Risk and Exposure Assessment for Review 

of the Secondary National Ambient Air Quality 

Standards for Oxides of Nitrogen and 

Oxides of Sulfur 

Final 

Main Content 

Photo courtesy of the National Park Service 

EPA-452/R-09-008a 

September 2009 

Risk and Exposure Assessment for Review of the Secondary National Ambient Air Quality 

Standards for Oxides of Nitrogen and Oxides of Sulfur 

Final 

Main Content 

U.S. Environmental Protection Agency 

Office of Air Quality Planning and Standards 

Health and Environmental Impacts Division 

Research Triangle Park, NC 
DISCLAIMER 

This document has been prepared by staff from the Health and Environmental Impacts 

and Air Quality Analysis Divisions of the Office of Air Quality Planning and Standards, the 

Clean Air Markets Division, Office of Air Programs, the National Center for Environmental 

Assessment, Office of Research and Development, and the National Health and Environmental 

Effects Research Laboratory, Office of Research and Development, U.S. Environmental 

Protection Agency. Any opinions, findings, conclusions, or recommendations are those of the 

authors and do not necessarily reflect the views of EPA. Questions concerning this document 

should be addressed to Dr. Anne Rea, U.S. Environmental Protection Agency, Office of Air 

Quality Planning and Standards, C539-02, Research Triangle Park, North Carolina 27711 (email: 

rea.anne@epa.gov). 
Table of Contents 

TABLE OF CONTENTS 

List of Appendices ......................................................................................................................... iv 

List of Figures ................................................................................................................................ iv 

List of Tables ................................................................................................................................ xv 

Acronyms and Abbreviations ...................................................................................................... xix 

Key Terms .................................................................................................................................. xxiii 

Executive Summary .................................................................................................................. ES-1 

1.0 Introduction ............................................................................................................................ 1-1 

1.1 Rationale and Background for Joint Review ................................................................ 1-1 

1.2 History........................................................................................................................... 1-4 

1.2.1 History of the Secondary NO2 NAAQS............................................................ 1-4 

1.2.2 History of the Secondary SO2 NAAQS ............................................................ 1-5 

1.2.3 History of Related Assessments and Agency Actions ...................................... 1-7 

1.3 Scope of the Risk and Exposure Assessment for the Current Review ......................... 1-9 

1.3.1 Species of Nitrogen Included in the Analyses .................................................. 1-9 

1.3.2 Species of Sulfur Included in the Analyses .................................................... 1-12 

1.3.3 Overview of Nitrogen- and Sulfur-Related Ecological Effects ...................... 1-12 

1.4 Framing Questions for the Risk and Exposure Assessment ....................................... 1-17 

1.5 References ................................................................................................................... 1-21 

2.0 Overview of Risk and Exposure Assessment ........................................................................ 2-1 

2.1 Introduction ................................................................................................................... 2-1 

2.2 Seven-Step Approach.................................................................................................... 2-7

2.3 Linkages for Structuring Ecologically Relevant Standards .......................................... 2-8 

2.4 Ecosystem Services ..................................................................................................... 2-10 

2.4.1 Aquatic Acidification ...................................................................................... 2-19 

2.4.2 Terrestrial Acidification .................................................................................. 2-19 

2.4.3 Aquatic Nutrient Enrichment .......................................................................... 2-19 

2.4.4 Terrestrial Nutrient Enrichment ...................................................................... 2-19 

2.4.5 Sulfur and Mercury Methylation .................................................................... 2-20 

2.5 Uncertainty .................................................................................................................. 2-22 

2.6 References ................................................................................................................... 2-28 

3.0 Sources, Ambient Concentrations, and Deposition ............................................................... 3-1 

3.1 Science Overview ......................................................................................................... 3-2 

3.2 Nationwide Sources, Concentrations, and Deposition of NOx, NH3, and SOx ............. 3-3 

3.2.1 Sources of Nitrogen and Sulfur......................................................................... 3-3 

3.2.2 Nationwide Atmospheric Concentrations of NOx and SOx ............................ 3-11 

3.2.3 Nationwide Deposition of Nitrogen and Sulfur .............................................. 3-16 

3.2.4 Policy-Relevant Background Concentrations ................................................. 3-23 

3.2.5 Non-atmospheric Loadings of Nitrogen and Sulfur........................................ 3-24 

3.3 Spatial and Temporal Characterization of Deposition for Case Study Areas ............. 3-25 

3.3.1 Purpose and Intent ........................................................................................... 3-25 

3.3.2 Data and Analytical Techniques ..................................................................... 3-25 

Final Risk and Exposure Assessment i September 2009 
Table of Contents 

3.3.3 Characterization of Deposition in Case Study Areas ...................................... 3-27 

3.4 Contributions of Emissions of NOx and NH3 to Deposition of Nitrogen ................... 3-83 

3.4.1 Purpose and Intent ........................................................................................... 3-83 

3.4.2 Analytical Techniques .................................................................................... 3-83 

3.4.3 Results and Findings ....................................................................................... 3-84 

3.4.4 Summary of Findings ...................................................................................... 3-86 

3.5 Relationships between Deposition and Concentrations .............................................. 3-93 

3.6 Discussion of Uncertainties ........................................................................................ 3-97 

3.6.1 Uncertainties Associated with Use of Model Predictions ............................... 3-98 

3.6.2 Uncertainties Associated with Use of Measured Data .................................. 3-102 

3.6.3 Uncertainties of Wet Deposition in Complex Terrain .................................. 3-103 

3.7 References ................................................................................................................. 3-108 

4.0 Acidification .......................................................................................................................... 4-1 

4.1 Science Overview ......................................................................................................... 4-1 

4.1.1 Aquatic Acidification ........................................................................................ 4-2 

4.1.2 Terrestrial Acidification .................................................................................... 4-3 

4.2 Aquatic Acidification .................................................................................................... 4-3 

4.2.1 Ecological Indicators, Ecological Responses, and Ecosystem Services ........... 4-5 

4.2.2 Characteristics of Sensitive Areas .................................................................... 4-8 

4.2.3 Case Study Area Selection .............................................................................. 4-10 

4.2.4 Current Conditions in Case Study Areas ........................................................ 4-14 

4.2.5 Degree of Extrapolation to Larger Assessment Areas .................................... 4-34 

4.2.6 Current Conditions for the Adirondack Case Study Area and the 

Shenandoah Case Study Area ......................................................................... 4-37 

4.2.7 Ecological Effect Function for Aquatic Acidification .................................... 4-39 

4.2.8 Uncertainty and Variability ............................................................................. 4-42 

4.3 Terrestrial Acidification .............................................................................................. 4-53 

4.3.1 Ecological Indicators, Ecological Responses, and Ecosystem Services ......... 4-53 

4.3.2 Characteristics of Sensitive Areas .................................................................. 4-62 

4.3.3 Case Study Selection....................................................................................... 4-64 

4.3.4 Current Conditions Assessment ...................................................................... 4-65 

4.3.5 Results for the Case Study Areas .................................................................... 4-69 

4.3.6 Evaluation of Representativeness of Case Study Areas ................................. 4-73 

4.3.7 Current Conditions for Sugar Maple and Red Spruce .................................... 4-75 

4.3.8 Ecological Effect Function for Terrestrial Acidification ................................ 4-78 

4.3.9 Uncertainty and Variability ............................................................................. 4-81 

4.4 Summary and Key Findings........................................................................................ 4-84 

4.5 References ................................................................................................................... 4-86 

5.0 Nutrient Enrichment ............................................................................................................... 5-1 

5.1 Science Overview ......................................................................................................... 5-1 

5.1.1 Aquatic Nutrient Enrichment ............................................................................ 5-3 

5.1.2 Terrestrial Nutrient Enrichment ........................................................................ 5-3 

5.2 Aquatic Nutrient Enrichment ........................................................................................ 5-4 

5.2.1 Ecological Indicators, Ecological Responses, and Ecosystem Services ........... 5-5 

5.2.2 Characteristics of Sensitive Areas .................................................................. 5-17 

5.2.3 Case Study Selection....................................................................................... 5-20 

Final Risk and Exposure Assessment ii September 2009 
Table of Contents 

5.2.4 Current Conditions in the Case Study Areas .................................................. 5-22 

5.2.5 Degree of Extrapolation to Larger Assessment Areas .................................... 5-32 

5.2.6 Current Conditions for Other/Additional Estuaries ........................................ 5-35 

5.2.7 Ecological Effect Function for Aquatic Nutrient Enrichment ........................ 5-36 

5.2.8 Uncertainty and Variability ............................................................................. 5-44 

5.3 Terrestrial Nutrient Enrichment .................................................................................. 5-47 

5.3.1 Ecological Indicators, Ecological Responses, and Ecosystem Services ......... 5-48 

5.3.2 Characteristics of Sensitive Areas .................................................................. 5-58 

5.3.3 Case Study Selection....................................................................................... 5-60 

5.3.4 Current Conditions in Case Study Areas ........................................................ 5-62 

5.3.5 Degree of Extrapolation to Larger Assessment Areas .................................... 5-74 

5.3.6 Current Conditions for Select Locations Nationwide ..................................... 5-76 

5.3.7 Ecological Effect Function for Terrestrial Nutrient Enrichment .................... 5-85 

5.3.8 Uncertainty and Variability ............................................................................. 5-85 

5.4 Conclusions ................................................................................................................. 5-87 

5.5 Summary and Key Findings........................................................................................ 5-87 

5.5.1 Aquatic Nutrient Enrichment .......................................................................... 5-87 

5.5.2 Terrestrial Nutrient Enrichment ...................................................................... 5-88 

5.6 References ................................................................................................................... 5-89 

6.0 Additional Effects .................................................................................................................. 6-1 

6.1 Visibility, Climate, and Materials ................................................................................. 6-1 

6.1.1 Nitrous Oxide .................................................................................................... 6-2 

6.2 Sulfur and Mercury Methylation .................................................................................. 6-3 

6.2.1 Science Background.......................................................................................... 6-4 

6.2.2 Qualitative Analysis .......................................................................................... 6-5 

6.3 Nitrogen Addition Effects on Primary Productivity and Biogenic Greenhouse 

Gas Fluxes................................................................................................................... 6-13 

6.3.1 Effects on Primary Productivity and Carbon Budgeting ................................ 6-13 

6.3.2 Biogenic Emissions of Nitrous Oxide............................................................. 6-20 

6.3.3 Methane Emissions and Uptake ...................................................................... 6-22 

6.3.4 Emission Factors ............................................................................................. 6-24 

6.3.5 Uncertainty ...................................................................................................... 6-25 

6.4 Direct Phytotoxic Effects of Gaseous SOx and NOx ................................................... 6-26 

6.4.1 SO2 .................................................................................................................. 6-26 

6.4.2 NO, NO2, and Peroxyacetyl Nitrate (PAN) .................................................... 6-27 

6.4.3 Nitric Acid (HNO3) ......................................................................................... 6-29 

6.5 Summary and Key Findings........................................................................................ 6-31 

6.6 References ................................................................................................................... 6-32 

7.0 Synthesis and Integration of Case Study Results ................................................................... 7-1 

7.1 Aquatic Acidification .................................................................................................... 7-2 

7.1.1 Available Data .................................................................................................. 7-2 

7.1.2 Modeling Approach .......................................................................................... 7-5 

7.1.3 Ecological Effect Function ............................................................................. 7-12 

7.1.4 Data Gaps and Research Needs ...................................................................... 7-15 

7.2 Terrestrial Acidification .............................................................................................. 7-16 

7.2.1 Available Data ................................................................................................ 7-16 

Final Risk and Exposure Assessment iii September 2009 
Table of Contents 

7.2.2 Modeling Approach ........................................................................................ 7-19 

7.2.3 Ecological Effect Function ............................................................................. 7-20 

7.2.4 Data Gaps and Research Needs ...................................................................... 7-22 

7.3 Aquatic Nitrogen Enrichment ..................................................................................... 7-22 

7.3.1 Available Data ................................................................................................ 7-22 

7.3.2 Modeling Approach ........................................................................................ 7-23 

7.3.3 Ecological Effect Function ............................................................................. 7-24 

7.3.4 Data Gaps and Research Needs ...................................................................... 7-25 

7.4 Terrestrial Nitrogen Enrichment ................................................................................. 7-26 

7.4.1 Available Data ................................................................................................ 7-26 

7.4.2 Modeling Approach ........................................................................................ 7-29 

7.4.3 Ecological Effect Function ............................................................................. 7-29 

7.4.4 Data Gaps and Research Needs ...................................................................... 7-30 

7.5 Conclusions ................................................................................................................. 7-30 

7.6 References ................................................................................................................... 7-35 

LIST OF APPENDICES 

Appendix 1 Description of CMAQ Applications and Model Performance Evaluation 

Appendix 2 Trends in Wet Deposition at NADP Sites 

Appendix 3 Components of Reactive Nitrogen Deposition: 2002–2005 

Appendix 4 Aquatic Acidification Case Study 

Attachment A Modeling Descriptions 

Attachment B EMAP/TIME/LTM Programs 

Appendix 5 Terrestrial Acidification Case Study 

Attachment A Relationship Between Atmospheric Nitrogen and Sulfur 

Deposition and Sugar Maple and Red Spruce Tree Growth 

Appendix 6 Aquatic Nutrient Enrichment Case Study 

Appendix 7 Terrestrial Nutrient Enrichment Case Study 

Appendix 8 Analysis of Ecosystem Services Impacts for the NOx/SOx Secondary 

NAAQS Review 

LIST OF FIGURES 

Figure 1.3-1. Schematic diagram of the cycle of reactive, oxidized nitrogen species in the 

atmosphere. Particulate-phase organic nitrates are also formed from the 

species on the right side of the figure (U.S. EPA, 2008). ................................ 1-11 

Figure 1.3-2. Schematic diagram of the cycle of sulfur species in the atmosphere ................... 1-12 

Figure 1.3-3. Nitrogen and sulfur cycling and interactions in the environment. ....................... 1-17 

Figure 1.4-1. Possible structure of a secondary NAAQS for NOx and SOx based on an 

ecological indicator. ........................................................................................ 1-20 

Final Risk and Exposure Assessment iv September 2009 
Table of Contents 

Figure 2.1-1. National map highlighting the eight case study areas and the Rocky 

Mountain National Park (a supplemental study area) evaluated in the 

Risk and Exposure Assessment. ........................................................................ 2-5 

Figure 2.3-1. Possible structure of a secondary NAAQS for NOx and SOx based on an 

ecological indicator. .......................................................................................... 2-9 

Figure 2.4-1. This figure depicts the strength of linkages between categories of ecosystem 

services and components of human well-being that are commonly 

indications of the extent to which it is possible for socioeconomic factors 

to mediate the linkage. (For example, if it is possible to purchase a 

substitute for a degraded ecosystem service, then there is a high potential 

for mediation.) The strength of the linkages, as indicated by arrow width, 

and the potential for mediation, as indicated by arrow color, differ in 

different ecosystems and regions (MEA, 2005a). ........................................... 2-12 

Figure 2.4-2. Representation of the benefits assessment process indicating where some 

ecological benefits may remain unrecognized, unquantified, or 

unmonetized. (Modified based on the Ecological Benefits Assessment 

Strategic Plan report [U.S. EPA, 2006]). ......................................................... 2-14 

Figure 2.4-3. Conceptual model showing the relationships among ambient air quality 

indicators and exposure pathways and the resulting impacts on 

ecosystems, ecological responses, effects, and benefits to characterize 

known or anticipated adverse effects to public welfare. ................................. 2-16 

Figure 2.4-4. Pathway from nitrogen deposition to valuation for an aquatic system. ............... 2-18 

Figure 3.2-1. Spatial distribution of annual total NOx emissions (tons/yr) for 2002. .................. 3-7 

Figure 3.2-2. Spatial distribution of annual total NH3 emissions (tons/yr) for 2002. .................. 3-8 

Figure 3.2-3. Spatial distribution of annual total SO2 emissions (tons/yr) for 2002. ................ 3-11 

Figure 3.2-4. Model-predicted annual average NOy concentrations (ppb) for 2002. ................ 3-14 

Figure 3.2-5. Model-predicted annual average SO2 concentrations (ppb) for 2002. ................. 3-16 

Figure 3.2-6. Total wet plus dry oxidized nitrogen deposition (kg N/ha/yr) in 2002. ............... 3-20 

Figure 3.2-7. Total wet plus dry reduced nitrogen deposition (kg N/ha/yr) in 2002. ................ 3-21 

Figure 3.2-8 Total reactive nitrogen deposition (kg N/ha/yr) in 2002. ...................................... 3-22 

Figure 3.2-9. Total wet and dry sulfur deposition (kg S/ha/yr) in 2002. ................................... 3-23 

Figure 3.3-1a. Annual total reactive nitrogen deposition (kg N/ha/yr) from 2002 through 

2005 for each case study area in the East. ....................................................... 3-31 

Figure 3.3-1b. Annual total reactive nitrogen deposition (kg N/ha/yr) from 2002 through 

2005 for case study areas in the West, and the Rocky Mountain National 

Park. ................................................................................................................. 3-32 

Figure 3.3-2. Relative amounts of oxidized and reduced nitrogen deposition in 2002 for 

case study areas and the Rocky Mountain National Park. ............................... 3-34 

Figure 3.3-3a. Components of total reactive nitrogen deposition for 2002 in the 

Adirondack Case Study Area. ......................................................................... 3-34 

Figure 3.3-3b. Components of total reactive nitrogen deposition for 2002 in the Hubbard 

Brook Experimental Forest Case Study Area. ................................................. 3-35 

Figure 3.3-3c. Components of total reactive nitrogen deposition for 2002 in the Kane 

Experimental Forest Case Study Area. ............................................................ 3-35 

Figure 3.3-3d. Components of total reactive nitrogen deposition for 2002 in the Neuse 

River/Neuse River Estuary Case Study Area. ................................................. 3-36 

Final Risk and Exposure Assessment v September 2009 
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Figure 3.3-3e. Components of total reactive nitrogen deposition for 2002 in the Potomac 

River/Potomac Estuary Case Study Area. ....................................................... 3-36 

Figure 3.3-3f. Components of total reactive nitrogen deposition for 2002 in the 

Shenandoah Case Study Area. ......................................................................... 3-37 

Figure 3.3-3g. Components of total reactive nitrogen deposition for 2002 in the Rocky 

Mountain National Park. ................................................................................. 3-37 

Figure 3.3-3h. Components of total reactive nitrogen deposition for 2002 in the Sierra 

Nevada Range portion of the Mixed Conifer Forest Case Study Area. .......... 3-38 

Figure 3.3-3i. Components of total reactive nitrogen deposition for 2002 in the 

Transverse Range portion of the Mixed Conifer Forest Case Study Area. ..... 3-38 

Figure 3.3-4a. Annual total dry plus wet reactive nitrogen deposition (kg N/ha/yr) in 2002 

for the case study areas in the East. ................................................................. 3-43 

Figure 3.3-4b. Annual total dry plus wet oxidized nitrogen deposition (kg N/ha/yr) in 

2002 for the case study areas in the East. ........................................................ 3-44 

Figure 3.3-4c. Annual total dry plus wet reduced nitrogen deposition (kg N/ha/yr) in 2002 

for the case study areas in the East. ................................................................. 3-45 

Figure 3.3-4d. Annual total wet reactive nitrogen deposition (kg N/ha/yr) in 2002 for the 

case study areas in the East. ............................................................................ 3-46 

Figure 3.3-4e. Annual total dry reactive nitrogen deposition (kg N/ha/yr) in 2002 for the 

case study areas in the East. ............................................................................ 3-47 

Figure 3.3-5a. Annual total dry plus wet reactive nitrogen deposition (kg N/ha/yr) in 2002 

for case study areas and Rocky Mountain National Park in the West. ............ 3-48 

Figure 3.3-5b. Annual total dry plus wet oxidized nitrogen deposition (kg N/ha/yr) in 

2002 for case study areas and Rocky Mountain National Park in the 

West. ................................................................................................................ 3-49 

Figure 3.3-5c. Annual total dry plus wet reduced nitrogen deposition (kg N/ha/yr) in 2002 

for case study areas and Rocky Mountain National Park in the West. ............ 3-50 

Figure 3.3-6a. Percentage of 2002 total reactive nitrogen deposition in the Adirondack 

Case Study Area. ............................................................................................. 3-52 

Figure 3.3-6b. Percentage of 2002 total reactive nitrogen deposition in the Hubbard 

Brook Experimental Forest Case Study Area. ................................................. 3-52 

Figure 3.3-6c. Percentage of 2002 total reactive nitrogen deposition in the Kane 

Experimental Forest Case Study Area. ............................................................ 3-53 

Figure 3.3-6d. Percentage of 2002 total reactive nitrogen deposition in the Potomac 

River/Potomac Estuary Case Study Area. ....................................................... 3-53 

Figure 3.3-6e. Percentage of 2002 total reactive nitrogen deposition in the Shenandoah 

Case Study Area. ............................................................................................. 3-54 

Figure 3.3-6f. Percentage of 2002 total reactive nitrogen deposition in the Neuse 

River/Neuse River Estuary Case Study Area. ................................................. 3-54 

Figure 3.3-6g. Percentage of 2002 total reactive nitrogen deposition in the Rocky 

Mountain National Park. ................................................................................. 3-55 

Figure 3.3-6h. Percentage of 2002 total reactive nitrogen deposition in the Sierra Nevada 

Range portion of the Mixed Conifer Forest Case Study Area. ........................ 3-55 

Figure 3.3-6i. Percentage of 2002 total reactive nitrogen deposition in the Transverse 

Range portion of the Mixed Conifer Forest Case Study Area. ........................ 3-56 

Final Risk and Exposure Assessment vi September 2009 
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Figure 3.3-7a. Percentage of 2002 reactive nitrogen deposition for each component of 

nitrogen deposition in the Adirondack Case Study Area. ............................... 3-56 

Figure 3.3-7b. Percentage of 2002 reactive nitrogen deposition for each component of 

nitrogen deposition in the Hubbard Brook Experimental Forest Case 

Study Area. ...................................................................................................... 3-57 

Figure 3.3-7c. Percentage of 2002 reactive nitrogen deposition for each component of 

nitrogen deposition in the Kane Experimental Forest Case Study Area. ........ 3-57 

Figure 3.3-7d. Percentage of 2002 reactive nitrogen deposition for each component of 

nitrogen deposition in the Potomac River/Potomac Estuary Case Study 

Area. ................................................................................................................ 3-58 

Figure 3.3-7e. Percentage of 2002 reactive nitrogen deposition for each component of 

nitrogen deposition in the Shenandoah Case Study Area. ............................... 3-58 

Figure 3.3-7f. Percentage of 2002 reactive nitrogen deposition for each component of 

nitrogen deposition in the Neuse River/Neuse River Estuary Case Study 

Area. ................................................................................................................ 3-59 

Figure 3.3-7g. Percentage of 2002 reactive nitrogen deposition for each component of 

nitrogen deposition in the Rocky Mountain National Park. ............................ 3-59 

Figure 3.3-7h. Percentage of 2002 reactive nitrogen deposition for each component of 

nitrogen deposition in the Sierra Nevada Range portion of the Mixed 

Conifer Forest Case Study Area. ..................................................................... 3-60 

Figure 3.3-7i. Percentage of 2002 reactive nitrogen deposition for each component of 

nitrogen deposition in the Transverse Range portion of the Mixed 

Conifer Forest Case Study Area. ..................................................................... 3-60 

Figure 3.3-8. Percentage of 2002 NH3 emissions by season for each state containing a 

case study area. ................................................................................................ 3-61 

Figure 3.3-9a. Annual sulfur deposition (kg S/ha/yr) from 2002 through 2005 for each 

case study area in the East. .............................................................................. 3-63 

Figure 3.3-9b. Annual sulfur deposition (kg S/ha/yr) from 2002 through 2005 for case 

study areas in the West, as well as the Rocky Mountain National Park. ........ 3-63 

Figure 3.3-10. Relative amount of wet and dry annual sulfur deposition in 2002 for case 

study areas. ...................................................................................................... 3-65 

Figure 3.3-11. Relative amount of wet and dry annual sulfur deposition based on 

deposition for the period 2002 through 2005 for each case study area and 

the Rocky Mountain National Park. ................................................................ 3-65 

Figure 3.3-12a. Annual total dry plus wet sulfur deposition (kg S/ha/yr) in 2002 for the 

case study areas in the East. ............................................................................ 3-68 

Figure 3.3-12b. Annual wet sulfur deposition (kg S/ha/yr) in 2002 for the case study areas 

in the East. ....................................................................................................... 3-69 

Figure 3.3-12c. Annual dry sulfur deposition (kg S/ha/yr) in 2002 for the case study areas 

in the East. ....................................................................................................... 3-70 

Figure 3.3-13. Annual total dry plus wet sulfur deposition (kg S/ha/yr) in 2002 for case 

study areas and Rocky Mountain National Park in the West. ......................... 3-71 

Figure 3.3-14a. Percentage of 2002 total sulfur deposition in the Adirondack Case Study 

Area. ................................................................................................................ 3-73 

Figure 3.3-14b. Percentage of 2002 total sulfur deposition in the Hubbard Brook 

Experimental Forest Case Study Area. ............................................................ 3-73 

Final Risk and Exposure Assessment vii September 2009 
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Figure 3.3-14c. Percentage of 2002 total sulfur deposition in the Kane Experimental 

Forest Case Study Area. .................................................................................. 3-74 

Figure 3.3-14d. Percentage of 2002 total sulfur deposition in the Potomac River/Potomac 

Estuary Case Study Area. ................................................................................ 3-74 

Figure 3.3-14e. Percentage of 2002 total sulfur deposition in the Shenandoah Case Study 

Area. ................................................................................................................ 3-75 

Figure 3.3-14f. Percentage of 2002 total sulfur deposition in the Neuse River/Neuse River 

Estuary Case Study Area. ................................................................................ 3-75 

Figure 3.3-14g. Percentage of 2002 total sulfur deposition in the Rocky Mountain 

National Park. .................................................................................................. 3-76 

Figure 3.3-14h. Percentage of 2002 total sulfur deposition in the Sierra Nevada Range 

portion of the Mixed Conifer Forest Case Study Area. ................................... 3-76 

Figure 3.3-14i. Percentage of 2002 total sulfur deposition in the Transverse Range 

portion of the Case Study Area. ...................................................................... 3-77 

Figure 3.3-15a. Percentage of 2002 deposition for each component of sulfur deposition in 

the Adirondack Case Study Area. ................................................................... 3-77 

Figure 3.3-15b. Percentage of 2002 deposition for each component of sulfur deposition in 

the Hubbard Brook Experimental Forest Case Study Area. ............................ 3-78 

Figure 3.3-15c. Percentage of 2002 deposition for each component of sulfur deposition in 

the Kane Experimental Forest Case Study Area. ............................................ 3-78 

Figure 3.3-15d. Percentage of 2002 deposition for each component of sulfur deposition in 

the Potomac River/Potomac Estuary Case Study Area. .................................. 3-79 

Figure 3.3-15e. Percentage of 2002 deposition for each component of sulfur deposition in 

the Shenandoah Case Study Area. ................................................................... 3-79 

Figure 3.3-15f. Percentage of 2002 deposition for each component of sulfur deposition in 

the Neuse River/Neuse River Estuary Case Study Area. ................................ 3-80 

Figure 3.3-15g. Percentage of 2002 deposition for each component of sulfur deposition in 

the Rocky Mountain National Park. ................................................................ 3-80 

Figure 3.3-15h. Percentage of 2002 deposition for each component of sulfur deposition in 

the Sierra Nevada Range portion of the Mixed Conifer Forest Case Study 

Area. ................................................................................................................ 3-81 

Figure 3.3-15i. Percentage of 2002 deposition for each component of sulfur deposition in 

the Transverse Range portion of the Mixed Conifer Forest Case Study 

Area. ................................................................................................................ 3-81 

Figure 3.4-1. The percentage impacts of a 50% decrease in NOx emissions on total 

reactive nitrogen deposition in the East. .......................................................... 3-87 

Figure 3.4-2. The percentage impacts of a 50% decrease in NOx emissions on oxidized 

nitrogen deposition in the East. ....................................................................... 3-88 

Figure 3.4-3. The percentage impacts of a 50% decrease in NOx emissions on reduced 

nitrogen deposition in the East. ....................................................................... 3-89 

Figure 3.4-4. The percentage impacts of a 50% decrease in NH3 emissions on total 

reactive nitrogen deposition in the East. .......................................................... 3-90 

Figure 3.4-5. The percentage impacts of a 50% decrease in NH3 emissions on oxidized 

nitrogen deposition in the East. ....................................................................... 3-91 

Figure 3.4-6. The percentage impacts of a 50% decrease in NH3 emissions on reduced 

nitrogen deposition in the East. ....................................................................... 3-92 

Final Risk and Exposure Assessment viii September 2009 
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Figure 3.4-7. The percentage impacts of a 50% decrease in SOx emissions on sulfur 

deposition in the East. ...................................................................................... 3-93 

Figure 3.5-1. Ratio of nitrogen deposition to nitrogen concentration based on oxidized 

nitrogen deposition and concentration (kg N/ha/μg/m3). ............................... 3-95 

Figure 3.5-2. Ratio of sulfur deposition to sulfur concentration based on oxidized sulfur 

deposition and concentration (kg S/ha/μg/m3)................................................ 3-96 

Figure 3.6-1. Fine-scale and 12-km annual total wet oxidized nitrogen deposition for the 

Adirondack Case Study Area and the surrounding region. ........................... 3-105 

Figure 3.6-2. Fine-scale and 12-km annual total wet reduced nitrogen deposition for the 

Adirondack Case Study Area and the surrounding region. ........................... 3-106 

Figure 3.6-3. Fine-scale and 12-km annual total wet sulfur deposition for the Adirondack 

Case Study Area and the surrounding region. ............................................... 3-107 

Figure 4.2-1. (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 significant relationship (p < .0001) 

between mean stream acid neutralizing capacity and the number of fish 

species. ............................................................................................................... 4-6 

Figure 4.2-2. Ecosystems sensitive to acidifying deposition in the eastern United States 

(U.S. EPA, modified from NAPAP, 2005). .................................................... 4-10 

Figure 4.2-3. Annual average total wet deposition (kg/ha/yr) for the period 1990 to 2006 

in SO4

2- (green) and NO3-

 (blue) from eight NADP/NTN sites in the 

Adirondack Case Study Area. ......................................................................... 4-12 

Figure 4.2-4. Air pollution concentrations and deposition for the period 1990 to 2006 

using one CASTNET and seven NADP/NTN sites in the Shenandoah 

Case Study Area. (a) Annual average air concentrations of SO2 (blue), 

oxidized nitrogen (red), SO4

2- (green), and reduced nitrogen (black). (b) 

Annual average total wet deposition (kg/ha/yr) of SO4

2- (green) and NO3-

(blue). ............................................................................................................... 4-13 

Figure 4.2-5. (Top) The location of lakes in the Adirondack Case Study Area used for 

MAGIC (red dots) and critical load (green dots) modeling sites. 

(Bottom) The location of streams used for both MAGIC and critical load 

modeling for the Shenandoah Case Study Area. ............................................. 4-15 

Figure 4.2-6. Trends over time for SO4

2-, NO3-

, and acid neutralizing capacity in 50 LTM 

lakes. SO4

2- and NO3-

 concentrations have decreased in surface waters by 

approximately 26% and 13%, respectively. .................................................... 4-18 

Figure 4.2-7. NO3

-

 concentrations of years 1860 (preacidification) and 2006 (current) 

conditions based on hindcasts of 44 lakes in the Adirondack Case Study 

Area modeled using MAGIC. .......................................................................... 4-20 

Figure 4.2-8. SO4

2- concentrations of years 1860 (preacidification) and 2006 (current) 

conditions based on hindcasts of 44 lakes in the Adirondack Case Study 

Area modeled using MAGIC. .......................................................................... 4-21 

Figure 4.2-9. Acid neutralizing capacity concentrations from 88 lakes in the Adirondack 

Case Study Area. Monitoring data from the TIME/LTM programs. .............. 4-22 

Final Risk and Exposure Assessment ix September 2009 
Table of Contents 

Figure 4.2-10. Acid neutralizing capacity levels of preacidification (1860) and current 

(2006) conditions based on hindcasts of 44 modeled lakes in the 

Adirondack Case Study Area. ......................................................................... 4-23 

Figure 4.2-11. Percentage of Adirondack Case Study Area lakes in the five classes of 

acidification (i.e., Acute, Severe, Elevated, Moderate, Low) for years 

1860 (preacidification) and 2006 (current condition) for 44 lakes 

modeled using MAGIC. Error bar indicates the 95% confidence interval. ..... 4-23 

Figure 4.2-12. Critical loads of acidifying deposition that each surface waterbody in the 

Adirondack Case Study Area can receive while maintaining or exceeding 

an acid neutralizing capacity concentration of 50 μeq/L based on 2002 

data. Watersheds with critical load values <100 meq/m2/yr (red and 

orange circles) are most sensitive to surface water acidification, whereas 

watersheds with values >100 meq/m2.yr (yellow and green circles) are 

the least sensitive sites. .................................................................................... 4-24 

Figure 4.2-13. Critical load exceedances (red circles) based on 2002 deposition 

magnitudes for Adirondack Case Study Area waterbodies where the 

critical limit acid neutralizing capacity is 0, 20, 50, and 100 μeq/L, 

respectively. Green circles represent lakes where current total nitrogen 

and sulfur deposition is below the critical load (see Table 4.2-3). .................. 4-25 

Figure 4.2-14. Trends over time for SO4

2- (blue), NO3-

 (green) and acid neutralizing 

capacity (red) concentrations in VTSSS LTM-monitored streams in the 

Shenandoah Case Study Area. ......................................................................... 4-27 

Figure 4.2-15. NO3

-

 concentrations of preacidification (1860) and current (2006) 

conditions based on hindcasts of 60 streams modeled using MAGIC in 

the Shenandoah Case Study Area. ................................................................... 4-28 

Figure 4.2-16. SO4

2- concentrations of preacidification (1860) and current (2006) 

conditions based on hindcasts of 60 streams modeled using MAGIC in 

the Shenandoah Case Study Area. ................................................................... 4-29 

Figure 4.2-17. Acid neutralizing capacity concentrations from 67 streams in the VTSSSSWAS/LTM monitoring network in the Shenandoah Case Study Area 

(2005–2006 data). ............................................................................................ 4-30 

Figure 4.2-18. Acid neutralizing capacity concentrations of preacidification (1860) and 

current (2006) conditions based on hindcasts of 60 streams modeled 

using MAGIC in the Shenandoah Case Study Area. ....................................... 4-31 

Figure 4.2-19. Percentage of streams in the five classes of acidification (i.e., Acute, 

Severe, Elevated, Moderate, Low Concern) for years 2006 and 1860 

(pre-acidification) for 60 streams modeled using MAGIC in the 

Shenandoah Case Study Area. The number of streams in each class is 

above the bar. Error bars indicate the 95% confidence interval. ..................... 4-31 

Figure 4.2-20. Critical loads of surface water acidity for an acid neutralizing capacity 

concentration of 50 μeq/L for streams in the Shenandoah Case Study 

Area. Each circle represents an estimated amount of acidifying 

deposition (i.e., critical load) that each stream’s watershed can receive 

and still maintain a surface water acid neutralizing capacity 

concentration >50 μeq/L. Watersheds with critical load values <100 

meq/m2/yr (red and orange circles) are most sensitive to surface water 

Final Risk and Exposure Assessment x September 2009 
Table of Contents 

acidification, whereas watersheds with values >100 meq/m2/yr (yellow 

and green circles) are the least sensitive sites. ................................................ 4-32 

Figure 4.2-21. Critical load exceedances for acid neutralizing capacity concentrations of 

0, 20, 50, and 100 μeq/L for streams in the Shenandoah Case Study Area. 

Green circles represent lakes where current total nitrogen and sulfur 

deposition is below the critical load and that maintain an acid 

neutralizing capacity concentration of 0, 20, 50, and 100 μeq/L, 

respectively. Red circles represent streams where current total nitrogen 

and sulfur deposition exceeds the critical load, indicating they are 

currently impacted by acidifying deposition. See Table 4.2-5. ....................... 4-33 

Figure 4.2-22. The depositional load function defined by the model. ....................................... 4-41 

Figure 4.2-23. Deposition load graphs for Clear Pond and Middle Flow Lake, New York. ..... 4-42 

Figure 4.2-24. The inverse cumulative frequency distribution for Little Hope Pond. The 

x-axis shows critical load exceedance in meq/ha/yr and y-axis is the 

probability. The dashed lines represent zero exceedance. In the case of 

Little Hope Pond, the dash line divides mostly the probability 

distribution on the left hand side, indicating Little Hope Pond has a 

relative low probability of being exceeded (0.3). Critical load and 

exceedances values were based on a critical level of protection of ANC = 

50 μeq/L. .......................................................................................................... 4-45 

Figure 4.2-25. Coefficients of variation of surface water critical load for acidity CL(A) 

and exceedances (EX(A)). Critical load and exceedances values were 

based on a critical level of protection of ANC = 50 μeq/L. ............................ 4-46 

Figure 4.2-26. Probability of exceedance of critical load for acidity for 2002. ......................... 4-47 

Figure 4.2-27. Simulated versus observed annual average surface water SO4

2-, NO3-

. 

ANC, and pH during the model calibration period for each of the 44 

lakes in the Adirondack Case Study Area. The black line is the 1:1 line. ....... 4-50 

Figure 4.2-28. Simulated versus observed annual average surface water SO4

2-, NO3-

. 

ANC, and pH during the model calibration period for each of the 60 

streams in the Shenandoah Case Study Area. The black line is the 1:1 

line. .................................................................................................................. 4-51 

Figure 4.2-29. MAGIC simulated and observed values of ANC for two lakes in the 

Shenandoah Case Study Area. Red points are observed data and the 

simulated values are the line. The Root Mean Squared Error (RMSE) for 

ANC was 7.81 μeq/L for Indiana Lake and 5.1 μeq/L for Dismal Pond. ....... 4-52 

Figure 4.2-30. MAGIC simulated and observed values of ANC for two lakes in the 

Shenandoah Case Study Area. Red points are observed data and the 

simulated values are the line. The Root Mean Squared Error (RMSE) for 

ANC was 11.8 μeq/L for Helton Creek and 4.0 μeq/L for Nobusiness 

Creek. ............................................................................................................... 4-53 

Figure 4.3-1. 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 controls (after 

Sverdrup and Warfvinge, 1993). ..................................................................... 4-55 

Figure 4.3-2. 2006 annual value of sugar maple and red spruce harvests and maple syrup 

production, by state. ........................................................................................ 4-60 

Final Risk and Exposure Assessment xi September 2009 
Table of Contents 

Figure 4.3-3. Map of areas of potential sensitivity of red spruce and sugar maple to 

acidification in the United States (see Table 1.2-1 of Appendix 5 for a 

listing of data sources to produce this map). ................................................... 4-65 

Figure 4.3-4. The critical load function created from the calculated maximum and 

minimum levels of total nitrogen and sulfur deposition (eq/ha/yr). The 

grey areas show deposition levels less than the established critical loads. 

The red line is the maximum amount of total sulfur deposition (valid 

only when nitrogen deposition is less than the minimum critical level of 

nitrogen deposition [blue dotted line]) in the critical load. The flat line 

portion of the curves indicates nitrogen deposition corresponding to the 

CLmin(N) (nitrogen absorbed by nitrogen sinks within the system). ............... 4-67 

Figure 4.3-5. Critical load function response curves for the three selected critical loads 

conditions (corresponding to the three levels of protection) for the Kane 

Experimental Forest Case Study Area. The 2002 CMAQ/NADP total 

nitrogen and sulfur (N+Scomb) deposition was greater than the highest and 

intermediate level of protection critical loads. The flat line portion of the 

curves indicates total nitrogen deposition corresponding to the CLmin(N) 

(nitrogen absorbed by nitrogen sinks within the system). ............................... 4-71 

Figure 4.3-6. Critical load function response curves for the three selected 

critical loads conditions (corresponding to the three levels of protection) 

for the Hubbard Brook Experimental Forest Case Study Area. The 2002 

CMAQ/NADP total nitrogen and sulfur (N+Scomb) deposition was greater 

than the highest level of protection critical load. The flat line portion of 

the curves indicates total nitrogen deposition corresponding to the 

CLmin(N) (nitrogen absorbed by nitrogen sinks within the system). ............... 4-71 

Figure 4.3-7. The influence of the 2002 CMAQ/NADP total reduced nitrogen (NHx-N) 

deposition on the critical function response curve, and in turn, the 

maximum amounts of sulfur (CLmax(S)) and oxidized nitrogen (NOx-N) 

in the critical load for the Kane Experimental Forest Case Study Area. 

The critical load of oxidized nitrogen (NOx-N) is 661 eq/ha/yr 

(910−249). The CLmin(N) (nitrogen absorbed by nitrogen sinks within 

the system) corresponds to the value depicted in Figure 4.3-5. ...................... 4-72 

Figure 4.3-8. The influence of the 2002 CMAQ/NADP total reduced nitrogen (NHx-N) 

deposition on the critical load function response curve and, in turn, the 

maximum amounts of sulfur (CLmax(S)) and oxidized nitrogen (NOx-N) 

in the critical load for the Hubbard Brook Experimental Forest Case 

Study Area. The critical load of oxidized nitrogen (NOx-N) is 328 

eq/ha/yr (487−159). The CLmin(N) (nitrogen absorbed by nitrogen sinks 

within the system) corresponds to the value depicted in Figure 4.3-6. ........... 4-73 

Figure 4.3.9. The lowest and highest critical load function response curves for the three 

levels of protection ((Bc/Al)crit = 0.6, 1.2, and 10.0) for the critical load 

assessments for the full geographical range of sugar maple. The 

CLmin(N) value for all curves is 42.86 eq/ha/yr, but this value is not 

indicated in the figure. ..................................................................................... 4-80 

Final Risk and Exposure Assessment xii September 2009 
Table of Contents 

Figure 4.3.10. The lowest and highest critical load function response curves for the three 

levels of protection ((Bc/Al)crit = 0.6, 1.2, and 10.0) for the critical load 

assessments for the full geographical range of red spruce. The CLmin(N) 

value for all curves is 42.86 eq/ha/yr, but this value is not indicated in the 

figure. ............................................................................................................... 4-81 

Figure 5.2-1. Descriptions of the five eutrophication indicators used in the NEEA 

(Bricker et al., 2007). ......................................................................................... 5-6 

Figure 5.2-2. Conceptual illustration of a reach network. ........................................................... 5-9 

Figure 5.2-3. ASSETS EI response curve. ................................................................................. 5-12 

Figure 5.2-4. Areas potentially sensitive to aquatic nutrient enrichment. Areas in red are 

most sensitive, and areas in dark green are least sensitive to wet nitrogen 

deposition. ....................................................................................................... 5-20 

Figure 5.2-5. Atmospheric deposition yields of oxidized nitrogen over the Potomac River 

and Potomac Estuary watershed. ..................................................................... 5-25 

Figure 5.2-6. Atmospheric deposition yields of reduced nitrogen over the Potomac River 

and Potomac Estuary watershed. ..................................................................... 5-25 

Figure 5.2-7. Atmospheric deposition yields of total nitrogen over the Potomac River and 

Potomac Estuary watershed. ............................................................................ 5-26 

Figure 5.2-8. Total nitrogen yields from all sources as predicted using version 3 of the 

Chesapeake Bay SPARROW application with updated 2002 atmospheric 

deposition inputs. ............................................................................................. 5-27 

Figure 5.2-9. Atmospheric deposition yields of oxidized nitrogen over the Neuse River 

and Neuse River Estuary watershed. ............................................................... 5-29 

Figure 5.2-10. Atmospheric deposition yields of reduced nitrogen over the Neuse River 

and Neuse River Estuary watershed. ............................................................... 5-29 

Figure 5.2-11. Atmospheric deposition yields of total nitrogen over the Neuse River and 

Neuse River Estuary watershed. ...................................................................... 5-30 

Figure 5.2-12. Total nitrogen yields from all sources predicted by a SPARROW 

application for the Neuse, Tar-Pamlico, and Cape Fear watersheds with 

2002 data inputs. .............................................................................................. 5-31 

Figure 5.2-13. Preliminary classifications of estuary typology across the nation (modified 

from Bricker et al., 2007). ............................................................................... 5-34 

Figure 5.2-14. ASSETS EI scores for 48 systems examined in the 2007 NEEA Update 

(Bricker et al., 2007). ....................................................................................... 5-36 

Figure 5.2-15. Response curve relating instream total nitrogen concentration (TNs) to 

total nitrogen atmospheric deposition load (TNatm) for the Potomac River 

watershed. ........................................................................................................ 5-38 

Figure 5.2-16. Example of fitted OEC curve for target ASSETS EI=2 for the Potomac 

Estuary. ............................................................................................................ 5-38 

Figure 5.2-17. Response curve relating instream total nitrogen concentration to total 

nitrogen atmospheric deposition load for the Neuse River/Neuse River 

Estuary Case Study Area. ................................................................................ 5-41 

Figure 5.2-18. Example of fitted response curve for target ASSETS EI=2 for the Neuse 

River Estuary. .................................................................................................. 5-42 

Figure 5.2-19. Theoretical SPARROW response curves demonstrating relative influence 

of sources on nitrogen loads to an estuary. ...................................................... 5-44 

Final Risk and Exposure Assessment xiii September 2009 
Table of Contents 

Figure 5.3-1. Importance of lichens as an indicator of ecosystem health (Jovan, 2008). .......... 5-50 

Figure 5.3-2. Benchmarks of atmospheric nitrogen deposition for several ecosystem 

indicators with the inclusion of the diatom changes in the Rocky 

Mountain lakes. ............................................................................................... 5-51 

Figure 5.3-3. Areas of highest potential nutrient enrichment sensitivity. (Acidophytic 

lichens, tree species, and the extent of the Mojave Desert come from data 

obtained from the United States Forest Service. The extents of coastal 

sage scrub and California mixed conifer forest come from the California 

Fire and Resource Assessment Program. Grasslands were obtained from 

the National Land Cover Dataset [USGS]). .................................................... 5-61 

Figure 5.3-4. Coastal sage scrub range and total nitrogen deposition using CMAQ 2002 

modeling results and NADP monitoring data. ................................................ 5-64 

Figure 5.3-5. Current fire threats to coastal sage scrub communities. ....................................... 5-66 

Figure 5.3-6. Mixed conifer forest range and total nitrogen deposition using CMAQ 2002 

modeling results and NADP monitoring data. ................................................ 5-68 

Figure 5.3-7. Presence of acidophyte lichens and total nitrogen deposition in the 

California mountain ranges using CMAQ 2002 modeling results and 

NADP monitoring data. ................................................................................... 5-73 

Figure 5.3-8. CMAQ 2002 modeling results and NADP monitoring data for deposition of 

total nitrogen in the western United States. ..................................................... 5-76 

Figure 5.3-9. Observed effects from ambient and experimental atmospheric nitrogen 

deposition loads in relation to using CMAQ 2002 modeling results and 

NADP monitoring data. Citations for effect results are from the ISA, 

Table 4.4 (U.S. EPA, 2008). ............................................................................ 5-78 

Figure 5.3-10. Illustration of the range of terrestrial ecosystem effects observed relative to 

atmospheric nitrogen deposition. ..................................................................... 5-79 

Figure 5.3-11. Habitats that may experience ecological benchmarks similar to coastal 

sage scrub and mixed conifer forest. ............................................................... 5-80 

Figure 5.3-12. Rocky Mountain National Park location relative to the Niwot Ridge LongTerm Ecological Research site and Denver metropolitan area. ...................... 5-82 

Figure 6.1-1. Percentage of total U.S. emissions of greenhouse gases in CO2 equivalents 

(U.S. EPA, 2007b). ............................................................................................ 6-3 

Figure 6.2-1. The mercury cycle in an ecosystem (USGS, 2006). .............................................. 6-5 

Figure 6.2-2. Biogeochemical process of mercury methylation. ................................................. 6-8 

Figure 6.2-3. Distribution pattern in 2006 for state fish consumption advisory listings 

(U.S. EPA, 2007a). .......................................................................................... 6-10 

Figure 6.2-4. Spatial and biogeochemical factors influencing methylmercury production. ...... 6-11 

Figure 6.2-5. Preliminary USGS map of mercury methylation–sensitive watersheds 

derived from more than 55,000 water quality sites and 2,500 watersheds 

(Myers et al., 2007). ........................................................................................ 6-12 

Figure 7.1-1. Number of fish species per lake or stream versus ANC level and aquatic 

status category (colored regions) for lakes in the Adirondack Case Study 

Area (Sullivan et al., 2006). The five aquatic status categories are 

described in Table 7.1-1. ................................................................................... 7-4 

Final Risk and Exposure Assessment xiv September 2009 
Table of Contents 

Figure 7.1-2. Simulated versus observed annual average surface water SO4

2-, NO3-

. ANC, 

and pH during the model calibration period for each of the 44 lakes in 

the Adirondack Case Study Area. The black line is the 1:1 line. ...................... 7-7 

Figure 7.1-3. Simulated versus observed annual average surface water SO4

2-, NO3-

. ANC, 

and pH during the model calibration period for each of the 60 streams in 

the Shenandoah Case Study Area. The black line is the 1:1 line. ..................... 7-8 

Figure 7.1-4. MAGIC simulated and observed values of ANC for two lakes in the 

Shenandoah Case Study Area. Red points are observed data, and the 

simulated values are the line. The Root Mean Squared Error (RMSE) for 

ANC was 7.81 μeq/L for Indiana Lake and 5.1 μeq/L for Dismal Pond. ......... 7-9 

Figure 7.1-5. MAGIC simulated and observed values of ANC for two lakes in the 

Shenandoah Case Study Area. Red points are observed data, and the 

simulated values are the line. The Root Mean Squared Error (RMSE) for 

ANC was 11.8 μeq/L for Helton Creek and 4.0 μeq/L for Nobusiness 

Creek. ............................................................................................................... 7-10 

Figure 7.1-6. The depositional load function defined by the model. ......................................... 7-15 

Figure 7.2-1. The relationship between the Bc/Al ratio in soil solution and the percentage 

of tree species (native and introduced; found growing in North America) 

exhibiting a 20% reduction in growth relative to controls (after Sverdrup 

and Warfvinge, 1993). ..................................................................................... 7-17 

Figure 7.2-2. The critical load function created from the calculated maximum and 

minimum levels of total nitrogen and sulfur deposition (eq/ha/yr). The 

grey areas show deposition levels less than the established critical loads. 

The red line is the maximum amount of total sulfur deposition (valid 

only when nitrogen deposition is less than the minimum critical level of 

nitrogen deposition [blue dotted line]) in the critical load. The flat line 

portion of the curves indicates nitrogen deposition corresponding to the 

CLmin(N) (i.e., nitrogen absorbed by nitrogen sinks within the system). ........ 7-21 

Figure 7.4-1. Benchmarks of atmospheric nitrogen deposition for several ecosystem 

indicators with the inclusion of the diatom changes in the Rocky 

Mountain lakes ................................................................................................ 7-28 

LIST OF TABLES 

Table 2.1-1. Summary of Sensitive Characteristics, Indicators, Effects, and Impacted 

Ecosystem Services Analyzed for Each Case Study Evaluated in This 

Review ............................................................................................................... 2-3 

Table 2.4-1. Ecological Impacts Associated with Acidification, Nutrient Enrichment, and 

Increased Mercury Methylation and Their Associated Ecosystem 

Services ............................................................................................................ 2-21 

Table 2.5-1. Overview of Models Used in This Assessment, Including Model 

Description, Case Study Application, Model Type, Temporal Features of 

the Model, Spatial Scale Used in This Analysis, Strengths, Weaknesses, 

Supporting Organization Endorsements, and Considerations in the 

Application to Nitrogen and Sulfur Deposition ............................................... 2-24 

Final Risk and Exposure Assessment xv September 2009 
Table of Contents 

Table 3.2-1. Annual National NOx Emissions across Major Source Categories in 2002. ........... 3-4 

Table 3.2-2a. Annual NOx Emissions across Major Source Categories in 2002 for the 

Eastern United States. ........................................................................................ 3-5 

Table 3.2-2b. Annual NOx Emissions across Major Source Categories in 2002 for the 

Western United States. ...................................................................................... 3-5 

Table 3.2-3. Annual National SO2 Emissions across Major Source Categories in 2002. ............ 3-9 

Table 3.2-4a. Annual SO2 Emissions across Major Source Categories in 2002 for the 

Eastern United States. ........................................................................................ 3-9 

Table 3.2-4b. Annual SO2 Emissions across Major Source Categories in 2002 for the 

Western United States. .................................................................................... 3-10 

Table 3.3-1. Annual Total Reactive Nitrogen Deposition (kg N/ha/yr) and Sulfur 

Deposition (kg S/ha/yr) in 2002 for Each Case Study Area, as Well as 

the Rocky Mountain National Park. ................................................................ 3-31 

Table 3.6-1. Annual Total Wet Plus Dry Oxidized Nitrogen Deposition (kg N/ha/yr) 

Predicted by CMAQv4.6 and CMAQ v4.7 for 2002. .................................... 3-101 

Table 3.6-2. Annual Total Wet Plus Dry Reduced Nitrogen Deposition (kg N/ha/yr) 

Predicted by CMAQv4.6 and CMAQ v4.7 for 2002. .................................... 3-102 

Table 3.6-3. Annual Total Wet Plus Dry Sulfur Deposition (kg S/ha/yr) Predicted by 

CMAQv4.6 and CMAQ v4.7 for 2002. ......................................................... 3-103 

Table 4.2-1. Aquatic Status Categories ...................................................................................... 4-17 

Table 4.2-2. Estimated Average Concentrations (and associated uncertainties) of Surface 

Water Chemistry at 44 Lakes in the Adirondack Case Study Area 

Modeled Using MAGIC for Preacidification (1860) and Current (2006) 

Conditions ........................................................................................................ 4-17 

Table 4.2-3. Critical Load Exceedances (Nitrogen + Sulfur Deposition > Critical Load) 

for 169 Modeled Lakes Within the TIME/LTM and EMAP Survey 

Programs. “No. Lakes” Indicates the Number of Lakes at the Given Acid 

Neutralizing Capacity Limit; “% Lakes” Indicates the Total Percentage 

of Lakes at the Given Acid Neutralizing Capacity Limit ................................ 4-26 

Table 4.2-4. Model Simulated Average Concentrations (and associated uncertainties) for 

Stream Chemistry at 60 Modeled Streams in the Shenandoah Case Study 

Area for Preacidification and Current Conditions ........................................... 4-27 

Table 4.2-5. Critical Load Exceedances (Nitrogen + Sulfur Deposition > Critical Load) 

for 60 Modeled Streams Within the VTSSS-LTM Monitoring Program 

in the Shenandoah Case Study Area. “No. Streams” Indicates the 

Number of Streams at the Given Acid Neutralizing Capacity Limit; “% 

Streams” Indicates the Total Percentage of Streams at the Given Acid 

Neutralizing Capacity Limit. ........................................................................... 4-34 

Table 4.2-6. Critical Load Exceedances (Nitrogen + Sulfur Deposition > Critical Load) 

for the Regional Population of 1,842 Lakes in the Adirondack Case 

Study Area That Are from 0.5 to 2000 ha in Size and at Least 1 m in 

Depth. Estimates Are Based on the EMAP Lake Probability Survey of 

1991 to 1994. ................................................................................................... 4-38 

Table 4.2-7. Parameters used and their uncertainty range. The range of surface water 

parameters (e.g. CA, MG, CL, NA, NO3, SO4) were determined from 

surface water chemistry data for the period from 1992 to 2006 from the 

Final Risk and Exposure Assessment xvi September 2009 
Table of Contents 

TIME-LTM monitoring network. Runoff(Q) and Acidic Deposition were 

set at 50% and 25%. ........................................................................................ 4-43 

Table 4.2-8. Means and coefficients of variation of critical loads and exceedances for 

surface water. ................................................................................................... 4-46 

Table 4.3-1. Summary of Linkages Between Acidifying Deposition, Biogeochemical 

Processes That Affect Ca2+, Physiological Processes That Are Influenced 

by Ca2+, and Effect on Forest Function ........................................................... 4-56 

Table 4.3-2. The Three Indicator (Bc/Al)crit Soil Solution Ratios and Corresponding 

Levels of Protection to Tree Health and Critical Loads .................................. 4-69 

Table 4.3-3. Number and Location of USFS FIA Permanent Sampling Plots (each plot is 

0.07 ha) Used in the Analysis of Critical Loads for Full Geographic 

Ranges of Sugar Maple and Red Spruce ......................................................... 4-74 

Table 4.3-4. Ranges of Critical Load Values, by Level of Protection (Bc/Al(crit) = 0.6, 

1.2, and 10.0) and by State, for the Full Geographical Distribution 

Ranges of Sugar Maple and Red Spruce ......................................................... 4-76 

Table 4.3-5. Percentages of Plots, by Protection Level (Bc/Al(crit) = 0.6, 1.2, and 10.0) 

and by State, Where 2002 CMAQ/NADP Total Nitrogen and Sulfur 

Deposition Was Greater Than the Critical Loads for Sugar Maple and 

Red Spruce ....................................................................................................... 4-77 

Table 5.2-1. Value of Commercial Landings for Selected Species in 2007 (Chesapeake 

Bay Region) ..................................................................................................... 5-14 

Table 5.2-2. Wet Nitrogen Deposition Level vs. EPA Total Nitrogen (TN) Criteria for 

Lakes and Reservoirs ....................................................................................... 5-19 

Table 5.2-3. Typology Group Categorizations .......................................................................... 5-34 

Table 5.2-4. Summary Statistics for Target Eutrophication Index Scenarios — Potomac 

Estuary ............................................................................................................. 5-39 

Table 5.2-5. Summary Statistics for Target Eutrophication Index Scenarios — Neuse 

River Estuary ................................................................................................... 5-42 

Table 5.3-1. Coastal Sage Scrub Ecosystem Area and Total Nitrogen Deposition ................... 5-63 

Table 5.3-2. Mixed Conifer Forest Ecosystem Area and Nitrogen Deposition ......................... 5-72 

Table 7.1.-1. Aquatic Status Categories....................................................................................... 7-5 

Table 7.2-1. Summary of Linkages among Acidifying Deposition, Biogeochemical 

Processes that Affect Ca2+, Physiological Processes that are Influenced 

by Ca2+, and the Effect on Forest Function ..................................................... 7-17 

Table 7.5-1. Summary of the Levels of Confidence Associated with the Available Data, 

Modeling Approach, and the Relationship between the Selected 

Ecological Indicator and Atmospheric Deposition as Described by the 

Ecological Effect Function for Each Targeted Effect Area Considered in 

this Review ...................................................................................................... 7-31 

Table 7.5-2. Summary of Information Assessed in the Risk and Exposure Assessment to 

Aid in Informing Policy Based on Welfare Effects ......................................... 7-33 

Final Risk and Exposure Assessment xvii September 2009 
Table of Contents 

Final Risk and Exposure Assessment xviii September 2009 

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Acronyms and Abbreviations 

ACRONYMS AND ABBREVIATIONS 

Al aluminum2+,3+

AM arbuscular mycorrhizae 

AN acid anions (NO3

-

 and SO4

2-) 

ANC acid neutralizing capacity 

AQCD Air Quality Criteria Document 

ASSETS EI Assessment of Estuarine Trophic Status eutrophication index 

Bc base cation (Ca2+ + K+

 + Mg2+) 

BC base cation (Ca2+ + K+ + Mg2+ + Na+

) 

Bcu base cation (Ca2+ + K+ + Mg2+) uptake 

Bcw base cation (Ca2+ + K+ + Mg2+) weathering 

BCw base cation (Ca2+ + K+ + Mg2+ + Na+) weathering 

Bc/Al base cation to aluminum ratio 

(Bc/Al)crit base cation to aluminum ratio (indicator) 

C carbon 

Ca2+ calcium 

CAA Clean Air Act 

CAAA Clean Air Act Amendments 

CAF Coastal Assessment Framework 

CAFO confined animal feeding operation 

CAIR Clean Air Interstate Rule 

CAL FIRE California Department of Forestry and Fire Protection 

CASAC Clean Air Scientific Advisory Committee 

CASTNET Clean Air Status and Trends Network 

CH4 methane 

Cl- chloride 

CLF critical load function 

cm centimeter 

CMAQ Community Multiscale Air Quality 

CO2 carbon dioxide 

CS2 carbon disulfide 

CSS coastal sage scrub 

DFO Determined Future Outlook 

DIN dissolved inorganic nitrogen 

DL depositional load 

DO dissolved oxygen 

DOC dissolved organic carbon 

DOI U.S. Department of the Interior 

EC ecosystem carbon content 

EES Ecological Effects Subcommittee 

EGU electric generating unit 

EMAP Environmental Monitoring and Assessment Program 

EPA U.S. Environmental Protection Agency 

ESRI Environmental Systems Research Institute, Inc. 

Final Risk and Exposure Assessment xix September 2009 
Acronyms and Abbreviations 

FASOMGHG Forest and Agriculture Sector Optimization Model – Greenhouse Gas 

version 

FHWAR Fishing, Hunting, and Wildlife-Associated Recreation 

FIA Forest Inventory and Analysis 

GHG greenhouse gas 

GIS geographic information systems 

GPP gross primary productivity 

H+ hydrogen ion 

H2O water 

H2S hydrogen sulfide 

H2SO4 sulfuric acid 

ha hectare 

HAB harmful algal bloom 

HBEF Hubbard Brook Experimental Forest 

HFC hydrofluorocarbon 

Hg2+ divalent mercury 

Hg0 elemental mercury 

HNO3 nitric acid 

HONO nitrous acid 

HUC hydrologic unit code 

ICP International Cooperative Programme 

IDW inverse distance weighted 

IPCC Intergovernmental Panel on Climate Change 

IPM Integrated Planning Model 

ISA Integrated Science Assessment 

K+ potassium 

KEF Kane Experimental Forest 

kg kilogram 

kg/ha/yr kilograms per hectare per year 

Kgibb gibbsite equilibrium constant 

km kilometers 

LTER Long-Term Ecological Research 

LTM Long-Term Monitoring 

m meters 

MAGIC Model of Acidification of Groundwater in Catchments 

MAHA Mid-Atlantic Highlands Assessment 

MCF mixed conifer forest 

MCIP Meteorology-Chemistry Interface Processor 

MEA Millennium Ecosystem Assessment 

mg/L milligrams per liter 

Mg2+ magnesium 

MSA metropolitan statistical area 

N nitrogen 

Nde denitrification 

Ni nitrogen immobilization 

Nr total reactive nitrogen 

Final Risk and Exposure Assessment xx September 2009 
Acronyms and Abbreviations 

Nret retention of nitrogen 

Nu nitrogen uptake 

N2 nitrogen gas 

N2O nitrous oxide 

N2O3 nitrogen trioxide 

N2O4 nitrogen tetroxide 

N2O5 dinitrogen pentoxide 

Na+ sodium 

NAAQS National Ambient Air Quality Standards 

NADP National Atmospheric Deposition Program 

NAPAP National Acid Precipitation Assessment Program 

NAWQA National Water Quality Assessment 

NEE net ecosystem exchange 

NEEA National Estuarine Eutrophication Assessment 

NEI National Emissions Inventory 

NEP net ecosystem productivity 

NH3 ammonia 

NH4

+

 ammonium 

NH4NO3 ammonium nitrate 

(NH4)2SO4 ammonium sulfate 

NHx reduced nitrogen 

NLCD National Land Cover Data 

NO nitric oxide 

NO2 nitrogen dioxide 

NO2

-

 nitrite 

NO3

-

 nitrate 

NOx nitrogen oxides 

NOy total oxidized nitrogen 

NOAA National Oceanic and Atmospheric Administration 

NPP net primary productivity 

NRC National Research Council 

NSRE National Survey on Recreation and the Environment 

NSWS National Surface Water Survey 

NTN National Trends Network 

NTR organic nitrate 

O2 oxygen 

O3 ozone 

OAQPS Office of Air Quality Planning and Standards 

OEC Overall Eutrophic Condition 

OH-

 hydroxide 

OHI Influencing Factors/Overall Human Influence 

ORD Office of Research and Development 

PAN peroxyacetyl nitrates 

PFC perfluorocarbons 

PM particulate matter 

PM2.5 fine particulate matter less than 2.5 microns in size 

Final Risk and Exposure Assessment xxi September 2009 
Acronyms and Abbreviations 

Final Risk and Exposure Assessment xxii September 2009 

ppb parts per billion 

ppm parts per million 

ppt parts per trillion 

REMAP Regional Environmental Monitoring and Assessment Program 

RFNRP Regional Forest Nutrition Research Project 

RSM response-surface model 

S sulfur 

Sret retention of sulfur 

S2O disulfur monoxide 

S2O3

2- thiosulfate 

S2O7

2- sulfur heptoxide 

SAB Science Advisory Board 

SAV submerged aquatic vegetation 

SF6 sulfur hexafluoride 

Si silicon 

SMB Simple Mass Balance 

SO sulfur monoxide 

SO2 sulfur dioxide 

SO3 sulfur trioxide 

SO4

2- sulfate 

SOx sulfur oxides 

SOM soil organic matter 

SPARROW SPAtially Referenced Regression on Watershed Attributes 

SRB sulfate-reducing bacteria 

SSURGO Soil Survey Geographic Database 

STORET STORage and RETrieval 

TIME Temporally Integrated Monitoring of Ecosystems 

TN total nitrogen 

TNatm total nitrogen atmospheric loading 

TNs instream total nitrogen concentration 

TP total phosphorus 

U.S. EPA U.S. Environmental Protection Agency 

USFS United States Forest Service 

USGS U.S. Geological Survey 

VIF variance inflation factor 

VOC volatile organic carbon 

WTP willingness to pay 

μeq/L microequivalent per liter 

μg/g microgram per gram 

μg/m3 microgram per cubic meter 

μM micromolar 
Key Terms 

KEY TERMS 

Acid Neutralizing Capacity: A key indicator of the ability of water to neutralize the acid or 

acidifying inputs it receives. This ability depends largely on associated biogeophysical 

characteristics, such as underlying geology, base cation concentrations, and weathering 

rates. 

Acidification: The process of increasing the acidity of a system (e.g., lake, stream, forest soil). 

Atmospheric deposition of acidic or acidifying compounds can acidify lakes, streams, 

and forest soils. 

Adverse Effect: The response or component of an ecosystem that is deemed harmful in its 

function. 

Air Quality Indicator: The substance or set of substances (e.g., fine particulate matter [PM2.5], 

nitrogen dioxide [NO2], sulfur dioxide [SO2]) occurring in the ambient air for which the 

National Ambient Air Quality Standards (NAAQS) set a standard level and monitoring 

occurs. 

Alpine: The biogeographic zone made up of slopes above the tree line, characterized by the 

presence of rosette-forming herbaceous plants and low, shrubby, slow-growing woody 

plants. 

Arid Region: A land region of low rainfall, where “low” is widely accepted to be less than 

250 millimeters (mm) of precipitation per year. 

Assessment Endpoint: An ecological entity and its attributes that are considered welfare effects, 

as defined in Clean Air Act Section 302(h), and that are analyzed in the assessment. 

ASSETS Rating: Assessment of Estuarine Trophic Status that builds on the U.S. National 

Estuarine Eutrophication Assessment developed by National Oceanic and Atmospheric 

Administration. The Overall Eutrophic Condition, Overall Human Influence, and 

Determination of Future Outlook are combined to provide a single eutrophication 

assessment rating for an estuary in one of five categories: high, good, moderate, poor, or 

Final Risk and Exposure Assessment xxiii September 2009 
Key Terms 

bad. These categories provide a scale for setting eutrophication-related reference 

conditions for different types of transitional waters. 

ASSETS rating High: Low pressure from influencing factors, low overall eutrophic condition 

OEC, and any expected improvement or no future change in eutrophic condition. 

ASSETS rating Good: Low to moderate pressure, low to moderate-low eutrophic condition, and 

any expected future change in condition. 

ASSETS rating Moderate: Any pressure, moderate-low to moderate-high eutrophic condition, 

and any expected future change in eutrophic condition. 

ASSETS rating Poor: Moderate-low to high pressure, moderate to moderate-high eutrophic 

condition, and any expected future change in condition. 

ASSETS rating Bad: Moderate to high pressure, moderate-high to high eutrophic condition, and 

any expected future change in eutrophic condition. 

ASSETS rating Unknown: Insufficient data for analysis. 

Atmospheric Deposition Transformation Function: Process by which ambient atmospheric 

concentrations of NOx and Sox are translated into a nitrogen and sulfur deposition metric. 

Base Cation Saturation: The degree to which soil cation exchange sites are occupied with base 

cations (e.g., Ca2+, Mg2+, K+

) as opposed to Al3+ and H+. Base cation saturation is a 

measure of soil acidification, with lower values being more acidic. There is a threshold 

whereby soils with base saturations less than 20% (especially between 10% and 20%) are 

extremely sensitive to change. 

Biologically Relevant Indicator: A physical, chemical, or biological entity/feature that 

demonstrates a consistent degree of response to a given level of stressor exposure and 

that is easily measured/quantified to make it a useful predictor of biological, 

environmental, or ecological risk. 

Final Risk and Exposure Assessment xxiv September 2009 
Key Terms 

Critical Load: A quantitative estimate of an exposure to one or more pollutants, below which 

significant harmful effects on specified sensitive elements of the environment do not 

occur, according to present knowledge. 

Denitrification: The anaerobic reduction of nitrogen oxides (NOx; e.g., nitrate or nitrite) to 

gaseous nitrogen (e.g., nitrous oxide [N2O] or gaseous nitrogen [N2]) by denitrifying 

bacteria. 

Determined Future Outlook: This index provides an assessment of the susceptibility of the 

system (in terms of the capacity of a system to dilute and/or flush nutrients) and a 

categorical indicator of foreseeable changes in nutrient loads. Predictions of nutrient 

loading (i.e., increase, decrease, unchanged) are based on expected population increase, 

planned management actions, and expected changes in watershed uses, and as such, are 

heuristically determined. A matrix is used for the final definition of the Determined 

Future Outlook index and shows that, conceptually, systems with slower flushing (i.e., 

higher susceptibility) are expected to improve at a slower rate than those of lower 

susceptibility if nutrient inputs are decreased in the future. 

Dry Deposition: The removal of gases and particles from the atmosphere to surfaces in the 

absence of precipitation (e.g., rain, snow) or occult deposition (e.g., fog). 

Ecological Dose: The concentration of a toxicant that causes an effect (i.e., morbidity or 

mortality) in an organism. This measure may be acute or chronic and may have an effect 

over a period of time. 

Ecological Effect Function: Process by which deposition of nitrogen and sulfur is related to a 

given ecological indicator. 

Ecological Exposure: The exposure of a nonhuman organism to an environmental stressor. 

Ecological Risk: The likelihood that adverse ecological effects may occur or are occurring as a 

result of exposure to one or more stressors (U.S. EPA, 1992). 

Final Risk and Exposure Assessment xxv September 2009 
Key Terms 

Ecological Risk Assessment: A process that evaluates the likelihood that adverse ecological 

effects may occur or are occurring as a result of exposure to one or more stressors (U.S. 

EPA, 1992). 

Ecosystem: The interactive system formed from all living organisms and their abiotic (i.e., 

physical and chemical) environment within a given area. Ecosystems cover a hierarchy of 

spatial scales and can comprise the entire globe, biomes at the continental scale, or small, 

well-circumscribed systems such as a small pond. 

Ecosystem Benefit: The value, expressed qualitatively, quantitatively, and/or in economic terms, 

where possible, associated with changes in ecosystem services that result either directly 

or indirectly in improved public welfare. Examples of ecosystem benefits that derive 

from improved air quality include improvements in habitats for sport fish species, the 

quality of drinking water and recreational areas, and visibility. 

Ecosystem Function: The processes and interactions that operate within an ecosystem. Such 

processes include but are not limited to nutrient flow, energy flow, water dynamics, and 

the flux of trace gases. 

Ecosystem Services: The ecological processes or functions having monetary or nonmonetary 

value to individuals or society at large. These are (1) supporting services, such as 

productivity or biodiversity maintenance; (2) provisioning services, such as food, fiber, or 

fish; (3) regulating services, such as climate regulation or carbon sequestration; and (4) 

cultural services, such as tourism or spiritual and aesthetic appreciation. 

Ecosystem Structure: Refers to species’ composition, stratification, and interactions with some 

abiotic attributes of the environment and with each other as they vary through space and 

time. 

Elasticity: The percentage of change in the response variable for a 1% change in the input 

physical or meteorological characteristic. 

Eutrophication: The process by which nitrogen additions stimulate the growth of autotrophic 

biota, usually resulting in the depletion of dissolved oxygen. 

Final Risk and Exposure Assessment xxvi September 2009 
Key Terms 

Greenhouse Gas: Those gaseous constituents of the atmosphere, both natural and 

anthropogenic, that absorb and emit radiation at specific wavelengths within the spectrum 

of infrared radiation emitted by the earth’s surface, the atmosphere, and clouds. This 

property causes the greenhouse effect. Water vapor (H2O), carbon dioxide (CO2), N2O, 

methane (CH4), and ozone (O3) are the primary greenhouse gases in the earth’s 

atmosphere. In addition to CO2, N2O, and CH4, the Kyoto Protocol deals with the 

greenhouse gases sulfur hexafluoride (SF6), hydrofluorocarbons, and perfluorocarbons. 

Key Elements of Secondary National Ambient Air Quality Standards: 

(a) Indicators 

(1) Air Quality Indicator (for secondary NAAQS): The air pollutant(s) whose 

concentration(s) in the ambient air is (are) measured for purposes of determining 

compliance with the NAAQS. An indicator may either be the actual criteria air pollutant 

listed in the Clean Air Act or an appropriate surrogate. For example, NO2 is the current 

indicator for the primary and secondary NOx NAAQS and represents all NOx, while the 

current indicator for the primary and secondary sulfur oxides (SOx) NAAQS is SO2, 

representing all SOx. 

(2) Ecological Indicator: A characteristic of an ecosystem that can provide quantitative 

information on its ecological condition. An indicator can be or contribute to a measure of 

integrity and sustainability. For example, one indicator of increasing acidification effects 

in an aquatic ecosystem is a decrease in acid neutralizing capacity (ANC). A decrease in 

ANC can lead to acidification of stream water, and thereby, to changes to fish community 

structure, a good indicator of overall stream health.

(b) Level (of secondary NAAQS): The specified value of the indicator or metric (see 

definition below) that is judged requisite to protect the public welfare from any known or 

anticipated adverse effects associated with the presence of the criteria pollutant in 

ambient air. The current level of the secondary NO2 NAAQS indicator is 0.053 parts per 

million (ppm) (same as primary). The current level of the secondary SO2 NAAQS 

Final Risk and Exposure Assessment xxvii September 2009 
Key Terms 

indicator is 0.5 ppm. The level of the W126 metric proposed in the 2007 O3 secondary 

NAAQS proposal was 21 ppm-hrs. 

(c) Averaging Time (for secondary NAAQS): The period of time over which exposure 

to metric values at or above the level of the standard is considered relevant. Over that 

time period, concentrations are averaged or cumulated to determine whether the level of 

the standard has been met. Examples include 3-hour, 8-hour, 24-hour, seasonal, or annual 

averages. The current averaging time for the secondary NO2 NAAQS is a year. The 

current averaging time for the secondary SO2 NAAQS is 3 hours. 

 (d) Form (of secondary NAAQS): The statistical characteristics of a standard that 

determine the stringency, stability, and robustness of that standard when implemented. 

For example, the current secondary O3 standard is set at the level of 0.075 ppm, averaged 

over an 8-hour period. To attain this standard, however, only the 3-year average of the 

fourth-highest daily maximum (rather than the maximum itself) 8-hour average O3

concentrations measured at each monitor within an area over each year is compared to the 

level of the standard and must not exceed 0.075 ppm. The current form of the secondary 

NO2 NAAQS is the annual arithmetic mean. The current form of the secondary SO2

NAAQS is not to be exceeded more than once per year. 

Maximum Depositional Load: The maximum amount of nitrogen and/or sulfur deposition that 

a given ecosystem can receive without the degradation of the ecological indicator for a 

targeted effect. 

Nitrogen Saturation: The point at which nitrogen inputs from atmospheric deposition and other 

sources exceed the biological requirements of the ecosystem; a level beyond nutrient 

enrichment. 

Nutrient Enrichment: The process by which a terrestrial system becomes enhanced by nutrient 

additions to a degree that stimulates the growth of plant or other terrestrial biota, usually 

resulting in an increase in productivity. 

Occult Deposition: The removal of gases and particles from the atmosphere to surfaces by fog 

or mist. 

Final Risk and Exposure Assessment xxviii September 2009 
Key Terms 

Overall Eutrophic Condition: An ASSETS index meaning an estimate of current eutrophic 

conditions derived from data for five symptoms known to be linked to eutrophication. 

Overall Human Influence: An ASSETS index meaning physical, hydrologic, and 

anthropogenic factors that characterize the susceptibility of the estuary to the influences 

of nutrient inputs (also quantified as part of the index) and eutrophication. 

Semi-arid Regions: Regions of moderately low rainfall that are not highly productive and are 

usually classified as rangelands. “Moderately low” is widely accepted as between 250 

and 500 mm of precipitation per year. 

Sensitivity: The degree to which a system is affected, either adversely or beneficially, by an 

effect of NOx and/or SOx pollution (e.g., acidification, nutrient enrichment). The effect 

may be direct (e.g., a change in growth in response to a change in the mean, range, or 

variability of nitrogen deposition) or indirect (e.g., changes in growth due to the direct 

effect of nitrogen consequently altering competitive dynamics between species and 

decreased biodiversity). 

Target Load: A policy-based metric that takes into consideration such factors as economic costs 

and time frame for emissions reduction. The target load can be lower than the critical 

load if a very sensitive area is to be protected in the short term, especially if deposition 

rates exceed critical loads. 

Total Reactive Nitrogen: All biologically, chemically, and radiatively active nitrogen 

compounds in the atmosphere and biosphere, such as ammonia gas (NH3), ammonium 

ion (NH4

+

), nitric oxide (NO), nitrite (NO2

-

), nitric acid (HNO3), N2O, nitrate (NO3

–

), and 

organic compounds (e.g., urea, amines, nucleic acids). 

Uncertainty: A measure of the knowledge of the magnitude of a parameter. Uncertainty can be 

reduced by research (i.e., the parameter value can be refined). Uncertainty is quantified as 

a distribution. For example, the volume of a lake may be estimated from its surface area 

and an average depth. This estimate can be refined by measurement (Webster and 

MacKay, 2003). 

Final Risk and Exposure Assessment xxix September 2009 
Key Terms 

Final Risk and Exposure Assessment xxx September 2009 

Valuation: The economic or noneconomic process of determining either the value of 

maintaining a given ecosystem type, state, or condition, or the value of a change in an 

ecosystem, its components, or the services it provides. 

Variability: The degree to which values in a distribution differ from each other. Variability can 

be measured as range, mean, variance and standard deviation. 

Variable Factors: Influences that, by themselves or in combination with other factors, may alter 

the effects of an air pollutant on public welfare [Clean Air Act Section 108 (a)(2)]. 

(a) Atmospheric Factors: Atmospheric conditions, such as precipitation, relative 

humidity, oxidation state, and co-pollutants present in the atmosphere, that may influence 

transformation, conversion, transport, and deposition, and thereby, the effects of an air 

pollutant on public welfare.

(b) Ecological Factors: Ecological conditions that may influence the effects of an air 

pollutant on public welfare once it is introduced into an ecosystem, such as soil base 

saturation, soil thickness, runoff rate, land use conditions, bedrock geology, and 

weathering rates. 

Vulnerability: The degree to which a system is susceptible to and unable to cope with the 

adverse effects of NOx and/or SOx air pollution. 

Welfare Effects: The effects on soils, water, crops, vegetation, manmade materials, animals, 

wildlife, weather, visibility, and climate, damage to and deterioration of property, and 

hazards to transportation, as well as effects on economic values and on personal comfort 

and well-being, whether caused by transformation, conversion, or combination with other 

air pollutants. [Clean Air Act Section 302(h)]. 

Wet Deposition: The removal of gases and particles from the atmosphere to surfaces by rain or 

other forms of precipitation. 
References 

REFERENCES 

U.S. Environmental Protection Agency (EPA). 1992. Framework for ecological risk assessment. 

Washington, DC: Risk Assessment Forum, U.S. Environmental Protection Agency. 

EPA/630/R-92/001. 

Webster, E., and D. MacKay. 2003. Defining Uncertainty and Variability in Environmental Fate 

Models. CEMC Report No. 200301. Canadian Environmental Modelling Centre, Trent 

University, Peterborough, ON, Canada. 

Final Risk and Exposure Assessment xxxi September 2009 

Executive Summary 

Final Risk and Exposure Assessment ES-1 September 2009 

The sum of mono-nitrogen oxides, nitrogen dioxide 

(NO2), and nitric oxide (NO) are typically referred to as 

nitrogen oxides (NOx) in the atmospheric science 

community. More formally, the family of NOx includes 

any gaseous combination of nitrogen and oxygen 

(e.g., NO2, NO, nitrous oxide [N2O], nitrogen trioxide 

[N2O3], nitrogen tetroxide [N2O4], and dinitrogen 

pentoxide [N2O5]). 

Sulfur dioxide (SO2) is one of a group of substances 

known as oxides of sulfur, or SOx, which include 

multiple gaseous substances (e.g., SO2, sulfur 

monoxide [SO], sulfur trioxide [SO3], thiosulfate [S2O3], 

and heptoxide [S2O7], as well as particulate species, 

such as ammonium sulfate [(NH4)2SO4]). 

RISK AND EXPOSURE ASSESSMENT FOR REVIEW 

OF THE SECONDARY NATIONAL AMBIENT AIR QUALITY 

STANDARDS FOR OXIDES OF NITROGEN AND 

OXIDES OF SULFUR 

EXECUTIVE SUMMARY 

INTRODUCTION 

The U.S. Environmental Protection Agency (EPA) is conducting a joint review of the 

existing secondary (welfare-based) National Ambient Air Quality Standards (NAAQS) for 

nitrogen oxides (NOx) and sulfur oxides (SOx).1 A joint secondary review of these pollutants is 

being conducted because the atmospheric chemistry and environmental effects of NOx, SOx, and 

their associated transformation products are linked, and because the National Research Council 

(NRC) has recommended that EPA consider multiple pollutants, as appropriate, in forming the 

scientific basis for the NAAQS. This is the first time since the NAAQS were established in 1971 

that a joint review of NOx, SOx, as well as of total reactive nitrogen, has been conducted. 

OVERVIEW OF NITROGEN AND SULFUR IN THE 

ENVIRONMENT 

Under Section 108 of the Clean Air Act, 

the secondary standard is to specify an 

acceptable level of the criteria pollutant(s) in 

the ambient air that is protective of known or 

anticipated adverse effects to public welfare. 

For this review, the relevant atmospheric 

indicators are ambient NOx and SOx

concentrations that can be linked to levels of 

deposition for which there are known or anticipated adverse ecological effects. The ecological 

effects of nitrogen and sulfur are caused both by the gas-phase and atmospheric deposition of the 

 

1 EPA is also conducting independent reviews of the primary (health-based) NAAQS for NOx and SOx. For 

documents related to this review, see http://www.epa.gov/ttn/naaqs/standards/no2so2sec/index.html. 
Executive Summary 

pollutants. The current secondary NAAQS were set to protect against direct damage to 

vegetation by exposure to gas-phase NOx or SOx, such as foliar injury, decreased photosynthesis, 

and decreased growth. 

Deposition of nitrogen- and sulfur-containing compounds that are derived from NOx and 

SOx may be wet (e.g., rain, snow), cloud and fog deposition, or dry (e.g., gases and particles) and 

can affect ecosystem biogeochemistry, structure, and function. Nitrogen and sulfur interactions 

in the environment are highly complex. Both are essential nutrients, and nitrogen can sometimes 

be limiting for productivity. Excess nitrogen (both oxidized and reduced forms) or sulfur can 

lead to acidification, and excess nitrogen can lead to nutrient enrichment and eutrophication. 

Acidification causes a cascade of effects that alter both terrestrial and aquatic ecosystems. When 

fully developed, acidification effects include lower biomass production rates, the injury and/or 

death of forest vegetation, and localized loss and extinction of fish and other aquatic species. In 

addition to contributing to acidification, NOx acts with other forms of reactive nitrogen 

(including reduced nitrogen) to increase the total amount of available nitrogen in ecosystems. 

Nitrogen deposition alone can alter numerous biogeochemical indicators, including 

primary productivity that leads to changes in community composition and eutrophication. In 

aquatic ecosystems, alterations in freshwater lake diatom communities and impaired water 

quality in the western United States have been observed. In estuarine ecosystems, additional 

nitrogen from anthropogenic atmospheric sources contributes to the total nitrogen loading and to 

increased phytoplankton and algal productivity, which leads to eutrophication. 

In terrestrial ecosystems, nitrate leaching is a well-documented phenomenon indicating 

that an ecosystem is receiving nitrogen in excess of biotic nutritional needs. Nitrogen deposition 

affects primary productivity, thereby altering terrestrial carbon cycling. This may result in shifts 

in population dynamics, species composition, community structure, and in extreme instances, 

ecosystem type. Lichens are the most nitrogen-sensitive terrestrial taxa, with documented 

adverse effects in the Pacific Northwest and in Southern California. Declining biodiversity 

within grasslands due to nitrogen deposition has also been observed in the central United States, 

along with changes in biodiversity in other ecosystems such as coastal sage scrub (CSS), mixed 

conifer forest (MCF) in California, and alpine ecosystems in the Rocky Mountains. 

A summary illustration of NOx and SOx effects on the environment is presented in 

Figure ES-1. 

Final Risk and Exposure Assessment ES-2 September 2009 
Executive Summary 

Figure ES-1. Nitrogen and sulfur cycling, and interactions in the environment. 

RISK AND EXPOSURE ASSESSMENT APPROACH 

Figure ES-2 shows the conceptual model framing this review describing a possible 

structure for establishing secondary standards based on meaningful ecological indicators that 

provides for protection against the range of potentially adverse ecological effects that are 

associated with the deposition of NOx, NHx, and SOx. In creating this framework, consideration 

has been given as to how the basic elements of NAAQS standards—indicator, averaging time, 

form, and level—would be reflected in such a structure. 

Final Risk and Exposure Assessment ES-3 September 2009 
Executive Summary 

2. Variable/Fixed 

Factors

Atmospheric 

Landscape

1. Air Quality 

Indicators

Measured over a 

specified 

averaging time; 

expressed in 

terms of a 

specified statistic 

(form)

3. 

Atmospheric 

Deposition 

Transformation 

Function

5. Variable/Fixed

 Factors

Ecological

4.

Deposition

Metric

6. 

Ecological 

Effect 

Function

7. Ecological 

Indicator

Calculated over a 

specified 

averaging time; 

expressed in terms 

of a specified 

statistic (form) 

(Ecological 

Benchmark)

9. Standard 

Level

Value of ecological 

indicator judged to 

provide requisite 

degree of 

protection for a 

specific endpoint

10. To Determine Whether Standard is Met:

Compare measured concentrations of the air quality 

indicator(s) in ambient air to the calculated combinations of 

air quality indicators such that the ecological indicator value 

is greater than or equal to the ecological benchmark.

8. Factors Related to 

Characterizing 

Adversity

Figure ES-2. Possible structure of a secondary NAAQS for NOx and SOx based 

on an ecological indicator. 

The framework shown in Figure ES-2 provides an example of how an ecologically 

meaningful secondary NAAQS might be structured. This example presents a system of linked 

functions that translate an air quality indicator (e.g., concentrations of NOx and SOx) into an 

ecological indicator that expresses either the potential for deposition of nitrogen and sulfur to 

acidify an ecosystem, or for nitrogen to over-enrich an ecosystem. This system encompasses the 

linkages between ambient air concentrations and resulting deposition metrics, as well as between 

the deposition metric and the ecological indicator of concern. For example, the atmospheric 

deposition transformation function (see box 3, Figure ES-2) translates ambient air 

concentrations of NOx and SOx to nitrogen and sulfur deposition metrics, while the ecological 

effect function (see box 6, Figure ES-2) relates the deposition metric into the ecological 

indicator. These two functions are very difficult to derive, taking into account geographical and 

seasonal variability of the relationship between concentrations and deposition, as well as 

uncertainty associated with measurements and model predictions. 

The amounts of NOx and SOx in the ambient air can be used to derive a deposition metric 

(via the atmospheric deposition transformation function), which can then be used to derive a 

level of an ecological indicator (through the ecological effect function) that falls within the range 

defined as acceptable by the standard; by definition, the levels of NOx and SOx will be 

Final Risk and Exposure Assessment ES-4 September 2009 
Executive Summary 

Final Risk and Exposure Assessment ES-5 September 2009 

considered to meet that standard of protection. The atmospheric levels of NOx and SOx that 

satisfy a particular level of ecosystem protection are those levels that result in an amount of 

deposition that is less than the amount of deposition a given ecosystem can accept without 

degradation of the ecological indicator for a targeted ecosystem effect. 

Because ecosystems differ in biota, climate, geochemistry, and hydrology, response to 

pollutant exposures can vary greatly between ecosystems. This Risk and Exposure Assessment 

addresses four main ecosystem effects identified in the 2008 Integrated Science Assessment 

(ISA) for Oxides of Nitrogen and Sulfur–Ecological Criteria (Final Report)(ISA): 

 Aquatic acidification due to nitrogen and sulfur 

 Terrestrial acidification due to nitrogen and sulfur 

 Aquatic nitrogen enrichment, including eutrophication 

 Terrestrial nitrogen enrichment. 

Since these ecosystem effects are not evenly distributed across the United States, case 

studies have been developed for these analyses based on ecosystems identified as sensitive to 

nitrogen and/or sulfur deposition effects. This assessment builds upon the scientific information 

presented in the ISA, and ecological indicator(s) and case study locations were selected based on 

this information. The case study areas that were identified and analyzed for the Risk and 

Exposure Assessment are described in Table ES-1, along with a summary of the ecosystem 

characteristics, indicators, and ecosystem service information regarding these areas. A map 

highlighting each of the case study areas is shown in Figure ES-3. 
Table ES-1. Summary of Sensitive Characteristics, Indicators, Effects, and Impacted Ecosystem Services Analy

Study Evaluated in This Review 

Targeted 

Ecosystem 

Effect 

Characteristics of 

Sensitivity (Variable 

Ecological Factors) 

Biological/Chemical 

Indicator Ecological Endpoint Ecological Effects 

Ecosystem Services 

Impacted 

Aquatic Acidification 

Geology, surface water flow, soil depth, weathering rates 

Al pH ANC 

Species richness, abundance, composition, ANC 

Species losses of fish, phytoplankton, and zooplankton; changed community composition, ecosystem structure, and function 

Subsistence fishing, recreational fishing, other recreational activities 

Terrestrial Acidification 

Geology, surface water flow, soil depth, weathering rates 

Soil base saturation Al Ca C:N ratio 

Tree health of red spruce and sugar maple, ANC, Bc:Al ratio 

Decreased tree growth, increased susceptibility to stress, episodic dieback; changed community composition, ecosystem structure, and function 

Provision of food and wood products, recreational activities, natural habitat, soil stabilization, erosion control, water regulation, climate regulation 

Aquatic Nutrient Enrichment 

Nitrogen-limited systems, presence of nitrogen in surface water, eutrophication status, nutrient criteria 

Chlorophyll a, macroalgae, dissolved oxygen, nuisance/toxic algal blooms, submerged aquatic vegetation (SAV) 

Changes in Eutrophication Index (EI) 

Habitat degradation, algal blooms, toxicity, hypoxia, anoxia, fish kills, decreases in biodiversity 

Commercial and recreational fishing, other recreational activities, aesthetic value, nonuse value flood and erosion control 

Terrestrial Nutrient Enrichment 

Presence of acidophytic lichens, anthropogenic land cover 

Cation exchange capacity, C:N ratios, Ca:Al ratios, NO3-

leaching and export 

Species composition, lichen presence/absence, soil root mass changes, NO3 breakthrough to 

water, biomass 

Species changes, nutrient enrichment of soil, changes in fire regime, changes in nutrient cycling 

Recreation, aesthetic value, nonuse value, firregulation, loss of habitat, loss of biodiversity, water quality 

Note: ANC = acid neutralizing capacity, SAV = submerged aquatic vegetation, EI = eutrophication index. Final Risk and Exposure Assessment ES-6 
Executive Summary 

Figure ES-3. National map highlighting the 8 case study areas and the Rocky 

Mountain National Park (a supplemental study area) evaluated in the Risk and 

Exposure Assessment. 

For assessing this set of secondary NAAQS, in addition to assessing the degree of 

scientific impairment of ecological systems relating to inputs of NOx and SOx, this Risk and 

Environmental Assessment presents an overview of the concept of ecosystem services. The 

analysis of the effects on ecosystem services will help link what is considered to be a 

biologically adverse effect with a known or anticipated adverse effect to public welfare. In this 

Risk and Exposure Assessment, ecosystem services is used to show the impacts of ecological 

effects on public welfare and to help explain how these effects are viewed by the public. The 

ability to inform decisions on the level of a secondary NAAQS will require the development of 

clear linkages between biologically adverse effects and effects that are known or anticipated to 

be adverse to public welfare. The concept of adversity to public welfare does not require the use 

of ecosystem services, yet it is envisioned as a beneficial tool for this review that may provide 

more information on the linkages between changes in ecological effects and known or 

anticipated adverse public welfare effects. 

Final Risk and Exposure Assessment ES-7 September 2009 
Executive Summary 

As described in the EPA’s Ecological Benefits Assessment Strategic Plan, it is necessary 

to recognize that in the analysis of the environmental responses associated with any particular 

policy or environmental management action, some of the ecosystem services likely to be affected 

are readily identified, while others will remain unquantified. Of those ecosystem services that are 

identified, some changes can be quantified, whereas others will remain unidentified. Within 

those services whose changes are quantified, only a few will likely be monetized, and many will 

remain unmonetized. Similar to health effects, only a portion of the ecosystem services affected 

by a policy can be monetized. A conceptual model integrating the role of ecosystem services in 

characterizing known or anticipated adverse effects to public welfare is shown in Figure ES-4. 

Knowledge about the relationships linking ambient concentrations and ecosystem 

services can be used to inform a policy judgment on a known or anticipated adverse public 

welfare effect. The conceptual model outlined for aquatic acidification in Figure ES-4 can be 

modified for any targeted effect area where sufficient data and models are available. This 

information can then be used to characterize known or anticipated adverse effects to public 

welfare and to inform a policy based on welfare effects. 

Final Risk and Exposure Assessment ES-8 September 2009 
Executive Summary 

NOx/SOx

Concentrations

Atmospheric N & S

Deposition

Aquatic

Acidification

(lake/stream ANC)

Change in Ecosystem

Structure & Processes

(fish species richness)

Change in

Ecosystem Services

(recreational fishing)

Secondary

Standard

Ambient Air Quality

Indicator

Exposure Pathway

Affected Ecosystem

Ecological Response

(ecological indicator)

Ecological Effect

Ecological Benefit/

Welfare Effect

Policy based on

Welfare Effects

NOx/SOx

Concentrations

Atmospheric N & S

Deposition

Aquatic

Acidification

(lake/stream ANC)

Change in Ecosystem

Structure & Processes

(fish species richness)

Change in

Ecosystem Services

(recreational fishing)

Secondary

Standard

Ambient Air Quality

Indicator

Exposure Pathway

Affected Ecosystem

Ecological Response

(ecological indicator)

Ecological Effect

Ecological Benefit/

Welfare Effect

Policy based on

Welfare Effects

Figure ES-4. Conceptual model showing the relationships among ambient air 

quality indicators and exposure pathways and the resulting impacts on 

ecosystems, ecological responses, ecological effects, and finally, on the quality of 

a particular activity (e.g., recreational fishing) known to influence public welfare. 

KEY FINDINGS 

The case study analyses in this Risk and Exposure Assessment have shown that, from a 

scientific perspective, there is confidence that known or anticipated adverse ecological effects 

are occurring under current ambient loadings of nitrogen and sulfur in sensitive ecosystems 

across the United States. Key findings from the air quality analyses, acidification and nutrient 

Final Risk and Exposure Assessment ES-9 September 2009 
Executive Summary 

enrichment case studies, as well as general conclusions from evaluating additional welfare 

effects, are presented below. 

AIR QUALITY ANALYSES 

The air quality analyses for this review encompass the current emissions sources of 

nitrogen and sulfur, as well as atmospheric concentrations, estimates of deposition of total 

nitrogen, policy-relevant background, and nonambient loadings of nitrogen and sulfur to 

ecosystems, both nationwide and in the case study areas. Spatial fields of deposition were created 

using wet deposition measurements from the National Atmospheric Deposition Program (NADP) 

National Trends Network and dry deposition predictions from the 2002 Community Multi-Scale 

Air Quality (CMAQ) model simulation. 

 Total reactive nitrogen deposition and sulfur deposition are much greater in the East 

compared to most areas of the West. 

 These regional differences in deposition correspond to the regional differences in NOx and 

SO2 concentrations and emissions, which are also higher in the East. 

 NOx emissions are much greater and generally more widespread than NH3 emissions 

nationwide; high NH3 emissions tend to be more local (e.g., eastern North Carolina) or 

sub-regional (e.g., the upper Midwest and Plains states). 

 The relative amounts of oxidized versus reduced nitrogen deposition are consistent with 

the relative amounts of NOx and NH3 emissions. 

- Oxidized nitrogen deposition exceeds reduced nitrogen deposition in most of the case 

study areas; the major exception being the Neuse River/Neuse River Estuary Case 

Study Area. 

- Reduced nitrogen deposition exceeds oxidized nitrogen deposition in the vicinity of 

local sources of NH3. 

 There can be relatively large spatial variations in both total reactive nitrogen deposition 

and sulfur deposition within a case study area; this occurs particularly in those areas that 

contain or are near a high emissions source of NOx, NH3, and/or SO2. 

 The seasonal patterns in deposition differ between the case study areas. 

- For the case study areas in the East, the season with the greatest amounts of total 

reactive nitrogen deposition correspond to the season with the greatest amounts of 

Final Risk and Exposure Assessment ES-10 September 2009 
Executive Summary 

sulfur deposition. Deposition peaks in spring in the Adirondack, Hubbard Brook 

Experimental Forest, and Kane Experimental Forest case study areas, and it peaks in 

summer in the Potomac River/Potomac Estuary, Shenandoah, and Neuse River/Neuse 

River Estuary case study areas. 

- For the case study areas in the West, there is less consistency in the seasons with 

greatest total reactive nitrogen and sulfur deposition in a given area. In general, both 

nitrogen and/or sulfur deposition peaks in spring or summer. The exception to this is 

the Sierra Nevada Range portion of the Mixed Conifer Forest Case Study Area, in 

which sulfur deposition is greatest in winter. 

ACIDIFICATION 

Aquatic 

The role of aquatic acidification in two eastern United States areas—northeastern New 

York’s Adirondack area and the Shenandoah area in Virginia—was analyzed to assess surface 

water trends in SO4

2-and NO3-

concentrations and acid neutralizing capacity (ANC) levels and to 

affirm the understanding that reductions in deposition could influence the risk of acidification. 

Monitoring data from the EPA-administered Temporally Integrated Monitoring of Ecosystems 

(TIME)/Long-Term Monitoring (LTM) programs and the Environmental Monitoring and 

Assessment Program (EMAP) were assessed for the years 1990 to 2006, and past, present, and 

future water quality levels were estimated using both steady-state and dynamic biogeochemical 

models. A summary of findings follows: 

Although wet deposition rates for SO2 and NOx in the Adirondack Case Study Area have 

reduced since the mid-1990s, current concentrations in are still well above preacidification 

(1860) conditions. Model of Acidification of Groundwater in Catchments (MAGIC) modeling 

predicts NO3

-

 and SO4

2- are 17- and 5-fold higher today, respectively. The estimated average 

ANC for 44 lakes in the Adirondack Case Study Area is 62.1 microequivalents per liter (μeq/L) 

(± 15.7 μeq/L); 78 % of all monitored lakes in the Adirondack Case Study Area have a current 

risk of Elevated, Severe, or Acute. Of the 78%, 31% experience episodic acidification, and 18% 

are chronically acidic today. 

Final Risk and Exposure Assessment ES-11 September 2009 
Executive Summary 

 Based on the steady-state critical load model for the year 2002, 18%, 28%, 44%, and 58% 

of 169 modeled lakes received combined total sulfur and nitrogen deposition that exceeded 

their critical load, with critical ANC limits of 0, 20, 50, and 100 μeq/L, respectively. 

 Based on a deposition scenario that maintains current emission levels to 2020 and 2050, 

the simulation forecast indicates no improvement in water quality in the Adirondack Case 

Study Area. The percentage of lakes within the Elevated to Acute Concern classes remains 

the same in 2020 and 2050. 

 Since the mid-1990s, streams in the Shenandoah Case Study Area have shown slight 

declines in NO3

-

 and SO4

2- concentrations in surface waters. ANC levels increased from 

about 50 μeq/L in the early 1990 to >75 μeq/L until 2002, when ANC levels declined back 

to 1991–1992 levels. Current concentrations are still above preacidification (1860) 

conditions. MAGIC modeling predicts surface water concentrations of NO3

-

 and SO4

2- are 

10- and 32-fold higher today, respectively. The estimated average ANC for 60 streams in 

the Shenandoah Case Study Area is 57.9 μeq/L (± 4.5 μeq/L). 55% of all monitored 

streams in the Shenandoah Case Study Area have a current risk of Elevated, Severe, or 

Acute. Of the 55%, 18% experience episodic acidification, and 18% are chronically acidic 

today. 

 Based on the steady-state critical load model for the year 2002, 52%, 72%, 85%, and 93% 

of 60 modeled streams received combined total sulfur and nitrogen deposition that 

exceeded their critical load, with critical ANC limits of 0, 20, 50, and 100 μeq/L, 

respectively. 

 Based on a deposition scenario that maintains current emission levels to 2020 and 2050, 

the simulation forecast indicates that a large number of streams still have Elevated to 

Acute problems with acidity. In fact, from 2006 to 2050, the percentage of streams with 

Acute Concern increases by 5%, while the percentage of streams in Moderate Concern

decreases by 5%. 

Terrestrial 

The role of terrestrial acidification was examined using a critical load analysis for sugar 

maple and red spruce forests in the eastern United States by using the base cation to aluminum 

(Bc/Al) ratio in acidified forest soils as an indicator to assess the impact of nitrogen and sulfur 

Final Risk and Exposure Assessment ES-12 September 2009 
Executive Summary 

deposition on tree health. These are the two most commonly studied species in North America 

for impacts of acidification. At a Bc/Al ratio of 1.2, red spruce growth can be reduced by 20%. 

Sugar maple growth can be reduced by 20% at a Bc/Al ratio of 0.6. Key findings of the case 

study are summarized below. 

 Case study results suggest that the health of at least a portion of the sugar maple and red 

spruce growing in the United States may have been compromised with acidifying total 

nitrogen and sulfur deposition in 2002: 

- 2002 CMAQ/NADP total nitrogen and sulfur deposition levels exceeded three 

selected critical loads in 3% to 75% of all sugar maple plots across 24 states. The 

three critical loads ranged from 107 to 6,008 eq/ha/yr for the Bc/Al ratios of 0.6, 1.2, 

and 10.0 (increasing levels of tree protection). 

- 2002 CMAQ/NADP total nitrogen and sulfur deposition levels exceeded three 

selected critical loads in 3% to 36% of all red spruce plots across 8 states. The three 

critical loads ranged from 180 to 4,278 eq/ha/yr for the Bc/Al ratios of 0.6, 1.2, and 

10.0 (increasing levels of tree protection). 

 The Simple Mass Balance model assumptions made for base cation weathering (Bcw) and 

forest soil ANC input parameters are the main sources of uncertainty since these 

parameters are rarely measured and require researchers to use default values. Bcw 

contributed 49% to the total variability in the critical load estimates, and forest soil ANC 

contributed 46% to the total variability. 

 The pattern of case study results suggests that nitrogen and sulfur acidifying deposition in 

the sugar maple and red spruce forest areas studied were very close to, if not greater than, 

the critical loads for those areas, and both ecosystems are likely to be sensitive to any 

future changes in the levels of deposition. 

NUTRIENT ENRISHMENT 

Aquatic 

The role of nitrogen deposition in two mainstem rivers feeding their respective estuaries 

was analyzed to determine if decreases in deposition could influence the risk of eutrophication as 

predicted using the Assessment of Estuarine Trophic Status eutrophication index (ASSETS EI) 

scoring system in tandem with SPAtially Referenced Regression on Watershed Attributes 

Final Risk and Exposure Assessment ES-13 September 2009 
Executive Summary 

(SPARROW) modeling. This modeling approach provides a transferrable, intermediate-level 

analysis of the linkages between atmospheric deposition and receiving waters, while providing 

results on which conclusions could be drawn. Future application of the methods to case study 

areas where atmospheric deposition plays a larger role in the nitrogen loading to an estuary will 

likely provide more tangible results. A summary of findings follows: 

 2002 CMAQ/NADP results showed that an estimated 40,770,000 kg of total nitrogen was 

deposited in the Potomac River watershed. SPARROW modeling predicted that 7,380,000 

kg N/yr of the deposited nitrogen reached the estuary (20% of the total load to the estuary). 

The overall ASSETS EI for the Potomac River and Potomac Estuary was Bad. 

 To improve the Potomac River and Potomac Estuary ASSETS EI score from Bad to Poor, 

there is a slim chance that a decrease of at least 78% in the 2002 total nitrogen atmospheric 

deposition load to the watershed would be required. 

 2002 CMAQ/NADP results showed that an estimated 18,340,000 kg of total nitrogen was 

deposited in the Neuse River watershed. SPARROW modeling predicted that 1,150,000 kg 

N/yr of the deposited nitrogen reached the estuary (26% of the total load to the estuary). 

The overall ASSETS EI for the Neuse River/Neuse River Estuary was Bad. 

 It was found that the Neuse River/Neuse River Estuary ASSETS EI score could not be 

improved from Bad to Poor with decreases only in the 2002 atmospheric deposition load 

to the watershed. Additional reductions would be required from other nitrogen sources 

within the watershed. 

The small effect of decreasing atmospheric deposition in the Neuse River watershed is 

because the other nitrogen sources within the watershed are more influential than atmospheric 

deposition to the total nitrogen loadings to the Neuse River Estuary as estimated with the 

SPARROW model. A waterbody’s response to nutrient loading depends on the magnitude (e.g., 

agricultural sources have a high influence in the Neuse), spatial distribution, and other 

characteristics of the sources within the watershed. 

Terrestrial 

California CSS and MCF were the focus of the Terrestrial Nutrient Enrichment Case 

Study. Geographic information systems (GIS) analysis supported a qualitative review of past 

field research to identify ecological benchmarks associated with CSS and mycorrhizal 

Final Risk and Exposure Assessment ES-14 September 2009 
Executive Summary 

communities, as well as MCF’s nutrient-sensitive acidophyte lichen communities, fine-root 

biomass in Ponderosa pine, and leached nitrate in receiving waters. These benchmarks, ranging 

from 3.1 to 17 kg N/ha/yr, were compared to 2002 CMAQ/NADP data to discern any 

associations between atmospheric deposition and changing communities. Evidence supports the 

finding that nitrogen alters CSS and MCF. Key findings include the following: 

 2002 CMAQ/NADP nitrogen deposition data show that the 3.3 kg N/ha/yr benchmark has 

been exceeded in more than 93% of CSS areas (654,048 ha). These deposition levels are a 

driving force in the degradation of CSS communities. Although CSS decline has been 

observed in the absence of fire, the contributions of deposition and fire to the CSS decline 

require further research. CSS is fragmented into many small parcels, and the 2002 

CMAQ/NADP 12-km grid data are not fine enough to fully validate the relationship 

between CSS distribution, nitrogen deposition, and fire. 

 2002 CMAQ/NADP nitrogen deposition data exceeds the 3.1 kg N/ha/yr benchmark in 

more than 38% (1,099,133 ha) of MCF areas, and nitrate leaching has been observed in 

surface waters. Ozone effects confound nitrogen effects on MCF acidophyte lichen, and 

the interrelationship between fire and nitrogen cycling requires additional research. 

ADDITIONAL EFFECTS 

Ecological effects have also been documented across the United States where elevated 

nitrogen deposition has been observed, including the eastern slope of the Rocky Mountains 

where shifts in dominant algal species in alpine lakes have occurred where wet nitrogen 

deposition was only about 1.5 kg N/ha/yr. High alpine terrestrial communities have a low 

capacity to sequester nitrogen deposition, and monitored deposition exceeding 3 to 4 kg N/ha/yr 

could lead to community-level changes in plant species, lichens, and mycorrhizae. 

Additional welfare effects that are documented, but examined less extensively, in this 

Risk and Exposure Assessment include the following: 

 Visibility and materials damage, such as corrosion, erosion, and soiling of paint and 

buildings. Both effects are being addressed in the particulate matter (PM) NAAQS review 

currently underway. 

 The causal relationship between sulfur deposition (as sulfate, SO4

2-) and increased 

mercury methylation in wetlands and aquatic environments. Decreases in sulfate 

Final Risk and Exposure Assessment ES-15 September 2009 
Executive Summary 

deposition will likely result in decreases in methyl mercury concentration; however, 

spatial and biogeochemical variations nationally hinder establishing large scale doseresponse relationships. 

 Nitrous oxide (N2O). A potent GHG, it is most appropriate to analyze the role of N2O in 

the context of all of the GHGs rather than as part of this Risk and Exposure Assessment. 

 Nitrogen deposition and its correlation with the rate of photosynthesis and net 

primary productivity. Nitrogen addition ranging from 15.4 to 300 kg N/ha/yr is 

documented as increasing wetland N2O production by an average of 207%. Nitrogen 

addition ranging from 30 to 240 kg N/ha/y increased CH4 emissions by 115%, averaged 

across all ecosystems, and methane uptake was reduced by 38% when nitrogen addition 

ranged from 10 to 560 kg N/ha/yr, but reductions were only significant for coniferous and 

deciduous forests. The heterogeneity of ecosystems across the United States, however, 

introduces variations into dose-response relationships. 

 Phytotoxic effects on vegetation. A unique secondary NAAQS exists for SO2, and 

concentrations of NO, NO2, and peroxyacetyl nitrates (PAN) are rarely high enough to 

have phtyotoxic effects on vegetation. Although relatively little is known about the direct 

effects of nitric acid (HNO3) vapor on vegetation in California’s Transverse Range MCF, 

HNO3 has been estimated to provide 60% of all dry deposited nitrogen and has been 

suspected as the cause of a dramatic decline in lichen species. 

SYNTHESIS AND INTEGRATION OF CASE STUDY RESULTS 

The case study analyses associated with each targeted effect area were synthesized by 

identifying the strengths, limitations, and uncertainties associated with the available data, 

modeling approach, and the relationship between the selected ecological indicator and 

atmospheric deposition as described by the ecological effect function. The level of confidence 

associated with each parameter, as well as the known data gaps and research needs associated 

with each targeted effect area, were identified. This information is summarized below. 

Final Risk and Exposure Assessment ES-16 September 2009 
Executive Summary 

AQUATIC ACIDIFICATION 

 The available data used for the targeted effect of aquatic acidification are robust and 

considered high quality. There is a high confidence about the use of these data and their 

value for extrapolating to a larger regional population of lakes. 

 There is fairly high confidence associated with the models, input parameters, and 

assessment of uncertainty used in the case study analysis for aquatic acidification. 

 There is high confidence associated with the ecological effect function developed for 

aquatic acidification. 

Data Gaps and Research Needs 

 Developing relationships between critical loads for aquatic acidity and effects on 

ecosystem services, especially due to incremental changes in an ecological indicator such 

as ANC 

 Developing nationwide weathering rates, or weathering rates for aquatic ecosystems 

sensitive to acidification 

 Developing a better understanding of the uncertainty in critical loads for acidity and 

exceedance values 

 Developing methods for calculating critical loads for surface water acidity when data are 

absent or of poor quality 

 Evaluating ways to combine multiple critical load estimates for surface waters and soils on 

a national scale 

 Estimating ways to determine critical load parameters across different media (e.g., surface 

waters, soils). 

TERRESTRIAL ACIDIFICATION 

 The available data used to quantify the targeted effect of terrestrial acidification are robust 

and considered high quality. There is high confidence about the use of these data and their 

value for extrapolating to a larger regional population of forests. 

 There is high confidence associated with the models, input parameters, and assessment of 

uncertainty used in the case study analysis for terrestrial acidification. 

Final Risk and Exposure Assessment ES-17 September 2009 
Executive Summary 

 There is fairly high confidence associated with the ecological effect function developed for 

terrestrial acidification. 

Data Gaps and Research Needs 

 Determining the most appropriate and accurate base cation weathering model to estimate 

terrestrial critical acid loads nationwide 

 Expanding analyses to examine the relationships between tree growth and (1) critical load 

exceedance and (2) nitrogen deposition (i.e., further refine analyses of sugar maple and red 

spruce, and expand analyses to include more tree species and a larger geographical area) to 

establish additional evidence of the connection between nitrogen and sulfur deposition and 

biological end points 

 Exploring field-based tree growth as a tool to determine the most suitable Bc/Al soil 

solution indicator ratio 

 Developing relationships between critical loads for terrestrial acidity and effects on 

ecosystem services. 

AQUATIC NUTRIENT ENRICHMENT 

 The available data used for the targeted effect of aquatic nitrogen enrichment are 

considered medium quality. There is intermediate confidence about the use of these data 

and their value for extrapolating to a larger regional area. 

 There is intermediate confidence associated with the models, input parameters, and 

assessment of uncertainty used in the case study analysis for excess aquatic nitrogen 

enrichment. 

 There is low confidence associated with the ecological effect function developed for excess 

aquatic nitrogen enrichment. 

Data Gaps and Research Needs 

 Refining development of adequate indicators of effects of nitrogen enrichment 

 Enhancing relationships between ecological indicators of nitrogen enrichment and 

atmospheric deposition used in this study 

 Applying the methods used in this study to an atmospheric deposition-dominated estuarine 

system 

Final Risk and Exposure Assessment ES-18 September 2009 
Executive Summary 

 Reducing model and data uncertainty 

 Expanding relationships between ecological indicators of nitrogen enrichment and 

ecosystem services associated with them 

 Exploring alternative relationships between ecological indicators and atmospheric 

deposition other than what was used in this study giving consideration to methods that can 

be extrapolated outside of the case study area 

 Improving knowledge of how individual chemical species of nitrogen contribute to 

eutrophication effects. 

TERRESTRIAL NUTRIENT ENRICHMENT 

 The available data used for the targeted effect of terrestrial nitrogen enrichment are 

considered high quality; however, there is a limited ability to extrapolate these data to a 

larger regional area. 

 No quantitative modeling was conducted for terrestrial nitrogen enrichment. 

 No ecological effect function was developed for excess terrestrial nitrogen enrichment. 

Data Gaps and Research Needs 

 Elucidating the interactions among elevated levels of atmospheric nitrogen, fire intensity 

and frequency, and invasive grasses for CSS and elevated nitrogen and fire for MCF 

 Increasing the understanding of CSS and MCF communities long-term response to 

elevated nitrogen and how benchmarks may change 

 Developing indicators of CSS ecosystem health 

 Using modeled data with a higher spatial resolution 

 Increasing the understanding of the interactions between ozone, climate change, and 

nitrogen deposition on CSS and MCF communities. 

CONCLUSIONS 

Although it is recognized that while there will always be inherent variability in ecological 

data and uncertainties associated with modeling approaches, there is a high level of confidence 

from a scientific perspective that known or anticipated adverse ecological effects are occurring 

Final Risk and Exposure Assessment ES-19 September 2009 
Executive Summary 

Final Risk and Exposure Assessment ES-20 September 2009 

under current ambient loadings of nitrogen and sulfur in sensitive ecosystems across the United 

States. 

For aquatic and terrestrial acidification effects, a similar conceptual approach was used 

(critical loads) to evaluate the impacts of multiple pollutants on an ecological endpoint, whereas 

the approaches used for aquatic and terrestrial nutrient enrichment were fundamentally distinct. 

Although the ecological indicators for aquatic and terrestrial acidification (i.e., ANC and Bc/Al) 

are very different, both ecological indicators are well-correlated with effects such as reduced 

biodiversity and growth. While aquatic acidification is clearly the targeted effect area with the 

highest level of confidence, the relationship between atmospheric deposition and an ecological 

indicator is also quite strong for terrestrial acidification. The main drawback with the 

understanding of terrestrial acidification is that the data are based on laboratory responses rather 

than field measurements. Other stressors that are present in the field but that are not present in 

the laboratory may confound this relationship. 

The ecological indicator chosen for aquatic nutrient enrichment, the ASSETS EI, seems 

to be inadequate to relate atmospheric deposition to the targeted ecological effect, likely due to 

the many other confounding factors. Further, there is far less confidence associated with the 

understanding of aquatic nutrient enrichment because of the large contributions from nonatmospheric sources of nitrogen and the influence of both oxidized and reduced forms of 

nitrogen, particularly in large watersheds and coastal areas. However, a strong relationship exists 

between atmospheric deposition of nitrogen and ecological effects in high alpine lakes in the 

Rocky Mountains because atmospheric deposition is the only source of nitrogen to these 

systems. There is also a strong weight-of-evidence regarding the relationships between 

ecological effects attributable to terrestrial nitrogen nutrient enrichment; however, ozone and 

climate change may be confounding factors. In addition, the response for other species or species 

in other regions of the United States has not been quantified. 

A summary of the information presented by this Risk and Exposure Assessment that may 

be useful for characterizing known or anticipated adverse effects to public welfare is shown in 

Table ES-2. This information may be useful to inform decision makers about what levels of 

protection might be appropriate to protect public welfare from known or anticipated adverse 

impacts on ecosystems. Characterizing known or anticipated adverse effects to public welfare 

from a policy perspective will be addressed in the policy assessment for this review.
Table ES-2. Summary of Information Assessed in the Risk and Exposure Assessment to Aid in Informing Policy Effects. 

Exposure Pathway 

(Current Deposition 

Levels) 

(NADP/CMAQ, 

2002) 

Affected Ecosystem 

(Case Study Areas) 

Ecological 

Response 

(Targeted Effect) 

Ecological 

Indicator Ecological Effect Eco

Adirondack Case Study Area: 10 kg N/ha/yr 9 kg S/ha/yr Shenandoah Case Study Area: 11 kg N/ha/yr 11 kg S/ha/yr 

Adirondack Mountains, NY Blue Ridge Mountains and Shenandoah National Park, VA

Acidification in lakes and streams 

Fish species richness, abundance, composition, ANC 

Species losses of fish, phytoplankton, zooplankton; changed community composition, ecosystem structure, and function 

AnnfishmorAppin imfrom and 

Kane Experimental Forest Case Study Area: 14 kg N/ha/yr 210 kg S/ha/yr Hubbard Brook Experimental Forest Case Study Area: 8 kg N/ha/yr 7 kg S/ha/yr 

Kane Experimental Forest (Allegheny Plateau, PA) Hubbard Brook Experimental Forest (White Mountains, NH) 

Acidification of forest soils 

Tree health Red spruce, sugar maple Bc/Al ratio 

Decreased tree growth Increased susceptibility to stress, episodic dieback; changed community composition, ecosystem structure, and function 

Prov(sug900 prod

Final Risk and Exposure Assessment ES-21 
Final Risk and Exposure Assessment ES-22 

Exposure Pathway 

(Current Deposition 

Levels) 

(NADP/CMAQ, 

2002) 

Affected Ecosystem 

(Case Study Areas) 

Ecological 

Response 

(Targeted Effect) 

Ecological 

Indicator Ecological Effect Eco

Potomac River/Potomac Estuary Case Study Area: 13 kg N/ha/yr Neuse River/Neuse River Estuary Case Study Area: 14 Kg N/ha/yr 

Potomac River Basin, Chesapeake Bay Neuse River Basin, Pamlico Sound

Nutrient enrichment in main stem river of an estuary 

ASSETS EI Habitat degradation, 

algal blooms, toxicity, hypoxia, anoxia, fish kills, decreases in biodiversity 

Currrecr26.1 (NoMas

Coastal Sage Scrub: from 3 to 10 kg N/ha/yr Mixed Conifer Forest (San Bernardino Mountains and Sierra Nevada Range): from 3 to 10 kg N/ha/yr 

Southern California Coastal Sage Scrub Mixed Conifer Forest (San Bernardino Mountains and Sierra Nevada Mountains, CA)

Nutrient enrichment in terrestrial ecosystems 

Species composition Species changes, 

nutrient enrichment of soil, changes in fire regime, changes in nutrient cycling 

Annresidwildapprstate supp(200
Chapter 1 – Introduction 

Final Risk and Exposure Assessment 1-1 September 2009 

1.0 INTRODUCTION 

1.1 RATIONALE AND BACKGROUND FOR JOINT REVIEW 

The U.S. Environmental Protection Agency (EPA or the Agency) is conducting a joint 

review of the existing secondary (welfare-based) National Ambient Air Quality Standards 

(NAAQS) for nitrogen oxides (NOx) and sulfur oxides (SOx), which are currently defined in 

terms of nitrogen dioxide (NO2) and sulfur dioxide (SO2), respectively.1 Sections 108 and 109 of 

the Clean Air Act (CAA or the Act) govern the establishment and periodic review of the 

NAAQS and of the air quality criteria upon which the standards are based. The NAAQS are 

established for pollutants that may reasonably be anticipated to endanger public health or welfare 

and whose presence in the ambient air results from numerous or diverse mobile or stationary 

sources. The NAAQS are based on air quality criteria that reflect the latest scientific knowledge, 

which is useful in indicating the kind and extent of identifiable effects on public health or 

welfare that may be expected from the presence of the pollutant in ambient air. Based on 

periodic reviews of the air quality criteria and standards, EPA makes revisions to the criteria and 

standards and promulgates any new standards as may be appropriate. The Act also requires that 

an independent scientific review committee advise the Administrator as part of this NAAQS 

review process, a function now performed by the Clean Air Scientific Advisory Committee 

(CASAC). 

In conducting this periodic review of the NO2 and SO2 secondary NAAQS, EPA has 

decided to jointly assess the scientific information, associated risks, and standards relevant to 

protecting the public welfare from adverse effects associated with NOx and SOx. As noted in 

Section 1.2 of this report, EPA has historically defined the NAAQS for these pollutants in terms 

 

1 EPA is also conducting independent reviews of the primary (health-based) NAAQS for NOx and SOx. 
Chapter 1 – Introduction 

of the specific compounds NO2 and SO2, which serve as indicators of the broader set of 

compounds that comprise NOx and SOx, respectively. The chemical species of nitrogen and 

sulfur compounds and the types of related ecological effects that are being considered within the 

scope of this review are discussed in Section 1.3 of this report. A joint secondary review of these 

pollutants is being conducted because the atmospheric chemistry and environmental effects of 

NOx, SOx, and their associated transformation products are linked and because the National 

Research Council (NRC) has recommended that EPA consider multiple pollutants, as 

appropriate, in forming the scientific basis for the NAAQS (NRC, 2004). This is the first time 

since the NAAQS were established in 1971 that a joint review of NOx, SOx, as well as total 

reactive nitrogen, has been conducted. There is a strong basis for considering these pollutants 

together, building upon EPA’s and CASAC’s past recognition of the interactions of these 

pollutants and on the growing body of scientific information that is now available related to these 

interactions and associated ecological effects. A series of framing questions that help to shape 

this review are presented in Section 1.4 of this report, together with an overview of how 

secondary NAAQS for NOx and SOx might be structured to reflect the complex interactions 

among relevant species of these pollutants that are ecologically meaningful. As discussed in the 

CAA [Section 109(b)(2)], the purpose of a secondary NAAQS is to protect the public welfare 

from any known or anticipated adverse effects associated with the presence of such air pollutants 

in the ambient air. 

This joint review is organized according to EPA’s current NAAQS review process, which 

consists of four major components and related documents: an Integrated Review Plan (U.S. EPA, 

2007), the Integrated Science Assessment (ISA) for Oxides of Nitrogen and Sulfur–Ecological 

Criteria (Final Report) (ISA) (U.S. EPA, 2008), the Risk and Exposure Assessment, and a 

policy assessment and rulemaking notices. The Integrated Review Plan provides the framework 

and schedule for this review and identifies policy-relevant questions to be addressed in the other 

components of the review. The ISA, released on December 12, 2008, provides an integrative 

assessment of the relevant scientific information and forms the scientific basis for the 

assessments presented in this Risk and Exposure Assessment, which describes the progress to 

date on the assessments being conducted as part of the third component of the review process. To 

view related documents developed as part of the planning and science assessment phases of this 

Final Risk and Exposure Assessment 1-2 September 2009 
Chapter 1 – Introduction 

review (e.g., Integrated Review Plan, the ISA), go to 

http://www.epa.gov/ttn/naaqs/standards/no2so2sec/index.html. 

When complete, the Risk and Exposure Assessment will evaluate the exposures of 

ecological receptors to both ambient and deposited species of NOx and SOx, as well as their 

transformation products (including reduced forms of ambient nitrogen), and assess, both 

quantitatively and qualitatively, the risks associated with these exposures. Where possible, the 

contributions of various sources and forms of atmospheric nitrogen to these risks are 

characterized. The following bullets outline the organization of this final draft report, which, to 

the degree possible, reflects the components of the Risk and Exposure Assessment: 

 Chapter 1 provides an overview of this review; a history of past reviews and other 

relevant scientific assessments and EPA actions; a discussion of the scope of this joint 

NOx and SOx review; and a series of framing questions, together with an overview of 

how secondary NAAQS for NOx and SOx might be structured. 

 Chapter 2 provides an overview of the Risk and Exposure Assessment, including the 

scope and approach to assessing current conditions for a targeted effect, a summary of the 

case study areas, a discussion of the identification and selection of ecosystem services, 

and a discussion on addressing uncertainty throughout the review. 

 Chapter 3 addresses the relevant air quality issues associated with this review, including 

the sources, emissions, and deposition of total reactive nitrogen and sulfur and their 

current contributions to ambient conditions. Both spatial and temporal characterizations 

of ambient concentrations of nitrogen and sulfur and the contributions of ambient 

concentrations of nitrogen and sulfur to deposition are explored in select case study areas. 

In addition, there is a discussion on the relationship between atmospheric concentrations 

and deposition and how the Atmospheric Deposition Transformation Function might be 

structured (see Figure 1.4-1). 

 Chapter 4 focuses on acidification, with an overview of the relevant science and 

progress on case study analyses and developing the associated ecological effect functions 

(see Figure 1.4-1) for both aquatic and terrestrial acidification. 

 Chapter 5 focuses on nitrogen nutrient enrichment, with an overview of the relevant 

science and progress on case study analyses and developing the associated ecological 

Final Risk and Exposure Assessment 1-3 September 2009 
Chapter 1 – Introduction 

effect functions (see Figure 1.4-1) for both aquatic and terrestrial nitrogen nutrient 

enrichment (commonly referred to as nutrient enrichment). 

 Chapter 6 qualitatively addresses additional effects, including visibility, climate, and 

materials. There is a discussion on the interactions between sulfur and methylmercury 

production, nitrous oxide (N2O) effects on climate, nitrogen addition effects on primary 

productivity and biogenic greenhouse gas fluxes, and phytotoxic effects on plants. 

 Chapter 7 synthesizes the case study analyses associated with each targeted effect area 

by identifying the strengths, limitations, and uncertainties associated with the available 

data, modeling approach, and relationship between the selected ecological indicator and 

atmospheric deposition as described by the ecological effect function. The level of 

confidence associated with each parameter, as well as the known data gaps and research 

needs associated with each targeted effect area, is identified. 

1.2 HISTORY 

1.2.1 History of the Secondary NO2 NAAQS 

On April 30, 1971, EPA promulgated identical primary and secondary NAAQS for NO2

under Section 109 of the CAA. The standards were set at 0.053 parts per million (ppm), annual 

average (36 FR 8186). In 1982, EPA published the air quality criteria document (AQCD) Air 

Quality Criteria for Oxides of Nitrogen (U.S. EPA, 1982), which updated the scientific criteria 

for NOx, upon which the initial NO2 standards were based. On February 23, 1984, EPA proposed 

to retain these standards (49 FR 6866). After taking into account public comments, EPA 

published the final decision to retain these standards on June 19, 1985 (50 FR 25532). 

On July 22, 1987, EPA announced that it was undertaking plans to revise the 1982 NOx

AQCD (52 FR 27580), and in November 1991, EPA released an updated draft AQCD for 

CASAC and public review and comment (56 FR 59285). This latter draft document provided a 

comprehensive assessment of the available scientific and technical information on health and 

welfare effects associated with NO2 and other NOx. CASAC reviewed the draft document at a 

meeting held on July 1, 1993, and concluded in a closure letter to the Administrator that the 

document “provides a scientifically balanced and defensible summary of current knowledge of 

the effects of this pollutant and provides an adequate basis for EPA to make a decision as to the 

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Chapter 1 – Introduction 

appropriate NAAQS for NO2” (Wolff, 1993). The AQCD Air Quality Criteria for Oxides of 

Nitrogen was then finalized (U.S. EPA, 1993). 

EPA also prepared a Staff Paper that summarized an air quality assessment for NO2

conducted by the Agency (McCurdy, 1994). This Staff Paper summarized and integrated the key 

studies and scientific evidence contained in the revised NOx AQCD and identified the critical 

elements to be considered in the review of the NO2 NAAQS. CASAC reviewed two drafts of the 

Staff Paper and concluded in a closure letter to the Administrator that the document provided a 

“scientifically adequate basis for regulatory decisions on nitrogen dioxide” (Wolff, 1995). In 

September 1995, EPA finalized the Staff Paper, entitled Review of the National Ambient Air 

Quality Standards for Nitrogen Dioxide: Assessment of Scientific and Technical Information

(U.S. EPA, 1995a). 

In October 1995, the Administrator announced her proposed decision not to revise either 

the primary or secondary NAAQS for NO2 (60 FR 52874; October 11, 1995). A year later, the 

Administrator made a final determination not to revise the NAAQS for NO2 after careful 

evaluation of the comments received on the proposal (61 FR 52852; October 8, 1996). The level 

for both the existing primary and secondary NAAQS for NO2 is 0.053 ppm (100 micrograms per 

cubic meter [μg/m3] of air), annual arithmetic average, calculated as the arithmetic mean of the 

1-hour NO2 concentrations. 

1.2.2 History of the Secondary SO2 NAAQS 

Based on the 1970 AQCD Air Quality Criteria for Sulfur Oxides (DHEW, 1970), EPA 

promulgated primary and secondary NAAQS for SO2 under Section 109 of the CAA on April 30, 

1971 (36 FR 8186). The secondary standards included a standard at 0.02 ppm in an annual 

arithmetic mean and a 3-hour average of 0.5 ppm, not to be exceeded more than once per year. 

These secondary standards were established solely on the basis of vegetation-effects evidence. In 

1973, revisions made to Chapter 5 (Effects of Sulfur Oxide in the Atmosphere on Vegetation) of 

the AQCD Effects of Sulfur Oxides in the Atmosphere on Vegetation; Revised Chapter 5 for Air 

Quality Criteria for Sulfur Oxides (U.S. EPA, 1973) indicated that it could not properly be 

concluded that the vegetation injury reported resulted from the average SO2 exposure over the 

growing season, rather than from short-term peak concentrations. Therefore, EPA proposed 38 

FR 11355 and then finalized 38 FR 25678, a revocation of the annual mean secondary standard. 

Final Risk and Exposure Assessment 1-5 September 2009 
Chapter 1 – Introduction 

At that time, EPA was aware that SOx has other public welfare effects, including effects on 

materials, visibility, soils, and water; however, the available data were considered insufficient to 

establish a quantitative relationship between specific atmospheric SOx concentrations and effects 

needed for setting a standard (38 FR 25679). 

In 1979, EPA announced that it was revising the 1973 SOx AQCD concurrently with that 

for particulate matter (PM) and would produce a combined PM and SOx criteria document. 

Following its review of a draft revised criteria document in August 1980, CASAC concluded that 

acidifying deposition was a topic of extreme scientific complexity because of the difficulty in 

establishing firm quantitative relationships among (1) emissions of relevant pollutants (e.g., SO2, 

NOx), (2) formation of acidifying wet and dry deposition products, and (3) effects on terrestrial 

and aquatic ecosystems. CASAC also noted that acidifying deposition involves, at a minimum, 

several different criteria pollutants: SOx, NOx, and the fine particulate fraction of suspended 

particles. CASAC felt that any document on this subject should address both wet and dry 

deposition because dry deposition was believed to account for at least one-half of the total 

acidifying deposition problem. 

For these reasons, CASAC recommended that a separate, comprehensive document on 

acidifying deposition be prepared prior to any consideration of using the NAAQS as a regulatory 

mechanism for the control of acidifying deposition. CASAC also suggested that a discussion of 

acidifying deposition be included in the AQCD for NOx, PM, and SOx. Following CASAC 

closure on the criteria document for SO2 in December 1981, EPA’s Office of Air Quality 

Planning and Standards (OAQPS) published a Staff Paper in November 1982, but the paper did 

not directly assess the issue of acidifying deposition. Instead, EPA subsequently prepared the 

following documents: The Acidic Deposition Phenomenon and Its Effects: Critical Assessment 

Review Papers, Volumes I and II (U.S. EPA, 1984a, b) and The Acidic Deposition Phenomenon 

and Its Effects: Critical Assessment Document (U.S. EPA, 1985) (53 FR 14935-14936). Though 

these documents were not considered criteria documents and did not undergo CASAC review, 

they represented the most comprehensive summary of relevant scientific information completed 

by EPA to that point. 

On April 26, 1988 (53 FR 14926), EPA proposed not to revise the existing primary and 

secondary standards. This proposal regarding the secondary SO2 NAAQS was due to the 

Administrator’s conclusions that (1) based upon the then-current scientific understanding of the 

Final Risk and Exposure Assessment 1-6 September 2009 
Chapter 1 – Introduction 

acidifying deposition problem, it would be premature and unwise to prescribe any regulatory 

control program at that time, and (2) when the fundamental scientific uncertainties had been 

reduced through ongoing research efforts, EPA would draft and support an appropriate set of 

control measures. 

1.2.3 History of Related Assessments and Agency Actions 

In 1980, Congress created the National Acid Precipitation Assessment Program 

(NAPAP) in response to growing public concern about acidifying deposition. The NAPAP was 

given a broad 10-year mandate to examine the causes and effects of acidifying deposition and to 

explore alternative control options to alleviate acidifying deposition and its effects. During the 

course of the program, the NAPAP issued a series of publicly available interim reports prior to 

the completion of a final report in 1990 (NAPAP, 1990). 

In spite of the complexities and significant remaining uncertainties associated with the 

acidifying deposition problem, it soon became clear that a program to address acidifying 

deposition was needed. The Amendments to the CAA passed by Congress and signed into law by 

the president on November 15, 1990, included numerous separate provisions related to the 

acidifying deposition problem that reflect the comprehensive approach envisioned by Congress. 

The primary and most important of the provisions, Title IV of the CAA Amendments, 

established the Acid Rain Program to reduce SO2 emissions by 10 million tons and NOx

emissions by 2 million tons from 1980 emission levels to achieve reductions over broad 

geographic regions. In this provision, Congress included a statement of findings that led them to 

take action, concluding that (1) the presence of acid compounds and their precursors in the 

atmosphere and in deposition from the atmosphere represents a threat to natural resources, 

ecosystems, materials, visibility, and public health; (2) the problem of acidifying deposition is of 

national and international significance; and (3) current and future generations of Americans will 

be adversely affected by delaying measures to remedy the problem. 

Second, Congress authorized the continuation of the NAPAP to assure that the research 

and monitoring efforts already undertaken would continue to be coordinated and would provide 

the basis for an impartial assessment of the effectiveness of the Title IV program. 

Third, Congress—clearly envisioning that further action might be necessary in the long 

term to address any problems remaining after implementation of the Title IV program and 

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Chapter 1 – Introduction 

reserving judgment on the form that action could take—included Section 404 of the 1990 

Amendments (CAA Amendments of 1990, Pub. L. 101-549, § 404), requiring EPA to conduct a 

study on the feasibility and effectiveness of an acidifying deposition standard or standards to 

protect “sensitive and critically sensitive aquatic and terrestrial resources.” At the conclusion of 

the study, EPA was to submit a report to Congress. Five years later, in fulfillment of this 

requirement, EPA submitted its report, entitled Acid Deposition Standard Feasibility Study: 

Report to Congress (U.S. EPA, 1995b). The report concluded that establishing acidifying 

deposition standards for sulfur and nitrogen deposition may at some point in the future be 

technically feasible, although appropriate deposition loads for these acidifying chemicals could 

not be defined with reasonable certainty at the time of the report (1995). 

Fourth, the 1990 Amendments also added new language to sections of the CAA 

pertaining to the scope and application of the secondary NAAQS designed to protect the public 

welfare. Specifically, the definition of “public welfare” in Section 302(h) was expanded to state 

that the welfare effects identified should be protected from adverse effects associated with 

criteria air pollutants “...whether caused by transformation, conversion, or combination with 

other air pollutants.” This change has particular relevance to the current review because the 

transformation products of NOx and SOx are associated with environmental impacts. 

In 1999, seven northeastern states cited this amended language in Section 302(h) in a 

petition asking EPA to use its authority under the NAAQS program to promulgate secondary 

NAAQS for the criteria pollutants associated with the formation of acid rain. The petition stated 

that this language “clearly references the transformation of pollutants resulting in the inevitable 

formation of sulfate and nitrate aerosols and/or their ultimate environmental impacts as wet and 

dry deposition, clearly signaling Congressional intent that the welfare damage occasioned by 

sulfur and nitrogen oxides be addressed through the secondary standard provisions of Section 

109 of the Act.” The petition further stated that “recent federal studies, including the NAPAP 

Biennial Report to Congress: An Integrated Assessment, document the continued-and increasingdamage being inflicted by acid deposition to the lakes and forests of New York, New England 

and other parts of our nation, demonstrating that the Title IV program had proven insufficient.” 

The petition also listed other adverse welfare effects associated with the transformation of these 

criteria pollutants, including impaired visibility, eutrophication of coastal estuaries, global 

warming, and depletion of tropospheric ozone and stratospheric ozone. 

Final Risk and Exposure Assessment 1-8 September 2009 
Chapter 1 – Introduction 

In a related matter, the Office of the Secretary of the U.S. Department of Interior (DOI) 

requested in 2000 that EPA initiate a rulemaking proceeding to enhance the air quality in 

national parks and wilderness areas to protect resources and values that are being adversely 

affected by air pollution. Included among the effects of concern identified in the request were the 

acidification of streams, surface waters, and/or soils; eutrophication of coastal waters; 

impairment of visibility; and foliar injury from ozone. 

In a Federal Register notice in 2001, EPA announced receipt of this request and asked for 

comments on the issues raised. EPA stated that it would consider any relevant comments and 

information submitted, along with the information provided by the petitioners and DOI, before 

making any decision concerning a response to this request for rulemaking (65 FR 48699). 

The 2005 NAPAP report states that “... scientific studies indicate that the emission 

reductions achieved by Title IV are not sufficient to allow recovery of acid-sensitive ecosystems. 

Estimates from the literature of the scope of additional emission reductions that are necessary in 

order to protect acid-sensitive ecosystems range from approximately 40-80% beyond full 

implementation of Title IV.... The results of the modeling presented in this Report to Congress 

indicate that broader recovery is not predicted without additional emission reductions” (NAPAP, 

2005). 

Given the state of the science as described in the ISA and in other recent reports, such as 

the 2005 NAPAP report, EPA believes it is appropriate, in the context of evaluating the 

adequacy of the current NO2 and SO2 secondary standards in this review, to revisit the question 

of the appropriateness and the feasibility of setting a secondary NAAQS to address remaining 

known or anticipated adverse public welfare effects resulting from the acidifying and nutrient 

deposition of these criteria pollutants and their transformation products. This document 

comprises the Risk and Exposure Assessment portion of the review. 

1.3 SCOPE OF THE RISK AND EXPOSURE ASSESSMENT FOR THE 

CURRENT REVIEW 

1.3.1 Species of Nitrogen Included in the Analyses 

The sum of mono-nitrogen oxides—nitrogen dioxide (NO2) and nitric oxide (NO)— 

typically is referred to as nitrogen oxides (NOx) in the atmospheric science community. More 

formally, the family of NOx includes any gaseous combination of nitrogen and oxygen (e.g., 

Final Risk and Exposure Assessment 1-9 September 2009 
Chapter 1 – Introduction 

NO2, NO, N2O, nitrogen trioxide [N2O3], nitrogen tetroxide [N2O4], and dinitrogen pentoxide 

[N2O5]).

With regard to NOx, it is also necessary in this review to distinguish between the 

definition of “nitrogen oxides” as it appears in the enabling legislation related to the NAAQS and 

the definition commonly used in the air pollution research and management community. In this 

document, the term “oxides of nitrogen” and “nitrogen oxides” refer to all forms of oxidized 

nitrogen compounds, including NO, NO2, and all other oxidized nitrogen-containing compounds 

transformed from NO and NO2. This definition is supported by Section 108(c) of the CAA, 

which states that “Such criteria [for oxides of nitrogen] shall include a discussion of nitric and 

nitrous acids, nitrites, nitrates, nitrosamines, and other carcinogenic and potentially carcinogenic 

derivatives of oxides of nitrogen.” The term used by the scientific community to represent the 

complete set of oxidized nitrogen compounds, including those listed in CAA Section 108(c), is 

total oxidized nitrogen (NOy). NOy includes all nitrogen oxides, including gaseous nitrate species 

such as nitric acid (HNO3) and peroxyacyl nitrates (PAN). 

In addition to oxidized forms of nitrogen, reduced forms of nitrogen also contribute to the 

atmospheric chemistry that leads to the deposition of ambient nitrogen species to the 

environment. Reduced atmospheric nitrogen species include ammonia (NH3) and ammonium ion 

(NH4

+

), the sum of which is referred to as reduced nitrogen (NHx). Total reactive nitrogen is 

recognized as the combination of both oxidized and reduced forms of nitrogen that are 

biologically available (i.e., forms other than the stable form of gaseous nitrogen [N2]). 

Atmospheric nitrogen deposition often is delineated further as dry (e.g., gas and particulate 

phases) or as wet (e.g., precipitation-derived ion phase) (see Figure 1.3-1). 

Organic nitrogen compounds include the PANs, nitrosamines, nitro-polycyclic aromatic 

hydrocarbons (PAHs), and the more recently identified nitrated quinones. Oxidation of volatile 

organic compounds (VOCs) produces organic peroxy radicals (RO2). Reaction of RO2 radicals 

with NO and NO2 produces RONO2 and peroxynitrates (RO2NO2). Considerable uncertainty 

attaches to estimates of the third form of atmospherically derived nitrogen (i.e., organic nitrogen) 

in part because convenient methods for measurement and analysis are not widely available; see 

ISA Table 2-11. Intensive studies at individual sites have shown, however, that for the North 

Carolina coast, for example, 30% of rainwater nitrogen and deposition consisted of organic 

Final Risk and Exposure Assessment 1-10 September 2009 
Chapter 1 – Introduction 

nitrogen, 20% to 30% of which was then available to primary producers on time scales of hours 

to days. 

Important compounds, reactions, and cycles are schematized in Figure 1.3-1. Figure 

1.3-1 also illustrates that NO2, itself an oxidant, can react to form other photochemical oxidants, 

including organic nitrates (RONO2) like the PANs and can react with toxic compounds like the 

PAHs to form nitro-PAHs, some of which demonstrate greater toxicity than either reactant alone. 

NO2 can also be further transformed to HNO3 and can contribute in that form to the acidity of 

cloud, fog, and rain water. 

In many areas, multiple forms of nitrogen from a variety of atmospheric and other 

sources enter ecosystems. The scientific community has long recognized that the effects from 

atmospheric deposition of nitrogen to ecosystems are due to both oxidized and reduced forms, 

rather than to one form alone. As a result, much of the published research on ecological response 

to nitrogen does not differentiate between the various sources of nitrogen, but instead reports 

only total nitrogen inputs to the ecosystem. 

Long-range transport to remote 

regions at low temperature

inorganic 

nitrates

Figure 1.3-1. Schematic diagram of the cycle of reactive, oxidized nitrogen species 

in the atmosphere. Particulate-phase organic nitrates are also formed from the 

species on the right side of the figure (U.S. EPA, 2008).

Note: IN = inorganic particulate species (e.g., sodium [Na+], calcium [Ca2+]), 

MPP = multiphase processes, PAN = peroxyacetyl nitrates, PAH = polycyclic 

aromatic hydrocarbon, hν = a solar photon, R = an organic radical. 

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Chapter 1 – Introduction 

1.3.2 Species of Sulfur Included in the Analyses 

SO2 is one of a group of substances known as “oxides of sulfur”, or SOx, which include 

multiple gaseous species (e.g., SO2, sulfur monoxide [SO], sulfur trioxide [SO3], thiosulfate 

[S2O3], sulfur heptoxide [S2O7]) and particulates (e.g., ammonium sulfate [(NH4)2SO4]) 

(Figure 1.3-2). SO2 is chiefly, but not exclusively, primary in origin; it is also produced by the 

photochemical oxidation of reduced and organic sulfur compounds, such as dimethyl sulfide 

(DMS), hydrogen sulfide (H2S), carbon disulfide (CS2), carbonyl sulfide (OCS), and methyl 

mercaptan, which are all mainly biogenic in origin. Acidification can result from the atmospheric 

deposition of SOx and NOx; in acidifying deposition, these species combine with water in the 

atmosphere to form sulfuric acid (H2SO4) and HNO3. Due to known acute effects on plants, SO2

served as the chemical indicator for SOx species in previous NAAQS reviews.

Figure 1.3-2. Schematic diagram of the cycle of sulfur species in the atmosphere 

(adapted from Berresheim et al. (1995); used with permission). 

Note: OCS = carbonyl sulfide, DMS = dimethyl sulfide, S(IV) = S+4, S(VI) = S+6. 

1.3.3 Overview of Nitrogen- and Sulfur-Related Ecological Effects 

The ecological effects of nitrogen and sulfur are caused both by the gas-phase and 

atmospheric deposition of the pollutants. The current secondary NAAQS were set to protect 

against direct damage to vegetation by exposure to gas-phase NOx or SOx. Acute and chronic 

exposures to SO2 can have phytotoxic effects on vegetation, such as foliar injury, decreased 

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Chapter 1 – Introduction 

photosynthesis, and decreased growth. Similarly, exposure to sufficient concentrations of NO2, 

NO, PAN, and HNO3 can cause foliar injury, decreased photosynthesis, and decreased growth 

(U.S. EPA 2008). 

With respect to direct gas-phase effects, the ISA for the secondary NAAQS review 

determined the following: 

The evidence is sufficient to infer a causal relationship between exposure to SO2, NO, 

NO2, PAN, and HNO3 and injury to vegetation. 

Even though these gas-phase chemicals will cause phytotoxicity, the evidence indicates 

there is little new evidence that current concentrations of gas-phase sulfur or nitrogen oxides are 

not sufficiently high to cause phytotoxic effects. One exception is that some studies indicate that 

current HNO3 concentrations may be contributing to the decline of lichen species in the Los 

Angeles basin. (U.S. EPA, 2008). 

Deposition of nitrogen-containing and sulfur-containing compounds that are derived from 

NOx and SOx may be wet (e.g., rain and snow), occult (e.g., cloud and fog), and dry (e.g., gases 

and particles) and can affect ecosystem biogeochemistry, structure, and function. Nitrogen and 

sulfur interactions in the environment are highly complex. Both are essential elements for 

vegetation growth and development and are needed for growth and productivity. However, 

excess nitrogen (both oxidized and reduced forms) or sulfur can lead to acidification, nitrogen 

nutrient enrichment, eutrophication, and sulfur-mediated mercury methylation. Acidification 

causes a cascade of effects that alter both terrestrial and aquatic ecosystems. These effects 

include slower biotic growth, the injury or death of forest vegetation, and the localized extinction 

of fish and other aquatic species. 

With respect to acidification, the ISA determined the following: 

The evidence is sufficient to infer a causal relationship between acidifying deposition and 

effects on 

(1) biogeochemistry related to terrestrial and aquatic ecosystems; 

(2) biota in terrestrial and aquatic ecosystems. 

The ISA highlights evidence from two well-studied areas to provide more detail on how 

acidification affects ecosystems: the Adirondack Case Study Area (New York) and the 

Shenandoah Case Study Area (Virginia) (U.S., EPA, 2008, Section 3.2). In the Adirondack Case 

Study Area, the current rates of nitrogen and sulfur deposition exceed the amount that would 

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Chapter 1 – Introduction 

allow recovery of the most acid-sensitive lakes. In the Shenandoah Case Study Area, legacy 

sulfate has accumulated in the soil and is slowly released from the soil into stream water, where 

it causes acidification and makes this region sensitive to current loading. Models for the latter 

study area suggest that the number of acidic streams will increase under the current deposition 

rates (U.S. EPA, 2008, Section 3.2). The ISA highlights forests in the Adirondack Case Study 

Area of New York, Green Mountains of Vermont, White Mountains of New Hampshire, and the 

Allegheny Plateau of Pennsylvania, and high-elevation forest ecosystems in the southern 

Appalachians as the regions most sensitive to terrestrial acidification effects from atmospheric 

deposition (U.S. EPA, 2008, Section 3.2). In this Risk and Exposure Assessment, these areas are 

targeted for the air quality modeling presented in Chapter 3 and the case study analyses 

presented in Chapter 4 of this report. 

In addition to acidification, NOx acts with other forms of total reactive nitrogen 

(including reduced nitrogen) to increase the total amount of available nitrogen in ecosystems. 

The contribution of nitrogen deposition to total nitrogen load varies among ecosystems. 

Atmospheric nitrogen deposition is the main anthropogenic source of new nitrogen to most 

headwater streams, high-elevation lakes, and low-order streams. Atmospheric nitrogen 

deposition contributes to the total nitrogen load in terrestrial, wetland, freshwater, and estuarine 

ecosystems that receive nitrogen through multiple pathways (i.e., biological nitrogen-fixation, 

agricultural land runoff, and wastewater effluent discharges) (U.S. EPA, 2008, Section 3.3). 

Nitrogen deposition alters numerous biogeochemical indicators, including primary productivity 

that may lead to changes in community composition and eutrophication. 

With respect to nitrogen nutrient enrichment, the ISA determined the following: 

The evidence is sufficient to infer a causal relationship between nitrogen deposition, to 

which NOx and NHx contribute, and the alteration of the following: 

(1) Biogeochemical cycling of nitrogen and carbon in terrestrial, wetland, freshwater 

aquatic, and coastal marine ecosystems 

(2) Biogenic flux of methane and nitrous oxide in terrestrial and wetland ecosystems 

(3) Species richness, species composition, and biodiversity in terrestrial, wetland, 

freshwater aquatic, and coastal marine ecosystems. 

In aquatic ecosystems, wet deposition loads of approximately 1.5 to 2 kg N/ha/yr are 

reported to cause alterations in diatom communities of freshwater lakes and to impair water 

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Chapter 1 – Introduction 

quality in the western United States, a region especially sensitive to increased nitrogen 

atmospheric inputs (U.S. EPA, 2008, Section 3.3). In estuarine ecosystems, additional nitrogen 

from anthropogenic atmospheric sources contributes to the total nitrogen loading and to 

increased phytoplankton and algal productivity, which may lead to eutrophication. Estuary 

eutrophication is a detrimental ecological problem indicated by water quality deterioration, 

resulting in numerous adverse effects, including hypoxic zones, species mortality, and harmful 

algal blooms. The ISA indicates that the contribution of atmospheric deposition to total nitrogen 

loads can be >40% in some eutrophic estuaries. The Chesapeake Bay is an example of a large, 

well-studied estuary that receives as much as 30% of its total nitrogen load from the atmosphere 

(U.S. EPA, 2008, Section 3.3). 

In terrestrial ecosystems, there are multiple chemical indicators that the biogeochemical 

cycling of nitrogen has been altered by the deposition of total reactive nitrogen. Nitrate leaching 

from terrestrial ecosystems is a well-documented effect that indicates the ecosystem is receiving 

more nitrogen than it uses; the atmospheric deposition threshold for nitrate leaching is calculated 

to be between 8 and 10 kg/ha/yr for eastern forests (U.S. EPA, 2008, Section 3.3). Nitrogen 

deposition can cause ecological effects prior to the onset of nitrate leaching. For example, 

nitrogen deposition affects primary productivity, thereby altering terrestrial carbon cycling. This 

may result in shifts in population dynamics, species composition, community structure, and, in 

extreme instances, ecosystem type. Lichen are the most sensitive terrestrial taxa, with 

documented adverse effects occurring at atmospheric inputs as low as 3 kg N/ha/yr (Pacific 

Northwest and Southern California); 5 kg N/ha/yr correlates to the onset of declining 

biodiversity within grasslands (Minnesota and the European Union); and 10 kg N/ha/yr causes 

changes in community composition of Alpine ecosystems and forest encroachment into 

temperate grasslands (U.S. EPA, 2008, Section 3.3). Some of the aquatic and terrestrial 

ecosystems highlighted in the ISA are targeted for the air quality modeling presented in Chapter 

3 and the case study analyses presented in Chapter 5 of this Risk and Exposure Assessment. 

There is increasing evidence on the relationship between sulfur deposition and increased 

methylation of mercury in aquatic environments; this effect occurs only where other factors are 

present at levels within a range to allow methylation. The production of methylmercury requires 

the presence of sulfate and mercury, but the amount of methylmercury produced varies with 

oxygen content, temperature, pH, and supply of labile organic carbon (U.S. EPA, 2008, Section 

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Chapter 1 – Introduction 

3.4). In watersheds where changes in sulfate deposition did not result in changes in 

methylmercury generation, one or several of those interacting factors were not in the range 

required for substantial methylation to occur (U.S. EPA, 2008, Section 3.4). Watersheds with 

conditions known to be conducive to mercury methylation can be found in the northeastern 

United States and southeastern Canada, but can occur elsewhere. The relationship between sulfur 

and methylmercury production is addressed qualitatively in Chapter 6 of this report. 

With respect to sulfur deposition and mercury methylation, the ISA determined the 

following: 

The evidence is sufficient to infer a causal relationship between sulfur deposition and 

increased mercury methylation in wetlands and aquatic environments. 

In terrestrial and wetland ecosystems, total reactive nitrogen deposition alters biogenic 

sources and sinks of N2O and methane—two potent greenhouse gases—resulting in a higher 

emission to the atmosphere of these gases. Terrestrial soil is the largest source of N2O, 

accounting for 60% of global emissions. Total reactive nitrogen deposition increases the flux of 

N2O in coniferous forests, deciduous forests, grasslands, and wetlands. Nitrogen deposition 

significantly reduces methane uptake in coniferous and deciduous forests, with a reduction of 

28% and 45%, respectively. In wetlands, nitrogen addition increases methane production, but has 

no significant effect on methane uptake (U.S. EPA, 2008, Section 3.4). These effects are also 

addressed qualitatively in Chapter 6 of this report. 

A summary illustration of NOx and SOx effects on the environment is presented in 

Figure 1.3-3. 

Final Risk and Exposure Assessment 1-16 September 2009 
Chapter 1 – Introduction 

Figure 1.3-3. Nitrogen and sulfur cycling and interactions in the environment. 

1.4 FRAMING QUESTIONS FOR THE RISK AND EXPOSURE 

ASSESSMENT 

As many years of research have clearly demonstrated, the ecological effects associated 

with acidification (due to both nitrogen and sulfur) and excess nitrogen nutrient enrichment 

derive from both oxidized and reduced nitrogen, not NOx alone, which is the current listed 

criteria pollutant. The questions framing this review recognize that the effects of NOx occur as 

part of the overall effects of total reactive nitrogen and address the need to understand the role of 

NOx relative to other sources of reactive nitrogen that contribute to adverse public welfare 

effects. Throughout the ISA and the Risk and Exposure Assessment, public welfare effects due 

to total reactive nitrogen are examined, and where possible, the contributions to these effects 

from oxidized and reduced forms of nitrogen are assessed. For this secondary NOx/SOx NAAQS 

review, the main questions directing the Risk and Exposure Assessment include the following: 

Overall Framing Questions: 

 What are the known or anticipated welfare effects influenced by ambient NOx, an 

important component of total reactive nitrogen, and SOx, and for which effects is there 

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Chapter 1 – Introduction 

sufficient information available to be useful as a basis for considering distinct secondary 

standard(s)? 

 To what extent do the current standards provide protection from the known or anticipated 

welfare effects associated with NOx and SOx? 

 To what extent does the current NOx standard provide protection against known or 

anticipated adverse effects associated with total reactive nitrogen? 

 For which ecological effects being considered is a joint NOx/SOx standard most 

appropriate, and for which ecological effects would separate standards be more 

appropriate? 

 Taking into consideration factors related to determining when the various detrimental 

ecological effects under consideration occur, what range of levels, averaging times, and 

forms of alternative ecological indicators are supported by the information and what are 

the uncertainties and limitations in that information? 

 To what extent do specific levels, averaging times, and forms of alternative ecological 

indicators reduce detrimental impacts attributable to NOx/SOx relative to current 

conditions, and what are the uncertainties in the estimated reductions? 

Air Quality Framing Questions: 

 Does the available information provide support for considering different air quality 

indicators for NOx and SOx? 

 Given that dry deposition can contribute significantly to total deposition, to what extent 

do receptor surfaces influence the deposition of gases and particles (i.e., dry deposition)? 

 Does the available information provide support for the development of appropriate 

atmospheric deposition transformation functions, and what atmospheric and 

environmental factors (e.g., co-pollutants, land use) are most appropriate to account for in 

such a function? 

Ecological Framing Questions: 

 What are the nature and magnitude of ecosystem responses to total reactive nitrogen, to 

which NOx contributes, and SOx that are understood to have known or anticipated 

detrimental public welfare effects, and what is the variability associated with those 

responses (e.g., ecosystem type, climatic conditions, interactions with other 

environmental factors, pollutants)? 

Final Risk and Exposure Assessment 1-18 September 2009 
Chapter 1 – Introduction 

 Does the available information provide support for the development of appropriate 

ecological effect functions that meaningfully relate to the ecological endpoints being 

considered, and what ecological factors (e.g., reduced forms of nitrogen, bedrock type, 

weathering rates) are most relevant for such functions? 

 To what extent can ecological effects due to NOx be distinguished from effects due to 

total reactive nitrogen? 

 Which ecological indicators adequately capture the relationships between ecosystem 

exposures and responses for the known or anticipated adverse welfare effects that are 

trying to be protected against? 

 Does the available information provide a basis for identifying relevant ecological 

indicators for the range of ecological endpoints being considered in the review? 

 Is there enough information to determine when ecological effects become adverse? 

In order to answer these questions, the relevant scientific and policy issues that need to be 

addressed in the science, risk and exposure, and policy assessment portions of this review 

include the following: 

 Identifying important nitrogen and sulfur chemical species in the atmosphere 

 Identifying the atmospheric pathways that govern the chemical transformation, transport, 

and deposition of total reactive nitrogen and SOx to the environment 

 Identifying the attributes of ecosystem receptors that govern their susceptibility to effects 

from deposition of nitrogen and sulfur compounds 

 Identifying the relationships between ambient air quality indicators and ecological 

indicators of effects (through deposition) 

 Identifying relationships between ecosystem services and ecological indicators 

 Evaluating alternative approaches to assess the adversity of effects on ecosystem 

services, including, but not limited to, economic valuation 

 Evaluating environmental impacts and sensitivities to varying meteorological scenarios 

and climate conditions 

 Evaluating the relationship between NOx and deposition of total reactive nitrogen, and 

between NOx and total nitrogen loadings that are related to ecological effects. 

To the extent the evidence suggests that the current standards do not provide appropriate 

protection from known or anticipated adverse public welfare effects associated with the criteria 

Final Risk and Exposure Assessment 1-19 September 2009 
Chapter 1 – Introduction 

pollutants NOx and SOx, ecologically meaningful revisions to the current standards will be 

considered. Recognizing the high degree of complexity that exists in relationships between 

ambient air concentrations of NOx and SOx, deposition of nitrogen and sulfur into sensitive 

aquatic and terrestrial ecosystems, and associated potential adverse ecological effects, it is 

anticipated that ecologically meaningful NAAQS need to be structured to take into account such 

complexity. To provide some context for addressing the key framing questions that are salient in 

this review, a possible structure for secondary standards based on meaningful ecological 

indicators that provides for protection against the range of potentially adverse ecological effects 

associated with the deposition of NOx, NHx, and SOx has been developed and is shown in Figure 

1.4-1. In so doing, it was considered how the basic elements of NAAQS standards—indicator, 

averaging time, form, and level—would be reflected in such a structure. 

2. Variable/Fixed 

Factors

Atmospheric 

Landscape

1. Air Quality 

Indicators

Measured over a 

specified 

averaging time; 

expressed in 

terms of a 

specified statistic 

(form)

3. 

Atmospheric 

Deposition 

Transformation 

Function

5. Variable/Fixed

 Factors

Ecological

4.

Deposition

Metric

6. 

Ecological 

Effect 

Function

7. Ecological 

Indicator

Calculated over a 

specified 

averaging time; 

expressed in terms 

of a specified 

statistic (form) 

(Ecological 

Benchmark)

9. Standard 

Level

Value of ecological 

indicator judged to 

provide requisite 

degree of 

protection for a 

specific endpoint

10. To Determine Whether Standard is Met:

Compare measured concentrations of the air quality 

indicator(s) in ambient air to the calculated combinations of 

air quality indicators such that the ecological indicator value 

is greater than or equal to the ecological benchmark.

8. Factors Related to 

Characterizing 

Adversity

Figure 1.4-1. Possible structure of a secondary NAAQS for NOx and SOx based 

on an ecological indicator. 

Figure 1.4-1 illustrates the working structure for an ecological effect-based secondary 

NAAQS for NOx and SOx, together with the combination of various elements that would serve to 

define such a standard. The subsequent chapters of this report will address each component of 

this structure. Starting from the left side of Figure 1.4-1, Chapter 3 of this report addresses the 

Final Risk and Exposure Assessment 1-20 September 2009 
Chapter 1 – Introduction 

atmospheric analyses covered in this review, including sources, emissions, concentrations, and 

deposition and characterization of the spatial and temporal patterns of concentration and 

deposition in the case study areas (boxes 1 to 4). The Atmospheric Deposition Transformation 

Function that quantifies the relationship between atmospheric concentrations and deposition of 

NOx and SOx (box 3), while taking atmospheric and landscape factors into account (i.e., 

deposition velocities, land use, co-pollutants), are addressed in Chapter 3 and Appendices 1–3 of 

this report. Chapters 4 and 5 and their associated appendices (Appendices 4–7) focus on the 

ecological effects of acidification and nutrient enrichment, respectively, and discuss the selection 

of ecological indicators, ecosystem services, the case study areas and their representativeness, 

and the evaluation of current conditions in these areas (boxes 4 to 7). For each targeted effect, 

the ecological effect functions are derived and described in Chapters 4 and 5 and Appendices 4–

7 (box 6), and the role of ecosystem services in defining adversity is discussed in Chapters 2, 4 

or 5, and 7 (box 8). Chapter 7 of this report synthesizes the case study analyses by evaluating the 

relative confidence level associated with the available data, modeling approach, and the 

relationship between the selected ecological indicator and atmospheric deposition as described 

by the ecological effect function (boxes 5 to 7). All of the components of Figure 1.4-1 will be 

evaluated in the policy assessment associated with this review, which will consider the structure 

of a secondary NAAQS from a statutory standpoint and characterize the atmospheric and 

ecological inputs discussed throughout the Risk and Exposure Assessment. In addition, the 

policy assessment will highlight boxes 8, 9, and 10 in Figure 1.4-1 in a discussion of the risks 

associated with alternative levels of ecological indicators for each targeted effect area. 

1.5 REFERENCES 

DHEW (U.S. Department of Health, Education, and Welfare). 1970. Air Quality Criteria for 

Sulfur Oxides. National Air Pollution Control Administration Publication No. AP-50. 

Washington, DC: U.S. Government Printing Office. 

Berresheim H; Wine PH; Davis DD. (1995). Sulfur in the atmosphere. In: Singh HB (Ed.), 

Composition, chemistry, and climate of the atmosphere (pp. 251-307). New York, NY: 

Van Nostrand Reinhold. 

Final Risk and Exposure Assessment 1-21 September 2009 
Chapter 1 – Introduction 

McCurdy, T.R. 1994. Analysis of High 1-Hour NO2 Values and Associated Annual Averages 

Using 1988-1992 Data. Report of the U.S. Environmental Protection Agency, Office of 

Air Quality Planning and Standards, Durham, NC. 

NAPAP (National Acid Precipitation Assessment Program). 2005. Report to Congress: An 

Integrated Assessment. National Acid Precipitation Assessment Program, Washington, 

DC. 

NAPAP (National Acid Precipitation Assessment Program).1990. Acidic Deposition: State of 

Science and Technology, Volumes I-IV. National Acid Precipitation Assessment Program, 

Washington, DC. 

NRC (National Research Council). 2004. Air Quality Management in the United States. 

Washington, DC: National Academies Press. 

U.S. EPA (Environmental Protection Agency). 1973. Effects of sulfur oxides in the atmosphere 

on vegetation; revised chapter 5 for air quality criteria for sulfur oxides. EPA/R3-73-

030. U.S. Environmental Protection Agency, Office of Research and Development, 

Research Triangle Park, NC. 

U.S. EPA (Environmental Protection Agency). 1982. Air quality criteria for oxides of nitrogen. 

EPA-600/8-82-026. U.S. Environmental Protection Agency, Office of Health and 

Environmental Assessment, Environmental Criteria and Assessment Office, Research 

Triangle Park, NC. 

U.S. EPA (Environmental Protection Agency). 1984a. The acidic deposition phenomenon and its 

effects: critical assessment review papers. Volume I: atmospheric sciences. EPA-600/8-

83-016-AF. U.S. Environmental Protection Agency, Office of Research and 

Development, Washington, DC. 

U.S. EPA (Environmental Protection Agency). 1984b. The acidic deposition phenomenon and its 

effects: critical assessment review papers. Volume II: effects sciences. EPA-600/8-83-

016-BF. U.S. Environmental Protection Agency, Office of Research and Development, 

Washington, DC. 

Final Risk and Exposure Assessment 1-22 September 2009 
Chapter 1 – Introduction 

U.S. EPA (Environmental Protection Agency). 1985. The acidic deposition phenomenon and its 

effects: critical assessment document. EPA/600/8-85/001. U.S. Environmental Protection 

Agency, Office of Acid Deposition, Environmental Monitoring, and Quality Assurance, 

Washington, DC. 

U.S. EPA (Environmental Protection Agency). 1993. Air quality criteria for oxides of nitrogen. 

EPA/600/8-91/049aF-cF. 3v. U.S. Environmental Protection Agency, Office of Health 

and Environmental Assessment, Environmental Criteria and Assessment Office, Research 

Triangle Park, NC. 

U.S. EPA (Environmental Protection Agency). 1995a. Review of the National Ambient Air 

Quality Standards for Nitrogen Dioxide: Assessment of Scientific and Technical 

Information. OAQPS Staff Paper. EPA-452/R-95-005. U.S. Environmental Protection 

Agency, Office of Air Quality Planning and Standards, Research Triangle Park, NC. 

September. 

U.S. EPA (Environmental Protection Agency). 1995b. Acid Deposition Standard Feasibility 

Study: Report to Congress. EPA 430-R-95-001a. U.S. Environmental Protection Agency, 

Office of Air and Radiation, Office of Atmospheric Programs, Acid Rain Division, 

Washington, DC. 

U.S. EPA (Environmental Protection Agency). 2007. Integrated Review Plan for the National 

Ambient Air Quality Standards for Particulate Matter. EPA 452/P-08-006. U.S. 

Environmental Protection Agency, National Center for Environmental Assessment, 

Office of Research and Development, and Health and Environmental Impacts Division, 

Office of Air Quality Planning and Standards, Office of Air and Radiation, Research 

Triangle Park, NC. October. 

U.S. EPA (Environmental Protection Agency). 2008. Integrated Science Assessment (ISA) for 

Oxides of Nitrogen and Sulfur–Ecological Criteria (Final Report). EPA/600/R08/082F. U.S. Environmental Protection Agency, National Center for Environmental 

Assessment–RTP Division, Office of Research and Development, Research Triangle 

Park, NC. Available at http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=201485. 

Final Risk and Exposure Assessment 1-23 September 2009 
Chapter 1 – Introduction 

Final Risk and Exposure Assessment 1-24 September 2009 

Wolff, G.T. 1993. On a NOx-focused control strategy to reduce O3. Journal of the Air and Waste 

Management Association 43:1593–1596. 

Wolff, G.T. 1995. CASAC closure letter for the 1995 OAQPS Staff Paper. Letter sent to Carol 

M. Browner, Administrator, U.S. Environmental Protection Agency. August 22. 
Chapter 2 – Overview of Risk and Exposure Assessment 

2.0 OVERVIEW OF RISK AND EXPOSURE ASSESSMENT 

2.1 INTRODUCTION 

The Risk and Exposure Assessment focuses on ecosystem welfare effects that result from 

the deposition of total reactive nitrogen and sulfur. Because ecosystems are diverse in biota, 

climate, geochemistry, and hydrology, response to pollutant exposures can vary greatly between 

ecosystems. In addition, these diverse ecosystems are not distributed evenly across the United 

States. To target nitrogen and sulfur acidification and nitrogen and sulfur enrichment, the Risk 

and Exposure Assessment addresses four main targeted ecosystem effects on terrestrial and 

aquatic systems identified by the Integrated Science Assessment (ISA) for Oxides of Nitrogen 

and Sulfur–Ecological Criteria (Final Report) (ISA; U.S. EPA, 2008a): 

 Aquatic acidification due to nitrogen and sulfur 

 Terrestrial acidification due to nitrogen and sulfur 

 Aquatic nutrient enrichment, including eutrophication 

 Terrestrial nutrient enrichment. 

In addition to these four targeted ecosystem effects, this assessment qualitatively 

addresses the influence of sulfur oxides (SOx) deposition on methylmercury production; nitrous 

oxide (N2O) effects on climate; nitrogen effects on primary productivity and biogenic 

greenhouse gas fluxes; and phytotoxic effects on plants. 

Because the targeted ecosystem effects outlined above are not evenly distributed across 

the United States, the Risk and Exposure Assessment identified case studies for the analyses 

based on ecosystems identified as sensitive to nitrogen and/or sulfur deposition effects. This Risk 

and Exposure Assessment builds upon the scientific information presented in the ISA, with 

ecological indicator(s) and case study areas selected based on the information presented (U.S. 

Final Risk and Exposure Assessment 2-1 September 2009 
Chapter 2 – Overview of Risk and Exposure Assessment 

Final Risk and Exposure Assessment 2-2 September 2009 

EPA, 2008a). Eight case study areas and two supplemental study areas (Rocky Mountain 

National Park and Little Rock Lake, WI) are summarized in Table 2.1-1 based on ecosystem 

characteristics, indicators, and ecosystem service information developed for this Risk and 

Exposure Assessment. Detailed explanations of this information are presented in Chapters 4 and 

5 of this report (i.e., Risk and Exposure Assessment for Review of the Secondary National 

Ambient Air Quality Standards for Oxides of Nitrogen and Oxides of Sulfur), and a map 

highlighting each of the eight case study areas and the Rocky Mountain National Park is shown 

in Figure 2.1-1. 
Chapter 2 – Overview of Risk and 

Table 2.1-1. Summary of Sensitive Characteristics, Indicators, Effects, and Impacted Ecosystem Services Analy

Study Evaluated in This Review

Targeted 

Ecosystem 

Effect 

Characteristics of 

Sensitivity 

(Variable 

Ecological Factors) 

Biological/ 

Chemical Indicator 

Ecological 

Endpoint Ecological Effects 

Ecosystem Service

Impacted 

Aquatic Acidification 

Geology, surface water flow, soil depth, weathering rates 

Al pH ANC 

Species richness, abundance, composition, ANC 

Species losses of fish, phytoplankton, and zooplankton; changed community composition, ecosystem structure, and function 

Subsistence fishing, recreational fishing, other recreational activities 

Terrestrial Acidification 

Geology, surface water flow, soil depth, weathering rates 

Soil base saturation Al Ca C:N ratio 

Tree health of red spruce and sugar maple, ANC, base cation :Al ratio 

Decreased tree growth, increased susceptibility to stress, episodic dieback; changed community composition, ecosystem structure, and function 

 Provision of food and wood products, recreational activities, natural habitat, soil stabilization, erosiocontrol, water regulation, climate regulation 

Aquatic Nutrient Enrichment 

nitrogen-limited systems, presence of nitrogen in surface water, eutrophication status, nutrient criteria 

Chlorophyll a, macroalgae, dissolved oxygen, nuisance/toxic algal blooms, submerged aquatic vegetation (SAV) 

Changes in Eutrophication Index (EI) 

Habitat degradation, algal blooms, toxicity, hypoxia, anoxia, fish kills, decreases in biodiversity 

Commercial and recreational fishing, other recreational activities, aesthetic value, nonuse value flood and erosion control 

Final Risk and Exposure Assessment 2-3 
Chapter 2 – Overview of Risk and 

Final Risk and Exposure Assessment 2-4 

Targeted 

Ecosystem 

Effect 

Characteristics of 

Sensitivity 

(Variable 

Ecological Factors) 

Biological/ 

Chemical Indicator 

Ecological 

Endpoint Ecological Effects 

Ecosystem Service

Impacted 

Terrestrial Nutrient Enrichment 

Presence of acidophytic lichens, anthropogenic land cover 

Cation exchange capacity, C:N ratios, Ca:Al ratios, NO3-

leaching and export 

Species composition, lichen presence/absence, soil root mass changes, NO3

breakthrough to water, biomass 

Species changes, nutrient enrichment of soil, changes in fire regime, changes in nutrient cycling 

Recreation, aesthetivalue, nonuse valuefire regulation, loss of habitat, loss of biodiversity, water quality 

Note: ANC = acid neutralizing capacity, SAV = submerged aquatic vegetation, EI = eutrophication index.
Final Risk and Exposure Assessment 2-5 

Chapter 2 – Overview of Risk and 

Figure 2.1-1. National map highlighting the eight case study areas and the Rocky Mountain National 

(a supplemental study area) evaluated in the Risk and Exposure Assessment.
Chapter 2 – Overview of Risk and Exposure Assessment 

To address the framing questions that guide the scope of this review, the Risk and 

Exposure Assessment evaluates the relationships between atmospheric concentrations, 

deposition, biologically relevant exposures, targeted ecosystem effects, and ecosystem services. 

To evaluate the nature and magnitude of ecosystem responses associated with adverse effects, 

the Risk and Exposure Assessment examines various ways to quantify the relationships between 

air quality indicators, deposition of biologically available forms of nitrogen and sulfur, 

ecologically relevant indicators relating to deposition, exposure and effects on sensitive 

receptors, and related effects resulting in changes in ecosystem structure and services. The intent 

of the Risk and Exposure Assessment is to determine the exposure metrics that incorporate the 

temporal considerations (i.e., biologically relevant timescales), pathways, and ecologically 

relevant indicators necessary to maintain the functioning of these ecosystems. To the extent 

feasible, this Risk and Exposure Assessment evaluates the overall load to the system for nitrogen 

and sulfur, as well as the variability in ecosystem responses to these pollutants. In addition, this 

Risk and Exposure Assessment evaluates the contributions of atmospherically deposited nitrogen 

and sulfur relative to the combined atmospheric loadings of both elements. Since oxidized 

nitrogen is the listed criteria pollutant (currently measured by the ambient air quality indicator 

NO2) for the atmospheric contribution to total nitrogen, this Risk and Exposure Assessment 

examines the contribution of nitrogen oxides (NOx) to total reactive nitrogen in the atmosphere, 

relative to the contributions of reduced forms of nitrogen (e.g., ammonia, ammonium), to 

ultimately assess how a meaningful secondary National Ambient Air Quality Standards 

(NAAQS) might be structured. 

The Risk and Exposure Assessment for the secondary NAAQS review for NOx and SOx

will aid the Administrator in judging whether the current secondary standards are requisite to 

protect public welfare from any known or anticipated adverse effects, or whether these standards 

should be retained, revised, revoked, and/or replaced with alternative standard(s) to provide the 

required protection. 

Previous reviews of secondary NAAQS have characterized adversity according to the 

ecological effects associated with that pollutant. For example, in the previous ozone (O3) 

secondary NAAQS review, biomass loss and foliar injury were the main effects determining 

adversity to public welfare on public lands, while in the particulate matter (PM) secondary 

NAAQS review, the loss of visibility was used. There is an important distinction between a 

Final Risk and Exposure Assessment 2-6 September 2009 
Chapter 2 – Overview of Risk and Exposure Assessment 

scientifically defined and documented adverse effect to a given ecological system or ecological 

endpoint and an adverse impact on public welfare from a statutory perspective. While adverse 

effects to ecosystems from a scientific perspective will be used to inform the Administrator’s 

decision, the degree of change in an ecological indicator or service that corresponds to an 

adverse public welfare effect is ultimately decided by the Administrator. 

For assessing this set of secondary NAAQS, in addition to assessing the degree of 

scientific impairment of ecological systems relating to inputs of NOx and sulfur oxides (SOx), 

this Risk and Exposure Assessment presents an overview of the concept of ecosystem services. 

The analysis of the effects on ecosystem services will help link what is considered to be a 

biologically adverse effect with a known or anticipated adverse effect to public welfare through 

ecosystem services. 

In this Risk and Exposure Assessment, ecosystem services is used to show the impacts of 

ecological effects on public welfare and help explain how these effects are viewed by the public. 

Ecosystem services are addressed in more detail in Section 2.4 of this chapter, throughout the 

case study analyses in Chapters 4 and 5, and in the examination of the structure of an 

ecologically meaningful secondary standard in the policy assessment document. The ability to 

inform decisions on the level of a secondary NAAQS will require the development of clear 

linkages between biologically adverse effects and effects that are adverse to public welfare as 

related to ecosystem services. The concept of adversity to public welfare does not require the use 

of ecosystem services, yet it is envisioned as a beneficial tool for this review that may provide 

more information on the linkages between adverse ecological effects and adverse public welfare 

effects. 

2.2 SEVEN-STEP APPROACH 

The seven basic steps guiding the overall Risk and Exposure Assessment and the 

assessments for each case study area of interest are highlighted below. These steps were initially 

presented in the scope and methods plan for this review (U.S. EPA, 2008b) and received Clean 

Air Scientific Advisory Committee (CASAC) approval; therefore, this approach is being carried 

forward in the Risk and Exposure Assessment. The seven steps address the selection of the 

targeted ecosystem effects, indicators, and ecosystem services measured for exposure via 

atmospheric deposition of total reactive nitrogen and sulfur from ambient air. The initial step of 

Final Risk and Exposure Assessment 2-7 September 2009 
Chapter 2 – Overview of Risk and Exposure Assessment 

identifying effects, sensitive ecosystems, and potential indicators is documented in the ISA (see 

Chapter 3, U.S. EPA, 2008a). In addition, the ISA identifies and reviews candidate multimedia 

models available for fate and transport analyses of a variety of ecosystems. The science 

documented in the ISA provides critical inputs into the Risk and Exposure Assessment. For some 

of the desired case study areas, data were not abundant enough to perform a quantitative 

assessment for each of the steps; in those cases, some steps have been executed in a qualitative or 

semiquantitative fashion. 

The details of the seven steps are addressed in each case study description. The steps are 

as follows: 

 Step 1. Plan for assessment using documented effects, such as biological, chemical, and 

ecological indicators; ecological responses; and potential ecosystem services. 

 Step 2. Map characteristics of sensitive areas that show ecological responses using 

research findings and geographic information systems (GIS) mapping. 

 Step 3. Select risk and exposure case study assessment area(s) within a sensitive area. 

 Step 4. Evaluate current loads and effects to case study assessment areas, including 

ecosystem services, where possible. 

 Step 5. Evaluate representativeness of case study areas to larger sensitive areas. 

 Step 6. Assess the current ecological conditions for those larger sensitive areas. 

 Step 7. Develop ecological effect functions for the targeted ecosystem effects (e.g., 

aquatic acidification). 

2.3 LINKAGES FOR STRUCTURING ECOLOGICALLY RELEVANT 

STANDARDS 

The framework shown in Figure 2.3-1 provides an example of how an ecologically 

meaningful secondary NAAQS might be structured. This example presents a system of linked 

functions that translate an air quality indicator (e.g., concentrations of NOx and SOx) into an 

ecological indicator that expresses either the potential for deposition of nitrogen and sulfur to 

acidify an ecosystem or for nitrogen to overenrich an ecosystem. This system encompasses the 

linkages between ambient air concentrations and resulting deposition metrics, as well as between 

the deposition metric and the ecological indicator of concern. For example, the atmospheric 

deposition transformation function (box 3) translates ambient air concentrations of NOx and SOx

Final Risk and Exposure Assessment 2-8 September 2009 
Chapter 2 – Overview of Risk and Exposure Assessment 

to nitrogen and sulfur deposition metrics, while the ecological effect function (box 6) relates the 

deposition metric into the ecological indicator. 

2. Variable/Fixed 

Factors

Atmospheric 

Landscape

1. Air Quality 

Indicators

Measured over a 

specified 

averaging time; 

expressed in 

terms of a 

specified statistic 

(form)

3. 

Atmospheric 

Deposition 

Transformation 

Function

5. Variable/Fixed

 Factors

Ecological

4.

Deposition

Metric

6. 

Ecological 

Effect 

Function

7. Ecological 

Indicator

Calculated over a 

specified 

averaging time; 

expressed in terms 

of a specified 

statistic (form) 

(Ecological 

Benchmark)

9. Standard 

Level

Value of ecological 

indicator judged to 

provide requisite 

degree of 

protection for a 

specific endpoint

10. To Determine Whether Standard is Met:

Compare measured concentrations of the air quality 

indicator(s) in ambient air to the calculated combinations of 

air quality indicators such that the ecological indicator value 

is greater than or equal to the ecological benchmark.

8. Factors Related to 

Characterizing 

Adversity

Figure 2.3-1. Possible structure of a secondary NAAQS for NOx and SOx based 

on an ecological indicator. 

The amounts of NOx and SOx in the ambient air can be used to derive a deposition metric 

(via the atmospheric deposition transformation function), which can then be used to derive a 

level of an ecological indicator (through the ecological effect function) that falls within the range 

defined as acceptable by the standard; by definition, the levels of NOx and SOx will be 

considered to meet that standard of protection. The atmospheric levels of NOx and SOx that 

satisfy a particular level of ecosystem protection are those levels that result in an amount of 

deposition that is less than the amount of deposition a given ecosystem can accept without 

degradation of the ecological indicator for a targeted ecosystem effect. 

Modifying factors that alter the relationship between ambient air concentrations of NOx

and SOx and depositional loads of nitrogen and sulfur, and those that modify the relationship 

between depositional loads and the ecological indicator, are discussed more fully throughout the 

discussion of atmospheric analyses in Chapter 3 and in the review of case study analyses in 

Final Risk and Exposure Assessment 2-9 September 2009 
Chapter 2 – Overview of Risk and Exposure Assessment 

Chapters 4 and 5. The role of ecosystem services in determining an adverse effect to public 

welfare is introduced below (Section 2.4) and highlighted throughout the case study analyses in 

Chapters 4 and 5. The role of ecosystem services in informing the standard-setting process will 

be discussed in the policy assessment document when characterizing risks associated with the 

development of a standard(s). 

2.4 ECOSYSTEM SERVICES 

The Risk and Exposure Assessment evaluates the benefits received from the resources 

and processes that are supplied by ecosystems. Collectively, these benefits are known as 

ecosystem services and include products or provisions, such as food and fiber; processes that 

regulate ecosystems, such as carbon sequestration; cultural enrichment; and supportive processes 

for services, such as nutrient cycling. Ecosystem services are distinct from other ecosystem 

products and functions because there is human demand for these services. 

In the Millennium Ecosystem Assessment (MEA), ecosystem services are classified into 

four main categories: 

 Provisioning. Includes products obtained from ecosystems, such as the production of 

food and water. 

 Regulating. Includes benefits obtained from the regulation of ecosystem processes, such 

as the control of climate and disease. 

 Cultural. Includes the nonmaterial benefits that people obtain from ecosystems through 

spiritual enrichment, cognitive development, reflection, recreation, and aesthetic 

experiences. 

 Supporting. Includes those services necessary for the production of all other ecosystem 

services, such as nutrient cycles and crop pollination (MEA, 2005a). 

The concept of ecosystem services can be used to help define adverse effects as they 

pertain to NAAQS reviews. The most recent secondary NAAQS reviews have characterized 

known or anticipated adverse effects to public welfare by assessing changes in ecosystem 

structure or processes using a weight-of-evidence approach that uses both quantitative and 

qualitative data. For example, the previous ozone review evaluated changes in foliar injury, 

growth loss, and biomass reduction on trees beyond the seedling stage using field measurement 

Final Risk and Exposure Assessment 2-10 September 2009 
Chapter 2 – Overview of Risk and Exposure Assessment 

data. The presence or absence of foliar damage in counties meeting the current standard has been 

used as a way to evaluate the impact of current ozone air quality on plants. 

Characterizing a known or anticipated adverse effect to public welfare is an important 

component of developing any secondary NAAQS. According to the Clean Air Act (CAA), 

welfare effects include the following: 

Effects on soils, water, crops, vegetation, manmade materials, 

animals, wildlife, weather, visibility, and climate, damage to and 

deterioration of property, and hazards to transportation, as well as 

effect on economic values and on personal comfort and well-being, 

whether caused by transformation, conversion, or combination 

with other air pollutants (Section 302(h)). 

In other words, welfare effects are those effects that are important to individuals and/or 

society in general. Ecosystem services can be generally defined as the benefits that individuals 

and organizations obtain from ecosystems. EPA has defined ecological goods and services as the 

“outputs of ecological functions or processes that directly or indirectly contribute to social 

welfare or have the potential to do so in the future. Some outputs may be bought and sold, but 

most are not marketed” (U.S. EPA, 2006). Conceptually, changes in ecosystem services may be 

used to aid in characterizing a known or anticipated adverse effect to public welfare. In the 

context of this review, ecosystem services may also aid in assessing the magnitude and 

significance of a resource and in assessing how NOx and SOx concentrations and deposition may 

impact that resource. 

Figure 2.4-1 provides the World Resources Institute’s schematic demonstrating the 

connections between the categories of ecosystem services and human well-being. The 

interrelatedness of these categories means that any one ecosystem may provide multiple services. 

Changes in these services can impact human well-being by affecting security, health, social 

relationships, and access to basic material goods (MEA, 2005b). 

Final Risk and Exposure Assessment 2-11 September 2009 
Chapter 2 – Overview of Risk and Exposure Assessment 

Figure 2.4-1. This figure depicts the strength of linkages between categories of 

ecosystem services and components of human well-being that are commonly 

indications of the extent to which it is possible for socioeconomic factors to 

mediate the linkage. (For example, if it is possible to purchase a substitute for a 

degraded ecosystem service, then there is a high potential for mediation.) The 

strength of the linkages, as indicated by arrow width, and the potential for 

mediation, as indicated by arrow color, differ in different ecosystems and regions 

(MEA, 2005a). 

Historically, ecosystem services have been undervalued and overlooked; however, more 

recently, the degradation and destruction of ecosystems has piqued interest in assessing the value 

of these services. In addition, valuation may be an important step from a policy perspective 

because it can be used to compare the costs and benefits of altering versus maintaining an 

ecosystem (i.e., it may be easier to protect than repair ecosystem effects). In this Risk and 

Exposure Assessment, valuation is used, where possible, based on available data in the case 

study areas. 

The economic approach to the valuation of ecosystem services is laid out as follows in 

EPA’s Ecological Benefits Assessment Strategic Plan: “Economists generally attempt to estimate 

the value of ecological goods and services based on what people are willing to pay (WTP) to 

increase ecological services or by what people are willing to accept (WTA) in compensation for 

reductions in them” (U.S. EPA, 2006). There are three primary approaches for estimating the 

value of ecosystem services: market-based approaches, revealed preference methods, and stated 

Final Risk and Exposure Assessment 2-12 September 2009 
Chapter 2 – Overview of Risk and Exposure Assessment 

preference methods (U.S. EPA, 2006). Because economic valuation of ecosystem services can be 

difficult, nonmonetary valuation using biophysical measurements and concepts also can be used. 

Examples of nonmonetary valuation methods include the use of relative-value indicators (e.g., a 

flow chart indicating uses of a waterbody, such as boatable, fishable, swimmable); another 

assigns values to ecosystem goods and services through the use of the common currency of 

energy. Energetic valuation attempts to assess ecosystem contributions to the economy by using 

one kind of energy (e.g., solar energy) to express the value of that type of energy required to 

produce designated services (Odum, 1996). This energy value is then converted to monetary 

units. This method of valuation, however, does not account for the premise that values arise from 

individual or societal preferences. 

Valuing ecological benefits, or the contributions to social welfare derived from 

ecosystems, can be challenging, as noted in EPA’s Ecological Benefits Assessment Strategic 

Plan (U.S. EPA, 2006). It is necessary to recognize that in the analysis of the environmental 

responses associated with any particular policy or environmental management action, some of 

the ecosystem services likely to be affected are readily identified, whereas others will remain 

unidentified. Of those ecosystem services that are identified, some changes can be quantified, 

whereas others cannot. Within those services whose changes can be quantified, only a few will 

likely be monetized, and many will remain unmonetized. Similar to health effects, only a portion 

of the ecosystem services affected by a policy can be monetized. The stepwise concept leading 

up to the valuation of ecosystems services is graphically depicted in Figure 2.4-2. 

Final Risk and Exposure Assessment 2-13 September 2009 
Chapter 2 – Overview of Risk and Exposure Assessment 

Ecosystems

Ecological goods and services 

affected by the policy

EPA Action

Planning and problem 

formulation

Goods and services 

identified

Goods and 

services not 

identified

Identified goods 

and services not 

Ecological analysis quantified

Goods and services 

quantified

Economic analysis

Quantified 

good and 

services not 

monetized

Goods and 

services 

monetized

Figure 2.4-2. Representation of the benefits assessment process indicating where 

some ecological benefits may remain unrecognized, unquantified, or unmonetized. 

(Modified based on the Ecological Benefits Assessment Strategic Plan report [U.S. 

EPA, 2006]).

A conceptual model integrating the role of ecosystem services in characterizing known or 

anticipated adverse effects to public welfare is shown in Figure 2.4-3. Under Section 108 of the 

CAA, the secondary standard is to specify an acceptable level of the criteria pollutant(s) in the 

ambient air that is protective of public welfare. For this review, the relevant air quality indicator 

is interpreted as ambient NOx and SOx concentrations that can be linked to levels of deposition 

for which there are adverse ecological effects. The air quality analyses described in Chapter 3 

explore the sources, emissions, and deposition of total reactive nitrogen and sulfur and their 

current contributions to ambient conditions. The case study analyses (described in Chapters 4 

and 5) link deposition in sensitive ecosystems (e.g., the exposure pathway) to changes in a given 

ecological indicator (e.g., for aquatic acidification, changes in acid neutralizing capacity [ANC]) 

and then to changes in ecosystems and the services they provide (e.g., fish species richness and 

Final Risk and Exposure Assessment 2-14 September 2009 
Chapter 2 – Overview of Risk and Exposure Assessment 

its influence on recreational fishing). To the extent possible for each targeted effect area, ambient 

concentrations of nitrogen and sulfur (i.e., ambient air quality indicators) were linked to 

deposition in sensitive ecosystems (i.e., exposure pathways), and then deposition was linked to 

system response as measured by a given ecological indicator (e.g., lake and stream acidification 

as measured by ANC). The ecological effect (e.g., changes in fish species richness) was then, 

where possible, associated with changes in ecosystem services and their ecological benefits or 

welfare effects (e.g., recreational fishing). 

Knowledge about the relationships linking ambient concentrations and ecosystem 

services can be used to inform a policy judgment on a known or anticipated adverse public 

welfare effect. The conceptual model outlined for aquatic acidification in Figure 2.4-3 can be 

modified for any targeted effect area where sufficient data and models are available. For 

example, changes in biodiversity would be classified as an ecological effect, and the associated 

changes in ecosystem services—productivity, recreational viewing, and aesthetics—would be 

classified as ecological benefits/welfare effects. This information can then be used to 

characterize known or anticipated adverse effects to public welfare and inform a policy based on 

welfare effects. 

Final Risk and Exposure Assessment 2-15 September 2009 
Chapter 2 – Overview of Risk and Exposure Assessment 

NOx/SOx

Concentrations

Atmospheric N & S

Deposition

Aquatic

Acidification

(lake/stream ANC)

Change in Ecosystem

Structure & Processes

(fish species richness)

Change in

Ecosystem Services

(recreational fishing)

Secondary

Standard

Ambient Air Quality

Indicator

Exposure Pathway

Affected Ecosystem

Ecological Response

(ecological indicator)

Ecological Effect

Ecological Benefit/

Welfare Effect

Policy based on

Welfare Effects

NOx/SOx

Concentrations

Atmospheric N & S

Deposition

Aquatic

Acidification

(lake/stream ANC)

Change in Ecosystem

Structure & Processes

(fish species richness)

Change in

Ecosystem Services

(recreational fishing)

Secondary

Standard

Ambient Air Quality

Indicator

Exposure Pathway

Affected Ecosystem

Ecological Response

(ecological indicator)

Ecological Effect

Ecological Benefit/

Welfare Effect

Policy based on

Welfare Effects

Figure 2.4-3. Conceptual model showing the relationships among ambient air 

quality indicators and exposure pathways and the resulting impacts on 

ecosystems, ecological responses, effects, and benefits to characterize known or 

anticipated adverse effects to public welfare. 

The ecosystems of interest in this Risk and Exposure Assessment are heavily impacted by 

the effects of anthropogenic air pollution, which may alter the services provided by the 

ecosystems in question. For example, changes in forest health as a result of soil acidification 

from NOx and SOx deposition may affect supporting services such as nutrient cycling; 

provisioning services such as timber production; and regulating services such as climate 

regulation. In addition, eutrophication caused by NOx deposition may affect supporting services 

Final Risk and Exposure Assessment 2-16 September 2009 
Chapter 2 – Overview of Risk and Exposure Assessment 

such as primary production; provisioning services such as food; and cultural services such as 

recreation and ecotourism. 

Where possible, linkages to ecosystem services from indicators of each effect identified 

in Step 1 of the Risk and Exposure Assessment were developed. These linkages were based on 

existing literature and models, focus on the services identified in the peer-reviewed literature, 

and are essential to any attempt to evaluate air pollution-induced changes in the quantity and/or 

quality of ecosystem services provided. According to EPA’s Science Advisory Board Committee 

on Valuing the Protection of Ecological Systems and Services, these linkages are critical 

elements for determining the valuation of benefits of EPA-regulated air pollutants (SAB CVPESS, 2007). Figure 2.4-4 provides an example pathway for nitrogen deposition in an aquatic 

ecosystem that links the ecological endpoints to changes in services and, finally, to valuation. 

This Risk and Exposure Assessment identifies the primary ecosystem service(s) for both 

acidification and enrichment and for the targeted ecosystem effects under consideration in this 

exposure assessment (see Table 2.1-1). Examples of some of the linkages between impacts and 

each targeted ecosystem effect in relation to specific ecosystem services are summarized below 

and in Table 2.4-1. 

Final Risk and Exposure Assessment 2-17 September 2009 
Chapter 2 – Overview of Risk and Exposure Assessment 

Figure 2.4-4. Pathway from nitrogen deposition to valuation for an aquatic system. 

Note: HABs = harmful algal blooms, DO = dissolved oxygen, SAV = submerged 

aquatic vegetation. 

Final Risk and Exposure Assessment 2-18 September 2009 
Chapter 2 – Overview of Risk and Exposure Assessment 

2.4.1 Aquatic Acidification 

In the current assessment, the analysis of effects on ecosystem services from aquatic 

acidification focused on recreational fishing. Fish abundance (decreased species richness) has 

been quantitatively linked to acidification through monitoring data and modeling of acid 

neutralizing capacity. Relevant ecosystem services were quantified, and values were estimated 

using a Random Utility model for fishing services and contingent valuation studies to estimate 

gains in total services provided by the Adirondack and New York State lakes case study area. 

2.4.2 Terrestrial Acidification 

The ecosystem services analysis for Terrestrial Acidification Case Study concentrated on 

the provision of food and wood products and on recreational activity. Sugar maple and red 

spruce abundance and growth (i.e., crown vigor, biomass, and geographic extent) were 

quantitatively linked to acidification symptoms through the Forest Inventory and Analysis 

National Program (FIA) database analyses. Results of the FIA database analysis were input to 

the Forest and Agriculture Sector Optimization Model – Green House Gas version 

(FASOMGHG) to estimate producer and consumer surplus gains associated with decreased 

acidification. 

2.4.3 Aquatic Nutrient Enrichment 

The ecosystem services analysis for aquatic nutrient enrichment evaluated several 

cultural ecosystem services, including recreational fishing, boating, and beach use. In addition, 

aesthetic and nonuse values were evaluated; the impacts on recreational fishing (e.g., closings, 

decreased species richness) to eutrophication symptoms through monitoring data were 

quantitatively linked; other recreational activities and aesthetic and non-use services to 

eutrophication symptoms were quantitatively related through user surveys and valuation 

literature; and the current commercial fishing markets were described. Although little data are 

available to link any decrease in commercial landings or subsistence fishing directly to 

eutrophication, it seems likely that these activities would be impacted. 

2.4.4 Terrestrial Nutrient Enrichment 

The ecosystem services analysis for terrestrial nutrient enrichment for the coastal sage 

scrub and mixed conifer forest ecosystems focused on services such as recreation, aesthetic, and 

Final Risk and Exposure Assessment 2-19 September 2009 
Chapter 2 – Overview of Risk and Exposure Assessment 

Final Risk and Exposure Assessment 2-20 September 2009 

non-use services, including existence values. Given the lack of data available to develop a 

quantitative analysis of service impacts, the impacts on these ecosystems were addressed in a 

qualitative fashion. 

2.4.5 Sulfur and Mercury Methylation 

The major ecosystem services potentially impacted by mercury methylation are 

provisioning and cultural services. Fishing and shellfishing can involve both commercial 

operations and sport fishing, both of which provide food for human populations. For some socioeconomic groups (especially low-income groups), fishing is a subsistence activity that makes a 

significant contribution to household food intake. Sport fishing often involves important 

recreational services, and for many groups (e.g., Native Americans, Alaska Native villagers), 

fishing and consuming local fish or shellfish is of cultural and spiritual significance. A synthesis 

of the ecosystem service and valuation aspects of fishing and shellfishing activities, with a focus 

on the mercury pollution issues affecting human health and well-being, is found in the 

Regulatory Impact Analysis of the Clean Air Mercury Rule (U.S. EPA, 2005) and in the Mercury 

Study Report to Congress (U.S. EPA, 1997). 
Chapter 2 – Overview of Risk and 

Table 2.4-1. Ecological Impacts Associated with Acidification, Nutrient Enrichment, and Increased Mercury MeAssociated Ecosystem Services 

Targeted Ecosystem 

Effect Provisioning Services Regulating Services Cultural Services Su

Aquatic Acidification  Fishing (subsistence)  Biological control  Recreational fishing 

 Nonuse 

 No

Terrestrial Acidification  Food, wood products  Erosion control 

 Fire regulation  Hydrologic  Climate 

 Recreational activity  Aesthetic  Nonuse 

 N

Aquatic Nutrient Enrichment 

 Commercial fishing  Erosion control 

 Flood control 

 Recreational activity  Aesthetic  Nonuse 

 N

Terrestrial Nutrient Enrichment Coastal Sage Scrub  Not Available  Fire regulation 

 Hydrologic control  Climate 

 Recreational activity  Aesthetic  Nonuse 

 N

Mixed Conifer Forest  Not Available  Hydrologic control 

 Climate 

 Recreational activity  Aesthetic  Nonuse 

 N

Sulfur and Mercury Methylation 

 Commercial and 

subsistence fishing 

 Not Available  Recreational fishing 

 Nonuse 

 N

Final Risk and Exposure Assessment 2-21 
Chapter 2 – Overview of Risk and Exposure Assessment 

2.5 UNCERTAINTY 

The scope of this Risk and Exposure Assessment involves quantifying a number of 

relationships along the path of moving from ambient concentrations of NOx, NHx, and SOx to 

their transformation products and deposition in the environment. The environmental effects of 

nitrogen and sulfur deposition vary widely and the extent of these effects in time and space is 

often uncertain in both terrestrial and aquatic ecosystems. The relationships between deposition, 

ecological effects, ecological indicators, and ecosystem services are also quantified. Uncertainty 

and variability are present at each step in this framework (as shown in Figure 2.3-1). In addition, 

extrapolating from a case study area to a larger assessment area introduces additional uncertainty 

and potential error into the process. Understanding the nature, sources, and importance of these 

uncertainties will help inform the standard setting process in the policy assessment phase of this 

review. 

Uncertainty represents a lack of knowledge about the true value of a parameter that can 

result from inadequate or imperfect measurement. Uncertainty can be reduced by obtaining 

additional measurements, data, and information. Conceptual and numerical uncertainty can be 

bounded by testing a range of inputs and parameters in atmospheric and ecological numerical 

process models, like the ones used in this assessment. Table 2.5.1 presents the models used in 

this assessment and includes model description, case study application, model type, temporal 

features of the model, spatial scale used in this analysis, strengths, weaknesses, supporting 

organization endorsements, and considerations in the application to nitrogen and sulfur 

deposition. An additional source of uncertainty is error due to the use of incorrect measurements, 

methods, data, or models. Error can be identified and addressed by thorough evaluation, review, 

and consultation with outside experts. 

Variability in space and time is a component of all environmental systems and represents 

actual differences in the value of a parameter or attribute of an ecological indicator. Variability 

describes the natural variation in a system and cannot be reduced by taking additional 

measurements of a parameter, although it is possible to characterize the range of variation in a 

measurement or parameter. For example, there is natural variability among similar ecosystems 

nationwide, some of which are more sensitive to acidification and/or nutrient enrichment than 

Final Risk and Exposure Assessment 2-22 September 2009 
Chapter 2 – Overview of Risk and Exposure Assessment 

Final Risk and Exposure Assessment 2-23 September 2009 

others, just as there is natural variability in the precipitation amounts that produce wet deposition 

loadings to these systems. 

Selected terms and sources of uncertainty and variability are discussed, as appropriate, in 

each section of this Risk and Exposure Assessment. 
Chapter 2 – Overview of Risk and 

Table 2.5-1. Overview of Models Used in This Assessment, Including Model Description, Case Study ApplicatiTemporal Features of the Model, Spatial Scale Used in This Analysis, Strengths, Weaknesses, Supporting Organ

and Considerations in the Application to Nitrogen and Sulfur Deposition

Model CMAQ MAGIC SMB SPARROW 

Complete Name 

Community Multiscale Air Quality 

Model of Acidification of Groundwater in Catchments 

Simple Mass Balance SPAtially Referenced 

Regression on Watershed Attributes 

Description The CMAQ model is a 

comprehensive, threedimensional grid-based Eulerian air quality model designed to simulate the formation and fate of gaseous and PM species, including ozone, oxidant precursors, and primary and secondary PM concentrations and deposition over urban, regional, and larger spatial scales. CMAQ is run for user-defined input sets of meteorological conditions and emissions. 

MAGIC is a lumpedparameter model that predicts long-term effects of acidifying deposition on concentrations of the major ions in soil solution and surface waters. The model represents the catchment with aggregated, uniform soil compartments and a surface water compartment that can either be a lake or a stream. The model is calibrated using observed values of surface water and soil chemistry for a specified time period (Aherne et al., 2003). 

Simple Mass Balance is a balance of system inputs of deposition and biological fixation with outputs of immobilization, uptake, adsorption, denitrification, combustion, erosion, volatilization, and leaching. It is most commonly used as a method for the analysis of the critical load of acid deposition. Its basic principle is based on identifying the long-term average sources of acidity and alkalinity to determine the maximum acid input that will balance the system at a biogeochemically safe limit. 

SPARROW relates instream water quality measurements to spatially referenced characteristics of watersheds, including contaminant sources and factors influencing terrestrial and stream transport. The model empirically estimates the origin and fate of contaminants in streams. 

Case Study Application 

All Aquatic acidification Terrestrial acidification Aquatic nutrient 

enrichment (in tandem with ASSETS) 

Model Type Deterministic, processdriven model Lumped-parameter model, which follows mass balance Mass balance model over average conditions Empirical/statistical model over average 

Final Risk and Exposure Assessment 2-24 
Chapter 2 – Overview of Risk and 

Final Risk and Exposure Assessment 2-25 

Model CMAQ MAGIC SMB SPARROW 

principles over time conditions 

Temporal Features 

Dynamic (hourly time step) 

Dynamic (monthly and annual time step) 

Steady-state (annual average results) 

Steady-state (annual average results) 

Spatial Scale Used in Case Study Analyses 

The 2002 simulation, performed for both the eastern and western domains, used horizontal spatial resolution of approximately 12 x 12–km grid cells. The 2002 through 2005 simulations were performed for the eastern domain (12 km) and for the continental United States domain (36 x 36 km). 

MAGIC is applied to 44 lakes in the Adirondack Case Study Area and 16 streams in the Shenandoah Case Study Area. 

The SMB is applied to plots within the Hubbard Brook Experimental Forest and the Kane Experimental Forest. It is then applied to multiple areas (each covering 0.07 ha) within 24 states for sugar maple and in 8 states for red spruce identified from the U.S. Forest Service Forest Inventory and Analysis database. 

The Potomac River and Neuse River case studies relied on the hydrology and catchments from the RF1 coverages from USGS to represent the watersheds contributing to each of the estuaries (Brakebill and Preston, 2004; Hoos et al., 2008). 

Strengths  Is used for the 

continental United States. 

 Is a process-based 

model, which includes chemical speciation.

 Has been in use for over 

20 years and is widely accepted by the modeling community. 

 Has been applied 

extensively in North America and Europe to both individual sites and regional networks of sites. 

 Has been used in Asia 

(e.g., alpine and desert soils of China), Africa, and South America. 

 Parameterization for new 

sites has much 

 Is widely used across 

Europe for development of terrestrial critical loads. 

 Is simple to apply.  Model performance 

depends on the quality of the input data because the model is a simple balance. 

 Considers both 

nitrogen and sulfur deposition. 

 Has been published 

and scientifically accepted for about a decade. 

 Has been applied on 

national and various regional scales. 

 Provides estimates for 

different sources of nitrogen. 

 Parameterization for 

new geographic domains and continuing refinement is being pursued by USGS. 
Chapter 2 – Overview of Risk and 

Final Risk and Exposure Assessment 2-26 

Model CMAQ MAGIC SMB SPARROW 

background information to draw from because of the numerous applications in its 20 years of use. 

 Has an automated builtin optimization 

procedure. 

 Has versatile application 

(e.g., investigation of temporal chemical changes in response to changing deposition or impact analyses of emission reduction options). 

 Simulates pH, sulfate, 

nitrate, ammonia, acid neutralizing capacity, and dissolved organic carbon. 

 Directly simulates water 

quality response to atmospheric deposition. 

 Model performance/ 

error is explicitly included (e.g., quantifies uncertainties based on model coefficient error and unexplained variability in the observed data). 

Weaknesses  Has current 

minimum grid scale of 12 km. 

 Must be parameterized 

for each application. 

 Has controlled release of 

program. 

 Makes it difficult to 

estimate reasonable input values. 

 Does not explicitly 

represent environmental processes. 

 Is not dynamic in 

time. 

 Model performance 

depends on the quality of the input data 

 Has empirically 

estimated land to water and instream delivery rates. 

 Is not dynamic in 

time. 

 Does not explicitly 

include deposition measurements. 

 Cannot differentiate 

between nitrogen species; only 
Chapter 2 – Overview of Risk and 

Final Risk and Exposure Assessment 2-27 

Model CMAQ MAGIC SMB SPARROW 

because the model is a simple balance. 

 Uncertainty analysis 

is not explicitly included. 

 Requires assumption 

that nitrogen and sulfur cycles and ion exchange are all at steady-state. 

 Assumes simple 

hydrology where infiltration is straight through the soil profile. 

simulates total nitrogen. 

 Can only be operated 

for one pollutant at a time. 

Supporting Organization (s)/ Agency Endorsements 

U.S. EPA’s Office of Research and Development 

Academic, with sponsorship of Norwegian Institute for Water Research and University of Virginia. MAGIC is also cited in numerous documents by government agencies. 

Utilized by multiple agencies, especially during critical load development, but not necessarily supported by any specific agency. 

U.S. Geological Survey 

Nitrogen and Sulfur Deposition Considerations 

The CMAQ deposition data for nitrogen and sulfur species (list provided in Appendix 1) are used to calculate oxidized and reduced wet and dry nitrogen deposition, wet and dry sulfur deposition, and total reactive nitrogen and total sulfur deposition. 

Time series (annual or monthly) of deposition fluxes of ions (wet plus dry deposition). 

Depending on the mass balance model used, either total nitrogen and/or sulfur or speciated nitrogen and/or sulfur atmospheric deposition rates can be incorporated. 

To date, SPARROW has focused on wet deposition input data from National Atmospheric Deposition Program. 

Note: PM = particulate matter, USGS = U.S. Geological Survey. 
Chapter 2 – Overview of Risk and Exposure Assessment 

2.6 REFERENCES 

Aherne, J, P.J. Dillon, and B.J. Cosby. 2003. Acidification and recovery of aquatic ecosystems in 

south central Ontario, Canada: regional application of the MAGIC model. Hydrology and 

Earth System Sciences 7(4): 561–573. 

Brakebill, J.W., and S.D. Preston. 2004. Digital Data Used to Relate Nutrient Inputs to Water 

Quality in the Chesapeake Bay Watershed, Version 3.0. USGS Open File Report 2004-

1433. U.S. Department of the Interior, U.S. Geological Survey, Baltimore, MD. 

Available at http://pubs.usgs.gov/of/2004/1433/pdf/sparv3.pdf. 

Hoos, A.B., S. Terziotti, G. McMahon, K. Savvas, K.G. Tighe, and R. Alkons-Wolinsky. 2008. 

Data to Support Statistical Modeling of Instream Nutrient Load Based on Watershed 

Attributes, Southeastern United States, 2002. Open File Report 2008-1163. U.S. 

Department of the Interior, U.S. Geological Survey, Reston, VA. 

MEA (Millennium Ecosystem Assessment Board). 2005a. Ecosystems and Human Well-being: 

Current State and Trends, Volume 1. Edited by R. Hassan, R. Scholes, and N. Ash. 

Washington: Island Press. Available at http://www.millenniumassessment.org/ 

documents/document.766.aspx.pdf. 

MEA (Millennium Ecosystem Assessment Board). 2005b. Millennium Ecosystem Assessment 

Reports. Washington: Island Press. Available at 

http://www.millenniumassessment.org/en/index.aspx. 

Odum, H.T. 1996. Ecological Accounting. New York: Wiley and Sons. 

SAB C-VPESS (Science Advisory Board Committee on Valuing the Protection of Ecological 

Systems and Services). 2007. Valuing the Protection of Ecological Systems and Services.

SAB CVPESS Draft Report, September 24. 

U.S. EPA (Environmental Protection Agency) 1997. Mercury Study Report to Congress. EPA452/R-97-003. Office of Air Quality Planning & Standards and Office of Research and 

Development, Washington, DC. December. 

Final Risk and Exposure Assessment 2-28 September 2009 
Chapter 2 – Overview of Risk and Exposure Assessment 

Final Risk and Exposure Assessment 2-29 September 2009 

U.S. EPA (Environmental Protection Agency) 2005. Regulatory Impact Analysis of the Final 

Clean Air Mercury Rule. U.S. Environmental Protection Agency, Office of Air Quality 

Planning and Standards Air Quality Strategies and Standards Division. Research Triangle 

Park, NC. EPA-452/R-05-003. March 2005 

U.S. EPA (Environmental Protection Agency). 2006. Ecological Benefits Assessment Strategic 

Plan. EPA-240-R-06-001. Office of the Administrator. Washington, DC. Available at 

http://www.epa.gov/economics. 

U.S. EPA (Environmental Protection Agency). 2008a. Integrated Science Assessment (ISA) for 

Oxides of Nitrogen and Sulfur–Ecological Criteria (Final Report). EPA/600/R08/082F. U.S. Environmental Protection Agency, National Center for Environmental 

Assessment–RTP Division, Office of Research and Development, Research Triangle 

Park, NC. Available at http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=201485. 

U.S. EPA (Environmental Protection Agency). 2008b. Draft Scope and Methods Plan for 

Risk/Exposure Assessment: Secondary NAAQS Review for Oxides of Nitrogen and 

Oxides of Sulfur. U.S. Environmental Protection Agency, Office of Air Quality Planning 

and Standards, Research Triangle Park, NC. EPA-452/D-08-002. March 2008. 

Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-1 September 2009 

3.0 SOURCES, AMBIENT CONCENTRATIONS, AND 

DEPOSITION 

This chapter discusses current emissions sources of nitrogen and sulfur, as well as 

atmospheric concentrations, estimates of deposition, policy-relevant background, and nonambient loadings of nitrogen and sulfur to ecosystems. Both measured and modeled data are 

used to evaluate current contributions of nitrogen and sulfur compounds to the Risk and 

Exposure Assessment case study areas. The case study areas are (1) Adirondack Mountains 

(referred to as Adirondack); (2) Blue Ridge Mountains/Shenandoah National Park, Virginia 

(referred to as Shenandoah); (3) Kane Experimental Forest (KEF) on the Allegheny Plateau of 

Pennsylvania; (4) Hubbard Brook Experimental Forest (HBEF) in the White Mountains of New 

Hampshire; (5) Potomac River/Potomac Estuary; (6) Neuse River/Neuse River Estuary; (7) 

southern California Coastal Sage Scrub (CSS); and (8) Pacific coast states’ Mixed Conifer Forest 

(MCF), including the Transverse (or Los Angeles) Range, which includes the San Bernardino 

Mountains, and the Sierra Nevada Range. The Rocky Mountain National Park (RMNP) is also 

highlighted as a supplemental area. A nationwide description of emissions, concentrations, and 

deposition is provided in Section 3.2; a detailed characterization of nitrogen and sulfur 

deposition in and near the case study areas1 is presented in Section 3.3; and the relative 

contributions of ambient concentrations to deposition are evaluated in Section 3.4. The 

deposition fields described here were used as modeling input for the individual case study 

ecological modeling presented in Chapters 4 and 5. 

 

1 The eight case study areas are shown in Figure 2.1-1 and discussed in Chapters 4 and 5 and Appendices 4 through 

7. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

3.1 SCIENCE OVERVIEW 

Prior to analyzing the effects of nitrogen and sulfur deposition to the environment, the 

ambient emissions, transformations, and transport of nitrogen and sulfur in the atmosphere must 

first be examined. As noted in Chapter 1, the terms “oxides of nitrogen” and “nitrogen oxides” 

(NOx) refer to all forms of oxidized nitrogen compounds, including nitric oxide (NO), nitrogen 

dioxide (NO2), and all other oxidized nitrogen-containing compounds transformed from NO and 

NO2. Additionally, reduced forms of nitrogen (ammonia [NH3] and ammonium ion [NH4

+

], 

collectively termed reduced nitrogen [NHx]) can also play an important role in the emission, 

transformations, and deposition, and are included in this review. Much like NOx, additional NHx

can lead to increased acidification and nutrient enrichment in ecosystems. Where possible, the 

analyses will separate oxidized from reduced forms of nitrogen to show the impact from each 

component, as well as the overall impact from total reactive nitrogen. This will be important for 

the policy assessment portion of this review. 

Sulfur oxides (SOx) refer to all gas-phase oxides of sulfur, including sulfur monoxide 

(SO), sulfur dioxide (SO2), sulfur trioxide (SO3), and disulfur monoxide (S2O); however, only 

SO2 is present in concentrations relevant for atmospheric chemistry and ecological exposures. 

Deposition of nitrogen and sulfur to water and land surfaces is a function of ambient 

concentrations of NOx, other forms of reactive nitrogen, NHx, and SOx, as well as their 

atmospheric transformation products, and of the earth’s surface properties through complex 

processes involving numerous meteorological variables and dependencies. Atmospheric 

pollutants deposit through direct contact with the surface (i.e., dry deposition), transfer into 

liquid precipitation (i.e., wet deposition), and through interaction with fog or mist (i.e., occult 

deposition). Occult deposition is an important process in coastal and mountain areas for 

delivering pollutants to the ground and vegetation, as described in Chapter 2.8 of the Integrated 

Science Assessment (ISA) for Oxides of Nitrogen and Sulfur–Ecological Criteria (Final Report)

(ISA) (U.S. EPA, 2008b). This Risk and Exposure Assessment review was not able to 

quantitatively account for occult deposition because of a lack of routine measurements and 

because atmospheric models do not fully account for this type of deposition. Wet and dry 

deposition are the two major mechanisms of deposition addressed here. The magnitude of wet 

and dry deposition is related to the ambient concentrations of NOx and SOx through the time-, 

location-, process-, and chemical-species–specific deposition velocity (Seinfeld and Pandis, 

Final Risk and Exposure Assessment 3-2 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

1998). The ambient concentrations of NOx, NH3, and SO2 that contribute to nitrogen and sulfur 

deposition are the result of emissions of these pollutants and oxidant precursor species (e.g., 

volatile organic compounds) from anthropogenic and natural sources. The emissions to 

atmospheric-concentrations-to deposition processes involving the chemical formation and fate of 

gas and particle-phase total reactive nitrogen and sulfur are described in Chapter 2.6 of the ISA. 

Figure 1.3-1 illustrates the cycle of reactive, oxidized nitrogen species in the atmosphere. 

Emissions of NOx lead to NO and NO2 concentrations that undergo chemical transformations to 

form other nitrogen-containing oxidants such as peroxyacetyl nitrates (PAN). Because NO and 

NO2 are only slightly soluble, they can be transported over longer distances in the gas phase than 

more soluble pollutants. During transport, NO and NO2 can be transformed into other pollutants, 

such as PAN, which can provide a major source of NOx in remote areas. NO2 can also form gasphase nitric acid (HNO3), which can increase the acidity of clouds, fog, and rain water and form 

particulate nitrate that contributes to nitrogen deposition in locations distant from the NOx

emissions source area. Emissions of SOx contain SO2, which is oxidized in the atmosphere 

through a series of reactions with hydroxide radicals (OH), hydroperoxyl radicals (HO2), oxygen 

(O2), and water (H2O) to form sulfuric acid (H2SO4). H2SO4 is also formed from SO3 emissions 

within or immediately after release into the atmosphere. H2SO4 is rapidly transformed to the 

aqueous phase of aerosol particles and cloud droplets and can participate in the formation of new 

particles. The transformation of sulfur compounds in the atmosphere is illustrated in 

Figure 1.3-2. Emissions of NH3 neutralize the acidity in ambient particles and form new 

particles through reactions with gas-phase HNO3 to form ammonium nitrate (NH4NO3) and with 

sulfate (SO4

2-) to form ammonium sulfates, which are important components of nitrogen and 

sulfur deposition. Thus, NOx, SOx, and NH3 emissions can not only affect atmospheric loadings 

of these pollutants in and near source locations, but they can also affect more distant areas 

through chemical transformation and transport. 

3.2 NATIONWIDE SOURCES, CONCENTRATIONS, AND 

DEPOSITION OF NOX, NH3, AND SOX

3.2.1 Sources of Nitrogen and Sulfur 

The National Emissions Inventory (NEI) annual total emissions data for 2002 (U.S. EPA, 

2006) are used to characterize the magnitude and spatial patterns in emissions of NOx, NH3, and 

Final Risk and Exposure Assessment 3-3 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-4 September 2009 

SO2 nationwide2. The spatial resolution of these data varies by source type. Emissions from most 

large stationary sources are represented by individual point sources (e.g., electric generating 

units, industrial boilers). Sources that emit over broad areas are reported as county total 

emissions. The national annual 2002 emissions of NOx, NH3, and SO2 by major source category 

are presented in Table 2-1 of the ISA (U.S. EPA, 2008b). 

3.2.1.1 NOx Emissions 

The distribution of national total NOx emissions across major source categories is 

provided in Table 3.2-1. Emissions summaries are also provided for the East3 and West in 

Tables 3.2-2a and b, respectively, to reveal regional differences in source emissions profiles. In 

addition to anthropogenic sources, there are also natural sources of NOx, including lightning, 

wildfires, and microbial activity in soils. Nationally, transportation-related sources (i.e., on-road, 

nonroad, and aircraft/locomotive/marine) account for ~60% of total anthropogenic emissions of 

NOx, while stationary sources (e.g., electrical utilities and industrial boilers) account for most of 

the remainder (U.S. EPA, 2008b, AX2, Table 2-1). Emissions from on-road vehicles represent 

the major component of mobile source NOx emissions. Approximately half the mobile source 

emissions are contributed by diesel engines, and half are emitted by gasoline-fueled vehicles and 

other sources (U.S. EPA, 2008b, AX2, Section 2.1.1 and Table 2-1). Nationwide, the nonroad, 

aircraft/locomotive/marine, and non-electric generating unit point emissions sectors each 

contribute generally similar amounts to the overall NOx inventory. Overall, NOx emissions are 

broadly split between NO and NO2 in a ratio of 90% NO and 10% directly emitted NO2. 

However, this split can vary by source category, as described in Chapter 2.2.1 of the ISA (U.S. 

EPA, 2008b). 

Table 3.2-1. Annual National NOx Emissions across Major Source Categories in 2002. 

NOx

National Totals Emissions (million tons) Percent of Total 

Electric Generation Units 4.619 22% 

Industrial Point Sources 2.362 11% 

Stationary Area 1.529 7% 

 

2 For the purposes of this analysis, nationwide emissions do not include emissions from Alaska or Hawaii. 

3 In this analysis, the East is defined as all states from Texas northward to North Dakota and eastward to the East 

Coast of the United States. States from New Mexico northward to Montana and westward to the West Coast are 

considered to be part of the West. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-5 September 2009 

NOx

National Totals Emissions (million tons) Percent of Total 

On-road 7.839 37% 

Nonroad 2.219 10% 

Aircraft/Locomotive/Marine 2.611 12% 

Fires 0.080 < 1% 

Total 21.259 

Table 3.2-2a. Annual NOx Emissions across Major Source Categories in 2002 for the Eastern 

United States. 

NOx

Eastern U.S. Emissions (million tons) Percent of Total 

Electric Generation Units 4.094 23% 

Industrial Point Sources 2.031 12% 

Stationary Area 1.295 7% 

On-road 6.250 36% 

Nonroad 1.709 10% 

Aircraft/Locomotive/Marine 2.038 12% 

Fires 0.028 < 1% 

Total 17.445 

Table 3.2-2b. Annual NOx Emissions across Major Source Categories in 2002 for the Western 

United States. 

NOx

Western U.S. Emissions (million tons) Percent of Total 

Electric Generation Units 0.525 14% 

Industrial Point Sources 0.331 9% 

Stationary Area 0.234 6% 

Onroad 1.589 42% 

Nonroad 0.510 13% 

Aircraft/Locomotive/Marine 0.573 15% 

Fires 0.055 1% 

Total 3.817 

In general, NOx emissions in the East are nearly 5 times greater that NOx emissions in the 

West. In both the eastern and western United States, the on-road sector is the largest contributor. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-6 September 2009 

Emissions from electric generation units are the second-largest contributor to NOx emissions in 

the East with 23% of the total. Emissions in the East from industrial point sources, nonroad 

engines, and aircraft-locomotives-marine engines each contribute in the range of 10 to 12%. In 

the West, the contribution to NOx emissions from electric generation units (14%) is in the same 

range as the contributions from nonroad engines (13%) and aircraft-locomotives-marine engines 

(15%). 

The spatial patterns of 2002 annual NOx emissions across the United States are shown in 

Figure 3.2-14. Emissions of NOx are concentrated in and near urban and suburban areas and 

along major highways. Moderate or higher levels of NOx emissions (>100,000 tons/yr)5 are also 

evident in some rural areas at locations (i.e., grid cells) containing major point sources. The 

amount of NOx emissions in and near each of the case study areas can be seen from this map. All 

of the case study areas contain or are near locations with NOx emissions in excess of 

100,000 tons/yr. 

 

4 To create this map, NOx emissions were allocated to a 36 x 36– km grid covering the United States in order to 

normalize for the differences in the geographic aggregation of point- and county-based emissions. The emissions 

are in tons per year per 36 x 36 km (1,296 km2

). 

5 Emissions are in tons per year per 36 x 36 km (1,296 km2

). 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-7 September 2009 

1 Adirondack

2 Shenandoah

3 Potomac River/Potomac Estuary

4 Neuse River/Neuse Estuary

5 Kane Experimental Forest

6 Hubbard Brook Experimental Forest

7 Mixed Conifer Forest (Transverse Range)

8 Mixed Conifer Forest (Sierra Nevada Range)

9 Rocky Mountain National Park

Figure 3.2-1. Spatial distribution of annual total NOx emissions (tons/yr) for 2002. 

3.2.1.2 NH3 Emissions 

The primary anthropogenic sources of NH3 emissions are fertilized soils and livestock.

Motor vehicles and stationary combustion are small emitters of NH3. Some NH3 is emitted as a 

byproduct of NOx reduction in motor vehicle catalysts. The spatial patterns of 2002 annual NH3

emissions are shown in Figure 3.2-26. The highest emissions of NH3 are generally found in areas 

of major livestock feeding and production facilities, many of which are in rural areas. In 

addition, NH3 emissions exceeding 1,000 tons/yr are evident across broad areas that are likely 

associated with the application of fertilizer to crops. The patterns in NH3 emissions are in 

contrast to the more urban-focused emissions of NOx. The Potomac River/Potomac Estuary, 

Neuse River/Neuse River Estuary, Shenandoah, and Mixed Conifer Forest (in the Sierra Nevada 

Range and the Transverse Range) case study areas all have sources with NH3 emissions 

 

6 Note that, because overall emissions of NH3 are much lower than emissions of NOx, we used a more refined set of 

ranges to display emissions of NH3 compared to what was used to display emissions of NOx. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

exceeding 5,000 tons/yr. Rocky Mountain National Park is adjacent to an area with relatively 

high NH3 emissions exceeding 2,500 tons/yr. The Adirondack, Hubbard Brook Experimental 

Forest, and Kane Experimental Forest case study areas are more distant from sources of NH3 of 

this magnitude. 

1 Adirondack

2 Shenandoah

3 Potomac River/Potomac Estuary

4 Neuse River/Neuse Estuary

5 Kane Experimental Forest

6 Hubbard Brook Experimental Forest

7 Mixed Conifer Forest (Transverse Range)

8 Mixed Conifer Forest (Sierra Nevada Range)

9 Rocky Mountain National Park

Figure 3.2-2. Spatial distribution of annual total NH3 emissions (tons/yr) for 2002. 

3.2.1.3 SOx Emissions 

The distributions of SO2 emissions for major source categories nationally are provided in 

Table 3.2-3. Emissions of SO2 for the East and West are presented in Tables 3.2-4a and b, 

respectively. Anthropogenic emissions of SO2 in the United States are mainly due to combustion 

of fossil fuels by electrical generation units (70%) and industrial point sources (15%); 

transportation-related sources contribute minimally (7%). Thus, most SO2 emissions originate 

from point sources. Almost all the sulfur in fuel is released as volatile components (SO2 or SO3) 

during combustion. The higher sulfur content of coal compared to other types of fossil fuels 

results in higher SO2 emissions from electrical utilities using coal as fuel. 

Final Risk and Exposure Assessment 3-8 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-9 September 2009 

Emissions of SO2 are more than 10 times greater in the East than in the West. Emissions 

from electric generation units are the largest contributor to SO2 emissions in both the East and 

West, but are a much greater fraction of the inventory in the East (71%) compared to the West 

(44%). Stationary area sources and the aircraft-locomotive-marine engine sector have a greater 

relative contribution to SO2 in the West compared to the East7. 

The largest natural sources of SO2 are volcanoes and wildfires. Although SO2 constitutes 

a relatively minor fraction (0.005% by volume) of total volcanic emissions (Holland, 1978), 

concentrations in volcanic plumes can be range up to tens of parts per million (ppm). Sulfur is a 

component of amino acids in vegetation and is released during combustion. Emissions of SO2

from burning vegetation are generally in the range of 1% to 2% of the biomass burned (Levine et 

al., 1999). 

Table 3.2-3. Annual National SO2 Emissions across Major Source Categories in 2002.

SO2

National Totals Emissions (million tons) Percent of Total 

Electric Generation Units 10.359 70% 

Industrial Point Sources 2.249 15% 

Stationary Area 1.250 8% 

On-road 0.242 2% 

Nonroad 0.188 1% 

Aircraft/Locomotive/Marine 0.533 4% 

Fires 0.050 < 1% 

Total 14.871 

Table 3.2-4a. Annual SO2 Emissions across Major Source Categories in 2002 for the Eastern 

United States. 

SO2

Eastern U.S. Emissions (million tons) Percent of Total 

Electric Generation Units 9.923 71% 

Industrial Point Sources 2.057 15% 

Stationary Area 1.116 8% 

On-road 0.214 2% 

 

7 Note that SO2 emissions from fires are understated in the NEI because of an error in the emissions calculations.
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-10 September 2009 

SO2

Eastern U.S. Emissions (million tons) Percent of Total 

Nonroad 0.162 1% 

Aircraft/Locomotive/Marine 0.398 3% 

Fires 0.011 < 1% 

Total 13.881 

Table 3.2-4b. Annual SO2 Emissions across Major Source Categories in 2002 for the Western 

United States. 

SO2

Western U.S. Emissions (million tons) Percent of Total 

Electric Generation Units 0.436 44% 

Industrial Point Sources 0.192 19% 

Stationary Area 0.134 14% 

On-road 0.029 3% 

Nonroad 0.026 3% 

Aircraft/Locomotive/Marine 0.136 14% 

Fires 0.035 4% 

Total 0.988 

The spatial patterns of 2002 annual SO2 emissions are shown in Figure 3.2-3. High SO2

emissions are scattered across the East, and there are large sources in both urban are rural 

locations. The greatest geographic concentration of SO2 sources is in the Midwest, particularly 

along the Ohio River, where numerous electric generating units are located. As noted above, SO2

emissions in the West are much lower than in the East, with sources concentrated in urban 

locations along with localized emissions in more rural areas associated with industrial sources 

(e.g., smelters) and gas-field operations. 

The Potomac River/Potomac Estuary, Neuse River/Neuse River Estuary, Shenandoah, 

and Mixed Conifer Forest (Transverse Range portion) case study areas each contain numerous 

locations of major SO2 emitters. The Kane Experimental Forest Case Study Area and Rocky 

Mountain National Park are relatively close to SOx emission locations exceeding 5,000 tons/yr. 

The Adirondack, Hubbard Brook Experimental Forest, and Mixed Conifer Forest (Sierra Nevada 

Range portion) case study areas are more distant from SOx sources of this magnitude. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

1 Adirondack

2 Shenandoah

3 Potomac River/Potomac Estuary

4 Neuse River/Neuse Estuary

5 Kane Experimental Forest

6 Hubbard Brook Experimental Forest

7 Mixed Conifer Forest (Transverse Range)

8 Mixed Conifer Forest (Sierra Nevada Range)

9 Rocky Mountain National Park

Figure 3.2-3. Spatial distribution of annual total SO2 emissions (tons/yr) for 2002.

3.2.2 Nationwide Atmospheric Concentrations of NOx and SOx

This section provides a nationwide view of the magnitude and spatial patterns in 

atmospheric concentrations of NOx and SOx. Measurements of these pollutants are made at 

numerous sampling sites comprising several routine and special study monitoring networks in 

the United States (see Section 2.9 of the ISA [U.S. EPA, 2008b] for a comprehensive review of 

these networks and measurement techniques). Monitoring data generally provide the most direct 

approach to characterizing concentrations in a particular location. However, for NOx, and to 

some extent SO2, the lack of geographic coverage and limitations in spatial representativeness of 

most existing sites affect the extent to which these monitoring data can be used to infer NOx and 

SO2 concentrations in unmonitored areas, particularly rural locations. As noted in the ISA (U.S. 

EPA, 2008b), ambient NO2 is normally measured at only a few locations in a given area. In view 

of the limitations of existing monitoring networks, and the large spatial gradients in NO2, as 

suggested by the gradients in NOy described below, the ISA states that air quality model 

predictions might be helpful for capturing the large-scale features of NO2 concentrations and 

Final Risk and Exposure Assessment 3-11 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

could be used in conjunction with measurements to provide a more complete picture of the 

variability of NO2 across the United States. Monitoring data are not as spatially limited for SO2

as for NO2 because SO2 measurements are also available from the Clean Air Status and Trends 

Network (CASTNET; http://www.epa.gov/CASTNET), which covers rural and remote locations, 

particularly in the eastern United States. 

This analysis used measured data, along with air quality model predictions of NOx and 

SO2, to characterize NO2 and SO2 concentrations in the United States. The air quality model 

predictions were taken from applications of the Community Multiscale Air Quality modeling 

system (Byun and Schere, 2006; U.S. EPA, 1999). CMAQ is a chemistry transport model that 

treats the chemical interactions among NOx; SOx; other pollutants and their precursors; the 

formation of secondary aerosols containing nitrogen, sulfur, and other species; the multi-day 

transport of these pollutants from local to national scales; and the removal of pollutants by 

deposition. CMAQ was used to simulate concentrations and deposition for 2002 using 

meteorology and emissions for that year. In this application, CMAQ was run with a horizontal 

resolution of approximately 12 × 12 km. Hourly predictions of NOx and SO2 were aggregated to 

provide annual average concentration fields of these pollutants across the United States. 

Additional information on this CMAQ application is provided in Appendix 1 of this report. 

3.2.2.1 NOx Concentrations 

For the period 2003 through 2005, mean annual average NO2 concentrations were ~15 

parts per billion (ppb) with an interquartile range of 10 to 25 ppb and a 90th percentile value of 

~30 ppb, based on measurements at all monitoring sites within metropolitan statistical areas 

(MSAs) in the United States (U.S. EPA, 2008b). Nationwide, NO2 concentrations have been 

trending downward, with an overall 30% decrease in concentrations from 1990 to 2006 (U.S. 

EPA, 2008b) as a result of various federal and state NOx emissions-control programs. 

As stated in Chapter 1, the terms “oxides of nitrogen” and “nitrogen oxides” in this 

document refer to all forms of oxidized nitrogen compounds, including NO, NO2, and all other 

oxidized nitrogen-containing compounds transformed from NO and NO2. In the scientific 

community and in terms of the predictions from CMAQ, this definition of oxides of nitrogen is 

referred to as NOy. Thus, we are using CMAQ predictions of NOy in our analysis to characterize 

concentrations of oxides of nitrogen from a national perspective. The spatial field of modelpredicted 2002 annual average NOy concentrations is shown in Figure 3.2-4. 

Final Risk and Exposure Assessment 3-12 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

The patterns in NOy concentrations show some similarity to the general patterns of NOx

emissions shown in Figure 3.2-1. For the most part, highest concentrations are predicted in the 

core portions of urban areas with a relatively large drop in concentrations with distance from the 

location of peak values. The spatial gradients from urban and rural areas appear to be greater in 

the West compared to those in the East. In the West, NOy concentrations outside source areas 

drop off rapidly to below 3 ppb. Annual average concentrations of NOy are predicted to exceed 3 

ppb in rural areas within broad portions of the East. The highest rural concentrations in the East 

extend across portions of the Midwest, Pennsylvania, and along the Northeast Corridor. Annual 

average NOy concentrations exceeding 10 ppb are predicted in portions of the Potomac 

River/Potomac Estuary, Neuse River/Neuse River Estuary, and Mixed Conifer Forest 

(Transverse Range portion) case study areas. The Kane Experimental Forest Case Study Area is 

within the area of regionally high NOy that extends across Pennsylvania. The other case study 

areas (Adirondack, Hubbard Brook Experimental Forest, and Mixed Conifer Forest [Sierra 

Nevada Range portion]) as well as the Rocky Mountains are predicted to have annual average 

NOy concentrations of ~3 ppb or less. 

Final Risk and Exposure Assessment 3-13 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

1 Adirondack

2 Shenandoah

3 Potomac River/Potomac Estuary

4 Neuse River/Neuse Estuary

5 Kane Experimental Forest

6 Hubbard Brook Experimental Forest

7 Mixed Conifer Forest (Transverse Range)

8 Mixed Conifer Forest (Sierra Nevada Range)

9 Rocky Mountain National Park

Figure 3.2-4. Model-predicted annual average NOy concentrations (ppb) for 2002.

3.2.2.2 SO2 Concentrations 

Measured annual average SO2 concentrations for the period 2003 through 2005 are 

presented in Table 2-23 of the ISA (U.S. EPA, 2008b). SO2 concentrations aggregated across 

urban sites and nonurban sites were generally very low at ~4 ppb. Interquartile concentrations 

were in the range of 1 to 6 ppb for urban sites and 1 to 5 ppb for nonurban sites. Urban and nonurban concentrations at the 90th percentile were 8 ppb. In an analysis of 11 cities, sites with the 

highest annual mean SO2 concentrations were in Steubenville, OH (8.6 to 14 ppb), and 

Pittsburgh, PA (6.8 to 12 ppb) (U.S. EPA, 2008b). Both of these cities are in areas with very high 

SO2 emissions from electric generating units. At suburban and rural CASTNET sites, annual 

average SO2 concentrations in 2007 were much higher by far at sites in the East compared to the 

West (U.S. EPA, 2008a). In the East, the highest concentrations were measured across the 

Midwest, Southeast, and mid-Atlantic states. Relatively low concentrations were measured 

across New England. 

Final Risk and Exposure Assessment 3-14 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

The 2002 annual average model-predicted SO2 concentration fields are shown in 

Figure 3.2-5. The model predictions are generally consistent with the magnitude and spatial 

patterns of concentrations from measured data. Peak predicted concentrations, exceeding 10.0 

ppb, coincide with the location of highest emissions (see Figure 3.2-3), with large decreases in 

concentrations with distance from sources. In the East, the localized peak concentrations are 

within a broad area of concentrations exceeding 1.0 ppb. SO2 predictions exceed 3.0 ppb in 

portions of the Midwest, across Pennsylvania, and into the mid-Atlantic states and decline to 

<0.5 ppb in northern Maine. In the West, SO2 predictions are much lower than in the East and 

are generally <0.5 ppb, except in the vicinity of sources of SO2. 

The Potomac River/Potomac Estuary Case Study Area has the highest SO2 predictions 

among the six case study areas in the East. The portion of the Potomac River/Potomac Estuary 

Case Study Area in western Virginia is predicted to have concentrations in the range of 1 to 3 

ppb, which increases to 3 to 5 ppb in Maryland. SO2 concentrations in the Kane Experimental 

Forest, Shenandoah, and Neuse River/Neuse River Estuary case study areas are in the range of 

1.0 to 3.0 ppb, with some locations having up to 3.0 to 5.0 ppb. The Adirondack, Hubbard Brook 

Experimental Forest, Mixed Conifer Forest (Sierra Nevada Range portion) case study areas, as 

well as the Rocky Mountains, all have predicted SO2 concentrations of <1.0 ppb. The portion of 

Mixed Conifer Forest (Transverse Range portion) Case Study Area near the city of Los Angeles 

has predictions exceeding 10.0 ppb. 

Final Risk and Exposure Assessment 3-15 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

1 Adirondack

2 Shenandoah

3 Potomac River/Potomac Estuary

4 Neuse River/Neuse Estuary

5 Kane Experimental Forest

6 Hubbard Brook Experimental Forest

7 Mixed Conifer Forest (Transverse Range)

8 Mixed Conifer Forest (Sierra Nevada Range)

9 Rocky Mountain National Park

Figure 3.2-5. Model-predicted annual average SO2 concentrations (ppb) for 2002.

3.2.3 Nationwide Deposition of Nitrogen and Sulfur 

As noted in Section 3.1 of this report, gaseous and particulate deposition of nitrogen and 

sulfur species to land and water surfaces occurs through both dry deposition and wet deposition 

processes. Additionally, nitrogen deposition is composed of both oxidized and reduced forms of 

total reactive nitrogen. The nationwide analysis of deposition examined the magnitude and 

spatial patterns of total sulfur deposition, total nitrogen deposition, and the oxidized and reduced 

forms of total reactive nitrogen. The analysis of current levels and trends in nitrogen and sulfur 

deposition is based in part on measured data as described in Section 2.10 of the ISA (U.S. EPA, 

2008b). A combination of measured data and model predictions to glean additional information 

on the magnitude and spatial patterns in deposition across the United States were also used. 

3.2.3.1 Approach for Assimilating Measured Data and Model Predictions 

To create spatial fields of deposition, wet deposition measurements from the National 

Atmospheric Deposition Program (NADP) National Trends Network 

Final Risk and Exposure Assessment 3-16 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

(http://nadp.sws.uiuc.edu/nadpoverview.asp) were used. Estimates of dry deposition are 

available from the CASTNET network (http://www.epa.gov/castnet/) (Clarke et al., 1997), but 

these data are calculated based on an “inferential model” involving measured air concentrations 

coupled with species- and location- dependent deposition velocities that reflect local land use 

and meteorological conditions at each monitoring site (U.S. EPA, 2008b). These dry deposition 

estimates may not be representative of dry deposition fluxes in unmonitored areas where land use 

or meteorological conditions are different from those at monitoring sites. Therefore, for the 

nationwide assessment of deposition, dry deposition predictions from the 2002 CMAQ model 

simulation were used because the model has information about meteorology and land use in each 

grid cell of the domain; therefore, it is not restricted to the cleared area nearest to the monitors, as 

is the case for the measurements. Thus annual total 2002 wet deposition from NADP 

measurements, coupled with the 2002 model-predicted dry deposition from CMAQ, were used. 

NADP data are collected at more than 250 locations across the contiguous United States. 

From these points, analysts at the NADP generated continuous surfaces at a 2.5-km grid cell 

resolution by using an inverse distance weighted (IDW) algorithm available at 

http://www.epa.gov/monitor/programs/nadpntn.html. Wet deposition of sulfur was calculated 

from deposition measurements of sulfate (SO4

2-). Oxidized nitrogen wet deposition was 

calculated from measured nitrate (NO3

-

) deposition, and reduced nitrogen wet deposition was 

calculated from measurements of wet ammonium (NH4

+

) deposition. 

The CMAQ data were generated at a 12-km grid cell size and consisted of many 

estimated deposition values, including total dry sulfur, total dry nitrogen, total dry oxidized 

nitrogen, and total dry reduced nitrogen. The oxidized nitrogen species extracted from CMAQ 

are NO3

-

, HNO3, NO, NO2, dinitrogen pentoxide (N2O5), PAN, HONO, and organic nitrates 

(NTR), while the reduced nitrogen species are NH3 and NH4

+

. Both the measured and modeled 

datasets provided deposition values in kg/ha/yr. The NADP data were at a finer spatial 

resolution, and in order to add the two gridded datasets together, the finer NADP dataset was 

resampled up to the 12-km scale of the CMAQ data. Once both datasets were at the same spatial 

resolution, the wet and dry deposition values for each component (e.g., oxidized nitrogen) were 

added together on a grid-cell by grid-cell basis to provide spatial fields of estimated annual total 

(i.e., wet plus dry) deposition across the United States. The combined measured plus modeled 

deposition fields were also used as input for the individual case study ecological modeling 

described in Chapters 4 and 5 and Appendices 4 through 7 of this report. 

Final Risk and Exposure Assessment 3-17 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

3.2.3.2 Nitrogen Deposition 

As noted in the ISA, increasing trends in urbanization, agricultural intensity, and 

industrial expansion during the previous 100 years have produced a nearly ten-fold increase in 

atmospherically deposited nitrogen (U.S. EPA, 2008b). Increased deposition of reduced nitrogen 

in the United States, measured as NH4

+

 deposition, correlates well with the local and regional 

increases in agricultural intensity. Although total reactive nitrogen deposition trends based on a 

sample of 34 NADP sites in the East show an overall decline from deposition levels in 1990, 

more recent trends beginning in the late 1990s have been less consistent (U.S. EPA, 2008b; 

Sickles and Shadwick, 2007a). 

From 2004 to 2006, estimated dry combined with measured wet nitrogen deposition was 

greatest in the Ohio River Valley, specifically in Indiana and Ohio, where there were values as 

high as 9.2 and 9.6 kg N/ha/yr, respectively. Nitrogen deposition was lower at sites in other parts 

of the East, including Florida and in northern New England, where nitrogen deposition was 4.0 

kg N/ha/yr or less. The greatest deposition in the central United States occurred in Kansas and 

Oklahoma, with estimates of 7.0 and 6.5 kg N/ha/yr, respectively. Nitrogen deposition levels 

were much lower in the West where values ranged from ~1.0 to 3.0 kg N/ha/yr. The highest 

deposition in the West (~4.0 to 5.0 kg N/ha/yr) was found at sites near Los Angeles, CA. In most 

areas of the country, measured wet deposition dominates estimated dry deposition in terms of the 

contribution to total deposition. The extent of wet versus dry deposition varies regionally to 

some extent because some western sites have more similar or higher rates of dry versus wet 

deposition than the more humid sites in the East. 

The spatial fields of oxidized nitrogen deposition, reduced nitrogen deposition, and total 

reactive nitrogen deposition across the United States for 2002 are shown in Figures 3.2-6, 3.2-7, 

and 3.2-8, respectively. In general, on a regional basis, both forms of nitrogen deposition are 

much higher in the East compared to the West. Within the eastern United States, there is a broad 

area with oxidized nitrogen deposition of 5.5 kg N/ha/yr or greater that extends from Louisiana 

northeastward across portions of the Southeast and Midwest to the mid-Atlantic region and most 

of New England. This area of elevated oxidized nitrogen deposition roughly corresponds to the 

areas with model-predicted NOx concentrations of 3.0 ppb or greater and, in general, where NOx

emissions are regionally highest. Oxidized nitrogen deposition levels of 7.5 kg N/ha/yr or greater 

are evident in and near NOx source areas and within much of a multistate area from Tennessee 

Final Risk and Exposure Assessment 3-18 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

northeastward to central New England. In the West, oxidized nitrogen deposition is 1.5 kg 

N/ha/yr or less across most of the region, except in urban areas, where NOx emissions are 

highest. 

As shown in Figure 3.2-7, the geographic patterns in reduced nitrogen deposition, 

indicate that the areas of high reduced nitrogen deposition in both the East and West generally 

correspond to areas of high NH3 emissions in each region (see Figure 3.2-2). In the East, 

deposition of reduced nitrogen of 3.5 kg N/ha/yr or greater is seen from central Texas, across the 

eastern Great Plains and the Midwest, to western Pennsylvania and western New York. 

Elsewhere in the East, high levels of reduced nitrogen deposition are found in and near areas of 

livestock/swine/poultry operations. Between these areas of elevated deposition, reduced nitrogen 

deposition levels are generally in the range of 1.5 to 3.5 kg N/ha/yr. In the West, reduced 

nitrogen deposition is <1.5 kg N/ha/yr, except near NH3 emissions source areas, especially the 

Central Valley of California.

The spatial patterns of total reactive nitrogen deposition in Figure 3.2-8 reflect the 

combination of the deposition from the reduced and oxidized nitrogen components. Much of the 

East has total nitrogen deposition of 9 to 14 kg N/ha/yr. Higher amounts of 14 kg N/ha/yr or 

greater cover portions of the Midwest and Northeast, as well as in or near sources of NOx and/or 

NH3 emissions in other parts of the East. In the West, total nitrogen deposition is highest in and 

near NOx and NH3 source areas, particularly those in California, where deposition exceeds 20 kg 

N/ha/yr. In most rural or remote portions of the West, total nitrogen deposition is generally <3 kg 

N/ha/yr. 

Final Risk and Exposure Assessment 3-19 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

8 Mixed Conifer Forest (Transverse Range)

1 Adirondack

2 Shenandoah

3 Potomac River/Potomac Estuary

4 Neuse River/Neuse Estuary

5 Kane Experimental Forest

6 Hubbard Brook Experimental Forest

7 Mixed Conifer Forest (Transverse Range)

8 Mixed Conifer Forest (Sierra Nevada Range)

9 Rocky Mountain National Park

Figure 3.2-6. Total wet plus dry oxidized nitrogen deposition (kg N/ha/yr) in 2002. 

Final Risk and Exposure Assessment 3-20 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Figure 3.2-7. Total wet plus dry reduced nitrogen deposition (kg N/ha/yr) in 2002. 

Final Risk and Exposure Assessment 3-21 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Figure 3.2-8 Total reactive nitrogen deposition (kg N/ha/yr) in 2002. 

3.2.3.3 Sulfur Deposition 

Annual average measured sulfur deposition during 2004 to 2006 was highest in the Ohio 

River Valley. In this region, measured sulfur deposition was 21.3 kg S/ha/yr at one monitoring 

site, and most sites reported 3-year averages >10.0 kg S/ha/yr (U.S. EPA, 2008b). Total sulfur 

deposition measured in the West was relatively low, and generally <2.0 kg S/ha/yr, with many 

sites measuring <1.0 kg S/ha/yr. The primary form of sulfur deposited is wet SO4

2-. Smaller 

contributions to deposition are made by dry SO2 and dry SO4

2-. 

The spatial fields of sulfur across the United States for 2002 are shown in Figure 3.2-9. 

As with the deposition of nitrogen species, sulfur deposition is much higher in the East than the 

West. Sulfur deposition across most of the West is <3.0 kg S/ha/yr. In the East, high levels of 

deposition exceeding 18 kg S/ha/yr are seen in the immediate vicinity of isolated major sources, 

as well as in and near areas having a high concentration of SO2 sources. This is particularly 

Final Risk and Exposure Assessment 3-22 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

notable along the Ohio River Valley, extending across Pennsylvania. The areas of highest 

deposition are within a broad area of sulfur deposition in the range of 6 to 12 kg S/ha/yr, which 

covers much of the East. 

1 Adirondack

2 Shenandoah

3 Potomac River/Potomac Estuary

4 Neuse River/Neuse Estuary

5 Kane Experimental Forest

6 Hubbard Brook Experimental Forest

7 Mixed Conifer Forest (Transverse Range)

8 Mixed Conifer Forest (Sierra Nevada Range)

9 Rocky Mountain National Park

Figure 3.2-9. Total wet and dry sulfur deposition (kg S/ha/yr) in 2002.

3.2.4 Policy-Relevant Background Concentrations 

Policy-relevant background concentrations are those concentrations that would occur in 

the United States in the absence of anthropogenic emissions in the continental North America 

(i.e., United States, Canada, Mexico). These analyses for the current ambient indicators, NO2 and 

SO2, as well as NOy and SOx, are summarized below (U.S. EPA 2008). Note that the analyses for 

the Risk and Exposure Assessment examined the contribution of total reactive nitrogen and 

sulfur above the policy-relevant background concentrations. 

For NO2, policy-relevant background concentrations are <300 parts per trillion (ppt) over 

most of the continental United States and <100 ppt in the eastern United States on an annual 

average basis (U.S. EPA, 2008b). In contrast to the levels associated with policy relevant 

background concentrations, 24-hour ambient NO2 concentrations in urban areas near monitoring 

Final Risk and Exposure Assessment 3-23 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

locations averaged <20 ppb and have a 99 percentile value of <50 ppb. Annual average NO2

concentrations over the continental United States are <5 ppb for nearly all urban, rural, and 

remote sites. According to the ISA (U.S. EPA, 2008b), background SO2 concentrations are <10 

ppt throughout most of the continental United States, except in areas of the Pacific Northwest, 

where natural SO2 sources are particularly strong because of volcanic activity. Maximum policyrelevant background SO2 concentrations are 30 ppt. In general, policy-relevant background 

concentrations of SO2 contribute <1% of current concentrations, except in the Pacific Northwest, 

where policy-relevant background concentrations can contribute up to 80% (U.S. EPA, 2008b). 

The spatial pattern of policy-relevant background NOY (defined in the model as HNO3

+

NH4NO3 + NOX + HO2NO2 +RONO2) in wet and dry deposition shows that the highest values are 

found in the eastern United States in and downwind of the Ohio River Valley. The pattern of 

nitrogen deposition in the PRB simulation shows maximum deposition centered over Texas and 

in the Gulf Coast region, reflecting a combination of nitrogen emissions from lightning in the 

Gulf Coast region, biomass burning in the southeast, and microbial activity in soils with maxima 

in central Texas and Oklahoma. The policy-relevant background contribution to nitrogen 

deposition is <20% over the eastern United States, and typically <50% in the western United 

States, where NOY deposition is already lower. 

Present-day deposition of SOx (SO2 and pSO4) is largest in the Ohio River Valley due to 

coal-burning power plants in that region, while background deposition is typically at least an 

order of magnitude smaller. Over the eastern United States, the predicted background 

contribution to SOx deposition was <10%, and even smaller, <1%, where present-day SOx

deposition was highest. The predicted contribution of policy-relevant background to sulfur 

deposition was highest in the western United States at >20% because of the geothermal sources 

of SO2 and oxidation of dimethyl sulfide at the water surface of the eastern Pacific. In summary, 

the PRB contribution to NOx and SOx concentrations and deposition over the continental United 

States. is very small, except for SO2 in areas with volcanic activity. 

3.2.5 Non-atmospheric Loadings of Nitrogen and Sulfur 

Not all loadings of nitrogen and sulfur compounds to ecosystems are due to atmospheric 

deposition. Other inputs, such as runoff from agricultural soils to waterbodies and point-source 

discharges, also contribute to acidification and nutrient enrichment. This assessment examines 

the atmospheric contribution due to total reactive nitrogen and sulfur, recognizing that some 

Final Risk and Exposure Assessment 3-24 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-25 September 2009 

systems may be solely impacted by atmospheric deposition, while effects in other systems might 

be largely due to non-atmospheric sources. This source distinction will play an important role in 

the standard-setting process. 

3.3 SPATIAL AND TEMPORAL CHARACTERIZATION OF 

DEPOSITION FOR CASE STUDY AREAS 

3.3.1 Purpose and Intent 

The purpose of this section is to describe the spatial and temporal patterns of total 

reactive nitrogen and sulfur deposition for the eight case study areas and the Rocky Mountain 

National Park supplemental study area. These areas are shown on the map in Figure 2.1-1. This 

analysis focused on the magnitude, spatial gradients, and the intra-annual (i.e., seasonal) and 

inter-annual (i.e., between 2002–2005) variation in nitrogen and sulfur deposition for each of 

these case study areas. In addition to improving the overall understanding of the spatial and 

temporal behavior of nitrogen and sulfur deposition, the results and findings of this analysis are 

intended to provide information on the case study areas about (1) the relative portion of total 

nitrogen deposition that is in the form of oxidized versus reduced nitrogen, and (2) the relative 

amounts of wet versus dry deposition of nitrogen and sulfur. 

These analyses are intended to aid in understanding the characteristic patterns of 

deposition in the case study areas and their current contribution to negative ecological effects. It 

is beyond the scope of this analysis to fully explain the characteristics revealed by the modeled 

and measured deposition and concentrations. Further exploration of these relationships and 

interactions should be the subject of future research efforts. 

3.3.2 Data and Analytical Techniques 

As previously discussed, both measured data and model predictions for the analyses were 

used in this assessment. The measured data include wet deposition of nitrogen and sulfur, as 

calculated from NO3

-

, NH4

+

, and SO4

2- wet deposition samples collected at NADP sites during 

the period 2002 through 2005. These wet deposition data are available as annual totals for each 

of the years 2002 through 2005 as spatial fields of gridded data at 12 × 12 km resolution for the 

continental United States. The CMAQ8 model predictions include wet and dry deposition of 

 

8 The CMAQ applications are described in detail in Appendix 1 of this report. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-26 September 2009 

nitrogen and sulfur from applications of CMAQ over this same time period. The hourly model 

predictions were aggregated to seasonal and annual time periods, as needed, for this assessment. 

For 2002, CMAQ predictions were at a resolution of 12 km for the continental United 

States9. These 2002 model predictions are based on model runs with CMAQ v4.6. The dry 

deposition predictions for 2002 from CMAQ v4.6 were coupled with the 2002 NADP wet 

deposition data to provide annual total reactive nitrogen and annual total sulfur deposition for 

input to the aquatic and terrestrial ecosystem modeling analyses described in Chapters 4 and 5 of 

this report. In October 2008, the EPA Office of Research and Development (ORD) released an 

updated version of CMAQ (CMAQ v4.7) and an updated version of CMAQ’s meteorological 

preprocessor (MCIPv3.4)10. Recently, the EPA ORD used the updated versions of CMAQ and 

Meteorology-Chemistry Interface Processor (MCIP) to remodel 2002 deposition and to model 

2003, 2004, and 2005 deposition. These 2002 through 2005 CMAQ runs were performed at 12-

km resolution for the East11 and at 36-km resolution for the West. This Risk and Exposure 

Assessment uses both sets of CMAQ runs. The CMAQ v4.6 2002 predictions are used in the 

analyses to characterize the magnitude, relative amounts, and spatial gradients in deposition 

within each case study area, as well as to examine the seasonal variability in deposition for 2002. 

The predictions for 2002 through 2005 from CMAQv4.7 were used as a consistent set of 

estimates to assess inter-annual variability in deposition and to determine whether the magnitude 

and relative amounts of deposition in 2002 are representative of conditions over the longer-term, 

4-year time period. A comparison of the two sets of 2002 CMAQ predictions is presented as part 

of the discussion on uncertainties in Section 3.5 of this report. 

In general, the case study analyses rely upon a combination of NADP-measured wet 

deposition and CMAQ (v4.6 or v4.7) dry deposition, with one exception. CMAQ predictions of 

both wet and dry deposition were used in the analysis of seasonal variations because gridded wet 

deposition data from NADP are not available at a subannual temporal resolution. 

 

9 The CMAQ modeling domains are shown in Figure 1 of Appendix 1 of this report. 

10 The scientific updates in CMAQ v4.7 and MCIP v3.4 can be found at the following web links: 

http://www.cmascenter.org/help/model_docs/cmaq/4.7/RELEASE_NOTES.txt 

http://www.cmascenter.org/help/model_docs/mcip/3.4/ReleaseNotes 

11 The 99° west meridian to separate the eastern and western United States was used in this assessment. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-27 September 2009 

3.3.2.1 Spatial Allocation of Gridded Data to Case Study Areas 

The gridded measured and modeled data were linked to the case study areas using several 

geographic information systems (GIS)–based techniques that differ depending on the geographic 

definition of each area, as follows12. The Potomac River/Potomac Estuary Case Study Area and 

Neuse River/Neuse River Estuary Case Study Area include contiguous watersheds that are 

defined in terms of 8-digit Hydrologic Unit Codes13 (HUCs). For these two areas, GIS was used 

to calculate the spatially weighted average deposition for each of these areas as a whole. The 

Adirondack Case Study Area includes individual noncontiguous watersheds14 that contain the 

lakes/ponds selected for ecological modeling as part of the aquatic acidification analysis (see 

Chapter 4 of this report). Similarly, the Shenandoah Case Study Area includes those 

watersheds15 containing the streams selected for ecological modeling. For the Adirondack and 

Shenandoah case study areas, individual grid cells were linked to each watershed if any part of 

the grid cell touched a portion of a watershed in the area. The Hubbard Brook Experimental 

Forest, Kane Experimental Forest, and Mixed Conifer Forest (Transverse Range and Sierra 

Nevada Range) case study areas, as well as the Rocky Mountain National Park, do not contain 

finer geographic elements. For these areas, GIS was used to calculate the spatially weighted 

average deposition for each area as a whole. 

3.3.3 Characterization of Deposition in Case Study Areas 

The characterizations of nitrogen and sulfur deposition for each case study area are 

discussed in this section as follows: 

 Overall area-wide magnitude of deposition in 2002 

 Variation in annual total deposition between 2002 through 2005 

 Relative amount of wet and dry, oxidized, and reduced nitrogen to total reactive nitrogen 

deposition and wet and dry to total sulfur deposition in 2002 

 Geographic variations in annual deposition for 2002 within and near the case study areas 

 

12 The number of 12 km grid cells assigned to each case study area as a result of this process is as follows: 

Adirondacks – 141; Shenandoah – 78; Potomac River/Potomac Estuary – 325; Neuse River/Neuse River Estuary 

– 136; Kane Experimental Forest – 2; Hubbard Brook Experimental Forest – 2; Rocky Mountain National Park – 

1; Transverse Range – 297; Sierra Nevada Range – 554. 

13These codes are used to identify the drainage basins within the United States. See 

http://imnh.isu.edu/digitalatlas/hydr/huc/huctxt.htm for additional information on HUCs. 

14 The Adirondack watersheds are defined by 10-digit HUCs. 

15 The Shenandoah watersheds are defined by 12-digit HUCs. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-28 September 2009 

 Seasonal variations in each component of deposition for 2002. 

The table and figures that provide and display the data used for this analysis are identified 

below. For ease of reference, the table and figures are provided at the end of each subsection. 

The modeled plus measured annual total reactive nitrogen and sulfur depositions for 2002 

for each case study area, as a whole, are presented in Table 3.3-1. The inter-annual variations in 

total reactive nitrogen deposition from 2002 through 2005 are shown in Figures 3.3-1a and 3.3-

1b for each case study area in the East and West. The relative amounts of oxidized versus 

reduced nitrogen deposition for each case study area in 2002 are shown in Figure 3.3-2. The 

relative amounts of wet and dry, oxidized, and reduced nitrogen deposition for 2002 are shown 

in Figures 3.3-3(a–i). The spatial patterns in annual nitrogen depositions for 2002 are shown in 

Figures 3.3-4(a–e) for the East and in Figures 3.3-5(a–c) for the West. The seasonal variations 

in total reactive nitrogen deposition for each case study area are shown in Figures 3.3-6(a–i). 

The seasonal data are presented in terms of the percentage of annual deposition that occurs in 

each season16. For wet and dry, oxidized and reduced nitrogen deposition seasonal variations are 

shown in Figures 3.3-7(a–i), along with the seasonal variation in precipitation. Seasonal patterns 

of NH3 emissions are shown in Figure 3.3-8. 

The annual total sulfur deposition from 2002 through 2005 is shown in Figures 3.3-9 

(a and b) for each case study area in the East and West. The relative amounts of wet and dry 

sulfur deposition in 2002 and, on average, for the period 2002 through 2005 are shown in 

Figures 3.3-10 and 3.3-11. The spatial patterns in annual sulfur deposition for 2002 are shown 

in Figures 3.3-12(a–c) for the East and in Figure 3.3-13 for the West. The seasonal variation in 

total sulfur deposition for each case study area is shown in Figures 3.3-14(a–i). Wet and dry 

sulfur deposition seasonal variations are shown in Figures 3.3-15(a–i). 

 

16 For the purposes of this analysis, data for December, January, and February 2002 were included in “winter;”; data 

for March, April, and May 2002 were included in “spring;” data for June, July, and August 2002 were included in 

“summer;” and data for September, October, and November 2002 were included in “fall.” Thus, data for 

December 2002 were included with data for January and February of this same year. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-29 September 2009 

3.3.3.1 Magnitude of Total Reactive Nitrogen Deposition in 2002 and Analysis of 

Inter-annual Variability17 

The amount of total reactive nitrogen deposition in 2002 varies among the case study 

areas (see Table 3.3-1). In the East, total reactive nitrogen deposition ranges from 8 kg N/ha/yr 

for the Hubbard Brook Experimental Forest Case Study Area up to 14 kg N/ha/yr for the Neuse 

River/Neuse River Estuary Case Study Area. Total reactive nitrogen deposition in 2002 is also 

high in the Transverse Range portion of the Mixed Conifer Forest Case Study Area (10 kg 

N/ha/yr), which reflects the high levels of NOx emissions in and around the Los Angeles urban 

area. The Sierra Nevada Range portion of the Mixed Conifer Forest Case Study Area, as well as 

the Rocky Mountain National Park, have very low amounts of nitrogen deposition (4 kg N/ha/yr 

for each location), which is consistent with the low amounts of NOx emissions near these areas. 

Annual total reactive nitrogen depositions varied by 1 to 3 kg N/ha/yr or less in 

individual case study areas from 2002 through 2005 (see Figures 3.3-1a and 3.3-1b). There is 

some evidence of a decline in deposition during this 4-year time period for the six case study 

areas in the East. No definitive trend18 is evident for the case study areas in the West. Since the 

negative effects of nitrogen deposition on sensitive ecosystems may be the result of long-term 

exposures, recent trends in measured deposition were examined to determine how the amounts of 

deposition in the 2002 analysis year relate to current conditions over a longer time period. As 

described in Section 3-2, analyses by CASTNET for an aggregate of 34 sites in the East indicates 

that dry nitrogen deposition has shown a general decline overall since 2002, but the annual 

concentration of nitrogen in precipitation has remained fairly steady over this time period (U.S. 

EPA, 2009). In general, inter-annual variations in meteorology and emissions lead to interannual variations in concentrations and deposition. 

In this section, information available from the NADP National Trends Network19 on 

nitrogen deposition for those sites located in and/or near each case study area is examined. To be 

included in this analysis, the site had to have valid measurements in 2002, as determined by 

 

17 Slight differences between the deposition reported in Table 3.3-1 versus what is shown in Figure 3.3-1a and b are 

due to the use of different versions of CMAQ, as described above in Section 3.3.2. 

18 In this analysis, we use the term “trend” to refer to the overall temporal signal (i.e., increase or decrease) in 

deposition for a particular time period. It is not the intent of this analysis to ascribe any statistical significance to 

the characterization of long-term trends in deposition at any individual location. 

19 See http://nadp.sws.uiuc.edu/sites/ntnmap.asp? 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-30 September 2009 

NADP completeness criteria20. The charts showing annual deposition for sites selected for this 

analysis are provided in Appendix 2 of this report. The level of measured annual total wet 

deposition in 2002 at each site was compared to the amount of deposition in other years over the 

most recent 10 years (i.e., 1998 through 2007)21. The trend information indicates that overall, for 

each case study area, the amount of nitrogen deposition in 2002 is generally representative of 

current conditions. 

However, deposition trends can vary from site to site, even within a case study area22. 

This is most notable for the two sites in the Adirondack Case Study Area and the three sites in 

the Potomac River/Potomac Estuary Case Study Area. In the Adirondack Case Study Area, the 

data from the Huntington Wildlife Forest site indicates that wet nitrogen deposition in 2002 is 

within the range of values measured during other years over the most recent 10-year period. Data 

from the Whiteface site shows that wet nitrogen deposition in 2002 was high compared to that in 

other years. The data at both sites show a downward pattern to 2006, with nitrogen deposition 

increasing again in 2007. For the Potomac River/Potomac Estuary Case Study Area, the trends in 

wet nitrogen deposition at the Arendtsville, PA, and Parsons, WV, sites indicate that the amount 

of deposition in 2002 is similar to that from 1998 through 2007. The Wye, MD, site on the 

Eastern Shore of Maryland shows large inter-annual variations compared to the other sites in the 

Potomac River/Potomac Estuary Case Study Area and that wet nitrogen deposition in 2002 was 

on the low end of the range over this time period. In 2002, wet nitrogen deposition for both 

Sierra Nevada Range portion of the Mixed Conifer Forest Case Study Area, as well as the Rocky 

Mountain National Park, were within the range of values measured from 1998 through 2007. For 

the Transverse Range portion of the Mixed Conifer Forest Case Study Area, wet nitrogen 

deposition was near the low end of the range of values for this period. It is beyond the scope of 

this analysis to determine the reasons for these differences other than to note that local terraininduced meteorological conditions and differential source-receptor relationships across a case 

study area may contribute to the differences noted in deposition trends. 

 

20 See http://nadp.sws.uiuc.edu/documentation/completeness.asp 21 Some sites do not have historical data back to 1998. For these sites, the amounts of deposition for the available 

data record were examined. 

22 See http://nadp.sws.uiuc.edu/sites/ntnmap.asp? for the location of NADP sites across. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Table 3.3-1. Annual Total Reactive Nitrogen Deposition (kg N/ha/yr) and Sulfur Deposition 

(kg S/ha/yr) in 2002 for Each Case Study Area, as Well as the Rocky Mountain National Park. 

Case Study Areasa

2002 Annual Total Deposition 

Total Reactive Nitrogen 

(kg N/ha/yr)

Total Sulfur 

(kg S/ha/yr) 

Adirondack 10 9 

Hubbard Brook Experimental Forest 8 7 

Kane Experimental Forest 13 20 

Potomac River/Potomac Estuary 12 14 

Shenandoah 11 11 

Neuse River/Neuse River Estuary 14 8 

Mixed Conifer Forest 

(Sierra Nevada Range portion) 4 1 

Mixed Conifer Forest 

(Transverse Range portion) 10 2 

Rocky Mountain National Park 

(a supplemental area) 4 1 a Excludes the Coastal Sage Scrub Case Study Area. 

Annual Total Reactive Nitrogen Deposition: 2002 - 2005

0

5

10

15

20

25

2002

2003

2004

2005

2002

2003

2004

2005

2002

2003

2004

2005

2002

2003

2004

2005

2002

2003

2004

2005

2002

2003

2004

2005

Nitrogen Deposition (kg/ha-yr)

Neuse 

River 

Kane 

Forest 

Potomac 

River 

Shenandoah Adirondack Hubbard 

Brook 

Figure 3.3-1a. Annual total reactive nitrogen deposition (kg N/ha/yr) from 2002 

through 2005 for each case study area in the East. 

Final Risk and Exposure Assessment 3-31 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Transverse 

Range 

Sierra Nevada 

Range 

Rocky Mountain 

National Park 

Annual Total Reactive Nitrogen Deposition: 2002 - 2005

0

5

10

15

20

25

2002

2003

2004

2005

2002

2003

2004

2005

2002

2003

2004

2005

Nitrogen Deposition (kg/ha-yr)

Figure 3.3-1b. Annual total reactive nitrogen deposition (kg N/ha/yr) from 2002 

through 2005 for case study areas in the West, and the Rocky Mountain National 

Park. 

3.3.3.2 Relative Amount of Oxidized and Reduced, Wet, and Dry Nitrogen Deposition 

The relative amounts of oxidized and reduced nitrogen deposition in 2002 for each case 

study area, as well as the Rocky Mountain National Park, are shown in Figure 3.3-2. Oxidized 

nitrogen deposition is the dominant contributor to total reactive nitrogen deposition in nearly all 

of the case study areas. This is consistent with the relative amount of emissions of NOx and NH3. 

As indicated by comparing Figures 3.2-2 and 3.2-3, NOx emissions are much greater and more 

widespread compared to emissions of NH3, which are more local in nature. 

In the Mixed Conifer Forest (Transverse Range portion), Hubbard Brook Experimental 

Forest, Kane Experimental Forest, and Adirondack case study areas, oxidized nitrogen comprises 

70% or more of the total reactive nitrogen. Oxidized nitrogen is 66% to 67% of total reactive 

nitrogen deposition in the Shenandoah, Potomac River/Potomac Estuary case study areas as well 

as the Rocky Mountain National Park. In the Neuse River/Neuse River Estuary Case Study Area, 

reduced nitrogen deposition is >50% of total reactive nitrogen. These findings are consistent with 

the relative magnitude and geographic distribution of NOx emissions compared with NH3

emissions, as described above in Section 3.2.1. The relative amount of oxidized versus reduced 

nitrogen deposition in an area depends on the proximity of the area to local sources of NH3. For 

example, certain portions of the Neuse River/Neuse River Estuary Case Study Area contain high 

Final Risk and Exposure Assessment 3-32 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

NH3 emissions from hog farm operations, and this area, as a whole, has the largest relative 

amount of reduced nitrogen deposition. In contrast, the Hubbard Brook Experimental Forest, 

Kane Experimental Forest, and Adirondack case study areas are distant from sources of high 

NH3 emissions, and they each have a low relative amount of reduced nitrogen deposition. 

The relative amounts of wet and dry, oxidized, and reduced nitrogen for 2002 are shown 

for each case study area in Figures 3.3-3(a–i). The relative amounts of total reactive nitrogen 

deposition based on average deposition for the period 2002 through 2005 are shown in Appendix 

3 of this report. The relative amounts of total reactive nitrogen deposition in 2002 are indicative 

of conditions over the 4-year period. Looking at the relative amounts of total reactive nitrogen 

deposition for individual case study areas in the East indicates similar distributions of deposition 

for several areas. In the Adirondack, Hubbard Brook Experimental Forest, and Kane 

Experimental Forest case study areas, the relative amount of oxidized nitrogen is about evenly 

split between wet and dry deposition, whereas the vast majority of reduced nitrogen occurs 

through wet deposition. In contrast, in the Potomac River/Potomac Estuary and Shenandoah case 

study areas, dry deposition dominates wet deposition for oxidized nitrogen (~65% of oxidized 

nitrogen is dry deposited versus 35% wet deposited). However, in these two areas, wet 

deposition of reduced nitrogen is only slightly greater than dry reduced nitrogen deposition. The 

Neuse River/Neuse River Estuary Case Study Area is somewhat unique among the case study 

areas because of the high levels of local NH3 emissions, which result in a relatively large amount 

of dry reduced nitrogen deposition compared to the other case study areas in the East. For the 

two case study areas in the West and the Rocky Mountain National Park, a common feature in 

the relative amount of nitrogen deposition is that dry oxidized nitrogen is the largest of the four 

components of total reactive nitrogen deposition at all three of these areas. 

Final Risk and Exposure Assessment 3-33 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Relative Amount of Oxidized vs Reduced Nitrogen

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Transverse Range

Hubbard Brook

Kane Forest

Adirondacks

Rocky Mtn

Potomac River

Shenandoah

Sierra Nevada

Neuse River

Percent of Total Reactive Nitrogen

Oxidized N Reduced N

Figure 3.3-2. Relative amounts of oxidized and reduced nitrogen deposition in 

2002 for case study areas and the Rocky Mountain National Park. 

Adirondack Area: 2002 Nitrogen Deposition

Ox N - Dry

32%

Ox N - Wet

38%

Re N - Wet

24%

Re N - Dry

6%

Adirondack Case Study Area: 2002 Total Reactive Nitrogen Deposition 

Figure 3.3-3a. Components of total reactive nitrogen deposition for 2002 in the 

Adirondack Case Study Area.

Final Risk and Exposure Assessment 3-34 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Hubbard Brook: 2002 Nitrogen Deposition

Ox N - Dry

38%

Ox N - Wet

35%

Re N - Wet

21%

Re N - Dry

6%

Hubbard Brook Experimental Forest Case Study Area: 2002 Total Reactive Nitrogen Deposition

Figure 3.3-3b. Components of total reactive nitrogen deposition for 2002 in the 

Hubbard Brook Experimental Forest Case Study Area. 

Kane Forest: 2002 Nitrogen Deposition

Ox N - Dry

40%

Ox N - Wet

34%

Re N - Wet

22%

Re N - Dry

4%

Kane Experimental Forest Case Study Area: 2002 Total Reactive Nitrogen Deposition

Figure 3.3-3c. Components of total reactive nitrogen deposition for 2002 in the 

Kane Experimental Forest Case Study Area. 

Final Risk and Exposure Assessment 3-35 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Neuse River: 2002 Nitrogen Deposition

Ox N - Dry

29%

Ox N - Wet

16%

Re N - Wet

17%

Re N - Dry

38%

Neuse River/Neuse River Estuary Case Study Area: 2002 Total Reactive Nitrogen Deposition

Figure 3.3-3d. Components of total reactive nitrogen deposition for 2002 in the 

Neuse River/Neuse River Estuary Case Study Area.

Potomac River: 2002 Nitrogen Deposition

Ox N - Dry

44%

Ox N - Wet

23%

Re N - Wet

18%

Re N - Dry

15%

Potomac River/Potomac Estuary Case Study Area: 2002 Total Reactive Nitrogen Deposition

Figure 3.3-3e. Components of total reactive nitrogen deposition for 2002 in the 

Potomac River/Potomac Estuary Case Study Area. 

Final Risk and Exposure Assessment 3-36 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Shenandoah Mtns: 2002 Nitrogen Deposition

Ox N - Dry

43%

Ox N - Wet

23%

Re N - Wet

18%

Re N - Dry

16%

Shenandoah Case Study Area: 2002 Total Reactive Nitrogen Deposition

Figure 3.3-3f. Components of total reactive nitrogen deposition for 2002 in the 

Shenandoah Case Study Area. 

Rocky Mtn NP: 2002 Nitrogen Deposition

Ox N - Dry

42%

Ox N - Wet

25%

Re N - Wet

23%

Re N - Dry

10%

Rocky Mountain National Park: 2002 Total Reactive Nitrogen Deposition

Figure 3.3-3g. Components of total reactive nitrogen deposition for 2002 in the 

Rocky Mountain National Park. 

Final Risk and Exposure Assessment 3-37 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Sierra Nevada Range: 2002 Nitrogen Deposition

Ox N - Dry

43%

Ox N - Wet

14%

Re N - Wet

24%

Re N - Dry

19%

Mixed Conifer Forest (Sierra Nevada Range) Case Study Area: 2002 Total Reactive Nitrogen Deposition

Figure 3.3-3h. Components of total reactive nitrogen deposition for 2002 in the 

Sierra Nevada Range portion of the Mixed Conifer Forest Case Study Area. 

Transverse Range: 2002 Nitrogen Deposition

Ox N - Dry

75%

Ox N - Wet

4%

Re N - Wet

5%

Re N - Dry

16%

Mixed Conifer Forest (Transverse Range) Case Study Area: 2002 Total Reactive Nitrogen Deposition

 

Figure 3.3-3i. Components of total reactive nitrogen deposition for 2002 in the 

Transverse Range portion of the Mixed Conifer Forest Case Study Area. 

Final Risk and Exposure Assessment 3-38 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-39 September 2009 

3.3.3.3 Geographic Variations in Annual Total Reactive Nitrogen Deposition for 

200223

The geographic variations in total reactive, oxidized, reduced, wet, and dry nitrogen 

deposition in 2002 are shown in Figures 3.3-4(a–e) for the case study areas in the East24. 

Figures 3.3-5(a–c) shows the geographic variations in total reactive nitrogen deposition and 

oxidized and reduced nitrogen deposition for the West25. 

Adirondack Case Study Area 

As shown in Figure 3.3-4a, total reactive nitrogen deposition in 2002 decreases from 

southwest to northeast across the Adirondack Case Study Area. For example, total reactive 

nitrogen deposition is >12 kg N/ha/yr in the southwestern portion of the Adirondack Case Study 

Area compared to <8 kg N/ha/yr in some parts of the eastern portion of this area. By comparing 

the oxidized nitrogen deposition map in Figure 3.3-4b to the reduced nitrogen deposition map in 

Figure 3.3-4c, it is evident that oxidized nitrogen deposition is much greater than reduced 

nitrogen across the entire case study area. Oxidized nitrogen values are generally in the range of 

5 to 7 kg N/ha/yr, with values of 7 to 9 kg N/ha/yr in the southwestern part of the area. In 

contrast, reduced nitrogen deposition is generally 2 to 3 kg N/ha/yr. From Figure 3.3-4a, it is 

evident that the relatively high total reactive nitrogen deposition in the far southwestern portion 

of this case study area is part of a broad area of high nitrogen deposition that stretches westward 

from the Adirondack Case Study Area along the southern shore of Lake Ontario toward western 

Pennsylvania and Ohio. 

The spatial patterns in wet and dry nitrogen are shown in Figure 3.3-4d and

Figure 3.3-4e, respectively. Wet deposition is in the range of 5 to 7 kg N/ha/yr across the region, 

with higher amounts in the southwestern section. Dry deposition is lower than wet deposition 

overall and declines fairly rapidly from values of 4 to 5 kg N/ha/yr in the western portion to 2 to 

3 kg N/ha/yr in the eastern portion. 

 

23 Note that an analysis of the spatial gradients in reactive nitrogen and sulfur deposition for the Kane Experimental 

Forest and Hubbard Brook Experimental Forest case study areas, as well as the Rocky Mountain National Park is 

not included because the size of each of these areas is small relative to the 12 x 12-km resolution-measured data 

and model predictions used in this analysis. 

24 Deposition in all of the figures is displayed at a resolution of 12 x 12 km to be consistent with the aggregated wet 

and dry deposition data sets described above. 

25 Because of the highly rugged terrain in the case study areas of the West, there is less confidence that the 12-km 

data represents the true geographic variations in deposition. This is particularly true for wet deposition, which is 

based on spatial interpolation from a relatively sparse monitoring network. Thus, a discussion of the geographic 

variations in wet and dry deposition for the case study areas in the West is not included. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Shenandoah Case Study Area 

As shown in Figure 3.3-4a, total reactive nitrogen deposition in the southern portion of 

the Shenandoah Case Study Area is in the range of 8 to 10 kg N/ha/yr, increasing to >14 kg 

N/ha/yr for the northern portions. Oxidized nitrogen ranges from 5 to 9 kg N/ha/yr, which is 

greater than the reduced nitrogen deposition in most of this area. However, the highest levels of 

nitrogen deposition found in the northern portion are mostly due to reduced nitrogen deposition, 

which can be seen by comparing Figure 3.3-4b with Figure 3.3-4c. The higher reduced nitrogen 

deposition (>9 kg N/ha/yr) is largely the result of high NH3 emissions in this northern portion of 

this case study area, as shown in Figure 3.2-3. These NH3 emissions are associated with poultry 

farm operations in this general location. Elsewhere across the Shenandoah Case Study Area, 

reduced nitrogen deposition is in the range of 2 to 3 kg N/ha/yr. 

Over most of the Shenandoah Case Study Area, wet nitrogen deposition in 2002 is in the 

range of 4 to 5 kg N/ha/yr, with lower amounts of 3 to 4 kg N/ha/yr in parts of the southern 

portion of this area. In contrast, dry nitrogen deposition exhibits a peak of relatively high NH3

emissions in the northern portion of the area. There, the amount of dry nitrogen deposition is 14 

kg N/ha/yr or greater. 

Potomac River/Potomac Estuary Case Study Area 

As shown in Figure 3.3-4a, there are large spatial variations in annual total reactive 

nitrogen deposition across the Potomac River/Potomac Estuary Case Study Area. The highest 

levels of total reactive nitrogen deposition in 2002 are seen in the portion of this area over 

northwestern Virginia and from southern Pennsylvania to the Baltimore-Washington, DC, 

metropolitan area. In these portions of this case study area, annual total reactive nitrogen 

deposition exceeds 14 kg N/ha/yr. Between these areas of high deposition, total reactive nitrogen 

deposition declines to the general range of 10 to 12 kg N/ha/yr. 

The spatial patterns in oxidized and reduced nitrogen deposition are shown in 

Figures 3.3-4b and 3.3-4c. From these figures, it is clear that oxidized nitrogen deposition is 

greater that reduced nitrogen deposition across most of this case study area. Oxidized nitrogen 

deposition is in the range of 9 to 14 kg N/ha/yr in and near the Baltimore-Washington, DC, urban 

area. Oxidized nitrogen levels decline from east to west across the remainder of this case study 

area down to the range of 5 to 7 kg N/ha/yr over the western portions of this area. The localized 

high levels of reduced nitrogen deposition correspond to the locations of high NH3 emissions, as 

Final Risk and Exposure Assessment 3-40 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

shown in Figure 3.2-3. Elsewhere in this case study area, reduced nitrogen deposition is fairly 

low, mostly in the range of 3 to 4 kg N/ha/yr. 

The patterns of wet nitrogen deposition in the Potomac River/Potomac Estuary Case 

Study Area indicate that in 2002, the northern portion of this area had higher amounts of wet 

nitrogen deposition (5 to 7 kg N/ha/yr) compared with the southern portion (4 to 5 kg N/ha/yr). 

Dry deposition was highest in the vicinity of the high NH3 emissions in the far southwestern 

portion of this area. Relatively large amounts of dry nitrogen deposition are also seen in the 

eastern half of this area. Considering the spatial distribution of NOx and NH3 emissions in and 

near the Potomac River, it appears that NH3 emissions from livestock farms in south-central 

Pennsylvania may be contributing to the higher amounts of dry nitrogen deposition close to the 

Maryland-Pennsylvania border. In contrast, the high NOx emissions near the Washington, DC, 

area may be contributing to the relatively high dry nitrogen deposition in this part of the Potomac 

River/Potomac Estuary Case Study Area. 

Neuse River/Neuse River Estuary Case Study Area 

The central portions of the Neuse River/Neuse River Estuary Case Study Area are 

impacted by high amounts of total reactive nitrogen deposition in amounts >20 kg N/ha/yr (see 

Figure 3.3-4a). These high levels of deposition are associated with high NH3 emissions from 

swine and poultry production facilities in the southeastern part of North Carolina (see Figure 

3.2-3). In contrast to the large spatial gradients seen in reduced nitrogen deposition, oxidized 

nitrogen deposition is fairly homogenous across this case study area. Most of the area has 

oxidized nitrogen deposition in the range of 5 to 7 kg N/ha/yr, which increases to 7 to 9 kg 

N/ha/yr near the Raleigh-Durham urban area. 

Wet and dry nitrogen deposition in the Neuse River/Neuse River Estuary Case Study 

Area show similar patterns in that the highest amounts of deposition are in the vicinity of high 

NH3 emissions near the central portion of this area. The lowest amounts of wet and dry nitrogen 

deposition are near the coast. 

Sierra Nevada Range (a Portion of the Mixed Conifer Forest Case Study Area) 

As seen from Figure 3.3-5a, there is a west to east gradient in total reactive nitrogen 

deposition across the Sierra Nevada Range portion of the Mixed Conifer Forest Case Study Area. 

In the extreme western portion of this area, which is near the San Joaquin Valley, total reactive 

nitrogen depositions are in the range of 6 to 8 kg N/ha/yr. Total reactive nitrogen deposition 

Final Risk and Exposure Assessment 3-41 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

declines to the range of 2 to 3 kg N/ha/yr in the eastern half of this case study area. Both 

oxidized and reduced nitrogen deposition exhibit similar west to east gradient in deposition as 

seen in Figures 3.3-5b and 3.3-5c. 

Transverse Range (a Portion of the Mixed Conifer Forest Case Study Area) 

High amounts of total reactive nitrogen deposition are evident across much of the 

Transverse Range portion of the Mixed Conifer Forest Case Study Area as evident in Figure 

3.3-5a. This figure shows total reactive nitrogen deposition levels of 12 kg N/ha/yr or greater 

over portions of the San Bernardino Mountains to the west and northwest of the Los Angeles 

urban area. As indicated above, oxidized nitrogen deposition is much greater than reduced 

nitrogen deposition throughout nearly all of this case study area. The large amounts of oxidized 

nitrogen deposition are associated with the high levels of NOx emissions in this portion of 

southern California, as seen in Figure 3.2-2. 

Final Risk and Exposure Assessment 3-42 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Figure 3.3-4a. Annual total dry plus wet reactive nitrogen deposition (kg N/ha/yr) 

in 2002 for the case study areas in the East. 

Final Risk and Exposure Assessment 3-43 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Figure 3.3-4b. Annual total dry plus wet oxidized nitrogen deposition (kg 

N/ha/yr) in 2002 for the case study areas in the East. 

Final Risk and Exposure Assessment 3-44 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Figure 3.3-4c. Annual total dry plus wet reduced nitrogen deposition (kg N/ha/yr) 

in 2002 for the case study areas in the East. 

Final Risk and Exposure Assessment 3-45 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Figure 3.3-4d. Annual total wet reactive nitrogen deposition (kg N/ha/yr) in 2002 

for the case study areas in the East.

Final Risk and Exposure Assessment 3-46 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Figure 3.3-4e. Annual total dry reactive nitrogen deposition (kg N/ha/yr) in 2002 

for the case study areas in the East. 

Final Risk and Exposure Assessment 3-47 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Mixed Conifer Forest (Transverse Range) 

Figure 3.3-5a. Annual total dry plus wet reactive nitrogen deposition (kg N/ha/yr) 

in 2002 for case study areas and Rocky Mountain National Park in the West.

Final Risk and Exposure Assessment 3-48 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Mixed Conifer Forest (Transverse Range) 

Figure 3.3-5b. Annual total dry plus wet oxidized nitrogen deposition (kg N/ha/yr) 

in 2002 for case study areas and Rocky Mountain National Park in the West. 

Final Risk and Exposure Assessment 3-49 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Mixed Conifer Forest (Transverse Range) 

Figure 3.3-5c. Annual total dry plus wet reduced nitrogen deposition (kg N/ha/yr) 

in 2002 for case study areas and Rocky Mountain National Park in the West.

Final Risk and Exposure Assessment 3-50 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-51 September 2009 

3.3.3.4 Seasonal Variations in Total Reactive Nitrogen Deposition for 2002 

The seasonal variations in model-predicted 2002 total reactive nitrogen deposition for 

each case study area are shown in Figures 3.3-6(a–i). In most of the case study areas, total 

reactive nitrogen is highest in spring or summer. Among the case study areas in the East, total 

reactive nitrogen is highest in spring for the Adirondack, Hubbard Brook Experimental Forest, 

and Kane Experimental Forest case study areas. In these areas, total reactive nitrogen deposition 

in spring is 30% or more of the annual total. The temporal variation in total reactive nitrogen 

deposition is fairly uniform in the other three seasons (20% to 25% of the annual total). The 

results on the seasonal patterns in nitrogen deposition for the case study areas in the East are 

generally consistent with the findings by Sickles and Shadwick (2007b). In the West, the 

seasonal variations in the Sierra Nevada Range portion of the Mixed Conifer Forest Case Study 

Area and the Rocky Mountain National Park are similar, with a peak in spring and relatively 

high amounts of deposition also seen in summer. Total reactive nitrogen deposition is highest in 

summer in the Transverse Range portion of the Mixed Conifer Forest Case Study Area. 

The seasonal variations in total reactive nitrogen deposition reflect the aggregate of the 

variations in dry and wet, oxidized, and reduced nitrogen deposition, which are shown in 

Figures 3.3-7(a–i)26. Seasonal patterns in precipitation27 for each case study area are also shown 

in Figures 3.3-7(a–i). Dry oxidized nitrogen deposition peaks in spring or summer and tends to 

have the least seasonal variation among the four components of total reactive nitrogen 

deposition. In contrast, reduced nitrogen deposition peaks in summer and exhibits a fairly large 

seasonal variation in each of the case study areas. The amount of reduced nitrogen dry deposition 

in summer accounts for >40% of the annual total reduced nitrogen dry deposition in each area, 

except for the Kane Experimental Forest Case Study Area and the Transverse Range portion of 

the Mixed Conifer Forest Case Study Area, where in summer, dry reduced nitrogen is 30% to 

35% of the annual total. The intra-annual variations in dry reduced nitrogen deposition are 

generally consistent with the temporal patterns in NH3 emissions, which exhibit a primary peak 

in summer and a secondary peak in spring for the states in which the case study areas are located, 

as shown in Figure 3.3-8. Wet reduced nitrogen deposition seasonal variations generally, but not 

always, align with the seasonal variations in precipitation. Seasonal variations in wet oxidized 

 

26 In these figures the percent of deposition by season for each category sums to 100 percent. 

27 The precipitation data used in this analysis are based on the MM-5 meteorological model predictions, which are 

used as inputs to the CMAQ model simulations. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

nitrogen deposition also appear to reflect precipitation patterns, but not as closely as do wet 

reduced nitrogen deposition. 

Percent of 2002 Total Reactive Nitrogen Deposition

Adirondack Case Study Area

30

25 22 24

0

5

10

15

20

25

30

35

40

45

50

Winter Spring Summer Fall

Percent of Annual

Figure 3.3-6a. Percentage of 2002 total reactive nitrogen deposition in the 

Adirondack Case Study Area. 

Percent of Total 2002 Reactive Nitrogen Deposition

Hubbard Brook Case Study Area

35

22 23

20

0

5

10

15

20

25

30

35

40

45

50

Winter Spring Summer Fall

Percent of Annual

Hubbard Brook Experimental Forest Case Study Area 

Figure 3.3-6b. Percentage of 2002 total reactive nitrogen deposition in the 

Hubbard Brook Experimental Forest Case Study Area.

Final Risk and Exposure Assessment 3-52 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Percent of Total 2002 Reactive Nitrogen Deposition

Kane Forest Case Study Area

31

25

21

23

0

5

10

15

20

25

30

35

40

45

50

Winter Spring Summer Fall

Percent of Annual

Kane Experimental Forest Case Study Area

Figure 3.3-6c. Percentage of 2002 total reactive nitrogen deposition in the Kane 

Experimental Forest Case Study Area. 

Percent of Total 2002 Reactive Nitrogen Deposition

Potomac River Case Study Area

26

28

33

14

0

5

10

15

20

25

30

35

40

45

50

Winter Spring Summer Fall

Percent of Annual

Potomac River/Potomac Estuary Case Study Area

Figure 3.3-6d. Percentage of 2002 total reactive nitrogen deposition in the 

Potomac River/Potomac Estuary Case Study Area.

Final Risk and Exposure Assessment 3-53 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Percent of Total 2002 Reactive Nitrogen Deposition

Shenandoah Mountains Case Study Area

26 26

33

16

0

5

10

15

20

25

30

35

40

45

50

Winter Spring Summer Fall

Percent of Annual

Shenandoah Forest Case Study Area

Figure 3.3-6e. Percentage of 2002 total reactive nitrogen deposition in the 

Shenandoah Case Study Area. 

Percent of Total 2002 Reactive Nitrogen Deposition

Neuse River Case Study Area

26

20

38

16

0

5

10

15

20

25

30

35

40

45

50

Winter Spring Summer Fall

Percent of Annual

Neuse River/Neuse River Estuary Case Study Area

Figure 3.3-6f. Percentage of 2002 total reactive nitrogen deposition in the Neuse 

River/Neuse River Estuary Case Study Area. 

Final Risk and Exposure Assessment 3-54 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Percent of Total 2002 Reactive Nitrogen Deposition

Rocky Mountain NP Case Study Area

23

30

28

20

0

5

10

15

20

25

30

35

40

45

50

Winter Spring Summer Fall

Percent of Annual

Rocky Mountain National Park

Figure 3.3-6g. Percentage of 2002 total reactive nitrogen deposition in the Rocky 

Mountain National Park.

Percent of Total 2002 Reactive Nitrogen Deposition

Sierra Nevada Range Case Study Area

18

33

29

20

0

5

10

15

20

25

30

35

40

45

50

Winter Spring Summer Fall

Percent of Annual

Mixed Conifer Forest (Sierra Nevada Range) Case Study Area

Figure 3.3-6h. Percentage of 2002 total reactive nitrogen deposition in the Sierra 

Nevada Range portion of the Mixed Conifer Forest Case Study Area.

Final Risk and Exposure Assessment 3-55 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Percent of Total 2002 Reactive Nitrogen Deposition

Transverse Range Case Study Area

22

28

34

16

0

5

10

15

20

25

30

35

40

45

50

Winter Spring Summer Fall

Percent of Annual

Mixed Conifer Forest (Transverse Range) Case Study Area

Figure 3.3-6i. Percentage of 2002 total reactive nitrogen deposition in the 

Transverse Range portion of the Mixed Conifer Forest Case Study Area.

Adirondack Case Study Area

Percent of 2002 Reactive Nitrogen Deposition in each Season

0

5

10

15

20

25

30

35

40

45

50

Dry Ox N Dry Re N Wet Ox N Wet Re N Precip

Percent of Annual Total

Winter Spring Summer Fall

Figure 3.3-7a. Percentage of 2002 reactive nitrogen deposition for each 

component of nitrogen deposition in the Adirondack Case Study Area. 

Final Risk and Exposure Assessment 3-56 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Hubbard Brook Case Study Area

Percent of 2002 Reactive Nitrogen Deposition in each Season

0

5

10

15

20

25

30

35

40

45

50

Dry Ox N Dry Re N Wet Ox N Wet Re N Precip

Percent of Annual Total

Winter Spring Summer Fall

Figure 3.3-7b. Percentage of 2002 reactive nitrogen deposition for each 

component of nitrogen deposition in the Hubbard Brook Experimental Forest 

Case Study Area. 

Kane Forest Case Study Area

Percent of 2002 Reactive Nitrogen Deposition in each Season

0

5

10

15

20

25

30

35

40

45

50

Dry Ox N Dry Re N Wet Ox N Wet Re N Precip

Percent of Annual Total

Winter Spring Summer Fall

Kane Experimental Forest Case Study Area

Figure 3.3-7c. Percentage of 2002 reactive nitrogen deposition for each 

component of nitrogen deposition in the Kane Experimental Forest Case Study 

Area.

Final Risk and Exposure Assessment 3-57 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-58 September 2009 

Potomac River Case Study Area

Percent of 2002 Reactive Nitrogen Deposition in each Season

0

5

10

15

20

25

30

35

40

45

50

Dry Ox N Dry Re N Wet Ox N Wet Re N Precip

Percent of Annual Total

Winter Spring Summer Fall

Potomac River/Potomac Estuary Case Study Area

Figure 3.3-7d. Percentage of 2002 reactive nitrogen deposition for each 

component of nitrogen deposition in the Potomac River/Potomac Estuary Case 

Study Area. 

Shenandoah Mtns Case Study Area

Percent of 2002 Reactive Nitrogen Deposition in each Season

0

5

10

15

20

25

30

35

40

45

50

Dry Ox N Dry Re N Wet Ox N Wet Re N Precip

Percent of Annual Total

Winter Spring Summer Fall

Shenandoah Case Study Area

Figure 3.3-7e. Percentage of 2002 reactive nitrogen deposition for each 

component of nitrogen deposition in the Shenandoah Case Study Area. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-59 September 2009 

Neuse River Case Study Area

Percent of 2002 Reactive Nitrogen Deposition in each Season

0

5

10

15

20

25

30

35

40

45

50

Dry Ox N Dry Re N Wet Ox N Wet Re N Precip

Percent of Annual Total

Winter Spring Summer Fall

Neuse River/Neuse River Estuary Case Study Area

Figure 3.3-7f. Percentage of 2002 reactive nitrogen deposition for each 

component of nitrogen deposition in the Neuse River/Neuse River Estuar

Study Area. 

y Case 

Rocky Mtn NP Case Study Area

Percent of 2002 Reactive Nitrogen Deposition in each Season

0

5

10

15

20

25

30

35

40

45

50

Dry Ox N Dry Re N Wet Ox N Wet Re N Precip

Percent of Annual Total

Winter Spring Summer Fall

Rocky Mountain National Park

Figure 3.3-7g. Percentage of 2002 reactive nitrogen deposition for each 

component of nitrogen deposition in the Rocky Mountain National Park. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-60 September 2009 

Sierra Nevada Range Case Study Area

Percent of 2002 Reactive Nitrogen Deposition in each Season

0

10

20

30

40

50

60

Dry Ox N Dry Re N Wet Ox N Wet Re N Precip

Percent of Annual Total

Winter Spring Summer Fall

Mixed Conifer Forest (Sierra Nevada Range) Case Study Area

Figure 3.3-7h. Percentage of 2002 reactive nitrogen deposition for each 

component of nitrogen deposition in the Sierra Nevada Range portion of the 

Mixed Conifer Forest Case Study Area. 

Transverse Range Case Study Area

Percent of 2002 Reactive Nitrogen Deposition in each Season

0

10

20

30

40

50

60

Dry Ox N Dry Re N Wet Ox N Wet Re N Precip

Percent of Annual Total

Winter Spring Summer Fall

Mixed Conifer Forest (Transverse Range) Case Study Area

 

Figure 3.3-7i. Percentage of 2002 reactive nitrogen deposition for each component of 

n orest Case 

S

itrogen deposition in the Transverse Range portion of the Mixed Conifer F

tudy Area. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-61 September 2009 

Seasonal Variation in 2002 NH3 Emissions

0

5

10

15

20

25

30

35

40

45

50

NY NH PA MD VA NC CO CA

Percent of Annual Total

Winter Spring Summer Fall 

Figure 3.3-8. Percentage of 2002 NH3 emissions by season for each state 

containing a case study area. 

3.3.3.5 Magnitude of Sulfur Deposition in 2002 and Analysis of Inter-annual 

Variability 

The amount of reactive sulfur deposition in 2002 varies among the case study areas (see 

Table 3.3-1). In the East, sulfur deposition ranges from 7 kg S/ha/yr at the Hubbard Brook 

Experimental Forest Case Study Area and up to 20 kg S/ha/yr at the Kane Experimental Forest 

Case Study Area (see Figure 3.3-9a). Sulfur deposition in the case study areas in the West is 

very low and ranged from 1 to 2 kg S/ha/yr (see Figure 3.3-9b). 

Annual sulfur deposition from 2002 through 2005 varied by 1 to 3 kg S/ha/yr or less at 

individual case study areas, except for the Kane Experimental Forest Case Study Area, where the 

range during this period was 8 kg S/ha/yr. There is evidence of a downward trend during this 4-

year time period for the Adirondack and Kane Experimental Forest case study areas. No trend is 

evident during this period for the other case study areas. Trends analyses by CASTNET for an 

aggregate of 34 sites in the East indicate that dry sulfur deposition levels were fairly steady from 

2002 . 

Over , 

but then increased from 2005 to 2007 back to the levels monitored in 2002. As in the analysis for 

 through 2005, followed by a decrease in deposition in 2006 and 2007 (U.S. EPA, 2009)

all for these 34 sites, sulfur concentrations in wet deposition declined from 2002 to 2004
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-62 September 2009 

nitrogen deposition, trends over the most recent 10-year period were reviewed for wet deposition 

of sulfur for NADP sites in or near each case study area (see Appendix 2). The site-specific trend 

information indicates that overall, for each case study area, the amount of sulfur deposition in 

2002 is generally representative of current conditions. As was found in the analysis of nitrogen 

deposition, trends in sulfur deposition can vary from site to site, even within a case study area, 

with the same sites showing high/low amounts of sulfur deposition. In the Adirondack Case 

Study Area, the data from the Huntington Wildlife Forest site indicate that wet sulfur deposition 

in 2002 is within the range of values over the most recent 10-year period. However, data from 

the Whiteface site show that wet sulfur deposition in 2002 was high compared to that in other 

years. The data at both sites show a downward trend to 2005, with nitrogen deposition increasing 

again by 2007. For the Potomac River/Potomac Estuary Case Study Area, the trends in wet 

sulfur deposition at the Arendtsville, PA, and Parsons, WV, sites indicate that the amount of 

deposition in 2002 is similar to that from 1998 through 2007. However, the Wye, MD, site on the 

Eastern Shore of Maryland shows large inter-annual variations compared with the other sites in 

the Pot on in 2002 was 

on the l time period. During the most recent 10-year period, wet 

sulfur d n st was 

low, and generally in the range of 1 to 3 kg S/ha/yr. In 2002, wet sulfur deposition for both the 

Transv

ixed 

e 

o determine the reasons for the 

observe

omac River/Potomac Estuary Case Study Area, and that wet sulfur depositi

ow end of the range over this 

epositio in the two case study areas and Rocky Mountain National Park in the We

erse Range portion of the Mixed Conifer Forest Case Study Area and the Rocky Mountain

National Park was at the low end of this range. In the Sierra Nevada Range portion of the M

Conifer Forest Case Study Area, wet sulfur deposition in 2002 was in the range of the magnitud

of deposition in other years during the period 1998 to 2007. Similar to the analysis of nitrogen

deposition trends, it was beyond the scope of the current analysis t

d trends other than to note that local terrain-induced meteorological conditions and 

differential source-receptor relationships across a case study area may contribute to the 

differences noted in deposition trends. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-63 September 2009 

Annual Total Sulfur Deposition: 2002 - 2005

0

5

10

15

20

25

2002

2003

2004

2005

2002

2003

2004

2005

2002

2003

2004

2005

2002

2003

2004

2005

2002

2003

2004

2005

2002

2003

2004

2005

Sulfur Deposition (kg/ha-yr)

Neuse 

River 

Kane 

Forest 

Potomac 

River 

Shenandoah Adirondack Hubbard 

Brook 

Figure 3.3-9a. Annual sulfur deposition (kg S/ha/yr) from 2002 through 2005 for 

each case study area in the East. 

Transverse 

Range 

Sierra 

Nevada 

Rocky 

Mtn 

Annual Sulfur Deposition: 2002 - 2005

0

5

10

15

20

25

2

3

4

5

Sulfur Deposition (kg/ha-yr)

200

200

200

200

2002

2003

2004

2005

2002

2003

2004

2005

Figure 3.3-9b. Annual sulfur deposition (kg S/ha/yr) from 2002 through 2005 for 

case study areas in the West, as well as the Rocky Mountain National Park. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-64 September 2009 

3.3.3.6 Relative Amount of Wet and Dry Sulfur Deposition 

The relative amounts of wet and dry sulfur deposition for each case study area are shown 

in Figure 3.3-10 for 2002 and in Figure 3.3-11 for the average of 2002 through 2005. These 

figures indicate that the relative amounts of wet and dry sulfur deposition in 2002 are consistent 

with the average over the 4-year time period. The results for the case study areas of the East, as 

described below, are generally consistent with the findings of Sickles and Shadwick (2007b) on 

the relative amount of wet and dry sulfur deposition for an aggregation of 34 eastern CASTNET 

sites. Factors that can influence the relative amounts of wet and dry sulfur deposition in a given 

location include geographic variations and climatological conditions, which determine the 

amount of precipitation and transport patterns and the proximity to local sources of SO2. In 

general, for the case study areas, those areas that are farthest from sources of high SO2 emissions 

tend to have more sulfur deposition from wet deposition than from dry deposition. 

Approximately 60% of total sulfur deposition in 2002 occurred through wet deposition in the 

Hubbard Brook Experimental Forest, Adirondack and Mixed Conifer Forest (Sierra Nevada 

Range se 

areas is fairly distant from sources of high SO2 emissions. The relative amounts of wet and dry 

deposition are about the same in the Shenandoah and Neuse River/Neuse River Estuary case 

study areas. In the Kane Experimental Forest and Potomac River/Potomac Estuary case study 

areas, which contain or are close to sources of relatively high SO2 emissions, dry deposition 

contributes nearly 60% of the total sulfur deposition. In the Transverse Range portion of the 

Mixed Conifer Forest Case Study Area, which has a more arid climatology compared with the 

other areas, >70% of the total sulfur deposition is dry deposited. 

portion) case study areas, as well as the Rocky Mountain National Park. Each of the
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-65 September 2009 

2002 Wet vs Dry Percent of Annual Total Sulfur Deposition

0

10

20

30

40

50

60

70

80

90

100

Sierra Nevada Range

Hubbard Brook

Adirondacks

Rocky Mtn

Neuse River

Shenandoah

Kane Forest

Potomac River

Transverse Range

Percent of Total

Dry S

Wet S

Figure 3.3-10. Relative amount of wet and dry annual sulfur deposition in 2002 

for case study areas. 

2002 - 2005 Wet vs Dry: Percent of Annual Total Sulfur Deposition

50

60

70

80

90

100

tal S Deposition

0

10

20

30

40

Rocky Mtn NP

Hubbard Brook

Adirondack Mtns

Sierra Nevada

Neuse River

Shenandoah Mtns

Kane Forest

Potomac River

Transverse Range 

Percent of To

Dry S

Wet S

Figure 3.3-11. Relative amount of wet and dry annual sulfur deposition based on 

deposition for the period 2002 through 2005 for each case study area and the 

Rocky Mountain National Park. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-66 September 2009 

3.3.3.7 Geographic Variations in Annual Sulfur Deposition for 200228

The spatial patterns in total sulfur deposition and wet and dry sulfur deposition in the 

East are shown in Figures 3.3-12(a–c). Spatial patterns in total sulfur deposition in the West are 

shown in Figure 3.3-1329. 

Adirondack Case Study Area 

The highest amounts of sulfur deposition in the Adirondack Case Study Area are found in 

the southwestern portion of this area, where sulfur deposition is >10 kg S/ha/yr. In the central 

and eastern sections of this area, sulfur deposition is <8 kg S/ha/yr. Wet deposition of sulfur is 

greater than dry deposition across all of this area. The spatial gradients in wet sulfur deposition 

appear to be much stronger than the gradients in dry sulfur deposition. Like nitrogen deposition, 

the relatively high total sulfur deposition in the southwestern portion of the Adirondack Case 

Study Area is part of a broad area of high sulfur deposition that stretches along the southern 

shore of Lake Ontario into western Pennsylvania and beyond. 

Shenandoah Case Study Area 

ur 

deposition that covers portions of the Ohio River Valley and West Virginia. Within the 

Shenandoah Case Study Area, there are several relatively isolated locations with sulfur 

deposition of >14 kg S/ha/yr. These locations appear to correspond to the location of local 

sources of high SO2 emissions, as shown in Figure 3.2-5. There is a large range in dry sulfur 

deposition within the Shenandoah Case Study Area, with amounts ranging from 3 to 4 kg S/ha/yr 

up to 14 kg S/ha/yr. Wet sulfur deposition appears to be spatially more homogeneous than dry 

sulfur deposition. Amounts of wet sulfur deposition range from 5 to 6 kg S/ha/yr across most of 

the area, with higher amounts, up to the range of 6 to 7 kg S/ha/yr, found in the northwestern part 

of the area. 

 

The Shenandoah Case Study Area is on the eastern side of the region of high sulf

28 Note that an analysis of the spatial gradients in reactive nitrogen and sulfur deposition for the Kane Experimental 

Forest rk, is 

not inc d data 

and m

29 See fo geographic variations in deposition for the case study areas 

in the West. 

 and Hubbard Brook Experimental Forest case study areas, as well as the Rocky Mountain National

luded because the size of each of these areas is small relative to the 12 × 12-km resolution-measure

odel predictions used in this analysis. 

otnote 19 for caveats concerning the analysis of 

Pa
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-67 September 2009 

Potomac River/Potomac Estuary Case Study Area 

There was considerable variation in sulfur deposition across the Potomac River/Potom

Estuary Case Study Area in 2002. The highest amounts of sulfur deposition in this area, of 24 kg 

S/ha/yr or more, are found 

ac 

in the far northwestern portion of this area, which is near sources of 

high SO wer amounts of sulfur deposition of 14 kg 

S/ha/yr or more is found over the eastern half 

t 

nd in particular, near a source of 

high SO rginia border. Sulfur deposition generally 

decreases from

r across most of this area. The highest amounts (1 to 2 kg S/ha/yr) are found in the 

extreme western portion of this area. 

Transverse Range (a Portion of the Mixed Conifer Forest Case Study Area) 

In the Transverse Range portion of the Mixed Conifer Forest Case Study Area, sulfur 

B

2 emissions in western Pennsylvania. Lo

of the Potomac River/Potomac Estuary Case Study 

Area. The lowest amount of sulfur deposition, in the range of 8 to 10 kg S/ha/yr, is seen in the far 

southwest portion of this area. Wet and dry sulfur depositions are both relatively high in the 

northwestern portion of this area. In the eastern portion of this area, near the sources of SO2

emissions in the vicinity of Washington, DC, dry sulfur deposition is greater than wet. 

Neuse River/Neuse River Estuary Case Study Area 

In the Neuse River/Neuse River Estuary Case Study Area, sulfur deposition is highes

near the Raleigh-Durham urban area (14 kg S/ha/yr or more), a

2 emissions located near the North Carolina/Vi

 northwest to southeast down to 6 to 8 kg S/ha/yr in the eastern portion of this 

area. Most of the spatial variation in sulfur deposition appears to be associated with dry 

deposition. Dry sulfur deposition increases from 2 to 3 kg S/ha/yr near the mouth of the Neuse 

River up to 9 to 14 kg S/ha/yr in the northwest corner of this case study area. In contrast, the 

amount of wet sulfur deposition appears to be fairly homogeneous across most of the case study 

area, with amounts in the range of 4 to 5 kg S/ha/yr. 

Sierra Nevada Range (a Portion of the Mixed Conifer Forest Case Study Area) 

There appears to be very little spatial variation in sulfur deposition in the Sierra Nevada 

Range portion of the Mixed Conifer Forest Case Study Area. The amount of sulfur deposition is 

<1 kg S/ha/y

deposition decreases with distance from the Los Angeles urban area. Sulfur deposition in the San 

ernardino Mountains north of Los Angeles is in the range of 0.5 to 2 kg S/ha/yr. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-68 September 2009 

Figure 3.3-12a. Annual total dry plus wet sulfur deposition (kg S/ha/yr) in 2002 

for the case study areas in the East. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Figure 3.3-12b. Annual wet sulfur deposition (kg S/ha/yr) in 2002 for the case 

study areas in the East. 

Final Risk and Exposure Assessment 3-69 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Figure 3.3-12c. Annual dry sulfur deposition (kg S/ha/yr) in 2002 for the case 

study areas in the East.

Final Risk and Exposure Assessment 3-70 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-71 September 2009 

8 Mixed Conifer Forest (Transverse Range)

Mixed Conifer Forest (Transverse Range) 

Figure 3.3-13. Annual total dry plus wet sulfur deposition (kg S/ha/yr) in 2002 

for case study areas and Rocky Mountain National Park in the West. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-72 September 2009 

3.3.3.8 Seasonal Variations in Sulfur Deposition for 2002 

The seasonal patterns in total sulfur deposition for each case study area are shown in 

Figures 3.3-14(a–i), and the seasonal patterns for wet and dry sulfur deposition and precipitation 

are shown in Figures 3.3-15(a–i). Sulfur deposition is greatest in spring or summer, except in the 

Sierra Nevada Range portion of the Mixed Conifer Forest Case Study Area, as described below. 

For the case study areas of the East, the seasonal patterns in sulfur deposition are generally 

similar to those of total reactive nitrogen deposition. Thus, these areas are affected by the highest 

amount of sulfur deposition and total reactive nitrogen deposition during the same season. 

Examination of the seasonal variations in wet and dry sulfur deposition in the case study areas in 

the East indicates that dry sulfur deposition is highest in winter and lowest in summer, whereas 

wet sulfur deposition peaks in spring or summer and generally tracks the seasonal patterns in 

precipitation. 

In the case study areas in the West, the seasonal patterns in wet sulfur deposition are very 

similar to the precipitation patterns that were found for the case study areas in the East. In the 

Sierra Nevada Range and Transverse Range (Mixed Conifer Forest Case Study Area), there are 

large seasonal variations in precipitation, which affect the seasonal variations in wet sulfur 

deposition. In these two areas, nearly all of the wet sulfur deposition occurs during winter and 

spring, which are the seasons with the most of the precipitation. The seasonal patterns in total 

sulfur deposition reflect the net effect of the seasonal variations in wet and dry sulfur deposition. 

In the Rocky Mountain National Park and the Transverse Range portion of the Mixed Conifer 

Forest Case Study Area, total sulfur deposition peaks in spring. In contrast, in the Sierra Nevada 

Range portion of the Mixed Conifer Forest Case Study Area, both winter and spring have much 

higher sulfur deposition compared with summer and fall. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-73 September 2009 

Percent of 2002 Total Sulfur Deposition

Adirondack Case Study Area

31

22

23 24

5

10

15

20

25

30

35

40

45

50

Percent of Annual

0

Winter Spring Summer Fall

Figure 3.3-14a. Percentage of 2002 total sulfur deposition in the Adirondack Case 

Study Area. 

Percent of 2002 Total Sulfur Deposition

Hubbard Brook Case Study Area

36

30

35

40

45

50

 Annual

22 21 21

0

5

10

15

20

25

Winter Spring Summer Fall

Percent of

Hubbard Brook Experimental Forest Case Study Area 

Figure 3.3-14b. Percentage of 2002 total sulfur deposition in the Hubbard Brook 

Experimental Forest Case Study Area. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-74 September 2009 

Percent of 2002 Total Sulfur Deposition

Kane Forest Case Study Area

31

21

24 24

0

5

10

15

20

25

30

35

40

45

50

Winter Spring Summer Fall

Percent of Annual

Kane Experimental Forest Case Study Area Kane Experimental Forest Case Study Area 

Figure 3.3-14c. Percentage of 2002 total sulfur deposition in the Kane Experimenta

Forest Case S

l 

tudy Area. 

Percent of 2002 Total Sulfur Deposition

Potomac River Case Study Area

25

29

26

20

0

5

10

15

20

25

30

35

40

45

50

Winter Spring Summer Fall

Percent of Annual

Potomac River/Potomac Estuary Case Study Area 

Figure 3.3-14d. Percentage of 2002 total sulfur deposition in the Potomac 

River/Potomac Estuary Case Study Area. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-75 September 2009 

Percent of 2002 Total Sulfur Deposition

Shenandoah Mtns Case Study Area

24

31

27

19

0

5

10

15

20

25

30

35

40

45

50

Winter Spring Summer Fall

Percent of Annual

Shenandoah Case Study Area 

Figure 3.3-14e. Percentage of 2002 total sulfur deposition in the Shenandoah Case 

Study Area.

Percent of 2002 Total Sulfur Deposition

Neuse River Case Study Area

20

33

23 24

0

5

10

15

20

25

30

35

40

45

50

Winter Spring Summer Fall

Percent of Annual

Neuse River/Neuse River Estuary Case Study Area

Figure 3.3-14f. Percentage of 2002 total sulfur deposition in the Neuse River/Neuse 

River Estuary Case Study Area. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-76 September 2009 

Percent of 2002 Total Sulfur Deposition

Rocky Mtn NP Case Study Area

24 25

32

19

0

5

10

15

20

25

30

35

40

45

50

Winter Spring Summer Fall

Percent of Annual

Rocky Mountain National Park

Figure 3.3-14g. Percentage of 2002 total sulfur deposition in the Rocky Mountain 

National Park. 

Percent of 2002 Total Sulfur Deposition

Sierra Nevada Range Case Study Area

9

14

38 39

0

5

10

15

20

25

30

35

40

45

50

Winter Spring Summer Fall

Percent of Annual

Mixed Conifer Forest (Sierra Nevada Range) Case Study Area

Figure 3.3-14h. Percentage of 2002 total sulfur deposition in the Sierra Nevada 

Range portion of the Mixed Conifer Forest Case Study Area. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-77 September 2009 

Percent of 2002 Total Sulfur Deposition

Transverse Range Case Study Area

21

24

28

26

0

5

10

15

20

25

30

35

40

45

50

Winter Spring Summer Fall

Percent of Annual

Mixed Conifer Forest (Sierra Nevada Range) Case Study Area

Figure 3.3-14i. Percentage of 2002 total sulfur deposition in the Transverse Range 

portion of the Case Study Area. 

Adirondack Case Study Area

Percent of 2002 Sulfur Deposition in each Season

0

5

10

15

20

25

30

35

40

45

50

Dry S Wet S Precip

Percent of Annual Total

Winter Spring Summer Fall

Figure 3.3-15a. Percentage of 2002 deposition for each component of sulfur 

deposition in the Adirondack Case Study Area.
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-78 September 2009 

Hubbard Brook Case Study Area

Percent of 2002 Sulfur Deposition in each Season

0

5

10

15

20

25

30

35

40

45

50

Dry S Wet S Precip

Percent of Annual Total

Winter Spring Summer Fall

Hubbard Brook Experimental Forest Case Study Area

Figure 3.3-15b. Percentage of 2002 deposition for each component of sulfur 

deposition in the Hubbard Brook Experimental Forest Case Study Area.

Kane Forest Case Study Area

Percent of 2002 Sulfur Deposition in each Season

0

5

10

15

20

25

30

35

40

45

50

Dry S Wet S Precip

Percent of Annual Total

Winter Spring Summer Fall

Kane Experimental Forest Case Study Area

Figure 3.3-15c. Percentage of 2002 deposition for each component of sulfur 

deposition in the Kane Experimental Forest Case Study Area. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Potomac River Case Study Area

Percent of 2002 Sulfur Deposition in each Season

0

5

10

15

20

25

30

35

40

45

50

Dry S Wet S Precip

Percent of Annual Total

Winter Spring Summer Fall

Potomac River/Potomac Estuary Case Study Area Potomac River/Potomac estuary Case Study Area

Figure 3.3-15d. Percentage of 2002 deposition for each component of sulfur 

deposition in the Potomac River/Potomac Estuary Case Study Area.

Shenandoah Mtns Case Study Area

Percent of 2002 Sulfur Deposition in each Season

0

5

10

15

20

25

30

35

40

45

50

Dry S Wet S Precip

Percent of Annual Total

Winter Spring Summer Fall

Shenandoah Case Study Area

Figure 3.3-15e. Percentage of 2002 deposition for each component of sulfur 

deposition in the Shenandoah Case Study Area. 

Final Risk and Exposure Assessment 3-79 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-80 September 2009 

Neuse River Case Study Area

Percent of 2002 Sulfur Deposition in each Season

0

5

10

15

20

25

30

35

40

45

50

Dry S Wet S Precip

Percent of Annual Total

Winter Spring Summer Fall

Neuse River/Neuse River Estuary Case Study Area

Figure 3.3-15f. Percentage of 2002 deposition for each component of sulfur 

deposition in the Neuse River/Neuse River Estuary Case Study Area.

Rocky Mtn NP Case Study Area

Percent of 2002 Sulfur Deposition in each Season

0

5

10

15

20

25

30

35

40

45

50

Dry S Wet S Precip

Percent of Annual Total

Winter Spring Summer Fall

Rocky Mountain National Park

Figure 3.3-15g. Percentage of 2002 deposition for each component of sulfur 

deposition in the Rocky Mountain National Park. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-81 September 2009 

Sierra Nevada Range Case Study Area

Percent of 2002 Sulfur Deposition in each Season

0

10

20

30

40

50

60

Dry S Wet S Precip

Percent of Annual Total

Winter Spring Summer Fall

Mixed Conifer Forest (Sierra Nevada Range) Case Study Area

Figure 3.3-15h. Percentage of 2002 deposition for each component of sulfur 

deposition in the Sierra Nevada Range portion of the Mixed Conifer Forest Case 

Study Area.

Transverse Range Case Study Area

Percent of 2002 Sulfur Deposition in each Season

0

10

20

30

40

50

60

Dry S Wet S Precip

Percent of Annual Total

Winter Spring Summer Fall

Mixed Conifer Forest (Sierra Nevada Range) Case Study Area Mixed Conifer Forest (Transverse Range) Case Study Area

 

Figure 3.3-15i. Percentage of 2002 deposition for each component of sulfur 

deposition in the Transverse Range portion of the Mixed Conifer Forest Case 

Study Area.
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-82 September 2009 

3.3.3.9 Summary of Case Study Analysis Findings 

The key findings from the case study analyses are summarized below. 

(1) Total reactive nitrogen deposition and sulfur deposition are much greater in the East 

compared to most areas of the West. 

(2) These regional differences in deposition correspond to the regional differences in NOx

and SO2 concentrations and emissions, which are also higher in the East. 

(3) NOx emissions are much greater and generally more widespread than NH3 emissions 

nationwide; high NH3 emissions tend to be more local (e.g., eastern North Carolina) or subregional (e.g., the upper Midwest and Plains states). 

(4) The relative amounts of oxidized versus reduced nitrogen deposition are consistent 

with the relative amounts of NOx and NH3 emissions. 

(a) Oxidized nitrogen deposition exceeds reduced nitrogen deposition in most of 

stuary 

ition exceeds oxidized nitrogen deposition in the 

vicinity of local sources of NH3. 

(5) There can be relatively large spatial variations in both total reactive nitrogen 

deposition and sulfur deposition within a case study area; this occurs particularly in those areas 

that contain or are near a high emissions source of NOx, NH3, and/or SO2. 

(6) The seasonal patterns in deposition differ between the case study areas. 

(a) For the case study areas in the East, the season with the greatest amounts of 

total reactive nitrogen deposition correspond to the season with the greatest amounts of 

sulfur deposition. Deposition peaks in spring in the Adirondack, Hubbard Brook 

Experimental Forest, and Kane Experimental Forest case study areas, and it peaks in 

summer in the Potomac River/Potomac Estuary, Shenandoah, and Neuse River/Neuse 

River Estuary case study areas. 

(b) For the case study areas in the West, there is less consistency in the seasons 

with greatest total reactive nitrogen and sulfur deposition in a given area. In general, both 

nitrogen and/or sulfur deposition peaks in spring or summer. The exception to this is the 

n which 

the case study areas; the major exception being the Neuse River/Neuse River E

Case Study Area. 

(b) Reduced nitrogen depos

Sierra Nevada Range portion of the Mixed Conifer Forest Case Study Area, i

sulfur deposition is greatest in winter. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-83 September 2009 

3.4 R X AND NH3 TO 

 to ambient 

concen

s 

spheric deposition of nitrogen and sulfur. 

Atmosp

atmospheric emissions of NOx, NH3, and 

SOx will direct

order to

necessary to understand the contribution of ambient NOx and SOx to the ecosystem pollutants of 

concern: sulfur

nitroge ogen, it is important to understand the contribution of 

NOx re scribes 

e 

AQ sensitivity runs 

to estim total nitrogen 

deposition (the

f 

nitroge

simulat l runs in which anthropogenic emissions of NOx, NH3, or 

SOx were redu

polluta

for this

emissio io 

 

CONT IBUTIONS OF EMISSIONS OF NO

DEPOSITION OF NITROGEN

3.4.1 Purpose and Intent 

The targeted ecological effect areas’ public welfare effects of concern in this review 

associated with ambient NOx and SOx do not occur due to direct exposure

trations of NOx and SOx, but rather due to deposition of these compounds in the 

environment. Ecosystem effects occur because of ecological exposures to loadings of all form

of nitrogen and sulfur, and this is due, in part, to atmo

heric deposition of nitrogen and sulfur is directly related to the concentrations of NOx, 

NH3, and SOx in the atmosphere, and thus, decreasing 

ly impact deposited nitrogen and sulfur and the associated ecosystem effects. In 

 set ambient standards for NOx and SOx that are protective of public welfare, it is 

 and total reactive nitrogen. Because the focus of this review is on oxides of 

n, rather than on total reactive nitr

lative to reduced forms of nitrogen (NH3 and NH4

+

) to deposition. This section de

the analysis of the contribution of NOx relative to reduced forms of nitrogen. It also examines th

contributions of SOx emissions to sulfur deposition. These analyses use CM

ate the relative percentage contribution of NOx, NH3, and SOx emissions to 

 oxidized and reduced forms of nitrogen and total sulfur deposition). 

3.4.2 Analytical Techniques 

For a more informed understanding of the roles of NOx, NH3, and SOx in deposition o

n and sulfur, the CMAQ model for several sensitivity simulations were run. These 

ions include three separate mode

ced by 50% from base case emissions levels (i.e., one run for each of the three 

nts). The 2005 12-km CMAQ run for the eastern United States was used as the base case 

 analysis. The NOx, NH3, and SOx emissions reductions were applied to the 2005 

ns for all states within the eastern modeling domain30. The 50% NOx reduction scenar

 

MAQ model configuration and modeling doma 30 The C in for these applications are described in Appendix 1 of this 

report. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-84 September 2009 

resulted in a NOx emissions reduction of ~ 9 million tons. This amount is more than 

ount of emissions reduced in the 50% NH3

four times 

the am scenario (~ 2 million tons of NH3). The 50% 

SOx emissions reduction scenario removed ~ 7 million tons of SOx from states in the eastern 

modeling dom

et and dry 

late the 

s between NOx emissions and total reactive nitrogen 

deposition, the im sition, as s

The 50% reduction in NOx generally had a small impact on reduced nitrogen deposition 

ain. 

Each sensitivity run was performed for January, April, July, and October 2005, to 

represent differences in emissions and meteorology in each season of that year. The w

deposition predictions from the CMAQ base case and sensitivity runs were used to calcu

4-month average deposition in each grid cell. The results are used to estimate (1) the relative 

contribution of emissions of NOx and NH3 to deposition of total, reduced, and oxidized nitrogen

deposition, and (2) the relative contribution of SOx emissions to sulfur deposition. The focus is 

on the percentage contribution in the six case study areas of the East. 

3.4.3 Results and Findings 

3.4.3.1 Contributions of NOx Emissions to Total Reactive Nitrogen Deposition 

Figure 3.4-1 shows the impacts of the 50% NOx scenario on total reactive nitrogen 

deposition in the East. In general, a 50% reduction in NOx had a 30% to 40% impact (i.e., 

reduction) on total reactive nitrogen deposition across much of the East, including all or most of 

the Kane Experimental Forest, Potomac River/Potomac Estuary, and Shenandoah case study 

areas. Portions of the East where NOx emissions had the least impact on total reactive nitrogen 

deposition, including the Neuse River/Neuse River Estuary Case Study Area, generally 

correspond to areas of highest NH3 emissions. 

To further explore the relationship

pact on oxidized and reduced nitrogen depo hown in Figures 3.4-2 

and 3.4-3, was examined. These figures reveal that the 50% reduction in NOx emissions resulted 

in a 40% to 50% reduction in oxidized nitrogen deposition, indicating that nearly all of the 

oxidized nitrogen deposition is due to NOx emissions. The Potomac River/Potomac Estuary, 

Shenandoah, and Neuse River/Neuse River Estuary case study areas each had reductions in 

oxidized nitrogen of 45% to 50%. The impacts were somewhat less in the Adirondack, Hubbard 

Brook Experimental Forest, and Kane Experimental Forest case study areas. 

across the East (+ 6%). Some case study areas had lower reduced nitrogen, whereas others had 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-85 September 2009 

slight increases. The Adirondack, Kane Experimental Forest, and Hubbard Brook Experimental 

Forest case study areas all had lower reduced nitrogen deposition. However, in the Neuse 

River/Neuse River Estuary Case Study Area and in portions of the Potomac River/Potomac 

Estuary and Shenandoah case study areas, the NOx emissions impacts are slightly positive, 

suggest

3.4.3.2 Contributions of NH3 Emissions to Total Reactive Nitrogen Deposition 

 impact of the 50% NH3 emissions scenario on deposition 

of total reactive nitrogen.

generally the same locations where the contribution from NO is the least. These locations 

include portions of the Potom

3

ac Estuary, Shenandoah, Kane 

Experim

3

rio 

NH lim

3 3

ing that NOx emissions contribute to greater deposition of reduced nitrogen. This 

relationship reflects the atmospheric reactions that lead to deposition of reduced nitrogen. One 

possible explanation for this is that reducing NOx reduces HNO3, which limits NH4NO3

formation, thereby increasing the lifetime of NH3. This change may result in a net increase in 

NH3/NH4

+

 deposition. Because the deposition velocity of NH3 is much higher than the deposition

velocity for NH4

+

 aerosol, dry deposition of NHx increases closer to sources of NH3. 

Figure 3.4-4 shows the relative

 The locations with the greatest contributions from NH3 emissions are 

x

ac River/Potomac Estuary, Shenandoah, and Neuse River/Neuse 

River Estuary case study areas. In the Adirondack, Kane Experimental Forest, and Hubbard 

Brook Experimental Forest case study areas, the contribution of total reactive nitrogen is 

generally 10% to 20% or less. 

Figures 3.4-5 and 3.4-6 explore the relationship between NH3 emissions and nitrogen 

deposition in more detail, examining separately the relative impacts of NH on oxidized and 

reduced forms of nitrogen. In the Potomac River/Potom

ental Forest, and Neuse River/Neuse River Estuary case study areas, the 50% NH3

emissions scenario results in a 40% to 50% impact, indicating that nearly all of the reduced 

nitrogen in these areas is likely associated with NH3 emissions. The contributions from NH to 

reduced nitrogen deposition were somewhat less (generally 30% to 40%) for the Adirondack and 

Hubbard Brook Experimental Forest case study areas. Also, in the Potomac River/Potomac 

Estuary, Shenandoah, and Neuse River/Neuse River Estuary case study areas, the NH3 scena

resulted in a slight increase in oxidized nitrogen deposition. This relationship reflects the 

atmospheric reactions that lead to the deposition of reduced and oxidized nitrogen. Reducing 

3 its NH4NO3 aerosol formation, increasing the lifetime of HNO3. The ratio of HNO3 to 

nitrate (NO -

) increases, and because the deposition velocity of HNO is much larger than that of
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-86 September 2009 

NO3

-

 aerosol, dry deposition of total oxidized nitrogen increases. In the Adirondack, Kane 

Experimental Forest, and Hubbard Brook Experimental Forest case study areas, the 50% N

scenario produced a small decrease (up to 2%) in oxidized nitrogen deposition. 

3.4.3.3 Contributions of SO2 Emissions to Sulfur Deposition 

As shown in Figure 3.4-7, a 50% reduction in SOx emissions resulted in nearly a 50% 

reduction in sulfur deposition in the Kane Experimental Forest, Potomac River/Potomac 

Shenandoah, and Neuse River/Neuse River Estuary case study areas. The contribution is 

somewhat less in the Adirondack and Hubbard Brook Experimental Forest case study areas, 

which are more distant from sources of high SO2 emissions compared with the other c

H3

Estuary, 

ase study 

areas. In general, the contribution of SO2 emissions to sulfur deposition is fairly linear for the 

50% re s

 that 

of 

3

. Because oxidized nitrogen deposition is a greater portion of 

total re

duction cenario that was modeled. 

3.4.4 Summary of Findings 

From this study of the contribution of emissions to deposition in the East, it is found

NOx emissions have significant impacts on total nitrogen deposition and account for almost all 

the oxidized nitrogen deposition. The contributions of NOx emissions compared with NH3

emissions appear to be separable in that NOx affects mainly oxidized nitrogen whereas NH

affects mainly reduced nitrogen

active nitrogen deposition in most areas, NOx emissions contribute more to total reactive

nitrogen than emissions of NH3. However, local NH3 emissions do make significant 

contributions to total reactive nitrogen deposition near the sources of these emissions. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Figure 3.4-1. The percentage impacts of a 50% decrease in NOx emissions on 

total reactive nitrogen deposition in the East. 

Final Risk and Exposure Assessment 3-87 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Figure 3.4-2. The percentage impacts of a 50% decrease in NOx emissions on 

oxidized nitrogen deposition in the East. 

Final Risk and Exposure Assessment 3-88 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Figure 3.4-3. The percentage impacts of a 50% decrease in NOx emissions on 

reduced nitrogen deposition in the East. 

Final Risk and Exposure Assessment 3-89 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-90 September 2009 

Figure 3.4-4. The percentage impacts of a 50% decrease in NH3 emissions on 

total reactive nitrogen deposition in the East. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Figure 3.4-5. The percentage impacts of a 50% decrease in NH3 emissions on 

oxidized nitrogen deposition in the East. 

Final Risk and Exposure Assessment 3-91 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Figure 3.4-6. The percentage impacts of a 50% decrease in NH3 emissions on 

reduced nitrogen deposition in the East. 

Final Risk and Exposure Assessment 3-92 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-93 September 2009 

Figure 3.4-7. The percentage impacts of a 50% decrease in SOx emissions on 

sulfur deposition in the East. 

3.5 RELATIONSHIPS BETWEEN DEPOSITION AND 

CONCENTRATIONS 

To address the framing questions that guide the scope of this review, this chapter has 

focused on characterizing the emissions, concentrations, and deposition of nitrogen and sulfur 

compounds. Characterizing the relationships between ambient air concentrations and deposition 

of both NOx and SOx is a key aspect of defining the Atmospheric Deposition Transformation 

function (box 3 of Figure 1.4-1) which is a central element of this analysis. In the policy 

assessment phase of this review, it will be important to use such relationships to estimate the 

amounts of nitrogen and sulfur deposition associated with ambient air concentrations. In this 

section we present one approach to quantifying the relationships between deposition and 

concentration for NOx and SOx. This approach expresses the relationships between deposition 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-94 September 2009 

and concentration using the ratio of nitrogen deposition to nitrogen concentration and sulfur 

deposition to sulfur concentrations. To calculate the deposition to concentration ratios we used 

CMAQ predicted 2002 annual total wet and dry deposition and annual average concentrations of 

sulfur and nitrogen from the individual species of NOx (i.e., NO, NO2, NO3, HNO3, NH3, N2O5, 

HONO, PANs, and nitrate) and SOx (i.e., SO2 and sulfate). The CMAQ predictions were used to 

calculate annual total nitrogen and sulfur deposition and annual average nitrogen and sulfur 

concentrations. These calculations were performed for the predictions in each CMAQ grid cell, 

nationwide. The estimates of deposition and concentration were then used to calculate the ratio 

of nitrogen deposition to nitrogen concentration and sulfur deposition to sulfur concentration. 

The nitrogen ratios are expressed in units of kg N/ha/μg/m3, and the sulfur ratios are expressed in 

units of kg S/ha/μg/m3

. The ratios provide a means of comparing the amount of deposition per 

unit amount of concentration for different geographic areas. The nitrogen and sulfur deposition 

to concentration ratios are displayed in Figure 3.5-1 for nitrogen and Figure 3.5-2 for sulfur. For 

most parts of the country, the deposition to concentration ratios for both nitrogen and sulfur are 

in the range of 0.5 to 7 kg/ha/μg/m3

. Locations with ratios near the lower end of this range 

receive less deposition per unit concentration than locations with ratios near the upper end of this 

range. 

In the following analysis, we describe several observations about the spatial variation in 

the ma the 

physical and chemical processes that lead to these spatial patterns will be the subject of future 

osition to 

concen occur in areas of relatively elevated terrain (e.g., the 

Adiron

 no 

, 

ntration 

d 

West are characterized by ratios of 3 kg N/ha/μg/m3

 or greater. 

gnitude of nitrogen and sulfur deposition to concentration ratios. Characterizing

research. As indicated by the map in Figure 3.5-1, the largest nitrogen dep

tration ratios are estimated to 

dacks) which may potentially reflect the effects higher wet deposition in such areas 

associated with terrain induced precipitation. The lower ratios tend to align geographically with

locations of highest NOx emissions and NOy concentrations, as shown in Figure 3.2-1 and 

Figure 3.2-4, respectively. It is interesting to note that although there are large geographic 

differences in NOx emissions and NOy concentrations between the East and West, there is

clear East-West difference in the deposition to concentration ratios. In both the East and West

areas in and near sources of NOx tend to have ratios less than 1 kg N/ha/μg/m3

. In most, but 

clearly not all, other lower terrain areas of the East and West nitrogen deposition to conce

ratios are in the range of 1 to 2 kg N/ha/μg/m3

. Many of the elevated terrain areas in the East an
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-95 September 2009 

Figure 3.5-1. Ratio of nitrogen deposition to nitrogen concentration based on 

ulfur 

lfur 

on to 

ure 

oxidized nitrogen deposition and concentration (kg N/ha/μg/m3

). 

As indicated by the map in Figure 3.5-2, the deposition to concentration ratios for s

are largest in areas of elevated terrain. In locations outside of these elevated terrain areas, there

are notable differences between the East and West with respect to the magnitude of su

deposition to concentration ratios. In the lower terrain areas of the East, the sulfur depositi

concentration ratios are generally greater than 2 kg S/ha/μg/m3

, whereas in the lower terrain

areas of the West, ratios are generally less than 2 kg S/ha/μg/m3. The general East-West 

difference in sulfur deposition to concentration ratios may be related to the East-West difference 

in SOx emissions and SO2 concentrations, as indicated by the maps in Figure 3.2-3 and Fig

3.2-5, respectively. In elevated terrain areas of both the East and West, sulfur deposition to 

concentration ratios are 4 kg S/ha/μg/m3

 or more. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-96 September 2009 

Figure 3.5-2. Ratio of sulfur deposition to sulfur concentration based on oxidiz

sulfur deposition and concentration (kg S/ha/μg/m3). 

ed 

: 

 Ratio of annual total wet oxidized nitrogen deposition to annual average NO2

concentrations (Figure 2-7) 

There are other possible deposition to concentration ratios which may be informative for 

examining the relationships between deposition and concentration. In this regard, we have 

provided in Appendix 2national maps of the following ratios species based on the CMAQ 

predictions for 2002 (the corresponding Appendix 2 figure numbers are provided in parentheses)

 Ratio of annual total dry sulfur deposition to annual average SO2 concentrations (Figure 

2-1) 

 Ratio of annual total wet sulfur deposition to annual average SO2 concentrations (Figure 

2-2) 

 Ratio of annual total wet+dry sulfur deposition to annual average SO2 concentrations 

(Figure 2-3) 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-97 September 2009 

 Ratio of annual total dry oxidized nitrogen deposition to annual average NO2

concentrations (Figure 2-8) 

 Ratio of annual total wet+dry oxidized nitrogen deposition to annual average NO2

concentrations (Figure 2-9) 

 Ratio of annual total dry nitrogen deposition to annual average NO2 concentrations 

(Figure 2-13) 

 Ratio of annual total wet nitrogen deposition to annual average NO2 concentrations 

(Figure 2-14) 

 Ratio of annual total wet+dry nitrogen deposition to annual average NO2 concentrations 

(Figure 2-15). 

In addition to the above maps, we have also included in Appendix 2 the following maps 

showing the ratio of CMAQ predicted 2002 deposition to 2002 emissions (the corresponding 

Appendix 2 figure numbers are provided in parentheses): 

 Ratio of annual total dry sulfur deposition to annual total SO2 emissions (Figure 2-4) 

 Ratio of annual total wet sulfur deposition to annual total SO2 emissions (Figure 2-5) 

 Ratio of annual total wet+dry sulfur deposition to annual total SO2 emissions (Figure 2-6) 

 R

(

 R

ions 

 of annual total wet nitrogen deposition to annual total NO2 emissions (Figure 2-17) 

re 2-18). 

ON OF UNCERTAINTIES 

s; NOx and 

 deposition, as well as a more focused 

characterization of nitrogen and sulfur deposition for the aquatic and terrestrial case study areas. 

atio of annual total dry oxidized nitrogen deposition to annual total NO2 emissions

Figure 2-10) 

atio of annual total wet oxidized nitrogen deposition to annual total NO2 emissions 

(Figure 2-11) 

 Ratio of annual total wet+dry oxidized nitrogen deposition to annual total NO2 emiss

(Figure 2-12) 

 Ratio of annual total dry nitrogen deposition to annual total NO2 emissions (Figure 2-16) 

 Ratio

 Ratio of annual total wet+dry nitrogen deposition to annual total NO2 emissions 

(Figu

3.6 DISCUSSI

This section provides a nationwide overview of NOx, SOx, and NH3 emission

SOx concentrations; and nitrogen and sulfur
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-98 September 2009 

When considering the uncertainties in this analysis, it is important to recognize that t

characterization of deposition in the

he 

 case study areas and the estimates of deposition used as 

DP 

om the CMAQ model. The NADP data and the 

at 

ainty in the model predictions of dry deposition than there is in the 

ted 

of this analysis, but does not attempt to quantify these uncertainties. 

tainties Associated with Use of Model Predictions 

A key uncertainty for this assessment is the lack of true measurements of dry deposition 

for nitrogen and sulfur. As noted in Secti

flect local land use and 

y deposition predictions from the CMAQ model 

photochemical model, uncertainties in 

ulated chemistry and transport processes within 

x x

that affect th x and SOx through deposition. 

NH3 emissions and other emissions 

input to CMAQ vary based on the method and unde

ories is 

determined by Continuous Emissions Monitors. For many other source categories, emissions are 

input to our ecological modeling relied upon measurements of wet deposition from the NA

network and predictions of dry deposition fr

CMAQ predictions each contain a number of areas of uncertainty. In general, we expect th

there is greater uncert

measurements of wet deposition. This section identifies and describes uncertainties associa

with the various aspects 

3.6.1 Uncer

on 3.2, above, the dry-deposition estimates from 

CASTNet are calculated based on an “inferential model” involving measured air concentrations 

coupled with species- and location-dependent deposition velocities that re

meteorological conditions at each monitoring site (U.S. EPA, 2008b). These dry-deposition 

estimates may not be representative of dry-deposition fluxes in unmonitored areas where land 

use or meteorological conditions are different from those at monitoring sites. Therefore, to 

characterize deposition nationwide and across each case study area, as well as to provide 

deposition estimates for ecological modeling, dr

were used. 

Although CMAQ is a “state-of-the-science” 

CMAQ, like those in other photochemical models, arise due to uncertainties in model 

formulation and in the inputs that drive the sim

the model. The model formulation uncertainties most relevant for this assessment include the 

aspects of the non-linear photochemical processes that determine the chemical form and 

transformations of NO and SO in the atmosphere over multiday time periods, and the processes 

e removal of NO

The uncertainties associated with NOx, SOx, and 

rlying measurements used to determine or 

estimate the particular set of emissions. The least uncertain of the various source categ

likely to be emissions from electric generating units, because emissions from these sources are 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-99 September 2009 

based on the application of emissions factors to the sector’s activity data. Uncertainties i

emissions may increase for a particular source category if the types and extent of source 

measurements and analytical procedures used to derive emissions factors are not fully 

representative of the source category for which they are applied. For some source categories,

calculations of emissions involve complex models that may not fully represent actual levels o

emissions in a particular location at a particular time. In addition, activity data used in “to

down” inventories that allocate national emissions to individual counties may not properly refle

local emissions for all areas. Of the three key pollutants for this assessment (SO2, NOx, and NH

n 

 the 

f 

pct 

3) 

SO2 emission may be expected to have the least uncertainty. Emissions of SO2 are dominated by 

electric generation units issions 

Monito

e 

Ox concentrations in the lower troposphere and to nitrogen deposition. The 

uncerta the 

tion rates 

because 

al feeding operations and from 

fertilize unt 

s 

31 and, as noted above, most of these sources have Continuous Em

rs that measure SO2 on an hourly basis. Emissions of NOx are less certain than emissions 

of SO2. Although 22% of nationwide NOx emissions are based on Continuous Emissions 

Monitor data from electric generation units, 55% of the NOx emissions are estimated using onroad and nonroad mobile models that may not fully reflect emissions rates across all vehicle 

types and operating conditions. 

Not included in our CMAQ modeling are emissions of NOx from lightning which may b

a significant contributor to regional NOx concentrations in the middle and upper free 

troposphere. Estimates of lighting NOx emissions are highly uncertain (U.S. EPA, 2008b, 

Section 2.2.2.4), and more research is needed to adequately characterize the contributions of 

lightning to N

inties in current estimates of lightning NOx stem from several factors, including (1) 

magnitude of NO production rates per meter of flash length, (2) differential NO produc

due to cloud-to-ground compared to in-cloud flashes, and (3) flash rates for cloud-to-ground and

in-cloud flashes. 

Emissions of NH3 are likely to be more uncertain than emissions of NOx and SO2 

of significant gaps and uncertainties in measurements needed to characterize emissions factors, 

activity levels, and the temporal patterns of emissions at anim

d soils. In addition, estimates of NH3 emissions input to air quality models do not acco

for the extent of re-emissions of NH3 (i.e., “bi-directional flux”) that affects NH3 concentration

 

31 Nationwide, 70% of annual emissions of SO2 are from electric generation units. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-100 September 2009 

and NH4 deposition and the neutralization of sulfuric acid and nitric acid in the formation o

sulfate and nitrate particles, respectively. 

Uncertainties in meteorological inputs, including the presence of clouds and fog

occurrence and amount of precipitation, and the extent of vertical mixing, affect the uncertainty 

in model predictions of pollutant concentrations and deposition. The degree of uncertainty in 

these inputs may be greater in complex terrain, in part because the 12 x 12 km resolution use

for the model simulations may not be able to fully resolve finer-scale meteorological events, 

especially terrain-induced precipitation. In addition, the model simulations do not account for 

occult deposition. It is likely that the deposition in high-terrain areas and coastal locations has 

been underestimated where occult deposition may be most important. 

The results of a model performance evaluation of 2002 CMAQ predictions compared to 

corresponding measurements in 2002 are provided in Appendix 1. The purpose of this eva

is to determine the degree of comparability between predictions and observations. The model 

performance statistics do not necessarily represent a quantitative estimate of model uncertain

since, aside from uncertainties in

f 

, the 

d 

luation 

ty 

 the modeling system, uncertainties exist in the measurements 

and unc

s of 

et plus 

ea for the two forms of nitrogen deposition and for sulfur deposition. On 

average

ertainty is introduced by the incommensurability between the grid-cell average model 

predictions and the point measurements at monitoring sites. 

In the analysis to characterize deposition in each of the case study areas, prediction

dry deposition for 2002 from both CMAQv4.6 and CMAQv4.7 were used. The rationale for 

using two versions of CMAQ for this purpose is presented in Section 3.3.2. Annual total w

dry deposition for 2002 in each case study area is presented in Table 3.6-1, Table 3.6-2, and

Table 3.6-3 for oxidized nitrogen, reduced nitrogen, and sulfur, respectively. The estimates of 

annual total deposition from CMAQv4.6 are generally comparable to those from CMAQv4.7 for 

each case study ar

, across all case study areas, CMAQv4.7 is higher than v4.6 by 0.45 kg N/ha/yr for 

oxidized nitrogen, 0.09 kg N/ha/yr for reduced nitrogen, and 0.69 kg S/ha/yr for sulfur 

deposition. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-101 September 2009 

Table 3.6-1. Annual Total Wet Plus Dry Oxidized N

by CMAQv4.6 and CMAQ v4.7 for 2002 

itrogen Deposition (kg N/ha/yr) Predicted 

Oxidized Nitrogen Deposition 

Case Study Area CMAQ v4.7 CMAQ v4.6 (v4.7 - v4.6) 

Adirondack 7.52 6.87 0.65 

Hubbard Brook 

Experimental Forest 6.48 6.16 0.31 

Kane Experimental 

Forest 10.06 9.41 0.65 

Neuse River 6.51 5.90 0.61 

Potomac River 8.64 8.09 0.55 

Shenandoah 7.53 7.07 0.46 

Rocky Mountain 

National Park 1.79 1.90 -0.11 

Sierra Nevada 

Range 2.59 2.14 0.44 

Transverse Range 8.17 7.70 0.46 

 

Average 

Difference = 0.45 

Table 3.6-2. Annual Total Wet Plus Dry Reduced Nitrogen Deposition (kg N/ha/yr) Predicted 

by CMAQv4.6 and CMAQ v4.7 for 2002 

Reduced Nitrogen Deposition 

Case Study Area CMAQ v4.7 CMAQ v4.6 (v4.7 - v4.6) 

Adirondack 3.33 3.07 0.26 

Hubbard Brook 

Experimental Forest 2.42 2.39 0.03 

Kane Experimental 

Forest 3.21 2.97 0.23 

Neuse River 8.06 8.07 -0.01 

Potomac River 4.14 4.15 -0.01 

Shenandoah 3.96 3.98 -0.02 

Rocky Mountain 

National Park 0.93 0.74 0.18 

Sierra Nevada 

Range 1.35 1.19 0.16 

Transverse Range 1.81 1.84 -0.04 

 

Average 

Difference = 0.09 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-102 September 2009 

Table 3.6-3. Annual Total Wet Plus Dry Sulfur Deposition (kg S/ha/yr) Predicted by CMAQv4.6 

and CMAQ v4.7 for 2002 

Sulfur Deposition 

Case Study Area CMAQ v4.7 CMAQ v4.6 (v4.7 - v4.6) 

Adirondack 11.5 10.2 1.25 

Hubbard Brook 

Experimental Forest 9.0 8.3 0.71 

Kane Experimental 

Forest 23.0 21.6 1.43 

Neuse River 10.1 9.4 0.73 

Potomac River 16.2 15.3 0.91 

Shenandoah 12.9 12.0 0.90 

Rocky Mountain 

National Park 1.2 1.0 0.17 

Sierra Nevada 

Range 0.9 0.9 0.04 

Transverse Range 1.8 1.7 0.12 

 

Averag

 = 0.69 

e 

Difference

ng NOx and SOx concentrations and nitrogen and 

sulfur deposition levels include uncertainties and measurement 

protocols, as s in ent o nitoring networks for these 

pollutant species. Another aspect of uncertainty applicable to this analysis is iated with the 

combination of wet deposition from NADP measurements with dry deposition from CMAQ. For 

example, uncertainties in the modeling system may result in times when the transport patterns 

and precipitation events simulated in th el do not full n in space and time with actual 

atmospheri a particular lo n. This may result physical and chemical 

inconsistencies between the measured w position and deled dry d ion. For 

example, because the NADP sites are in non-urban areas, the spatial allocation of NADP wet 

deposition is unlikely to capture the influen issions sources, whereas the CMAQ 

predictions of dry deposition will more closely reflect urban sources. This m w the 

relationship between wet and dry deposition in and near urban/suburban areas, as well as in the 

vicinity of large point sources. 

3.6.2 Uncertainties Associated with Use of Measured Data 

Areas of uncertainty in characterizi

 in monitoring instrumentation

 well as limitation the spatial ext f existing mo

 assoc

e mod y alig

c conditions in catio

et de the mo eposit

ce of urban em

ay ske
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-103 September 2009 

3.6.3 Uncertainties of Wet Deposition in Complex Terrain 

In addition to the uncertainties identified above, there are uncertainties associated with 

the spatial resolutions of the measured and modele analysis. This includes 

uncertainties associated with (1) gridding th

(2) the repr f 12-km data for characterizing deposition in the case study areas, 

especially for those areas with complex terrain. To examine this issue, the 2002 12-km gridded 

NADP deposition fields were compared to outputs from a high-resolution wet deposition 

model32 (Grimm-Lynch), which provides fine-scale estim of deposition 002 based on 

an integrati precipitation and wet depositi

gridded wet deposition predictions we included in omparison since these data were 

used in Section 3.3.3.4 to characterize seasonal trends in deposition. For the purposes of this 

analysis, th h data was used as the benchmark even though there are also 

uncertaintie s data set. 

The analysis of spatial resolution was condu e Adirondack Case Study Area 

because this area has the highest elevations and the x terrain of all the case study 

reas in the eastern United States. The comparison of gridded data includes annual wet 

deposit 2-km CMAQ data, 

(b) 12- cale 

of 

tween the 

ppear 

the 

d data used in this 

e NADP measurements to a 12-km resolution and 

esentativeness o

ates for 2

on of measured on and topography. The CMAQ 12-km

re also this c

e Grimm-Lync

s in thi

cted for th

 most comple

a

ion of oxidized and reduced nitrogen and sulfur for 2002 for (a) 1

km NADP data, (c) fine-scale Grimm-Lynch data, and (d) an aggregation of the fine-s

data to 12 km. The 12-km aggregation of the fine-scale data was included to isolate the effects 

grid resolution from the confounding effects introduced by other properties and uncertainties of

the CMAQ and NADP data sets. Maps showing the magnitude and spatial patterns of wet 

deposition for the four data sets are provided in Figures 3.6-1, 3.6-2, and 3.6-3 for oxidized and 

reduced nitrogen deposition and for sulfur deposition, respectively. The figures reveal both 

similarities and differences in wet deposition. Comparing the native fine-scale Grimm-Lynch 

data to the 12-km aggregate of these data indicates only slight, very local differences be

fine-scale and 12-km deposition for each of the three deposition species. Thus, it does not a

that the use of the 12-km resolution data masks any significant terrain-induced features of 

deposition, at least for this case study area. There are both similarities and notable differences 

between the CMAQ, NADP, and Grimm-Lynch deposition fields at 12 km. Again, using 

Grimm-Lynch predictions as the benchmark, the NADP fields are perhaps too smooth while the 

 

32 Grimm, J.W. and J.A. Lynch. Enhanced Wet Deposition Estimates Using Modeled Precipitation Inputs. 

Environmental Monitoring and Assessment 90: 243-268, 2004. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-104 September 2009 

CMAQ ta sets show an area of 

relative

se 

erall, 

 predictions tend to show enhanced spatial gradients. All three da

ly high wet deposition which extends westward from Lake Ontario across the southwest

portion of the Adirondack Case Study Area. The Grimm-Lynch data also suggest that a 

secondary maximum of wet deposition extends from the northern border of the Adirondack Ca

Study Area southward into the central portion of the area. The CMAQ shows this feature as a 

small area of high deposition near the central part of the Adirondack Case Study Area. The 

secondary maximum does not appear to be captured by the NADP 12-km gridded data. Ov

the spatial patterns in nitrogen and sulfur deposition across the Adirondacks seen from the three

data sets examined here are similar to the patterns in NO3

-

 and SO4

2- wet deposition, 

respectively, found by Ito, Mitchell, and Driscoll (2002) based on an analysis of measured 

precipitation, temperature, precipitation chemistry, elevation and other factors. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-105 September 2009 

Figure 3.6-1. Fine-scale and 12-km annual total wet oxidized nitrogen deposition 

for the Adirondack Case Study Area and the surrounding region. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Figure 3.6-2. Fine-scale and 12-km annual total wet reduced nitrogen deposition 

for the Adirondack Case Study Area and the surrounding region. 

Final Risk and Exposure Assessment 3-106 September 2009 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-107 September 2009 

Figure 3.6-3. Fine-scale and 12-km annual total wet sulfur deposition for the 

Adirondack Case Study Area and the surrounding region. 

While there are uncertainties in the data, models, and techniques used for this assessment, 

this analysis relies upon the most applicable measurements and state-of-the-science models. In 

addition, we have attempted to use these data and models in a manner that considers their 

relative strengths and limitations. Although we are not able to quantify the uncertainties 

associated with the tools, data, and predictions used in this assessment, we recognize that 

measurement, modeling and other analytical research efforts by EPA, academia, and other 

organizations will, over time, increase the certainty of our ability to characterize nitrogen and 

sulfur deposition and concentrations for sensitive ecosystems in future risk and exposure 

assessments for a secondary NOx/SOx NAAQS review. 
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-108 September 2009 

3.7 REFERENCES 

Byun, D.W., and K.L. Schere. 2006. Review of the governing equations, computational 

algorithms, and other components of the models-3 Community Multiscale Air Quality 

(CMAQ) modeling system. Journal of Applied Mechanics Reviews 59(2):51–77. 

Clarke, J.F., E.S. Edgerton, and B.E. Martin. 1997. Dry deposition calculations for the Clean Air 

Status and Trends Network. Atmospheric Environment 31:3667–3678. 

Holland, H.D. 1978. The Chemistry of the Atmosphere and Oceans. New York: John Wiley & 

Sons. 

Ito, M. Mitchell, M.J. and Driscoll, C.T. 2002. Spatial patterns of precipitation quantity and 

chemistry and air temperature in the Adirondack region of New York. Atmospheric 

Environment Vol. 36: 1051-1062 

Levine, J.S., T. Bobbe, N. Ray, R.G. Witt, and A. Singh. 1999. Wildland Fires and the 

Environment: A Global Synthesis. Report no. UNEP/DEIAEW/TR.99.1. United Nations 

Environment Programme (UNEP), Division of Environmental Information, Assessment 

and Early Warning (DEIA&EW), Nairobi, Kenya. Available at 

http://www.na.unep.net/publications/wildfire.pdf. 

Seinfeld, J.H., and S.N. Pandis. 1998. Atmospheric Chemistry and Physics: From Air Pollution 

Sickles

heric 

: 

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tal Protection Agency, National 

Exposure Research Laboratory, Research Triangle Park, NC. 

to Climate Change. New York: John Wiley-Interscience Publishers. 

, J.E., and D.S. Shadwick. 2007a. Changes in air quality and atmospheric deposition in 

the eastern United States: 1990-2004. Journal of Geophysical Research 112(D17). 

Sickles, J.E., II, and Shadwick, D.S. 2007b. Seasonal and regional air quality and atmosp

deposition in the eastern United States, Journal of Geophysical Research, Vol. 112

D17302. 

U.S. EPA (Environmental Protection Agency). 1999. Science Algorithms of EPA Models-3 

Community Multiscale Air Quality (CMAQ) Modeling System. D.W. Byun and J.K

Ching, eds. EPA/600/R-99/030. U.S. Environmen
Chapter 3 – Sources, Ambient Concentrations, and Deposition 

Final Risk and Exposure Assessment 3-109 September 2009 

U.S. EPA (Environmental Protection Agency). 2006. 2002 National Emissions Inventory Data & 

twork, 

http://www.epa.gov/ttn/chief/net/2002inventory.html (accessed May 28, 2009). 

U.S. EP ends Network, 

2007 Annual Report. U.S. Environmental Protection Agency, Office of Air and 

ww.epa.gov/castnet/docs/annual_report_2007.pdf. 

or 

ection Agency, National Center for Environmental 

U.S. EP

 Agency, Office of Air 

ngton, DC. Available at 

Documentation. U.S. Environmental Protection Agency, Technology Transfer Ne

Clearinghouse for Inventories & Emissions Factors, Office of Air Quality Planning and

Standards, Research Triangle Park, NC. Available at 

A (Environmental Protection Agency). 2008a. Clean Air Status and Tr

Radiation, Clean Air Markets Division, Washington, DC. December. Available at 

http://w

U.S. EPA (Environmental Protection Agency). 2008b. Integrated Science Assessment (ISA) f

Oxides of Nitrogen and Sulfur–Ecological Criteria (Final Report). EPA/600/R08/082F. U.S. Environmental Prot

Assessment–RTP Division, Office of Research and Development, Research Triangle 

Park, NC. Available at http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=201485. 

A (Environmental Protection Agency). 2009. Clean Air Status and Trends Network 

(CASTNET). Online information. U.S. Environmental Protection

and Radiation, Clean Air Markets Division, Washi

http://www.epa.gov/CASTNET (accessed May 2009). 

Chapter 4 –Acidification 

4.0 ACIDIFICATION 

4.1 SCIENCE OVERVIEW 

Acidification is the decrease of 

acid neutralizing capacity in 

water or base saturation in soil 

caused by natural or 

anthropogenic processes. 

Air emissions of sulfur oxides (SOx), nitrogen oxides 

(NOx), and reduced forms of nitrogen (NHx) react in the 

atmosphere through a complex mix of reactions and 

thermodynamic processes in gaseous, liquid, and solid 

phases to form various acidifying compounds. These compounds are removed from the 

atmosphere through wet (e.g., rain, snow), cloud and fog, or dry (e.g., gases, particles) 

deposition. Deposition of SOx, NOx, and NHx leads to ecosystem exposure to acidification. The 

Integrated Science Assessment (ISA) for Oxides of Nitrogen and Sulfur–Ecological Criteria 

(Final Report) (ISA) (U.S. EPA, 2008) reports that acidifying deposition has altered major 

biogeochemical processes in the United States by increasing the sulfur and nitrogen content of 

soils, accelerating sulfate (SO4

2−

) and nitrate (NO3

−

) leaching from soil to drainage water, 

depleting soil exchangeable base cations (especially calcium [Ca2+] and magnesium [Mg2+]) from 

soils, and increasing the mobility of aluminum (Al) (U.S. EPA, 2008, Section 3.2.1) 

The extent of soil acidification is a critical factor that regulates virtually all acidificationrelated ecosystem effects from sulfur and nitrogen deposition. Soil acidification occurs in 

response to both natural factors and acidifying deposition (U.S. EPA, 2008, Section 3.2.1). 

Under conditions of low atmospheric deposition of nitrogen and sulfur, the naturally produced 

bicarbonate anion is often the dominant mobile anion, with SO4

2- and NO3-

 playing a limited role 

with respect to cation leaching. Increased atmospheric deposition of sulfur and nitrogen can 

result in marked increases in SO4

2- and NO3-

 soil fluxes resulting in the concomitant leaching of 

nutrient (Ca2+, Mg2+) and toxic (Aln+ and H+

 cations). 

Final Risk and Exposure Assessment 4-1 September 2009 
Chapter 4 –Acidification 

Acidification can impact the health of terrestrial and aquatic ecosystems. One of the 

effects of soil acidification is the increased mobility 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). 

Both the aquatic and terrestrial effects of acidification have been studied and are 

highlighted in this chapter. For each effect, information is presented on the following: 

 Ecological indicators, ecological responses, and ecosystem services 

 Characteristics of areas sensitive to acidification 

 Criteria for case study selection 

 Current conditions in case study areas 

 The ability to extrapolate case study findings to larger areas 

 Current conditions for these other areas 

 Ecological effect functions 

 Uncertainty and variability identified for the case studies. 

The case studies on aquatic acidification and terrestrial acidification were performed as 

part of this Risk and Exposure Assessment (Appendices 4 and 5, respectively) to aid in 

determining whether a link can be established between NOx and SOx deposition and ecosystem 

response. These case studies are also intended to test whether area-based risk and exposure 

assessments are a suitable method for predicting acidification effects on other ecosystems and 

geographic regions. The studies facilitate extrapolation of impacts from smaller-scale (yet 

representative) areas to other sensitive areas in the country. 

4.1.1 Aquatic Acidification 

The changes in major biogeochemical processes and soil conditions caused by acidifying 

deposition have significant ramifications for the water chemistry and biological functioning of 

associated surface waters. Surface water chemistry indicates the negative effects of acidification 

on the biotic integrity of freshwater ecosystems. Because surface water chemistry integrates the 

sum of terrestrial and aquatic processes that occur upstream within a watershed. Important 

terrestrial processes include nitrogen saturation, 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). 

Final Risk and Exposure Assessment 4-2 September 2009 
Chapter 4 –Acidification 

The Aquatic Acidification Case Study, reported in Appendix 4 and summarized in this 

chapter, is intended to estimate the ecological exposure and risk posed to aquatic ecosystems 

from the acidification effects of the deposition of nitrogen and sulfur for two sensitive regions of 

the eastern United States: the Adirondack Mountains and Shenandoah National Park (Virginia) 

and the surrounding areas of Virginia (henceforth referred to as the Adirondack Case Study Area 

and the Shenandoah Case Study Area, respectively). 

4.1.2 Terrestrial Acidification 

Deposition of NOx and SOx can result in acidification of some terrestrial ecosystems. 

Terrestrial acidification occurs as a result of both natural biogeochemical processes and 

acidifying deposition where strong mineral acids (e.g., H2SO4 and HNO3) are deposited or 

generated within the soil. If soil base saturation (i.e., the concentration of exchangeable base 

cations as a percentage of the total cation exchange capacity, or the sum total of exchangeable 

cations that a soil can absorb) is 20% to 25%, or lower, dissolved inorganic Al can be mobilized, 

leading to the leaching of Al from soils to surface waters (Reuss and Johnson, 1985). Because 

ecosystems and biological species may respond differently to acidic deposition, case studies have 

been used to illustrate the potential effects of acidification on different ecosystem and species. 

Section 4.3 of this chapter presents the quantitative approach used to analyze the acidification 

effects of total nitrogen, NOx (as a component of total nitrogen), and SOx deposition on red 

spruce and sugar maple. 

4.2 AQUATIC ACIDIFICATION 

For the purpose of this case study, acid neutralizing capacity (ANC) 

of surface waters is simply measured as the total amount of strong 

base ions minus the total amount of strong acid anions: 

ANC = (Ca2+ + Mg2+ + K+

 + Na+ + NH4) – (SO4

2- + NO3-

+ Cl-) 

The unit of ANC is usually microequivalents per liter (μeq/L). If the 

sum of the equivalent concentrations of the base cations exceeds 

those of the strong acid anions, then the ANC of a waterbody will 

be positive. To the extent 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 Ca2+ concentrations; lower 

ANC is generally associated with low pH and Al3+ concentrations 

and a greater likelihood of toxicity to biota. 

When sulfur or 

nitrogen leaches from soils to 

surface waters in the form of 

SO4

2- or NO3-

 an equivalent 

amount of positive cations, or 

countercharge, is also 

transported. This maintains 

electroneutrality. If the 

countercharge is provided by base cations, such as calcium (Ca2+), magnesium (Mg2+), sodium 

(Na+

), or potassium (K+), rather than hydrogen (H+) and aluminum (Al3+), the acidity of the soil 

Final Risk and Exposure Assessment 4-3 September 2009 
Chapter 4 –Acidification 

water is neutralized, but the base saturation of the soil is reduced. Continued SO4

2- or NO3-

leaching can deplete available base cation pools in the soil. As the base cations are removed, 

continued deposition and leaching of SO4

2- and/or NO3-

 (with H+ and Al3+) leads to acidification 

of soil water, and by connection, surface water. Loss of soil base saturation is a cumulative effect 

that increases the sensitivity of the watershed to further acidifying deposition. 

It is important to note that these chemical changes can occur over both long- and shortterm timescales. Short-term (i.e., hours or days) episodic changes in water chemistry have can 

also have significant biological effects. Episodic chemistry refers to conditions during 

precipitation or snowmelt events when proportionately more drainage water is routed through 

upper soil horizons that tends to provide less acid neutralizing than was passing through deeper 

soil horizons. Surface water chemistry has lower pH and acid neutralizing capacity (ANC) 

during events than during baseflow conditions. One of the most important effects of acidifying 

deposition on surface water chemistry is the short-term change in chemistry that is termed 

“episodic acidification.” Some streams may have chronic or base flow chemistry that is suitable 

for aquatic biota, but may be subject to occasional acidic episodes with lethal consequences. 

Episodic declines in pH and ANC are nearly ubiquitous in drainage waters throughout the 

eastern United States and are caused partly by acidifying deposition and partly by natural 

processes. 

The ISA concludes the following: Documented Evidence of Changes in 

Aquatic Biota Due to Acidifying Deposition 

Species 

 Mayflies, crustaceans, and mollusks from 

some streams 

 Salmonid fish, smallmouth bass 

(Micropterus dolomieu) 

 young-of-the year brook trout. 

Community 

 Species richness of plankton, 

invertebrates, and fish 

 Invertebrate taxa, including mayflies, 

amphipods, snails, and clams 

 Loss of species diversity and absence of 

several sensitive fish species 

 Early life stages more sensitive to acidic 

conditions than the young-of-the-year, 

yearlings, and adults. 

(U.S. EPA, 2008, Section 3.2.3.4) 

 The evidence is sufficient to infer a 

causal relationship between acidifying 

deposition and changes in 

biogeochemistry related to aquatic 

ecosystems. The strongest evidence 

comes from studies of changes in 

surface water chemistry, including 

concentrations of SO4

 2−

, NO3 −, 

dissolved inorganic Al and Ca, surface 

water pH, sum of base cations, ANC, 

and base cation surplus. 

 The evidence is sufficient to infer a 

causal relationship between acidifying deposition and changes in aquatic biota. The 

Final Risk and Exposure Assessment 4-4 September 2009 
Chapter 4 –Acidification 

strongest evidence comes from studies of aquatic systems exposed to elevated levels of 

acidifying deposition that support fewer species of fish, macroinvertebrates, and diatoms. 

Decreases in ANC and pH and increases in dissolved inorganic Al concentration 

contribute to declines in taxonomic richness of zooplankton, macroinvertebrates, and 

fish. 

4.2.1 Ecological Indicators, Ecological Responses, and Ecosystem Services 

4.2.1.1 Ecological Indicators 

Surface water chemistry is a primary indicator of acidification and the resulting negative 

effects on the biotic integrity of freshwater ecosystems. Chemical parameters can be used to 

assess effects of acidifying deposition on lake or stream acid-base chemistry. These receptors 

include surface water pH and concentrations of SO4

2-, NO3-

, Al, and Ca2+; the sum of base 

cations; and the recently developed base cation surplus. Another widely used water chemistry 

indicator for both atmospheric deposition sensitivity and effects is 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, Ca2+, and Al.

 ANC is also used 

because it integrates overall acid status and because surface water acidification models do a 

better job projecting ANC than they do for projecting pH and dissolved inorganic Al 

concentrations. The Aquatic Acidification Case Study, therefore, used ANC as the indicator of 

aquatic acidification. 

Process-based models, such as the Model of Acidification of Groundwater in Catchment 

(MAGIC) and PnET-BGC (an integrated biogeochemical model), use the ANC calculated from 

charge balance. 

4.2.1.2 Ecological Responses 

Low ANC coincides with effects on aquatic systems (e.g., individual species fitness loss 

or death, reduced species richness, altered community 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 (Schreck, 1981, 1982; Wedemeyer et al., 1990). For 

example, Sullivan et al. (2006) found a logistic relationship between fish species richness and 

ANC class for Adirondack Case Study Area lakes (Figure 4.2.-1, a) that indicates the probability 

Final Risk and Exposure Assessment 4-5 September 2009 
Chapter 4 –Acidification 

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 4.2-1, b). In fact, ANC has been found in various studies to be the best 

single indicator of the biological response and health of aquatic communities in acid-sensitive 

systems (Lien et al., 1992; Sullivan et al., 2006). 

Biota are generally not harmed when ANC values are >100 microequivalents per liter 

(μeq/L). The number of fish species also peaks at ANC values >100 μeq/L (Bulger et al., 1999; 

Driscoll et al., 2001; Kretser et al., 1989; Sullivan et al., 2006). Below 100 μeq/L, ANC fish 

fitness and community diversity begin to decline (Figure 4.2-1). At ANC levels between 100 

and 50 μeq/L, the fitness of sensitive species (e.g., brook trout, zooplankton) also begins to 

decline. When ANC concentrations are <50 μeq/L, they are generally associated with death or 

loss of fitness of biota that are sensitive to acidification (Kretser et al., 1989; Dennis and Bulger, 

1995). 

(a) (b) 

Figure 4.2-1. (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 significant relationship (p < .0001) between mean stream acid neutralizing 

capacity and the number of fish species. 

When ANC levels drop to <20 μeq/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, 

Final Risk and Exposure Assessment 4-6 September 2009 
Chapter 4 –Acidification 

1988; Driscoll et al., 2001). Stoddard et al. (2003) showed that to protect biota from episodic 

acidification in the springtime, base flow ANC levels need to have an ANC of at least 30–40 

μeq/L (Figure 4.1-1 of Appendix 4). 

Complete loss of fish populations and extremely low diversity of planktonic communities 

occur when ANC levels stay <0 μeq/L. Only acidophilic species are present, but their population 

numbers are sharply reduced (Sullivan et al., 2006). 

4.2.1.3 Ecosystem Services 

Because acidification primarily affects the diversity and abundance of aquatic biota, it 

also affects the ecosystem services that are derived from the fish and other aquatic life found in 

these surface waters. 

Provisioning Services 

Food and fresh water are generally the most important provisioning services provided by 

inland surface waters (MEA, 2005). Whereas acidification is unlikely to have serious negative 

effects on, for example, water supplies for municipal, industrial, or agricultural uses, it can limit 

the productivity of surface waters as a source of food (i.e., fish). In the northeastern United 

States, the surface waters affected by acidification are not a major source of commercially raised 

or caught fish; however, they are a source of food for some recreational and subsistence 

fishermen and for other consumers. Although data and models are available for examining the 

effects on recreational fishing, relatively little data are available for measuring the effects on 

subsistence and other consumers. For example, although there is evidence that certain population 

subgroups in the northeastern United States, such as the Hmong and Chippewa ethnic groups, 

have particularly high rates of self-caught fish consumption (Hutchison and Kraft, 1994; 

Peterson et al., 1994), it is not known if and how their consumption patterns are affected by the 

reductions in available fish populations caused by surface water acidification.

Cultural Services 

Inland surface waters support several cultural services, such as aesthetic and educational 

services; however, the type of service that is likely to be most widely and significantly affected 

by aquatic acidification is recreational fishing. Recreational fishing in lakes and streams is 

among the most popular outdoor recreational activities in the northeastern United States. Data 

from the 2006 National Survey of Fishing, Hunting, and Wildlife Associated Recreation 

Final Risk and Exposure Assessment 4-7 September 2009 
Chapter 4 –Acidification 

(FHWAR) indicate that >9% of adults in this part of the country participate annually in 

freshwater (excluding Great Lakes) fishing. The total number of freshwater fishing days 

occurring in those states (by both residents and nonresidents) in 2006 was 140.8 million days. 

Roughly two-thirds of these fishing days were at ponds, lakes, or reservoirs, and the remaining 

one-third were at rivers or streams. Based on studies conducted in the northeastern United States, 

Kaval and Loomis (2003) estimated average consumer surplus values per day of $35.91 for 

recreational fishing (in 2007 dollars); therefore, the implied total annual value of freshwater 

fishing in the northeastern United States was $5.06 billion in 2006. Consumer surplus value is a 

commonly used and accepted measure of economic benefit (see, for example, U.S. EPA, 2000). 

It is the difference between (1) the maximum amount individuals are, on average, willing and 

able to pay for a good, service, or activity (in this case, a day of recreational fishing) and (2) the 

amount they actually pay (in out-of-pocket and time costs). For recreation days, it is most 

commonly measured using recreation demand, travel cost models. 

Regulating Services 

In general, inland surface waters, such as lakes, rivers, and streams provide a number of 

regulating services associated with hydrological and climate regulation. There is little evidence 

that acidification of freshwaters in the northeastern United States has significantly degraded 

these services; however, freshwater ecosystems also provide biological control services by 

providing environments that sustain aquatic food webs. These services are certainly disrupted by 

the toxic effects of acidification on fish and other aquatic life. Although it is difficult to quantify 

these services and how they are affected by acidification, it some of these services may be 

captured through measures of provisioning and cultural services. 

4.2.2 Characteristics of Sensitive Areas 

The ISA reports that the principal factor governing the sensitivity of terrestrial and 

aquatic ecosystems to acidification from sulfur and nitrogen deposition is geology (particularly 

surficial geology). Geologic formations having low base cation supply generally underlie the 

watersheds of acid-sensitive 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. Surface waters in the same setting can have different sensitivities to 

acidification, depending on the relative contributions of near-surface drainage water and deeper 

groundwater (Chen et al., 1984; Driscoll et al., 1991; Eilers et al., 1983). Lakes and streams in 

Final Risk and Exposure Assessment 4-8 September 2009 
Chapter 4 –Acidification 

the United States that are sensitive to episodic and chronic acidification in response to SOx, and 

to a lesser extent NOX, 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). 

The regions of the United States with low surface water ANC values are sensitive to 

acidifying deposition. The majority of lakes and streams in the United States have ANC levels 

>200 μeq/L and are not sensitive to the deposition of NOx and SOx air pollution. Figure 4.2-2

shows the acid-sensitive regions of the eastern United States with the potential of low surface 

water ANC, as determined by geology and surface water chemistry. 

Freshwater surveys and monitoring in the eastern United States have been conducted by 

many programs since the mid-1980s, including EPA’s Environmental Monitoring and 

Assessment Program (EMAP), National Surface Water Survey (NSWS), Temporally Integrated 

Monitoring of Ecosystems (TIME) (Stoddard, 1990), and Long-term Monitoring (LTM) (Ford et 

al., 1993; Stoddard et al., 1998) programs. Based on analyses of surface water data from these 

programs, New England, the Adirondack Mountains, the Appalachian Mountains (northern 

Appalachian Plateau and Ridge/Blue Ridge region), northern Florida, and the Upper Midwest 

contain the most sensitive lakes and streams (i.e., ANC less than about 50 μeq/L) since the 

1980s. 

New England, the Adirondack Mountains, the northern Appalachian Plateau, the 

Ridge/Blue Ridge region, and the Upper Midwest contain 95% of the lakes and 84% of the 

streams in the United States that have been anthropogenically acidified through deposition. 

Stoddard et al. (2003) suggested that although improvement in ANC had occurred, ~8% of lakes 

in the Adirondack Mountains and from 6% to 8% of streams in the northern Appalachian Plateau 

and Ridge/Blue Ridge region were acidic at base-flow conditions. Because they are still 

receiving substantial NOx/SOx deposition inputs and still contain a large number of waterbodies 

that are acidic, areas in New England, the Adirondack Mountains, the Northern Appalachian 

Plateau, and the Ridge/Blue Ridge region provide ideal case study areas to assess the risk to 

aquatic ecosystems from NOx/SOx acidifying deposition. 

Final Risk and Exposure Assessment 4-9 September 2009 
Chapter 4 –Acidification 

Northern Florida 

Highlands 

Appa

Plateau 

Ridge/Blue Ridge 

Upper Mid-west 

New England 

Adirondack

Mountains 

Northern Florida 

Highlands 

Appalachian

Plateau 

Ridge/Blue Ridge 

Upper Midwest 

New England 

Mountains 

Figure 4.2-2. Ecosystems sensitive to acidifying deposition in the eastern United 

States (U.S. EPA, modified from NAPAP, 2005). 

4.2.3 Case Study Area Selection 

Selection of case study areas was based on Figure 4.2-2 (showing areas of the potential 

sensitivity to aquatic acidification), potential case study areas identified in the ISA (U.S. EPA, 

2008, Table 4-4), and sites recommended for consideration by the Ecological Effects 

Subcommittee (EES) of the Advisory Council for Clean Air Compliance Analysis (U.S. EPA, 

2005). Using the rationale described in the following subsections, the Adirondack Mountains and 

Shenandoah Mountains were selected for case study areas. 

4.2.3.1 Adirondack Case Study Area 

The Adirondack Case Study Area is situated in northeastern New York and is 

characterized by dense forest cover and abundant surface waters, with 46 peaks that extend up to 

1600 meters (m) in elevation. This area includes the headlands of five major drainage basins: 

Lake Champlain and the Hudson, Black, St. Lawrence, and Mohawk rivers. There are more than 

2,800 lakes and ponds, and more than 1,500 miles of rivers that are fed by an estimated 30,000 

miles of brooks and streams. 

Final Risk and Exposure Assessment 4-10 September 2009 
Chapter 4 –Acidification 

The Adirondack Case Study Area, particularly its southwestern section, is sensitive to 

acidifying deposition because it receives high precipitation amounts with high concentrations of 

pollutants, has shallow base-poor soils, and is underlain by igneous bedrock with low weathering 

rates and buffering ability (Driscoll et al., 1991; Sullivan et al., 2006). The Adirondack Case 

Study Area is among the most severely acid-impacted regions in North America (Driscoll et al., 

2003; Landers et al., 1988; Stoddard et al., 2003). It has long been used as an indicator of the 

response of forest and aquatic ecosystems to changes in emissions of sulfur dioxide (SO2) and 

NOx resulting, in part, from the Clean Air Act Amendments of 1990 (NAPAP, 1998; U.S. EPA, 

1995).

Wet deposition in the Adirondack Case Study Area has been monitored by the National 

Atmospheric Deposition Program/National Trends Network (NADP/NTN) since 1978 at two 

sites (i.e., Huntington Forest and Whiteface Mountain) and since the 1980s at seven other sites. 

Since 1990, wet SO4

-

 and NO3

-

 deposition at these NADP/NTN sites in the Adirondack Case 

Study Area has declined by about 45% and 40%, respectively (Figure 4.2-3). However, annual 

total wet deposition is still more than 15 and 10 kilograms/hectare/year (kg/ha/yr) of SO4

2- and 

NO3

-

, respectively. 

Final Risk and Exposure Assessment 4-11 September 2009 
Chapter 4 –Acidification 

Figure 4.2-3. Annual average total wet deposition (kg/ha/yr) for the period 1990 

to 2006 in SO4

2- (green) and NO3-

 (blue) from eight NADP/NTN sites in the 

Adirondack Case Study Area. 

4.2.3.2 Shenandoah Case Study Area 

The Shenandoah Case Study Area straddles 

the crest of the Blue Ridge Mountains in western 

Virginia, on the eastern edge of the central 

Appalachian Mountain region. Several areas in 

Shenandoah National Park have been designated 

Class 1 Wilderness areas. Shenandoah National 

Park is known for its scenic beauty, outstanding 

natural features, and biota. Air pollution within the 

Shenandoah Case Study Area, including 

concentrations of sulfur, nitrogen, and ozone (O3), 

“Bulger et al. (2000) predicted that future 

losses of native brook trout (Salvelinus 

fontinalis) populations in the streams of 

western Virginia will be substantial unless 

acidic deposition reductions are much 

greater than the 1990 Clean Air Act 

Amendments will provide...Despite recent 

declines in acidic deposition and some 

encouraging evidence for initial recovery in 

other parts of the country, recovery in the 

central Appalachian region in general, and 

the Shenandoah National Park in 

particular, has been limited and impairment 

of surface waters due to acidic deposition 

continues (Stoddard et al. 2003; Webb et 

al. 2004).” (Webb, 2004) 

Final Risk and Exposure Assessment 4-12 September 2009 
Chapter 4 –Acidification 

is higher than in most other national parks in the United States. 

This area is sensitive to acidifying deposition because it receives high precipitation, has 

shallow base-poor soils, and is underlain by igneous and silicon (Si)-based bedrock with low 

weathering rates and poor ANC. The Shenandoah Case Study Area is also among the most 

severely acid-impacted regions in North America (Stoddard et al., 2003; Webb et al., 2004). 

Wet deposition in the Shenandoah National Park monitored at 7 sites by the NADP/NTN 

since the 1980s shows wet SO4

2- and NO3-

 deposition declining by about 28% and 20%, 

respectively (Figure 4.2-4, a and b). However, annual total deposition is still over 15 and 10 

kg/ha/yr of SO4

2- and NO3-

, respectively. 

Figure 4.2-4. Air pollution concentrations and deposition for the period 1990 to 

2006 using one CASTNET and seven NADP/NTN sites in the Shenandoah Case 

Study Area. (a) Annual average air concentrations of SO2 (blue), oxidized 

nitrogen (red), SO4

2- (green), and reduced nitrogen (black). (b) Annual average 

total wet deposition (kg/ha/yr) of SO4

2- (green) and NO3-

 (blue).

Final Risk and Exposure Assessment 4-13 September 2009 
Chapter 4 –Acidification 

4.2.4 Current Conditions in Case Study Areas 

4.2.4.1 Surface Water Trends and Input Data 

Status of current conditions and trends in SO4

2- and NO3-

 concentrations and ANC 

measured in surface water were used to characterize links to the effects of acidifying deposition 

on the acid-base chemistry of a waterbody. Trends in these sensitive chemical receptors show 

whether the conditions of a waterbody are improving and heading toward recovery or are 

continuing to degrade. 

MAGIC Modeling and Input Data 

To assess surface water trends in SO4

2- and NO3-

 concentrations and ANC surface water 

monitoring data from the EPA-administered LTM program were used (see Appendix 4’s 

Attachment 4.B for more details on TIME/LTM network). Trends in SO4

2- and NO3-

concentrations and ANC were assessed using average yearly values for the period from 1990 to 

2006. 

The preacidification condition of a waterbody is rarely known because historical 

measurements are not available. Likewise, it is also difficult to empirically determine whether a 

waterbody has recovered or will recover from acidification as acidifying deposition inputs 

decline, because recovery may take many years to occur. For these reasons, biogeochemical 

models, such as MAGIC, enable estimates of past, present, and future water chemistry that can 

be used to evaluate (1) the associated risk and uncertainty of the current levels of acidification as 

compared with preacidification conditions, and (2) low concern (Table 4.2-1). 

MAGIC was used to determine the past (preacidification), present (2002 and 2008), and 

future (2020 and 2050) acidic conditions of 44 lakes in the Adirondack Case Study Area and 60 

streams in the Shenandoah Case Study Area (Figure 4.2-5). Furthermore, MAGIC was used to 

evaluate the associated risk and uncertainty of the current levels of acidification given the preacidification water quality and the levels of uncertainty in the input parameters. The MAGIC 

model output for each waterbody was summarized into five ANC levels that correspond to the 

aquatic status categories Acute Concern, Severe Concern, Elevated Concern, Moderate Concern, 

and Low Concern. This grouping offers an assessment of the current risk to the biota of current 

condition compared to preacidification and future conditions. Surface water chemistry data were 

used from two EPA-administered surface water monitoring and survey programs: the TIME and 

Final Risk and Exposure Assessment 4-14 September 2009 
Chapter 4 –Acidification 

the LTM programs. Average yearly ANC concentrations were calculated from annual 

measurements. 

Figure 4.2-5. (Top) The location of lakes in the Adirondack Case Study Area 

used for MAGIC (red dots) and critical load (green dots) modeling sites. 

(Bottom) The location of streams used for both MAGIC and critical load 

modeling for the Shenandoah Case Study Area. 

Final Risk and Exposure Assessment 4-15 September 2009 
Chapter 4 –Acidification 

Critical Load and Input Data 

Connecting current total nitrogen and sulfur deposition to acid-base conditions of lakes and 

streams: The critical load approach. The critical load approach was 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. Calculating critical load exceedances (i.e., the amount of deposition 

above the critical load) allows the determination of whether current deposition poses a risk of 

acidification to a given group of waterbodies. This approach also allows for the comparison of 

different levels of ANC thresholds (e.g., 0, 20, 50, 100 μeq/L) and their associated risk to the 

biological community. Table 4.2-1 provides a summary of the biological effects experienced at 

each of these limits.

Critical loads and their exceedances at four levels 

of biological protection were calculated for 169 lakes in 

the Adirondack Case Study Area and 60 streams in the 

Shenandoah Case Study Area. Four ANC limits (i.e., 

ANClimit) of biological protection were used: 0 μeq/L 

(acidic), 20 μeq/L (minimal protection), 50 μeq/L 

(moderate protection), and 100 μeq/L (full protection). A 

full and complete description of the biological effects at a 

given ANC limit appears in Appendix 4, Section 4.1. 

The critical load approach provides a 

means of gauging whether a group of 

lakes or streams in a given area 

receives deposition that results in a 

level of biological harm that is defined 

by an ANC concentration, known as 

the critical limit, which corresponds to 

harmful biological effects (e.g., ANC of 

50 μeq/L). A critical load estimate is 

analogous to determining the 

“susceptibility” of a waterbody to 

become acidified from the deposition 

of nitrogen and sulfur. Low critical load 

values (i.e., less than 50 meq/m2.yr) 

mean that the watershed has a limited 

ability to neutralize the addition of 

acidic anions, and hence, it is 

susceptible to acidification. The greater 

the critical load value, the greater the 

ability of the watershed to neutralize 

the additional acidic anions and protect 

aquatic life. 

From the 169 modeled lakes and 60 streams in the 

Adirondack and Shenandoah case study areas, 

respectively, the number and percentage of waterbodies 

that receive acidifying deposition above their critical 

loads for a given ANC limit of 0, 20, 50, and 100 μeq/L 

were determined. 

Final Risk and Exposure Assessment 4-16 September 2009 
Chapter 4 –Acidification 

Table 4.2-1. Aquatic Status Categories 

Category Label ANC Levels* Expected Ecological Effects 

Acute 

Concern 

<0 micro 

equivalent 

per Liter 

(μeq/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 μeq/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 μeq/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, including loss of health, reproduction 

capacity, and fitness. Diversity and distribution of zooplankton 

communities decline. 

Moderate 

Concern 

50–100 

μeq/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. Diversity and distribution of zooplankton 

communities also begin to decline as species that are sensitive to 

acidifying deposition are affected. 

Low 

Concern 

>100 μeq/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. 

4.2.4.2 Current Conditions in Adirondack Case Study Area Surface Waters 

Current and Preacidification 

Conditions of Surface Waters Table 4.2-2. Estimated Average 

Concentrations (and associated 

uncertainties) of Surface Water Chemistry at 

44 Lakes in the Adirondack Case Study Area 

Modeled Using MAGIC for Preacidification 

(1860) and Current (2006) Conditions 

Preacidification Current 

μeq/L Avg. (±) Avg. (±) 

ANC 120.3 13.6 62.1 15.7 

SO4

2- 12.4 2.1 66.1 1.24 

NO3

- 0.2 1.7 3.4 14.8 

NH4

+ 0.0 0.0 0.1 0.1 

Since the mid-1990s, lakes in the 

Adirondack Case Study Area have shown 

signs of improvement in NO3

-

 and SO4

2-

concentrations in surface waters. Wet 

deposition rates for SO2 and NOx, and their 

atmospheric reaction products, have decreased 

(see Figure 4.2-3), and, as a result, NO3

-

 and 

SO4

2- concentrations have decreased in surface 

Final Risk and Exposure Assessment 4-17 September 2009 
Chapter 4 –Acidification 

Final Risk and Exposure Assessment 4-18 September 2009 

Current NO3

-

 and SO4

2-

concentrations are 17- 

and 5-fold higher in 

Adirondack Case Study 

Area lakes today than 

they were in 1860. 

waters by approximately 26% and 13%, respectively (Figure 4.2-6). 

The decline in SO4

2- concentrations in surface waters in the Adirondack Case Study Area 

is −2.1 μeq/L/year, while the decline in NO3

- is −0.23 μeq/L/year. However, current 

concentrations of NO3

-

 and SO4

2- are still well above preacidification 

conditions based on MAGIC model simulations. Figure 4.2-7 and 

Figure 4.2-8 show the modeled condition of the lakes in 1860 

“preacidification” and in 2006 “current” conditions. On average, 

NO3

-

 and SO4

2- concentrations are 17- and 5-fold higher today, 

respectively (Table 4.2-2). 

Figure 4.2-6. Trends over time for SO4

2-, NO3-

, and acid neutralizing capacity in 

50 LTM lakes. SO4

2- and NO3-

 concentrations have decreased in surface waters by 

approximately 26% and 13%, respectively. 
Chapter 4 –Acidification 

Although NO3

-

 deposition can be an important factor in acid precipitation, these current 

results demonstrate that acidification in the Adirondack Case Study Area is currently being 

driven by SO4

2- deposition because the current average SO42- concentration in the 44 modeled 

lakes is some 19-fold greater than NO3

- concentrations in surface waters (Table 4.2-2). 

An increase in ANC of +1 μeq/L/year has corresponded to the declines in NO3

-

 and SO4

2-

,

despite reductions in base cations of Ca2+ and Mg2+ during the same period of time. This decline 

in base cation concentration is important because base cation supply neutralizes the inputs of 

NO3

-

 and SO4

2-, which will likely limit future recovery of ANC. In the Adirondack Case Study 

Area, levels of dissolved inorganic Al also declined slightly (data not shown). 

Based on the observed annual average concentration of ANC, there is still a substantial 

number of lakes in the Adirondack Case Study Area that have Elevated (i.e., ANC <50 μeq/L) to 

Severe (i.e., ANC <20 μeq/L) condition of acidity (Figure 4.2-9). 

Based on monitoring data, only 22% of monitored lakes are “not acidic,” which include 

the Moderate to Low Concern classes, and thus have water quality that poses little risk to aquatic 

biota. On the other hand, 78% of all monitored lakes have a current risk of Elevated, Severe, or 

Acute. Of that 78%, 31% experience episodic acidification (i.e., severe concern) and 18% are 

chronically acidic today (i.e., acute concern). 

Final Risk and Exposure Assessment 4-19 September 2009 
Chapter 4 –Acidification 

Figure 4.2-7. NO3

-

 concentrations of years 1860 (preacidification) and 2006 

(current) conditions based on hindcasts of 44 lakes in the Adirondack Case Study 

Area modeled using MAGIC. 

Final Risk and Exposure Assessment 4-20 September 2009 
Chapter 4 –Acidification 

Figure 4.2-8. SO4

2- concentrations of years 1860 (preacidification) and 2006 

(current) conditions based on hindcasts of 44 lakes in the Adirondack Case Study 

Area modeled using MAGIC.

Final Risk and Exposure Assessment 4-21 September 2009 
Chapter 4 –Acidification 

An estimate of the level of current 

condition at these lakes that can be attributed 

to the effects of industrially generated 

acidifying deposition can be made by 

examining the hindcast conditions of the lakes 

derived from the MAGIC model output. 

Based on these simulations, preacidification 

average ANC concentration of 44 modeled 

lakes was 120.3±13.6 ueq/L, as compared 

with 62.1±15.7 μeq/L for today (see Table 

4.2-2). Furthermore, 89% of the modeled 

lakes were likely “not acidic” prior to the 

onset of acidifying deposition (Figure 4.2-10 

and Figure 4.2-11). The other 11% of lakes 

have ANC of >20 μeq/L. The hindcast 

simulations produced no lakes with Acute or 

Severe Concern preacidification condition, suggesting that current ambient concentrations of 

NOx and SOx and their associated levels of NO3

-

 and SO4

2- deposition pose a risk of acidification 

to approximately 32% of modeled lakes. 

Figure 4.2-9. Acid neutralizing capacity 

concentrations from 88 lakes in the 

Adirondack Case Study Area. Monitoring 

data from the TIME/LTM programs.

Final Risk and Exposure Assessment 4-22 September 2009 
Chapter 4 –Acidification 

Final Risk and Exposure Assessment 4-23 September 2009 

Figure 4.2-10. Acid neutralizing capacity levels of preacidification (1860) and 

current (2006) conditions based on hindcasts of 44 modeled lakes in the 

Adirondack Case Study Area.

0

10

20

30

40

50

60

1860 2006

70

Acute (Below 0 :eq/L)

Severe (0–20 :eq/L)

Elevated (20–50 :eq/L)

Moderate (50–100 :eq/L)

Low (Above 100 :eq/L)

Figure 4.2-11. Percentage of Adirondack Case Study Area lakes in the five 

classes of acidification (i.e., Acute, Severe, Elevated, Moderate, Low) for years 

1860 (preacidification) and 2006 (current condition) for 44 lakes modeled using 

MAGIC. Error bar indicates the 95% confidence interval. 
Chapter 4 –Acidification 

The biological risk from current total nitrogen and sulfur deposition: Critical load 

assessment. In Figure 4.2-12, a critical load indicates the amount of acidic input of total sulfur 

and nitrogen deposition that a lake can neutralize and still maintain an ANC of 50 μeq/L. Sites 

labeled by red or orange circles have less neutralizing ability than sites labeled with yellow and 

green circles, and hence, indicate those lakes that are most sensitive to acidifying deposition, due 

to a host of environmental factors. Approximately 50% of the 169 lakes modeled in the 

Adirondack Case Study Area are sensitive or at risk to acidifying deposition. 

In Figure 4.2-13, a critical load exceedance “value” indicates combined total sulfur and 

nitrogen deposition in year 2002 that is greater than the amount of deposition the lake could 

neutralize and still maintain the ANC level above each of the four different ANC limits of 0, 20, 

50, and 100 μeq/L. For the year 2002, 18%, 28%, 44%, and 58% of the 169 lakes modeled 

received levels of combined total sulfur and nitrogen deposition that exceeded their critical load 

with critical limits of 0, 20, 50, and 100 μeq/L, respectively (Table 4.2-3). 

Figure 4.2-12. Critical loads of acidifying deposition that each surface waterbody 

in the Adirondack Case Study Area can receive while maintaining or exceeding an 

acid neutralizing capacity concentration of 50 μeq/L based on 2002 data. 

Watersheds with critical load values <100 meq/m2

/yr (red and orange circles) are 

most sensitive to surface water acidification, whereas watersheds with values >100 

meq/m2.yr (yellow and green circles) are the least sensitive sites.

Final Risk and Exposure Assessment 4-24 September 2009 
Chapter 4 –Acidification 

Figure 4.2-13. Critical load exceedances (red circles) based on 2002 deposition 

magnitudes for Adirondack Case Study Area waterbodies where the critical limit 

acid neutralizing capacity is 0, 20, 50, and 100 μeq/L, respectively. Green circles 

represent lakes where current total nitrogen and sulfur deposition is below the 

critical load (see Table 4.2-3). 

Final Risk and Exposure Assessment 4-25 September 2009 
Chapter 4 –Acidification 

Recovery from Acidification Given Current Emission Reductions. 

In considering the future responses of lakes, the question becomes whether lakes can 

recover to healthy systems (i.e., ANC > 50 μeq/L) under current levels of deposition. The 

forecast model runs using MAGIC were used to determine whether current deposition could lead 

to recovery of the acidified lakes. 

Based on a 

deposition scenario that 

maintains current emission 

levels up to years 2020 and 

2050, the simulation forecast 

indicates no improvement in 

water quality over either of 

the periods. The percentage 

of lakes within the Elevated

to Acute Concern classes 

remains the same in 2020 and 2050. Moreover, the percentage of modeled lakes classified as 

“not acidic” remains the same, suggesting that current emission will not likely improve the 

recovery from acidification. 

Table 4.2-3. Critical Load Exceedances (Nitrogen + Sulfur 

Deposition > Critical Load) for 169 Modeled Lakes Within the 

TIME/LTM and EMAP Survey Programs. “No. Lakes” 

Indicates the Number of Lakes at the Given Acid Neutralizing 

Capacity Limit; “% Lakes” Indicates the Total Percentage of 

Lakes at the Given Acid Neutralizing Capacity Limit

ANC Limit 

100 μeq/L 

ANC Limit 

50 μeq/L 

ANC Limit 

20 μeq/L 

ANC Limit 

0 μeq/L 

No. 

Lakes

% 

Lakes

No. 

Lakes

% 

Lakes

No. 

Lakes

% 

Lakes 

No. 

Lakes

% 

Lakes

98 58 74 44 47 28 30 18 

Lake No. = 169 

4.2.4.3 Current Conditions in Shenandoah Case Study Area Surface Waters 

Current and Preacidification Conditions of Surface Waters 

Since the mid-1990s, streams in the Shenandoah Case Study Area have shown slight 

signs of improvement in NO3

-

 and SO4

2- concentrations in surface waters. Deposition of SOx and 

NOx has decreased, but has not resulted in much improvement in NO3

-

 and SO4

2- stream 

concentrations (Figure 4.2-14). However, ANC concentrations increased from the about 50 

μeq/L in the early 1990 to >75 μeq/L until 2002, when ANC levels declined back to 1991 to 

1992 levels (Figure 4.2-14). It is not known what has caused this temporal pattern of ANC in 

this case study.

Final Risk and Exposure Assessment 4-26 September 2009 
Chapter 4 –Acidification 

Figure 4.2-14. Trends over time for SO4

2- (blue), NO3-

 (green) and acid 

neutralizing capacity (red) concentrations in VTSSS LTM-monitored 

streams in the Shenandoah Case Study Area. 

The slight decline in SO4

2-

concentrations in surface waters of the 

Shenandoah Case Study Area is −0.09 

μeq/L/year, while the decline in NO3

- is −0.1 

μeq/L/year. Current concentrations of NO3

-

 and 

SO4

2- are still well above preacidification 

conditions based on MAGIC model 

simulations. Figure 4.2-15 and Figure 4.2-16

show the condition of the streams in 1860 

(preacidification) and in 2006 (current) 

conditions. On average, NO3

-

 and SO4

2- 

concentrations are 10- and 32-fold higher today, respectively (Table 4.2-4). 

Table 4.2-4. Model Simulated Average 

Concentrations (and associated uncertainties) 

for Stream Chemistry at 60 Modeled Streams 

in the Shenandoah Case Study Area for 

Preacidification and Current Conditions

PreAcidification Current 

μeq/L Avg. (±) Avg. (±) 

ANC 101.4 9.5 57.9 4.5 

SO4

2- 2.1 0.1 68.0 8.4 

NO3

- 0.6 0.01 6.2 0.1 

NH4

+ N/A N/A N/A N/A 

N/A = Not available. 

Final Risk and Exposure Assessment 4-27 September 2009 
Chapter 4 –Acidification 

Final Risk and Exposure Assessment 4-28 September 2009 

Current NO3

-

 and SO4

2-

concentrations are 10- and 

32-fold higher in Shenandoah 

Case Study Area streams 

today than in 1860. 

Although NO3

-

 deposition can be an important factor in 

acid precipitation, these results demonstrated that acidification 

in the Shenandoah Case Study Area is currently being driven 

by SO4

2- deposition since current average SO42- concentration 

is 11-fold greater than NO3

- concentrations in surface waters (Table 4.2-4). 

An increase in ANC concentrations of +0.08 μeq/L/year has occurred since 1990, but for 

the majority of the 68 monitoring sites of the Shenandoah Case Study Area, ANC levels did not 

significantly differ from 1990 to 2006. 

Figure 4.2-15. NO3

-

 concentrations of preacidification (1860) and current (2006) 

conditions based on hindcasts of 60 streams modeled using MAGIC in the 

Shenandoah Case Study Area. 

Based on the monitored annual average for ANC, there are a significant number of 

streams in the Shenandoah Case Study Area that currently have Elevated (ANC <50 μeq/L) to 

Severe (ANC <20 μeq/L) classes of acidity (Figure 4.2-17). Only 45% of monitored streams are 

considered “not acidic” (i.e., of Moderate to Low Concern) and thus have water quality that 

poses less risk to aquatic biota. Approximately 55% of all monitored streams have a current risk 

of Elevated, Severe, or Acute Concern. Of that 55%, 18% experience episodic acidification 
Chapter 4 –Acidification 

(Severe Concern) and 12% are chronically acidic (i.e., Acute Concern) at current level of 

acidifying deposition and ambient concentration of NOx and SO2. 

An estimate of how much of this current condition is attributed to the effects of 

acidifying deposition can be made by examining the hindcast conditions of the streams. Based on 

the MAGIC model simulations, preacidification average ANC concentration of the 60 modeled 

streams was 101.4±9.5 μeq/L, as compared with 57.9 ±4.5 μeq/L for today (Table 4.2-4). 

Figure 4.2-16. SO4

2- concentrations of preacidification (1860) and current (2006) 

conditions based on hindcasts of 60 streams modeled using MAGIC in the 

Shenandoah Case Study Area.

Final Risk and Exposure Assessment 4-29 September 2009 
Chapter 4 –Acidification 

Figure 4.2-17. Acid neutralizing capacity concentrations from 67 streams in the 

VTSSS-SWAS/LTM monitoring network in the Shenandoah Case Study Area 

(2005–2006 data). 

Furthermore, 92% of the modeled streams likely were “not acidic” prior to the onset of 

acidifying deposition (Figure 4.2-18 and Figure 4.2-19). The other 8% of streams had ANC of 

>27 μeq/L. The hindcast simulations produced no streams with Acute or Severe Concern. These 

results based on model reconstructions suggest that current and recent ambient concentrations of 

NO3

-

 and SO4

2- and their associated anthropogenic acidifying deposition are likely responsible 

for acidifying (ANC below 50 μeq/L) approximately 45% of streams modeled in the Shenandoah 

Case Study Area. 

Final Risk and Exposure Assessment 4-30 September 2009 
Chapter 4 –Acidification 

Final Risk and Exposure Assessment 4-31 September 2009 

Figure 4.2-18. Acid neutralizing capacity concentrations of preacidification 

(1860) and current (2006) conditions based on hindcasts of 60 streams modeled 

using MAGIC in the Shenandoah Case Study Area. 

0

10

20

30

40

50

1860 2006

60

Acute (Below 0 :eq/L)

Severe (0–20 :eq/L)

Elevated (20–50 :eq/L)

Moderate (50–100 :eq/L)

Low (Above 100 :eq/L)

Figure 4.2-19. Percentage of streams in the five classes of acidification (i.e., 

Acute, Severe, Elevated, Moderate, Low Concern) for years 2006 and 1860 (preacidification) for 60 streams modeled using MAGIC in the Shenandoah Case 

Study Area. The number of streams in each class is above the bar. Error bars 

indicate the 95% confidence interval. 
Chapter 4 –Acidification 

The biological risk from current total nitrogen and sulfur deposition: Critical load 

assessment. In Figure 4.2-20, sites labeled by red or orange circles have less ability to neutralize 

acid inputs than sites labeled with yellow and green circles, and hence, indicate those streams 

that are most sensitive to acidifying deposition, due to a host of environmental factors. 

Approximately 75% of the 60 streams modeled in the Shenandoah Case Study Area are sensitive 

or at risk to acidifying deposition.

Figure 4.2-20. Critical loads of surface water acidity for an acid neutralizing 

capacity concentration of 50 μeq/L for streams in the Shenandoah Case Study 

Area. Each circle represents an estimated amount of acidifying deposition (i.e., 

critical load) that each stream’s watershed can receive and still maintain a surface 

water acid neutralizing capacity concentration >50 μeq/L. Watersheds with 

critical load values <100 meq/m2

/yr (red and orange circles) are most sensitive to 

surface water acidification, whereas watersheds with values >100 meq/m2

/yr 

(yellow and green circles) are the least sensitive sites.

In Figure 4.2-21, a critical load exceedance “value” indicates combined total sulfur and 

nitrogen deposition in year 2002 that is greater than the amount of deposition the stream could 

buffer and still maintain the ANC level of above each of the four different ANC limits of 0, 20, 

50, and 100 μeq/L. For the year of 2002, 52%, 72%, 85%, and 92% of the 60 streams modeled 

receive levels of combined total sulfur and nitrogen deposition that exceeded their critical load 

with critical limits of 0, 20, 50, and 100 μeq/L, respectively (Table 4.2-5). 

Final Risk and Exposure Assessment 4-32 September 2009 
Chapter 4 –Acidification 

Figure 4.2-21. Critical load exceedances for acid neutralizing capacity 

concentrations of 0, 20, 50, and 100 μeq/L for streams in the Shenandoah Case 

Study Area. Green circles represent lakes where current total nitrogen and sulfur 

deposition is below the critical load and that maintain an acid neutralizing capacity 

concentration of 0, 20, 50, and 100 μeq/L, respectively. Red circles represent 

streams where current total nitrogen and sulfur deposition exceeds the critical load, 

indicating they are currently impacted by acidifying deposition. See Table 4.2-5.

Final Risk and Exposure Assessment 4-33 September 2009 
Chapter 4 –Acidification 

Table 4.2-5. Critical Load Exceedances (Nitrogen + Sulfur Deposition > Critical Load) for 60 

Modeled Streams Within the VTSSS-LTM Monitoring Program in the Shenandoah Case Study 

Area. “No. Streams” Indicates the Number of Streams at the Given Acid Neutralizing Capacity 

Limit; “% Streams” Indicates the Total Percentage of Streams at the Given Acid Neutralizing 

Capacity Limit. 

ANC Limit 

100 μeq/L 

ANC Limit 

50 μeq/L 

ANC Limit 

20 μeq/L 

ANC Limit 

0 μeq/L 

No. 

Streams 

% 

Streams 

No. 

Streams

% 

Streams

No. 

Streams 

% 

Streams 

No. 

Streams 

% 

Streams

55 92 51 85 43 72 31 52 

Stream No. = 60 

Recovery from Acidification Given Current Emission Reductions 

Based on a deposition scenario that maintains current emission levels up to years 2020 

and 2050, a large number of streams in the Shenandoah Case Study Area will still have Elevated

to Acute problems with acidity. In the short term (i.e., by the year 2020) and in the long term 

(i.e., by the year 2050), the response of the 60 modeled streams shows no improvement in the 

number of streams that are “not acidic.” In fact, the modeling suggests conditions may degrade 

by 2050 under current emission levels. From 2006 to 2050, the percentage of streams in Acute 

Concern increases by 5%, while the percentage of streams in Moderate Concern decreases by 

5%. 

4.2.5 Degree of Extrapolation to Larger Assessment Areas 

The EPA EMAP and Regional-EMAP (REMAP) surveys have been conducted on lakes 

and streams throughout the United States with the objective of characterizing the ecological 

condition of various populations of surface waters. EMAP surveys are probability surveys where 

sites are selected using a spatially balanced systematic randomized sample, so that the results can 

be used to make regional estimates of surface water conditions (e.g., number of lakes, length of 

stream). Sampling typically consists of measures of aquatic biota, water chemistry, and physical 

habitat. With respect to acidifying deposition effects, two EMAP surveys were conducted in the 

1990s: the Northeastern Lake Survey and the Mid-Atlantic Highlands Assessment (MAHA) of 

streams. To make more precise estimates of the effects of acidifying deposition, the sampling 

grid was intensified to increase the sample-site density in the Adirondack Case Study Area and 

New England Upland areas known to be especially susceptible to acidifying deposition. The 

Final Risk and Exposure Assessment 4-34 September 2009 
Chapter 4 –Acidification 

MAHA study was conducted on 503 stream sites from 1993 to 1995 in the states of West 

Virginia, Virginia, Pennsylvania, Maryland, and Delaware and the Catskill Mountain region of 

New York (Herlihy et al., 2000). Results from both of these surveys were used to develop and 

select the sampling sites for the TIME program. 

The TIME program and the LTM program are two surface water chemistry monitoring 

programs, administered by EPA, that inform the assessment of aquatic ecosystem responses to 

changes in atmospheric deposition. These efforts focus on portions of the United States most 

affected by the acidifying influence of total sulfur and nitrogen deposition, including lakes in the 

Adirondack Case Study Area and in New England, and streams in the Shenandoah Case Study 

Area. 

At the core of the TIME project is the concept of probability sampling, whereby each 

sampling site is chosen statistically from a predefined target population. The target populations 

in these regions include lakes and streams likely to be responsive to changes in acidifying 

deposition, defined in terms of ANC. Measurement of Gran ANC uses the Gran technique to find 

the inflection point in an acid-base titration of a water sample (Gran, 1952). In the Northeast, the 

TIME target population consists of lakes with a Gran ANC <100 μeq/L. In the mid-Atlantic, the 

target population is upland streams with Gran ANC <100 μeq/L. In both regions, the sample sites 

selected for future monitoring were selected from the EMAP survey sites in the region that met 

the TIME target population definition. Each lake or stream is sampled annually (in summer for 

lakes; in spring for streams), and results are extrapolated with known confidence to the target 

population(s) as a whole using the EMAP site population expansion factors or weights (Larsen et 

al., 1994; Larsen and Urquhart, 1993; Stoddard et al., 1996; Urquhart et al., 1998). 

Data from 43 Adirondack Case Study Area lakes can be extrapolated to the target 

population of low ANC lakes in that region. There are about 1,000 low-ANC Adirondack Case 

Study Area lakes, out of a total population of 1,842 lakes with surface areas greater than 1 

hectare (ha). Data from 30 lakes (representing about 1,500 low-ANC lakes, out of a total 

population of 6,800) form the basis for TIME monitoring in New England. Probability 

monitoring of mid-Atlantic streams began in 1993. Stoddard et al. (2003) analyzed data from 30 

low-ANC streams in the Northern Appalachian Plateau (representing about 24,000 kilometer 

(km) of low-ANC stream length out of a total stream length of 42,000 km). After pooling TIME 

target sites taken from both MAHA and another denser random sample in 1998, there are now 21 

Final Risk and Exposure Assessment 4-35 September 2009 
Chapter 4 –Acidification 

TIME sites in the Blue Ridge and Ridge and Valley that can be used for trend detection in this 

aggregate region in the mid-Atlantic in addition to the Northern Appalachian Plateau ecoregion. 

As a complement to the statistical lake and stream sampling in TIME, the LTM program 

samples a subset of generally acid-sensitive lakes and streams that have long-term data, many 

dating back to the early 1980s. These sites are sampled 3 to 15 times per year. Monitored water 

chemistry variables include pH, ANC, major anions and cations, monomeric Al, Si, specific 

conductance, dissolved organic carbon, and dissolved inorganic carbon. Details of LTM data 

from each region include the following: 

 New England lakes. Data from 24 New England lakes were available for the trend 

analysis reported by Stoddard et al. (2003) for the time period 1990 to 2000. The majority 

of New England LTM lakes have mean Gran ANC values ranging from 20 to 100 μeq/L; 

two higher ANC lakes (Gran ANC between 100 and 200 μeq/L) are also monitored. 

 Adirondack lakes. The trend analysis of Stoddard et al. (2003) included data from 48 

Adirondack lakes. Sixteen of the lakes have been monitored since the early 1980s; the 

others were added to the program in the 1990s. The Adirondack LTM dataset includes 

both seepage and drainage lakes, most with Gran ANC values in the range –50 to 100 

μeq/L; three lakes with Gran ANC between 100 μeq/L and 200 μeq/L are also monitored. 

 Appalachian Plateau streams. Data from four streams in the Catskill Mountains 

(collected by the USGS; Murdoch and Stoddard, 1993) and five streams in Pennsylvania 

(collected by Pennsylvania State University; DeWalle and Swistock, 1994) were 

analyzed by Stoddard et al. (2003). All of the Northern Appalachian LTM streams have 

mean Gran ANC values in the range 25 to 50 μeq/L. 

 Upper Midwest lakes. Forty lakes in the Upper Midwest were originally included in the 

LTM project, and due to funding constraints, sampling has continued at only a subset of 

Wisconsin lakes, as well as an independent subset of seepage lakes in the state. The data 

reported by Stoddard et al. (2003) included 16 lakes (both drainage and seepage) sampled 

quarterly (Webster et al., 1993) and 22 seepage lakes sampled annually in the 1990s. All 

of the Upper Midwest LTM lakes exhibit mean Gran ANC values from 30 to 80 μeq/L. 

 Ridge/Blue Ridge streams. Data from the Ridge and Blue Ridge provinces consist of a 

large number of streams sampled quarterly throughout the 1990s as part of the Virginia 

Trout Stream Sensitivity Study (Webb et al., 1989) and a small number of streams 

sampled more intensively (as in the Northern Appalachian Plateau). A total of 69 streams 

Final Risk and Exposure Assessment 4-36 September 2009 
Chapter 4 –Acidification 

had sufficient data for the trend analyses by Stoddard et al. (2003). All of these streams 

were located in the Ridge section of the Ridge and Valley province or within the Blue 

Ridge province, and all were within the state of Virginia. Mean Gran ANC values for the 

Ridge and Blue Ridge data range from 15 to 200 μeq/L, with 7 of the 69 sites exhibiting 

mean Gran ANC >100 μeq/L. 

Appendix 4’s Attachment 4.B of the Aquatic Acidification case study report provides a 

more complete discussion of the EMAP/TIME/LTM programs.

4.2.6 Current Conditions for the Adirondack Case Study Area and the 

Shenandoah Case Study Area 

4.2.6.1 Regional Assessment of All Lakes in the Adirondack Case Study Area 

Estimating regional risks due to ambient NOx and SOx concentrations and deposition 

associated with acidification in lakes involved scaling up from the 169 modeled lakes to the 

entire population of lakes in the Adirondack Case Study Area. Of the 169 lakes modeled for 

critical loads, 117 of these lakes were within the 1,842 in the entire Adirondack Case Study 

Area. Using weighting factors derived from the EMAP probability survey and critical load 

calculations from the 117 lakes, estimates of exceedances were derived for the entire 1,842 lakes 

in the Adirondack Case Study Area. Based on this approach, 945, 666, 242, and 135 lakes 

exceed their critical load for ANC limits of 100, 50, 20, and 0 μeq/L, respectively (Table 4.2-6). 

Given a low level of protection from acidification (i.e., an ANC limit of 20 μeq/L), the 

current risk of acidification is 242 lakes, or 13% of the total population. Because some lakes in 

the Adirondack Case Study Area have natural sources of acidity, some lakes would have never 

had ANC concentrations of above 50 and 100 μeq/L. For this reason, the actual number of lakes 

at risk of acidification at an ANC level of 50 and 100 μeq/L is lower than the estimate based 

solely using the critical load criterion. Using the hindcast simulation from the MAGIC model, 

11% of modeled lakes have preacidification (1860) ANC levels of less than 50 μeq/L. Excluding 

these naturally acidic lakes, the current risk of acidification is 666 lakes or 36% for a moderate 

protective ANC concentration of 50 μeq/L. For an ANC level of 100 μeq/L, 51% of lakes have 

natural ANC concentrations below 100 μeq/L. Excluding these naturally acidic lakes, the current 

risk is 945 lakes or 51% for a protective ANC concentration of 100 μeq/L. Even with corrections 

Final Risk and Exposure Assessment 4-37 September 2009 
Chapter 4 –Acidification 

for natural acidity, 8 to 41% of lakes in the Adirondack Case Study Area are at risk of 

acidification given current ambient concentration of NOx and SO2. 

Because some lakes in the Adirondack Case Study Area have natural sources of acidity, 

some lakes would never have ANC concentrations above 50 or 100 μeq/L, even in the absence of 

all anthropogenically derived acidifying deposition. Based on the hindcast simulations of 44 

lakes using the MAGIC model, no modeled lakes have ANC levels below 20 μeq/L. However, 5 

modeled lakes or 11% have ANC concentrations between 22 and 47 μeq/L. This equates to 

approximately 300 lakes or 16% of the representative population of lakes in the Adirondack Case 

Study Area that likely had preacidification ANC concentrations below 50 μeq/L. On the other 

hand, potentially more than 52% of lakes likely had preacidification ANC concentrations below 

100 μeq/L. The higher percentage of lakes in the regional population compared to the modeled 

population is because the lake classes or sizes likely to have a preacidification ANC 

concentration below 50 or 100 μeq/L are more abundant in the Adirondack Case Study Area than 

lakes with a preacidification ANC concentration above 50 or 100 μeq/L. 

Table 4.2-6. Critical Load Exceedances (Nitrogen + Sulfur Deposition > Critical Load) for the 

Regional Population of 1,842 Lakes in the Adirondack Case Study Area That Are from 0.5 to 

2000 ha in Size and at Least 1 m in Depth. Estimates Are Based on the EMAP Lake Probability 

Survey of 1991 to 1994. 

ANC Limit 

100 μeq/L 

ANC Limit 

50 μeq/L 

ANC Limit 

20 μeq/L 

ANC Limit 

0 μeq/L 

No. 

Lakes 

% 

Lakes 

No. 

Lakes 

% 

Lakes 

No. 

Lakes 

% 

Lakes 

No. 

Lakes 

% 

Lakes 

945 51 666 36 242 13 135 7 

Lake No. = 1842 

4.2.6.2 Regional Assessment of All Streams in the Shenandoah Case Study Area 

The 60 trout streams modeled are characteristic of first- and second-order streams on 

nonlimestone bedrock in the Shenandoah Case Study Area. Because of the strong relationship 

between bedrock geology and ANC in this region, it is possible to consider the results in the 

context of similar trout streams in the Southern Appalachian Mountains that have similar 

bedrock geology and size. The total number of brook trout streams in the Shenandoah Case 

Study Area represented is 440, of which 308 lie on limestone and/or have not been significantly 

affected by human activity within their watersheds. In addition, the 60 modeled streams are a 

Final Risk and Exposure Assessment 4-38 September 2009 
Chapter 4 –Acidification 

subset of 344 streams sampled by the Virginia Trout Stream Sensitivity Study, of which 304 

represent the different sizes and bedrock types found to be sensitive to acidification. Using the 

304 streams to which the analysis applies directly as the total, 279, 258, 218, and 157 streams 

exceed their critical load for 2002 deposition with critical limits of 100, 50, 20, and 0 μeq/L, 

respectively. However, it is likely that many more of the ~12,000 trout streams in the 

Shenandoah Case Study Area would exceed their critical load given the extent of similar bedrock 

geology outside the study area in the Southern Appalachian Mountains. 

4.2.7 Ecological Effect Function for Aquatic Acidification 

Atmospheric deposition of NOx and SOx contributes to acidification in aquatic 

ecosystems through the input of acid anions, such as NO3

-

 and SO4

2-. The acid balance of 

headwater lakes and streams is controlled by the level of this acidifying deposition of NO3

-

 and 

SO4

2- and a series of biogeochemical processes that produce and consume acidity in watersheds. 

In basic soils, inputs of NO3

-

 and SO4

2- will have little or no effect on the acid balance of 

headwater waterbodies. The biotic integrity of freshwater ecosystems is then a function of the 

acid-base balance and the resulting acidity-related stress on the biota that occupy the water. 

The calculated ANC of the surface waters is a measure of the acid-base balance: 

ANC = [BC]* - [AN]* (1) 

where [BC]* and [AN]* are the sum of base cations and acid anions (NO3

-

 and SO4

-

), 

respectively. Although ANC has not generally been used as a parameter for predicting the health 

of the biotic communities, it provides useful information of the potential acidity related biotic 

stress and, hence, is a useful ecological indicator. 

The ANC concentration then provides a link between the surface water acidification and 

the ecological integrity of the aquatic community where a given level of ANC corresponds to an 

ecological effect (see Table 4.2-1). It also provides a link between the deposition of NOx and 

SOx and the acidification through the input of acid anions of NO3

-

 and SO4

-

. 

Equation (1) forms the basis of the linkage between deposition and surface water acidic 

condition and the modeling approach used. Given some “target” ANC concentration [ANClimit]), 

which protects biological integrity, the amount of deposition of acid anions (AN) or depositional 

load (DL(N) + DL(S)) is simply the input flux of acid anions from atmospheric deposition that 

result in a surface water ANC concentration equal to the [ANClimit] when balanced by the 

Final Risk and Exposure Assessment 4-39 September 2009 
Chapter 4 –Acidification 

sustainable flux of base cations input and the sinks of nitrogen and sulfur in the lake and 

watershed catchment. The sustainable flux of base cations input and sinks of nitrogen and sulfur 

is equal to the uptake (Nupt), immobilization (Nimm), and denitrification (Nden) of nitrogen in the 

catchment, the in-lake retention of nitrogen (Nret) and sulfur (Sret), and the preindustrial flux of 

base cations ([BC]0

*

) to the watershed. Thus, the amount of deposition that will maintain an 

ANC level above an ANClimit is described as 

 DL(N) + DL(S) = {fNupt + (1 − r)(Nimm + Nden) + (Nret + Sret)} + ([BC]0

* − [ANClimit])Q (2) 

where f and r are dimensionless parameters that define the fraction of forest cover in the 

catchment and the lake/catchment ratio, respectively, and Q is runoff. Surface water 

concentrations are converted to fluxes by multiplying concentration by runoff Q (mm/yr). 

Several major assumptions are made: (1) steady-state conditions exist, (2) the effect of nutrient 

cycling between plants and soil is negligible, (3) there are no significant nitrogen inputs from 

sources other than atmospheric deposition, (4) ammonium leaching is negligible because any 

inputs are either taken up by biota or adsorbed onto soils or nitrate compounds, and (5) long-term 

sinks of sulfate in the catchment soils are negligible. 

It is not possible to define a maximal loading for a single total of acidity (i.e., both 

nitrogen and sulfur deposition) because the acid anions sulfate and nitrate behave differently in 

the way they are transported with hydrogen ions; one unit of deposition of sulfur will not have 

the same net effect on surface water ANC as an equivalent unit of nitrogen deposition. However, 

the individual maximum and minimum depositional loads for nitrogen and sulfur are defined 

when nitrogen or sulfur do not contribute to the acidity in the water. The maximum depositional 

load for sulfur (DLmax(S)) is equal to the amount of sulfur the catchment can remove and still 

maintain an ANC concentration above the ANClimit: 

 DLmax(S) = [([BC]0

*

 - [ANClevel])Q]/ (1- ps) (3) 

when nitrogen deposition does not contribute to the acidity balance and where ps defines the 

fraction of in-lake retention of Sret. Given the assumption that the long-term sinks of sulfate in the 

catchment soils are negligible, the amount of sulfur entering the catchment is equal to the amount 

loaded to the surface water. For this reason, the minimal amount of sulfur is equal to zero: 

 DLmin(S) = 0 (4) 

Final Risk and Exposure Assessment 4-40 September 2009 
Chapter 4 –Acidification 

In the case of nitrogen, DLmin(N) is the minimum amount of deposition of total nitrogen (NHx + 

NOx) that catchment processes can effectively remove (e.g., Nupt + Nimm + Nden +Nret) without 

contributing to the acidic balance: 

 DLmin(N) = fNupt + (1-r)(Nimm + Nden) (5) 

The DLmax(N) is the load for total nitrogen deposition when sulfur deposition is equal to 

zero: 

 DLmax(N) = fNupt + (1-r)(Nimm + Nden) + [([BC]0

*

 - [ANClevel])Q]/ (1-pn) (6) 

where pn defines the fraction of in-lake retention of Nret. 

In reality, neither nitrogen nor sulfur deposition will ever be zero, so the depositional load 

for the deposition of one is fixed by the deposition of the other, according to the line defining in 

Figure 4.2-22. 

N Deposition 

DLmax(N)

S Deposition 

DLmin(N)

DLmax(s)

N Deposition 

DLmax(N)

S Deposition 

DLmin(N)

DLmax(s)

Figure 4.2-22. The depositional load function defined by the model. 

The thick lines indicate all possible combinations of depositional loads of nitrogen and 

sulfur acidity that a catchment can receive and still maintain an ANC concentration equal to its 

ANClimit. Note that in the above formulation, individual depositional loads of nitrogen and 

sulfur are not specified; each combination of depositions (Sdep and Ndep) fulfilling Equations 2 

through 6. (Figure 4.2-23) shows the depositional load function for two lakes in New York 

Final Risk and Exposure Assessment 4-41 September 2009 
Chapter 4 –Acidification 

0

100

200

300

400

500

0 100 200 300 400 500

N (meq/m2

/yr)

S (meq/m2/yr)

Clear Pond, NY

0

100

200

300

400

500

0 100 200 300 400 500

N (meq/m2

/yr)

S (meq/m2/yr)

Middle Flow, NY

Figure 4.2-23. Deposition load graphs for Clear Pond and Middle Flow Lake, New York. 

4.2.8 Uncertainty and Variability 

4.2.8.1 Steady-State Critical Load Modeling 

There is uncertainty associated with the parameters in the steady-state critical load model 

used to estimate aquatic critical loads. The strength of the critical load estimate and the 

exceedance calculation relies on the ability to estimate the catchment-average base-cation supply 

Final Risk and Exposure Assessment 4-42 September 2009 
Chapter 4 –Acidification 

(i.e., input of base cations from weathering of bedrock and soils and air), runoff, and surface 

water chemistry. The uncertainty associated with runoff and surface water measurements is fairly 

well known. However, the ability to accurately estimate the catchment supply of base cations to 

a water body is still poorly known. This is important because the catchment supply of base 

cations from the weathering of bedrock and soils is the factor that has the most influence on the 

critical load calculation and also has the largest uncertainty (Li and McNulty, 2007). Although 

the approach to estimate base-cation supply in the case study areas (e.g., F-factor approach) has 

been widely published and analyzed in Canada and Europe, and has been applied in the United 

States (e.g., Dupont et al., 2005), the uncertainty in this estimate is unclear and is likely large. 

For this reason, an uncertainty analysis of the state-steady critical load model was completed to 

evaluate the uncertainty in the critical load and exceedances estimations. 

A probabilistic analysis using a range of parameter uncertainties was used to assess (1) 

the degree of confidence in the exceedance values and (2) coefficient of variation (CV) of the 

critical load and exceedance values. The probabilistic framework is Monte Carlo, whereby each 

steady-state input parameter varies according to specified probability distributions and their 

range of uncertainty (Table 4.2-7). The purpose of the Monte Carlo methods was to propagate 

the uncertainty in the model parameters in the steady-state critical load model. 

Table 4.2-7. Parameters used and their uncertainty range. The range of surface water parameters 

(e.g. CA, MG, CL, NA, NO3, SO4) were determined from surface water chemistry data for the 

period from 1992 to 2006 from the TIME-LTM monitoring network. Runoff(Q) and Acidic 

Deposition were set at 50% and 25%. 

Parameter Units Uncertainty range Distribution 

Q μeq/L 50% Normal 

CA μeq/L 65% Normal 

MG μeq/L 64% Normal 

CL μeq/L 52% Normal 

NA μeq/L 58% Normal 

NO3 μeq/L 30% Normal 

SO4 μeq/L 57% Normal 

Acidic Deposition 

(NOx & SO4) 

meq/L 25% Lognormal 

Final Risk and Exposure Assessment 4-43 September 2009 
Chapter 4 –Acidification 

Within the Monte Carlo analysis, model calculations were run a sufficient number of 

times (i.e. 1,000 times) to capture the range of behaviors represented by all variables. The 

analysis tabulated the number of lakes where the confidence interval is entirely below the critical 

load, the confidence interval is entirely above the critical load, and the confidence interval 

straddles zero. Similar results are given for the number of sites with all realizations above the 

critical load, all realizations below the critical load, and some realizations above and some below 

the critical load. An inverse cumulative distribution function for exceedances was constructed 

from the 1000 model runs for each site, which describes the probability of a site to exceed its 

critical load. For each site, the probability of exceeding its critical load (i.e. probability of 

exceedance) is determined at the percent of the cumulative frequency distribution that lies above 

zero. The probability of exceedance, where the percentage of the cumulative frequency 

distribution lies above zero, was calculated for all sites and assigned to one of the following five 

classes: 

 • 0–5% probability: unlikely to be exceeded 

 • 5–25% probability: relatively low risk of exceedance 

 • 25–75% probability: potential risk of exceedance 

 • 75–95% probability: relatively high risk of exceedance 

 • >95% probability: highly likely to be exceeded. 

This provides a measure of the degree of confidence in whether the site exceeds its 

critical load. The CDF for Little Hope Pond is shown in Figure 4.2-24. 

The CV was also calculated on each site for both the critical load and exceedance 

calculations. The CV represents the ratio of the standard deviation to the mean and is a useful 

statistic for comparing the degree of variation in the data. The CV allows a determination of how 

much uncertainty (risk) comparison to its mean. 

Final Risk and Exposure Assessment 4-44 September 2009 
Chapter 4 –Acidification 

Probability of 

exceedance, where 

the % of the 

cumulative 

frequency chart lies 

above zero 

N=1000

Figure 4.2-24. The inverse cumulative frequency distribution for Little Hope 

Pond. The x-axis shows critical load exceedance in meq/ha/yr and y-axis is the 

probability. The dashed lines represent zero exceedance. In the case of Little 

Hope Pond, the dash line divides mostly the probability distribution on the left 

hand side, indicating Little Hope Pond has a relative low probability of being 

exceeded (0.3). Critical load and exceedances values were based on a critical level 

of protection of ANC = 50 μeq/L. 

Results of the Uncertainty Analysis 

The means and CVs for critical load (CL(A)) and exceedances (EX(A)) values are shown 

for all sites in Table 4.2-8 for four ANC limits (0, 20, 50, 100 μeq/L. The average CV for the 

various critical load values for all sites are remarkably low except for those calculated using a 

critical limit of 100 μeq/L. It is noticeable that although all the relevant input parameters have 

spreads of 25% to 65%, the CVs for CL(A) are only 4%, 5%, 9%, and 100% for critical load 

limits of 0%, 20%, 50%, and 100% μeq/L, respectively. In the case of the absolute value of the 

exceedances (EX(A)), the average CVs for all sites are higher, but still relatively low at 18%, 

17%, 25%, and 33%. The individual CV for each site and an ANC limit of 50 μeq/L are shown 

in Figure 4.2-25. Although the average CV is relatively small for the population of sites 

modeled, an individual site CV can varies from 1% to 45% for CL(A) and to 5% to over 100% 

for EX(A). This difference is due to the high degree of uncertainty in site-specific parameters for 

Final Risk and Exposure Assessment 4-45 September 2009 
Chapter 4 –Acidification 

particular sites and a low degree of confidence in the exceedance value itself for these sites. In 

addition, when the mean value is near zero, as is the case for exceedance values, the CV is 

sensitive to small changes in the mean, which likely explains why some sites have high CV 

compare to others. 

Table 4.2-8. Means and coefficients of variation of critical loads and exceedances for surface 

water. 

Parameter Critical load Limit 

(μeq/L) 

Mean 

(meq/L) 

Coefficient of 

variation (%) 

CL(A) 0 247.8 4 

20 227.0 5 

50 196.7 9 

100 140.3 100 

EX(A) 0 -178.3 18 

20 -157.6 17 

50 -127.2 25 

100 -75.0 33 

0

20

40

60

80

100

120

CV (%)

CL(A) EX(A)

Figure 4.2-25. Coefficients of variation of surface water critical load for acidity 

CL(A) and exceedances (EX(A)). Critical load and exceedances values were 

based on a critical level of protection of ANC = 50 μeq/L. 

The probability of exceedance results, where the percentage of the cumulative frequency 

distribution lies above zero, are shown in Figure 4.2-26. Those areas that have less than 5% 

Final Risk and Exposure Assessment 4-46 September 2009 
Chapter 4 –Acidification 

probability of exceedance are those with a high degree of confidence that the critical loads are 

not exceeded; conversely, areas with more than a 95% probability of exceedance are the most 

certain to be exceeded. 

For the sites in the aquatic case study areas, the probability of exceeding the critical load 

at an ANC limit of 0, 20, 50, and 100 μeq/L were relatively high. The waterbodies that exceeded 

their critical loads had a greater than 80% probability of doing so. The range of probability of 

exceedance was from 80% to 98%, indicating a relatively high confidence that these sites 

exceeded their critical load. The results suggest a relatively robust estimate of critical loads and 

exceedance rates for the case study areas. It is important to note that this analysis may understate 

the actual uncertainty because some of the range and distribution types of parameters are not 

well known for the United States at this time. 

Figure 4.2-26. Probability of exceedance of critical load for acidity for 2002. 

Final Risk and Exposure Assessment 4-47 September 2009 
Chapter 4 –Acidification 

4.2.8.2 MAGIC Modeling 

The sensitivity analyses described above were designed to address specific assumptions 

or decisions that had to be made in order to assemble the data for the 44 or 60 modeled sites in a 

form that could be used for calibration of the model. In all cases, the above analyses address the 

questions of what the effect would have been if alternate available choices had been taken. These 

analyses were undertaken for a subset of sites for which the alternate choices were available at 

the same sites. As such, the analyses above are informative, but they provide no direct 

information about the uncertainty in calibration or simulation arising from the choices that were 

incorporated into the final modeling protocol for all sites. That is, having made the choices about 

soils assignments, high elevation deposition, and stream samples for calibration (and provided an 

estimate of their inherent uncertainties), the need arises for a procedure for estimating 

uncertainty at each and all of the individual sites using the final selected calibration and 

simulation protocol. 

These simulation uncertainty estimates were derived from the multiple calibrations at 

each site provided by the “fuzzy optimization” procedure employed in this project. For each of 

the modeled sites, 10 distinct calibrations were performed with the target values, parameter 

values, and deposition inputs for each calibration, reflecting the uncertainty inherent in the 

observed data for the individual site. The effects of the uncertainty in the assumptions made in 

calibrating the model (and the inherent uncertainties in the data available) can be assessed by 

using all successful calibrations for a site when simulating the response to different scenarios of 

future deposition. The model then produces an ensemble of simulated values for each site. The 

median of all simulated values in a year is considered the most likely response of the site. The 

simulated values in the ensemble can also be used to estimate the magnitude of the uncertainty in 

the projection. Specifically, the difference in any year between the maximum and minimum 

simulated values from the ensemble of calibrated parameter sets can be used to define an 

“uncertainty” (or a “confidence”) width for the simulation at any point in time. All 10 of the 

successful model calibrations will lie within this range of values. These uncertainty widths can 

be produced for any variable and any year to monitor model performance. 

Direct comparison of simulated versus observed water chemistry values were compared 

to determine the uncertainty and variability in the MAGIC model output. Average water 

chemistry (SO4

2-, NO3-

, and ANC) simulated versus observed values during the calibration 

Final Risk and Exposure Assessment 4-48 September 2009 
Chapter 4 –Acidification 

period (i.e., reference year) were compared for all modeled sites. In addition, simulated versus 

observed average yearly values for ANC for the period of 1980 to 2007 for 4 sites were 

completed. The observed water chemistry data were from the Adirondack Long-Term 

Monitoring Virginia Trout Stream Sensitivity Survey (VTSSS) Long-Term Monitoring, and 

Temporally Integrated Monitoring of Ecosystems (TIME) water quality measurement programs 

and represent annual average concentrations. The statistic of Root Mean Squared Error (RMSE) 

was also calculated for predicted versus observed values for both the calibration period and the 

period of 1980 to 2007. RMSE is a frequently used measure of the differences between values 

predicted by a model or an estimator and the values actually observed from the thing being 

modeled or estimated. The RMSE was based on an annual average ANC over a 5-year period. 

Results of the Uncertainty Analysis 

Based on the MAGIC model simulations, the 95% confidence interval for the preacidification and current average ANC concentrations of the 44 modeled lakes was 106.8 to 

134.0 and 50.5 to 81.8 μeq/L, respectively, which is on average a 15 μeq/L difference in ANC 

concentrations, or 10%. The 95% confidence interval for pre-acidification and current average 

ANC concentrations of the 60 modeled streams was 91.9 to 110.9 and 53.4 to 62.4 μeq/L, 

respectively, which is on average 8 μeq/L difference in ANC concentration, or 5%.

These direct comparisons show good agreement between simulated and observed water 

quality values. Results of predicted versus observed average water chemistry during the 

calibration period (i.e., reference year) are in Figures 4.2-27and 4.2-28 for MAGIC modeling. 

The model showed close agreement with measured values at all sites for the one-year 

comparison of modeled values. For all sites’ SO4

2-, NO3-

, and ANC simulations, the RMSE for 

predicted versus observed values were 0.1 μeq/L, 0.05 μeq/L, and 3.5 μeq/L for lakes in the 

Adirondack Case Study Area and 1.0 μeq/L, 0.06 μeq/L, and 1.0 μeq/L for streams in the 

Shenandoah Case Study Area. Plots of simulated and observed ANC values for the period of 

1980 to 2007 are graphed in Figures 4.2-29 and 4.2-30 for two lakes in the Adirondack Case 

Study Area and for two streams in the Shenandoah Case Study Area. The RMSE of ANC was 

7.8 μeq/L and 5.1 μeq/L for the two lakes in the Adirondack Case Study Area and was 11.8 

μeq/L and 4.0 μeq/L for the two streams in Shenandoah Case Study Area. 

Final Risk and Exposure Assessment 4-49 September 2009 
Chapter 4 –Acidification 

0

50

100

150

0 50 100 150

Observed Chemistry

Simulated Chemistry

SO4

2- μeq/L 1:1

0

5

10

15

20

0 5 10 15 20

Observed Chemistry

Simulated Chemistry

1:1 NO3- μeq/L

-100

0

100

200

300

-100 0 100 200 300

Observed Chemistry

Simulated Chemistry

1:1

ANC μeq/L

4

5

6

7

8

45678

Observed Chemistry

Simulated Chemistry

1:1 pH μeq/L

Figure 4.2-27. Simulated versus observed annual average surface water SO4

2-, 

NO3

-

. ANC, and pH during the model calibration period for each of the 44 lakes 

in the Adirondack Case Study Area. The black line is the 1:1 line. 

Final Risk and Exposure Assessment 4-50 September 2009 
Chapter 4 –Acidification 

Final Risk and Exposure Assessment 4-51 September 2009 

0

50

100

150

0 50 100 150

Observed Chemistry

Simulated Chemistry

SO4

2- μeq/L 1:1

0

10

20

30

40

50

0 10 20 30 40 5

Observed Chemistry

Simulated Chemistry

1:1

0

NO3- μeq/L

-100

0

100

200

300

-100 0 100 200 300

Observed Chemistry

Simulated Chemistry

ANC μeq/L

4

5

6

7

8

4567

Observed Chemistry

Simulated Chemistr

8

y

1:1 pH μeq/L

Figure 4.2-28. Simulated versus observed annual average surface water SO4

2-, 

NO3

-

. ANC, and pH during the model calibration period for each of the 60 

streams in the Shenandoah Case Study Area. The black line is the 1:1 line. 
Chapter 4 –Acidification 

-25

0

25

50

ANC (μeq/L)

Observed

Simulated

Indian Lake

-50

-25

0

25

50

1975 1980 1985 1990 1995 2000 2005 2010

Years

ANC (μeq/L)

Dismal Pond

Figure 4.2-29. MAGIC simulated and observed values of ANC for two lakes in 

the Shenandoah Case Study Area. Red points are observed data and the simulated 

values are the line. The Root Mean Squared Error (RMSE) for ANC was 7.81 

μeq/L for Indiana Lake and 5.1 μeq/L for Dismal Pond. 

Final Risk and Exposure Assessment 4-52 September 2009 
Chapter 4 –Acidification 

0

50

100

150

200

ANC (μeq/L)

Observed

Simulated

Helton Creek

-25

0

25

50

1975 1980 1985 1990 1995 2000 2005 2010

Years

ANC (μeq/L)

Nobusiness Creek

Figure 4.2-30. MAGIC simulated and observed values of ANC for two lakes in 

the Shenandoah Case Study Area. Red points are observed data and the simulated 

values are the line. The Root Mean Squared Error (RMSE) for ANC was 11.8 

μeq/L for Helton Creek and 4.0 μeq/L for Nobusiness Creek. 

4.3 TERRESTRIAL ACIDIFICATION 

4.3.1 Ecological Indicators, Ecological Responses, and Ecosystem Services 

4.3.1.1 Ecological Indicators 

The ISA (U.S. EPA, 2008) identified a variety 

of indicators supported by the literature that can be used 

to measure the effects of acidification in soils. Much of 

the literature discussing terrestrial acidification focuses 

on Ca2+ and Al as the primary indicators of detrimental effects for trees and other terrestrial 

vegetation. Both of these indicators are strongly influenced by soil acidification, and both have 

been shown to have quantitative links to tree health (see Appendix 5 for more information). 

Indicator: The Bc/Al molar ratio in 

the soils solution was selected as the 

indicator to estimate critical 

deposition loads of acidity for the 

Terrestrial Acidification Case Study.

Final Risk and Exposure Assessment 4-53 September 2009 
Chapter 4 –Acidification 

Therefore, the Ca/Al ratio in soil solution was selected as the basis for the indicator in the 

Terrestrial Acidification Case Study (Appendix 5) to evaluate the critical load of acidity in 

terrestrial systems. Within the calculations of critical loads, the base cation (Bc) to Al ratio 

(Bc/Al), consisting of molar equivalents of Ca2+, Mg2+ and K+

, was used to represent the Ca/Al 

indicator. This Bc/Al ratio was selected because it is the most commonly used indicator or 

critical ratio (Bc/Al(crit)) in the Simple Mass Balance (SMB) model used to estimate critical acid 

loads in the European Union, Canada, and the United States (McNulty et al., 2007; Ouimet et al., 

2006; UNECE, 2004), and the SMB model was applied to this case study (see Section 4.3.4 for 

description of model). In addition, tree species show similar sensitivities to Ca/Al and Bc/Al soil 

solution ratios. Therefore, the Bc/Al ratio represents a good indicator of the negative impacts of 

soil acidification on terrestrial vegetation. Sverdrup and Warfvinge (1993), in a meta-data 

analysis of laboratory and field studies, reported that the critical Bc/Al ratios for a large variety 

of tree species ranged from 0.2 to 0.8. This range is similar to that described by Cronan and 

Grigal (1995) for Ca/Al. In their meta-data assessment of studies examining sensitivities to the 

Ca/Al ratio, plant toxicity or nutrient antagonism was reported to occur at Ca/Al ratios ranging 

from 0.2 to 2.5. 

4.3.1.2 Ecological Responses 

In a meta-analysis of studies that explored the relationship between Bc/Al ratio in soil 

solution and tree growth, Sverdrup and Warfvinge (1993) reported the Bc/Al ratios at which 

growth was reduced by 20% relative to control trees. Figure 4.3-1 presents the findings of 

Sverdrup and Warfvinge (1993) based on 46 of the tree species (native and introduced) that grow 

in North America. This summary indicates that there is a 50% chance of negative tree response 

(i.e., >20% reduced growth) at a soil solution Bc/Al ratio of 1.2 and a 75% chance at a Bc/Al 

ratio of 0.6. These findings 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. 

Final Risk and Exposure Assessment 4-54 September 2009 
Chapter 4 –Acidification 

Final Risk and Exposure Assessment 4-55 September 2009 

0.01

0.1

1

10

0 25 50 75

Bc/Al Ratio in Soil Solution 

100

(Bc/Al)crit = 1.2

(Bc/Al)crit = 0.6

0.01

0.1

1

10

0 25 50 75

Bc/Al Ratio in Soil Solution 

100

(Bc/Al)crit = 1.2

(Bc/Al)crit = 0.6

Cumulative Percentage of Species Exhibiting Reduced Growth Response

Figure 4.3-1. 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 controls 

(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 are red spruce (i.e., Picea Rubens) and 

sugar maple (i.e., Acer saccharum). Based on the results from a compilation of laboratory 

studies, red spruce growth can be reduced by 20% at a Bc/Al soil solution ratio of approximately 

1.2, and a similar reduction in growth may be experienced by sugar maple at a Bc/Al ratio of 0.6 

(Sverdrup and Warfvinge 1993). Both species are found in the eastern United States, and soil 

acidification is widespread throughout this area (Warby et al., 2009). 

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 mountains 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, acidic 

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 respond to stresses, such as 

insect defoliation, drought, and cold weather damage (DeHayes et al., 1999; Driscoll et al., 
Chapter 4 –Acidification 

2001), thereby decreasing tree health and increasing mortality. Additional linkages between 

acidifying deposition and red spruce physiological 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 SO2 emissions, and therefore acidic deposition, was recorded 

(Webster et al., 2004). 

Sugar maple is found throughout the northeastern United States and the central 

Appalachian Mountain region. This species has been declining in the 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 susceptible 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 probability of a decrease in crown vigor or an increase in 

tree mortality has been noted to increase at sites with low Ca2+ and Mg2+ as a result of leaching 

caused by acidifying deposition (Drohan and Sharpe, 1997). Low levels of Ca2+ in leaves and 

soils have been shown to be related to lower rates of photosynthesis and higher antioxidant 

enzyme activity in sugar maple stands in Pennsylvania (St. Clair et al., 2005). Additionally, plots 

of sugar maples in decline were found to have Ca2+/Al ratios less than 1, as well as lower base 

cation concentrations and pH values compared with plots of healthy sugar maples (Drohan et al., 

2002). Sugar maple regeneration has also been noted to be restricted under conditions of low soil 

Ca2+ levels (Juice et al., 2006). These 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 4.3-1. 

Table 4.3-1. Summary of Linkages Between Acidifying Deposition, Biogeochemical Processes 

That Affect Ca2+, Physiological Processes That Are Influenced by Ca2+, and Effect on Forest 

Function 

Biogeochemical Response to 

Acidifying deposition Physiological Response Effect on Forest Function 

Leach Ca2+ from leaf membrane Decrease the cold tolerance of 

needles in red spruce 

Loss of current-year needles in 

red spruce 

Reduce the ratio of Ca2+/Al in 

soil and soil solutions 

Dysfunction in fine roots of red 

spruce blocks uptake of Ca2+

Decreased growth and increased 

susceptibility to stress in red 

spruce 

Final Risk and Exposure Assessment 4-56 September 2009 
Chapter 4 –Acidification 

Final Risk and Exposure Assessment 4-57 September 2009 

Biogeochemical Response to 

Acidifying deposition Physiological Response Effect on Forest Function 

Reduce the ratio of Ca2+/Al in 

soil and soil solutions 

More energy is used to acquire 

Ca2+ in soils with low Ca2+/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 et al., 2006. 

Although the main focus of the Terrestrial Acidification Case Study is an evaluation 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 deposition can have a 

positive impact on tree health. Nitrogen limits the growth of many forests (Chapin et al., 1993; 

Killam, 1994; Miller, 1988), and therefore, in such forests, nitrogen deposition may act as a 

fertilizer and stimulate growth. Forests where critical acid loads 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 analyses are presented, in Attachment A of 

Appendix 5. 

In summary, among potential influencing factors, 

including elevated ozone levels and changes in climate, 

the acidification of soils is one of the factors that can 

negatively impacts the health of red spruce and sugar 

maple. Mortality and susceptibility to disease and injury can be increased and growth decreased 

with acidifying deposition. Therefore, the health of sugar maple and red spruce was used as the 

endpoints (ecological responses) to evaluate acidification in terrestrial systems. “Health” in the 

context of this case study is defined as the physiological condition of a tree that impacts growth 

and/or mortality, 

4.3.1.3 Ecosystem Services 

A number of impacts on the ecological endpoints of forest health, water quality, and 

habitat exist, including the following: 

 Decline in habitat for threatened and endangered species—cultural 

End Point: The health of sugar 

maple and red spruce was 

selected as the endpoints to 

estimate critical deposition loads of 

acidity in this case study. 
Chapter 4 –Acidification 

 Decline in forest aesthetics—cultural 

 Decline in forest productivity—provisioning 

 Increases in forest soil erosion and reductions in water retention—cultural and regulating. 

These impacts are described below. (Existing ecosystem services that are primarily 

impacted by the terrestrial acidification resulting from total nitrogen and sulfur deposition are 

being quantified for the Risk and Exposure Assessment.) 

Provisioning Services 

Forests in the northeastern United States provide several important and valuable 

provisioning services, which are reflected in measures of production and sales of tree products.

Sugar maples (also referred to as hard maples) are a particularly important commercial 

hardwood tree species in the United States. The two main types of products derived from sugar 

maples are wood products and maple syrup. The wood from sugar maple trees is particularly 

hard, and its primary uses include construction, furniture, and flooring (Luzadis and Gossett, 

1996). According to data from the U.S. Forest Service’s National Forest Inventory and Analysis 

(FIA) database, the total removal of sugar maple saw timber from timberland in the United States 

was almost 900 million board feet in 2006 (USFS, 2006). During winter and early spring 

(depending, in part, on location and diurnal temperature differences), sugar maple trees also 

generate sap that is used to produce maple syrup. From 2005 to 2007, annual production of 

maple syrup in the United States varied between 1.2 million and 1.4 million gallons, which 

accounted for roughly 19% of worldwide production. The total annual value of U.S. production 

in these years varied between $157 million and $168 million (NASS, 2008). 

Red spruce is a common commercial softwood species whose wood is used in a variety 

of products including lumber, pulpwood, poles, plywood, and musical instruments. According to 

FIA data, the total removal of red spruce saw timber from timberland in the United States was 

328 million board feet in 2006 (USFS, 2006). 

Figure 4.3-2 shows and compares the value of annual production of sugar maple and red 

spruce wood products and of maple syrup in 2006. Across states in the northeastern United 

States, wood from sugar maple harvests consistently generated the highest total sales value of the 

three products. Although total sales of red spruce saw timber and maple syrup were of roughly 

the same magnitude in the United States as a whole, the red spruce harvest was concentrated in 

Maine, whereas maple syrup production was largest in Vermont and New York. 

Final Risk and Exposure Assessment 4-58 September 2009 
Chapter 4 –Acidification 

Final Risk and Exposure Assessment 4-59 September 2009 

Cultural Services 

Forests in the northeastern United States are also an important source of cultural 

ecosystem services—nonuse (i.e., existence value for threatened and endangered species), 

recreational, and aesthetic services. Red spruce forests are home to two federally listed species 

and one delisted species: 

 Spruce-fir moss spider (Microhexura montivaga)—endangered 

 Rock gnome lichen (Gymnoderma lineare)—endangered 

 Virginia northern flying squirrel (Glaucomys sabrinus fuscus)—delisted, but important. 

Forest lands support a wide variety of outdoor recreational activities, including fishing, 

hiking, camping, off-road driving, hunting, and wildlife viewing. Regional statistics on 

recreational activities that are specifically forest based are not available; however, more general 

data on outdoor recreation provide some insights into the overall level of recreational services 

provided by forests. For example, most recent data from the National Survey on Recreation and 

the Environment (NSRE) indicate that, from 2004 to 2007, 31% of the U.S. adult (16 and older) 

population visited a wilderness or primitive area during the previous year, and 32% engaged in 

day hiking (Cordell et al., 2008). From 1999 to 2004, 16% of adults in the northeastern United 

States1 participated in off-road vehicle recreation, for an average of 27 days per year (Cordell 

et al., 2005). Using the meta-analysis results reported by Kaval and Loomis (2003), which found 

that the average consumer surplus value per day of off-road driving in the United States was 

$25.25 (in 2007 dollars), the implied total annual value of off-road driving recreation in the 

northeastern United States was more than $9.25 billion. 

State-level data on other outdoor recreational activities associated with forests are also 

available from the 2006 National Survey of Fishing, Hunting, and Wildlife-Associated 

Recreation (U.S. FWS and U.S. Census Bureau, 2007). Five and one-half percent of adults in the 

northeastern United States participated in hunting, and the total number of hunting days 

occurring in those states was 83.8 million. Data from the survey also indicated that 10% of adults 

in northeastern states participated in wildlife viewing away from home. The total number of 

away-from-home wildlife viewing days occurring in those states was 122.2 million in 2006. For 

these recreational activities in the northeastern United States, Kaval and Loomis (2003) 

 

1 This area includes Connecticut, Delaware, District of Columbia, Illinois, Indiana, Maine, Maryland,

Massachusetts, Michigan, New Hampshire, New Jersey, New York, Ohio, Pennsylvania, Rhode Island, Vermont, 

West Virginia, and Wisconsin. 
Chapter 4 –Acidification 

estimated average consumer surplus values per day of $52.36 for hunting and $34.46 for wildlife 

viewing (in 2007 dollars). The implied total annual value of hunting and wildlife viewing in the 

northeastern United States was, therefore, $4.38 billion and $4.21 billion, respectively, in 2006. 

Figure 4.3-2. 2006 annual value of sugar maple and red spruce harvests and maple 

syrup production, by state.

As previously mentioned, it is difficult to estimate the portion of these recreational 

services that are specifically attributable to forests and to the health of specific tree species. 

However, one recreational activity that is directly dependent on forest conditions is fall color 

viewing. Sugar maple trees, in particular, are known for their bright colors and are, therefore, an 

essential aesthetic component of most fall color landscapes. Statistics on fall color viewing are 

much less available than for the other recreational and tourism activities; however, a few studies 

have documented the extent and significance of this activity. For example, based on a 1996 to 

1998 telephone survey of residents in the Great Lakes area, Spencer and Holecek (2007) found 

that roughly 30% of residents reported at least one trip in the previous year involving fall color 

viewing. In a separate study conducted in Vermont, Brown (2002) reported that more than 22% 

of households visiting Vermont in 2001 made the trip primarily for the purpose of viewing fall 

colors. Unfortunately, data on the total number or value of these trips are not available, although 

Final Risk and Exposure Assessment 4-60 September 2009 
Chapter 4 –Acidification 

the high rates of participation suggest that numbers might be similar to the wildlife viewing 

estimates reported above. 

Although these statistics provide useful indicators of the total recreational and aesthetic 

services derived from forests in the northeastern United States, they do not provide estimates of 

how these services are affected by terrestrial acidification. Very few empirical studies have 

directly addressed this issue; however, there are two studies that have estimated values for 

protecting high-elevation spruce forests in the southern Appalachian Mountains. Kramer et al., 

(2003) conducted a contingent valuation study estimating households’ willingness to pay (WTP) 

for programs to protect remaining high-elevation spruce forests from damages associated with air 

pollution and insect infestation (Haefele et al., 1991; Holmes and Kramer, 1995). The study 

collected data from 486 households using a mail survey of residents living within 500 miles of 

Asheville, NC. The survey presented respondents with photographs representing three stages of 

forest decline and explained that, without forest protection programs, high-elevation spruce 

forests would all decline to worst conditions (with severe tree mortality). The survey then 

presented two potential forest protection programs, one of which would prevent further decline 

in forests along roads and trail corridors (one-third of the at-risk ecosystem) and the other would 

prevent decline in all at-risk forests. Both programs would be funded by tax payments going to a 

conservation fund. Median household WTP was estimated to be roughly $29 (in 2007 dollars) 

for the first program, and $44 for the more extensive program. 

Jenkins et al. (2002) conducted a very similar study in 1995, using a mail survey of 

households in seven Southern Appalachian states. In this study, respondents were presented with 

one potential program, which would maintain forest conditions at initial (status quo) levels. It 

was explained that, without the program, forest conditions would decline to worst conditions 

(with 75% dead trees). In contrast to the previously described study, in this survey the initial

level of forest condition was varied across respondent. In one version of the survey, the initial 

condition was described and shown as 5% dead trees, while the other version described and 

showed 30% dead trees. Household WTP was elicited from 232 respondents using a 

dichotomous choice and tax payment format. The overall mean annual WTP for the forest 

protection programs was $208 (in 2007 dollars), which is considerably larger than the WTP 

estimates reported by Kramer et al. (2003). One possible reason for this difference is that 

respondents to the Jenkins et al. (2002) survey, on average, lived much closer to the affected 

ecosystem. Multiplying the average WTP estimate from this study by the total number of 

Final Risk and Exposure Assessment 4-61 September 2009 
Chapter 4 –Acidification 

households in the seven-state Appalachian region results in an aggregate annual value of $3.4 

billion for avoiding a significant decline in the health of high-elevation spruce forests in the 

Southern Appalachian region. 

Regulating Services 

Forests in the northeastern United States also support and provide a wide variety of 

valuable regulating services, including soil stabilization and erosion control, water regulation, 

and climate regulation (Krieger, 2001). Forest vegetation plays an important role in maintaining 

soils in order to reduce erosion, runoff, and sedimentation that can negatively impact surface 

waters. In addition to protecting the quality of water in this way, forests also help store and 

regulate the quantity and flows of water in watersheds. Finally, forests help regulate climate 

locally by trapping moisture and globally by sequestering carbon. The total value of these 

ecosystem services is very difficult to quantify in a meaningful way, as is the reduction in the 

value of these services associated with total nitrogen and sulfur deposition. As terrestrial 

acidification contributes to root damages, reduced biomass growth, and tree mortality, all of 

these services are likely to be affected; however, the magnitude of these impacts is currently very 

uncertain.

4.3.2 Characteristics of Sensitive Areas 

In general, forest ecosystems of the Adirondack Mountains of New York, Green 

Mountains of Vermont, White Mountains of New Hampshire, the Allegheny Plateau of 

Pennsylvania, and high-elevation forests in the southern Appalachian Mountains are considered 

to be the regions most sensitive to terrestrial acidification effects from acidifying deposition 

(U.S. EPA, 2008). Such areas tend to be dominated by relatively nonreactive bedrock in which 

base cation production via weathering is limited (Elwood et al., 1991). The soils also usually 

have thick organic horizons, high organic matter content in the mineral horizons, and low pH 

(Joslin et al., 1992). Because of the largely nonreactive bedrock, base-poor litter and organic acid 

anions produced by the conifers, high precipitation, and high leaching rates, soil base saturation 

in these high elevation forests tends to be below 10%, and the soil cation exchange complex is 

generally dominated by Al (Eagar et al., 1996; Johnson and Fernandez, 1992). These soil 

systems have a lower capacity to neutralize acidic deposition and are not able to recover from the 

input of acidifying anions as easily as other systems. The areas where sugar maples appear to be 

at greatest risk are along ridges and where this species occurs on nutrient-poor soils (U.S. EPA, 

Final Risk and Exposure Assessment 4-62 September 2009 
Chapter 4 –Acidification 

2008, Section 3.2.4). In addition, these forests support the growth of sugar maple and red spruce, 

two species that are particularly sensitive to acidification. 

Several characteristics were used to identify areas potentially sensitive to terrestrial 

acidification. These characteristics included the following: 

 Soil depth 

 Bedrock composition 

 Soil pH 

 Presence of sugar maple or red spruce. 

Geology is one of the most important factors in determining the potential sensitivity of an 

area to terrestrial acidification (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 are those which contain low levels of exchangeable 

base cations and low base saturation (U.S. EPA, 2008, Section 3.2.4). 

It is important that soils be of sufficient depth for the rooting zone. Fine roots, which are 

responsible for the vast majority of nutrient uptake, are typically concentrated in the upper 10 to 

20 centimeters (cm) of soil (van der Salm and de Vries, 2001). These roots are most susceptible 

to the impacts of acidification. 

Bedrock composition and soil pH are two characteristics that are directly related to the 

ability of a system to neutralize acid. Soils overlying bedrock, such as calcium carbonate (e.g., 

limestone), which is reactive with acid, are more likely to successfully neutralize acidifying 

deposition than soils overlying nonreactive bedrock. In addition, soils with higher pH (i.e., more 

alkaline) have a greater capacity to neutralize acidifying deposition. 

Areas with acid-sensitive geology were cross-referenced with the geographical ranges of 

the ecological endpoints for this case study. As a result, locations with sugar maple or red spruce, 

soil pH less than or equal to 5.0, soils less than or equal to 51 cm in depth, and bedrock with a 

low ability to neutralize acid inputs (not dominated by carbonate rocks) were selected to 

represent areas with potential sensitivity to acidification. A geographic information systems 

(GIS) analysis was performed on datasets and data layers of physical, chemical, and biological 

properties to map areas of potential sensitivity to acidification in the United States 

(Figure 4.3-3). 

Final Risk and Exposure Assessment 4-63 September 2009 
Chapter 4 –Acidification 

4.3.3 Case Study Selection 

Following the identification of regions of potential sensitivity to acidification, risk and 

exposure assessment sites recommended in the ISA (U.S. EPA, 2008, Appendix A) by the 

Science Advisory Board – Ecological Effects Sub-committee (SAB-EES) (U.S. EPA, 2005) and 

the body of published and unpublished literature were reviewed to determine the most suitable 

areas for the red spruce and sugar maple case study areas. 

Selection of an area for the sugar maple case study focused on the Allegheny Plateau 

region in Pennsylvania, where a large proportion of published and unpublished research has been 

focused. A significant amount of the research work in the Plateau region has been sponsored by 

the United States Forest Service (USFS) and has produced extensive datasets of soil and tree 

characteristics (Bailey et al., 2004; Hallett et al., 2006; Horsley et al., 2000). The USFSdesignated Kane Experimental Forest (KEF) was selected as the area for the sugar maple 

terrestrial acidification case study. The KEF has been the focus of several long-term studies since 

the 1930s. Seven plots (plot 1-plot 7) in the forest were assessed for this case study of the effects 

of terrestrial acidification on sugar maples. Sugar maple accounted for 23% to 44% of the basal 

area in these plots. 

Selection of a case study area for red spruce involved the consideration of a variety of 

regions. Four studies that examined the relationship between the Ca2+/Al soil solution ratio and 

tree health were identified, and relevant soil and tree information for each of the study regions 

was compiled. A review of this information led to the selection of the Hubbard Brook 

Experimental Forest (HBEF) in New Hampshire’s White Mountains as the area for the red 

spruce terrestrial acidification case study. The HBEF was also recommended in the ISA (U.S. 

EPA, 2008, Appendix A) as a good area for risk and exposure assessment. This forest has 

experienced high total nitrogen and sulfur deposition levels and low Ca2+/Al soil solution ratios, 

and has been the subject of extensive nutrient investigations and provided a large data set from 

which to work on the case study. The case study of the effects of terrestrial acidification on red 

spruce focused on a study area consisting of nine grid cells (total of 0.56 ha) within Watershed 6 

in the HBEF. Red spruce accounted for 19% of the total basal area (131.3 m2

/ha) in this 0.56 ha 

study area. 

Final Risk and Exposure Assessment 4-64 September 2009 
Chapter 4 –Acidification 

Final Risk and Exposure Assessment 4-65 September 2009 

Figure 4.3-3. Map of areas of potential sensitivity of red spruce and sugar maple 

to acidification in the United States (see Table 1.2-1 of Appendix 5 for a listing of 

data sources to produce this map).

4.3.4 Current Conditions Assessment 

The Simple Mass Balance (SMB) model, outlined in the International Cooperative 

Programme (ICP) Mapping and Modeling Manual2 (UNECE, 2004), was used to evaluate 

critical loads of acidifying nitrogen and sulfur deposition in the KEF and HBEF case study

according to Equation 7 

 areas, 

dep −=+ dep + − + + + deuiuw − ANC NNNBcBCClBCN)CL(S critle,

 

 (7) 

where 

 CL(S+N) = forest soil critical load for combined nitrogen and sulfur acidifying 

deposition (N+Scomb) 

2 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. Neither the HBEF nor KEF case study areas are located less than 70 km for the 

coast, so this correction was not used. 
Chapter 4 –Acidification 

 BCdep = base cation (Ca2+ + K+ + Mg2+ + Na+) deposition 

 Cldep = chloride deposition 

 BCw = base cation (Ca2+ + K+ + Mg2+ + Na+

) weathering 

 Bcu = uptake of base cations (Ca2+ + K+

 + Mg2+) by trees 

 Ni = nitrogen immobilization 

 Nu = uptake of nitrogen by trees 

 Nde = denitrification 

 ANCle,crit = forest soil acid neutralizing capacity of critical load leaching 

This model is currently one of the most commonly used approaches to estimate critical 

loads and has been widely applied in Europe (Sverdrup and de Vries, 1994), the United States 

(McNulty et al., 2007; Pardo and Duarte, 2007), and Canada (Arp et al., 2001; Ouimet et al., 

2006; Watmough et al., 2006). It examines a long-term, steady-state balance of base cation, 

chloride, and nutrient inputs, “sinks,” and outputs within an ecosystem, and base cation 

equilibrium is assumed to equal the system’s critical load for ecological effects. A limitation of 

the SMB model is that it is a steady-state model and does not capture the cumulative changes in 

ecosystem conditions. However, as stated by the UNECE (2004), “Since critical loads are 

steady-state quantities, the use of dynamic models for the sole purpose of deriving critical loads 

is somewhat inadequate.” In addition, if a dynamic model is “used to simulate the transition to a 

steady state for the comparison with critical loads, care has to be taken that the steady-state 

version of the dynamic model is compatible with the critical load model.” Therefore, the 

selection of the SMB model was seen as the most suitable approach for this case study 

examining critical loads for sugar maple and red spruce. 

A component of critical load determinations is the establishment of the critical load 

function (CLF). The CLF expresses the relationship between the critical load and all 

combinations of total nitrogen and sulfur deposition (N+Scomb) of an ecosystem. To define the 

CLF, minimum and maximum amounts of total nitrogen and sulfur deposition that combine to 

create the critical load must be determined (UNECE, 2004). The maximum amount of sulfur in 

the critical load (CLmax(S)) occurs when total nitrogen deposition does not exceed the nitrogen 

sinks (i.e., nitrogen immobilization, nitrogen uptake and removal by tree harvest, and 

denitrification) within the ecosystem. These nitrogen sinks are accounted for by the minimum 

amount of nitrogen in the critical load (CLmin(N). Above this CLmin(N) level, total nitrogen 

deposition can no longer be absorbed by the system, and acidification effects can occur. The 

maximum amount of nitrogen in the critical load (CLmax(N)) occurs when there is no sulfur 

deposition, and all of the acidity is due to the deposition of nitrogen. 

Final Risk and Exposure Assessment 4-66 September 2009 
Chapter 4 –Acidification 

An example of a CLF is depicted in Figure 4.3-4. All combinations of total nitrogen and 

sulfur deposition that fall on the black line representing the CLF are at the critical load. Any 

deposition combination that falls below the line or within the grey area is below the critical load. 

All combinations of nitrogen and sulfur deposition that are located above the line or within the 

white area are greater than the critical load. 

CLmin(N)

N Deposition 

S De

position 

CLmax(N)

CLmax(S)

Figure 4.3-4. The critical load function created from the calculated maximum and 

minimum levels of total nitrogen and sulfur deposition (eq/ha/yr). The grey areas show 

deposition levels less than the established critical loads. The red line is the maximum 

amount of total sulfur deposition (valid only when nitrogen deposition is less than the 

minimum critical level of nitrogen deposition [blue dotted line]) in the critical load. The 

flat line portion of the curves indicates nitrogen deposition corresponding to the 

CLmin(N) (nitrogen absorbed by nitrogen sinks within the system). 

4.3.4.1 Input Data 

This section summarizes the input data used in the calculations, the results for each case 

study area, and a comparison of these results with 2002 wet and dry nitrogen and sulfur 

deposition (combination of Community Multiscale Air Quality [CMAQ]-modeled 2002 

deposition results and 2002 National Atmospheric Deposition Program [NADP] deposition data). 

Additional detail, including an examination of the influence of different parameter values and 

methods, on the assessment of current conditions in the KEF and HBEF case study areas can be 

found in Appendix 5. Only the parameter values that were chosen to represent the current 

condition of the KEF and HBEF case study areas are presented here. 

The majority of the data used to calculate critical loads for sugar maple and red spruce in 

the KEF and HBEF case study areas was specific to the case study areas and was compiled from 

published research studies and models, site-specific databases, or spatially-explicit GIS data 

Final Risk and Exposure Assessment 4-67 September 2009 
Chapter 4 –Acidification 

layers. However, several of the parameters (e.g., denitrification, nitrogen immobilization, the 

gibbsite equilibrium constant, rooting zone soil depth) required the use of default values or 

values used in published critical load assessments. Denitrification loss of nitrogen was assumed 

to be 0 eq/ha/yr because both the KEF and HBEF study plots are upland forests, and 

denitrification is considered negligible in such forests (McNulty et al. 2007; Ouimet et al., 2006; 

Watmough et al., 2006). The nitrogen mobilization value was set to 42.86 eq/ha/yr for both 

forests in this case study (McNulty et al., 2007). A 300 m6

/eq2 value for the gibbsite equilibrium 

constant (Kgibb) (used in the calculation of ANC) was selected because it is the most commonly 

used default value (UNECE, 2004). Fifty centimeters (0.5 m) was selected as the rooting zone 

soil depth for the forest soils of the two case study areas (Sverdrup and de Vries, 1994; Hodson 

and Langan 1999). Base cation weathering (BCw) rates were calculated using the clay-substrate 

method (McNulty et al., 2007; Watmough et al., 2006). This is one of the most commonly used 

methods to estimate base cation weathering for critical load analyses in North America. Base 

cation (Bcu) and nitrogen (Nu) uptake values were calculated in two different ways for the two 

case study areas. In the SMB model, if a stand is not actively harvested, nutrient (i.e., nitrogen 

and base cation) uptake is estimated to be 0 eq/ha/yr because the nutrients are assumed to be 

recycled within the forest and not removed from the site. Watershed 6, in the HBEF Case Study 

Area, is a reference watershed. Although this watershed was harvested in 1906 and 1917 (Aber 

et al., 2002), it has not been actively managed since that time and will not be harvested in the 

future. Therefore,, Bcu and Nu were assumed to be 0 eq/ha/yr in the critical load calculations. In 

contrast, in the KEF Case Study Area, the case study plots were assumed to be recently managed 

and harvested on a regular basis. Values of Bcu and Nu for this scenario were therefore calculated 

using species-specific tree data and uptake estimates and were >0 eq/ha/yr. Three values of the 

indicator of critical load, (Bc/Al)crit soil solution ratio, were selected to represent different levels 

of tree protection associated with total nitrogen and sulfur deposition: 0.6, 1.2, and 10 (Table 

4.3.2). The (Bc/Al)crit ratio of 0.6 represents the highest level of impact (lowest level of 

protection) to tree health and growth and was selected because 75% of species found growing in 

North America experience reduced growth at this Bc/Al ratio (see Figure 4.3.1). 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 growing in North America) was 

negatively impacted at this soil solution ratio. The (Bc/Al)crit ratio of 10.0 represents the lowest 

Final Risk and Exposure Assessment 4-68 September 2009 
Chapter 4 –Acidification 

level of impact (greatest level of protection) to tree 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). 

Table 4.3-2. 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 

4.3.5 Results for the Case Study Areas 

Based on the input data described above, the three critical loads for the KEF case study 

area, in order of lowest to highest protection level, were 2,009, 1,481 and 910 eq/ha/yr (for 

Bc/Al(crit) = 0.6, 1.2, and 10.0, respectively). In the HBEF Case Study Area, these values, in the 

same order of protection, were 1,237, 892, and 487 eq/ha/yr (for Bc/Al(crit) = 0.6, 1.2, and 10.0, 

respectively). 

The (Bc/Al)crit ratio of 0.6 represents the highest level of impact (lowest level of 

protection) to tree health and growth; as much as 75% of 46 tree species found in North America 

experience reduced growth at this ratio (Sverdrup and Warfvinge, 1993). Both red spruce and 

sugar maple show at least a 20% reduction in growth at the 0.6 (Bc/Al)crit ratio. 

4.3.5.1 Comparison with 2002 Deposition Data 

This section discusses the impact of 2002 CMAQ/NADP total nitrogen and sulfur 

deposition relative to the estimated critical loads at the KEF and HBEF case study areas. 

According to 2002 CMAQ/NADP total nitrogen and sulfur deposition, the KEF Case Study Area 

received 13.6 kg N/ha (967.5 eq/ha) and 20.7 kg S/ha (646.4 eq/ ha), and the HBEF Case Study 

Area experienced 8.4 kg N/ha (601.1 eq/ha) and 7.5 kg S/ha (233.1 eq/ha). 

As outlined above, 2,009, 1,481, and 910 eq/ha/yr were the critical loads selected to 

represent the three levels of protection for the KEF Case Study Area and 1,237, 892, and 487 

eq/ha/yr were the critical loads selected for the HBEF Case Study Area. These estimates are 

based on the critical load parameters suggested and most frequently used by scientists and 

Final Risk and Exposure Assessment 4-69 September 2009 
Chapter 4 –Acidification 

previous research. When compared to the 2002 CMAQ/NADP total nitrogen and sulfur 

deposition levels, it was evident that the deposition levels were greater than the most protective 

critical load (Bc/Al(crit) = 10.0) for both case study areas and also greater than the intermediate 

protection critical load (Bc/Al(crit) = 1.2) for the KEF Case Study Area (Figure 4.3-5 and

Figure 4.3-6). In these comparisons, total nitrogen and sulfur deposition exceeded the KEF Case 

Study Area critical load by 132 – 704 eq/ha/yr and exceeded the HBEF Case Study Area’s 

critical load by 347 eq/ha/yr. Similar results have been reported in other studies that have 

assessed the two case study areas. McNulty et al. (2007) and Pardo and Driscoll (1996) found 

that deposition levels were greater than the estimated critical loads in the HBEF Case Study 

Area. McNulty et al. (2007) also reported that total nitrogen and sulfur deposition in the KEF 

exceeded the calculated critical loads for the case study area in KEF. These results suggest that 

the health of red spruce at HBEF and sugar maple at KEF may have been compromised by the 

acidifying nitrogen and sulfur deposition received in 2002. 

Acidifying total nitrogen deposition consists of both reduced (NHx) and oxidized (NOx) 

forms of nitrogen. However, only NOx is currently regulated as a criteria pollutant. Therefore, to 

gain an understanding of the relationship between the two states (reduced and oxidized) of total 

nitrogen deposition and the critical loads for the KEF and HBEF case study areas, total nitrogen 

deposition must be separated into NHx--N and NOx-N. Figure 4.3-7 and Figure 4.3-8 present the 

CLF response curves for the most protective critical load condition (Bc/Al(crit) = 10.0) for the 

KEF and HBEF case study areas, respectively. In these relationships, the CLF function has been 

modified by maintaining NHx-N deposition at the 2002 deposition level; only sulfur and NOx-N 

deposition levels vary to indicate the combined critical load. Based on 2002 CMAQ/NADP total 

nitrogen and sulfur deposition, NHx-N accounted for 25.7 % (249 eq/ha) and 26.4 % (159 eq/ha) 

of total nitrogen deposition in the KEF and HBEF case study areas, respectively. These fixed 

amounts of NHx-N influenced the highest protection CLF response curves for both areas. For 

both case studies, the maximum sulfur critical load (CLmax(S)) and the maximum nitrogen 

critical load (CLmax(N)), as NOx, were lowered. In the calculations for the KEF Case Study Area, 

the CLmax(S) was reduced by 5 % to 661 eq/ha/yr, and in the HBEF Case Study Area 

calculations, the CLmax(S) was reduced by 26 % to 328 eq/ha/yr. Similarly, the CLmax(N) (as 

NOx) for the KEF Case Study Area was reduced by 27% to 661 eq/ha/yr, and the CLmax(N) (as 

NOx) for the HBEF Case Study Area was reduced by 33% to 328 eq/ha/yr when NHx-N 

deposition was held constant.

Final Risk and Exposure Assessment 4-70 September 2009 
Chapter 4 –Acidification 

Final Risk and Exposure Assessment 4-71 September 2009 

2009

1796

1481

1268

910

697

213

0

3500

0 3500

N Deposition 

(eq/ha/yr)

S Depositio

n

(eq/ha/yr)

Low Protection (Bc/Al = 0.6)

Intermediate Protection (Bc/Al = 1.2)

High Protection (Bc/Al = 10.0)

CLmin(N)

2002 CMAQ N and S Deposition

Figure 4.3-5. Critical load function response curves for the three selected critical 

loads conditions (corresponding to the three levels of protection) for the Kane 

Experimental Forest Case Study Area. The 2002 CMAQ/NADP total nitrogen and 

sulfur (N+Scomb) deposition was greater than the highest and intermediate level of 

protection critical loads. The flat line portion of the curves indicates total nitrogen 

deposition corresponding to the CLmin(N) (nitrogen absorbed by nitrogen sinks within 

the system). 

1237

1194

892

849

487

444

43

0

3000

0 3000

N Deposition 

 (eq/ha/yr)

S Depositio

n

 (eq/ha/yr)

Low Protection (Bc/Al = 0.6) 

Intermediate Protection (Bc/Al = 1.2)

High Protection (Bc/Al = 10.0)

CLmin(N)

2002 CMAQ N and S Deposition

Figure 4.3-6. Critical load function response curves for the three selected critical 

loads conditions (corresponding to the three levels of protection) for the Hubbard 

Brook Experimental Forest Case Study Area. The 2002 CMAQ/NADP total 

nitrogen and sulfur (N+Scomb) deposition was greater than the highest level of 

protection critical load. The flat line portion of the curves indicates total nitrogen 

deposition corresponding to the CLmin(N) (nitrogen absorbed by nitrogen sinks 

within the system).
Chapter 4 –Acidification 

CLmax(S)

1200

0

0 249 910 1200

NHx-N deposition (fixed amount)

NOx-N deposition

2002 CMAQ N and S deposition

CLmin(N)

S Deposition 

(eq/ha/yr)

N Deposition 

(eq/ha/yr)

Adj. CLmax(S) 661

CLmin(N)

213

Figure 4.3-7. The influence of the 2002 CMAQ/NADP total reduced nitrogen 

(NHx-N) deposition on the critical function response curve, and in turn, the 

maximum amounts of sulfur (CLmax(S)) and oxidized nitrogen (NOx-N) in the 

critical load for the Kane Experimental Forest Case Study Area. The critical load 

of oxidized nitrogen (NOx-N) is 661 eq/ha/yr (910−249). The CLmin(N) (nitrogen 

absorbed by nitrogen sinks within the system) corresponds to the value depicted 

in Figure 4.3-5. 

Final Risk and Exposure Assessment 4-72 September 2009 
Chapter 4 –Acidification 

CLmax(S)

750

0

0 159 487 750

Adj. CLmax(S) 328

NHx-N deposition (fixed amount)

NOx-N deposition

2002 CMAQ N and S deposition

CLmin(N)

S Deposition 

(eq/ha/yr)

N Deposition 

(eq/ha/yr)

43 CLmin(N)

Figure 4.3-8. The influence of the 2002 CMAQ/NADP total reduced nitrogen 

(NHx-N) deposition on the critical load function response curve and, in turn, the 

maximum amounts of sulfur (CLmax(S)) and oxidized nitrogen (NOx-N) in the 

critical load for the Hubbard Brook Experimental Forest Case Study Area. The 

critical load of oxidized nitrogen (NOx-N) is 328 eq/ha/yr (487−159). The 

CLmin(N) (nitrogen absorbed by nitrogen sinks within the system) corresponds to 

the value depicted in Figure 4.3-6. 

4.3.6 Evaluation of Representativeness of Case Study Areas 

Although the case studies estimated critical load assessments for red spruce and sugar 

maple in two areas and established that 2002 CMAQ/NADP total nitrogen and sulfur deposition 

was greater than the calculated loads, these results cannot be directly extrapolated to the full 

ranges of the two species. Critical loads are largely determined by soil characteristics, and these 

characteristics vary by location. Therefore, to characterize the critical loads of sugar maple and 

red spruce and determine the extent to which total nitrogen and sulfur deposition is greater than 

or less than these loads, it is necessary to calculate critical loads in multiple locations throughout 

the ranges of the two species to determine the critical loads for these species. 

Critical load calculations were applied to multiple areas within 24 states for sugar maple 

and in 8 states for red spruce. Individual site locations within each state were determined by the 

U.S. Forest Service Forest Inventory and Analysis (FIA) database permanent sampling plots’ 

Final Risk and Exposure Assessment 4-73 September 2009 
Chapter 4 –Acidification 

Final Risk and Exposure Assessment 4-74 September 2009 

locations on forestland3 (timberland4 for New York, Arkansas, Kentucky, and North Carolina), 

each covering 0.07 ha. Only database information for nonunique5, permanent sampling plots that 

supported the growth of sugar maple or red spruce and had the necessary soil, parent material, 

atmospheric deposition, and runoff data were included in the analyses. With these restrictions, 

7,992 of the 14,669 sugar maple plots and 763 of the 2,875 red spruce plots were included in the 

calculations of the plot-specific critical loads (Table 4.3-3). Although only a subset of the total 

sugar maple and red spruce plots were included in the analyses, the results are thought to 

accurately capture the range and trends of critical loads of the two species. Because of the 

randomness of the plot restrictions, it is unlikely that a bias was incorporated into the analyses. 

The calculated critical loads for the three levels of protection (Bc/Al(crit) = 0.6, 1.2, and 

10.0) for all plots were compared to 2002 CMAQ/NADP total nitrogen and sulfur deposition to 

determine which plots with sugar maple and/or red spruce experienced deposition levels greater 

than the critical load values. 

Table 4.3-3. Number and Location of USFS FIA Permanent Sampling Plots (each plot is 

0.07 ha) Used in the Analysis of Critical Loads for Full Geographic Ranges of Sugar 

Maple and Red Spruce 

State Sugar Maple Red Spruce 

Alabama 13 – 

Arkansas 10 – 

Connecticut 35 – 

Illinois 29 – 

Indiana 306 – 

Iowa 13 – 

Kansas NA – 

Kentucky 14 – 

Maine 271 560 

 

3 Forestland is defined as, “land at least 10 percent stocked by forest trees of any size, or formerly having such tree 

cover, and not currently developed for non-forest uses, with a minimum area classification of 1 acre.” (USFS, 

2002a). 

4 Timberland is defined as, “forest land capable of producing in excess of 20 cubic feet per acre per year and not 

legally withdrawn from timber production, with a minimum area classification of 1 acre.” (USFS, 2002b). 

5 Nonunique permanent sampling plot locations are those that have critical load attribute values (e.g., soils, runoff, 

atmospheric deposition) that are not distinct and are repeated within a 250-acre area of the plot location. This 

“confidentiality” filter is a requirement of the USFS to prevent the disclosure of data that can be directly linked to 

a location on private land. To comply with the necessary “confidentiality,” full coverages of the data required for 

the critical load deposition calculations were given to the USFS, and the USFS matched and provided the data to 

each nonunique, permanent sampling plot. 
Chapter 4 –Acidification 

Final Risk and Exposure Assessment 4-75 September 2009 

State Sugar Maple Red Spruce 

Maryland 4 – 

Massachusetts 33 3 

Michigan 633 – 

Minnesota 289 – 

Missouri 147 – 

New Hampshire 82 55 

New Jersey 6 – 

New York 485 52 

North Carolina 17 1 

Ohio 374 – 

Pennsylvania 285 NA 

Rhode Island NA – 

South Carolina NA – 

Tennessee 319 1 

Vermont 114 11 

Virginia 175 NA 

West Virginia 378 7 

Wisconsin 960 – 

TOTAL 4,992 763 

NA = data not available for state 

“–” = tree species not present on forestland in state 

4.3.7 Current Conditions for Sugar Maple and Red Spruce 

The critical loads of acidifying deposition for sugar maple in 24 states for the three levels 

of protection were found to range from 107 to 6,008 eq/ha/yr (Table 4.3-4). Critical loads for red 

spruce in the 8 states ranged from 180 to 4,278 eq/ha/yr. In a comparison of the 2002 

CMAQ/NADP total nitrogen and sulfur deposition levels and calculated critical loads, 3% to 

75% of all sugar maple plots and 3% to 36% of all red spruce plots were found to have total 

nitrogen and sulfur deposition greater than the critical loads; the highest protection critical loads 

(Bc/Al(crit) = 10.0) had the highest frequency of exceedance (Table 4.3-5). Aggregated by state, a 

large proportion of the sugar maple and red spruce plots showed high levels of critical load 

exceedance for the highest protection level (Bc/Al(crit) = 10.0), and comparatively lower 

exceedance frequency at the lowest protection level ((Bc/Al(crit) = 0.6)) (Table 4.3-5). In general, 

New Hampshire displayed the greatest degree of critical load exceedance at all protection levels 

for both species. 
Chapter 4 –Acidification 

Collectively, given the limitations and uncertainties associated with the SMB model to 

estimate critical acid loads (see Section 4.3.9 in Chapter 4 and Section 5 in Appendix 5 for 

further description), these results suggest that the health of at least a portion of the sugar maple 

and red spruce growing in the United States may have been compromised with the acidifying 

total nitrogen and sulfur deposition in 2002; even with the lowest level of protection, half the 

states contained sugar maple and red spruce stands that were negatively impacted by acidifying 

deposition. At the highest level of protection (Bc/Al(crit) = 10.0), the apparent impact of the 2002 

CMAQ/NADP total nitrogen and sulfur deposition was much greater. A large portion of sugar 

maple (i.e., >80% of plots in 13 of 24 states) and the majority of red spruce (i.e., 100% of plots 

in 5 of 8 states) experienced deposition levels that exceeded the critical loads. If this high 

protection critical load accurately represents the conditions of the two species, a large proportion 

of both sugar maple and red spruce, throughout their ranges, were most likely negatively 

impacted by total nitrogen and sulfur deposition in 2002. 

Table 4.3-4. Ranges of Critical Load Values, by Level of Protection (Bc/Al(crit) = 0.6, 1.2, and 

10.0) and by State, for the Full Geographical Distribution Ranges of Sugar Maple and Red 

Spruce 

State 

Ranges of Critical Load Values (eq/ha/yr) 

Sugar Maple Red Spruce 

Bc/Al = 0.6 Bc/Al = 1.2 Bc/Al = 10.0 Bc/Al = 0.6 Bc/Al = 1.2 Bc/Al = 10.0 

Alabama 1,592 to 5,337 1,114 to 3,638 617 to 2,015 – – –

Arkansas 2,239 to 4,290 1,536 to 2,913 857 to 1,623 – – –

Connecticut 1,519 to 2,468 1,058 to 1,702 581 to 941 – – –

Illinois 2,543 to 3,671 1,730 to 2,485 965 to 1,390 – – –

Indiana 1,478 to 5,859 1,020 to 3,971 573 to 2,214 – – –

Iowa 2,260 to 3,791 1,533 to 2,560 854 to 1,424 – – –

Kansas NA NA NA – – –

Kentucky 2,044 to 3,994 1,390 to 2,707 749 to 1,497 – – –

Maine 746 to 4,284 535 to 2,983 295 to 1,620 599 to 4,278 439 to 2,979 249 to 1,623 

Maryland 2,066 to 3,090 1,417 to 2,122 929 to 1,178 – – –

Massachusetts 791 to 2,414 566 to 1,661 319 to 919 1,706 to 1,736 1,191 to 1,213 656 to 669 

Michigan 400 to 6,008 294 to 4,070 169 to 2,269 – – –

Minnesota 220 to 4,916 166 to 3,318 107 to 1,861 – – –

Missouri 978 to 4,891 681 to 3,304 377 to 1,843 – – –

New 

Hampshire 580 to 1,994 419 to 1,439 236 to 780 418 to 1,994 324 to 1,439 180 to 780 

Final Risk and Exposure Assessment 4-76 September 2009 
Chapter 4 –Acidification 

Final Risk and Exposure Assessment 4-77 September 2009 

State 

Ranges of Critical Load Values (eq/ha/yr) 

Sugar Maple Red Spruce 

Bc/Al = 0.6 Bc/Al = 1.2 Bc/Al = 10.0 Bc/Al = 0.6 Bc/Al = 1.2 Bc/Al = 10.0 

New Jersey 1,452 to 2,651 1,029 to 1,824 566 to 1,012 – – –

New York 503 to 4,467 370 to 3,039 209 to 1,686 526 to 3,146 386 to 2,156 217 to 1,195 

North Carolina 1,415 to 3,444 1,010 to 2,426 558 to 1,319 1256 926 501 

Ohio 1,226 to 4,986 855 to 3,366 469 to 1,877 – – –

Pennsylvania 1,026 to 4,047 723 to 2,752 402 to 1,530 NA NA NA 

Rhode Island NA NA NA – – –

South Carolina NA NA NA – – –

Tennessee 921 to 5,755 653 to 3,901 351 to 2,175 2,065 1,433 788 

Vermont 479 to 5,660 351 to 3,846 201 to 2,142 846 to 2,305 601 to 1,648 336 to 888 

Virginia 1,036 to 5,852 726 to 3,968 410 to 2,208 NA NA NA 

West Virginia 369 to 4,134 270 to 2,819 152 to 1,560 2,300 to 3,634 1,610 to 2,533 884 to 1,382 

Wisconsin 400 to 5,031 290 to 3,393 166 to 1,898 – – –

Combined 

(all plots) 220 to 6,008 166 to 4,070 107 to 2,269 418 to 4,278 324 to 2,979 180 to 1,623 

NA = data not available for state 

“–” = tree species not present on forestland in state 

Table 4.3-5. Percentages of Plots, by Protection Level (Bc/Al(crit) = 0.6, 1.2, and 10.0) and by 

State, Where 2002 CMAQ/NADP Total Nitrogen and Sulfur Deposition Was Greater Than the 

Critical Loads for Sugar Maple and Red Spruce

State 

Percentage of Plots Where Critical Load is Exceeded (%) 

Sugar Maple Red Spruce 

Bc/Al = 0.6 Bc/Al = 1.2 Bc/Al = 10.0 Bc/Al = 0.6 Bc/Al = 1.2 Bc/Al = 10.0 

Alabama 0 23 31 – – –

Arkansas 0 0 10 – – – 

Connecticut 0 23 100 – – – 

Illinois 0 0 66 – – – 

Indiana 0.3 12 87 – – – 

Iowa 0 0 23 – – – 

Kansas NA NA NA – – – 

Kentucky 0 0 86 – – – 

Maine 0 0.7 20 0.2 0.5 16 

Maryland 0 25 100 – – – 

Massachusetts 6 33 100 0 100 100 

Michigan 6 14 70 – – – 

Minnesota 2 7 30 – – – 

Missouri 0.7 2 46 – – v 
Chapter 4 –Acidification 

Final Risk and Exposure Assessment 4-78 September 2009 

State 

Percentage of Plots Where Critical Load is Exceeded (%) 

Sugar Maple Red Spruce 

Bc/Al = 0.6 Bc/Al = 1.2 Bc/Al = 10.0 Bc/Al = 0.6 Bc/Al = 1.2 Bc/Al = 10.0 

New 

Hampshire 29 38 84 27 38 78 

New Jersey 0 67 100 – – – 

New York 6 20 95 14 15 79 

North Carolina 0 6 71 0 0 100 

Ohio 1 16 95 – – – 

Pennsylvania 7 22 98 NA NA NA 

Rhode Island NA NA NA – – – 

South Carolina NA NA NA – – – 

Tennessee 0.3 3 50 0 0 100 

Vermont 2 7 99 2 6 100 

Virginia 2 9 59 NA NA NA 

West Virginia 2 8 95 0 0 100 

Wisconsin 2 10 82 – – – 

Combined 

(all plots) 3 12 75 3 5 36 

NA = data not available for state 

“–” = tree species not present on forestland in state 

4.3.8 Ecological Effect Function for Terrestrial Acidification 

As described earlier and explained in greater detail in Appendix 5, there is an established 

relationship between atmospheric deposition of nitrogen and sulfur and the Bc/Al ratio in the soil 

solution. In areas with high amounts of acidifying nitrogen and sulfur deposition, protons can 

replace exchangeable base cations, which are then leached from the soil, and the resulting lower 

soil pH increases the mobilization of soil Al. The Bc/Al ratio in the soil solution is thereby 

decreased, and this can negatively impact trees through direct Al toxicity to roots and reduced 

uptake of base cation nutrients. As indicated in Figure 4.3.1, as the Bc/Al ratio in the soil 

solution decreases, the incidence of reduced tree growth increases. 

The Bc/Al ratio in the soil solution is the indicator selected to estimate critical loads of 

acidity for terrestrial acidification and is an influential parameter in the ANC term of the SMB 

model critical load equation (Equation 7 in Section 4.3.4). The equation to estimate ANC is 

presented below, in Equation 8. 
Chapter 4 –Acidification 

Final Risk and Exposure Assessment 4-79 September 2009 

crit

dep w u

1/3

crit

gibb

2/3 dep w u

crit)(le,

Al

Bc

BcBcBc

1.5

Al

Bc

BcBcBc

ANC 1.5

⎟

⎠

⎞ ⎜

⎝

⎛

−+

×−

⎟

⎟

⎟

⎟

⎟

⎠

⎞

⎜

⎜

⎜

⎜

⎜

⎝

⎛

⎟

⎠

⎞ ⎜

⎝

⎛ ×

−+

××−=

K

Q (8) 

where 

 Q = annual runoff in m3/ha/yr 

 Bcdep = base cation (Ca2++ K+

 + Mg2+) deposition6 

 Bcw = soil base cation (Ca2++ K + Mg2+) weathering7

 Bcu = base cation (Ca2++ K + Mg2+) uptake by trees 

 Kgibb = the gibbsite equilibrium constant (a function of forest soil organic 

matter content that affects Al solubility) (UNECE, 2004) 

 (Bc/Al)crit = the base cation to aluminum ratio (indicator) 

The three (Bc/Al)crit ratios (0.6, 1.2, and 10.0) used in this case study were selected to 

represent the range of protection levels to the health of red spruce and sugar maple. The 

Bc/Al(crit) ratio of 10.0 corresponds to the highest level of protection, and, when included in the 

calculation of the ANC term, results in the lowest critical load. A terrestrial system with such a 

condition would only be able to tolerate comparatively low levels of total nitrogen and sulfur 

deposition. A (Bc/Al)crit ratio of 1.2 represents an intermediate level of protection and moderate 

critical load. The (Bc/Al)crit ratio of 0.6 ratio provides the lowest level of protection to tree health 

and results in the estimation of a high critical load. 

In the expansion of the critical load assessments to the full geographic ranges of sugar 

maple and red spruce, as discussed in Section 4.3.6, critical loads were estimated in multiple 

locations for each of the three levels of protection (Bc/Al)crit = 0.6, 1.2, and 10.0) for each 

species. Because of the differences in soil conditions, runoff, base cation, and chloride deposition 

patterns, this analysis produced a wide range of critical load estimates. Depicting the extremes 

(lowest and highest) and the average critical load values in CLF curves provides an indication of 

the combinations of total nitrogen and sulfur deposition that could occur without exceeding the 

critical loads associated with the upper and lower limits and averages of the three protection 

levels (Figure 4.3.9 and Figure 4.3.10). As is depicted in the figures, the lowest critical loads 

corresponding to the three protection levels (Bc/Al)crit ratio = 0.6, 1.2, and 10.0) were 387, 284, 

 

6 Bcdep is not the same as BCdep used in Equation 1. BCdep includes Ca2+, K+

, Mg2+, and Na+, whereas Bcdep includes 

base cations that are taken up by vegetation (i.e., only includes Ca2+, K+

, and Mg2+). 

7 Bcw is not the same as BCw used in Equation 1. BCw includes Ca2+, K+

, Mg2+, and Na+, whereas Bcw includes base 

cations that are taken up by vegetation (i.e., only includes Ca2+, K+

, and Mg2+). 
Chapter 4 –Acidification 

Final Risk and Exposure Assessment 4-80 September 2009 

and 163 eq/ha/yr for sugar maple and 526, 386, and 217 eq/ha/yr for red spruce. In contrast, the 

highest critical loads for the three protection levels for sugar maple were 5,660, 3,846, and 2,142 

eq/ha/yr and for red spruce were 4,265, 2,976, and 1621 eq/ha/yr. The 1,979 to 5,273 eq/ha/yr 

differences between the extreme estimates for sugar maple and 1,404 to 3,739 eq/ha/yr 

differences for the red spruce estimates indicate the amount of total nitrogen and sulfur 

deposition that separates the lower and upper limits of the lowest and highest protection levels. 

5617

5660

344

3803

3846 2142

2099

387

241

284

120

163

0

6500

0 6500

N Deposition 

 (eq/ha/yr)

S Depositio

n

 (eq/ha/yr)

Highest Critical Load (Bc/Al = 0.6)

Highest Critical Load (Bc/Al = 1.2)

Highest Critical Load (Bc/Al = 10.0)

Lowest Critical Load (Bc/Al = 0.6)

Lowest Critical Load (Bc/Al = 1.2)

Lowest Critical Load (Bc/Al = 10.0)

Figure 4.3.9. The lowest and highest critical load function response curves for the 

three levels of protection ((Bc/Al)crit = 0.6, 1.2, and 10.0) for the critical load 

assessments for the full geographical range of sugar maple. The CLmin(N) value 

for all curves is 42.86 eq/ha/yr, but this value is not indicated in the figure. 
Chapter 4 –Acidification 

Final Risk and Exposure Assessment 4-81 September 2009 

4222

4265

526

483

2976

2933

1621

1578

343

386

174

217

0

5000

0 5000

N Deposition 

(eq/ha/yr)

S Depositio

n

(eq/ha/yr)

Highest Critical Load (Bc/Al = 0.6)

Highest Critical Load (Bc/Al = 1.2)

Highest Critical Load (Bc/Al =10.0)

Lowest Critical Load (Bc/Al = 0.6)

Lowest Critical Load (Bc/Al = 1.2)

Lowest Critical Load (Bc/Al = 10.0)

Figure 4.3.10. The lowest and highest critical load function response curves for 

the three levels of protection ((Bc/Al)crit = 0.6, 1.2, and 10.0) for the critical load 

assessments for the full geographical range of red spruce. The CLmin(N) value for 

all curves is 42.86 eq/ha/yr, but this value is not indicated in the figure. 

4.3.9 Uncertainty and Variability 

4.3.9.1 Kane Experimental Forest and Hubbard Brook Experimental Forest Case 

Study Areas 

Despite the extensive use of the SMB model to estimate critical loads, there is uncertainty 

regarding the output from the model and calculations. To a large degree, this uncertainty comes 

from the dependence of the SMB calculations on assumptions made by the researcher and the 

use of default values. Parameters including base cation weathering, forest soil ANC of critical 

load leaching, Kgibb, base cation and nitrogen uptake, nitrogen immobilization, and 

denitrification are rarely measured at each location and must be selected based on the literature 

or on other calculations and models. In an analysis conducted by Li and McNulty (2007), it was 

determined that the base cation weathering and forest soil ANC of critical load leaching 
Chapter 4 –Acidification 

parameters were the main sources of uncertainty, with 

each respectively contributing 49% and 46% to the 

total variability in critical load estimates. It has, 

therefore, been suggested that the calculation of 

critical loads using a relevant range of parameter 

values can provide the foundation for an uncertainty 

analysis (Hall et al., 2001; Hodson and Langan 1999; 

Li and McNulty, 2007;); it is likely that the correct 

critical load of a system will be contained within the 

range of load estimates from such an approach. If all 

or a large majority of estimates indicate that the 

critical load of a system is exceeded with current total 

nitrogen and sulfur deposition rates, it is likely that 

deposition is greater than the critical load and that the trees and vegetation in that system are 

being negatively impacted by acidification. Conversely, if deposition is not greater than the 

majority of critical load estimates, there can be greater confidence that the system is not being 

impacted by acidifying deposition. Under a scenario of a near equal number of estimates 

indicating exceedance and nonexceedance, however, it is not possible to confidently determine 

the actual acidification status of a system. Nonetheless, such results do suggest that the system is 

near the critical load level and should be monitored or assessed more thoroughly. 

“Uncertainty is a measure of the 

knowledge of the magnitude of a 

parameter. Uncertainty can be reduced 

by research, i.e., the parameter value 

can be refined. Uncertainty is quantified 

as a distribution. For example, the 

volume of a lake may be estimated from 

its surface area and an average depth. 

This estimate can be refined by 

measurement. Variance is a measure of 

the heterogeneity of a landscape 

parameter or the inherent variability in a 

chemical property. Variance can not be 

reduced by further research. It is 

quantified as a distribution. For example, 

the organic carbon content of the soil in 

a region may vary, even over short 

distances. The soil is not homogenous 

and thus the organic carbon content can 

be described with a distribution of 

values” (Webster and MacKay, 2003). 

In this case study, multiple values were used for several parameters in the SMB 

calculations and are detailed in Appendix 5. Therefore, it was possible to use the range of output 

values from the calculations to access the certainty of the acidification status of the HBEF and 

KEF case study areas. The patterning of the results suggest that the 2002 total nitrogen and sulfur 

deposition levels were very close to, if not greater than, the critical loads of the two case study 

areas, and both ecosystems are likely to be sensitive to any future changes in the levels of 

nitrogen and sulfur acidifying deposition. 

4.3.9.2 Expansion of Critical Load Assessments to Determine Current Conditions for 

Sugar Maple and Red Spruce 

Critical load estimates for individual plots within the distribution ranges of sugar maple 

and red spruce were calculated using the clay-substrate method to estimate BCw. As discussed 

Final Risk and Exposure Assessment 4-82 September 2009 
Chapter 4 –Acidification 

earlier, the BCw term within the SMB model is one of the most influential terms in the 

calculation of a critical load, and the determination of this BCw value is strongly influenced by 

the classified acidity of the soil parent material. In large-scale analyses, descriptions of the 

mineralogy of parent material underlying the soil may be missing, nondescriptive, only 

suggestive of mineralogy, or these may only represent the dominant mineralogy in a large area 

(and therefore not accurately capture the smaller-scale variation in mineralogy). Therefore, it is 

possible to misclassify the parent material acidity in the BCw term. 

In the analyses of critical loads for the full distribution ranges of sugar maple and red 

spruce in this Risk and Exposure Assessment, two fine-scale databases, the Soil Survey 

Geographic Database (SSURGO) of soils [USDA-NRCS, 2008] and USGS state-level geology 

[USGS, 2009] databases, were used as the sources for parent material mineralogy to allow for 

location-specific mineralogy descriptions. In addition, a systematic protocol based on known and 

probable silica and ferromagnesium content, spatial patterns of local and geologic settings, and 

implied depositional mechanisms and environments was used to determine the parent material 

acidity classifications. Therefore, steps were taken to determine accurate, location-specific 

acidity classifications. Nonetheless, parent material in some of the plots may have been 

misclassified. 

To evaluate the degree to which critical load estimates could change with a 

misclassification of parent material acidity, a simple analysis of absolute (eq/ha/yr) and 

percentage change associated with misclassifications of parent materials was conducted, using 

the critical loads associated with the three levels of protection ((Bc/Al)crit = 0.6, 1.2, and 10.0) for 

sugar maple and red spruce. The differences between all combinations of critical loads calculated 

with basic, intermediate, and acidic parent materials were determined, and these differences in 

values were expressed as a percentage of the original critical load estimates (described further in 

Appendix 5). 

The comparisons of critical loads revealed that changes in critical load values could range 

from 0 to 3,631 eq/ha/yr for sugar maple and 0 to 1,584 eq/ha/yr for red spruce with the 

misclassification of parent material acidity. These ranges corresponded to percentage differences 

ranging from 0% to 492% and 0% to 453% for sugar maple and red spruce, respectively. The 

results also indicated that the biggest impacts of a misclassification on critical load estimates 

would occur with an acidic parent material being misclassified as basic; the average percentage 

changes in the estimated critical loads, in such a scenario, were 67% to 70% for sugar maple and 

Final Risk and Exposure Assessment 4-83 September 2009 
Chapter 4 –Acidification 

74% to 78% for red spruce, and the median percentage changes were 60% to 61% and 71% to 

74% for the two species, respectively. In contrast, the smallest impacts on critical load estimates 

would occur when a basic parent material was incorrectly classified as intermediate and vice 

versa. In this scenario, the average and median percentage changes in critical load estimates were 

only 7% to 8% and 6% to 7% for sugar maple and 5% to 6% and 4% to 5% for red spruce. Given 

the potential significant impacts of a misclassification of parent material acidity on critical load 

estimates, this potential source of error should be considered in the accuracy and application of 

the critical load estimates. 

4.4 SUMMARY AND KEY FINDINGS 

Sulfur and nitrogen deposition have been linked to changes in biogeochemistry related to 

aquatic ecosystems. Deposition of SOx, NOx, and NHx leads to ecosystems’ exposure to 

acidification due to the reactions in the atmosphere that form various acidifying compounds. 

Acidifying deposition can lower the pH and ANC of aquatic systems. As ANC values decline 

below 100 μeq/L, an increase in the direct effects are exhibited on individual aquatic species, 

including fitness loss or death, reduced species richness, and altered community structure. 

Further, acidifying deposition can significantly increase the concentration of anions in soil, 

leading to an accelerated base cation leaching of Ca2+ and Mg2+ and, subsequently, an increase in 

the mobility of inorganic Al, which is toxic to fish, algae, and aquatic invertebrates. 

The role of aquatic acidification in two eastern United States areas—northeastern New 

York’s Adirondack area and the Shenandoah area in western Virginia—was analyzed to assess 

surface water trends in SO4

2- and NO3-

 concentrations and ANC levels and to affirm the 

understanding that reductions in deposition could influence the risk of acidification. Monitoring 

data from the EPA-administered TIME/LTM and EMAP programs were assessed for the years 

1990 to 2006, and past, present, and future water quality levels were estimated both steady-state 

and dynamic biogeochemical models. A summary of findings follows: 

 Although wet deposition rates for SO2 and NOx in the Adirondack Case Study Area have 

been reduced since the mid-1990s, current concentrations in are still well above 

preacidification (1860) conditions. MAGIC modeling predicts NO3

-

 and SO4

2- are 17- and 

5-fold higher today, respectively. The estimated average ANC for 44 lakes in the 

Adirondack Case Study Area is 62.1 μeq/L (± 15.7 μeq/L); 78 % of all monitored lakes in 

Final Risk and Exposure Assessment 4-84 September 2009 
Chapter 4 –Acidification 

the Adirondack Case Study Area have a current risk of Elevated, Severe, or Acute. Of the 

78%, 31% experience episodic acidification, and 18% are chronically acidic today. 

 Based on the steady-state critical load model for the year 2002, 18%, 28%, 44%, and 58% 

of 169 modeled lakes received combined total sulfur and nitrogen deposition that exceeded 

their critical load, with critical ANC limits of 0, 20, 50, and 100 μeq/L, respectively. 

 Based on a deposition scenario that maintains current emission levels to 2020 and 2050, 

the simulation forecast indicates no improvement in water quality in the Adirondack Case 

Study Area. The percentage of lakes within the Elevated to Acute Concern classes remains 

the same in 2020 and 2050. 

 Since the mid-1990s, streams in the Shenandoah Case Study Area have shown slight 

declines in NO3

-

 and SO4

2- concentrations in surface waters. ANC levels increased from 

about 50 μeq/L in the early 1990 to >75 μeq/L until 2002 when ANC levels declined back 

to 1991–1992 levels. Current concentrations are still above preacidification (1860) 

conditions. MAGIC modeling predicts surface water concentrations of NO3

-

 and SO4

2- are 

10- and 32-fold higher today, respectively. The estimated average ANC for 60 streams in 

the Shenandoah Case Study Area is 57.9 μeq/L (± 4.5 μeq/L). 55% of all monitored 

streams in the Shenandoah Case Study Area have a current risk of Elevated, Severe, or 

Acute. Of the 55%, 18% experience episodic acidification, and 18% are chronically acidic 

today. 

 Based on the steady-state critical load model for the year 2002, 52%, 72%, 85%, and 93% 

of 60 modeled streams received combined total sulfur and nitrogen deposition that 

exceeded their critical load, with critical ANC limits of 0, 20, 50, and 100 μeq/L, 

respectively. 

 Based on a deposition scenario that maintains current emission levels to 2020 and 2050, 

the simulation forecast indicates that a large number of streams still have Elevated to 

Acute problems with acidity. In fact, from 2006 to 2050, the percentage of streams with 

Acute Concern increases by 5%, while the percentage of streams in Moderate Concern

decreases by 5%. 

Tree health has been linked to base cations (Bc) in soil (such as Ca2+, Mg2+ and 

potassium), as well as soil Al content. Acidifying nitrogen and sulfur deposition can deplete soils 

of base cations and subsequently mobilize Al, making the toxic Al available to sensitive trees 

and other terrestrial vegetation. A critical load analysis was performed for sugar maple and red 

Final Risk and Exposure Assessment 4-85 September 2009 
Chapter 4 –Acidification 

spruce forests in the eastern United States by using the ratio of Bc to Al in acidified forest soils 

as an indicator to assess the impact of nitrogen and sulfur deposition on tree health. These are the 

two most commonly studied species in North America for impacts of acidification. At a Bc/Al 

ratio of 1.2, red spruce growth can be reduced by 20%. Sugar maple growth can be reduced by 

20% at a Bc/Al ratio of 0.6. Key findings of the case study are summarized below. 

 Case study results suggest that the health of at least a portion of the sugar maple and red 

spruce growing in the United States may have been compromised with acidifying total 

nitrogen and sulfur deposition in 2002: 

− 2002 CMAQ/NADP total nitrogen and sulfur deposition levels exceeded three selected 

critical loads in 3% to 75% of all sugar maple plots across 24 states. The three critical 

loads ranged from 107 to 6,008 eq/ha/yr for the Bc/Al ratios of 0.6, 1.2, and 10.0 

(increasing levels of tree protection). 

− 2002 CMAQ/NADP total nitrogen and sulfur deposition levels exceeded three selected 

critical loads in 3% to 36% of all red spruce plots across eight states. The three critical 

loads ranged from 180 to 4,278 eq/ha/yr for the Bc/Al ratios of 0.6, 1.2, and 10.0 

(increasing levels of tree protection). 

 The Simple Mass Balance model assumptions made for base cation weathering (Bcw) and 

forest soil ANC input parameters are the main sources of uncertainty since these 

parameters are rarely measured and require researchers to use default values. Bcw 

contributed 49% to the total variability in the critical load estimates, and forest soil ANC 

contributed 46% to the total variability. 

 The pattern of case study results suggests that nitrogen and sulfur acidifying deposition in 

the sugar maple and red spruce forest areas studied were very close to, if not greater than, 

the critical loads for those areas, and both ecosystems are likely to be sensitive to any 

future changes in the levels of deposition. 

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Chapter 5 – Nutrient Enrichment 

5.0 NUTRIENT ENRICHMENT 

5.1 SCIENCE OVERVIEW 

Nutrient enrichment is an increase 

in a nutrient, such as nitrogen, 

that may result in an imbalance in 

ecological stoichiometry, causing 

effects on processes, structure, 

and function. Organisms in their 

natural environment are 

commonly adapted to a specific 

regime of nutrient availability 

(Sterner and Elser, 2002). 

Nitrogen and sulfur enrichment represents a 

continuum of effects that can be characterized as positive or 

negative, depending on the selected ecological endpoint, 

location, and baseline conditions of an ecosystem. Nutrient 

enrichment describes a condition where an increase in a 

nutrient, such as nitrogen, may result in an imbalance in 

ecological stoichiometry, causing effects on ecological 

processes, structure, and function. Organisms in their natural environment are commonly adapted 

to a specific regime of nutrient availability (Sterner and Elser, 2002). Some organisms may at 

first respond positively to an initial increase in nutrients, exhibiting a fertilized increase in 

growth. However, as the nutrient load continues to rise, the imbalance can have negative effects 

in the organism’s response or the invasion of new organisms that benefit from increased 

nutrients. In general, ecosystems that are most responsive to nutrient enrichment from 

atmospheric nitrogen deposition are those that receive high levels of deposition relative to 

nonanthropogenic nitrogen loading, those that are nitrogen-limited, or those that contain species 

that have evolved in nutrient-poor environments (U.S. EPA, 2008, Section 3.3). Nutrient 

enrichment in ecosystems may alter the native terrestrial species composition (e.g., species shift 

from wildflower meadows to shrubs) and can result in eutrophication in aquatic systems (see 

Section 3.3 of the Integrated Science Assessment (ISA) for Oxides of Nitrogen and Sulfur–

Ecological Criteria (Final Report) (ISA) (U.S. EPA, 2008). 

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Chapter 5 – Nutrient Enrichment 

Both aquatic and terrestrial effects of nutrient enrichment have been studied, and nitrogen 

enrichment is highlighted in this chapter. (Sulfur enrichment is discussed in Chapter 6.) For each 

effect, information is presented on the following: 

 Ecological indicators, ecological responses, and ecosystem services 

 Characteristics of areas sensitive to nutrient enrichment 

 Selection of case study area(s) 

 Current conditions in case study areas 

 The ability to extrapolate case study findings to larger regions 

 Current conditions for larger regions (based on extrapolation) 

 Ecological effect functions 

 Uncertainty and variability associated with the case study analyses. 

Case studies on aquatic nutrient enrichment and terrestrial nutrient enrichment were 

performed as part of this Risk and Exposure Assessment (Appendices 6 and 7, respectively) to 

aid in determining whether a link can be established between deposition of nitrogen oxides 

(NOx) (and/or total reactive nitrogen) and ecosystem response, as well as the impact of total 

reactive nitrogen deposition relative to NOx deposition. These case studies are also intended to 

test whether area-based risk and exposure assessments are a suitable method for predicting 

nutrient enrichment effects on other ecosystems and geographic regions. The studies facilitate 

extrapolation of impacts from smaller-scale that are representative of sensitive areas to similar 

ecosystems across the country. 

It should be noted that while the case studies were designed to provide the best 

representation of an ecosystem and its response to nutrient enrichment as the state of science 

allows, not all nutrient-cycling processes could be detailed. Specifically, while the volatilization 

of nitrogen from both aquatic and terrestrial ecosystems is recognized as an important piece of 

the nitrogen cycle (as highlighted in Annex C of the ISA [U.S. EPA, 2008] and discussed in 

Appendix 6 of this Risk and Exposure Assessment), the complexity of the environmental 

controls on the nutrient cycling processes involved precluded quantifying or considering 

volatilization. 

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Chapter 5 – Nutrient Enrichment 

5.1.1 Aquatic Nutrient Enrichment 

Nutrient enrichment can result in eutrophication of aquatic systems (U.S. EPA, 2008, 

Section 3.3). Eutrophication is the process whereby a body of water becomes overenriched in 

nutrients, resulting in increased productivity. As productivity increases with concomitant 

increases in organic matter production, dissolved oxygen levels in the waterbody may decrease 

and lead to hypoxia (i.e., low dissolved oxygen levels). Total reactive nitrogen (Nr) can promote 

eutrophication in inland freshwater, estuarine, and coastal marine ecosystems. Eutrophication 

ultimately reduces biodiversity because of the lack of available oxygen needed for the survival of 

many aquatic plants and animals. The ISA concluded that there is sufficient evidence to infer a 

causal relationship between nitrogen deposition and the biogeochemical cycling of nitrogen in 

estuaries and coastal marine waters. Atmospheric nitrogen deposition is not the sole source of 

nitrogen loading to estuaries, and it is unknown if atmospheric deposition alone is sufficient to 

cause eutrophication. However, the contribution of atmospheric nitrogen deposition to total 

nitrogen load is calculated for some estuaries and can be >40%. In general, estuaries tend to be 

nitrogen-limited, and many currently receive high levels of nitrogen input from human activities 

to cause eutrophication. Because ecosystems may respond differently to enrichment, it is 

necessary to first perform risk and exposure assessments unique to the effect and ecosystem type. 

Appendix 6 presents a case study on two river basins and their estuaries: the Potomac 

River/Potomac Estuary and the Neuse River/Neuse River Estuary, and Section 5.2 summarizes 

the science, methodologies, and findings of the Aquatic Nutrient Enrichment Case Study. 

5.1.2 Terrestrial Nutrient Enrichment 

The ISA (U.S. EPA, 2008, Section 3.3) documented the current understanding of nutrient 

enrichment effects on terrestrial ecosystems and concluded that there is sufficient information to 

infer a causal relationship between atmospheric nitrogen deposition and biogeochemical cycling 

and fluxes of nitrogen in terrestrial systems. The ISA also concluded that there is a causal 

relationship between atmospheric nitrogen deposition and changes in species richness, species 

composition, and biodiversity in terrestrial systems. These conclusions are based on an extensive 

literature review, which is summarized in Table 4-4 of the ISA. The research involves both 

observational and experimental (nitrogen-addition) projects and includes alpine ecosystems, 

grasslands (including arid and semiarid ecosystems), forests, and deserts. It should be noted that 

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Chapter 5 – Nutrient Enrichment 

ecosystems and their component parts demonstrate different sensitivities to atmospheric nitrogen 

deposition. For example, shifts in lichen communities may occur at low levels of nitrogen 

deposition, 3 kg/ha/yr (Fenn et al., 2008), while shifts in serpentine grassland species were seen 

to occur at 10 to 15 kg N/ha/yr (Fenn et al., 2003). 

The extensive documentation in the ISA was used to assist in the selection of the case 

study areas for this Risk and Exposure Assessment and to identify and compare ecological 

benchmarks of different ecosystems. Appendix 7 presents the case study report for two 

ecosystems: California coastal sage scrub (CSS) and San Bernardino Mountains mixed conifer 

forest (MCF). Section 5.3 summarizes the Terrestrial Nutrient Enrichment Case Study. 

5.2 AQUATIC NUTRIENT ENRICHMENT 

Aquatic nutrient enrichment is described in the ISA (U.S. EPA, 2008, Section 3.3) for 

both freshwater and coastal marine and estuarine systems. In nitrogen-limited freshwater aquatic 

systems, atmospheric inputs of nitrogen increase productivity and alter biological communities, 

especially phytoplankton. A freshwater lake or stream must be nitrogen-limited to be sensitive to 

nitrogen-mediated eutrophication. There are many examples of fresh waters that are nitrogenlimited or nitrogen and phosphorus co-limited (e.g., Baron, 2006; Bergström and Jansson, 2006; 

Bergström et al., 2005; Elser et al., 1990; Fenn et al., 2003; Tank and Dodds, 2003). In a metaanalysis that included 653 datasets, Elser et al. (2007) found that nitrogen limitation occurred as 

frequently as phosphorus limitation in freshwater ecosystems. Recently, a comprehensive study 

(Bergström and Jansson, 2006) of available data from the northern hemisphere survey of lakes 

along gradients of nitrogen deposition showed increased inorganic nitrogen concentrations and 

productivity to be correlated with atmospheric nitrogen deposition, leading to the conclusion that 

the results are evidence of nitrogen limitation in lakes with low ambient inputs of nitrogen and 

increased nitrogen concentration in lakes receiving nitrogen solely from atmospheric nitrogen 

deposition (Bergström and Jansson, 2006). 

In coastal marine ecosystems, the nutrients most commonly associated with 

phytoplankton growth are nitrogen, phosphorus, and silicon. Interactions among the supplies of 

these nutrients can affect phytoplankton species composition in ways that might affect ecosystem 

function (Paerl et al., 2001a; Riegman, 1992). The relative proportions of these nutrients are 

important determinants of primary production, food web structure, and energy flow through the 

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Chapter 5 – Nutrient Enrichment 

ecosystem (Dortch and Whitledge, 1992; Justic et al., 1995a; Justic et al., 1995b; Turner et al., 

1998). 

There is strong scientific consensus that nitrogen is the principal cause of coastal 

eutrophication in the United States (NRC, 2000). On average, human activity has likely 

contributed to a six-fold increase in the nitrogen flux to U.S. coastal waters, and nitrogen now 

represents the most significant coastal pollution problem (Howarth et al., 2002b; Howarth and 

Marino, 2006). Atmospheric deposition is responsible for a portion of this nitrogen input 

(Howarth et al., 2002a). 

Estuaries and coastal waters tend to be nitrogen-limited and are, therefore, inherently 

sensitive to increased nitrogen loading (D’Elia et al., 1986; Howarth and Marino, 2006). There is 

a scientific consensus that nitrogen-driven eutrophication in shallow estuaries has increased over 

the past several decades and that the environmental degradation of coastal ecosystems is now a 

widespread occurrence (Paerl et al., 2001a). For example, the frequency of phytoplankton 

blooms and the extent and severity of hypoxia have increased in the Chesapeake Bay (Officer et 

al., 1984) and Pamlico estuaries in North Carolina (Paerl et al., 1998) and along the continental 

shelf adjacent to the Mississippi and Atchafalaya rivers’ discharges to the Gulf of Mexico (Eadie 

et al., 1994). It is partly because many estuaries and near-coastal marine waters are degraded by 

nutrient enrichment that they are highly sensitive to potential negative impacts from nitrogen 

addition from atmospheric deposition. 

The Aquatic Nutrient Enrichment Case Study for this Risk and Exposure Assessment 

(Appendix 6) focuses on two estuarine systems—the Potomac Estuary and the Neuse River 

Estuary. The ecological indicator selected, risk and exposure assessment methodology, and 

findings for each system are described in this section. 

5.2.1 Ecological Indicators, Ecological Responses, and Ecosystem Services 

5.2.1.1 Indicators 

Overview 

Nitrogen is an essential nutrient for estuarine and marine ecosystem fertility; a key 

nutrient in the primary production of aquatic vegetation; and is often the algal growth-limiting 

nutrient (U.S. EPA, 2008, Section 3.3.5.3). Excessive nitrogen contributions increase primary 

productivity excessively and, in turn, cause habitat degradation, algal blooms, toxicity, hypoxia, 

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Chapter 5 – Nutrient Enrichment 

anoxia, fish kills, and decreases in biodiversity (Paerl, 2002). To evaluate these impacts, five 

biological indicators were used in the recent national assessment of estuary trophic condition: 

chlorophyll a, macroalgae, dissolved oxygen, nuisance/toxic algal blooms, and submerged 

aquatic vegetation (SAV) (Bricker et al., 2007). Figure 5.2-1, excerpted from the National 

Oceanic and Atmospheric Administration’s (NOAA’s) National Estuarine Eutrophication 

Assessment (NEEA) Update, provides a brief description of each of the indicators. For greater 

detail on each of the indicators, refer to the ISA (U.S. EPA, 2008, Section 3.3) and the NEEA 

Update (Bricker et al., 2007). 

Figure 5.2-1. Descriptions of the five eutrophication indicators used in the NEEA 

(Bricker et al., 2007).

Selection of an Ecological Indicator 

After examining several estuarine assessment options, the most comprehensive 

evaluation technique that could be applied on a wide scale was determined to be an assessment 

of eutrophication as conducted in NOAA’s NEEA. The NEEA Program defined and developed a 

Pressure-State-Response framework to assess the potential for eutrophication. This assessment 

framework has been titled the Assessment of Estuarine Trophic Status Eutrophication Index and 

is commonly referred to as ASSETS EI (Bricker et al., 2007). The “pressure” is the nitrogen, the 

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Chapter 5 – Nutrient Enrichment 

“state” is the current eutrophic condition, and the “response” would be the change in the state of 

the system. ASSETS EI is an estimation of the likelihood that the estuary is experiencing 

eutrophication or will experience eutrophication in the future based on the five indicators 

described above. The ASSETS EI served as the ecological indicator for the Aquatic Nutrient 

Enrichment Case Study. 

The ASSETS EI incorporates indirect deposition over the watershed (i.e., deposition to 

terrestrial systems which, in turn, may be transported to aquatic systems) through the evaluation 

of nitrogen loading to the estuary. This was achieved by inputting 2002 Community Multiscale 

Air Quality (CMAQ)–modeled and National Atmospheric Deposition Program (NADP)–

monitored data (see Chapter 3) to the U.S. Geological Survey’s (USGS’s) SPAtially Referenced 

Regressions on Watershed attributes (SPARROW) model. The combination of SPARROW 

modeling and the ASSETS EI (Appendix 6, Figure 2.2-1) provides a sound basis for conducting 

an eutrophication assessment. 

ASSETS EI 

The ASSETS EI (a Pressure-State-Response framework) is categorical, where each of 

three indices produces a score. The three scores are combined, and the overall score (the 

ASSETS EI) represents the estuary’s health. The indices are as follows: 

 Influencing Factors/Overall Human Influence (OHI). The physical, hydrologic, and 

anthropogenic factors that characterize the susceptibility of the estuary to the influences 

of nutrient inputs (also quantified as part of the index) and eutrophication. 

 Overall Eutrophic Condition (OEC). An estimate of current eutrophic conditions 

derived from data for five symptoms known to be linked to eutrophication. 

 Determined Future Outlook (DFO). A qualitative measure of expected changes in the 

system. 

(See Figures 2.2-6 and 2.2-8 in Appendix 6 for the ASSETS EI approach to assessing 

OEC and DFO.) 

The ASSETS EI scores fall into one of six categories: High, Good, Moderate, Poor, Bad, 

or Unknown. These ratings can be summarized as follows (Bricker et al., 2007): 

 High: Low pressure, low eutrophic condition, and any expected improvement or no 

future change in eutrophic condition 

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Chapter 5 – Nutrient Enrichment 

 Good: Low to moderate pressure, low to moderate-low eutrophic condition, and any 

expected future change in condition 

 Moderate: Any pressure, moderate-low to moderate-high eutrophic condition, and any 

expected future change in eutrophic condition 

 Poor: Moderate-low to high pressure, moderate to moderate-high eutrophic condition, 

and any expected future change in condition 

 Bad: Moderate to high pressure, moderate-high to high eutrophic condition, and any 

expected future change in eutrophic condition 

 Unknown: Insufficient data for analysis. 

NOAA’s ASSETS EI method was first reported in 1999. Since that time, it has been used 

in several assessments across the country and internationally, and it has undergone revision and 

validation (Bricker et al., 1999, 2003, 2007; Ferreira et al., 2007; Whitall et al., 2007). 

SPARROW 

SPARROW is a watershed modeling technique designed and supported by the USGS. 

The model relies on a nonlinear regression formulation to relate water quality measurements 

throughout the watershed of interest to attributes of the watershed. (Note that with a nonlinear 

model, errors of the model are assumed to be independent across observations and have zero 

mean; the variance of each observation may be observation-specific.) Both point and diffuse 

sources within the watershed are considered, along with nonconservative transport processes 

(i.e., loss and storage of contaminants within the watershed). SPARROW follows the rules of 

mass balance while using a hybrid statistical and process-based approach. Utilization of the 

SPARROW model results in estimates of long-term, steady-state water quality in a stream 

(typically mean annual stream loadings of a contaminant). 

A key component of SPARROW is its reliance on the spatial distribution of watershed 

characteristics and sources. The stream reach network is spatially referenced against all 

monitoring stations, geographic information systems (GIS) data for watershed properties, and 

source information. This structure allows for the simulation of fate and transport of contaminants 

from sources to streams and their downstream ecological endpoints. Figure 5.2-2 shows how 

each watershed and stream reach within the stream network defined for the SPARROW 

application (represented by different colors in the figure) is processed separately and linked to 

derive a final loading at a downstream location (i.e., the star labeled X). The SPARROW model 

Final Risk and Exposure Assessment 5-8 September 2009 
Chapter 5 – Nutrient Enrichment 

is calibrated at each monitoring station (represented by stars in Figure 5.2-2) by comparing the 

modeled loads (i.e., a total of loads from each watershed segment and any upstream loads from 

previous calibrations) against monitored data at the station. In this case, the modeled load at 

downstream monitoring station X would include loads from upstream monitoring station Y and 

the five watershed segments between the two monitoring stations. 

Figure 5.2-2. Conceptual illustration of a reach network. 

The mathematical formulation of SPARROW used to determine nitrogen loadings for 

this case study is presented in Appendix 6. The equations used in SPARROW represent the mass 

loading, which includes sources, losses due to transport to the stream reaches (i.e., landscape 

characteristics that influence the delivery of diffuse sources of contamination to the stream), and 

instream or reservoir losses (i.e., stream attenuation processes that act on contaminant flux as it 

travels along stream reaches). 

Within SPARROW, instream losses depend on a first-order loss rate and the length of the 

stream, while losses within a lake or reservoir depend on a first-order loss rate and the areal 

hydraulic load of the lake or reservoir (i.e., ratio of water-surface area to outflow discharge). 

Results of the SPARROW model may be presented in three different accounting 

measures. These measures allow for the examination of how much nitrogen originates within a 

specific subbasin, how much of that nitrogen reaches the estuary, and finally, the total amount of 

nitrogen that reaches the estuary. Specifically, these measures are defined by the following: 

Final Risk and Exposure Assessment 5-9 September 2009 
Chapter 5 – Nutrient Enrichment 

 Delivered Yield (load per area). This is the amount of nutrients generated locally for 

each stream reach and weighted by the amount of instream loss that would occur with 

transport from the reach to the receiving water. The cumulative loss of nutrients from 

generation to delivery to the receiving water is dependent on the travel time and instream 

loss rate of each individual reach (Preston and Brakebill, 1999). 

 Incremental Yield (load per area). This yield represents the local generation of 

nutrients. It is the amount of nutrients generated locally (independent of upstream load) 

and contributed to the downstream end of each stream reach. Each stream reach and 

associated watershed is treated as an independent unit, quantifying the amount of nutrient 

generated (Preston and Brakebill, 1999). 

 Total Yield (load per area). This is the amount of nutrients, including upstream load, 

contributed to each stream reach. These estimates are calculated by stream reach and 

account for all potential sources cumulatively and individually (Preston and Brakebill, 

1999). 

The statistical basis of SPARROW means that the model is empirical, even though it 

attempts to represent fate and transport processes such as instream loss due to denitrification. As 

such, any model created by SPARROW is a function of the data used in the calibration. The 

steady-state, mean annual average predictions remain valid as long as there is no great change in 

the conditions (in this case, the nitrogen loadings within each subbasin) underlying the model. 

By using the same model for both the current conditions and the alternative effects levels, it is 

necessary to assume that the steady-state predictions remain valid over both assessments. Given 

the large decreases in atmospheric deposition loading being considered, this assumption may not 

be correct and is a limitation of the analysis. However, given the time and data availability for 

the analysis, the assumption was required to carry out both assessments. Further confounding 

factors of the SPARROW model are discussed with the assessment results. 

5.2.1.2 Assessments of Ecological Responses Using SPARROW and ASSETS EI 

To assess ecological response, the SPARROW output serves as the nitrogen load for the 

calculation of the OHI index in the ASSETS EI. In this case study, a complete analysis from 

atmospheric deposition load to the ASSETS EI ecological endpoint requires the following: 

 An assessment of the relative changes in the deposition load 

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Chapter 5 – Nutrient Enrichment 

 The resulting instream nitrogen load to the estuary 

 The change in the ASSETS EI. 

Because an iterative assessment of changing nitrogen loads to predict ASSETS EIs has 

not been undertaken previously, a process to link the SPARROW model to the ASSETS EI was 

developed and used (See Appendix 6, Section 2.2.3). 

A series of response curves was created to relate nitrogen inputs to ecosystem responses 

in the watershed and estuary. First, the SPARROW model was used to predict the total nitrogen 

loads at the outlet of the watershed that result from changes in the total nitrogen atmospheric 

deposition loads (i.e., changes in the ambient air NOx concentrations and subsequent deposition 

that result from any new standard-setting scenarios). Second, a response curve was plotted for 

the ASSETS EI based on the OHI and OEC index scores (Appendix 6, Section 2.2.2), which are 

functions of total nitrogen load to the estuary. Bricker et al. (2007) noted that the shape of the 

response curve would vary depending on the susceptibility of the system. 

It is possible to combine all the OEC, OHI, and DFO index scores with the ASSETS EI 

into a single response curve when the susceptibility rating and DFO index score are held 

constant. The DFO index score may be held constant when alternative effects levels are being 

evaluated based on a current condition scenario. The susceptibility rating is based on physical 

and hydrological conditions, which are unlikely to change. For example, Figure 5.2-3 highlights 

this combination of scores where the susceptibility rating is “High” and the DFO index score is 

set at “Improve.” Additionally, by holding the susceptibility constant, the OHI index score 

becomes a function of the instream nitrogen concentration. This is evident in the double x-axis. 

The state response is the OEC index score along the y-axis. Underlying these combinations of 

OHI and OEC index scores is the ASSETS EI. 

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Chapter 5 – Nutrient Enrichment 

Figure 5.2-3. ASSETS EI response curve.

Within the analysis space created by both the OHI and OEC index scores, the axes are 

limited to the scores of zero (actually categorized as one in the NEEA Update) to five, but the 

corresponding instream nitrogen concentrations must be determined separately. Point “a” 

represents the background nitrogen concentration that would occur in the system with no 

anthropogenic inputs (assuming the system is not naturally eutrophic) or with the system at a 

pristine state. In almost all cases, this value will be unknown because of the extent to which 

anthropogenic inputs have influenced the nation’s ecosystems. A lower bound and upper bound 

on this value were specified between which the algorithm randomly selects a different realization 

for each iteration. The upper bound of the instream total nitrogen concentration (TNs), Point “b,” 

is the maximum nitrogen concentration at which the stream is nitrogen-limited; above this point, 

the nitrogen inputs to the system no longer affect the eutrophication condition. Again, because of 

natural variations, a constant value is unknown, and upper and lower bounds of the value must be 

specified for uncertainty analyses. 

The creation of the two response curves enables working backward from the ecological 

endpoint to the source of the impairment; in this case, from the ASSETS EI to the atmospheric 

Final Risk and Exposure Assessment 5-12 September 2009 
Chapter 5 – Nutrient Enrichment 

deposition loading of oxidized nitrogen. Specifically, the analysis in this case study sought to 

determine the change in oxidized nitrogen load required to improve the ASSETS EI by one, two, 

and three categories from its current level set in the 2002 current condition analysis. 

5.2.1.3 Ecosystem Services 

Provisioning Services 

Estuaries in the eastern United States are an important source of food production, in 

particular fish and shellfish production. The estuaries are capable of supporting large stocks of 

resident commercial species, and they serve as the breeding grounds and interim habitat for 

several migratory species. 

To provide an indication of the magnitude of provisioning services associated with 

coastal fisheries, from 2005 to 2007, the average value of total catch was $1.5 billion per year in 

15 East Coast states. It is not known, however, what percentage of this value is directly 

attributable to or dependent upon the estuaries in these states. Table 5.2-1 focuses specifically on 

commercial landings in Maryland and Virginia in 2007 and reports values for the main 

commercial species in these states. Although these values also include seafood caught outside of 

the Chesapeake Bay, the values for two key species—blue crab and striped bass—are 

predominantly from the estuary itself. These data indicate that blue crab landings in 2007 totaled 

nearly $44 million in the Chesapeake Bay. The value of striped bass and menhaden totaled about 

$9 million and $25 million, respectively. 

To most accurately assess how eutrophication in East Coast estuaries is related to the 

long-term provisioning services from their seafood resources requires bioeconomic models (i.e., 

models that combine biological models of fish population dynamics with economic models 

describing fish harvesting and consumption decisions). In most cases, these models address the 

dynamic feedback effects between fish stocks and harvesting behavior, and they characterize 

conditions for a “steady-state” equilibrium, where stocks and harvest levels are stabilized and 

sustainable over time. 

Section 5.2 describes one bioeconomic model linking blue crab harvests to nutrient loads 

in the Neuse River Estuary, and it applies the model to estimate how decreases in nitrogen loads 

to the estuary would affect the societal value of future blue crab harvests. In practice, however, 

very few other studies have developed empirical bioeconomic models to estimate how changes 

Final Risk and Exposure Assessment 5-13 September 2009 
Chapter 5 – Nutrient Enrichment 

in environmental quality affect seafood harvests and the value of these services (Knowler, 2002). 

One exception is Kahn and Kemp (1985), which estimated a bioeconomic model of commercial 

and recreational striped bass fishing using annual data from 1965 to 1979, measuring the effects 

of SAV levels on fish stocks, harvests, and social welfare. They estimated, for example, that a 

50% decrease in SAV from levels existing in the late 1970s (similar to current levels [CBP, 

2009]) would decrease the net social benefits from striped bass by roughly $16 million (in 2007 

dollars). 

In a separate analysis, Anderson (1989) developed an empirical dynamic simulation 

model of the effects of SAV changes on commercial blue crab harvests in the Virginia portion of 

the Chesapeake Bay. Applying the empirical model results, long-run (15-year) dynamic 

equilibria were estimated under baseline conditions (assuming SAV area constant at 1987 levels) 

and under conditions with “full restoration” of SAV (i.e., 284% increase). In equilibrium, the 

increase in annual producer surplus and consumer surplus with full restoration of SAV was 

estimated to be $3.5 million and $4.4 million (in 2007 dollars), respectively. 

Table 5.2-1. Value of Commercial Landings for Selected Species in 2007 

(Chesapeake Bay Region) 

State Species Value 

Maryland 

Blue crab $30,433,777 

Striped bass $5,306,728 

Clams or bivalves $5,007,952 

Sea scallop $2,808,984 

Oyster, Eastern $2,524,045 

Other $6,190,474 

Total $52,271,960 

Virginia 

Sea scallop $62,891,848 

Menhaden $25,350,740 

Blue crab $13,222,135 

Croaker, Atlantic $4,615,924 

Striped bass $3,834,906 

Clam, Northern Quahog $3,691,319 

Summer flounder $3,186,229 

Other $16,954,893 

Total $130,561,765 

Source: NOAA (2007, August). “Annual Commercial Landing Statistics.” 

(http://www.st.nmfs.noaa.gov/st1/commercial/landings/annual_landings.html) 

Final Risk and Exposure Assessment 5-14 September 2009 
Chapter 5 – Nutrient Enrichment 

Final Risk and Exposure Assessment 5-15 September 2009 

One study examining the short-term effects of dissolved oxygen (DO) levels on crab 

harvests is by Mistiaen et al. (2003). Focusing on three Chesapeake Bay tributaries―the 

Patuxent, Chester, and Choptank rivers—this study estimated a “stress-availability” model 

measuring the effects of DO levels on the availability of blue crabs for commercial harvest, 

given the stock levels and number of fishing vessels. The model results indicated that, below a 

threshold of 5 milligrams per liter (mg/L), decreases in DO cause a statistically significant 

decrease in commercial harvest and revenues. For the Patuxent River alone, a simulated decrease 

of DO from 5.6 to 4.0 mg/L was estimated to reduce crab harvests by 49% and decreased total 

annual earnings in the fishery by $275,000 (in 2007 dollars). However, this is an upper-bound 

estimate because it does not account for changes in fishing effort that would likely occur, and if 

the measured changes are due to migration of crab populations to other areas rather than to crab 

mortality, then the broader net effects on crab harvests may also be considerably smaller.1 

In addition to affecting provisioning services through commercial seafood harvests, 

eutrophication in estuaries may also affect these services through its effects on the demand for 

seafood. For example, a well-publicized toxic pfiesteria bloom in the Maryland Eastern Shore in 

1997, which involved thousands of dead and lesioned fish, led to an estimated $56 million (in 

2007 dollars) in lost seafood sales for 360 seafood firms in Maryland in the months following the 

outbreak (Lipton, 1999). Additional evidence regarding potential losses in provisioning services 

due to eutrophication-related fish kills is provided by Whitehead et al. (2003) and Parsons et al. 

(2006). The survey used in both studies was conducted with more than 5,000 respondents in 

states bordering the Chesapeake Bay area and in North Carolina. The survey asked respondents 

to consider how their consumption patterns would change in response to news about a large fish 

kill caused by a toxic pfiesteria bloom. To address the fact that not all fish kills are the same, the 

size and type of the described fish kill―either “major,” involving more than 300,000 dead fish 

and 75% with pfiesteria lesions, or “minor,” involving 10,000 dead fish and 50% with 

lesions―were randomized across respondents. Based on respondents’ stated behaviors, the 

 

1 The estimated relationship between harvest and DO is discontinuous at 5 mg/L. The size of the measured effect on 

harvests is relatively small below 5 mg/L and is zero above the 5 mg/L threshold; therefore, any sizable benefits 

would require DO to cross the 5 mg/L threshold. Moreover, the 5 mg/L threshold was an assumption of the model 

rather than a tested hypothesis, which raises additional questions about the accuracy of benefit estimates for 

changes across the threshold. 
Chapter 5 – Nutrient Enrichment 

Final Risk and Exposure Assessment 5-16 September 2009 

studies estimated decreases in consumer surplus per seafood meal ranging from $2 to $5.2 The 

survey also found that 42% of residents in the four-state area (i.e., Maryland, Virginia, Delaware, 

and North Carolina) were seafood consumers and that the average number of seafood meals per 

month among these consumers was between four and five. As a result, they estimated aggregate 

consumer surplus losses of $43 million to $84 million (in 2007 dollars) in the month after a fish 

kill. 

Cultural Services 

Estuaries in the eastern United States also provide an important and substantial variety of 

cultural ecosystem services, including water-based recreational and aesthetic services. One of the 

difficulties with quantifying recreational services from estuaries is that much of the national and 

regional statistics are jointly collected and reported for estuarine and other coastal areas. 

Nevertheless, even these combined statistics provide several useful indicators of recreational 

service flows. For example, data from the Fishing, Hunting, and Wildlife-Associated Recreation 

(FHWAR) indicate that, in 2006, 4.8% of the 16 and older population in coastal states from 

North Carolina to Massachusetts participated in saltwater fishing (U.S. DOI, 2007). The total 

number of days of saltwater fishing in these states was 26.1 million in 2006. Based on estimates 

from Kaval and Loomis (2003), the average consumer surplus value for a fishing day was $35.91 

(in 2007 dollars) in the Northeast and $87.23 in the Southeast. Therefore, the total recreational 

consumer surplus value from these saltwater fishing days was approximately $1.28 billion (in 

2007 dollars). Consumer surplus value is a commonly used and accepted measure of economic 

benefit (see, for example, U.S. EPA, 2000b). It is the difference between (1) the maximum 

amount individuals are, on average, willing and able to pay for a good, service, or activity (in 

this case, a day of recreational fishing) and (2) the amount they actually pay (in out-of-pocket 

and time costs). For recreation days, it is most commonly measured using recreation demand, 

travel cost models. 

Recreational participation estimates for several other coastal recreational activities were 

also available for 1999 to 2000 from the National Survey on Recreation and the Environment. 

Almost 6 million individuals age 16 and older participated in motorboating in coastal states from 

North Carolina to Massachusetts, for a total of nearly 63 million days annually during 1999 to 

 

2 Surprisingly, these estimates were not sensitive to whether the fish kill was described as major or minor or to the 

different types of information included in the survey. 
Chapter 5 – Nutrient Enrichment 

2000. Using a national daily value estimate of $32.69 (in 2007 dollars) for motorboating from 

Kaval and Loomis (2003), the aggregate value of these coastal motorboating outings was $2.08 

billion per year. Almost 7 million individuals participated in bird watching, for a total of nearly 

175 million participant days per year, and more than 3 million individuals participated in visits to 

non-beach coastal waterside areas, for a total of more than 35 million participant days per year. 

In contrast, less than 1 million individuals per year participated in canoeing, kayaking, or 

waterfowl hunting. 

Regulating Services 

Estuaries and marshes have the potential to support a wide range of regulating services, 

including those that are important for the quality and quantity of water and those that have 

effects on climate, including impacts from storms (MEA, 2005c). It is more difficult, however, to 

identify the specific regulating services that are significantly impacted by changes in nutrient 

loadings. One potentially affected service is provided by SAV, which can help decrease wave 

energy levels and thus protect shorelines against excessive erosion. Declines in SAV may, 

therefore, also increase the risks of episodic flooding and associated damages to near-shore 

properties or public infrastructure. In the extreme, these declines may even contribute to 

shoreline retreat, such that land and structures are lost to the advancing waterline. 

5.2.2 Characteristics of Sensitive Areas 

It is the general consensus that 

nitrogen is the limiting element to 

primary production in coastal marine 

ecosystems in the temperate zone. 

Howarth and Marino (2006) provide a 

comprehensive summary of the literature and scientific 

findings on eutrophication over the past 3 decades. That 

summary has led to the general consensus (1) that freshwater lakes and estuaries differ in terms 

of nutrient limitation as the cause of eutrophication, and (2) that nitrogen is the limiting element 

to primary production in coastal marine ecosystems in the temperate zone. The factors that make 

estuarine systems sensitive to nutrient enrichment are still weakly understood, but it is suggested 

that factors that influence the residence time of the estuarine waters and the complex interactions 

affecting nutrient and light limitation all play a role in determining sensitivity (Howarth and 

Marino, 2006). In general, ecosystems that are most vulnerable to nutrient enrichment from 

atmospheric nitrogen deposition are those that receive high levels of deposition relative to 

Final Risk and Exposure Assessment 5-17 September 2009 
Chapter 5 – Nutrient Enrichment 

Final Risk and Exposure Assessment 5-18 September 2009 

nonanthropogenic nitrogen loading, those that are nitrogen limited, or those that contain species 

that have evolved in nutrient-poor environments (U.S. EPA, 2008, Section 3.3) 

The selection of case study areas specific to eutrophication began with national GIS 

mapping to identify sensitive areas. Spatial datasets were reviewed that included physical, 

chemical, and biological properties indicative of eutrophication potential in order to identify 

sensitive areas of the United States. Datasets included in the USGS National Water Quality 

Assessment (NAWQA) Program files, U.S. EPA STORage and RETrieval (STORET) database, 

NOAA Estuarine Drainage Areas data, and EPA’s water quality standards nutrient criteria for 

rivers and lakes (see Appendix 6, Table 1.2-1). To define areas of national aquatic nutrient 

enrichment sensitivity, eutrophic estuaries from NOAA’s Coastal Assessment Framework (CAF) 

and areas that exceed the nutrient criteria for lakes/reservoirs (U.S. EPA, 2002) were combined. 

Exceedance levels were determined by first converting nitrogen concentration nutrient criteria 

amounts (mg/l) to wet nitrogen deposition amounts (kg/ha/yr) using a formula published by 

Bergström and Jansson (2006). These nitrogen deposition amounts were then compared to wet 

NADP nitrogen deposition (2002) amounts to determine areas of the United States that are either 

above or below the nutrient criteria levels for lakes/reservoirs. 

The resulting map revealed areas of highest potential sensitivity to nitrogen deposition as 

shown in Figure 5.2-4. These areas are identified in blue as nutrient-sensitive estuaries contained 

in NOAA’s CAF, and in red in areas where deposition exceeds the nutrient criteria. Yellow areas 

indicate those areas that are below the nutrient criteria, but are within 5 kilograms (kg) N/ha/yr 

of exceeding it. White areas do not have EPA nutrient criteria for lake/reservoirs. While this map 

delineates those regions that are sensitive to deposition by virtue of bedrock and topography, it 

may not represent regions with perched waterbodies that receive nitrogen deposition. 

The exceedance information was averaged spatially by nutrient criteria region using GIS. 

The nutrient criteria limit for total nitrogen for lakes/reservoirs, its equivalent in wet nitrogen 

deposition (using Bergström and Jansson’s equation), the mean wet nitrogen deposition from 

NADP, and the difference are shown in Table 5.2-2. While none of the regions exceed the 

nutrient criteria level using this aggregated data, it should be noted that this comparison used 

only wet nitrogen deposition. 
Chapter 5 – 

Table 5.2-2. Wet Nitrogen Deposition Level vs. EPA Total Nitrogen (TN) Criteria for Lakes and Reservoirs

Agg 

Ecor 

II 

Agg 

Ecor 

III 

Agg 

Ecor 

IV 

Agg 

Ecor 

V 

Agg 

Ecor 

VI 

Agg 

Ecor 

VII 

Agg 

Ecor 

VIII 

Agg 

Ecor 

IX 

Agg 

Ecor 

XI 

Agg 

Ecor 

XII 

TN EPA criteria (μg/L) 

100 400 440 560 780 660 240 360 460 520 

N wet dep (kg N/ha/yr) 

4.46 12.55 13.47 16.13 20.65 18.23 8.57 11.60 13.93 15.26 

NADP mean wet N dep (kg N/ha/yr) 

1.19 1.16 2.36 3.02 5.01 6.36 5.21 4.44 4.93 3.28 

Source: Prepared by Lingli Liu, U.S. EPA Office of Research and Development and transmitted in communication from T

Office of Research and Development, May 2008. (Comparable information was not available for rivers and streams.) 

Note: kg N/ha/yr = kilograms of nitrogen per hectare per year; μg/L = micrograms per liter. 

Final Risk and Exposure Assessment 5-19 
Chapter 5 – Nutrient Enrichment 

Final Risk and Exposure Assessment 5-20 September 2009 

Figure 5.2-4. Areas potentially sensitive to aquatic nutrient enrichment. Areas in 

red are most sensitive, and areas in dark green are least sensitive to wet nitrogen 

deposition. 

5.2.3 Case Study Selection 

Recommended case study areas are presented in the ISA (U.S. EPA, 2008, Sections 3.2, 

3.3, 3.4, 4.2, 4.3, 4.4, Annex B, and Annex C) as candidates for risk and exposure assessments. 

The Ecological Effects Subcommittee of the Advisory Council on Clean Air Compliance 

Analysis also made recommendations (see Appendix 6, Table 1.2-3). These recommendations, in 

tandem with the areas identified in the national characterization previously described, were used 

to select case study areas for this Risk and Exposure Assessment. 

Two regions were selected for case study analysis to which a common methodology 

could be applied—the Chesapeake Bay and the Pamlico Sound. Both estuaries were selected 

primarily based on the availability of research data. For aquatic nutrient enrichment, special 

emphasis was given to the Chesapeake Bay region because it has been the focus of many 

previous studies and modeling efforts, and it is currently one of the few systems within the 
Chapter 5 – Nutrient Enrichment 

Final Risk and Exposure Assessment 5-21 September 2009 

United States in which economic-related ecosystem services studies have been conducted. T

Pamlico Sound, an economically important estuary due to its fisheries, has been studied and 

modeled greatly by the local universities and has also been known to exhibit symptoms of 

extreme eutrophication. Factors including availability of atmospheric deposition data, exist

water quality modeling, and generalization opportunities for risk analysis from results were 

considered in choosing these case study areas. Other candidate estuarine systems could be 

evaluated for potential future analyses, while freshwater ecosystems in the western United S

would most likely require a separate analysis. Because the Chesapeake Bay and Pamlico Sound 

are fed by multiple river systems, the case study was scaled to one main stem river for each 

system: the Potomac River/Potomac Estuary and the Neuse River/Neuse River Estuary. Deta

on each basin are provided in Appendix 6, Sections 1.2.3 and 1.2.4, respectively. 

The Potomac River contains diverse watersheds in terms of topography, el

he 

ing 

tates 

ils 

evation (e.g., 

extendi

d 

 river in North Carolina and is a mainstem river to the 

Pamlic the 

role in 

ecause 

ng into the Shenandoah Mountains), and nutrient point and nonpoint sources (e.g., 

forestland, farmland, and the Washington, DC, metropolitan area). The 14,670 mi2 (38,000

kilometers [km]2

) basin lies in five geological provinces: the Appalachian Plateau, Ridge an

Valley, Blue Ridge, Piedmont Plateau, and Coastal Plain. The watershed is approximately 12%

urbanized, 36% agricultural use, and 52% forested. Atmospheric deposition has been reported to

contribute from 5% to 15%–20% of the basin’s total nitrogen load (U.S. EPA, 2000; Boyer et al., 

2002). 

The Neuse River is the longest

o Sound—one of the two largest estuaries on the Atlantic Coast. The drainage area for

basin is approximately 14,210 mi2

 (36,804 km2) (NC DENR, 2002). The Neuse River watershed 

has a population of approximately 1,320,379, according to the 2000 census. Fifty-six percent of 

the land in the basin is forested, and approximately 23% is in cultivated cropland. There are 

134,540 estuarine hectares (332,457 acres) classified for shellfish harvesting (Class SA 

[shellfishing]) in the Neuse River Estuary. Atmospheric deposition is believed to play a 

nutrient loading to the Neuse River and Pamlico Sound. According to Whitall and Paerl (2001),

atmospheric deposition accounts for approximately 24% of the Neuse River watershed’s total 

nitrogen loading. Of these atmospheric deposition measurements, it is expected that the 

contributions will be greater from reduced forms of nitrogen than from oxidized forms b

of the large amounts of agriculture within the watershed. One of the reasons for selecting the 
Chapter 5 – Nutrient Enrichment 

Final Risk and Exposure Assessment 5-22 September 2009 

Neuse River/Neuse River Estuary Case Study Area is to evaluate the impact of a NOx-based 

standard on an area dominated by reduced forms of nitrogen. 

5.2.4 Current Conditions in the Case Study Areas 

States and has a complex 

ecosyst f five 

gram’s 

.aspx?menuitem=13989. In 2007, it was 21% of the 

t 

f 

Enrichment Case Study. 

The Chesapeake Bay is the largest estuary in the United 

em of important habitats and food webs. The Potomac River is the second largest o

major rivers that feed the Chesapeake Bay. Most of the Chesapeake Bay’s waters are degraded. 

Remediation goals over multiple categories were set forth in the Chesapeake 2000 Commitment,

an agreement between the heads of several state and commission stakeholders (Chesapeake Bay 

Executive Council, 2000). Because there are numerous indices and categories in which 

remediation goals have been set, the reader is instructed to view the Chesapeake Bay Pro

Remediation Web site for specific inquiries: 

http://www.chesapeakebay.net/bayrestoration

way toward meeting water quality goals (e.g., 40% decrease in nitrogen and phosphorus over 

1987 levels). The Chesapeake Bay’s current habitats and lower food web are at 44% of desired

levels (e.g., increased number of oysters, restored area of wetlands). Many of the Chesapeake 

Bay’s fish and shellfish populations are below historic levels. Currently, the Chesapeake Bay’s

fish and shellfish are at 52% of desired levels (e.g., counts of blue crabs, oysters, striped bass). 

Runoff from winter and spring rains delivers loads of sediment and nutrient pollutants that drive

summer water quality conditions. Past observations reveal that summer weather conditions also 

contribute to summer water quality when intense storms increase erosion. Nutrients reach the 

Chesapeake Bay from point and nonpoint source discharges and atmospheric deposition from a

570,000-mi2

 airshed (CBP, 2009) The National Water Quality Assessment states that although 

nitrogen and phosphorus occur naturally, elevated concentrations of nutrients often result from 

human activities. Atmospheric deposition from combustion of fossil fuels alone accounts for 

32% of nitrogen inputs (http://pubs.usgs.gov/circ/circ1166/circ1166.pdf). Although NAWQA

states that the water quality concentration of nutrients in the Potomac River watershed does no

pose a direct exposure threat to human health or wildlife, excessive nitrogen or phosphorus in 

streams can cause eutrophication. It is the condition of the Potomac Estuary (as a component o

the Chesapeake Bay) and its eutrophication potential that are the focus of the Aquatic Nutrient 
Chapter 5 – Nutrient Enrichment 

Final Risk and Exposure Assessment 5-23 September 2009 

Eutrophication became a water quality concern in the lower Neuse River watershed in th

late 1970s and early 1980s

e 

, and fish kills, algal blooms, and correspondingly high levels of 

chlorop

a 

s necessary to have atmospheric 

deposit

nses 

 Neuse 

SPARROW Assessment 

Study A 00 kg of total nitrogen was deposited in the Potomac River 

watersh

tal yield derived within each 

catchm .e., the 

n 

s 

he 

hyll a prompted the State of North Carolina to place the Neuse River Estuary on the 

1994, 1996, 1998, and 2000 303(d) List of Impaired Waters. 

To assess current conditions for the Potomac River/Potomac Estuary Case Study Are

and Neuse River/Neuse River Estuary Case Study Area, it wa

ion data available to input to SPARROW. The deposition data used for the Aquatic 

Nutrient Enrichment Case Study are based on the 2002 CMAQ model year and NADP 

monitoring data; therefore, current conditions for this case study evaluated ecosystem respo

for the year 2002. In both the Potomac River/Potomac Estuary Case Study Area and the

River/Neuse River Estuary Case Study Area, the best attempts were made to use monitoring and 

modeling data from that time period (2002). Annual averages for 2002 were used in this study. 

5.2.4.1 Potomac River and Potomac Estuary Current Conditions 

For the current condition 2002 analysis of the Potomac River/Potomac Estuary Case 

rea, an estimated 40,770,0

ed for an average deposition of 12.9 kg N/ha/yr. Figure 5.2-5 through Figure 5.2-7

reveal highly different spatial patterns in oxidized, reduced, and total nitrogen atmospheric 

deposition across the watershed. Note that the scales across the three figures use the same 

increments and colors, so that they can be compared directly. 

Application of a previously calibrated version of the SPARROW model for the 

Chesapeake Bay watershed provides estimates of the incremen

ent of the Potomac River watershed, as well as estimates of the delivered yield (i

fraction of the incremental flux that ultimately reaches the estuary) (Figure 5.2-8). (Details o

the use of the Version 3 Chesapeake Bay SPARROW model can be found in Appendix 6.) By 

looking at catchment-scale results, the spatial variability among the loading contributions acros

the watershed can be shown. Differences between the incremental and delivered yields reflect t

instream losses that occur as the load from each catchment travels downstream to the target 

estuary. 
Chapter 5 – Nutrient Enrichment 

Final Risk and Exposure Assessment 5-24 September 2009 

SPARROW modeling for 200

predicts that atmospheric 

00 kg N/yr to the estuary, or 20% of the total loading. 

These modeling estimates are consistent with previous 

modeling estimates for the system (Preston and Brakebill, 

1999). The instream total nitrogen concentration (TNs) 

resulting from this loading was approximately 3.4 mg/L. 

2 

deposition was 20% of the total 

odel the loads from the Potomac River and its watershed to the upper portions of the 

Potoma f 

e 

 the 

nd 

timated at 

7,380,0

nitrogen loading to the Potomac

River’s estuary, producing an 

TNs of 3.4 mg/L. 

For this application and analysis of the 2002 current condition case, SPARROW was

used to m

c Estuary. The most downstream modeled catchment in the analysis lies downstream o

several major point sources between Washington, DC, and the mixing zone of the estuary. Thes

point sources were major contributors of nutrients to the estuary, and by including them in the 

analysis, a more accurate load from the Potomac River watershed is defined rather than if the 

modeling stopped at the fall line of the river. Direct runoff from catchments surrounding the 

estuary and direct deposition to the estuary were not considered in this preliminary model 

application. The majority of the nitrogen loading to the estuary was expected to derive within

Potomac River watershed because of overall larger land area and applications of fertilizer a

manure. Additionally, the major point sources to the Potomac Estuary were included in the most 

downstream watersheds at the mouth of the estuary modeled in this application. 

Overall, the SPARROW model produced an estimate of total nitrogen loading to the 

Potomac Estuary of 36,660,000 kg N/yr. The atmospheric deposition load was es
Chapter 5 – Nutrient Enrichment 

Figure 5.2-5. Atmospheric deposition yields of oxidized nitrogen over the 

Potomac River and Potomac Estuary watershed.

Figure 5.2-6. Atmospheric deposition yields of reduced nitrogen over 

the Potomac River and Potomac Estuary watershed. 

Final Risk and Exposure Assessment 5-25 September 2009 
Chapter 5 – Nutrient Enrichment 

Figure 5.2-7. Atmospheric deposition yields of total nitrogen over the 

Potomac River and Potomac Estuary watershed. 

ASSETS EI Assessment 

An ASSETS EI was completed for the Potomac Estuary in a 2006 NOAA project on the 

Gulf of Maine (Bricker et al., 2006) using 2002 data to determine the scoring. That assessment 

showed that the system has a high susceptibility to pressures and a high score for nutrient inputs, 

resulting in a High OHI score. Individual scores for the primary and secondary indicators varied 

but resulted in an overall High OEC score. The score of Improve Low for the DFO is based on 

the expectations that future nutrient pressures will decrease and there will be significant 

population and development increases. 

The ASSETS EI for the 2002 

Potomac River estuary current 

condition scenario is Bad.

For the Aquatic Nutrient Enrichment Case Study, the 

ratings for the nutrient inputs and OEC were re-created and 

verified using methods consistent with the 2007 NEEA 

Update, which included separate area-weighted consideration of the tidal fresh, mixing, and 

saltwater zones within the estuary (Bricker et al., 2007). Index scores for the updated analysis 

were compiled using the scoring methods and matrices as shown in Figures 2.2-6 and 2.2-7 of 

Appendix 6. Combination of the primary and secondary scores (both High) provided an overall 

OEC score of High, which agreed with the original analysis. The OHI score (confirmed with the 

Final Risk and Exposure Assessment 5-26 September 2009 
Chapter 5 – Nutrient Enrichment 

modeled nitrogen load from the 2002 SPARROW application) and the DFO scores remain the 

same as in the original analysis. Therefore, the ASSETS EI for the 2002 current condition 

scenario is Bad. 

Figure 5.2-8. Total nitrogen yields from all sources as predicted using version 

3 of the Chesapeake Bay SPARROW application with updated 2002 

atmospheric deposition inputs. 

Final Risk and Exposure Assessment 5-27 September 2009 
Chapter 5 – Nutrient Enrichment 

5.2.4.2 Neuse River and Neuse River Estuary Current Conditions 

The current condition 2002 analysis of the Neuse River and Neuse River Estuary used 

recently released data from the USGS to calibrate a new SPARROW application for 2002 to the 

Neuse watershed. (Because of a limited number of calibration points within the Neuse watershed 

itself, the SPARROW model assessment was expanded to include the Tar-Pamlico and Cape 

Fear River basins, providing a total of 41 calibration points on which to base the SPARROW 

model.) Developing the ASSETS EI for the Neuse River Estuary proved to be a greater challenge 

than for the Potomac Estuary due to data sources being less consolidated and more varied. 

SPARROW Assessment 

Figure 5.2-9 through Figure 5.2-11 present the atmospheric deposition inputs used 

within the modeling effort. For 2002, an estimated 18,340,000 kg of total nitrogen was deposited 

in the Neuse River watershed for an average deposition of 14.0 kg N/ha/yr. The model was based 

on total nitrogen loads from deposition, but oxidized and total reactive nitrogen yields are also 

presented to highlight source information within the watershed. The Neuse River watershed is 

the location of major agricultural operations focusing on swine facilities. These operations are 

evident in the high levels of reduced nitrogen found within the south-central catchments of the 

watershed (Figure 5.2-10). 

Final Risk and Exposure Assessment 5-28 September 2009 
Chapter 5 – Nutrient Enrichment 

Figure 5.2-9. Atmospheric deposition yields of oxidized nitrogen over the 

Neuse River and Neuse River Estuary watershed.

Figure 5.2-10. Atmospheric deposition yields of reduced nitrogen over the 

Neuse River and Neuse River Estuary watershed.

Final Risk and Exposure Assessment 5-29 September 2009 
Chapter 5 – Nutrient Enrichment 

Figure 5.2-11. Atmospheric deposition yields of total nitrogen over the 

Neuse River and Neuse River Estuary watershed. 

SPARROW modeling for 2002 

predicts that atmospheric 

deposition was 26% of the total 

nitrogen loading to the Neuse 

River’s estuary, producing a TNs

of 1.1 mg/L. 

As with the Potomac River and Potomac Estuary watershed results, the Neuse River and 

Neuse River Estuary SPARROW application modeled watershed loads to the upper edges of the 

estuary. Both the incremental and delivered yields are presented in Figure 5.2-12. The total 

nitrogen load estimated to enter the estuary from the Neuse River is 4,380,000 kg N/yr, equating 

to a TNs of 1.11 mg/L. Atmospheric deposition was 

estimated to contribute 1,150,000 kg N/yr, or 26% of the 

total load. These estimates fall in line with instream 

monitoring data and previous loadings from the Neuse River 

estimated at 9.61 million pounds or 4,359,000 kg N/yr 

(Spruill et al., 2004). 

Final Risk and Exposure Assessment 5-30 September 2009 
Chapter 5 – Nutrient Enrichment 

Figure 5.2-12. Total nitrogen yields from all sources predicted by a SPARROW 

application for the Neuse, Tar-Pamlico, and Cape Fear watersheds with 2002 

data inputs.

ASSETS EI Assessment 

Previous work was completed by NOAA using 

the ASSETS EI on the Neuse River Estuary as part of 

the NEEA Update (Bricker et al., 2007). The exact 

Combining the OEC, OHI, and DFO 

indices results in an overall ASSETS 

EI for the Neuse River Estuary for 

2002 of Bad. 

Final Risk and Exposure Assessment 5-31 September 2009 
Chapter 5 – Nutrient Enrichment 

source of the load estimate and the exact timeframe of the data used to calculate the ASSETS EI 

are still unknown at this time, although the data should fall between 2000 to 2002 (S. Bricker, 

personal communication, 2008). That analysis revealed a Highly/Moderately Influenced or High

score for influencing factors where the nitrogen load was ranked as Moderate to High, resulting 

in a Bad overall ASSETS score for the estuary. 

To develop an updated ASSETS EI specific to the 2002 baseline for this assessment, 

available data from multiple sources, including the Neuse River Estuary Modeling and 

Monitoring Project, were combined to form a 2002 OEC score. Because both the chlorophyll a

and harmful algal bloom data were available and overwhelmingly pointed to a system with both 

High primary and secondary scores, a High OEC rating is given with confidence for 2002. The 

High susceptibility ranking, combined with the total nitrogen loads estimated by the SPARROW 

assessment, rank the OHI as High as well. The DFO set during the 2007 NEEA Update remains 

unchanged, with a ranking of Worsen High due to nutrient decreases from improved 

management practices in recent years being offset by increases in human populations and factors 

related to swine production (Burkholder et al., 2006). Combining the three indexes results in an 

overall ASSETS EI for the Neuse River/Neuse River Estuary Case Study Area for 2002 of Bad. 

5.2.5 Degree of Extrapolation to Larger Assessment Areas 

Selection of the analysis method for aquatic nutrient enrichment considered applications 

beyond a small number of case studies. The chosen method, consisting of a combination of 

SPARROW modeling for nitrogen loads and an assessment of estuary conditions under the 

NOAA ASSETS EI, provides a highly scalable and widely applicable analysis method. Both 

components have been applied on a national scale—the national nutrient assessment using 

SPARROW (Smith and Alexander, 2000) and the NEEA using the ASSETS EI (Bricker et al., 

1999, 2007). Additionally, both have been used on a smaller scale. These previous analyses 

supply a large body of work—data, methods, and supporting experts—to draw from when 

conducting additional analyses or updating past applications. 

Requirements for applying this method to other systems include mandatory data inputs, 

the ability to formulate a SPARROW application on a reliable stream network, and an estuary 

likely to be subject to eutrophication. Data requirements and model formulations have been 

described and detailed throughout this report. 

Final Risk and Exposure Assessment 5-32 September 2009 
Chapter 5 – Nutrient Enrichment 

The method is not currently designed to assess eutrophication impacts on inland waters; 

however, a separate analysis was conducted of the extent inland waters exceed national nutrient 

criteria for nitrogen. Results are presented in the GIS analysis for sensitive areas of the United 

States that are identified in Appendix 6. SPARROW modeling can be applied to determine 

nitrogen loadings to an inland waterway, but the ASSETS EI would not apply, and as such, the 

indicators and overall likelihood of eutrophication could not be assessed. For these inland waters, 

an alternate methodology would be necessary to examine the effects of changing nitrogen loads 

within the waterbody. A variety of methods could possibly be applied, including empirical 

relationships or dynamic modeling. An additional case study, the Aquatic Acidification Case 

Study, examines the effects of aquatic acidification on inland waters using dynamic modeling. 

The scalability of the methods and approaches taken in these case studies will rely on the 

ability to group estuaries across the country into patterns of similar behavior either in terms of 

nitrogen sources or eutrophication effects. In 2003 and 2004, NOAA and the Kansas Geological 

Survey conducted a series of workshops to develop a type classification system for the 138 

estuarine systems assessed in the original NEEA (Bricker et al., 1999). Participants considered 

70 classification variables for grouping the estuarine systems. These variables included 51 

physical characteristics (e.g., estuary depth and volume, tidal range, salinity, nitrogen and 

phosphorus concentrations, estimates of flushing time, evaporation), 10 perturbation 

characteristics (e.g., population in watershed, estimates of nutrient loading), and nine response 

characteristics (e.g., SAV loss, presence of nuisance, toxic blooms). Ultimately, the workgroup 

selected five variables (i.e., depth, openness of estuary mouth, tidal range, mean annual air 

temperature, the log of freshwater inflow/estuarine area) deemed to be the most critical physical 

and hydrological characteristics influencing nutrient processing and the expression of eutrophic 

symptoms in a waterbody. Based on these five variables, the 138 estuarine systems were 

classified into 10 groups (Table 5.2-3; Figure 5.2-13). The two estuary systems included in this 

case study, Potomac River Estuary and Neuse River Estuary systems, were in groups one and 

nine, respectively (Bricker et al., 2007). 

Final Risk and Exposure Assessment 5-33 September 2009 
Chapter 5 – Nutrient Enrichment 

Table 5.2-3. Typology Group Categorizations

Group Number of Systems Overriding Characteristics 

Group 0 13 Low freshwater inflow:estuarine area ratio; low depth; 

low estuary mouth openness 

Group 1 35 Medium depth; medium estuary mouth openness; high 

annual air temperature 

Group 2 5 High depth; low annual air temperature 

Group 3 8 High estuary mouth openness; high depth 

Group 4 18 Low estuary mouth openness; high freshwater 

inflow:estuarine area ratio; low annual air temperature 

Group 5 3 High estuary mouth openness; high depth 

Group 6 2 High depth; high estuary mouth openness 

Group 7 16 High tidal range; medium estuary mouth openness; low 

annual air temperature 

Group 8 17 High freshwater inflow:estuarine area ratio; low depth 

Group 9 21 Low depth; medium estuary mouth openness; high 

annual air temperature 

Figure 5.2-13. Preliminary classifications of estuary typology across the nation 

(modified from Bricker et al., 2007).

Final Risk and Exposure Assessment 5-34 September 2009 
Chapter 5 – Nutrient Enrichment 

Given that the response curve of the OEC to total nitrogen (TN) is expected to change 

shapes with different values of susceptibility, the typology classes thus defined in Table 5.2-3

provide an opportunity to assess the validity of this expectation. The first step in assessing this 

statement would be to examine the nutrient loadings in other estuaries that fall within groups 1 or 

9, the groups corresponding to the two case studies. Once the shape and behavior of the response 

curve for the estuary grouping is confirmed, work can begin to scale the results between estuaries 

of that group. The ASSETS EI rating of an estuary may also be considered within this analysis. 

Scaling of results will also need to account for the response of the watershed to 

atmospheric nitrogen deposition inputs. If SPARROW continues to be used, either through the 

in-development Web-enabled national SPARROW application or through regional or sitespecific applications, the shape of the response curve will be determined by the model and its 

parameters. If a different approach is taken to developing total nitrogen loadings, then the 

systems will need to be grouped according to the shape and behavior of the response curve. 

Additional consideration should be given to the magnitude of the percentage contributions of the 

atmospheric deposition to the total nitrogen load to the watershed and the resulting total nitrogen 

load to the estuary. 

5.2.6 Current Conditions for Other/Additional Estuaries 

For 48 systems for which an ASSETS EI rating was developed in the 2007 NEEA 

Update, only one system was rated as High (i.e., Connecticut River), while five were rated as 

Good (i.e., Biscayne Bay, Pensacola Bay, Blue Hill Bay, Sabine Lake, Boston Harbor). Eighteen 

were rated as Moderate, and 24 systems were rated as Poor or Bad (Figure 5.2-14). Comparing 

the spatial distribution of these results to the preliminary typology groups described in the 

previous section, the majority of estuaries in Group one, the group to which the Potomac Estuary 

belongs, received scores of Bad. These conditions provide an opportunity to extrapolate between 

the analysis methods and results determined for the Potomac Estuary and the other estuaries 

matching in typology and current condition. For Group nine, to which the Neuse River Estuary 

belongs, a greater range in ASSETS EI scores is found. Extrapolation of results within this group 

must be examined in greater detail. 

Final Risk and Exposure Assessment 5-35 September 2009 
Chapter 5 – Nutrient Enrichment 

Bad: Moderate-high to high pressure, moderate-high to high eutrophic condition, and any expected future change in eutrophic condition.

Poor: Moderate-low to high pressure, moderate to moderate-high eutrophic condition, and any expected future change in condition.

Moderate: Any pressure, moderate-low to moderate-high eutrophic condition, and any expected future change in eutrophic condition.

Good: Low to moderate pressure, low to moderate-low eutrophic condition, and any expected future change in condition.

High: Low pressure, low eutrophic condition, and any expected improvement or no future change in eutrophic condition.

Unknown: Insufficient data for analysis.

Figure 5.2-14. ASSETS EI scores for 48 systems examined in the 2007 NEEA 

Update (Bricker et al., 2007). 

5.2.7 Ecological Effect Function for Aquatic Nutrient Enrichment 

Alternative effects levels were assessed for both the Potomac River and Neuse River 

watersheds separately by applying percentage decreases to the oxidized nitrogen loads in the 

estimated atmospheric deposition. Model estimates then relied on the SPARROW models used 

(for the Potomac River) or developed (for the Neuse River) for the 2002 current condition 

analysis to determine how the changing atmospheric inputs (i.e., total nitrogen load evaluated 

with changes in oxidized nitrogen deposition, NOx) affect the overall total nitrogen load to the 

estuary of interest. These results were used to create the response curve relating instream total 

nitrogen concentrations to atmospheric deposition loads as first described in Appendix 6, Section 

2.2.3. The second response curve described in Section 2.2.3 was defined for the alternative 

effects level analysis using historical data compilations of OEC scores and instream total 

nitrogen concentrations while holding the susceptibility portion of the OHI (at its 2002 current 

Final Risk and Exposure Assessment 5-36 September 2009 
Chapter 5 – Nutrient Enrichment 

condition level— in both cases a ranking of High) and the DFO constant (at a ranking of No 

Change [3]). 

Upon creation of the two response curves, the back calculation coded program described 

in Appendix 6, Section 2.2.3 (referred to as BackCalculation through the remainder of this 

document) was applied to the curves with the intent of defining the atmospheric loads that are 

needed to improve the ASSETS EI from a score of Bad (1) to Poor (2), Moderate (3), Good (4),

or High (5). These improvements represent improvements by 1, 2, 3, and 4 categories. 

5.2.7.1 Potomac River and Potomac Estuary 

Beginning with the data and model used for the current condition analysis, the 

atmospheric deposition inputs derived from national coverage of CMAQ and NADP data were 

altered to create various alternative effects levels by decreasing the oxidized nitrogen loads by 

rates of 5%, 10%, 20%, 30%, and 40% from their original 2002 levels. A zero percentage 

decrease corresponds to the 2002 current condition analysis. The remaining inputs to the 

SPARROW model remained the same, and the model was rerun for each of these alternative 

effects level scenarios. The total nitrogen load to the estuary calculated from the model was then 

converted to TNs using the annual average flow of the Potomac River. Plotting these 

concentrations against the new total nitrogen atmospheric deposition loading (TNatm) 

incorporating the oxidized nitrogen decrease leads to the development of the first response curve 

and relationship (Figure 5.2-15) for the Potomac River and Potomac Estuary watershed. 

For the second response curve, historical modeling data was used to determine total 

nitrogen loads to the Potomac Estuary, which are then combined with annual average flow 

values to calculate a final TNs. These instream concentrations were then combined with the OEC 

index scores, which were also determined from historical data, to create the data points needed to 

create the 4-parameter logistic response curve in the BackCalculation program. Figure 5.2-16

presents an example of the logistic curve fit to the Potomac River and Potomac Estuary data 

during an uncertainty analysis of a target ASSETS EI = 2.

Final Risk and Exposure Assessment 5-37 September 2009 
Chapter 5 – Nutrient Enrichment 

y = 1.69E-08x + 2.72

R2

 = 1

3.00

3.05

3.10

3.15

3.20

3.25

3.30

3.35

3.40

3.45

3.50

0

5,000,000

10,000,00015,000,00020,000,00025,000,00030,000,00035,000,00040,000,00045,000,000

Total Nitrogen Atmospheric Deposition Load (kg/yr)

Instream Total Nitrogen Concentration 

(mg/L)

Figure 5.2-15. Response curve relating instream total nitrogen 

concentration (TNs) to total nitrogen atmospheric deposition load (TNatm) 

for the Potomac River watershed. 

0

1

2

3

4

5

0.0 1.0 2.0 3.0 4.0 5.0 6.0

TN (mg/L)

OEC Score

Calibration Points

Fit Logistic Curve

Figure 5.2-16. Example of fitted OEC curve for target 

ASSETS EI=2 for the Potomac Estuary.

Table 5.2-4 presents the summary statistics of 500 iterations for each target ASSETS EI 

scenario for the Potomac Estuary. In these Monte Carlo type simulations, the TNatm to the 

watershed is evaluated as a function of the TNs for each step in improvement of the ASSETS EI. 

The target ASSETS EI scenario where EI = 2 

(improving from an ASSETS EI score of Bad to Poor) is 

the most interesting scenario and illustrates the power of 

There is a slim chance that the 

Potomac River Estuary can move 

from an EI score of Bad to a score 

of Poor by reducing deposition of 

total nitrogen by 78%. 

Final Risk and Exposure Assessment 5-38 September 2009 
Chapter 5 – Nutrient Enrichment 

the uncertainty analysis. The mean and 

median TNatm values are negative, 

meaning again that not only must all 

total nitrogen atmospheric deposition 

load (including all NOx) be removed, 

but additional nitrogen from other 

sources must be removed as well. 

However, there is a slim chance that 

scenario ASSETS EI = 2 can be 

attained only from TNatm deposition 

load decrease, as indicated by the 

positive 95th percentile TNatm value of 

9.02 × 106 (representing a 78% decrease). 

Table 5.2-4. Summary Statistics for Target 

Eutrophication Index Scenarios — Potomac Estuary 

(Current condition Eutrophication Index score of Bad)

Statistic TNatm (kg N/yr) % TNatm

Decrease 

ASSETS EI = 2 (Poor) 

Mean -1.78 × 106 104 

Median -1.46 × 106 104 

5th Percentile -3.67 × 106 109 

95th Percentile 9.02 × 106 78 

ASSETS EI = 3 (Moderate) 

No feasible solutions found 

ASSETS EI=4 (Good) and ASSETS EI = 5 (High) 

All TNatm = -1.61 × 108, i.e., TNs = 0 mg/L 

Target scenario ASSETS EI = 3 (Moderate) is a unique case because all solutions were 

infeasible. With a TNs value of 0 mg/L, the other (fixed) components of the ASSETS scoring 

methodology (i.e., DFO and Susceptibility Score) preclude satisfying any of the 95 combinations 

of DFO, OEC, and OHI that comprise the EI=3 combinations in the ASSETS lookup table. 

Target scenario ASSETS EI = 4 and 5 had identical results. All 500 iterations returned a 

TNs

*

i = 0, and a corresponding TNatm*i negative load equal to TNatm*i = (0 – 2.72)/1.69 × 10-8 

= -

1.61 × 10-8 kg/yr. Clearly, target EIs equaling 4 and 5 are very much unattainable when 

decreasing the total atmospheric nitrogen deposition load is the only policy option. To reach the 

target ASSETS EI scenario, total nitrogen atmospheric deposition (TNatm) must be removed plus 

an additional amount (represented by the negative resultant load corresponding to TNs

*

i = 0) that 

is approximately equal to one order of magnitude greater than the original atmospheric 

deposition load. These amounts could be compared to the other nitrogen sources in the watershed 

(e.g., fertilizer and manure application or point sources) that were used as inputs to the 

SPARROW model to determine the relative nature of the required removal with other sources in 

the watershed. However, consideration must be given that this load is a reflection of the 

characteristics of the source in the SPARROW model (e.g., spatial distribution, magnitude of 

loads, sources/sinks), and a decrease required in atmospheric load is not equal to a decrease in 

another source. Therefore, a decrease of an order of magnitude greater than the original 

Final Risk and Exposure Assessment 5-39 September 2009 
Chapter 5 – Nutrient Enrichment 

atmospheric deposition load may or may not be possible, depending on these different source 

contributors. Relative proportions can be examined by comparing the source characteristics and 

model parameters. 

The SPARROW response curve can also be used to examine the role of atmospheric 

nitrogen deposition in achieving specified decreases in total nitrogen estuarine load. For 

example, the SPARROW modeling results predict that the 41 × 106 kg N/yr deposited 

(atmospheric deposition input) over the Potomac River watershed in 2002 results in a loading of 

7,380,000 kg N/yr, or 20% of the annual total nitrogen load, to the Potomac Estuary. If a 30% 

decrease in annual total nitrogen load to the estuary (i.e., a decrease of 11 × 106

 kg N/yr) were 

desired, a decrease of 61 × 106 kg N/yr in nitrogen inputs to the watershed would be required 

according to the SPARROW response curve based on atmospheric deposition. This represents a 

100% decrease in the total nitrogen (including total reactive nitrogen) atmospheric deposition 

inputs (41 × 106

 kg N/yr) plus an additional 20 × 106 kg N/yr removal of nitrogen from other 

sources in the Potomac River watershed (i.e., point and nonpoint sources). Note that this value of 

20 × 106 kg N/yr is an approximate value when applied to the other sources because they differ 

in characteristics (e.g., spatial distribution and magnitude) from atmospheric deposition that was 

used to estimate the loading. 

5.2.7.2 Neuse River and Neuse River Estuary 

The same methods for creating alternative effects levels were applied to the data from the 

Neuse River/Neuse River Estuary Case Study Area as to data from the Potomac River/Potomac 

Estuary Case Study Area. The oxidized nitrogen atmospheric deposition loads were decreased by 

rates of 5%, 10%, 20%, 30%, and 40% from their original 2002 levels. A zero percent decrease 

corresponds to the 2002 current condition analysis. With the remaining inputs to the SPARROW 

model kept the same, the SAS-developed model was rerun for each of these alternative effects 

level scenarios. The total nitrogen load to the estuary calculated from the model was then 

converted to a TNs using the annual average flow of the Neuse River. Plotting these 

concentrations against the new total nitrogen atmospheric deposition load and incorporating the 

oxidized nitrogen decreases leads to the development of the first response curve and relationship 

(Figure 5.2-17). Note that the instream concentration range is discussed at the end of this 

section. 

Final Risk and Exposure Assessment 5-40 September 2009 
Chapter 5 – Nutrient Enrichment 

y = 2.0E-09x + 1.07

R2

 = 1

1.100

1.105

1.110

1.115

-

2,000,0004,000,0006,000,0008,000,000

10,000,00012,000,00014,000,00016,000,00018,000,00020,000,000

Total Nitrogen Atmospheric Deposition Load (kg/yr)

Instream Total Nitrogen Concentration 

(mg/L)

Figure 5.2-17. Response curve relating instream total nitrogen 

concentration to total nitrogen atmospheric deposition load for the Neuse 

River/Neuse River Estuary Case Study Area. 

Historical monitoring data were used to determine instream total nitrogen concentrations 

at the downstream end of the Neuse River where the SPARROW model was used to determine 

current condition and alternative effects levels nitrogen loads. The monitoring data were derived 

from data downloaded from EPA’s STORET Web site for monitoring location J8290000 from 

the North Carolina Division of Water Quality. These TNs were then combined with the OEC 

index scores, which were also determined from historical data, to create the data points needed to 

create the logistic response curve in the BackCalculation program. Data from as many years as 

possible were gathered for both the TNs and OEC index scores. However, due to the limited 

amount of complete data from the various sources identified under the current condition analysis, 

only three corresponding years of data were found. The theoretical ecological endpoints of the 

curve were also used to create the 4-parameter logistic curve representing the second response 

curve for the analysis (Figure 5.2-18). 

Final Risk and Exposure Assessment 5-41 September 2009 
Chapter 5 – Nutrient Enrichment 

Final Risk and Exposure Assessment 5-42 September 2009 

0

1

2

3

4

5

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5

TN (mg/L)

OEC Score

Calibration Points

Fit Logistic Curve

Figure 5.2-18. Example of fitted response curve for target 

ASSETS EI=2 for the Neuse River Estuary.

Each of the four ASSETS EI scores representing state improvements (Poor-2, 

Moderate-3, Good-4, High-5) was treated as a “target” ASSETS EI score, and 500 Monte Carlo 

simulations were run under each target ASSETS EI scenario to relate instream total nitrogen 

concentrations (TNs) to total nitrogen atmospheric deposition (TNatm). 

The summary statistics of the 500 iterations for each target ASSETS EI scenario are 

presented in Table 5.2-5. 

For target scenario ASSETS EI = 2 (improving from an ASSETS EI score of Bad to 

Poor), all decreases exceed 100%, m

removed to meet ASSETS EI =

but considerably more nitrogen 

from other sources as well. G

these results, the Neuse River 

Estuary is currently somewhere 

between these two ASSETS EI 

values (Bad and Poor) as was the 

Potomac Estuary. There is some 

evidence that it is slightly more 

eutrophic than the Potomac Estua

because there was at least a slim 

eaning that not only must all TNatm deposition load be 

 2, 

iven 

ry, 

Table 5.2-5. Summary Statistics for Target 

Eutrophication Index Scenarios — Neuse River Estuary

(Current condition Eutrophication Index score of Bad) 

Statistic TNatm (kg N/yr) % TNatm

Decrease 

ASSETS EI = 2 (Poor) 

Mean -1.43 × 108 880 

Median -1.43 × 108 880 

5th Percentile -1.47 × 108 901 

95th Percentile -1.01 × 108 653 

ASSETS EI = 3 (Moderate) 

No feasible solutions found 

ASSETS EI=4 (Good) and ASSETS EI = 5 (High) 

All TNatm = -5.35 × 108, i.e. TNs = 0 mg/L 
Chapter 5 – Nutrient Enrichment 

chance for the Potomac Estuary (at the 95th percentile) that a decrease in TNatm (of <100%) 

would achieve ASSETS EI = 2. 

Target scenario ASSETS EI = 3 (Moderate) is again a unique case because all solutions 

were infeasible as described above for the Potomac River watershed and the Potomac Estuary. 

(See Appendix 6 for further explanation.) 

To change the Neuse River Estuary’s EI 

score from Bad to Poor, not only must 100% 

of the total atmospheric nitrogen deposition 

be eliminated, but considerably more 

nitrogen from other sources as well must be 

decreased. 

Target scenarios ASSETS EI = 4 (Good) and 5 (High) had identical results. All 500 

iterations returned a TNs = 0, and a corresponding TNatm negative load equal to TNatm = (0 – 

1.07)/2.0 × 10-9= -5.35 × 108

 kg/yr. Clearly, target scenarios of ASSETS EI equal 4 (Good) and 5 

(High) are unattainable when decreasing the TNatm (including all NOx) is the only option. Again, 

the decrease required includes all of the total reactive nitrogen atmospheric deposition source 

plus a load an order of magnitude greater than the original atmospheric deposition load (108

kg/yr), which could be compared to the other nitrogen sources used as inputs to the SPARROW 

model giving consideration to the characteristics 

of each of these sources. Again, this additional 

magnitude of decrease may or may not be 

feasible based on the relative contributions from 

the other sources. 

The SPARROW response curve can be used to examine the role of atmospheric nitrogen 

deposition in achieving desired decreased loads to the Neuse River Estuary. In the Neuse River 

watershed, modeling results indicate that 18 × 106

 kg N/yr was deposited in 2002. SPARROW 

modeling predicts that this deposition input results in a loading of 1.2 × 106

 kg N/yr (26% of the 

annual total nitrogen load) to the Neuse River Estuary. Unlike the Potomac River and Potomac 

Estuary, little change is seen in the total nitrogen loading to the Neuse River Estuary, with large 

decreases in the nitrogen deposition. If all atmospheric nitrogen deposition inputs were 

eliminated (100% decrease), the total annual nitrogen load to the Neuse River Estuary would 

only decrease by 4%. This small effect is because the total nitrogen loadings to the Neuse River 

Estuary are so dependent on the other sources within the SPARROW model. That is, the 

SPARROW response curve cannot be used to predict the relative magnitudes of loads needed to 

produce decreases greater than this 4%. This lack of predictive power of the response curve 

based on atmospheric deposition is due to the differences in characteristics between the sources 

within the watershed, where fertilizer, in particular, has a strong signature (i.e., indicating the 

Final Risk and Exposure Assessment 5-43 September 2009 
Chapter 5 – Nutrient Enrichment 

large influence of agriculture within the watershed). This result shows that the SPARROW 

response curves of total nitrogen load to other sources would be quite different. Figure 5.2-19 

illustrates the theoretical response curves that may result when the SPARROW modeled loads 

are plotted against the other total nitrogen source inputs. The green curve, or least influential 

source, displays the behavior of the atmospheric deposition for the Neuse River Estuary. The red 

curve, or highly influential source, likely corresponds to how agricultural sources within the 

watershed behave. These response curves will depend on the source magnitudes, spatial 

distributions, and other characteristics. Instream TN Concentration (mg/L) or 

Source Input Load (kg N/ yr) 

TN Load to Estuary (kg N/yr)

Current conditions concentration or loading 

Least influential source where a large

change in input loading produces a 

small change in load to the estuary 

Moderately influential source where a 

large change in input loading produces 

a large change in load to the estuary 

Highly influential source where a small

change in input loading produces a 

large change in load to the estuary 

Figure 5.2-19. Theoretical SPARROW response curves demonstrating relative 

influence of sources on nitrogen loads to an estuary.

5.2.8 Uncertainty and Variability 

The use of multiple datasets, predictive modeling, and a multi-indicator assessment tool, 

such as ASSETS, requires consideration of the impact of data variability and the uncertainties in 

case study results. 

“Uncertainty is a measure of the knowledge of the magnitude of a parameter. Uncertainty 

can be reduced by research, i.e., the parameter value can be refined. Uncertainty is quantified as 

a distribution. For example, the volume of a lake may be estimated from its surface area and an 

average depth. This estimate can be refined by measurement. Variance is a measure of the 

heterogeneity of a landscape parameter or the inherent variability in a chemical property. 

Variance cannot be reduced by further research. It is quantified as a distribution. For example, 

Final Risk and Exposure Assessment 5-44 September 2009 
Chapter 5 – Nutrient Enrichment 

the organic carbon content of the soil in a region may vary, even over short distances. The soil is 

not homogenous and thus the organic carbon content can be described with a distribution of 

values.” (Webster and MacKay, 2003) 

Uncertainty with this method of assessment for aquatic nutrient enrichment may include 

the following: 

 Data inputs to SPARROW. For this study, the data used were developed under separate 

studies and published by the USGS. Because the data were independently verified before 

publication by the USGS, only quality checks were performed on the data, rather than full 

validation exercises. 

 Modeling uncertainty in SPARROW estimates. The Version 3 Chesapeake Bay 

SPARROW application met evaluation criteria based on degrees of freedom, model error, 

and R squared values. The calibration of the Neuse watershed SPARROW model using 

SAS examined the standard deviation, t-statistics, p-values, and Variance Inflation 

Factors (VIF) for each estimated parameter. The model derived for the Neuse River 

watershed did produce some model parameters (e.g., manure production, urban area, 

decay terms) that did not reach desired statistical significance levels. 

 Sensitivity of SPARROW formulation due to atmospheric inputs in the Aquatic 

Nutrient Enrichment Case Study. While it is certain that the parameter estimated to 

apply to the atmospheric deposition source will change, what is uncertain at this point is 

the extent to which the other model parameters and the overall nitrogen load estimates 

will be affected by using the CMAQ/NADP estimates in the model calibrated against the 

wet nitrate deposition values. 

 Calibration data for SPARROW estimates. Monitoring data were used to calibrate the 

SPARROW model. By relying on data from federally recognized data systems, the aim is 

to use data that has undergone quality assurance/quality control procedures. Additionally, 

collaboration has been completed with the researchers who have conducted the previous 

SPARROW applications in each case study area to provide a rigorous check on the data 

used.

 Data inputs to the ASSETS EI. Because of the numerous data requirements and sources 

required to conduct a full ASSETS EI analysis, there is a large range of uncertainty that 

can enter into the calculations. Best attempts were made to apply standardized evaluation 

Final Risk and Exposure Assessment 5-45 September 2009 
Chapter 5 – Nutrient Enrichment 

methods in order to minimize any uncertainties due to subjectivity or processing 

differences. 

 Heuristic estimates of future outlook. The estimation of the future outlook score in the 

ASSETS EI currently relies on heuristic estimates from systems experts. 

 Steady-state estimates/mean annual estimates. Both SPARROW and the ASSETS EI 

currently provide only longer-term estimates of the system conditions. 

 Use of a Screening Method. The methods used in this study are only of the screening 

level. The screening method provides a response curve that can be used in the evaluation 

of ecosystem services. Additionally, many of the complex concepts linking the indicators 

of eutrophication to the effects of eutrophication are not highly developed or understood 

at this time (Howarth and Marino, 2006). 

 Use of a partially empirical framework. Because SPARROW is, at its core, an 

empirical relationship, any model obtained using SPARROW is a function of the data 

used in the calibration. Therefore, the predictions remain valid as long as there is no great 

change in the conditions (in this case, the nitrogen loadings within each subbasin) 

underlying the model. This aspect of the model introduces uncertainty into the alternative 

effects results because they are calculated using a model calibrated under current 

conditions. 

Uncertainties in the Back Calculation Methods include the following: 

 Missing ASSETS EI rankings per combinations of index scores. The combinations of 

OHI, OEC, and DFO scores provided by Bricker et al. (2003) leave out 30 of the possible 

125 combinations that represent overall ASSETS scores. 

 Better rationale for TN minimum and maximum uncertainty range. The assigned 

uncertainty ranges were based on best professional judgment, but more research is 

needed. The results presented herein for the Potomac and Neuse River estuaries should be 

interpreted as illustrative of the methodology, not strictly valid. 

 Methodology to incorporate uncertainty in the SPARROW model. Estimates of TNs

at the head of the estuary, predicted by SPARROW and driven by the TNatm (i.e., total 

nitrogen deposition evaluated on decreases in NOx) over the watershed and other nitrogen 

sources, are uncertain. That uncertainty was not considered in these two case studies; 

Final Risk and Exposure Assessment 5-46 September 2009 
Chapter 5 – Nutrient Enrichment 

therefore, the probability distributions of TNatm*

i presented are artificially “tight” (i.e., the 

true distributions would exhibit more variability). 

 More convergence testing to determine appropriate numbers of samples. Some 

modest convergence testing was completed to determine how many samples of the 

OEC(TN) function need to be used in order for the statistics of interest for the resulting 

NOxi* distributions to be reasonably stable. More convergence testing is needed. 

 Crossing of a categorical ranking system with a continuous nitrogen concentration 

scale. Several assumptions and considerations had to be made in order to create and 

evaluate the logistic response curve because the OEC index score is a categorical ranking 

of 1 through 5, whereas TNs is a continuous variable. The functions evaluated in 

BackCalculation treat the OEC index score as a continuous function. Until higher-level 

models are developed to relate the nitrogen concentrations in the system to eutrophication 

effects, these assumptions are necessary. Future applications with additional data should 

be used to test and validate these assumptions and results. 

5.3 TERRESTRIAL NUTRIENT ENRICHMENT 

Terrestrial nutrient enrichment is described in the ISA (U.S. EPA, 2008, Section 3.3) for 

many different ecosystems. In particular, additional nitrogen may affect the plants in these 

sensitive ecosystems. Nitrogen, however, is known to limit the growth of trees in some forests, 

especially commercial forests, and growth may be enhanced initially in these systems in response 

to nitrogen additions (U.S. EPA, 2008, Section 4.3.1). In noncommercial ecosystems reviewed in 

this analysis, changes to the individual plants, as well as changes to populations and communities 

of plants, have been documented. Over the last half century, landscapes in the United States have 

been exposed to atmospherically deposited nitrogen from anthropogenic activities. Some of the 

highest nitrogen deposition has occurred in Southern California, where researchers have 

documented measurable ecological changes related to atmospheric deposition. Evidence from the 

two ecosystems discussed in this case study—CSS and MCF communities in the Sierra Nevada 

Range and San Bernardino Mountains of California—supports the finding that nitrogen alters 

these habitats. Changes in nitrogen loading may also affect the ecological services provided by 

the CSS and MCF ecosystems, including regulation (e.g., water, habitat), cultural and aesthetic 

value (e.g., recreation, natural landscape, sense of place), and provisioning (e.g., timber) (MEA, 

Final Risk and Exposure Assessment 5-47 September 2009 
Chapter 5 – Nutrient Enrichment 

2005). The Terrestrial Nutrient Enrichment Case Study also evaluated research conducted on 

these complex ecosystems to understand the relationships among the effects of nitrogen loads, 

fire frequency and intensity, and invasive plants. 

Section 3.3 of the ISA (U.S. EPA, 2008) describes the ecosystems and species of 

concern, identifies trends in the ecosystems and the effects of these trends, and discusses 

research efforts that investigated the variables and driving forces that may affect the 

communities. The CMAQ 2002 modeling results and the NADP monitoring data for 2002 were 

used to gain an understanding of how atmospheric deposition of nitrogen is spatially distributed. 

GIS data on the spatial extent of the habitat and associated habitat changes, the location of fire 

threat, and the location of sensitive species were used to compare these patterns to the 

CMAQ/NADP data. In sum, spatial information and observed, experimental effects were used to 

help identify the trends in these ecosystems and to describe the past and current spatial extent of 

the ecosystems. 

Current analysis of the effects of terrestrial nutrient enrichment from atmospheric 

nitrogen deposition in both CSS and MCF ecosystems seeks to improve scientific understanding 

of the interactions among nitrogen deposition, fire events, and community dynamics. The 

available scientific information is sufficient to identify ecological benchmarks that are affected 

by nitrogen deposition. Ecological benchmarks have been identified for CSS and MCF. 

5.3.1 Ecological Indicators, Ecological Responses, and Ecosystem Services 

5.3.1.1 Indicators 

Ecosystems may respond to the addition of nitrogen in a number of ways. There may be 

gains in productivity and growth initially. Increasing levels of nitrogen; however, may lead to 

changes in community structure and function, with changes in species composition or changes in 

the abundance and distribution of organisms. If changes include loss of threatened, endangered 

or rare species, or rare communities or a diminished productivity or increased fire threat, then 

such changes would be cause for concern. Indicators of possible changes can be identified that 

would assist in determining an acceptable ambient air concentration of nitrogen oxides. 

Terrestrial nutrient enrichment research has measured ecosystems’ exposure to deposition of 

various atmospheric nitrogen species, including nitrogen oxides, reduced nitrogen, and total 

nitrogen. The ISA (U.S. EPA, 2008, Section 3.3) documents current understanding of the effects 

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Chapter 5 – Nutrient Enrichment 

of nitrogen nutrient enrichment on terrestrial ecosystems. The ISA concludes that there is 

sufficient information to infer a causal relationship between atmospheric nitrogen deposition and 

biogeochemical cycling and fluxes of nitrogen in terrestrial systems. The ISA further concludes 

that there is a causal relationship between atmospheric nitrogen deposition and changes in 

species richness, species composition, and biodiversity in terrestrial systems. These conclusions 

are based on an extensive literature review that is summarized in Table 4-4 of the ISA. The 

science review includes both observational and experimental (nitrogen addition) research. Alpine 

ecosystems, grasslands (including arid and semiarid ecosystems), forests, and deserts were 

included. This extensive documentation was used to assist in selecting the case study sites to 

identify and compare ecological benchmarks from different ecosystems (see Section 5.3.3 for 

more detail on case study selection). 

 CSS is subject to several pressures, such as land conversion, grazing, fire, and pollution, 

all of which have been observed to induce declines in other ecosystems (Allen et al., 1998). 

Research has shown that both fire and increased nitrogen can enhance the growth of nonnative 

grasses in established CSS communities (Keeley et al., 2005; Wood et al., 2006). It is 

hypothesized that many CSS stands are no longer limited by nitrogen and have instead become 

nitrogen-saturated because of atmospheric nitrogen deposition (Allen et al., 1998; Westman, 

1981). Nitrogen availability may favor the germination and growth of nonnative grasses, which 

can create a dense network of shallow roots that slow the diffusion of water through soil, 

decrease the percolation depth of precipitation, and decrease the water storage capability of the 

soil and underlying bedrock (Wood et al., 2006). CSS has been declining in land area and in 

shrub density for the past 60 years, and in many places it is being replaced by nonnative annual 

grasses (Allen et al., 1998; Padgett and Allen, 1999). Replacement by nonnative grasses results 

in less habitat for threatened and endangered species and also appears to increase fire 

vulnerability. Atmospheric nitrogen deposition has been suggested as a possible cause or factor 

in this ecosystem alteration (U.S. EPA, 2008, Section 3.3). Changes in community metrics may, 

therefore, be useful indicators of atmospheric nitrogen deposition for CSS. 

The ISA discusses the extensive land areas in the western United States that receive low 

levels of atmospheric nitrogen deposition and that are interspaced with areas of relatively higher 

atmospheric deposition downwind of large metropolitan centers and agricultural areas. Fenn et 

al. (2008) determined that empirical critical loads (i.e., measured levels of nitrogen at a specific 

Final Risk and Exposure Assessment 5-49 September 2009 
Chapter 5 – Nutrient Enrichment 

location where biological impacts occur) for atmospheric nitrogen deposition in MCF based on 

changes in leached nitrate in receiving waters, decreased fine-root biomass in Ponderosa pine 

(Pinus ponderosa) and epiphytic lichen communities. Lichens are good early indicators of 

atmospheric nitrogen deposition effects on other MCF species because lichens rely entirely on 

atmospheric nitrogen and cannot regulate uptake (Figure 5.3-1). 

Figure 5.3-1. Importance of lichens as an 

indicator of ecosystem health (Jovan, 2008).

From the lichen data, Fenn et 

al. (2008) predicted that a critical load 

of 3.1 kg N/ha/yr would be protective 

for all components of the forest 

ecosystem. The study further found 

that an atmospheric nitrogen 

deposition of 17 kg N/ha/yr was 

associated with NO3

- leaching and an 

approximately 25% decrease in fineroot biomass. 

5.3.1.2 Ecological Responses: Benchmark Values Selected for This Case Study 

The data limitations on atmospheric nitrogen deposition described above, along with 

current data to describe the full extent and distribution of nitrogen sensitive U.S. ecosystems, 

presented a barrier to designing a case study that uses quantitative monitoring and modeling 

tools. Instead, this case study used published research results to identify meaningful ecological 

benchmarks associated with different levels of atmospheric nitrogen deposition. 

The ecological benchmarks that were identified for the CSS and the MCF are included in 

the suite of benchmarks identified in the ISA (U.S. EPA, 2008, Section 3.3). There are sufficient 

data to confidently relate the ecological effect to a loading of atmospheric nitrogen. For the CSS 

community, the following ecological benchmarks were identified: 

 3.3 kg N/ha/yr – the amount of nitrogen uptake by a vigorous stand of CSS; above this 

level, nitrogen may no longer be limiting 

 10 kg N/ha/yr – mycorrhizal community changes 

For the MCF community, the following ecological benchmarks were identified: 

 3.1 kg N/ha/yr – shift from sensitive to tolerant lichen species 

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Chapter 5 – Nutrient Enrichment 

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

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

 17 kg N/ha/yr – leaching of nitrate into streams. 

These benchmarks, as well as those from other systems, are presented in Figure 5.3-2. 

Figure 5.3-2. Benchmarks of atmospheric nitrogen deposition for several ecosystem 

indicators with the inclusion of the diatom changes in the Rocky Mountain lakes.

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Chapter 5 – Nutrient Enrichment 

5.3.1.3 Ecosystem Services 

The ecosystem service impacts of terrestrial nutrient enrichment include primarily 

cultural and regulating services. This section provides a qualitative discussion of the services and 

benefits offered by these ecosystems. In CSS, concerns focus on a decline in CSS and an 

increase in nonnative grasses and other species, impacts on the viability of threatened and 

endangered species associated with CSS, and an increase in fire frequency. Changes in MCF 

include changes in habitat suitability and increased tree mortality, increased fire intensity, and a 

change in the forest’s nutrient cycling that may affect surface water quality through nitrate 

leaching (U.S. EPA, 2008). 

Both CSS and MCF are located in areas of California valuable for housing, recreation, 

and development. CSS runs along the coast through densely populated areas of California. MCF 

covers less densely populated areas that are valuable for recreation. (Appendix 8, Figure 5.1-1) 

The proximity of CSS and MCF to population centers and recreational areas and the potential 

value of these landscape types in providing regulating ecosystem services suggest that the value 

of preserving CSS and MCF to California could be quite high. The value that California residents 

and the U.S. population as a whole place on CSS and MCF habitats is reflected in the various 

federal, state, and local government measures that have been put in place to protect these 

habitats. Threatened and endangered species are protected by the Endangered Species Act. The 

State of California passed the Natural Communities Conservation Planning Program in 1991, and 

CSS was the first habitat identified for protection under the program (see 

http://www.dfg.ca.gov/habcon/nccp/). Private organizations, such as The Nature Conservancy, 

the Audubon Society, and local land trusts also protect and restore CSS and MCF habitats. 

According to the 2005 National Land Trust Census Report (Land Trust Alliance, 2006), 

California has the most land trusts of any state, with a total of 1,732,471 acres either owned, 

under conservation easement, or conserved by other means. 

Cultural 

The primary cultural ecosystem services associated with CSS and MCF are recreation, 

aesthetic, and nonuse values. The possible ecosystem service benefits from decreasing nitrogen 

enrichment in CSS and MCF and a general overview of the types and relative magnitude of the 

benefits are discussed below. 

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Chapter 5 – Nutrient Enrichment 

CSS, once the dominant landscape type in the area, is a unique ecosystem that provides 

cultural value to California and the nation as a whole. Culturally, the remaining patches of CSS 

contain a number of threatened and endangered species, and patches of CSS are present in a 

number of parks and recreational areas. More generally, the patches of CSS represent the iconic 

landscape of Southern California and serve as a reminder of what the area looked like predevelopment. Changes that might impact cultural ecosystem services in CSS resulting from 

nutrient enrichment potentially include the following: 

 Decline in CSS habitat, shrub abundance, and species of concern 

 Increased abundance of nonnative grasses and other species 

 Increase in wildfires. 

For MCF, the changes from nutrient enrichment that might impact cultural ecosystem 

services include the following: 

 Change in habitat suitability and increased tree mortality 

 Decline in MCF aesthetics. 

Recreation 

CSS and MCF are found in numerous recreational areas in California. Three national 

parks and monuments in California contain CSS, including Cabrillo National Monument, 

Channel Islands National Park, and Santa Monica National Recreation Area. All three parks 

showcase CSS habitat with educational programs and information provided to visitors, guided 

hikes, and research projects focused on understanding and preserving CSS. A total of 1,456,879 

visitors traveled through these three parks in 2008. MCF is highlighted in Sequoia and Kings 

Canyon National Park, Yosemite National Park, and Lassen Volcanic National Park, where a 

total of 5,313,754 people visited in 2008. In addition, numerous state and county parks 

encompass CSS and MCF habitat. For example, California’s Torrey Pines State Natural Reserve 

protects CSS habitat (see http://www.torreypine.org/). Visitors to these parks engage in activities 

such as camping, hiking, attending educational programs, horseback riding, wildlife viewing, 

water-based recreation, and fishing. 

The 2006 FHWAR for California (U.S. DOI, 2007) reports on the number of individuals 

involved in fishing, hunting, and wildlife viewing in California. Millions of people are involved 

in these three activities each year. The quality of these trips depends in part on the health of the 

ecosystems and their ability to support the diversity of plants and animals found in important 

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Chapter 5 – Nutrient Enrichment 

habitats. Based on estimates from Kaval and Loomis (2003), in the Pacific Coast region of the 

United States, a day of fishing has an average value of $48.86 (in 2007 dollars) based on 15 

studies. For hunting and wildlife viewing in this region, average day values were estimated to be 

$50.10 and $79.81 from 18 and 23 studies, respectively. Multiplying these average values by the 

total participation days reported in Appendix 8, Table 5.1-1, the total benefits in 2006 from 

fishing, hunting, and wildlife viewing away from home in California were approximately $947 

million, $169 million, and $3.59 billion, respectively. 

In addition, data from California State Parks (2003) indicate that in 2002, 68.7% of adult 

residents participated in trail hiking, for an average of 24.1 days per year. Applying these same 

rates to Census estimates of the California adult population in 2007 suggests that there were 

roughly 453 million days of hiking by residents in California in 2007. According to Kaval and 

Loomis (2003), the average value of a hiking day in the Pacific Coast region is $25.59, based on 

a sample of 49 studies. Multiplying this average day value by the total participation estimate 

indicates that the aggregate annual benefit for California residents from trail hiking in 2007 was 

$11.59 billion. 

Aesthetic 

Beyond the recreational value, the CSS landscape and MCF provide aesthetic services to 

local residents and homeowners who live near CSS or MCF. Aesthetic services not related to 

recreation include the view of the landscape from houses, as individuals commute, and as 

individuals go about their daily routine in a nearby community. Studies find that scenic 

landscapes are capitalized into the price of housing. While there are no known studies that look 

at the value of housing as a function of the view in landscapes that include CSS or MCF, other 

studies document the existence of housing price premia associated with proximity to forest and 

open space (Acharya and Bennett, 2001; Geoghegan et al., 1997; Irwin, 2002; Mansfield, et al., 

2005; Smith et al., 2002; Tyrvainen and Miettinen, 2000). The CSS landscape itself is closely 

associated with Southern California, which should increase the aesthetic value of the landscape 

in general. CSS areas border a number of areas along the coast near large cities with very high 

home values, as well as areas between the cities where home values are lower. 

Nonuse Value 

Nonuse value, also called existence value or preservation value, encompasses a variety of 

motivations that lead individuals to place value on environmental goods or services that they do 

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Final Risk and Exposure Assessment 5-55 September 2009 

not use. The values individuals place on protecting rare species, rare habitats, or landscape types 

that they do not see or visit and that do not contribute to the pleasure they get from other 

activities are examples of nonuse values. 

While measuring the public’s willingness to pay to protect endangered species poses 

theoretical and technical challenges, it is clear that the public places a value on preserving 

endangered species and their habitats. Data on charitable donations, survey results, and the time 

and effort different individuals or organizations devote to protecting species and habitats suggest 

that endangered species have intrinsic value to people beyond the value derived from using the 

resource (e.g., recreational viewing or aesthetic value). CSS and MCF are home to a number of 

important and rare species and habitat types. CSS displays richness in biodiversity, with more 

than 550 herbaceous annual and perennial species. Of these herbs, nearly half are endangered, 

sensitive, or of special status (Burger et al., 2003). Additionally, avian, arthropod, herpetofauna, 

and mammalian species live in CSS habitat or use the habitat for breeding or foraging. 

Communities of CSS are home to three important federally endangered species. MCF is 

home to one federally endangered species and a number of state-level sensitive species. The 

Audubon Society lists 28 important bird areas in CSS habitat and at least 5 in MCF in California 

(http://ca.audubon.org/iba/index.shtml).3

Only one known study has specifically estimated values for protecting CSS habitat in 

California. Stanley (2005) uses a contingent valuation (CV) survey to measure willingness to pay 

(WTP) to support recovery plans for endangered species in Southern California. The survey of 

Orange County, CA, residents asked respondents to value the recovery of a single species (i.e., 

the Riverdale fairy shrimp) and a larger bundle of 32 species found in the county. The 

acquisition of critical habitat and implementation of the recovery plan were the specific goods 

being valued in the WTP question, and the programs would be financed by an annual tax 

payment. The average WTP for Riverdale fairy shrimp recovery was roughly $29 (in 2007 

dollars), and for all 32 species, it was $61 per household, depending on the model used. 

Aggregating benefits (i.e., multiplying average household WTP by the number of households in 

the county) results in total estimated WTP of more than $27 million annually for protecting 

Riverdale fairy shrimp and $57 million annually for protecting all 32 species. 

 

3 Important Bird Areas are sites that provide essential habitat for one or more species of bird. 
Chapter 5 – Nutrient Enrichment 

In a more general study valuing endangered species protection, Loomis and White (1996) 

synthesize key results from 20 threatened and endangered species valuation studies using metaanalysis methods. They find that annual WTP estimates range from a low of $11 for the Striped 

Shiner fish to a high of $178 for the Northern Spotted Owl (in 2007 dollars). None of the studies 

summarized by Loomis and White are found in CSS or MCF, but the study provides another 

indication of the value that the public places on preserving endangered species in general. 

Regulating 

Excessive nitrogen deposition upsets the balance between CSS and nonnative plants, 

changing the ability of an area to support the biodiversity found in CSS. The composition of 

species in CSS changes fire frequency and intensity, as nonnative grasses fuel more frequent and 

more intense wildfires. More frequent and intense fires also decrease the ability of CSS to 

regenerate after a fire and increase the proportion of nonnative grasses (U.S. EPA, 2008). A 

healthy MCF ecosystem supports native species, promotes water quality, and helps regulate fire 

intensity. Excess nitrogen deposition leads to changes in the forest structure, such as increased 

density and loss of root biomass, which, in turn, can result in more intense fires and water quality 

problems related to nitrate leaching (U.S. EPA, 2008). 

The importance of CSS and MCF as homes for sensitive species and their aesthetic 

services have been discussed in Appendix 8, Section 5.1.1. Here the contribution of CSS and 

MCF to fire regulation and water quality is discussed. 

Fire Regulation 

The terrestrial enrichment case study identified fire regulation as a service that could be 

affected by nutrient enrichment of the CSS and MCF ecosystems by encouraging growth of more 

flammable grasses. Wildfires represent a serious threat in California and cause billions of dollars 

in damage. Over the 5-year period from 2004 to 2008, Southern California experienced, on 

average, more than 4,000 fires per year burning, on average, more than 400,000 acres per year 

(NASF, 2009). Improved fire regulation leads to short-term and long-term benefits. The shortterm benefits include the value of avoided residential property damages, avoided damages to 

timber, rangeland, and wildlife resources, avoided losses from fire-related air quality 

impairments, avoided deaths and injury due to fire, improved outdoor recreation opportunities, 

and savings in costs associated with fighting the fires and protecting lives and property. For 

example, the California Department of Forestry and Fire Protection (CAL FIRE) estimated that 

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Chapter 5 – Nutrient Enrichment 

average annual losses to homes due to wildfire from 1984 to 1994 were $163 million per year 

(CAL FIRE, 1996) and were more than $250 million in 2007 (CAL FIRE, 2008). In fiscal year 

2008, CAL FIRE’s costs for fire suppression activities were nearly $300 million (CAL FIRE, 

2008). Therefore, even a 1% decrease in these damages and costs would imply benefits of more 

than $5 million per year. 

CSS overlaps with areas of very high to extremely high fire threat. MCF is found in some 

areas closer to the coast with extremely high fire threat and in areas in the mountains also under 

very high fire threat. 

In the long term, decreased frequency of fires could result in an increase in property 

values in fire-prone areas. Mueller et al. (2007) conducted a hedonic pricing study to determine 

whether increasing numbers of wildfires affect house prices in Southern California. They 

estimated that house prices would decrease 9.71% ($30,693 in 2007 dollars) after one fire and 

22.7% ($71,722; $102,417 cumulative) after a second wildfire within 1.75 miles of a house in 

their study area. After the second fire, the housing prices took between 5 and 7 years to recover. 

The results come from a sample of 2,520 single-family homes located within 1.75 miles of one 

of five fires during the 1990s. 

Long-term decreases in wildfire risks are also expected to provide outdoor recreation 

benefits. The empirical literature contains several articles measuring the relationship between 

wildfires and recreational values; however, very few address fires in California, particularly in 

CSS areas. One exception is Loomis et al. (2002), which estimates the changes in deer harvest 

and deer hunting benefits resulting from controlled burns or a prescribed fire in the San 

Bernardino National Forest in Southern California. Using a CV survey of deer hunters in 

California, they estimated that the net economic value of an additional deer harvested is on 

average $122 (in 2007 dollars). Based on predicted changes in deer harvest in response to a 

prescribed fire, they estimated annual economic benefits for an additional 1,000 acres of 

prescribed burning ranges from $3,328 to $3,893. 

Water Quality 

In the MCF Case Study, maintaining water quality emerged as a regulating service that 

can be upset by excessive nitrogen. When the soil becomes saturated, nitrates may leach into the 

surface water and cause acidification. Several large rivers and Lake Tahoe cut through MCF 

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Chapter 5 – Nutrient Enrichment 

areas (see Appendix 8, Figure 5.1-10). Additional nitrogen from MCF areas could further 

degrade waters that are already stressed by numerous other sources of nutrients and pollution. 

Value of Coastal Sage Scrub and Mixed Conifer Forest Ecosystem Services 

The CSS and MCF were selected as case studies for terrestrial nutrient enrichment 

because of the potential that these areas could be adversely affected by excessive nitrogen 

deposition. To date, the detailed studies needed to identify the magnitude of the adverse impacts 

due to nitrogen deposition have not been completed. Based on available data, this Risk and 

Exposure Assessment report provides a qualitative discussion of the services offered by CSS and 

MCF and a sense of the scale of benefits associated with these services. California is famous for 

its recreational opportunities and beautiful landscapes. CSS and MCF are an integral part of the 

California landscape, and together the ranges of these habitats include the densely populated and 

valuable coastline and the mountain areas. Through recreation and scenic value, these habitats 

affect the lives of millions of California residents and tourists. Numerous threatened and 

endangered species at both the state and federal levels reside in CSS and MCF. Both habitats 

may play an important role in wildfire frequency and intensity, an extremely important problem 

for California. The potentially high value of the ecosystem services provided by CSS and MCF 

justify careful attention to the long-term viability of these habitats. 

5.3.2 Characteristics of Sensitive Areas 

“Effects are most likely to occur where areas 

of relatively high atmospheric nitrogen 

deposition intersect with nitrogen limited 

plant communities. The factors that govern 

the sensitivity...include the degree of 

nitrogen limitation, rates and form of 

atmospheric nitrogen deposition, elevation, 

species composition, length of growing 

season, and soil nitrogen retention capacity.” 

ISA, Section 3.3 (U.S. EPA 2008) 

The ISA (U.S. EPA, 2008, Section 3.3) 

indicates that information is limited about the 

spatial extent and distribution of terrestrial 

ecosystems most sensitive to nutrient enrichment 

from atmospheric nitrogen deposition. Examples 

of sensitive ecosystems include the following: 

 Alpine tundra (low rates of primary production, short growing season, low temperature, 

wide moisture variation, low nutrient supply). 

 Western United States ecosystems, such as the alpine ecosystems of the Colorado Front 

Range, chaparral watersheds of the Sierra Nevada Range, lichen communities in the San 

Bernardino Mountains and the Pacific Northwest, and CSS communities in Southern 

California. 

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Chapter 5 – Nutrient Enrichment 

 Eastern United States ecosystems, where sensitivities are typically assessed in terms of 

the degree of nitrate leaching from soils into ground and surface waters. These 

ecosystems are expected to include hardwood forests and grassland ecosystems, but 

effects on individual plant species have not been studied well. 

In the Mediterranean systems of Southern California where rainfall is concentrated 

during some months of the year, dry deposition is particularly important. Individual studies 

measuring atmospheric nitrogen deposition to terrestrial ecosystems that involve throughfall 

estimates for forested ecosystems can provide better approximations for total atmospheric 

nitrogen deposition levels; however, such estimates and related bioassessment data are not 

available for the entire country. Further, dry deposition methodologies themselves need to be 

improved. 

Finally, the exact relationship between atmospheric nitrogen loadings, fire frequency and 

intensity, and nonnative plants, particularly in the CSS ecosystem, have not been quantified. 

Various conceptual models linking these factors have been developed, but an understanding of 

cause and effect, seasonal influences, and thresholds remains undeveloped. 

The selection of case study areas specific to terrestrial nutrient enrichment began with 

national GIS mapping to identify terrestrial areas potentially sensitive to atmospheric nitrogen 

deposition. GIS datasets of physical, chemical, and biological properties that were indicative of 

potential terrestrial nutrient enrichment were considered. Not all sensitive systems have adequate 

datasets. The case study areas considered included places where data on species sensitive or 

vulnerable to nitrogen deposition were available and excluded areas of the United States with 

anthropogenic influence (e.g., urban, farmland). 

Acidophytic lichens are known to be sensitive to increased levels of nitrogen loading. In 

turn, other species are dependent upon lichens for both food and habitat. Locations where 

acidophytic lichen were identified were defined as being sensitive. 

Urban and agricultural land covers were also mapped, so they could be used to exclude 

areas that are not sensitive to terrestrial nutrient enrichment, such as agricultural areas and 

urbanized areas. Analysis of the presence of lichen over time compared to atmospheric nitrogen 

deposition records and benchmarks can indicate the potential influence of nitrogen deposition. 

Although there is no known nationwide species that has shown range loss because of 

additional nitrogen, it was possible to assemble a “patchwork quilt” of species and forest types 

Final Risk and Exposure Assessment 5-59 September 2009 
Chapter 5 – Nutrient Enrichment 

from across the United States that are identified in the published literature as sensitive. These 

species have evolved in settings across the United States to be able to assimilate specific levels 

of nitrogen exposure. Some settings may naturally have low background concentrations of 

nitrogen, so the species requires a relatively small amount to thrive. Other settings may have 

higher background concentrations, where native species have evolved to thrive at those levels. 

When exposed to nitrogen levels higher than natural background, the native species may be 

vulnerable to invasion from species that use nitrogen in the shallow root zone before the nutrient 

reaches deeper zones of the native ecosystem vegetation. 

Soil nitrogen content data dating to pre-1980 were not available, and the quality of any 

available data was uncertain. The physiographic provinces of the United States were considered 

to provide leeward sides of mountains that tend to receive a greater amount of atmospheric 

nitrogen deposition. However, this dataset was not used because terrain is already taken into 

account by the CMAQ modeling. 

The resulting map illustrates the areas of highest potential sensitivity (see Figure 5.3-3.), 

including CSS, grasslands, and desert, as well as certain forest species and lichens. 

This information facilitated the review of candidate case study areas. 

5.3.3 Case Study Selection 

Figure 5.3-3, showing the areas of potential sensitivity to nutrient enrichment, was used 

in conjunction with potential areas identified in the ISA (U.S. EPA, 2008, Section 4.3.1.2, Table 

4.4) to select ecosystems for the case study. After considering this information, California’s CSS 

and MCF ecosystems were selected for this Terrestrial Nutrient Enrichment Case Study analysis 

based on the following selection factors, in addition to the factors listed in Section 5.3.1: 

 Availability of atmospheric ambient and deposition data (monitored or modeled) 

 Availability of digitized datasets of biotic communities; fire-prone areas; and sensitive, 

rare species 

 Scientific results of research on nitrogen effects for the case study area 

 Representation of western United States ecosystems potentially impacted by atmospheric 

nitrogen deposition 

 Scalability and generalization opportunities for risk analysis results from the case studies. 

Final Risk and Exposure Assessment 5-60 September 2009 
Chapter 5 – Nutrient Enrichment 

California’s CSS has been the subject of intensive research in the past 10 years, which 

has provided the data needed for a first phase of GIS analysis of the role of atmospheric nitrogen 

deposition in terrestrial ecosystems. California’s MCF has an even longer record of study that 

includes investigations into the effects of atmospheric pollution, changes to forest structure, 

changes to the lichen communities, and measurements of nitrogen saturation. Another ecosystem 

that was considered, but not selected for this case study, was the alpine ecosystem in the Rocky 

Mountains (see Section 5.3.6). As noted in the ISA (U.S. EPA, 2008, Section 3.3), results from a 

number of studies indicate that nitrates may be leaching from alpine catchments, and there 

appear to be changes in plant communities related to the deposition of atmospheric nitrogen. The 

amount of data from these alpine ecosystems is more limited than that from the CSS and MCF. 

However, the ecological benchmarks suggested for alpine ecosystems were comparable to the 

lower-level benchmarks from CSS and MCF ecosystems (see Figure 5.3-2). 

Figure 5.3-3. Areas of highest potential nutrient enrichment sensitivity. 

(Acidophytic lichens, tree species, and the extent of the Mojave Desert come from data 

obtained from the United States Forest Service. The extents of coastal sage scrub and 

California mixed conifer forest come from the California Fire and Resource Assessment 

Program. Grasslands were obtained from the National Land Cover Dataset [USGS]). 

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Chapter 5 – Nutrient Enrichment 

5.3.4 Current Conditions in Case Study Areas 

CSS and MCF were selected as case study 

areas for the following reasons: 

 Significant geographic coverage and they 

are located where urban areas interface with 

wilderness areas. 

 Nitrogen deposition gradients, ranging from 

low background levels to some of the highest 

deposition levels recorded in the United 

States. 

 Researched for extended periods to 

understand the interactive effects of 

deposition, climate change, fire, and other 

stressors. 

 Research investigations are well 

documented in the peer-reviewed literature. 

To assess current conditions, the ISA (U.S. EPA, 2008) provided the basis for identifying 

the published scientific literature on CSS and MCF ecosystems. In addition, spatially distributed 

data are available and support a GIS analysis. 

Section 2.2 of Appendix 7 describes the data 

sources used in the GIS analysis. 

One of the central analytical tasks was 

to quantify the amount of CSS (and MCF 

loss) and to see whether this corresponded 

spatially to areas of high total nitrogen 

deposition or fire threat, or both. 

5.3.4.1 Coastal Sage Scrub 

CSS is subject to several pressures, such as land conversion, grazing, fire, and pollution, 

all of which have been observed to induce declines in other ecosystems (Allen et al., 1998). At 

one extreme, development pressure (i.e., the conversion of CSS to residential and commercial 

land uses) will simply eliminate acres of CSS. Other pressures will come into play in modifying 

the remaining ecosystem. Research suggests that both fire and increased atmospheric nitrogen 

deposition can enhance the growth of nonnative grasses in established CSS communities. 

Additionally, CSS declines have been observed when fire frequency is held constant and/or 

nitrogen is held constant, suggesting that both fire and nitrogen play a role in CSS decline when 

direct destructive factors are not an imminent threat. Table 3.1-1 of Appendix 7 contains a 

summary of selected experimental variables across multiple CSS study areas. 

Increased atmospheric nitrogen deposition has been observed to alter vegetation types 

when nitrogen is a limiting nutrient to growth. This is observed in alpine plant communities in 

the Colorado Front Range, as well as in lichen communities in the western Sierra Nevada region 

(Fenn et al., 2003, 2008); however, in the case of CSS, it is hypothesized that many stands are no 

longer limited by nitrogen and have instead become nitrogen-saturated because of atmospheric 

nitrogen deposition (Allen et al., 1998; Westman, 1981). This is supported by the positive 

correlation between atmospheric nitrogen and soil nitrogen, increased long-term mortality of 

CSS shrubs, and increased nitrogen-cycling rates in soil and litter and soil fertility (Allen et al., 

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Chapter 5 – Nutrient Enrichment 

1998; Padgett et al., 1999; Sirulnik et al., 

2007; Vourlitis et al., 2007). Figure 5.3-4 

illustrates the levels of atmospheric nitrogen 

deposition in CSS communities using 

CMAQ/NADP data. 

Wood et al. (2006) investigated the 

amount of nitrogen utilized by healthy and degraded CSS systems. In healthy stands, the authors 

estimated that 3.3 kg N/ha/yr was used for CSS plant growth (Wood et al., 2006). It is assumed 

that 3.3 kg N/ha/yr is near the point where nitrogen is no longer limiting in the CSS community. 

Therefore, this amount can be considered an ecological benchmark for the CSS community. 

Figure 5.3-4 displays the spatial extent of CSS where total nitrogen deposition is above the 

ecological benchmark of 3.3 kg N/ha/yr. Table 5.3-1 displays the areas (in hectares) of CSS 

experiencing different total nitrogen deposition levels. 

Table 5.3-1. Coastal Sage Scrub Ecosystem 

Area and Total Nitrogen Deposition

N Deposition 

(kg/ha/yr) 

Area 

(hectares) 

Percent of 

CSS Area, % 

≥3.3 654048.4179 93.51 

≥10 138019.8922 19.73 

In the rainy, winter season, deposited surface nitrogen is transported deeper into the soil 

and is rapidly mineralized by microbes, favoring the germination and growth of nonnative 

grasses (e.g., Bromus madritensis, Avena fatua, and Hirschfeldia incana). Flourishing of grasses 

can create a dense network of shallow roots, which slows the diffusion of water through soil, 

decreases the percolation depth of precipitation, and decreases the amount of water for soil and 

ground water recharge (Wood et al., 2006). Growth of CSS species, such as Artemisia 

californica, Eriogonum fasciculatum, and Encelia farinose, may be decreased because of 

decreased water and nitrogen availability at the deeper soil layers where more woody CSS tap 

roots are found (Keeler-Wolf, 1995; Wood et al., 2006). 

Mutualistic fungal communities, such as arbuscular mycorrhizae (AM) (EgertonWarburton and Allen, 2000; Siguenza et al., 2006), increase the surface area and capacity for 

nutrient uptake. CSS is predominantly colonized by a coarse AM species, and nonnative grasses 

are more likely mutualistic with finer AM species. In the presence of elevated nitrogen, coarse 

AM colonizations were depressed in number and volume. Egerton-Warburton and Allen (2000) 

documented shifts in AM species as well as declines in spore abundance and colonization at 

approximately 10 kg N/ha/yr. Therefore, it is suggested that these decreased mutualistic 

associations of coarse AM may contribute to a decline in the overall health of CSS via a loss in 

nutrient uptake capacity and represent an ecological benchmark for the CSS ecosystem. Figure 

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Chapter 5 – Nutrient Enrichment 

5.3-4 displays the levels of total nitrogen deposition on CSS communities above the ecological 

benchmark of 10 kg N/ha/yr using CMAQ/NADP data. The 12 km CMAQ/NADP data indicate 

that CSS communities within the Los Angeles and San Diego airsheds are likely to experience 

the noted effects at the 10 kg N/ha/yr ecological benchmark. 

Figure 5.3-4. Coastal sage scrub range and total nitrogen deposition using 

CMAQ 2002 modeling results and NADP monitoring data.

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Chapter 5 – Nutrient Enrichment 

Studies have suggested that plant-available nitrogen in soils may be increasing because of 

soil fertility in conjunction with atmospheric deposition, so that the soil itself becomes an 

intrinsic source of nitrogen (Padgett et al., 1999). In combination with decreased establishment 

and the capacity for nutrient uptake, these responses to elevated nitrogen levels may represent a 

detrimental and long-term pressure on CSS at varying levels of nitrogen additions. Table 3.1-3 of 

Appendix 7 summarizes the various ecosystem responses to nitrogen levels that affect CSS 

communities. 

Fire is also an inextricable and significant component in CSS losses. Although CSS 

communities are fire resilient, nonnative grass seeds are quick to establish in burned lands, 

decreasing the water and nutrient amounts available to CSS for reestablishment (Keeler-Wolf, 

1995). Additionally, when annual grasses have established dominance, these species alter and 

increase the fire frequency as they senesce earlier in the annual season, which increases dry, 

ignitable fuel availability (Keeley et al., 2005). With increased fire frequencies and faster 

nonnative colonizations, CSS seed banks are eventually eradicated from the soil, and the 

probability of reestablishment decreases significantly (Keeley et al., 2005). Figure 5.3-5

represents the fire threats to CSS communities. 

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Chapter 5 – Nutrient Enrichment 

Figure 5.3-5. Current fire threats to coastal sage scrub communities.

5.3.4.2 Mixed Conifer Forest Ecosystems 

The MCF ecosystem has been a subject of study for many years. There are a number of 

important stressors on the community, including fire, bark beetles, ozone, particulates, and 

atmospheric nitrogen. Although fire suppression in the 20th century is probably the most 

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Chapter 5 – Nutrient Enrichment 

significant change that has led to alterations in morphology and perhaps to shifts in forest 

composition (Minnich et al., 1995), stress from elevated levels of ambient atmospheric nitrogen 

concentrations is the subject of increasing research. 

Measurements documenting increases in atmospheric nitrogen deposition have been 

recorded with some regularity since the 1980s (Bytnerowicz and Fenn, 1996); however, the Los 

Angeles area has seen elevated ambient atmospheric nitrogen concentrations for the last 50 years 

(Bytnerowicz and Fenn, 1996). Also, some data have been published for the primary nitrogen 

species of dry atmospheric nitrogen deposition in the San Bernardino Mountains (i.e., nitric acid 

[HNO3] and ammonia gas [NH3]) from passive samplers (Bytnerowicz et al., 2007). The 

pressures exerted on MCF ecosystems in California form a gradient across the Sierra Nevada 

Range and San Bernardino Mountains. Nitrogen throughfall levels in the northern Sierra Nevada 

Range are as low as 1.4 kg N/ha/yr, whereas forests in the western San Bernardino Mountains 

experience measured throughfall nitrogen levels up to 33 to71 kg N/ha/yr. (Note that the high 

levels of nitrogen seen in some measured throughfall values are not reflected in the 

CMAQ/NADP data, which is developed from 12 square km grids. Throughfall values reflect 

atmospheric deposition as well as canopy exchange.) The primary source of nitrogen in the 

western San Bernardino Mountains stems from fossil fuels combustion, such as vehicle exhaust. 

Other sources, such as agricultural processes, also play a prominent role in the western portions 

of the San Bernardino and Sierra Nevada Range (Grulke et al., 2008). Figure 5.3-6 illustrates the 

current total atmospheric nitrogen deposition on MCF in California. 

Final Risk and Exposure Assessment 5-67 September 2009 
Chapter 5 – Nutrient Enrichment 

Figure 5.3-6. Mixed conifer forest range and total nitrogen deposition using 

CMAQ 2002 modeling results and NADP monitoring data. 

At the individual tree level, elevated atmospheric nitrogen can shift the ratio of 

aboveground to belowground biomass. Elevated pollution levels allow increased uptake of 

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Chapter 5 – Nutrient Enrichment 

nutrients via the canopy, reduced nitrogen intake requirements on root structures, and increased 

demand for carbon dioxide (CO2) uptake and photosynthetic structures to maintain the carbon 

balances. Therefore, the increased nutrient availability stimulates aboveground growth and 

increases foliar production while decreasing the demand for belowground nutrient uptake (Fenn 

et al., 2000) resulting in diminished fine-root biomass (Fenn and Bytnerowicz, 1997). Grulke et 

al. (1998) observed a 6- to 14-fold increase in fine-root mass in areas of low atmospheric 

nitrogen deposition as compared to areas of high deposition. 

At the stand level, elevated atmospheric nitrogen has been associated with increased 

stand density, although other factors, such as fire suppression, also contribute to increased 

density and can increase mortality rates (U.S. EPA, 2008). As older trees die, they are replaced 

with younger, smaller trees. Smaller trees allow more sunlight through the canopy and, combined 

with an increased availability of nitrogen, may allow for more trees to be established. Increased 

stand densities with younger-age classes are observed in the San Bernardino Mountains, where 

air pollution levels are among the highest found in the California conifer ranges studied (Minnich 

et al., 1995; Fenn et al., 2008). These shifts in stand density and age distribution result in 

vegetation structure shifts which, in turn, may impact population and community dynamics of 

understory plants and animals, including threatened and endangered species. 

It should be noted that the effects of ozone and atmospheric nitrogen are difficult to 

separate. The atmospheric transformation of nitrogen oxides can yield moderate concentrations 

of ozone as a byproduct (Grulke et al., 2008). Therefore, since elevated nitrogen levels are 

generally correlated with ozone concentrations, researchers often report changes in tree growth 

and vigor as being the result of both (Grulke and Balduman, 1999). 

High concentrations of ozone and atmospheric nitrogen can generate increased needle 

and branch turnover. In areas subjected to low pollution, conifers may retain needles across 4 or 

5 years; however, in areas of high pollution, such as Camp Paivika in the San Bernardino 

Mountains, needle retention was generally less than 1 year (Grulke and Balduman, 1999; Grulke 

et al, 2008). Needle turnover significantly increases litterfall. Litter biomass has been observed to 

increase in areas with elevated atmospheric nitrogen deposition up to 15 times more than in areas 

with low deposition, and the litter is seen to have higher concentrations of nitrogen (Fenn et al., 

2000; Grulke et al., 2008). Elevated litter nitrogen levels may facilitate faster rates of microbial 

decomposition initially, but over the long term, high nitrogen levels slow litter decomposition 

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Chapter 5 – Nutrient Enrichment 

and litter accumulates on the forest floor (Grulke et al., 2008; U.S. EPA, 2008). The increased 

litter depth may then affect subcanopy growth and stand regeneration over long periods of time. 

At the highest levels of atmospheric nitrogen deposition, native understory species were 

seen to decline (Allen et al., 2007). In addition to the decline in native understory diversity, 

changes in decreased fine-root mass, increased needle turnover, and the associated 

chemostructural alterations, MCF exposed to elevated pollutant levels have an increasing 

susceptibility to drought and beetle attack (Grulke et al., 1998, 2001; Takemoto et al., 2001). 

These stressors often result in the death of trees, producing an increased risk of wildfires. 

Lichens emerged as an indicator of nutrient enrichment from the research on the effects 

of acid rain. Lichen species are sensitive to air pollution; in particular, atmospheric nitrogen. 

Since the 1980s, information about lichen communities has been gathered, and lichens have been 

used as indicators to detect changes in forest communities. 

As atmospheric nitrogen deposition increases, the relative abundance of acidophytic 

lichens decreases, and the concentration of nitrogen in one of those species, Letharia vulpine, 

increases (Fenn et al., 2008). Fenn et al. (2008) were able to quantify the change in the lichen 

community, noting that for every 1 kg N/ha/yr increase, the abundance of acidophytic lichens 

declined by 5.6%. Figure 5.3-7 illustrates the presence of acidophyte lichens and the total 

atmospheric nitrogen deposition in the California ranges. 

In addition to abundance changes, species richness, cover, and health are affected in areas 

of high ozone and nitrogen concentrations. Fifty percent fewer lichen species were observed after 

60 years of elevated air pollution in San Bernardino Mountains MCF, with the areas of highest 

pollution levels exhibiting low species richness, decreased abundance and cover, and 

morphological deterioration of existing lichens (Sigal and Nash, 1983). 

Fenn et al. (2008) found that at 3.1 kg N/ha/yr, the community of lichens begins to 

change from acidophytic to tolerant species; at 5.2 kg N/ha/yr, the typical dominance by 

acidophytic species no longer occurs; and at 10.2 kg N/ha/yr, acidophytic lichens are totally lost 

from the community. Additional studies in the Colorado Front Range of the Rocky Mountain 

National Park support these findings and are summarized in Chapter 5.3.6.2 of this Risk and 

Exposure Assessment. These three values (3.1, 5.2, and 10.2 kilograms per hectare per year 

[kg/ha/yr]) are one set of ecologically meaningful benchmarks for the MCF. Figure 5.3-7 shows 

the presence of acidophytic lichen species above the three ecological benchmarks. Nearly all of 

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Chapter 5 – Nutrient Enrichment 

the MCF communities receive total nitrogen deposition levels above the 3.1 N kg/ha/yr 

ecological benchmark according to the 12- km 2002 CMAQ/NADP data, with the exception of 

the easternmost Sierra Nevada Range. MCF in the southern portion of the Sierra Nevada forests 

and nearly all MCF communities in the San Bernardino forests receive total nitrogen deposition 

levels above the 5.2 N kg/ha/yr ecological benchmark. Figure 5.3-7 also displays the potential 

areas where acidophytic lichens are extirpated because of nitrogen deposition levels above 10.2 

kg N kg/ha/yr. 

The established signs of nitrogen saturation have been shown within the MCF ecosystem. 

These symptoms include the following: 

 Increased carbon and nitrogen cycling 

 Decreased nitrogen uptake efficiency of plants 

 Increased loss of forest nitrates to streamwater (NO3

-

 leachate). 

Fenn et al. (2008) established a critical loading benchmark of 17 kg throughfall N/ha/yr 

(which is the actual nitrogen deposited on the forest floor as opposed to modeled nitrogen 

deposition) in the San Bernardino and Sierra Nevada Range MCF ecosystems. This benchmark 

represents the level of atmospheric nitrogen deposition at which elevated concentrations of 

streamwater NO3

-

 leachate or potential nitrogen saturation may occur. At this deposition level, a 

26% decrease in fine-root biomass is anticipated (Fenn et al., 2008). Root:shoot ratios are, 

therefore, altered, and changes in nitrogen uptake efficiencies, litterfall biomass, and microbial 

decomposition are anticipated to be present at this atmospheric nitrogen deposition level. This 

benchmark is based on 30 to 60 years of exposure to elevated atmospheric concentrations. At 

longer exposure levels, the benchmark is lower because of decreased nitrogen efficiencies of the 

ecosystem. This benchmark is exceeded in areas of the western San Bernardino Mountains, such 

as Camp Paivika. 

Nitrate leaching is a symptom that an ecosystem is saturated by nitrogen. Nitrate leaching 

is also known to cause acidification in adjacent surface waters. The ecological benchmark of 17 

kg N/ha/yr is the last benchmark identified in this study. At this level of atmospheric nitrogen 

deposition, nitrate is observed in streams in the MCF (Fenn et al., 2008), denoting a change in 

ecosystem function. 

Table 5.3-2 shows the area of MCF experiencing levels of nitrogen deposition 

corresponding to the identified benchmarks. 

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Chapter 5 – Nutrient Enrichment 

Table 5.3-2. Mixed Conifer Forest Ecosystem Area and Nitrogen Deposition

N Deposition 

(kg/ha/yr) 

Area 

(hectares) 

Percent of MCF 

Area, % 

≥3.1 1099133.482 38.62 

≥5.2 130538.2573 4.59 

≥10.2 11963.08815 0.42 

≥17 0 0.00 

Note: According to the 12-km CMAQ data, there is too little 

area receiving >17 kg N/ha/yr to be measurable. 

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Chapter 5 – Nutrient Enrichment 

Figure 5.3-7. Presence of acidophyte lichens and total nitrogen deposition in the 

California mountain ranges using CMAQ 2002 modeling results and NADP 

monitoring data.

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Chapter 5 – Nutrient Enrichment 

5.3.5 Degree of Extrapolation to Larger Assessment Areas 

The Terrestrial Nutrient Enrichment Case Study examined the effects of atmospheric 

nitrogen on two ecosystem types in California, CSS and MCF. Figure 5.3-8 presents CMAQ 

2002–modeled and NADP-monitored deposition of total nitrogen in the western United States. In 

the western United States, other arid and forested ecosystems exposed to deposition at levels 

discussed in this case study may experience altered effects. As noted in the previous section, 

research on grasslands and chaparral ecosystems is underway. Nitrate leaching in forests with 

elevated deposition may result in nitrate leaching that subsequently enriches and affects aquatic 

ecosystems. Research on lichen species in the Pacific Northwest and in Central California that 

are also exposed to elevated levels of atmospheric nitrogen deposition is also being conducted. 

Extensive research on the eastern Front Range of the Rocky Mountain National Park has been 

conducted in alpine and subalpine terrestrial and aquatic systems at elevations about 3,300 

meters (m), where communities are typically adapted to low nutrient availability but are now 

being exposed to >10 kg N/ha/yr in some study areas. 

Locations were identified where data were available that might have implications for 

other ecosystems and ecosystem services, as well as where a compelling case may be found to 

show that the effects were due to atmospheric deposition of nitrogen. Other systems that are also 

sensitive might include the following: 

 Ecosystems with nitrogen-sensitive epiphytes, such as lichens or mycorrhizae. Such 

systems may demonstrate shifts in community structure through changes in nutrient 

availability or modified provisioning services. 

 Ecosystems that may have been exposed to long periods of elevated atmospheric 

nitrogen deposition. The established signs of nitrogen saturation are increased leaching 

of NO3

-

 into streamwater, decreased nitrogen uptake efficiency of plants, and increased 

carbon and nitrogen cycling. At prolonged elevated nitrogen levels, ecosystems are 

generally less likely to use, retain, or recycle nitrogen species efficiently at both the 

species and community levels. 

 Critical habitats. Ecosystems that are necessary for endemic species or special 

ecosystem services should be monitored for possible changes due to nitrogen. 

 Locations where there are seasonal releases of nitrogen. In both the California CSS 

and MCF ecosystems discussed in the case study, a large portion of nitrogen is dryFinal Risk and Exposure Assessment 5-74 September 2009 
Chapter 5 – Nutrient Enrichment 

deposited and remains on the foliage and soil surface until the beginning of the winter 

rainy season when nitrogen will be flushed into the soil. 

In addition to the documented signs of nitrogen saturation, it is interesting to note that 

both CSS and the MCF ecosystems had responses in epiphytic associations, as well as increased 

susceptibility to wildfire and invasion of exotic species. Water use was also modified in these 

systems. The implication and inferential magnitude of these results may warrant future 

investigations. 

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Chapter 5 – Nutrient Enrichment 

Figure 5.3-8. CMAQ 2002 modeling results and NADP monitoring data for 

deposition of total nitrogen in the western United States.

5.3.6 Current Conditions for Select Locations Nationwide 

5.3.6.1 Overview 

Figure 5.3-9 displays a map of observed effects from ambient and experimental 

atmospheric nitrogen deposition loads in relation to CMAQ 2002 modeling results and NADP 

monitoring data. The map depicts the sites where empirical effects of terrestrial nutrient 

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Chapter 5 – Nutrient Enrichment 

enrichment have been observed and site proximity to elevated levels of atmospheric nitrogen 

deposition. The ISA (U.S. EPA, 2008, Section 3.3) also identifies areas of the western United 

States where atmospheric nitrogen deposition effects have been reported. 

A range of ecological benchmarks were developed in the results. All benchmarks are tied 

to a level of atmospheric nitrogen deposition but include a number of different ecological 

processes. All of the benchmarks are ecologically significant in that changes that are related to 

community structure and function are seen. The benchmarks span a range from 3.1 to 17 kg 

N/ha/yr (see Figure 5.3-2) and include the following: 

 3.1 kg N/ha/yr – shift from sensitive to tolerant lichen species in MCF 

 3.3 kg N/ha/yr – the amount of nitrogen uptake by a vigorous stand of CSS; above this 

level, nitrogen may no longer be limiting 

 5.2 kg N/ha/yr – dominance of tolerant lichen species in MCF 

 10 kg N/ha/yr – mycorrhizal community changes in CSS 

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

 17 kg N/ha/yr – nitrate leaching into streams in MCF. 

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Chapter 5 – Nutrient Enrichment 

1. Nitrogen enrichment or eutrophication of lakes (Loch 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 NO3

-

 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 nitrification (Loch Vale, CO (spruce): 1.7 kg/ha/yr)

7. Alpine tundra with increased plant foliage and decreased species richness (Niwot Ridge, CO: 50 kg/ha/yr) 

8. Nitrogen saturation, high NO3

-

 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 NO3

-

 in streamwater (San Bernardino Mountains, CA (coniferous): 2.9 and 18.8 kg/ha/yr) 

10. NO3

-

 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 Bernardino Mountains, CA (Ponderosa): 8 and 82 kg/ha/yr) 

13. Enhanced growth of black cherry and yellow poplar; possible 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 communities (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, increase 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 5.3-9. Observed effects from ambient and experimental atmospheric 

nitrogen deposition loads in relation to using CMAQ 2002 modeling results and 

NADP monitoring data. Citations for effect results are from the ISA, Table 4.4 

(U.S. EPA, 2008). 

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Chapter 5 – Nutrient Enrichment 

This range of ecological benchmarks may be used to develop a “green line/red line” 

schematic, similar to the forest screening model discussed in Lovett and Tear (2007) that 

illustrates the levels at which ecosystem effects may occur or are known to occur. In Figure 

5.3-10, the green area/line denotes that point at which there do not appear to be any effects, and 

the red line denotes the point at which known negative effects occur. 

Figure 5.3-10. Illustration of the range of terrestrial ecosystem effects observed 

relative to atmospheric nitrogen deposition. 

For the benchmarks identified, effects may occur at the level of atmospheric nitrogen 

deposition associated with the “green line” illustrated in Figure 5.3-10, so the “green line” may 

be somewhat lower. The higher levels of atmospheric nitrogen deposition (both at 10.2 and 17 

kg/ha/yr) better resemble a “red line,” where a known negative effect occurs. 

The range of ecological benchmarks in CSS and MCF are not dissimilar from those 

identified in other ecosystems with related characteristics, such as arid systems, other forested 

systems, or grasslands (see Figure 5.3-11). Egerton-Warburton et al. (2001) report that at 10 kg 

N/ha/yr, nitrogen changes in mycorrhizal communities/grass biomass are observed in chaparral 

ecosystems. Nitrates are found to leach into streams of the northeastern United States at 

deposition levels between 9 and 13 kg N/ha/yr (Aber et al., 2003). Results from several studies 

suggest ecosystem changes that are related to atmospheric nitrogen deposition. The capacity of 

alpine catchments to sequester nitrogen is exceeded at input levels <10 kg N/ha/yr (Baron et al., 

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Chapter 5 – Nutrient Enrichment 

1994). Changes in the Carex plant community were observed to occur at deposition levels near 

10 kg N/ha/yr (Bowman et al., 2006). Clark and Tilman (2008) predict that at 5.3 kg N/ha/yr, 

there is a loss of species diversity in grasslands. In the Pacific Northwest and in Central 

California, a number of investigators have observed declines in sensitive lichen species as air 

pollution increases (Jovan and McCune, 2005; Geiser and Neitlich, 2007). In Europe, acidophyte 

decline has been identified in regions with 8 to 10 kg N/ha/yr (Bobbink, 1998; Bobbink et al., 

1998). 

CA Mixed Conifer Forest 

Figure 5.3-11. Habitats that may experience ecological benchmarks similar to 

coastal sage scrub and mixed conifer forest.

5.3.6.2 Atmospheric Nitrogen Deposition Influence on Eastern Slope of Rocky 

Mountains 

Rocky Mountain National Park encompasses approximately 265,770 acres (1,076 km2

) of 

land in Colorado's northern Front Range. The park is split by the Continental Divide, which 

gives the eastern and western portions of the park a different character. The east side of the park 

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tends to be drier, with heavily glaciated peaks and cirques. The west side of the park is wetter 

and lusher, dominated by deep forests. The park contains 150 lakes and 450 miles (720 km) of 

streams. The park contains more than 60 named peaks higher than 12,000 feet (3,700 m), and 

over one-fourth of the park resides above tree line. The lowest elevations in the park are montane 

forests and grassland. The ponderosa pine, which prefers drier areas, dominates, though at higher 

elevations Douglas fir trees are found. Above 9,000 feet (2,700 m) the montane forests give way 

to the subalpine forest. Engelmann spruce and subalpine fir trees are common in this zone. These 

forests tend to have more moisture than the montane and tend to be denser. Above tree line, at 

approximately 11,500 feet (3,500 m), trees disappear, and it becomes alpine tundra. 

Since Rocky Mountain National Park spans the Continental Divide, there are higher 

levels of atmospheric nitrogen deposition to the east (the Front Range) than for the western parts 

of the park due to transport of emissions from densely populated areas (e.g., the Denver 

metropolitan area). Most of the detailed scientific studies documenting acid rain effects have 

involved alpine or subalpine settings, usually at elevations of 3,100 m or more above mean sea 

level. Rocky Mountain National Park is surrounded by other federal public lands. The Niwot 

Ridge Long-Term Ecological Research (LTER) site is located in the Roosevelt National Forest 

to the immediate southwest of Rocky Mountain National Park, and Niwot Ridge research 

findings have applicability to patterns relevant to the Front Range (west of the Continental 

Divide) portions of Rocky Mountain National Park. (Figure 5.3-12) 

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Chapter 5 – Nutrient Enrichment 

Figure 5.3-12. Rocky Mountain National Park location relative to the Niwot 

Ridge Long-Term Ecological Research site and Denver metropolitan area. 

Aquatic Systems: Lakes and Streams 

Some alpine lakes in the west (including the Rocky Mountains) show a seasonal pattern 

of episodic acidification for lakes (and also for streams) from melting of snowpack in the early 

spring, related to poor acid neutralizing capacity of the sparse soils and receiving waters and 

flushing of dissolved organic carbon (Denning et al., 1991;Williams and Tonnessen, 2000). The 

hydrologic cycle in higher elevation areas is dominated by the annual accumulation and melting 

of a dilute, mildly acidic snowpack. While these areas are not as sensitive as other parts of the 

West, the ISA (U.S. EPA, 2008) presents information showing that lakes in the Rocky Mountain 

area have been documented as acid-sensitive waters in the EPA Western Lakes Survey (Landers 

et al., 1987; Stoddard et al., 2003). Chronic acidification effects (e.g., as in the Adirondacks, are 

not prevalent for western lakes, but episodic acidification has been reported for lakes in the 

Colorado Front Range [Brooks et al., 1996; Williams et al., 1996]). 

The ISA (U.S. EPA, 2008) presents scientific studies that show that increased 

atmospheric nitrogen deposition in lakes and streams can cause a shift in community 

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Chapter 5 – Nutrient Enrichment 

composition and decrease algal biodiversity. Elevated nitrogen deposition results in changes in 

algal species composition, especially in sensitive oligotrophic lakes. Field experiments show 

responses to nitrogen for two opportunistic diatom species, Asterionella formosa and Fragilaria 

crotonensis (McKnight et al., 1990; Lafrancois et al., 2004; Saros, 2005). These species now 

dominate the flora of at least several alpine and montane Rocky Mountain lakes, with similar 

filed data showing shifts in dominant algal species in other parts of the West. These shifts in the 

dominant algal species show up in Front Range lakes starting in the 1950s (Baron, 2006; Das et 

al., 2005; Enders et al., 2008; Wolfe et al., 2001, 2003). Ambient nitrogen levels associated with 

maximum species diversity for alpine lakes are estimated to be at or <3 micromoles (μmol) 

based on studies in the Yellowstone National Park (Interlandi and Kilham, 1998). A hindcasting 

exercise has concluded that the change in Rocky Mountain National Park lake algae that 

occurred between 1850 and 1964 was associated with an increase in wet nitrogen deposition that 

was only about 1.5 kg N/ha (Baron, 2006). Similar changes inferred from lake sediment cores of 

the Beartooth Mountains of Wyoming also occurred at about 1.5 kg N/ha deposition (Saros et al., 

2003). 

Terrestrial Systems 

Because alpine plant species are typically adapted to low nutrient availability, they often 

are sensitive to effects from nutrient enrichment. The ISA (U.S. EPA, 2008) presents results 

from several studies suggesting that the capacity of Rocky Mountain alpine catchments to 

sequester nitrogen is exceeded at input levels of about 4 kg N/ha/yr (Baron et al., 1994; Williams 

and Tonnessen, 2000). For the Front Range, atmospheric deposition levels are typically 3 to 5 kg 

N/ha/yr, with nitrogen deposition levels of 1 to 2 kg N/ha/yr typical in the areas to the west of the 

Continental Divide (Baron et al., 2000). 

Research on nutrient enrichment effects on alpine and subalpine ecosystems in the 

western U.S. has been limited mainly to studies at the Loch Vale Watershed in Rocky Mountain 

National Park and the Niwot Ridge LTER site, both located east of the Continental Divide in 

Colorado (Burns, 2004). Research has been conducted in this area on both the terrestrial and 

aquatic effects of nutrient enrichment. At these locations, experiments have involved controlled 

fertilization to document the effects on species composition simulating the effects of nitrogen 

atmospheric deposition. Increased cover and total biomass of both grasses and sedges (Carex

spp.) was a common response pattern. 

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Chapter 5 – Nutrient Enrichment 

High elevation alpine terrestrial communities exhibit a relatively low capacity to 

sequester atmospheric deposition of nitrogen because of steep slopes, shallow soils, sparse 

vegetation, short growing season, and other factors (Baron et al., 1994; Williams et al., 1996). 

Results from several studies suggest that the capacity of individual indicator species in Rocky 

Mountain alpine catchments to sequester nitrogen is exceeded at deposition levels of 3-4 kg 

N/ha/yr (Baron et al., 1994; Williams and Tonnessen, 2000). Effects of Nr deposition to alpine 

terrestrial ecosystems in this area could include community-level changes in plants, lichens, and 

mycorrhizae. A variety of species could serve as useful indicators. The changes in plant species 

that occur in response to atmospheric nitrogen deposition in the alpine zone can result in further 

increased leaching of NO3

-

 from the soils, because the plant species favored by higher nitrogen 

supply are often associated with greater rates of nitrogen mineralization and nitrification than the 

preexisting species (Bowman et al., 1993, 2006; Steltzer and Bowman, 1998; Suding et al., 

2006). 

The ISA (U.S. EPA, 2008) presents results from several studies that suggest the capacity 

of Rocky Mountain alpine catchments to sequester nitrogen is exceeded at input levels <3-4 kg 

N/ha/yr (Baron et al., 1994; Williams et al., 1996). Changes in an individual species (Carex 

rupestris and Trisetum spicatum) were estimated to occur at deposition levels near 4 kg N/ha/yr 

(Bowman et al., 2006). Changes in the community, based on the first axis of a detrended 

correspondence analysis, were estimated to occur at deposition levels near 10 kg N/ha/yr. 

(Bowman et al., 2006). In comparison, critical loads for alpine plant communities in Europe are 

5 to 15 kg N/ha/yr (Bobbink, 1998). It is also worth noting that some state agencies have pursued 

the use of critical loads independently to link science and policy in addressing the management 

of natural resources. For instance, in the State of Colorado, critical loads for atmospheric 

nitrogen deposition that were developed for Rocky Mountain National Park (Baron, 2006) are 

being used to develop goals for nitrogen emissions decreases by the State of Colorado, U.S. 

EPA, and NPS. (See “Nitrogen Deposition Reduction Plan” at 

http://www.cdphe.state.co.us/ap/rmnp.html) 

Effects of Nr deposition to alpine terrestrial ecosystems in this area could include 

community-level changes in plants, lichens, and mycorrhizae. A variety of species could serve as 

useful indicators. The ISA (U.S. EPA, 2008) notes that there are difficulties, however, in 

correlating community or indicator species responses exclusively with atmospheric nitrogen 

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Chapter 5 – Nutrient Enrichment 

deposition. In many instances, the confounding influences of climatic change, particularly 

changes in precipitation, cannot be ruled out (Williams et al., 1996; Sherrod and Seastedt, 2001; 

Fenn et al., 2003). 

5.3.7 Ecological Effect Function for Terrestrial Nutrient Enrichment 

There are many factors that determine whether or not an ecological effect occurs in 

response to ambient concentrations of NOx and SOx. These may be ecological or atmospheric 

factors, both of which influence deposition or exposure and the subsequent ecological effects 

(i.e., acidification or nutrient enrichment). In the Terrestrial Nutrient Enrichment Case Study, 

establishing a quantitative linkage between a given ecological indicator and deposition, as 

influenced by the variable ecological factors, was not addressed because deposition was used, 

rather than a traditional environmental indicator, as the direct metric for this GIS analysis of 

ecological response. 

5.3.8 Uncertainty and Variability 

The analyses for the terrestrial nutrient enrichment case study were based on measured 

data and model predictions that each contain a number of areas of uncertainty. For example, 

characterizing NOx and SOx deposition includes uncertainties in monitoring instrumentation and 

measurement protocols, as well as limitations in the spatial extent of existing monitoring 

networks, especially in remote areas. Also, there are no “true” measurements of dry deposition. 

Geographic limitations in monitoring led to reliance on CMAQ model predictions. CMAQ has 

its own uncertainties in model formulation and in the inputs which drive the model’s simulation 

chemistry and transport processes. 

There are also uncertainties associated with the spatial resolutions of the measured and 

modeled data used in this case study, as well as spatial and temporal variability associated with 

measurement and modeling. Uncertainties are associated with gridding the NADP measurements 

to 12 km resolution and the representativeness of 12 km data for characterizing deposition in this 

case study area, particularly for the small sites of CSS as noted below. Specific areas of 

uncertainty associated with this case study of CSS include the following: 

 CSS declines have been observed in the absence of fire when elevated nitrogen levels are 

present; declines have also been observed in the absence of elevated nitrogen, but due to 

fire. Therefore, there is still a need for quantifiable and predictive results to indicate the 

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Chapter 5 – Nutrient Enrichment 

 Many studies allude to a degradation of CSS by assessing species richness and 

abundance, but it is not clear that indicators of CSS ecosystem health have been 

adequately explored. 

 Ongoing CSS experiments are beginning to show changes in CSS in response to elevated 

nitrogen over relatively long periods of time (Allen, personal communication, 2008). The 

incremental process may be occurring more slowly than previous field research 

experiments have lasted, making the reasons for the decline appear variable or 

imperceptible over the duration of a typical study. 

 At this point, CSS is fragmented into many relatively small parcels. The CMAQ 2002 

data is being modeled at 4-km resolution. When these 4-km data become available, there 

may be a better sense of the relationship between the current distribution of CSS and 

atmospheric nitrogen loads and fire threat. 

 Very little research exists regarding the effects of ozone on CSS. Although there is some 

support that ozone is negatively correlated with CSS, the role has yet to be quantified or 

consistently studied (Westman, 1981). 

 There is uncertainty in the relationship between current CSS distribution and the 

changing climate. 

Areas of uncertainty for MCF include the following: 

 The long-term consequences of increased nitrogen on conifers are unclear. 

 The effects of ozone for both MCF and lichens confound the effects of nitrogen. 

 The intermingling of fire and nitrogen cycling require additional research. 

 Research suggests that critical load benchmarks can decrease over time if the nitrogen 

benchmark is exceeded for long periods of time because of decreasing nitrogen 

efficiencies within nitrogen-saturated ecosystems (Fenn et al., 2008). 

 There remains considerable uncertainty in the potential response of soil carbon to 

increases in total reactive nitrogen additions. 

 Although there are uncertainties in the data, models and techniques used for this case 

study, the most applicable measurements and state-of-the-science models were used with 

consideration for data and models’ relative strengths and limitations. 

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Chapter 5 – Nutrient Enrichment 

5.4 CONCLUSIONS 

This chapter has examined the sensitivity and effects of nutrient enrichment on aquatic 

and terrestrial ecosystems, and, although a diverse array of U.S. ecosystems exist, exposure 

levels at which negative effects are observed appear to be generally comparable to levels 

identified in other sensitive U.S. ecosystems (benchmarks range from 1.5 to 30.5 kg N/ha/yr). 

Enrichment benchmarks are also comparable to those found in the Aquatic Acidification and 

Terrestrial Acidification case studies (see Chapter 4). Further consideration of these comparable 

benchmarks can inform the decision-making process for mitigating terrestrial and aquatic 

acidification and enrichment. 

5.5 SUMMARY AND KEY FINDINGS 

Atmospheric nitrogen deposition has been linked quantitatively to negative ecological 

effects from overenrichment of nutrient-sensitive terrestrial and aquatic ecosystems. Although 

some organisms may at first respond positively to nutrient loads, their ability to use additional 

nitrogen may be limited. Overenrichment may lead to excess nitrogen leaching to water, or it 

may lead to shifts in communities to other organisms that are able to utilize higher levels of 

nitrogen. 

5.5.1 Aquatic Nutrient Enrichment 

The role of nitrogen deposition in two mainstem rivers feeding their respective estuaries 

was analyzed to determine if decreases in deposition could influence the risk of eutrophication as 

predicted using the ASSETS EI scoring system in tandem with SPARROW modeling. This 

modeling approach provides a transferrable, intermediate-level analysis of the linkages between 

atmospheric deposition and receiving waters, while providing results on which conclusions could 

be drawn. Future application of the methods to case study areas where atmospheric deposition 

plays a larger role in the nitrogen loading to an estuary will likely provide more tangible results. 

A summary of findings follows: 

 2002 CMAQ/NADP results showed that an estimated 40,770,000 kg of total nitrogen was 

deposited in the Potomac River watershed. SPARROW modeling predicted that 

7,380,000 kg N/yr of the deposited nitrogen reached the estuary (20% of the total load to 

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Chapter 5 – Nutrient Enrichment 

the estuary). The overall ASSETS EI for the Potomac River and Potomac Estuary was 

Bad. 

 A decrease of 78% or more in the 2002 atmospheric deposition load of total nitrogen to 

the watershed might possibly improve the Potomac River and Potomac Estuary ASSETS 

EI score from Bad to Poor. 

 2002 CMAQ/NADP results showed that an estimated 18,340,000 kg of total nitrogen was 

deposited in the Neuse River watershed. SPARROW modeling predicted that 1,150,000 

kg N/yr of the deposited nitrogen reached the estuary (26% of the total load to the 

estuary). The overall ASSETS EI for the Neuse River/Neuse River Estuary was Bad. 

 It was found that the Neuse River/Neuse River Estuary ASSETS EI score could not be 

improved from Bad to Poor with decreases only in the 2002 atmospheric deposition load 

to the watershed. Additional reductions would be required from other nitrogen sources 

within the watershed. 

The small effect achieved from reducing atmospheric deposition in the Neuse River 

watershed is because the total nitrogen loadings to the Neuse River Estuary are dependent on the 

other nitrogen sources in the watershed as estimated with the SPARROW model. A waterbody’s 

response to nutrient loading depends on the magnitude (e.g., agricultural sources have a high 

influence in the Neuse), spatial distribution, and other characteristics of the sources within the 

watershed. 

5.5.2 Terrestrial Nutrient Enrichment 

California CSS and MCF were the focus of the Terrestrial Nutrient Enrichment Case 

Study. GIS analysis supported a qualitative review of past field research to identify ecological 

benchmarks associated with CSS and mycorrhizal communities, as well as MCF’s nutrientsensitive acidophyte lichen communities, fine-root biomass in Ponderosa pine, and leached 

nitrate in receiving waters. These benchmarks, ranging from 3.1 to 17 kg N/ha/yr, were 

compared to 2002 CMAQ/NADP data to discern any associations between atmospheric 

deposition and changing communities. Evidence supports the finding that nitrogen alters CSS 

and MCF. Key findings include the following: 

 2002 CMAQ/NADP nitrogen deposition data show that the 3.3 kg N/ha/yr benchmark 

has been exceeded in more than 93% of CSS areas (654,048 ha). These deposition levels 

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Chapter 5 – Nutrient Enrichment 

are a driving force in the degradation of CSS communities. Although CSS decline has 

been observed in the absence of fire, the contributions of deposition and fire to the CSS 

decline require further research. CSS is fragmented into many small parcels, and the 2002 

CMAQ/NADP 12-km grid data are not fine enough to fully validate the relationship 

between CSS distribution, nitrogen deposition, and fire. 

 2002 CMAQ/NADP nitrogen deposition data exceeds the 3.1 kg N/ha/yr benchmark in 

more than 38% (1,099,133 ha) of MCF areas, and nitrate leaching has been observed in 

surface waters. Ozone effects confound nitrogen effects on MCF acidophyte lichen, and 

the interrelationship between fire and nitrogen cycling requires additional research. 

Ecological effects have also been documented across the United States where elevated 

nitrogen deposition has been observed (See Appendix 7, Figure 1.1-1.). On the eastern slope of 

the Rocky Mountains, shifts in dominant algal species in alpine lakes have occurred where wet 

nitrogen deposition was only about 1.5 kg N/ha/yr. High alpine terrestrial communities have a 

low capacity to sequester nitrogen deposition, and monitored deposition exceeding 3 to 4 kg 

N/ha/yr could lead to community-level changes in plant species, lichens, and mycorrhizae. 

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Chapter 6 – Additional Effects 

6.0 ADDITIONAL EFFECTS 

The Clean Air Act (CAA) definition of welfare effects includes, but is not limited to, 

effects on soils, water, wildlife, vegetation, visibility, weather, and climate, as well as effects on 

man-made materials, economic values, and personal comfort and well-being. This Risk and 

Exposure Assessment focuses primarily on ecological effects resulting from current deposition 

of compounds containing nitrogen and sulfur as discussed in Chapter 1 and Chapter 2. 

Acidification (from both sulfur and nitrogen) and nutrient enrichment (from nitrogen) are the 

central ecological effects addressed in this Risk and Exposure Assessment (see Chapters 4 and 

5). The additional welfare effects addressed in this chapter include the influence of sulfur oxides 

(SOx) deposition effects on mercury methylation, nitrous oxide (N2O) effects on climate, 

deposition effects of nitrogen oxides (NOx) on biogenic greenhouse gas (GHG) fluxes, and 

phytotoxic effects on plants. While a quantitative assessment of these important effects is beyond 

the scope of this review, this chapter will evaluate them qualitatively. 

6.1 VISIBILITY, CLIMATE, AND MATERIALS 

It is well understood that impairment of visibility, effects on climate, and materials 

damage can result from atmospheric particulate matter (PM), which is composed in part of 

sulfate (SO4

2-)- and nitrate (NO3 ̄)-based particulates (i.e., ammonium sulfate [(NH4)2SO4 ] and 

ammonium nitrate [NH4NO3]). The relationship between PM and visibility impairment has been 

well established in previous National Ambient Air Quality Standards (NAAQS) reviews dating 

back as early as the 1982 Air Quality Criteria for Particulate Matter and Sulfur Oxides (PM/SOx

Air Quality Criteria Document [AQCD]) document (U.S. EPA, 1982b). Visibility impairment is 

caused by light scattering and absorption by suspended particles and gases. There is strong and 

consistent evidence that PM is the overwhelming source of visibility impairment in both urban 

Final Risk and Exposure Assessment 6-1 September 2009 
Chapter 6 – Additional Effects 

and remote areas. Furthermore, it has been acknowledged that decreases in visibility can 

adversely affect transportation safety, property values, aesthetics, and people’s overall sense of 

well being. PM can also have effects on climate, including both direct effects on radiative 

forcing and indirect effects that involve cloud feedbacks that influence precipitation formation 

and cloud lifetimes. In addition to atmospheric effects, the deposition of PM has been shown to 

result in materials damage, such as accelerated corrosion of metal, erosion, soiling of paint, and 

soiling of buildings and other structures. Because these effects are largely considered to be PM 

effects, they are being addressed in detail in the PM NAAQS review currently underway (See 

http://www.epa.gov/ttn/naaqs/standards/pm/s_pm_index.html for documents related to that 

review). 

6.1.1 Nitrous Oxide 

N2O has not been considered in setting previous nitrogen dioxide (NO2) NAAQS. In the 

first NOx review, N2O was not considered an air contaminant because there was “no evidence to 

suggest N2O is involved in photochemical reactions in the lower atmosphere” (U.S. EPA, 1971). 

Nitrous oxide was addressed in both the 1982 and 1993 Air Quality Criteria for Oxides of 

Nitrogen (NOx AQCD) documents (U.S. EPA, 1982a, 1993). In 1982, it was described as one of 

the eight nitrogen oxides that may be present in the ambient air, but “not generally considered a 

pollutant.” The effect of N2O on stratospheric ozone was described, and the 1982 NOx AQCD 

noted that N2O may cause a small decrease in stratospheric ozone (U.S. EPA, 1982a). Finally, 

the 1982 NOx AQCD concluded that N2O significantly contributes to the atmospheric 

greenhouse effect by trapping outgoing terrestrial radiation, and that although the issue was 

being investigated, many years of research were still needed to assess the issue reliably (U.S. 

EPA, 1982a). The 1993 NOx AQCD also identified N2O as an oxidized nitrogen compound that 

is not generally considered to be an air pollutant, but it does have an impact on stratospheric 

ozone and is considered to be among the more significant GHGs (U.S. EPA, 1993). Although not 

considered within the scope of the previous review, these documents clearly considered N2O to 

be within the scope of the listed nitrogen oxides’ criteria for pollutants. 

The Integrated Science Assessment (ISA) for Oxides of Nitrogen and Sulfur–Ecological 

Criteria (Final Report) (ISA) (U.S. EPA, 2008, Section 2.2) acknowledges that N2O is a potent 

GHG and discusses N2O sources and emissions in the United States, as well as the 

Final Risk and Exposure Assessment 6-2 September 2009 
Chapter 6 – Additional Effects 

biogeochemistry of N2O’s microbial-mediated production via denitrification and nitrification in 

natural ecosystems. Based on the current U.S. GHG inventory (U.S. EPA, 2007b), N2O 

contributes approximately 6.5% to total GHG emissions (in carbon dioxide [CO2] equivalents) 

(Figure 6.1-1). 

Figure 6.1-1. Percentage of total U.S. emissions of greenhouse gases 

in CO2 equivalents (U.S. EPA, 2007b). 

Since the definition of “welfare effects” includes effects on climate [CAA Section 

302(h)], N2O is included within the scope of this review. However, it is most appropriate to 

analyze the role of N2O in anthropogenic climate change in the context of all of the GHGs. 

Because such an analysis is outside the scope of this review, it will not be a quantitative part of 

this assessment. 

Although the atmospheric concentration of N2O (319 parts per billion in 2005) is much 

lower than CO2 (379 parts per million in 2005), its global warming potential per molecule is 296 

times that of CO2. Human activities have increased the atmospheric concentration of N2O by 

18% since preindustrial times (IPCC, 2007). 

6.2 SULFUR AND MERCURY METHYLATION 

Behavioral, reproductive, neurochemical, and hormonal effects due to mercury have been 

demonstrated in fish and in piscivorous mammals and birds (U.S. EPA, 1996; Scheuhammer 

et al., 2007). Methylmercury has been shown to be the mercury compound that accumulates in 

the tissues of affected fish and piscivorous species (Becker and Bigham, 1995; Bloom, 1992; 

Harris et al., 2003; Scheuhammer et al., 2007). The production of the large majority of 

methylmercury is mediated by sulfate-reducing bacteria (SRB), and changes in SO4

2- deposition 

have resulted in changes in both mercury methylation and mercury concentrations in fish. 

Final Risk and Exposure Assessment 6-3 September 2009 
Chapter 6 – Additional Effects 

6.2.1 Science Background 

Current evidence indicates that in 

watersheds where mercury is present, 

increased SOx deposition very likely results 

in methylmercury accumulation in fish 

(Munthe et al, 2007; Drevnick et al., 2007). 

The ISA (U.S. EPA, 2008, Sections 3.4.1 

and 4.5) states that mercury is a highly neurotoxic 

contaminant that enters the food web as a 

methylated compound, methylmercury. The 

contaminant is concentrated in higher trophic levels, including fish eaten by humans. 

Experimental evidence has established that only inconsequential amounts of methylmercury can 

be produced in the absence of SO4

2-. Many variables influence how much mercury accumulates 

in fish, but elevated mercury levels in fish can only occur where substantial amounts of 

methylmercury are present. Current evidence indicates that in watersheds where mercury is 

present, increased SOx deposition, specifically SO4

2-, very likely results in methylmercury 

accumulation in fish (Drevnick et al., 2007; Munthe et al, 2007). 

Establishing the quantitative relationship between SO4

2- and mercury methylation in 

natural settings is difficult because of the presence of multiple interacting factors in aquatic and 

terrestrial environments, including wetlands, where SO4

2-, SRBs, and mercury are present. The 

amount of methylmercury produced by bacteria varies with oxygen content, temperature, pH, 

and supply of labile organic carbon. When these interacting factors are outside of the ranges 

most favorable for methylation, increasing levels of SO4

2- deposition will not increase the 

amount of methylmercury in the aquatic environment. For example, effects on mercury 

methylation in high-altitude lakes in the Western United States have been recorded with changes 

in SO4

2- deposition, where some of those interacting factors were also outside of the ranges most 

favorable for methylation (U.S. EPA, 2008, Sections 3.4 and 4.5). Watersheds with conditions 

known to be conducive to mercury methylation have been identified in the northeastern United 

States and southeastern Canada (Chen et al., 2005; Evers et al., 2007; Scheuhammer and 

Blancher, 1994; Scheuhammer et al., 2007), but watersheds with elevated methylmercury levels 

observed in water or in fish are seen in most of the continental United States, where conditions 

have not been fully characterized. 

Several interrelated factors seem to affect mercury uptake in fish, including low lakewater pH, dissolved organic carbon, and suspended PM concentrations in the water column 

(Driscoll et al., 1994; Grieb et al., 1990; Kamman et al., 2004; Mierle and Ingram, 1991; Suns 

Final Risk and Exposure Assessment 6-4 September 2009 
Chapter 6 – Additional Effects 

and Hitchin, 1990; U.S. EPA, 1996). For example, a lower pH can increase the ability of 

methylmercury to permeate fish membranes and speed the rate of uptake, thus increasing 

mercury residues in fish (Weiner et al., 2003). In addition, phosphorus and nitrogen can be 

important as these factors regulate aquatic productivity and, thus, mercury concentrations in 

aquatic organisms (Driscoll et al., 2007). The proportion of upland to wetland land area within a 

watershed, as well as wetland type and annual water yield, also appears to be important (St. 

Louis et al., 1996). Figure 6.2-1 shows the process of mercury methylation in an aquatic 

environment. 

Figure 6.2-1. The mercury cycle in an ecosystem (USGS, 2006). 

6.2.2 Qualitative Analysis 

The role of atmospherically deposited sulfur species in mercury methylation varies 

greatly across ecosystems. Field studies have determined that the majority of mercury 

methylation occurs within anoxic waters and sediments (Gilmour et al., 1998; Hammerschmidt et 

Final Risk and Exposure Assessment 6-5 September 2009 
Chapter 6 – Additional Effects 

al., 2004; Watras et al., 1995); however, several studies have observed that quantitative 

prediction of mercury methylation is impeded by the presence of multiple known interacting 

factors whose influence on methylation has not been quantified. These include types of SRB, 

sulfur species, mercury species, pH, organic acids, and other factors (Benoit et al., 2003; 

Gilmour et al., 1992; Langer et al., 2001; Munthe et al., 2007; Watras and Morrison, 2008). 

Methylation via iron-reducing bacteria has also been observed in anoxic, iron-rich sediments; 

however, this process is not well understood and appears to be less extensive than the SRBmediated mercury methylation (Fleming et al., 2006; Kerin et al., 2006). 

Methyl mercury output by SRBs is a by-product of the conversion of SO4

2- to sulfide 

(Benoit et al., 2003; Branfireun et al., 1999; Compeau and Bartha, 1985; Gilmour et al., 1992). In 

general, the rate of methylmercury generation depends on the factors that affect SRB propagation 

and activity, the availability of inorganic mercury, and the demethylation of mercury. The 

introduction of SO4

2- to SRB in the presence of divalent mercury (Hg+2), usually in low oxygen 

sediments, leads to the following biomediated transformation: 

 (1) 

The presence of SO4

2-, inorganic mercury, and SRB are, thus, the primary requirements 

for bacterially mediated sulfate-reducing mercury conversion. Additional factors affecting 

conversion include the presence of anoxic conditions, temperature, the presence and types of 

organic matter, the presence and types of mercury-binding species, and watershed effects (e.g., 

watershed type, land cover, waterbody limnology, runoff loading). Demethylation, which 

involves aerobic and anaerobic microbial processes, as well as sunlight-dependent processes 

(e.g., photodemethylation), can also have a substantial effect; therefore, increased methylation in 

natural environments should be understood as increased net mercury methylation (Benoit et al., 

2003). 

The role of SO4

2- in mercury methylation has been confirmed through a series of 

independent and interdependent studies. As noted in the ISA, early studies on Little Rock Lake, 

WI, first observed the link between sulfur enrichment, acidification, and methylmercury 

concentrations (Hrabik and Watras, 2002). Other important studies include Branfireun et al. 

Final Risk and Exposure Assessment 6-6 September 2009 
Chapter 6 – Additional Effects 

(1999) and Jeremiason et al. (2006). The beneficial effect of decreased SO4

2- deposition on fish 

tissue methylmercury concentrations has also recently been observed in an isolated Lake 

Superior ecosystem, where fish tissue concentrations fell below fish consumption advisory levels 

in the absence of any change in atmospheric mercury deposition (Drevnick et al., 2007). Other 

studies have focused on the biogeochemical process of mercury cycling to determine factors that 

are responsible for the link between methylmercury and acidification. Early research by Faust 

and Osman (1981) estimated that 90% to 99% of the total mercury concentration in surface 

waters was associated with sediment. With regard to methylmercury, the highest concentrations 

in the environment generally occur at or near the sedimentary surface, below the oxic–anoxic 

boundary. The formation of methylmercury has also been associated with macrophytic 

vegetation and periphyton (Mauro et al., 2002). Mercury methylation rate and organic carbon 

substrates (e.g., acetate, lactate) may fluctuate when associated with the presence of SRB and 

environmental conditions (Mitchell et al., 2008). Figure 6.2-2 illustrates the general SRB 

methylation process. It should be noted that mercury can also be supplied from sediments. 

Although mercury methylation can occur within the water column, there is generally a far 

greater contribution of mercury methylation from sediments because of anoxia and of greater 

concentrations of SRB, substrate, and SO4

2-. The conditions within sediment pores and 

conditions affecting sediment porewater may, therefore, play a key role in mercury methylation. 

The relative contribution of methylmercury from porewater in the surficial sediment layer is 

dependent on the size of the hypolimnic anoxic zone, the location of the bacterioplankton 

activity, and several other factors, such as temperature, organic carbon content, and the presence 

of sulfides (Watras et al., 1995). 

Final Risk and Exposure Assessment 6-7 September 2009 
Chapter 6 – Additional Effects 

Figure 6.2-2. Biogeochemical process of mercury methylation. 

6.2.2.1 Watershed Influences 

Methylmercury production generally 

increases with increasing proportion of 

wetlands in the area contributing to 

surface water systems (Benoit et al., 

2003; Watras and Morrison, 2008). 

The effect of watersheds on methylmercury production is dependent on many factors 

(e.g., dissolved organic carbon, temperature, anoxia, SO4

2-); however, watershed influences also 

include physical, chemical, and ecological variables that, in turn, have an impact on those 

factors; they include land cover, precipitation response, 

hydrology, nutrient loading, and limnology. Watershed 

influences may also play a role in the uptake of 

methylmercury into fish and other aquatic species. 

Land cover and land use affect the transport of chemical species, such as mercury, 

nutrients, and dissolved organic carbon. Methylmercury production generally increases with 

increasing proportion of wetlands in the contributing area to surface water systems (Benoit et al., 

2003; Watras and Morrison, 2008). In general, wetland environments tend to promote mercury 

methylation because of increased anoxic environments, fresh organic matter, moderated 

temperature, and macrophytic environments for bacterial activity (Back et al., 2002). 

Additionally, increased forest cover and mixed agriculture have been correlated with increased 

mercury methylation in downstream surface waters, presumably due to organic matter (Driscoll 

et al., 2007; Krabbenhoft et al., 1999). Land disturbance may also contribute to increased 

mercury methylation downstream by increasing erosion and, therefore, the mobility of mercury 

and organic matter (Driscoll et al., 2007). 

Final Risk and Exposure Assessment 6-8 September 2009 
Chapter 6 – Additional Effects 

Final Risk and Exposure Assessment 6-9 September 2009 

There were 3,080 fish consumption 

advisories in the United States in 

2006, with 48 states, one territory, 

and two tribes having mercury 

advisories. 

State-level fish consumption advisories for 

mercury are based on state criteria, many of which are 

based on EPA’s fish tissue criterion for methylmercury at 

0.3 microgram per gram (μg/g) or on U.S. Food and Drug 

Administration action limits of 1.0 mg/kg, equal to 1ppm by weight. Fish tissue concentrations 

of methylmercury at this level or above are extremely unlikely to be observed without substantial 

methylating activity in the watershed affected. There were 2,436 fish consumption advisories 

across the United States in 2004; 2,682 in 2005; and 3,080 in 2006. Forty-eight states, one 

territory, and two tribes issued mercury advisories in 2006. Eighty percent of all fish 

consumption advisories have been issued, at least in part, because of mercury. In 2006, a total of 

14,177,175 lake acres and 882,963 river miles were under advisory for mercury (U.S. EPA, 

2007a). Figure 6.2-3 summarizes the spatial distribution patterns by state for documented fish 

consumption advisory listings.
Chapter 

Figure 6.2-3. Distribution pattern in 2006 for state fish consumption advisory listings (U.S. EPA, 2007a)

Final Risk and Exposure Assessment 6-10 
Chapter 6 – Additional Effects 

6.2.2.2 Conclusions 

The ISA concluded that evidence is sufficient to infer a casual relationship between 

sulfur deposition and increased mercury methylation in wetlands and aquatic environments. 

Specifically, there appears to be a relationship between SO4

2- deposition and mercury 

methylation; however, the rate of mercury methylation varies according to several spatial and 

biogeochemical factors whose influence has not been fully quantified (see Figure 6.2-4).

Therefore, the correlation between SO4

2- deposition and methylmercury could not be quantified 

for the purpose of interpolating the association across waterbodies or regions. Nevertheless, 

because changes in methylmercury in ecosystems represent changes in significant human and 

ecological health risks, the association between sulfur and mercury cannot be neglected (U.S. 

EPA, 2008, Sections 3.4.1 and 4.5). 

Figure 6.2-4. Spatial and biogeochemical factors influencing methylmercury production. 

As research evolves and the computational capacity of models expands to meet the 

complexity of mercury methylation processes in ecosystems, the role of interacting factors may 

be better parsed out to identify ecosystems or regions that are more likely to generate higher 

Final Risk and Exposure Assessment 6-11 September 2009 
Chapter 6 – Additional Effects 

concentrations of methylmercury. Figure 6.2-5 illustrates the type of current and forwardlooking research being developed by the U.S. Geological Survey (USGS) to synthesize the 

contributing factors of mercury and to develop a map of sensitive watersheds. The mercury score 

referenced in Figure 6.2-5 is based on SO4

2- concentrations, acid neutralizing capacity (ANC), 

levels of dissolved organic carbon and pH, mercury species concentrations, and soil types to 

gauge the methylation sensitivity (Myers et al., 2007). 

It is evident that decreases in 

sulfate deposition will likely 

result in decreases in 

methylmercury concentration. 

Interdependent biogeochemical factors preclude the 

existence of simple sulfate-related mercury methylation 

models (see Figure 6.2-4). It is clear that decreasing sulfate 

deposition is likely to result in decreased methylmercury concentrations. Future research may 

allow for the characterization of a usable sulfate-methylmercury response curve; however, no 

regional or classification calculation scale can be created at this time because of the number of 

confounding factors. 

Figure 6.2-5. Preliminary USGS map of mercury methylation–sensitive watersheds 

derived from more than 55,000 water quality sites and 2,500 watersheds 

(Myers et al., 2007). 

Final Risk and Exposure Assessment 6-12 September 2009 
Chapter 6 – Additional Effects 

Decreases in SO4

2- deposition have already shown promising reductions in 

methylmercury. Observed decreases in methylmercury fish tissue concentrations have been 

linked to decreased acidification and declining SO4

2- and mercury deposition in Little Rock 

Lake, WI (Hrabik and Watras, 2002), and to decreased SO4

2- deposition in Isle Royale in Lake 

Superior, MI (Drevnick et al., 2007). Although the possibility exists that reductions in SO4

2-

emissions could generate a pulse in methylmercury production because of decreased sulfide 

inhibition in sulfate-saturated waters, this effect would likely involve a limited number of U.S. 

waters (Harmon et al., 2007). Also, because of the diffusion and outward flow of both mercurysulfide complexes and SO4

2-, increased mercury methylation downstream may still occur in 

sulfate-enriched ecosystems with increased organic matter and/or downstream transport 

capabilities. 

Remediation of sediments heavily contaminated with mercury has yielded significant 

reductions of methylmercury in biotic tissues. Establishing quantitative relations in biotic 

responses to methylmercury levels as a result of changes in atmospheric mercury deposition, 

however, presents difficulties because direct associations can be confounded by all of the factors 

discussed in this section. Current research does suggest that the levels of methylmercury and 

total mercury in ecosystems are positively correlated, so that reductions in mercury deposited 

into ecosystems would also eventually lead to reductions in methylmercury in biotic tissues. 

Ultimately, an integrated approach that involves the reduction of both sulfur and mercury 

emissions may be most efficient because of the variability in ecosystem responses. Reducing SOx 

emissions could have a beneficial effect on levels of methylmercury in many waters of the 

United States. This will be addressed, as appropriate, in the policy assessment portion of this 

review. 

6.3 NITROGEN ADDITION EFFECTS ON PRIMARY PRODUCTIVITY 

AND BIOGENIC GREENHOUSE GAS FLUXES 

6.3.1 Effects on Primary Productivity and Carbon Budgeting 

This section discusses the mechanisms by which atmospheric nitrogen deposition alters 

productivity and carbon sequestration in all nonagricultural ecosystems in the United States for 

which data is available. Rates of photosynthesis and net primary productivity (NPP) of 

ecosystems typically correlate with metrics of nitrogen availability (Field and Mooney, 1986; 

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Chapter 6 – Additional Effects 

Reich et al., 1997a, 1997b; Smith et al., 2002) along with other factors. The addition of nitrogen 

from an exogenous source will alter the productivity of nitrogen-limited ecosystems. In a metaanalysis that included terrestrial, freshwater, and marine ecosystems, Elser et al. (2007) found 

that there were similar patterns of nitrogen and phosphorus limitation among ecosystem types. 

This finding is in contrast with the existing paradigm that nitrogen-limitation dominates in 

terrestrial and marine ecosystems, and phosphorus-limitation dominates in freshwater 

ecosystems. 

It is important to distinguish between effects on primary productivity and effects on 

carbon sequestration. Nitrogen addition to a given ecosystem may increase primary productivity. 

In some ecosystems, especially forests, this causes increased carbon sequestration (U.S. EPA, 

2008, Section 3.3.3.1). However, in other ecosystems (e.g., tundra and wetlands) carbon lost 

from the ecosystem by respiration (i.e., heterotrophic + autotrophic) may offset the carbon 

gained by production. For example, a long-term nitrogen fertilization study in an arctic tundra 

ecosystem found that nitrogen addition increased aboveground plant production and carbon 

accumulation in the upper organic soil layer. However, nitrogen addition also stimulated soil 

carbon decomposition in the lower organic layer and in mineral soil. The carbon loss from the 

lower soil layer offset the carbon accumulation in biomass and the upper soil layer and caused a 

net ecosystem carbon loss (Mack et al., 2004). Similarly, Bragazza et al. (2006) investigated 

peatlands across a gradient of nitrogen deposition levels and found higher atmospheric nitrogen 

deposition resulted in higher carbon loss by increasing heterotrophic respiration and dissolved 

organic carbon leaching. 

6.3.1.1 Terrestrial Ecosystems 

Productivity 

Experimental nitrogen additions to forest ecosystems have elicited positive growth 

responses in some, but not all, organisms (DeWalle et al., 2006; Elvir et al., 2003; Emmett, 1999; 

Högberg et al., 2006). A meta-analysis by LeBauer and Treseder (2008) of 126 nitrogen addition 

studies showed that most ecosystems are nitrogen-limited with an average increase of 29% in 

aboveground growth response to nitrogen. The response ratio was significant within temperate 

forests, tropical forests, temperate grasslands, tropical grasslands, wetlands, and tundra, but not 

within deserts (LeBauer and Treseder, 2008). 

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Chapter 6 – Additional Effects 

Multiple long-term forest experiments have demonstrated transient growth increases 

followed by increased mortality, especially at higher rates of fertilization (Elvir et al., 2003; 

Högberg et al., 2006; Magill and Aber, 2004; McNulty et al., 2005). Forest growth enhancement 

can potentially exacerbate other nutrient deficiencies, such as calcium, magnesium, or potassium 

(K+

). An additional line of evidence comes from the experimental nitrogen removal studies: 

removal of nitrogen and sulfur from throughfall increased tree growth in Europe (Beier et al., 

1995; Boxman et al., 1998). 

Caspersen et al. (2000) found little evidence for growth enhancement due to nitrogen 

deposition after evaluating tree growth rates in five states (i.e., Minnesota, Michigan, Virginia, 

North Carolina, and Florida). Magnani et al. (2007) reported a strong positive correlation 

between estimated average long-term net ecosystem productivity (Levine et al., 1999) and 

estimated 1990 nitrogen wet deposition (Holland et al., 2005) for 20 forest stands mostly in 

Western Europe and the conterminous United States, although there have been critiques of the 

method and the magnitude of these reported effects (De Schrijver et al., 2008; De Vries et al., 

2008; Sutton et al., 2008). 

Nitrogen deposition can affect the patterns of carbon allocation between aboveground 

and belowground production. Increased nitrogen availability increases the shoot-to-root ratio, 

which can be detrimental to the plant because of decreased resistance to environmental stressors, 

such as drought and windthrow (Braun et al., 2003; Fangmeier et al., 1994; Krupa, 2003; 

Minnich et al., 1995). Nitrogen saturation also leads to the replacement of slow-growing sprucefir forest stands by fast-growing deciduous forests that cycle nitrogen more rapidly (McNulty et 

al., 1996; 2005). In the western United States, atmospheric nitrogen deposition has been shown 

to cause increased litter accumulation and carbon storage in aboveground woody biomass, which 

in turn may lead to increased susceptibility to more severe fires (Fenn et al., 2003). 

Carbon Sequestration 

Nitrogen addition stimulates aboveground plant growth in most ecosystems (LeBauer and 

Treseder, 2008), which may in turn increase carbon sequestration in plant biomass. This is 

observed for many forest ecosystems (U.S. EPA, 2008, Section 3.3.3). On the other hand, 

nitrogen deposition may alter autotrophic and heterotrophic respiratory losses of carbon from 

ecosystems. When the respiratory loss is stimulated by nitrogen, it will offset some proportion of 

the gains made by increasing productivity (U.S. EPA, 2008, Section 3.3.3). For example, it is 

Final Risk and Exposure Assessment 6-15 September 2009 
Chapter 6 – Additional Effects 

known that nitrogen deposition increases the concentration of nitrogen in leaf tissue, and 

autotrophic maintenance respiration is positively correlated with tissue nitrogen content (Reich 

et. al., 2008).Carbon loss by heterotrophic respiration may be increasing in some ecosystems, 

while decreasing in others. The increased nitrogen availability could favor microbial 

decomposition by removing nitrogen constrains on microbial metabolism and stimulating soil 

organic carbon (SOC) decomposition, as observed in nitrogen-limited peat bogs and tundra 

(Mack et al., 2004; Bragazza et al., 2006). However, decomposition studies conducted in a forest 

ecosystem showed that higher litter nitrogen could stabilize soil organic carbon by fostering 

humus formation in the late decomposition stage (Berg and Laskowski, 2006). Because of the 

complexity of interactions between nitrogen and carbon cycling, the effects of nitrogen on 

carbon budgets (quantified input and output of carbon to the ecosystem) are variable. 

Many nitrogen fertilization studies have investigated the effect of nitrogen addition on 

ecosystem carbon sequestration. Adams et al. (2005) examined whether nitrogen fertilization 

affects carbon sequestration of four Douglas-fir plantation sites in the Pacific Northwest. Those 

sites were initially established as part of the Regional Forest Nutrition Research Project 

(RFNRP) and received either three or four additions of 224 kilograms (kg) nitrogen(N)/hectare 

(ha) as urea (672 to 896 kg N/ha total) over 16 years. They found that the nitrogen-fertilized sites 

(161 megagrams [Mg] C/ha) had an average of 20% more carbon in the aboveground tree 

biomass compared to unfertilized sites (135 Mg C/ha), and nitrogen-fertilized soils (260 Mg 

C/ha) had 48% more soil carbon compared to unfertilized soils (175 Mg C/ha). Canary et al. 

(2000) studied carbon sequestration of another three RFNRP sites. They also found that nitrogen 

fertilization, a total of 896 to 1120 kg N/ha over a 16-year-period, increased carbon sequestration 

of Douglas-fir plantations. However, the response magnitudes were smaller than those reported 

by Adams et al. (2005). Nitrogen fertilization increased tree biomass carbon by 19% (200.2 Mg 

C/ha for control, and 238.6 Mg C/ha for nitrogen fertilized site) and soil carbon by 6.2% (123 

Mg C/ha for control, and 131 Mg C/ha for nitrogen fertilized site). 

In the ISA (U.S. EPA, 2008, Section 3.3.3.1), a meta-analysis was conducted of 17 

observations from nine studies in U.S. forests to examine the effect of nitrogen fertilization on 

forest ecosystem carbon content (EC). In that study, EC was defined as the sum of carbon 

content of vegetation, forest floor, and soil (Johnson et al., 2006). Details on those publications, 

including study site, ecosystem type, nitrogen addition level, chemical form of nitrogen, and 

Final Risk and Exposure Assessment 6-16 September 2009 
Chapter 6 – Additional Effects 

experimental condition, appear in Annex C of the ISA (U.S. EPA, 2008). To avoid possible 

confounded variability caused by site conditions, this meta-analysis only included studies of 

those control and treatment sites that experienced the same climatic, soil, and vegetation 

conditions. The EPA meta-analysis revealed that while there was a great deal of variation in 

response, overall nitrogen addition, ranging from 25 to 200 kg N/ha/yr, increased EC by 6% for 

U.S. forest ecosystems. Different from Magnani et al. (2007), this study did not find any 

correlation between the amount of nitrogen addition and the response magnitudes of ecosystem 

carbon sequestration. 

Less is known regarding the effects of nitrogen deposition on carbon budgets of nonforest ecosystems. The EPA meta-analysis, including 16 observations from nine publications, 

showed that nitrogen addition from 16 to 320 kg N/ha/yr has no significant effect on net 

ecosystem exchange (NEE) of nonforest ecosystems (U.S. EPA, 2008, Sections 3.3.3.1 and 

4.3.1.1). Details on those publications, including study site, ecosystem type, nitrogen addition 

level, chemical form of nitrogen, and experimental condition, are given in Annex C of the ISA 

(U.S. EPA, 2008). 

ISA Conclusion 

The evidence is sufficient to 

infer a causal relationship 

between nitrogen deposition and 

the alteration of biogeochemical 

cycling of carbon in terrestrial 

ecosystems. 

The ISA (U.S. EPA, 2008, Section 4.3.1.1) concluded 

that the evidence is sufficient to infer a causal relationship

between nitrogen deposition and the alteration of 

biogeochemical cycling of carbon in terrestrial ecosystems. 

Nitrogen is often the most limiting nutrient to growth in ecosystems. Nitrogen deposition thus 

often increases primary productivity; thereby altering the biogeochemical cycling of carbon. 

Nitrogen deposition can cause changes in ecosystem carbon budgets. However, whether nitrogen 

deposition increases or decreases, ecosystem carbon-sequestration remains unclear. The metaanalysis conducted for the ISA indicated that nitrogen addition, ranging from 25 to 200 kg 

N/ha/yr, slightly increased ecosystem carbon content in forest ecosystem. However, nitrogen 

addition, ranging from 16 to 320 kg N/ha/yr, had no significant effect on NEE for nonforest 

ecosystems. 

In terrestrial ecosystems, nitrogen deposition can accelerate plant growth and change 

carbon allocation patterns (e.g. shoot-to-root ratio), which can increase susceptibility to severe 

fires, drought, and wind damage. These effects have been studied in the western United States 

Final Risk and Exposure Assessment 6-17 September 2009 
Chapter 6 – Additional Effects 

and Europe (Adams et. al., 2005; Braun et. al., 2003; Canary et. al., 2000; Fenn et. al., 2003). 

The alteration of primary productivity can also alter competitive interactions among plant 

species. The increase in growth is greater for some species than for others, leading to possible 

shifts in population dynamics, species composition, community structure, and, in a few 

instances, ecosystem type. 

6.3.1.2 Wetland Ecosystems 

Productivity 

The 1993 NOx AQCD (U.S. EPA, 1993) reported that nitrogen applications, ranging from 

7 to 3120 kg N/ha/yr, stimulated standing biomass production in wetlands by 6% to 413%. The 

magnitude of the changes in primary production depended on soil nitrogen availability and 

limitation of other nutrients. However, negative growth rates were observed for some wetland 

species that were adapted to low-nitrogen environments. For example, increasing nitrogen 

availability reduced population growth of Sarracenia purpurea (commonly known as the Purple 

pitcher plant or Side-saddle flower). Gotelli and Ellison (2002) reported that the extinction risk 

of S. purpurea within the next 100 years increased substantially if nitrogen deposition rate 

increased (1% to 4.7%) from the rate of 4.5 to 6.8 kg N/ha/yr. A study of Sphagnum fuscum

(Rusty peat moss) in six Canadian peatlands showed a weak, although significant, negative 

correlation between NPP and nitrogen deposition when deposition levels were greater than 3 kg 

N/ha/yr (y = 150 – 3.4(x); r2

=0.01, p = 0.04) (Vitt et al., 2003).

Carbon Sequestration 

The evidence is sufficient to 

infer a causal relationship 

between nitrogen deposition and 

the alteration of biogeochemical 

cycling of carbon in transitional 

ecosystems. 

In the ISA (U.S. EPA, 2008, Sections 4.3.1.1 and 

4.3.2.1), a meta-analysis was conducted that included 

wetlands with other nonforest ecosystems, and the results 

indicated no effect of nitrogen deposition on overall NEE of 

carbon. In other words, any gain in carbon capture by photosynthesis was offset by ecosystem 

respiration and carbon leaching. There were not enough studies to evaluate wetlands as a 

separate category. A study of 23 ombrotrophic peatlands in Canada with deposition levels 

ranging from 2.7 to 8.1 kg N/ha/yr showed that peat accumulation increases linearly with 

nitrogen deposition; however, in recent years this rate has begun to slow, indicating limited 

Final Risk and Exposure Assessment 6-18 September 2009 
Chapter 6 – Additional Effects 

capacity for nitrogen to stimulate accumulation (Turunen et al., 2004). Soil respiration has been 

studied in European countries under a natural gradient of atmospheric nitrogen deposition from 2 

to 20 kg N/ha/yr. It was found that enhanced decomposition rates for material accumulated under 

higher atmospheric nitrogen supplies resulted in higher CO2 emissions and dissolved organic 

carbon release (Bragazza et al. 2006). 

ISA Conclusion 

The ISA (U.S. EPA, 2008, Section 4.3.2.1) concluded that the evidence is sufficient to 

infer a causal relationship between nitrogen deposition and the alteration of biogeochemical 

cycling of carbon in transitional ecosystems. Nitrogen deposition often increases ecosystem 

productivity of wetlands, but it also leads to negative population growth rates of some wetland 

species that were adapted to low-nitrogen environments. 

There was little evidence for an apparent effect on ecosystem carbon sequestration on 

wetlands. 

6.3.1.3 Aquatic Ecosystems 

Productivity 

In a meta-analysis of more than 600 experiments, Elser et al. (2007) found that nitrogen 

limitation occurs frequently in freshwater ecosystems, in contrast to the traditional paradigm that 

freshwater ecosystems are mainly phosphorus-limited. Numerous other studies have also 

provided strong evidence indicating that nitrogen deposition has played an important role in 

influencing the productivity of oligotrophic, high-elevation lakes in the western United States 

and Canada, as well as in the Canadian Arctic (Das et al., 2005; Lafrancois et al., 2003; Saros et 

al., 2005; Wolfe et al., 2001, 2003, 2006). A comprehensive study of available data from the 

northern hemisphere surveys of lakes along gradients of nitrogen deposition showed increased 

inorganic nitrogen concentrations and productivity to be correlated with atmospheric nitrogen 

deposition (Bergström and Jansson, 2006).

Estuaries and coastal waters tend to be nitrogen-limited and are, therefore, inherently 

sensitive to increased atmospheric nitrogen loading (D’Elia et al., 1986; Elser et al., 2007; 

Howarth and Marino, 2006). There is a strong scientific consensus that nitrogen is the principal 

Final Risk and Exposure Assessment 6-19 September 2009 
Chapter 6 – Additional Effects 

cause of coastal eutrophication in the United States (see the Aquatic Nutrient Enrichment Case 

Study in Chapter 5 and Appendix 6 of this Risk and Exposure Assessment; NRC, 2000). 

Carbon Sequestration 

Little information is reported regarding the effects of nitrogen deposition on carbon 

budgets of freshwater, estuarine, and near coastal ecosystems. 

ISA Conclusion 

The evidence is sufficient to 

infer a causal relationship 

between nitrogen deposition and 

the alteration of biogeochemical 

cycling of carbon in aquatic 

ecosystems. 

The ISA (U.S. EPA, 2008, Section 4.3.3) concluded 

that the evidence is sufficient to infer a causal relationship

between nitrogen deposition and the alteration of 

biogeochemical cycling of carbon in aquatic ecosystems. The 

productivity of many freshwater ecosystems is nitrogen-limited. Nitrogen deposition can alter 

species assemblages and cause eutrophication of aquatic ecosystems where nitrogen is the 

growth-limiting nutrient. In estuarine ecosystems, nitrogen from atmospheric and 

nonatmospheric sources contributes to increased phytoplankton and algal productivity, leading to 

eutrophication. 

Ecosystem carbon sequestration is determined by the difference between input (net 

carbon fixed by photosynthesis) and output (autotrophic and heterotrophic respiration). Although 

many studies have shown nitrogen increases productivity in aquatic ecosystems, there is a 

limited understanding on how nitrogen affects NEE or ecosystem respiration of aquatic 

ecosystems. Quantification of how nitrogen deposition increases or decreases carbon 

sequestration of freshwater, estuarine, and near-coastal ecosystems remains unclear. 

6.3.2 Biogenic Emissions of Nitrous Oxide 

6.3.2.1 Science Overview 

Nitrous oxide emissions from the United States are currently thought to be dominated by 

agricultural (managed) soils (>75%; U.S. EPA, 2008); however, it is important to note that this 

value does not include non-managed ecosystem emissions. Emissions from forests are thought to 

be >1%; however, at this point the United States, national emissions inventory does not calculate 

N2O emissions from wetlands and rivers, which could be substantial. Total U.S. biogenic 

emissions from managed and non-managed systems have yet to be calculated. Globally, biogenic 

Final Risk and Exposure Assessment 6-20 September 2009 
Chapter 6 – Additional Effects 

sources are the dominant contributors (>90%) to atmospheric N2O. Terrestrial soil is the largest 

source of atmospheric N2O, accounting for 60% of global emissions (IPCC, 2001). Nitrous oxide 

production in soil is mainly governed by microbial nitrification and denitrification (Dalal et al., 

2003). The contribution of each process to total N2O production varies with environmental 

conditions. Denitrifying bacteria reduce NO3 ̄or nitrite (NO2 ̄) into N2O or nitrogen (N2) under 

anaerobic conditions. In submerged soils, such as wetland soil, denitrification should be the 

dominant process to N2O emissions (Conrad, 1996). Increasing NO3 ̄ input generally increases 

the denitrification rate under suitable conditions of temperature and organic carbon supply. High 

soil NO3 ̄ concentrations also inhibit the reduction of N2O to N2 and result in a high N2O/N2 ratio 

(Dalal et al., 2003). Under aerobic environments, autotrophic nitrifying bacteria obtain energy by 

reducing ammonium (NH4

+

). Nitrous oxide is an intermediate product of the oxidation of NH4

+

to NO2 ̄ or the decomposition of NO2 ̄. The increase in N2O emissions following NH4

+

 addition 

has been observed in many laboratory and field experiments (Aerts and De Caluwe, 1999; Aerts 

and Toet, 1997; Keller et al., 2005). 

EPA conducted a meta-analysis, including 99 observations from 30 publications, to 

evaluate the effects of nitrogen addition on N2O emissions from nonagricultural ecosystems 

(U.S. EPA, 2008, Section 3.3.4.2). Details on those publications, including study site, ecosystem 

type, nitrogen addition level, chemical form of nitrogen, and experimental condition appear in 

Annex C of the ISA (U.S. EPA, 2008). Overall, the results of the meta-analysis indicated that 

nitrogen addition, ranging from 10 to 562 kg N/ha/yr, increased N2O emissions by 230% 

(statistically significant) across all ecosystems. Ecosystem type, chemical form of nitrogen, and 

nitrogen addition level affected the response magnitude of N2O emissions. Compared to other 

ecosystems, tropical forests emitted more N2O under nitrogen enrichment condition (+735%). 

However, this difference was only significant between tropical and coniferous forests. NO3 ̄ 

caused a higher stimulation (+494%) of N2O emissions than NH4

+ did (+95%). Although the 

mean response ratio increased with the amount of nitrogen addition, the differences among the 

three levels (<75, 75–150, and >150 kg N/ha/yr) were not significant. 

There were no clear dose-response relationships between GHG emission/uptake and the 

amount of nitrogen addition to nonagricultural ecosystems, a result consistent with observations 

in agricultural ecosystems (FAO/IFA, 2001). However, Butterbach-Bahl et al. (1998) found that 

increasing NH4

+

 wet deposition led to a linear increase in N2O emissions and a decrease in CH4

Final Risk and Exposure Assessment 6-21 September 2009 
Chapter 6 – Additional Effects 

oxidation at a red spruce forest site. The dose-response relationship was observed at a small scale 

characterized by homogenous conditions (such as a specific site), in contrast to the large 

heterogeneous scale investigated in the EPA meta-analysis. This inconsistency is likely caused 

because GHG production is influenced by multiple interactions of soil, climate, and vegetation 

(IPCC, 2001). 

6.3.2.2 ISA Conclusion 

The evidence is sufficient to 

infer a causal relationship 

between total reactive nitrogen 

deposition and (a) the alteration 

of biogeochemical flux of N2O in 

terrestrial ecosystems and (b) 

N2O flux in wetland ecosystems. 

The ISA concluded that the reviewed evidence is

sufficient to infer a causal relationship between total reactive 

nitrogen deposition and the alteration of N2O emissions from 

terrestrial ecosystems (U.S. EPA, 2008, Section 4.3.1.1). 

Averaged across 80 observations from terrestrial ecosystems, 

the meta-analysis conducted by EPA indicated that nitrogen addition, ranging from 10 to 562 kg 

N/ha/yr, increased N2O emissions by 215% in terrestrial ecosystems. The response of N2O 

emissions to nitrogen addition for coniferous forest, deciduous forest, and grasslands was 

statistically significant. 

The ISA also concluded that the evidence reviewed was sufficient to infer a causal 

relationship between total reactive nitrogen deposition and the alteration of N2O flux in wetland 

ecosystems (U.S. EPA, 2008, Section 4.3.2.1). Averaged across 19 observations from wetland 

studies, the meta-analysis conducted by EPA indicated that nitrogen addition, ranging from 15.4 

to 300 kg N/ha/yr, increased wetland N2O production by 207% (U.S. EPA, 2008, Section 

4.3.2.1). 

6.3.3 Methane Emissions and Uptake 

6.3.3.1 Science Overview 

Atmospheric methane (CH4) originates mainly (70% to 80%) from biogenic sources (Le 

Mer and Roger, 2001). Methane is produced in an anaerobic environment by methanogenic 

archaea (a type of single-celled organism) bacteria during decomposition of organic matter. Once 

produced in soil, CH4 can then be released to the atmosphere or oxidized by methanotrophic 

bacteria in the aerobic zone (Le Mer and Roger, 2001). Methane production and oxidation 

processes occur simultaneously in most ecosystems. Wetland soils are generally CH4 sources, 

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Chapter 6 – Additional Effects 

accounting for about 20% of global CH4 emissions. Nonflooded upland soils are the most 

important biological sink for CH4, consuming about 6% of the atmospheric CH4 (Le Mer and 

Roger, 2001). Numerous studies have demonstrated that nitrogen is an important regulatory 

factor for both CH4 production and oxidation (Bodelier and Laanbroek, 2004). 

The evidence is sufficient to infer a 

causal relationship between 

nitrogen deposition and the 

alteration of biogeochemical flux of 

CH4 in terrestrial ecosystems and 

the alteration of CH4 flux in 

wetland ecosystems. 

The EPA conducted a meta-analysis, including 61 observations from 27 publications, to 

evaluate the relationship between nitrogen addition and CH4 flux. Details on those publications, 

including study site, ecosystem type, nitrogen addition 

level, chemical form of nitrogen, and experimental 

condition, appear in Annex C of the ISA (U.S. EPA, 

2008). The impacts of nitrogen addition on CH4 source 

and sink strength were estimated by CH4 emissions and 

CH4 uptake, respectively. 

Nitrogen addition, ranging from 30 to 240 kg N/ha/yr significantly increased CH4

emissions by 115% when averaged across all ecosystems. Methane uptake was significantly 

reduced by 38% under nitrogen addition, ranging from 10 to 560 kg N/ha/yr. Methane uptake 

was reduced for all investigated ecosystems (i.e., coniferous forest, deciduous forest, grassland, 

and drained wetland), but this inhibition was significant only for coniferous and deciduous 

forests, with a reduction of 28% and 45%, respectively. 

Several studies found that CH4 uptake rates decreased with increasing nitrogen input 

(Butterbach-Bahl et al., 1998; King and Schnell, 1998; Schnell and King, 1994). However, this 

meta-analysis did not find significant correlation between the amount of nitrogen addition and 

the response ratio of CH4 uptake/emission. The lack of a dose-response relationship likely 

occurred because CH4 production is influenced by multiple interactions of soil nitrogen content, 

soil moisture, pH, and temperature (Le Mer and Roger, 2001), and varies greatly over small 

spatial and temporal scales (IPCC, 2007). 

6.3.3.2 ISA Conclusion 

The ISA (U.S. EPA, 2008, Section 4.3.1.1) concluded that the evidence is sufficient to 

infer a causal relationship between nitrogen deposition and the alteration of biogeochemical flux 

of CH4 in terrestrial ecosystems. Averaged across 41 observations from terrestrial ecosystems, 

including four forms of nitrogen (NH4

+

, NO3 ̄, NH4NO3, and urea) and the addition rates, ranging 

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Chapter 6 – Additional Effects 

from 10 to 560 kg N/ha/yr, the meta-analysis conducted by EPA indicated that nitrogen addition 

reduced CH4 uptake, but this inhibition was significant only for coniferous and deciduous forests 

(U.S. EPA, 2008, Section 4.3.1.1). 

The ISA (U.S. EPA, 2008, Section 4.3.2.1) also concluded that the evidence is sufficient 

to infer a causal relationship between nitrogen deposition and the alteration of CH4 flux in 

wetland ecosystems. Wetlands are generally net sources of CH4, but some wetlands can be net 

sinks, depending on environmental conditions such as drainage and vegetation (Crill et al., 1994; 

Saarnio et al., 2003). A meta-analysis was performed on a dataset of 17 observations to assess 

the effects of nitrogen additions on wetland CH4 fluxes. This dataset included four forms of 

nitrogen (NH4

+

, NO3 ̄, NH4NO3, and urea) and the addition rates ranged from 30 to 240 kg 

N/ha/yr. The results indicated that nitrogen addition increased CH4 production from the wetlands 

but had no significant effect on CH4 uptake of wetlands (U.S. EPA, 2008, Section 4.3.2.1). 

In conclusion, nitrogen addition to ecosystems can affect primary productivity and 

biogenic GHG fluxes. Due to the complexity of interactions between nitrogen and carbon 

cycling, the effects of nitrogen on carbon budgets (i.e., quantified input and output of carbon to 

the ecosystem) are variable. Nitrogen deposition can affect the patterns of carbon allocation 

because most growth occurs aboveground, and nitrogen deposition also has been found to alter 

biogeochemical cycling of carbon in transitional ecosystems, such as wetlands, and in aquatic 

ecosystems. Causal relationships also exists between total reactive nitrogen deposition and (a) 

the alteration of biogeochemical flux of N2O in terrestrial and wetland ecosystems and (b) the 

alteration of biogeochemical flux of CH4 in terrestrial and wetland ecosystems. 

6.3.4 Emission Factors 

By adapting the methodology of the Intergovernmental Panel on Climate Change (IPCC) 

guidelines (Mosier et al., 1998), a nitrogen addition-induced GHG emission/uptake factor (F) 

can be estimated by the following equation: 

= − CN /)( NGGF (2) 

where 

GN is annual flux of GHG from fertilized treatment (kg carbon or kg N/ha/yr) 

GC is annual flux of GHG from control (kg carbon or kg N/ha/yr) 

N is annual nitrogen input (kg N/ha/yr). 

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Chapter 6 – Additional Effects 

A dataset of nitrogen effects on GHG emissions from ecosystems around the world was 

developed for the EPA ecosystem carbon content (EC), N2O, and CH4 meta-analyses (U.S. EPA, 

2008, Section 4.3). Using this dataset, emission/uptake factors were calculated for the three 

GHGs. Only field studies that measured growing season or annual GHG fluxes were included in 

that calculation. Averaged across nitrogen addition treatments ranging from 25 to 200 kg 

N/ha/yr, the estimated carbon uptake factor (same as C:N response ratio) is 24.5± 8.7 kg CO2-

C/ha/yr per 1 kg N/ha/yr added to forest ecosystem (n=14), which is much lower than a C:N 

response of 175 to 225:1 reported by Magnani et al. (2008), but close to the C:N response ratio 

of 40:1 reported by Högberg (2007) and the C:N response ratio of 50 to 75:1 reported by Sutton 

et al. (2008). Averaged across nitrogen addition treatments ranging from 10 to 450 kg N/ha/yr, 

the mean N2O emissions increased by 0.0087 ± 0.0025 kg N2O-N/ha/yr per 1 kg N/ha/yr added 

to the natural ecosystem (n=42), which is comparable to the default N2O emission factor of 

0.0125 kg N2O-N/ha/yr for agricultural field given by IPCC (2000). Averaged across nitrogen 

addition treatments ranging from 10 to 450 kg N/ha/yr, the mean CH4 uptake decreased by 

0.015±0.004 kg CH4-C/ha/yr per 1 kg N/ha/yr added to the ecosystem (n=23). There are no 

emission factors published for which to compare this number. The emission factor for CH4 was 

not calculated because there were few field studies that investigated growing season or annual 

CH4 emissions under nitrogen addition. 

6.3.5 Uncertainty 

There is substantial evidence that nitrogen addition causes altered rates of biogenic GHG 

flux. However, there are limitations to the application of these data to calculate nitrogen 

deposition effects on net GHG fluxes for the United States. The first obstacle is that ecosystems 

are heterogeneous across the United States and clear dose-response curves are not available for 

large heterogeneous landscapes. Micrometeorological factors, including temperature, soil 

moisture, and precipitation, can vary substantially between ecosystems across the large spatial 

area of the United States. These factors influence the microbial response to nitrogen addition and 

introduce variation into the dose-response relationship. Another way to evaluate nitrogen effect 

on GHG flux is by emission factors (see Section 6.3.4 of this chapter). Emission factors are 

calculated by combining data from a range of nitrogen addition levels to produce one quantified 

rate. This method is a coarse evaluation that introduces several uncertainties: (1) the range of 

Final Risk and Exposure Assessment 6-25 September 2009 
Chapter 6 – Additional Effects 

nitrogen addition by studies that are included if the emission factor exceeds those which would 

be caused by deposition, and (2) the emission factor does not take into account how shifting 

micrometeorology causes variation in flux rates. 

6.4 DIRECT PHYTOTOXIC EFFECTS OF GASEOUS SOX AND NOX 

The current secondary NAAQS for SOx and NOx were set to protect against direct 

damage to vegetation by the gaseous forms of these pollutants. Uptake of these gaseous 

pollutants in a plant canopy is a complex process involving adsorption to surfaces (leaves, stems, 

and soil) and absorption into leaves. These pollutants penetrate into leaves through to the 

stomata, although there is evidence for limited pathways via the cuticle. Pollutants must be 

transported from the bulk air to the leaf boundary layer in order to get to the stomata. The entry 

of gases into a leaf is dependent upon the physical and chemical processes of gas phase and 

surfaces as well as the stomatal aperture. The aperture of the stomata is controlled largely by the 

prevailing environmental conditions, such as humidity, temperature, and light intensity. When 

the stomata are closed, as occurs under dark or drought conditions, resistance to gas uptake is 

very high and the plant has a very low degree of susceptibility to injury. In contrast, mosses and 

lichens do not have a protective cuticle barrier to gaseous pollutants or stomates and are 

generally more sensitive to gaseous sulfur and nitrogen than vascular plants (U.S. EPA, 2008). 

Outlined below are the effects of the major SOx and NOx gases that have phytotoxic 

effects on vegetation. 

6.4.1 SO2

Currently, SO2 is the only criteria pollutant with a secondary NAAQS distinct from the 

primary standard. This standard is intended to protect acute foliar injury resulting from SO2

exposure. The standard is a 3-hour average of 0.50 ppm and was promulgated in 1970 to protect 

against acute foliar injury in vegetation. The last AQCD for ecological effects of SOx was 

completed in 1982 and concluded that controlled experiments and field observations supported 

retaining this secondary standard (U.S. EPA, 1971, 1982a, 1982c). 

Acute foliar injury usually happens with hours of exposure, involves a rapid absorption of 

a toxic dose, and involves collapse or necrosis of plant tissues. Another type of visible injury is 

termed chronic injury and is usually a result of variable SO2 exposures over the growing season. 

The appearance of foliar injury can vary significantly between species and growth conditions 

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Chapter 6 – Additional Effects 

affecting stomatal conductance. Currently, no regular monitoring occurs for SO2 foliar injury 

effects in the United States. 

Besides foliar injury, long-term lower SO2 concentrations can result in reduced 

photosynthesis, growth, and yield of plants. These effects are cumulative over the season and are 

often not associated with visible foliar injury. As with foliar injury, these effects vary among 

species and growing environment. SO2 is also considered to be the primary factor causing the 

death of lichens in many urban and industrial areas, with fruticose lichens being more susceptible 

to SO2 than many foliose and crustose species (Hutchinson et al., 1996). Damage caused to 

lichens in response to SO2 exposure includes reduced photosynthesis and respiration, damage to 

the algal component of the lichen, leakage of electrolytes, inhibition of nitrogen fixation, reduced 

K+ absorption, and structural changes (Belnap et al., 1993; Farmer et al., 1992; Hutchinson et al., 

1996). The 1982 SOx AQCD summarized the concentration-response information available at the 

time (U.S. EPA, 1982b). Effects on growth and yield of vegetation were associated with 

increased SO2 exposure concentration and time of exposure. However, that document concluded 

that more definitive concentration-response studies were needed before useable exposure metrics 

could be identified. 

Because of decreases in ambient SO2 concentrations and focus on O3 vegetation effects 

research, few studies have emerged to better inform a metric and levels of concern for effects of 

SO2 on growth and productivity of vegetation. The few new studies published since the 1982 

SOx AQCD continue to report associations between exposure to SO2 and reduced vegetation 

growth. However, the majority of these studies have been performed outside the United States 

and at levels well above ambient concentrations observed in the United States. In light of limited 

new data, there is little evidence of phytotoxic effects on vegetation below the level of the 

current standard. However, the current evidence to date supports the appropriateness of the 

current standard level to protect vegetation from phytotoxic effects at higher exposure levels. 

6.4.2 NO, NO2, and Peroxyacetyl Nitrate (PAN) 

It is well known that in sufficient concentrations, NO, NO2, and PAN can have phytotoxic 

effects on plants through decreasing photosynthesis and induction of visible foliar injury 

(U.S. EPA, 1993). However, the 1993 NOx AQCD concluded that concentrations of NO, NO2,

and PAN in the atmosphere are rarely high enough to have phytotoxic effects on vegetation 

Final Risk and Exposure Assessment 6-27 September 2009 
Chapter 6 – Additional Effects 

(U.S. EPA, 1993). The current ISA (U.S. EPA, 2008, Section 3.4) stated that very little new 

research has been done on these phytotoxic effects at concentrations currently observed in the 

United States. 

The functional relationship between ambient concentrations of NO or NO2 and a specific 

plant response, such as foliar injury or growth, is complex. Factors such as inherent rates of 

stomatal conductance and detoxification mechanisms and external factors, including plant water 

status, light, temperature, humidity, and the particular pollutant exposure regime, all affect the 

amount of a pollutant needed to cause symptoms of foliar injury. Plant age and growing 

conditions, and experimental exposure techniques also vary widely among reports of 

experimental exposures of plants to NO2. An analysis conducted in the 1993 NOx AQCD of over 

50 peer-reviewed reports on the effects of NO2 on foliar injury indicated that plants are relatively 

resistant to NO2, especially in comparison to foliar injury caused by exposure to O3 (U.S. EPA, 

1993). With few exceptions, visible injury was not reported at concentrations below 0.20 ppm, 

and these occurred when the cumulative duration of exposures extended to 100 hours or longer. 

Reductions in rates of photosynthesis have also been recorded in experimental exposures of 

plants to both NO and NO2, but usually at concentrations significantly higher than would 

normally be encountered in ambient air (U.S. EPA, 2008). 

Since the 1993 NOx AQCD was completed, the current ISA (U.S. EPA, 2008) found 

most new research on NO2 exposure to vegetation has taken place in Europe and other areas 

outside the United States. For example, foliar nitrate (NO3

-

) reductase activity was increased in 

Norway spruce (Picea abies) trees growing near a highway with average exposures of about 

0.027 ppm compared to trees growing 1,300 meters away from the highway with NO2 exposures 

less than 0.005 ppm (Ammann et al., 1995). This was consistent with other studies on Norway 

spruce in the field and laboratory (Von Ballmoos et al., 1993; Thoene et al., 1991). Muller et al. 

(1996) found that the uptake rate of NO3

-

 by roots of Norway spruce seedlings was decreased by 

the exposure to 0.1 ppm of NO2 for 48 hours. Similarly, soybean plants grown in Australia had 

decreased NO3

-

 uptake by roots and reduced growth of plants exposed to 1.1 ppm of NO2 for 7 

days (Qiao and Murray, 1998). In a Swiss study, poplar cuttings exposed to 0.1 ppm of NO2 for 

approximately 12 weeks resulted in decreased stomatal density and increased specific leaf 

weight, but did not result in other effects such as leaf injury or a change in growth (GunthardtGoerg et al., 1996). However, NO2 enhanced the negative effects of ozone on these poplars, 

Final Risk and Exposure Assessment 6-28 September 2009 
Chapter 6 – Additional Effects 

including leaf injury, when the pollutants were applied in combination (Gunthardt-Goerg et al., 

1996). 

Peroxyacetyl nitrate (PAN) is a well-known photochemical oxidant, which has been 

shown to cause injury to vegetation (See reviews by Cape, 2003, 1997; Kleindienst, 1994; Smidt, 

1994; Temple and Taylor, 1983). Acute foliar injury symptoms resulting from exposure to PAN 

are generally characterized as a glazing, bronzing, or silvering of the underside of the leaf 

surface; some sensitive plant species include spinach, Swiss chard, lettuces, and tomatoes. 

Petunias have also been characterized as sensitive to PAN exposures and have been used as 

bioindicators of in areas of Japan (Nouchi et al., 1984). Controlled experiments have also shown 

significant negative effects on the net photosynthesis and growth of petunia (Petunia hybrida L.) 

and kidney bean (Phaseolus vulgaris L.) after exposure of 30 ppb of PAN for four hours on each 

of three alternate days (Izuta et al., 1993). As mentioned previously, it is known that oxides of 

nitrogen, including PAN, could be altering the nitrogen cycle in some ecosystems, especially in 

the western United States, and contributing nitrogen saturation (Bytnerowicz and Fenn, 1996; 

Fenn et al., 2003, see Section 3.3). However, PAN is a very small component of nitrogen 

deposition in most areas of the United States. Although PAN continues to persist as an important 

component of photochemical pollutant episodes, there is little evidence in recent years 

suggesting that PAN poses a significant risk to vegetation in the United States (U.S. EPA, 2008). 

6.4.3 Nitric Acid (HNO3)

Relatively little is known about the direct effects of HNO3 vapor on vegetation. However, 

the current ISA (U.S. EPA, 2008) highlighted recent research identifying HNO3 as the cause for 

decline of sensitive lichen species in areas with relatively high HNO3 deposition. Further, HNO3

has a very high deposition velocity compared to other NOx pollutants and may be an important 

source of nitrogen for plants (Hanson and Lindberg, 1991; Hanson and Garten, 1992; Vose and 

Swank, 1990). This deposition could contribute to nitrogen saturation of some ecosystems near 

sources of photochemical smog (Fenn et al., 1998). For example, in mixed conifer forests 

(MCFs) of the Transverse Range (i.e., Los Angeles basin mountain ranges), HNO3 has been 

estimated to provide 60 percent of all dry deposited nitrogen (Bytnerowicz et al., 1999). 

HNO3 deposition has been suspected as the cause of a dramatic decline in lichen species 

in the Los Angeles basin (Nash and Sigal, 1999). This suggestion was strengthened by an 

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Chapter 6 – Additional Effects 

experiment that transplanted Ramalina lichen species from clean air habitats (Mount Palomar 

and San Nicolas Island) to analogous polluted habitats in the Los Angeles basin and repeatedly 

observed death of the lichens over a few weeks in the summer (Boonpragob and Nash, 1991). 

Associated with this death was massive accumulation of H+

 and NO3

−

 by the lichen thalli 

(bodies) (Boonpragob et al., 1989). Recently, Riddell et al. (2008) exposed the healthy Ramalina 

menziesii thalli to moderate (8–10 ppb) and high (10–14 ppb) HNO3 concentrations in monthlong fumigations and reported a significant decline in chlorophyll content and carbon exchange 

capacity compared to thalli in control chambers. Thalli treated with HNO3 showed visual signs 

of bleaching and were clearly damaged and dead by day 28. The damage may have occurred 

through several mechanisms including acidification of pigments and cell membrane damage 

(Riddell et al., 2008). The authors concluded that Ramalina menziesii has an unequivocally 

negative response to the HNO3 concentrations common to ambient summer conditions in the Los 

Angeles air basin and that it is very likely that HNO3 has contributed to the disappearance of this 

sensitive lichen species from the Los Angeles air basin, as well as other locations with arid 

conditions and high HNO3 deposition loads (Riddell et al., 2008). 

At high ambient concentrations, HNO3 can also cause damage to vascular plants (U.S. 

EPA, 2008). Seedlings of ponderosa pine and California black oak subjected to short-term 

exposures from 50–250 ppb of HNO3 vapor for 12 hours showed deterioration of the pine needle 

cuticle in light at 50 ppb (Bytnerowicz et al., 1998a). Oak leaves appeared to be more resistant to 

HNO3 vapor, however, with 12-hour exposures in the dark at 200 ppb producing damage to the 

epicuticular wax structure (Bytnerowicz et al., 1998a). The observed changes in wax chemistry 

caused by HNO3 and accompanying injury to the leaf cuticle (Bytnerowicz et al., 1998a) may 

predispose plants to damage by various environmental stresses such as drought, pathogens, and 

other air pollutants. Because elevated concentrations of HNO3 and ozone co-occur in 

photochemical smog (Solomon et al. 1988), synergistic interactions between the two pollutants 

are possible (Bytnerowicz et al., 1998b). It should be noted that the experiments described above 

were observed at relatively short-term exposures at above ambient concentrations of HNO3. 

Long-term effects of lower air concentrations that better approximate ambient HNO3

concentrations should be investigated. 

Final Risk and Exposure Assessment 6-30 September 2009 
Chapter 6 – Additional Effects 

6.5 SUMMARY AND KEY FINDINGS 

This Risk and Exposure Assessment focused on acidification and nutrient enrichment as 

welfare effects; however, additional effects have been documented. For example, in 1982, EPA 

acknowledged that particulate species of nitrates can reduce visibility. Also, materials damage 

such as corrosion, erosion, and soiling of paint and buildings has also been long documented. 

Both visibility and materials damage are being addressed in the PM NAAQS review in progress. 

The ISA concluded that, based on research evidence, a causal relationship can be inferred 

between sulfur deposition (as sulfate, SO4

2-) and increased mercury methylation in wetlands and 

aquatic environments. However, because the rate of methylation varies spatially and with 

biogeochemical factors, the correlation of sulfate deposition and methyl mercury could not be 

quantified for the purpose of interpolating the association across waterbodies or regions. The 

evidence indicates that decreases in sulfate deposition will likely result in decreases in methyl 

mercury concentration which is important given that in 2006, there were 3,080 fish consumption 

advisories for mercury in the United States, including 48 states, one territory, and two tribes. 

USGS mapping of mercury methylation-sensitive watersheds is underway as a means to better 

understand the extent of sensitivity. 

Nitrous oxide (N2O) has not been considered in setting previous NO2 NAAQS; however, 

the current ISA acknowledges that N2O is a potent GHG, contributing 6.5% of total U.S. GHG 

emissions (in CO2 equivalents). Although the Clean Air Act definition of “welfare effects” 

includes effects on climate, it is most appropriate to analyze the role of N2O in the context of all 

of the GHGs. Therefore, it was not part of this Risk and Exposure Assessment. 

The ISA concludes that the evidence is sufficient to infer a causal relationship between 

nitrogen deposition and the alteration of biogeochemical cycling of carbon in terrestrial, 

transitional, and aquatic ecosystems. Biogenic GHG fluxes, including N2O and CH4, are 

acknowledged in the ISA as being altered by nitrogen deposition in terrestrial and wetland 

ecosystems. There are no clear dose-response relationships between N addition and biogenic 

GHG fluxes, mainly due to the heterogeneity of ecosystems across the United States. 

Finally, SOx and NOx gases have different degrees of phytotoxic effects on vegetation. A 

unique secondary NAAQS exists for SO2 to protect against acute foliar injury, but it was 

determined in 1993 that concentrations of NO, NO2, and PAN are rarely high enough to have 

phytotoxic effects on vegetation; therefore, no unique secondary standard exists. Relatively little 

Final Risk and Exposure Assessment 6-31 September 2009 
Chapter 6 – Additional Effects 

is known about the direct effects of HNO3 vapor on vegetation, however, recent research on the 

decline of sensitive lichen species was highlighted in the ISA. HNO3 also has a very high 

deposition velocity and may be an important source of nitrogen to plants. In the Transverse 

Range’s MCF, HNO3 has been estimated to provide 60% of all dry deposited nitrogen, and it has 

been suspected as the cause of a dramatic decline in lichen species. At high concentrations over 

the short-term, HNO3 can damage vascular plants such as seedlings of ponderosa pine and 

California black oak. More research is needed to determine long-term exposure effects at lower 

concentrations. 

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U.S. EPA (Environmental Protection Agency). 1971. Air Quality Criteria for Nitrogen Oxides. 

No. AP-84. U.S. Environmental Protection Agency, Air Pollution Control Office, 

Washington, DC. January. 

U.S. EPA (Environmental Protection Agency) 1982a. Air Quality Criteria for Oxides of 

Nitrogen. EPA-600/8-82-026. U.S. Environmental Protection Agency, Office of Research 

and Development, National Center for Environmental Assessment, Washington, DC. 

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U.S. EPA (Environmental Protection Agency). 1982b. Air Quality Criteria for Particulates and 

Sulfur Oxides. Volume 1. EPA-600/8-82-029a. U.S. Environmental Protection Agency, 

Office of Air Quality Planning and Standards, Research Triangle Park, NC. December. 

U.S. EPA (Environmental Protection Agency). 1982c. Review of the National Ambient Air 

Quality Standards for Sulfur Oxides: Assessment of Scientific and Technical Information;

OAQPS staff paper. (Report no. EPA-450/5-82-007). Research Triangle Park, NC, Office 

of Air Quality Planning and Standards, U.S. Environmental Protection Agency. 

U.S. EPA (Environmental Protection Agency). 1993. Air Quality Criteria for Oxides of 

Nitrogen. EPA/600/8-91/049aF-cF. 3v. U.S. Environmental Protection Agency, Office of 

Health and Environmental Assessment, Environmental Criteria and Assessment Office, 

Research Triangle Park, NC. 

U.S. EPA (Environmental Protection Agency). 1996. Air Quality Criteria for Ozone and Related 

Photochemical Oxidants. EPA/600/AP-93/004aF-cF. 3v. U.S. Environmental Protection 

Agency, Office of Research and Development, Research Triangle Park, NC. Available at 

http://cfpub2.epa.gov/ncea. 

U.S. EPA (Environmental Protection Agency). 2007a. National Listing of Fish Advisories 

Technical Fact Sheet: 2005/06 National Listing Fact Sheet. EPA-823-F-07-003. U.S. 

Environmental Protection Agency, Office of Water, Washington, DC. Available at 

http://www.epa.gov/waterscience/fish/advisories/2006/tech.html. 

U.S. EPA (Environmental Protection Agency). 2007b. The U.S. Inventory of Greenhouse Gas 

Emissions and Sinks: Fast Facts. EPA 430-F-07-004. U.S. Environmental Protection 

Agency, Office of Atmospheric Programs, Washington, DC. April. 

U.S. EPA (Environmental Protection Agency). 2008. Integrated Science Assessment (ISA) for 

Oxides of Nitrogen and Sulfur–Ecological Criteria (Final Report). EPA/600/R08/082F. U.S. Environmental Protection Agency, National Center for Environmental 

Assessment–RTP Division, Office of Research and Development, Research Triangle 

Park, NC. Available at http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=201485. 

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USGS (U.S. Geological Survey). 2006. Investigations and Monitoring of Mercury in Indiana by 

the U.S. Geological Survey. U.S. Department of the Interior, U.S. Geological Survey, 

Indiana Water Science Center, Indianapolis, IN. Available at 

http://in.water.usgs.gov/mercury. 

Vitt, D.H., K. Wieder, L.A. Halsey, and M. Turetsky. 2003. Response of Sphagnum fuscum to 

nitrogen deposition: A case study of ombrogenous peatlands in Alberta, Canada. 

Bryologist 106:235–245. 

Von Ballmoos, P., S. Nussbaum, and C. Brunold. 1993. The relationship of nitrate reductase 

activity to uptake and assimilation of atmospheric 15NO2-nitrogen in needles of Norway 

Spruce (Picea abies [L.] Karst.). Isotopes in Environmental and Health Studies 29:59–70. 

Vose, J.M., and W.T. Swank. 1990. Preliminary estimates of foliar absorption of 15 N-labeled 

nitric acid vapor (HNO3) by mature eastern white pine (Pinus strobus). Canadian Journal 

of Forest Research 20:857–860. 

Watras, C.J., and K.A. Morrison. 2008. The response of two remote, temperate lakes to changes 

in atmospheric mercury deposition, sulfate, and the water cycle. Canadian Journal of 

Fisheries and Aquatic Sciences 65:100–116. 

Watras, C.J., K.A. Morrison, J.S. Host, and N.S. Bloom. 1995. Concentration of mercury species 

in relationship to other site-specific factors in the surface waters of northern Wisconsin 

lakes. Limnology and Oceanography 40:556–565. 

Wiener, J.G., D.P. Krabbenhoft, G.H. Heinz, and A.M. Scheuhammer. 2003. Ecotoxicology of 

mercury. Pp. 409–643 in Handbook of Ecotoxicology. 2nd edition. Edited by D.J. 

Hoffman, B.A. Rattner, G.A. Burton, and J. Cairns. Boca Raton, FL: CRC Press.

Wolfe, A.P., J.S. Baron, and R.J. Cornett. 2001. Anthropogenic nitrogen deposition induces 

rapid ecological changes in alpine lakes of the Colorado Front Range (USA). Journal of 

Paleolimnology 25:1–7. 

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Final Risk and Exposure Assessment 6-49 September 2009 

Wolfe, A.P., A.C. Van Gorpe, and J.S. Baron. 2003. Recent ecological and biogeochemical 

changes in alpine lakes of Rocky Mountain National Park (Colorado, USA): A response 

to anthropogenic nitrogen deposition. Geobiology 1:153–168. 

Wolfe, A.P., C.A. Cooke, and W.O. Hobbs. 2006. Are current rates of atmospheric nitrogen 

deposition influencing lakes in the eastern Canadian Arctic? Arctic, Antarctic, and Alpine 

Research 38:465–476. 

Chapter 7 – Synthesis and Integration of Case Study Results 

7.0 SYNTHESIS AND INTEGRATION OF CASE STUDY 

RESULTS 

This chapter synthesizes the case study analyses associated with each targeted effect area 

by identifying the strengths, limitations, and uncertainties associated with the available data, 

modeling approach, and relationship between the selected ecological indicator and atmospheric 

deposition as described by the ecological effect function. The known data gaps and research 

needs associated with each targeted effect area are also identified. As noted in Chapter 2, there 

are different levels of uncertainty associated with the relationships between deposition, 

ecological effects, and ecological indicators. In addition, extrapolating from a case study area to 

a larger assessment area introduces additional uncertainty and potential error that needs to be 

addressed. Understanding the nature, sources, and importance of these uncertainties will help 

inform the standard-setting process. The Intergovernmental Panel on Climate Change (IPCC) 

Fourth Assessment Report (IPCC, 2007) addresses uncertainty across many disciplines and from 

diverse approaches using language associated with both qualitative and quantitative uncertainty 

that is based on expert judgment and statistical analysis. A similar approach will be used here, 

adapted specifically to the analyses covered in this review. 

For this overview, the following terms are defined for each targeted effect area as 

follows: 

 Data Availability: high, medium or low quality. This criterion is based on the availability 

and robustness of data sets, monitoring networks, availability of data that allows for 

extrapolation to larger assessment areas, and input parameters for modeling and 

developing the ecological effect function. The scientific basis for the ecological indicator 

selected is also incorporated into this criterion. 

Final Risk and Exposure Assessment 7-1 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

 Modeling Approach: high, fairly high, intermediate, or low confidence. This value is 

based on the strengths and limitations of the models used in the analysis and how accepted 

they are by the scientific community for their application in this analysis. 

 Ecological Effect Function: high, fairly high, intermediate, or low confidence. This 

ranking is based on how well the ecological effect function describes the relationship 

between atmospheric deposition and the ecological indicator of an effect. 

All of these parameters are necessary to evaluate the strength of the scientific basis for 

setting a national standard to protect against a given targeted effect. 

7.1 AQUATIC ACIDIFICATION 

7.1.1 Available Data 

For many years, research has focused on characterizing the ecological response of aquatic 

systems due to acidifying deposition. Surface water monitoring data from 1990–2006 for sulfate 

and nitrate concentrations and ANC levels used for this analysis came from the U.S. 

Environmental Protection Agency (EPA)–administered Temporally Integrated Monitoring of 

Ecosystems (TIME)/Long Term Monitoring (LTM) network. At the core of the TIME project is 

the concept of probability sampling, whereby each sampling site is chosen to represent a 

particular segment of a target population so that the entire data set is representative of the 

broader population. The target populations in these regions include lakes and streams likely to be 

responsive to changes in acidifying deposition, defined in terms of ANC. 

In addition, data from the EPA EMAP and Regional-EMAP (REMAP) surveys were used 

to characterize ecological conditions across populations of surface waters. EMAP and REMAP 

surveys have been conducted on lakes and streams throughout the country. EMAP surveys are 

probability surveys where sites are selected using a spatially balanced, systematic, randomized 

sample so that the results can be used to make estimates of regional extent of condition (e.g., 

number of lakes, length of stream). In both the Adirondack and Shenandoah case study areas, the 

sample sites selected for future monitoring were chosen based on the EMAP survey sites in the 

area that met the TIME target population definition. Each lake or stream is sampled annually (in 

summer for lakes; in spring for streams), and the results are extrapolated with known confidence 

to the target population(s) as a whole using the EMAP site population expansion factors or 

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Chapter 7 – Synthesis and Integration of Case Study Results 

weights (Larsen et al., 1994; Larsen and Urquhart, 1993; Stoddard et al., 1996; Urquhart et al., 

1998). (Note: for more details about the TIME/LTM network and EMAP probability surveys, see 

Section 4.2.5 of Chapter 4 and Attachment B of Appendix 4) 

The impact of acidifying deposition on aquatic systems is controlled by several 

environmental factors, such as geology, surface water flow, soil depth, and weathering rates, all 

of which influence the ability of a watershed to neutralize the additional acidifying deposition 

and prevent the lowering of surface ANC. ANC is a useful ecological indicator because it 

integrates the overall acid-base status of a lake or stream and reflects how aquatic ecosystems 

respond to acidifying deposition over time. There is also a relationship between ANC and the 

surface water constituents that directly contribute to or ameliorate acidity-related stress; in 

particular, concentrations of hydrogen ion (as pH), calcium (Ca2+), and aluminum (Al). In 

aquatic systems, there is a direct relationship between ANC and fish and phyto-zooplankton 

diversity and abundance (Baker et al., 1993). 

The ANC of surface waters is widely used as a chemical indicator of acidic conditions 

because it has been found in many studies to be the best single indicator of the biological 

response and health of aquatic communities in acid-sensitive systems (Lien et al., 1992; Sullivan 

et al., 2006). Logistic regression of species presence/absence data against ANC provides a 

quantitative dose-response function that indicates the probability of occurrence of an organism 

for a given value of ANC. For example, the number of fish species present in a waterbody has 

been shown to be positively correlated with the ANC level in the water, with higher values 

supporting a greater richness and diversity of fish species (Figure 7.1-1). The diversity and 

distribution of phyto-zooplankton communities are also positively correlated with ANC. 

Final Risk and Exposure Assessment 7-3 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

Figure 7.1-1. Number of fish species per lake or stream versus ANC level and 

aquatic status category (colored regions) for lakes in the Adirondack Case Study 

Area (Sullivan et al., 2006). The five aquatic status categories are described in 

Table 7.1-1. 

For freshwater systems, ANC levels can be grouped into five major classes: <0, 0–20, 

20–50, 50–100, and >100 microequivalents per liter (μeq/L), with each range representing a 

probability of ecological damage to the community. ANC values >100 μeq/L are generally not 

harmful (see Figure 7.1-1) to biota. With ANC <100 μeq/L, fish fitness and community diversity 

begin to decline, but the overall health of the community remains high as long as ANC 

concentrations do not fall below 50 μeq/L. ANC concentrations <50 μeq/L result in negative 

effects on sensitive biota. From 50 to 20 μeq/L, fish diversity and the overall fitness (i.e., health 

and reproduction) of most aquatic organisms in the waterbody are reduced. For ANC <20 μeq/L, 

all biota exhibit some level of negative effects, particularly because surface waters at this level 

are susceptible to episodic acidification and their associated harmful effects (i.e., toxic and lethal 

effects on fish). Fish and plankton diversity and the structure of the communities continue to 

decline sharply to levels where acidophilic species begin to outnumber all other species. Below 

an ANC level of 0 μeq/L, nearly complete loss of fish populations and extremely low diversity of 

planktonic communities occur. At these low levels, only acidophilic species are present, but even 

their population and community structure are sharply reduced. The five categories of ANC and 

Final Risk and Exposure Assessment 7-4 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

expected ecological effects are described in Table 7.1-1 and are supported by a large body of 

research completed throughout the eastern United States (Sullivan et al., 2006). 

Table 7.1.-1. Aquatic Status Categories

Category Label ANC Levels and Expected Ecological Effects 

Acute 

Concern 

<0 μeq/L Complete loss of fish populations is expected. Planktonic communities 

have extremely low diversity and are dominated by acidophilic forms. 

The numbers of individuals in plankton species that are present are 

greatly reduced. 

Severe 

Concern 

0–20 μeq/L Highly sensitive to episodic acidification. During episodes of high 

acidifying deposition, brook trout populations may experience lethal 

effects. The diversity and distribution of zooplankton communities 

decline sharply. 

Elevated 

Concern 

20–50 μeq/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, including loss of health, ability to 

reproduce, and fitness. Diversity and distribution of zooplankton 

communities decline. 

Moderate 

Concern 

50–100 

μeq/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. Diversity and distribution of zooplankton 

communities also begin to decline as species that are sensitive to 

acidifying deposition are affected. 

Low 

Concern 

>100 μeq/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. 

One of the strengths of this case study is that there is a great deal of data available on 

surface water trends and ANC levels in the case study locations. 

CONCLUSION: The available data used for the targeted effect of aquatic acidification are robust and 

considered high quality. There is high confidence about the use of these data and their value for 

extrapolating to a larger regional population of lakes. 

7.1.2 Modeling Approach 

The Model of Acidification of Groundwater in Catchments (MAGIC) was used to 

determine the past (pre-acidification), present (2002 and 2008), and future (2020 and 2050) 

acidic conditions in the case study areas. MAGIC is a lumped-parameter model of intermediate 

complexity, developed to predict the long-term effects of acidic deposition on surface water chemistry 

Final Risk and Exposure Assessment 7-5 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

(Cosby et al., 1985a,b). The model simulates soil solution chemistry and surface water chemistry to 

predict annual average concentrations of the major ions in lakes and streams. Model inputs include 

deposition and physical and chemical surface water parameters. Weathering rates and initial (preindustrial) base saturation values are calibrated by comparing model outputs and observed surface water 

chemistry. The benefits of MAGIC are that the input parameters are readily available and, once 

calibrated for a specific site, the model is easy to use. 

The uncertainty in the water quality estimates (i.e., ANC) from MAGIC was derived by 

running multiple calibrations. These simulation uncertainty estimates were derived from the 

multiple calibrations at each site provided by the “fuzzy optimization” procedure employed in 

this project. For each of the modeled sites, 10 distinct calibrations were performed with the target 

values, parameter values, and deposition inputs for each calibration reflecting the uncertainty 

inherent in the observed data for the individual site. The effects of the uncertainty in the 

assumptions made in calibrating the model (and the inherent uncertainties in the data available) 

can be assessed by using all successful calibrations for a site when simulating the response to 

different scenarios of future deposition. The model then produces an ensemble of simulated 

values for each site (e.g., a median ANC). 

Based on the MAGIC model simulations, the 95% confidence interval for the preacidification and current average ANC concentrations of 44 modeled lakes is 106.8 to 134.0 and 

50.5 to 81.8 μeq/L, respectively, which is, on average, a 15 μeq/L difference in ANC 

concentrations, or 10%. The 95% confidence interval for pre-acidification and current average 

ANC concentrations of the 60 modeled streams is 91.9 to 110.9 and 53.4 to 62.4 μeq/L, 

respectively, which is, on average, a 8 μeq/L difference in ANC concentration, or 5%.

Results of predicted versus observed average water chemistry during the calibration 

period (i.e., reference year) are in Figures 7.1-2 and 7.1-3 for MAGIC modeling. The model 

showed close agreement with measured values at all sites for the 1-year comparison of modeled 

values. For all sites’ SO4

2-, NO3-

, and ANC simulations, the root mean squared error (RMSE) for 

predicted versus observed values, based on average ANC over a 5-year period, was 0.1 μeq/L, 

0.05 μeq/L, and 3.5 μeq/L, respectively, for lakes in the Adirondack Case Study Area and 1.0 

μeq/L, 0.06 μeq/L, and 1.0 μeq/L, respectively, for streams in the Shenandoah Case Study Area. 

RMSE is a frequently-used measure of the differences between values predicted by a model or 

an estimator and the values actually observed from the thing being modeled or estimated. Plots 

Final Risk and Exposure Assessment 7-6 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

of simulated and observed annual average ANC values for the period of 1980 to 2007 are 

graphed in Figures 7.1-4 and 7.1-5 for two lakes in the Adirondack Case Study Area and two 

streams in the Shenandoah Case Study Area. The simulated and observed values are yearly 

average ANC values. Observed water chemistry data are from the LTM, ALTM, VTSSS, and 

TIME water quality measurement programs. The RMSE for ANC were 7.8 μeq/L and 5.1 μeq/L 

for lakes in the Adirondack Case Study Area and 11.8 μeq/L and 4.0 μeq/L for streams in 

Shenandoah Case Study Area. These direct comparisons show good agreement between 

simulated and observed water quality values. 

0

50

100

150

0 50 100 150

Observed Chemistry

Simulated Chemistry

SO4

2- μeq/L 1:1

0

5

10

15

20

0 5 10 15 20

Observed Chemistry

Simulated Chemistry

1:1 NO3- μeq/L

-100

0

100

200

300

-100 0 100 200 300

Observed Chemistry

Simulated Chemistry

1:1

ANC μeq/L

4

5

6

7

8

45678

Observed Chemistry

Simulated Chemistry

1:1 pH μeq/L

Figure 7.1-2. Simulated versus observed annual average surface water SO4

2-, 

NO3

-

, ANC, and pH during the model calibration period for each of the 44 lakes 

in the Adirondack Case Study Area. The black line is the 1:1 line. 

Final Risk and Exposure Assessment 7-7 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

Final Risk and Exposure Assessment 7-8 September 2009 

0

50

100

150

0 50 100 150

Observed Chemistry

Simulated Chemistry

SO4

2- μeq/L 1:1

0

10

20

30

40

50

0 10 20 30 40 5

Observed Chemistry

Simulated Chemistry

1:1

0

NO3- μeq/L

-100

0

100

200

300

-100 0 100 200 300

Observed Chemistry

Simulated Chemistry

ANC μeq/L

4

5

6

7

8

4567

Observed Chemistry

Simulated Chemistr

8

y

1:1 pH μeq/L

Figure 7.1-3. Simulated versus observed annual average surface water SO4

2-, 

NO3

-

, ANC, and pH during the model calibration period for each of the 60 

streams in the Shenandoah Case Study Area. The black line is the 1:1 line. 
Chapter 7 – Synthesis and Integration of Case Study Results 

-25

0

25

50

ANC (μeq/L)

Observed

Simulated

Indian Lake

-50

-25

0

25

50

1975 1980 1985 1990 1995 2000 2005 2010

Years

ANC (μeq/L)

Dismal Pond

Figure 7.1-4. MAGIC simulated and observed values of ANC for two lakes in the 

Shenandoah Case Study Area. Red points are observed data, and the simulated 

values are the line. The Root Mean Squared Error (RMSE) for ANC was 7.81 

μeq/L for Indiana Lake and 5.1 μeq/L for Dismal Pond. 

Final Risk and Exposure Assessment 7-9 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

0

50

100

150

200

ANC (μeq/L)

Observed

Simulated

Helton Creek

-25

0

25

50

1975 1980 1985 1990 1995 2000 2005 2010

Years

ANC (μeq/L)

Nobusiness Creek

Figure 7.1-5. MAGIC simulated and observed values of ANC for two lakes in the 

Shenandoah Case Study Area. Red points are observed data, and the simulated 

values are the line. The Root Mean Squared Error (RMSE) for ANC was 11.8 

μeq/L for Helton Creek and 4.0 μeq/L for Nobusiness Creek. 

The critical load approach was used to connect current deposition of nitrogen and sulfur 

to the acid-base condition and biological risk to biota of lakes and streams. Calculating critical 

load exceedances (i.e., the amount of deposition above the critical load) allows the determination 

of whether current deposition poses a risk of acidification to a given group of waterbodies. This 

approach also allows for the comparison of different levels of ANC thresholds (e.g., 0, 20, 50, 

100 μeq/L) and their associated risk to the biological community. 

The critical load of acidity for lakes or streams was derived from present-day water 

chemistry using the steady-state critical load models. These models are based on the principle 

that excess base cation production within a catchment area should be equal to or greater than the 

acid anion input, thereby maintaining the ANC above a preselected level (Reynolds and Norris, 

2001). This model assumes steady-state conditions and assumes that all SO4

2– in runoff 

originates from sea salt spray and anthropogenic deposition. Given a critical ANC protection 

Final Risk and Exposure Assessment 7-10 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

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 surface water. An F-factor was used to correct the concentrations and 

estimate preindustrial base concentrations for lakes in the Adirondack Case Study Area. A 

detailed description of the F-factor approach is given in Section 1.2.2 of Attachment A of 

Appendix 4. 

There is uncertainty associated with the parameters in the steady-state critical load model 

used to estimate aquatic critical loads. The strength of the critical load estimate and the 

exceedance calculation relies on the ability to estimate the catchment-average base cation supply 

(i.e., input of base cations from weathering of bedrock and soils and air), runoff, and surface 

water chemistry. The uncertainty associated with runoff and surface water measurements is fairly 

well known; however, the ability to accurately estimate the catchment supply of base cations to a 

waterbody is still poorly known. This is important because the catchment supply of base cations 

from the weathering of bedrock and soils is the factor that has the most influence on the critical 

load calculation and also has the largest uncertainty (Li and McNulty, 2007). Although the 

approach to estimate base cation supply in the case study areas (e.g., F-factor) approach has been 

widely published and analyzed in Canada and Europe, and has been applied in the United States 

(e.g., Dupont et al., 2005), the uncertainty in this estimate is unclear and is likely large. For this 

reason, an uncertainty analysis of the state-steady critical load model was completed to evaluate 

the uncertainty in the critical load and exceedances estimations. 

 A probabilistic analysis using a range of parameter uncertainties was used to assess (1) 

the degree of confidence in the exceedance values and (2) the coefficient of variation (CV) of the 

critical load and exceedance values. The probabilistic framework is Monte Carlo, whereby each 

steady-state input parameter varies according to specified probability distributions and their 

range of uncertainty (see Table 4.2-7 in Chapter 4). The purpose of the Monte Carlo methods 

was to propagate the uncertainty in the model parameters in the steady-state critical load model. 

Within the Monte Carlo analysis, model calculations were run a sufficient number of 

times (i.e. 1,000 times) to capture the range of behaviors represented by all variables. The 

analysis tabulated the number of lakes where the confidence interval is entirely below the critical 

load, the confidence interval is entirely above the critical load, and the confidence interval 

straddles zero. Similar results are given for the number of sites, with all realizations above the 

Final Risk and Exposure Assessment 7-11 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

critical load, all realizations below the critical load, and some realizations above and some below 

the critical load. An inverse cumulative distribution function for exceedances was constructed 

from the 1000 model runs for each site, which describes the probability of a site to exceed its 

critical load. For each site, the probability of exceeding its critical load (i.e. probability of 

exceedance) is determined at the percent of the cumulative frequency distribution that lies above 

zero. The probability of exceedance, where the percentage of the cumulative frequency 

distribution lies above zero, was calculated for all sites and assigned to one of the following five 

classes: 

 0–5% probability: unlikely to be exceeded; 

 5–25% probability: relatively low risk of exceedance; 

 25–75% probability: potential risk of exceedance; 

 •5–95% probability: relatively high risk of exceedance; 

 >95% probability: highly likely to be exceeded. 

This gives us a measure of the degree of confidence in whether the site exceeds its critical 

load. The CDF for Little Hope Pond is shown in Figure 4.2-24 in Chapter 4. 

The CV was also calculated on each site for both the critical load and exceedance 

calculations. The CV represents the ratio of the standard deviation to the mean and is a useful 

statistic for comparing the degree of variation in the data. The CV allows a determination of how 

much uncertainty (risk) comparison to its mean. 

CONCLUSION: There is fairly high confidence associated with the models, input parameters, and 

assessment of uncertainty used in the case study analysis for aquatic acidification. 

7.1.3 Ecological Effect Function 

The ecological effect function, which relates the contribution of atmospheric deposition 

of NOx and SOx to acidification in aquatic ecosystems, is described in detail in Section 4.2.7 of 

Chapter 4. Briefly, the acid balance of a lake or stream is controlled by acidifying deposition of 

nitrate, sulfate, watershed processes impacting the level of base cations present, and the sinks for 

nitrogen and sulfur in the watershed. The biotic integrity of freshwater ecosystems is then a 

function of the acid-base balance and the resulting acidity-related stress on the biota that occupy 

the water. 

Final Risk and Exposure Assessment 7-12 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

The calculated ANC of surface waters accounts for the inputs of base cations and acid 

anions, providing an indicator of the overall integrity of the ecosystem. The ANC concentration 

then provides a link between the surface water acidification and the ecological integrity of the 

aquatic community where a given level of ANC corresponds to an ecological effect (see Table 

7.1-1). It also provides a link between the deposition of NOx and SOx and the acidification 

through the input of acid anions of NO3

-

 and SO4

-

. 

Given some “target” ANC concentration [ANClimit]), which protects biological integrity, 

the amount of deposition of acid anions (AN) or depositional load (DL(N) + DL(S)) is simply 

the input flux of acid anions from atmospheric deposition that result in a surface water ANC 

concentration equal to the [ANClimit] when balanced by the sustainable flux of base cations input 

and the sinks of nitrogen and sulfur in the lake and watershed catchment. The sustainable flux of 

base cations input and sinks of nitrogen and sulfur is equal to the uptake (Nupt), immobilization 

(Nimm), and denitrification (Nden) of nitrogen in the catchment; the in-lake retention of nitrogen 

(Nret) and sulfur (Sret); and the preindustrial flux of base cations ([BC]0

*

) to the watershed. Thus, 

the amount of deposition that will maintain an ANC level above an ANClimit is described as 

 DL(N) + DL(S) = {fNupt + (1 − r)(Nimm + Nden) + (Nret + Sret)} + ([BC]0

* − [ANClimit])Q (1) 

where f and r are dimensionless parameters that define the fraction of forest cover in the 

catchment and the lake/catchment ratio, respectively, and Q is runoff. To convert surface water 

concentrations into surface water fluxes, multiply by runoff (Q) (in m/yr) from the site. Several 

major assumptions are made: (1) steady-state conditions exist, (2) the effect of nutrient cycling 

between plants and soil is ignored, (3) there are no significant nitrogen inputs from sources other 

than atmospheric deposition, (4) ammonium leaching is negligible because any inputs are either 

taken up by biota or adsorbed onto soils or nitrate compounds, and (5) long-term sinks of sulfate 

in the catchment soils are negligible. 

It is not possible to define a maximal loading for a single total of acidity (i.e., both 

nitrogen and sulfur deposition) because the acid anions sulfate and nitrate behave differently in 

the way they are transported with hydrogen ions; one unit of deposition of sulfur will not have 

the same net effect on surface water ANC as an equivalent unit of nitrogen deposition. However, 

the individual maximum and minimum depositional loads for nitrogen and sulfur are defined 

when nitrogen or sulfur do not contribute to the acidity in the water. As shown in Equation 2, the 

Final Risk and Exposure Assessment 7-13 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

maximum depositional load for sulfur (DLmax(S)) is equal to the amount of sulfur the catchment 

can remove and still maintain an ANC concentration above the ANClimit: 

 DLmax(S) = [([BC]0

*

 - [ANClevel])Q]/ (1- ps) (2) 

when nitrogen deposition does not contribute to the acidity balance and where ps defines the 

fraction of in-lake retention of Sret. Given the assumption that the long-term sinks of sulfate in the 

catchment soils are negligible, the amount of sulfur entering the catchment is equal to the amount 

loaded to the surface water. For this reason, as shown in Equation 3, the minimal amount of 

sulfur is equal to zero: 

 DLmin(S) = 0 (3) 

In the case of nitrogen, DLmin(N) is the minimum amount of deposition of total nitrogen (NHx + 

NOx) that catchment processes can effectively remove (e.g., Nupt + Nimm + Nden +Nret) without 

contributing to the acidic balance: 

 DLmin(N) = fNupt + (1-r)(Nimm + Nden) (4) 

The DLmax(N) is the load for total nitrogen deposition when sulfur deposition is equal to 

zero: 

 DLmax(N) = fNupt + (1-r)(Nimm + Nden) + [([BC]0

*

 - [ANClevel])Q]/ (1-pn) (5) 

where pn defines the fraction of in-lake retention of Nret. 

In reality, neither nitrogen nor sulfur deposition will never be zero, so the depositional 

load for the deposition of one is fixed by the deposition of the other, according to the line 

defining in Figure 7.1-6. 

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Chapter 7 – Synthesis and Integration of Case Study Results 

N Deposition 

DLmax(N)

S Deposition 

DLmin(N)

DLmax(s)

N Deposition 

DLmax(N)

S Deposition 

DLmin(N)

DLmax(s)

Figure 7.1-6. The depositional load function defined by the model. 

The thick lines indicate all possible pairs of depositional loads of nitrogen and sulfur acidity that 

a catchment can receive and still maintain an ANC concentration equal to its ANClimit. Note that 

in the above formulation, individual depositional loads of nitrogen and sulfur are not specified; 

each pair of depositions (Sdep and Ndep) fulfills Equations 1 through 5. 

One important parameter, the preindustrial flux of base cations ([BC]0

*

), is difficult to 

quantify. Present-day surface water concentrations of base cations are elevated above their 

steady-state preindustrial concentrations because of base cation leaching through ion exchange in 

the soil due to anthropogenic inputs of SO4

2- to the watershed. For this reason, present-day 

surface water base cation concentrations are higher than natural or preindustrial levels, which if 

not corrected for, would result in critical load values not in steady-state condition. Input 

parameters for this include atmospheric deposition, base cation uptake and retention, and 

weathering rates. Of these parameters, weathering rates are difficult to obtain on a nationwide 

basis. 

CONCLUSION: There is high confidence associated with the ecological effect function developed for 

aquatic acidification. 

7.1.4 Data Gaps and Research Needs 

Based on the data and analyses presented in this chapter, Chapter 4, and Appendix 4, 

several data gaps arise that suggest further research is needed in the following areas: 

Final Risk and Exposure Assessment 7-15 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

 Developing relationships between critical loads for aquatic acidity and effects on 

ecosystem services, especially due to incremental changes in an ecological indicator such 

as ANC 

 Developing nationwide weathering rates, or weathering rates for aquatic ecosystems 

sensitive to acidification 

 Developing a better understanding of the uncertainty in critical loads for acidity and 

exceedance values 

 Developing methods for calculating critical loads for surface water acidity when data are 

absent or of poor quality 

 Evaluating ways to combine multiple critical load estimates for surface waters and soils on 

a national scale 

 Estimating ways to determine critical load parameters across different media (e.g., surface 

waters, soils). 

7.2 TERRESTRIAL ACIDIFICATION 

7.2.1 Available Data 

A meta-analysis of laboratory studies examining the relationship between base cation to 

aluminum ratio (Bc/Al) in soil solution and tree growth showed that tree growth was reduced by 

20% relative to controls for 46 tree species (native and introduced) in North America (Sverdrup 

and Warfvringe, 1993). These data are summarized in Figure 7.2-1, which indicates that there is 

a 50% chance of negative tree response (i.e., >20% reduced growth) at a soil solution Bc/Al ratio 

of 1.2 and a 75% chance at a Bc/Al ratio of 0.6. These findings clearly demonstrate a relationship 

between Bc/Al ratio and tree health (i.e., as the Bc/Al is reduced, there is a greater likelihood of a 

negative impact on tree health). 

Final Risk and Exposure Assessment 7-16 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

Final Risk and Exposure Assessment 7-17 September 2009 

0.01

0.1

1

10

0 25 50 75

Bc/Al Ratio in Soil Solution 

100

(Bc/Al)crit = 1.2

(Bc/Al)crit = 0.6

0.01

0.1

1

10

0 25 50 75

Bc/Al Ratio in Soil Solution 

100

(Bc/Al)crit = 1.2

(Bc/Al)crit = 0.6

Cumulative Percentage of Species Exhibiting Reduced Growth Response

Figure 7.2-1. The relationship between the Bc/Al ratio in soil solution and the 

percentage of tree species (native and introduced; found growing in North 

America) exhibiting a 20% reduction in growth relative to controls (after 

Sverdrup and Warfvinge, 1993). 

This review focused on sugar maple and red spruce because they occur in areas that 

receive high acidifying deposition and are known to be negatively affected by Ca2+ depletion and 

high concentrations of available Al, as measured by Bc/A1 ratios in soils. The ecological effects 

associated with acidifying deposition are summarized in Table 7.2-1. Bc/Al ratios in the soil 

solution were selected as the indicator to evaluate acidifying deposition loadings in terrestrial 

systems using the U.S. Forest Service Forest (USFS) Inventory and Analysis (FIA) database as a 

source of plot locations where sugar maple and/or red spruce are found growing. 

Table 7.2-1. Summary of Linkages among Acidifying Deposition, Biogeochemical Processes 

that Affect Ca2+, Physiological Processes that are Influenced by Ca2+, and the Effect on Forest 

Function

Biogeochemical Response to 

Acidifying Deposition Physiological Response Effect on Forest Function 

Leach Ca2+ from leaf membrane Reduce the cold tolerance of 

needles in red spruce 

Loss of current year needles in 

red spruce 

Reduce the ratio of Ca2+/Al in 

soil and soil solutions 

Dysfunction in fine roots of red 

spruce blocks uptake of Ca2+

Decreased growth and increased 

susceptibility to stress in red 

spruce 
Chapter 7 – Synthesis and Integration of Case Study Results 

Final Risk and Exposure Assessment 7-18 September 2009 

Biogeochemical Response to 

Acidifying Deposition Physiological Response Effect on Forest Function 

Reduce the ratio of Ca2+/Al in 

soil and soil solutions 

More energy is used to acquire 

Ca2+ in soils with low Ca2+/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 et al., 2006. 

Known areas of sensitivity to terrestrial acidification were identified in the Integrated

Science Assessment (ISA) for Oxides of Nitrogen and Sulfur–Ecological Criteria (Final Report)

(ISA) (U.S. EPA, 2008), and a significant amount of the research work in the Allegheny Plateau 

region by the USFS has produced extensive peer-reviewed datasets of soil and tree 

characteristics (Bailey et al., 2004; Hallett et al., 2006; Horsley et al., 2000). The USFSdesignated Kane Experimental Forest (KEF) has been the focus of several long-term studies 

since the 1930s. The seven plots in the forest with the highest concentrations of sugar maple 

trees were assessed for this case study of the effects of terrestrial acidification on sugar maple. A 

review of this information led to the selection of the Hubbard Brook Experimental Forest 

(HBEF) in New Hampshire’s White Mountains as the location to examine the impacts of 

acidifying deposition on red spruce. This area has experienced high total nitrogen and sulfur 

deposition levels and low Ca2+/Al soil solution ratios, and HBEF has been the site of extensive 

nutrient investigations and provided a large data set from which to work on the case study. The 

case study of the effects of terrestrial acidification on red spruce focused on Watershed 6 in the 

HBEF. 

The analysis was expanded to a larger region based on the USFS FIA database permanent 

sampling plots’ locations on forestland1 (timberland2

 for New York, Arkansas, Kentucky, and 

North Carolina), each covering 0.07 ha. Only database information for nonunique3

, permanent 

 

1 Forestland is defined as, “land at least 10% stocked by forest trees of any size, or formerly having such tree cover, 

and not currently developed for non-forest uses, with a minimum area classification of 1 acre” (USFS, 2002a). 

2 Timberland is defined as, “forest land capable of producing in excess of 20 cubic feet per acre per year and not 

legally withdrawn from timber production, with a minimum area classification of 1 acre” (USFS, 2002b). 

3 Nonunique permanent sampling plot locations are those that have critical load attribute values (e.g., soils, runoff, 

atmospheric deposition) that are not distinct and are repeated within a 250-acre area of the plot location. This 

“confidentiality” filter is a requirement of the USFS to prevent the disclosure of data that can be directly linked to 

a location on private land. To comply with the necessary “confidentiality,” full coverages of the data required for 

the critical load deposition calculations were given to the USFS, and the USFS matched and provided the data to 

each nonunique, permanent sampling plot. 
Chapter 7 – Synthesis and Integration of Case Study Results 

Final Risk and Exposure Assessment 7-19 September 2009 

sampling plots that supported the growth of sugar maple or red spruce and had the necessary soil, 

parent material, atmospheric deposition, and runoff data were included in the analyses. With 

these restrictions, 7,992 of the 14,669 sugar maple plots and 763 of the 2,875 red spruce plots 

were included in the analyses. Although only subsets of the plots were included in the analyses, 

the results are thought to accurately capture the range and trends in the datasets. Due to the 

randomness of the plot restrictions, it is unlikely that a bias was incorporated into the analyses. 

In the analyses of critical loads for the full distribution ranges of sugar maple and red 

spruce, two fine-scale databases, the Soil Survey Geographic Database (SSURGO) of soils 

[USDA-NRCS, 2008] and U.S. Geological Survey (USGS) state-level geology [USGS, 2009] 

databases, were used as the sources for parent material mineralogy to allow for location-specific 

mineralogy descriptions. Although steps were taken to avoid misclassification, it is possible that 

parent material in some of the plots may have been misclassified. 

7.2.2 Modeling Approach 

The Simple Mass Balance (SMB) model, outlined in the International Cooperative 

Programme (ICP) Mapping and Modeling Manual4 (UNECE, 2004), was used to evaluate 

critical loads of acidifying nitrogen and sulfur deposition in the KEF and HBEF case study areas

This model is currently one of the most commonly used approaches to estimate critical loads and

has been widely applied in Europe (Sverdrup and de Vries, 1994), the United States (McNulty et 

al., 2007; Pardo and Duarte, 2007), and Canada (Arp et al., 2001; Ouimet et al., 2006; 

Watmough et al., 2006). It examines a long-term, steady-state balance of base cation, chloride

and nutrient inputs, “sinks,” and outputs within an ecosystem, and base cation equilibrium is 

assumed to equal the system’s critical load for ecological effects. A limitation of the SMB model 

is that it is a steady-state model and does not capture the cumulative changes in ecosystem 

conditions. However, as stated by the UNECE (2004), “Since critical loads are steady-state 

quantities, the use of dynamic models for the sole purpose of deriving critical loads is somewhat

. 

, 

 

4 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. Neither the HBEF nor KEF case study areas are located less than 70 km for 

the coast, so this correction was not used. 

CONCLUSION: The available data used to quantify the targeted effect of terrestrial acidification are 

robust and considered high quality. There is high confidence about the use of these data and their 

value for extrapolating to a larger regional population of forests. 
Chapter 7 – Synthesis and Integration of Case Study Results 

Final Risk and Exposure Assessment 7-20 September 2009 

inadequate.” In addition, if a dynamic model is “used to simulate the transition to a steady 

for the comparison with critical loads, care has to be taken that the steady-state version of the 

dynamic model is compatible with the critical load model” (UNECE, 2004). Therefore, the 

selection of the SMB model was seen as the most suitable approach for this case study 

examining critical loads for sugar mapl

state 

e and red spruce. 

7.2.3 Ecological Effect Function 

Note: Both the aquatic and terrestrial acidification case study analyses used a critical 

loads approach to determine impacts from atmospheric deposition to acidity. There are 

similarities in the approach, although different data sets and assumptions were used. 

A component of critical load determinations is the establishment of the critical load 

function (CLF), or the ecological effect function used for this targeted effect. The CLF expresses 

the relationship between the critical load and all combinations of total nitrogen and sulfur 

deposition (N+Scomb) of an ecosystem. To define the CLF, minimum and maximum amounts of 

total nitrogen and sulfur deposition that combine to create the critical load must be determined 

(UNECE, 2004). The maximum amount of sulfur in the critical load (CLmax(S)) occurs when 

total nitrogen deposition does not exceed the nitrogen sinks (i.e., nitrogen immobilization, 

nitrogen uptake and removal by tree harvest, and denitrification) within the ecosystem. These 

nitrogen sinks are accounted for by the minimum amount of nitrogen in the critical load 

(CLmin(N)). Above this CLmin(N) level, total nitrogen deposition can no longer be absorbed by 

the system, and acidification effects can occur. The maximum amount of nitrogen in the critical 

load (CLmax(N)) occurs when there is no sulfur deposition, and all of the acidity is due to the 

deposition of nitrogen. 

An example of a CLF is depicted in Figure 7.2-2. All combinations of total nitrogen and 

sulfur deposition that fall on the black line representing the CLF are at the critical load. Any 

deposition combination that falls below the line or within the grey area is below the critical load. 

All combinations of nitrogen and sulfur deposition that are located above the line or within the 

white area are greater than the critical load. 

CONCLUSION: There is high confidence associated with the models, input parameters, and 

assessment of uncertainty used in the case study analysis for terrestrial acidification. 
Chapter 7 – Synthesis and Integration of Case Study Results 

CLmin(N)

N Deposition 

S De

position 

CLmax(N)

CLmax(S)

Figure 7.2-2. The critical load function created from the calculated maximum and 

minimum levels of total nitrogen and sulfur deposition (eq/ha/yr). The grey areas 

show deposition levels less than the established critical loads. The red line is the 

maximum amount of total sulfur deposition (valid only when nitrogen deposition 

is less than the minimum critical level of nitrogen deposition [blue dotted line]) in 

the critical load. The flat line portion of the curves indicates nitrogen deposition 

corresponding to the CLmin(N) (i.e., nitrogen absorbed by nitrogen sinks within 

the system). 

The majority of the data used to calculate critical loads for sugar maple and red spruce in 

the KEF and HBEF case study areas were specific to the case study areas and were compiled 

from published research studies and models, site-specific databases, or spatially-explicit GIS 

data layers. However, several of the parameters (e.g., denitrification, nitrogen immobilization, 

the gibbsite equilibrium constant, rooting zone soil depth) required the use of default values or 

values used in published critical load assessments. These assumptions are described in detail in 

Section 4.3.4.1 of Chapter 4. Default values were selected based on the literature. As with 

aquatic acidification, estimating base cation weathering rates is difficult. The clay-substrate 

method was used for estimating base cation weathering because it one of the most-commonly 

used methods for estimating this parameter. 

As noted previously, it is possible that the parent material acidity—a component of the 

clay-substrate model to estimate base cation weathering—was misclassified for the critical loads 

analysis for the full distribution ranges of sugar maple and red spruce. Uncertainties associated 

with this potential misclassification are largest if and acidic parent material is misclassified as 

basic (median percent differences 60% to 61% for sugar maple and 71% to74% for red spruce), 

Final Risk and Exposure Assessment 7-21 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

compared to a basic parent material being misclassified as intermediate or vice versa (median 

percent differences 6% to 7% for sugar maple and 4% to5% for red spruce). 

CONCLUSION: There is fairly high confidence associated with the ecological effect function 

developed for terrestrial acidification. 

7.2.4 Data Gaps and Research Needs 

Based on the data and analyses presented in this chapter, Chapter 4, and Appendix 5, 

several data gaps arise that suggest further research is needed in the following areas: 

 Determining the most appropriate and accurate base cation weathering model to estimate 

terrestrial critical acid loads nationwide 

 Expanding analyses to examine the relationships between tree growth and (1) critical load 

exceedance and (2) nitrogen deposition (i.e., further refine analyses of sugar maple and red 

spruce and expand analyses to include more tree species and a larger geographical area) to 

establish additional evidence of the connection between nitrogen and sulfur deposition and 

biological end points 

 Exploring field-based tree growth as a tool to determine the most suitable Bc/Al soil 

solution indicator ratio 

 Developing relationships between critical loads for terrestrial acidity and effects on 

ecosystem services. 

7.3 AQUATIC NITROGEN ENRICHMENT 

7.3.1 Available Data 

Assessment of the atmospheric contribution to total nitrogen loads in an estuary requires 

a large-scale modeling approach. Although this assessment took the approach of looking at the 

main-stem river to an estuary (including the estuary) rather than an entire estuary system or bay, 

a number of datasets were still required. Five biological indicators were used to develop an 

assessment of the eutrophication status: chlorophyll a, macroalgae, dissolved oxygen, 

nuisance/toxic algal blooms, and submerged aquatic vegetation. The National Oceanic and 

Atmospheric Administration’s (NOAA’s) Assessment of Estuarine Trophic Status (ASSETS) 

produces a categorical eutrophication index (EI) that is an estimation of the likelihood that the 

estuary is experiencing specific discrete levels of eutrophication or will experience 

Final Risk and Exposure Assessment 7-22 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

eutrophication in the future based on five biological indicators: chlorophyll a, macroalgae, 

dissolved oxygen, nuisance/toxic algal blooms, and submerged aquatic vegetation. Taking these 

factors into consideration, many national databases were evaluated including the USGS’s 

National Water Quality Assessment (NAWQA) program files, EPA’s STORage and RETrieval 

(STORET) database, NOAA’s Estuarine Drainage Areas data, and EPA’s water quality 

standards nutrient criteria for rivers and lakes (see Appendix 6, Table 1.2-1). 

The analytical approach consisted of a combination of SPAtially Referenced Regression 

on Watershed Attributes (SPARROW) modeling for nitrogen loads and assessment of estuary 

conditions under the NOAA ASSETS EI, which is highly scalable. Both components have been 

applied on a national scale—the national nutrient assessment using SPARROW (Smith and 

Alexander, 2000) and the NEEA using the ASSETS EI (Bricker et al., 1999, 2007), as well as on 

smaller scales. The data inputs for the SPARROW model were developed under separate studies 

and published by USGS, and only quality checks were performed, rather than full data 

validation. The ASSETS EI requires numerous data inputs and sources, resulting in a large 

amount of uncertainty associated with the calculations. 

CONCLUSION: The available data used for the targeted effect of aquatic nitrogen enrichment are 

considered medium quality. There is intermediate confidence about the use of these data and their 

value for extrapolating to a larger regional area. 

7.3.2 Modeling Approach 

SPARROW is a watershed modeling technique designed and supported by USGS. The 

model relies on a nonlinear regression formulation to relate water quality measurements 

throughout the watershed of interest to attributes of the watershed. Both point and diffuse 

sources within the watershed are considered, along with non-conservative transport processes 

(i.e., loss and storage of contaminants within the watershed). SPARROW follows the rules of 

mass balance while using a hybrid statistical and process-based approach. SPARROW is a 

statistical model and provides measures of statistical uncertainty in model coefficient and water 

quality predictions. Utilization of the SPARROW model results in estimates of long-term, 

steady-state water quality in a stream. It uses a spatially distributed model structure based on a 

defined stream network allowing separate statistical estimations of land and water parameters 

that quantify the rates of pollutant delivery from sources to streams and the transport of 

pollutants to downstream locations within the stream network (i.e., reaches, reservoirs, and 

Final Risk and Exposure Assessment 7-23 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

estuaries) (Schwarz et al., 2006). The model is calibrated at each available monitoring station by 

comparing the modeled loads (i.e., a total of loads from each watershed segment and any 

upstream loads from previous calibrations) against monitored data at the station. 

The link between the SPARROW model and the ASSETS EI occurs when the 

SPARROW output is used as the nitrogen load in the overall human influence index calculation 

of the ASSETS EI score. For the purposes of this study, a complete analysis from atmospheric 

deposition loading to ecological endpoint of the ASSETS EI score required an assessment of the 

relative changes in the deposition load, the resulting in-stream nitrogen load to the estuary, and 

the change in ASSETS EI score. An iterative assessment of the various possible ecological 

endpoints due to changing nitrogen loads has not been previously undertaken. A detailed listing 

of the uncertainties associated with predictive modeling and the use of a multi-indicator 

assessment tool are described in Section 5.2.8 of Chapter 5 and Section 5 of Appendix 6. These 

include data inputs to both SPARROW and ASSETS, uncertainty and sensitivity of SPARROW 

modeling to atmospheric inputs, heuristic estimates used in ASSETS, missing ranking in 

ASSETS scores, uncertainty ranges used, and the crossing of a categorical ranking system with a 

continuous nitrogen concentration scale. 

CONCLUSION: There is intermediate confidence associated with the models, input parameters, and 

assessment of uncertainty used in the case study analysis for excess aquatic nitrogen enrichment. 

7.3.3 Ecological Effect Function 

The relationship between atmospheric deposition and shifts in the ASSETS index values 

were assessed by applying percent decreases to the oxidized nitrogen loads in the estimated total 

nitrogen atmospheric deposition. The SPARROW model output for the 2002 current condition 

analysis was used to determine how the changing atmospheric inputs affected the overall total 

nitrogen load to the estuary of interest. These results were used to create the response curve 

relating instream total nitrogen concentrations to atmospheric deposition loads. A second 

response curve was defined for the alternative effects level analysis using historical data 

compilations of overall eutrophic condition scores and instream total nitrogen concentrations 

while holding the susceptibility portion of the overall human influence and the determined future 

outlook rankings constant. Then a “back--calculation” procedure was applied to the curves with 

Final Risk and Exposure Assessment 7-24 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

the intent of defining the atmospheric loads that are needed to improve the ASSETS EI from the 

current score of Bad (1) to Poor (2), Moderate (3), Good (4), or High (5). 

The results of this analysis indicated reductions in atmospheric deposition alone could not 

solve coastal eutrophication problems due to multiple non-atmospheric nitrogen inputs, leading 

to questions and concerns regarding the utility of this approach in areas not dominated by 

atmospheric deposition and the appropriateness of the selected ecological indicator. 

CONCLUSION: There is low confidence associated with the ecological effect function developed for 

excess aquatic nitrogen enrichment. 

Note: In addition to the case studies for the Potomac and Neuse River estuaries, the ISA 

(U.S. EPA, 2008) presents scientific studies that show that increased atmospheric nitrogen 

deposition in high alpine lakes and streams can cause a shift in community composition and 

reduce algal biodiversity. Elevated nitrogen deposition results in changes in algal species 

composition, especially in sensitive oligotrophic lakes. Two opportunistic diatom species, 

Asterionella formosa and Fragilaria crotonensi (McKnight et al., 1990; Lafrancois et al., 2004; 

Saros, 2005) now dominate the flora of at least several alpine and montane Rocky Mountain 

lakes, with similar field data showing shifts in dominant algal species in other parts of the 

western United States. A hindcasting exercise has concluded that the change that occurred in 

Rocky Mountain National Park lake algae between 1850 and 1964 was associated with an 

increase of only about 1.5 kg N/ha in wet nitrogen deposition (Baron, 2006). Similar changes 

inferred from lake sediment cores of the Beartooth Mountains of Wyoming also occurred in 

about 1.5 kg N/ha deposition (Saros et al., 2003). A strong relationship exists between excess 

aquatic nitrogen enrichment of high alpine lakes in the Rocky Mountains and atmospheric 

deposition because atmospheric deposition is the only source of nitrogen to these systems. 

7.3.4 Data Gaps and Research Needs 

Based on the data and analyses presented in this chapter, Chapter 5, and Appendix 6, 

several data gaps arise that suggest further research is needed in the following areas: 

 Refining development of adequate indicators of effects of nitrogen enrichment 

 Enhancing relationships between ecological indicators of nitrogen enrichment and 

atmospheric deposition used in this study 

Final Risk and Exposure Assessment 7-25 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

 Applying the methods used in this study to an atmospheric deposition-dominated estuarine 

system 

 Reducing model and data uncertainty 

 Expanding relationships between ecological indicators of nitrogen enrichment and 

ecosystem services associated with them 

 Exploring alternative relationships between ecological indicators and atmospheric 

deposition other than what was used in this study giving consideration to methods that can 

be extrapolated outside of the case study area 

 Improving knowledge of how individual chemical species of nitrogen contribute to 

eutrophication effects. 

7.4 TERRESTRIAL NITROGEN ENRICHMENT 

7.4.1 Available Data 

For terrestrial nitrogen enrichment, there is a substantial amount of empirical evidence 

indicating that ecological alterations are occurring due to atmospheric deposition nationwide. 

The assessment of ecological effects due to terrestrial nitrogen enrichment was based on a 

weight-of-evidence approach that used the current scientific literature to determine benchmark 

values for ecological effects attributable to atmospheric nitrogen deposition in sensitive southern 

California coastal sage scrub (CSS) and mixed conifer forest (MCF) communities in the Sierra 

Nevada and San Bernardino mountains of California (see Section 7.4.1-1). This approach does 

not develop a separate ecological effect function relating atmospheric deposition to an ecological 

indicator. 

There are sufficient data to relate an ecological effect to atmospheric nitrogen deposition. 

For the CSS community, the following ecological thresholds were identified: 

 3.3 kg N/ha/yr — the amount of nitrogen uptake by a vigorous stand of CSS; above this 

level, nitrogen may no longer be limiting 

 10 kg N/ha/yr — mycorrhizal community changes, CSS decline. 

Fire is also an inextricable and significant component in CSS losses. Although CSS 

communities are fire resilient, nonnative grass seeds are quick to establish in burned lands, 

decreasing the water and nutrient amounts available to CSS for reestablishment (Keeler-Wolf, 

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Chapter 7 – Synthesis and Integration of Case Study Results 

1995). Additionally, when annual grasses have established dominance, these species alter and 

increase the fire frequency as they senesce earlier in the annual season, which increases dry, 

ignitable fuel availability (Keeley et al., 2005). With increased fire frequencies and faster 

nonnative colonizations, CSS seed banks are eventually eradicated from the soil, and the 

probability of reestablishment decreases significantly (Keeley et al., 2005). 

For the MCF community in the Pacific Coast states, the following ecological thresholds 

were identified: 

 3.1 kg N/ha/yr — shift from sensitive to tolerant lichen species 

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

 10.2 kg N/ha/yr — loss of sensitive lichen species 

 17 kg N/ha/yr — leaching of NO3

- into streams. 

At the highest levels of atmospheric nitrogen deposition, native understory species were 

seen to decline (Allen et al., 2007). In addition to the decline in native understory diversity, 

changes in decreased fine-root mass, increased needle turnover, and the associated 

chemostructural alterations, MCF exposed to elevated pollutant levels have an increasing 

susceptibility to drought and beetle attack (Grulke et al., 1998, 2001; Takemoto et al., 2001). 

These stressors often result in the death of trees, producing an increased risk of wildfires. In 

addition to the documented signs of nitrogen saturation, it is interesting to note that both CSS 

and the MCF ecosystems had responses in epiphytic associations, as well as increased 

susceptibility to wildfire and invasion of exotic species. 

Note that the effects of ozone and atmospheric nitrogen are difficult to separate, and 

lichen may be reacting to ozone effects and effects due to climate change. 

The deposition loads used are presented in Figure 7.4-1. 

Final Risk and Exposure Assessment 7-27 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

Figure 7.4-1. Benchmarks of atmospheric nitrogen deposition for several 

ecosystem indicators with the inclusion of the diatom changes in the Rocky 

Mountain lakes

CONCLUSION: The available data used for the targeted effect of terrestrial nitrogen enrichment are 

considered high quality; however, there is a limited ability to extrapolate these data to a larger regional 

area. 

Final Risk and Exposure Assessment 7-28 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

7.4.2 Modeling Approach 

As shown in Figure 7.4-1, a number of significant ecological endpoints have been 

identified. These results come from empirical results and from spatial databases. Dose/response 

relationships beyond benchmark values were investigated, but these have not yet been well 

quantified. Nitrogen deposition data was available at a 12-km resolution, and many of the 

ecosystems, especially CSS, are fragmented into smaller areas. The analysis was, therefore, 

somewhat limited by the discrepancy between resolution of the nitrogen deposition data and the 

distribution of habitats, as well as by the specific areas where ecological processes were 

measured. Further, some models have been tested, but with limited results. For example, the 

steady-state simple mass-balance model (UNECE, 2004) still has many unresolved uncertainties. 

Uncertainty exists in establishing the linkage between soil and biological impacts and the ability 

to account for forest management and wildfires (Fenn et al., 2008). The DayCent biogeochemical 

model is not a watershed-scale model and may not represent NO3

-

 leaching accurately. However, 

application of DayCent yielded results more comparable to empirically based findings than the 

steady-state model (Fenn et al., 2008). 

For these reasons, empirical data, in tandem with GIS analysis, were deemed more 

suitable to develop potential correlations between atmospheric nitrogen deposition and 

ecological endpoints. There is no response curve associated with the atmospheric nitrogen 

deposition loads for the observed ecological effects. As such, the endpoint cannot be shifted and 

associated with another response (as in the ANC response curve shown in Figure 7.1-1). In 

addition, while the data may be high quality for lichen, they may not have quantitative value for 

evaluating the response for other species or species in other regions of the United States. For 

these reasons, other than the spatial analysis of quantitative values of nitrogen effects and 

sensitivity, no additional modeling approaches were undertaken for this assessment. 

CONCLUSION: No quantitative modeling was conducted for terrestrial nitrogen enrichment. 

7.4.3 Ecological Effect Function 

There are many factors that determine whether or not an ecological effect occurs in 

response to ambient concentrations of NOx and SOx. These may be ecological or atmospheric 

factors, both of which influence deposition or exposure and the subsequent ecological effects 

(i.e., acidification or nutrient enrichment). In the excess Terrestrial Nutrient Enrichment case 

Final Risk and Exposure Assessment 7-29 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

study, establishing a quantitative linkage between a given ecological indicator and deposition, as 

influenced by the variable ecological factors, was not addressed because deposition was used—

rather than a traditional environmental indicator—as the direct metric for ecological response. 

CONCLUSION: No ecological effect function was developed for excess terrestrial nitrogen 

enrichment. 

7.4.4 Data Gaps and Research Needs 

Based on the data and analyses presented in this chapter, Chapter 5 and Appendix 7, 

several data gaps arise that suggest further research is needed in the following areas: 

 Elucidating the interactions among elevated levels of atmospheric nitrogen, fire intensity 

and frequency, and invasive grasses for CSS and elevated nitrogen and fire for MCF 

 Increasing the understanding of CSS and MCF communities long-term response to 

elevated nitrogen and how benchmarks may change 

 Developing indicators of CSS ecosystem health 

 Using modeled data with a higher spatial resolution 

 Increasing the understanding of the interactions between ozone, climate change and 

nitrogen deposition on CSS and MCF communities. 

7.5 CONCLUSIONS 

Although it is recognized that while there will always be inherent variability in ecological 

data and uncertainties associated with modeling approaches, there is a high level of confidence 

from a scientific perspective that known or anticipated adverse ecological effects are occurring 

under current ambient loadings of nitrogen and sulfur in sensitive ecosystems across the United 

States. 

For aquatic and terrestrial acidification effects, a similar conceptual approach was used 

(critical loads) to evaluate the impacts of multiple pollutants on an ecological endpoint (compare 

Figures 7.1-6 and 7.2-2), whereas the approaches used for aquatic and terrestrial nutrient 

enrichment were fundamentally distinct. Although the ecological indicators for aquatic and 

terrestrial acidification (i.e., ANC and Bc/Al) are very different, both ecological indicators are 

well-correlated with effects such as reduced biodiversity and growth. While aquatic acidification 

is clearly the targeted effect area with the highest level of confidence (see Table 7.5-1), the 

relationship between atmospheric deposition and an ecological indicator is also quite strong for 

Final Risk and Exposure Assessment 7-30 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

terrestrial acidification. The main drawback with the understanding of terrestrial acidification is 

that the data are based on laboratory responses rather than field measurements. Other stressors 

that are present in the field but not present in the laboratory may confound this relationship. 

The ecological indicator chosen for aquatic nutrient enrichment, the ASSETS EI, seems 

to be inadequate to relate atmospheric deposition to the targeted ecological effect, likely due to 

the many other confounding factors. Further, there is far less confidence associated with the 

understanding of aquatic nutrient enrichment because of the large contributions from nonatmospheric sources of nitrogen and the influence of both oxidized and reduced forms of 

nitrogen, particularly in large watersheds and coastal areas. However, a strong relationship exists 

between atmospheric deposition of nitrogen and ecological effects in high alpine lakes in the 

Rocky Mountains because atmospheric deposition is the only source of nitrogen to these 

systems. There is also a strong weight-of-evidence regarding the relationships between 

ecological effects attributable to terrestrial nitrogen nutrient enrichment; however, ozone and 

climate change may be confounding factors. In addition, the response for other species or species 

in other regions of the United States has not been quantified. 

Table 7.5-1. Summary of the Levels of Confidence Associated with the Available Data, 

Modeling Approach, and the Relationship between the Selected Ecological Indicator and 

Atmospheric Deposition as Described by the Ecological Effect Function for Each Targeted 

Effect Area Considered in this Review 

Available Data Modeling 

Approach 

Ecological Effect 

Function 

Aquatic 

Acidification 

High quality Fairly high 

confidence 

High confidence 

Terrestrial 

Acidification 

High quality High confidence Fairly high 

confidence 

Excess Aquatic 

Nitrogen 

Enrichment 

Medium quality Intermediate 

confidence 

Low confidence 

Excess Terrestrial 

Nitrogen 

Enrichment 

High quality, 

limited ability to 

extrapolate 

None None 

A summary of the information presented by this Risk and Exposure Assessment that may 

be useful for characterizing known or anticipated adverse effects to public welfare is shown in 

Table 7.5-2. This information may be useful to inform decision makers about what levels of 

Final Risk and Exposure Assessment 7-31 September 2009 
Chapter 7 – Synthesis and Integration of Case Study Results 

Final Risk and Exposure Assessment 7-32 September 2009 

protection might be appropriate to protect public welfare from known or anticipated adverse 

impacts on ecosystems. Characterizing known or anticipated adverse effects to public welfare 

from a policy perspective will be addressed in the policy assessment for this review.
Chapter 7 – Synthesis and Integration 

Table 7.5-2. Summary of Information Assessed in the Risk and Exposure Assessment to Aid in Informing Policy 

Effects 

Exposure Pathway 

(Current Deposition 

Levels) 

(NADP/CMAQ, 

2002) 

Affected Ecosystem 

(Case Study Areas) 

Ecological 

Response 

(Targeted Effect) 

Ecological 

Indicator Ecological Effect Eco

Adirondack Case Study Area: 10 kg N/ha/yr 9 kg S/ha/yr Shenandoah Case Study Area: 11 kg N/ha/yr 11 kg S/ha/yr 

Adirondack Mountains, NY Blue Ridge Mountains and Shenandoah National Park, VA

Acidification in lakes and streams 

Fish species richness, abundance, composition, ANC 

Species losses of fish, phytoplankton, zooplankton; changed community composition, ecosystem structure, and function 

AnnfishmorAppin imfrom and 

Kane Experimental Forest Case Study Area: 14 kg N/ha/yr 210 kg S/ha/yr Hubbard Brook Experimental Forest Case Study Area: 8 kg N/ha/yr 7 kg S/ha/yr 

Kane Experimental Forest (Allegheny Plateau, PA) Hubbard Brook Experimental Forest (White Mountains, NH) 

Acidification of forest soils 

Tree health Red spruce, sugar maple Bc/Al ratio 

Decreased tree growth Increased susceptibility to stress, episodic dieback; changed community composition, ecosystem structure, and function 

Prov(sug900 prod

Final Risk and Exposure Assessment 7-33 
Chapter 7 – Synthesis and Integration 

Final Risk and Exposure Assessment 7-34 

Exposure Pathway 

(Current Deposition 

Levels) 

(NADP/CMAQ, 

2002) 

Affected Ecosystem 

(Case Study Areas) 

Ecological 

Response 

(Targeted Effect) 

Ecological 

Indicator Ecological Effect Eco

Potomac River/Potomac Estuary Case Study Area: 13 kg N/ha/yr Neuse River/Neuse River Estuary Case Study Area: 14 Kg N/ha/yr 

Potomac River Basin, Chesapeake Bay Neuse River Basin, Pamlico Sound

Nutrient enrichment in main stem river of an estuary 

ASSETS EI Habitat degradation, 

algal blooms, toxicity, hypoxia, anoxia, fish kills, decreases in biodiversity 

Currrecr26.1 (NoMas

Coastal Sage Scrub from 3 to 10 kg N/ha/yr Mixed Conifer Forest (San Bernardino Mountains and Sierra Nevada Range): from 3 to 10 kg N/ha/yr 

Southern California Coastal Sage Scrub Mixed Conifer Forest (San Bernardino Mountains and Sierra Nevada Mountains, CA)

Nutrient enrichment in terrestrial ecosystems 

Species composition Species changes, 

nutrient enrichment of soil, changes in fire regime, changes in nutrient cycling 

Annresidwildapprstate supp(200
Chapter 7 – Synthesis and Integration of Case Study Results 

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