desired the model may 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 161 be run to calculate the corresponding deposition load that should not be exceeded (i.e. the critical 1 load). The following discussion will focus on the critical load application of the acidification 2 model. It is important to emphasize that the aci dification models are only applied at the spatial 3 scale of the catchment. Spatial aggregation of critical loads are nece ssary to inform the 4 discussion of appropriate design and levels of a national standard. 5 Acidification models are parameterized for catchments. The critical loads that they 6 calculate for N and S deposition based on a specified ANC limit vary at the small spatial scale of 7 the catchment to the degree that acid-balancing properties of the catchments vary. Despite this 8 variation, the goal of aggregating critical lo ads from multiple catchments is to develop an 9 appropriately representative depo sition value, which is adequately protective of ecosystems and 10 could be applied over la rger spatial areas. 11 Staff proposes evaluating the critical loads for a specified ANC limit of a population of 12 waterbodies to calculate a benchmark depositional load in which a specified percentage of the 13 population does not exceed their critical load. This approach uses the distribution of critical loads 14 from a population to derive a value that is intended to provide pr otection over a sp atial area that 15 is larger than the individual catchment for whic h a single critical load may be calculated. An 16 example of this technique is calc ulated in section 5.5. The ecologi cal indicator woul d be a single 17 value of ANC, and the acidifica tion models would calculate the cr itical loads for the specified 18 ANC level for individual catchments across a spa tial area. The deposition metric would be an 19 amount of deposition such that a specified perc entage of a population of water bodies does not 20 exceed a critical load for the specified value of ANC. The deposition metrics could be calculated 21 for populations of catchments that are categorized according to acid-sensitivity, as described in 22
the next section. 23

5.2.2.4 How are modifying factors of the ecological response to deposition function 24
considered at the national-scale? 25 As previously noted, critical loads for ANC vary at a small spatial scale, catchment by 26 catchment. As it is implausible to model the acidi fication status of every catchment in the U.S, 27 an alternative is to develop a deposition metric for a population of catchments, assuggested in the 28 previous section. The following design options focus on relating acid-sensitivity, based on ANC, 29 to a feature(s) of the lands cape at a national-scale by creatin g acid-sensitivity categories. A 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 162 population of catchments could then be defined to represent these categories and a representative 1 deposition metric chosen. 2
Acid sensitivity classes based on bed rock geology 3 Here an approach is presented in whic h ecosystem sensitivity to acidification is 4 categorized into classes based on bedrock geology/ lithology. The approach is supported by 5 conclusions from the ISA in which geologic bedr ock is determined to be the governing factor 6 that drives ecosystem sensitivity to acidification ( ISA 3.2.4.1 ). Specifically, geologic bedrock 7 with a low base cation supply leads to ecosystems that are sensitive to acidifying deposition. A 8 method to develop a deposition metric, based on the distribution of critical loads of a 9 representative population, for each category of acid-sensitivity is presented here. 10 A map was developed to capture the heterogeneity of geologic bedrock that occurs across 11 the eastern U.S. and link it to ecosystem aci d-sensitivity (Fig5-4). The method is based on 12 Sullivan et al.(2007) in which 70+ primary lith ologies are grouped into 5 categories of acid13 sensitivity, using ANC as the ecosystem indicat or upon which acid-sensitivity is based. Sullivan 14 et al. (2007) evaluated multiple features of th e landscape and found that geology is the landscape 15 parameter that governs ecosystem sensitivity to acid ic deposition. The analysis in Sullivan et al. 16
2007 was conducted in the Southern Appalachian Mountai ns region, which included sites from 17 the states of GA, TN, NC, KT, VA and WV. EPA is conducting a dditional analyses to further 18 test the concept that lithology correlates to acid sensitivity in case study areas and in the western 19
U.S. EPA staff intends that some of these addition al analyses will be available at for review in 20 the second draft of the policy assessment. 21 As previously stated, acidification often va ries catchment by catchment. Therefore there 22 will be variation in terms of acid-sensitivity am ong catchments within each acid-sensitivity class 23 designated by the map. Despite this variati on, lithology is a nationally applicable landscape 24 feature which is known to govern acid-sensitivity . Ultimate detail and rigor would be provided 25 by modeling deposition and consequential acidifi cation of each catchment in the U.S., an 26 approach which would require knowledge of 17+ environmental parameters for each catchment. 27 However classification of the landscape into categories based on ge ology provides a national28 scale landscape feature to extrapolate th e results of catchment-scale modeling. 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 163 1 Fig 5-4. A map of acid sensitive areas of th e Eastern U.S. developed from a 2 lithology-based five-unit geol ogic classification system after methods in Sullivan 3 et al. (2007). 4
Acid sensitivity based on multiple landscape features 5 Although bedrock geology is a governing factor of acid sensitivity, multiple factors have 6
been shown to contribute to sens itivity. Topography is a characteri stic of the landscape that is 7 often shown to correlate with acid-sensitivity, specifically low elevations, which generally 8 receive some cations from higher elevation sites, are less sensitive that higher elevation sites 9 ( ISA 3.2.4.1 ). Could both topography and bedrock geol ogy be included a national map of acid10 sensitivity? A map of high eleva tion could be layered over the map of bedrock categories. If all 11 high elevation areas were within the sensitive geologic categories , then the additional parameter 12 would further refine the spatial resolution of sensitivity within the bedrock categorization. 13 Moreover, the approach will provide more spatial detail on the sensitivity within areas already 14 considered sensitive based on bedrock geology. It’s unclear if eleva tion alone would help 15Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 164 identify new sensitive areas. It’s also unclear if greater spatial resolution of sensitivity within 1 areas already identified as sens itive would be helpful in term s of relating the national-scale 2 landscape features to critical loads. Should a dditional multiple features be considered when 3 categorizing the landscape according to acid-sensitivity? We are providing this design option to 4 elicit comment; it is presented as a conceptual idea. 5

5.2.2.5 How is a deposition metric developed so that critical loads for catchments are 6 aggregated to adequately represent cla sses of acid sensitivity based on 7 geology? 8 The values that represent a deposition metric for the acid-sensitivity categories could be 9
derived from the critical loads calculated for the case study analysis in the REA. The case study 10 sites (Adirondack and Shenandoah areas) occur in areas that are predominately composed of the 11 two most acid-sensitive types of bedrock geology. Therefore the case study sites would represent 12 those sensitivity categories. Th e deposition and atmospheric con centration tradeoff curves for a 13 specified level of ANC for each bedrock geology site would be based on a deposition metric 14
derived from the distribution of cr itical loads within the case st udy areas. It could be a central 15
value such as the mean or median value or a va lue representing a percent ile of the distribution, 16
such as the 95 th percentile. Central estimates, such as the mean, would likely not be projected to 17 achieve the target ANC of the majority of acid-sensitive ecosystems; therefore it may be 18 preferable to calculate the spat ially aggregated value for some percentage of catchments to 19 project achieving the ANC for the more sensitive ecosystem types. For ex ample, if projecting 20 85%, 90% or 95% of the aquatic ecosystems achie ving the ANC is selected, then the deposition 21 metric that represents the critical load for the 85 th , 90 th or 95 th percentile of the population would 22 be selected. An example calculation for the Adirondacks is presen ted in section 5.5. 23

5.2.2.6 How is reduced nitrogen appropriately considered in the deposition metric? 24 Reduced forms of nitrogen deposition are quickly converted to nitrate in the environment 25 and use up the assimilative capacity of ANC at the same rate as oxidized forms of nitrogen 26 deposition; therefore, reduced ni trogen deposition must be accounted for in the watershed. There 27 are two basic approaches to accounting for the use of this assimilative capacity. 28 The suggested approach is to subtract the lo adings of reduced form s of nitrogen derived 29 for a given spatial area from the deposition metric th at represents selected percentage of critical 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 165 loads for a given population, such that the result ant deposition metric is for sulfur and oxidized 1 nitrogen only. This approach assumes that the re duced forms of nitrogen deposition are relatively 2 constant over time. This assumption could lead to over or under protectio n for an area depending 3
on whether the actual concentrations of reduced forms of nitrogen in crease or decrease over 4 time. An example for how to subtract reduced nitrogen from the deposition metric based on 5 nitrogen and sulfur is given in section 5.5. 6

5.2.2.7 Summary 7 In summary, the ecological components of the conceptual design for a standard base on 8 aquatic acidification include th e ecological indicator, ecologi cal response function and its 9 modifiers and the deposition me tric. A summary how each compone nt is considered in the 10 conceptual design is given in Table 5-2. Using ANC as the ecological indi cator, an approach is 11 suggested for using an acidifica tion model constrained by a parame ter for ecosystem N retention 12 to represent the ecological respon se function. The best way to cal culate ecosystem N retention is 13 as of yet unclear. It is proposed that the national landscape is categorized in terms of criteria that 14 denote acid-sensitivity. It is well known that bedrock geology is a governing factor of acid15 sensitivity, in other words ecosy stem response is modified acros s the landscape due in part to 16 bedrock geology. It is unclear if landscape categoriza tion based on geology is the best approach 17
or other criteria/combination of criteria should be used. 18
The distribution of critical loads for a specified target ANC from a population of 19 catchments representing an acid-sensitivity catego ry, based on geology or some combination of 20 factors, can be calculated From this a deposi tion metric, an amount of deposition, could be 21 calculated such that a specified target percentage of the populati on of water bodies in the acid22 sensitivity category does not exceed a critical load for the specified value of ANC. Moreover, the 23 deposition metric would reflect bo th the selected level of ANC and the percentage of catchments 24 in the representative populat ion that do not exceed their cr itical load. Reduced nitrogen 25 deposition, average over a determ ined spatial scale, would be subtracted from the deposition 26 metric yielding a value for allowable deposition from NO y and SO x . The deposition from NO y 27
and SO x would be converted to atmo spheric concentrations of NO y and SO x by the methods 28
described in section 5.4. 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 166 Table 5-2. Summary of the ecological com ponents of design option 1. Values given for illustrative purposes only. Levels are discussed in Chapter 6 and ultimately selected by the administrator.

Ecological Indicator Ecological Response Function Modifying Factor Deposition Metric

ANC; level reflects degree of Effects on aquatic biota in the ecosystem Acidification model constrained by a parameter for N retention Acid-sensitivity categories, based on geologic bed rock or a combination of factors, that may be applied at a national scale Determined from the distribution of critical loads from a population that can berelated to an acidsensitivity category. Reduced nitrogen subtracted from the deposition metric to yield allowable deposition from NO x and SO x . Concentration of Air Quality Indicator(s) Ecological Indicator

ANC

Proposed levels based

on biological effects Ecological Response to Deposition Function
Acidifcation model Atmospheric Deposition Transformation Function See Section 5.4 Deposition

Metric

Determined by

the % of ecosystems re p resented Modifying Factor

Geology 5 categories of sensitivity Variable/Fixed Modifying

FactorsPolicy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 167 

### 5.3 ECOLOGICAL COMPON ENTS OF THE STANDARD: 1 

### TERRESTRIAL ACIDIFICATION, TERRESTRIAL NUTRIENT 2 

### ENRICHMENT AND SURF ACE WATER NUTRIENT 3 

### ENRICHMENT 4 These effects were not included in the concep tual design for the first draft of the PA, 5 however a brief summary of our approach for de veloping standards that are protective of these 6 ecological effects follows. 7

5.3.1 Terrestrial Acidification 8
The deleterious effects of terrestrial acidif ication on tree species is indicated by base 9 cation to aluminum ratio (Bc:Al) of soils. Critical load functions were developed in the REA that 10 relate Bc:Al threshold values (0 .6, 1.2 and 10) to values of N+ S deposition using the simple mass 11 balance (SMB) model. The exceedance of these cr itical loads were calcu lated at the two study 12 sites and then extrapolated over 24 states. Like aquatic acidification, sensitivity of terrestrial 13 ecosystems to acidification is linked to the geolog ic bedrock. Moreover, areas that are sensitive 14 to aquatic acidification should al so be sensitive to terrestria l acidification. Therefore, an 15 approach similar to that described for aquatic ac idification could be deve loped. This would mean 16
that a critical load based on Bc:A l at either 1.2 or 10 would be cal culated to protect a percentage 17 of the terrestrial landscape. This value would then be assigned to categories of acid sensitivity 18 based on geology. 19 This could result in two standards, one fo r aquatic ecosystems and one for terrestrial 20 ecosystems. This leads to the question, are aquatic or terrestrial ecosystem more sensitive? To 21 answer this question, an analys is was conducted in which criti cal loads for the Adirondacks and 22 Shenandoah case study areas were ca lculated based on the terrestrial ecosystem indicator, Bc:Al, 23
at the level of 1.2 and 10. The terrestrial critical loads were compared to the critical loads for 24 aquatic ecosystems. A full description of this analysis and results is available in Chapter 7, the 25 results are briefly summarized here. In the Adir ondacks case study area, 7 of the 16 watersheds 26 had terrestrial critical acid loads (based on a Bc :Al of 10.0) that were lower and therefore more 27
sensitive to acidification than all the lakes in the watershed. Howeve r, when the terrestrial critical 28
loads were calculated with a Bc:Al soil solution ra tio of 1.2, only 5 of the 16 watersheds were 29 protected by a terrestrial critical load that was lowe r than the aquatic critical loads of the lakes. In 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 168 the Shenandoah case study area terrestrial critical loads offered a higher le vel of protection than 1 aquatic critical loads in only one watershed. If two standards were proposed, the one that allows 2
lower ambient levels of NO x and SO x would be controlli ng in a given area. 3

5.3.2 Terrestrial and surface water nutrient enrichment 4

NO x and NH x are the main contributors to nitrog en deposition. The effects of nitrogen 5 deposition on terrestrial ecosyst ems and surface waters are many. Most notable are the effects on 6 ecosystem biodiversity found across the U.S a nd affecting multiple taxonomic groups including 7 vascular plants, algae, mycorrhiza and lichens ( ISA 3.3 ). Unlike terrestrial and aquatic 8 acidification, there is no one, well-supported chemical or biol ogical indicator of ecosystem 9
effects that occurs across the nation. In order to develop a NA AQS based on nitrogen enrichment 10
effects there needs to be one indicator that can be applied across the nation. It is possible that we 11 could develop an index in which information on different ecological indi cators could be input 12 and the output would be an index sc ore that could be consistently applied across the U.S. It is not 13 clear how to develop such an index. 14 Nitrogen critical loads are known for many ecosystem endpoints in the U.S. and are 15 published in the scientific literature. Additionally , critical loads for ecosystems in Europe, many 16 of which are similar to U.S. ecosystems, ha ve been reported for over a decade, they are 17 continually refined through periodic assessments of the scientific literature, and they are 18 currently supported by a strong weight of peer-reviewed scientific information ( ISA 3.3 ). 19 Additional critical load modeling was not conduct ed in the REA because of two factors. There 20 are numerous reports in the peer-reviewed scientif ic literature and there is no model available to 21 conduct such analysis for multiple endpoints and ecosystems. However, based on nitrogen 22 critical loads published in the literature, th e REA evaluated the extent of the landscape 23 represented by those critical loads and their exceedances ( REA 5.0 ). 24 A standard that integrates aci dification and nutrient effects could conceptually be quite 25 simple. The total nitrogen deposition allowed for a deposition metric base d on acidification could 26
be constrained so that it does not exceed a va lue based on a deposition metric for a nutrient 27
related effect. 28Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 169 5.3.3 Summary 1 Conceptual design of NO x and SO x NAAQS were not developed for terrestrial 2 acidification and terrestrial/surface water nitroge n enrichment in the first draft PA, however a 3 brief summary of a potential structure for these ecological effects is presented. The ecological 4
indicator for terrestrial acidif ication would be Bc:Al because it relates to both atmospheric 5 deposition of N+S and deleterious effects on tree gr owth. Critical loads would be related to acid6 sensitivity categories and calculated according to similar methods presented for aquatic 7
acidification effects. This could result in two standards, one fo r aquatic ecosystems and one for 8 terrestrial ecosystems. If two standards were proposed, the one that allows lower ambient levels 9
of NO x and SO x would be controlling in a given area. Un like terrestrial and aquatic acidification, 10 there is no one, well-supported ec ological indicator of nitrogen deposition effects that occurs 11 across the nation. In order to develop a NAAQ S based on nitrogen enrichment effects there 12 needs to be one indicator that can be applied across the nation. Although, the specifics of an 13 approach are unclear, it may be possible that we could develop an index in which information on 14 different ecological indicators co uld be input and the output would be an i ndex score that could 15 be consistently applied across the U.S. A standard that integrates acidification and nutrient 16 effects could conceptually be quite simple. The total nitrogen deposition allowed for a deposition 17
metric based on acidification coul d be constrained so that it does not exceed a value based on a 18 deposition metric for a nutrient related effect. 19



### 5.4 LINKING DEPOSITION TO ATMOSPHERIC CONCENTRATION 20

5.4.1 Background 21 Atmospheric pollutants deposit onto land and water surfaces through at least two major 22
mechanisms: direct contact w ith the surface (dry deposition) , and transfer into liquid 23 precipitation (wet deposition). The magnitude of each deposition process is related to the 24 ambient concentration through the time-, location-, pro cess- and species-specific deposition 25 velocity (Seinfeld and Pandis, 1998) a nd can be conceptualized as: 26

Amb i Dry i Dry i C v Dep

⋅ = (1) 27

Amb i Wet i Wet i C v Dep

⋅ = (2) 28Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 170 where v Dry i and v Wet i are the dry and wet deposition velocities, Dep Dry i and Dep Wet i are the dry and 1 wet deposition fluxes, C Amb i is the ambient concentration, and the i subscript indicates the 2 pollutant species under study. The wet deposition velocity term is a conceptualized term and not 3 a state variable that allows for the grouping of wet and dry deposition. The total deposition of 4 each pollutant is 5

Wet i Dry i Tot i Dep Dep Dep + = (3) 6

Substituting Equations 1 and 2 into Equation 3 yields 7

Amb i Wet i Amb i Dry i Tot i C v C v Dep

⋅ + ⋅ = (4) 8

The total deposition of sulfur or nitrogen would therefore be: 9 

# ∑

⋅ ⋅ + =
i Amb i i Wet i Dry i Tot N S C m v v Dep ) ( | (5) 10

where m i is the molar ratio of the atom (sulfur or nitrogen) of interest to the i th pollutant. 11 Ambient sulfur- and nitrogen-cont aining pollutants include gases such as sulfur dioxide (SO 2 ), 12 ammonia (NH 3 ), various nitrogen oxides (NO, NO 2 , HONO, N 2 O 5 ), nitric acid (HNO 3 ), and 13 organic nitrates such as peroxyace tyl nitrates (PAN); as well as part iculate species such as sulfate 14 (SO 4 2- ), nitrate (NO 3 - ), and ammonium (NH 4 + ). As discussed in chapter 4, the definitions of NO y 15
and SO x species for the purposes of this review in clude the sulfur-containing species above and 16 the above oxidized forms of nitrogen (NO y ); ammonia and ammonium are not currently included 17 as listed pollutants (see Chapter 8 for an expanded discussion of the role of NH x ). 18

5.4.2 Aggregation Issues 19 Equation 5 provides a relati onship for converting sulfur or nitrogen deposition to 20 “equivalent” ambient concentratio ns,. A major issue to consider during such conversion is the 21 treatment of spatial, temporal and chemical reso lutions of the deposition data and the resulting 22 standards. Since the objective is to set an ambient air quality sta ndard for total oxidized sulfur 23 and nitrogen, and this is also the chemical resolution provided by the ecosystem models, it is 24
convenient to use a relationshi p with the following form: 25Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 171 Amb N S N S Tot N S C V Dep / / | ⋅ = (6) 1

where V S/N can be considered an aggregateddepos ition to ambient air transformation ratio, 2 referred to herein as the depositi on transformation ratio, that relate s total deposition of sulfur or 3 nitrogen to the total ambient concentration, a nd represents an average of the species specific v i Tot 4 ( = v i Dry + v i Wet ) values in Equation 5. The sulfur and nitrogen concentrations are the result of 5 applying the m i values to the C i Amb values in Equation 5. 6 Since the deposition criti cal loads are expressed in terms of annual total deposition, the 7 most relevant averaging time for equivalent ambi ent concentrations is th e annual average. Data 8
used to derive annual V S/N values will need to have the same spatial representativeness as the 9 depositional loads. To be clear, the deposition transformation ratio is no t a state variable, but 10 simply is a calculated term that facilitates the linkage between deposit ion and concentrations 11 which is a necessary step in developing ambient ai r indicators that are us ed to assess compliance 12 with a NAAQS. There will be a tendency that is not scientifically defensible to compare 13 deposition ratios with deposition velocities that are uniquely determined on a species by species 14 basis influenced by numerous f actors as discussed earlier. 15

5.4.3 Air Quality Simulation Models 16 Ideally, V S/N values would be derived for each area of interest from concurrently collected 17 sulfur and nitrogen depositi on and concentration measurem ents. However, no monitoring 18 network currently exists that can provide such information. We therefore propose using output of 19 the CMAQ model for initial calculation of V S/N values. 20 CMAQ provides both concentratio ns and depositions for a large suite of pollutant species 21 on an hourly basis for 12 km gr ids across the continental U.S. Its comprehensive structure is 22 ideal for providing V S/N values that appropriately address th e chemical and temporal aggregation 23 issues discussed above, and weight ed spatial averages of the gri dded data can be used for areas 24 that span multiple grid cells. Potential concerns with using CMAQ-predicted concentrations and 25 depositions for this purpose stem from the va rious, but unquantifiable uncertainties in model 26 formation and input data, which will be di scussed in the next draft of this PAD. 27 CMAQ does not directly calculate or use V S/N values; instead the following procedures 28 are used in the code to model deposition: 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 172 1) v dry values of gaseous pollutants are calc ulated in the CMAQ weather module called 1 the Meteorology-Chemistry Interface Proce ssor (MCIP) through a complex function of 2 meteorological parameters (e.g. temperature, re lative humidity) and properties of the geographic 3 surface (e.g. leaf area in dex, surface wetness) 4 2) v dry values for particulate pollutants are cal culated in the aerosol module of CMAQ, 5 which, in addition to the parameters needed for the gaseous calculations, also accounts for 6 properties of the aero sol size distribution 7 3) v wet values are not explicitly calculated . Wet deposition is derived from the cloud 8 processing module of CMAQ, which performs simu lations of mass transfer into cloud droplets 9 and aqueous chemistry to incorpor ate pollutants into rainwater, all of which is conceptually 10
contained in the v wet parameter in Equation 2. 11 Due to lack of direct measurements, no performance evaluations of CMAQ’s dry 12 deposition calculations can be found; however, the current state of MC IP is the product of 13 research that has been based on peer-reviewed literature from the past two decades (EPA, 1999) 14
and is considered to be EPA’s best estimate of dry deposition velocities. Some bias has been 15 found between CMAQ’s wet deposition predictions and measured values (Morris et al., 2005); 16 recent analyses suggest that poor simulation of pr ecipitation could be responsible for this (Davis 17 and Swall, 2006), which can pot entially be dealt with by recal culating wet deposition using 18 precipitation measurements. A lthough the model is continually undergoing improvement, 19 CMAQ is EPA’s state-of-the-science comput ational framework for calculating deposition 20 velocities, and was therefore the lo gical first choice as a source for V S/N values. 21

5.4.4 Oxidized Sulfur and Nitrogen Pollutant Species 22 Ideally, all possible air pollutant species that contribute to ecologica l adversity would be 23
considered for V S/N values. The pollutant list is constrained by the source of V S/N values, which is 24 currently CMAQ output. Table 1 lists the oxidized sulfur and nitrogen species currently available 25 in CMAQ whose data will be used for V S/N values. 26 One issue that needs explicit consideration is the contributions of particles larger than 27
PM 2.5 to sulfur and nitrogen deposition. A recen t review of particle deposition measurements 28 (Grantz, Garner, and Johnson, 2003) showed that coarse particles gene rally deposit far more 29 sulfate and nitrate in forest ecosystems than fi ne particles. However, CMAQ does not currently 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 173 provide simulationsof coarse partic ulate sulfate and nitrate. This is an issue that needs to be 1 addressed by developers of eith er the model or the future SO x /NO x measurement network to set 2 scientifically sound standards. 3

5.4.5 Example Calculations 4 Figure 5-5 shows annual inverse V S/N values 16 calculated for each 12 km grid in the 5 eastern and western domains for a 2002 CMAQ v4.6 simulation, which is the quantity that would 6 be used for conversion of deposition load tradeo ff curves which illustrate (see Section 6) the 7
combinations of NO y and SO x conventartions that would corres pond to an established critical 8 load. Figure 5-6 shows an example application of these ratios for a lake in the Adirondacks. 9 Deposition load tradeoff curves for this lake (see Section 6for their calculation) are multiplied by 10
the inverse V S/N value from the appropriate grid cell in Figure 1 to c onvert those depositions to 11
ambient concentrations of sulfur and nitrogen. 12 A CMAQ v4.7 simulation for multiple year s (2002-2005) recently became available, 13 which was used to examine the inter-annual variability of inverse V S/N values. The grid-specific 14 coefficients of variation (CV) are shown in Figure 3. Figure 5-7 shows that CV values are 15 relatively small (< 25%) in the Adirondacks and Shenandoah case study areas . This suggests that 16 a 3-year average of the ratios may be a sufficien tly stable representati on of deposition velocities 17 for converting the deposition load curves to ambi ent concentrations in future applications. 18

16 Inverse V S/N

values represent the multiplier needed to convert de position levels into atmospheric concentrations of NOx and SOx.Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 Draft – Do Not Quote or Cite 174 Table 5-3. Oxidized sulfur and nitrogen species currently available in CMAQ simulations. Note that PNA concentrations are not av ailable in current CMAQ extractions.

1 2

3

4 Figure 5-5. V S/N values for each grid cell in the eastern (right) and western (left) 5 U.S. domains. The top maps are for su lfur and the bottom are for nitrogen. 6Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 175 Draft –D o Not Quote or Cite 1 Figure 5-6. Schematic Diagram illustrating the procedure for converting 2 deposition tradeoff curves of sulfur and n itrogen to atmospheric concentrations of 3 SO x and NO x . 4Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 176 Draft –D o Not Quote or Cite a) 1

b) 2 Figure 5-7. Inter-annual coefficients of variation (CV) of a) nitrogen and b) sulfur 3 V S/N values, based on a series of 2002-2005 CMAQ v4.7 simulation. 4

5Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 177 Draft –D o Not Quote or Cite 

### 5.5 EXAMPLE CALCULATION FO R THE CONCEPTUAL DESIGN 1 

### AND DERIVATION OF AAPI 2 Section 5.2 describes a proposed conceptual design for a NO x and SO x NAAQS based on 3 aquatic acidification. To summarize the process of acidification, atmos pheric deposition of NO x 4
and SO x contributes to acidification in aquatic ecosystems through the input of acid anions, such 5
as NO 3 - and SO 4 2- . The acid-base balance of headwater la kes and streams is controlled by the 6 level of this acidifying deposition of NO 3 - and SO 4 2- and a series of biogeochemical processes 7 that produce and consume acidity in the watershed. The biotic integrity of freshwater ecosystems 8 is then a function of the, acid-base balance and the resulting acidity-rela ted stress on the biota 9 that occupy the water. Given some “benchmark level” of ANC [ANClim it]) that appropriately 10 protects biological integrity, the depositional load of acidity DL(N+S) is simply the input flux of 11 acid anions from atmospheric deposition that re sult in a surface water ANC level equal to the 12 [ANClimit] when balanced by the sustainable flux of base cations input a nd the sinks of nitrogen 13
and sulfur in the watershed catchment. 14

5.5.1 Example calculation for the conceptual design 15 This section summarizes and provides an exam ple calculation of the approach proposed 16 by EPA staff to calculate (1) the acid-base balan ce of a catchment for a specified ANC level, (2) 17 the N and S deposition tradeoff curves for a de position metric, which represents a specified 18 percentage of the total population of water bodies that do not exceed their critical load at a 19 specified ANC level and (3) the conversion from tradeoff curves for N and S deposition to those 20 for atmospheric concentrations of NO y and SO x . The equations representing deposition loads and 21 associated tradeoff curves for a specified level of ANC are the basis for de riving the form of the 22 standard discussed above in section (5.5.2). 23 Equation (1) expresses the model that we sugge st using to determine the amount of N and 24 S that may be deposited onto a catchmen t to yield a specified level of ANC. 25 

## ( ) 

## [ ] [ ]

eco O ANC N Q ANC BC S N DL +

− = + ) ( lim * lim (1) 26

where, 27Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 178 Draft –D o Not Quote or Cite DL ANClim (N+S) = depositional load of S and N that does not cause the ecosystems to exceed a 1 given ANC lim 2 [BC] 0 * = the preindustrial concentrati on of base cations (equ/L) 3
ANC limit = a “target” ANC level (equ/L) 4 Q= surface water runoff (m/yr) (this is typical ly equal to precipitation –evapotranspiration 5
N eco = nitrogen retention and denitrif ication by terrestrial catchment and nitrogen retention in the 6
lake 7
The term N eco could be derived multiple ways. The first is by taking the mean value 8 calculated to represent the long-term amount of N an ecosy stem can immobilize and denitrify 9 before leaching (i.e. N saturation) that is deri ved from the FAB model. This approach requires 10 the input of multiple ecosystem parameters. Its components are expressed by eq 2. 11 

## ( ) ( ) den imm ret eco N N r N fNupt N +

− + + = 1 (2) 12

where, 13
N upt = nitirogen uptake by the catchment 14
N imm = nitrogen immobilization by the catchment soil 15
N den =denitrification of nitrogen in the catchment, 16
N ret = in-lake retention of nitrogen 17
f =forest cover in the catchm ent (dimensionless parameter) 18
r = fraction lake/catchment ra tio (dimensionless parameter) 19
20 The second approach for estimating N eco is to take the difference between N deposition 21 and measured N leaching in a catchment as expressed by eq 3. 22

leach eco N N DL N

− = ) ( (3) 23

N deposition is composed of NH x deposition (NH xdep ) and NO y deposition. It is known that 24
NH Xdep contributes to acidification, however the definition of NO x in the CAA does not include 25
NH x , and as such is not defined to provide protection from the acidifying effects of NH x . 26 Therefore, DL ANClim (N) is separated into NH x and NO y . 27 

## ( ) 

## [ ] ) ( ) ( ) ( lim lim lim lim SOx DL NHx DL N DL S Noy DL ANC ANC ANC ANC +

− = + (4) 28Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 179 Draft –D o Not Quote or Cite Equation 1 and 4 will differ catchment by catchment because the acid-base balance of a 1 catchment is a function of site-specific characteristic s. However, for the standard it is desirable to 2 calculate a deposition load for a specified ANC not for an individual catchment, but a larger 3 population of catchments. The site specific values from equation 1 can be used to derive such a 4 deposition loading, here called the deposition metr ic, which represents a group or percentage of 5 water bodies that reach a specified ANC (or higher). For example, if it is desired that all water 6 bodies reach a specified ANC, the allowable amount of deposition for all wa ter bodies is equal to 7 the lowest value calculated from equation 1 for the population of water bodies. Because the 8 deposition metric represents a percentage of individual catchments from a population of water 9 bodies, and not an individual catchment like DL ANClim (S+N), the deposition metric is noted by 10
the follow abbreviation DL %ECO. 11 As an example of the above approach, we evaluate the population of 169 waterbodies in 12 the Adirondacks used in the REA analysis. For each individual water body in the population 13
DL ANClim (S+N) at ANC lim = 50 was calculated using the two equations for deriving the Neco 14 term (eq 2 and 3). The distribution of depositi on loads for the population was assessed and Table 15
5-5 shows the a few selected values for DL %ECO . The mean value for DL %ECO for the 169 water 16 bodies is presented, as well as the values for which 50, 75, 85, 95 and 100% of the water bodies 17 in the population will not exceed th eir critical load at ANC=50. Note, only 32% of water bodies 18
would not exceed their critical load at ANC=50 for the mean value DL %ECO because variability is 19 high in the data set. The depos ition and atmospheric concentration tradeoff curves for DL %ECO 20 equal to 32% and 50% are plotted in the subs equent figures. The Administrator will choose 21 which % of water bodies are projected to reach a targeted level of ANC as part of the overall 22 decision on the elements of the standard; this sele ction may be higher or lower than the examples 23 given here. 24Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 180 Draft –D o Not Quote or Cite Table 5-4. Example Calculations for Determining the Percent of Water Bodies Achieving Target ANC Levels This example is based the population of DL ANClim for and ANC=50 for 169 catchments in the Adirondacks. These catchments occur across on three categories of geologic sensitivity. We could separate the DL ANClim values into sensitivity categories (if info is available) and do the analysis for each category or calculate one DL ANClim for combined geologic categories. Units are in meq/m2/yr.

NH x dep Neco (eq2) DL %ECO (S+N) using N eco eq 2 Neco (eq3) DL %ECO (S+N) using N eco eq 3 % of lakes within the population that

have ANC ≥ 50 Mean 20.40 19.19 162.36 63.95 207.55 31.7% St dev 3.22 3.03 162.92 11.15 165.42 St er 0.25 0.23 13.04 0.86 13.24 Rank %tile 50% 99.33 139.22 50% 75% 65.62 110.37 75% 85% 54.89 95.53 85% 95% 45.12 83.99 95% 100% 30.22 59.07 100% 1 The deposition tradeoff curves for N and S based on DL %ECO at ANC=50 using the two 2 approaches for Neco and protective of 32 and 50% of the population of wa ter bodies, are plotted 3 on Fig 5-8 and 5-9. The values for the maximu m deposition values for N and S are given in 4
Table 5-5. 5
6

Table 5-5. Values for N and S deposition tradeoff curv es for ANC = 50, protecting 32 and 50% of the population, in Adirondacks case study area as illustrated on Fig 5-8 and Fig 5-9. Units are in meq/m2/yr unless noted otherwise.

% protection NH x dep Neco DL %ECO (max N) DL %ECO (max S) DL %ECO (max NOY) 32 Eq 2 20.4 19.19 162.36 143.97 141.96 50 Eq 2 20.4 19.19 99.33 80.14 78.9.3 32 Eq 3 20.4 63.75 207.5 143.6 187.15 50 Eq 3 20.4 63.75 139.22 75.27 118.82 7Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 181 Draft –D o Not Quote or Cite Fig 5.1 Tradeoff curve for S and N deposition to protect from aquatic acidification in the Adirondacks using Neco eq 2

Max(N) =162.36 Max(S)=143.97

Max(N)= 99.33

N eco=19.19 NHx dep=20.40 Max(S)=80.14

0 50 100 150 200

0 50 100 150 200 N (meq/m2/yr)S (meq/m2/yr) ANC=50 & 32% lakes protected ANC=50 & 50% lakes protected Neco NHx Deposition

1 Figure 5-8. Tradeoff curve for S and N deposition to protect from aquatic 2 acidification in the Adirondacks using N eco equation 2. 3

Fig 5.2 Tradeoff curve for S and N deposition to protect from aquatic acidification in the Adirondacks using Neco eq 3

Max(N) =207.5 Max(S) =143.6

Max(N)= 139.22 Max(S)=75.57

NHx dep =20.40 Neco =63.75 

### 0 50 100 150 200

0 50 100 150 200 N (meq/m2/yr)S (meq/m2/yr) ANC=50 & 32% lakes protected ANC=50 & 50% lakes protected Neco NHx Deposition

4 Figure 5-9. Tradeoff curve for S and N deposition to protect from aquatic 5 acidification in the Adirondacks using N eco equation 3. 6Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 182 Draft –D o Not Quote or Cite As previously stated, it is known that NH x deposition (NH xdep ) contributes to 1 acidification. However, the criter ia pollutant listed by EPA pursua nt to section 108 (a) of the Act 2 is oxides of nitrogen does not include NH x , and as such is not define d to provide protection from 3 the acidifying effects of NH x . Therefore, in order to represent the role of NH xdep as a component 4
of acidification it is subtracted from DL %ECO (S+N). The difference is the total allowable 5 deposition from NO y and SO x to protect a selected % of catchments in the population at a 6 selected level of ANC [DL %ECO (S + NO y )] as expressed in equation 5. 7 

# ( ) ( ) DEP ECO OY ECO NHx S N DL S N DL

− + = + % % (5) 8

The NO y and S deposition tradeoff curves for ANC =50, protecting 32 and 50% of the 9 water bodies, are presented in Table 5-6 and plotted on Fig 5-10 and 5-11. If NH x deposition is 10 greater than Neco, then Neco disappears from the tradeoff curve (i.e. Fig 5-11). 11

Table 5-6. Values for NO y and S deposition tradeoff curves for ANC = 50, protecting 32 and 50% of the population in Adirondacks case study area as illustrated on Fig 5.10 and Fig 5.11. Units are in meq/m2/yr unless noted otherwise.

% protection NH x dep Neco (Noy) DLmax(S) DLmax(Noy)

32 Eq 2 20.4 Neco < NH x dep 141.96 141.96 50 Eq 2 20.4 Neco < NH x dep 78.93 78.93 32 Eq 3 20.4 43.35 143.6 187.15 50 Eq 3 20.4 43.35 75.27 118.82 12Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 183 Draft –D o Not Quote or Cite acidification in the Adirondacks using Neco eq 2

Max(N) =141.96 Max(S)=141.96

Max(N)=77.72 Max(S)= 78.93

0 50 100 150 200

0 50 100 150 200 Noy (meq/m2/yr)S (meq/m2/yr) ANC=50 & 32% lakes protected ANC=50 & 50% lakes protected

1 Figure 5-10. Tradeoff curve for S and NO y deposition to protect from aquatic 2 acidification in the Adirondacks using N eco equation 2. 3

aq u atic acidification in the Adirondacks u sing Neco eq 3

Max(S)=143.6

Max(Noy) =187.15 Max(S)=75.27

Max(Noy)=118.82 Neco(Noy)=43.35 

### 0 50 100 150 200

0 50 100 150 200 NOy (meq/m2/yr)S (meq/m2/yr) ANC=50 & 32% lakes protected ANC=50 & 50% lakes protected Neco

4 Figure 5-11. Tradeoff curve for S and NO y deposition to protect from aquatic 5 acidification in the Adirondacks using N eco equation 3. 6 The tradeoff curves for the atmospheric concentration of NO y and SO x are presented in 7 Fig 5-12 and 5-13. Deposition values for NO y and S (from Table 5-6, Fig 5-10 and 5-11) were 8 multiplied by the ratio of concentrations to depositions (previously referred to as aggregate 9Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 184 Draft –D o Not Quote or Cite effective deposition velocities17) for NO x and SO x (VSO x = 0.03824755 μ g/m 3 /meq/m2 and 1
VNO x = 0.04386373 μ g/m 3 /meq/m2). This is expressed in eq uation 5. These velocities were 2 calculated by taking the median value of the concentration of oxidized N to deposition of 3 oxidized N ratio in CMAQ for all grid cel ls over the Adirondack case study area. 4 

# ( ) 

# [ ] ( ) 

## [ ] ( ) DEP ECO ECO OY ECO NHx S N DL Vsox S DL Vnoy N DL

− + = ⋅ + ⋅ % % % (6) 5

Fig 5.5 Tradeoff curve for atmospheric concentration of Sox and Noy to protect from aquatic acidification in the Adirondacks using Neco eq 2

0 5 10

0.00 10.00 Noy (ug/m3)Sox (ug/m3) ANC=50 & 32% lakes protected ANC=50 & 50% lakes protected

6 Figure 5-12. Tradeoff curve for atmospheric concentration of SO x and NO y to 7 protect from aquatic acidificat ion in the Adirondacks using N eco equation 2. 8

17 Note to reviewers: in previous drafts we have referred to the ratios of deposition to concentration for NO y and SOx as “aggregate effective velocities.” We are revisiting th is choice of terms, as it is not as accurate a reflection of the parameter as we might prefer. The concern with continui ng to use the term “velocity” in this context is that it will be misinterpreted by the scientif ic community, and in order to avoid co nfusion, we will likely replace the term with “deposition ratio” or some other term that more accurately describes the parameter.Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 185 Draft –D o Not Quote or Cite Fig 5.6 Tradeoff curve for Sox and Noy atmospheric concentrations to protect from aquatic acidification in the Adirondacks using Neco eq 3

0.00 10.00

0.00 10.00 Noy (ug/m 3 )Sox (ug/m3) ANC=50 & 32% lakes protected ANC=50 & 50% lakes protected

1 Figure 5-13. Tradeoff curve for atmospheric concentration of SO x and NO y to 2 protect from aquatic acidificat ion in the Adirondacks using N eco equation 3. 3
5.5.2 Derivation of the Atmospheric Acid ification Potential Index (AAPI): 4 While the conceptual framework above provi des a means for calculating tradeoff curves 5 associated with a specific level of protection (indicated by a target ANC level) and a specific 6 percentage of ecosystems protected within an ov erall sensitive area, it does not provide a clearly 7 integrated statement that can be expressed as a level such as would be needed for the secondary 8 standard. The goal of this development of the AAP I is to create an index which can be applied 9 across the nation to convey the pot ential of an ecosystem to become acidified from atmospheric 10 deposition. 11
The definition of the AAPI form considered here is: 12 Annual Average AAPI: Natural backgr ound ANC minus the contribution to 13 acidifying deposition from NH x , minus the acidifying contribution of NO y and 14 SO x . This term is essentially a calculated ANC value that represents a percentage 15 of catchments in a population. 16 In order to derive the AAPI, we start with th e basic framework of critical loads discussed 17 in the example above. 18 The approach used to calculate N and S de position values for a specified ANC at a 19 catchment-scale is expressed in Equation 1. The deposition value for a specified ANC will vary 20Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 186 Draft –D o Not Quote or Cite from catchment to catchment based on how the properties that counter balance the acidifying 1 deposition vary among catchments. Equation 5 expre sses how to calculate a deposition metric for 2 a specified ANC for a population of waterbodies that could represent a national acid-sensitivity 3 category. Moreover, the quantity of deposition equal to a specified ANC limit (i.e. critical load) 4 will vary in eq 1 and 5 depending on the char acteristics of the catch ment or population of 5 catchments, respectively. The goal for a secondary NO x and SO x NAAQS is to develop a form 6 for the standards that allows us to set a sing le value for the standard across the U.S. To 7 accomplish this, we rearrange equation (1) to solve for ANC (place ANC on the left hand side of 8 the equation): 9 

## [ ] ( ) ( ) 

## [ ] S DL N DL Q BC N ANC Q O eco +

− ⋅ + = ⋅ * lim (7) 10



## [ ] ( ) () 

## [ ] S DL N DL Q BC N Q ANC O eco +

− + = 1 1 * lim (8) 11

In order to develop a form for the standard in which the level can be expressed as a single 12 national value related to protec tion against effects that occur at specific values of ANC, a 13 simplified version of equation (8) is: 14

) ( 1 ) ( lim S N DL Q g ANC +

− ⋅ = (9) 15

where, 

## ( )

⋅ g = sustainable flux of base cations from the ecosystem + ecological sinks of N. This 16 term is equivalent to the pre-industrial ANC le vel, or the natural bac kground ANC, expressed as: 17


## ( ) 

## [ ] * 1

O eco BC N Q g + ⋅ = ⋅ (10) 18

Building from equation 9, total nitrogen de position is split into oxidized and reduced 19 nitrogen because we need to be able to specify the standards in terms of oxides of nitrogen, and 20
so the contribution of reduced ni trogen has to be separated. 21


## ( ) ( ) () 

## [ ] ( ) NHx DL Q S DL N DL Q g ANC OY ⋅ − +

− ⋅ = 1 1

lim (11) 22Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 187 Draft –D o Not Quote or Cite where, 1 DL(N OX )= the depositional load of oxidized nitrogen 2 DL(NH x )= the depositional load of reduced nitrogen, NH x . 3
4 In order to judge whether an ecosystem or group of ecosystems meets the ANC limit given 5
observed NO y and SO x levels, the associated depositional loadings of NO y and S can be 6 compared directly against calculated depos ition tradeoff curves (eq 4), atmospheric 7
concentrations of NO y and SO x can be compared against the atmospheric concentration tradeoff 8 curves (eq 5) or, loadings of NO x and SO x can be input into the follo wing equations to obtain the 9 calculated value of ANC, equal to ANC*: 10 

## ( ) ( ) 

## [ ] ) ( ) ( * NHx L SOx L Noy L g ANC

− +

− ⋅ = (11) 11

where, 12 ANC*= the calculated value of ANC given load ings of N and S for comparison against an 13
ANC limit . 14 L(N ox +S)= the load of N ox +S anions based on observed atmospheric concentrations of NO y and 15
SO x 16 L(NH x ) = the load of reduced nitrogen deposition 17 [Note that L(N) = L(N ox +NH x )] 18
19 In equation 11, the ANC* will vary base d on the deposition load inputs of N ox , NH x and 20
S at the site of interest. The deposition loads caused by NO y and S and NH x are inputs, leading to 21


## ( ) () 

## [ ] ( ) NHx DL Q S L N L Q g ANC OX ⋅ − +

− = 1 1 * (12) 22

If ANC* < ANC lim , then the deposition of N and S exceeds the deposition load to maintain 23
ANC limit . ANC* is still representative of the cal culated ANC based on specific catchment level 24 estimates of g, Q and NH x . 25 AAPI is equivalent to the equation for cal culating ANC* when the catchment specific 26 values for g in equation (9) in Section 5.5.1. are replaced by representa tive values for acid 27 sensitive areas (based on a per centile of water bodies targeted for an ANC level selected by the 28Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 188 Draft –D o Not Quote or Cite Administrator), Q and NH x are replaced by average values for aggregate ecosystem areas, and 1 L(N OX ) and L(S) are replaced by terms translating atmospheric NO y and SO x into deposition: 2


## ( ) 

# [ ] SOx V NOy V Q NHx L Q g AAPI SOx NOy ⋅ + ⋅ − − ⋅ = 1 ) ( 1 (13) 3

where NO y and SO x are concentrations of NO y and SO x , respectively, V NOy and VSO x are the 4 ratios of deposition to concentrations (deposition transformation ratios) for NO y and SO x , 5 respectively. 6



### 5.6 REFERENCES 7 Davis, J. M., Swall, J. L., 2006. An examination of the CMAQ simulations of the wet deposition 8 of ammonium from a Bayesian perspec tive. Atmospheric Environment 40, 4562–4573. 9

EPA, 1999. Science Algorithms of the EPA M odels-3 Community Multiscale Air Quality 10 (CMAQ) Modeling System. Tech. Rep. EPA/600/R-99/030, U.S. Environmental 11 Protection Agency, Washington DC. 12

Grantz, D., Garner, J., Johnson, D., 2003. Ecologi cal effects of particulate matter. Environment 13 International 29, 213-239. 14

Lien L; Raddum GG; Fjellheim A. (1992). Critical loads for surface waters: invertebrates and 15 fish. (Acid rain research report no 21). Os lo, Norway: Norwegian Institute for Water 16
Research 17

Morris, R. E., McNally, D. E., Tesche, T. W., Tonnesen, G., Boylan, J. W., Brewer, P., 2005. 18 Preliminary evaluation of the community mu ltiscale air quality model for 2002 over the 19
Southeastern United States. Journal of the Air and Waste Management Association 55, 20
1694–1708. 21

Seinfeld, J., Pandis, S., 1998. Atmospheric Chemis try and Physics. John Wiley and Sons, Inc., 22
New York. 23Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 189 Draft –D o Not Quote or Cite Sullivan TJ; Webb JR; Snyder KU; Herlihy AT; Co sby BJ. (2007). Spatial distribution of acid1 sensitive and acid-impacted streams in relati on to watershed features in the southern 2 Appalachian mountains. Water Air Soil Pollut, 182, 57-71. 3

Sullivan TJ; Fernandez IJ; Herlihy AT; Dris coll CT; McDonnell TC; Nowicki NA; Snyder KU; 4 Sutherland JW. (2006). Acid-base characterist ics of soils in the Adirondack Mountains, 5 New York. Soil Sci Soc Am J, 70, 141-152. 6

7Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 190 Draft –D o Not Quote or Cite 

### 6. OPTIONS FOR ELEMEN TS OF THE STANDARD 1

The elements of the standard include the ambi ent air indicator, the form, the level and the 2 averaging time. The “indicator” of a standard de fines the chemical species or mixture of the 3 criteria air pollutant that is to be measured in determining whether an area attains the standard. 4 The “form” of a standard defines the air quality stat istic that is to be compared to the level of the 5 standard in determining whether an area attain s the standard. The “averaging time” defines the 6 period of time over which the air quality indicator is averaged, e.g. annual average. The “level” 7 is the specific quantity to which the air quality statistic will be compared. 8 EPA has historically established NAAQS so that the locally-monitored ambient 9 concentration of an air pollutant indicator is compared against a specif ied numerical level of 10 atmospheric concentration, using a specified av eraging time and statistical form. For example, 11 the current secondary standard for oxides of nitrogen uses ambient concentrations of NO 2 as the 12 indicator. Attainment is determined by compari ng the annual arithmetic mean of the measured 13 maximum daily1-hour NO 2 concentrations, for a calendar year , against the level of 0.053 ppm. 14 As discussed in Chapters 4 and 5, a standard us ing this kind of approach for defining indicator, 15 averaging time, form, and level is not the most appropriate way to protect sensitive ecosystems 16
from effects associated with ambient concentrations of NO x and SO x . Moreover, the inherently 17 complex and variable linkages betw een ambient concentrations of NO x and SO x , their deposited 18 forms of nitrogen and sulfur, and the ecological re sponses that are associat ed with public welfare 19 effects call for consideration of a more complex and ecologically relevant design of the standard 20 that reflects these linkages. 21 Chapter 5 provided a conceptual framework for a secondary standard that is designed to 22 provide protection of ecosystems against the e ffects associated with deposition of ambient 23
concentrations of NO x and SO x . This conceptual framework takes into account variable factors, 24 such as atmospheric and ecosystem conditi ons that modify the amounts of deposited NO x and 25
SO x , and the associated effects of deposited N and S on ecosystems. Based on the conceptual 26 framework described in Chapter 5, this chapter provides a set of potentia l options for specifying 27 the elements of the framework to define a secondary standard for NO x and SO x . Our 28 development of options for the standards recognizes the need for a nationally applicable standard 29 for protection against adverse e ffects to public welfare, while recognizing the complex and 30 heterogeneous interactions between atmospheric concentrations of NO x and SO x , deposition, and 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 191 Draft –D o Not Quote or Cite ecological response. These options will include el ements of the framewor k related to the air 1 quality indicator, the averaging time, the form, and the level, which are based on the ecological 2 indicator, the ecological response to deposit ion function, the deposition metric, and the 3 atmospheric deposition transformation function. 4 To make the transition from the conceptual framework in Chapter 5, which is developed 5 largely around the concept of critical loads, to elements of the standard, we propose to focus on 6 developing a form of the standa rd that is based on the concepts of critical loads of NO x and SO x 7 deposition linked to target ANC va lues, recognizing the limitations in available data and related 8 uncertainties. Our goal in developi ng the form of the standard is to create an index, directly 9 expressed in terms of atmos pheric concentrations of NO y and SO x , that can be applied across the 10 nation to convey the potentia l of an ecosystem to become acidi fied from atmospheric deposition. 11 This chapter is structured around questions rela ted to the various elements of a standard. 12 The chapter begins in section 6.1 with a discussi on of atmospheric indica tors. Section 6.2 then 13 discusses averaging times for the atmospheric indicators. Section 6.3 suggests a possible 14 ecologically relevant form of the standard. Sec tion 6.4 provides a discussion of issues regarding 15 the spatial area over which a standa rd might be evaluated, and re lated issues regarding spatial 16 averaging within areas. Secti on 6.5 discusses options for spec ifying target levels for the 17 ecological indicator for aquatic aci dification. Section 6.6 addresse s issues relating to monitoring 18 of the atmospheric indicators. Section 6.7 conclu des with a discussion of potential ranges of 19
levels for the standard. 20



### 6.1 WHAT ATMOSPHERIC INDICA TORS OF OXIDIZED NITROGEN 21 

### AND SULFUR ARE APPROPRIAT E FOR USE IN A SECONDARY 22 

### NAAQS THAT PROVIDES PROTEC TION FOR PUBLIC WELFARE 23 

### FROM EXPOSURE RELATED TO DEPOSITION OF N AND S? 24 

### WHAT AVERAGING TIMES AN D STATISTICS FOR SUCH 25 

### INDICATORS ARE APPROPRIATE TO CONSIDER? 26

Staff concludes that i ndicators other than NO 2 and SO 2 should be considered as the 27 appropriate pollutant indicators fo r protection against the acidifi cation effects associated with 28 deposition of NO x and SO x . This conclusion is based on th e recognition that all forms of 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 192 Draft –D o Not Quote or Cite oxidized nitrogen and sulfur in the atmosphe re contribute to de position and resulting 1 acidification, and as such NO 2 and SO 2 are incomplete indicators. Furthermore, staff concludes 2
that NO y (total oxidized nitrogen) sh ould be considered as an appr opriate indicator for oxides of 3 nitrogen. NO y is defined as NO x (NO and NO 2 ) and all oxidized NO x products: including NO, 4
NO 2 , and all other oxidized N-containing compounds transformed from NO and NO 2 (Finlayson5 Pitts and Pitts, 2000). As described in Chapter 4, this set of compounds includes NO 2 + NO + 6
HNO 3 + PAN +2N 2 O 5 + HONO+ NO 3 + organic nitrates + particulate NO 3. Staff concludes that 7
SO x should be considered as an appropria te indicator for oxides of sulfur. SO x includes sulfur 8 monoxide (SO), sulfur dioxi de, sulfur trioxide (SO 3 ), and disulfur monoxide (S2O), and 9 particulate-phase S compounds that result from gas- phase sulfur oxides intera cting with particles. 10 In principle, measured NO y based on catalytic conversion of all oxidized species to NO 11 followed by chemiluminescence NO detection is cons istent with this definition. We recognize 12
the caveats associated with instrument conversio n efficiency and possible inlet losses which are 13 discussed in Section 5.6. The development of the function that converts atmospheric 14
concentrations of NO y and SO x to N and S deposition which incorporates NO y estimates is based 15 on the Community Multi-scale Air Quality (CMAQ) model (EPA, 1999). CMAQ treats the 16
dominant NO y species as explicit species while th e minor contributing non-PAN organic 17 nitrogen compounds are aggregat ed. Total oxidized sulfur, SO x , requires independent 18 measurements of particle bound sulfate and ga seous sulfur dioxide; methodology and network 19
considerations are discussed in Se ction 5.6. The CMAQ treatment of SO x is the simple addition 20 of both species which are treated explicitly in th e model formulation. All particle size fractions 21 are included in the CMAQ SO x estimates. At this time, we cons ider the contribution of coarse 22 fraction (aerodynamic diameters between 2.5 and 10 microns) particle bound sulfate to be 23 insignificant from a measurement perspective. Consequently, the routinely measured sulfate 24 from IMPROVE and EPA speciation networks, as well as CASTNET, are viable candidates for 25
measurement consideration. Consis tent with units and the charge balance relationships applied in 26 ecosystem acidification models, only mass as su lfur or nitrogen is considered requiring 27 conversion of reported particle bound sulfate and nitrate. Pr ecipitation mass is not included 28 explicitly as part of an atmospheric NAAQS indicator. 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 193 Draft –D o Not Quote or Cite 

### 6.2 WHAT IS THE APPROPRIATE AVERAGING TIME FOR THE AIR 1 

### QUALITY INDICATORS NO Y 

### AND SO X 

### TO PROVIDE 2 

### PROTECTION OF PUBLIC WELF ARE FROM ADVERSE EFFECTS 3 

### FROM ACIDIFICATION? 4

Based on the review of the scientific ev idence, welfare effect s associated with 5
acidification result from annual cumulative deposition of nitrogen and sulfur, reflected in effects 6 on the chronic ANC level (measured as annual ANC) . It is important to note that chemical 7 changes can occur over both long- and short-term timescales. S hort-term (i.e., hours or days) 8 episodic changes in water chemistry can also have significant biologi cal effects. Episodic 9 chemistry refers to conditions during precipitation or snowmelt events when proportionately 10 more drainage water is routed through upper soil horizons th at tend to provide less acid 11 neutralizing than was passing through deeper soil horizons. Surface water chemistry has lower 12 pH and acid neutralizing capacity (ANC) during events than during baseflow conditions. One of 13 the most important effects of acidifying depositio n on surface water chemistry is the short-term 14 change in chemistry that is termed “episodic aci dification.” Some stream s may have chronic or 15 base flow chemistry that is suitable for aquati c biota, but may be subject to occasional acidic 16 episodes with lethal consequences. Episodic declin es in pH and ANC are nearly ubiquitous in 17 drainage waters throughout th e eastern United States and ar e caused partly by acidifying 18 deposition and partly by natural pr ocesses. As noted in Chapter 3 of the ISA, while ecosystems 19 are also affected by episodic increases in acidit y due to pulses of acid ity during high rainfall 20 periods and snowmelts, protection against thes e episodic acidity events can be achieved by 21 establishing a higher chronic ANC level. Episodic acidification can result from either shorter 22 term deposition episodes, or from longer term deposition on snowpack . Snowmelt can release 23 stored N deposited throughout the winter, leading to episodic aci dification in the absence of 24 increased deposition during the actual episodic acidification event. Protection against a low 25 chronic ANC level is provided by reducing overall annual average deposition levels for nitrogen 26 and sulfur. This supports the conclusion that long term NO x and SO x concentrations are 27 appropriate to provide protecti on against low chronic ANC levels , which protects against both 28 long term acidification and acute acidic episodes. 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 194 Draft –D o Not Quote or Cite Long term concentrations are often measured using annual averages. However, given the 1 multi-year nature of responses to chronic acidification, multi-year averages of concentrations of 2
NO y and SO x may also be appropriate. In the second dr aft policy assessment, we will provide an 3 expanded discussion of the support for different op tions for the averaging time to best represent 4 long-term concentrations of NO y and SO x related to chronic acidification. 5


### 6.3 WHAT FORM(S) OF THE STAN DARD ARE MOST APPROPRIATE 6 

### TO PROVIDE PROTECTION OF SENSITIVE ECOSYSTEMS 7 

### FROM THE EFFECTS OF ACIDI FYING DEPOSITION RELATED 8 

### TO AMBIENT NO X 

### AND SO X 

### CONCENTRATIONS? 9 Based on the evidence for joint effects of NO x and SO x through acidifying deposition, 10 staff concludes that it is appr opriate to consider changes to the form of the existing NO x and SO x 11 secondary standards to provide protection to ecosyst ems. Staff notes that in recent reviews of the 12 secondary ozone standards, EPA has considered us e of a form of the standard that reflects 13 ecologically relevant exposures, by using a cumulative index whic h weights exposures at higher 14 concentrations greater than those at lower c oncentrations based on scientific literature 15 demonstrating the cumulative nature of O 3 -induced plant effects and th e need to give greater 16 weight to higher concentrations (EPA, 2007). S ee 75 FR 2938, 2999 (Janaury 19, 2010) In order 17 to recognize the roles that NO x and SO x play in acidification based on their acidifying potentials, 18 and to incorporate the important roles that reduced nitrogen a nd non-atmospheric variables play 19 in determining the acidifying potentials of NO x and SO x , staff suggests using an Atmospheric 20 Acidification Potential Index (AAPI) that is a mo re ecologically relevant form relative to the 21 current ambient concentration based forms, based on the derivations in Section 5.5.1. The intent 22 of the AAPI is in effect to weight atmospheric concentrations of NO x and SO x by their 23 propensity to contribute to aci dification through deposition, gi ven the fundamental acidifying 24 potential of each pollutant, and the ecological fact ors that govern acid sensitivity in different 25 ecosystems. Thus the APPI is more relevant to protecting ecosystems from acidifying deposition 26 compared to simple ambient concentration fo rms which do not reflect factors that affect 27 acidifying potential. 28 The AAPI is closely tied to the ecological indicator of acidification, ANC, so that the 29 form of AAPI is intended to identify the atmospheric concentrations of NO x and SO x that will 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 195 Draft –D o Not Quote or Cite result in an equivalent level of a target ANC for a percentage of aquatic ecosystems within a 1 particular acid sensitive area. Thus , this form is ecologically relevant as it is tied directly to the 2 ecological indicator that is most direc tly linked with known eco logical effects. 3 The AAPI incorporates the processes wh ich modify both rates of deposition and 4 ecological response to deposition caused by NO x and SO x . There is strong evidence in the 5 scientific literature demonstrating that the amount of deposition caused by NO x and SO x is 6 modified by atmospheric and landscap e factors. Within the ecosystem there are factors, such as 7 bedrock geology and topography, which modify th e acidifying potential of the nitrogen and 8 sulfur deposition resulting from ambient NO x and SO x concentrations. In addition reduced 9 nitrogen contributes to total nitrogen loading. In this review, reduced nitr ogen is treated as an 10 additional modifying factor within the ecosyst em, which reduces the buffering capacity of the 11 ecosystem, and therefore it increases the impact or sensitivity to additiona l loading from oxidized 12 forms of nitrogen. In effect this leav es less allowable deposition loading from NO x and SO x 13 before the ecosystem fails to achieve a target ANC level. Based on this evidence staff concludes 14
that the form should include la ndscape and atmospheric factors, including redu ced nitrogen, 15 which modify the acidifyi ng potential of ambient NO x and SO x concentrations. This form is 16 consistent with the language of the CAA as discussed in Section 1.5. 17 Selecting a more ecologically-r elevant secondary standard fo rm would also be directly 18 responsive to the recommendation of the 2004 Na tional Research Council ’s report titled Air 19 Quality Management in the United States (NRC, 2004) which encourages the Agency to evaluate 20 its historic practice of setting the s econdary NAAQS equal to the primary. 21 In theory, the AAPI could address acidifica tion potential related to both terrestrial 22 acidification and aquatic acidification. For this first draft policy assessment, as discussed in 23 Chapter 5, we define the AAPI for protection ag ainst aquatic acidification. In the second draft 24 policy assessment, we will explore the potential to include protection against terrestrial 25
acidification in the AAPI or a related index. 26
The definition of the AAPI form considered here is: 27 Annual Average AAPI: Natural backgr ound ANC minus the contribution to 28 acidifying deposition from NH x , minus the acidifying contribution of deposition 29 from NO y and SO x . 30 Building from the derivation of ANC* provided in Section 5.5.2, the AAPI is equivalent 31 to the equation for calculating ANC* when the catch ment specific values for g in equation (9) in 32Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 196 Draft –D o Not Quote or Cite Section 5.5.2. are replaced by repr esentative values for acid sensitiv e areas (based on a percentile 1 of water bodies targeted for an ANC leve l selected by the Administrator), Q and NH x are 2 replaced by average values for aggregate ecosystem areas, and L(N OX ) and L(S) are replaced by 3 terms translating atmospheric NO y and SO x into deposition: 4


## ( ) 

# [ ] SOx V NOy V Q NHx L Q g AAPI SOx NOy ⋅ + ⋅ − − ⋅ = 1 ) ( 1 (1) 5

where NO y and SO x are concentrations of NO y and SO x , respectively, V NOy and VSO x are the 6 ratios of deposition to concentrations (deposition transformation ratios) for NO y and SO x , 7 respectively. Deposition transf ormation ratios are the estim ated relationships between 8 atmospheric concentrations of NO y and SO x and the collocated deposition of N OX and S. See 9 Chapter 5.4.4 and 5.4.5 for further descripti on of calculation of ra tios of deposition to 10
concentrations. 11 Note that while equation (1) is used to calculate the value of AAPI for any observed 12
values of NO y and SO x , the level of the standard for AAPI selected by the administrator should 13
reflect a wide number of factor s, including desired level of pr otection indicated by a target 14
ANC limit , the specified percentile of waterbodies pr ojected to achieve th e target ANC, and the 15 various factors and uncertainties involved in spec ifying all of the other aspects of the standard, 16 such as the classification of landscape areas, the specification of reduced n itrogen deposition, the 17 methodology to determine deposition of NO y and SO x , and the averaging time. As such the 18 administrator may choose an AAPI level higher or lower th an the target ANC limit to reflect the 19
combined effect of the all of the components of the standard a nd their related uncertainty, such 20 that the chosen AAPI, in the context of the overall standard, reflects her informed judgment as to 21
a standard that is sufficient but not more than necessary to protect against adverse public welfare 22
effects. 23 How are AAPI parameters determined? 24
Other than ambient levels of NO x and SO x , which would be measured values, EPA would 25 determine and specify all of the values for the AAPI parameters, as discussed below. 26 The natural background ANC, g , is a calculated value and is determined by two 27 components: [BC]o* which is closely associat ed with underlying bedrock which strongly 28
influences the contribution of ba se cations due to weathering, fo r which a representative value 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 197 Draft –D o Not Quote or Cite could be determined for a limited set of geologic acid sensit ivity classes, and N eco , which 1 represents the amount of deposit ed nitrogen that is available for acidification due to uptake, 2
denirification and immobilization. Neco is estimated using two different approaches: (1) the 3 individual terms are estimated through available data and modeling or (2) N eco is calculated as 4 nitrogen deposited minus nitrogen leached, us ing streamwater measurements of nitrate for 5 leaching and estimates of nitrogen deposition based on model results and measurements. The 6 details of these procedures are addressed in chapter 4 a nd Appendix 4 of the REA. 7 The runoff parameter Q for each acid sensitive area is determined based on USGS 8 mapping of runoff values (REFERENCE NEEDED). 9
V NOy , V SO x are calculated from CMAQ by dividing the annual average NO y , SO x 10 concentration by the total NO y or SO x deposition, respectively, for each grid cell and then 11 aggregating all grid cells in the acid sensitive area. 12 L(NH x ) is calculated using the same procedur es applied to CMAQ results for deposited 13
NH x . 14
The V NOy and VSO x are spatially variable, and for th e purposes of setting the standard, 15
are determined based on the ratios of total sulfur and nitrogen depositions to concentrations from 16 CMAQ model outputs (see Chapter 5 for details of calculation of deposition ratios). V NOy , V SO x 17 are calculated from CMAQ by di viding the annual average NO y or SO x concentration by the total 18
NO y or SO x deposition, respectively, for each grid ce ll and then computing the mean or median 19 of all grid cells in the acid sensitive area (the decision on whether the median or mean value 20 should be used is an option for discussion; the mean will give more we ight to outlier values 21 relative to the median). 22
NH x is spatially variabe and determined based on monitored and/or CMAQ modeled 23 outputs. The average NH x deposition across grid cells within an acid sensitive region will be 24 used to represent the depositional load of NH x . 25 There will be multiple combinations of concentrations of NO x and SO x that result in a 26 specific value of the AAPI. There will be no single combination of NO x and SO x that solves for a 27 particular value of AAPI in all locations. easured concentr ations of annual average NO x and SO x 28 necessary to meet the standards are thus expressed conditionally by the equality in (1), and not 29 by fixed quantities. 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 198 Draft –D o Not Quote or Cite In order to provide a set of values for elemen ts of the form, e.g. to develop a specific set 1 of parameter values for g, V NOy , V S , and Nx, we propose to classify locations in the U.S. into a 2 set of areas based on sensitivity to acidification. Each area would be assigned a classification for 3 the g parameter; for example, as described in Se ction 5.2.2.4, a set of classes of acidification 4 sensitivity might be able to be developed based on underlying bedroc k geology, or bedrock 5 geology plus other ecosystem variables. The g pa rameter (natural background, or preindustrial, 6 ANC) would then be estimated for each of those se nsitivity classes, base d on the critical load 7 modeling available for each class. Each acid sensitive area would then be assigned a value of g 8 based on the geology class in which it falls. In the case of V NOy , V S , and NH x , values for specific 9
areas would be estimated based on the best avai lable monitoring and/or modeling data. Given the 10 limited availability of measured deposition velocities, staff concludes that the calculated 11 deposition ratios based on the CMAQ modeling from 2005 provides the best available source of 12
estimates of V NOy and V S . Evaluation of the stability of thes e estimates of deposition ratios over 13 time (see Chapter 5) suggests that in most acid sensiive areas, deposition ratios are quite stable, 14 with a coefficient of variation less than 25 per cent across a four year period. While there are a 15
limited number of sites that direct ly measure deposition of reduced nitrogen, staff concludes that 16 the most widely available and defensible es timates of reduced nitrogen deposition (NH x ) are the 17 estimates obtained from the CMAQ modeling from 2005. 18 18 It is important to note for this form of th e standard that the same AAPI can be obtained 19
with differentcombinations of ambient NO x and SO x concentrations. The implication of the form 20 of the standard expressed in equa tion (1) is that there will be a tradeoff curve that reflects the 21
combinations of NO x and SO x that satisfy equation (1) for any specific value of the standard. The 22 shape of the tradeoff curve will depend on the specific values of G, V NOy , V S , and NH x for a 23 limited number of specific areas classified based on acid-sensitivity. As discussed in Chapter 5, 24 all parts of the U.S. would be classified into areas based on acid-sensitivity. Within each such 25 area, EPA would specify the parameter values of APPI, leading to a specific tradeoff curve for 26
each area. The levels of NO y and SO x that meet an AAPI standard expressed for a given 27 

## ( )

⋅ g [preindustrial ANC], Q, L(NH x ) and V NOy and VSO x: 28

18 Note to readers: Maps of CMAQ 2005 estimates of NHx deposition will be included in the second draft policy assessment, along with an evaluation of the represen tativeness of the 2005 NHx deposition for characterizing conditions over a multiyear period.Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 199 Draft –D o Not Quote or Cite 

## ( ) Q AAPI NHx L Q g ST V NOy V ST

NOy ⋅ − − ⋅ ⋅ = ⋅ + ⋅ ) ( (2) 1

Note that 

# [ ] ST V NOy V ST

NOy ⋅ + ⋅ is essentially the critical load of NO y and S, expressed in terms 2 of atmospheric concentrations. As such, equation (2 ) can also be expressed in a form similar to a 3 typical critical load equation as discussed in Chapter 5, e.g. 4 

# ( ) ) ( * 0 NHx L N Q APPI BC ST V NOy V
eco ST NOy − − − = ⋅ + ⋅ (3) 5

This expression is based on 6 

## ( ) 

# ( ) Q AAPI NHx L BC g ⋅ − − + = ⋅ ) ( * 0 (4) 7

The pairs of NO y and SO x that will meet a given AAPI limit are related through the following 8 equations 9 

# ( )

y y NO C NO min * = (5) 10

) ( ) ( min max * y y x NO C NO SOx C SO < ∀ = (6) 11

) ( )) ( ) ( ( ) ( ) ( min *

max min max
max * y y y y y x NO C NO NO NO C NO C SOx C SOx C SO > ∀

⋅ ⎥ ⎥ ⎦ ⎤ ⎢ ⎢ ⎣ ⎡

− + = (7) 12

where, 13

* y NO is the coordinate point for NO y 14

*

x SO is the coordinate point for SO x 15 ) (
max SOx C is the concentration of SO x in the atmosphere consistent with DLmax (S) 16 ) (
max NOy C is the concentration of NO y in the atmosphere consistent with DL max (N) 17 ) ( min y NO C is the concentration of NO y in the atmosphere consistent with DL min (N) 18



## ( ) ) ( 1

max max S DL Vs SOx C = (8) 19Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 200 Draft –D o Not Quote or Cite 

## ( ) ( ) () N DL NHx NHx N DL V NO C

y NO Y min min min 1 < ∀

− = (9) 1



## ( ) N DL NHx min 0 >

∀ = 2


## ( ) ( ) N DL V NO C

N Y max max 1

= (10) 3

where DLmax(S), DLmax (N), and DLmin(N).are based on the critic al load within a sensitive 4 areas that protects a spec ified percentile (e.g. 95 % ) of water bodies in the area. 5
Note that C min (NO y ) is a conditional function determined by the relationship between 6 total nitrogen buffering capacity in an ecosystem and the amount of reduced nitrogen deposition. 7 When reduced nitrogen deposition exceeds the buffering capacity of an ecosystem, then all 8 atmospheric oxidized nitrogen cont ributes to acidification. When reduced nitrogen deposition is 9 less than the buffering capacity of an ecosystem, then some amount of NO y is buffered (i.e. is 10
reflected in C min (NO y ) but that amount reflec ts the contribution of NH x to total nitrogen (the 11 amount of buffering capacity used up by reduced n itrogen). In this case, some fraction of the 12 atmospheric oxidized nitrogen may not contribute to acidification. 13
Recall that these three variab les are conditional on the chosen level of APPI, and reflect 14 the depositional loadings that are associated with an equivalent level of ANC, e.g. for an APPI of 15 50, the DL max (S), DL max (N), and DL min (N) are associated with an ANC of 50. Also recall than 16
DL max (S) for a given ANC is a function of the “natur al” flux of base cations to a watershed, 17 runoff, and the amount of sulfur retention within a waterbody; DL min (N) is the minimum amount 18 of deposition of total nitrogen (NH x + NO x ) that catchment processes can effectively remove 19 without contributing to th e acidic balance; and DL max (N) for a given ANC is a function of 20
DL min (N) and the “natural” flux of base cations to a watershed, runoff, and the amount of 21 nitrogen retention w ithin a waterbody, assuming S is zero. In our framework, DL min (N) is 22 calculated from the FAB critical load modeling (equation 5 from Attachment A of the REA) or 23 estimated through measured or modeled values of total nitrogen deposition and nitrate leaching. 24 As discussed in Chapter 5, the specific estimation of G, V NOy , V S , and NH x in a specific 25 sensitive area will depend on the spatial scale of the sensitive area. Sensitivity can be assessed at 26 the level of individual catchments, however, this presents practical limitations for establishing 27Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 201 Draft –D o Not Quote or Cite meaningful standards, as there are thousands of catchments with in the U.S. Binning classes of 1 sensitivity within larger spatial areas, e.g. th e sensitive ecosystem areas displayed in Figure 6-1 2 (reproducing Figure 4.2-2 in the REA), can provid e a more manageable set of values of G, V NOy , 3
V S , and NH x. These parameters can be estimated in se veral ways for the larger spatial areas. 4 Mean or median values can be generated ac ross catchments, however, this would lead to 5 parameter estimates that do not reflect conditions in the more sensitive lakes in the region. 6 Alternatively, in order to provi de a desired level of protection in these la rger defined spatial 7 areas, estimates based on higher percentiles of th e distributions of para meters across catchments 8 can be generated, e.g. the 75 th or 95 th percentile values of G, V NOy , V S , and NH xr could be used to 9 provide protection for the more vulnerable aquati c ecosystems, however this would potentially 10 lead to over-protection for less vulnerable ecosystems in the area. The Administrator may 11 consider the balance between protection of par ticularly sensitive ecosystems and the overall 12 protection for ecosystems in an area as an important element to consider in making decisions 13 about the target level of ANC and the percent of aquatic ecosystems within an area targeted to 14 achieve the specified ANC level. One potentially important modification to this process would 15
be to first remove water bodies th at are naturally acidic (e.g. that will not benefit from reductions 16 in atmospheric NO x and SO x deposition) from the distribution of water bodies in the area prior to 17 determining the mean or 95 th percentile. This will increase the likelihood that the estimated g 18 parameter will be representative of ecosystems within an area that are sensitive to NO x and SO x 19 deposition. The second draft policy assessment w ill explore the implications of alternative 20 combinations of target ANC and percent of aqua tic ecosystems protected at the target ANC in 21 areas of different sizes. The second draft pol icy assessment will also explore methods for 22 determining values of g for areas that are clearly not sensitive to acidifi cation from deposition of 23
NO x and SO x . These areas may be areas that have very high levels of natural buffering, or may 24 also be areas that are naturally aci dified, such that the value of g is less than the target value of 25 ANC. In these naturally acidified areas, reducing deposition from NO x and SO x will not be 26 beneficial, because the areas are ad apted to high levels of acidity. 27Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 202 Draft –D o Not Quote or Cite 1 Figure 6-1. Ecosystems sensitive to acidifyi ng deposition in the Eastern U.S. 2 (Note that Florida represents a special case where high levels of natural 3 acidification exist unrelated to deposition) This map does not include all sensitive 4 areas in the U.S. Certain m ountainous areas of the Wester n U.S. are also sensitive 5 to acidifying deposition. 6Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 203 Draft –D o Not Quote or Cite 

### 6.4 WHAT ARE THE APPROPRIAT E SPATIAL EXTENTS OF THE 1 

### BOUNDARIES FOR EVALUATI NG AAPI? WITHIN THOSE 2 

### BOUNDARIES, WHAT ARE THE AP PROPRIATE STATISTICS TO 3 

### USE IN CALCULATING THE PARAM ETERS OF THE AAPI, E.G. 4 

### G, V NOY 

### , V S 

### , AND NH X 

### ? WITHIN THOSE BOUNDARIES, WHAT S 5 

### THE APPROPRIATE SPATIAL AVERAGING FOR THE AIR 6 

### QUALITY INDICATORS NO Y 

### AND SO X 

### TO PROVIDE 7 

### PROTECTION OF PUBLIC WELF ARE FROM ADVERSE EFFECTS 8 

### FROM ACIDIFICATION? 9
[Note to reviewers: This s ection will be added in the sec ond draft policy assessment. In 10 the second draft we plan to provide initial sets of paramete i r values for acid sensitive areas of 11 the U.S., and include an explorati on of how the standard might be sp ecified for areas of the U.S. 12
that are not sensiti ve to deposition of NO x and SO x . In addition, we plan to discuss the 13
correlation between the ext ent of a spatial area and the impo rtance of evaluating alternative 14 percentiles of critical loads to protect a percentage of water bodies in an area, and to discuss 15 how averaging of the VNOY, V SO x , and NH x should be conducted to best represent the 16 parameters for an area.] 17



### 6.5 WHAT ARE THE OPTIONS FO R SPECIFYING THE TARGETS 18 

### FOR THE ECOLOGICAL I NDICATOR FOR AQUATIC 19 

### ACIDIFICATION? 20 Chapter 5 discusses the rationale for use of ANC as the ecologi cal indicator best suited to 21 reflect the sensitivity of aquatic ecosystems to acidi fication. ANC as an indicator of acidification 22 is causally linked to a number of measures of adversity to ecosys tems, including declines in fish 23 populations and diversity of aqua tic species. ANC is also caus ally linked with deposition of 24 nitrogen and sulfur. ANC is thus ideally suited to serve as the bridge between deposition and 25 ecological effects. As such, staff concludes th at ANC is the best available choice as the 26 ecological indicator. CASAC has agreed that ANC represents a suitable ecological indicator for 27 aquatic acidification (EPA-CASAC -09-013). Results from the RE A confirm that ANC may be 28Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 204 Draft –D o Not Quote or Cite used to establish impacts from current depositio nal loadings ( REA 4.2.6 ). As explained above, 1 ANC is an indicator of the effects expected to occur given the natural buffering capacity of an 2 ecosystem and the loadings of nitrogen and su lfur resulting from atmospheric deposition. A 3 target ANC limit based on a desired level of protec tion is an important input to the decisions of 4 the level of AAPI and the percent of ecosystems to be protected. 5

6.5.1 What levels of impairment are re lated to alternative levels of ANC? 6 As discussed in Chapters 2, 3, and 4, specifi c levels of ANC are associated with differing 7 levels of ecosystem impairment, with higher levels of ANC resulting in fewer ecosystem 8 impacts, and lower levels resulting in both hi gher intensity of impact s and a broader set of 9 impacts. Logistic regression of species pr esence/absence data against ANC provides a 10 quantitative dose-response func tion, which indicates the prob ability of occurrence of an 11 organism for a given value of ANC. For exampl e, the number of fish species present in a 12 waterbody has been shown to be positively correlated with the ANC level in the water, with 13 higher values supporting a greate r richness and diversity of fi sh species (Figure 6-2). The 14 diversity and distribution of phyt o-zooplankton communities are also positively correlated with 15
ANC. 16 The relationship between ANC and ecosystem impacts is non-linear, with a sigmoidal 17 shape. For freshwater systems, ANC levels can be grouped into five major classes: <0, 0–20, 20– 18 50, 50–100, and >100 microequivalents per liter ( μ eq/L), with each range representing a 19 probability of ecological damage to the community. The five categories of ANC and expected 20 ecological effects are described Table 2-1 in Chapter 2 and are supported by a large body of 21 research completed throughout the eastern United States (Sul livan et al., 2006). 22 Biota are generally not harmed when ANC values are >100 microequivalents per liter 23 ( μ eq/L). The number of fish specie s also peaks at ANC values >100 μ eq/L. This suggests that at 24 ANC greater than 100, little risk from acidification exists in mo st aquatic ecosystems. At ANC 25
levels below 100 μ eq/L, overall health of an aquatic community can be maintained; however, 26 fish fitness and community diversity begin to decline

. At ANC levels between 100 and 50 μ eq/L, 27 the fitness of sensitive species (e.g., brook trout, zooplankton) also begins to decline. When ANC 28
concentrations are <50 μ eq/L, negative effects on aquatic bi ota are observed, including large 29 reductions in diversity of fish species, and ch anges in health of fi sh populations, affecting 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 205 Draft –D o Not Quote or Cite reproductive ability and fitness. ANC levels below 50 are generally associated with death or loss 1
of fitness of biota that are sensitive to acidification. ( ISA 5.2.2.1 and REA 5.2.1.2 ). 2
Based on the field data from the Adirond acks and Shenendoah case study areas, ANC 3 levels less than 50 are clearly adverse to ecosystem health, and are likely to lead to reductions in 4 ecosystem services related to recreational fishing. ANC le vels between 50 and 100 are 5 potentially adverse to ecosystem health, and may re sult in losses in ecosystem services, but the 6 effects are less severe and greater uncertainty ex ists as to the magnitude of ecosystem service 7 impacts. A more comprehensive discussion of un certainties related to ecological effects at 8 different ANC levels and related ecosystem serv ices will be included in the second draft policy 9

assessment. 10 The implications of the data from the Adirondacks and Shenendoah case study areas for 11 relating ANC to adverse ecological impacts is tran sferable to other acid sensitive areas of the 12 U.S. The relationship between species diversity and ANC is quite similar between the two case 13 study areas (see REA Figure 4.2-1 ), which have different wa ter body types and different 14 geological and topographical features. While the species composition and thereby relative 15 sensitivities of species are likely to vary across th e landscape, the rate of impact is likely to be 16 similar. The plot in Figure 6-2 shows a rapid decrease in fish species between an ANC of 100 17
and an ANC of 0. This trend is what would be expected in many systems given similar changes 18
in ANC. 19
Consideration of the a ppropriate levels of ANC to target in the standard to reduce the 20 likelihood of effects from aquatic acidification can be based upon the above presented categories 21 of aquatic status in Table 2-1. Using this info rmation as well as information provided by both the 22 ISA and REA, the lowest two categories (0 and 0< 20) would appear inadequa te to protect against 23 catastrophic loss of ecosystem function. While ec ological effects occur at ANC levels below 50, 24 the degree and nature of those effects is less sign ificant than at levels be low 20. Therefore, three 25 levels of ANC – 20, 50, and 100 - would provide the Administrator with reasonable range of 26 options in designing an AAPI fo r protecting public welfare. 27 Given the level of ecosystem impairment occu rring at ANC levels below 50, staff suggest 28 that the greatest support is for the Administrator to consider a range for the target ANC between 29 50 and 100 as a basis for the design of the standard . Selection of target ANC values closer to 50 30 places less weight on the vulnerabilit y of sensitive aquatic ecosystems, while selection of target 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 206 Draft –D o Not Quote or Cite ANC values closer to 100 places more weight on sensitive species within acid sensitive 1 ecosystems. Staff conclude that while target ANC values between 20 and 50 will not result in 2 complete impairment of aquatic systems, the le vel of damages due to ANC as you get lower in 3 this range are highly likely to result in advers e impacts to public welfar e in many locations, due 4 to the significant reductions in the number of fish species in affect ed waterbodies, and the 5 reductions in health and reproductive fitness of fish populations and othe r aquatic organisms. 6

7 Figure 6-2. Number of fish species per lake or stream versus ANC level and 8 aquatic status category 19 (colored regions) for lakes in the Adirondack Case Study 9 Area (Sullivan et al., 2006). 10 The target ANC level specified in designing the standard is only one part in determining 11 the overall protectiveness of the standard. The de gree of protectiveness is based on all elements 12 of the standard, including the target ANC, the size of the spatial areas over which the standard is 13 applied, the percent of aquatic ecosystems targeted within a spatial area that is selected by the 14
Administrator to achieve the selected ANC leve l, the atmospheric indicator, the method for 15 calculating g, the calculated values fo r the deposition transf ormation ratios (VNO x and VSO x ), 16

19 The aquatic status categories are based on the literature and are discussed in detail in the REA ( REA Appendix 4- 20 )Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 207 Draft –D o Not Quote or Cite and the calculated value for re duced nitrogen deposition (NH x ). There are widely varying 1 degrees of uncertainty associated with all of th ese elements, some being much more certain and 2 others being much less certain. The specified targ et ANC level is a crucia l part of developing a 3 standard that is requisite to protect, but it is th e overall design and content of the standard that 4 must be considered in judging the ad equacy of protection it provides. 5 Consideration of the target ANC should also reflect that an adequate level of ANC should 6 protect against episodic as well as long term e ffects. Selecting a highe r chronic ANC level can 7 provide greater protection against short term peaks in acidification. In addition, selection of ANC 8 values in the range of 20 to 50 provides less prot ection against these short term episodic effects. 9 Selection of target ANC values in the range from 50 to 100 provide s additional protection 10 against episodic peaks in acidification. 11 When considering the appropr iate level of a standard to protect against aquatic 12 acidification, it is necessary to take into account both the time period desired for recovery as well 13 as the potential of recovery. Ecosystems become adversely im pacted by acidifying deposition 14 over long periods of time and have variable ti me frames and abilities to recover from such 15 perturbations. Modeling pr esented in the REA ( REA Section 4.2.4 ) shows the estimated ANC 16
values for Adirondack lakes and Shenandoah st reams under pre-acidification conditions and 17 indicates that for a small percentage of lakes a nd streams, natural ANC levels would have been 18 below 50. Therefore, for these waterbodies, no reduc tion in input is likely to achieve an ANC of 19 50 or greater. Conversely, for some lakes and st reams the level of perturbation from long periods 20 of acidifying deposition has resulted in very lo w ANC values compared to estimated natural 21 conditions. For such waterbodies, the time to re covery would be largel y dependent on future 22 inputs of acidifying deposition. These concepts become important in the consideration of the 23 desired level of protection of a standard and will be discussed further in the next draft of this 24
document. 25Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 208 Draft –D o Not Quote or Cite 

### 6.6 WHAT ARE THE APPROPRIATE AMBIENT AIR MONITORING 1 

### METHODS TO CONSIDER IN DEVELOPING THE STANDARDS? 2

6.6.1 What measurements would be used to characterize NO y and SO x ambient air 3 concentrations for the purposes of the AAPI based standard? 4
Ambient NO y , gaseous SO 2 and particulate sulfate concen trations would be used in 5 determining compliance with the AAPI. This would require measurements of NO y , sulfate and 6 sulfur dioxide, all which are conducted as part of current routine mon itoring networks (section 7 3.2). There are issues requiri ng resolution associated with Fe deral Reference or Equivalency 8 Measurement (FRM/FEM) status of measurement techniques, that to da te have served as 9 supplemental information, which will require resolution. A FRM for SO 2 exists, but not for NO y 10 or sulfate. Only recently have NO y measurements, which historica lly were viewed as research 11 venue measurements, been incorporated as “routine” observations, partly as a result of the NCore 12 program. Acquiring FRM status may require be tter characterizati on of the conversion 13 efficiencies, mass loss and clear guidance on opera ting and siting procedures. Particulate sulfate 14 has been measured for several years in th e IMPROVE, CASTNET and EPA CSN networks. The 15 nation has over 500 24-hour average, every th ird day sulfate measurements produced by the 16
PM 2.5 speciation networks (IMPROVE and EPA CS N) and nearly 80 CASTNET sites that 17 provide continuous weekly average samples of sulfate with an open inlet accommodating all 18 particle sizes. However, with minor exceptions, the PM 2.5 fraction accounts for nearly all sulfate 19 mass. The sample collection period is not an issue for gaseous measurements of NO y and SO 2 20 that operate continuously. Some c oncerns have been raised about the possibility of exclusion of 21 coarse particles from NO y samplers operating at low flow conditions as well as potential 22 difficulties of reducing organically bound and mine ralized nitrate. These conversion efficiency 23 and particle size fraction issues are viewed by EPA as relativ ely minor mass accounting issues 24 that require more clarification but not necessarily technical resolution. 25

6.6.2 What sampling frequency would be required? 26 The averaging time for the standard is likel y to be an annual average. Conceptually, 27 extended sampling periods as long as one year would be adequate for the specific purposes of 28 comparing to a standard. However, future assess ments that characterize acidification and form 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 209 Draft –D o Not Quote or Cite the scientific basis for subsequent standards reviews and allow for systematic checking of 1 progress through accountability procedures benefit from more highly resolved data, especially 2 the evaluation of air quality models that are ke y components of N/S deposition assessments. In 3 addition, many of the monitoring approaches that are used throughout the nation sample (or at 4 least report out ) on daily (PM 2.5 chemical speciation), weekly (CASTNET) and hourly (all 5 inorganic gases) periods. There is a tradeoff to consider in samp ling period design. For example, 6 the weekly CASTNET collection scheme covers all time periods throughout a year, but only 7 provides weekly resolution that misses key te mporal and episodic f eatures valuable for 8 diagnosing model behavior. The every third day, 24-hour sampli ng scheme used in IMPROVE 9 and EPA speciation monitoring does provide more in formation for a specific day of interest yet 10 misses 2/3 of all sampling periods. The missing sa mpling period generally is not a concern when 11 aggregating upward to a longer te rm average value as the sample number adequately represents 12 an aggregated mean value. Additionally, there is a benefit to leveraging existing networks which 13 should be considered in sampling frequency recommendations. A possible starting point would 14 be to assume gaseous oxidized species, NO y and SO 2 , are run continually all year reporting 15 values every hour, consistent with current rou tine network operations. Su lfate sampling periods 16
should coincide with either th e chemical speciation network sc hedules or CASTNET. There are 17 advantages to coordinating with either netw ork. Ammonia gas and ammonium ion present 18 challenges in that they are not routinely sample d and analyzed for, and the combined quantity, 19
NH x is of interest. Because NH x is of interest, some of the problems of volatile ammonia loss 20 from filters may be mitigated. However, for model diagnostic purposes, delineation of both 21 species at the highest temporal resolution is preferred. While levels of deposited reduced 22 nitrogen would be specified by EPA for purposes of the APPI, m onitoring of reduced nitrogen 23 would be important but would not be used in the APPI itself. 24

6.6.3 What are the spatial scale issues asso ciated with monitoring for compliance, 25
and how should these be addressed? 26
The observation network for NO y , NH x and SO x is very modest and includes a 27 monitoring network infrastructure th at is largely populati on oriented. While there is platform and 28 access infrastructure support provided by CAST NET, NADP and IMPROVE, those locations by 29 themselves are not likely to provide the needed spatial coverage to address acid sensitive 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 210 Draft –D o Not Quote or Cite watersheds across the United States. Ambient mon itoring at every watershed may not be required 1 due to the nature of the ambient air quality in acid sensitive areas. An understanding of the 2 spatial variability of NO y , NH x , sulfate and SO 2 will help inform mon itoring. Critical load 3 models are based on annual averages, which effec tively serves to dampen much of the spatial 4 variability. Furthermore, the de velopment of an area-wide de positional load tradeoff curve 5 implies focus on region wide charac terization. Toward that end, CMAQ concentration fields will 6 provide insight into the likely spatial representativeness of monitors leading to efficient 7 application of monitoring resources. For ex ample, the CMAQ based spatial coefficient of 8 variation (standard deviation/mean) of oxidi zed nitrogen in the Adirondacks was 1.46%. 9 Improved dry deposition estimates will result from enhancements of ambient monitoring 10 addressing the N/S secondary standards as each additional location could serves a similar role 11 that existing CASTNET sites provide in estimating dry deposition. 12



### 6.7 TAKING INTO CONSIDER ATION INFORMATION ABOUT 13 

### ECOSYSTEM SERVICES AND OT HER FACTORS RELATED TO 14 

### CHARACTERIZING ADVERSITY FOR THE ECOLOGICAL 15 

### EFFECTS BEING ASSESSED IN TH IS REVIEW, WHAT IS AN 16 

### APPROPRIATE RANGE OF AL TERNATIVE STANDARDS FOR 17 

### THE AGENCY TO CONSIDER? 18 The secondary NAAQS will reflect the pub lic welfare policy judgments of the 19 Administrator, based on the science, as to the level of air quality which is requisite to protect the 20 public welfare from any known or an ticipated adverse effects associat ed with the po llutant in the 21 ambient air. The exposure and risk assessmen t provide information regarding the effects 22
associated with a number of different welfare endpoints at different levels of air quality, 23 expressed in terms of the joint annual mean concentrations of NO x and SO x determined such that 24 specific levels of ecosystem prot ection (for example, ANC greater than 50) are met. Staff also 25 recognizes that in certain naturally acidic eco systems, even though the ecological benchmarks 26 are exceeded, e.g. ANC may be quite low; NO x and SO x are not contributing to effects because 27 those systems have chronic natural acidity and w ill not benefit from reductions in atmospheric 28 deposition. The secondary NAAQS are not intended to provide protection in these types of 29Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 211 Draft –D o Not Quote or Cite naturally acidic systems. As noted earlier, we wi ll be exploring methods to address the design of 1
the standard relative to these naturally acidic systems in th e second draft policy assessment. The 2 secondary NAAQS are focused on providing protection in areas where ambient NO x and SO x are 3 resulting in effects in ecosystems with low natura l levels of acidification that are highly sensitive 4 to additional inputs of acid deposition. 5 Staff believes that ecosystem effects of NO x and SO x deposition in aquatic ecosystems 6 are an important public welfare e ffect of concern. There are seve ral sources of benchmark values 7 for ANC that can help to inform a determin ation of adversity. [Additional information on 8 benchmark values will be provided in the second draft policy assessment] Staff concludes that 9 achieving ANC in the range of 50 to 100 would be likely to provide adequate protection against 10 the effects of acidification on ecosystems. 11 Based on our analyses of risks of impacts on aquatic species diversity and fitness and on 12
the basis of the scientific effect s literature, we anticipate that achieving the upper end of this 13 ANC range would substantially decrease the effects of acidification due to NO x and SO x on 14 aquatic ecosystems. Additionally, it is anticipate d that achieving the upper end of this range 15 would provide increased protection from NO x and SO x in areas with higher levels of variability 16 in ecosystem sensitivity due to variability in meteorology, bedrock geology, topography, land 17 use characteristics, or reduced nitrogen deposition. 18 These ANC levels are estimated to protect se nsitive aquatic ecosystems from significant 19 negative effects of NO x and SO x deposition on aquatic biota, in cluding large re ductions in 20 diversity of fish species, and ch anges in health of fish populati ons, affecting reproductive ability 21 and fitness. It is recognized, how ever, that a standard set within this range would not protect the 22 most sensitive aquatic ecosystems or species wi thin those ecosystems from the effects of NO x 23
and SO x . At ANC levels below 100, while overall health of an aquatic community can be 24 maintained, ANC levels are expected to be such that fish fitness and community diversity begin 25
to decline

. At ANC levels between 100 and 50, ANC leve ls are expected to be such that the 26 fitness of sensitive species (e.g., brook trout, zoopla nkton) also begins to decline. Staff notes that 27 at levels of ANC above 100, bi ota are generally not harmed. As such, achieving an ANC of 28 greater than 100 would be expected to result in little damage from NO x and SO x deposition to 29 aquatic ecosystems. 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 212 Draft –D o Not Quote or Cite Specifying an appropriate range of levels for an AAPI standard that is designed and 1 specified as discussed above i nvolves consideration of the degree to which any specific AAPI 2 would lead to achieving the desire d ANC level, and a judgment as to the degree of protection of 3 public welfare that is warranted. In general, staff initially conclude that it would be appropriate 4
for the Administrator to consider an AAPI in the range of 50 to 100. Selection of a range of 5 AAPI and selection of a specific level of AAPI within that ra nge should incorporate a wide 6 number of considerations, includ ing the percent of water bodies w ithin acid sensi tive areas that 7
the Administrator determines should be protected at the targeted ANC level. 8
The Administrator should consider the uncerta inties in the ecological effects observed in 9 the literature and the adversity to public welfare a ssociated with those eff ects. In determining the 10 requisite level of protection for the public we lfare from effects on aquatic ecosystems, the 11 Administrator will need to weigh the importance of the predicted risks of these effects in the 12 overall context of public welfare protection, along with a determ ination as to the appropriate 13 weight to place on the associated uncertainti es and limitations of this information. 14 In addition, selection of a specific level of AAPI should c onsider uncertainties in the 15 design and calculation of the parameters include d in the AAPI, including uncertainties in the 16
characterization of natural b ackground ANC (indicated by g in the AAPI equation), spatial and 17 temporal averaging of aggregate effec tive deposition velocities (indicated by V NOY and VSO x in 18 the AAPI equation), and spatial and temporal averaging of NH x deposition (indicated by NH x in 19 the AAPI equation). 20

21Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 213 Draft –D o Not Quote or Cite 

## 7. CO-PROTECTION FOR OTHER EFFECTS USING 1 

## STANDARDS TO PROTECT AGAINST ACIDIFICATION 2
To this point, the standard for NO x and SO x centers on ecosystem protection against 3 aquatic acidification. This chapter focuses on the le vel of co-protection that this standard would 4 provide for other ecologi cal effects, including terrestrial acidification, terrestrial nutrient 5 enrichment, and estuarine eutrophication. 6



### 7.1 TO WHAT EXTENT WOULD A STANDARD SPECIFICALLY 7 

### DEFINED TO PROTECT AGAINS T AQUATIC ACIDIFICATION 8 

### LIKELY PROVIDE PROTECTI ON FROM TERRESTRIAL 9 

### ACIDIFICATION? 10

In order to understand the leve l of protection provided by a NO x /SO x standard based on 11 aquatic acidification to protect ag ainst terrestrial acidification e ffects, an analysis was conducted 12 comparing the critical loads for lakes and streams that would be developed to protect for an 13 aquatic ANC of 50 to the critical loads to protect for either a terrestrial Bc:Al ratio of 1.2 or 10 14 averaged across a watershed area. See Appendix B fo r full analysis results. The analysis selected 15
16 watersheds with 29 lakes in the Adirondacks case study area, 4 watershe ds randomly selected 16 from each of 4 categories of sensitivity reported in the REA: highly sensitive, moderately 17 sensitive, low sensitivity, and not sensitive. In the Shenandoah case study area, there were a 18 limited number of watersheds in the low sensitivity and not sensitive range, so 18 of the 20 19
streams in 16 watersheds selected were located in highly and moderately sensitive categories. 20
Results for the Adirondacks showed that critic al loads for 29 lakes at an ANC of 50 were 21
lower for 13 lakes than the critical load for the terrestrial watershed areas at a Bc:Al ratio of 10 22 and for 21 lakes at a Bc:Al ratio of 1.2. Perhaps more significant was the result that 13 of the 16 23 lakes in the highly and moderately sensitive area s had a lower critical load than the Bc:Al 10 24 areas and 16 of 16 lakes in the highly and modera tely sensitive areas had lower critical loads 25 than the Bc:Al 1.2 areas. The Shenandoah region re flected similar results. See table 7.1 below 26
for tabulated results. 27
28Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 214 Draft –D o Not Quote or Cite Table 7-1. Results of comparing aquatic ANC50 critical loads to average terrestrial watershed area Bc:Al ratios. Left numbers in each column are the number of lakes or streams that had a lower critical load than the terrestrial calculated critical load. Right numbers in each column are the number of lakes that had a higher critical lo ad than the watershed calculated terrestrial critical loads.
Highly Sensitive Moderately Sensitive Low Sensitivity Not Sensitive Adirondack Bc:Al 10 7-0 6-3 0-7 0-6 Adirondack Bc:Al 1.2 7-0 9-0 5-2 0-6 Shenandoh Bc:Al 10 13-0 5-0 0-1 0-1 Shenandoh Bc:Al 1.2 13-0 5-0 0-1 0-1 1 In summary, a comparison of th e terrestrial and aquatic critic al acid loads for watersheds 2 in the Adirondacks and Shenandoah Case Study Ar eas indicated that, in general, the aquatic 3 critical acid loads offered greater protection to the watersheds th an did the terrestrial critical 4 loads. Generally in situations where the terrestria l critical loads were more protective, the lakes 5 or streams in the watershed were rated as having “Low Sensitivity” or “Not Sensitive” to 6 acidifying nitrogen and sulfur deposition. Conversely, when the water bodies were more 7 sensitive to deposition (“Highly Sensitive” or “Mode rately Sensitive”), the aquatic critical acid 8 loads generally provided a grea ter level of protection against acidifying nitrogen and sulfur 9 deposition in the watershed. In the next draft of the Policy Assessment Document, we intend to 10 expand this analysis by comparing more levels of ANC to other Bc:Al ratios. 11



### 7.2 TO WHAT EXTENT WOULD A STANDARD SPECIFICALLY 12 

### DEFINED TO PROTECT AGAINS T AQUATIC ACIDIFICATION 13 

### LIKELY PROVIDE PROTECTI ON FROM TERRESTRIAL 14 

### NUTRIENT ENRICHMENT? 15 This question will be answered in the next draft of the Policy Assessment Document. 16 Once maximum depositional loads are calculated for broad areas, we can compare the derived 17
maximum NO y limits to nutrient enrichment benchm arks found in the REA. Benchmarks for 18 lichens, grasses, mychorrizae, and diatoms will be compared to the aquatic acidification limits 19 for nitrogen. 20Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 215 Draft –D o Not Quote or Cite 

### 7.3 TO WHAT EXTENT WOULD A STANDARD SPECIFICALLY 1 

### DEFINED TO PROTECT AGAINS T AQUATIC ACIDIFICATION 2 

### LIKELY PROVIDE PROTECTION FROM AQUATIC NUTRIENT 3 

### ENRICHMENT? 4 The REA found that deposition of reactive ni trogen contributed to eutrophication of 5 estuaries; however, it was also noted that atmosp heric deposition of nitrog en is only part of the 6 total nitrogen load to the estuaries. Due to the complications of separati ng out the effects of 7 atmospheric deposition from the effects of othe r nitrogen loads, CASA C did not recommend that 8 a secondary NAAQS be set to speci fically protect against estuarin e eutrophication. In the next 9 draft of the Policy Assessment Document, we will attempt to analyze the benefit to the 10 Chesapeake Bay that attaining an aquatic acidification standa rd would provide by decreasing 11 nitrogen deposition to the watershed. 12
13

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## 8. CONSIDERATION OF ISSUES REGARDING REDUCED 1 

## AND OXIDIZED FORMS OF NITROGEN 2
[To be added in the seco nd draft Policy Assessment] 3
4

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### 9. INITIAL CONCLUSIONS 1 Staff initial conclusions on the elements of the secondary NO x and SO x standards for the 2
Administrator’s consideration in making decisions on the secondary NO x and SO x standards are 3 summarized below, together with supporting conclusions from prev ious chapters. We recognize 4 that selecting from among alternative policy options will necessarily reflect consideration of 5 qualitative and quantitative uncerta inties inherent in the relevant evidence and in the assumptions 6 of the quantitative exposure and risk assessments . Any such standard s hould protect public 7 welfare from any known or anticipated adverse effects associated with the presence of the 8 pollutant(s) in the ambient air. In providing thes e options for consideration, we are mindful that 9 the Act requires standards that, in the judgment of the Administrator, are requisite to protect 10 public welfare. The standards are to be neith er more nor less stringent than necessary. 11 To evaluate whether the current secondary NAA QS is adequate or whether consideration 12 of revisions is appropriate, the conclusions and options for the Administrator to consider in this 13 review are based on effects-, exposure- and risk -based considerations. The exposure and risk 14 assessments reflect the availability of new t ools, assessment methods, and a larger and more 15 diverse body of evidence than was available in the last reviews. We have taken a weight of 16 evidence approach that evaluates information across the variety of research areas described in the 17
ISA and in addition includes assessments of air quality, exposures, and qualitative and 18 quantitative risks associated with alternative air quality scenarios. 19 Staff notes that since the last review, a dditional policy-relevant developments have 20 occurred that may also warrant consideration by the Administrator when making decisions about 21 what is requisite to protect public welfare. Th e NRC report (described in Chapter 6) states: 22
“Whatever the reason that led EPA to use identical primary and secondary NAAQS in the past, it 23 is becoming increasingly evident that a new appr oach will be needed in the future. There is 24 growing evidence that the current forms of the NAAQS are not providing adequate protection to 25 sensitive ecosystems and crops” (NRC, 2004). 26 The last review raised the following key issues as a rationale for not setting a separate 27
standard for NO x to protect against acidification and nutrient enrichment effects in sensitive 28 ecosystems: 29 1) Lack of enough consistent information to support a revision of the current secondary 30 standard to protect these aquatic systems. 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 218 Draft –D o Not Quote or Cite 2) Lack of adequate quantitative eviden ce on the relationship between deposition rates 1 and environmental impacts 2 3) Significant uncertainties with regard to the long-term role of nitrogen deposition in 3 surface water acidity and with regard to the quantification of the magnitude and 4 timing of the relationship between atmos pheric deposition and the appearance of 5 nitrogen in surface water. 6 In this current review, staff concludes th at important new information has become 7
available since the last review that supports revising the current NO x and SO x standards. 8 Specifically, the ISA has concluded that there are causal relationships between NO x and SO x 9 acidifying deposition and effects on aquatic and terrestrial ecosystems, and the ISA and REA 10 provide substantial quantita tive evidence of effects occurring in locations that meet the current 11
NO 2 and SO 2 standards. In addition, substantial new information, based on observational data 12 and rigorous atmospheric modeling, has become avai lable regarding the role of both nitrogen and 13 sulfur deposition in acid ification of sensitive water bodies. This information is sufficient to 14 inform the development of revi sed secondary standards for NO x and SO x to protect against the 15
effects of acidification 20 . While there is also new informati on available on the ro le of nitrogen 16 deposition on nutrient enrichment effects in terrestrial and aq uatic ecosystems, and the ISA 17
concludes there is a causa l relationship between NO x and nutrient enrichment effects, for this 18 first draft policy assessment, staff have focused on acidification effects due to the substantially 19 greater amount of information available to info rm the development of secondary standards. 20 Staff highlights the progress made in consider ing the joint nature of ecosystem responses 21 to acidifying deposition of NO x and SO x , and notes that the ability to consider revisions to the 22
NO x and SO x secondary standards has been enhanced by our ability to consider a joint standard 23
for NO x and SO x to protect against acidification effects. The development of an appropriate form 24
of the standard linked to a common indicator of aquatic acidification, ANC, is also a significant 25 step forward, as it allows for development of a standard for aquatic acidification designed to 26 provide generally the sme degr ee of protection across the count ry, while still reflecting the 27 underlying variability in ecosystem sensitivity to acidifying NO x and SO x deposition. 28
29

20 As we have note earlier in the document, in this draft we have focused on aquatic acidification. However, in the second draft policy assessment we plan to more fully explore the possibility of expanding the conceptual model to address terrestrial acidification.Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 219 Draft –D o Not Quote or Cite 

### 9.1 CONCLUSIONS 1 As noted throughout this document, because of the complex interactions between NO x 2
and SO x in the atmosphere and their impacts once de posited in ecosystems, the consideration of 3 indicators, averaging times, forms, and levels for the two pollutants is bein g conducted jointly. In 4 addition, as discussed in Chapters 5 and 6, we are considering structures for the standards that 5 reflect a more scientifically derived understa nding of the relationshi ps between atmospheric 6
concentrations of NO x and SO x and the primary indicators of ecosystem impacts. 7 With respect to soil and wate r effects information, we have evaluated the conclusions 8 drawn at the end of the last review in light of more recent evidence from studies for a variety of 9 ecological effects endpoints. We place greater weight on U.S. studies due to the species-, site-, 10 and climate-specific nature of ecological responses . With respect to quan titative exposure- and 11 risk-based considerations, we have relied on both monitored and modeled NO x and SO x ambient 12 concentrations and related deposition, as described in Chapter 3 of the REA. 13
Uncertainties associated with the exposure and risk assessments are also discussed, 14 including, where possible, some sense of the dire ction and/or magnitude of the uncertainties that 15
should be taken into account as one considers these estimates. As w ith any analysis that relies on 16 complex scientific models, there are a num ber of unknown and unquan tifiable sources of 17 uncertainty. However, each model that has been applied in the risk and exposure assessment 18 represents the best available scie nce and the models have all been subject to substantial levels of 19 peer-review. 20 The following secondary NAAQS conclusions en compass the breadth of policy-relevant 21 considerations described in this policy assessment: 22 (1) Based on the policy-relevant findings from the ISA described in Chapter 2, and while 23 recognizing that important uncertainties and research questions remain, staff conclude 24 that great progress has been made since th e last reviews of th e secondary standards 25
for NO x and SO x . We generally find support in the available effects-based evidence 26
for consideration of NO x and SO x standards that are at l east as protective as the 27
current standard and do not find support for consideration of NO x and SO x standards 28 that are less protective than the current standard. The staff also concludes that 29 consideration of joint standards for NO x and SO x is appropriate given the common 30 atmospheric processes gove rning the deposition of NO x and SO x to sensitive 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 220 Draft –D o Not Quote or Cite ecosystems, and given the combined effects of N and S deposition on acidification of 1
soil and water. 2 (2) Staff concludes that ambient NO x is a significant component of atmospheric nitrogen 3 deposition, even in areas with relatively high rates of deposition of reduced nitrogen. 4
Staff make this conclusion based on the an alysis in Chapter 3 of the REA, which 5 provides a thorough assessment of the contribution of NO x to nitrogen deposition 6 throughout the U.S., and the relati ve contributions of ambient NO x and reduced forms 7 of nitrogen. 8 (3) Staff concludes based on the case study results provided in the REA, that current 9
levels of NO x and SO x are associated with deposition th at leads to ANC values below 10 benchmark values that cause ecological harm and losses in ecosystem services. Staff 11
concludes that the evidence and risk a ssessment support strongly a relationship 12 between atmospheric deposition of NO x and SO x and ANC, and that ANC is an 13 excellent indicator of aquatic acidification. Staff also concludes that at levels of 14 deposition associated with NO x and SO x concentrations at or below the current 15 standards, ANC levels are expected to be below benchmark values that are associated 16 with significant losses in fish species richness, which is associated with reductions in 17 recreational fishing services. While th ere are many other ecosystem services 18 potentially affected by reduc tions in ANC, including subs istence fishing, natural 19 habitat provision, and biological control, confidence in the specific translation of 20 ANC values to these additional ecosystem services is much lower. 21 (4) Losses in aquatic resources associated with ANC levels below 50 are clearly 22 associated with significant lo sses in economic value. Based on the best available data, 23 just in the northeastern U.S., current acidifi cation levels are resulting in $4 million to 24 $300 million in damages annually from lost recreational fishing. This estimate 25 represents only a fraction of the total economic value of ecosystem damages as many 26 impacted resources are not amenable to economic valuation methods. In addition, 27 economic damages are also likely to occur in other areas affected by acidification, 28 including New England, the Appalachian Mountains (northern Appalachian Plateau 29 and Ridge/Blue Ridge region), and the Upper Midwest. Staff conc ludes that reducing 30 acidifying deposition of NO x and SO x will result in improve ments in public welfare 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 221 Draft –D o Not Quote or Cite by increasing the quantity and quality of ecosystem services, including recreational 1 fishing and other services associ ated with improved water quality. 2 (5) Staff initially concludes based on the case st udy results that current levels of ambient 3
NO x and SO x are associated with deposition that leads to BC:Al values below 4 benchmark values that cause ecological harm and losses in ecosystem services. Staff 5
concludes that the evidence and risk a ssessment support strongly a relationship 6 between atmospheric deposition of NO x and SO x and BC:Al, and that BC:Al is a 7 good indicator of terrestrial ac idification. Staff also conc ludes that at levels of 8 deposition associated with NO x and SO x concentrations at or below the current 9 standards, BC:Al levels are expected to be below benchmark values that are 10 associated with significant losses in tree health and growth, which are associated with 11 reductions in timber production. While th ere are many other ecosystem services, 12 including maple syrup production, natural ha bitat provision, and regulation of water, 13 climate, and erosion, potentially affected by reductions in BC:Al, confidence in the 14 specific translation of BC:Al values to these additional ecosystem services is much 15
lower. 16 (6) On the basis of the acidification and nut rient enrichment effects that have been 17
observed to still occur under current ambient conditions and those predicted to occur 18 under the scenario of just meeting the curr ent secondary NAAQS, staff concludes that 19 the current secondary NAAQS are inadequa te to protect the public welfare from 20 known and anticipated adverse welfare e ffects from aquatic and terrestrial 21
acidification associated with deposition of NO x and SO x .. As discussed above, this 22
conclusion derives from several lines of evidence. 23 (7) Staff has concluded, based on the comp leteness of the available evidence and 24 quantitative risk information, that effects due to aquatic and terrestrial acidification 25 are most suitable for defining secondary standards for NO x and SO x . Staff notes that 26 in developing a standard desi gned to protect against the e ffects of acidification due to 27 deposition of NO x and SO x , the resulting standards may not provide protection 28 against known effects associated with nutri ent enrichment in aquatic and terrestrial 29 ecosystems. 30Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 222 Draft –D o Not Quote or Cite (8) It is appropriate to consid er using indicators other than NO 2 and SO 2 as the indicators 1
for a standard that is inte nded to address the ecological effects associated with 2 deposition of NO x and SO x to sensitive ecosystems. Given the reasons discussed in 3 Chapters 2, 4, and 5 of this polic y assessment, staff concludes that NO x , as defined in 4 the CAA, is best represented by the atmospheric indicator NO y , defined as NO 2 + NO 5
+ HNO 3 + PAN +2N 2 O 5 + HONO+ NO 3 + organic nitrates + particulate NO 3 is the 6 more appropriate indicator of oxides of nitrogen, and that SO x , defined to include 7 sulfur monoxide (SO), sulfur dioxide, sulfur trioxide (SO 3 ), and disulfur monoxide 8 (S2O), and particulate-phase S compounds, is the more appropriate indicator of 9
oxides of sulfur. 10 (9) It is appropriate to use the a nnual average of concentrations of NO y and SO x as the 11 averaging time for the secondary standa rds, based on the chronic nature of 12 acidification, and the protection against epis odic acidification pr ovided by a standard 13 based on annual average concentrations. 14 (10) It is appropriate to c onsider changing the form of the secondary standards for NO x 15
and SO x as the current form does not take into account the linkages between NO x and 16
SO x in the causation of effects associated with acidification of aquatic ecosystems. 17 Based on the causal linkages between NO x and SO x , deposition of N and S, and the 18 indicator of acidification, ANC, staff concludes that th e current forms should be 19 replaced with an atmospheric acidification potential index (AAPI), which reflects the 20 important roles of underlying ecosystem char acteristics, determinants of deposition, 21 and reduced nitrogen deposition in determin ing the potential eff ects from deposition 22
of NO x and SO x . 23 (11) Staff initial conclusions regarding the elem ents of the standard, e.g. the target ANC, 24 spatial extent of areas in which the standard will be evaluated, percentiles of aquatic 25 ecosystems within sensitivity classes to be protected for alternative target ANC 26 values, calculated values of deposition transformation ratios, natural buffering 27 capacity, and reduced nitrogen deposition will be provided in the second draft of the 28 policy assessment. In addition, staff initia l conclusions regardi ng consideration of 29 uncertainty and variability in elements of th e standard will be de veloped in the second 30
draft. 31Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 223 Draft –D o Not Quote or Cite 

### 9.2 SUMMARY OF KEY UNCERT AINTIES AND RESEARCH 1 

### RECOMMENDATIONS RELATED TO SETTING A SECONDARY 2 

### STANDARD FOR NO X 

### AND SO X 3 [This section is still under de velopment. Summary of key uncertainties to be added in 4 second draft policy assessment. Research and data needs are partial lists that will be more 5 completely developed in subsequent versions.] 6

9.2.1 Research Needs to Reduce Uncertaint y in the Next Review (focused on 7 aquatic acidification) 8 Based on the information presented in this policy assessment, several information gaps 9 arise that suggest further research is needed in the following areas: 10

 Developing relationships betw een aquatic acidity as measured by ANC, and effects on 11 ecological effects and ecosystem services, especially due to incremental changes 12

 Developing nationwide weatheri ng rates, or weathering rate s for aquatic ecosystems 13
sensitive to acidification 14

 Developing a better understan ding of the uncertainty in critical loads for acidity 15

 Developing methods for calculati ng critical loads for surface wa ter acidity when data are 16 absent or of poor quality 17

 Evaluating ways to combine multiple critical load estimates for surface waters and soils on 18
a national scale 19

 Estimating ways to determine critical load pa rameters across different media (e.g., surface 20 waters, soils). 21

9.2.2 Data Needs to Reduce Uncertainty in the Next Review (focused on aquatic 22 acidification) 23 Improved measurements of reduced nitrogen: Nitrification processes within watershed 24 soil, sediment and vegetation systems effectivel y convert ammonia gas a nd ammonium ions to 25 nitrates, which contribute to the overall acidif ying loads in ecosystems; consequently, the 26 atmospheric contributions of reduced nitrogen must be accounted for in acidification 27 assessments. We would expect that all or a s ubset of ambient monito ring platforms supporting 28Policy Assessment for the Review of the Secondary National Ambient Air Quality Standards for NO x and SO x

March 2010 224 Draft –D o Not Quote or Cite the N/S secondary standard will measure bot h ammonia gas and ammonium ion along with 1 oxidized sulfur and nitrogen species. 2 Extended modeling of air quality and depositi on to inform monitoring network design: In 3 addition to providing deposition i nputs for watershed models and critical loads analysis, the 4 spatial and temporal flexibility afforded by ai r quality modeling can support monitoring network 5 design and in inform the averaging time period (one or more years) to more appropriately 6 account for inter-annual variability in NO x and SO x concentrations. 7 Development of data fusion approaches to combine model results with observational 8 data: Consideration also will be given to fusing model results with observation fields to improve 9 spatial resolution by taking advantage of the landscape, emissions and meteorological 10 information that affect spatial gradients while relying on observations to reduce the influence of 11
model uncertainties. 121

2 

# APPENDIX A 3 

# CHAPTER 5: CONCEPTUAL DESIGN OF THE 4 

# STANDARD 5

6

7 

# First External Review Draft 8

9 10 11 Prepared by: 12 13 U.S. Environmental Protection Agency 14 Office of Air Quality Planning and Standards 15 Research Triangle Park, NC 27711 16 17 18 191Appendix A

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### TABLE OF CONTENTS 1
Appendix A Chapter 5: Conceptu al Design of the Standard ........................................................ 1 2 A.1 Technical summary of methods used in th e REA Aquatic Acidification analysis .......... 1 3 A.2 Technical summary of critical loads modeling in the REA ............................................. 2 4 1.2.1 Preindustrial Base Cation Concentration ............................................................. 5 5 1.2.2 F-factor ................................................................................................................. 6 6 7 8


### LIST OF TABLES 9 Table A.1. Brief summary of objects and methods used in the REA Aquatic Acidification 10 analysis. ................................................................................................................ 1 11 Table A.2 Illustrates SSWC Approach – Environmental Variables ............................................... 7 12 Table A.3 FAB Approach – Environmental Variables ................................................................... 8 13 14 15Appendix A

March 2010 ii Draft – Do Not Quote or Cite This page intentionally left blank. 1 2Appendix A

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## APPENDIX A 1 

## CHAPTER 5: CONCEPTUAL DESIGN OF THE STANDARD 2
This is supplemental information to support th e discussion of the conceptual design of the 3 standard that is presented in Chapter 5 of the Policy Assessment Document. The aquatic 4 acidification analyses develope d in the REA used a number of different models and calculation 5 techniques that are important fo r the development of the standar d. The goal of this Appendix is 6 to summarize information from the REA analysis th at is most relevant to the Policy Assessment. 7 A brief summary of the REA analyses are presente d in section 1. In section 2 there is a general 8 summary and technical discussion of the critical lo ads modeling approaches that were used in the 9 REA, followed by a brief description of MAGIC model data requirements. 10



### A.1 TECHNICAL SUMMARY OF METHODS USED IN THE REA 11 

### AQUATIC ACIDIFICATION ANALYSIS 12 The aquatic acidification analysis is presen ted in Chapter 4 and Appendix 4 of the REA. 13 The analysis uses multiple techniques to show the relationship between ANC and NO x and SO x 14 deposition, as well as determine th e current level of risk to wate r bodies that occur in sensitive 15 areas. A brief summary of the techniques and objectiv es of the REA analysis is given in Table 1. 16

Table A.1. Brief summary of objects and methods us ed in the REA Aquatic Acidification 17 analysis. 18 Technique Objectives Time-series graphs of current conditions 1 Data from monitoring networks collected from 1990 to 2006 were plotted to show trends in concentr ations of pollutants, deposition and acidification for each case study site. The data included surface water concentration of nitrate, sulfate and ANC; deposition of sulfate and nitrate; as well as air concentration of SO x , NO x and NH 4 MAGIC 1 Used to estimate the relationship between ANC values and anthropogenic NO x and SO x emission from the past (preacidification ~1860), present (2002 and 2006) and projected into the future (2020 and 2050). Analysis included 44 lakes from Adirondacks and 60 streams from Shenandoah. 2 Used to develop input paramete rs for critical loads modeling (i.e. weathering rates) 3 Used for uncertainty analysisAppendix A

March 2010 2 Draft – Do Not Quote or Cite Technique Objectives Critical Loads modeling 1 SSWC and FAB models used to calculate critical loads for critical limits of ANC = 0, 20, 50, 100 2 Critical loads for ANC critical limits calculated for 169 lakes in the Adirondacks and 60 streams in the Shenandoah using water quality data from monitoring sites collected in 2006 3 Critical loads exceedences calculate d by comparing the critical loads that were calculated by SSWC with deposition data from NADP for wet deposition and CMAQ for dry deposition, both for the year 2002 Regional Extrapolation 1 117 of the critical loads calcu lated for the Adirondacks were extrapolated to lakes defined by the New England EMAP probability survey, representing 1842 lakes, to in fer the # of lakes that exceeded their critical load 2 69 of the critical loads calculated for the Shenandoah were extrapolated to 330 streams based on bed rock geology classification. 1


### A.2 TECHNICAL SUMMARY OF CRI TICAL LOADS MODELING IN 2 

### THE REA 3 The critical load of acidity for lakes or streams was derived from present-day water 4 chemistry using a combination of steady-state models. Both the Steady-State Water Chemistry 5 (SSWC) model and First-order Acidity Balance model (FAB) is based on the principle that 6 excess base-cation production within a catchment area should be equal to or greater than the acid 7 anion input, thereby maintaini ng the ANC above a preselected le vel (Reynolds and Norris, 2001; 8 Posch et al. 1997). These models assume stea dy-state conditions and assume that all SO 4 2– in 9 runoff originates from sea salt spray and an thropogenic deposition. Given a critical ANC 10 protection level, the critical lo ad of acidity is simply the input flux of acid anions from 11 atmospheric deposition (i.e., natural and anthro pogenic) subtracted fr om the natural (i.e., 12 preindustrial) inputs of base ca tions in the surface water. Final Risk and Exposure Assessment 13 September 2009 Appendix 4, Attachment A – 15 Aquatic Acidification Case Study Atmospheric 14 deposition of NO x and SO x contributes to acidific ation in aquatic ecosystems through the input of 15 acid anions, such as NO3- and SO 4 2– The acid balance of headwa ter lakes and streams is 16 controlled by the level of this acidifying deposition of NO3- and SO 4 2– and a series of 17 biogeochemical processes that produce and consum e acidity in watersheds. The biotic integrity 18 of freshwater ecosystems is then a function of the acid-base balance, a nd the resulting acidity- 19Appendix A

March 2010 3 Draft – Do Not Quote or Cite related stress on the biota that occupy the wate r. The calculated ANC of the surface waters is a 1
measure of the acid-base balance: 2
ANC = [BC]* - [AN]* (1) 3
where [BC]* and [AN]* are the sum of ba se cations and acid anions (NO3- and SO 4 2– ), 4 respectively. Equation (1) forms the basis of the linkage between deposition and surface water 5 acidic condition and the modeling approach used. Given some “target” ANC concentration 6 [ANClimit]) that protects biologi cal integrity, the amount of depos ition of acid anions (AN) or 7 depositional load of acidity CL(A) is simply the input flux of acid anions from atmospheric 8 deposition that result in a su rface water ANC concentration e qual to the [ANClimit] when 9 balanced by the sustainable flux of base cations input and the sinks of nitrogen and sulfur in the 10
lake and watershed catchment. 11 Critical loads for nitrogen and su lfur (CL(N) + CL(S) ) or cr itical load of acidity CL(A) 12 were calculated for each waterbody from the prin ciple that the acid load should not exceed the 13 nonmarine, nonanthropogenic base cation input and sources and si nks in the catchment minus a 14 neutralizing to protect selected biota from being damaged: 15
CL(N) + CL(S) or CL(A) = BC*dep + BCw – Bcu – AN - ANClimit (2) 16
Where, 17 BC*dep = (BC*=Ca*+Mg*+K*+Na*), nonanthropogenic deposition flux of base cations BCw = 18 the average weathering fl ux, producing base cations 19 Bcu (Bc=Ca*+Mg*+K*) = the net long-term averag e uptake flux of base cations in the biomass 20 (i.e., the annual average removal of base cations due to harvesting) 21 AN = the net long-term average uptake, denitrif ication, and immobilization of nitrogen anions 22 (e.g. NO 3 -) and uptake of SO 4 2– 23 ANClimit = the lowest ANC-flux that protects the biological communities. 24 Since the average flux of base cations weathe red in a catchment and reaching the lake or 25 streams is difficult to measure or compute from available information, the average flux of base 26 cations and the resulting critical load estimation were derived from water quality data (Henriksen 27 and Posch, 2001; Henriksen et al ., 1992; Sverdrup et al., 1990). Weighted annual mean water 28 chemistry values were used to estimate average base cation fluxes, which were calculated from 29 water chemistry data collected from the Tem porally Integrated Monitoring of Ecosystems 30Appendix A

March 2010 4 Draft – Do Not Quote or Cite (TIME)/Long-Term Monitoring (LTM) monitoring networks, that include Adirondack Longterm 1 Monitoring (ALTM), Virginia Trout Stream Sensitivity Study (VTSSS), and the Shenandoah 2 Watershed Study (SWAS), and Environmental M onitoring and Assessment Program (EMAP) 3 (see Section 4.1.2.1 of Chapter 4). 4 The preacidification nonmarine flux of base cations for each lake or stream, BC*0, is 5
BC*0 = BC*dep + BCw - Bcu (3) 6
Thus, critical load for acidity can be rewritten as 7
CL(N) + CL(S) = BC*0 – AN - ANClimit = Q.([BC*]0 – [AN] - [ANC]limit), (4) 8
where the second identity expresse s the critical load for acidity in terms of catchment runoff (Q) 9 m/yr and concentration ([x] = X/Q). The sink of n itrogen in the watershed is equal to the uptake 10 (Nupt), immobilization (Nimm), and denitrificati on (Nden) of nitrogen in the catchment. Thus, 11 critical load for acidity can be rewritten as 12
CL(N) + CL(S) = {fNupt + (1

− r)(Nimm + Nden)} + ( [BC]0*

− [ANClimit])Q (5) 13
where f and r are dimensionless parameters that define the fraction of forest cover in the 14
catchment and the lake/catchment ratio. The in-lak e retention of nitrogen and sulfur was assumed 15 to be negligible. Equation 5 described the FAB model that was applied wh en sufficient data was 16 available to estimate the uptake, immobilizat ion, and denitrification of nitrogen and the 17
neutralization of acid an ions (e.g. NO3-) in the catchment. In the case were data was not 18 available, the contribution of n itrogen anions to acidification wa s assumed to be equal to the 19 nitrogen leaching rate (Nleach) into the surface water. The flux of acid anions in the surface 20 water is assumed to represent the amount of nitrogen that is not retained by the catchment, which 21
is determined from the sum of measured concentration of NO3- and ammonia in the stream 22 chemistry. This case describes the SSWC m odel and the critical load for acidity is 23
CL(A) = Q.([BC*]0 – [ANC]limit) (6) 24

where the contribution of acid anions is consider ed as part of the exceedances calculation (see 25 Section 1.2.5, below). For the assessment of cu rrent condition in both case study areas, the 26
critical load calculation described in Equation 6 was used for most lakes and streams. The lack of 27 sufficient data for quantifying nitrogen denitrif ication and immobilization prohibited the wide 28 use of the FAB model. In addition, given the unce rtainty in quantifying n itrogen denitrification 29Appendix A

March 2010 5 Draft – Do Not Quote or Cite and immobilization, the flux of nitrogen anions in the surface water was assumed to more 1 accurately reflect the contribution of NO3- to aci dification. Several major assumptions are made: 2 (1) steady-state conditions exist, (2) the effect of nutrient cycling between plants and soil is 3 negligible, (3) there are no signi ficant nitrogen inputs from s ources other than atmospheric 4 deposition, (4) ammonium leaching is negligible because any inputs are either taken up by biota 5 or adsorbed onto soils or nitrate compounds, and (5 ) longterm sinks of sulfate in the catchment 6 soils are negligible. 7

1.2.1 Preindustrial Base Cation Concentration 8 Present-day surface water concentrations of base cations are elevated above their 9 steadystate preindustrial concentrations because of base cation leaching through ion exchange in 10
the soil due to anthr opogenic inputs of SO 4 2– to the watershed. For this reason, present-day 11 surface water base cation concentrations are higher than natural or preindustrial levels, which, if 12 not corrected for, would result in critical load values not in steady-st ate condition. To estimate 13 the preacidification flux of base cations, the present flux of base cations was estimated, 14
BC*t, given by BC*t = BC*dep + BCw – Bcu +BCexc, (7) 15

Where BCexc = the release of base cations du e to ion-exchange processes. Assuming that 16 deposition, weathering rate, and net uptake have not changed ove r time, BCexc can be obtained 17 by subtracting Equation 5 from Equation 7: 18
BCexc = BC*t – BC*0 (8) 19
This present-day excess production of base cations in the catchment was related to the long-term 20 changes in inputs of nonmarine acid anions ( Δ SO*2 + Δ NO3) by the F-factor (see below): 21
BCexc = F ( Δ SO*2 + Δ NO3) (9) 22
For the preacidification base cation flux, solv ing Equation 5 for BC*0 and then substituting 23 Equation 8 for BCexc and explicitly describing the long-term changes in nonmarine acid ion 24 inputs: 25
BC*0 = BC*t – F (SO*4,t - SO*4,0 + NO*3,t - NO*3,0) (10) 26
The preacidification NO3- concentra tion, NO*3,0, was assumed to be zero. 27Appendix A

March 2010 6 Draft – Do Not Quote or Cite 1.2.2 F-factor 1
An F-factor was used to correct the concentrations and estimate preindustrial base concentrations 2 for lakes in the Adirondack Case Study Area. In the case of streams in the 3 Shenandoah Case Study Area, the preindustrial ba se concentrations were derived from the 4 MAGIC model as the base cation supply in 1860 (h indcast) because the F-factor approach is 5 untested in this region. An F-factor is a ra tio of the change in nonmarine base cation 6 concentration due to changes in strong acid anion concentrations (Henriksen, 1984; Brakke et al., 7 1990): 8
F =([BC*]t - [BC*]0)/([SO4*]t - [S O4*]0 + [NO3*]t - [NO3*]0), (12) 9
where the subscripts t an d 0 refer to present and preacidific ation conditions, re spectively. If F=1, 10 all incoming protons are neutralized in the catchment (only soil acidification); at F=0, none of 11 the incoming protons are neutralized in the catc hment (only water acidification). The F-factor 12 was estimated empirically to be in the range 0.2 to 0.4, based on the analysis of historical data 13 from Norway, Sweden, the United States, and Ca nada (Henriksen, 1984). Brakke et al. (1990) 14 later suggested that the F-factor should be a function of the base cation concentration: 15
F = sin ( π /2 Q[BC*]t/[S]) (13) 16

where 17 Q = the annual runoff (m/yr). [S] = the base cation concentration at which F=1; and for 18 [BC*]t>[S] F is set to 1. For Norway [S] has been set to 400 milliequivalents per cubic meter 19 (meq/m3)(circa.8 mg Ca/L) (Brakk e et al., 1990). The preacidification SO42- concentration in 20 lakes, [SO4*]0, is assumed to consist of a c onstant atmospheric cont ribution and a geologic 21 contribution proportional to the concentration of base cations (Bra kke et al., 1989). The 22 preacidification SO42- concentration in lakes, [SO4*]0 was estimated from the relationship 23 between [SO42-]o* and [BC]t* based on work co mpleted by Henriksen et al., 2002 as described 24 by the following equation: 25
[SO42-]o* = 15 + 0.16 * [BC]t* (14) 26Appendix A

March 2010 7 Draft – Do Not Quote or Cite Table A.2 Illustrates SSWC Approach – Environmental Variables 1 CL(A) = BC * dep + BC w – Bc u – ANC limit 2 CL(A) = Q
. ([BC * ] 0 – [ANC] limit ) 3 Variable Code Description Source

1 BC * dep Sum (Ca*+Mg*+K*+Na*), nonanthropogenic deposition flux of base cations Wet NADP and Dry CASTNET 2 BC w Average weathering flux of base cations Calculated (5-17) 3 Bc u Sum (Ca+Mg+K), the net long-term average uptake flux of base cations in the biomass USFS-FIA data

4 ANC limit Lowest ANC-flux that protects the biological communities Set

5 Ca * Sea Salt corrected Surface water concentration ( μ eq/L) growing season average. (Ca – (CL × 0.0213)) Water quality data

6 Mg * Sea Salt corrected Surface water concentration ( μ eq/L) growing season average. (Mg – (CL × 0.0669)) Water quality data

7 Na * Sea Salt corrected Surface water concentration ( μ eq/L) growing season average. (Na – (CL × 0.557)) Water quality data

8 K * Sea Salt corrected Surface water concentration ( μ eq/L) growing season average. (K – (CL × 0.0.0206)) Water quality data

9 SO 4 * Sea Salt corrected Surface water concentration ( μ eq/L) growing season average. (SO 4 – (CL × 0.14)) Water quality data

10 CL Surface water concentration ( μ eq/L) growing season average. Water quality data

11 SO 4 * Surface water concentration ( μ eq/L) growing season average. Water quality data

12 NO 3 * Surface water concentration ( μ eq/L) growing season average. Water quality data

13 Q The annual runoff (m/yr) USGS

14 [BC * ] 0 Preindustrial flux of base cations in surface water, corrected for sea salts Calculated from water quality data 15 [SO 4 * ] 0 Preindustrial flux of sulfate in surface water, corrected for sea salts Estimated

16 [NO 3 * ] 0 Preindustrial flux of nitrate, corrected for sea salts Equal to 0 17 F Calculated factor Fix values 4 5Appendix A

March 2010 8 Draft – Do Not Quote or Cite Table A.3 FAB Approach – Environmental Variables 1 DL(N) + DL(S) = {fN upt + (1

− r)(N imm + N den ) + (N ret + S ret )} + ( [BC] 0 *

− [ANC limit ])Q 2 Variable Code Description Source

1 Ndepo Total N deposition NADP/CMAQ 2 ANClimit Lowest ANC-flux that protects the biological communities Set

3 [BC*] 0 Preindustrial flux of base cations in surface water, corrected for sea salt Calculated from water quality data 4 Ca * Sea Salt corrected Surface water concentration ( μ eq/L) growing season average. (Ca – (CL × 0.0213)) Water quality data

5 Mg * Sea Salt corrected Surface water concentration ( μ eq/L) growing season average. (Mg – (CL × 0.0669)) Water quality data

6 Na * Sea Salt corrected Surface water concentration ( μ eq/L) growing season average. (Na – (CL × 0.557)) Water quality data

7 K * Sea Salt corrected Surface water concentration ( μ eq/L) growing season average. (K – (CL × 0.0.0206)) Water quality data

8 SO 4 * Sea Salt corrected Surface water concentration ( μ eq/L) growing season average. (SO 4 – (CL × 0.14)) Water quality data

9 CL Surface water concentration ( μ eq/L) growing season average. Water quality data

10 SO 4 * Surface water concentration ( μ eq/L) growing season average. Water quality data

11 NO 3 * Surface water concentration ( μ eq/L) growing season average. Water quality data

12 Q The annual runoff (m/yr) USGS 13 f f is a dimensionless parameter that define the fraction of forest cover in the catchment 14 r r is a dimensionless parameter that define the lake/catchment ratio 14 N ret The in-lake retention of nitrogen Estimated 15 S ret The in-lake retention of sulfur Estimated 16 N upt The net long-term average uptake flux of N in the biomass USFS-FIA data

17 N imm Immobilization of N in the soils Estimated fix value 18 N den Denitrification Estimated fix value 19 Lake Size Lake size (ha) DLMs 20 WSH Watershed area (ha) Calculated 3Appendix A

March 2010 9 Draft – Do Not Quote or Cite Data requirements for MAGIC 1 The MAGIC model (Cosby et al., 1985a; 1985b ; 1985c) is a mathematical model (a 2 lumped-parameter model) of soil and surface wa ter acidification in response to atmospheric 3 deposition based on process-level information a bout acidification. A process model, such as 4 MAGIC, characterizes acidification into (1)a sect ion in which the concentrations of major ions 5 are assumed to be governed by si multaneous reactions involving SO 4 2- adsorption, cation 6 exchange, dissolution-precipitation- speciation of aluminum, and disso lution-speciation of 7 inorganic carbon; and (2) a mass balance section in which the flux of major ions to and from the 8 soil is assumed to be controlled by atmospheri c inputs, chemical weathering, net uptake and loss 9
in biomass and losses to runoff. At the heart of MAGIC is the size of the pool of exchangeable 10
base cations in the soil. As the fluxes to and fr om this pool change over time owing to changes in 11 atmospheric deposition, the chemical equilibria between soil and soil so lution shift to give 12 changes in surface water chemistry. The degree and ra te of change of surface water acidity thus 13 depend both on flux factors and the inherent characteristics of the affected soils. 14 There are numerous input data required to run MAGIC making it rath er data intensive. 15 Atmospheric deposition fluxes for the base cations and strong acid anions are required as inputs 16 to the model. These inputs are generally assumed to be uniform over the catchment. The volume 17 discharge for the catchment must also be provided to the model. In general, the model is 18 implemented using average hydrologic conditio ns and meteorological conditions in annual 19 simulations, i.e., mean annual deposition, precipita tion and lake discharge are used to drive the 20 model. Values for soil and surface water temper ature, partial pressure of carbon dioxide and 21 organic acid concentrations must also be provided at the appr opriate temporal resolution. 22 The aggregated nature of the model requires th at it be calibrated to observed data from a 23 system before it can be used to examine poten tial system response. Ca librations are based on 24 volume weighted mean annual or seasonal fluxes for a given period of observation. The length of 25 the period of observation used for calibration is not arbitrary. Model output will be more reliable 26
if the annual flux estimates used in calibration ar e based on a number of years rather than just 27 one year. There is a lot of y ear-to-year variability in atmospheric deposition and catchment 28 runoff. Averaging over a number of years reduces th e likelihood that an “out lier” year (very dry, 29 etc.) is used to specify the primary data on wh ich model forecasts are based. On the other hand, 30Appendix A

March 2010 10 Draft – Do Not Quote or Cite averaging over too long a period may remove impor tant trends in the data that need to be 1 simulated by the model. 2 The calibration procedure require s that stream water qualit y, soil chemical and physical 3 characteristics, and atmospheric deposition data be available for each catchment. The water 4 quality data needed for calibrati on are the concentrations of the individual ba se cations (Ca, Mg, 5 Na, and K) and acid anions (Cl, SO 4 2- , and NO 3 - ) and the pH. The soil data used in the model 6 include soil depth and bulk density, soil pH, so il cation-exchange capacity, and exchangeable 7 bases in the soil (Ca, Mg, Na, and K). The atmo spheric deposition inputs to the model must be 8 estimates of total deposition, not just wet depositi on. In some instances, direct measurements of 9 either atmospheric deposition or so il properties may not be availabl e for a given site with stream 10 water data. In these cases, the required data can often be estimated by: (a) assigning soil 11 properties based on some landscape classification of the catchmen t; and (b) assigning deposition 12 using model extrapolations from some nationa l or regional atmospheric deposition monitoring 13
network. Soil data for model calibration are usuall y derived as aerially av eraged values of soil 14 parameters within a catchment. If soils data for a given location are vertic ally stratified, the soils 15
data for the individual soil horizons at that sampling site can be aggregated based on horizon, 16 depth, and bulk density to obtain si ngle vertically aggregated values for the site, or the stratified 17 data can be used directly in the model. 18
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# Methodologies for National Terrestrial and Aquatic Acidification Maximum Depositional Load Approaches: Determining Weathering Rates

First External Review Draft

Prepared for:
U.S. Environmental Protection Agency Office of Air Quality Planning and Standards Research Triangle Park, NC 27711

Prepared by:

RTI International P.O. Box 12194 Research Triangle Park, NC 27709

EPA Contract Number EP-D-06-003 RTI Project Number 0209897.004.080

January 11, 20091Appendix B

March 2010 i Draft – Do Not Quote or Cite Table of Contents 1 2
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32 1. PURPOSE ....................................................................................................................... ....................... 1
2. OVERVIEW OF ACIDIFICATION ..................................................................................................... . 1
2.1 EPA’s Integrated Science Assessment and Risk and Exposure Assessment ............................ 1
2.2 Aquatic Acidification and Critical Acid Loads ......................................................................... 4

2.1.2 Terrestrial Acidification and Critical Acid Loads ................................................................. 9
3. AQUATIC BASE CATION WEATHERING METHODOLOGY ..................................................... 14
3.1 Aquatic Base Cation Weathering ............................................................................................ 14
3.2 Methodologies for Determining Base Cation Weathering Values in the United States .......... 16

3.2.1 Difficulties in estimating base cation weathering ............................................................... 16
3.2.2 Approaches to estimating BC w for Aquatic Acidification .................................................. 17
3.3 Proposed Methodology for Estimating and Ma pping Base Cation Weathering for Aquatic Critical Acid Load Calculations .............................................................................................. 27
3.3.1 Potential limitations of proposed methodology .................................................................. 33
3.3.2 Uncertainty analyses .......................................................................................................... . 34
4. TERRESTRIAL BASE CATION WEATHERING METHODOLOGY ............................................. 35
4.1 Introduction .................................................................................................................. ........... 35
4.2 Terrestrial Base Cation Weathering ........................................................................................ 36
4.3 Methodologies for Determining Base Cation Weathering Values in the United States .......... 39

4.3.1 Difficulties in estimating base cation weathering ............................................................... 39
4.3.2 Approaches to estimating BCw: ......................................................................................... 40
4.3.3 Proposed methodology for estimating and mapping base cation weathering for terrestrial critical acid load calculations ............................................................................. 50
4.3.5 Potential limitations of proposed methodology .................................................................. 78
4.3.6 “Field Tests” of model and uncertainty analyses ................................................................ 79
5. CONCLUSIONS AND RECOMMENDATIONS ............................................................................... 81
6. REFERENCES .................................................................................................................... ................. 82 APPENDIX 1 Potentially Applicable Na tional-Scale Geochemical Data .................................................. 97
APPENDIX 2 References for Table 3-2: Applications of the MAGIC Model ......................................... 102Appendix B

March 2010 ii Draft – Do Not Quote or Cite List of Figures 1

2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 2-1. (a) Number of fish species per lake or stre am versus acidity, expressed as acid neutralizing capacity for Adirondack Case Study Area lakes (S ullivan et al., 2006). (b) Number of fish species among 13 streams in Shenandoah Na tional Park. Values of acid neutralizing capacity are means based on quarterly meas urements from 1987 to 1994. The regression analysis shows a highly significant relationship (p < .0001) between mean stream acid neutralizing capacity and the number of fish species. ..................................................................... 5 2-2. The relationship between the Bc/Al ratio in so il solution and the percentage of tree species (found growing in North America – native a nd introduced species) exhibiting a 20% reduction in growth relative to controls (after Sverdrup and Warfvinge, 1993). ........................... 10 3-1. Process steps for estimating BC w using the MAGIC model with regional extrapolation .................... 28 4-1 . Areas of continental U.S. that were covered during the last glacial event (Reed and Bush, 2005). ........................................................................................................................ ..................... 39 4-2. Process Steps for Estimating BC w Using the PROFILE Regional Model ........................................... 52 4-3. Map Showing the Distribution a nd Status of SSURGO Data ............................................................. 64 4-4. Soil Sampling Locations Included in the USGS Shackle tte Dataset ................................................... 66 4-5 . Sample Density of USGS Nati onal Geochemical Survey ................................................................... 68 4-6. NRCS Soil Pedon Sample Pit Locations (30,000 total) ....................................................................... 70 4-7. NRCS Soil Pedon Pit Sample Locations with Geochemical and Mineralogy Data ............................ 71

List of Tables 2-1. Aquatic Status Categories .................................................................................................... .................. 6 2-2. Summary of Linkages between Acidifying Deposition, Biogeochemical Processes That Affect Ca 2+ , Physiological Processes That Are Influenced by Ca 2+ , and Effect on Forest Function ...................................................................................................................... ................... 11 2-3. The Three Indicator (Bc/Al) crit Soil Solution Ratios and Corresponding Levels of Protection to Tree Health and Critical Loads ............................................................................................. ..... 14 3-1. Review of Modeling Approaches (and mode ls) to Estimate Base Cation Weathering for Aquatic Critical Acid Load Determinations .................................................................................. 23 3-2. Locations of Previous MAGIC Applications within the U.S. and Canada 1 ........................................ 29 3-3 . Input Data Requirements of MAGIC Model ...................................................................................... . 31 4-1 . Review of modeling approaches (and models ) to estimate base cation weathering for terrestrial critical acid load determinations. ................................................................................ ... 46 4-2. The fourteen dominant minerals modeled within PROFILE. .............................................................. 50 4-3a. Data required to estimate BC w with the regional PROFILE model (version 5.0). The data in this table must be input by the user and ar e currently available as a continuous coverage layers for at least a portion of the conterminous United States. ..................................................... 53 4-3b. Data required to estimate BC w with the regional PROFILE model (version 5.0). The data in this table must be input by the user and are not currently available as a continuous coverage layers for at least a portion of the conterminous United States (will require development of nationa l coverage layer). ...................................................................................... 53Appendix B

March 2010 iii Draft – Do Not Quote or Cite 4-3c. Data required to estimate BC w with the regional PROFILE model (version 5.0). The data in this table are used to support calculations w ithin the model and should be reviewed by the

user. ......................................................................................................................... ....................... 54 1 2 3 4 5 6 7 8 9 10 11 12 4-4. Available datasets and databases for the conterminous United States that could be used to estimate BC w with the regional application of the PROFILE model (version 5.0). ....................... 55 4-5 . Nitrogen and base cation uptake by forest type (from McNulty et al., 2007). ................................... 58 4-6 Datasets with Geochemical and Mine ralogy Data fo r US Soils ........................................................... 61 4-7 . Long-Term Ecological Research (LTER) sites th at could potentially be suitable as “field test” sites to validate BC w estimates generated with the regional application of the PROFILE model (version 5.0). .................................................................................................. .... 74Appendix B

March 2010 iv Draft – Do Not Quote or Cite 1 2Appendix B

March 2010 1 Draft – Do Not Quote or Cite 1. PURPOSE 1

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29 The purpose of this Work Assignment Task is to develop methodologies for estimating national terrestrial and aquatic acidification ma ximum depositional loads. Separate approaches are developed for terrestrial a nd aquatic acidification because biogeochemical processes in aquatic and terrestrial ecosystems for nitrogen an d sulfur are not identical. Information about the key physical, chemical, and biological parameters needed to predict acidification po tential in ecosystems is not always available. For example, weathering rates are key to acidification but are not available in all parts of th e U.S. Knowledge of an ecosyst em’s weathering characteristics
enables a more accurate assessment of whethe r acidifying deposition can be neutralized or exceeds an ecosystem’s critical load beyond which negative effects in aquatic and terrestrial health may occur. This report presents an introduction to aqua tic and terrestrial aci dification, followed by reviews of different approaches to estimating base cation weathering and detailed methodologies
that could be used to estimate base cation weat hering for aquatic and terrestrial critical load
calculations.

2. OVERVIEW OF ACIDIFICATION
2.1 EPA’s Integrated Science Assessment and Risk and Exposure Assessment Deposition of SO x , NO x , and NH x can lead to ecosystem exposure to acidification. The Integrated Science Assessment (ISA) for Oxid es of Nitrogen and Sulfur–Ecological Criteria (Final Report) (ISA) (U.S. EPA, 2008) reports that acidifying depositi on has altered major biogeochemical processes in the United States by increasing the sulfur an d nitrogen content of soils, accelerating sulfate (SO 4 2

− ) and nitrate (NO 3 − ) leaching from soil to drainage water, depleting soil exchangeable base cations (especially calcium [Ca 2+ ] and magnesium [Mg 2+ ]) from soils, and increasing the mobility of alum inum (Al) within the soil (U.S. EPA, 2008, Section 3.2.1)
The extent of soil acidification is a critical fact or that regulates virt ually all acidificationrelated ecosystem effects from sulfur and nitr ogen deposition. Soil acidification occurs in response to both natural factors and acidif ying deposition (U.S. EPA, 2008, Section 3.2.1). Under conditions of low atmospheric deposition of nitrogen and sulfur, the naturally producedAppendix B

March 2010 2 Draft – Do Not Quote or Cite bicarbonate anion is often the dominant mobile anion, with SO 4 2- and NO 3 - playing a limited role with respect to cation leaching. Increased atmo spheric deposition of sulfur and nitrogen can
result in marked increases in SO 4 2- and NO 3 - soil fluxes resulting in the concomitant leaching of base cations (Ca 2+ , Mg 2+ ) and toxic cations (Al n+ and H + ). 1

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30 Acidification can impact the health of terre strial and aquatic ecosystems. One of the
effects of soil acidification is the increased mob ility of dissolved inorganic Al, which is toxic to tree roots, fish, algae, and aquatic invertebrates (U.S. EPA, 2008, Sections 3.2.1.5, 3.2.2.1, and 3.2.3). The changes in major biogeochemical proce sses and soil conditions caused by acidifying deposition have significant ramifications for th e water chemistry and biological functioning of associated surface waters. Surface water chemistry indicates the negative e ffects of acidification on the biotic integrity of freshwater ecosystems . Surface water chemistry integrates the sum of terrestrial and aquatic processe s that occur upstream within a watershed. Important terrestrial processes include nitrogen satura tion, forest decline, and soil acidification (Stoddard et al., 2003). Thus, water chemistry integrates and reflects changes in soil and vegetative properties and biogeochemical processes (U.S. EPA, 2008, Section 3.2.3.1). Ecological effects occur at four levels of biological organi zation: (1) the individual; (2) the population, which is composed of a single species of individuals ; (3) the biological community, which is composed of many species; and (4) the ecosystem. Low ANC concentrations are linked with negative effects on aquatic systems at all four of these biological levels. For the individual level, impacts are assessed in terms of fitness (i.e., growth, development, and reproduction) or sublethal effects on condition. Surface water with low ANC concentrations can directly influence aquatic organism fitness or mortality by disrupting ion regulation and can mobilize dissolved inorganic al uminum, which is highly toxic to fish under acidic conditions (i.e., pH <6 and ANC <50 μ eq/L). For example, research showed that as the pH of surface waters decreased to <6, many aqua tic species, including fish, invertebrates, zooplankton, and diatoms, tended to decline sharply causing species richness to decline (Schindler, 1988). Van Sickle and colleague s (1996) also found that blacknose dace ( Rhinichthy spp.) were highly sensitive to low pH and could not tolerate inorganic Al concentrations greater than about 3.7 micromolar ( μ M) for extended periods of time. Fo r example, they found that afterAppendix B

March 2010 3 Draft – Do Not Quote or Cite 6 days of exposure to high inorganic Al, blackno se dace mortality increased rapidly to nearly
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30 At the community level, species richness and community structure can be used to
evaluate the effects of acidifica tion. Species composition refers to the mix of species that are represented in a particular ecosystem, whereas sp ecies richness refers to the total number of species in a stream or lake. Acidification a lters species composition and richness in aquatic ecosystems. There are a number of species comm on to many oligotrophic waterbodies that are
sensitive to acidification and ca nnot survive, compete, or reprodu ce in acidic waters. In response to small to moderate changes in acidity, acid-s ensitive species are often replaced by other more acid-tolerant species, resulting in changes in community composition and richness, but with little or no change in total community biomass. The e ffects of acidification are continuous, with more species being affected at higher degrees of acidi fication. At a point, typically a pH <4.5 and an
ANC <0 μ eq/L, complete to near-complete loss of many classes of organisms occur, including fish and aquatic insect populat ions, whereas others are reduce d to only a few acidophilic forms. These changes in species integrity are becau se energy cost in maintaining physiological homeostasis, growth, and reproduction is high at low ANC levels (Schreck, 1981, 1982; Wedemeyer et al., 1990).
In EPA’s Risk and Exposure Assessment for Revi ew of the Secondary National Ambient Air Quality Standards for Oxid es of Nitrogen and Sulfur (U.S. EPA, 2009), the negative impacts of acidifying deposition were assessed by conducting case studies of 1) a quatic acidification in
Adirondack Mountains lakes and Sh enandoah Mountains streams, and 2) terrestrial acidification in red spruce and sugar maple forests in th e White Mountains of New Hampshire and in Pennsylvania, respectively. The results of these case studies revealed the significance of base cation weathering in predicting a quatic and terrestrial acidificati on impacts. The results further highlighted the need to select weathering met hodologies that can be a pplied across geologically diverse ecosystems in the United States. This re port uses the information from the Risk and Exposure Assessment as a starting point to iden tify and evaluate approaches to predicting weathering at other locations a nd larger scales in the United States. In this report, RTI recommends methodologies (including computer models) for application in the United States, assesses the availability of input data for those methodologies, id entifies potential remedies toAppendix B

March 2010 4 Draft – Do Not Quote or Cite limited data availability, and describes uncertainties with the methodologies in predicting acidification impacts. 1

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30 2.2 Aquatic Acidification a nd Critical Acid Loads Surface water chemistry is a primary indicator of acidification and the resulting negative
effects on the biotic inte grity of freshwater ecosystems. Chem ical parameters can be used to assess effects of acidifying depos ition on lake or stream acid-ba se chemistry. These receptors include surface water pH a nd concentrations of SO 4 2- , NO 3 - , Al, and Ca 2+ ; the sum of base cations; and the recently developed base cation su rplus. Another widely used water chemistry indicator for both atmospheric deposition sensitiv ity and effects is acid neutralizing capacity (ANC). The utility of the ANC criterion lies in the association between ANC and the surface water constituents that directly contribute to or ameliorate acidity-related stress, in particular pH,
Ca 2+ , and Al. ANC is also used because it integr ates overall acid status and because surface water acidification models do a better job proj ecting ANC than they do for projecting pH and dissolved inorganic Al concentrations. For the purpose of this study, ANC of surface waters is simply measured as the total amount of strong base ions minus the total amount of strong acid anions:

ANC = (Ca 2+ + Mg 2+ + K + + Na + + NH 4 ) – (SO 4 2- + NO 3 - + Cl - ) (2-1)

The unit of ANC is usually mi croequivalents per liter ( μ eq/L). If the sum of the equivalent concentrations of the base cations exceeds those of the str ong acid anions, then the ANC of a waterbody will be positive. To the ex tent that the base cation sum exceeds the strong acid anion sum, the ANC will be higher. Higher ANC is generally associated with high pH and
Ca 2+ concentrations; lower ANC is genera lly associated with low pH and Al 3+ concentrations and a greater likelihood of toxicity to biota. Low ANC coincides with effects on aquatic systems (e.g., individual species fitness loss or death, reduced species richness, altered co mmunity structure). At the community level, species richness is positively correlated with pH and ANC (Kretser et al., 1989; Rago and Wiener, 1986) because energy cost in maintaining physiological homeostasis, growth, and reproduction is high at low ANC levels (Sch reck, 1981, 1982; Wedemeyer et al., 1990). For example, Sullivan and colleagues (2006) found a logistic relationship between fish species richness and ANC class for Adirondack Case Study Area lakes ( Figure 2-1a ) that indicates theAppendix B

March 2010 5 Draft – Do Not Quote or Cite probability of occurrence of an organism for a given value of ANC. In the Shenandoah Case Study Area, a statistically robust relationship between acid-base status of streams and fish species richness was also documented ( Figure 2-1b ). In fact, ANC has been found in various studies to be the best single indicator of th e biological response and health of aquatic communities in acid-sensitive systems (L ien et al., 1992; Sullivan et al., 2006). 1

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12 Biota are generally not harmed when ANC values are >100 microequivalents per liter ( μ eq/L). The number of fish specie s also peaks at ANC values >100 μ eq/L (Bulger et al., 1999; Driscoll et al., 2001; Kret ser et al., 1989; Sullivan et al., 2006). Below 100 μ eq/L, ANC fish fitness and community diversity begin to decline ( Figure 2-1). At ANC levels between 100 and
50 μ eq/L, the fitness of sensitive species (e.g., brook trout, zooplankton) also begins to decline.
When ANC concentrations are <50 μ eq/L, they are generally associated with death or loss of
fitness of biota that are sensit ive to acidification (Kretser et al., 1989; Dennis and Bulger, 1995).

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24 Figure 2-1. (a) Number of fish species per lake or stream versus acidity, expressed as acid neutralizing capacity for Adirondack Case Study Area lakes (Sullivan et al., 2006). (b) Number of fish species among 13 streams in Shenandoah National Park. Values of acid neutralizing capacity are means based on quarterly measurements from 1987 to 1994. The regression analysis shows a highly sign ificant relationship (p < .0001) between mean stream acid neutralizing capacity and the number of fish species. When ANC levels drop to <20 μ eq/L, all biota exhibit some level of negative effects. Fish and plankton diversity and the structure of the communities continue to decline sharply to levels where acid-tolerant species begin to outnumber all other species (Matuszek and Beggs, 1988; Driscoll et al., 2001). Stoddard and colleague s (2003) showed that to protect biota from episodic acidification in the springtime, base flow ANC levels need to have an ANC of at leastAppendix B

March 2010 6 Draft – Do Not Quote or Cite 30–40 μ eq/L. Complete loss of fish populations a nd extremely low diversity of planktonic communities occur when ANC levels stay <0 μ eq/L. Only acidophilic species are present, but their population numbers are sharpl y reduced (Sullivan et al., 2006). 1

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15 The critical load approach can be used to connect current deposition of nitrogen and
sulfur to the acid-base condition and biological risk to biota of lakes and streams in the study through the defined ANC thresholds. Calculating critical load exceedances (i.e., the amount of deposition above the critical load) allows the de termination of whether cu rrent deposition poses a risk of acidification to a given group of waterbodies. Low critical load values (i.e., less than 50 meq/m 2. yr) mean that the watershed has a limited ability to neutralize the addition of acidic anions, and hence, it is susceptibl e to acidification. The greater the critical load value, the greater the ability of the watershed to neutralize the a dditional acidic anions and protect aquatic life. This approach also allows for the comparison of different levels of ANC thresholds (e.g., 0

μ eq/L (acidic), 20 μ eq/L (minimal protection), 50 μ eq/L (moderate protection), and 100 μ eq/L (full protection)) and their associated risk to the biological community. Table 2-1 provides a summary of the biological effects ex perienced at each of these limits.

Table 2-1. Aquatic Status Categories Category Label ANC Levels* Expected Ecological Effects
Acute Concern <0 micro equivalent per Liter ( μ eq/L) Near complete loss of fish populations is expected. Planktonic communities have extremely low diversity and are dominated by acidophilic forms. The number of individuals in plankton species that are present is greatly reduced.

Severe Concern 0–20 μ eq/L Highly sensitive to episodic acidification. During episodes of high acidifying deposition, brook trout populations may experience lethal effects. Diversity and distribution of zooplankton communities decline sharply.

Elevated Concern 20–50 μ eq/L Fish species richness is greatly reduced (i.e., more than half of expected species can be missing). On average, brook trout populations experience sublethal effects, incl uding loss of health, reproduction capacity, and fitness. Diversit y and distribution of zooplankton communities decline.

Moderate Concern 50–100 μ eq/L Fish species richness begins to decline (i.e., sensitive species are lost from lakes). Brook trout populations are sensitive and variable, with possible sublethal effects. Divers ity and distribution of zooplankton communities also begin to decline as species that are sensitive to acidifying deposition are affected.Appendix B

March 2010 7 Draft – Do Not Quote or Cite Category Label ANC Levels* Expected Ecological Effects
Low Concern >100 μ eq/L Fish species richness may be unaffected. Reproducing brook trout populations are expected where habitat is suitable. Zooplankton communities are unaffected and exhibit expected diversity and distribution.

There are numerous methods and models that can be used to calculate critical loads for acidity. Drawing on the peer-reviewed scientific literature (Dupont et al., 2005), this study will use a steady-state critical load model that uses surface water chemistry as the base for calculating the critical load. A combination of the Steady- State Surface Water Chemistry (SSWC) and FirstOrder Acidity Balance (FAB) models were used to calculate the critical load. Both the SSWC model and FAB are based on the pr inciple that excess base-cation production within a catchment area should be equal to or grea ter than the acid anion input, th ereby maintaining the ANC above a preselected level (Reynolds and Norris, 2001; Posch et al ., 1997). These models assume steady-state conditions and assume that all SO 4 2– in runoff originates from sea salt spray and anthropogenic deposition. Given a critical ANC protec tion level, the critical load of acidity is simply the input flux of acid anions from atmospheric deposition (i.e., natural and anthropogenic) subtracted from the natural (i.e ., preindustrial) inputs of base cations in the
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25 Critical loads for nitrogen and sulfur (CL(N) + CL(S)) or crit ical load of acidity CL(A) are calculated for each waterbody from the princi ple that the acid load should not exceed the nonmarine, nonanthropogenic base cation input and sources and si nks in the catchment minus a neutralizing to protect selected biota from being damaged:

CL(N) + CL(S) or CL(A) = BC * dep + BC w – Bc u – AN - ANC limit (2-2)

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BC * dep = nonanthropogenic deposition flux of base cations (BC*=Ca*+Mg*+K*+Na*)
BC w = the average weathering fl ux, producing base cations
Bc u = the net long-term average uptake flux of base cations (Bc=Ca*+Mg*+K*) in the biomass (i.e., the annual averag e removal of base cations due to harvesting)Appendix B

March 2010 8 Draft – Do Not Quote or Cite AN = the net long-term average uptake, denitrification, a nd immobilization of nitrogen anions (e.g. NO 3 - ) and uptake of SO 4 - 1

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27 ANC limit = the lowest ANC-flux that protects the biological communities.

In order to estimate a critical load from water quality data alone, a relation to the preacidification nonmarine flux of base cations for each lake or stream, BC *
0 , is used.

BC * 0 = BC * dep + BC w - Bc u (2-3)

Thus, the critical load for aci dity can be rewritten as

CL(N) + CL(S) = BC * 0 – AN - ANC limit = Q

. ([ BC * ] 0 – [AN] - [ANC] limit ) (2-4)

where the second identity expresse s the critical load for acidity in terms of catchment runoff (Q) m/yr and concentration ([x] = X/Q). In cases where data are available, the FAB model is applied to quantify the [AN] term of the critical load calculation (derivation provided in Appendix 4, Attachment A of U.S. EPA, 2009). Where data ar e not available the cont ribution of nitrogen anions to acidification was assumed to be equal to the nitrogen leaching rate into the surface
water. The flux of acid anions in the surface water is assumed to represent the amount of nitrogen that is not retained by the catchment, which is determ ined from the sum of measured
concentration of NO 3 - and ammonia in the stream chemistry. This case describes the SSWC
model and the critical load for acidity is

CL(A) = Q

. ([BC * ] 0 – [ANC] limit ) (2-5)

where the contribution of acid anions is consider ed as part of the exceedances calculation. With this approach several major assumptions are made: (1 ) steady-state conditions exist, (2) the effect of nutrient cycling between plan ts and soil is negligible, (3) there are no significant nitrogen inputs from sources other than atmospheric de position, (4) ammonium leaching is negligible because any inputs are either take n up by biota or adsorbed onto soils or nitrate compounds, and (5) long-term sinks of sulfate in the catchment soils are negligible.
To determine a value for BC *
0 with the SSWC method, estimates of BC dep are available from previous works including the recent REA (U .S. EPA, 2009). Assumptions or estimates for
BC u and AN can be made based on attributes of the area of study, including vegetationAppendix B

March 2010 9 Draft – Do Not Quote or Cite characteristics. But the average flux of base ca tions weathered in a catchment and reaching the lake or streams (BC w ) is difficult to measure or compute fr om available information (Henriksen and Posch, 2001; Henriksen et al., 2002; Langan et al., 2001). In th e previous work for the Risk and Exposure Assessment case studies (U.S. EPA, 2009) the average flux of base cations and the resulting critical load estimation were derived from water quality data (Henriksen and Posch, 2001; Henriksen et al., 1992; Sverdrup et al., 1990). Weighted annual mean water chemistry values were used to estimate average base ca tion fluxes, which were calculated from water chemistry data collected from several national and regional monitoring pr ograms. For a national assessment, however, new methods must be developed to estimate the BC w flux, which is critical to the critical load calculation, through consistent, nationally-a pplicable means. 1

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29 2.1.2 Terrestrial Acidification and Critical Acid Loads Due to the impact of acidifying nitrogen and sulfur deposition on soil solution base cation (Bc) and aluminum concentrations, the Bc/Al ra tio in the soil solution is often used as the
chemical or critical indicator of terrestrial acidification. It was recently used as an indicator in the U.S. EPA’s Risk and Exposure Assessment for ox ides of nitrogen and oxides of sulfur (U.S. EPA, 2009). This Bc/Al ratio links acidifying de position to biological responses or end points, such as reduced plant or tree gr owth, within an ecosystem. In a meta-analysis of studies that explored the relationship between Bc/Al ratio in soil solution and tree growth, Sverdrup and Warfvinge (1993a) reported the Bc /Al ratios at which growth wa s reduced by 20% relative to
control trees. This 20% reduction in tree growth was selected as th e critical value because it was thought to represent a significant reduction in growth (H. Sverdrup personal communication, 2009b) and approximates the Bc/Al value that woul d result in a 10% reduction in normal tree growth under field conditions (Sverdrup and Warfvinge, 1993a). Figure 2-2 presents the findings of Sverdrup and Warfvinge (1993a) ba sed on 46 of the tree species (native and introduced) that grow in North America. This su mmary indicates that there is a 50% chance of negative tree response (i.e., >20% reduced grow th) at a soil solution Bc/Al ratio of 1.2 and a 75% chance at a Bc/Al ratio of 0.6. These finding s clearly demonstrate a relationship between Bc/Al ratio and tree health; as the Bc/Al is reduced, there is a greater likelihood of a negative impact on tree health.Appendix B

March 2010 10 Draft – Do Not Quote or Cite 0.01

0.1

1 10

0 2 5 5 0 7 5Bc/Al Ratio in Soil Solution

1 0 0 (Bc/Al) crit = 1.2 (Bc/Al) crit = 0.6

0.01

0.1

1 10

0 2 5 5 0 7 5Bc/Al Ratio in Soil Solution

1 0 0 (Bc/Al) crit = 1.2 (Bc/Al) crit = 0.6

Cumulative Percentage of Species Exhibiting Reduced Growth Response 1

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21 Figure 2-2. The relationship between the Bc/Al ratio in soil solution and the percentage of tree species (found growing in North America – native and introduced species) exhibiting a 20% reduction in growth relative to co ntrols (after Sverdrup and Warfvinge, 1993). The tree species most commonly studied in North America to assess the impacts of acidification due to total nitrogen and sulfur deposition ar e red spruce (i.e., Picea Rubens ) and sugar maple (i.e., Acer saccharum ). Both species are found in the eastern United States, and soil acidification is widespread thr oughout this area (Warby et al., 2009). Based on the results from a compilation of laboratory studies, red spruce gr owth can be reduced by 20% at a Bc/Al soil solution ratio of approximately 1.2, and a simila r reduction in growth may be experienced by sugar maple at a Bc/Al ratio of 0.6 (Sverdrup and Warfvinge 1993a). Red spruce is found scattered throughout high-elevation sites in the Appalachian Mountains, including the southern peaks. Noticeable fractions of the canopy red spruce died within the Adirondack, Green, and White mounta ins in the 1970s and 1980s . Although a variety of conditions, such as changes in climate and exposure to ozone, may impact the growth of red spruce (Fincher et al., 1989; Johnson et al., 1988), acidifying deposition has been implicated as one of the main factors causing this decline. Based on the research conducted to date, acidifying deposition can cause a depletion of base cations in upper soil horizons , Al toxicity to tree roots, and accelerated leaching of base cations from foliage (U.S. EPA, 2008, Section 3.2.2.3). Such
nutrient imbalances and deficiencies can reduce the ability of trees to resp ond to stresses, such as insect defoliation, drought, and cold weather da mage (DeHayes et al., 1999; Driscoll et al.,Appendix B

March 2010 11 Draft – Do Not Quote or Cite 2001), thereby decreasing tree health and incr easing mortality. Add itional linkages between acidifying deposition and red spruce physio logical responses are indicated in Table 4.3-1

. Within the southeastern United States, periods of red spruce decline slowed after the 1980s, when a corresponding decrease in SO 2 emissions, and therefore ac idic deposition, was recorded (Webster et al., 2004). 1

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23 Sugar maple is found throughout the northeas tern United States and the central Appalachian Mountain region. This sp ecies has been declining in th e eastern United States since the 1950s. Studies on sugar maple have found that one source of this decline in growth is related to both acidifying deposition and base-poor soils on geologies dominated by sandstone or other base-poor substrates (Bailey et al., 2004; Horsley et al., 2000 ). These site conditions are representative of the conditions expected to be most su sceptible to impacts of acidifying deposition because of probable low initial base cation pools and high base cation leaching losses (U.S. EPA, 2008, Section 3.2.2.3). The pr obability of a decrease in cr own vigor or an increase in tree mortality has been noted to increase at sites with low Ca 2+ and Mg 2+ as a result of leaching caused by acidifying deposition (Drohan and Sharpe, 1997). Low levels of Ca 2+ in leaves and
soils have been shown to be related to lowe r rates of photosynthesis and higher antioxidant enzyme activity in sugar maple stands in Pennsyl vania (St. Clair et al., 2005). In addition, plots of sugar maples in decline were found to have Ca 2+ /Al ratios less than 1, as well as lower base cation concentrations and pH valu es compared with plots of hea lthy sugar maples (Drohan et al., 2002). Sugar maple regeneration has also been note d to be restricted unde r conditions of low soil
Ca 2+ levels (Juice et al., 2006). Thes e indicators have all been shown to be related to the deposition of atmospheric nitrogen and sulfur. Additional linkages between acidifying deposition and sugar maple physiological responses are indicated in Table 2-2

.

Table 2-2. Summary of Linkages between Acidifying Deposition, Biogeochemical Processes That Affect Ca 2+ , Physiological Processes That Are Influenced by Ca 2+ , and Effect on Forest Function

Biogeochemical Response to Acidifying deposition Physiological Response Effect on Forest Function Leach Ca 2+ from leaf membrane Decrease the cold tolerance of needles in red spruce Loss of current-year needles in red spruce Reduce the ratio of Ca 2+ /Al in soil and soil solutions Dysfunction in fine roots of red spruce blocks uptake of Ca 2+ Decreased growth and increased susceptib ility to stress in red spruceAppendix B

March 2010 12 Draft – Do Not Quote or Cite

Biogeochemical Response to Acidifying deposition Physiological Response Effect on Forest Function Reduce the ratio of Ca 2+ /Al in soil and soil solutions More energy is used to acquire Ca 2+ in soils with low Ca 2+ /Al ratios Decreased growth and increased photosynthetic allocation to red spruce roots Reduce the availability of nutrient cations in marginal soils Sugar maples on drought-prone or nutrient-poor soils are less able to withstand stresses Episodic dieback and growth impairment in sugar maple

Source: Fenn and colleagues, 2006. Although the main focus of the Terrestrial Acidification Case Study outlined in the Risk and Exposure Assessment for Review of the Seco ndary National Ambient Air Quality Standards for Oxides of Nitrogen and Sulfur (U.S. EPA, 2009) was an evalua tion of the negative impacts of nitrogen and sulfur deposition on soil acidification and tree health, it should be recognized that under certain conditions, nitrogen and sulfur depo sition can have a positive impact on tree health. Nitrogen limits the growth of many forests (Chapin et al., 19 93; Killam, 1994; Miller, 1988), and therefore, in such forests, n itrogen deposition may act as a fe rtilizer and stimulate growth.
Forests where critical acid lo ads are not exceeded by nitrogen and sulfur deposition could potentially be included within this group of forests that respond positively to deposition. These potential positive growth impacts of nitrogen and sulfur deposition are discussed further, and the results of case study analyses are presente d in Attachment A of Appendix 5 of the Risk and Exposure Assessment (U.S. EPA, 2009). 1

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23 In summary, among potential influencing factor s, including elevated ozone levels and changes in climate, the acidification of soils is one of the factors that can negatively impact the health of red spruce and sugar maple. Mortality a nd susceptibility to disease and injury can be increased and growth decreased w ith acidifying deposition. Therefor e, the health of sugar maple and red spruce was used as the endpoints (ecolo gical responses) to evaluate acidification in terrestrial systems. “Health” in the context of the Risk and Exposure Assessment terrestrial acidification case study was defined as the physiol ogical condition of a tree that impacts growth and/or mortality. The Simple Mass Balance (SMB) model was used to estimate critical loads of acidity in the Risk and Exposure Assessment case study (Equati on 2-1). The full derivation of this equation is detailed in the ICP Mapping and Modeling Manual (UNECE, 2004).Appendix B

March 2010 13 Draft – Do Not Quote or Cite critle, deuiuw dep dep ANC NNNBcBCClBCN)CL(S

− + + +

− + −=+ (2-1) 1

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27 where CL(S+N) = forest soil critical load fo r combined nitrogen and sulfur acidifying deposition ((N+S) comb )
BC dep = base cation (Ca 2+ + K + + Mg 2+ + Na + ) deposition 1
Cl dep = chloride deposition
BC w = base cation (Ca 2+ + K + + Mg 2+ + Na + ) weathering
Bc u = uptake of base cations (Ca 2+ + K + + Mg 2+ ) by trees
N i = nitrogen immobilization
N u = uptake of nitrogen by trees
N de = denitrification
ANC le,crit = forest soil acid neutralizi ng capacity of critical load leaching

Some of these parameters had defi ned or selected input values (BC dep , Cl dep , N i , N u and N de ), while four of these parameters, including BC w , Bc u , N u and ANC le,crit , required calculation. For the Risk and Exposure Assessment’s terrestr ial acidification case study, three values
of the indicator of critical load, expressed as (Bc/Al) crit soil solution ratio, were selected to represent different levels of tree protection associ ated with total nitrogen and sulfur deposition: 0.6, 1.2, and 10 ( Table 2-3 ). The (Bc/Al) crit ratio of 0.6 represents th e highest level of impact (lowest level of protecti on) to tree health and growth and wa s selected because 75% of species found growing in North America experience reduced growth at this Bc/Al ratio. In addition, a
soil solution Bc/Al ratio of 0. 6 has been linked to a 20% and 35% reduction in sugar maple and red spruce growth, respectively. The (Bc/Al) crit ratio of 1.2 is considered to represent a moderate level of impact, as the growth of 50% of tree species (found gr owing in North America) was negatively impacted at this soil solution ratio. The (Bc/Al) crit ratio of 10.0 represents the lowest level of impact (greatest level of protection) to tr ee growth; it is the most conservative value used
in studies that have calculated critical loads in the United States and Canada (Canada (McNulty et al., 2007; NEG/ECP, 2001; Watmough et al., 2004).

1 The ICP Mapping and Modeling Manual (UNECE, 2004) recommends that wet deposition be corrected for sea salt

on sites within 70 km of the coast. Both the HBEF and KEF case study areas are greater than 70 km from the coast,

so this correction was not used.Appendix B

March 2010 14 Draft – Do Not Quote or Cite Table 2-3. The Three Indicator (Bc/Al) crit Soil Solution Ratios and Corresponding Levels of Protection to Tree Health and Critical Loads Indicator (Bc/Al) crit Soil Solution Ratio Level of Protection to Tree Health Critical Load 0.6 Low High 1.2 Intermediate Intermediate 10.0 High Low
The prediction of tree protection achieved usi ng each of these three indicator ratios of 0.6, 1.2, and 10.0 includes an important estim ation of base cation weathering as shown in Equation 2-1, above. The purpose of this repor t is to describe the methodologies, data requirements, data availability, and uncertain ties associated with estimating base cation weathering. 1

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25 3. AQUATIC BASE CATION WEATHERING METHODOLOGY The ISA (US EPA, 2008) reports that the principal factor governi ng the sensitivity of terrestrial and aquatic ecosystems to acidificati on from sulfur and nitrogen deposition is geology (particularly surficial geology). Geologic formations having low base cation supply generally
underlie the watersheds of acid-se nsitive lakes and streams. Other factors that contribute to the sensitivity of soils and surface waters to acidifying deposition include topography, soil chemistry, land use, and hydrologic flowpath. Su rface waters in the same setting can have different sensitivities to acidification, depending on the relative contributions of near-surface drainage water and deeper groundw ater (Chen et al., 1984; Driscoll et al., 1991; Eilers et al., 1983). Lakes and streams in the United States that are sensitive to episodic and chronic acidification in response to SO x , and to a lesser extent NO X , deposition tend to occur at relatively high elevation in areas that have base-poor bedrock, high relief , and shallow soils (U.S. EPA, 2008, Section 3.2.4.1). 3.1 Aquatic Base Cation Weathering Base cation weathering for aquati c acidification critical loads must be representative of the catchment around the waterbody of interest. This aspect of quantification of the weathering rate provides the difference when calculating weathering rates for aquatic versus terrestrial analysis purposes. The process of weathering itse lf provides the only natu ral in-soil source of alkalinity that is available to neutralize acidity inputs to the system over the long term. Chemical weathering of the mineral matrix within soils supplies base cations that are removed from soilAppendix B

March 2010 15 Draft – Do Not Quote or Cite due to acid inputs. Therefore, th e rate of weathering of the soils within a catchment is dependent on the chemical and physical prope rties of the soil (S verdrup et al., 1992; Wh itfield et al., 2006). As indicated in Section 2.2, the average flux of base cations weathered in a catchment and reaching the lake or streams (BC w ) is difficult to measure or com pute from available information (Henriksen and Posch, 2001; Henriksen et al., 20 02; Langan et al., 2001). Approaches also differ based on whether the weathering rate needs to account for only in-so il processes (profile measurements and models) or whether it needs to account for the flux of base cations to surface water (spatially integrated catchment da ta and models) (Langan et al., 2001). 1

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29 In the Aquatic Acidification case study in the REA Report (U.S. EPA, 2009), BC w rates were not directly calculated. Instead, the F-factor approach was used to calculate the preacidification, non-marine fl ux of base cations (BC * 0 ) for each lake or stream. An F-factor (explained in Section 3.2.2) is a ratio of the ch ange in non-marine base cation concentration due to changes in strong acid anion concentrations (Henriksen, 1984; Brakke et al., 1990), as shown in the following equations:

BC * 0 = BC * t – F (SO * 4,t - SO * 4,0 + NO * 3,t - NO * 3,0 ) (3-1)

F = ([BC * ] t - [BC * ] 0 )/([SO 4 *] t - [SO 4 * ] 0 + [NO 3 * ] t - [NO 3 * ] 0 ) (3-2)

where the subscripts t and 0 refer to present a nd pre-acidification conditions, respectively. The pre-acidification NO 3 - concentration, NO * 3,0 , was assumed to be zero. Several attempts have been made to create empiri cal relations for the F-factor and the pre-acidification SO 4 * concentration. Although the Aquati c Acidification case st udy relied on two of these relations, it must be noted that they were de veloped for areas outside of the U.S. and, therefore, cannot be applied to the conditions found within U.S. soils and climates without introducing a source of uncertainty (Henriksen and Posch, 2001; Henriksen et al., 2002; Brakke et al., 1989; Posch et al., 1997). Notwithstanding the lack of U.S.-based empi rical relations, the F-f actor can be used to
derive BC w estimates. Assuming that all atmospheric depos ition of base cations that falls within a catchment passes through to the surface water a nd that one can accurately estimate the uptake of base cations within the catchment, the BC w could ultimately be backed out of these relationships. However, both of these assumptions are likely to introduce an additional amount of uncertainty into the BC w estimates.Appendix B

March 2010 16 Draft – Do Not Quote or Cite For a national aquatic acidification assessmen t, different methods must be employed to
estimate BC w rates. In some studies, simple assumptions for the BC w are utilized. For instance, in a study by Dupont and colleagues (2005) using the SSWC, the authors assumed that weathering rates were time-independent and di d not affect critical load estimat es. In more advanced process modeling applications, su ch as ones using the Model of Acidification of Groundwater in Catchments (MAGIC) , weathering rates can be adjusted duri ng calibration and allowed to vary over ranges like 0 and 5 times the observed wa tershed base cation export for base cation weathering (Sullivan et al., 2004). There are seve ral different approaches to estimating the weathering rate of a soil or a catchment, ra nging from empirical relations to mass balance methods to calibrated process models. According to Whitfield and colleagues (2006) “to date no method has proven to be superior in application to different soil types and differing levels of soil
acidification.” The remainder of this section is intended to examine the BC w estimation methods that would be applicable to a national aquati c acidification critical loads analysis giving
consideration to the limitations of the method and the possible data and processing requirements for the analysis. 1

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31 3.2 Methodologies for Determining Base Cation Weathering Values in the United States 3.2.1 Difficulties in estimating base cation weathering Consideration must be given to several factors in the estima tion of base cation weathering fluxes for aquatic acidification (S verdrup et al., 1992; Whitfield et al., 2006; Rapp and Bishop, 2009; Henriksen and Posch, 2001; Henriksen et al., 2002):
1. The weathering contribution of the entir e catchment must be understood and not simply the weathering contribution of certa in soil profiles within the catchment. Additionally, the various types of land us e (e.g. agriculture or forest) within a catchment may all affect weathering rates differently.
2. When utilizing soil profile weat hering methods, the characteri stics of the entire soil profile must be considered and weighted according to catchment composition as opposed to only the rooting zone in indi vidual profiles as used in determining weathering for terrestria l acidification purposes.
3. Based on the critical load method chosen, it is often necessary to assume that the BC w remains constant over the length of the an alysis. While this simplifies the estimation
of BC w , it introduces uncertainty into any an alysis. The length of the analysisAppendix B

March 2010 17 Draft – Do Not Quote or Cite scenario must be sufficiently long and have supporting data in order to provide a long-term average, which is not su bjected to short-term variations. 1

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31 4. The data requirements for a national assessment necessitate using similar data sources for all applications so that assumptions and methods can remain constant across the
nation.
5. The application of any empirical relations for calculation of BC w or intermediate component of BC w (e.g., the F-factor) must be validated against the geographic region in which they will be applied. Given that most empirical relations developed to date were based on data from European nations, th ese relations need to be recalibrated to
data from the U.S. Given all of these factors, estimation of BC w for a national applica tion poses a significant challenge. The methods detailed in the following section seek to balance the limitations and benefits of each approach to estimation of BC w . 3.2.2 Approaches to estimating BC w for Aquatic Acidification Work presented in the scientific literature over the last two decades provides several different approaches researchers have taken to estimate the BC w rates for aquatic effects. These approaches do not always differe ntiate between the actual weat hering processes in-soil and the other ion exchange processes taking place (Langa n et al., 2001). Approaches to estimating BC w also vary between terrestrial and aquatic studies . Aquatic studies of acidification must capture the weathering rates of all soil horizons which contribute base cat ions and not solely the rooting zone as specified in terrestrial acidifi cation studies (Whitfie ld et al., 2006). Four general categories of approach es are outlined for determining BC w for aquatic
acidification critical loads calculations using the SSWC. 1. Budgets studies of catchments or watersheds; 2. Historical weathering rate determinations; 3. Empirical relations; and
4. Process-based models. In the case of empirical data relations a nd process-based models, specific methods are provided. The strengths and wea knesses of either the general category or specific approach in terms of both utilization in aquatic acidificati on critical loads calculati ons and estimation of BC w are examined in the following paragraphs and Table 3-1

.Appendix B

March 2010 18 Draft – Do Not Quote or Cite Budget Studies – Budget studies are simple means of determining fluxes within a system by balancing the masses coming into and going out of a system. In determining the BC w , a mass balance would be performed around the base cations fluxes within a watershed, where atmospheric deposition constitutes the main source input and streamflow the main output. Within the balance, base cation retention is also accounted for through uptake by biomass and
immobilization in the soil. The BC w developed from budget studies represent integrated values for the whole watershed as desired for aquatic acidification estimates as opposed to only weathering from the rooting zone as desired for terrestrial acidification (Sverdrup and Warfvinge 1988; Miller, 2001). Depending on how the balance is set up, the balance can be a single equation around the total base cati on flux or a series of equations for each individual cation. The setup of the equations leads to the primary limitation of the method in that while it is a relatively simple concept, the individual fluxes within the balance are not easily measured or known (Bricker et al., 2003). 1

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23 Most mass balance calculations require an assumption of steady-state behavior. This assumption is easily justifiable over long periods of record. Additional limitations of the method evolve from the number of unknown fluxes (e.g. w eathering rate of individual minerals) within the equations defining the balance. Researchers ha ve utilized a variety of techniques to overcome this limitation, including applying simplifying assumptions or adding additional equations. However, with each assumption or additional equa tion, a greater amount of uncertainty that must be quantified is added into the analysis. Data sources for a mass balance can also be variable depending on the complexity of the relationships defined within the balance. While databases and studies may exist for major elements at a variet y of sites, comparable data for trace or more complex elements may be lacking (Velbel and Price, 2007).
Historical Rate Determinations – This approach is detailed in Section 4 for terrestrial acidification approaches. Because the BC w flux required for aquatic acidification approaches requires characterization of the w hole soil profile averag ed across a catchment or watershed, this approach can become computationally intensive for aquatic purposes. While it is possible to conduct such an approach on a small scale for an aquatic acidification a ssessment, it is more likely suited to terrestrial applications and so explanation is provided in those sections of the
document. 24

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30Appendix B

March 2010 19 Draft – Do Not Quote or Cite Empirical Relations – A number of empiri cal relationships have been developed to
calculate BC w , or related factors, from water quality da ta alone. Empirical re lationships are only as strong as the data on which th ey are based and are only appli cable to the geographic regions
from which the calibration data is obtained. 1

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F-Factor : The F-factor is defined as the ratio of ch ange in non-marine base cation concentrations due to changes in strong acid anion concentrations (Henriksen, 1984; Brakke et al., 1990). (See Section 3.1.) A situation where F = 1 indicates that only soil acidification occurs within the catchment, i.e. all incoming protons are neutrali zed in the catchment. When F = 0, then only water acidification is occurring and none of the incoming protons are neutralized in the catchment. Using historical data from Norway, Sweden, U.S.A. and Canada, the F-factor was estimated empirically to be in the range 0.2–0.4 (Henriksen, 1984). Several empirical relationships have been develope d in order to calculate the F-factor based on current base cation concentrations using data from Norway (Brakke et al., 1990) or on pre-acidification base cation concentration using data from Finland (Posch et al., 1993). 5 6 7 8 9 10 11 12 13 14
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22 23 24 25 26 27 There are several limitations to using the F-factor . While it is simple to apply anywhere the data is available to satisfy the empirical relations, these relations are really only valid in Norway, Finland, or wherever the specific relation was derived. In several instances, researchers have applied the Norway- or Finland-based relations to Canadian (Watmough et al., 2005) and U.S. study locations (Henriksen et al., 2002; Dupont et al., 2005; U.S. EPA, 2009) with the assumption that the empirical equations provide adequate ch aracterization of the relationship between base cation concentrations and the F-factor. A second major limitation in utilizing the F-factor is that this derived factor does not specifically quantify the BC w flux. Instead it provides calculation of the base cations leached from the soil, which includes BCw and base cations derived th rough deposition inputs to the system, or removed by harvesting (Henriksen et al., 2002; Rapp and Bishop, 2009). Although the SSWC is most often used with the F-factor, in a national a pplication where we seek to specifically quantify the BC w , an alternative method should be used. Indicator element in conjunction with weathering ratios : Chen et al., 2004: “Weathering rates at Arbutus watershed could also be obtained using sodium as indicator element, as described by Gbondo-Tugbawa et al. (2001). The weathering inputs of the indicator element (sodium) could be derived using a mass balance approach, and the derived sodium weathering rate was used in conjunction with base cation weathering ratios repor ted by Johnson and Lindberg (1992) for the HF to derive weathering rates of other base cati ons. Using this method, the weathering rates of sodium and calcium derived for Arbutus watershed are very si milar to values derived through calibration, whereas rates of magnesium and pot assium derived using these two methods showed some discrepancies (Table II).” 28 29 30 31 32 33 34 35 36 Weathering rates vs. Stream chemistry or landscape variables : This approach begins with a set of BC w for a specific set of water bodies. The values of BC w are then regressed against the stream chemistry parameters, such as ANC, in order to find a correlation relationship. These regression relationships are then applied to stream chemistr y of other water bodies within a defined region of interest to find the BC w for the water bodies. In areas where stream chemistry is not available, landscape variables can be used in place to find correlations with the BC w . 37 38 39 40 41 42
43 44 45 The limitation with this approach is that a statistically significant number of BC w values must be available from which to create a regression re lationship. Also, the region in which the extrapolation is valid must be defined. In work by Sullivan and colleagues (2004), extrapolationAppendix B

March 2010 20 Draft – Do Not Quote or Cite of modeled BC w values was completed using groupings of physiographic region and ANC class. The value of this approach is that it can specifically be applied to BC w and can be based on modeled, monitored, or estimated BC w values as long as there are a sufficient number of values for extrapolation. Other works have extrapol ated ANC values based on chemistry and landscape variables in a similar manner with a high leve l of success (Sullivan et al., 2007b, Nanus et al., 2009). 1 2 3 4 5 6 Process-based Models – Mineral weathering terms within modeling simulations can be a large source of uncertainty as the weathering term u tilized in most process models, in attempts to represent reality, impacts the loss of base cations to surface wate rs. Therefore, when little is known about the true weathering rate or the c onstraints on its values, models must utilize calibration procedures against in-stream water chemis try data to arrive at a likely weathering rate (Chen et al., 2004; Sullivan et al., 2004). 7

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21 Process-based models vary greatly in their ra nge of processes represented, complexity of representations, time step, and required data inpu ts. Overall, there is no perfect model but the best candidate for a task can be chosen provided the available data, the area of concern, and the goals of the analysis. In this case, we would seek to use all available data resources in order to derive a range of spatially-explicit BC w values across the nation. Descriptions of the four candi date process models available for use across the country for determining BC w are provided below. In order to provide as concise a description as possible, these model summaries are taken directly from the scientific literature. Summation of the strengths and weaknesses of each model is provided after the model description.
DayCent-Chem : “DayCent-Chem links together two widely accepted and tested models—(1) a daily time-step nutrient cycling and soil hydrol ogy model, version 5 of the DayCent model [Parton et al., 1998], and (2) PHREEQC, an a queous geochemical equilibrium model [Parkhurst and Appelo, 1999]—to form a model that simulates N, P, S, and carbon (C) ecosystem dynamics and soil and stream water acid-base chemistry (fi g. 1.2). DayCent-Chem computes atmospheric deposition, soil water fluxes, snowpack and stre am dynamics, plant production and uptake, soil organic matter decomposition, mineralization, nitrific ation, and denitrification (left side of fig. 1.2) while utilizing PHREEQC’s low-temperature aqueous geochemical equilibrium calculations, including CO 2 dissolution, mineral denudation, and cation exchange, to compute soil water and stream chemistry (right side of figure). DayCen t-Chem’s daily soil solution and stream water chemistry calculations make it possible to use th e model to investigate the potential for episodic acidification” (Hartman et al., 2009). 22 23 24 25 26 27 28 29 30 31 32 33
34 35 36 37 38 39 40 DayCent-Chem was recently applied to eight diffe rent mountain watersheds from the west to the east with success in certain capacities, therefor e, making it a suitable candidate for a national analysis. These applications did highlight difficu lties in determining realistic weathering rates in certain areas. With DayCent-Chem, a user must specify an initial value for weathering, which may be adjusted during calibration. In several instances, this value was first set to measured or estimated values for the area of interest and then modified largely during calibration (Hartman et al., 2009). While the daily time step and biotic processes represented by the model provide aAppendix B

March 2010 21 Draft – Do Not Quote or Cite more complex view of the environment, they also add a complexity to the model that appears to greatly impact the estimation of the key parameter for this analysis. 1 2
MAGIC : “MAGIC is a lumped-parameter model of intermediate complexity, developed to predict the long-term effects of acidic deposition on surface water chemistry [Cosby et al., 1985a, 1985b]. The model simulates soil solution chemistry and surface water chemistry to predict the monthly and annual average concentrations of the major ions in these waters. MAGIC consists of (1) a section in which the concentrations of major ions are assumed to be governed by simultaneous reactions involving SO 4 2- adsorption, cation exchange, dissolution-precipitationspeciation of Al and dissolution-speciation of inorganic C and (2) a mass balance section in which the flux of major ions to and from the soil is assumed to be controlled by atmospheric inputs, chemical weathering, net uptake and loss in biomass and losses to runoff. At the heart of MAGIC is the size of the pool of exchangeable base cations in the soil. As the fluxes to and from this pool change over time owing to changes in atmospheric deposition, the chemical equilibria between soil and soil solution shift to give cha nges in surface water chemistry. The degree and rate of change of surface water acidity thus depend both on flux factors and the inherent characteristics of the affected soils” (Sullivan et al., 2004). 3 4 5 6 7 8 9 10 11 12 13 14 15 16
17 18 19 20 21 22 23 24 25 The strengths of MAGIC lie in its simplicity an d ability to be applied for a large number of lakes/streams in batch processes. MAGIC has b een in use since the 1980s, has been widely applied within the eastern portions of the country wi th more limited applications in the West. (See Section 3.3 for further discussion.) The simplicity of MAGIC’s mass balances approach also counts as one of its limitations because it may not account for all of the biotic processes that affect the weathering rate. MAGIC determines the BC w through calibration to water chemistry data. The “fuzzy optimization” procedures now built into MAGIC allow for an optimized value of the BC w to be determined from a series of calibra tions at each modeling location (Sullivan et al., 2004).
PnET-BGC : “PnET-BGC is an integrated forest-soil-wa ter model that has been used to assess the effects of air pollution and land disturbances on forest and aquatic ecosystems [Gbondo-Tugbawa et al., 2001]. The model was developed by lin king two submodels: PnET-CN (PnET-carbon and nitrogen) [Aber et al., 1997] and BGC [Gbondo-Tugbawa et al., 2001]. The main processes in the model include tree photosynthesis, growth a nd productivity, litter production and decay, mineralization of organic matter, immobilization of nitrogen, nitrification [Aber et al., 1997], vegetation and organic matter interactions of major elements, abiotic soil processes, solution speciation, and surface water processes [Gbondo-Tugbawa et al., 2001].... For lake simulations, it is assumed that the water column is completely mixed. The model predicts monthly concentrations and fluxes of major solutes in la ke water, monthly concentrations and pools of exchangeable cations and adsorbed sulfate in soil, and monthly fluxes of major solutes from soil and forest vegetation” (Zhai et al., 2008). 26 27 28 29 30 31 32 33 34 35 36 37
38 39 40 41 42 43 44 45 46 47 48 Chen and others (2004) nicely summarize the tradeoffs associated with utilizing the PnET-BGC model: “A strength of PnET-BGC over other acidi fication models is its ability to simulate [vegetation and microbial processes]. However, this representation can also be a limitation. The model depicts large element pools in soil and la rge fluxes through biotic processes. Any change in these pools and fluxes will greatly influence the element budgets. If these simulated fluxes are not accurate, then model predictions will misrepre sent element dynamics.” Additionally, almost all of the PnET-BGC applications to date have been completed within the eastern portions of the country mostly focusing in the Adirondacks and Hubbard Brook Experimental Forest (GbondoTugbawa et al., 2001; Chen et al., 2004; Zhai et al., 2008). Expanding this model to western or southern areas would necessitate large amounts of data gathering and processing as well as testing of the representation of the biotic processes found in these differing ecosystems.Appendix B

March 2010 22 Draft – Do Not Quote or Cite PROFILE : “PROFILE [Warfvinge and Sverdrup, 1992] is a steady-state soil chemical model with a weathering rate sub-model that calculat es weathering rates (for each base cation) explicitly using independent soil properties. Mineral dissolu tion reactions governing the rate of weathering involve many components in the liquid phase including H 2 O, H + , OH − , CO 2 and organic acids. These serve as the principle method for cataloguing the contribution of chemical reactions between soil solution and silicate minerals to base cation release. Inhibition of the reactions through increased concentrations of the products is accounted for by rate reduction factors. Precipitation of secondary minerals is subtracted from the total base cation release rate. Climate data, soil properties and detailed soil mineralogy are used as inputs to the model [Warfvinge and Sverdrup, 1992]” (Whitfield et al., 2006). 1 2 3 4 5 6 7 8 9 10
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18 19 The PROFILE model is more fully explained in Section 4 for the terrestrial BC w approaches. While the PROFILE model provides a highly de terministic, process-based representation of mineral weathering, trying to utilize this mode l to determine the base cations weathering and reaching surface water bodies requires the representation of all soil horizons that may contribute to weathering and the summarization of BC w calculations by catchments surrounding each water body of interest. These two qualif ications on top of the basic PROFILE application introduce a large amount of complexity into the modeling analysis.Appendix BTable 3-1.Review of Modeling Approaches (and models) to Estimate BaseCation Weathering for Aquatic Critical Acid Load DeterminationsModelApproachDescription ofMethodDataRequirementsModelComplexitySuitability forEstimating BCwforAquatic Critical AcidLoad Determinations inThe United StatesSuitability tor MappingBCwOver LargeRegions in The UnitedStatesReferencesBudget Studiesmass balance ofinputs and outputs ofbase cations withincatchment orwatershedmediumMediumlow; BCwestimate isoften an integrated valuefor whole catchment orwatershedlow - medium (based ondata availability); mayrequire Sr isotope ratio ofstream chemistry toseparate exchangeableversus weathered basecation sourcesBricker et al., 1993;Velbel and Price, 2007Historical RateDeterminationsloss of base cationsin soil profile relativeto stable element(Zr, Ti, quartz orrutile)lowLowmedium; restricted tosites with young soils ofknown age (eg., soilsthat have formed sincethe most recent glacialevent, ~20,000 yearsago)low; restricted to siteswith young soils andsites where historical ratedeterminations havebeen conductedSverdrup et al., 1998;Sverdrup et al., 1990Empirical DataRelationsmodeledrelationshipsbetween surfacewater characteristicsand site conditionsor atmosphericdeposition measureslow - highlow – highlow-mediumlow-mediumF-Factora factor thatcombines the effectsof deposition andweatheringlow -mediumLowlow; most accuratelyapplied to sites similar tothose where the modelwas derived; if newderivations can becompleted for the U.S.the suitability of thismethod would increaselow; most accuratelyapplied to sites similar tothose where the modelwas derived; if newderivations can becompleted for the U.S.the suitability of thismethod would increaseBrakke et al., 1990;Henriksen and Posch,2001; Henriksen et al.,2002; Rapp andBishop, 2009March 201023Draft – Do Not Quote or CiteAppendix BMarch 201024Draft – Do Not Quote or CiteModelApproachDescription ofMethodDataRequirementsModelComplexitySuitability forEstimating BCwforAquatic Critical AcidLoad Determinations inThe United StatesSuitability tor MappingBCwOver LargeRegions in The UnitedStatesReferencesIndicatorelement inconjunction withweatheringratiosdetermineweathering ratethrough massbalance methods forelement such assodium (Na) thenapply defined ratiosto determineweathering rates ofadditional elementslow-mediumlowlow; most accuratelyapplied to sites similar tothose where the modelwas derivedlow; most accuratelyapplied to sites similar tothose where the modelwas derivedGbondo-Tugbawa etal., 2001, 2002; Chenet al., 2004Weatheringrates vs. Streamchemistry orlandscapevariablesutilize weatheringrates determined byother methods andextrapolate toadditional areasbased on sitecharacteristicslow -mediumlowmedium; suitability willdepend on the ease atwhich derived weatheringrates can be obtainedand how strong theregressions betweenBCwand sitecharacteristics aremedium; relatively goodsuccess has been had atextrapolating BCwtoadditional sites based onstream chemistry;suitability will depend ondata availabilitySullivan et al., 2004,2007a, 2007b; Webbet al., 1994; Nanus etal., 2009Process-BasedModelsSteady-state anddynamic models thatrely on mathematicalrelationshipsrepresenting soil andsurface waterprocessesmedium -highmedium - highAppendix BMarch 201025Draft – Do Not Quote or CiteModelApproachDescription ofMethodDataRequirementsModelComplexitySuitability forEstimating BCwforAquatic Critical AcidLoad Determinations inThe United StatesSuitability tor MappingBCwOver LargeRegions in The UnitedStatesReferencesDayCent-ChemMineral weatheringrates are set andthen calibratedwithin the processmodel; Rates arespecified by mineraland not necessarilybase cations alonehighhighmedium - high; providesdaily time step resultswhich can be used toestimate timeto recoveryor time to damage;uncertainty on how wellmodel can simulate BCwin some areas will impactconfidence of results inthese areasmedium; DayCent-Chemhas had trouble inestimating mineralweathering rates in someareas of the countryHartman et al., 2007;Hartman et al., 2009MAGICBCwdeterminedthrough calibrationto fulfill therequirements of acatchment massbalance byoptimizing simulatedsoil and surfacewater chemistry tomonitored valuesmedium -highmedium - highmedium - high;numerous applications inthe east with some, butfewer in number,applications in the west;little coverage in theMidwest but these areasare less of a concern foraquatic acidificationeffectsmedium - high; will berestricted in areas wheresoils data are lacking(some western areas);otherwise, highlyapplicable in any areaswhere MAGICapplications have beencompletedCosby et al., 1985a,1985b, 1989a; Sullivanet al., 2004; Sullivan etal., 2008PnET-BGCBCwdeterminedthrough calibrationand held constantthroughout dynamicmodelingsimulationshighmedium - highlow-medium; modelapplications mostlycompleted only withinnortheastern U.S.vegetation and otherbiotic processesrepresented by themodel would needvalidation to otherregions of the countrylow-medium; becauseBCwis found throughcalibration alone for thismodel, the other modelprocesses and input datamust be validated for anyapplication beforecalibration can be usedfor BCwGbondo-Tugbawa etal., 2001; Chen et al.,2004; Zhai et al., 2008Appendix BMarch 201026Draft – Do Not Quote or CiteModelApproachDescription ofMethodDataRequirementsModelComplexitySuitability forEstimating BCwforAquatic Critical AcidLoad Determinations inThe United StatesSuitability tor MappingBCwOver LargeRegions in The UnitedStatesReferencesPROFILEBCwdetermined asa function ofweathering ofindividual soilminerals and fieldbased soil and bioticconditionshighhighmedium - high; may haverestrictions in desertregions and areas thatare lacking necessarydata; also must be ableto characterizecatchment summaryvalues and not solelyindividual profilesmedium - high; may haverestrictions in desertregions and areas thatare lacking necessarydataWarfvinge andSverdrup, 1992 and1995; Sverdrup, 1990Appendix B

March 2010 27 Draft – Do Not Quote or Cite 3.3 Proposed Methodology for Estimating and Mapping Base Cation Weathering for Aquatic Critical Acid Load Calculations 1

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31 32 In determining the proposed methodology fo r a national assessme nt, the identified strengths and weaknesses of each approach in the previous section had to be weighed against one another. Because every method required a larg e environmental data component, the largest deciding factor in the proposed approach b ecame the number and spat ial representation of previous applications of an approach within the United States. This decision fact or immediately ruled out applying any of the empirical re lationships (e.g. F-factor, relation of BC w to stream chemistry) derived primarily with data from ot her countries, although it di d not rule out deriving new relationships using the same methods. Ultimat ely, the F-factor approach was not chosen because it did not directly provide a BC w rate. Additionally, applicati on of an empirical relation alone provided little informa tion on the long-term versus current state of the ecosystem. Therefore, a combination of a process-based model determination of BC w rates with regional expansion of these rates through empirical re lations is proposed at the methodology for a
national assessment. Utilizing a process-based model, which can calibrate BC w rates to stream or lake chemistry across any number of years, provi des a credible long-term estimate of the BC w rate that can be input into the SSWC in order to ob tain the system critical load. The process-based model most widely applied throughout the U.S. to date is the MAGIC model. The intermediate complexity of this model provides a balance betw een data inputs required to run the model and the processes involving base ca tions, nitrogen, and sulfur w ithin a watershed, which is considered a requirement of providing a natio nal assessment. Finally, because of its wide application, MAGIC has been extensively tested against independent da tabases providing the opportunity for iterative model testin g and refinement (Sullivan, 2000). The following steps outline the main processes of the method:
Step 1. Definition of MAGIC study sites and the regions to which each grouping of study sites may be extrapolated. Step 2. Data gathering and processing for population of the MAGIC model for each study site with additional re gional data gathering of available stream/lake chemistry and landscape parameters. Step 3. MAGIC modeling application on selected stream/lake study sites where BC w is arrived at through calibrati on against water chemistry data.Appendix B

March 2010 28 Draft – Do Not Quote or Cite Step 4. Extrapolation of BC w for modeled streams/lakes to other waterbodies within the region through correlation an alysis using stream chemistry data, where available, and landscape parameters in its absence. 1 2 3

4 Figure 3-1 provides a flow chart of thes e steps and their components.

I n p u t D a t a C l a s s e s Identification of input data for the MAGIC model and of stream chemistry and landscape parameters

Stream Chemistry Soil Composition Atmospheric Deposition (including annual

precipitation)

Construct Model Input Tables

MAGIC Application at Study Sites with Calibration to Water Chemistry for BCw

Correlation Analysis between Site BCw Values and Stream Chemistry or Landscape Parameters

Mapping of BCw Values Across Regions of the Nation 2

3 Identification MAGIC study sites and applicable regions for extrapolation 1

Catchment/ Landscape Properties

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Application of Regional Regression Relationships

Developed by Site Grouping to Un-Modeled Sites

5 6 7 Figure 3-1. Process steps for estimating BC w using the MAGIC model with regional extrapolationAppendix B

March 2010 29 Draft – Do Not Quote or Cite Step 1. Definition of MAGIC study sites and the regions to which each grouping of study sites may be extrapolated. 1 2

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11 MAGIC has been used to assess acidification impacts in a large num ber of areas across North America ( Table 3-2 ). These previous applications should be utilized where possible to provide a starting point for the national analysis . Sites within the eastern United States likely provide a wide range of coverage from which initial extrapolations can begin. Within the midwest and western areas of the country, additional sites will need to be investigated. Authors of
these studies should be contacted to obtain da ta sources and model results. Previous model applications should be compared for the years an d objectives of the analysis and input data to determine if the results already created could be utilized in an extrapol ation analysis without rerunning the model.

Table 3-2. Locations of Previous MAGIC Applications within the U.S. and Canada 1
Location(s) Reference 25 lakes in south-central Ontario, Canada Aherne, J, P.J. Dillon, and B.J. Cosby. 2003. 2 catchments located in Nova Scotia, Canada De nnis, I.F., T.A. Clair, and B.J. Cosby. 2005 Maryland Ellis, H., and M. Bowman. 1994. 36 lake catchments in the Adirondack Mountains of New York Church, M.R. and J. Van Sickle. 1999.

40 to 50 sites within each of three physiographic provinces in the eight-state southern Appalachian Mountains region Sullivan, T.J., B.J. Cosby, A.T. Herlihy, J.R. Webb, A.J. Bulger, K.U. Snyder, P.F. Brewer, E.H. Gilbert, and D.L. Moore. 2004. 33 representative watersheds in the Adirondacks Sinha, R., M.J. Small, P.F. Ryan, T.J. Sullivan, and B.J. Cosby. 1998.
Shenandoah National Park Bulger, A. J; Dolloff, C. A.; Cosby, B. J.; Eshleman, K. N.; Webb, J. R., and Galloway, J. N. 1995 60 Southern Appalachian streams Bulger AJ, Cosby BJ, Webb JR. 2000. Joyce Kilmer And Shining Rock Wilderness Areas (North Carolina/Tennessee) Sullivan, T.J. and B.J. Cosby. 2002
Monongahela National Forest, West Virginia Sullivan, T.J. and B.J. Cosby. 2004 Shasta Lake, Idaho Eilers J.M., B.J. Cosby, J.A. Bernet, T.A. Sullivan, 1998. Libby Lake, Montana Bernett, J.A., Eilers J.M., B.J. Cosby. 1997. Popo Agie Wilderness, WY, and Weminuche Wilderness, CO Sullivan, T.J., Cosby, B.J ., Bernert, J.A., and Eilers, J.M. 1998. Rocky Mountain, Grand Teton, Sequoia, and Mount Rainier National Parks Cosby and Sullivan. 2001

The Loch, a subalpine lake in Rocky Mountain National Park in Colorado Sullivan, T.J., B.J. Cosby, K.A. Tonnessen, and D.W. Clow. 2005. 2 locations in the Sierra Nevadas Sullivan and Eilers, 1996

1 References from this table are presented in Appendix 2.Appendix B

March 2010 30 Draft – Do Not Quote or Cite When selecting sites for MAGIC analyses that will later be used in an extrapolation analysis, Sullivan and colleagues (20 04) outlined two key considerations: 1

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31 1. Do not select too many watersheds for modeling that occurred in the same general area in order to avoid skewing the results t oo heavily to one por tion of the region for the following extrapolation step
2. Screen sites to remove those in which the water chemistry data were not internally
consistent or for which available data suggested the possibil ity of significant influence from road salt, geological sulf ur, land use, or insect defoliation.
Step 2. Data gathering and processing for population of the MAGIC model for each study site with additional re gional data gathering of available stream/lake chemistry and landscape parameters. The data requirements of the MAGIC model are summarized in Table 3-3 . The table includes both data inputs derived from monitoring data and consta nt parameters that the user
must set based on available data and methods suggested by previous MAGIC applications. Additional information on data inputs can be found in: Cosby and colleagues, 1985a; Cosby et al., 1985b; Sullivan and Cosby, 2004; Sullivan et al., 2007c. Due to the wide range of water quality m onitoring assessments conducted within the United States, a large amount of water quality data is typically available to work from. Similarly,
in recent times advances a nd expansions of atmospheric modeling have been conducted providing a large amount of deposition estimates fr om which to pull model input data. The area of data most lacking, especially in the wester n United States, is the composition of soils. Sources
of soil data are discussed in Sect ion 4.3.3. Given that there may be areas in which soils data are not available, work by Sullivan and others used a tiered assessment of MAGIC applications to overcome this obstacle. The tiers consisted of: (1) chemistry data were available from within the watershed to be modeled with multiple soil sampli ng sites in an individual watershed aggregated on an area-weighted basis; (2) so ils data within the catchment were missing but were available from a nearby watershed underlain by similar geol ogy; and (3) soils data were neither available from within the watershed nor from nearby wate rsheds on similar geology. In order to populate soil characteristics for tier 2 and 3 watersheds, a surrogate approach was used meaning that these watersheds were paired with a wa tershed for which all input data we re available. In order to be paired, watersheds had to have similar streamwater characteristics (ANC, sulfate, and base cationAppendix B

March 2010 31 Draft – Do Not Quote or Cite concentrations), physical char acterization (location, eleva tion), and bedrock geology data (Sullivan et al., 2004). 1

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Table 3-3 . Input Data Requirements of MAGIC Model

Data Class Data Element Measure

Catchment Area Relative area of lake/stream fraction

Stream Chemistry pH unitless ANC eq/L Ca 2 + eq/L Mg 2 + eq/L K + eq/L Na + eq/L SO 4 2

- eq/L NO 3 - eq/L Cl - eq/L Aluminum solubility constant log 10 Slope of pH-pAl relationship unitless

Aqueous Phase - Equilibrium Constants Organic acid log 10 Organic aluminum Inorganic aluminum speciation Inorganic carbon speciation and dissociation of water
Solid Phase – Weathering and Exchange Constants Cation exchange selectivity coefficients log 10 Weathering rates (Ca 2 + , Mg 2 + , K +

, NH 4 , SO 4 2- , Cl - , NO 3 - , F) eq/m 2 /yr

Soil Composition Thickness Depth (m) Total cation exchange capacity eq/kg Exchangeable bases (Ca 2 + , Mg 2 +

, K + , and Na + ) mg/kg
Bulk Density kg/m 3 Porosity fraction pH unitless Sulfate adsorption half saturation eq/m 3 Aluminum solubility constant log 10 Slope of pH-pAl relationship unitless

Atmospheric Deposition Annual precipitation Volume (m/yr) Ca 2 + Total annual deposition (eq/ha/yr) Mg 2 + K + Na + SO 4 2

- NH 4 NO 3 - Cl 3Appendix B

March 2010 32 Draft – Do Not Quote or Cite Step 3. MAGIC modeling application on selected stream/lake study sites where BC w is arrived at through calibrati on against water chemistry data. 1 2

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31 As was completed with the REA (U.S. EPA, 2009), batch processi ng of MAGIC models at a range of sites can be completed. Calibration of those sites with available data (streamwater chemistry, soil chemical and physical characteristics, and atmospheric deposition) is completed by setting values of the “fixed parameters” with in the system and comparing the output of the
model run to the observed values of such ch aracteristics as stream ANC. There are eight parameters optimized through this method including the BC w rate. The eight observations used to drive the calibration pro cedure include the current soil exchang eable pool size and current output
flux of each of the four base cations. The m odel is iteratively run adjusting the “fixed parameters” from a specified range of values (r epresenting uncertainty in knowledge of these parameters), so that the outputs match the obser ved parameters within an acceptable margin of error. The set of “fixed parameters” that ar e obtained that allow the model to meet this acceptable of margin of error become the range of calibrated parameters from which the median is chosen to represent the parameter value for th e watershed. “The use of median values assures that the simulated responses approximate the most likely behavior of each watershed, given the assumptions inherent in the model and the data used to constrain and calibrate the model” (Sullivan et al., 2004). This “fuzzy optimization” procedure has been developed for use with MAGIC modeling to help quantify the uncertainties within the modeled parameters (Sullivan et al., 2004). Using these calibration procedures of e ach site MAGIC run will provide not only an
estimate of BC w but an expected range of values in which BC w falls, thereby providing bounds and certainty limits for the following extrapolation step.
Step 4. Extrapolation of BC w for modeled streams/lakes to other waterbodies within the region through correlation an alysis using stream chemistry data, where available, and landscape parameters in its absence. Regionalization of MAGIC modeling results can be completed through either “binning” sites based on characteristics like physiographic region and ANC concentra tion (Sullivan et al., 2004) or creating regional re gressions to relate site characteris tics (chemistry or landscape) to a parameter of interest (e.g., ANC; Sullivan et al., 2007a). In order to provide some measure of “goodness of fit” to the extrapolations, we have chosen to proceed w ith creating regression relationships between the BC w determined through calibration of the MAGIC model and eitherAppendix B

March 2010 33 Draft – Do Not Quote or Cite water chemistry or landscape parameters. In previous studies, the landscap e variables considered for regression relationships with ANC have in cluded elevation, watershed area, ecoregion, lithology, forest type and geological sensitivity class (Sullivan et al., 2007b). We expect to
follow similar methods to create the relations with BC w (i.e., the response variable). Within each region of extrapolation landscape variables appropriate to the region will be selected. For example, the types of forest selected for incl usion may vary between an extrapolation in the Southern Appalachians as opposed to the Rocky Mountains. In all instances, there must be adequate representation of the va riable within all m odeled and non-modeled watersheds or it will be eliminated from the pool of candidate va riables available for re gression analysis. 1

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31 Sullivan and others (2007b) relied on the co rrected Aikake’s Information Criteria (AIC) to evaluate all possible correlation relations. The corrected version of the evaluation criteria was used because of the relatively small sample sizes available from which to build the regressions. Additional evaluation criteria can easily be applied for choosing the best-fitting and most meaningful regressions for extrapolation from a set of individual modeled sites to a larger set of regional sites. Potential criteria for evaluati ng individual variables wi thin correlation models include partial F tests, t-values, and variance inflation factors. To evaluate the model as a whole statistics such as PRESS, coefficient of determ ination, adjusted coefficient of determination, Mallow’s Cp, and root mean square error of th e model can all be utili zed (Helsel and Hirsch, 1992). If a commercial statis tical package, such as SAS, is chosen to complete this portion of the analysis the predefined routines and groupings of evaluation statistics can be employed with
relative ease.
3.3.1 Potential limitations of proposed methodology The limitations with the proposed methodology can be divided into five distinct categories:
1. MAGIC is an intermediate level model that does not take into account biotic processes which may affect the calculation of BC w rates within a watershed.
2. While MAGIC is the most widely applied ac idification model with in the U.S. it still faces the challenge of having limited applic ations in the Midwest and western states.
3. As an extension of the bias in eastern a pplications, processing and organization of the data required for input into the MAGIC m odel in the East far exceeds that of the West. Additionally, there is an indication that soils data are more incomplete or hardAppendix B

March 2010 34 Draft – Do Not Quote or Cite to obtain in the West. Note that the terrest rial acidification national assessment faces even greater demands in terms of soil composition data needs. As such, there can be a combined effort in obtaining new data that will benefit both assessments. 1

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31 4. The population and calibration of specific si te applications of MAGIC across the country constitutes a major modeling effort. However, it may be possible to leverage previous applications.
5. The proposed approach calls for the cr eation of several different regional extrapolations of BC w rates based on sets of individual MAGIC applications. The success of these extrapolations remains to be seen and will depend upon the limitations mentioned above in even appl ying the MAGIC model at a multitude of locations and upon the availability of a statistically signifi cant number of model outcomes on which to base the regressions for each regional analysis. While these limitations may seem extensive, there are many possibilities for overcoming the limitations. For example, criteria on model a pplication years can be relaxed to include more of the previously completed MAGIC applications in lieu of updating and rerunning models at the same sites. And, joint data collection between the aquatic and terrestrial acidification
assessments can allow the most efficient use of resources and demands on other agencies. 3.3.2 Uncertainty analyses As typical with any process based model, the major uncertainties in MAGIC include input data variability, model ca libration uncertainty, and the ability of the mathematical model processes to represent reality. Within this na tional analysis, there will also be uncertainty associated with regional extrap olation of modeling results from individual watersheds to the region. However, Sullivan and colleagues (2004) st ate that these “errors and uncertainties are not additive, but rather would be expected to some extent to cancel each other out.” Several research projects have undertaken a ttempts to quantify the relative magnitude of the effects of sources of uncertainty for regi onal, long-term MAGIC si mulations using Monte Carlo methods (Cosby et al., 1989b, 1989c, 1990; Hornberger et al., 1989, 1990). While the
results of these studies indicated that the differen t sources of uncertainty can have varying levels of impacts on the outputs of the MAGIC model, the development of the “fuzzy optimization” technique for calibration was de signed to reduce these impacts of uncertainty. With “fuzzy optimization” there is an explicit accounting within different uncertainty categories and aAppendix B

March 2010 35 Draft – Do Not Quote or Cite resulting time-variable measure of overall simulation uncertainty for each state variable. One way the optimization procedure redu ces uncertainty is in its selection of parameter and variable values for the “fixed parameters” from distributi ons of possible values ra ther than having a user select a single value during a single calibration (Sullivan et al., 2004). 1

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30 Outside of the operation and calibration of the MAGIC model, the parameterization of the input data provides another sour ce of uncertainty. As identified in previous sections, the soils composition data are expected to be the greatest source of uncerta inty. If a tiered approach to populating soils data for watersheds lacking in data is used, uncer tainty with the method can be examined by calibrating selected tier 1 watersheds twice, once using the a ppropriate site-specific soils data, and a second time using borrowed soils da ta from an alternate s ite, using either tier 2 or tier 3 protocols. A comparison between the results from each of the scenarios can then be made to determine the magnitude of difference in output parameters. If this analysis can be done at multiple sites, than a sensitivity analysis can be performed over the results to determine if
there is a consistent bias in results from mode ling analyses utilizing ti er 2 or 3 procedures (Sullivan et al., 2004).

4. TERRESTRIAL BASE CATION WEATHERING METHODOLOGY

4.1 Introduction Geology is one of the most important factors in determining the potential sensitivity of an
area to terrestrial acidif ication (U.S. EPA, 2008, Section 3.2.4) . In particular, the characteristics of the soils and the upper portion of the bedrock can impact the acid-neutralizing ability of the soils in a particular area. Acid-sensitive soils ar e those which contain low levels of exchangeable base cations and low base saturation (U.S. EP A, 2008, Section 3.2.4). Bedrock composition and soil pH are two characteristics that are directly related to the ab ility of a system to neutralize acid. Soils overlying bedrock, such as calcium car bonate (e.g., limestone), which is reactive with acid, are more likely to successfully neutra lize acidifying depositi on than soils overlying nonreactive bedrock. In addition, soils with high er pH (i.e., more alka line) have a greater capacity to neutralize ac idifying deposition.
This section reviews the e ffect of acidification known as base cation weathering, describes its significance in es timating critical acid loads, and identifies methodologies for estimating base cation weathering. Further, th is report recommends a methodology for potentialAppendix B

March 2010 36 Draft – Do Not Quote or Cite use in the review of the NO x and SO x secondary National Ambient Air Quality Standards and describes the steps and information resources needed to apply that methodology across the
United States. 1

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29 4.2 Terrestrial Base Cation Weathering In the calculation of terrestrial critical acid loads using the simple mass balance (SMB) methodology, base cation weathering (BC w ) 2 is defined as “the release of base cations from
minerals in the soil matrix due to chemical dissolution” (UNECE, 2004) , and this weathering occurs in the rooting zone of the soil profile and consists of the release of calcium (Ca 2+ ), magnesium (Mg 2+ ), potassium (K + ) and sodium (Na + ). It does not include the removal of base cations from soil ion exchange complexes (cation exchange sites) or the degradation of soil organic matter. Base cations from these sour ces have already been released through the weathering process. Base cation we athering is often a dominant sour ce of base cations in soils, replacing Ca 2+ , Mg 2+ , K + and Na + that are lost through leaching and uptake by plant (Langan et al., 1995; Langan et al., 1996; Ouimet, 2008). Therefore, BC w plays an important role in determining the sensitivity of a site to acidi fying nitrogen and sulf ur deposition (Hodson and Langan 1999a). The BC w term is also one of the most influential parameters in the SMB
calculations of terrestrial critical acid loads. Li and McNulty ( 2007) determined that 49% of the variability in critical load estimates was due to this term . Sverdrup and colleagues (1995) (reference in Langan et al., 1996) determined that BC w can account for 90% of the variation in
critical loads. For the Terrestrial Acidification case study in the Risk and Exposure Assessment (U.S. EPA, 2009), BC w rates were calculated using the clay-s ubstrate method (McNulty et al., 2007). This method was selected for the Risk and Exposure Assessment because it is one of the most commonly used methods to estimate BC w for critical load analyses in North America (Ouimet et al., 2006; Watmough et al., 2006; Mc Nulty et al., 2007; Pardo and Duarte, 2007), and has been used to map critical loads acr oss the United States (McNulty et al., 2007). However, the applicability of the clay-substrate method is most likely limited because it is an empirical model that appears to be based on a modification of th e soil type – texture a pproximation method that was developed on a restricted number sites in northe rn Europe that were glaciated during the last

2 Within the SMB equation, Bc w refers to the weathering of Ca 2+ , Mg 2+ and K +

.Appendix B

March 2010 37 Draft – Do Not Quote or Cite glacial advance (CLAD, 2009; H. Sverdrup personal communication, 2009a, UNECE, 2004). It relies on a classification of the acidity of soil pare nt material and soil clay content and consists of three equations (equations 4-1 – 4-34). 1

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Acid Substrate: 

## ( ) ( ) 

# ( ) 2

e clay%32.0clay%7.56BC ×−×= (4-1) 4

Intermediate Substrate: 

## ( ) ( ) 

# ( ) 2 5 e clay%18.0clay%6.53500BC ×−×+= (4-2)

Basic Substrate: 

## ( ) clay2.59 % 500BC
e × + = (4-3) 6

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BC e = empirical soil base cation (Ca 2+ + K + + Mg 2+ + Na + ) weathering rate (eq/ha/yr) % clay = the percentage of clay (determi ned by particle size) within the rooting zone of soil profile.

Critical load experts from both the United States and Canada have commented that the claysubstrate model, in general, appears to perfor m well in young soils that have formed since the last glaciations (approximately 20,000 years befo re present). However, the model may not be suitable or provide accurate estimates on older, more weathered soils that were not impacted by the last glaciation (P. Arp personal communication, 2009). These soils have undergone weathering for a longer period of time and the rela tionships between clay particle size and base cation release may not be as str ong as in younger soils (H. Sverdrup personal communication, 2009a). To our knowledge, however, there have been no published studies that have tested this hypothesis and compared BC w estimates generated with the clay-substrate model and other methods on sites underlain by old, more weathered and recently glaciated soils. At least one study has compared the clay-substrate BC w method with estimates from other models on glaciated soils in Canada and found that the rate estimates we re similar with in the area of assessment (Whitfield et al., 2006). Results from the Risk and Exposure Assessm ent (U.S. EPA, 2009) appear to support the distinction between the suitability of applying the clay-substrate m odel to glaciated versus older, non-glaciated soil environments. As outlined in Appendix 5 of the Risk and ExposureAppendix B

March 2010 38 Draft – Do Not Quote or Cite Assessment, the regression analysis assessing the relationship between the growth of sugar maple ( Acer saccharum ) and critical acid load exceedance was not significant (p=0.38) when all plots were included in the analysis . However, when the analyses we re restricted to sites located on younger, glaciated soils, which re sulted in the removal of 25% of the data from the analyses, the linear regression relationshi p was significant at the p=0.10 level. Improvements in the significance of the relations hip may, in part, have been due to the greater accuracy of the BC w estimates in the critical load calculations fo r the plots north of the glaciations line. 1

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20 The majority of the conterminous United Stat es was not directly impacted by the most recent glacial advance ( Figure 4-1 ) and some of the soils in these areas have not been influenced by glaciations in at least 700,000 y ears (Sverdrup et al., 1992). Only ten states had their full land area impacted by glaciers during th e glacial advance 20,000 years ago. Therefore, if the concerns and supportive results regarding the suitability of the clay-substrate model for the estimation of
BC w on older, non-recently-glaciated soils are co rrect, the model may not be an appropriate
method to estimate BC w for a large portion of the United States. Given that the BC w parameter is one of the most influential variables within the SMB calculations to estimate critical acid loads, it is particularly important to use a method that provides accurate and defendable estimates of
BC w . Therefore, any and all future work focused on estimating and mapping terrestrial critical acid loads in the United States, should acknowledge the potential limitations of the clay-substrate
model and consider the adoption of a BC w modeling approach that is transferable and can be applied to multiple locations and diffe rent soil conditions and soil ages.Appendix B

March 2010 39 Draft – Do Not Quote or Cite 1 2 3

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13 Figure 4-1 . Areas of continental U.S. that were covered during the last glacial event (Reed and Bush, 2005). 4.3 Methodologies for Determining Base Cation Weathering Values in the United States 4.3.1 Difficulties in estimating base cation weathering Base cation weathering is one of the most di fficult parameters to estimate (Sverdrup et al., 1990; Ouimet and Duchesne, 2005; Langan et al., 1996), as it is a function of a time, soil mineralogy, and a variety of other environmental biotic and abiotic factors. Weathering occurs
over centuries and millenia and results in the chemi cal and physical alterations of parent material and minerals. Minerals that are present in the soil may no longer resemble the original bedrock parent material (C. Smith personal communication, 2009). In addition, the soil may be derived from parent material that was transported to its current location and does not resemble the underlying bedrock. Abiotic fact ors including temperature and moisture and location on theAppendix B

March 2010 40 Draft – Do Not Quote or Cite landscape and biotic factors including vegetation and soil microbes can also impact base cation weathering through removal of base cations and chemical weathering of minerals (Brady and Weil, 2002). Combined, these factors pos e many challenges to determining BC w in the soil profile for terrestrial critical acid load estimations. As a result, a variety of BC w methods and approaches have been deve loped (Sverdrup et al., 1990). 1

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Methods and models that have been developed to estimate BC w for critical acid load determinations differ significantly in the appr oaches used to generate weathering estimates (Langan et al., 1995; Sverdrup et al., 1990; UNECE, 2004). For th e purposes of this work assignment, BC w methods and models are grouped into three main approaches: 1. budget studies of catchments or watersheds; 2. historical weathering ra te determinations; and 3. empirical and mathematical models. Each of these approaches vary in complexity, data intensity and scalab ility, thereby offering different strengths and w eaknesses to estimating BC w . In addition, these approaches differ in their abilities to map BC w over regional and larger land areas. Table 4-1 provides a summary of the approaches to BC w , critical load models that use the approaches, the strengths and
weaknesses of the different models , and the suitability of the a pproaches and models to map BC w and therefore critical lo ads over large areas. For a model to be suitable for large-scale mapping, it must be quick to apply, supported by existing databases, not require extensive and costly analyses, and be transferable to sites with varying conditions a nd geological histories (Sverdrup et al., 1990). Budget Studies - The budget study approach, also refe rred to as input- output balances (Kolka et al., 1996; Lang an et al., 1996; Starr et al., 1998), estimates BC w as a component of the mass balance input and output of cations within a catchment or watershed (Langan et al., 1996; Sverdrup et al., 1990; Sver drup et al., 1998). In most catchments, the main source of input is atmospheric deposition and output is streamflow, and base ca tion retention is accounted for through uptake by biomass and immobilization in th e soil. Base cation we athering is therefore determined through mass balance differences betw een these different input, output and storage pools. The main strengths of this method are that it only requir es a moderate amount of input
data and relies on data collected from the catchment or watershe d. In addition, it offers the 23

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March 2010 41 Draft – Do Not Quote or Cite potential for mapping multiple catchments, if the necessary input data is available. However,
several of the drawbacks to this method include an assumption that the catchment is in a steadystate condition and the cation exch ange capacity does not change over time (Langan et al., 1996; Miller, 2001; Sverdrup et al., 1998). In addi tion, it is often difficult to determine BC w within the rooting zone of individual soil profiles because the BC w estimates from budget studies represent integrated values for the whole watershed, the full soil profile, bedroc k weathering and all soil processes (Sverdrup and Warfvi nge 1988; Miller, 2001). It is also difficult to separate contributions of base cations from exchange sites versus mineral weathering and chemical dissolution (Sverdrup et al., 1990; Miller, 2001). Therefore, it is challenging, and potentially erroneous, to use budget studies of catchments to estimate BC w for terrestrial critical acid loads. It may be possible to modify the budget study approach and evaluate base cation input and output in the rooting zone of indi vidual soil profiles (Kolka et al., 1996), and to separate base cations from exchanges soil pool versus weathering sources using techniques such as the analysis of strontium (Sr) isotope ratios (Miller et al., 1993). However, the soil profile approach would require lysimeter measurements of soil solution ch emistry at each site and the soil solution would also need to be analyzed for Sr isotope ratios ( 87 Sr/ 86 Sr). Both of these analyses would be very time intensive and would not be practical over large areas. 1

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17 Historical Rate Determinations – The historical weathering rate approach, also sometimes referred to as element depletion (Lan gan et al., 1996; Miller , 2001) or pedological mass balance (PMB) (Ouimet and Duchesne, 2005; Ouimet, 2008), estimates BC w by determining the relative depleti on of base cations to the deplet ion of a stable element as a function of the age of the soil pr ofile (Langan et al., 1996). Zircon ium (Zr), titanium (Ti), rutile and sometimes quartz are typically selected as the stable soil elements for this method (Langan et al., 1996; Sverdrup et al., 1998) beca use they are very resistant to weathering (Starr et al., 1998). This technique is commonly applied to soils th at were formed since th e last glaciation, and
characterizes the ratio of base cations to the stable element in the upper weathered soil horizons and the unweathered C horizon. It assumes that pos t glaciation, the mineral matrix of the soil consisted of freshly ground materi al that was not previously expos ed to weathering (Sverdrup et al., 1998), the lowermost soil is repr esentative of the parent materi al and the stable element is found in a constant proportion th roughout the soil profile (Langan et al., 1996; Star r et al., 1998). Over time, base cations are weathered and lost from the profile through uptake and leaching, but 18

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31Appendix B

March 2010 42 Draft – Do Not Quote or Cite the concentration of the stable element remains cons tant due to resistance to weathering (Starr et al., 1998). Main strengths of this approach are that it is a good technique to estimate weathering in young soils, does not require a large amount of data and BC w is relatively easy to calculate. However, this approach also presents some major weaknesses. It estimates the historic BC w rate which may be differ from the current weathe ring rate. Historic weathering rates may
underestimate current BC w because the historical weatheri ng occurred under more neutral conditions with less acidifying deposition (Sve rdrup et al., 1990). Conversely, historic weathering rates may be higher than current BC w if the original post glaciations soil contained a significant proportion of easily weat hered material that have sin ce been depleted (Miller, 2001).
Studies have indicated that th e initial phase of weathering lasts a few hundred to several thousand years and can deplete a maximum of 25 % of the mass during this period (Sverdrup et al., 1998). In addition, the historic rate approach is not suitable fo r older, more weathered soils. In such soils, it is often difficult to determine the amount of time since the last glacial or mass
disturbance event that caused the forma tion of newly ground material (H. Sverdrup personal communication, 2009b). Therefore, this method cannot be app lied to all locations and it is often difficult or impossible to extrapol ate results to larger geographical areas. Since a large proportion
of the soils in the United States were not influe nced by the most recent glaciation, the historic rate approach to estimate BC w for terrestrial critical acid load estimates could only be applied to
a fraction of the land area. 1

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19 Empirical and Mathematical Models – Empirical and mathematical models estimate BC w based on laboratory- and field-base d relationships between soil, abio tic and biotic factors. Over the past several decades , a large number of BC w models have been developed for terrestrial
critical acid load determinations. Initial mode ls were developed from a limited number of sites and data. More recent models incorporate a larg er number of factors and are more complex and
data intensive. One of the first BC w models was the Skokloster Assignment which is a semiempirical method that was devised during the Cri tical Load Workshop in Skokloster, Sweden in 1988 (UNECE, 2004). It divides minerals into 5-6 mineral classes based on the dominant weatherable soil minerals and assigns a range of critical acid loads to each. This method was later expanded to include a larger range of minerals and to estimate BC w based on the relative abundance of fast versus slow weathering minera ls. The Skokloster Assignment was originally based on soils with density, moisture content, cl ay content and pH conditions similar to the soils 20

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March 2010 43 Draft – Do Not Quote or Cite in the three Gårdsjön catchments in Sweden, and was validated against a preliminary version of the PROFILE model, described further below (Hodson and Langan 1999b; H. Sverdrup personal communication, 2009b). 1

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31 A second model, the Soil Type – Texture A pproximation assigns weathering rate classes to soils based on soil texture and parent material acidity classes. It was developed for European forest soils (UNECE, 2004). As described earlier, it is believed that the clay-substrate model that is used extensively throughout North America was derived from the Soil Type – Texture Approximation. A third model, the Total Base Cation Conten t Correlation was developed using Zr(SiO4) and historical rate approach applied to eleven sites in Sweden (UNECE, 2004). Correlation
between historical BC w rates and the total content of base cations in the undisturbed bottom soil, corrected for temperature, were used to deve lop equations to estimate the weathering of Ca 2+ , K + and Mg +2 ( Olsson et al., 1993). For a more complete review and description of these three empirical models see Hodson and Langan (1999) and UNECE (2004). In general, the main benefits of these models are the minimal data requirements, transferability, and the potential to be applied to multiple sites. Therefore, su ch models offer good options for mapping of BC w for critical acid load determinations. However, these models also have several key weaknesses which limit their utility for estimating BC w in many locations, includi ng a large proportion of the United States. All of the models were determined using data from a limited number of sites within Sweden and other regions of Europe and are based on average or generalized relationships. Therefore, similar to the clay-s ubstrate model, these models may do a reasonable job of estimating BC w on sites that were recently glaciated and/or have similar conditions to the Swedish sites. However, they should not be a pplied everywhere, as they may poorly estimate
BC w on sites with older, more weathered soils. As stated for Total Base Cation Content Correlation, the method is only applicable to granitic soils (Hodson and Langan, 1999) and
should be used with caution because the relati onships are based on Nord ic geological history (UNECE, 2004). A fourth model that supported the creation of some of the aforementioned empirical BC w models, and is currently in its 5 th version is PROFILE (Warfvinge and Sverdrup 1992 and 1995; Sverdrup, 1990). PROFILE (version 5.0) is a m echanistic, mathematical, steady-state, kinetics
model that calculates the weathering of Ca 2+ , Mg 2+ , and K + in each horizon of a soil profileAppendix B

March 2010 44 Draft – Do Not Quote or Cite (Akselsson et al., 2005). It is unique and differs from other empi rical models in that it calculates
BC w rates for soil from independently measured ge ochemistry and soil conditions (Jönsson et al., 1995; Ouimet and Duschesne 2005). It combines laboratory-based evaluations of mineralspecific chemical dissolution with field-base d conditions and other soil measurements to
estimate individual w eathering rates of Ca 2+ , Mg 2+ , and K + (Langan et al., 1996). The model includes 14 of the most common prim ary and secondary soil minerals ( Table 4-2 ) 1

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release of base cations in fi ve separate reactions (Sverdr up et al., 1990; H odson et al., 1997; Sverdrup et al., 1998): i) Reaction with hydrogen ion (H + ) and dissolved aluminum (Al)

ii) Reaction with water and dissolved Al

iii) Reaction with hydroxyl ion (OH - ) and dissolved Al

iv) Reaction with carbon dioxide (CO 2 )

v) Reaction with strongly complexi ng polydentate organic acids

The reaction rates are calculated using constants contained within the model and data input by the user, and the total base cati on release rate by chemical weathe ring is calculated as the sum of all parallel simultaneous process rates minus the rate of precipitation of secondary solid phases (Sverdrup et al., 1998). The rate equation (Equation 4-4) for th e weathering of all minerals within the rooting zone of the soil profile is defined as:

RW = Σ (horizons) Σ (minerals) i r i · A exp · x i · θ · z (4-4)

where

r i = dissolution rate of mineral i (kmol c /m 2 /s) – sum of the 5 separate reactions

A exp = exposed surface of mineral matrix (m 2 /m 3 )

θ

= soil moisture saturation (m 3 /m 3 )

3 Thirteen additional minerals can be adde d to PROFILE, as necessary (H. Sverdrup personal communication ).Appendix B

March 2010 45 Draft – Do Not Quote or Cite x i = fraction of mineral i in the mineral matrix of the soil horizon 1

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The weathering rate is either increased or reduced by differen t soil and biotic and abiotic conditions, many of which are entere d as input data by the user. Input data includes site climatic and deposition attributes, soil physical and chem ical characteristics a nd biological components that influence the soil chemistry and BC w (input data required by PROFILE discussed further in Section 4.3.3). As summarized by Jönsson a nd colleagues (1995), “The weathering rate is increased by a high H + concentration, a high soil moistu re (water) content, and a high CO 2 pressure. Weathering reactions ar e product inhibited, i.e., decreas e by high concentrations of reaction products in the soil solution such as inorganic aluminum and base cations. The surface activity is calculated as dependent on the mine ral surface area, temperature and soil moisture saturation. The soil temperature impact on the we athering rate is expressed as an Arrhenius equation, as dependent on the ac tivation energy. The soil moisture saturation is important for the reaction rate as the reactions will only ta ke place on wetted surfaces. The degree of surface wetting, and thus surface activity, is considered to be a function of the soil moisture saturation. This is calculated from soil bulk density, the solid particle density and the volumetric water content.” For a more detailed description of th e theory and calculations behind PROFILE, see Sverdrup (1990), Sverdrup and Warfvinge (1992, 1993a, 1995).
A main weakness of the PROFILE model is that it is data intensive and complex, and can be difficult to parameterize. However, PROFILE doe s offer some significant benefits that set it apart from the other models. As described, it determines current BC w rates from laboratoryderived weathering rates of indivi dual minerals and therefore is not bound to data from a specific location or region. Therefore, it can be used to determine and map BC w over large areas (Miller et al., 1993). Although it was developed in Swed en, it has been successfully applied to the mapping of BC w and critical loads in th e Northeastern United States, Maryland, Minnesota, Pennsylvania, Thailand, China, Argentina, a nd Greece (Duan et al., 2002; Miller, 2001; Sverdrup et al., 1992; H. Sverdrup personal communication, 2009b).Appendix BTable 4-1. Review of modeling approaches (and models) to estimate base cation weathering for terrestrial critical acid load determinations.Model ApproachDescription ofMethodData RequirementsModel ComplexitySuitability forEstimating BCwforTerrestrial Critical AcidLoad Determinations inThe United StatesSuitability forMapping BCwOver LargeRegions in TheUnited StatesReferencesBudget Studiesmass balance of inputsand outputs of basecations withincatchment, watershedor soil profilemediummediumlow; BCw estimate is oftenan integrated value forwhole catchment orwatershedlow - medium(based on dataavailability); mayrequire Srisotope ratio ofstream chemistryto separateexchangeableversusweathered basecation sourcesSverdrup et al.,1998; Sverdrup etal., 1990Historical RateDeterminationsloss of base cations insoil profile relative tostable element (Zr, Ti,quartz or rutile)lowlowmedium; restricted to siteswith young soils of knownage (e.g., soils that haveformed since the mostrecent glacial event,~20,000 years ago)low; restricted tosites with youngsoils and siteswhere historicalratedeterminationshave beenconductedSverdrup et al.,1998; Sverdrup etal., 1990EmpiricalModelsmodeled relationshipsbetween soil attributesand abiotic and bioticsite conditionslow - highlow - highlow - highlow - highMarch 201046Draft – Do Not Quote or CiteAppendix BMarch 201047Draft – Do Not Quote or CiteModel ApproachDescription ofMethodData RequirementsModel ComplexitySuitability forEstimating BCwforTerrestrial Critical AcidLoad Determinations inThe United StatesSuitability forMapping BCwOver LargeRegions in TheUnited StatesReferencesSkoklosterAssignmentBCwrate categoricallydetermined by relativeabundance of mineralsgrouped into 5-6weathering rateclasses; originallydeveloped for soilssimilar to those foundin the 3 Gårdsjöncatchments in Swedenlowlowlow; most accuratelyapplied to sites similar tothose where the modelwas derivedlow; mostaccuratelyapplied to sitessimilar to thosewhere the modelwas derivedUNECE, 2004;Hodson andLangan, 1999Soil Type -TextureApproximationBCwcategoricallydetermined as afunction of parentmaterial acidity andsoil texture, modifiedby temperature;developed from datafrom European forestsoilslowlowlow - medium; mostaccurately applied to sitessimilar to those where themodel was derivedlow - medium;most accuratelyapplied to sitessimilar to thosewhere the modelwas derivedUNECE, 2004;Hodson andLangan, 1999Appendix BMarch 201048Draft – Do Not Quote or CiteModel ApproachDescription ofMethodData RequirementsModel ComplexitySuitability forEstimating BCwforTerrestrial Critical AcidLoad Determinations inThe United StatesSuitability forMapping BCwOver LargeRegions in TheUnited StatesReferencesTotal BaseCation ContentCorrelationBCwdetermined bycorrelations betweenhistorical ratedeterminations (Zr)and total content ofbase cations in theundisturbed bottomsoil, corrected fortemperature; based ondata from eleven sitesin Swedenlowlowlow; restricted to sites withgranitic soils and Nordicgeological historieslow; restricted tosites with graniticsoils and NordicgeologicalhistoriesUNECE, 2004;Hodson andLangan, 1999Clay-SubstrateModelBCwdetermined byone of three equationsbased on parentmaterial acidity and %clay content; mostlikely a modification ofthe Soil Type - TextureApproximationlowlowlow - medium; mostaccurately applied to sitessimilar to those where themodel was derived (mostlikely young soils formedsince the last glaciation)low - medium;most accuratelyapplied to sitessimilar to thosewhere the modelwas derived(most likelyyoung soilsformed since thelast glaciation)original sourceunknown; Ouimet etal., 2006;Watmough et al.,2006; McNulty etal., 2007; Pardo andDuarte, 2007Appendix BMarch 201049Draft – Do Not Quote or CiteModel ApproachDescription ofMethodData RequirementsModel ComplexitySuitability forEstimating BCwforTerrestrial Critical AcidLoad Determinations inThe United StatesSuitability forMapping BCwOver LargeRegions in TheUnited StatesReferencesPROFILEBCwdetermined as afunction of weatheringof individual soilminerals and fieldbased soil and bioticconditionshighhighmedium - high; may haverestrictions in desertregions and areas that arelacking necessary datamedium - high;may haverestrictions indesert regionsand areas thatare lackingnecessary dataWarfvinge andSverdrup, 1992 and1995; Sverdrup,1990Appendix B

March 2010 50 Draft – Do Not Quote or Cite Table 4-2. The fourteen dominant minerals modeled within PROFILE

. Dominant Minerals K-Feldspar Plagioclase Albite Hornblende

Pyroxene

Epidote Garnet Biotite Muscovite Fe-Chlorite Mg-Vermiculite Apatite Kaolinite Calcite 1

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18 4.3.3 Proposed methodology for estimating a nd mapping base cation weathering for
terrestrial critical acid load calculations As has been outlined in the above review, there are multiple approaches to estimate BC w for terrestrial critical aci d loads. However, not all are suit able for both calculating and mapping
terrestrial critical acid loads throughout the United States. Such an approach has to be quick and easy to apply, be supported by available data and be easily and accurately transferable to sites within the United States that differ in soil, bi otic and abiotic propert ies and conditions. In addition, as stated by Miller ( 2001), “the most promising approach for a logically consistent estimation of the present-day weat hering rate over broad regions is the applicati on of model(s) that predict the weathering rate from first prin ciples, given detailed measurements of the soil environment and laboratory-derived rate consta nts for specific mineral weathering reactions.” Therefore, an approach that is based on soil mi neralogy and weathering of individual minerals is preferable. Of all the models that ar e currently available for determining BC w for terrestrial critical acid load determinations, PROFILE meet s these requirements and appears to be the most suitable. Methodologically, it has few lo cation restrictions and models BC w based on sitespecific mineralogy and soil and si te conditions. In addition, it has already been successfully applied in both glaciated and non-glaciated regions of the United States to estimate and map BC wAppendix B

March 2010 51 Draft – Do Not Quote or Cite and critical acid loads (Miller et al., 1993; Sverdrup et al., 1992; H. Sverdrup personal communication, 2009b ) . Although, as with all models, PR OFILE does have some weaknesses and limitations (discussed further in Section 4.3.5) that need to be acknowledged and addressed prior to application, critical lo ad experts, in general, agree th at PROFILE is the best model to date for estimating and mapping BC w rates for terrestrial critical acid load determinations in the United States (J. Aherne personal communication, 2009, J. Cosby personal communication,
2009

, J. Lynch personal communication, 2009, R. Ouimet personal communication, 2009

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20 There are two forms of PROFILE (version 5. 0) that can be used for estimating BC w : the single site application which estimates BC w for a single location or so il profile, and the regional application which PROFILE can be run for a region or conterminous areas (C. Akselsson personal communication, 2009). For mapping BC w in the conterminous United States, the regional application of the model would be applied, a nd the estimation and mapping of BC w would involve two main steps:
Step 1. Identification of input data required by PROFILE and development of spatial data layers, national databases and default values for each data element within the model Step 2. Determination of polygon layer to spatially define the BC w rates and development of continuous coverage map of calculated BC w values. These process steps are further illustrated in the flowchart presented in Figure 4-2

.Appendix B

March 2010 52 Draft – Do Not Quote or Cite 

### I n p u t D a t a C l a s s e s Identification of input data required by PROFILE to estimate BC w

Existing National-Level GIS Coverages

(see table 3a) Requires Development and Delineation of National-Level GIS Datalayers
(see table 3b) PROFILE Default Values
Requires review by user
(see table 3c)

Construct National GIS Data Layers and convert to raster format

Determine and Delineate BCw polygons

Calculate mean values for National GIS Data Layers for each BCw Polygon

Organize and Format

BCw Polygon data
as PROFILE model input file

Calculate BCw For BCw polygons 1

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1 2 Figure 4-2. Process Steps for Estimating BC w Using the PROFILE Regional ModelAppendix B

March 2010 53 Draft – Do Not Quote or Cite Step 1. Identification of input data required by PROFILE and development of spatial data layers, national databases and default values for each data element within the model 1 2 3

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12 PROFILE (version 5.0) is data in tensive and requires the user to provide or review a total of 26 soil, climatic and biological input data ( Table 4-3a-c ). In addition, to run the regional application of PROFILE, it would be necessary to have each of these data parameters available as continuous coverages. A larg e proportion of these variables are already included in existing databases in the United States and could be easily converted into continuous coverage data layers for the conterminous United States, if not curr ently available in continuous coverage format. Others, such as soil mineralogy, would need be modeled or constructed from other data. Still others may need to be represented by default values from the literature, until more unique, spatially site-specific values are determined.

Table 4-3a. Data required to estimate BC w with the regional PROFILE model (version 5.0). The data in this table must be input by the user and are currently available as a continuous coverage layers for at least a portion of the conterminous United States.

PARAMETER UNITS DESCRIPTION precipitation m/yr 30-year long-term average cation deposition kEq/ha/yr ammonium (NH 4 + ), Ca 2 + , Mg 2 + , K + , Na + , Al - wet and dry deposition anion deposition kEq/ha/yr sulphate (SO 4 2

- ), chloride (Cl - ) and nitrate (NO 3 - ) - wet and dry deposition number of soil layers # up to 5 layers (wit h the forest floor/organic layer being the first horizon) soil layer height m by layer temperature °C mean annual soil temperature by layer dry soil bulk density kg/m 3 by layer run-off m/yr number between 0 and the precipitation rates. If there is no lateral flow, runoff rate should equal the precipitation rate times the % of precipitation leaving the last soil layer. 13

Table 4-3b. Data required to estimate BC w with the regional PROFILE model (version 5.0). The data in this table must be input by the user and are not curren tly available as a continuous coverage layers for at least a portion of the conterminous United States (will require development of national coverage layer).

PARAMETER UNITS DESCRIPTION net uptake kEq/ha/yr nitrogen (N), Ca 2 + , Mg 2 + , K + - only applied if biomass removed through harvesting or fire cation uptake % % of total soil profile (all soil layers combined should sum to 100%). Can be estimated using root distribution nitrogen uptake % % of total soil profile (all soil layers combined should sum to 100%). Can be estimated using root distribution litterfall kEq/ha/yr N, Ca 2 + , Mg 2 + and K + - input to forest floor soil water content m 3 /m 3 by layer surface area m 2 /m 3 soil surface area by layerAppendix B

March 2010 54 Draft – Do Not Quote or Cite PARAMETER UNITS DESCRIPTION logKgibbsite - by layer dissolved organic carbon (DOC) mg/L by layer
mineralogy % % abundance of 14 dominant mineral groups (K-Feldspar, Plagioclase, Albite, Hornblende, Pyroxene, Epidote, Garnet, Biotite, Muscovite, Fe-Chlorite, Mg-Vermicu lite, Apatite, Kaolinte, Calcite) 1

Table 4-3c. Data required to estimate BC w with the regional PROFILE model (version 5.0). The data in this table are used to support calculations within the model and should be reviewed by the user.

PARAMETER UNITS DESCRIPTION forest canopy kEq/ha/yr N, Ca 2 + , Mg 2 + , K + - nutrients removed by or leached from canopy net mineralization kEq/ha/yr N, Ca 2 + , Mg 2 + , K + - net accumulation of soil organic matter precipitation entering soil horizon % expressed as % of precipitation. If no lateral flow, % leaving top layer should be same as % entering underlying layer precipitation leaving soil horizon % expressed as % of precipitation. If no lateral flow, % leaving top layer should be same as % entering underlying layer CO 2 pressure x atm entered as multiple of atmospheric pressure; typically ranges from 5 in the organic horizons to 40 in the mineral soil layers immobilization - nitrogen immobilization - constant nitrification - constant denitrification - constant nutrient uptake kinetics - coupled vs. uncoupled uptake of N and base cations / uptake mechanism (unspecific, vanselow and none) A total of eight parameters including climat e, deposition, run-off and many of the soil
variables have data available as continuous coverages for the conterminous the United States ( Table 4-4 ), and for most of these vari ables, data exist for all 48 states. However, some of these databases are missing variables and/or data or ma y need to be modified. Currently, there is no data that describes wet and dry Al deposition. This data, however, is not available in most locations where PROFILE is applied, and this para meter is typically left blank within model (H. Sverdrup personal communication, 2009b). Therefore, the absence of this datalayer in the United States should not pose a problem for the BC w estimates. The soil temperature parameter within the SSURGO database is poorly pop ulated and data only exists fo r seventeen states. However, mean annual air temperature is often used as a surrogate for soil temperature within PROFILE because the two temperature measures are simila r in some of regions (Miller, 2001). In some cases, models describing the relationship between air and soil temperature are also available (e.g., Yin and Arp, 1993). Therefore, the use of air temperature instead of soil temperature or modeled soil temperature could be explored wi th the application of PROFILE in the United States, if necessary. 2

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16Appendix BTable 4-4.Available datasets and databases for the conterminousUnited States that could be used to estimate BCwwith the regional applicationof the PROFILE model (version 5.0).DATASOURCE URL or REFERENCEDATE(S) OFAVAILABLEDATAUNITSRESOLUTIONSTATES WITH COVERAGETotal annualprecipitationhttp://prism.oregonstate.edu/products/matrix.phtml?vartype=ppt&view=maps1971-2000in/yr0.64 km2allAverage maximumair temperaturehttp://prism.oregonstate.edu/products/matrix.phtml?vartype=ppt&view=maps1971-2000°F0.64 km2allAverage minimumair Temperaturehttp://prism.oregonstate.edu/products/matrix.phtml?vartype=ppt&view=maps1971-2000°F0.64 km2allRun-offhttp://pubs.er.usgs.gov/djvu/HA/ha_710_plt.djvu1951-1980in/yr1:2,000,000allDry cationdeposition(NH4+, Ca2+, Mg2+,K+, Na+)http://www.epa.gov/castnet/data.html1987-2008kg/ha86 stations in the48 conterminousstatesall (except: ID, SD, NE, NM,and TX)Extrapolated 400 km fromeach stationWet cationdeposition(NH4+, Ca2+, Mg2+,K+, Na+)http://www.epa.gov/castnet/data.html,http://nadp.sws.uiuc.edu/maplib/grids/2008/1987-2008,1994-2006kg/ha86 stations in the48 conterminousstates, 6.25 km2all (except ID, SD, NE, NM,and TX)Extrapolated 400 km fromeach stationDry aniondeposition(SO42-, Cl-, NO3-)http://www.epa.gov/castnet/data.html1987-2008kg/ha86 stations in the48 conterminousstatesall (except ID, SD, NE, NM,and TX)Extrapolated 400 km fromeach stationWet aniondeposition(SO42-, Cl-, NO3-)http://www.epa.gov/castnet/data.html,http://nadp.sws.uiuc.edu/maplib/grids/2008/1987-2008,1994-2006kg/ha86 stations in the48 conterminousstates, 6.25 km2all (except ID, SD, NE, NM,and TX)Extrapolated 400 km fromeach stationNH4+ and NO3-wet and drydepositionCommunity Multiscale Air Quality (CMAQ) -http://www.epa.gov/AMD/CMAQ/2002kg/ha12 km2allSoil horizon depthHZDEPT_R field of chorizon table(http://soildatamart.nrcs.usda.gov/documents/SSURGOMetadataTableColumnDescriptions.pdf)1987-2008,1994-2006cm1:12,000 -1:63,360allSoil bulk densityDB3BAR_R field of CHORIZON table(http://soildatamart.nrcs.usda.gov/documents/SSURGOMetadataTableColumnDescriptions.pdf)N/Ag/cm31:12,000 -1:63,360allMarch 201055Draft – Do Not Quote or CiteAppendix BMarch 201056Draft – Do Not Quote or CiteDATASOURCE URL or REFERENCEDATE(S) OFAVAILABLEDATAUNITSRESOLUTIONSTATES WITH COVERAGESoil texture (%sand, silt, andclay)SANDTOT_R, SILTTOT_R, and CLAYTOT_Rfields of CHORIZON table(http://soildatamart.nrcs.usda.gov/documents/SSURGOMetadataTableColumnDescriptions.pdf)N/A%1:12,000 -1:63,360allSoil stoniness (%of soil withparticles >2mm)FRAGVOL_R in CHFRAGS table(http://soildatamart.nrcs.usda.gov/documents/SSURGOMetadataTableColumnDescriptions.pdf)N/A%1:12,000 -1:63,360allSoil temperatureSOITEMPMM field of the COSOILTEMP table(http://soildatamart.nrcs.usda.gov/documents/SSURGOMetadataTableColumnDescriptions.pdf)N/A°C(averageby month)1:12,000 -1:63,360AK,CA,CO,GA,ID,KS,MI,MN,MO,MT,NC,NE,NM,OR,PR,TX,VAAppendix B

March 2010 57 Draft – Do Not Quote or Cite Although a portion of the input data to estimate BC w with PROFILE are already available as national data coverages, there are nine addi tional input parameters that are not currently described by nationwide datasets, and nine paramete rs that are built into the regional application of the model and may require review and adjust ment prior to applying PROFILE in the United States. The nine input parameters that would re quire the development of national GIS coverages or datasets that could be app lied throughout the Unites States incl ude: net uptake, % base cation and nitrogen uptake, litterfall, soil water cont ent, surface area, logKgibbsite, mineralogy, and dissolved organic carbon (DOC). 1

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24 A national dataset of net uptake of nutrients by forest systems could be developed using the approach outlined by McNulty and colleague s (1997). Briefly, the United States Forest Service (USFS) and United States Geological Survey (USGS) dataset describing the 21 different forest types would be used to map forest cover in the 48 states , and nitrogen and base cation (Ca 2+ , Mg 2+ , K + ) uptake by each forest type would be determined using the average values presented in Table 4-5 . These values were calculated by McNulty and colleagues (2007) and incorporate annual volume growth by region from the USFS Forest Inventory and Analysis (FIA) database and nitrogen and base cation c ontents by tree species and tree component from the Tree Chemistry Database (Pardo et al., 2004) . Net uptake would only be necessary for sites that are actively managed and experience rem oval of biomass through logging and/or fire. Therefore, based on the assumption that only wild erness and conservation areas are not harvested or managed, these nitrogen and base cation uptake estimates w ould only be applied to forest areas that are not designated as wilderness by the National Wilderness Preservation System of the United States (McNulty et al., 2007).Appendix B

March 2010 58 Draft – Do Not Quote or Cite Table 4-5 . Nitrogen and base cation uptake by forest type (from McNulty et al., 2007).

FOREST COVER TYPE NITROGEN UPTAKE (eq/ha/yr) BASE CATION UPTAKE (eq/ha/yr) white-red-jack pine 59.07 77.14 spruce fir 54.27 83.72 longleaf slash pine 154.74 227.22 loblolly shortleaf pine 140.41 208.58 oak pine 129.71 213.75 oak hickory 102.56 254.87 oak-gum-cypress 124.18 235.68 elm-ash-cottonwood 79.74 156.3 maple-beech-birch 101.76 190.51 aspen-birch 81.69 125.46 douglas-fir 109.89 179.03 hemlock-sitka-spruce 98.88 161.12 ponderosa pine 75.29 174.39 western white pine 40.69 37.11 lodgepole pine 40.19 61.25 Larch 65.1 77.14 fir-spruce 94.65 146 Redwood 100.92 156.62 Chaparral 106.6 201.61 pinyon-juniper 40.87 58.21 western hardwoods 135.21 263.33 1

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11 Soil surface area is commonly determined in the laboratory using the Brunauer-EmmettTeller (BET) nitrogen absorption technique (Hodson et al., 1997). However, data from such analyses are not available for all soils in the United States. Theref ore, it would be necessary to
estimate surface area from other soil data. Within the PROFILE model, surface area is calculated with soil texture and particle size distribution data (Equation 4-5) (Alveteg et al., 2004), and Sverdrup and colleagues (1992), used this equation in their study of critical acid loads in Maryland. This same approach could be used fo r mapping soil surface areas in the United States. Soil texture is part of the U.S. Department of Agriculture- Natura l Resources Conservation Service (USDA-NRCS) Soil Survey Geographic (SSURGO) database (Table 4.0). Therefore, itAppendix B

March 2010 59 Draft – Do Not Quote or Cite would be possible to produce a continuous cove rage map of soil surface areas in the United
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28 Soil mineralogy is one of the most important and influential variab les within PROFILE. However, it is also a very time intensive and ex pensive measurement. Therefore, soil mineralogy data in the United States is sparse, and a contin uous coverage layer of soil mineralogy does not exist. In most regional applic ations of PROFILE in Europe and other regions, the mineralogy input data are based on a combination of data from soil geochemical and mineralogy analyses and mineralogical composition base d on output from a model such as the Analysis to Mineral (A2M) model (Posch and Kurz, 2007). The A2M model estimates all possible mineral compositions from total chemical analyses (Ca 2+ , Mg 2+ , K + , Na + , Ti, Al, phosphorus (P), silicon (Si), iron (Fe)) of the soil and a pre-specified set of minerals that are likely to be present in the soil. The highest probability mineral composition is an output of the arithmetic mean of all extreme mineral modes. The resulting mineralogi es are then mapped to “geological provinces” (Sverdrup et al., 1990) that have the same parent material bedrock but may differ in soil mineralogy in a consistent pattern (Sverdrup et al., 1990). Alternatively, the mineralogies can be mapped to “mineralogy polygons” that are delineated based on probable similarities in mineral compositions of the soils. Typically, the spatial borders of mineralogy po lygons are determined by underlying parent material geolog y and/or soil type groupings th at are likely to have the same mineralogies (H. Sverdrup personal communication, 2009b). In areas where the soils have formed from transported materials, such as glacia l till, it is sometimes necessary to consider the surficial geology and model the origin and transport of materials to determine the parent material geology (McKenzie and Ryan, 1999).Appendix B

March 2010 60 Draft – Do Not Quote or Cite Due to the diverse geological history of the United States, it may be necessary to include a variety of variables and databases in the ch aracterization and mapping of mineralogy. Parent materials underlying soils in the conterminous Un ited States vary extremely. These materials include not only bedrock beneath young soils, but also a variety of young and old regolith
materials that include both residuum formed in place and all varieties of transported sediments. In addition, the soils are old a nd highly weathered in a large portion of the United States, and therefore, no longer resembles the mineral compos ition of the parent material. For example, the mineralogy of soils atop ancient residuum of the Appalachian regi on will vary significantly from the mineralogy of younger residuum of the West ern mountain ranges. Also, the mineralogy of soil developed on the older loessal plain in th e Mississippi basin will vary from the younger glacial deposits along the northern regions of the United States. Th erefore, determination of soil mineralogy in the United States would require an approach that is able to recognize the varied geological histories, different pare nt material origins, and soil mi neralogies that differ from the original parent material sour ces. Such an approach would involve the following steps be conducted simultaneously: 1

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2. Determination of mineralogy and geochemical data availability for each mineralogy polygon
3. Comparison of mineralogy polygons with unde rlying bedrock and surficial geology
4. Testing modeled mineralogy against actual mineralogy measurements
Delineation of mineralogy polygons based on so il classification at a level supported by 22 available data - Mapping and creation of a national GIS coverage of mineralogy in the conterminous United States would require the delineation of “mineralogy polygons”. “Mineralogy polygons” are spatially-defined poly gons that are delineated based on probable similarities in mineral compos itions of the soils. These polygons would need to be large enough in scale to be adequately covered by availabl e mineralogy and soil analysis data, yet small enough to only represent single assemblages of soil minerals. Ideally, each mineralogy polygon
should have at least one data point or soil profile analysis th at describes the total analysis (Ca 2+

, Mg 2+ , K + , Na + , Ti, Al, P, Si, and Fe) and/or minera logy of the soil layers. Where data are missing, it would be necessary to interpolate data from other locations using correlations with 23

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March 2010 61 Draft – Do Not Quote or Cite surrounding and adjacent known data and other supporting criteria indi cative of similar mineralogies and weathering patterns (e.g., geol ogic and physiographic re gions, bedrock geology data, climatic regi ons, and others). 1

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23 Within the United States, one of the most suitable coverages for the delineation of the soil mineralogy polygons is the SSURGO soils database ( Table 4-6 ). The smallest unit within this database is the soil mapping unit which can consis t of up to five individual soil series. A soil
series is defined as “soils that are similar in all major profile characteristics (Brady and Weil, 2002), and soils within the same series have b een influenced by similar climate, topographic location, biota, parent material and pedological time frame. Theref ore, the soil within a series, regardless of location would be expected to have identical or sufficiently similar mineralogies (C. Smith personal communication, 2009). The soil groupings within the higher levels of soil taxonomy may also be based on characteristics such as soil mineralogy. For example, soil orders are largely classified by the degree of weat hering and soil development, with Entisols representing the youngest, least weathered soils, and Ultisols and Spodosols being more highly weathered. Therefore, it may be possible to group the soil mappi ng units at a higher level of taxonomy, such as the great group, family or order, as the “mineralogy polygons”. However, since soils are classified based on multiple fo rmative factors, the “mineralogy polygons” could be a mixture of groupings based on different levels of soil taxonomy, with all groupings based on factors indicative of similar mineral assemblages in the soil. Detailed soil delineations have been completed for more than 80% of the conterminous
United States and are used in the NRCS Soil Survey Geographic (SSURGO) dataset ( Figure 4-
3 ). Data are missing for many public land areas (e.g., national forest lands), and there are approximately 21,000 soil series delineations within the conterminous United States.

Table 4-6 Datasets with Geochemical and Mineralogy Data for U.S. Soils

DATA SOURCE RESOLUTION INCLUDED DATA Soil Survey Geographic Database (SSURGO) http://soils.usda.gov/survey/g eography/ssurgo/ 1:12,000 to 1:63,360 SSURGO is linked to a National Soil Information System (NASIS) attribute database. The attribute database gives the proportionate extent of the component soils (i.e., u soil series) and their properties for each map unit. The SSURGO map units consist of 1 to 3 components each. There are approximately 15,000 and 20,000 soil series polygons delineated across the United StatesAppendix B

March 2010 62 Draft – Do Not Quote or Cite DATA SOURCE RESOLUTION INCLUDED DATA U.S. General Soil Map (STATSGO II) http://soils.usda.gov/survey/g eography/statsgo/ 1:250,000 The tabular data contain estimated ranges (low, high, and representative values) of physical and chemical soil properties, soil interpretations depicting the range for the geographic extent of the map unit. Soil map units are linked to attributes in the tabular data, which give the proportionate extent of the component soils and their properties. Surficial Geology of the United States (1977) (also Map of Surficial Deposits and Materials in the Eastern and Central United States (East of 102° West Longitude)) http://tin.er.usgs.gov/geology/ state/ or http://water.usgs.gov/GIS/met adata/usgswrd/XML/ofr99- 77_geol75m.xml alsohttp://pubs.usgs.gov/imap/i2789/ 1:7,500,000 (E of 102° W Longitude: 1:2,000,000) Provides approximate areal extent of about 45 categories of regolith types across the conterminous United States. Compilation East of 102° West Longitude has further classified deposits generally within original polygons.

Element Concentrations in Soils and Other Surficial Materials of the Conterminous United States (Shacklette Data, 1977) USGS, Denver Federal Center Offices Sampling density: 1 sample per 6,000 km 2 .; equivalent to the collection of samples on a 75-km grid. Ultra-low-density geochemical baseline data from 1,323 samples locations characterizing soils and other surficial materials in the conterminous United States. Elements analyzed included: Ag, Al, Ba, Be, B, Ca, Ce, Cr, Co, Cu, Ga, Ge, Hg, Fe, La, Li, Pb, Mg, Mn, Mo, Na, Nd, Ni, Nb, P, K, Rb, S, Sc, Se, Sr, Th, Ti, U, V, Yb, Y, Zn, Zr, and total carbon. The National Geochemical Survey – Database and Documentation(Version 5.0, ongoing) http://tin.er.usgs.gov/geoche m/doc/home.htm and http://tin.er.usgs.gov/geoche m/ Nominal grid spacing of 17 by 17 kilometers (i.e., minimum sample density of 1 sample per 289 km 2 in all land areas of the country Stream-sediment-based geochemical survey for the United States; Analytical methods include a 40-element ICP package plus single-element determinations of As, Se, and Hg by atomic absorption for every sample. about 60,000 stream-sediment samples that have been analyzed. Digital data files are presented in 6 categories. In total there are 43 individual data files for the Unites States. Some of the data has also been processed into vector data to produce maps showing the elemental concentration of As, Se, Hg, Pb, Zn, Cu, Al, Na, Mg, P, Ca, Ti, Mn, and Fe at the county level. Database contains 287 attributes (77,212 records). Integrated Geologic Map Databases for the United States (1998-2007) http://gsa.confex.com/gsa/20 06AM/finalprogram/abstract_ 110914.htm and http://tin.er.usgs.gov/geology/ state/ 1:100,000 Seamless national-scale geologic spatial data-layer and database to support national and regional level projects, including mineral resource and geoenvironmental assessments. Data include general geologic unit age, dominant lithology (rocktype1 must be >50% of unit) and second most dominant lithology (rocktype2).Appendix B

March 2010 63 Draft – Do Not Quote or Cite DATA SOURCE RESOLUTION INCLUDED DATA Soil Pedon Pit Data (on-going) USDA NRCS Area covered by a pedon varies from 10 - 100 square feet; approximately 30,000 soil pits/pedons in the NRCS database Geochemical elements: Al, Ca, Fe, K, Mg, Mn, Na, P, Si, Sr, Ti, and Zr. X-ray diffraction for clay mineralogy by horizon; optical mineralogy analysis is performed on the dominant sand fractions of the soilfrom the A-horizon, B-horizon, and Chorizon, or the most dominant horizon. More than 60 fields describing the minerals are listed in the database. The dataset is not uniform in that elemental analyses were routinely done through the 1970’s but then these analyses were suspended through the 1980’s. Elemental analyses were resumed during the early 1990’s. It is estimated that as much as one third of the 30,000 soil pedons have geochemical data. Likewise, optical mineralogy is not performed for all pedons and the NRCS staff estimate that approximately as many as one third of the 30,000 soil pits have optical analysis results. Even though the number of pedons with data are similar for geochemical and optical analysis results, the data are not necessarily associated with the same set of pedons or even soil series. Physiographic Regions of the United States (Fenneman, 1946) http://water.usgs.gov/GIS/dsd l/physio.e00.gz 1:7,000,000 Geomorphic / physiographic broad-scale subdivisions based on terrain texture, rock type, and geologic structure and history. Nevin Fenneman's (1946) three-tiered classification of the United States - by division, province, and section. 1Appendix BImagesource:http://soils.usda.gov/survey/geography/ssurgo/Figure 4-3.Map Showing the Distribution and Status of SSURGO DataMarch 201064Draft – Do Not Quote or CiteAppendix B

March 2010 65 Draft – Do Not Quote or Cite Determination of mineralogy and total analysis data availability for each mineralogy 1 polygon - The soils for each spatially-defi ned “mineralogy polygon” would require % mineralogy to determine BC w with the PROFILE model. The relative abundances of 14 dominant minerals are required as model input, and this % mineralogy can be based on direct measurements of soil mineralogy or can be determ ined with the A2M model. As outlined earlier, the A2M model is able to estimate the most pr obable % mineral composition, or proportion of mineral phases, of a soil based on total analysis data and the identification of the minerals that are likely to be present in the soil. Therefore, it would be necessary to determine the availability of such data for each of the “mineralogy polygons” in the conterminous United States. 2

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31 Currently, there are potentially three consistent national-scale datasets that contain various levels of mineralogy and total analysis data to serve as inputs for the A2M and PROFILE
models. These include:

• Chemical Analyses of Soils and other Surfici al Materials of the Conterminous United
States ( Shacklette dataset) and accompanying Geochemical Landscapes Project data,

• the more recent National Geochemical Survey data, and

• the United States Department of Agricultu re (USDA) NRCS pedon soil pit dataset

. A summary of these datasets is outlined in Table 4-6. Chemical Analyses of Soils and other Surfici al Materials of the Conterminous United States (Shacklette Data) and the Geochemical Landscapes Project datasets provide geochemical
baseline data for soils and other surficial ma terials in the conterminous United States. The original Shacklette dataset contains geochemical data from soils and other regolith collected and analyzed by Hans Shacklette and colleagues be ginning in 1958 and continuing until about 1976. This dataset has approximately 1,323 samples, at a sampling density of approximately 1 sample per 6,000 square kilometers ( Figure 4-4 ). The soil samples within this dataset were analyzed for a large number of elements, including Ca, Fe, Mg , Na, P, K, and Ti (Gustavsson et al., 2001), that are required by the A2M model. However, assessments of mineralogy were not included in these original analyses. An additional drawback w ith the data set is its extremely low numbers of samples for the entire conterminous United States . However, more recent high-resolution studies (e.g., Smith et al., 2005) for select elements (e.g ., Calcium) have illust rated that the regional patterns established by the Shacklette data are generally maintained except where areas have been affected by anthropogenic factors (Smith, 2006).Appendix BPoints on map show geochemical sample stations:•Black dots indicate samples from sample-collectionphase 1,•white dots indicate samples from sample-collectionphase 2,•gray dots indicate samples whose placement intophase 1 or phase 2 is uncertain.(All archived sample have been reanalyzed (personalcommunication with David Smith, 1-4-2009)Shacklette,HansfordT.,andJosephineG.Boerngen,1984Figure 4-4.Soil Sampling Locations Included in the USGS Shacklette DatasetMarch 201066Draft – Do Not Quote or CiteAppendix B

The Geochemical Landscapes Project was begun in 1998 with mo st work occurring after 2002. The purpose of the data collection is to increase th e density of the Shacklette data locations to produce a high resolution geochemical dataset for North American soils of 6,000 data points (D. Smith personal communication, 2009). This is an on-going colla borative effort by the USGS, USDA Natural Resource Conservation Service, other federal agencies, and academia to build a national-scale soil geochemical survey. The pr oject has just completed a third year of continental-sampling and completed sample collection for approximately 80% of the conterminous United States (D. Smith personal communication, 2009). The USGS anticipates that sampling may be completed for the conter minous United States in 2010; or 2011 at the latest. Both total and mineralogy analyses ar e being performed on these samples. Mineralogy analyses include x-ray diffracti on on the clay fraction and optical analyses on the fine sands and silts. In addition, the original Shacklette da ta have been re-analyzed for mineralogy. The National Geochemical Survey (NGS) dataset is being built by on-going efforts by the USGS to produce a new stream-sediment-based geochemical survey for the United States at a spacing of 17 by 17 kilometers (i.e., minimum sample density of 1 sample per 289 km 2 in all land areas of the country) ( Figure 4-5 ). The project has sought to capitalize on existing datasets and archived samples. For this reason the NGS is based primarily on analyses of stream
sediments to build on the massive archives of data and samples from DOE’s National Uranium Evaluation (NURE) program. Much of the surv ey has entailed reanalysis of approximately 35,000 archival samples from the NURE program . Where NURE samples do not exist, USGS has been working with cooperators to obtain new samples. In tota l, the project is expecting to have more than 60,000 samples. Most or all of the sampling has b een completed for the conterminous United States and only few an alyses are left to complete (D. Smith personal communication, 2009). The samples are being analyzed fo r 40 elements, including all of the elements which are necessary input for the A2M model. In addition, for a select number of samples mineralogy analyses (x-r ay diffraction of clay fraction and optimal analyses of fine sands and silts) are al so being conducted.

March 2010 67 Draft – Do Not Quote or CiteAppendix BImagesource:http://tin.er.usgs.gov/geochem/doc/status.htmFigure 4-5. Sample Density of USGS National Geochemical SurveyMarch 201068Draft – Do Not Quote or CiteAppendix B

March 2010 69 Draft – Do Not Quote or Cite USDA NRCS Soil Pedon Pit Data were collected by the USDA NRCS for data required for delineation of soil series, map units, and associated attributes. The data are contained in the NRCS USSOILS database that provides data for the SSURGO database. There are currently approximately 30,000 soil pits/pedon s in the NRCS database, and soil samples from these pits or pedons have been analyzed for a large variet y of physical and chemical properties. These analyses include total chemical analysis, which includes elements required by A2M (e.g., Al, Ca, Fe, K, Mg, Na, P, Si, Ti). In addition, minera logy has been characterized through two analyses: x-ray diffraction, which identifie s clay mineralogy, and optical mineralogy which determines the mineral composition of the fine sand and silt fractions of the soil (C. Smith personal communication, 2009). However, these three analyses have not been conducted on all soils. Only 11,747 of the 30,000 soil pits have been analyzed for at least one of the three parameters ( Figure
4-6 ), and only 4,710 soils have been analyzed for all three ( Figure 4-7 ). 1

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12Appendix BMarch 201070Draft – Do Not Quote or Cite1234Figure 4-6.NRCS Soil Pedon Sample Pit Locations (30,000 total)(Image created by RTI using data provided by NRCS on 12/2009)March 201071Draft – Do Not Quote or CiteAppendix BFigure 4-7.NRCS Soil Pedon Pit Sample Locations with Geochemical and Mineralogy Data(Image created by RTI using data provided by NRCS on 12/2009)123Appendix B

March 2010 72 Draft – Do Not Quote or Cite In summary, three main datasets have been identified that could provide the necessary total analyses and mineralogy data for each “mineralogy polygon.” These datasets would be combined into a single database and overlaid on top of the “mineralogy polygon” datalayer to determine the degree to which each polygon is cove red by mineralogy and total analysis data. At the scale of a nationwide analysis, the data from each of these datasets is considered comparable given the sampling and analysis protoc ols that have been used (D. Smith personal communication, 2009). Although the combined database would be large and offer over 75,000 data points, it is not likely th at data would be available for all “mineralogy polygons.” In such cases, it would be necessary to determine the mineralogy through alternate methods. Potentially, interpolation between data points could be conduc ted using numerical probabilistic methods. In addition, it may be possible to determine proba ble mineralogy based on underlying bedrock or surficial geology (described further in next se ssion). Methods involving professional judgment could also be used to interpret patterns and a ssign reasonable and appropr iate values to express the apparent condition. If such an approach were ta ken, it would be necessary to work with soils experts who are familiar with the SSURGO database (e.g., NRCS Re gional Staff) to make such judgments. 1

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16 Comparison of mineral polygons with unde rlying bedrock and surficial geology - In many locations in the United States, soils ha ve developed from the underlying bedrock or surficial materials. Therefore, it may be possible to validate, support or identify the mineralogies of each of the “mineralogy polygons” through a co mparison with the physiographic regions of the United States and the underlying bedrock and surficial geology. The p hysiographic provinces are based on geology and topography. Therefore, these provinces relate geology and geological history with expected soil characteristics, and the locati ons of “mineralogy polygons” should broadly follow the patterns within these province boundaries . Similarly, the “mineralogy polygons” could be compared against the underlying geologies to determine the accuracy of the soil taxonomy groupings that were used to delineate the polygons. In addition, overlays of the “mineraology polygon” datalayer and bedrock or surficial geology could support the estimation of probable mineralogies and percent compositio ns for “mineralogy polygons” that are missing soil mineralogy and or total analysis data. 17

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31 The USGS 1:100,000 scale bedrock geology GI S cover would be first used for the comparison between the “mineralogy polygons” and bedrock geology (Table 6.0). Most rockAppendix B

March 2010 73 Draft – Do Not Quote or Cite types are typically characterized by less than 4 mineral types. Correlating the “mineralogy polygons” with the bedrock type can be used to obtain a gross approximation of mineral phases that would be expected in the residual parent materials and the correspon ding soils. This would be a particularly useful protocol to apply to areas where the soils have formed in place from the weathering of the bedrock. For example, this approach could be used in unglaciated regions where Entisols or residuum predominant. 1

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20 The 1:7,500,000 scale USGS surficial geology layer could be used as the source for comparison between “mineralogy polygon” and su rficial geology (refer to Table 6.0). The surficial geology layer would id entify the type of regolith on which the soil has developed. Regolith is defined here as any unconsolidated ma terials on top of bedrock, and consists of residuum which has formed in place and transported materials that have been deposited by gravity, wind, water or ice. Therefore, this laye r will indicate the type of parent material that supported the development of the soil and will provide an indication of the potential mineral composition of the soil. Specific correlation of mineral types can be more difficult for transported deposits. However, an association is still possible as correlated with general up-grade areas that relate the likely origin , or areas of parent material, fo r the transported deposit. Even though more generalized approaches to dete rmining the mineralogy are suggested by the available data, modeling the geologic source of parent materials by applying techniques similar to soil-landscape modeling or environmenta l correlation modeling could be conducted (McKenzie and Ryan, 1999). Test modeled mineralogy against actual mineralogy measurements - To validate and test the accuracy of the % mineral values assi gned to the “mineralogy polygons”, comparisons should be made between the “mineralogy polygon” da ta layer and areas with detailed mineralogy soil analyses. Such sites may incl ude the LTER sites outlined in Table 4-7 or those detailed within the scientific and geological literature. In addition, there may be locations where detailed mineralogy assessments have been conducted by mi ning companies or resear ch groups that could
be used to test the “mineral ogy polygon” data layer. Compar isons would be particularly important for mineralogy polygons with % mineralogy determined by the A2M model. 21

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28Appendix B

March 2010 74 Draft – Do Not Quote or Cite Table 4-7 . Long-Term Ecological Research (LTER) sites that could potentially be suitable as “field test” sites to validate BC w estimates generated with the regional ap plication of the PROFILE model (version 5.0).

LTER STUDY LOCATION ADDITIONAL INFORMATION

H.J. Andrews Experimental Forest Cascade Mountains, Oreg on http://andrewsfores t.oregonstate.edu/

Coweeta LTER Southern Appalachian mountains, North Carolina http://www.lternet.edu/sites/cwt/
Harvard Forest Massachusetts http://www.lternet.edu/sites/hfr/ Hubbard Brook Experimental Forest White Mountain National Forest, New Hampshire http://www.lternet.edu/sites/hbr/ Kellogg Biological Station Southwest Michigan http://www.lternet.edu/sites/kbs/
Konza Prairie LTER Northeastern Kansas http://www.lternet.edu/sites/knz/ Niwot Ridge Colorado http://www.lternet.edu/sites/nwt/ Santa Barbara Coastal LTER California http://www.lternet.edu/sites/sbc/
Sevilleta LTER New Mexico http://www.lternet.edu/sites/sev/ 1 PROFILE Input Parameters Assigned Default Values 2

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19 Development of national datasets or default values for the % base cation and nitrogen uptake (by layer), litterfall, soil water content, logKgibbsite, and DOC input parameters would most likely require the use of data from the literature and research conducted in the United States. The % base cation and nitrogen uptake by soil layer variables are a function of the distribution of fine roots, and r ooting distributions are typically entered as one of four classes into PROFILE (H. Sverdrup personal communication, 2009b). These root distribution classes are
based on data from an extensive literature sear ch on the rooting habitats of common tree species in Europe (Sverdrup and Stjernquist, 2002). A si milar literature search could be conducted for the main species within the 21 forest types in the United States, and the four root distribution classes could be adjusted accordingly. The litterfall parameter within PROFI LE characterizes the amounts of N, Ca 2+ , Mg 2+ and
K + returned to the soil with the senescence of leav es, branches and stems. It is calculated as a function of the site-specific growth rates of indi vidual tree species and the nutrient content of the different litter components. Since PROFILE is a steady-state model, the growth rates are averaged over the rotation of the stand. Litterfa ll values have been determined for European tree species (Sverdrup et al, 1990; Sverdrup and Stjernquist, 2002), a nd the same procedure could be used for estimating values for the main species in the 21 forest types in the United States. TheAppendix B

March 2010 75 Draft – Do Not Quote or Cite Tree Chemistry Database (Pardo et al., 2004) co uld be serve as the source of litte r nutrient
content and the USFS FIA database could potentially supply speci es-specific growth rates. 1

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29 Soil water content is highly variable. Howeve r, since PROFILE is a steady-state model, it is necessary to use a single value representativ e of the water content throughout the year. In Sweden, a default value of 0.2 m 2 /m 3 is often used (Halveteg et al., 2004), and it would be necessary to establish a similar default value or set of default values for the United States. Such
values could be obtained from the literature. In addition, it may be possible to estimate a set of soil water content estimates based on a simple wa ter balance model that includes the influences of precipitation, run-off, soil texture a nd/or soil drainage classes (H. Sverdrup personal communication, 2009b). Data outlined in Table 4 and soil texture and the six drainage classes (Well Drained; Excessive; Moderately Well; Poorly; Somewhat Excessively; Somewhat Poorly)
included within the SSURGO soils database could potentially be used in this simple water
balance model. Soil dissolved organic carbon ( DOC) and the logKgibbsite coe fficient would also require the use of values from the literature. Currently, with the application of PROFILE within Europe, DOC is entered as 20 mg/L in the organic layers but drops rapidly with depth in the mineral soil horizons (Alveteg et al., 2004). Th ese values are based on a compila tion of data from European field sites (H. Sverdrup personal communication, 2009b) and are a function of the organic matter content of the soil (Sverd rup et al, 1990). Similar values a nd relationships would need to be established for forest systems in the United States based on available data and studies outlined in the literature. LogKgibbsite is a coefficient that describes the concentration of Al in the soil solution. It depends on the soil solution pH and differs by soil layer. Two sets of values have been developed for the applicati on of PROFILE within Europe, with one set being used for clay
soils and the other for non-cl ay soils (Sverdrup and Stjer nquist, 2002). These values and grouping by soil clay content were based on data from the literature and the consistent trends in the gibbsite coefficients within and between soils (H. Sverdrup personal communication, 2009b). For the application of PROFILE within the United States, it would be n ecessary to review the logKgibbsite values, review the l iterature and potentially adjust the values as necessary to be representative of conditions found in the United States.Appendix B

March 2010 76 Draft – Do Not Quote or Cite Regionally-based Built-in PROFILE Input Parameters 1

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31 There are nine variables that are curr ently built into the calculations of BC w for the regional application of PROFILE (version 5.0) and do not require input data from the user. The
values of these variables were determined by field research in Europe, and are thought to vary minimally between sites or are calculated based on the input data. These variables include: forest canopy, net mineralization, % pr ecipitation enteri ng layer, % precipitatio n leaving layer, CO 2 pressure, immobilization, nitrification, denitrification, nutrient uptake kinetic variables (C.
Akselsson personal communication, 2009). Prior to applyi ng PROFILE to map BC w throughout the United States, the values and equations used for each of these variables should be examined. It may be necessary to modify the model equa tions and/or replace the current values with
those from the literature to ensure that the values within PROFILE are representative of conditions and processes in th e United States (H. Sverdrup personal communication, 2009). Forest canopy, within PROFILE, accounts for the Ca 2+ , Mg 2+ , K + and N (as NH 4 + ) that is absorbed from or leached into the precipitation that is in contact with the canopy. Potassium,
Ca 2+ , Mg 2+ are typically leached from the foliage and NH 4 + is absorbed. The default values within PROFILE are currently based on the results of field studies in Europe and are divided by forest type (deciduous versus non- deciduous). Net mineralization w ithin the model is a function of soil organic matter content. Currently, net mineralization is set to “0” within PROFILE assuming that the forests are managed sustainably and net mineralization is at an equilibrium;
Ca 2+ , Mg 2+ , K + and NH 4 + released through mineralization of organic matter is taken up by the vegetation, returned as litter and remineralized. Ther efore, there is no net loss or gain of nutrients through mineralization. However, the net mineraliz ation default value of “0” can be changed if forest management is not sustai nable and involves short rotations and/or practices such as whole tree harvesting which remove the foliage and a large pool of “mineralized” nutrients from the
site. The % of precipitation entering and leaving th e soil layers variables within PROFILE are
determined based on the fine root distribution in the soil profile. Carbon di oxide pressure in the
soil is estimated from a small dataset of meas urements conducted in di fferent regions of the
world. The values that are used within PR OFILE are a function of soil particle size. Immobilization of nitrogen within PROFILE is currently set to range between 0.5 – 1.0 kg N/ha/yr. This range of values was determined by the amount of the amount of nitrogen that hasAppendix B

March 2010 77 Draft – Do Not Quote or Cite accumulated in Northern European soils sin ce the last glaciations. Denitrification and nitrification are currently determined by mathema tical equations that include the influences of temperature, available soil nitrogen, soil moistu re and soil pH. Nutrient uptake kinetics within PROFILE consists of coupled versus uncoupled uptake of nitrogen and base cations. Within PROFILE, uptake is set to “coupled” as a defa ult because the uptake of Ca, Mg and Al and K and NH4+ are coupled (Sverdrup et al., 1990). Up take kinetics within the model are also described as unspecified or va nselow depending on the uptake dyna mics of base cations and Al
absorbed to the root surface. Currently, within PROFILE, deciduous species and domestic crops are defaulted to vanselow kinetics and grasse s, and conifers use uns pecified kinetics (H. Sverdrup personal communication, 2009). Unspecified kinetics indi cates that the ion exchange
matrix on the root surface is indifferent to th e valence of the absorbing ions (Sverdrup and Warfvinge, 1993). 1

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29 Step 2. Determination of polygon layer to spatially define the BC w rates and development of continuous coverage map of calculated BC w values. Following the establishment of continuous cove rage databases and na tional datasets and default values for the application of PROFILE (v ersion 5.0) within the United States, it would be necessary to construct a spatially-explicit continuous datalayer for mapping BC w throughout the
48 states. The resolution of the datalayer should be small scal e and provide the highest level of detail permitted by the data. In a ddition, the location of individual BC w polygons should be tied
to a variable or set of vari ables which strongly influence BC w . Since soil attributes including mineralogy, bulk density, volumetric water co ntent and exposed surf ace area of minerals (discussed further in Section 4.3.6) are th e largest sources of variability in the BC w calculations, it may be most appropriate to map BC w according to mineralogy, soil series or a higher level of soil taxonomy. Input data and default values for the 26 PROFILE vari ables would then be mapped to the delineated BC w polygon layer. When multiple or sections of multiple polygons of the same datalayer are present in a BC w polygon, a weighted average value for the data would be
calculated. All the data for each BC w polygon would then be formatted according to the requirements of PROFILE and the PROFILE regi onal model would be run to produce maps of
BC w .Appendix B

March 2010 78 Draft – Do Not Quote or Cite 4.3.5 Potential limitations of proposed methodology 1

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31 Although PROFILE is arguably the most su itable model currently available for estimating and mapping BC w for terrestrial critical acid load determinations in the United States,
the model does have some limitations that s hould be acknowledged and potentially remedied prior to application. The model and algorithms contained therein were developed in Sweden using Swedish soils as the basis for the soil chem ical and physical relati onships (Hodson et al., 1997). The soils in Sweden are comparatively yo ung, having formed since the last glaciations, approximately 10,000 years ago (Sverdrup and Wa rfvinge, 1988). Therefore, there is some concern that PROFILE may not accurately model base cation release in older soils (C. Smith personal communication, 2009). As discussed by Hodson and Langan (1999), PROFILE does
not take into account the decrea sing reactivity of minerals with duration of dissolution, and
assumes that the reaction rates are constant regardless of time and duration of dissolution. In addition, the model assumes a constant versus decreasing reactive surface area as total surface area increases. According to the authors, these sh ortfallings were two of the main reasons that PROFILE did not show a decreased weathering rate with soil age relative to other models. However, at the same time PROFILE has been used to estimate BC w in multiple locations with older, more weathered soils, such as Maryland, China, Thailand, Argentina and Greece, and has performed with apparent succes s (Duan et al., 2002; Sverdrup et al., 1992; H. Sverdrup). PROFILE currently accounts for the weathe ring of 14 different minerals, with the potential to include 13 additional minerals, if necessary. Potentially, there may be minerals within the United States that are not represented w ithin the 27 that are currently included within PROFILE. However, a total of 48 minerals have been investigated by the researchers that developed the model (H. Sverdrup personal communication, 2009b). Therefore, it may be possible to add additional minera ls to PROFILE to ensure th at it is able to address BC w in all regions of the United States.
Additional limitations and con cerns regarding the applicati on of PROFILE to estimate
BC w rates have been identified in a thorough revi ew by Hodson and colleagues (1997). Some of the main issues brought up by the au thors include: the need for a mo re consistent set of constants for the weathering rate equations; inaccuracies in the mineral compositions; errors in the calculation to determine surface area; and confoundi ng influences of soil pa rticles greater than 2mm in size on soil bulk density. Hodson and colleagues (1997) point out the need to reexamineAppendix B

March 2010 79 Draft – Do Not Quote or Cite the reaction rate coeffici ents associated with hornblende, tourmaline, staurolite, kaolinite, garnet, augite, biotite and chlorite, arguing that coefficients assigned to these minerals are not correct. Similarly, the authors claim that the compositions of the minerals used within PROFILE may be incorrect in some applications and may need to be modified by the user to more accurately reflect the soil being modeled. Hodson and collea gues (1997) also demonstrate the potential to over and underestimate BET surface area using the soil texture equation provided within PROFILE. They claim that the equation underest imated the surface area of a British soil by 65%. In part, the authors attributed these inaccuracies to the development of the soil texture – surface area relationship from only 92 mineral soil samp les from Sweden. Lastly, Hodson and colleagues (1997) point out the need to recognize soil par ticles greater than 2mm in size in the soil bulk density estimates, as such particles can impact the density by as much as 50% for stony soils. The concerns raised by Hodson and colleagues (1997) appear to be valid and should be considered by users of the PROFILE model. However, the authors of the review critiqued an early version of PROFILE (version 3.01) and th e most recent version of PROFILE may have already addressed some of these limitations. For ex ample, the abundance of particle sizes greater than 2 mm is included in the current regional mode l of PROFILE (version 5.0). It should also be noted that Hodson and colleagues (1997) did acknow ledge that despite th e apparent weaknesses of PROFILE, BC w rates calculated with the model are comp arable to those calculated using other
methods. 1

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31 In addition to the potential limitations of PROFILE as a model, application of PROFILE to map BC w rates throughout the United States may also present some drawb acks or restrictions. There may be areas of the United States where input data required by the model is not available. In such situations, it would be necessary to extrap olate data from areas with similar soil, biotic or abiotic conditions. Similarly, if data for speci fic variables are limited in many areas, it may be necessary to adopt best available default values over large areas, until more data and better coverage across the states is available. 4.3.6 “Field Tests” of model and uncertainty analyses As outlined in the preceding sections, the proposed methodology to map BC w throughout
the United States would involve the use of the regional application of PROFILE (version 5.0), continuous coverage data, and in some cases, i nput and default values from the literature. Therefore, at least a portion of the input data would not be site specific and would be entered asAppendix B

March 2010 80 Draft – Do Not Quote or Cite class values or generated by sub-models or ma thematical relationships. Soil water content and soil mineralogy are examples of such data. It is largely unknown to what degree, if any, this proposed methodology designed for ma pping large areas would influe nce and potentially distort
the estimates of BC w . Therefore, to validate the weatheri ng estimates from the proposed mapping methodology, it would be worthwhile to conduct “fie ld tests” of the model output in different regions of the United States. Such “field tests” could consist of comparing the regional estimates
of BC w with those determined with the single site version of PROFILE and site-specific data. (No actual on-the-ground field re search required.) In addition, where available, the PROFILEgenerated BC w rate estimates could be compared w ith weathering rates determined by other methods. Both approaches would provide an indi cation of the quality and accuracy of estimates from the mapping methodology and regional appli cation of PROFILE. Sites within the LongTerm Ecological Research (LTER) network would be good locations for the “field tests” due to the large amounts of data available at many of thes e sites. In addition, at some sites, such as Hubbard Brook, base cation weathering has been determined using methods other than the
PROFILE model. A list of LTER s ites within the conterminous 48 st ates that could potentially serve as “field test” sites is presented in Table 6. 0. A sub-set of these site s representing different regions and conditions within the United Stat es should be selected to validate the BC w estimates. 1

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31 In addition to the validating the proposed me thodology with “field test” site comparisons, uncertainty analyses should also be conducted on the BC w estimates that are generated with the methodology. There are a total of 26 parameters within the regional ap plication of PROFILE (version 5.0) that require data entry by the user or review prior to applying the model, and each of these parameters could be expected to have a level of uncertainty. Therefore, cumulatively,
the uncertainties associated with the BC w estimates could be quite large. In addition, because
BC w is one of the most influential terms in the calculation of terrestrial critical acid loads, and
critical loads can be used as a measure of the im pact of acidifying nitrogen and sulfur deposition on terrestrial ecosystems, it is important to gain a good understanding of the uncertainty
associated with the BC w estimates. Critical acid loads c ould potentially be used by decision makers to set policy and NO x and SO x emission standards within the United States. Furthermore, uncertainty analyses can reveal which para meters are the most influential in the BC w estimates, thereby guiding which parameters should receive the greatest attention in the development of the datasets and national coverage s for the PROFILE model.Appendix B

March 2010 81 Draft – Do Not Quote or Cite Earlier versions of the PROFILE model (ver sion 3.01) have alrea dy been reviewed and analyzed by researchers based on the applicati on of the model to sites in Norway, Sweden, Scotland and Wales (Jönsson et al., 1995; Hodson et al., 1996; Zak et al., 1996). Monte Carlo analyses testing the uncertainty associated with user defined input va riables indicated that varying input parameter errors individually a nd simultaneously (within the range of values reported in the literature) resulted in a varia tion in model output of +/- 40% (Jönsson et al., 1995). The authors also determined that bulk de nsity, volumetric water content and exposed
surface area of minerals were th e largest source of variation in the output values. The least sensitive parameters were soil stratification, prec ipitation and percolation. Similar analyses were conducted by Hodson and colleagues (1996) who determined the influence of single input parameters, one at a time. Based on their analyses, BC w estimates could vary by over 100% using the ranges in parameters values measured in field studies. The author s also found that some minerals, such as K-feldspar, were particularly sensitive to variation in input values, and soil temperature, moisture content and exposed mi neral surface area caused the largest amounts of
variation in the BC w estimates. These results based on an earlier version of PROFILE suggest that ranges in input va lues can cause the BC w estimates from the model to vary by moderate to large amounts. However, the level of uncertainty a ssociated with outputs from the most current, regional application of PROFILE (v ersion 5.0) is still unknown. In addition, there has yet to be an assessment of the performance of the model in the United States and a determination of how ranges in data from different regions in the c ountry would impact the variation in model output. Therefore, uncertainty analyses should be conducted as a compone nt of the proposed methodology, to provide bounds to the range of output values associated with the BC w estimates
for terrestrial critical acid load calculations in the United States. 1

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29 5. CONCLUSIONS AND RECOMMENDATIONS The goal of this task was to inform EPA a bout the tools and data available to develop maximum deposition loads across the United States for aquatic and terrestrial acidification. In particular, this effort focuse d on methodologies to estimate Bc w , a parameter that plays a crucial role in predicting an ecosystem’s ability to ne utralize acid deposition. Based on the findings of this literature review, discussions with expert s, evaluation of tools, and assessment of dataAppendix B

March 2010 82 Draft – Do Not Quote or Cite availability, two process-based models are reco mmended: MAGIC for aqua tic acidification (with extrapolation through regional regr ession modeling) and PROFILE fo r terrestrial acidification. 1

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28 It is clear that addressing limitations on soil data availability in the United States will require considerable effort to populate both mode ls; however, resources invested to satisfy this data need can be leveraged to th e benefit of both terres trial and aquatic modeli ng goals. It is also
clear that the MAGIC and PROF ILE models’ application in th e United States has focused on select regions; however, model de velopers believe these models can be applied successfully in other regions, particularly regions with more sensitive ecosystems. Finally, neither MAGIC nor PROFILE models are readily accessible for public use. Therefore, it will not be practical to assume states and regions could operate the models . Rather, it would be more manageable for the models to be run at the Agency level with states a nd regional offices providing the needed input
data. It is recommended that following EPA review of this report, candidate regions of the United States be identified for modeling and levels of effort be estimated to prepare the MAGIC and PROFILE models for operation and to collect a nd/or predict their input data. As part of the effort, it is recommended that RTI collaborate with recognized experts in the development and application of these two models.

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Ouimet, R., P.A. Arp, S.A. Watmough, J. Aher ne, and I. DeMerchant. 2006. Determination and mapping critical loads of acidity and exceed ances for upland forest soils in Eastern
Canada. Water, Air and Soil Pollution 172 :57–66.

Ouimet R. and L. Duchesne. 2005. Base cation mi neral weathering and tota l release rates from
soils in three calibrated forest watersheds on the Canadian Boreal Shield. Canadian Journal of Soil Science

. 85 : 245-260.

Pardo, L.H., and N. Duarte. 2007. Assessment of Effects of Acidic Deposition on Forested Ecosystems in Great Smoky Mountains National Park using Critical Loads for Sulfur and Nitrogen. U.S. Department of Agriculture, Fo rest Service. Prepared for Tennessee Valley Authority, S. Burlington, VT.

Pardo, L.H., M. Robin-Abbott, N. Duarte, E.K. Miller. 2004. Tree Chemistry Database (Version 1.0). General Technical Report NE-324. U.S. De partment of Agriculture, Forest Service,
Northeastern Research Stati on, Newton Square, PA, 45 pp.

Posch, M., M. Forsius, and J. Kämäri. 1993. Critic al loads of sulphur and nitrogen for lakes I: Model description and estim ation of uncertainties. Water, Air, and Soil Pollut. 66 , 173–
192.
Posch, M., J. Kämäri, M. Forsius, A. Henrik sen, and A. Wilander. 1997. Exceedance of critical loads for lakes in Finland, Norway and Sweden: Reduction requirements for acidifying nitrogen and sulfur deposition. Environmental Management 21 : 291–304.Appendix B

March 2010 91 Draft – Do Not Quote or Cite Rago, P. J., and J.G. Wiener. 1986. Does pH af fect fish species richness when lake area is
considered? Transactions of the American Fisheries Society 115 :438–447. 1

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27 Rapp, L. and Bishop, K. 2009. Surface water acidi fication and critical loads: exploring the Ffactor. Hydrology and Earth System Sciences 13 : 2191-2201
Reynolds, B., and D.A. Norris. 2001. Fres hwater critical loads in Wales. Water, Air, and Soil
Pollution: Focus 1 :495–505.
Schindler, D.W. 1988. Effects of acid rain on freshwater ecosystems. Science 239: 232–239.
Schreck, C.B. 1982. Stress and compensation in teleostean fishes: response to social and physical factors. pp. 295–321 in Stress and Fish . Edited by A.D. Pickering. New York: Academic
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Schreck, C.B. 1981. Stress and rearing of salmonids. Aquaculture 28 :241–249.
Smith, C. Personal communication. 2009. Co mmunication between Chris Smith (U.S. Department of Agriculture Natural Resources Conservation Service, USA) and Jennifer Phelan (RTI International, USA) by telephone. December 2009.

St. Clair, S.B., J.E. Carlson, and J.P. Lynch. 2005. Evidence for oxidativ e stress in sugar maple stands growing on acidic, nutrient imbalanced forest soils. Oecologia 145 :258-369.

Starr, M., A.J. Lindroos, T. Tarvainen, and H. Tanskanen. 1998. Weathering rates in the Hietajärvi integrated monitoring catchment. Boreal Environment Research

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Stoddard, J., J.S. Kahl, F.A. Deviney, D.R. DeWa lle, C.T. Driscoll, A.T. Herlihy, J.H. Kellogg; P.S. Murdoch, J.R. Webb, and K.E. Webster. 2003. Response of Surface Water Chemistry to the Clean Air Act Amendments of 1990. EPA 620/R-03.001. U.S. Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Research Triangle Park, NC.
Sullivan, T.J., B.J. Cosby, J.R. Webb, R.L Denni s, A.J. Bulger, and F.A. Deviney Jr. 2008. Streamwater acid-base chemistry and critical loads of atmospheric sulfur deposition in Shenandoah National Park, Virginia. Environmental Monitoring and Assessment 137 : 85–99.Appendix B

March 2010 92 Draft – Do Not Quote or Cite Sullivan, T.J., C.T. Driscoll, B.J. Cosby, I.J. Fernandez, A.T. Herlihy, J. Zhai, R. Stemberger, K.U. Snyder, J.W. Sutherland, S.A. Nierzwicki-Bauer, C.W. Boylen, T.C. McDonnell,
and N.A. Nowicki. 2006. Assessment of the Extent to which Intensively-Studied Lakes are Representative of the Adirondack Mountain Region . Final report. New York State Energy Research and Development Authority ( NYSERDA), Albany, NY. Available at 1

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28 http://nysl.nysed.gov/uhtbin/cgi sirsi/Qcwd6NzFby/NYSL/138650099/8/4298474 (accessed November 1, 2007).
Sullivan, T.J., B.J. Cosby, A.T. Herlihy, C.T. Driscoll, I.J. Fernandez, T.C. McDonnell, C.W. Boylen, S.A. Nierzwicki-Bauer, and K.U. Snyder. 2007a. Assessment of the Extent to Which Intensively-studied Lakes are Repr esentative of the Adirondack Region and Response to Future Changes in Acidic Deposition. Water, Air, & Soil Pollution 185 : 279-
291.
Sullivan, T.J., J.R. Webb, K.U. Snyder, A.T. Herlihy, and B.J. Cosby. 2007b. Spatial Distribution of Acid-sensitive and Acid-imp acted Streams in Relation to Watershed
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71.
Sullivan, T.J., B.J. Cosby, K.U. Snyder, A.T. Herlihy, B. Jackson. 2007c. Model-Based Assessment of the Effects of Acidic Depositi on on Sensitive Watershed Resources in the National Forests of North Carolina, Tennessee, and South Carolina. Report Prepared for USDA Forest Service, Asheville, NC.
Sullivan, T. J. Cosby, B.J. Herlihy, A.T. Webb, J.R. Bulger, A.J. Snyder, K.U. Brewer, P.F. Gilbert, E.H. Moore, D.L. 2004. Regional model projections of future effects of sulfur and nitrogen deposition on streams in the southern Appalachian Mountains. Water
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Sullivan, T. J., B. J. Cosby, J. R. Webb, K. U. Snyde r, A. T. Herlihy, A. J. Bulger, E. H. Gilbert,
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Sullivan, T.J. 2000. Aquatic Effects of Acidic De position. Lewis Publishers: Washington, D.C.Appendix B

March 2010 93 Draft – Do Not Quote or Cite Sverdrup, H. Personal communication. 2009a. Communication between Harald Sverdrup (Lund University, Sweden) and Jennifer Phelan (RTI International, USA) during the Canadian
Council of Ministers of the Environment Ac id Deposition Critical Loads: Status of Methods and Indicators Workshop, March 18 and 19, 2009. Ottawa, Ontario, Canada. 1

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26 Sverdrup, H. Personal communication. 2009b. Co mmunication between Ha rald Sverdrup (Lund University, Sweden) and Jennifer Phelan (RTI International, USA) by telephone.
December 2009.

Sverdrup, H. and I. Stjernquist. (editors) 2002. Managing Forest Ec osystems. Developing Principles and Models for Sustainable Forest ry in Sweden. Kluwer Academic Publishers, The Netherlands. 321 pp.

Sverdrup, H., W. de Vries, and A. Henriksen. 2001. Mapping Critical Loads. A guidance to the criteria, calculations data collection and mapping of cr itical loads. Milforapport (Environmental Report) 1990: 14. Nordic C ouncil of Ministers, Copenhagen, NORD: 1990: 98, 124 pp.

Sverdrup, H., P. Warfvinge, and T. Wickman. 1 998. Estimating the weathering rate at Gårdsjön using different methods. In: Hultberg, H. and R. Skeffington editors. 1998. Experimental Reversal of Acid Rain Effects: The Gårdsjön Roof Project. John Wiley & Sons Ltd. p. 232-249.

Sverdrup, H., W. de Vries, M. Hornung, M.S. Cr esser, S.J. Langan, B. Reynolds, R. Skeffington,
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Sverdrup, H.U. and P. Warfvinge. 1995. Estima ting field weathering rates using laboratory kinetics. IN: White, A. and S. Brantley editors. Weathering Kinetics of Silicate Minerals

. Volume 8. Reviews in Mineralogy, Minera logical Society of America. p. 485-541.Appendix B

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27 Sverdrup, H. and P. Warfvinge. 1993a. Calculatin g field weathering rates using a mechanistic geochemical model PROFILE. Applied Geochemistry

. 8 : 273-283.

Sverdrup, H., and P. Warfvinge. 1993b. The effect of soil acidificati on on the growth of trees, grass and herbs as expressed by the (Ca+ Mg+ K)/Al ratio . Reports in Ecology and Environmental Engineering 2. Lund University , Department of Chemical Engineering, Lund, Sweden.

Sverdrup, H., P. Warfvinge, M. Rabenhorst, A. Janicki, R. Morgan, and M. Bowman. 1992. Critical loads and steady-state chemistry for streams in the state of Maryland.
Environmental Pollution

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Sverdrup H.U. 1990. The Kinetics of Base Cation Rele ase Due to Chemical Weathering . Lund University Press, 246pp.

Sverdrup, H., W. de Vries, and A. Henriksen. 1990. Mapping Critical Loads . Miljörapport 14. Nordic Council of Ministers, Copenhagen, Denmark.
Sverdrup, H. and P. Warfvinge. 1988. Weathering of primary silicate minerals in the natural soil environment in relation to a chemical weathering model. Water, Air and Soil Pollution

. 38 : 387-408.

UNECE (United Nations Econom ic Commission for Europe). 2004. Manual on Methodologies and Criteria for Modeling and Mapping Criti cal Loads and Levels and Air Pollution Effects, Risks, and Trends. Convention on Long-Range Transboundary Air Pollution,
Geneva Switzerland. Available at http://www.icpmapping.org (accessed August 16, 2006).Appendix B

March 2010 95 Draft – Do Not Quote or Cite U.S. EPA, 2008. Integrated Science Assessment (ISA) for Oxides of Nitrogen and Sulfur– Ecological Criteria (Final Report) (ISA). U. S. Environmental Protection Agency, Office of Research and Development, National Cent er for Environmental Assessment, Research Triangle Park, NC. EPA/600/R-08/082. 1

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29 U.S. EPA, 2009. Risk and Exposure Assessment for Review of the Secondary National Ambient Air Quality Standards for Oxides of N itrogen and Oxides of Sulfur. Final . U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park , NC. EPA-452/R-09-008b.

Van Sickle, J., J.P. Baker, H.A. Simonin, B.P. Baldigo, W.A. Kretser, and W.E. Sharpe. 1996. Episodic acidification of small streams in the northeastern United States: Fish mortality in field bioassays. Ecological Applications 6 :408–421.
Velbel, M.A. and J.R. Price. 2007. Solute ge ochemical mass-balances and mineral weathering rates in small watersheds: Methodology, recent advances, and future directions. Applied Geochemistry 22 : 1682–1700.
Warfvinge, P. and H. Sverdrup. 1992. Calcula ting critical loads of acid deposition with PROFILE, a steady-state soil chemistry model. Water, Air and Soil Pollution

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143.

Watmough S.A., J. Aherne, and P.J. Dillion. 2004. Critical Loads Ontario: Relating Exceedance of the Critical Load with Biological Effects at Ontario Forests. Report 2. Environmental and Resource Studies, Trent University, ON, Canada. Watmough, S.A., J. Ahern, and P.J. Dillon. 2005. E ffect of declining base cation concentrations
on freshwater critical load calculations. Environmental Science & Technology. 39 : 3255-
3260.
Watmough, S., J. Aherne, P. Arp, I. DeMerchant , and R. Ouimet. 2006. Canadian experiences in development of critical loads for sulphur and nitrogen. Pp. 33–38 in Monitoring Science and Technology Symposium: Unifying Knowle dge for Sustainability in the Western Hemisphere Proceedings RMRS-P-42CD . Edited by C. Aguirre-Bravo, P.J. Pellicane, D.P. Burns, and S. Draggan. U.S. Departme nt of Agriculture, Forest Service, Rocky Mountain Research Station, Fort Collins, CO.Appendix B

March 2010 96 Draft – Do Not Quote or Cite Webb, J.R., Deviney, F. A., Galloway, J. N., Ri nehart, C. A., Thompson, P. A., & Wilson, S. (1994). The acid-base status of native brook trout streams in the mountains of Virginia; a regional assessment based on the Virginia trou t stream sensitivity study. Charlottesville, VA: University of Virginia. 1

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20 Webster K.L., I.F. Creed, N.S. Nicholas, and H.V. Miegroet. 2004

. Exploring interactions between pollutant emissions and climatic variability in growth of red spruce in the Great Smoky
Mountains National Park. Water, Air, and Soil Pollution 159: 225-248

. Wedemeyer, G.A., B.A. Barton, and D.J. MeLeay. 1990. Stress and acclimation. pp. 178–198 in Methods for Fish Biology . Edited by C.B. Schreck and P.B. Moyle. Bethesda, MD: American Fisheries Society.
Whitfield, C.J., S.A. Watmough, J. Aherne, and P.J. Dillon. 2006. A comparison of weathering
rates for acid-sensitive catchments in Nova Scotia, Canada and their impact on critical
load calculations. Geoderma

. 136 : 899-911.

Yin, X. and P.A. Arp. 1993. Predicting forest soil temperatures from monthly mean air temperature and precipitation records. Canadian Journal of Forest Research, 23 : 2521-
2536.

Zhai, J., C. T. Driscoll, T. J. Sullivan, and B. J. Cosby. 2008. Regional application of the PnETBGC model to assess historical ac idification of Adirondack lakes. Water Resources
Research 44 , W01421, doi:10.1029/2006WR005532.Appendix B

March 2010 97 Draft – Do Not Quote or Cite 

### APPENDIX 1 Potentially Applicable National-Scale Geochemical Data 1
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27 28 29 30 31 32 33 34 35 36 Currently, there are potentially three consistent national-scale data sets that are most appropriate for use in this project: the Shacklette data , the more recent National Geochemical Survey data, and the NRCS pedon soil pit (i.e., LIMS database).
Chemical Analyses of Soils and other Surfici al Materials of the Conterminous United States (Shacklette Data) & the Geochemical Landscapes Project These data provide an ultra-low-density geoc hemical baseline for soils and other surficial materials in the conterminous United States. It is the most widely cited reference for geochemical background data and the data are most appropriately used to provide information on background concentrations of el ements in soil for areas repr esented by small map scales. The data set contains geochemical data fr om soils and other regolith collected and analyzed by Hans Shacklette and colleagues be ginning in 1958 and continuing until about 1976. Originally compiled as a paper record, the data was later included as part of the original USGS PLUTO database. Approximately 1,323 samples were collected through 1976. The 1,323 sample locations that comprise the Shacklette data re present a sampling density of approximately 1 sample per 6,000 square kilometers (metadata); equivalent to the coll ection of samples on a 75- km grid across the country. The sampling protocol called for removal of loose organic debris from the surface and then collection of soil from a depth of 0-20 cm (Smith et al., 2005). Where possible, sample locations were selected where surf icial materials had been altered very little from their natural condition as evidenced by the pres ence of native plants. The sample material at most sites could be termed "soil" because it was a mixture of disi ntegrated rock and organi c matter. Some of the sampled deposits, however, were not soils as defi ned above, but were other regolith types. These included desert sands, sand dunes, some loess deposits, and beach and alluvial deposits that contained little or no vi sible organic material. This national-level geochemical data set of 1,323 samples has been collected and analyzed according to standardized protocols. This is considered one of the principal strengths of the data set overall. The samples were chemically analyzed by various bu t compatible techniques in the U.S. Geological Survey laboratories in Denver, CO. Geochemical point-symbol maps were plotted for 40 elemental results and published as USGS. Professional Paper 1270 (Shacklette and Boerngen, 1984). The original elements analyzed included: Ag, Al, Ba, Be, B, Ca, Ce, Cr, Co, Cu, Ga, Ge, Hg, Fe, La, Li, Pb, Mg, Mn, Mo, Na, Nd , Ni, Nb, P, K, Rb, S, Sc, Se, Sr, Th, Ti, U, V, Yb, Y, Zn, Zr, and total carbon. A newer set of national-level interpolated maps displaying the geochemical distribution for 22 elements using the Shacklette data has since been published (Gustavsson, et al, 2001). Using weighted-median and Bootstrap procedures for interpolation andAppendix B

March 2010 98 Draft – Do Not Quote or Cite smoothing, full-color maps were produced for seve n major elements (Al, Ca, Fe, K, Mg, Na, and Ti) and 15 trace elements (As, Ba, Cr, Cu, Hg, Li, Mn, Ni, Pb, Se, Sr, V, Y, Zn, and Zr). 1 2

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36 37 The major drawback with the data set is its extremely low numbers of samples for the entire conterminous United States. However, more recent high-resolution studies (e.g., Smith et al., 2005) have illustrated that the regional patterns es tablished by the Shacklette data are generally maintained except where areas have be en affected by anthropogenic factors (Smith, 2006). Efforts are also on-going to build upon the Shacklette data by incr easing the density of the sample locations and producing a high resolu tion geochemical data set for North America. Also referred to as the Geochemical Landscapes Project , this is a collaborative effort by the USGS, USDA Natural Resource Conservation Servi ce, other federal agencies, and academia to build a national-scale soil geochemical survey that will eventually increase the sample density of the Shacklette data set. The Geochemical La ndscapes project began in October 2002 in collaboration with partners in Canada (Geological Survey of Canada; Agriculture and Agri-Food Canada) and Mexico (Consejo de Recursos Mine rales/Servicio Geológico de México; Instituto Nacional de Estadística Geograf ia e Informática) that has as its long-term goal a soil geochemical survey of North America (Smith et al., 2005). A 3-year pilo t project was completed n 2004. During the pilot project soil samples were collected for major- and trace-elements from 265 soil samples collected from tw o continental-scale transects in North America (Smith et al., 2005). The project has just completed a third year of continental-sampling and completed sample collection for approximately 60% of th e conterminous United States (D. Smith personal communication, 2009). The state areas that have been co mpleted to date are: ME, NH, VT, CT, RI, MA, NY, MO, AR, MS, LA, NV, UT, CO, WY, KS, NJ, MD, WV, DE, NE, FL, SC, GA, AL, OK, NM, MT, ID, MN, and SD. The USGS antic ipates that sampling may be completed for the conterminous US in 2010; or 2011 at the late st. However, funding doesn’t allow for analyses to be completed for a number of samples and several hundred grams of each sample is being archived for on-going and future analysis.
National Geochemical Survey (NGS) Efforts are on-going by the USGS to produce a new stream-sediment-based geochemical survey for the United States at a nominal spac ing of 17 by 17 kilometers (i.e., minimum sample density of 1 sample per 289 km 2 in all land areas of the country ). Project mapping shows that the work is either complete or nearly completed. Unlike other national geochemical data collection efforts, the analytical routines and standards will be consistent throughout the survey. Analytical methods include a 40-element ICP package plus si ngle-element determinations of As, Se, and Hg by atomic absorption for every sample. The project has sought to capitalize on existi ng datasets and also achieved samples. For this reason the NGS is based primarily on analyses of stream sediments to build on the massiveAppendix B

March 2010 99 Draft – Do Not Quote or Cite achieves of data and samples from DOE’s National Uranium Evaluation (NURE) program. Much of the survey has entailed reanalysis of approximately 35,000 archival samples from the NURE program. Where NURE sample s do not exist, USGS has been working with cooperators to obtain new samples. The project website re ports a total of about 50,000 stream-sediment samples that have been analyzed for 42 elements, including arsenic, seleni um, and mercury. Last reported during 2004, only about 10,000 more samples needed to be collected and analyzed to complete the national survey. Samples are generally categorized as follows: 1 2 3 4 5 6 7

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30 31 32 33 34 35 36 37 38 3⁄4 Inherited Data : Much of the RASS and PLUTO data were inherited into the NGS;

8 3⁄4 Independent Reanalyses of NURE samples: These sample were reanalyzed by USGS 9 projects other than the NGS. Prior to th e NGS, numerous USGS projects reanalyzed samples from the NURE archives. Other USGS projects have continued to reanalyze NURE samples in parallel with the NGS. In the majority of these cases, most or all of the NURE samples in an ar ea were reanalyzed. 3⁄4 NURE-Systematic . Systematic reanalyses of NURE samples done by the NGS. An archive of stream sediment and soil sample s collected by the NURE program is stored at the USGS in Denver, Colo. Rules were establ ished to select a subset of samples for reanalysis that maintains the NGS coverage. 3⁄4 NURE-Targeted . Targeted reanalyses of NURE samples done by the NGS for various

reasons. 3⁄4 USGS-Resampling . Reanalyses of USGS archived project samples done by the NGS. The archive includes most of the samples for which there are analytical data in the National Geochemical Database, including th ose collected by USGS programs. 3⁄4 Collaborative Sampling with State Programs . Collaborative sampling programs by the USGS and states. Digital data files are presented in 6 categories. In total there are 43 individual data files for the United States. Some of the data has also b een processed into vector data to produce maps showing the elemental concentration of As, Se, Hg, Pb, Zn, Cu, Al, Na, Mg, P, Ca, Ti, Mn, and Fe at the county level.

USDA NRCS Soil Pedon Pit Data The USDA NRCS measures soil geochemical characteristics along with performing quantitative and bulk mineralogy tests and other physiochemical measurements for soil series delineated across the United States. This data set and associated detail was discovered through communication with NRCS staff (C. Smith personal communication, 2009; T. Reinsch personal communication , 2009). Most of the geochemical and mi neralogy data is associated with individual soil pedons. The NRCS de fines a pedon as the smallest unit that can be called a soil. It is a three-dimensional sample that extends from the soil surface to the deepest roots or genetic soil horizons. The area covere d by a pedon varies from 10 - 100 square feet, depending on changes in soil properties. Pits are dug to expos e the pedons and the NRCS generally refers toAppendix B

March 2010 100 Draft – Do Not Quote or Cite the data associated with the pe dons as soil pit data. There are cu rrently approximately 30,000 soil pits/pedons in the NRCS database. 1 2

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15 16 17 18 19 20 21 22 23 24 25

26 27 28 29 30 31 32 33 34 35 36 37 38 39 Groups of pedons with very similar characteri stics that are closely associated in the landscape are called polypedons. Polypedons that have a common set of characteristics that fall within a particular range are delin eated as a basic soil unit referred to as a soil series which have been identified as the basic unit of the proposed data framework, as previously discussed. The same soil series delineations can occur in differe nt and distant areas (i.e., across county areas, states, or regions). A variety of data are used to define a soil (e.g., ge omorphic position in the landscape, relationship to the wa ter-table, supported flora, geology, number and type of horizons, sediment texture, sediment color variations, etc.), and therefore geochemical and mineralogy data has not been collected from every soil pedon associated with an individual series of the same name since associations can be made based on a number of these other related characteristics. However, geochemical and quant itative mineralogy data has been measured for a significant number of pedons and soil series locations across the country. Since soils of the same series name possess enough similarities to be classified as similar soils it is thought that the geochemistry data can also be extrapolated to pedons of like soil series (C. Smith personal communication , 2009). Assigning mineral phases to the soil series that do not have either geochemical or mineralogy data associated with their pedons will require professional judgment by researchers familiar with the soil pit data and soil taxonomy to make geochemical data extrapolations with a degree of confidence. In these case s the characteristics of surrounding soils would be used to extrapolate geochemistry or mi neralogy, or another data set could be used to aid in the characterization. GI S tools would be used to help automate these determinations where necessary. NRCS staff woul d aid RTI in determining rules and developing database relationship tables that could be used in automating any extrapolation of this data. The NRCS would also aid RTI in evaluati ng the reasonableness of the results.

Since soil series are delineated across the conterminous United States the pit data could potentially provide a complete geochemical and mineralogy data layer for determining mineralogy. Since mineralogy is already associat ed with the geochemical data a more accurate assignment of mineral modes may be possible using this data se t. Laboratory analysis includes the major geochemical elements: Al, Ca, Fe, K, Mg , Mn, Na, P, Si, Sr, Ti, and Zr. In addition, xray diffraction is used to indentify clay mine ralogy generally for each horizon of a pedon, and optical mineralogy analysis is performed on the dominant sand fractions of the soil from the Ahorizon, B-horizon, and C-horizon, or the most do minant horizon. More th an 60 fields describing the minerals are listed in the database. The dataset is not uniform in that elemental analyses were routinely done through the 1970’s but then thes e analyses were suspended through the 1980’s. Elemental analyses were resumed during the early 1990’s. It is estimated that as much as one third of the 30,000 soil pedons have geochemical data. Likewise, optical mineralogy is not performed for all pedons and the NRCS staff estimat e that approximately as many as one third of the 30,000 soil pits have optical analysis results. Even though the number of pedons with data areAppendix B

March 2010 101 Draft – Do Not Quote or Cite similar for geochemical and optical analysis results the data is not necessar ily associated with the same set of pedons or even soil series. 1 2

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8

9 References
Smith, Chris, 2009. Personal communication be tween Chris Smith, (affiliation) and Scott Guthrie, RTI International, 12/16/09.
Reinsch, Thomas, 2009. Personal communication between Thomas Reinsch, (affiliation) and Scott Guthrie, RTI International, 12/18/09.Appendix B

March 2010 102 Draft – Do Not Quote or Cite 

### APPENDIX 2 References for Table 3-2: App lications of the MAGIC Model 1
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25 Aherne, J, P.J. Dillon, and B.J. Cosby. 2003. Acid ification and recovery of aquatic ecosystems in south central Ontario, Canada: region al application of the MAGIC model. Hydrol. Earth Syst. Sci 7 : 561-573.

Bernett, J.A., J.M. Eilers, and B.J. Cosby. 1997. Overview, Libby Lake Modeling Workshop. E&S Environmental Chemistry, Inc., Corvallis, OR.

Bulger A.J., B.J. Cosby, and J.R. Webb. 2000. Cu rrent, reconstructed past , and projected future status of brook trout ( Salvelinus fontinalis ) streams in Virginia. Canadian Journal of Fish and Aquatic Science 57:1515-1523.

Bulger, A.J., C.A. Dolloff, B.J. Cosby, K.N. Eshleman, J.R. Webb, and J.N. Galloway. 1995. Sensitivity of Blacknose Dace ( Rhinichthys Atratulus ) to Moderate Acidification Events in Shenandoah National Park, U.S.A. Water, Air, & Soil Pollution 153 (1-4): 125-134.

Church, M. R. and J. Van Sickle. 1999. Potentia l relative future effects of sulfur and nitrogen deposition on lake chemistry in th e Adirondack Mountains, United States. Water
Resource. Res. 35 : 2199-2211.

Cosby, B.J. and T.J. Sullivan. 2001. Quantifica tion of dose-response rela tionships and critical loads of sulfur and nitrogen for six head water catchments in Rocky Mountain, Grand Teton, Sequoia, and Mount Rainer national parks. E&S Report 97-15-01.

Dennis, I.F., T.A. Clair, and B.J. Cosby. 2005. Testing the MAGIC acid rain model in highly organic, low-conductivity wate rs using multiple calibrations. Environmental Modeling
and Assessment 10 (4): 303-314.

Eilers J.M., B.J. Cosby, J.A. Bernet, and T.A. Sullivan. 1998. Analysis of the Response of Shasta Lake, Idaho to Increases in Atmospheri c Sulfur and Nitroge n Using the MAGIC MODEL. E&S Environmental Chemistry, Inc., Corvallis, OR.Appendix B

March 2010 103 Draft – Do Not Quote or Cite Ellis, H., and M. Bowman. 1994. Critical Loads a nd Development of Acid Rain Control Options. Journal of Environmental Engineering 120 (2): 273-289 1

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26 Sinha, R., M.J. Small, P.F. Ryan, T.J. Sullivan, and B.J. Cosby. 1998. Reduced-Form Modelling of Surface Water and Soil Chemistry for the Tracking and Analysis Framework. Water, Air, & Soil Pollution 105 (3-4): 617-642.

Sullivan, T.J. and B.J. Cosby. 2004. Aquatic Critical Load Development for the Monongahela National Forest, West Virginia. Report prepared for the USDA Forest Service Monongahela National Forest.

Sullivan, T.J. and B.J. Cosby. 2002. Critical Lo ads of Sulfur Deposition to Protect Streams within Joyce Kilmer and Shining Rock Wilderness Areas from Future Acidification. Report for the USDA Forest Service.

Sullivan, T.J., and J.M. Eilers. 1996. Assessment of Deposition Levels of sulfur and Nitrogen Required to Protect Aquatic Resources in Se lected Sensitive Regions of North America. E and S Environmental Chemistry, EP A/600/R-96-123, Corvallis Environmental Research Lab, OR.

Sullivan, T.J., B.J. Cosby, K.A. Tonnessen, and D.W. Clow. 2005. Surface water acidification responses and critical loads of sulfur and nitrogen deposition in Loch Vale watershed,
Colorado. Water Resources Research 41 : WO1021.

Sullivan, T.J., B.J. Cosby, A.T. Herlihy, J.R. Webb, A.J. Bulger, K.U. Snyder, P.F. Brewer, E.H. Gilbert, and D.L. Moore. 2004. Regional model pr ojections of future ef fects of sulfur and nitrogen deposition on streams in the southern Appalachian Mountains. Water Resour.
Res. 40 : W02101.

Sullivan, T.J., B.J. Cosby, J.A. Bernert, and J.M. Eilers. 1998. Model Evaluation of dose/response relationships and critical load s for nitrogen and sulf ur deposition to the watersheds of lower saddlebag and white dome lakes.United StatesEnvironmental ProtectionAgencyOffice of Air Quality Planning and StandardsHealth and Environmental Impacts DivisionResearch Triangle Park, NCPublication No. EPA-452/P-10-006March, 2010