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
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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
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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).
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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 ofNOx, 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
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3.3.3 Characterization of Deposition in Case Study Areas 3-27
3.4 Contributions of Emissions of NOX andNH3 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 Deposit! on 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
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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 SOxandNOx 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
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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
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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 SC>2 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 SCh concentrations (ppb) for 2002 3-16
Figure 3.2-6. Total wet plus dry oxidized nitrogen deposition (kgN/ha/yr) in 2002 3-20
Figure 3.2-7. Total wet plus dry reduced nitrogen deposition (kgN/ha/yr) in 2002 3-21
Figure 3.2-8 Total reactive nitrogen deposition (kgN/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-la. 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-lb. 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 3.3-3 a. 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
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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 3.3-3L 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 3.3-6L Percentage of 2002 total reactive nitrogen deposition in the Transverse
Range portion of the Mixed Conifer Forest Case Study Area 3-56
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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 3.3-7L 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
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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 3.3-141. 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 3.3-151. 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 NHa 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
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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/|ig/m3) 3-95
Figure 3.5-2. Ratio of sulfur deposition to sulfur concentration based on oxidized sulfur
deposition and concentration (kg S/ha/|ig/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 offish species per lake or stream versus acidity, expressed as
acid neutralizing capacity for Adirondack Case Study Area lakes
(Sullivan et al., 2006). (b) Number offish 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 offish
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 SO42" (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 SC>2 (blue),
oxidized nitrogen (red), SC>42" (green), and reduced nitrogen (black), (b)
2-
Annual average total wet deposition (kg/ha/yr) of 864 " (green) and NO
3
(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 SC>42", N(V, and acid neutralizing capacity in 50 LTM
lakes. SC>42" and N(V concentrations have decreased in surface waters by
approximately 26% and 13%, respectively 4-18
Figure 4.2-7. N(V 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. SC>42" 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
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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 ueq/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 ueq/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 SO42" (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. N(V 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. SC>42" 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 VTSSS-
SWAS/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 ueq/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 ueq/L. Watersheds with critical load values <100
meq/m2/yr (red and orange circles) are most sensitive to surface water
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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 ueq/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 ueq/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 ueq/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 ueq/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 SC>42", N(V.
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 SC>42", N(V.
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 ueq/L for Indiana Lake and 5.1 ueq/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 ueq/L for Helton Creek and 4.0 ueq/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
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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
CLm;n(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 CLm;n(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
CLm;n(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 CLm;n(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 CLm;n(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
CLm;n(N) value for all curves is 42.86 eq/ha/yr, but this value is not
indicated in the figure 4-80
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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 CLm;n(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 El 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 El 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
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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 andNADP 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 andNADP 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 Long-
Term Ecological Research site and Denver metropolitan area 5-82
Figure 6.1-1. Percentage of total U.S. emissions of greenhouse gases in CC>2 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 offish 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
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Figure 7.1-2. Simulated versus observed annual average surface water SC>42", N(V. 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 SO42", 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 |ieq/L for Indiana Lake and 5.1 |ieq/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 |ieq/L for Helton Creek and 4.0 |ieq/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
CLm;n(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
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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 SC>2 Emissions across Major Source Categories in 2002 3-9
Table 3.2-4a. Annual SC>2 Emissions across Major Source Categories in 2002 for the
Eastern United States 3-9
Table 3.2-4b. Annual SC>2 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, NOs, 804) were determined from
surface water chemistry data for the period from 1992 to 2006 from the
Final Risk and Exposure Assessment xvi September 2009
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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 Protect!on 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
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Final Risk and Exposure Assessment xviii September 2009
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Acronyms and Abbreviations
Al
AM
AN
ANC
AQCD
ASSETS El
Be
BC
Bcu
Bcw
BCW
Bc/Al
C
Ca2+
CAA
CAAA
CAP
CAFO
CAIR
CALFIRE
CASAC
CASTNET
CH4
cr
CLF
cm
CMAQ
CO2
CS2
CSS
DFO
DIN
DL
DO
DOC
DOT
EC
EES
EGU
EMAP
EPA
ESRI
ACRONYMS AND ABBREVIATIONS
aluminum2+'3+
arbuscular mycorrhizae
acid anions (NCV and SO42")
acid neutralizing capacity
Air Quality Criteria Document
Assessment of Estuarine Trophic Status eutrophication index
base cation (Ca2+ + K+ + Mg2+)
base cation (Ca2+ + K+ + Mg2+ + Na+)
base cation (Ca2+ + K+ + Mg2+) uptake
base cation (Ca2+ + K+ + Mg2+) weathering
base cation (Ca2+ + K+ + Mg2+ + Na+) weathering
base cation to aluminum ratio
base cation to aluminum ratio (indicator)
carbon
calcium
Clean Air Act
Clean Air Act Amendments
Coastal Assessment Framework
confined animal feeding operation
Clean Air Interstate Rule
California Department of Forestry and Fire Protection
Clean Air Scientific Advisory Committee
Clean Air Status and Trends Network
methane
chloride
critical load function
centimeter
Community Multiscale Air Quality
carbon dioxide
carbon disulfide
coastal sage scrub
Determined Future Outlook
dissolved inorganic nitrogen
depositional load
dissolved oxygen
dissolved organic carbon
U.S. Department of the Interior
ecosystem carbon content
Ecological Effects Subcommittee
electric generating unit
Environmental Monitoring and Assessment Program
U.S. Environmental Protection Agency
Environmental Systems Research Institute, Inc.
Final Risk and Exposure Assessment
xix
September 2009
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Acronyms and Abbreviations
FASOMGHG
FHWAR
FIA
GHG
GIS
GPP
H+
H2O
H2S
H2SO4
ha
HAB
HBEF
HFC
Hg2+
Hg°
HNO3
HONO
HUC
ICP
IDW
IPCC
IPM
ISA
K+
KEF
kg
kg/ha/yr
km
LTER
LTM
m
MAGIC
MAHA
MCF
MCIP
MEA
mg/L
Mg2+
MSA
N
Nde
N,
Nr
Forest and Agriculture Sector Optimization Model - Greenhouse Gas
version
Fishing, Hunting, and Wildlife-Associated Recreation
Forest Inventory and Analysis
greenhouse gas
geographic information systems
gross primary productivity
hydrogen ion
water
hydrogen sulfide
sulfuric acid
hectare
harmful algal bloom
Hubbard Brook Experimental Forest
hydrofluorocarbon
divalent mercury
elemental mercury
nitric acid
nitrous acid
hydrologic unit code
International Cooperative Programme
inverse distance weighted
Intergovernmental Panel on Climate Change
Integrated Planning Model
Integrated Science Assessment
potassium
Kane Experimental Forest
kilogram
kilograms per hectare per year
gibbsite equilibrium constant
kilometers
Long-Term Ecological Research
Long-Term Monitoring
meters
Model of Acidification of Groundwater in Catchments
Mid-Atlantic Highlands Assessment
mixed conifer forest
Meteorology-Chemistry Interface Processor
Millennium Ecosystem Assessment
milligrams per liter
magnesium
metropolitan statistical area
nitrogen
denitrification
nitrogen immobilization
total reactive nitrogen
Final Risk and Exposure Assessment
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September 2009
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Acronyms and Abbreviations
Nret
Nu
N2
N20
N203
N204
N205
Na+
NAAQS
NADP
NAPAP
NAWQA
NEE
NEEA
NEI
NEP
NH3
NH4+
NH4NO3
(NH4)2S04
NHX
NLCD
NO
N02
NO3"
NOX
NOy
NOAA
NPP
NRC
NSRE
NSWS
NTN
NTR
02
03
OAQPS
OEC
OFT
OKI
ORD
PAN
PFC
PM
PM2.5
retention of nitrogen
nitrogen uptake
nitrogen gas
nitrous oxide
nitrogen trioxide
nitrogen tetr oxide
dinitrogen pentoxide
sodium
National Ambient Air Quality Standards
National Atmospheric Deposition Program
National Acid Precipitation Assessment Program
National Water Quality Assessment
net ecosystem exchange
National Estuarine Eutrophication Assessment
National Emissions Inventory
net ecosystem productivity
ammonia
ammonium
ammonium nitrate
ammonium sulfate
reduced nitrogen
National Land Cover Data
nitric oxide
nitrogen dioxide
nitrite
nitrate
nitrogen oxides
total oxidized nitrogen
National Oceanic and Atmospheric Administration
net primary productivity
National Research Council
National Survey on Recreation and the Environment
National Surface Water Survey
National Trends Network
organic nitrate
oxygen
ozone
Office of Air Quality Planning and Standards
Overall Eutrophic Condition
hydroxide
Influencing Factors/Overall Human Influence
Office of Research and Development
peroxyacetyl nitrates
perfluorocarbons
particulate matter
fine particulate matter less than 2.5 microns in size
Final Risk and Exposure Assessment
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September 2009
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Acronyms and Abbreviations
ppb
ppm
ppt
REMAP
RFNRP
RSM
S
Sret
S2O
s2o32-
s2o72-
SAB
SAV
SF6
Si
8MB
SO
SO2
SO3
SO42"
SOX
SOM
SPARROW
SRB
SSURGO
STORE!
TIME
TN
TNatm
TNS
TP
U.S. EPA
USFS
USGS
VIF
VOC
WTP
ueq/L
parts per billion
parts per million
parts per trillion
Regional Environmental Monitoring and Assessment Program
Regional Forest Nutrition Research Project
response-surface model
sulfur
retention of sulfur
disulfur monoxide
thiosulfate
sulfur heptoxide
Science Advisory Board
submerged aquatic vegetation
sulfur hexafluoride
silicon
Simple Mass Balance
sulfur monoxide
sulfur dioxide
sulfur trioxide
sulfate
sulfur oxides
soil organic matter
SPAtially Referenced Regression on Watershed Attributes
sulfate-reducing bacteria
Soil Survey Geographic Database
STORage and RETrieval
Temporally Integrated Monitoring of Ecosystems
total nitrogen
total nitrogen atmospheric loading
instream total nitrogen concentration
total phosphorus
U.S. Environmental Protection Agency
United States Forest Service
U.S. Geological Survey
variance inflation factor
volatile organic carbon
willingness to pay
microequivalent per liter
microgram per gram
microgram per cubic meter
micromolar
Final Risk and Exposure Assessment
xxn
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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
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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 A13+ 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.
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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 psy) 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).
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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.
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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 (F^O), carbon dioxide (CO2), N2O,
methane (CH/t), and ozone (Os) are the primary greenhouse gases in the earth's
atmosphere. In addition to CC>2, N2O, and CFU, 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, NC>2 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 SC>2,
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 862 NAAQS
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Key Terms
indicator is 0.5 ppm. The level of the W126 metric proposed in the 2007 Os 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 NC>2 NAAQS is a year. The
current averaging time for the secondary 862 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 Os
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 SC>2
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.
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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).
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Key Terms
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.
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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/63 O/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.
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Executive Summary
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
,..,,, ff . , ,r ,f pentoxide [N205]).
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
The sum of mono-nitrogen oxides, nitrogen dioxide
(NC>2), 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
[N2Os], nitrogen tetroxide [N2O4 and dinitrogen
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 [S2O/], as well as particulate species,
such as ammonium sulfate
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.
Final Risk and Exposure Assessment ES-1 September 2009
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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
SOxmay 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 offish 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
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Executive Summary
Dissolution
2H++S
H*+NOj
Oxidation
SO2 > H2SO,
NO, *HNO3
Wet Deposition
H*, NH4*, NOj",
Dry deposition s°2
NOX, NH». SO, NO
Acidification of water + Eutrophication
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.
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Executive Summary
Atmospheric
Deposition
Transformation
Function
8. Factors Related to
Characterizing
Adversity
7. Ecological
Indicator
Calculated over a
specified
averaaina 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.
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
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September 2009
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Executive Summary
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.
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Executive Summary
Table ES-1. Summary of Sensitive Characteristics, Indicators, Effects, and Impacted Ecosystem Services Analyzed for Each Case
Study Evaluated in This Review
Targeted
Ecosystem
Effect
Aquatic
Acidification
Terrestrial
Acidification
Aquatic Nutrient
Enrichment
Terrestrial
Nutrient
Enrichment
Characteristics of
Sensitivity (Variable
Ecological Factors)
Geology, surface water
flow, soil depth,
weathering rates
Geology, surface water
flow, soil depth,
weathering rates
Nitrogen-limited
systems, presence of
nitrogen in surface
water, eutrophication
status, nutrient criteria
Presence of acidophytic
lichens, anthropogenic
land cover
Biological/Chemical
Indicator
Al
PH
ANC
Soil base saturation
Al
Ca
C:N ratio
Chlorophyll a,
macroalgae, dissolved
oxygen, nuisance/toxic
algal blooms,
submerged aquatic
vegetation (SAV)
Cation exchange
capacity, C:N ratios,
CaAl ratios, NO3"
leaching and export
Ecological Endpoint
Species richness,
abundance,
composition,
ANC
Tree health of red
spruce and sugar maple,
ANC, Bc:Al ratio
Changes in
Eutrophication Index
(El)
Species composition,
lichen presence/absence,
soil root mass changes,
NOs breakthrough to
water, biomass
Ecological Effects
Species losses offish,
phytoplankton, and
zooplankton; changed
community
composition, ecosystem
structure, and function
Decreased tree growth,
increased susceptibility
to stress, episodic
dieback; changed
community
composition, ecosystem
structure, and function
Habitat degradation,
algal blooms, toxicity,
hypoxia, anoxia, fish
kills, decreases in
biodiversity
Species changes,
nutrient enrichment of
soil, changes in fire
regime, changes in
nutrient cycling
Ecosystem Services
Impacted
Subsistence fishing,
recreational fishing,
other recreational
activities
Provision of food and
wood products,
recreational activities,
natural habitat, soil
stabilization, erosion
control, water
regulation, climate
regulation
Commercial and
recreational fishing,
other recreational
activities, aesthetic
value, nonuse value
flood and erosion
control
Recreation, aesthetic
value, nonuse value, fire
regulation, loss of
habitat, loss of
biodiversity, water
quality
Case Study Areas
Adirondack Mountains,
NY (referred to as
Adirondack)
Shenandoah National
Park, VA (referred to as
Shenandoah)
Kane Experimental
Forest (Allegheny
Plateau, PA)
Hubbard Brook
Experimental Forest
(White Mountains, NH)
Potomac River Basin,
Chesapeake Bay
(referred to as Potomac
River/Potomac Estuary)
Neuse River Basin,
Pamlico Sound (referred
to as Neuse River/Neuse
River Estuary)
Coastal Sage Scrub
(southern, coastal
California) and Mixed
Conifer Forest (San
Bernardino Mountains
of the Transverse Range
and Sierra Nevada
Mountain Ranges,
California); Rocky
Mountain National Park
(a supplemental study
area)
Note: ANC = acid neutralizing capacity, SAV = submerged aquatic vegetation, El = eutrophication index.
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Executive Summary
I
/N«jt*ffiwrJ
•N«ti*fl Rlvw Eiluary
250 500 750 1.000
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.
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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.
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Executive Summary
Ambient Air Quality
Indicator
Exposure Pathway
Affected Ecosystem
Ecological Response
(ecological indicate?)
Ecological Effect
Ecological Benefit/
Welfare Effect
Policy based on
Welfare Effects
NCX/SO
Atmospheric
Deposition
Acidification
(lake/stream ANC)
unange in hcosystem
Structure & Processes
(fish species richness)
Change in
Ecosystem Services
(recreational fishing)
T
Secondary
Standard
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
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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
SC>2 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 SC>2.
• 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
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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 SC>42"and NCVconcentrations 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 862 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 SO42" 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 (ueq/L)
(± 15.7 (j,eq/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.
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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 ueq/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 N(V and SC>42" concentrations in surface waters. ANC levels increased from
about 50 ueq/L in the early 1990 to >75 ueq/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 N(V and SC>42" are
10- and 32-fold higher today, respectively. The estimated average ANC for 60 streams in
the Shenandoah Case Study Area is 57.9 ueq/L (± 4.5 ueq/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 ueq/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
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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 El)
scoring system in tandem with SPAtially Referenced Regression on Watershed Attributes
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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 El for the Potomac River and Potomac Estuary was Bad.
• To improve the Potomac River and Potomac Estuary ASSETS El 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 El for the Neuse River/Neuse River Estuary was Bad.
• It was found that the Neuse River/Neuse River Estuary ASSETS El 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
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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, SC>42) and increased
mercury methylation in wetlands and aquatic environments. Decreases in sulfate
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Executive Summary
deposition will likely result in decreases in methyl mercury concentration; however,
spatial and biogeochemical variations nationally hinder establishing large scale dose-
response relationships.
• Nitrous oxide (NiO). 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 SC>2, and
concentrations of NO, NC>2, 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 (HNOs) vapor on vegetation in California's Transverse Range MCF,
HNOs 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.
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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
asANC
• 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.
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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
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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
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Executive Summary
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 El, 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 non-
atmospheric 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.
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Executive Summary
Table ES-2. Summary of Information Assessed in the Risk and Exposure Assessment to Aid in Informing Policy Based on Welfare
Effects.
Exposure Pathway
(Current Deposition
Levels)
(NADP/CMAQ,
2002)
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
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
Affected Ecosystem
(Case Study Areas)
Adirondack
Mountains, NY
Blue Ridge Mountains
and Shenandoah
National Park, VA
Kane Experimental
Forest (Allegheny
Plateau, PA)
Hubbard Brook
Experimental Forest
(White Mountains,
NH)
Ecological
Response
(Targeted Effect)
Acidification in
lakes and streams
Acidification of
forest soils
Ecological
Indicator
Fish species
richness, abundance,
composition,
ANC
Tree health
Red spruce, sugar
maple
Bc/Al ratio
Ecological Effect
Species losses of
fish, phytoplankton,
zooplankton;
changed community
composition,
ecosystem structure,
and function
Decreased tree
growth
Increased
susceptibility to
stress, episodic
dieback; changed
community
composition,
ecosystem structure,
and function
Ecosystem Service Affected
Annual recreational freshwater
fishing in New York State =
more than 13 million days
Approximately $66.4 million
in implied value to NY anglers
from a zero-out of nitrogen
and sulfur deposition
Provision of wood products
(sugar maple)
900 million board feet timber
production
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September 2009
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Executive Summary
Exposure Pathway
(Current Deposition
Levels)
(NADP/CMAQ,
2002)
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
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
Affected Ecosystem
(Case Study Areas)
Potomac River Basin,
Chesapeake Bay
Neuse River Basin,
Pamlico Sound
Southern California
Coastal Sage Scrub
Mixed Conifer Forest
(San Bernardino
Mountains and Sierra
Nevada Mountains,
CA)
Ecological
Response
(Targeted Effect)
Nutrient enrichment
in main stem river
of an estuary
Nutrient enrichment
in terrestrial
ecosystems
Ecological
Indicator
ASSETS El
Species composition
Ecological Effect
Habitat degradation,
algal blooms,
toxicity, hypoxia,
anoxia, fish kills,
decreases in
Hi oH i VPTQI tv
U1UU.1 V Wl olLV
Species changes,
nutrient enrichment
of soil, changes in
fire regime, changes
in nutrient cycling
Ecosystem Service Affected
Current saltwater
recreational fishing
26.1 million activity days
(North Carolina-
Massachusetts)
Annual benefits to California
residents hunting, fishing, and
wildlife viewing =
approximately $4.6 billion;
state expenditures for fire
suppression = $300 million
(2008)
Final Risk and Exposure Assessment
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September 2009
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Chapter 1 - Introduction
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 (802), 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.
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Chapter 1 - Introduction
of the specific compounds NC>2 and 862, 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 (FinalReport) (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
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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
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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 NC>2
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 NC>2 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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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 Re view 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 [ng/m3] of air), annual arithmetic average, calculated as the arithmetic mean of the
l-hourNO2 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.
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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, CAS AC 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., 862,
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 SC>2 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 andII (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
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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 SC>2 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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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 increasing-
damage 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.
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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.,
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NO2, NO, N2O, nitrogen trioxide [N^Os], nitrogen tetroxide [N2O4], and dinitrogen pentoxide
[N205]).
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 (HNOs) 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 (NHa) 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
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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 NC>2, 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.
NC>2 can also be further transformed to HNOs 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
v HNO,,
PANS
TRCI ojoo
XJ •.
TI !
mtrosammes,
nitro phenols, etc
I \oor> I
emissions
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, hv = a solar photon, R = an organic radical.
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1.3.2 Species of Sulfur Included in the Analyses
SC>2 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 [SOs], thiosulfate
[8203], sulfur heptoxide [820?]) and particulates (e.g., ammonium sulfate [(NFL^SO^)
(Figure 1.3-2). SC>2 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 (€82), 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 (H^SC^) and HNOs. Due to known acute effects on plants, SC>2
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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photosynthesis, and decreased growth. Similarly, exposure to sufficient concentrations of NC>2,
NO, PAN, and HNOs 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, andHNOs 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 HNOs 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 SOxmay 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
offish 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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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) Biogenicflux 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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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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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
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Oxidation Dissolution
SO2 - > H2SO4 -- > 2H*
NO,
Wet Deposition
Dry deposition s°z
NO,, NHX, SO* NO
Acidification of water + Eutrophication
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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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)?
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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
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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.
1. Air Quality
Indicators
Measured over a
specified
averaging time:
expressed in
terms of a
specified statistic
fforml
3.
Atmospheric
Deposition
Transformation
Function
8. Factors Related to
Characterizing
Adversity
7. Ecological
Indicator
Calculated over a
specified
averaging time:
expressed in terms
of a specified
statistic fforml
(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.
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
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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
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Chapter 1 - Introduction
McCurdy, T.R. 1994. Analysis of High 1-Hour NO 2 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 andits
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 andits
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
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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 Paniculate 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/R-
08/082F. U.S. Environmental Protection Agency, National Center for Environmental
Assessment-RTF 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
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Chapter 1 - Introduction
Wolff, G.T. 1993. On a NOx-focused control strategy to reduce Os. Journal of the Air and Waste
Management Association 43:1593-1596.
Wolff, G.T. 1995. CAS AC closure letter for the 1995 OAQPS Staff Paper. Letter sent to Carol
M. Browner, Administrator, U.S. Environmental Protection Agency. August 22.
Final Risk and Exposure Assessment 1-24 September 2009
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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
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Chapter 2 - Overview of Risk and Exposure Assessment
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
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Chapter 2 - Overview of Risk and Exposure Assessment
Table 2.1-1. Summary of Sensitive Characteristics, Indicators, Effects, and Impacted Ecosystem Services Analyzed for Each Case
Study Evaluated in This Review
Targeted
Ecosystem
Effect
Aquatic
Acidification
Terrestrial
Acidification
Aquatic
Nutrient
Enrichment
Characteristics of
Sensitivity
(Variable
Ecological Factors)
Geology, surface
water flow, soil
depth, weathering
rates
Geology, surface
water flow, soil
depth, weathering
rates
nitrogen-limited
systems, presence of
nitrogen in surface
water,
eutrophication
status, nutrient
criteria
Biological/
Chemical Indicator
Al
pH
ANC
Soil base saturation
Al
Ca
C:N ratio
Chlorophyll a,
macroalgae,
dissolved oxygen,
nuisance/toxic algal
blooms, submerged
aquatic vegetation
(SAV)
Ecological
Endpoint
Species richness,
abundance,
composition,
ANC
Tree health of
red spruce and sugar
maple,
ANC, base
cation :A1 ratio
Changes in
Eutrophication
Index (El)
Ecological Effects
Species losses of
fish, phytoplankton,
and zooplankton;
changed community
composition,
ecosystem structure,
and function
Decreased tree
growth,
increased
susceptibility to
stress, episodic
dieback; changed
community
composition,
ecosystem structure,
and function
Habitat degradation,
algal blooms,
toxicity, hypoxia,
anoxia, fish kills,
decreases in
biodiversity
Ecosystem Services
Impacted
Subsistence fishing,
recreational fishing,
other recreational
activities
Provision of food
and wood products,
recreational
activities, natural
habitat, soil
stabilization, erosion
control, water
regulation, climate
regulation
Commercial and
recreational fishing,
other recreational
activities, aesthetic
value, nonuse value
flood and erosion
control
Case Study Areas
Adirondack
Mountains, NY
(referred to as
Adirondack)
Shenandoah
National Park, VA
(referred to as
Shenandoah)
Kane Experimental
Forest (Allegheny
Plateau, PA)
Hubbard Brook
Experimental Forest
(White Mountains,
NH)
Potomac River
Basin, Chesapeake
Bay (referred to as
Potomac
River/Potomac
Estuary)
Neuse River Basin,
Pamlico Sound
(referred to as Neuse
River/Neuse River
Estuary)
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September 2009
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Chapter 2 - Overview of Risk and Exposure Assessment
Targeted
Ecosystem
Effect
Terrestrial
Nutrient
Enrichment
Characteristics of
Sensitivity
(Variable
Ecological Factors)
Presence of
acidophytic lichens,
anthropogenic land
cover
Biological/
Chemical Indicator
Cation exchange
capacity, C:N ratios,
Ca:Al ratios, NO3"
leaching and export
Ecological
Endpoint
Species
composition,
lichen
presence/absence,
soil root mass
changes, NO3
breakthrough to
water, biomass
Ecological Effects
Species changes,
nutrient enrichment
of soil, changes in
fire regime, changes
in nutrient cycling
Ecosystem Services
Impacted
Recreation, aesthetic
value, nonuse value,
fire regulation, loss
of habitat, loss of
biodiversity, water
quality
Case Study Areas
Coastal Sage Scrub
(southern, coastal
California) and
Mixed Conifer
Forest (San
Bernardino
Mountains of the
Transverse Range
and Sierra Nevada
Mountain Ranges,
California); Rocky
Mountain National
Park (a supplemental
study area)
Note: ANC = acid neutralizing capacity, SAV = submerged aquatic vegetation, El = eutrophication index.
Final Risk and Exposure Assessment
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September 2009
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Chapter 2 - Overview of Risk and Exposure Assessment
Potomac River/
Shenandoah^H Potomac Estuary
250 500 750 1,000
Kilometers
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.
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September 2009
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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
NC>2) 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
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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
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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
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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
5. Variable/Fixed
Factors
Atmospheric
Landscape
1. Air Quality
Indicators
3.
Atmospheric
Deposition
Transformation
Function
Measured over a
specified
8. Factors Related to
Characterizing
Adversity
expressed in
terms of a
specified statistic
(form)
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.
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 deposit!onal 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
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September 2009
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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
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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
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Chapter 2 - Overview of Risk and Exposure Assessment
ECOSYSTEM SERVICES
Provisioning
1 FOOD ^
• FRESH WATER h
WOOD AND FIBER
FUEL
^^^^^^^_
Supporting Regulating
NUTRIENT CYCLING CLIMATE REGULATION
mil FnpMiTiniu FLOOD REGULATION
SSS5S™ w— ™ i
...
Cultural
AESTHETIC '
• SPIRITUAL
• EDUCATIONAL
RECREATIONAL
LIFE ON EARTH - BIODIVERSITY
CONSTITUENTS OFV
^^ Security
^^^^^ PERSONAL SAFETY
^^^ SECURE RESOURCE ACCESS
^ff- SECURITY FROM DISASTERS
N(£
^^1 Basic material
for good life
ADEQUATE LIVELIHOODS
SUFFICIENT NUTRITIOUS FOOD
SHELTER
rl ^k ACCESS TO GOODS
r'^^M Health
STRENGTH
FEELING WELL
ACCESS TO CLEAN AIR
AND WATER
Good social relations
SOCIAL COHESION
MUTUAL RESPECT
ABIUTYTO HELP OTHERS
VELL-BEING
Freedom
of choice
and action
OPPORTUNITY TO BE
ABLE TO ACHIEVE
WHAT AN INDIVIDUAL
VALUES DOING
AND BEING
Source: Millennium Ecosystem 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
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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
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Chapter 2 - Overview of Risk and Exposure Assessment
/
EPA Action
^ i i ^
Ecosystems
4.7 ^7 -^7
Ecological goods and services
affected by the policy
/
Planning and problem
formulation
Goods and services
identified
/
Ecological analysis
Goods and services
quantified
/
Economic analysis
^^
Goods and
services
monetized ^^-~-^~^
^^^^^
A
3
y services not
J [/ identified
/ |\ Identified goods
y and services not
1 |/ quantified
/ i\ Quantified
\ good and
\/ services not
/ * 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
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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.
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Chapter 2 - Overview of Risk and Exposure Assessment
Ambient Air Quality
Indicator
Exposure Pathway
Affected Ecosystem
Ecological Response
(ecological indicate?)
Ecological Effect
Ecological Benefit/
Welfare Effect
Policy based on
Welfare Effects
NOX/SOX
Concentrations
T
Atmospheric N & S
Deposition
Acidification
(lake/stream ANC)
Change in Ecosystem
Structure & Processes
(fish species richness)
Change in
Ecosystem Services
(recreational fishing)
T
Secondary
idard
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
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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 C-
VPESS, 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
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Chapter 2 - Overview of Risk and Exposure Assessment
Aquatic Enrichment Example
Stressor Effects
Ecological 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. Indicators
may be utilized at several levels of ecosystem analysis.
Symptoms: The signs of response to a given level of stressor exposure within an ecosystem
that are not readily measured/quantifiable.
Symptoms*
. Changes in dominant . Loss of submerged
algal species aquatic vegetation
. Excessive macroalgae . Habitat alteration
Prowth . HABs
. Low water clarity . Hypoxia/low DO
. Increased organic . Species a|teration
matter/chlorophyll a
Ecological Indicators
• Type/duration/frequency/
size of HABs
• Change in areal SAV
coverage
• Clarity/light penetration
through secchi depth
• Frequency/areal coverage
of anoxia/hypoxia
Endpoint: An ecological
entity and its attributes.
Biological*
Ecosystem Services:
The ecological processes or
functions having monetary or
nonmonetary value to individual
or society at large.
Fish population - Fish kills
Fish population - Species
diversity
Water quality - Surface
scum
Provisioning*
Physical*
Food
Habitat
Health protection
Valuation of
Ecosystem Services:
The determination of the
monetary or nonmonetary 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.
Habitat quality - Loss of
SAV over time
Shoreline quality -
Increased erosion
Regulating*
Monetary*
Chemical*
Flood control
Water purification
Climate control
Control of invasives
Producer/consumer
surplus
Willingness to pay/
accept
Avoided costs
Water quality —
Elevated toxics
Water quality - Odors
Cultural*
Non-Monetary*
Recreation
• Swimmable
• Beatable
Tourism
Perceived impacts
Qualitative measures
Supporting*
Primary production
Nutrient cycling
'Lists are examples and not meant to be comprehenisve
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.
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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
eutrophi cation 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
eutrophi cation, 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
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Chapter 2 - Overview of Risk and Exposure Assessment
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 socio-
economic 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).
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Chapter 2 - Overview of Risk and Exposure Assessment
Table 2.4-1. Ecological Impacts Associated with Acidification, Nutrient Enrichment, and Increased Mercury Methylation and Their
Associated Ecosystem Services
Targeted Ecosystem
Effect
Aquatic Acidification
Terrestrial Acidification
Aquatic Nutrient
Enrichment
Provisioning Services
• Fishing (subsistence)
• Food, wood products
• Commercial fishing
Regulating Services
• Biological control
• Erosion control
• Fire regulation
• Hydrologic
• Climate
• Erosion control
• Flood control
Cultural Services
• Recreational fishing
• Nonuse
• Recreational activity
• Aesthetic
• Nonuse
• Recreational activity
• Aesthetic
• Nonuse
Supporting Services
• Not Available
• Not Available
• Nutrient cycling
Terrestrial Nutrient Enrichment
Coastal Sage Scrub
Mixed Conifer Forest
Sulfur and Mercury
Methylation
• Not Available
• Not Available
• Commercial and
subsistence fishing
• Fire regulation
• Hydrologic control
• Climate
• Hydrologic control
• Climate
• Not Available
• Recreational activity
• Aesthetic
• Nonuse
• Recreational activity
• Aesthetic
• Nonuse
• Recreational fishing
• Nonuse
• Not Available
• Nutrient cycling,
• Not Available
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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
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Chapter 2 - Overview of Risk and Exposure Assessment
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.
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Chapter 2 - Overview of Risk and Exposure Assessment
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
Model
Complete
Name
Description
Case Study
Application
Model Type
CMAQ
Community Multiscale
Air Quality
The CMAQ model is a
comprehensive, three-
dimensional 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.
All
Deterministic, process-
driven model
MAGIC
Model of Acidification of
Groundwater in Catchments
MAGIC is a lumped-
parameter 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
(Aherneetal.,2003).
Aquatic acidification
Lumped-parameter model,
which follows mass balance
8MB
Simple Mass Balance
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 biogeo-
chemically safe limit.
Terrestrial acidification
Mass balance model over
average conditions
SPARROW
SPAtially Referenced
Regression on Watershed
Attributes
SPARROW relates in-
stream 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.
Aquatic nutrient
enrichment (in tandem
with ASSETS)
Empirical/statistical
model over average
ASSETS
Assessment of
Estuarine Trophic
Status
ASSETS represents a
Pressure-State-
Response framework to
assess the potential for
eutrophication now or
in the future for an
estuary. It is a
categorical ranking,
where each of three
indices results in a
score that, when
combined, result in a
final overall score. The
three indices consist of
(1) Influencing Factors/
Overall Human
Influence, (2) Overall
Eutrophic Condition,
and (3) Determined
Future Outlook.
Aquatic nutrient
enrichment (in tandem
with SPARROW)
Categorical, based on
three numeric and
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Model
Temporal
Features
Spatial Scale
Used in Case
Study Analyses
Strengths
CMAQ
Dynamic (hourly time
step)
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).
• Is used for the
continental United
States.
• Is a process-based
model, which
includes chemical
speciation.
MAGIC
principles over time
Dynamic (monthly and
annual time step)
MAGIC is applied to 44
lakes in the Adirondack
Case Study Area and 16
streams in the Shenandoah
Case Study Area.
• 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
8MB
Steady-state (annual
average results)
The 8MB 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.
• 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.
SPARROW
conditions
Steady-state (annual
average results)
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).
• 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.
ASSETS
categorical indices for
average conditions
Steady-state (typically
annual average results)
ASSETS considers the
tidal, mixing, and
freshwater zones across
a single estuary.
• Has been used to
assess estuarine
status in all major
coastal estuaries in
the continental
United States and at
sites in Europe.
• Accounts for several
different classes of
evaluation: water
quality, nitrogen
loadings, physical
conditions within
the estuary, and
future expected
changes for the
estuary.
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Model
Weaknesses
CMAQ
• Has current
minimum grid scale
of 12 km.
MAGIC
background information
to draw from because of
the numerous
applications in its 20
years of use.
• Has an automated built-
in 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.
• Must be parameterized
for each application.
• Has controlled release of
program.
8MB
• 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
SPARROW
• Model performance/
error is explicitly
included (e.g.,
quantifies
uncertainties based on
model coefficient
error and unexplained
variability in the
observed 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
ASSETS
• Provides an
opportunity to link
to watershed
nitrogen loading
models, such as
SPARROW.
• Has categorical
index.
• Is not dynamic in
time.
• Does not explicitly
include deposition
measurements.
• Cannot differentiate
between nitrogen
species.
• Does not explicitly
include uncertainty
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Model
CMAQ
MAGIC
8MB
SPARROW
ASSETS
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.
analysis.
Has limited
extrapolation of
results outside of
specific estuary
studied.
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
National Oceanic and
Atmospheric
Administration
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.
Deposition is not
explicitly included in
the assessment, but
may be included in the
watershed model used
to determine loadings
to the estuary (e.g.,
SPARROW).
Note: PM = participate matter, USGS = U.S. Geological Survey.
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2.6 REFERENCES
Aherne, J, PJ. Dillon, and BJ. 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, andR. Alkons-Wolinsky. 2008.
Data to Support Statistical Modeling oflnstream 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. EPA-
452/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
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Chapter 2 - Overview of Risk and Exposure Assessment
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/R-
08/082F. U.S. Environmental Protection Agency, National Center for Environmental
Assessment-RTF 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.
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
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 non-
ambient 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 (FffiEF) 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.
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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 (802), sulfur trioxide (SOs), and disulfur monoxide (82©); 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,
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
1998). The ambient concentrations of NOX, NH3, and 862 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 NC>2 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 gas-
phase nitric acid (HNOs), 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
(02), and water (H2O) to form sulfuric acid (H2SO/t). 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 HNOs to form ammonium nitrate (NFLtNOs) and with
sulfate (SO42") to form ammonium sulfates, which are important components of nitrogen and
sulfur deposition. Thus, NOX, SOX, and NHa 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
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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, NHa, and SC>2 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.
National Totals
Electric Generation Units
Industrial Point Sources
Stationary Area
NOX
Emissions (million tons)
4.619
2.362
1.529
Percent of Total
22%
11%
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.
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National Totals
On-road
Nonroad
Aircraft/Locomotive/Marine
Fires
Total
NOX
Emissions (million tons)
7.839
2.219
2.611
0.080
21.259
Percent of Total
37%
10%
12%
<1%
Table 3.2-2a. Annual NOX Emissions across Major Source Categories in 2002 for the Eastern
United States.
Eastern U.S.
Electric Generation Units
Industrial Point Sources
Stationary Area
On-road
Nonroad
Aircraft/Locomotive/Marine
Fires
Total
NOX
Emissions (million tons)
4.094
2.031
1.295
6.250
1.709
2.038
0.028
17.445
Percent of Total
23%
12%
7%
36%
10%
12%
<1%
Table 3.2-2b. Annual NOX Emissions across Major Source Categories in 2002 for the Western
United States.
Western U.S.
Electric Generation Units
Industrial Point Sources
Stationary Area
Onroad
Nonroad
Aircraft/Locomotive/Marine
Fires
Total
NOX
Emissions (million tons)
0.525
0.331
0.234
1.589
0.510
0.573
0.055
3.817
Percent of Total
14%
9%
6%
42%
13%
15%
1%
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.
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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).
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
Legend
NOx tons/year
while =0.0
> 0 to 25.000
> 25.000 to 100 000
> 100 000 to 250.000
| > 250.000 to 500.000
^| > 500.000 to 1.000.000
^H »1.000.000 to 2.458.200
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 NHa emissions are fertilized soils and livestock.
Motor vehicles and stationary combustion are small emitters of NHa. Some NHa is emitted as a
byproduct of NOX reduction in motor vehicle catalysts. The spatial patterns of 2002 annual NH3
emissions are shown in Figure S.2-26. The highest emissions of NHa 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 NHa 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.
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exceeding 5,000 tons/yr. Rocky Mountain National Park is adjacent to an area with relatively
high NHs 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.
Legend
NH3 tonstyear
white -0.0
>0lc>100
MOD to 1.000
> 1,00010 2.500
[ > 1.500 to 5.000
^| > 5.000 to 10.000
^H > 10.000 to 21.908
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 Rangi
9 Rocky Mountain National Park
Figure 3.2-2. Spatial distribution of annual total NHa emissions (tons/yr) for 2002.
3.2.1.3 SOX Emissions
The distributions of SC>2 emissions for major source categories nationally are provided in
Table 3.2-3. Emissions of 862 for the East and West are presented in Tables 3.2-4a and b,
respectively. Anthropogenic emissions of 862 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 (SC>2 or
during combustion. The higher sulfur content of coal compared to other types of fossil fuels
results in higher SC>2 emissions from electrical utilities using coal as fuel.
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Emissions of SC>2 are more than 10 times greater in the East than in the West. Emissions
from electric generation units are the largest contributor to 862 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 SC>2 in the West compared to the East7.
The largest natural sources of SC>2 are volcanoes and wildfires. Although SC>2 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 862
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 SO2Emissions across Major Source Categories in 2002.
National Totals
Electric Generation Units
Industrial Point Sources
Stationary Area
On-road
Nonroad
Aircraft/Locomotive/Marine
Fires
Total
SO2
Emissions (million tons)
10.359
2.249
1.250
0.242
0.188
0.533
0.050
14.871
Percent of Total
70%
15%
8%
2%
1%
4%
<1%
Table 3.2-4a. Annual SC>2 Emissions across Major Source Categories in 2002 for the Eastern
United States.
Eastern U.S.
Electric Generation Units
Industrial Point Sources
Stationary Area
On-road
SO2
Emissions (million tons)
9.923
2.057
1.116
0.214
Percent of Total
71%
15%
8%
2%
Note that SO2 emissions from fires are understated in the NEI because of an error in the emissions calculations.
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Eastern U.S.
Nonroad
Aircraft/Locomotive/Marine
Fires
Total
SO2
Emissions (million tons)
0.162
0.398
0.011
13.881
Percent of Total
1%
3%
<1%
Table 3.2-4b. Annual SO2 Emissions across Major Source Categories in 2002 for the Western
United States.
Western U.S.
Electric Generation Units
Industrial Point Sources
Stationary Area
On-road
Nonroad
Aircraft/Locomotive/Marine
Fires
Total
SO2
Emissions (million tons)
0.436
0.192
0.134
0.029
0.026
0.136
0.035
0.988
Percent of Total
44%
19%
14%
3%
3%
14%
4%
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.
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Legend
S02 tons/year
white =00
> 010100
> 100 to 1,000
>roootos.ooo
| > 5.000 to 25.000
^| > 25.00010100,000
^H > 100.000 to 245,740
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 SC>2 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 SC>2, 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
SC>2 concentrations in unmonitored areas, particularly rural locations. As noted in the ISA (U.S.
EPA, 2008b), ambient NC>2 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 NC>2, 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 NC>2 concentrations and
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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 x 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, NCh, 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 model-
predicted 2002 annual average NOy concentrations is shown in Figure 3.2-4.
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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.
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Legend
< 1 Oppb
^)
>= 3.0 to < 5.0
| | >= 5.0 10 < 7.0
= 7.0 to < 10.0
I >= 25.0
Annual Average 2002 CM Ad-Predicted NOy (ppb)
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 862 concentrations for the period 2003 through 2005 are
presented in Table 2-23 of the ISA (U.S. EPA, 2008b). 862 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 non-
urban concentrations at the 90th percentile were 8 ppb. In an analysis of 11 cities, sites with the
highest annual mean SC>2 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
SC>2 emissions from electric generating units. At suburban and rural CASTNET sites, annual
average 862 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.
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The 2002 annual average model-predicted 862 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. SC>2 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, 862 predictions are much lower than in the East and
are generally <0.5 ppb, except in the vicinity of sources of 862.
The Potomac River/Potomac Estuary Case Study Area has the highest 862 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. SC>2 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 862 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.
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
^]>=1.0to<3.0
L^ »= 3.0 to f 5.0
| | >= 5.0 to < 7.0
| j >= 7.0 to < 10.0
H >= 10.0 to < 25.0
B| ---= 25.0
Annual Average 2002 CMAQ-Preclicted S02 (ppb)
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 parti culate 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
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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 (SO42") Oxidized nitrogen wet deposition was
calculated from measured nitrate (N(V) 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 N(V, HNOs, NO, NO2, dinitrogen pentoxide (TSPzOs), 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.
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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
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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 NHa 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 NHa 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.
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
Legend
^| >= J 0 to < 3 0
. >- 3.0 ta< 4.0
| |a-4.0to<5.0
^]>=5.0to<7.0
I I >- 7.0 to < 9.0
^H >= 9.0 to < 14.0
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
•total On N - CMAQ dry + NADP wet
Figure 3.2-6. Total wet plus dry oxidized nitrogen deposition (kg N/ha/yr) in 2002.
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
1 Adirondack
2 Shenandoah
3 Potomac River / Polomac Estuary
4 Neuse River I Neuse Estuary
5 Kane Experimental Forest
fi Hubbard Brook Experimental Forest
7 Mixed Conifer Forest (Transverse Range)
8 Mixed Conifer Forest (Sierra Nevada Range)
9 Rocky Mountain National Park
Total Re N - CMAQdry + NADPwet
Figure 3.2-7. Total wet plus dry reduced nitrogen deposition (kg N/ha/yr) in 2002.
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
Legend
| » 2.0(0 < 30
~]«3.Cto<40
i >= 4 0 to < 5.0
= 5.0 to < 7.0
= 7.0 (o < 9.0
= 9.0(0<14.0
^t40to<20.0
20.0
| 1
1 Adirondack
2 Shenandoah
3 Polomac River 1 Potomac Estuary
4 Neuse River/Neuse Estuary
5 Kane Experimental Foresl
6 Hubbard Brook Experimental Foresl
7 Mixed Conifer Foresl {Transverse Range)
S Mixed Conifer Forest (Sierra Nevada Range)
9 Rocky Mountain National Park
Total N - CMAOdfy + NADPoet
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 SC>42". Smaller
contributions to deposition are made by dry SC>2 and dry SC>42".
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
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September 2009
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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.
Legend
I 5-=100»<160
^B >= 16 Ota-; 540
^B •>» ;-j o to < HI o
• » 30.0
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
y
Tufa/ S. CMAQ dry t NADP MX
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, NC>2 and
SC>2, 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.
ForNC>2, 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
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September 2009
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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 policy-
relevant background SC>2 concentrations are 30 ppt. In general, policy-relevant background
concentrations of SC>2 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 HNOs+
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
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
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 NCV, NH4+, and SC>42" 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.
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
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
1* The 99° west meridian to separate the eastern and western United States was used in this assessment.
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
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 (GlS)-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 Paver 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.
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
• 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-la and 3.3-
Ib 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 NHa 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.
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
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-la and 3.3-lb). 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 inter-
annual 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-la 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?
Final Risk and Exposure Assessment 3-29 September 2009
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
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 terrain-
induced 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.
Final Risk and Exposure Assessment 3-30 September 2009
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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 Areas"
Adirondack
Hubbard Brook Experimental Forest
Kane Experimental Forest
Potomac River/Potomac Estuary
Shenandoah
Neuse River/Neuse River Estuary
Mixed Conifer Forest
(Sierra Nevada Range portion)
Mixed Conifer Forest
(Transverse Range portion)
Rocky Mountain National Park
(a supplemental area)
2002 Annual Total Deposition
Total Reactive Nitrogen
(kg N/ha/yr)
10
8
13
12
11
14
4
10
4
Total Sulfur
(kg S/ha/yr)
9
7
20
14
11
8
1
2
1
a Excludes the Coastal Sage Scrub Case Study Area.
Annual Total Reactive Nitrogen Deposition: 2002 - 2005
25
T-20
15
o
0.
a, 10
I 5
Neuse
River
Kane
Forest
Potomac
River
Shenandoah Adirondack
Hubbard
Brook
Figure 3.3-la. Annual total reactive nitrogen deposition (kg N/ha/yr) from 2002
through 2005 for each case study area in the East.
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September 2009
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
Annual Total Reactive Nitrogen Deposition: 2002 - 2005
25
s-20
15
o
~ 5
Transverse
Range
Sierra Nevada
Range
Rocky Mountain
National Park
Figure 3.3-lb. 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 NET?.
As indicated by comparing Figures 3.2-2 and 3.2-3, NOX emissions are much greater and more
widespread compared to emissions of NHa, 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 NHa
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
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September 2009
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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
NH? 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.
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
Relative Amount of Oxidized vs Reduced Nitrogen
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 Case Study Area: 2002 Total Reactive Nitrogen Deposition
Re N-Dry
6%
Re N - Wet
24%
OxN -Dry
32%
OxN-Wet
38%
Figure 3.3-3a. Components of total reactive nitrogen deposition for 2002 in the
Adirondack Case Study Area.
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September 2009
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
Hubbard Brook Experimental Forest Case Study Area: 2002 Total Reactive Nitrogen Deposition
Re N - Dry
6%
Re N - Wet
21%
Ox N - Dry
38%
Ox N - Wet
35%
Figure 3.3-3b. Components of total reactive nitrogen deposition for 2002 in the
Hubbard Brook Experimental Forest Case Study Area.
Kane Experimental Forest Case Study Area: 2002 Total Reactive Nitrogen Deposition
Re N - Dry
4%
Re N - Wet
22%
Ox N - Dry
40%
Ox N - Wet
34%
Figure 3.3-3c. Components of total reactive nitrogen deposition for 2002 in the
Kane Experimental Forest Case Study Area.
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September 2009
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
Neuse River/Neuse River Estuary Case Study Area: 2002 Total Reactive Nitrogen Deposition
Re N - Dry
38%
Ox N - Dry
29%
Re N - Wet
17%
Ox N - Wet
16%
Figure 3.3-3d. Components of total reactive nitrogen deposition for 2002 in the
Neuse River/Neuse River Estuary Case Study Area.
Potomac River/Potomac Estuary Case Study Area: 2002 Total Reactive Nitrogen Deposition
Re N - Dry
15%
Re N - Wet
18%
Ox N - Dry
44%
Ox N - Wet
23%
Figure 3.3-3e. Components of total reactive nitrogen deposition for 2002 in the
Potomac River/Potomac Estuary Case Study Area.
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September 2009
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
Shenandoah Case Study Area: 2002 Total Reactive Nitrogen Deposition
Re N - Dry
16%
Re N - Wet
18%
Ox N - Dry
43%
Ox N - Wet
23%
Figure 3.3-3f. Components of total reactive nitrogen deposition for 2002 in the
Shenandoah Case Study Area.
Rocky Mountain National Park: 2002 Total Reactive Nitrogen Deposition
Re N - Dry
10%
Re N - Wet
23%
Ox N - Dry
42%
Ox N - Wet
25%
Figure 3.3-3g. Components of total reactive nitrogen deposition for 2002 in the
Rocky Mountain National Park.
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September 2009
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
Mixed Conifer Forest (Sierra Nevada Range) Case Study Area: 2002 Total Reactive Nitrogen Deposition
Re N - Dry
19%
Ox N - Dry
43%
Re N - Wet
24%
Ox N - Wet
14%
Figure 3.3-Sh. Components of total reactive nitrogen deposition for 2002 in the
Sierra Nevada Range portion of the Mixed Conifer Forest Case Study Area.
Mixed Conifer Forest (Transverse Range) Case Study Area: 2002 Total Reactive Nitrogen Deposition
Re N - Dry
16%
Ox N - Dry
75%
Figure 3.3-Si. Components of total reactive nitrogen deposition for 2002 in the
Transverse Range portion of the Mixed Conifer Forest Case Study Area.
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September 2009
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
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.
Final Risk and Exposure Assessment 3-39 September 2009
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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 NHs 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 NHa
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
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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 NHa 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 NHa 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
NHa 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
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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
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
Adirondack
Shenandoah
Potomac River / Potomac Estuary
Neuse River / Neuse Estuary
Kane Experimental Forest
Hubbard Brook Experimental Forest
<3.0
>= 3.0 to < 4.0
>= 4.0 to < 6.0
>=6.0to<:8.0
>=8.0to< 100
I I >= 10.0 to < 120
^| >=12.0to< 14.0
H -•= 14.0 to < 24.0
^H >= 24.0
Total Deposition - Nitrogen
CMAQ dry + NADP wet
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
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September 2009
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
Adirondack
Shenandoah
Potomac River / Potomac Estuary
Neuse River / Neuse Estuary
Kane Experimental Forest
Hubbard Brook Experimental Forest
<2.0
>=2.0to<30
>=3.0to<40
>=4.0 to < 5.0
>=5.0to<70
I |>=7.0tO<90
^| >=9.0to< 14.0
BB >= 140to<20.0
^H >= 20.0
Total Deposit/on - Ox N
CMAQdry + NADPwet
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
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September 2009
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
Adirondack
Shenandoah
Potomac River / Potomac Estuary
Neuse River / Neuse Estuary
Kane Experimental Forest
Hubbard Brook Experimental Forest
<2.0
>=2.0to<30
>=3.0to<40
>=4.0 to < 5.0
>=5.0to<70
I |>=7.0tO<90
^| >=9.0to< 14.0
H >= 14.0 to < 20.0
^H >= 20.0
Total Deposit/on - Re N
CMAQdry + NADPwet
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.
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September 2009
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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
<2.0
>=2.0to<30
>=3.0to<40
>=4.0 to < 5.0
>=5.0to<70
I |>=7.0tO<90
^| >=9.0to< 14.0
BB >= 140to<20.0
^H >= 20.0
NADP Wet Deposition - Total N
Figure 3.3-4d. Annual total wet reactive nitrogen deposition (kg N/ha/yr) in 2002
for the case study areas in the East.
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September 2009
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
Adirondack
Shenandoah
Potomac River / Potomac Estuary
Neuse River / Neuse Estuary
Kane Experimental Forest
Hubbard Brook Experimental Forest
<2.0
>=2.0to<30
>=3.0to<40
>=4.0 to < 5.0
>=5.0to<70
I |>=7.0tO<90
^| >=9.0to< 14.0
H >= 14.0 to < 20.0
^H >= 20.0
CMAQ Dry Deposition - Total N
Figure 3.3-4e. Annual total dry reactive nitrogen deposition (kg N/ha/yr) in 2002
for the case study areas in the East.
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September 2009
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
•=2.0
>= 2.0 to < 3.0
>= 3.0 to < 6.0
>= 6.0 to < 8.0
>= 8.0 to < 12,0
>= 12 0 to < 18.0
>= 18.0 to < 24.0
>= 24 0
7 Mixed Conifer Forest (Transverse Range)
8 Mixed Conifer Forest (Sierra Nevada Range)
9 Rocky Mountain National Park
CMAQ Dry + NADP Wet Deposition - Total N
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.
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September 2009
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
<2.0
>= 2.0 to < 3.0
•>= 3.0 to < 6.0
>= 6.0 to < 8.0
>- 8.0 to < 12.0
>= 12.0 to < 18.0
>= 18.0 to < 24.0
>= 24.0
7 Mixed Conifer Forest (Transverse Range)
8 Mixed Conifer Fores! (Sierra Nevada Range)
9 Rocky M our tain National Park
CMAQ Dry + NADP Wet Deposition - Total Ox N
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.
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September 2009
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
>=2.0to<3.0
>=3.0to <6.0
| | >= 6.0 to < 8.0
>=8.0to< 12.0
>= 12.0 to < 18.0
>= 18.0to <24.0
>= 24.0
7 Mixed Conifer Forest (Transverse Range)
8 Mixed Conifer Forest (Sierra Nevada Range)
9 Rocky Mountain National Park
CMAQ Dry + NADP Wet Deposition - Total Re N
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.
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September 2009
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
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.
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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
c
<
s.
Winter
Spring
Summer
Fall
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 Experimental Forest Case Study Area
Winter
Spring
Summer
Fall
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 Experimental Forest Case Study Area
Winter
Spring
Summer
Fall
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/Potomac Estuary Case Study Area
Winter
Spring
Summer
Fall
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 Forest Case Study Area
Winter
Spring
Summer
Fall
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/Neuse River Estuary Case Study Area
ra
3
I
•5
Winter
Spring
Summer
Fall
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 National Park
50
45
40
35
30
25
20
15
10
5
0
30
20
28
23
Winter
Spring
Summer
Fall
Figure 3.3-6g. Percentage of 2002 total reactive nitrogen deposition in the Rocky
Mountain National Park.
Percent of Total 2002 Reactive Nitrogen Deposition
Mixed Conifer Forest (Sierra Nevada Range) Case Study Area
Winter
Spring
Summer
Fall
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
en
AC
Af\
oe _
CU
3
c on
c JU
<
0 25
4-1
C
P*" on
-------
Chapter 3 - Sources, Ambient Concentrations, and Deposition
Hubbard Brook Case Study Area
Percent of 2002 Reactive Nitrogen Deposition in each Season
Dry Ox N Dry Re N
Wet Ox N
Wet Re N
Precip
(Winter
B Spring
D Summer
DFall
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 Experimental Forest Case Study Area
Percent of 2002 Reactive Nitrogen Deposition in each Season
S
Dry Ox N Dry Re N
Wet Ox N
Wet Re N
Precip
I Winter
H Spring
D Summer
DFall
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
Potomac River/Potomac Estuary Case Study Area
Percent of 2002 Reactive Nitrogen Deposition in each Season
<
1
Dry Ox N Dry Re N
Wet Ox N Wet Re N
Precip
I Winter
H Spring
D Summer
DFall
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 Case Study Area
Percent of 2002 Reactive Nitrogen Deposition in each Season
50
45
40
1 35
1 30
c
< 25
•5
£ 20
8
11S
10
I
i
i
i
fa
n
\
l
i
i
i
fa
i — |
1
fa
i
i
i
z
i
\
i
i
fa
i — i
1
i
i
i
fa
fa
Dry Ox N Dry Re N
Wet Ox N
Wet Re N
Precip
I Winter
Spring
DSummer
DFall
Figure 3.3-7e. Percentage of 2002 reactive nitrogen deposition for each
component of nitrogen deposition in the Shenandoah Case Study Area.
Final Risk and Exposure Assessment
3-58
September 2009
-------
Chapter 3 - Sources, Ambient Concentrations, and Deposition
Neuse River/Neuse River Estuary Case Study Area
Percent of 2002 Reactive Nitrogen Deposition in each Season
Dry Ox N Dry Re N
Wet Ox N
Wet Re N
Precip
(Winter
B Spring
D Summer
DFall
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.
Rocky Mountain National Park
Percent of 2002 Reactive Nitrogen Deposition in each Season
Dry Ox N Dry Re N
Wet Ox N Wet Re N
Precip
(Winter
a Spring
• Summer
DFall
Figure 3.3-7g. Percentage of 2002 reactive nitrogen deposition for each
component of nitrogen deposition in the Rocky Mountain National Park.
Final Risk and Exposure Assessment
3-59
September 2009
-------
Chapter 3 - Sources, Ambient Concentrations, and Deposition
Mixed Conifer Forest (Sierra Nevada Range) Case Study Area
Percent of 2002 Reactive Nitrogen Deposition in each Season
Dry Ox N Dry Re N
Wet Ox N Wet Re N
Precip
I Winter
B Spring
D Summer
DFall
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.
Mixed Conifer Forest (Transverse Range) Case Study Area
Percent of 2002 Reactive Nitrogen Deposition in each Season
60
50
40
< 30
14—
o
•£
8 20
10
Dry Ox N Dry Re N
Wet Ox N Wet Re N
Precip
I Winter
0 Spring
D Summer
DFall
Figure 3.3-7L 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.
Final Risk and Exposure Assessment
3-60
September 2009
-------
Chapter 3 - Sources, Ambient Concentrations, and Deposition
Seasonal Variation in 2002 NH3 Emissions
NY
NH
PA
MD
VA
NC
CO
CA
D Winter D Spring D Summer DFall
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 through 2005, followed by a decrease in deposition in 2006 and 2007 (U.S. EPA, 2009).
Overall for these 34 sites, sulfur concentrations in wet deposition declined from 2002 to 2004,
but then increased from 2005 to 2007 back to the levels monitored in 2002. As in the analysis for
Final Risk and Exposure Assessment
3-61
September 2009
-------
Chapter 3 - Sources, Ambient Concentrations, and Deposition
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 Potomac River/Potomac Estuary Case Study Area, and that wet sulfur deposition in 2002 was
on the low end of the range over this time period. During the most recent 10-year period, wet
sulfur deposition in the two case study areas and Rocky Mountain National Park in the West was
low, and generally in the range of 1 to 3 kg S/ha/yr. In 2002, wet sulfur deposition for both the
Transverse 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 Mixed
Conifer Forest Case Study Area, wet sulfur deposition in 2002 was in the range of the magnitude
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 to determine the reasons for the
observed 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.
Final Risk and Exposure Assessment 3-62 September 2009
-------
Chapter 3 - Sources, Ambient Concentrations, and Deposition
25 -,
?20:
re
O)
f 15-
o
U)
o
S"10
Q
a -
3 5
0
<
Annual Total Sulfur Deposition:
,— I
2002-
2005
PI
c\f co ^f- *o f\f co ^f- *o
r— |
f\f Co ^- *O
a o o o
Kane Potomac Shenandoah
Forest River
a
V
IV
V
<0
V
Neuse
e
a
V
V
§
"
<0
IV
e
ts
V
—
=>
—
IV
<0
V
Adirondack Hubbard
River
Brook
Figure 3.3-9a. Annual sulfur deposition (kg S/ha/yr) from 2002 through 2005 for
each case study area in the East.
>, 20
re
-E
C
O
U)
o
0. 1U
o
3
^ *%
Annual Sulfur Deposition: 2002 - 2005
mnn
Transverse
Range
°
^^^^ ^^m^
Sierra Rocky
Nevada Mtn
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.
Final Risk and Exposure Assessment
3-63
September 2009
-------
Chapter 3 - Sources, Ambient Concentrations, and Deposition
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 SC>2. In
general, for the case study areas, those areas that are farthest from sources of high SC>2 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 portion) case study areas, as well as the Rocky Mountain National Park. Each of these
areas is fairly distant from sources of high 862 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 SC>2 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.
Final Risk and Exposure Assessment 3-64 September 2009
-------
Chapter 3 - Sources, Ambient Concentrations, and Deposition
2002 Wet vs Dry Percent of Annual Total Sulfur Deposition
o
o
1—
o
Q.
100
80
70
60
30
20
10
0
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
100
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.
Final Risk and Exposure Assessment
3-65
September 2009
-------
Chapter 3 - Sources, Ambient Concentrations, and Deposition
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
The Shenandoah Case Study Area is on the eastern side of the region of high sulfur
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.
28 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.
29 See footnote 19 for caveats concerning the analysis of geographic variations in deposition for the case study areas
in the West.
Final Risk and Exposure Assessment 3-66 September 2009
-------
Chapter 3 - Sources, Ambient Concentrations, and Deposition
Potomac River/Potomac Estuary Case Study Area
There was considerable variation in sulfur deposition across the Potomac River/Potomac
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 in the far northwestern portion of this area, which is near sources of
high SC>2 emissions in western Pennsylvania. Lower amounts of sulfur deposition of 14 kg
S/ha/yr or more is found over the eastern half 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 862
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 highest
near the Raleigh-Durham urban area (14 kg S/ha/yr or more), and in particular, near a source of
high SC>2 emissions located near the North Carolina/Virginia border. Sulfur deposition generally
decreases from 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/yr 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
deposition decreases with distance from the Los Angeles urban area. Sulfur deposition in the San
Bernardino Mountains north of Los Angeles is in the range of 0.5 to 2 kg S/ha/yr.
Final Risk and Exposure Assessment 3-67 September 2009
-------
Chapter 3 - Sources, Ambient Concentrations, and Deposition
Adirondack
Shenandoah
Potomac River / Potomac Estuary
Neuse River / Neuse Estuary
Kane Experimental Forest
Hubbard Brook Experimental Forest
30
= 3.0 to < 4.0
= 4.0 to < 6.0
= 6.0 to < 8.0
= 8.0 to < 100
= 10.0 to < 120
= 12.0 to < 14.0
>= 14.0 to < 24.0
>=24.0
Total Deposition Sulfur
CMAQ dry + NADP wet
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.
Final Risk and Exposure Assessment
3-68
September 2009
-------
Chapter 3 - Sources, Ambient Concentrations, and Deposition
Adirondack
Shenandoah
Potomac River / Potomac Estuary
Neuse River / Neuse Estuary
Kane Experimental Forest
6 Hubbard Brook Experimental Forest
<2.0
>=2.0to<30
>=3.0to<40
>=4.0to<5.0
>=5.0to<6.0
I I >= 6.0 to < 7.0
^| >=7.0to<8.0
••-=.? 0:o- y 0
' I >= 9 0
NADP Wet Deposition Sulfur
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
1 Adirondack
2 Shenandoah
3 Potomac River / Potomac Estuary
4 Neuse River / Neuse Estuary
5 Kane Experimental Forest
6 Hubbard Brook Experimental Forest
<2.0
>=2.0to<30
>=3.0to<40
>=4.0 to < 5.0
>=5.0to<70
I |>=7.0tO<90
^| >=9.0to< 14.0
H >= 14.0 to < 20.0
^H >= 20.0
Dry Deposition Sulfur
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
Legend
| | »=0.5to<1.0
I | >=1.0tO<2.0
I | >= 2.0 to < 3.0
I | >= 3.0 to < 4.0
^B >-4 Oto<50
^•l >- 5.0
7 Mixed Conifer Forest (Transverse Range)
8 Mixed Conifer Forest (Sierra Nevada Range)
9 Rocky Mountain National Park
total deposition Sulfur
CMAO dry + NADP wet
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.
Final Risk and Exposure Assessment
3-71
September 2009
-------
Chapter 3 - Sources, Ambient Concentrations, and Deposition
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.
Final Risk and Exposure Assessment 3-72 September 2009
-------
Chapter 3 - Sources, Ambient Concentrations, and Deposition
Percent of 2002 Total Sulfur Deposition
Adirondack Case Study Area
50
45
40
35
30
25
20
15
10
5
0
31
23
24
22
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 Experimental Forest Case Study Area
in
AH
Af\
n
"(5
D
c •in
c JU
<
0 2<5
*j
c
O on
-------
Chapter 3 - Sources, Ambient Concentrations, and Deposition
Percent of 2002 Total Sulfur Deposition
Kane Experimental Forest Case Study Area
50
45
40
35
30
25
20
15
10
5
0
31
24
24
21
Winter
Spring
Summer
Fall
Figure 3.3-14c. Percentage of 2002 total sulfur deposition in the Kane Experimental
Forest Case Study Area.
Percent of 2002 Total Sulfur Deposition
Potomac River/Potomac Estuary Case Study Area
50
45
40
35
30
25
20
15
10
5
0
29
25
20
26
Winter
Spring
Summer
Fall
Figure 3.3-14d. Percentage of 2002 total sulfur deposition in the Potomac
River/Potomac Estuary Case Study Area.
Final Risk and Exposure Assessment
3-74
September 2009
-------
Chapter 3 - Sources, Ambient Concentrations, and Deposition
Percent of 2002 Total Sulfur Deposition
Shenandoah Case Study Area
50
45
40
35
30
25
20
15
10
5
0
31
24
19
27
Winter
Spring
Summer
Fall
Figure 3.3-14e. Percentage of 2002 total sulfur deposition in the Shenandoah Case
Study Area.
Percent of 2002 Total Sulfur Deposition
Neuse River/Neuse River Estuary Case Study Area
Winter
Spring
Summer
Fall
Figure 3.3-14f. Percentage of 2002 total sulfur deposition in the Neuse River/Neuse
River Estuary Case Study Area.
Final Risk and Exposure Assessment
3-75
September 2009
-------
Chapter 3 - Sources, Ambient Concentrations, and Deposition
Percent of 2002 Total Sulfur Deposition
Rocky Mountain National Park
50
45
40
35
30
25
20
15
10
5
0
32
19
24
25
Winter
Spring
Summer
Fall
Figure 3.3-14g. Percentage of 2002 total sulfur deposition in the Rocky Mountain
National Park.
Percent of 2002 Total Sulfur Deposition
Mixed Conifer Forest (Sierra Nevada Range) Case Study Area
CA
AZ -
Af\ -
oc
15
D
1 3°
<
"S 9*
+j
M on
0)
a.
A C
Af\
39 38
14
9
Winter Spring Summer
Fall
Figure 3.3-14H. Percentage of 2002 total sulfur deposition in the Sierra Nevada
Range portion of the Mixed Conifer Forest Case Study Area.
Final Risk and Exposure Assessment
3-76
September 2009
-------
Chapter 3 - Sources, Ambient Concentrations, and Deposition
Percent of 2002 Total Sulfur Deposition
Mixed Conifer Forest (Sierra Nevada Range) Case Study Area
50
45
40
35
30
25
20
15
10
5
0
28
26
24
21
Winter
Spring
Summer
Fall
Figure 3.3-141. 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
1
ra
c
<
•E
fl>
o
I
50
45
40
35
30
25
20
15
10
5
0
l\
If
DryS
WetS
Precip
D Winter
D Spring
D Summer
DFall
Figure 3.3-15a. Percentage of 2002 deposition for each component of sulfur
deposition in the Adirondack Case Study Area.
Final Risk and Exposure Assessment
3-77
September 2009
-------
Chapter 3 - Sources, Ambient Concentrations, and Deposition
Hubbard Brook Experimental Forest Case Study Area
Percent of 2002 Sulfur Deposition in each Season
50
45
40
1 35
g so
< 25
•5
? 20
11S
10
5
En
I
i
u
DryS
WetS
Precip
D Winter
H Spring
D Summer
DFall
Figure 3.3-15b. Percentage of 2002 deposition for each component of sulfur
deposition in the Hubbard Brook Experimental Forest Case Study Area.
Kane Experimental Forest Case Study Area
Percent of 2002 Sulfur Deposition in each Season
50
45
40
•§ 35
§ 30
c
< 25
•5
20
10
5
DryS
WetS
Precip
D Winter
B Spring
D Summer
DFall
Figure 3.3-15c. Percentage of 2002 deposition for each component of sulfur
deposition in the Kane Experimental Forest Case Study Area.
Final Risk and Exposure Assessment
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September 2009
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Potomac River/Potomac Estuary Case Study Area
Percent of 2002 Sulfur Deposition in each Season
50
45
40
•§ 35
§ 30
c
< 25
•5
£ 20
8
11S
10
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-n
I
1
I
I
DryS
WetS
Precip
D Winter
D Spring
D Summer
DFall
Figure 3.3-15d. Percentage of 2002 deposition for each component of sulfur
deposition in the Potomac River/Potomac Estuary Case Study Area.
Shenandoah Case Study Area
Percent of 2002 Sulfur Deposition in each Season
50
45
40
'o 35
\-
^ 30
< 25
•5
r 20
10
5
I
'i
I
\
i
Dry S
WetS
Precip
D Winter
H Spring
DSummer
DFall
Figure 3.3-15e. Percentage of 2002 deposition for each component of sulfur
deposition in the Shenandoah Case Study Area.
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Neuse River/Neuse River Estuary Case Study Area
Percent of 2002 Sulfur Deposition in each Season
50
45
40
| 35
1 30
< 25
•5
• 20
10
5
i
I
i
DryS
WetS
Precip
D Winter
D Spring
D Summer
DFall
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 Mountain National Park
Percent of 2002 Sulfur Deposition in each Season
50
45
40
•§ 35
I-
g so
c
< 25
•5
£ 20
8 ._
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0.
10
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DryS
WetS
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D Winter
D Spring
D Summer
DFall
Figure 3.3-15g. Percentage of 2002 deposition for each component of sulfur
deposition in the Rocky Mountain National Park.
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Mixed Conifer Forest (Sierra Nevada Range) Case Study Area
Percent of 2002 Sulfur Deposition in each Season
60
50
P 40
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
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 SC>2 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 sub-
regional (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 NHa emissions.
(a) 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.
(b) Reduced nitrogen deposition 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, NHs, and/or SC>2.
(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
Sierra Nevada Range portion of the Mixed Conifer Forest Case Study Area, in which
sulfur deposition is greatest in winter.
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3.4 CONTRIBUTIONS OF EMISSIONS OF NOX AND NH3 TO
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 to ambient
concentrations 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 forms
of nitrogen and sulfur, and this is due, in part, to atmospheric deposition of nitrogen and sulfur.
Atmospheric deposition of nitrogen and sulfur is directly related to the concentrations of NOX,
NH3, and SOX in the atmosphere, and thus, decreasing atmospheric emissions of NOX, NH3, and
SOX will directly impact deposited nitrogen and sulfur and the associated ecosystem effects. In
order to set ambient standards for NOX and SOX that are protective of public welfare, it is
necessary to understand the contribution of ambient NOX and SOX to the ecosystem pollutants of
concern: sulfur and total reactive nitrogen. Because the focus of this review is on oxides of
nitrogen, rather than on total reactive nitrogen, it is important to understand the contribution of
NOX relative to reduced forms of nitrogen (NHa and NH4+) to deposition. This section describes
the analysis of the contribution of NOX relative to reduced forms of nitrogen. It also examines the
contributions of SOX emissions to sulfur deposition. These analyses use CMAQ sensitivity runs
to estimate the relative percentage contribution of NOX, NH3, and SOX emissions to total nitrogen
deposition (the 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, NHa, and SOX in deposition of
nitrogen and sulfur, the CMAQ model for several sensitivity simulations were run. These
simulations include three separate model runs in which anthropogenic emissions of NOX, NHa, or
SOX were reduced by 50% from base case emissions levels (i.e., one run for each of the three
pollutants). The 2005 12-km CMAQ run for the eastern United States was used as the base case
for this analysis. The NOX, NFL?, and SOX emissions reductions were applied to the 2005
emissions for all states within the eastern modeling domain30. The 50% NOX reduction scenario
30 The CMAQ model configuration and modeling domain for these applications are described in Appendix 1 of this
report.
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resulted in a NOX emissions reduction of ~ 9 million tons. This amount is more than four times
the amount of emissions reduced in the 50% NHa scenario (~ 2 million tons of NHa). The 50%
SOX emissions reduction scenario removed ~ 7 million tons of SOX from states in the eastern
modeling domain.
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 wet and dry
deposition predictions from the CMAQ base case and sensitivity runs were used to calculate the
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 ofNOx 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 NHs emissions.
To further explore the relationships between NOX emissions and total reactive nitrogen
deposition, the impact on oxidized and reduced nitrogen deposition, as shown 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.
The 50% reduction in NOX generally had a small impact on reduced nitrogen deposition
across the East (+ 6%). Some case study areas had lower reduced nitrogen, whereas others had
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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,
suggesting thatNOx 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 FINOs, 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 forNH4+ aerosol, dry deposition of NHX increases closer to sources of NH3.
3.4.3.2 Contributions ofNHs Emissions to Total Reactive Nitrogen Deposition
Figure 3.4-4 shows the relative impact of the 50% NFL? emissions scenario on deposition
of total reactive nitrogen. The locations with the greatest contributions from NH3 emissions are
generally the same locations where the contribution from NOX is the least. These locations
include portions of the Potomac 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 NFL? 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/Potomac Estuary, Shenandoah, Kane
Experimental 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 NFL? emissions. The contributions from NFL? 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 NH? scenario
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
NH3 limits NH4NO3 aerosol formation, increasing the lifetime of HNOs. The ratio of HNOs to
nitrate (N(V) increases, and because the deposition velocity of HNOs is much larger than that of
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aerosol, dry deposition of total oxidized nitrogen increases. In the Adirondack, Kane
Experimental Forest, and Hubbard Brook Experimental Forest case study areas, the 50% NFL?
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 Estuary,
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 case study
areas. In general, the contribution of SC>2 emissions to sulfur deposition is fairly linear for the
50% reduction scenario 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 that
NOX emissions have significant impacts on total nitrogen deposition and account for almost all of
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 NFL?
affects mainly reduced nitrogen. Because oxidized nitrogen deposition is a greater portion of
total reactive nitrogen deposition in most areas, NOX emissions contribute more to total reactive
nitrogen than emissions of NFL?. However, local NFL? emissions do make significant
contributions to total reactive nitrogen deposition near the sources of these emissions.
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Legend
^H •:= -45
| > -45 to <= -40
> -40 to <= -30
> -30 to <= -20
' >-20to<=-10
>-10to<=0
> 0 to <= 5
> 5 to <= 10
1 Adirondack
2 Shenandoah
3 Potomac River / Potomac Estuary
4 Neuse River / Neuse Estuary
5 Kane Experimental Forest
6 Hubbard Brook Experimental Forest
Percent Change in Avg Monthly Deposition for Nitrogen, 50% NOx Reduction
Figure 3.4-1. The percentage impacts of a 50% decrease in NOX emissions on
total reactive nitrogen deposition in the East.
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Legend
^H •:= -45
| > -45 to <= -40
> -40 to <= -30
> -30 to <= -20
' >-20to<=-10
>-10to<=0
> 0 to <= 5
> 5 to <= 10
1 Adirondack
2 Shenandoah
3 Potomac River / Potomac Estuary
4 Neuse River / Neuse Estuary
5 Kane Experimental Forest
6 Hubbard Brook Experimental Forest
Percent Change in Avg Monthly Deposition for Oxidized Nitrogen, 50% NOx Reduction
Figure 3.4-2. The percentage impacts of a 50% decrease in NOX emissions on
oxidized nitrogen deposition in the East.
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Legend
^H •:= -45
| > -45 to <= -40
> -40 to <= -30
> -30 to <= -20
' >-20to<=-10
>-10to<=0
> 0 to <= 5
> 5 to <= 10
1 Adirondack
2 Shenandoah
3 Potomac River / Potomac Estuary
4 Netiw River / Neuse Estuary
5 Kane Experimental Forest
6 Hubbard Brook Experimental Forest
Percent Change in Avg Monthly Deposition for Reduced Nitrogen, 50% NOx Reduction
Figure 3.4-3. The percentage impacts of a 50% decrease in NOX emissions on
reduced nitrogen deposition in the East.
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Legend
^H •:= -45
| > -45 to <= -40
> -40 to <= -30
> -30 to <= -20
' >-20to<=-10
>-10to<=0
> 0 to <= 5
> 5 to <= 10
1 Adirondack
2 Shenandoah
3 Potomac River / Potomac Estuary
4 Neuse River / Neuse Estuary
5 Kane Experimental Forest
6 Hubbard Brook Experimental Forest
Percent Change in Avg Monthly Deposition for Nitrogen, 50% NH3 Reduction
Figure 3.4-4. The percentage impacts of a 50% decrease in
total reactive nitrogen deposition in the East.
emssons on
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Legend
^H •:= -45
| > -45 to <= -40
> -40 to <= -30
> -30 to <= -20
' >-20to<=-10
>-10to<=0
> 0 to <= 5
> 5 to <= 10
1 Adirondack
2 Shenandoah
3 Potomac River / Potomac Estuary
4 Neuse River / Neuse Estuary
5 Kane Experimental Forest
6 Hubbard Brook Experimental Forest
Percent Change in Avg Monthly Deposition for Oxidized Nitrogen, 50% NH3 Reduction
Figure 3.4-5. The percentage impacts of a 50% decrease in
oxidized nitrogen deposition in the East.
emssons on
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
Legend
^H •:= -45
| > -45 to <= -40
> -40 to <= -30
> -30 to <= -20
' >-20to<=-10
>-10to<=0
> 0 to <= 5
> 5 to <= 10
1 Adirondack
2 Shenandoah
3 Potomac River / Potomac Estuary
4 Netiw River / Neuse Estuary
5 Kane Experimental Forest
6 Hubbard Brook Experimental Forest
Percent Change in Avg Monthly Deposition for Reduced Nitrogen, 50% NH3 Reduction
Figure 3.4-6. The percentage impacts of a 50% decrease in
reduced nitrogen deposition in the East.
emssons on
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> -40 to <= -30
> -30 to <= -20
' >-20to<=-10
>-10to<=0
> 0 to <= 5
> 5 to <= 10
1 Adirondack
2 Shenandoah
3 Potomac River / Potomac Estuary
4 Netiw River / Neuse Estuary
5 Kane Experimental Forest
6 Hubbard Brook Experimental Forest
Percent Change in Avg Monthly Deposition for Sulfur, 50% SOx Reduction
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
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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, NC>2, NOs, HNOs, NH3, ^Os,
HONO, PANs, and nitrate) and SOX (i.e., 862 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/|ig/m3, and the sulfur ratios are expressed in
units of kg S/ha/|ig/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/|ig/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 magnitude of nitrogen and sulfur deposition to concentration ratios. Characterizing the
physical and chemical processes that lead to these spatial patterns will be the subject of future
research. As indicated by the map in Figure 3.5-1, the largest nitrogen deposition to
concentration ratios are estimated to occur in areas of relatively elevated terrain (e.g., the
Adirondacks) 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 no
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/|ig/m3. In most, but
clearly not all, other lower terrain areas of the East and West nitrogen deposition to concentration
ratios are in the range of 1 to 2 kg N/ha/|ig/m3. Many of the elevated terrain areas in the East and
West are characterized by ratios of 3 kg N/ha/|ig/m3 or greater.
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1 Adirondack
2 shenandoah
3 Potomac River / Potomac Estuary
4 Ne use River /Neuse Estuary
B Kane Experimental Fores!
6 Hubbard Brook Experimental Forest
7 Mixed Conifer Forest (Transverse Range)
8 Mixed Conifer Forest (Sierra Nevada Range)
9 Rocky Mountain National Park
Ratio of2Q02ac annuat NOx_N deposition to /VOx_W concentration
Figure 3.5-1. Ratio of nitrogen deposition to nitrogen concentration based on
oxidized nitrogen deposition and concentration (kg N/ha/|ig/m3).
As indicated by the map in Figure 3.5-2, the deposition to concentration ratios for sulfur
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 sulfur
deposition to concentration ratios. In the lower terrain areas of the East, the sulfur deposition to
concentration ratios are generally greater than 2 kg S/ha/|ig/m3, whereas in the lower terrain
areas of the West, ratios are generally less than 2 kg S/ha/|ig/m3. The general East-West
difference in sulfur deposition to concentration ratios may be related to the East-West difference
in SOX emissions and SC>2 concentrations, as indicated by the maps in Figure 3.2-3 and Figure
3.2-5, respectively. In elevated terrain areas of both the East and West, sulfur deposition to
concentration ratios are 4 kg S/ha/|ig/m3 or more.
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1 Adirondack
2 Shenandoah
3 Potomac River / Potomac Estuary
4 Ne use River/Neuse Estuary
B Kane Experimental Fores!
6 Hubbard Brook Experimental Forest
7 Mixed Conifer Fores! (Transverse Range)
8 Mixed Conifer Forest (Sierra Nevada Range)
9 Rocky Mountain National Part
•'•
Ratio Qf2QQ2ac annual 5Ox_$ deposition to SOx_S concentration
Figure 3.5-2. Ratio of sulfur deposition to sulfur concentration based on oxidized
sulfur deposition and concentration (kg S/ha/|ig/m3).
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 SC>2 concentrations (Figure
2-1)
• Ratio of annual total wet sulfur deposition to annual average SC>2 concentrations (Figure
2-2)
• Ratio of annual total wet+dry sulfur deposition to annual average 862 concentrations
(Figure 2-3)
• Ratio of annual total wet oxidized nitrogen deposition to annual average NC>2
concentrations (Figure 2-7)
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• 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)
• Ratio of annual total dry oxidized nitrogen deposition to annual total NO2 emissions
(Figure 2-10)
• Ratio 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 emissions
(Figure 2-12)
• Ratio of annual total dry nitrogen deposition to annual total NO2 emissions (Figure 2-16)
• Ratio of annual total wet nitrogen deposition to annual total NO2 emissions (Figure 2-17)
• Ratio of annual total wet+dry nitrogen deposition to annual total NO2 emissions
(Figure 2-18)
3.6 DISCUSSION OF UNCERTAINTIES
This section provides a nationwide overview of NOX, SOX, and NH3 emissions; NOX and
SOX concentrations; and nitrogen and sulfur deposition, as well as a more focused
characterization of nitrogen and sulfur deposition for the aquatic and terrestrial case study areas.
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When considering the uncertainties in this analysis, it is important to recognize that the
characterization of deposition in the case study areas and the estimates of deposition used as
input to our ecological modeling relied upon measurements of wet deposition from the NADP
network and predictions of dry deposition from the CMAQ model. The NADP data and the
CMAQ predictions each contain a number of areas of uncertainty. In general, we expect that
there is greater uncertainty in the model predictions of dry deposition than there is in the
measurements of wet deposition. This section identifies and describes uncertainties associated
with the various aspects of this analysis, but does not attempt to quantify these uncertainties.
3.6.1 Uncertainties 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 Section 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 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, to
characterize deposition nationwide and across each case study area, as well as to provide
deposition estimates for ecological modeling, dry deposition predictions from the CMAQ model
were used.
Although CMAQ is a "state-of-the-science" photochemical model, uncertainties in
CMAQ, like those in other photochemical models, arise due to uncertainties in model
formulation and in the inputs that drive the simulated chemistry and transport processes within
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 NOX and SOX in the atmosphere over multiday time periods, and the processes
that affect the removal of NOX and SOX through deposition.
The uncertainties associated with NOX, SOX, and NHa emissions and other emissions
input to CMAQ vary based on the method and underlying measurements used to determine or
estimate the particular set of emissions. The least uncertain of the various source categories is
likely to be emissions from electric generating units, because emissions from these sources are
determined by Continuous Emissions Monitors. For many other source categories, emissions are
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based on the application of emissions factors to the sector's activity data. Uncertainties in
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, the
calculations of emissions involve complex models that may not fully represent actual levels of
emissions in a particular location at a particular time. In addition, activity data used in "top-
down" inventories that allocate national emissions to individual counties may not properly reflect
local emissions for all areas. Of the three key pollutants for this assessment (862, NOX, and NH3)
SO2 emission may be expected to have the least uncertainty. Emissions of 862 are dominated by
electric generation units31 and, as noted above, most of these sources have Continuous Emissions
Monitors that measure SO2 on an hourly basis. Emissions of NOX are less certain than emissions
of SC>2. 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 on-
road 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 be
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 NOX concentrations in the lower troposphere and to nitrogen deposition. The
uncertainties in current estimates of lightning NOX stem from several factors, including (1) the
magnitude of NO production rates per meter of flash length, (2) differential NO production rates
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 because
of significant gaps and uncertainties in measurements needed to characterize emissions factors,
activity levels, and the temporal patterns of emissions at animal feeding operations and from
fertilized soils. In addition, estimates of NH3 emissions input to air quality models do not account
for the extent of re-emissions of NHa (i.e., "bi-directional flux") that affects NHa concentrations
3! Nationwide, 70% of annual emissions of SO2 are from electric generation units.
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
and NH4 deposition and the neutralization of sulfuric acid and nitric acid in the formation of
sulfate and nitrate particles, respectively.
Uncertainties in meteorological inputs, including the presence of clouds and fog, the
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 uncertainly in
these inputs may be greater in complex terrain, in part because the 12x12 km resolution used
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 evaluation
is to determine the degree of comparability between predictions and observations. The model
performance statistics do not necessarily represent a quantitative estimate of model uncertainty
since, aside from uncertainties in the modeling system, uncertainties exist in the measurements
and uncertainty 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, predictions of
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 wet plus
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 area for the two forms of nitrogen deposition and for sulfur deposition. On
average, 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.
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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
Case Study Area
Adirondack
Hubbard Brook
Experimental Forest
Kane Experimental
Forest
Neuse River
Potomac River
Shenandoah
Rocky Mountain
National Park
Sierra Nevada
Range
Transverse Range
Oxidized Nitrogen Deposition
CMAQ v4.7
7.52
6.48
10.06
6.51
8.64
7.53
1.79
2.59
8.17
CMAQ v4.6
6.87
6.16
9.41
5.90
8.09
7.07
1.90
2.14
7.70
Average
Difference =
(V4.7 - v4.6)
0.65
0.31
0.65
0.61
0.55
0.46
-0.11
0.44
0.46
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
Case Study Area
Adirondack
Hubbard Brook
Experimental Forest
Kane Experimental
Forest
Neuse River
Potomac River
Shenandoah
Rocky Mountain
National Park
Sierra Nevada
Range
Transverse Range
Reduced Nitrogen Deposition
CMAQ v4.7
3.33
2.42
3.21
8.06
4.14
3.96
0.93
1.35
1.81
CMAQ v4.6
3.07
2.39
2.97
8.07
4.15
3.98
0.74
1.19
1.84
Average
Difference =
(V4.7 - V4.6)
0.26
0.03
0.23
-0.01
-0.01
-0.02
0.18
0.16
-0.04
0.09
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Table 3.6-3. Annual Total Wet Plus Dry Sulfur Deposition (kg S/ha/yr) Predicted by CMAQv4.6
and CMAQv4.7 for 2002
Case Study Area
Adirondack
Hubbard Brook
Experimental Forest
Kane Experimental
Forest
Neuse River
Potomac River
Shenandoah
Rocky Mountain
National Park
Sierra Nevada
Range
Transverse Range
Sulfur Deposition
CMAQ v4.7
11.5
9.0
23.0
10.1
16.2
12.9
1.2
0.9
1.8
CMAQ v4.6
10.2
8.3
21.6
9.4
15.3
12.0
1.0
0.9
1.7
Average
Difference =
(V4.7 - V4.6)
1.25
0.71
1.43
0.73
0.91
0.90
0.17
0.04
0.12
0.69
3.6.2 Uncertainties Associated with Use of Measured Data
Areas of uncertainty in characterizing NOX and SOX concentrations and nitrogen and
sulfur deposition levels include uncertainties in monitoring instrumentation and measurement
protocols, as well as limitations in the spatial extent of existing monitoring networks for these
pollutant species. Another aspect of uncertainty applicable to this analysis is associated 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 the model do not fully align in space and time with actual
atmospheric conditions in a particular location. This may result physical and chemical
inconsistencies between the measured wet deposition and the modeled dry deposition. For
example, because the NADP sites are in non-urban areas, the spatial allocation of NADP wet
deposition is unlikely to capture the influence of urban emissions sources, whereas the CMAQ
predictions of dry deposition will more closely reflect urban sources. This may skew the
relationship between wet and dry deposition in and near urban/suburban areas, as well as in the
vicinity of large point sources.
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
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 modeled data used in this analysis. This includes
uncertainties associated with (1) gridding the NADP measurements to a 12-km resolution and
(2) the representativeness of 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
mode!32 (Grimm-Lynch), which provides fine-scale estimates of deposition for 2002 based on
an integration of measured precipitation and wet deposition and topography. The CMAQ 12-km
gridded wet deposition predictions were also included in this comparison since these data were
used in Section 3.3.3.4 to characterize seasonal trends in deposition. For the purposes of this
analysis, the Grimm-Lynch data was used as the benchmark even though there are also
uncertainties in this data set.
The analysis of spatial resolution was conducted for the Adirondack Case Study Area
because this area has the highest elevations and the most complex terrain of all the case study
areas in the eastern United States. The comparison of gridded data includes annual wet
deposition of oxidized and reduced nitrogen and sulfur for 2002 for (a) 12-km CMAQ data,
(b) 12-km NADP data, (c) fine-scale Grimm-Lynch data, and (d) an aggregation of the fine-scale
data to 12 km. The 12-km aggregation of the fine-scale data was included to isolate the effects of
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 between the
fine-scale and 12-km deposition for each of the three deposition species. Thus, it does not appear
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 the
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.
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
CMAQ predictions tend to show enhanced spatial gradients. All three data sets show an area of
relatively 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 Case
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. Overall,
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 MV and SO42" wet deposition,
respectively, found by Ito, Mitchell, and Driscoll (2002) based on an analysis of measured
precipitation, temperature, precipitation chemistry, elevation and other factors.
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
Legend
^H<2.0
; | >= 2.0 toe 30
I >= 3 0 to < 4.0
! >= 4 0 to < 5.0
CMAQ 12km
NADP12km
Grimm-Lynch 12km
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.
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
Legend
• •• :o
H>=2.Qto<3,0
1>=3.0lQ-:4.0
|>=4.0to<5.0
>=5.0to<6.0
|>=6.0to<7.0
CMAQ 12km
2002 Reft/
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.
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
Legend
^|<20
L I >= 2.0 to < 3.0
>=3.0to<4.0
j >M,Oto<50
~>=5.0to<6.0
| | >= 6.0 to < 7,0
^H>=7.0to<8.0
^| >=8.0to<9.0
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.
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
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 37:3667-3678.
Holland, H.D. 1978. The Chemistry of the Atmosphere and Oceans. New York: John Wiley &
Sons.
Ito, M. Mitchell, MJ. 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. WildlandFires 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
to Climate Change. New York: John Wiley-Interscience Publishers.
Sickles, 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 772(D17).
Sickles, J.E., II, and Shadwick, D.S. 2007b. Seasonal and regional air quality and atmospheric
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.S.
Ching, eds. EPA/600/R-99/030. U.S. Environmental Protection Agency, National
Exposure Research Laboratory, Research Triangle Park, NC.
Final Risk and Exposure Assessment 3-108 September 2009
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Chapter 3 - Sources, Ambient Concentrations, and Deposition
U.S. EPA (Environmental Protection Agency). 2006. 2002 National Emissions Inventory Data &
Documentation. U.S. Environmental Protection Agency, Technology Transfer Network,
Clearinghouse for Inventories & Emissions Factors, Office of Air Quality Planning and
Standards, Research Triangle Park, NC. Available at
http://www.epa.gov/ttn/chief/net/2002inventory.html (accessed May 28, 2009).
U.S. EPA (Environmental Protection Agency). 2008a. Clean Air Status and Trends Network,
2007 Annual Report. U.S. Environmental Protection Agency, Office of Air and
Radiation, Clean Air Markets Division, Washington, DC. December. Available at
http://www.epa.gov/castnet/docs/annual_report_2007.pdf.
U.S. EPA (Environmental Protection Agency). 2008b. Integrated Science Assessment (ISA) for
Oxides of Nitrogen and Sulfur-Ecological Criteria (Final Report). EPA/600/R-
08/082F. U.S. Environmental Protection Agency, National Center for Environmental
Assessment-RTF 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). 2009. Clean Air Status and Trends Network
(CASTNET). Online information. U.S. Environmental Protection Agency, Office of Air
and Radiation, Clean Air Markets Division, Washington, DC. Available at
http://www.epa.gov/CASTNET (accessed May 2009).
Final Risk and Exposure Assessment 3-109 September 2009
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Chapter 4 -Acidification
4.0 ACIDIFICATION
4.1 SCIENCE OVERVIEW
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
Acidification is the decrease of
acid neutralizing capacity in
water or base saturation in soil
caused by natural or
anthropogenic processes.
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
(FinalReport) (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 (SC>42 ) and nitrate (NOs ) 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 acidification-
related 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 SC>42" and N(V playing a limited role
with respect to cation leaching. Increased atmospheric deposition of sulfur and nitrogen can
result in marked increases in SC>42" and N(V soil fluxes resulting in the concomitant leaching of
nutrient (Ca2+, Mg2+) and toxic (Aln+ and H+ cations).
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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).
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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 HNOs) 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
When sulfur or
nitrogen leaches from soils to
surface waters in the form of
2-
SC>4 " or N(V an equivalent
amount of positive cations, or
countercharge, is also
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) - (SO42~ + NO3"+
The unit of ANC is usually microequivalents per liter (ueq/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 Ca + concentrations; lower
transported. This maintains ' 3+
is generally associated with low pH and Al concentrations
and a greater likelihood of toxicity to biota.
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 (A13+), the acidity of the soil
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Chapter 4 -Acidification
water is neutralized, but the base saturation of the soil is reduced. Continued SC>42" or N(V
leaching can deplete available base cation pools in the soil. As the base cations are removed,
continued deposition and leaching of SO42" and/or NO3" (with H+ and A13+) 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 short-
term 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:
• The evidence is sufficient to infer a
causal relationship between acidifying
deposition and changes in
biogeochemistry related to aquatic
• young-of-the year brook trout.
ecosystems. The strongest evidence
dissolved inorganic Al and Ca, surface
water pH, sum of base cations, ANC,
and base cation surplus.
(U.S. EPA, 2008, Section 3.2.3.4)
The evidence is sufficient to infer a
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)
Community
• Species richness of plankton,
invertebrates, and fish
comes from studies of changes in
surface water chemistry, including
2 • Invertebrate taxa, including mayflies,
concentrations of SO4 , NO3 , 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.
causal relationship between acidifying deposition and changes in aquatic biota. The
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Chapter 4 -Acidification
strongest evidence comes from studies of aquatic systems exposed to elevated levels of
acidifying deposition that support fewer species offish, 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 SC>42", NCV, 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
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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
(ueq/L). The number offish species also peaks at ANC values >100 ueq/L (Bulger et al., 1999;
Driscoll et al., 2001; Kretser et al., 1989; Sullivan et al., 2006). Below 100 ueq/L, ANC fish
fitness and community diversity begin to decline (Figure 4.2-1). At ANC levels between 100
and 50 ueq/L, the fitness of sensitive species (e.g., brook trout, zooplankton) also begins to
decline. When ANC concentrations are <50 ueq/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) -,
|io -
« : .
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5 0 25 50 T5 ICO U5 150 175 2CO 225 250 27
Average AWC ((jeqrt_)
Figure 4.2-1. (a) Number offish species per lake or stream versus acidity,
expressed as acid neutralizing capacity for Adirondack Case Study Area lakes
(Sullivan et al., 2006). (b) Number offish 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 offish species.
When ANC levels drop to <20 ueq/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,
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September 2009
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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
ueq/L (Figure 4.1-1 of Appendix 4).
Complete loss offish populations and extremely low diversity of planktonic communities
occur when ANC levels stay <0 ueq/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
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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
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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 ueq/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 ueq/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.
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Chapter 4 -Acidification
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.
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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 (802) 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 S(V and N(V 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 SC>42" and
N(V, respectively.
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Chapter 4 -Acidification
1990 1992 1994 1996 1998 2000 2002 2004 2006
Source: NADP
NADP Sites: NY08,NY20,NY52,NY68,NY98,NY99,VT01VT99
Figure 4.2-3. Annual average total wet deposition (kg/ha/yr) for the period 1990
to 2006 in SO42" (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 (63),
"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)
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September 2009
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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 SC>42" and NCV 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 SC>42" and N(V, respectively.
10
8
4 -
S02
S04
Oxidized N
NH4
1990 1992 1994 1996 1998 2000 2002 2004 2006
Source: CASTNET
CASTNET Sites: SHN418
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 SC>2 (blue), oxidized
nitrogen (red), SC>42" (green), and reduced nitrogen (black), (b) Annual average
total wet deposition (kg/ha/yr) of SC>42" (green) and N(V (blue).
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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 SC>42" and N(V 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 SC>42" and N(V 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 SC>42" and NCV
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 pre-
acidification 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
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Chapter 4 -Acidification
the LTM programs. Average yearly ANC concentrations were calculated from annual
measurements.
(a)
Adirondack Case Study Area
• MAGIC Locations
• Crritical Locations
| | Adirondack Boundary
Watershed Boundary
Source: EPA 2009
(b)
Shenandoah Case Study Area
• MAGIC & Critical Load Locations
| | Case Study Boundary
Watersheds
Source: EPA 2009
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.
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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 ueq/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.,
ANCumit) of biological protection were used: 0 ueq/L
(acidic), 20 ueq/L (minimal protection), 50 ueq/L
(moderate protection), and 100 ueq/L (full protection). A
full and complete description of the biological effects at a
given ANC limit appears in Appendix 4, Section 4.1.
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 ueq/L
were determined.
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 ueq/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/m2yr)
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.
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September 2009
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Chapter 4 -Acidification
Table 4.2-1. Aquatic Status Categories
Category Label ANC Levels* Expected Ecological Effects
Acute
Concern
Severe
Concern
<0 micro
equivalent
per Liter
0-20 ueq/L
Near complete loss offish 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.
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 ueq/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
ueq/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 ueq/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
Since the mid-1990s, lakes in the
Adirondack Case Study Area have shown
signs of improvement in N(V and SC>42"
concentrations in surface waters. Wet
deposition rates for SC>2 and NOX, and their
atmospheric reaction products, have decreased
(see Figure 4.2-3), and, as a result, N(V and
SC>42" concentrations have decreased in surface
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
ueq/L
ANC
SO42
NO3
NFC
Preacidification
Avg.
120.3
12.4
0.2
0.0
(±)
13.6
2.1
1.7
0.0
Current
Avg.
62.1
66.1
3.4
0.1
(±)
15.7
1.24
14.8
0.1
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September 2009
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Chapter 4 -Acidification
waters by approximately 26% and 13%, respectively (Figure 4.2-6).
The decline in SC>42" concentrations in surface waters in the Adirondack Case Study Area
is -2.1 ueq/L/year, while the decline in NO3"is -0.23 ueq/L/year. However, current
concentrations of N(V and SC>42"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,
MV and SC>42" concentrations are 17- and 5-fold higher today,
respectively (Table 4.2-2).
Current NO3" and SO4
concentrations are 17-
and 5-fold higher in
Adirondack Case Study
Area lakes today than
they were in 1860.
CT
0)
120.0
100.0
80.0
60.0
40.0
20.0
0.0
Annual Average Suface Water Trends 1990-2006
(Adirondack Case Study Area)
1990 1992 1994
Source: ALTM-50 Lakes
1996 1998 2000 2002 2004 2006
Figure 4.2-6. Trends over time for SC>42", N(V, and acid neutralizing capacity in
50 LTM lakes. SC>42" and N(V concentrations have decreased in surface waters by
approximately 26% and 13%, respectively.
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September 2009
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Chapter 4 -Acidification
Although MV 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 SO42" deposition because the current average SO42" concentration in the 44 modeled
lakes is some 19-fold greater than N(V concentrations in surface waters (Table 4.2-2).
An increase in ANC of+1 ueq/L/year has corresponded to the declines in NCV and SC>42";
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
NCV and SC>42", 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 ueq/L) to
Severe (i.e., ANC <20 ueq/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).
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Chapter 4 -Acidification
(a) Nitrate Preacidification (1860) and Current Condition (2006)
Preacidification (1860)
Current (2006)
Nitrate (peq/L)
• 0-3
• 3-6
6-9
• 9-12
Source: EPA 2009
Figure 4.2-7. N(V concentrations of years 1860 (preacidification) and 2006
(current) conditions based on hindcasts of 44 lakes in the Adirondack Case Study
Area modeled using MAGIC.
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Chapter 4 -Acidification
Sulfate Preacidification (1860) and Current condition (2006)
Preacidification(1860)
Current (2006)
Sulfate (ueq/L)
• 0-25
• 25-50
50-75
>75
Source: EPA 2009
Figure 4.2-8. SC>42" concentrations of years 1860 (preacidification) and 2006
(current) conditions based on hindcasts of 44 lakes in the Adirondack Case Study
Area modeled using MAGIC.
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September 2009
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Chapter 4 -Acidification
TIME/LTM: 2005-2006
ANC
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 ueq/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 ueq/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 N(V and SC>42" deposition pose a risk of acidification
to approximately 32% of modeled lakes.
Source: TIME/ALTM 2009
Figure 4.2-9. Acid neutralizing capacity
concentrations from 88 lakes in the
Adirondack Case Study Area. Monitoring
data from the TIME/LTM programs.
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September 2009
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Chapter 4 -Acidification
ANC Preacidification (1860) and Current Condition (2006)
Preacidification (1860)
Current (2006)
Source: EPA 2009
ANC (Meq/L)
• >0
0-20
20-50
• 50-100
• >100
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.
70
60
50
40
30
20
10
0
I
T
Acute (Below 0 ueq/L)
Severe (0-20 ueq/L)
Elevated (20-50 ueq/L)
Moderate (50-100 ueq/L)
Low (Above 100 ueq/L)
1860
2006
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.
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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 ueq/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 ueq/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 ueq/L, respectively (Table 4.2-3).
Current Condition of Acidity
and Sensitivity
Criticial Load
meq/m2/yr
• Highly Sensitive: < 50
Moderately Sensitive: 51 • 100
Low Sensitivity: 101 - 200
• Not Sensitive: > 201
Source: EPA 2009
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 ueq/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/m2yr (yellow and green circles) are the least sensitive sites.
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Chapter 4 -Acidification
Critical Load Exceedances
(100
Critical Load Exceedences
(> ANC of 100 Meq/L)
Deposition does not Exceed Critical Load
• Deposition Exceeds Critical Load
Critical Load Exceedances
(20 peq/L)
Critical Load Exceedences
( > ANC of 20 Meq/L)
Deposition does not Exceed Critical Load
• Deposition Exceeds Critical Load
Source: EPA 2009
Critical Load Exceedances
(50 peq/L)
Critical Load Exceedences
( > ANC of 50 peq/L)
Deposition does not Exceed Critical Load
• Deposition Exceeds Critical Load
Source: EPA 2009
Critical Load Exceedances
(0 neq/L)
Critical Load Exceedences
( > ANC of 0 Meq/L)
• Deposition does not Exceed Critical Load
• Deposition Exceeds Critical Load
Source: EPA 2008
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 ueq/L, respectively. Green circles
represent lakes where current total nitrogen and sulfur deposition is below the
critical load (see Table 4.2-3).
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September 2009
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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 ueq/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
Table 4.2-3. Critical Load Exceedances (Nitrogen + Sulfur
deposition scenario that
maintains current emission
levels up to years 2020 and
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
2050, the simulation forecast Lakes at the Given Acid Neutralizing Capacity Limit
indicates no improvement in
water quality over either of
the periods. The percentage
of lakes within the Elevated
to Acute Concern classes
ANC Limit
100 jieq/L
No.
Lakes
98
%
Lakes
58
ANC Limit
50 jieq/L
No.
Lakes
74
%
Lakes
44
ANC Limit
20 jieq/L
No.
Lakes
47
%
Lakes
28
ANC Limit
0 jieq/L
No.
Lakes
30
%
Lakes
18
Lake No. = 169
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.
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 N(V and SC>42" concentrations in surface waters. Deposition of SOX and
NOX has decreased, but has not resulted in much improvement in N(V and SC>42" stream
concentrations (Figure 4.2-14). However, ANC concentrations increased from the about 50
ueq/L in the early 1990 to >75 ueq/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.
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Chapter 4 -Acidification
120.0
100.0
Annual Average Suface Water Trends 1990-2006
(SWAS-VTSSS-LTM)
o.o
1990 1992 1994 1996
Source: SWAS-VTSSS-LTM-67 Streams
1998
2000
2002
2004
2006
Figure 4.2-14. Trends over time for SO42" (blue), NO3" (green) and acid
neutralizing capacity (red) concentrations in VTSSS LTM-monitored
streams in the Shenandoah Case Study Area.
The slight decline in SC>42"
concentrations in surface waters of the
Shenandoah Case Study Area is -0.09
ueq/L/year, while the decline in N(V is -0.1
ueq/L/year. Current concentrations of MV and
SC>42" 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, NOs" and
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
jieq/L
ANC
SO42
NO3
NH4+
Pre-
Acidification
Avg.
101.4
2.1
0.6
N/A
(±)
9.5
0.1
0.01
N/A
Current
Avg.
57.9
68.0
6.2
N/A
(±)
4.5
8.4
0.1
N/A
2-
N/A = Not available.
concentrations are 10- and 32-fold higher today, respectively (Table 4.2-4).
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Chapter 4 -Acidification
Current NO3" and SO4
concentrations are 10- and
32-fold higher in Shenandoah
Case Study Area streams
today than in 1860.
Although MV 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 SC>42" deposition since current average SC>42" concentration
is 11-fold greater than NCV concentrations in surface waters (Table 4.2-4).
An increase in ANC concentrations of+0.08 ueq/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.
(a) Nitrate Preacidification (1860) and Current Conditions (2006)
Preacidification (1860) Current (2006)
Source: EPA 2009
Nitrate {peq/L)
• 0-5
• 5-10
10-15
• 15-20
• >20
Figure 4.2-15. NCV 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 ueq/L) to
Severe (ANC <20 ueq/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
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September 2009
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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 862.
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 ueq/L, as compared with 57.9 ±4.5 ueq/L for today (Table 4.2-4).
(b) Sulfate Preacidification (1860) and Current Conditions (2006)
Preacidification (1860) Current (2006)
Source: EPA 2009
Sulfate (|jeq/L)
• 0-25
• 25-50
50-75
75-100
• >100
2-
Figure 4.2-16. SC>4 " concentrations of preacidification (1860) and current (2006)
conditions based on hindcasts of 60 streams modeled using MAGIC in the
Shenandoah Case Study Area.
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September 2009
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Chapter 4 -Acidification
SWAS-VTSSS/LTM: 2005 - 2006
ANC
Source: SWAS-VTSSS/LTM 2009
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 ueq/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
NOs" and SC>42" and their associated anthropogenic acidifying deposition are likely responsible
for acidifying (ANC below 50 ueq/L) approximately 45% of streams modeled in the Shenandoah
Case Study Area.
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September 2009
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Chapter 4 -Acidification
ANC Preacidification (1860) and Current Condition (2006)
Pre-acidification (1860) Current (2006)
Source: EPA 2009
ANC (Meq/L)
• <0
0-20
20-50
• 50-100
• > 100
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.
en
50
40
30
on
ZU
10
I
1861
±
T
D
1
J
T
-P-,
1
2001
I
5
• Acute (Below 0 |jeq/L)
D Severe (0-20 |jeq/L)
D Elevated (20-50 |jeq/L)
D Moderate (50-1 00 |jeq/L)
• Low (Above 1 00 |jeq/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 (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.
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September 2009
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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.
Current Condition of Acidity
and Sensitivity
Criticial Load
meq/m!tyr
• Highly Sensitive: < 50
Moderately Sensitive: 51 -100
Low Sensitivity: 101 -200
• Not Sensitive: > 201
Source: EPA 2009
Figure 4.2-20. Critical loads of surface water acidity for an acid neutralizing
capacity concentration of 50 ueq/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 ueq/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 ueq/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 ueq/L, respectively (Table 4.2-5).
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September 2009
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Chapter 4 -Acidification
Critical Load Exceedances
(100 peq/L)
Critical Load Exceedences
(>ANCof lOOneq/L)
• Deposition does not Exceed Critical Load
• Deposition Exceeds Critical Load
Source: EPA 2009
Critical Load Exceedances
(20 |jeq/L)
Critical Load Exceedences
( > ANC of 20 (jeq/L)
• Deposition does not Exceed Critical Load
• Deposition Exceeds Critical Load
Source: EPA 2009
Critical Load Exceedances
(50 |jeq/L)
Critical Load Exceedences
( > ANC of 50 peq/L)
• Deposition does not Exceed Critical Load
• Deposition Exceeds Critical Load
Source: EPA 2009
Critical Load Exceedances
(0 Meq/L)
Critical Load Exceedences
( > ANC of 0 (icq/L)
» Deposition does not Exceed Critical Load
• Deposition Exceeds Critical Load
Source: EPA 2009
Figure 4.2-21. Critical load exceedances for acid neutralizing capacity
concentrations of 0, 20, 50, and 100 ueq/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 [^eq/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.
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September 2009
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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 jieq/L
No.
Streams
55
%
Streams
92
ANC Limit
50 jieq/L
No.
Streams
51
%
Streams
85
ANC Limit
20 jieq/L
No.
Streams
43
%
Streams
72
ANC Limit
0 jieq/L
No.
Streams
31
%
Streams
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
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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 ueq/L. In the mid-Atlantic, the
target population is upland streams with Gran ANC <100 ueq/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
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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 ueq/L;
two higher ANC lakes (Gran ANC between 100 and 200 ueq/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
ueq/L; three lakes with Gran ANC between 100 ueq/L and 200 ueq/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 ueq/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 ueq/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
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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 ueq/L, with 7 of the 69 sites exhibiting
mean Gran ANC >100 ueq/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 ueq/L, respectively (Table 4.2-6).
Given a low level of protection from acidification (i.e., an ANC limit of 20 ueq/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 ueq/L. For this reason, the actual number of lakes
at risk of acidification at an ANC level of 50 and 100 ueq/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 ueq/L. Excluding
these naturally acidic lakes, the current risk of acidification is 666 lakes or 36% for a moderate
protective ANC concentration of 50 ueq/L. For an ANC level of 100 ueq/L, 51% of lakes have
natural ANC concentrations below 100 ueq/L. Excluding these naturally acidic lakes, the current
risk is 945 lakes or 51% for a protective ANC concentration of 100 ueq/L. Even with corrections
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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 862.
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 |ieq/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 jieq/L. However, 5
modeled lakes or 11% have ANC concentrations between 22 and 47 jieq/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 |ieq/L. On the other
hand, potentially more than 52% of lakes likely had preacidification ANC concentrations below
100 jieq/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 |ieq/L are more abundant in the Adirondack Case Study Area than
lakes with a preacidification ANC concentration above 50 or 100 jieq/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 jieq/L
No.
Lakes
945
%
Lakes
51
ANC Limit
50 jieq/L
No.
Lakes
666
%
Lakes
36
ANC Limit
20 jieq/L
No.
Lakes
242
%
Lakes
13
ANC Limit
0 jieq/L
No.
Lakes
135
%
Lakes
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
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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 ueq/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 NCV and SC>42". The acid balance of
headwater lakes and streams is controlled by the level of this acidifying deposition of NCV and
SC>42" and a series of biogeochemical processes that produce and consume acidity in watersheds.
In basic soils, inputs of NCV and SC>42" 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 (NCV and 804"),
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 NCV and SCV
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 [ANCumit]),
which protects biological integrity, the amount of deposition of acid anions (AN) or deposit!onal
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 [ANCi;mit] when balanced by the
Final Risk and Exposure Assessment 4-39 September 2009
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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]o ) to the watershed. Thus, the amount of deposition that will maintain an
ANC level above an ANCimut 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 ANCiimit:
DLmax(S) = [([BC]0* - [ANCievei])Q]/ (1-A) (3)
when nitrogen deposition does not contribute to the acidity balance and where/>s 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:
DLmm(S) = 0 (4)
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Chapter 4 -Acidification
In the case of nitrogen, DLm;n(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:
DLmm(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) = fNUIrt + (l-r)(Nimm + Nden) + [([BC]0* - [ANClevel])Q]/ (l-pn) (6)
where^n 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
E
_l
Q
DLmax(N)
N Deposition
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
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Chapter 4 -Acidification
I"
W
Clear Pond, NY
500
400
300
200
100
100
200
300
400
500
N (meq/m2/yr)
Middle Flow, NY
500 n
400 -
300 -
200 -
100 -
100
200 300
N (meq/m2/yr)
400
500
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
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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, NOs, 804) 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
Q
CA
MG
CL
NA
NO3
SO4
Acidic Deposition
(NOX & SO4)
Units
(ieq/L
(ieq/L
(ieq/L
(ieq/L
(ieq/L
(ieq/L
(ieq/L
meq/L
Uncertainty range
50%
65%
64%
52%
58%
30%
57%
25%
Distribution
Normal
Normal
Normal
Normal
Normal
Normal
Normal
Lognormal
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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.
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Chapter 4 -Acidification
1
0.9
0.8
0.7
|T 0.6
"i 0.5
0.3
0.2
0.1
Probability
exceedance. where
the % of the
-etmiulative
\SVIIIIVIIMhl V \*
frequency chart Vies
above zero
-400 -300 -200 -100 0
Exceedance (meq/ha/yr)
100
200
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 ueq/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 ueq/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 ueq/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% ueq/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 ueq/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
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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
CL(A)
EX(A)
Critical load Limit
(^eq/L)
0
20
50
100
0
20
50
100
Mean
(meq/L)
247.8
227.0
196.7
140.3
-178.3
-157.6
-127.2
-75.0
Coefficient of
variation (%)
4
5
9
100
18
17
25
33
190 -,
100
on
^ RO
0
An
on
Q
+
!
_i_
i
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 ueq/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%
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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 jieq/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.
Critical Load Exceedances
Probability
• 0-5% - unlikely to be exceeded
5-25% - relatively low risk of exceedance
25-75% - potential risk of ecceedence
• 75-95% - relatively high risk of exceedence
% > 95% - highly likely to be exceeded
Figure 4.2-26. Probability of exceedance of critical load for acidity for 2002.
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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 (SC>42", N(V, and ANC) simulated versus observed values during the calibration
Final Risk and Exposure Assessment 4-48 September 2009
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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 pre-
acidification and current average ANC concentrations of the 44 modeled lakes was 106.8 to
134.0 and 50.5 to 81.8 ueq/L, respectively, which is on average a 15 ueq/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 ueq/L,
respectively, which is on average 8 ueq/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' SC>42", N(V, and ANC simulations, the RMSE for
predicted versus observed values were 0.1 ueq/L, 0.05 ueq/L, and 3.5 ueq/L for lakes in the
Adirondack Case Study Area and 1.0 ueq/L, 0.06 ueq/L, and 1.0 ueq/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 ueq/L and 5.1 ueq/L for the two lakes in the Adirondack Case Study Area and was 11.8
ueq/L and 4.0 ueq/L for the two streams in Shenandoah Case Study Area.
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Chapter 4 -Acidification
150
£•
•| 100
4 ",
NOs". 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.
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Chapter 4 -Acidification
150
£•
•| 100
-------
Chapter 4 -Acidification
50
25
0)
O
-25
Observed
Simulated
Indian Lake
1975 1980 1985 1990 1995
Years
2000
2005
2010
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
|ieq/L for Indiana Lake and 5.1 |ieq/L for Dismal Pond.
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Chapter 4 -Acidification
200
^150
i
"S-
0)
=: 100
0
< 50
o
en
"g- 25
0)
1 °
19
» Observed . . .. _ .
Helton Creek
Qimi il^*«^^J
^
Nobusiness Creek
^T^n^-^^^
75 1980 1985 1990 1995 2000 2005 2G
Years
10
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
|ieq/L for Helton Creek and 4.0 |ieq/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/AI molar ratio in
the soils solution was selected as the
indicator to estimate critical
deposition loads of acidity for the
Terrestrial Acidification Case Study.
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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 (Be) 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 (8MB) 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 8MB 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.
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Chapter 4 -Acidification
10
o
"o
2 1 -
'o
t/3
fl
,0
~5
PQ
.01 >
(
V, (Bc/Al^ = 1.2
^^*. (Bc/AlXit = 0.6
^"\.
^^\
\
V
1 1
) 25 50 75 1(
Cumulative Percentage of Species Exhibiting Reduced Growth Response
30
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.,
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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 SC>2 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
Leach Ca2+ from leaf membrane
Reduce the ratio of Ca2+/Al in
soil and soil solutions
Physiological Response
Decrease the cold tolerance of
needles in red spruce
Dysfunction in fine roots of red
spruce blocks uptake of Ca2+
Effect on Forest Function
Loss of current-year needles in
red spruce
Decreased growth and increased
susceptibility to stress in red
spruce
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Chapter 4 -Acidification
Biogeochemical Response to
Acidifying deposition
Reduce the ratio of Ca2+/Al in
soil and soil solutions
Reduce the availability of
nutrient cations in marginal soils
Physiological Response
More energy is used to acquire
Ca2+ in soils with low Ca2+/Al
ratios
Sugar maples on drought-prone
or nutrient-poor soils are less
able to withstand stresses
Effect on Forest Function
Decreased growth and increased
photosynthetic allocation to red
spruce roots
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.
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.
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
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• 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.
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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 montivagd)—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.
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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.
J
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
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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
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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,
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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)
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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 USFS-
designated 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 (FffiEF) in New Hampshire's White Mountains as the area for the red
spruce terrestrial acidification case study. The FffiEF 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.
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\ States
Potentially Sensitive to Terrestrial Acidification
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 (8MB) 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 areas,
according to Equation 7
CL(S + N) = BCdep - Cldep + BCW -Bcu
Nu + Nde - ANCle,cnt
(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.
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p = 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
N; = nitrogen immobilization
Nu = uptake of nitrogen by trees
Nde = denitrification
ANCie,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 8MB 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 8MB 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 (CLm;n(N). Above this CLm;n(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.
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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.
O
O
a
OJ
Q
05
CLmax(N)
N Deposition
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
CLm;n(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 [CMAQJ-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 FffiEF 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
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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 8MB 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
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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
0.6
1.2
10.0
Level of Protection to Tree
Health
Low
Intermediate
High
Critical Load
High
Intermediate
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
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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 FffiEF 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 FffiEF 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^t) = 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.
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3500
o
a
1796
1268
697
0
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
0 213
910
1481
2009
3500
N Deposition
(eq/ha/yr)
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 CLm;n(N) (nitrogen absorbed by nitrogen sinks within
the system).
R
• °, ^
If
& "9
1) CT1
Q & 1194
t/3
849
444
o
(
Low Protection (Bc/Al =0.6)
Intermediate Protection (Bc/Al =1.2)
- - - - High Protection (Bc/Al = 10.0)
PT minrtVn
• 2002 CMAQ N and S Deposition
"^ ^^^.
X
V
^^\
X ^
j 43 487 892 1237 3C
N Deposition
(eq/ha/yr)
00
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 CLm;n(N) (nitrogen absorbed by nitrogen sinks
within the system).
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September 2009
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Chapter 4 -Acidification
1 °nn
.2 'D
'« ~^§ CLmax(S) 697
NHX-N deposition (fixed amount)
NOx-N deposition
2002 CMAQ N and S deposition
CLmm(N)
>
s
S
[•>
r
-U-
\
0 |
0 213 249
CLmin(N)
N Deposition
(eq/ha/yr)
•
rVv
a=0|
910 1200
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.
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September 2009
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Chapter 4 -Acidification
750
o /->
: - -k
05 ^3
O W
CLmax(S)
Q o
&0 Adj. CLmax(S) 328
G NHX-N deposition (fixed amount)
H NOX-N deposition
• 2002 CMAQ N and S deposition
'• CLmm(N)
CLmin(N)
159
487
750
N Deposition
(eq/ha/yr)
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
CLm;n(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'
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Chapter 4 -Acidification
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
Alabama
Arkansas
Connecticut
Illinois
Indiana
Iowa
Kansas
Kentucky
Maine
Sugar Maple
13
10
35
29
306
13
NA
14
271
Red Spruce
-
-
-
-
-
-
-
-
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.
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Chapter 4 -Acidification
State
Maryland
Massachusetts
Michigan
Minnesota
Missouri
New Hampshire
New Jersey
New York
North Carolina
Ohio
Pennsylvania
Rhode Island
South Carolina
Tennessee
Vermont
Virginia
West Virginia
Wisconsin
TOTAL
Sugar Maple
4
33
633
289
147
82
6
485
17
374
285
NA
NA
319
114
175
378
960
4,992
Red Spruce
-
3
-
-
-
55
-
52
1
-
NA
-
-
1
11
NA
7
-
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.
Final Risk and Exposure Assessment
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Chapter 4 -Acidification
Collectively, given the limitations and uncertainties associated with the 8MB 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^t) = 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
Alabama
Arkansas
Connecticut
Illinois
Indiana
Iowa
Kansas
Kentucky
Maine
Maryland
Massachusetts
Michigan
Minnesota
Missouri
New
Hampshire
Ranges of Critical Load Values (eq/ha/yr)
Sugar Maple
Bc/Al = 0.6
1,592 to 5,337
2,239 to 4,290
1,5 19 to 2,468
2,543 to 3,671
1,478 to 5,859
2,260 to 3, 791
NA
2,044 to 3,994
746 to 4,284
2,066 to 3,090
791 to 2,4 14
400 to 6,008
220 to 4,9 16
978 to 4,891
580 to 1,994
Bc/Al = 1.2
1,114 to 3,638
1,536 to 2,913
1,058 to 1,702
1,730 to 2,485
1,020 to 3, 971
1,533 to 2,560
NA
1,390 to 2,707
535 to 2,983
1,417 to 2,122
566 to 1,661
294 to 4,070
166 to 3,3 18
681 to 3,304
419 to 1,439
Bc/Al = 10.0
617 to 2,015
857 to 1,623
581 to 941
965 to 1,390
573 to 2,2 14
854 to 1,424
NA
749 to 1,497
295 to 1,620
929 to 1,178
3 19 to 919
169 to 2,269
107 to 1,861
377 to 1,843
236 to 780
Red Spruce
Bc/Al = 0.6
-
-
-
-
-
-
-
-
599 to 4,278
-
1,706 to 1,736
-
-
-
418 to 1,994
Bc/Al = 1.2
-
-
-
-
-
-
-
-
439 to 2,979
-
1,191 to 1,213
-
-
-
324 to 1,439
Bc/Al = 10.0
-
-
-
-
-
-
-
-
249 to 1,623
-
656 to 669
-
-
-
180 to 780
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September 2009
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Chapter 4 -Acidification
State
New Jersey
New York
North Carolina
Ohio
Pennsylvania
Rhode Island
South Carolina
Tennessee
Vermont
Virginia
West Virginia
Wisconsin
Combined
(all plots)
Ranges of Critical Load Values (eq/ha/yr)
Sugar Maple
Bc/Al = 0.6
1,452 to 2,651
503 to 4,467
1,415 to 3,444
1,226 to 4,986
1,026 to 4,047
NA
NA
921 to 5,755
479 to 5,660
1,036 to 5,852
369 to 4,134
400 to 5,031
220 to 6,008
Bc/Al = 1.2
1,029 to 1,824
370 to 3,039
1,0 10 to 2,426
855 to 3,366
723 to 2,752
NA
NA
653 to 3,901
351 to 3,846
726 to 3,968
270 to 2,8 19
290 to 3,393
166 to 4,070
Bc/Al = 10.0
566 to 1,012
209 to 1,686
558 to 1,319
469 to 1,877
402 to 1,530
NA
NA
351 to 2,175
201 to 2, 142
4 10 to 2,208
152 to 1,560
166 to 1,898
107 to 2,269
Red Spruce
Bc/Al = 0.6
-
526 to 3, 146
1256
-
NA
-
-
2,065
846 to 2,305
NA
2,300 to 3,634
-
418 to 4,278
Bc/Al = 1.2
-
386 to 2,156
926
-
NA
-
-
1,433
601 to 1,648
NA
1,610 to 2,533
-
324 to 2,979
Bc/Al = 10.0
-
217 to 1,195
501
-
NA
-
-
788
336 to 888
NA
884 to 1,382
-
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
Alabama
Arkansas
Connecticut
Illinois
Indiana
Iowa
Kansas
Kentucky
Maine
Maryland
Massachusetts
Michigan
Minnesota
Missouri
Percentage of Plots Where Critical Load is Exceeded (%)
Sugar Maple
Bc/Al = 0.6
0
0
0
0
0.3
0
NA
0
0
0
6
6
2
0.7
Bc/Al = 1.2
23
0
23
0
12
0
NA
0
0.7
25
33
14
7
2
Bc/Al = 10.0
31
10
100
66
87
23
NA
86
20
100
100
70
30
46
Red Spruce
Bc/Al = 0.6
-
-
-
-
-
-
-
-
0.2
-
0
-
-
-
Bc/Al = 1.2
-
-
-
-
-
-
-
-
0.5
-
100
-
-
-
Bc/Al = 10.0
-
-
-
-
-
-
-
-
16
-
100
-
-
V
Final Risk and Exposure Assessment
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September 2009
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Chapter 4 -Acidification
State
New
Hampshire
New Jersey
New York
North Carolina
Ohio
Pennsylvania
Rhode Island
South Carolina
Tennessee
Vermont
Virginia
West Virginia
Wisconsin
Combined
(all plots)
Percentage of Plots Where Critical Load is Exceeded (%)
Sugar Maple
Bc/Al = 0.6
29
0
6
0
1
7
NA
NA
0.3
2
2
2
2
3
Bc/Al = 1.2
38
67
20
6
16
22
NA
NA
o
6
7
9
8
10
12
Bc/Al = 10.0
84
100
95
71
95
98
NA
NA
50
99
59
95
82
75
Red Spruce
Bc/Al = 0.6
27
-
14
0
-
NA
-
-
0
2
NA
0
-
3
Bc/Al = 1.2
38
-
15
0
-
NA
-
-
0
6
NA
0
-
5
Bc/Al = 10.0
78
-
79
100
-
NA
-
-
100
100
NA
100
-
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 8MB
model critical load equation (Equation 7 in Section 4.3.4). The equation to estimate ANC is
presented below, in Equation 8.
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September 2009
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Chapter 4 -Acidification
ANC(le,cnt)=-e2/3x
1.5x-
Bcdep+Bcw-Bcu
-1.5x-
Bc +Bc -Be
'crit j vAlycnt
where
Q = annual runoff in m3/ha/yr
= 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+).
Final Risk and Exposure Assessment 4-79 September 2009
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Chapter 4 -Acidification
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.
6500
5617
S3
•2
.-
Q
GO
3803
2099
344
120
0
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)
2142
3846
5660
6500
N Deposition
(eq/ha/yr)
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 CLm;n(N) value
for all curves is 42.86 eq/ha/yr, but this value is not indicated in the figure.
Final Risk and Exposure Assessment
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September 2009
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Chapter 4 -Acidification
5000
4222
O
Q
GO
2933
1578
483
174
0
• 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)
^H OO (M
-------
Chapter 4 -Acidification
"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).
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.
In this case study, multiple values were used for several parameters in the 8MB
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
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Chapter 4 -Acidification
earlier, the BCW term within the 8MB 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 BCwterm.
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
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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 ueq/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 SC>42" and N(V 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 SC>2 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 NCV and SC>42" are 17- and
5-fold higher today, respectively. The estimated average ANC for 44 lakes in the
Adirondack Case Study Area is 62.1 ueq/L (± 15.7 ueq/L); 78 % of all monitored lakes in
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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 ueq/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 MV and SO42" concentrations in surface waters. ANC levels increased from
about 50 ueq/L in the early 1990 to >75 ueq/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 NCV and SO42" are
10- and 32-fold higher today, respectively. The estimated average ANC for 60 streams in
the Shenandoah Case Study Area is 57.9 ueq/L (± 4.5 ueq/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 ueq/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 (Be) 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
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Chapter 4 -Acidification
spruce forests in the eastern United States by using the ratio of Be 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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Urquhart, N.S., S.G. Paulsen, and D.P. Larsen. 1998. Monitoring for policy-relevant regional
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U.S. EPA (Environmental Protection Agency). 2008. Integrated Science Assessment (ISA) for
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08/082F. U.S. Environmental Protection Agency, National Center for Environmental
Assessment-RTF Division, Office of Research and Development, Research Triangle
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U.S. EPA (Environmental Protection Agency). 2005. EPA Advisory Council on Plans for
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-Benefits and Costs of the Clean Air Act, 1990-2020. EPA-COUNCIL-ADV-05-001.
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U.S. EPA (Environmental Protection Agency). 1995. Review of the national ambient air quality
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Watmough, S., J. Aherne, P. Arp, I. DeMerchant, and R. Ouimet. 2006. Canadian experiences in
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Watmough, S.A., J. Aherne, and P.J. Billion. 2004. Critical Loads Ontario: Relating Exceedance
of the Critical Load with Biological Effects at Ontario Forests. Report 2. Environmental
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Chapter 5 - Nutrient Enrichment
5.0 NUTRIENT ENRICHMENT
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).
5.1 SCIENCE OVERVIEW
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 (FinalReport) (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). Eutrophi cation 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
eutrophi cation in inland freshwater, estuarine, and coastal marine ecosystems. Eutrophi cation
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 nitrogen-
limited or nitrogen and phosphorus co-limited (e.g., Baron, 2006; Bergstrom and Jansson, 2006;
Bergstrom et al., 2005; Elser et al., 1990; Fenn et al., 2003; Tank and Dodds, 2003). In a meta-
analysis 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
(Bergstrom 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 (Bergstrom 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).
Primary symptoms
Description
'* -i \ Chlorophyll a
(Phytoplankton)
Macroalgal blooms
Secondary symptoms
A measure used to indicate the amount of microscopic algae
(phytoplankton) growing in a water body. High concentrations can lead
to low dissolved oxygen levels as a result of decomposition.
Large algae commonly referred to as "seaweed" Blooms can cause
losses of submerged aquatic vegetation by blocking sunlight.
Additionally, blooms may smother immobile shellfish, corals, or other
habitat. The unsightly nature of some blooms may impact tourism due
to the declining value of swimming, fishing, and boating.
Description
Dissolved
oxygen
Submerged
aquatic vegetation
Nuisance/toxic
blooms
Low dissolved oxygen is a eutrophic symptom because it occurs as a
result of decomposing organic matter (from dense algal blooms), which
sinks to the bottom and uses oxygen during decay. Low dissolved
oxygen can cause fish kills, habitat loss, and degraded aesthetic values,
resulting in the loss of tourism and recreational water use.
Loss of submerged aquatic vegetation (SAV) occurs when dense algal
blooms caused by excess nutrient additions (and absence of grazers)
decrease water clarity and light penetration. Turbidity caused by other
factors (e.g.. wave energy, color) similarly affects SAV. The loss of SAV can
have negative effects on an estuary's functionality and may impact
some fisheries due to loss of a critical nursery habitat.
Thought to be caused by a change in the natural mixture of nutrients
that occurs when nutrient inputs increase over a long period of time.
These blooms may release toxins that kill fish and shellfish. Human
health problems may also occur due to the consumption of
contaminated shellfish or from inhalation of airborne toxins. Many
nuisance/toxic blooms occur naturally, some are advected into
estuaries from the ocean; the role of nutrient enrichment is unclear.
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 El (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 El 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 El served as the ecological indicator for the Aquatic Nutrient
Enrichment Case Study.
The ASSETS El 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 El (Appendix 6, Figure 2.2-1) provides a sound basis for conducting
an eutrophication assessment.
ASSETS El
The ASSETS El (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 El) 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 El approach to assessing
OEC and DFO.)
The ASSETS El 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 El 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
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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.
Stream
reach
segment
Downstream
monitoring
station, X
Upstream
monitoring
station, Y
Reservoir
Reach
contributing
area
Point source
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-surf ace 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:
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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 SPARRO Wand ASSETS El
To assess ecological response, the SPARROW output serves as the nitrogen load for the
calculation of the OHI index in the ASSETS EL In this case study, a complete analysis from
atmospheric deposition load to the ASSETS El 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 EL
Because an iterative assessment of changing nitrogen loads to predict ASSETS Els has
not been undertaken previously, a process to link the SPARROW model to the ASSETS El 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 El 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 El
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 EL
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Chapter 5 - Nutrient Enrichment
8
CO
O
LLJ
O
Low
Nitrogen lustre am Concentration
-I 1 1 r-
Moderate Low Moderate Moderate High
OHI Score (assuming constant susceptibility)
High
Figure 5.2-3. ASSETS El 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 El to the atmospheric
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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 El 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 offish 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
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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
Striped bass
Clams or bivalves
Sea scallop
Oyster, Eastern
Other
Total
$30,433,777
$5,306,728
$5,007,952
$2,808,984
$2,524,045
$6,190,474
$52,271,960
Virginia
Sea scallop
Menhaden
Blue crab
Croaker, Atlantic
Striped bass
Clam, Northern Quahog
Summer flounder
Other
Total
$62,891,848
$25,350,740
$13,222,135
$4,615,924
$3,834,906
$3,691,319
$3,186,229
$16,954,893
$130,561,765
Source: NOAA (2007, August). "Annual Commercial Landing Statistics."
(http://www.st.nmfs .noaa.gov/st l/commercial/landings/annual_landings.html)
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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.
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Chapter 5 - Nutrient Enrichment
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. DOT, 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.
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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
Howarth and Marino (2006) provide a
comprehensive summary of the literature and scientific
It is the general consensus that
nitrogen is the limiting element to
primary production in coastal marine
~ ,. 1 • • 1 o j j T,, ecosystems in the temperate zone.
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
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Chapter 5 - Nutrient Enrichment
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 (STORE!) 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 (CAP)
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/1) to wet nitrogen deposition amounts (kg/ha/yr) using a formula published by
Bergstrom 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 CAP, 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 Bergstrom 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.
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Chapter 5 - Nutrient Enrichment
Table 5.2-2. Wet Nitrogen Deposition Level vs. EPA Total Nitrogen (TN) Criteria for Lakes and Reservoirs
TNEPA
criteria
(Hg/L)
N wet dep
(kg
N/ha/yr)
NADP
mean wet N
dep (kg
N/ha/yr)
Agg
Ecor
II
100
4.46
1.19
Agg
Ecor
III
400
12.55
1.16
Agg
Ecor
IV
440
13.47
2.36
Agg
Ecor
V
560
16.13
3.02
Agg
Ecor
VI
780
20.65
5.01
Agg
Ecor
VII
660
18.23
6.36
Agg
Ecor
VIII
240
8.57
5.21
Agg
Ecor
IX
360
11.60
4.44
Agg
Ecor
XI
460
13.93
4.93
Agg
Ecor
XII
520
15.26
3.28
Agg
Ecor
XIII
1270
29.72
3.35
Agg
Ecor
XIV
320
10.62
4.22
Source: Prepared by Lingli Liu, U.S. EPA Office of Research and Development and transmitted in communication from Tara Greaver, U.S. EPA
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; (ig/L = micrograms per liter.
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Chapter 5 - Nutrient Enrichment
Total Wet N Dep Exceedance d Z! -9.99 • -5
^•-26.41 --15 H -4.99-0
-14.99 --10 ••001-192
NOAA CAP
Nutrient Criteria Bdy
Lakes
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
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Chapter 5 - Nutrient Enrichment
United States in which economic-related ecosystem services studies have been conducted. The
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, existing
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 States
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. Details
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, elevation (e.g.,
extending 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 and
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 river in North Carolina and is a mainstem river to the
Pamlico Sound—one of the two largest estuaries on the Atlantic Coast. The drainage area for the
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 role in
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 because
of the large amounts of agriculture within the watershed. One of the reasons for selecting the
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Chapter 5 - Nutrient Enrichment
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
The Chesapeake Bay is the largest estuary in the United States and has a complex
ecosystem of important habitats and food webs. The Potomac River is the second largest of five
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 Program's
Remediation Web site for specific inquiries:
http://www.chesapeakebay.net/bayrestoration.aspx?menuitem=13989. In 2007, it was 21% of the
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/circl 166/circl 166.pdf). Although NAWQA
states that the water quality concentration of nutrients in the Potomac River watershed does not
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 of
the Chesapeake Bay) and its eutrophication potential that are the focus of the Aquatic Nutrient
Enrichment Case Study.
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Chapter 5 - Nutrient Enrichment
Eutrophication became a water quality concern in the lower Neuse River watershed in the
late 1970s and early 1980s, and fish kills, algal blooms, and correspondingly high levels of
chlorophyll 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 Area
and Neuse River/Neuse River Estuary Case Study Area, it was necessary to have atmospheric
deposition 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 responses
for the year 2002. In both the Potomac River/Potomac Estuary Case Study Area and the Neuse
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
SPARROW Assessment
For the current condition 2002 analysis of the Potomac River/Potomac Estuary Case
Study Area, an estimated 40,770,000 kg of total nitrogen was deposited in the Potomac River
watershed 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 incremental yield derived within each
catchment of the Potomac River watershed, as well as estimates of the delivered yield (i.e., the
fraction of the incremental flux that ultimately reaches the estuary) (Figure 5.2-8). (Details on
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 across
the watershed can be shown. Differences between the incremental and delivered yields reflect the
instream losses that occur as the load from each catchment travels downstream to the target
estuary.
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Chapter 5 - Nutrient Enrichment
For this application and analysis of the 2002 current condition case, SPARROW was
used to model the loads from the Potomac River and its watershed to the upper portions of the
Potomac Estuary. The most downstream modeled catchment in the analysis lies downstream of
several major point sources between Washington, DC, and the mixing zone of the estuary. These
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 the
Potomac River watershed because of overall larger land area and applications of fertilizer and
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 estimated at
7,380,000 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.
SPARROW modeling for 2002
predicts that atmospheric
deposition was 20% of the total
nitrogen loading to the Potomac
River's estuary, producing an
TNS of 3.4 mg/L.
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Chapter 5 - Nutrient Enrichment
Potomac River Watershed: Atmospheric Deposition - Oxidized Nitrogen
Legend
^ Potomac River Vtetershed
I | NOAAUW, HUC6 Border
Atmospheric Deposition "
By Watershed Unit
IAN unitsiiiein I
-------
Chapter 5 - Nutrient Enrichment
Potomac River Watershed: Atmospheric Deposition - Total Nitrogen
Legend
^J Potomac River V^tershed
I I NOMUV* HUCB Border
Atmospheric Deposition "
By Watershed Unit
(All units-lie in
I |6-B
I I 8-10
"Total nitrogen is the sum of
oxidized and reduced nitrogen
species. Oxidized nitrogen
species and sources: wet -
nitrate (NADP); dry - paniculate
nitrate, nitric acid, nitrogen
pentoxide. nitrous acid, nitric
oxide, nitrogen dioxide.
peroxycyl nitrate, and organic
nitrate (CMAQ). Reduced
nitrogen species and sources:
wet- ammonium (NADP); dry-
ammonia and ammonium (CMAQ).
D 10 20 40 60
Vyatershed boundary layers aid mapping
i-fat.i •....«- IJ'OVCJolfiyl.iy:-1;. Th- ;ite I.IRI. r,
Ittp: ilm d .ysts-.usgs.gov.igis£hesbay/
'-'. h*!Ti-a:-:tiur.l
Figure 5.2-7. Atmospheric deposition yields of total nitrogen over the
Potomac River and Potomac Estuary watershed.
ASSETS El Assessment
An ASSETS El 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.
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
The ASSETS El for the 2002
Potomac River estuary current
condition scenario is Bad.
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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 El for the 2002 current condition
scenario is Bad.
2002 Base Case Results for Potomac Watershed
Map #1: Local Nitrogen Generation
(Incremental Yield)
Map #2: Local Nitrogen Load at Receiving Estuary
(Delivered Yield)
Legend
| | Potomac River
Watershed
~~| Cathments not included
J in SPARROW Modeling
Nitrogen Yield
by Watershed Unit
(all units are in kg/ha/yr)
Map#1
Incremental Yield
| | 4-6
I I 6-8
| | 10-12
Map #2
Delivered Yield
^4-6
| 8-10
10-12
0 10 20
40 CO
80
Watershed boundary layers
and mapping data were provided
by USOS. The site URLis:
http:ffmd.waterusgs.gov/gis/chesbay/
sp arrows do c/retv 3 . htm#se cti on 1
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
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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 El 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
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Chapter 5 - Nutrient Enrichment
Neuse River Watershed: Atmospheric Deposition - Oxidized Nitrogen
Legend
Atmospheric Deposition "
By Watershed Unit
(All units .ire in kg hayi)
I |4-6
** Oxidized nitrogen species and
sources: wet- nitrate (HADP); dry-
particulate nitrate, nitric acid,
nitrogen pentoxide, nitrous acid,
nitric oxide, nitrogen dioxide,
peroxycyl nitrate, and organic
nitrate (CMAQ)
0 5 10 20 30
50
Watershed boundary layers
and mapping data were provided
by USGS. The site URL is:
http://md.water.usgs.gov/gis/chesbay/
sparrow3/doc/retv3.htm#sectton1
Figure 5.2-9. Atmospheric deposition yields of oxidized nitrogen over the
Neuse River and Neuse River Estuary watershed.
Neuse River Watershed: Atmospheric Deposition - Reduced Nitrogen
Atlantic Oce.in
Legend
Atmospheric Deposition '
By Watershed Unit
(All units are in ktj lmyi|
I 2-4
I 4-e
fi-8
• MO
** Reduced nitrogen species and
sources: wet- ammonium (NADP);
(CMAQ).
16 24 32
40
Watershed boundary layers
and mapping dataware provided
by USES. The sita URLis:
http://md.water.usgs.gov/gis/chesbay/
sparrow3/doc/retv3.htm#section1
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
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Chapter 5 - Nutrient Enrichment
Neuse River Watershed: Atmospheric Deposition - Total Nitrogen
Atmospheric Deposition "
By Watershed Unit
(All units ,ne in kg hayil
"Total nitrogen is the sum of
oxidized and reduced nitrogen
species. Oxidized nitrogen
species and sources: wet-
nitrste (NADP); dry - particulate
nitrate, nitric acid, nitrogen
pentoxide, nitrous acid, nitric
oxide, nitrogen dioxide,
peroxycyl nitrate, and organic
nitrate (CMAQ). Reduced
nitrogen species and sources:
wet- ammonium (WADP); dry-
ammonia and ammonium (CMAQ)
l tnji.r '.--:-'•• Sv-:r: .aid mapfJiriS
data were provided by USGS. The site URL is
cttp /And.wste usgs goWgis/diesbay/
'.. - »:• '•.:.:- " -•. . ..'_ ,'.:•--..i:.';.;
Figure 5.2-11. Atmospheric deposition yields of total nitrogen over the
Neuse River and Neuse River Estuary watershed.
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).
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.
Final Risk and Exposure Assessment
5-30
September 2009
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Chapter 5 - Nutrient Enrichment
2002 Base Case Results for Neuse River Watershed
Map #1: Local Nitrogen Generation
(Incremental Yield)
Map #2: Local Nitrogen Load at Receiving Estuary
(Delivered Yield)
\
Legend
Nitrogen Yield
by Watershed Unit
(all units are in kg/ha/yr)
Map#1
Incremental Yield
| |4-6
i I 6-8
^H 8-10
IB > in
Map #2
Delivered Yield
]2-4
J4-6
0 10 20 40 60
VXktershed boundary layers
and mapping data were
provided byUSGS. The
site URL is:
http://md .water.usgs.gov/
gis/chesbay/sparrow3/
doo'retv3.htm#section1
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 El Assessment
Previous work was completed by NOAA using
the ASSETS El 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
El for the Neuse River Estuary for
2002 of Bad.
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September 2009
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Chapter 5 - Nutrient Enrichment
source of the load estimate and the exact timeframe of the data used to calculate the ASSETS El
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 El 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 El 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 El, 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 El (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
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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 El 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
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Chapter 5 - Nutrient Enrichment
Table 5.2-3. Typology Group Categorizations
Group
Group 0
Group 1
Group 2
Group 3
Group 4
Group 5
Group 6
Group 7
Group 8
Group 9
Number of Systems
13
35
5
8
18
3
2
16
17
21
Overriding Characteristics
Low freshwater inflow:estuarine area ratio; low depth;
low estuary mouth openness
Medium depth; medium estuary mouth openness; high
annual air temperature
High depth; low annual air temperature
High estuary mouth openness; high depth
Low estuary mouth openness; high freshwater
inflow :estuarine area ratio; low annual air temperature
High estuary mouth openness; high depth
High depth; high estuary mouth openness
High tidal range; medium estuary mouth openness; low
annual air temperature
High freshwater inflow :estuarine area ratio; low depth
Low depth; medium estuary mouth openness; high
annual air temperature
n
Group
• 3
06
07
rn 9
Figure 5.2-13. Preliminary classifications of estuary typology across the nation
(modified from Bricker et al., 2007).
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September 2009
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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 El 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 site-
specific 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 El 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 El scores is found. Extrapolation of results within this group
must be examined in greater detail.
Final Risk and Exposure Assessment 5-35 September 2009
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Chapter 5 - Nutrient Enrichment
0 200 400
1 Kilometers
Assessment of estuarine trophic status (ASSETS)
^B Bad: Moderate-high to high pressure, moderate-high to high eutrophic condition, and any expected future change in eutrophic condition.
1 1 Poor: Mode rate- low to high pressure, moderate to moderate-high eutrophic condition, and any expected future change in condition.
I ' Moderate: Any pressure, moderate-low to moderate-h gh eutrophic condition, and any expected future change in eutrophic condition.
i i Good: Low to moderate pressure, low to moderate-low eutrophic condition, and any expected future change in condition.
^S High: Low pressure, low eutrophic condition, and any expected improvement or no future change in eutrophic condition.
1 ' Unknown: Insufficient data for analysis.
Figure 5.2-14. ASSETS El 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
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September 2009
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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 El 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 El = 2.
Final Risk and Exposure Assessment 5-37 September 2009
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Chapter 5 - Nutrient Enrichment
c
.0
(0
+J
s
c
o
O
O LT>
•<~ ^~
o
o
o
o
o
o
Q
CM
Total Nitrogen Atmospheric
O
o
o
o
o
o
LO
CM
^f
^^
*
i
o o o c
o o o c
1
•5
o o o o
o o o c
o o o c
1
-)
o o o o
O LO O U
CO CO ^- ^
1
f
Deposition Load (kg/yr)
Figure 5.2-15. Response curve relating instream total nitrogen
concentration (TNS) to total nitrogen atmospheric deposition load (TNatm)
for the Potomac River watershed.
CO
o
• Calibration Points
- Fit Logistic Curve
0.0
1.0
2.0 3.0
TN (mg/L)
4.0
5.0
6.0
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 El
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 El.
The target ASSETS El scenario where El = 2
(improving from an ASSETS El 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 El score of Bad to a score
of Poor by reducing deposition of
total nitrogen by 78%.
Final Risk and Exposure Assessment
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September 2009
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Chapter 5 - Nutrient Enrichment
Table 5.2-4. Summary Statistics for Target
Eutrophication Index Scenarios — Potomac Estuary
(Current condition Eutrophication Index score of Bad)
Statistic
TNatm(kgN/yr)
% TNatm
Decrease
ASSETS El = 2 (Poor)
Mean
Median
5th Percentile
95th Percentile
-1.78 x IO6
-1.46 x IO6
-3.67 x IO6
9.02 x IO6
104
104
109
78
ASSETS El = 3 (Moderate)
No feasible solutions found
ASSETS EI=4 (Good) and ASSETS El
All TNatm = - 1.61 x 108,i.e.,TNs =
= 5 (High)
Omg/L
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 El = 2 can be
attained only from TNatm deposition
load decrease, as indicated by the
positive 95th percentile TNatm value of
9.02 x io6 (representing a 78% decrease).
Target scenario ASSETS El = 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 El = 4 and 5 had identical results. All 500 iterations returned a
TNs*i = 0, and a corresponding TNatm*inegative load equal to TNatm*i = (0 - 2.72)71.69 x IO"8 = -
1.61 x 10"8kg/yr. Clearly, target Els 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 El scenario, total nitrogen atmospheric deposition (TNatm) must be removed plus
an additional amount (represented by the negative resultant load corresponding to TNS ; = 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
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September 2009
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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 x io6 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 x IO6 kg N/yr) were
desired, a decrease of 61 x IO6 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 x IO6 kg N/yr) plus an additional 20 x IO6 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 x io6 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
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Chapter 5 - Nutrient Enrichment
c
;§ 1.115 -
TO
J=
§ ;
c
o 1110
o
c
O 1
0) ==
o u>
1
0
TO 1.100 -
y = 2.0E-09X + 1 .07
R2 = 1
f
-r
/
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m
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-------
Chapter 5 - Nutrient Enrichment
Calibration Points
Fit Logistic Curve
0.0
0.5
1.0
1.5 2.0
TN (mg/L)
2.5
3.0
3.5
Figure 5.2-18. Example of fitted response curve for target
ASSETS EI=2 for the Neuse River Estuary.
Each of the four ASSETS El scores representing state improvements (Poor-2,
Moderate-^, Good-4, High-5) was treated as a "target" ASSETS El score, and 500 Monte Carlo
simulations were run under each target ASSETS El 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 El scenario are
presented in Table 5.2-5.
For target scenario ASSETS El = 2 (improving from an ASSETS El score of Bad to
Poor), all decreases exceed 100%, meaning that not only must all TNatm deposition load be
removed to meet ASSETS El = 2,
but considerably more nitrogen
from other sources as well. Given
these results, the Neuse River
Estuary is currently somewhere
between these two ASSETS El
values (Bad and Poor) as was the
Potomac Estuary. There is some
Table 5.2-5. Summary Statistics for Target
Eutrophication Index Scenarios — Neuse River Estuary
(Current condition Eutrophication Index score of Bad)
evidence that it is slightly more
eutrophic than the Potomac Estuary,
because there was at least a slim
Statistic
TNatm (kg N/yr)
% TNatm
Decrease
ASSETS El = 2 (Poor)
Mean
Median
5th Percentile
95th Percentile
-1.43 x 108
-1.43 x 108
-1.47 x 108
-1.01 x 108
880
880
901
653
ASSETS El = 3 (Moderate)
No feasible solutions found
ASSETS EI=4 (Good) and ASSETS El = 5 (High)
All TNatm = -5.35 x 108, i.e. TNS = 0 mg/L
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September 2009
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Chapter 5 - Nutrient Enrichment
chance for the Potomac Estuary (at the 95th percentile) that a decrease in TNatm (of < 100%)
would achieve ASSETS El = 2.
Target scenario ASSETS El = 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.)
Target scenarios ASSETS El = 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)72.0 x 10'9= -5.35 x 108 kg/yr. Clearly, target scenarios of ASSETS El 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
f .,,,,,,,,. , ., .. f nitrogen from other sources as well must be
feasible based on the relative contributions from decreased
To change the Neuse River Estuary's El
score from Bad to Poor, not only must 100%
of the total atmospheric nitrogen deposition
be eliminated, but considerably more
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 x 106 kg N/yr was deposited in 2002. SPARROW
modeling predicts that this deposition input results in a loading of 1.2 x 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
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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.
1$
C D)
ro >^
H
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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 El. Because of the numerous data requirements and sources
required to conduct a full ASSETS El analysis, there is a large range of uncertainty that
can enter into the calculations. Best attempts were made to apply standardized evaluation
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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 El currently relies on heuristic estimates from systems experts.
Steady-state estimates/mean annual estimates. Both SPARROW and the ASSETS El
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 El 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;
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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,
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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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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
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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
(Pinusponderosa) 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).
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 NCV leaching and an
approximately 25% decrease in fine-
root biomass.
INDICATES
CAUSE-\\NDICATES
EFFECT
CONDITION OF
RliSOURCI.:
Fores! productivity.
btodi\crsst\, health
KNVIRONMKNTAL
STRF.SSORS
N- and S-bosed air polluiams:
direct loxicily and Modifying mid
fcni.li/ing effects
Figure 5.3-1. Importance of lichens as an
indicator of ecosystem health (Jovan, 2008).
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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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.
Rocky Mountain alpine lakes: shift in diatom community dominance (Baron, 2006)
Southern California: CSS loss (Wood et al., 2006)
San Bernardino Mountains and Sierra Nevada Mountains: acidophytic lichen
decline in MCF (Fenn et al., 2008)
Eastern Rocky Mountain Slope: low carbon:nitrogen; low lignin:nitrogen (Baron et
al,, 2000)
Eastern Rocky Mountain Slope: increased foliar nitrogen; increased mineralization
(Baron etai., 2000)
> San Bernardino Mountains and Sierra Nevada Mountains: shift from acidophytic
to neutral or nitrogen-tolerant lichen in MCF (Fenn et al., 2008)
• Minnesota grasslands: decreased plant species (Clark and Tilman, 2008)
• Northeast U.S.: N03 leaching (Aber et al., 2003)
Bay Area, CA: Increased cover of nonnative grasses; decreased native
grasses (Weiss, 1999)
San Bernardino Mountains and Sierra Nevada Mountains: loss of acidophytic
lichen in MCF (Fenn et al., 2008)
Southern California: shift in mycorrhizal species in CSS (Egerton-Warburton
and Allen, 2000}
Southern California: shift from native species to invasive grasses in CSS (Allen,
2008)
• San Bernardino Mountains: high dissolved organic nitrogen (Meixner
and Fenn, 2004)
• San Bernardino Mountains: nitrogen saturation (Fenn et al., 2000)
• Increased nitrogen in lichen (Fenn et al., 2007)
MCF: NO3 leaching (Fenn et al., 2008)
MCF: 25% decrease in fine-root biomass (Fenn et al., 2008)
• Southern California: NO3" leaching (Fenn et al., 2003)
• Southern California: high foliar nitrogen (Bytnerowicz and
Fenn, 1996)
• Los Angeles Basin, California: High NO emissions
(Bytnerowicz and Fenn, 1996)
Fraser Experimental Forest, CO:
increased foliar nitrogen; increased
mineralization (Rueth et al., 2003)
0246 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50
Nitrogen Deposition, kg/ha/yr
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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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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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 pre-
development. 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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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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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.
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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 meta-
analysis 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 short-
term 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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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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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
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:
"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)
• 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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• 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
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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.
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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).
\ RM Pin»
I SugM M jp»fl««Ji
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Chapter 5 - Nutrient Enrichment
5.3.4 Current Conditions in Case Study Areas
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 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.
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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1998; Padgett etal., 1999; Sirulniketal., ^ ,, c „ , ^ . , c c , ^
& ' Table 5.3-1. Coastal Sage Scrub Ecosystem
2007; Vourlitis et al., 2007). Figure 5.3-4 Area and Total Nitrogen Deposition
illustrates the levels of atmospheric nitrogen
deposition in CSS communities using
CMAQ/NADP data.
N Deposition
(kg/ha/yr)
>3.3
Area
(hectares)
654048.4179
138019.8922
Percent of
CSS Area, %
93.51
19.73
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.
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, andHirschfeldia 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, Eriogonumfasciculatum, 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) (Egerton-
Warburton 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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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.
| ] Counties
| Coastal Sage Scrub
Total N Deposition
kg/ha/yr
^] less than 3.3
| | 3.3-9.9
I 10 or greater
Source of CSS range is the California Department
of Forestry and Fire Protection.
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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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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Fresno
Santa Maria
cities
^B Coastal Sage Scrub 2002
Fire Threat
| Moderate
[ | High
^j Very High
I Extreme
Source ol CSS range and fire threat is the
California Department
of Forestry and Fire Protection.
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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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
[HNOs] 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.
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Sierra Nevada
| | San Bernardino NF
^^| Mixed Conifer
CMAQ
kg/ha/yr
less than 3.1
3.1 -5.1
5.2-10.1
102-16.9
17 or greater
Yosemite National Park
Kings Canyon National Park
) National Park
Source of Mixed Conifer: California Fire and
Resource Assessment Program
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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nutrients via the canopy, reduced nitrogen intake requirements on root structures, and increased
demand for carbon dioxide (€62) 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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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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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 (N(V 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 N(V leachate or potential nitrogen saturation may occur. At this deposition level, a
26% decrease in fine-root biomass is anticipated (Fenn et al., 2008). Rootshoot 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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Table 5.3-2. Mixed Conifer Forest Ecosystem Area and Nitrogen Deposition
N Deposition
(kg/ha/yr)
>3.1
>5.2
>10.2
>17
Area
(hectares)
1099133.482
130538.2573
11963.08815
0
Percent of MCF
Area, %
38.62
4.59
0.42
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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San Francis-
Acidophyte Lichens
San Bernardino NF
| | Sierra Nevada
CMAQ Total N Dep
kg/ha/yr
| | less than 3.1
~] 3.1 -5.1
5.2-10.1
10 2 or greater
••I' A"
J..--...7.
San Diego)
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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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 N(V 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 dry-
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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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Rocky Mountain
National Park
Transverse
Range
Total N Deposition
kg/ha/yr
1H 0.8 to < 1.5
>= 1.5 to < 3
>= 3 to < 6
>= 6 to < 9
>= 9 to < 12
>=12to<18
>= 18 to 20
Deposition data is the result of
combining CMAQ (dry) and
NADP (wet) over 12-km grid cells
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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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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* •
Legend
Total N Deposition
|kf|'h.i,'yr>
•• High: 66.507
, Low: 0.761
1 Material Parks
I National Ferct
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 NOs" 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 NOs" 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 NOs" in streamwater (San Bernardino Mountains, CA (coniferous): 2.9 and 18.8 kg/ha/yr)
10. NOs- 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, VW:
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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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.
High Probability of Negative Effects
Nitrogen Leaching to Streams
Moderate Probability of Negative Effects
Low Probability of Negative Effects
Loss of Acidophyte Lichen
Shift in AM Community in CSS
Decline in Acidophyte Lichen
Amount Nitrogen Utilized by
Healthy CSS Community
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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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).
Coverage Areas of Interest
Alpine Areas
PNW and CA Regions with Lichen
| NE Forests
| Bluestern Grasslands
| CAMiYRrl-Cnniffir Fnresr
CA Mixed Conifer Forest
coastal sage scruD
| California Grassland Over Serpentinite Bedrock
I California Grasslands
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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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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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 (jimol)
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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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 N(V 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 NFS. (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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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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• 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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and
5.4 CONCLUSIONS
This chapter has examined the sensitivity and effects of nutrient enrichment on aquatic
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 El 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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the estuary). The overall ASSETS El 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
El 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 El for the Neuse River/Neuse River Estuary was Bad.
• It was found that the Neuse River/Neuse River Estuary ASSETS El 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 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
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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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Allen, E.B., PJ. Temple, A. Bytnerowicz, MJ. Arbaugh, A.G. Sirulnik, and L.E. Rao. 2007.
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Whitall, D., S. Bricker, J. Ferreira, A.M. Nobre, T. Simas, and M. Silva. 2007. Assessment of
eutrophication in estuaries: Pressure-state-response and nitrogen source apportionment.
Environmental Management 40:678-690.
Whitehead, J.C., T.C. Haab, and G.R. Parsons. 2003. "Economic Effects of Pfiesteria." Ocean &
Coastal Management 46(9-10): 845 -8 5 8.
Williams, M.W., J.S. Baron, N. Caine, R. Sommerfeld, and J.R. Sanford. 1996. Nitrogen
saturation in the Rocky Mountains. Environmental Science and Technology 30: 640-646.
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Chapter 5 - Nutrient Enrichment
Williams, M.W. and K. A. Tonnessen. 2000 Critical loads for inorganic nitrogen deposition in the
Colorado Front Range, USA. Ecological Applications 10:1648-1665.
Wolfe, A.P., J.S. Baron, and RJ. Cornett, 2001. Unprecedented changes in alpine ecosystems
related to anthropogenic nitrogen deposition. Journal ofPaleolimnology 25:1-1.
Wolfe, A.P., Van Gorp, A.C. & J.S. Baron, 2003. Recent ecological and bioecological changes
in alpine lakes of Rocky Mountain National Park (Colorado, U.S.A.): a response to
anthropogenic nitrogen deposition. Geobiology 1: 153-168.
Wood, Y., T. Meixner, PJ. Shouse, and E.B. Allen. 2006. Altered Ecohydrologic response
drives native shrub loss under conditions of elevated N-deposition. Journal of
Environmental Quality 35:76-92.
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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 (SC>42")- and nitrate (NO3~)-based particulates (i.e., ammonium sulfate [(NFL^SO/t] and
ammonium nitrate [NHJSTOs]). 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
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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 thatN2O may cause a small decrease in stratospheric ozone (U.S. EPA, 1982a). Finally,
the 1982 NOX AQCD concluded thatN2O 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 (FinalReport) (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
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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)
2.2%
MFCs. PFCs.
SF6
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 SC>42" deposition
have resulted in changes in both mercury methylation and mercury concentrations in fish.
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Chapter 6 - Additional Effects
6.2.1 Science Background
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
(Munthe et al, 2007; Drevnick et al., 2007).
methylated compound, methylmercury. The
Current evidence indicates that in
watersheds where mercury is present,
increased SOX deposition very likely results
in methylmercury accumulation in fish
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 SC>42". 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 SC>42", very likely results in methylmercury
accumulation in fish (Drevnick et al., 2007; Munthe et al, 2007).
Establishing the quantitative relationship between SC>42" and mercury methylation in
natural settings is difficult because of the presence of multiple interacting factors in aquatic and
terrestrial environments, including wetlands, where SC>42", 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 SC>42" 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 SC>42" 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 lake-
water 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
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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.
VOLATILIZATION and
RE-DEPOSITION
*" OVERLAND RUNOFF >T°™WATER DISCHARGE ^ °OUTFLOW" .^ POINT-SOURCE DISCHARGE
INORGANIC MERCURY
o
I MORGAN 1C MERCURY
SEDIMENTATION
•X
6ROUND-WATER DISCHARGE'
DE-METHYLATION
* METHYLATION
S< « - I
METHYLMERCURY FOOD-CHAIN MAGNIFICATION
DIFFUSION and
RE-SUSPENSION
DE-METHYLATION
METHYLATION-
METHYLMERCURY
SEDIMENTATION
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
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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 SRB-
mediated mercury methylation (Fleming et al., 2006; Kerin et al., 2006).
Methyl mercury output by SRBs is a by-product of the conversion of SC>42"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 SC>42" to SRB in the presence of divalent mercury (Hg+2), usually in low oxygen
sediments, leads to the following biomediated transformation:
Hg-
[SRB] -> MeHg+
The presence of SC>42", 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 SC>42" 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.
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Chapter 6 - Additional Effects
(1999) and Jeremiason et al. (2006). The beneficial effect of decreased SC>42" 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 SC>42". 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).
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Chapter 6 - Additional Effects
Oxic Zone
scv
Hg (ii)
Anoxic Zone
SRB
32-
CH3Hg
Figure 6.2-2. Biogeochemical process of mercury methylation.
6.2.2.1 Watershed Influences
The effect of watersheds on methylmercury production is dependent on many factors
(e.g., dissolved organic carbon, temperature, anoxia, SC>42"); 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.
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).
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).
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Chapter 6 - Additional Effects
State-level fish consumption advisories for
, , 4 4 -4 • f u- u advisories in the United States in
mercury are based on state criteria, many of which are
based on EPA's fish tissue criterion for methylmercury at
advisories.
0.3 microgram per gram (ug/g) or on U.S. Food and Drug
There were 3,080 fish consumption
2006, with 48 states, one territory,
and two tribes having mercury
Administration action limits of 1.0 mg/kg, equal to Ippm 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.
Final Risk and Exposure Assessment 6-9 September 2009
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Chapter 6 - Additional Effects
NH-9
MA = 166
D Advisories exist for specific walerbodies only
E3 Statewide la adviiwi« forchemieakoniamifiants
AS =1 n VI
GU = 2 O PR
= 0 u
= 0u
A -IrxlUtfW < I > advisory from Hhe CSfye«ir* filv*r S*CH»a Trifte
t> -itwl(x)«i (281 advi«xi«. ftwrv the GWH L*fc« indiifv Fish ari«. r
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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 SC>42" 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 SC>42" 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).
<^=
Spatial Factors
Lake/Reservoir
Sediment Disturbance
Upstream Wetlands
Upstream Forested Land
Upstream Erosion
Upstream Urban Land
^=^
=>
=£>
>
^>
Mercury
SRB ) Methylmercury
Sulfate
=i>
A K
Does not promote meihylation Promotes metriylaiion
N V
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
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September 2009
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Chapter 6 - Additional Effects
concentrations of methylmercury. Figure 6.2-5 illustrates the type of current and forward-
looking 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 SC>42" 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).
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.
It is evident that decreases in
sulfate deposition will likely
result in decreases in
methylmercury concentration.
Mercury iensitivity
Store iniiii k'. i
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).
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Chapter 6 - Additional Effects
Decreases in SC>42" deposition have already shown promising reductions in
methylmercury. Observed decreases in methylmercury fish tissue concentrations have been
linked to decreased acidification and declining SO42" and mercury deposition in Little Rock
Lake, WI (Hrabik and Watras, 2002), and to decreased SC>42" deposition in Isle Royale in Lake
Superior, MI (Drevnick et al., 2007). Although the possibility exists that reductions in SC>42"
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 mercury-
sulfide complexes and SC>42", 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 meta-
analysis 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;
Hogberg 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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Multiple long-term forest experiments have demonstrated transient growth increases
followed by increased mortality, especially at higher rates of fertilization (Elvir et al., 2003;
Hogberg 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;Boxmanetal., 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 spruce-
fir 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
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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
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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 non-
forest 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 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.
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 meta-
analysis 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
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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 Sarraceniapurpurea (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
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
The evidence is sufficient to
infer a causal relationship
between nitrogen deposition and
the alteration of biogeochemical
cycling of carbon in transitional
ecosystems.
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
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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 CC>2 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 (Bergstrom 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
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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 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
The evidence is sufficient to
infer a causal relationship
between nitrogen deposition and
the alteration of biogeochemical
cycling of carbon in aquatic
ecosystems.
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
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sources are the dominant contributors (>90%) to atmospheric N2O. Terrestrial soil is the largest
source of atmospheric N2O, accounting for 60% of global emissions (TPCC, 2001). Nitrous oxide
production in soil is mainly governed by microbial nitrification and denitrification (Dalai et al.,
2003). The contribution of each process to total N2O production varies with environmental
conditions. Denitrifying bacteria reduce NC>3~or nitrite (NC>2~) into N2O or nitrogen (TS^) under
anaerobic conditions. In submerged soils, such as wetland soil, denitrification should be the
dominant process to N2O emissions (Conrad, 1996). Increasing NOs" input generally increases
the denitrification rate under suitable conditions of temperature and organic carbon supply. High
soil NOs" concentrations also inhibit the reduction of N2O to N2 and result in a high N2O/N2 ratio
(Dalai 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 NC>2~ or the decomposition of NC>2~. 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 nonagri cultural 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 kgN/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. NOs"
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 nonagri cultural 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
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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
(TPCC, 2001).
6.3.2.2 ISA Conclusion
The ISA concluded that the reviewed evidence is
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.
Averaged across 80 observations from terrestrial ecosystems,
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).
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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accounting for about 20% of global Cttt 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 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
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.
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+, NOs", NH4NO3, and urea) and the addition rates, ranging
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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+, NOs", 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:
F = (GN-GC)IN (2)
where
GNis 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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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 Hogberg (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
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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, 862 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 862 exposures over the growing season.
The appearance of foliar injury can vary significantly between species and growth conditions
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affecting stomatal conductance. Currently, no regular monitoring occurs for 862 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. SC>2 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 862 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 SC>2 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 862 concentrations and focus on 63 vegetation effects
research, few studies have emerged to better inform a metric and levels of concern for effects of
SC>2 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
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(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 NC>2 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 MV 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 MV, especially in comparison to foliar injury caused by exposure to Os (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 MV 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 MV 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 (Gunthardt-
Goerg et al., 1996). However, NO2 enhanced the negative effects of ozone on these poplars,
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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 FINOs vapor on vegetation. However,
the current ISA (U.S. EPA, 2008) highlighted recent research identifying FINOs as the cause for
decline of sensitive lichen species in areas with relatively high FINOs deposition. Further, HNOs
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), FINOs has been
estimated to provide 60 percent of all dry deposited nitrogen (Bytnerowicz et al., 1999).
FINOs 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 NOs 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) HNOs concentrations in month-
long fumigations and reported a significant decline in chlorophyll content and carbon exchange
capacity compared to thalli in control chambers. Thalli treated with HNOs 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 HNOs concentrations common to ambient summer conditions in the Los
Angeles air basin and that it is very likely that HNOs 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 HNOs deposition loads (Riddell et al., 2008).
At high ambient concentrations, HNOs 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 HNOs 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 HNOs 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 HNOs 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
Long-term effects of lower air concentrations that better approximate ambient HNO3
concentrations should be investigated.
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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, SO42") 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 NC>2 NAAQS; however,
the current ISA acknowledges thatN2O is a potent GHG, contributing 6.5% of total U.S. GHG
emissions (in CC>2 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 862 to protect against acute foliar injury, but it was
determined in 1993 that concentrations of NO, NC>2, and PAN are rarely high enough to have
phytotoxic effects on vegetation; therefore, no unique secondary standard exists. Relatively little
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Chapter 6 - Additional Effects
is known about the direct effects of HNOs vapor on vegetation, however, recent research on the
decline of sensitive lichen species was highlighted in the ISA. HNOs also has a very high
deposition velocity and may be an important source of nitrogen to plants. In the Transverse
Range's MCF, HNOs 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, HNOs 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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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.
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• 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 offish 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 offish species (Figure 7.1-1). The diversity and
distribution of phyto-zooplankton communities are also positively correlated with ANC.
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Chapter 7 - Synthesis and Integration of Case Study Results
14
2 12-
& 10 -
o.
8 -
£
OT 6 -
iE 4.
o
•- 2 -
o>
1 °-
z 2 "
_4
-21
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^ \ ^
M X
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.
.
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I Til
X) -100 0 100 200 300 400 S
ANC(peq/L)
)0
Figure 7.1-1. Number offish 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 (ueq/L), with each range representing a
probability of ecological damage to the community. ANC values >100 ueq/L are generally not
harmful (see Figure 7.1-1) to biota. With ANC <100 ueq/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 ueq/L. ANC concentrations <50 ueq/L result in negative
effects on sensitive biota. From 50 to 20 ueq/L, fish diversity and the overall fitness (i.e., health
and reproduction) of most aquatic organisms in the waterbody are reduced. For ANC <20 ueq/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 ueq/L, nearly complete loss offish 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
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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 ueq/L
Complete loss offish 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 ueq/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 ueq/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
ueq/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 ueq/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
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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 (pre-
industrial) 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 pre-
acidification and current average ANC concentrations of 44 modeled lakes is 106.8 to 134.0 and
50.5 to 81.8 ueq/L, respectively, which is, on average, a 15 ueq/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 ueq/L,
respectively, which is, on average, a 8 ueq/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' SC>42", N(V, 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 ueq/L,
0.05 ueq/L, and 3.5 ueq/L, respectively, for lakes in the Adirondack Case Study Area and 1.0
ueq/L, 0.06 ueq/L, and 1.0 ueq/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
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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 |ieq/L and 5.1 |ieq/L
for lakes in the Adirondack Case Study Area and 11.8 |ieq/L and 4.0 |ieq/L for streams in
Shenandoah Case Study Area. These direct comparisons show good agreement between
simulated and observed water quality values.
150
£•
I 100
4 ",
N(V, 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.
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150
£•
I 100
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Chapter 7 - Synthesis and Integration of Case Study Results
50
25
0)
O
-25
Observed
Simulated
Indian Lake
******
Dismal Pond
1975 1980 1985 1990 1995 2000 2005 2010
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
|ieq/L for Indiana Lake and 5.1 |ieq/L for Dismal Pond.
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Chapter 7 - Synthesis and Integration of Case Study Results
200
^150
_J
"fr
0)
=: 100
O
< 50
n
en
* 25
0)
z 0
oc
19
• Observed . . .. _ .
Helton Creek
Nobusiness Creek
*»*' »****'*•*'*»»•»
75 1980 1985 1990 1995 2000 2005 20
Years
10
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
|ieq/L for Helton Creek and 4.0 |ieq/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 ueq/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 SC>42 in runoff
originates from sea salt spray and anthropogenic deposition. Given a critical ANC protection
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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
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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.
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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 N(V and 804".
Given some "target" ANC concentration [ANCiimit]), 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 [ANCumit] 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]o ) to the watershed. Thus,
the amount of deposition that will maintain an ANC level above an ANCi;mit is described as
DL(N) + DL(S) = (fNupt + (1 - r)(Nimm + Nden) + (Nret + Sret)} + ([BC]0* - [ANCHmit])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
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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 ANCiimit:
DLmax(S) = [([BC]0* - [ANQevei])Q]/ (1-A) (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:
DLmm(S) = 0 (3)
In the case of nitrogen, DLm;n(N) is the minimum amount of deposition of total nitrogen (NHX +
NOX) that catchment processes can effectively remove (e.g., Nupt + N;mm + Nden +Nret) without
contributing to the acidic balance:
DLmm(N) = fNupt + (l-r)(Nimm + Nden) (4)
The DLmax(N) is the load for total nitrogen deposition when sulfur deposition is equal to
zero:
DLmax(N) = fNUpt + (l-r)(Nimm + Nden) + [([BC]0* - [ANCieVei])Q]/ (!-/?„) (5)
wherein 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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E
_l
Q
DLmax(N)
N Deposition
Figure 7.1-6. The deposit!onal load function defined by the model.
The thick lines indicate all possible pairs of deposit!onal loads of nitrogen and sulfur acidity that
a catchment can receive and still maintain an ANC concentration equal to its ANCimut. 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 SC>42" 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:
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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
asANC
• 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).
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Chapter 7 - Synthesis and Integration of Case Study Results
10
o
"o
2 1 -
'o
t/3
fl
,0
~5
PQ
.01 >
(
V, (Bc/Al^ = 1.2
^^*. (Bc/AlXit = 0.6
^"\.
^^\
\
V
1 1
) 25 50 75 1(
Cumulative Percentage of Species Exhibiting Reduced Growth Response
30
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/Al 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
Leach Ca2+ from leaf membrane
Reduce the ratio of Ca2+/Al in
soil and soil solutions
Physiological Response
Reduce the cold tolerance of
needles in red spruce
Dysfunction in fine roots of red
spruce blocks uptake of Ca2+
Effect on Forest Function
Loss of current year needles in
red spruce
Decreased growth and increased
susceptibility to stress in red
spruce
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Chapter 7 - Synthesis and Integration of Case Study Results
Biogeochemical Response to
Acidifying Deposition
Reduce the ratio of Ca2+/Al in
soil and soil solutions
Reduce the availability of
nutrient cations in marginal soils
Physiological Response
More energy is used to acquire
Ca2+ in soils with low Ca2+/Al
ratios
Sugar maples on drought-prone
or nutrient-poor soils are less
able to withstand stresses
Effect on Forest Function
Decreased growth and increased
photosynthetic allocation to red
spruce roots
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 USFS-
designated 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
(FffiEF) 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.
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Chapter 7 - Synthesis and Integration of Case Study Results
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.
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.
7.2.2 Modeling Approach
The Simple Mass Balance (8MB) 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 8MB 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.
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Chapter 7 - Synthesis and Integration of Case Study Results
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" (UNECE, 2004). Therefore, the
selection of the 8MB model was seen as the most suitable approach for this case study
examining critical loads for sugar maple and red spruce.
CONCLUSION: There is high confidence associated with the models, input parameters, and
assessment of uncertainty used in the case study analysis for terrestrial acidification.
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.
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Chapter 7 - Synthesis and Integration of Case Study Results
=
O
OJ
Q
CLmax(N)
N Deposition
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 CLm;n(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),
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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 (El) that is an estimation of the likelihood that the
estuary is experiencing specific discrete levels of eutrophication or will experience
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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 El, 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 El (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 El 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
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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 El occurs when the
SPARROW output is used as the nitrogen load in the overall human influence index calculation
of the ASSETS El score. For the purposes of this study, a complete analysis from atmospheric
deposition loading to ecological endpoint of the ASSETS El 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 El 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
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the intent of defining the atmospheric loads that are needed to improve the ASSETS El 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,
Asterionellaformosa 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
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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 NCV 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.
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Chapter 7 - Synthesis and Integration of Case Study Results
Rocky Mountain alpine lakes: shift in diatom community dominance (Baron, 2006)
• Southern California: CSS loss (Wood et al., 2006)
• San Bernardino Mountains and Sierra Nevada Mountains: acidophytic lichen
decline in MCF (Fenn et al., 2008)
• Eastern Rocky Mountain Slope: low carbon:nitrogen; low lignin:nitrogen (Baron et
•I., 2000)
• Eastern Rocky Mountain Slope: increased foliar nitrogen; increased mineralization
(Baron etal., 2000)
• San Bernardino Mountains and Sierra Nevada Mountains: shift from acidophytic
to neutral or nitrogen-tolerant lichen in MCF (Fenn et al., 2008)
• Minnesota grasslands: decreased plant species (Clark and Tilman, 2008)
» Northeast U.S.: NOj leaching (Aber et al.. 2003)
Bay Area, CA: Increased cover of nonnative grasses; decreased native
grasses (Weiss, 1999)
San Bernardino Mountains and Sierra Nevada Mountains: loss of acidophytic
lichen in MCF (Fenn et al., 2008)
Southern California: shift in mycorrhizal species in CSS (Egerton-Warburton
and Allen, 2000)
Southern California: shift from native species to invasive grasses in CSS (Allen,
2008)
• San Bernardino Mountains: high dissolved organic nitrogen (Meixner
and Fenn, 2004)
• San Bernardino Mountains: nitrogen saturation (Fenn et al., 2000)
• Increased nitrogen in lichen (Fenn et al., 2007)
MCF: NO3 leaching (Fenn et al., 2008)
MCF: 25% decrease in fine-root biomass (Fenn et al., 2008)
• Southern California: NO3" leaching (Fenn et al., 2003)
• Southern California: high foliar nitrogen (Bytnerowicz and
Fenn, 1996)
• Los Angeles Basin, California: High NO emissions
(Bytnerowicz and Fenn, 1996)
Fraser Experimental Forest, CO:
increased foliar nitrogen; increased
mineralization (Rueth et al., 2003)
0246 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50
Nitrogen Deposition, kg/ha/yr
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.
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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 NCV 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
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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
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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 El, 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 non-
atmospheric 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
Aquatic
Acidification
Terrestrial
Acidification
Excess Aquatic
Nitrogen
Enrichment
Excess Terrestrial
Nitrogen
Enrichment
Available Data
High quality
High quality
Medium quality
High quality,
limited ability to
extrapolate
Modeling
Approach
Fairly high
confidence
High confidence
Intermediate
confidence
None
Ecological Effect
Function
High confidence
Fairly high
confidence
Low confidence
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
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Chapter 7 - Synthesis and Integration of Case Study Results
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.
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Chapter 7 - Synthesis and Integration of Case Study Results
Table 7.5-2. Summary of Information Assessed in the Risk and Exposure Assessment to Aid in Informing Policy Based on Welfare
Effects
Exposure Pathway
(Current Deposition
Levels)
(NADP/CMAQ,
2002)
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
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
Affected Ecosystem
(Case Study Areas)
Adirondack
Mountains, NY
Blue Ridge Mountains
and Shenandoah
National Park, VA
Kane Experimental
Forest (Allegheny
Plateau, PA)
Hubbard Brook
Experimental Forest
(White Mountains,
NH)
Ecological
Response
(Targeted Effect)
Acidification in
lakes and streams
Acidification of
forest soils
Ecological
Indicator
Fish species
richness, abundance,
composition,
ANC
Tree health
Red spruce, sugar
maple
Bc/Al ratio
Ecological Effect
Species losses of
fish, phytoplankton,
zooplankton;
changed community
composition,
ecosystem structure,
and function
Decreased tree
growth
Increased
susceptibility to
stress, episodic
dieback; changed
community
composition,
ecosystem structure,
and function
Ecosystem Service Affected
Annual recreational freshwater
fishing in New York State =
more than 13 million days
Approximately $66.4 million
in implied value to NY anglers
from a zero- out of nitrogen
and sulfur deposition
Provision of wood products
(sugar maple)
900 million board feet timber
production
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Exposure Pathway
(Current Deposition
Levels)
(NADP/CMAQ,
2002)
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
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
Affected Ecosystem
(Case Study Areas)
Potomac River Basin,
Chesapeake Bay
Neuse River Basin,
Pamlico Sound
Southern California
Coastal Sage Scrub
Mixed Conifer Forest
(San Bernardino
Mountains and Sierra
Nevada Mountains,
CA)
Ecological
Response
(Targeted Effect)
Nutrient enrichment
in main stem river
of an estuary
Nutrient enrichment
in terrestrial
ecosystems
Ecological
Indicator
ASSETS El
Species composition
Ecological Effect
Habitat degradation,
algal blooms,
toxicity, hypoxia,
anoxia, fish kills,
decreases in
Hi oH i VPTQI tv
U1UU.1 V Wl olLV
Species changes,
nutrient enrichment
of soil, changes in
fire regime, changes
in nutrient cycling
Ecosystem Service Affected
Current saltwater
recreational fishing
26.1 million activity days
(North Carolina-
Massachusetts)
Annual benefits to California
residents hunting, fishing, and
wildlife viewing =
approximately $4.6 billion;
state expenditures for fire
suppression = $300 million
(2008)
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Agency Research Triangle Park, NC
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