UnitedStates August 2008
Environmental Protection EPA/600/R-08/082
Integrated Science Assessment for
Oxides of Nitrogen and Sulfur -
Environmental Criteria
(Second External Review Draft)
National Center for Environmental Assessment-RTF Division
Office of Research and Development
U.S. Environmental Protection Agency
Research Triangle Park, NC
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DISCLAIMER
This document is a first external review draft being released for review purposes only and does
not constitute U.S. Environmental Protection Agency policy. Mention of trade names or
commercial products does not constitute endorseent or recommendation for use.
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Contents
Tables
Figures
Acronyms and Abbreviations
Authors and Contributors
Clean Air Scientific Advisory Committee
Project Team
Executive Summary
Chapter 1. Introduction
1.1. Scope
1 .2. History of the NOx Review
1 .3. History of the SOx Review
1 .4. History of the Current Review
1 .5. Development of the ISA
1 .6. Causality Framework
1.6.1. First Step: Determination of Causality
1.6.2. Second Step: Evaluation of Ecoloaical Response
1.7. Organization of the ISA
Chapter 2. Source to Dose
2.1. Introduction
2.2. Sources and Emissions of Troposphere NOx
2.2.1 . Major Anthropoaenic Sources
2.2.2. Major Bioaenic Sources
2.2.2.1. Soils
2.2.2.2. Live Veaetation
2.2.2.3. Biomass Burnina
2.2.2.4. Liahtnina
2.2.3. Anthropoaenic and Bioaenic Sources of ixhO
2.3. Sources and Emissions of Tropospheric SOx
2.3.1 . Major Anthropoaenic Sources
2.3.2. Major Bioaenic Sources
2.4. NHx Emissions
2.5. Evaluatina Emissions Inventories
2.6. NOx-SOx-NHx Chemistry in the Troposphere
2.6.1. Introduction
2.6.2. NOx Chemistry
2.6.2. 1.0s Formation
2.6.2.2. Multiphase Interactions
2.6.2.3. Nitro-PAH Formation
2.6.3. SOx Chemistry
2.6.3.1 . Multi-phase SOx Chemistry
2.6.4. NHx Interactions
2.6.5. Transport-related Effects
2.7. Samplina and Analysis Techniques
2.7.1 . Methods for Relevant Gas-Phase N Species
2.7.1.1. NO and N02
2.7.1.2. NOY
2.7.1.3. HN03
2.7.1.4. Other Nitrates
2.7.1.5. NH3
2.7.2. Methods for Relevant Gas-phase S Species
V
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1-1
1-2
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1-7
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2-2
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2-11
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2-19
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2-44
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2-64
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2.7.2.1. Positive Interference
2.7.2.2. Neaative Interference
2.7.2.3. Other Methods
2.7.3. Methods for Relevant Aerosol-phase N and S Species
2.7.3.1. Artifacts
2.7.3.2. Other Methods
2.8. Methods to Compute NOx and SOx Concentrations, Chemical Interactions, and Deposition
2.8.1. CTMs
2.8.1.1. Global Scale
2.8.1.2. Regional Scale
2.8.1.3. Sub-reaional Scale
2.8.1 .4. Modeling Effects of Convection for Chemical Transport
2.8.2. Computed Deposition
2.8.2.1 . N Deposition and Flux with Biota
2.8.3. Air Quality Model Evaluation
2.8.3.1 . Ground-based Comparisons of Photochemical Dynamics
2.8.3.2. Deposition with CTMs
2.8.4. Computing Atmospheric Deposition to Specific Locations
2.8.5. PRB Concentrations of NOx and SOx
2.9. Ambient Monitoring and Reported Concentrations of Relevant N and S Species
2.9.1 . Routine Air Monitoring Networks in North America
2.9. 1.1. Pollutant Categories
2.9.2. Intensive Field Campaigns
2.9.3. Satellite-Based Air Quality Observing Systems
2.9.3.1. Satellite Coverages
2.9.3.2. Measurement Issues
2.9.4. European Air Monitoring Networks
2.9.5. Ambient Concentrations of Relevant N Compounds
2.9.5.1. NO and N02
2.9.5.2. NOY and NOz
2.9.5.3. Nitro-PAHs
2.9.5.4. NH3
2.9.5.5. NH4N03
2.9.6. Ambient Concentrations of Relevant S Compounds
2.9.6.1 . S02 and S042- Near Urban Areas
2.9.6.2. S02 and S042~ in rural and remote areas
2.10. Deposition of N and S Species
2. 10.1. Nitrogen
2.10.1 .1 . Example of N02 and HNOs Deposition and Flux Data from Harvard Forest
2.10.2. Sulfur
2.11. Summary
2.1 1 .1 . Emissions and Atmospheric Concentrations
2.1 1 .2. Field Sampling and Analysis
2.1 1 .3. Deposition of N and Sulfur
Chapter 3. Ecological and Other Welfare Effects
3.1. Introduction to Ecological Concepts
3.1 .1 . Critical Loads as an Organizing Principle for Ecological Effects of Atmospheric Deposition
3.1.2. Ecosystem Scale, Function, and Structure
3.1.3. Ecosystem Services
3.2. Ecological Effects of Acidification
3.2.1 . Effects on Major Biogeochemical Processes
3.2. 1.1. Soil Acidification
3.2.1.2. Sulfur Accumulation and S042~ Leaching
3.2.1 .3. N Accumulation and NOs" Leaching
3.2.1.4. Base-Cation Leaching
3.2.1 .5. Aluminum Leaching
3.2.1.6. Episodic Acidification
3.2.2. Terrestrial Ecosystems
3.2.2.1. Chemical Effects
3.2.2.2. Biological Effects
3.2.3. Aquatic Ecosystems
3.2.3.1. Chemical Effects
2-71
2-71
2-72
2-72
2-74
2-77
2-78
2-78
2-81
2-83
2-86
2-87
2-88
2-90
2-93
2-96
2-101
2-103
2-108
2-115
2-116
2-120
2-123
2-126
2-129
2-131
2-132
2-134
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2-148
2-155
2-156
2-158
2-165
2-165
2-178
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2-198
2-199
2-200
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3-1
3-3
3-4
3-5
3-5
3-6
3-8
3-9
3-12
3-13
3-14
3-19
3-20
3-25
3-36
3-36
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3.2.3.2. Biological Effects 3-57
3.2.4. Most Sensitive and Most Affected Ecosystems and Regions 3-68
3.2.4.1. Characteristics of Sensitive Ecosystems 3-68
3.2.4.2. Extent and Distribution of Sensitive Ecosystems 3-70
3.2.4.3. Levels of Deposition at Which Effects are Manifested 3-78
3.2.4.4. Acidification Case Study #1: Adirondack Region of New York 3-84
3.2.4.5. Acidification Case Study #2: Shenandoah National Park, Virginia 3-95
3.3. Nutrient Enrichment Effects from N Deposition 3-102
3.3.1. Reactive Nitrogen and the N Cascade 3-103
3.3.2. N Enrichment Effects on N Cycling 3-105
3.3.2.1. Terrestrial Ecosystems 3-107
3.3.2.2. Wetland Ecosystems 3-117
3.3.2.3. Freshwater Aquatic Ecosystems 3-119
3.3.2.4. Estuarine and Coastal Marine Ecosystems 3-123
3.3.2.5. Summary of Nr Effects on Biogeochemical Cycling of N and Associated Chemical Indicators 3-127
3.3.3. N Deposition Effects on Productivity and C Budgets 3-129
3.3.3.1. Terrestrial Ecosystems 3-129
3.3.3.2. Wetlands 3-139
3.3.3.3. Freshwater Aquatic 3-141
3.3.3.4. Estuarine and Marine 3-146
3.3.3.5. Summary 3-151
3.3.4. Biogenic Nitrous Oxide and Methane Flux 3-153
3.3.4.1. Methane 3-153
3.3.4.2. Nitrous oxide 3-156
3.3.4.3. Summary 3-160
3.3.5. Species Composition, Species Richness and Biodiversity 3-161
3.3.5.1. Terrestrial Ecosystem Biodiversity 3-162
3.3.5.2. Transitional Ecosystems 3-175
3.3.5.3. Freshwater Aquatic Ecosystems 3-179
3.3.5.4. Estuarine and Marine Ecosystems 3-182
3.3.5.5. Summary 3-184
3.3.6. Nr Deposition Effects on NOs" Toxicity 3-186
3.3.7. Critical Loads and Other Quantified Relationships between Deposition Levels and Ecological Effects 3-186
3.3.7.1. Empirical Critical Loads for Europe 3-187
3.3.7.2. U.S. 3-188
3.3.8. Characterization of Sensitivity and Vulnerability 3-191
3.3.8.1. Extent and Distribution of Sensitive and Vulnerable Ecosystems 3-191
3.3.9. Ecosystem Services 3-206
3.4. Other welfare effects 3-207
3.4.1. Non-acidification Effects of Sulfur 3-208
3.4.1.1. Biological Role of Sulfur 3-208
3.4.1.2. Cycling and Storage of Sulfur 3-212
3.4.1.3. Export of Sulfur 3-216
3.4.1.4. Sulfur and Methylation of Mercury 3-218
3.4.1.5. Summary 3-227
3.4.1.6. S Nutrient Enrichment Case Study: Interactive Effects of S and Hg in Little Rock Lake, Wl 3-227
3.4.2. Direct Phytotoxic Effects of Gaseous N and S on Vegetation 3-228
3.4.2.1. Direct Phytotoxic Effects of S02 on Vegetation 3-229
3.4.2.2. Direct Phytotoxic Effects of NO, N02 and Peroxyacetyl Nitrate (PAN) 3-231
3.4.2.3. Direct Phytotoxic Effects of HN03 3-235
Chapter 4. Summary and Conclusions 4-1
4.1. Source to Dose 4-1
4.1.1. Relevant Chemical Families and Constituent Species 4-1
4.1.2. Emissions and Atmospheric Concentrations 4-2
4.1.3. Deposition of N and S 4-3
4.1.4. Field Sampling and Analysis 4-4
4.2. Acidification 4-5
4.2.1. Terrestrial 4-5
4.2.1.1. Biogeochemistry and Chemical Effects 4-6
4.2.1.2. Biological Effects 4-7
4.2.1.3. Regional Vulnerability and Sensitivity 4-8
4.2.2. Aquatic 4-9
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4.2.2.1. Biological Effects 4-13
4.3. N Nutrient Enrichment 4-15
4.3.1. Terrestrial 4-16
4.3.1.1. Biogeochemical effects 4-17
4.3.1.2. Species richness, composition and biodiversity 4-19
4.3.2. Transitional 4-23
4.3.2.1. Biogeochemical Effects 4-23
4.3.2.2. Biological Effects 4-25
4.3.2.3. Regional vulnerability and sensitivity 4-26
4.3.3. Freshwater Aquatic 4-27
4.3.3.1. Biogeochemical Effects 4-27
4.3.3.2. Biological Effects 4-28
4.3.3.3. Regional Vulnerability and Sensitivity 4-29
4.3.4. Estuarine Aquatic 4-29
4.3.4.1. Biogeochemical effects 4-29
4.3.4.2. Biological Effects 4-31
4.3.4.3. Regional Vulnerability and Sensitivity 4-32
4.4. Direct Phytotoxic Effects 4-32
4.4.1. S02 4-32
4.4.2. NO, N02 and PAN 4-33
4.4.3. HN03 4-33
4.5. Mercury Methylation 4-33
Glossary
References
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Tables
Table 1-1. Aspects to aid in judging causality. 1-7
Table 1-2. Descriptors for weight of evidence for use in causal determination. 1-9
Table 2-1. Emissions of NOX, NH3, and SO2 in the U.S. by source and category, 2002. 2-2
Table 2-2. Total and non-EGU SC>2 emissions densities for selected U.S. counties, 2001. 2-15
Table 2-3. Relative contributions of various gas and aqueous phase reactions to aqueous NO3 formation
within a sunlit cloud, 10 minutes after cloud formation. 2-37
Table 2-4. Atmospheric lifetimes of SO2 and reduced sulfur species with respect to reaction with OH,
NO3, and Cl radicals. 2-46
Table 2-5. Relative contributions of various reactions to the total S(IV) oxidation rate within a sunlit cloud,
10 min after cloud formation. 2-50
Table 2-6. Satellite instruments used to retrieve tropospheric NO2 columns. 2-63
Table 2-7. Characteristics of principal airsheds for reduced-N deposition. 2-64
Table 2-8. Verified ambient NH3 monitors. 2-69
Table 2-9. Performance characteristics of the 7 EPA ETV tested NH3 methods. 2-69
Table 2-10. Atmospheric N loads relative to total N loads in selected great waters.* 2-105
Table 2-11. Natural and anthropogenic sources of atmospheric N compounds. 2-106
Table 2-12. Characteristics of oxidized-nitrogen airsheds. 2-107
Table 2-13. Characteristics of principal airsheds for reduced-N deposition. 2-108
Table 2-14. Major routine operating air monitoring networks.5 2-116
Table 2-15. Air monitoring networks/campaigns for non-routine special intensive studies. 2-125
Table 2-16. Satellite-based air quality observing systems.1'4 2-126
Table 2-17. Key atmospheric chemistry and dynamics data sets at the NASAGoddard DAAC. 2-128
Table 2-18. International and European air monitoring programs. 2-133
Table 2-19. Ambient NH3 concentrations summarized by study. 2-157
Table 2-20. Monitor counts for California and San Diego County, 2005. 2-166
Table 2-21. Monitor counts for Ohio and Cuyahoga County, 2005. 2-166
Table 2-22. Regional distribution of SO2 and SO42~ ambient concentrations, averaged for 2003-05. 2-170
Table 2-23. Distributions of temporal averaging inside and outside CMSAs. 2-170
Table 2-24. Range of mean annual SO2 concentrations and Pearson correlation coefficients in urban
areas having at least four regulatory monitors, 2003-2005. 2-172
Table 2-25. Regional changes in wet and dry N and S atmospheric concentrations and deposition, 1989-
1991 and 2003-2005. 2-201
Table 3-2. Examples of chemical indicators of effects from acidifying deposition to terrestrial ecosystems. 3-20
Table 3-3. Example biological effects indicators in terrestrial ecosystems. 3-26
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Table 3-4. Examples of chemical indicators of effects from acidifying deposition to aquatic ecosystems. 3-37
Table 3-5. Estimates of change in number and proportion of acidic surface waters in acid-sensitive
regions of the North and East, based on applying current rates of change in Gran ANC to
past estimates of population characteristics from probability surveys. 3-46
Table 3-6. Regional trend results for long-term monitoring lakes and streams for the period 1990 through
2000 (values are median slopes for the group of sites in each region). 3-47
Table 3-7. Model estimates of long-terms S deposition load required to achieve certain surface water
quality criteria (ANC above 0, 20, or 50 eq/L) in different endpoint years (approximately 2040
or 2100) and estimates of historic acidification in response to S deposition. 3-54
Table 3-8. General summary of biological changes anticipated with surface water acidification, expressed
as a decrease in surface water pH. 3-81
Table 3-9. Studies that either did or did not yield evidence that acidifying deposition affected certain
species of birds. 3-84
Table 3-10. Observed relationships between zooplankton species richness and lakewater ANC
in the Adirondack Mountains. 3-91
Table 3-11. Summary biogeochemical indicators of N addition to terrestrial ecosystems. 3-114
Table 3-12. Effects of fire on nutrient concentrations in forests in Nevada and California 3-116
Table 3-13. Summary of N cycling studies for wetlands. 3-118
Table 3-14. Summary of N deposition effects on leaching in freshwater aquatic ecosystems. 3-123
Table 3-15. Summary of N effects on forest carbon cycling. 3-132
Table 3-16. Summary of additional evidence of N effects on productivity of freshwater ecosystems. 3-144
Table 3-17. Summary of N effects on grassland biodiversity. 3-165
Table 3-18. Summary of N effects on arid and semi-arid ecosystems. 3-168
Table 3-19. Summary of N effects on desert ecosystems. 3-170
Table 3-20. Summary of N effects on lichens. 3-173
Table 3-21. Summary of N effects on alpine ecosystems. 3-174
Table 3-22. Summarized responses of coastal marshes ecosystem to N fertilization. 3-178
Table 3-23. N effects on species composition and biodiversity 3-181
Table 3-24. Biological indicators for the effects of elevated N deposition and related empirical critical
loads for major ecosystem types (according to the eunis classification) occurring in Europe. 3-188
Table 3-25. Summary of dose-response curves for N deposition and ecological indicators. 3-189
Table 3-26. changes in aquatic ecosystems associated with elevated N loadings in the Western U.S. 3-196
Table 3-27. Primary Goods and Services Provided by Ecosystems 3-207
Table 3-28. Summary of recent studies of SC>2 exposure to plants. 3-236
Table 4-1. Studies on chemical indicators of acidification to terrestrial ecosystems. 4-7
Table 4-2. Studies on chemical indicators of acidification in surface water. 4-12
Table 4-3. Indicators of estuarine eutrophication. 4-31
Table 4-4. Summary of N deposition levels and corresponding ecological effects. 4-34
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Figures
Figure 1-1. Biogeochemical cycles of NOxand SOx. 1-3
Figure 2-1. 2001 county-level total U.S. NO and NO2 emissions. 2-4
Figure 2-2. 2001 county-level total U.S. NO and NO2 emissions densities (tons per square mile). 2-5
Figure 2-3. 2001 county-level total U.S. NO and NO2 emissions densities (tons per square mile) from
EGUs. 2-5
Figure 2-4. 2001 county-level total U.S. NO and NO2 emissions densities (tons per square mile) from on-
road mobile sources. 2-6
Figure 2-5. 2001 county-level total U.S. SO2 emissions. 2-14
Figure 2-6. 2001 county-level total U.S. SO2 emissions densities (tons per square mile). 2-14
Figure 2-7. 2001 county-level SO2 emissions densities (tons per square mile) from EGUs. 2-15
Figure 2-8. 2001 county-level SO2 emissions densities (tons per square mile) from on-road mobile
sources. 2-16
Figure 2-9. 2001 county-level SO2 emissions densities (tons per square mile) from off-road mobile and
other transportation sources. 2-16
Figure 2-10. 2001 county-level total U.S. NH3 emissions. 2-19
Figure 2-11. 2001 county-level total U.S. NH3 emissions densities. 2-20
Figure 2-12. 2001 county-level NHs emissions densities from on-road mobile sources. 2-21
Figure 2-13. 2001 county-level NHs emissions densities from EGUs. 2-21
Figure 2-14. 2001 county-level NH3 emissions densities from miscellaneous and biogenic sources 2-22
Figure 2-15. Schematic diagram of the cycle of reactive oxidized N species in the atmosphere. 2-27
Figure 2-16. The combined NOx+SOx+NHx System showing how atmospheric fates and lifetimes of
reduced and oxidized N components are linked. 2-28
Figure 2-17. Measured values of O3 and NOZ (NOY- NOX). 2-36
Figure 2-18. Structures of some nitro-PAHs. 2-44
Figure 2-19. Formation of 2NP from the reaction of OH with gaseous PY. 2-45
Figure 2-20. Transformations of sulfur compounds in the atmosphere. 2-47
Figure 2-21. Comparison of aqueous-phase oxidation paths. 2-49
Figure 2-22. Relative humidity (RH) effects on deliquescence and efflorescence points for a
NaCI+Na2SO4 particle, indicating deliquescence at-72% RH and re-crystallization at-52%
RH. 2-51
Figure 2-23. Predicted isolines of particulate NO3 concentrations (ug/m3) as a function of total HNO3 and
NH3 at 293 K and 80 percent relative humidity, and with 25 ug/m3 SO42" and 2 ug/m3 total Cl. 2-54
Figure 2-24. Predicted particulate NO3 concentration as a function of relative humidity for a typical
environment. Actual measured values depend on aging characteristics of the particle. 2-54
Figure 2-25. Tropospheric NO2 columns (molecules NO2/cm2) retrieved from the SCIAMACHY satellite
instrument for 2004-2005. 2-64
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Figure 2-26. Schematic of the resistance-in-series analogy for atmospheric deposition. Function of wind
speed, solar radiation, plant characteristics, precipitation/moisture, and soil/air temperature. 2-89
Figure 2-27. 8 km southeast U.S. CMAQ doma Function of wind speed, solar radiation, plant
characteristics, precipitation/ moisture, and soil/air temperature in zoomed over Tampa Bay. 2-95
Figure 2-28. 2 km southeast U.S. CMAQ domain zoomed over Tampa Bay. 2-95
Figure 2-29. Hourly averages for 1-31 May, 2002, CMAQ 8 km and 2 km results and measured
concentrations of NO (a), NO2 (b), and total NOX (c). 2-96
Figure 2-30. May 2002 daily concentrations and 8 km CMAQ predictions for ethene at Sydney, FL. 2-96
Figure 2-31. May 2002 daily concentrations and 8 km CMAQ predictions for isoprene at Sydney, FL 2-97
Figure 2-32. Observed hourly PM25 concentrations at St. Petersburg, FL and results from CMAQ 8 km. 2-97
Figure 2-33. Observed and modeled ratios of O3to NOX. 2-97
Figure 2-34. Observed and CMAQ 8 km and 2 km predicted formaldehyde concentrations. 2-98
Figure 2-35. Hourly concentrations of H peroxide, observed and predicted by CMAQ 8 km and 2 km, 1-
31 May, 2002 at Sydney, FL. 2-98
Figure 2-36. Hourly and CMAQ-predicted HNO3 concentrations at Sydney, FL, 1-31 May, 2002. 2-100
Figure 2-37. Hourly and CMAQ-predicted NH3 concentrations at Sydney, FL, 1—31 May, 2002. 2-100
Figure 2-38. Scatter plot of total nitrate (HMOs plus aerosol nitrate) wet deposition (mg N/m2/yr) of the
mean model versus measurements for the North American Deposition Program (NADP)
network. 2-102
Figure 2-39. Scatter plot of total SO42~ wet deposition (mg S/m2/yr) of the mean model versus
measurements for the North American Deposition Program (NADP) network. 2-102
Figure 2-40. Principal airsheds and watersheds for oxides of nitrogen for estuaries. 2-104
Figure 2-41. Annual mean concentrations of NO2 (ppb) in surface air over the U.S. in the present-day
(upper panel) and policy relevant background (middle panel) MOZART-2 simulations. The
bottom panel shows the percentage contribution of the background to the present-day
concentrations. 2-109
Figure 2-42. Annual mean concentrations of SO2 (ppb) in surface air over the U.S. in the present-day
(upper panel) and policy relevant background (middle panel) MOZART-2 simulations. 2-110
Figure 2-43. Annual mean concentrations of wet and dry deposition of HNO3, NhfyNOs, NOX, HO2NO2,
and organic nitrates (mg N/m2/yr) in surface air over the U.S. in the present-day (upper
panel) and policy relevant background (middle panel) MOZART-2 simulations. 2-112
Figure 2-44. Annual mean concentrations of SOX deposition (SO2 + pSO4) (mg S/m /yr) in surface air
over the U.S. in the present-day (upper panel) and policy relevant background (middle panel)
MOZART-2 simulations. 2-113
Figure 2-45. July mean soil NO emissions (upper panels; 1 * 109 molecules/cm2/s) and surface PRB NOX
concentrations (lower panels; ppt) over the U.S. from MOZART-2 (left) and GEOS-Chem
(right) model simulations in which anthropogenic O^ precursor emissions were set to zero in
North America. 2-114
Figure 2-46. Aggregate map of the majority routine U.S. monitoring stations illustrating relatively broad
coverage across the continental U.S. with noted spatial gaps in low populated areas. 2-118
Figure 2-47. Trends in regional chemical composition of PM25 aerosols based on urban speciation sites
and averaged over the entire 2006 sampling period. 2-119
Figure 2-48. Original 3-tiered NCore design (left) and proposed site locations for Level 2 multiple
pollutant sites. 2-119
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Figure 2-49. Maps illustrating breadth of PM25 FRM and FEM and O3 network (left); and PM25 continuous
samplers (right). 2-121
Figure 2-50. Locations of chemical speciation sites delineated by program type. 2-122
Figure 2-51. Routinely operating North American precipitation and surface water networks. 2-124
Figure 2-52. Correlation surfaces between MODIS AOD and hourly PM25 surface sites from April-
September 2002. 2-130
Figure 2-53. Comparisons between GEOSchem global model and GOME derived formaldehyde fields
(left); Summer 2006 OMI column HCHO and translation to isoprene emission estimates
(right). 2-130
Figure 2-54. Superimposed eastern U.S. emission and combined GOME and SCIAMACHY NO2
1997-2002 trends (left); GOME NO2 trends from 1995-2002 (right). 2-132
Figure 2-55. 2004 OMI NO2 column images aggregated for all Fridays (left) and Sundays (right) indicating
weekend/weekday patterns associated with reduced Sunday emissions. 2-132
Figure 2-56. Location of ambient-level NO2 monitors for NAAQS compliance in 2007. Shaded states have
NO2 monitors; unshaded states have none. 2-134
Figure 2-57. Ambient concentrations of NO2 measured at all monitoring sites located within Metropolitan
Statistical Areas in the U.S. from 2003 through 2005. 2-135
Figure 2-58. Monthly average NO2 concentrations for January 2002 (left panel) and July 2002 (right
panel) calculated by CMAQ (36 X 36 km horizontal resolution). 2-136
Figure 2-59. Nationwide trend in NO2 concentrations. 2-136
Figure 2-60. Time series of 24-h avg NO2 concentrations at individual sites in Atlanta, GAfrom 2003
through 2005. A natural spline function (with 9 degrees of freedom) was fit and overlaid to the
data (dark solid line). 2-138
Figure 2-61. Time series of 24-h avg NO2 concentrations at individual sites in New York City from 2003
through 2005. A natural spline function (with 9 degrees of freedom) was fit and overlaid to the
data (dark solid line). 2-139
Figure 2-62. Time series of 24-h avg NO2 concentrations at individual sites in Chicago, IL from 2003
through 2005. 2-140
Figure 2-63. Time series of 24-h avg NO2 concentrations at individual sites in Baton Rouge, LA from
2003 through 2005. 2-141
Figure 2-64. Time series of 24-h avg NO2 concentrations at individual sites in Houston, TX from 2003
through 2005. 2-142
Figure 2-65. Time series of 24-h avg NO2 concentrations at individual sites in Los Angeles, CA from
2003 through 2005. 2-143
Figure 2-66. Time series of 24-h avg NO2 concentrations at individual sites in Los Angeles, CA from
2003 through 2005. 2-144
Figure 2-67. Time series of 24-h avg NO2 concentrations at individual sites in Riverside, CA from 2003
through 2005. A natural spline function (with 9 degrees of freedom) was fit and overlaid to the
data (dark solid line). 2-145
Figure 2-68. Time series of 24-h avg NO2 concentrations at individual sites in Riverside, CA from 2003
through 2005. 2-146
Figure 2-69. Mean hourly NO2 concentrations on weekdays and weekends measured at two sites in
Atlanta, GA. 2-148
Figure 2-70. Measured O^ (ppb) versus PAN (pptv by volume) in Tennessee, including (a) aircraft
measurements, and (b, c, and d) suburban sites near Nashville. 2-149
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Figure 2-71. Ratios of PAN to NO2 observed at Silwood Park, Ascot, Berkshire, U.K. from July 24 to
August 12, 1999. 2-150
Figure 2-72. Ratios of HNO2 to NC>2 observed in a street canyon (Marylebone Road) in London, U.K.
from 11 a.m. to midnight during October 1999. Data points reflect 15-min average
concentrations of MONO and NC>2. 2-151
Figure 2-73. Annual average gas-phase HNO3 concentrations, 2004-2006. 2-153
Figure 2-74. Concentrations of particulate NC>3 measures as part of the EPA's speciation network. 1
ug/m3 -0.40 ppb equivalent gas phase concentration for NOs". 2-154
Figure 2-75. Annual average gas-phase NO3 concentrations, 2004-2006. 2-155
Figure 2-76. County-scale NHs emissions densities from the CMU inventory model. 2-158
Figure 2-78. Estimated county-scale ambient NHs concentrations. 2-158
Figure 2-79. IMPROVE network measured annual averaged ammonium NO3 concentration for 2000 (left)
and for 2004 (right), (maps produced by VIEWS) 2-160
Figure 2-80. IMPROVE and CSN (labeled STN) monitored mean ammonium nitrate concentrations for
2000 through 2004. 2-161
Figure 2-81. Regional and local contributions to annual average PM2.s by pNOs for select urban areas
based on paired IMPROVE and CSN monitoring sites. 2-161
Figure 2-82. Maps of spatial patterns for average annual particulate NO3 measurements (top), and for
NH3 emissions for April 2002 from the WRAP emissions inventory (bottom). 2-163
Figure 2-83. CMAQ simulation of January monthly averaged particulate NO3 concentration using 1996
emissions (left), and fora 50% decrease in NH3 emissions (right). Source: U.S. EPA/WRAP. _ 2-163
Figure 2-84. Particulate NO3 source attribution by region using CAMx modeling for six western remote
area monitoring sites. 2-164
Figure 2-85. Criteria pollutant monitor locations (A) and SO2 monitor locations (B), California, 2005.
Shaded counties have at least one monitor. 2-167
Figure 2-86. Criteria pollutant monitor locations (A) and SO2 monitor locations (B), Ohio, 2005. Shaded
counties have at least one monitor. 2-167
Figure 2-87. Criteria pollutant monitor locations (A) and SO2 monitor locations (B), Arizona, 2005. Shaded
counties have at least one monitor. 2-168
Figure 2-88. Criteria pollutant monitor locations (A) and SO2 monitor locations (B), Pennsylvania, 2005.
Shaded counties have at least one monitor. 2-168
Figure 2-89. Criteria pollutant monitor locations (A) and SO2 monitor locations (B), New York, 2005.
Shaded counties have at least one monitor. 2-169
Figure 2-90. Criteria pollutant monitor locations (A) and SO2 monitor locations (B), Massachusetts, 2005.
Shaded counties have at least one monitor. 2-169
Figure 2-91. Steubenville, OH, 2003-2005. (a) Monthly mean, minimum, and maximum SO2
concentrations, (b) Monthly mean, minimum, and maximum SO42~ concentrations, (c)
Monthly mean SO42~ concentrations as a function of SO2 concentrations. 2-173
Figure 2-92. Philadelphia, 2003-2005. (a) Monthly mean, minimum, and maximum SO2 concentrations.
(b) Monthly mean, minimum, and maximum SO42~ concentrations, (c) Monthly mean SO42~
concentrations as a function of SO2 concentrations. 2-174
Figure 2-93. Los Angeles, 2003-2005. (a) Monthly mean, minimum, and maximum SO2 concentrations.
(b) Monthly mean, minimum, and maximum SO42~ concentrations, (c) Monthly mean SO42~
concentrations as a function of SO2 concentrations. 2-175
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Figure 2-94. Riverside, CA, 2003-2005. (a) Monthly mean, minimum, and maximum SO2 concentrations.
(b) Monthly mean, minimum, and maximum SO42~ concentrations, (c) Monthly mean SO42~
concentrations as a function of SO2 concentrations. 2-176
Figure 2-95. Phoenix, 2003-2005. (a) Monthly mean, minimum, and maximum SO2 concentrations, (b)
Monthly mean, minimum, and maximum SC>42~ concentrations, (c) Monthly mean SC>42~
concentrations as a function of SO2 concentrations. 2-177
Figure 2-96. Annual mean ambient SO2 concentration, 1989 through 1991 (top), and 2003 through 2005
(bottom). 2-179
Figure 2-97. Annual mean ambient SO42~ concentration, 1989 through 1991 (top), and 2003 through
2005 (bottom). 2-180
Figure 2-98. IMPROVE network measured annual averaged pSO4 concentration for 2000 (top) and for
2004 (bottom). Note difference in scale. 2-181
Figure 2-99. IMPROVE mean ammonium SO42" concentrations for 2000 through 2004. 2-182
Figure 2-100. IMPROVE and CSN (labeled STN) monitored mean ammonium SO42~ concentrations for
2000 through 2004. 2-182
Figure 2-101. Regional and local contributions to annual average PM2s by pSO4 for select urban areas
based on paired IMPROVE and CSN monitoring sites. 2-183
Figure 2-102. Contributions of the Pacific Coast area to the (NH4)2SO4 (ug/m3) at 84 remote-area
monitoring sites in Western U.S. based on trajectory regression (dots denote locations of the
IMPROVE aerosol monitoring sites). From Xu, et al. (2006). 2-184
Figure 2-103. pSO4 source attribution by region using CAMx modeling for six western remote area
monitoring sites. 2-185
Figure 2-104. Trends, 1990-2005 in S (left) and N (right) deposition for 34 sites in the eastern U.S. 2-186
Figure 2-105. Total average yearly wet and dry inorganic N deposition, excepting NH3, for 2004-2006
(top) and 1989-1991 (bottom). 2-188
Figure 2-106. Total average yearly inorganic nitrogen deposition by species, excepting NH3, for 2004-
2006 (top) and 1989-1991 (bottom). 2-189
Figure 2-107. NO3~ concentration in NADP wet deposition samples, 2004-2006. 2-190
Figure 2-108. Average NO3" concentration in NADP wet deposition samples, 2004-2006. 2-190
Figure 2-109. Diel cycles of median concentrations (upper panels) and fluxes (lower panels) for the
Northwest clean sector, left panels) and Southwest (polluted sector, right panels) wind
sectors at Harvard Forest, April-November, 2000, for [NO], [NO2], and [O3/10]. 2-191
Figure 2-110. Simple NOx photochemical canopy model outputs. 2-192
Figure 2-111. Hourly (dots) and median nightly (pluses) NO2 flux vs. concentration, with results of least
squares fit on the hourly data (curve). 2-193
Figure 2-112. Averaged profiles at Harvard Forest give some evidence of some NO2 input near the
canopy top from light-mediated ambient reactions, or emission from open stomates. 2-194
Figure 2-113. Summer (June-August) 2000 median concentrations (upper panels), fractions of NOy
(middle panels), and fluxes (lower panels) of NOy and component species separated by wind
direction (Northwest on the left and Southwest on the right). 2-195
Figure 2-114. Total average yearly wet and dry sulfur deposition for 2004-2006 (top) and 1989-1991
(bottom). 2-196
Figure 2-115. Total average yearly sulfur deposition by species for 2004-2006 (top) and 1989-1991
(bottom). 2-197
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Figure 3-1. Illustration of major fluxes of ions associated with S-driven acidification of drainage water. 3-6
Figure 3-2. Diagram illustrates "ideal" soil horizons to which many soils conform. 3-7
Figure 3-3. Results of an in situ bioassay during a period of episodic acidification in Buck Creek,
Adirondack Mountains, in spring 1990. 3-16
Figure 3-5. Diagram based on Fenn et al. (Fenn, 2006) shows indicators of forest physiological function,
growth and structure that are linked to biogeochemical cycles through processes that control
rates of Ca supply. 3-23
Figure 3-6. Distribution of red spruce (rose) and sugar maple (green) in the eastern U.S. 3-27
Figure 3-7. Mean (± standard error) of current-year red spruce needle winter injury in reference and
calcium-addition watersheds and among crown classes, expressed as foliar injury (A) and
bud mortality (B). 3-29
Figure 3-8. Conceptual diagram outlining the current understanding of sugar maple decline. 3-31
Figure 3-9. Native range of flowering dogwood (Cornus florida) (dk. gray) and the documented range of
dogwood anthracnose in the eastern U.S. (red). 3-32
Figure 3-10. Surface water alkalinity in the conterminous U.S. 3-37
Figure 3-11. Summary of regional trends in surface water chemistry from 1990 to 2000 in regions
covered by the Stoddard et al. (2003) report. 3-41
Figure 3-12. Concentration of inorganic Al in Adirondack streams as a function of the calculated base
cation surplus. 3-44
Figure 3-13. F-factors calculated from PnET-BGC model results for the period 1850 to 1980 as a function
of simulated ANC in 1980 for 44 EMAP lakes in the Adirondack region of New York. 3-50
Figure 3-14. Median and range of projected change in ANC (ueq/L) of Adirondack lakes for 50-year
MAGIC simulations versus median future change in sulfur deposition (kg/ha/yr) for each
deposition scenario (points on each line correspond to -50%, -30%, -20%, 0%, +20%, +30%
change from current deposition). 3-52
Figure 3-15. Number of fish species as a function of mean stream ANC among 13 streams in
Shenandoah National Park, Virginia. 3-64
Figure 3-16. Number of fish species per lake versus acidity status, expressed as ANC, for Adirondack
lakes. 3-65
Figure 3-17. Regions of the eastern U.S. that contain appreciable numbers of lakes and streams that are
sensitive to acidification from acidifying deposition. 3-72
Figure 3-18. Spatial patterns in predicted wet SC>42~ and NC>3 deposition in the Adirondack Park during
the period 1988 to 1999. 3-86
Figure 3-19. Measured wet deposition of sulfur at the Huntington Forest NADP/NTN monitoring station. 3-87
Figure 3-21. Time series data for SC>42~, NC>3, base cations [Ca plus Mg], Gran ANC, pH, and dissolved
OC in one example Long-Term Monitoring Lake in the Adirondack Park. 3-93
Figure 3-22. Mean rates of change in solute concentration in 16 lakes of the Adirondack Long-Term
monitoring (ALTM) program from 1982 to 2000. 3-94
Figure 3-23. Simulated cumulative frequency distributions of lakewater ANC at three dates for the
population of Adirondack lakes, based on MAGIC model simulations reported by Sullivan et
al., 2006. 3-95
Figure 3-24. Wet sulfur deposition for the period of record at the Big Meadows NADP/NTN monitoring
station in Shenandoah National Park. 3-96
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Figure 3-25. Length-adjusted condition factor (K), a measure of body size in blacknose dace (Rhinichthys
atratulus) compared with mean stream pH among 11 populations (n = 442) in Shenandoah
National Park.
Figure 3-26. Illustration of the N cascade showing the movement of the human-produced reactive
nitrogen (Nr) as it cycles through the various environmental reservoirs in the atmosphere,
terrestrial ecosystems, and aquatic ecosystems. 3-105
Figure 3-27. N cycle (dotted lines indicated processes altered by N saturation). 3-106
Figure 3-28. Schematic illustration of the response of temperate forest ecosystems to long-term, chronic
N additions. 3-109
Figure 3-29. Surface water NO3~ concentrations as a function of N deposition at the base of each
watershed in summer and spring. 3-111
Figure 3-30. a) N export in stream water as a function of N deposition at the base of sampled
watersheds. 3-112
Figure 3-31. Mean annual NO3~ concentrations in 230 lakes and streams across the northeastern U.S. 3-120
Figure 3-32. NO3~ concentrations in high-elevation lakes in western North America. 3-121
Figure 3-33. A conceptualization of the relationship between overall eutrophic conditions, associated
eutrophic symptoms, and influencing factors (N loads and susceptibility). 3-124
Figure 3-34. Estimated anthropogenic N inputs to the estuaries of the northeastern U.S., in kg/ha/yr. 3-126
Figure 3-35. Interactions between the carbon and N cycles. 3-131
Figure 3-36. Mean 5-year radial increment from 31,606 core samples from Picea abies during the period
1945 to 1996 for three atmospheric N deposition zones (high, medium, and low wet N-
deposition in 1990), respectively. 3-133
Figure 3-37. Effects of N addition on forest ecosystem C content. 3-137
Figure 3-38. Effects of N addition on NEE of non-forest ecosystems. 3-141
Figure 3-39. N cycle in freshwater ecosystem. 3-142
Figure 3-40. Description of the eutrophic symptoms included in the national estuary condition
assessment. 3-148
Figure 3-41. A high chlorophyll a rating was observed in a large number of the nation's estuaries. 3-149
Figure 3-42. Frequency of hypoxia in Long Island Sound, 1994 to 2002. 3-151
Figure 3-43. Effects of N addition on biogenic CH4 emission. 3-154
Figure 3-44. Effects of N addition on biological CH4 uptake. 3-155
Figure 3-45. Effects of N addition on biological ChU uptake. 3-155
Figure 3-46. Effects of N addition on biogenic N2O emission. 3-157
Figure 3-47. Effects of N addition on biogenic N2O emission. 3-159
Figure 3-48. The relationship between N2O emission and N deposition. 3-159
Figure 3-49. Diatom assemblage sediment patterns in Emerald Lake, WY. 3-180
Figure 3-50. Microscopic counts of phytoplankton species composition in the Neuse River Estuary, NC
following 36-h in situ bioassaysto manipulate available forms of N. 3-184
Figure 3-51. Map of the western U.S. showing the primary geographic areas where N deposition effects
have been reported. 3-193
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Figure 3-52. Map of location of wetlands in the eastern U.S. 3-194
Figure 3-53. Overall eutrophication condition on a national scale. 3-197
Figure 3-54. Changes in plant species composition associated with N addition treatments in an alpine dry
meadow of the Colorado Front Range. 3-201
Figure 3-55. Diagram of multiple factors contributing to forest susceptibility to wildfire. 3-205
Figure 3-56. Representation of the S cycle in forest ecosystems. 3-213
Figure 3-57. Simplified cycle of Mercury, showing the role of Sulfur. Arrows are not proportional with
actual rates. 3-220
Figure 3-58. (A) SC>42~ and (B) methylmercury (MeHg) concentrations as a function of time in sediment
slurries made from Quabbin Reservoir littoral sediments. Each delta point represents the
average value from three separate incubations and the associated standard error. 3-222
Figure 3-59. Methylmercury produced in sediment cores incubated two weeks under artificial lake water
containing 3-1040 uM Na2SO4. 3-224
Figure 3-60. The microarchitecture of a dicot leaf. While details among species vary, the general
overview remains the same. Light that drives photosynthesis generally falls upon the upper
(adaxial leaf surface. CC>2, SOx, NOx, and O^ gases generally enter through the stomata on
the lower (abaxial) leaf surface, while water vapor exits through the stomata (transpiration). 3-230
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Acronyms and Abbreviations
ACCENT Atmospheric Composition Change: the European Network of
excellence
AIRMoN Atmospheric Integrated Research Monitoring Network
AIRS Atmospheric Infrared Sounder (instrument)
Al aluminum
A13+ aluminum ion
A^ inorganic aluminum
AF+ aluminum ion
A10 organic aluminum
A1(OH)3 aluminum hydroxide
ALSC Adirondack Lake Survey Corporation
ALTM Adirondack Long Term Monitoring
AMD acid mine drainage
ANC acid neutralizing capacity
AOD aerosol optical depth
AQCD Air Quality Criteria Document
AQEG Air Quality Expert Group
AQI Air Quality Index
AQS Air Quality System (database)
Ar argon
ARP Acid Rain Program
ARS Agricultural Research Service
As arsenic
ASI Acid Stress Index
asl above sea level
ATMOS Atmospheric Trace Molecule Spectroscopy
ATTILA type of Lagrangian model
AUSPEX Atmospheric Utility Signatures, Predictions, and Experiments
AVTRIS Airborne Visible and Infrared Imaging Spectrometer
Ba barium
BBW Bear Brook Watershed
BB WM Bear Brook Watershed, Maine
BC black carbon
BCS base-cation surplus
BGC BioGeoChemical (model)
B-IBI benthic index of biological integrity
BMPs best management practices
BNF bacterial nitrogen fertilization
Br bromine
Br bromine ion
Br2 molecular bromine
BrCl bromine chloride
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BrO
BUY
BUVD
C
12C
13C
ca
Ca
Ca2+
CAA
CAAA
CAAAC
CaCl2
CaCO3
CALIPSO
Ca(NO3)2
Ca(OH)2
CAPMoN
CaSO4-2H2O
CASTNet
CB4
Cd
CEC
CENTURY
CFCs
CG
chl a
CH4
C2H4
C2H6
C5H8
CH3CHO
CH3C(O)
CH3C(O)OO
CH2I2
CH2O
CH3OOH
CH3-S-CH3
CH3-S-H
(CH3)2SO
CH3SO3H
CH3-S-S-CH3
bromine oxide
Backscatter Ultraviolet Spectrometer
Beneficial Use Values Database
carbon; concentration
carbon-12, stable isotope of carbon
carbon-13, stable isotope of carbon
ambient air concentration
calcium
calcium ion
Clean Air Act
Amendments to the Clean Air Act
Clean Air Act Advisory Committee
calcium chloride
calcium carbonate
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation
(satellite)
calcium nitrate
calcium hydroxide
Canadian Air and Precipitation Monitoring Network
gypsum
Clean Air Status and Trends Network
Carbon Bond 4 (model)
cadmium
cation exchange capacity
model that simulates carbon, nitrogen, phosphorus, sulfur, and water
dynamics in the soil-plant system at monthly intervals over time scales
of centuries and millennia
chlorinated fluorocarbons
cloud-to-ground (lightning flash)
chlorophyll a
methane
ethene
ethane
isoprene
acetaldehyde
acetyl radical
acetyl peroxy radical
diiodomethane
formaldehyde
methyl hydroperoxide
dimethylsulfide, DMS
methyl mercaptan
dimethyl sulfoxide, DMSO
methanesulfonic acid
dimethyl disulfide, DMDS
interstitial air concentration
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CL critical load
Cl chlorine
Cl chlorine ion
C12 molecular chlorine
CLaMS type of Lagrangian model
CloudSat NASA Earth observation satellite
C1NO2 nitryl chloride
CMAQ Community Multiscale Air Quality (modeling system)
CMSA consolidated metropolitan statistical area
CO carbon monoxide
CO2 carbon dioxide
C(V carbonate
CONUS continental United States
CPUE catch per unit effort
CRREL U.S. Army Cold Regions Research and Engineering Laboratory
CS Consumer surplus
CS2 carbon disulfide
CSS coastal sage scrub (ecosystem)
CTM chemical transport model
Cu copper
CV contingent valuation
CVM contingent valuation method
A difference; change
DayCent model for daily biogeochemistry for forest, grassland, cropland, and
savanna systems
Day Cent-Chem combination of Day Cent-Chem and PHREEQC models
DC dichotomous choice
DDRP Direct Delayed Response Project
DDT Damage Delay Time
DECOMP decomposition model based on soil-plant system dynamics
DEP Department of Environmental Protection
DIG dissolved inorganic carbon
DIN dissolved inorganic nitrogen
DMDS dimethyl disulfide, CH3-S-S-CH3
DMS dimethyl sulfide, CH3-S-CH3
DMSO dimethylsulfoxide
DNDC Denitrification-Decomposition (model)
DO dissolved oxygen
DOC dissolved organic carbon
DON dissolved organic nitrogen
EBB East Bear Brook
EC elemental carbon
EEAs Essential Ecological Attributes
ELA Experimental Lakes Area
ELS Eastern Lakes Survey
EMAP Environmental Monitoring and Assessment Program
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EMEFS Eulerian Model Evaluation Field Study
EMEP Co-operative Programme for Monitoring and Evaluation of the Long-
range Transmission of Air Pollutants in Europe
EMF ectomycorrhizal fungi
EOS Earth Observation System
EPA U.S. Environmental Protection Agency
EPT Ephemeroptera-Plecoptera-Tricoptera (index)
ERP Episodic Response Project
ESA European Space Agency
EVRI Environmental Valuation Reference Inventory
F flux
F~ fluorine ion
FAB First-order Acidity Balance model
FACE free-air CO2 enrichment (studies)
Fe iron
FePO4 iron phosphate
FeS iron sulfide
F-factor fraction of the change in mineral acid anions that is neutralized by base
cation release
FHM Forest Health Monitoring
FIA Forest Inventory and Analysis (program)
FISH Fish in Sensitive Habitats (project)
FLEXPART type of Lagrangian model
ForSAFE three-component model using nitrogen, carbon cycling, and soil
chemistry
FRM Federal Reference Method
FTIR Fourier Transform Infrared Spectroscopy
FW2 black carbon soot
Fx flux
yN2O5 reaction potential coefficient for N2O5
GAW Global Atmospheric Watch (program)
GCE Goddard Cumulus Ensemble (model)
GDP gross domestic product
GEOS Goddard Earth Observing System
GEOS-Chem Goddard Earth Observing System (with global chemical transport
model)
GEOS- ID AS Goddard Earth Observing System Data Assimilation System
GFED Global Fire Emissions Database
GHG greenhouse gas
GOES Geostationary Operational Environmental Satellites
GOME Global Ozone Monitoring Experiment
gs stomatal conductance
GtC global ton carbon
Gton global ton
GWP global warming potential
H hydrogen; hydrogen atom
2H hydrogen-2, deuterium, stable isotope of hydrogen
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H+
ha
HAPs
HBEF
HBES
HBN
HC
HCHO
HC1
Hg
HNO2, HONO
HNO3, HOONO
HNO4
HO2
H2O2
HO2NO2
HOBr
HOC1
HOX
HP
HSCV
HSO4~
H2S
H2S03
H2SO4
hv
I
I2
IA
IADN
1C
ICARTT
ILWAS
IPC
lEc
IIASA
IMPROVE
ICARTT
INO3
INTEX-NA
10
IPCC
IPCC-AR4
IPCC-TAR
proton, hydrogen ion; relative acidity
hectare
hazardous air pollutants
Hubbard Brook Experimental Forest
Hubbard Brook Ecosystem Study
Hydrologic Benchmark Network
hydrocarbon
formaldehyde
hydrochloric acid
mercury
nitrous acid
nitric acid
pernitric acid
hydroperoxyl radical
hydrogen peroxide
peroxynitric acid
hypobromous acid
hypochlorous acid
hypohalous acid
hedonic pricing
bisulfate ion
sulfuric acid ion
hydrogen sulfide
sulfurous acid
sulfuric acid
photon with energy at wavelength v
iodine
molecular iodine
Integrated Assessment
Integrated Atmospheric Monitoring Deposition Network
intracloud (lightning flash)
International Consortium for Atmospheric Research on Transport and
Transformation
Integrated Lake-Watershed Acidification Study
International Cooperative Programme
Industrial Economics
International Institute for Applied Systems Analysis
Interagency Monitoring of Protected Visual Environments
International Consortium for Atmospheric Research on Transport and
Transformation
iodine nitrate
Intercontinental Chemical Transport Experiment - North America
iodine oxide
Intergovernmental Panel on Climate Change
Intergovernmental Panel on Climate Change 4th Assessment Report
Intergovernmental Panel on Climate Change 3rd Assessment Report
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IQR interquartile range
IR infrared
ISA Integrated Science Assessment
J flux from a leaf
JPL Jet Propulsion Laboratory
JRGCE Jasper Ridge Global Climate Change Experiment
K potassium
K+ potassium ion
Ka dissociation constant
Kb dissociation constant
KH Henry's Law constant in M atm-1
KNO3 potassium nitrate
Kw ion product of water
LAP Lake Acidification and Fisheries
LAR leaf-area ratio
LB laboratory bioassay
LCo.oi lethal concentration at which 0.01% of exposed animals die
LD33 lethal dose at which 33% of exposed animals die
LDH lactic acid dehydrogenase
LIDAR Light Detection and Ranging (remote sensing system)
LIF laser-induced fluorescence
LIMS Limb Infrared Monitor of the Stratosphere
LOD limit of detection
LP long-path
LRTAP Long Range Transport of Air Pollution
LTER Long-Term Ecological Research (program)
LTM Long-Term Monitoring (project)
M air molecule
MA Millennium Ecosystem Assessment
MAGIC Model of Acidification of Groundwater in Catchments (model)
MAHA Mid-Atlantic Highlands Assessment of streams
MAQSIP Multiscale Air Quality Simulation Platform (model)
MAT moist acidic tundra
MAX-DOAS multiple axis differential optical absorption spectroscopy
MBL marine boundary layer
MDN Mercury Deposition Network
MeHg methylmercury
MEM model ensemble mean
ueq microequivalent
Mg magnesium
Mg2+ magnesium ion
MIMS membrane inlet mass spectrometry
MM5 National Center for Atmospheric Research/Penn State Mesoscale
Model, version 5
Mn manganese
MOBILE6 Highway Vehicle Emission Factor Model
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MODIS Moderate Resolution Imaging Spectroradiometer
MOPITT Measurement of Pollution in the Troposphere
MOZAIC Measurement of Ozone and Water Vapor by Airbus In-Service Aircraft
MOZART Model for Ozone and Related Chemical Tracers
MPAN peroxymethacrylic nitrate
MSA metropolitan statistical area
Mt million tons
N nitrogen
N, n number of observations
14N nitrogen-14, stable isotope of nitrogen
15N nitrogen-15, stable isotope of nitrogen
N2 molecular nitrogen; nonreactive nitrogen
NA not available; insufficient data
Na sodium
Na+ sodium ion
NAAQS National Ambient Air Quality Standards
NaCl sodium chloride
NADP National Atmospheric Deposition Program
Na2MoO4 sodium molybdate
NAMS National Air Monitoring Stations
NANI Net anthropogenic nitrogen inputs
NAPAP National Acid Precipitation Assessment Program
NASQAN National Stream Quality Accounting Network
NARSTO program formerly known as North American Regional Strategy for
Atmospheric Ozone
NAS National Academy of Sciences
NASA National Aeronautics and Space Administration
Na2SO4 sodium sulfate
NASQAN National Stream Quality Accounting Network
NATTS National Air Toxics Trends (network)
NAWQA National Water Quality Assessment (program)
NCore National Core Monitoring Network
NEE net ecosystem exchange
NEG/ECP New England Governors and Eastern Canadian Premiers
NEI National Emissions Inventory
NEON National Ecological Observatory Network
NEP net ecosystem productivity
NFI net factor income
NH3 ammonia
NH2 amino (chemical group)
NH4+ ammonium ion
NH4C1 ammonium chloride
NH4NO3 ammonium nitrate
(NH4)2SO4 ammonium sulfate
NHX category label for NH3 plus NH4+
NHY total reduced nitrogen
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Ni
NILU
NITREX
nitro-PAH
NLCD
NMOC
NO
NO2
N02
NO3
N2O
N2O5
NOAA
NOAA-ARL
NOAEL
NOEC
NOX
NOY
NOZ
NPOESS
NPP
NFS
Nr
NRC
NS
NSF
NSS
nss
NSTC
NSWS
NTN
NuCM
02
03
16Q
18Q
190
oc
oco
ocs
0(JD)
OH
OMI
0(3P)
nickel
Norwegian Institute for Air Research
NITRogen saturation Experiments
nitro-polycyclic aromatic hydrocarbon
National Land Cover Data
nonmethane organic compound
nitric oxide
nitrogen dioxide
nitrite
nitrate
nitrous oxide
dinitrogen pentoxide
U.S. National Oceanic and Atmospheric Administration
U.S. National Oceanic and Atmospheric Administration Air Resources
Laboratory
no-observed-adverse-effect level
no-observed-effect concentration
sum of NO and NO2
sum of NOX and NOZ; odd nitrogen species; total oxidized nitrogen
sum of all inorganic and organic reaction products of NOX (HONO,
HNO3, HNO4, organic nitrates, paniculate nitrate, nitro-PAHs, etc.)
National Polar-orbiting Operational Environmental Satellite System
net primary production
National Park Service
reactive nitrogen
National Research Council
nonsignificant
National Science Foundation
National Stream Survey
non-sea salt
National Science and Technology Council
National Surface Water Survey
National Trends Network
nutrient cycling model
molecular oxygen
ozone
oxygen-16, stable isotope of oxygen
oxygen-18, stable isotope of oxygen
oxygen-19, radioactive isotope of oxygen
organic carbon
Orbiting Carbon Observatory
carbonyl sulfide
electronically excited oxygen atom
hydroxyl radical
Ozone Monitoring Instrument
ground-state oxygen atom
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P phosphorus
P, p probability value
PI Istpercentile
P5 5th percentile
P95 95th percentile
P99 99th percentile
PAHs polycyclic aromatic hydrocarbons
PAMS Photochemical Assessment Monitoring Stations
PAN peroxyacetyl nitrate
PANs peroxyacyl nitrates
PARASOL Polarization and Anisotropy of Reflectances for Atmospheric Sciences
coupled with Observations from a Lidar (satellite)
Pb lead
PEL planetary boundary layer
PC payment card
PCBs poly chlorinated biphenyl compounds
pH relative acidity
P(HNO3) production of nitric acid
PHREEQC model for soil and water geochemical equilibrium
PIRLA Paleocological Investigation of Recent Lake Acidification (projects)
pKa dissociation constant
PM paniculate matter
PM2 5 paniculate matter with aerodynamic diameter of #2.5 um
PMi o paniculate matter with aerodynamic diameter #10 um
PM10-2.5 paniculate matter with aerodynamic diameter between 10 and 2.5 um
PM-CAMx Comprehensive Air Quality Model with extensions and with paniculate
matter chemistry
PnET Photosynthesis and EvapoTranspiration (model)
PnET-BGC Photosynthesis and EvapoTranspiration-BioGeoChemical (model)
PnET-CN Photosynthesis and EvapoTranspiration model of C, water, and N
balances
PnET-N-DNDC Photosynthesis and EvapoTranspiration-Denitrification-Decomposition
(model)
pNCV paniculate nitrate
P(O3) production of O3
PCV, PO43~ phosphate
POPs persistent organic pollutants
ppb parts per billion
PPN peroxypropionyl nitrate
ppt parts per trillion
PRB policy relevant background
PRE-STORM Preliminary Regional Experiment for STORM
PROFILE model using soil mineralogy as input
PS producer surplus
pSO42~ paniculate sulfate
P(SO42~) production of sulfate
August 2008
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Q flow rate; discharge
Qio temperature coefficient
QAPP Quality Assurance Project Plan
R generic organic group attached to a molecule
R2 coefficient of determination
r2 correlation coefficient
Ra aerodynamic resistance
Rb boundary layer resistance
Rc internal resistance
RADM Regional Acid Deposition Model
RAMS Regional Atmospheric Modeling System
RAPS Regional Air Pollution Study
RCOO-s strongly acidic organic anions
RC(O)OO organic peroxy radical
RDT Recovery Delay Time
REMAP Regional Environmental Monitoring and Assessment Program
RH relative humidity
RLTM Regional Long-Term Monitoring
RMCC Research and Monitoring Coordinating Committee
RMSE root mean squared error
RO2 organic peroxyl; organic peroxy
RONO2 organic nitrate
RO2NO2 peroxynitrate
RP revealed preferences
RRX lognormal-transformed response ratio
RuBisCO ribulose-l,5-bisphosphate carboxylase/oxygenase
S sulfur
32S sulfur-32, stable isotope of sulfur
34S sulfur-34, stable isotope of sulfur
35S sulfur-35, radioactive isotope of sulfur
S AA sum of mineral acid anion concentrations
SAFE Soil Acidification in Forest Ecosystems (model)
SAMAB Southern Appalachian Man and the Biosphere (program)
S AMI Southern Appalachian Mountains Initiative
SAO Smithsonian Astrophysical Observatory
SAPRAC Statewide Air Pollution Research Center
SBC sum of base cation concentrations
SBUV Solar Backscatter Ultraviolet Spectrometer
SC safe concentration
SCAQS Southern California Air Quality Study
SCIAMACHY Scanning Imaging Absorption Spectrometer for Atmospheric
Chartography
Se selenium; standard error
SEARCH Southeastern Aerosol Research and Characterization Study (monitoring
program)
Si silicon
August 2008
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SIP State Implementation Plan
SJAQS San Joaquin Valley Air Quality Study
SLA specific leaf area
SLAMS State and Local Air Monitoring Stations
SMART Simulation Model for Acidification's Regional Trends (model)
8MB Simple Mass Balance (model)
SO sulfur monoxide
SO2 sulfur dioxide
SO3 sulfur trioxide
SO32~ sulfite
SO42~ sulfate ion
S2O disulfur monoxide
SONEX Subsonics Assessment Ozone and Nitrogen Oxides Experiment
SOS Southern Oxidant Study
SOS/T State of Science/Technology (report)
SOX sulfur oxides
SP stated preferences
SPARROW SPAtially Referenced Regressions on Watershed Attributes (model)
Sr strontium
86Sr strontium-86, stable isotope of strontium
87Sr strontium-87, stable isotope of strontium
SRB sulfate-reducing bacteria
SRP soluble reactive phosphorus
SSWC Steady State Water Chemistry (model)
STE stratospheric-tropospheric exchange
STN Speciation Trends Network
SUM06 seasonal sum of all hourly average concentrations 3 0.06 ppm
SVOC semivolatile organic compound
SWAS Shenandoah Watershed Study
T atmospheric lifetime
T time; duration of exposure
TAP Tracking and Analysis Framework (model)
Tmr air temperature
TAMM Timber Assessment Market Model
TAR Third Assessment Report
TC total carbon; travel cost
TCM travel cost method
TDLAS Tunable Diode Laser Absorption Spectrometer
Tg teragram
TIME Temporally Integrated Monitoring of Ecosystems (program)
TN total nitrogen
TOMS Total Ozone Mapping Spectrometer
TOR tropospheric ozone residual
TP total phosphorus
TRACE-P Transport and Chemical Evolution over the Pacific
TSI timber-stand improvement
August 2008
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TSS total suspended solids
Twater water temperature
UMD-CTM University of Maryland Chemical Transport Model
UNECE United Nations Economic Commission for Europe
USDA U.S. Department of Agriculture
USFS U.S. Forest Service
USGS U.S. Geological Survey
UV ultraviolet
UV-A ultraviolet radiation of wavelengths from 320 to 400 nm
UV-B ultraviolet radiation of wavelengths from 280 to 320 nm
Vd deposition rate
VOC volatile organic compound
VSD Very Simple Dynamic (soil acidification model)
VTSSS Virginia Trout Stream Sensitivity Study
WARMS Waterfowl Acidification Response Modeling System
WATERSN Watershed Assessment Tool for Evaluating Reduction Scenarios for
Nitrogen
WBB West Bear Brook
WEBB Water, Energy, and Biogeochemical Budgets
WFPS water-filled pore space
WGE Working Group on Effects
WLS Western Lakes Survey
WMO World Meteorological Organization
WMP Watershed Manipulation Project
WSA Wadeable Stream Assessment (survey)
wt % percent by weight
WTA willingness-to-accept
WTP willingness-to-pay
XNO3 nitrate halogen-X salt
XO halogen-X oxide
Zn zinc
ZnO zinc oxide
August 2008
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Authors and Contributors
Authors
Dr. Tara Greaver (NOX and SOX Project Manager)—National Center for Environmental Assessment
(B243-01), U.S. Environmental Protection Agency, Research Triangle Park, NC 27711
Dr. Jeffrey Arnold—National Center for Environmental Assessment (B243-01), U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711
Dr. Jill S. Baron—U.S. Geological Survey, Natural Resource Ecology Laboratory, Colorado State
University, Fort Collins CO 80523-1499
Dr. Bernard J. Cosby, Jr.—Department of Environmental Sciences, University of Virginia, Charlottesville,
VA 22904
Dr. Ila Cote—National Center for Environmental Assessment (B243-01), U.S. Environmental Protection
Agency, Research Triangle Park, NC 27711
Ms. Rebecca Daniels— National Health and Environmental Effects Research Laboratory (B305-02), U.S.
Environmental Protection Agency, Research Triangle Park, NC 27711
Dr. Jean-Jacques B. Dubois—National Center for Environmental Assessment (B243-01), U.S.
Environmental Protection Agency, Research Triangle Park, NC 27711
Dr. Christine L. Goodale—Department of Ecology and Evolutionary Biology, Cornell University, Ithaca,
NY 14853
Dr. Alan T Herlihy—Department of Fisheries & Wildlife, Oregon State University, Corvallis, OR 97331
Dr. Jeffrey D. Herrick—National Center for Environmental Assessment (B243-01), U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711
Dr. Alan J. Krupnick—Resources for the Future, 1616 P St NW, Washington, DC 20036-1400
Dr. Kathleen Fallen Lambert—Ecologic: Analysis and Communications, 39 Central Street, Suite 204,
Woodstock, VT 05 091
Dr. Gregory B. Lawrence—U.S. Geological Survey Troy, NY
Dr. Lingli Liu—National Center for Environmental Assessment (B243-01), U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711
Dr. Todd C. McDonnell—E&S Environmental Chemistry, Inc., P.O. Box 609, Corvallis, OR 97339
Dr. Kristopher Novak—National Center for Environmental Assessment (B243-01), U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711
Dr. Joseph Pinto—National Center for Environmental Assessment (B243-01), U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711
Dr. Rich Scheffe—Office of Air Quality Planning and Standards (C304-02), U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711
Dr. Juha Siikamaki—Resources for the Future, 1616 P StNW, Washington, DC 20036-1400
August 2008 xxvii DRAFT-DO NOT QUOTE OR CITE
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Dr. Timothy J. Sullivan—E&S Environmental Chemistry, Inc., P.O. Box 609, Corvallis, OR 97339
Dr. Helga Van Miegroet—Department of Wildland Resources, Department of Watershed Sciences, Utah
State University, Logan, UT 84322-5230
Dr. Paul F. Wagner—National Center for Environmental Assessment (B243-01), U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711
Contributors
Dr. Russell Dickerson—Dept. of Atmospheric and Oceanic Sciences, University of Maryland, College
Park, MD
Dr. Tina Fan— Environmental and Occupational Health Sciences Institute/ University of Medicine and
Dentistry: New Jersey, Piscataway, NJ
Dr. Arlene Fiore—Geophysical Fluid Dynamics Laboratory/NOAA, Princeton, NJ
Dr. Larry Horowitz—Geophysical Fluid Dynamics Laboratory/NOAA, Princeton, NJ
Dr. William Keene—Dept. of Environmental Sciences, University of Virginia, Charlottesville, VA
Dr. Randall Martin—Dept. of Physics, Dalhousie University, Halifax, Nova Scotia, Canada
Dr. William Munger—Center for Earth and Planetary Physics, Harvard University, Cambridge, MA
Dr. Sandy Sillman—Dept. of Atmospheric and Oceanic Sciences, University of Michigan, Ann Arbor, MI
Mr. Greg Miller—Office of Policy, Economics, and Innovation (1809T), 1200 Pennsylvania Avenue, N.
W., Washington, DC 20460
Dr. Brooke Hemming—National Center for Environmental Assessment (C604-01), U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711
Dr. Brian Heninger—Office of Policy, Economics, and Innovation (1809T), 1200 Pennsylvania Avenue,
N. W., Washington, DC 20460
Dr. Jason Lynch—Office of Air and Radiation, Office of Atmospheric Programs (6204J), Ariel Rios
Building, 1200 Pennsylvania Avenue, N. W., Washington, DC 20460
Dr. Rick Scheffe—Office of Air and Radiation, Office of Air Quality Planning and Standards (C304-02),
U.S. Environmental Protection Agency, Research Triangle Park, NC 27711
Dr. Dale Evarts—Office of Air and Radiation, Office of Air Quality Planning and Standards (C504-04),
U.S. Environmental Protection Agency, Research Triangle Park, NC 27711
Dr. Bryan Hubbell—Office of Air and Radiation, Office of Air Quality Planning and Standards (C504-
02), U.S. Environmental Protection Agency, Research Triangle Park, NC 27711
Dr. Anne Rea—Office of Air and Radiation, Office of Air Quality Planning and Standards (C539-02),
U.S. Environmental Protection Agency, Research Triangle Park, NC 27711
Ms. Vicki Sandiford—Office of Air and Radiation, Office of Air Quality Planning and Standards (C504-
06), U.S. Environmental Protection Agency, Research Triangle Park, NC 27711
Mr. Randy Waite—Office of Air and Radiation, Office of Air Quality Planning and Standards (C5 04-04),
U.S. Environmental Protection Agency, Research Triangle Park, NC 27711
August 2008 xxviii DRAFT-DO NOT QUOTE OR CITE
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Dr. Robin Dennis—National Effects Research Laboratory (E243-01), U.S. Environmental Protection
Agency, Research Triangle Park, NC 27711
Dr. John Walker—National Risk Management Research Laboratory (E305-02), U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711
Dr. Jana Compton—National Health and Environmental Effects Research Laboratory,
U.S. Environmental Protection Agency, 200 S.W. 35th Street, Corvallis, OR 97333-4902
Dr. William Hogsett—National Health and Environmental Effects Research Laboratory,
U.S. Environmental Protection Agency, 200 S.W. 35th Street, Corvallis, OR 97333-4902
Dr. Paul Ringold—National Health and Environmental Effects Research Laboratory, U.S. Environmental
Protection Agency, 200 S.W. 35th Street, Corvallis, OR 97333-4902
Dr. Dave A. Evans—Office of Policy, Economics, and Innovation (1809T), 1200 Pennsylvania Avenue,
N. W., Washington, DC 20460
Ms. Lydia Wegman—Office of Air and Radiation, Office of Air Quality Planning and Standards (C504-
02,) U.S. Environmental Protection Agency, Research Triangle Park, NC 27711
Dr. William Wilson—National Center for Environmental Assessment (B243-01), U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711
August 2008 xxix DRAFT-DO NOT QUOTE OR CITE
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Clean Air Scientific Advisory Committee
NOx and SOx Secondary NAAQS Review Panel
Science Advisory Board Staff Office
Dr. Armistead (Ted) Russell (Chairperson)—Georgia Power Distinguished Professor of Environmental
Engineering, Environmental Engineering Group, School of Civil and Environmental Engineering,
Georgia Institute of Technology, Atlanta, GA
Dr. Ellis B. Cowling, Emeritus Professor, Colleges of Natural Resources and Agriculture and Life
Sciences, North Carolina State University, Raleigh, NC
Dr. Donna Kenski, Director, Lake Michigan Air Directors Consortium, Rosemont, IL
Dr. Praveen Amar, Director, Science and Policy, Northeast States for Coordinated Air Use Management,
Boston, MA
Dr. Andrzej Bytnerowicz, Senior Scientist, Pacific Southwest Research Station, USDA Forest Service,
Riverside, CA
Ms. Lauraine Chestnut, Managing Economist, Stratus Consulting Inc., Boulder, CO
Dr. Douglas Crawford-Brown, Professor and Director, Department of Environmental Sciences and
Engineering, Carolina Environmental Program, University of North Carolina at Chapel Hill, Chapel Hill,
NC
Dr. Charles T Driscoll, Jr., Professor, Environmental Systems Engineering, College of Engineering and
Computer Science, Syracuse University, Syracuse, NY
Dr. Paul J. Hanson, Distinguished R&D Staff Member, Environmental Sciences Division, Oak Ridge
National Laboratory, Oak Ridge, TN
Dr. Rudolf Husar, Professor and Director, Mechanical Engineering, Engineering and Applied Science,
Center for Air Pollution Impact and Trend Analysis, Washington University, St. Louis, MO
Dr. Dale Johnson, Professor, Department of Environmental and Resource Sciences, College of
Agriculture, University of Nevada, Reno, NV
Dr. Naresh Kumar, Senior Program Manager, Environment Division, Electric Power Research Institute,
Palo Alto, CA
Dr. Myron Mitchell, Distinguished Professor and Director of Council on Hydrologic Systems Science,
College of Environmental and Forestry, State University of New York, Syracuse, NY
Mr. Richard L. Poirot, Environmental Analyst, Air Pollution Control Division, Department of
Environmental Conservation, Vermont Agency of Natural Resources, Waterbury, VT
Mr. David J. Shaw, Director, Division of Air Resources, New York State Department of Environmental
Conservation, Albany, NY
Dr. Kathleen Weathers, Senior Scientist, Institute of Ecosystem Studies, Millbrook, NY
August 2008 xxx DRAFT-DO NOT QUOTE OR CITE
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Project Team
Oxides of Nitrogen and Sulfur
Executive Direction
Dr. Ila Cote (Acting Director)—National Center for Environmental Assessment-RTF Division,
(B243-01), U.S. Environmental Protection Agency, Research Triangle Park, NC 27711
Ms. Debra Walsh (Deputy Division Director)— National Center for Environmental Assessment-RTP
Division, (B243-01), U.S. Environmental Protection Agency, Research Triangle Park, NC 27711
Dr. Mary Ross (Branch Chief)—National Center for Environmental Assessment (B243-01), U.S.
Environmental Protection Agency, Research Triangle Park, NC 27711
Scientific Staff
Dr. Tara Greaver (NOX and SOX Project Manager)—National Center for Environmental Assessment
(B243-01), U.S. Environmental Protection Agency, Research Triangle Park, NC 27711
Dr. Jeffrey R. Arnold—National Center for Environmental Assessment (B243-01), U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711
Dr. Jean-Jacques Dubois—Oak Ridge Institute for Science and Education, Postdoctoral Research Fellow
to National Center for Environmental Assessment (B243-01), U.S. Environmental Protection Agency,
Research Triangle Park, NC 27711
Dr. Jeffrey Herrick—National Center for Environmental Assessment (B243-01), U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711
Dr. Lingli Liu— Oak Ridge Institute for Science and Education, Postdoctoral Research Fellow to
National Center for National Center for Environmental Assessment (B243-01), U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711
Dr. Kristopher Novak—National Center for Environmental Assessment (B243-01), U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711
Dr. Paul F. Wagner—National Center for Environmental Assessment (B243-01), U.S. Environmental
Protection Agency, Research Triangle Park, NC 27711
Technical Support Staff
Ms. Ellen Lorang—Information Manager, National Center for Environmental Assessment (B243-01),
U.S. Environmental Protection Agency, Research Triangle Park, NC 27711
Ms. Connie Meacham—Science Assessment Coordinator, National Center for Environmental Assessment
(B243-01), U.S. Environmental Protection Agency, Research Triangle Park, NC 27711
Ms. Deborah Wales—Information Specialist, National Center for Environmental Assessment (B243-01),
U.S. Environmental Protection Agency, Research Triangle Park, NC 27711
August 2008 xxxi DRAFT-DO NOT QUOTE OR CITE
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EXECUTIVE SUMMARY
Introduction
This draft Integrated Science Assessment (ISA)
is a concise synthesis and evaluation of the
most policy-relevant science to help form the
scientific foundation for the review of the
secondary (welfare-based) national ambient air
quality standards (NAAQS) for oxides of
nitrogen (NOX) and sulfur oxides (SOX). The
Clean Air Act 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. The current secondary
NAAQS for SOX, set in 1973, is a 3-hour
average of 0.5 ppm sulfur dioxide (SO2), not to
be exceeded more than once per year. The
secondary NAAQS for NOX is identical to the
primary standard set in 1971: an annual average
of 0.053 ppm nitrogen dioxide (NO2), not to be
exceeded. The current secondary NAAQS were
set to protect against direct damage to
vegetation by exposure to gas-phase NOX or
SOX.
Scope
This draft ISA is focused on ecological effects
resulting from deposition of N- and S-containing
compounds at current levels. Both N and S
contribute to acidifying deposition and
subsequent effects on ecosystems. Deposition
of Nitrogen contributes to N-nutrient enrichment
and eutrophication. An assessment of the
complex ecological effects of atmospheric N
deposition requires consideration of many
different chemical forms of Nr; for this reason,
the ISA includes evaluation of data on the most
common reduced inorganic forms of N,
ammonia (NH3) and ammonium (NH4+); on
oxidized inorganic forms including NO and NO2,
nitrate (NO3), HNO3, and nitrous oxide (N2O),
and organic N compounds including PAN
Other welfare effects addressed in the ISA
include S-deposition effects on mercury
methylation, along with recent evidence related
to direct exposure to gas-phase NOX and SOX.
The key conclusions of the draft ISA follow.
Current concentrations and deposition in the
US
Ambient annual NOX and SOx concentrations
have decreased significantly. NOx decreased
-35% in the period 1990-2005, to current
annual average concentrations of ~15 ppb.
Emissions of SOX have been significantly
reduced in recent years: ambient annual SOX
concentrations have decreased ~50% in the
period 1990-2005 and now stand at ~ 4 ppb for
both aggregate annual and 24 h average
concentrations nation-wide.
Deposition is spatially heterogeneous across the
U.S. In the years 2004-2006, mean S
deposition in the United States was greatest
east of the Mississippi River with the highest
reported deposition, 21 kg/ha/yr, in the Ohio
River valley where most recording stations
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reported three-year averages for this period of
more than 10 kg/ha'yr. Numerous other stations
in the eastern United States reported S
deposition greater than 5 kg/ha/yr. Data are
sparse for the central United States between the
100th meridian and the Mississippi River; but,
where available, deposition values there were
lower than in most of the eastern United States,
ranging from 4 to over 5 kg/ha/yr. Total S
deposition in the United States west of the 100th
meridian is lower than in the East or upper Mid-
west, owing to lower densities of high-emitting
sources there. In the years 2004—2006, all
recording stations in the West reported less than
2 kg/ha/yr and many reported less than 1
kg/ha/yr. S was primarily deposited in the form
of wet sulfate (SO42~), followed by a smaller
proportion of dry SO2, and a much smaller
proportion of dry SO42".
Expanding urbanization, agricultural intensity,
and industrial production during the previous
100 years have produced a nearly 10-fold
increase in N deposited from the atmosphere.
NOX, chiefly from fossil fuel combustion, often
dominates total N pollution in the United States
and comprises ~50 to 75% of total N
atmospheric deposition. This wet and dry
atmospheric N deposition is spatially
heterogeneous owing to precipitation patterns
and land use.
For 2004-2006, routine national monitoring
networks reported the highest mean N
deposition totals in the Ohio River valley,
specifically in the states of Indiana and Ohio,
with values greater than 9 kg/ha/yr. N deposition
was lower in other parts of the East, including
the Southeast and in northern New England. In
the central United States the highest N
deposition totals were on the order of 6 to 7
kg/ha/yr. Measured concentrations and inferred
deposition totals were dominated by wet NO3"
and NH4+ species, followed by dry HNO3, dry
NH4+, and dry NO3". Significantly, NH3 is not yet
measured routinely in any national networks;
however, smaller-scale intensive monitoring and
numerical modeling both indicate that it may
account for more than 80% of the dry reduced N
deposition total. Although deposition in most
areas of the United States occurred as wet
deposition, there were some exceptions,
including parts of California where N deposition
was primarily dry.
The thin coverage of monitoring sites in many
areas, especially in the rural West, means that
no data exist on deposition totals in a significant
number of potentially sensitive places.
Numerical modeling experiments can help fill-in
these data gaps and suggest that local and even
regional areas of high concentration and
deposition exist where no data exist. Model-
predicted values for N deposition in some
regions of the Adirondacks in New York are
greater than 20 kg/ha/yr; other model estimates
as high as 32 kg/ha/yr have been made for a
region of southern California, with more than half
of that total predicted to come from NO and
NO2. Because adverse biological outcomes
have been measured in these areas of model-
predicted locally high N deposition, the ISA
concludes that the national-scale networks
routinely monitoring N deposition are inadequate
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to characterize either the full range of reduced
and oxidized forms of N deposition or the
significant regional heterogeneity across the
landscape of the U.S.
Ecological effects of acidification
The available evidence is sufficient to infer a
causal relationship between acidifying
deposition at current levels and effects on the
following aspects of ecosystem structure and
function:
(1) biogeochemistry related to terrestrial and
aquatic ecosystems;
(2) biota in terrestrial and aquatic ecosystems.
Both N and S can acidify ecosystems. Sensitivity
of terrestrial and aquatic ecosystems to
acidification from S and N deposition is
predominantly governed by surficial geology.
Other factors contributing to the sensitivity of
soils and surface waters to acidifying deposition
include topography, vegetation, soil chemistry,
land use, and hydrologicflowpath. Soil
acidification is a natural process, but is often
accelerated by acidifying deposition, which can
decrease concentrations of exchangeable base
cations in soils. Biological effects of acidification
on terrestrial ecosystems are generally
attributable to aluminum toxicity and decreased
ability of plant roots to take up base cations.
Forests in the Adirondack Mountains of New
York, Green Mountains of Vermont, White
Mountains of New Hampshire, the Allegheny
Plateau of Pennsylvania, and high-elevation
forest ecosystems in the southern Appalachians
are among the areas most sensitive to terrestrial
acidification effects from acidifying deposition.
In aquatic systems, consistent and coherent
evidence from multiple studies of many species
shows that acidification can cause the loss of
acid-sensitive species, and that more species
are lost with greater acidification. These effects
are linked to changes in surface water chemistry,
including concentrations of SO42", NO3",
inorganic Al, and Ca, surface water pH, sum of
base cations, acid neutralizing capacity (ANC),
and base cation surplus. Decreases in ANC and
pH and increases in inorganic Al concentration
contribute to declines in zooplankton,
macroinvertebrates, and fish species richness.
Although both N and S deposition can cause
terrestrial and aquatic acidification, S deposition
is the primary cause of chronic acidification.
Following decreases in S deposition in the
1980's and 1990's, one quarter to one third of
the chronically acidic lakes and streams in the
U.S. were no longer acidic in the year 2000. A
number of lakes and streams, however, remain
acidic even though wet SO42" deposition has
fallen by 19 to more than 30 % since 1989. N
deposition, which has also fallen in the years
since 1990 in most places in the U.S. with
routine monitoring, is the primary cause of
episodic acidification which, despite its short
duration, has been shown to cause long-term
biological effects.
Many surface waters most sensitive to
acidification in the U.S. are found in the
Northeast and mountainous West. In the West,
acidic surface waters are rare and the extent of
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chronic surface water acidification that has
occurred to date has been limited. However,
episodic acidification does occur. In both the
mountainous West and the Northeast, the most
severe acidification of surface waters generally
occurs during spring snowmelt. The ISA
highlights evidence from two well-studied areas
to provide more detail on how acidification
affects ecosystems: The Adirondacks (NY) and
Shenandoah National Park (VA). In the
Adirondacks, the current rates of N and S
deposition exceed the amount that would allow
recovery of the most acid sensitive lakes. In the
Shenandoah, past SO42" has accumulated in the
soil and is slowly released from the soil into
stream water where it causes acidification and
makes parts of this region sensitive to current
loading. Numeric models specifically calibrated
to these locations and conditions suggest that
the number of acidic streams will increase under
the current deposition rates.
Ecological effects of N deposition
The available evidence is sufficient to infer a
causal relationship between N deposition at
current levels and the alteration of the following
aspects of ecosystem structure and function:
(1) biogeochemical cycling of N and C in
terrestrial, wetland, freshwater aquatic, and
coastal marine ecosystems;
(2) biogenic flux of methane (CH4), and N2O in
terrestrial and wetland ecosystems;
(3) species richness, species composition, and
biodiversity in terrestrial, wetland, freshwater
aquatic and coastal marine ecosystems
The contribution of N deposition to total N load
varies among ecosystems. Atmospheric N
deposition is the main source of new N to most
terrestrial ecosystems, high elevation lakes and
low-order streams. Atmospheric N deposition
contributes to the total N load of some wetland
and aquatic ecosystems that receive N through
multiple pathways (i.e. agricultural land runoff
and waste water effluent).
In terrestrial ecosystems, there are multiple
chemical indicators of N deposition effects on
biogeochemical cycling. NO3" leaching is one of
the best documented and indicates that an
ecosystem is receiving more N that it uses; the
onset of leaching is calculated to be between 5.6
and 10 kg N/ha/yrfor Eastern forests.
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N deposition often increases primary
productivity. This does not necessarily increase
C sequestration. C budgets are complicated by
numerous factors that influence carbon
exchange (e.g. climate). However alteration of
primary productivity can alter competitive
interactions among plant species. The increase
in growth is greater for some species than
others, leading to shifts in population dynamics,
species composition, community structure and,
in extreme instances, ecosystem type.
Lichen are the most sensitive terrestrial taxa to
N deposition, with documented adverse effects
occurring at 3 kg N/ha/yr (Pacific NWand S.
California), 5 kg N/ha/yr correlates to the onset
of declining biodiversity within grasslands
(Minnesota and the E.U.), and at 10 kg N/ha/yr
causes community composition of Alpine
ecosystems and forest encroachment into
temperate grasslands.
N deposition alters the biogenic sources and
sinks of CH4 and N2O in terrestrial and wetland
ecosystems resulting in more GHG flux to the
atmosphere. Non-flooded upland soil uptakes
about 6% of atmospheric CH4 and is the largest
biological sink. N addition significantly reduced
CH4 uptake in coniferous and deciduous forests,
with a reduction of 28% and 45%, respectively.
In wetlands, N addition increases CH4
production, but has no significant effect on CH4
uptake. Terrestrial soil is the largest source of
N2O, accounting for 60% of global emissions. Nr
deposition increases the biogenic emission of
N2O in coniferous forest, deciduous forests,
grasslands and wetlands.
In aquatic ecosystems, N deposition alters
primary productivity, leading to changes in
community composition and eutrophication. In
the western U.S., deposition loads of
approximately 1.5-2 kg N/ha/yr are reported to
alter species composition in the diatom
communities in some freshwater lakes, an
indicator of impaired water quality.
In estuarine ecosystems, additional N from
atmospheric and non-atmospheric sources
contributes to increased phytoplankton and algal
productivity leading to eutrophication. Estuary
eutrophication is an ecological problem indicated
by water quality deterioration, resulting in
numerous adverse effects including hypoxic
zones, species mortality, and harmful algal
blooms. The contribution of atmospheric
deposition to total N loads can be greater than
72% in estuaries. The Chesapeake Bay is an
example of a large, well-studied and severely
eutrophic estuary that receives 21-30% of its
total N load from the atmosphere.
Other welfare effects
The available evidence is sufficient to infer a
causal relationship between S deposition at
current levels and increased Hg methylation in
aquatic environments; this effect occurs only
where other factors are present at levels within a
range to allow methylation.
Hg is a highly neurotoxic contaminant, which is
primarily taken up by organisms in the
methylated form. Methyl-mercury (MeHg) is then
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concentrated in higher trophic levels, including
fish eaten by humans. The production of
meaningful amounts of MeHg requires the
presence of SO42" and Hg, but the amount of
MeHg produced varies with oxygen content,
temperature, pH, and supply of labile organic
carbon. Watersheds with conditions known to be
conducive to Hg methylation can be found in the
northeastern United States and southeastern
Canada, but studies in other regions with
significant Hg accumulation in biota have not
been as extensive.
The available evidence is sufficient to infer a
causal relationship between exposure to SO2,
NO, NO2, PAN, and HNO3 and injury to
vegetation.
deposition resulting from NOX and SOX
pollution. It causes a cascade of effects that
harm terrestrial and aquatic ecosystems,
including slower growth and injury to forests,
and localized extinction of fishes and other
aquatic species. In addition to acidification,
deposition resulting from NOx, along with other
sources of reactive nitrogen (e.g., fertilizers,
wastewater, and atmospheric ammonia
deposition), causes a suite of ecological
problems including biodiversity losses, disease,
eutrophication, and harmful algal blooms.
Particulate sulfate can interact with
methanogenic bacteria to produce
methylmercury, a powerful toxin that can
bioaccumulate to toxic amounts in higher trophic
levels (e.g. otters, and kingfishers).
Acute and chronic exposures to SO2 have
phytotoxic effects on vegetation which include
foliar injury, decreased photosynthesis, and
decreased growth. Exposures to NO2, nitric
oxide (NO), peroxyacetyl nitrate (PAN), and
nitric acid (HNO3) cause similar forms of plant
foliar injury and decreased growth. In addition,
current atmospheric concentrations of these
gas-phase nitrogen (N) oxides may contribute to
N saturation in some areas of the U.S. Overall,
little new evidence exists for phytotoxic effects
from direct exposures of vegetation to gas-
phase sulfur (S) or N oxides at current
concentrations in the US.
Conclusion
The three main effects presented in the ISA are
acidification, nitrogen enrichment and mercury
methylation. Acidification is driven by the
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Chapter 1. Introduction
1 This draft Integrated Science Assessment (ISA) is a concise synthesis and evaluation of the most
2 policy-relevant science used to help form the scientific foundation for review of the secondary (welfare-
3 based) National Ambient Air Quality Standards (NAAQS) for oxides of nitrogen (NOx) and sulfur oxides
4 (SOx). The Clean Air Act definition of welfare effects includes, but is not limited to, effects on soils,
5 water, wildlife, vegetation, visibility, weather, and climate, as well as effects on materials, economic
6 values, and personal comfort and well-being.
7 The intent of the ISA, according to the Clean Air Act, is to "accurately reflect the latest scientific
8 knowledge expected from the presence of [a] pollutant in ambient air" (U.S. Code\, 2003). It includes
9 scientific research from atmospheric sciences, exposure and deposition, biogeochemistry, hydrology, soil
10 science, marine science, plant physiology, animal physiology, and ecology conducted at multiple scales
11 (e.g., population, community, ecosystem, landscape levels). Key information and judgments formerly
12 found in the Air Quality Criteria Documents (AQCDs) for NOX and SOX are included; Annexes provide a
13 more detailed discussion of the most pertinent scientific literature. Together, the ISA and Annexes serve to
14 update and revise the last NOX and SOX AQCDs which were published in 1993 and 1982, respectively.
15 As discussed in the Draft Integrated Plan for the Review of the Secondary NAAQS for Nitrogen
16 Dioxide (NO2) and Sulfur Dioxide (SO2) (EPA, 2007), a series of policy-relevant questions frames this
17 review of the scientific evidence used to provide a scientific basis for evaluation of the secondary
18 NAAQS for NC>2 (0.053 parts per million [ppm], annual average) and SC>2 (0.5 ppm, 3-h average). The
19 framing questions considered are:
20 1. What are the known or anticipated welfare effects influenced by ambient NOX and SOX? For
21 which effects is there sufficient information available to be useful as a basis for considering
22 distinct secondary standards?
23 2. What is the nature and magnitude of ecosystem responses to NOX and SOX that are
24 understood to have known or anticipated adverse effects? What is the variability associated
25 with these responses, (including ecosystem type, climatic conditions, environmental effects,
26 and interactions with other environmental factors and pollutants)?
27 3. To what extent do the current standards provide the requisite protection for the public welfare
28 effects associated with NOx and SOx?
29 4. Which biotic species are most vulnerable to the adverse effects of NOX and SOX air
30 pollution? How is adversity defined?
31 5. What ecosystems are most sensitive to NOX and SOX pollution?
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1 6. How does NOX and SOX pollution impact ecosystem services?
2 7. What are the most appropriate spatial and temporal scales to evaluate impacts on ecosystems?
3 8. What is the relationship between ecological vulnerability to NOX and SOX pollution and
4 variations in current meteorology or gradients in climate?
1.1. Scope
5 NOX and SOX are being considered jointly due to the joint role they play in acidification and their
6 effects on ecosystems. The scope of this document includes:
7 1. Effects related to the deposition of nitrogen (N)- and sulfur (S)-containing compounds.
8 Ecological effects from acidification and N-nutrient enrichment and eutrophication are the
9 two types of effects studied most extensively in the ecological literature. An assessment of the
10 complex ecological effects of N deposition requires consideration of multiple forms of N;
11 thus, this assessment includes evaluation of data on inorganic reduced forms of N (e.g.,
12 ammonia (NH3) and ammonium ion [NH4+]), inorganic oxidized forms (e.g., NOX, nitric acid
13 [HNOs], nitrous oxide [TS^O], nitrate (NOs), and organic N compounds (e.g., urea, amines,
14 proteins, nucleic acids). In addition to acidification and N-nutrient enrichment, other welfare
15 effects related to deposition of N- and S-containing compounds are discussed, such as SOX
16 interactions with mercury (Hg) methylation.
17 2. Evidence related to direct ecological effects of gas-phase NOX and SOX. The direct effects of
18 gas-phase SOX on vegetation formed a primary basis for the initial establishment of the
19 secondary NAAQS for SO2. The contribution of gas-phase NOX as greenhouse gas (GHG),
20 particularly N2O, is considered, chiefly in the response of soils to reactive nitrogen (Nr)
21 enrichment.
22 NOX and SOX alter numerous linked biogeochemical cycles. A simplified diagram of the combined
23 NOX and SOX cycle is presented in Figure 1-1. Figures with these elements presented in more detail are
24 found throughout the ISA. These figures include atmospheric cycling, interactions between the N cycle
25 and carbon (C), the N cycle and phosphorous (P), and the S cycle and Hg.
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Ambient Air
Concentration
Dissolution
2H*+S04*-
H*+N03-
Wet Deposition
H*, NH4+, NO3-, SO42
Atmosheric cycle
Dry deposition
NO,,, NHX, SOX NO,
NOK
/
Foliar and
nutrient effects
C and N cycle in
teneslnal ecosysiem
See Figure 3-35
,/xrv^^m
I I I I I I Ml
of water + Eutrophication ^.
V %
Hg cycle in
aquatic ecosysiem
See figure 3-57
C, N and P cycle in
aqualic ecosystem
See figure 3-39
Figure 1-1. Biogeochemical cycles of NOx and SOx
1 Recent data on direct welfare effects of particulate-phase NOX and SOX in the ambient air —
2 primarily visibility impairment and positive and negative climate interactions — will be evaluated in the
3 participate matter (PM) NAAQS review, currently underway. (For more information, see
4 http://www.epa. gov/ttn/naaqs/standards/pm/s_pm_index.html .)
1.2. History of the NOx Review
5 In 1971, EPA promulgated identical primary and secondary NAAQS for NO2: 0.053 ppm as an
6 annual average (36 FR 8186). The scientific and technical bases for these NAAQS are provided in the
7 AQCD for NOX (EPA, 1971).
8 In 1984, EPA proposed to retain these standards (49 FR 6866), and after the public commentary
9 period, finalized that decision in 1985 (50 FR 25532); the scientific bases for this review was provided by
10 the 1982 AQCD forNOx (EPA, 1982).
11 In 1991, EPA released an updated draft AQCD for the Clean Air Scientific Advisory Committee
12 (CASAC) and public review and comment (56 FR 59285). CASAC reviewed the document and
13 concluded it "provides a scientifically balanced and defensible summary of current knowledge of the
14 effects of this pollutant and provides an adequate basis for EPA to make a decision as to the appropriate
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1 NAAQS for NO2" (Wolff, 1993). The EPA also prepared a draft Staff Paper that summarized and
2 integrated the key studies and scientific evidence contained in the revised AQCD and identified the
3 critical elements to be considered in the review of the NO2 NAAQS. In September 1995, EPA finalized
4 the Staff Paper, Review of the National Ambient Air Quality Standards for Nitrogen Dioxide: Assessment
5 of Scientific and Technical Information, (EPA, 1995). The Administrator made a final determination that
6 revisions to the primary and secondary NAAQS for NO2 were appropriate at that time (61 FR 52852,
7 October 8, 1996). The level for both the existing primary and secondary NAAQS for NO2 remains
8 0.053 ppm (equivalent to 100 micrograms per cubic meter of air [fig/m3]) in annual arithmetic average,
9 calculated as the arithmetic mean of the 1-h NO2 concentrations.
1.3. History of the SOx Review
10 Based on the 1970 SOX AQCD (U.S. Department of Health, 1970), EPA promulgated primary and
11 secondary NAAQS for SO2, under section 109 of the Clean Air Act on April 30, 1971 (36 FR 8186). The
12 secondary standard had been set at 0.02 ppm in an annual arithmetic mean and a 3-h average of 0.5 ppm,
13 not to be exceeded more than once per year. These standards were established solely on the basis of
14 vegetation effects evidence. In 1973, revisions made to Chapter 5 "Effects of Sulfur Oxide in the
15 Atmosphere on Vegetation" of the SOX AQCD (EPA, 1973), indicated that it could not properly be
16 concluded that the reported vegetation injury resulted from the average SO2 exposure over the growing
17 season, rather than from short-term peak concentrations. EPA, therefore, proposed (38 FR 11355) and
18 then finalized a revocation of the annual mean secondary standard (38 FR 25678).
19 In 1979, EPA announced that it was revising the SOx AQCD concurrently with the PM review, and
20 would produce a combined PM-SOx AQCD. Following its review of a draft revised criteria document in
21 August 1980, CASAC concluded that acidic deposition was a topic of extreme scientific complexity
22 because of the difficulty in establishing firm quantitative relationships among (a) emissions of relevant
23 pollutants (e.g., SO2 and NOX), (b) formation of acidic wet and dry deposition products, and (c) effects on
24 terrestrial and aquatic ecosystems. CASAC also noted that acidic deposition involves, at a minimum,
25 several different criteria pollutants (i.e., SOX, NOX, and the fine particulate fraction of suspended
26 particles). The Committee felt that any document on this subject should address both wet and dry
27 deposition, since dry deposition was believed to account for at least half of the total acid deposition
28 problem.
29 For these reasons, CASAC recommended that a separate, comprehensive document on acidic
30 deposition be prepared prior to any regulatory consideration for the control of acidic deposition. CASAC
31 also suggested that a discussion of acidic deposition be included in the AQCDs for both NOX and PM-
32 SOx- Following CASAC closure on the criteria document for SO2 in 1981, EPA's Office of Air Quality
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1 Planning and Standards (OAQPS) published a Staff Paper (EPA, 1982); it did not, however directly
2 address this issue. EPA followed CASAC guidance and subsequently prepared the following documents:
3 The Acidic Deposition Phenomenon and Its Effects: Critical Assessment Review Papers, Volumes I and II
4 (EPA, 1984; EPA, 1984), and The Acidic Deposition Phenomenon and Its Effects: Critical Assessment
5 Document (EPA, 1984). These documents, though they were not considered criteria documents and did
6 not undergo CASAC review, represented the most comprehensive summary of relevant scientific
7 information completed by the EPA up until that point.
8 On April 26, 1988 (53 FR 14926), EPA proposed not to revise the existing primary and secondary
9 standards. Regarding the secondary SO2 NAAQS, the EPA Administrator concluded that (1) based upon
10 then-current scientific understanding of the acidic deposition problem, it would be premature and unwise
11 to prescribe any regulatory control program at that time, and (2) when the fundamental scientific
12 uncertainties had been reduced through ongoing research efforts, EPA would draft and support an
13 appropriate set of control measures. On May 22, 1996, EPA's final decision, that revisions of the NAAQS
14 for SOxwere not appropriate at that time, was announced in the Federal Register (61 FR 25566).
1.4. History of the Current Review
15 EPA's National Center for Environmental Assessment in Research Triangle Park, NC announced
16 the official initiation of the current periodic review of air quality criteria for NOX on December 9, 2005
17 (70 FR 73236), and for SOX on May 15, 2006 (71 FR 28023) with a call for information. A workshop
18 addressing the separate, joint review of the secondary standards for these two pollutants was announced in
19 the Federal Register on June 20, 2007 (72 FR 11960). The review of the secondary NAAQS for NO2 and
20 SO2 is under a court-ordered schedule; it includes a deadline for completion of the final ISA of December
21 12, 2008. The first external review draft of the ISA was published in December, 2007 (72 FR 72719) and
22 reviewed by CASAC at a public meeting on April 2-3, 2008. Comments received have been addressed in
23 this second external review draft.
1.5. Development of the ISA
24 Publications were identified through an extensive literature search process; additional publications
25 were identified by EPA scientists in a variety of disciplines. In addition to peer-reviewed literature,
26 previous EPA reports and materials obtained from scouring reference lists were examined. The focus of
27 this ISA is on literature published since the 1993 NOX AQCD and the 1982 SOX AQCD. Key findings
28 and conclusions from the 1993 and 1982 reviews are discussed in conjunction with recent studies. In
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1 addition, analyses of air quality and emissions data, and studies on atmospheric chemistry, transport, and
2 fate of these emissions were scrutinized. Further information was acquired from consultation with content
3 and area experts, CAS AC and the public.
4 Emphasis has been placed on studies that evaluate effects near ambient levels and studies that
5 consider NOx and SOx as components of a complex mixture of air pollutants. Studies conducted in any
6 country that contribute significantly to the knowledge base have been considered for inclusion, but
7 emphasis has been placed on findings from studies conducted in the U.S. and Canada where differences in
8 emissions and the air pollutant mixture are important. In assessing the relative scientific quality of studies
9 reviewed here and to assist in interpreting their findings, the following considerations were taken into
10 account:
11 1. To what extent are the aerometric data/exposure metrics of adequate quality and sufficiently
12 representative to serve as credible exposure indicators?
13 2. Were the study populations well defined and adequately selected so as to allow for
14 meaningful comparisons between study groups?
15 3. Were the ecological assessment endpoints reliable and policy relevant?
16 4. Were the statistical analyses used appropriate and properly performed and interpreted?
17 5. Were likely important covariates (e.g., potential confounders or effect modifiers) adequately
18 controlled or taken into account in the study design and statistical analyses?
19 6. Were the reported findings consistent, biologically plausible, and coherent in terms of
20 consistency with other known facts?
21 These guidelines provide benchmarks for evaluating various studies and for focusing on the highest
22 quality studies in assessing the body of environmental effects evidence. Detailed critical analysis of all
23 NOX and SOX environmental effects studies, especially in relation to the above considerations, is beyond
24 the scope of the ISA and its Annexes. Of most relevance for evaluation of studies is whether they provide
25 useful qualitative or quantitative information on exposure effect or exposure response relationships for the
26 environmental effects associated with current ambient air concentrations of NOx and SOx or deposition
27 levels likely to be encountered in the U.S.
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1.6. Causality Framework
1 EPA uses a two-step approach to evaluate the scientific evidence on welfare effects of criteria
2 pollutants, similar to the approach it uses for health effects. The steps address two general policy-relevant
3 questions:
4 1. Given the total body of evidence, what, if any, are the welfare effects of NOx and SOx?
5 2. Can levels of exposure at which welfare effects of concern occur be defined?
6 The first step determines the weight of evidence in support of causation, and characterizes the
7 strength of any resulting causal classification. The second step includes further evaluation of the
8 quantitative evidence with respect to concentration-response relationships and the levels, duration, and
9 pattern of exposures at which effects are observed.
10 The most widely cited aspects of causality in public health were articulated by Sir Austin Bradford
11 Hill (1965), and have been widely used (IARC, 2006; Samet, 2008). Several adaptations of the Hill
12 aspects have been used in aiding causality judgments in the ecological sciences (Adams, 2003; Buck,
13 2000; Collier, 2003; Fox, 1991; Gerritsen, 1998). Based on these adaptations, EPA uses eight aspects in
14 judging causality (see Table 1-1). The broad national scale of this assessment differs from the site-specific
15 scale of ecological assessment for which applications of the Hill aspects have been published. The
16 following were developed to meet the scope of this ISA:
Table 1 -1. Aspects to aid in judging causality.
CONSISTENCY of the observed association. The inference of causality is strengthened when the same
association between agent and effect is observed across similar, independent studies. The reproducibility of
findings constitutes one of the strongest arguments for causality. If there are discordant results among
comparable investigations, possible reasons such as differences in exposure, confounding factors, and the
power of the study are considered.
STRENGTH of the observed association. The finding of large, well demarcated effects increases confidence
that the association is causal. However, given a truly causal agent, a small magnitude in the effect could
follow from a lower level of exposure, a lower potency, or the prevalence of other agents causing similar
effects. While large effects support causality, modest effects therefore do not preclude it.
SPECIFICITY of the observed association. The effect is only observed after exposure to that agent, and the
agent produces only that effect. Hill (1965), and subsequent authors, consider specificity a weak aspect. At
the scale of ecosystems, as in epidemiology, complexity is such that single agents causing single effects,
and single effects following single causes, are extremely unlikely. The absence of specificity cannot be used
to exclude causality, especially at those scales. However, if specificity can be demonstrated, as in some
laboratory or other experimental studies, it does add strong support to causality.
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TEMPORALITY of the observed association. Evidence of a temporal sequence between the introduction of an
agent, and appearance of the effect, constitutes another argument in favor of causality.
GRADIENT. A clear exposure-response relationship (e.g., increasing effects associated with greater exposure)
strongly suggests cause and effect.
PLAUSIBILITY. A credible ecological basis for the observed association adds strength to an inference of causality.
A proposed mechanistic linking between an effect, and exposure to the agent, is an important source of
support for causality, especially when data establishing the existence and functioning of those mechanistic
links are available. A lack of biological understanding, however, is not sufficient reason to reject causality.
EXPERIMENTAL evidence. Controlled exposure to the stressors provides results that support the proposed
causal relationship. The practical limits on control, as the number of potential interacting factors increases,
are such that the most compelling experiments can only be conducted at the scale of a laboratory, growth
chamber, or at most, mesocosm. Therefore, since a judgment of causality derived from experimental
evidence often cannot be extended very far beyond the scale at which the experiment was conducted,
experimental evidence is generally only one element of the information that comes to bear in determining
causality at the ecosystem, regional, or greater scales.
COHERENCE. Given the scale and complexity of the environment and of ecosystems, determinations of causality
are usually based on many lines of evidence, considered jointly. Evidence may be drawn from a variety of
experimental approaches (e.g., greenhouse, laboratory, and field) and subdisciplines of ecology (e.g.,
community ecology, biogeochemistry and paleological/historical reconstructions). The coherence of the
available sources is a critical aspect of assessing the strength of a causal association. The coherence of
evidence from various fields, and at various scales, greatly adds to the strength of an inference of causality.
1
2 While these aspects provide a framework for assessing the evidence, they are not simple formulas
3 or fixed rules of evidence leading to conclusions about causality (Hill, 1965). The principles in Table 1-1
4 cannot be used as a strict checklist, but rather to determine the weight of the evidence for inferring
5 causality. In particular, the absence of one or more of the aspects does not automatically exclude a study
6 from consideration (e.g., see discussion in, Department of Health and Human Services, 2004). For
7 example, one cannot simply count the number of studies reporting statistically significant or non-
8 significant results, and reach credible conclusions about the relative weight of the evidence and the
9 likelihood of causality. Rather, the aspects are an important part of the assessment, whose goal is to
10 produce an objective appraisal of the evidence, and is informed by peer and public comment and advice,
11 including weighing of alternative views on controversial issues.
1.6.1. First Step: Determination of Causality
12 In this ISA, EPA assesses results of recent publications available since the previous NAAQS
13 review. This evaluation builds upon evidence available and conclusions drawn in the previous review in
14 order to draw conclusions on the causal relationships between relevant pollutant exposures and welfare
15 outcomes. A five-level hierarchy is used to classify the weight of evidence for causation, as assessed by
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1 the reviewing group with input from peers, CASAC, and the public. Through integration of the evidence
2 from all relevant lines, such as laboratory studies, ecosystem experiments, simulation models and regional
3 observations, the weight of evidence in support of causality is expressed using one of the five descriptors
4 (see Table 1-2).
Table 1-2. Descriptors for weight of evidence for use in causal determination.
SUFFICIENT TO INFER A CAUSAL RELATIONSHIP Evidence is sufficient to conclude that there is a causal
relationship between relevant pollutant exposure and the outcome. Causality is supported when an
association has been observed between the pollutant and the outcome in studies in which chance, bias, and
confounding could be ruled out with reasonable confidence. Controlled exposure (laboratory or small- to
medium-scale field studies) provides the strongest evidence for causality, but the scope of inference may be
limited. Generally, determination is based on multiple studies conducted by multiple research groups, and
evidence that is considered sufficient to infer a causal relationship is usually obtained from the joint
consideration of many lines of evidence that reinforce each other.
SUFFICIENT TO INFER A LIKELY CAUSAL RELATIONSHIP Evidence is sufficient to conclude that there is a
likely causal association between relevant pollutant exposures and the outcome. That is, an association has
been observed between the pollutant and the outcome in studies in which chance, bias and confounding are
minimized, but uncertainties remain. For example, field studies show a relationship, but suspected
interacting factors cannot be controlled, and other lines of evidence are limited or inconsistent. Generally,
determination is based on multiple studies in multiple research groups.
SUGGESTIVE, BUT NOT SUFFICIENT TO INFER A CAUSAL RELATIONSHIP Evidence is suggestive of
an association between relevant pollutant exposures and the outcome, but chance, bias and confounding
cannot be ruled out. For example, at least one high-quality study shows an association, but the results of
other studies are inconsistent.
INADEQUATE TO INFER THE PRESENCE OR ABSENCE OF A CAUSAL RELATIONSHIP The available
studies are of insufficient quality, consistency or statistical power to permit a conclusion regarding the
presence or absence of an association between relevant pollutant exposure and the outcome.
SUGGESTIVE OF NO CAUSAL RELATIONSHIP Several adequate studies, examining relationships between
relevant exposures and outcomes, are consistent in failing to show an association between exposure and
the outcome at any level of exposure.
1.6.2. Second Step: Evaluation of Ecological Response
5
6
7 include:
• V •
Beyond judgments regarding causality are questions re levant to characterizing exposure and risk to
ecosystems (e.g., the levels and loads of pollution at which ecological effects occur). Such questions
What elements of the ecosystem (e.g., types, regions, taxonomic groups, populations,
functions, etc.) appear to be affected, or are more susceptible to effects?
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1 2. Under what exposure conditions (amount or concentration, duration and pattern) are effects
2 seen?
3 3. What is the shape of the concentration-response or exposure-response relationship?
4 Causal and likely causal claims typically characterize how the probability of ecological effects
5 changes in response to exposure. The ecological scale at which those quantitative considerations are valid
6 is an overriding concern. Initially, responses are evaluated within the range of observation, but ecological
7 data for concentration-response analyses are often not available at the national or even regional scale.
8 They are therefore typically presented site by site. Where greenhouse or animal ecotoxicological studies
9 are available, they may be used to aid in characterizing concentration-response relations, particularly
10 relative to mechanisms of action, and characteristics of sensitive biota.
1.7. Organization of the ISA
11 This ISA includes four chapters. Chapter 1 provides background information on the purpose of the
12 document, explains how policy-relevant scientific studies are identified and selected for inclusion in the
13 ISA, and introduces the causality framework used in EPA's assessments. Chapter 2 presents fundamental
14 and applied atmospheric science data to support assessing the environmental exposures and effects
15 associated with N and S oxides. Information relevant to the review of the welfare effects of NOX and SOX
16 is integrated and evaluated in Chapter 3. Findings are organized into three categories: ecological effects of
17 acidification, ecological effects of N nutrient pollution, and other welfare effects, which address several
18 minor welfare effects, including gas phase foliar toxicity and the role of S in Hg methylation. Finally,
19 summary and conclusions are found in Chapter 4. The ISA is supplemented by Annexes, which provide
20 additional details.
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Chapter 2. Source to Dose
1 This chapter provides fundamental and applied atmospheric science data to support assessing the
2 environmental exposures and effects associated with N and S oxides. More specifically, these data relate
3 to N and S emissions sources and rates, atmospheric transformation and transport, total atmospheric
4 loadings, measurement and modeling techniques, and deposition issues relevant to this review of the
5 NAAQS. These data are prologue for the detailed descriptions of the evidence of environmental effects
6 from N and S oxides that follow in Chapter 3, and as a source of information to help interpret those
7 effects when integrated with these data on atmospheric concentrations and biological exposures.
2.1. Introduction
8 As noted in Chapter 1, the definition of "nitrogen oxides" appearing in the NAAQS enabling
9 legislation differs from the one used by atmospheric scientists and air quality control experts. The
10 atmospheric sciences community defines NOX as the sum of NO and NO2. However, in the Federal
11 Register Notice (FRN) for the most recently published (October 8, 1996) AQCD for NO2 (61 FR 52852,),
12 the term "nitrogen oxides" was used to "describe the sum of NO, NO2, and other oxides of nitrogen." This
13 ISA uses the legal, rather than the technical definition; hence the terms "oxides of nitrogen" and "nitrogen
14 oxides" here refer to all forms of oxidized N compounds, including NO, NO2, and all other oxidized
15 N-containing compounds transformed from NO and NO2.: Additionally, because some of the constituent
16 members of the NOX family of chemical species interact with particulate-phase chemical species and
17 change phase themselves, the chemistry, concentrations, and deposition of particulate N compounds are
18 also considered in this assessment.
19 SOx is defined here to include sulfur monoxide (SO), sulfur dioxide (SO2)—the largest component
20 of SOX and the EPA Criteria Air Pollutant—sulfur trioxide (SO3), and disulfur monoxide (S2O). Of these,
21 only SO2 is present in the lower troposphere at concentrations relevant for environmental considerations.
22 Moreover, some gas-phase sulfur oxides interact with particles and change phase themselves, just as do
23 some constituent members of the N family of gas-phase chemical species; hence, particulate-phase S
24 compounds are also assessed here.
25 NH3 is included in this ISA both because its oxidation can be a minor source of NOX and because it
26 is the precursor for ammonium ion (NH4+), which plays a key role in neutralizing acidity in ambient
1 This follows usage in the Clean Air Act, Section 108(c): "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 category label
used by the air pollution research and control community for the sum of all oxidized N compounds, including those listed in Section 108(c), is
NOY.
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1 particles produced from NO2 and SO2 and in cloud, fog, and rain water. (NH3 and NH4+ are
2 conventionally grouped together under the category label NHX.) Excess NH3 is also an actor in
3 nitrification of aqueous and terrestrial ecosystems, participating alone and together with NOX in the
4 N cascade (Galloway, 2003). Additionally, NH3 is involved in the ternary nucleation of new particles and
5 reacts with gas-phase HNO3 to form ammonium nitrate (NH4NO3), a major component of N deposition in
6 many areas of the contiguous U.S. (CONUS).
2.2. Sources and Emissions of Troposphere NOx
7 Troposphere NOx emissions sources can be anthropogenic, resulting from human activity, or
8 biogenic, resulting from the activity of non-human organisms, though sometimes with the addition of
9 human activities, as with production from livestock or agriculture. However, anthropogenic sources
10 contribute substantially more mass than biogenic ones. The anthropogenic and biogenic sources of NOX
11 are described in detail and their emissions totals are provided just below.
2.2.1. Major Anthropogenic Sources
12 Anthropogenic NOx emissions are dominated by fossil fuel combustion sources which release
13 NOx predominantly in the form of NO with variable amounts of NO2. In 2002, anthropogenic NOx
14 emissions in the U.S. totaled 23.19 Tg/year. Table 2-1 lists fractions and totals from anthropogenic NOx
15 sources collected for the 2002 National Emissions Inventory (NEI) (EPA, 2006).
Table 2-1. Emissions of NOx,
2002 Emissions (Tg/yr)
Total All Sources
Fuel Combustion Total
Fuel Combustion Electrical Utilities
Coal
Bituminous
Subbituminous
Anthracite & Lignite
Other
Oil
Residual
Distillate
Gas
Natural
Process
Other
Internal Combustion
Fuel Combustion Industrial
Coal
Bituminous
NH3, and
NOx1
23.19
9.11
5.16
4.50
2.90
1.42
0.18
<0.01
0.14
0.13
0.01
0.30
0.29
0.01
0.05
0.17
3.15
0.49
0.25
S02
NHs2
4.08
0.02
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
in the
S02
16.87
14.47
11.31
10.70
8.04
2.14
0.51
0.38
0.36
0.01
0.01
0.21
0.01
2.53
1.26
0.70
U.S. by source and category, 2002.
2002 Emissions (Tg/yr)
Subbituminous
Anthracite & Lignite
Other
Oil
Residual
Distillate
Other
Gas
Natural
Process
Other
Other
Wood/Bark Waste
Liquid Waste
Other
Internal Combustion
Fuel Combustion Other
Commercial/Institutional Coal
Commercial/Institutional Oil
Commercial/Institutional Gas
NOx1
0.07
n n/i
U.U4
0.13
0.19
0.09
0.09
0.01
1.16
0.92
0.24
<0.01
0.16
0.11
0.01
0.04
1.15
0.80
0.04
0.08
0.25
NHs2
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
SO2
0.10
fl -10
U. lo
0.33
0.59
0.40
0.16
0.02
0.52
0.15
0.01
0.63
0.16
0.28
0.02
August 2008 2-2 DRAFT-DO NOT QUOTE OR CITE
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2002 Emissions (Tg/yr)
Misc. Fuel Combustion (Exc. Residential)
Residential Wood
Residential Other
Distillate Oil
Bituminous/Subbituminous
Other
Industrial Process Total
Chemical & Allied Product Mfg
Organic Chemical Mfg
Inorganic Chemical Mfg
Sulfur Compounds
Other
Polymer & Resin Mfg
Agricultural Chemical Mfg
Ammonium Nitrate/Urea Mfg.
Other
Paint, Varnish, Lacquer, Enamel Mfg
Pharmaceutical Mfg
Other Chemical Mfg
Metals Processing
Non-Ferrous Metals Processing
Copper
Lead
Zinc
Other
Ferrous Metals Processing
Metals Processing
Petroleum & Related Industries
Oil & Gas Production
Natural Gas
Other
Petroleum Refineries & Related Industries
Fluid Catalytic Cracking Units
Other
Asphalt Manufacturing
Other Industrial Processes
Agriculture, Food, & Kindred Products
Textiles, Leather, & Apparel Products
Wood, Pulp & Paper, & Publishing Products
Rubber & Miscellaneous Plastic Products
Mineral Products
Cement Mfg
Glass Mfg
Other
Machinery Products
Electronic Equipment
Transportation Equipment
Miscellaneous Industrial Processes
Solvent Utilization
Degreasing
Graphic Arts
Dry Cleaning
Surface Coating
Other Industrial
Nonindustrial
Solvent Utilization Nee
Storage & Transport
Bulk Terminals & Plants
Petroleum & Petroleum Product Storage
Petroleum & Petroleum Product Transport
Service Stations: Stage II
Organic Chemical Storage
Organic Chemical Transport
Inorganic Chemical Storage
Inorganic Chemical Transport
Bulk Materials Storage
Waste Disposal & Recycling
Incineration
Industrial
Other
NOx1
0.03
0.03
0.36
0.06
0.26
0.04
1.10
0.12
0.02
0.01
<0.01
0.05
0.00
0.00
0.03
0.09
0.01
0.07
0.01
0.16
0.07
0.05
0.04
0.54
0.01
<0.01
0.09
<0.01
0.42
0.24
0.01
0.10
<0.01
<0.01
<0.01
0.01
0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
0.01
<0.01
<0.01
0.01
0.17
0.06
NHs2
<0.01
0.21
0.02
<0.01
<0.01
<0.01
0.02
<0.01
0.02
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
0.05
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
0.05
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
0.14
<0.01
SO2
0.01
<0.01
0.16
0.15
<0.01
<0.01
1.54
0.36
0.01
0.18
0.17
0.02
<0.01
0.05
0.00
0.00
0.12
0.30
0.17
0.04
0.07
0.01
<0.01
0.11
0.02
.38
0.11
0.11
0.01
0.26
0.16
0.07
0.01
0.46
0.01
<0.01
0.10
<0.01
0.33
0.19
0.09
<0.01
<0.01
<0.01
0.02
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
0.03
0.02
<0.01
2002 Emissions (Tg/yr)
Open Burning
Industrial
Land Clearing Debris
Other
Public Operating Treatment Works
Industrial Waste Water
Treatment, Storage, And Disposal Facility
Landfills
Industrial
Other
Other
Transportation Total
Highway Vehicles
Light-Duty Gas Vehicles & Motorcycles
Light-Duty Gas Vehicles
Motorcycles
Light-Duty Gas Trucks
Light-Duty Gas Trucks 1
Light-Duty Gas Trucks 2
Heavy-Duty Gas Vehicles
Diesels
Heavy-Duty Diesel Vehicles
Light-Duty Diesel Trucks
Light-Duty Diesel Vehicles
Off-Highway
Non-Road Gasoline
Recreational
Construction
Industrial
Lawn & Garden
Farm
Light Commercial
Logging
Airport Service
Railway Maintenance
Recreational Marine Vessels
Non-Road Diesel
Recreational
Construction
Industrial
Lawn & Garden
Farm
Light Commercial
Logging
Airport Service
Railway Maintenance
Recreational Marine Vessels
Aircraft
Marine Vessels
Diesel
Residual Oil
Other
Railroads
Other
Liquefied Petroleum Gas
Compressed Natural Gas
Miscellaneous
Agricultures Forestry
Agricultural Crops
Agricultural Livestock
Other Combustion
Health Services
Cooling Towers
Fugitive Dust
Other
Natural Sources
1 Emissions are expressed in terms of N02.
NOx1
0.10
<0.01
<0.01
<0.01
<0.01
<0.01
12.58
8.09
2.38
2.36
0.02
1.54
1.07
0.47
0.44
3.73
3.71
0.01
0.01
4.49
0.23
0.01
0.01
0.01
0.10
0.01
0.04
<0.01
<0.01
<0.01
0.05
1.76
0.00
0.84
0.15
0.05
0.57
0.08
0.02
0.01
<0.01
0.03
0.09
1.11
1.11
0.98
0.32
0.29
0.04
0.39
<0.01
3.10
NHs2
<0.01
0.14
<0.01
<0.01
<0.01
<0.01
0.32
0.32
0.20
0.10
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
3.53
3.45
<0.01
2.66
0.08
0.03
SO2
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
<0.01
0.76
0.30
0.10
0.10
0.00
0.07
0.05
0.02
0.01
0.12
0.46
0.01
0.22
0.01
0.18
0.05
0.00
0.10
<0.01
0.10
2 Natural emissions of non-methane volatile organic compounds, carbon monoxide,
and oxides
Source: (EPA, 2006)
August 2008
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1 Of this total, emissions from all types of transportation accounted for -56% of NOX, or 12.58 Tg,
2 with on-road highway vehicles representing the major mobile source component, 8.09 Tg. Roughly one-
3 half of these on-road emissions have diesel engine sources and one-half have gasoline engine sources.
4 (Sawyer et al. (2000) reviewed the in detail factors associated with NOx emissions by mobile sources.)
5 The next largest source category, electric-generating utilities (EGUs), accounted for -22%, or 5.16 Tg of
6 total NOx in 2002. Stationary engines, non-road vehicles, and industrial facilities also emit NOx, but
7 because they are fewer in number or burn less fuel, their mass contributions to total NOx are less than
8 transportation and EGUs.
9 The values in Table 2-1 are U.S. national averages; thus, they may not reflect differences in the
10 relative contributions of NOX sources to ambient mass loadings at any particular location; hence, these
11 values are not likely to be useful predictors of any particular localized exposures to NOX. As a partial
12 refinement of scale, county-level NOX emissions are depicted in Figure 2-1:. A further refinement appears
13 in Figure 2-2, where the same 2001 NOX emissions data are plotted as area-normalized intensities: tons
14 per square mile. This normalized emissions intensity base is also used to show the separate contributions
15 from EGUs and on-road mobile sources in Figure 2-3 and Figure 2-4, respectively.
2001 County Emissions (1000 Tons per Yeor) of Nitrogen Oxides
1.2-2.5
>D-0.5+
6-16
0.54-1.2
16+
Source: U.S. EPA (2006)
Figure 2-1.2001
county-level total
U.S. NO and N02
emissions.
1 The maps in Figures 2-1 through 2-9 and 2-13 through 2-15 all use this scale for their range values: white, 0 or no reported value; cyan, from the
smallest non-zero to the 10th percentile value; green, from above the 10th to the 25th percentile; gold, from above the 25th to the 50th percentile;
rose, from above the 50th to the 75th percentile; red, from above the 75th to the 90th percentile; brown, from above the 90th percentile to the
highest reported value.
August 2008
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2001 County Emissions Density (Tons per sq.mi.) of Nitrogen Oxides
Jfl >0-Q.79 0.79-1.8 1.6-4.1
4.1-10 ^H 10-30 ^B 30+
Source: U.S. EPA (2006)
Figure 2-2.2001
county-level total
U.S. NO and N02
emissions densities
(tons per square
mile).
2001 County Emissions Density (Tons per sq.mi.) of Nitrogen Oxides
0 >0-0.0022 0,0021-0.025 0.025-0.3
I O-J-5.4 • 5.4-25 • !5»
Source: U.S. EPA (2006)
Figure 2-3.2001
county-level total
U.S. NO and N02
emissions densities
(tons per square
mile) from EGUs.
August 2008
2-5
DRAFT-DO NOT QUOTE OR CITE
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2001 County Emissions Density (Tons per sq.mi.) of Nitrogen Oxides
0.65-1.7
0
1.7-4.1
>0-0.2
4.1-10
0.2-0.65
10+
Source: U.S. EPA (2006)
Figure 2-4.2001
county-level total
U.S. NO and N02
emissions densities
(tons per square
mile) from on-road
mobile sources.
1 Emissions of NOx from combustion are derived from both fuel N and atmospheric N. Combustion-
2 zone temperatures > -1300 K are required to fix atmospheric N2 by the reaction
N2 + O2
2NO
Reaction 1
3 Below this temperature NO can be formed from fuel N by the reaction
CaHhOcNd + O2 -» xCO2 + yH2O + zNO
Reaction 2
4 Both Reaction 1 and Reaction 2 have temperature dependencies and vary with concentrations of hydroxyl
5 radical (OH), hydroperoxy radical (HO2), and Q^
6 The N content in fossil fuels and its specific chemical form vary strongly with source type, fuel,
7 engine emissions controls, and running conditions. N content in fuel stocks ranges from 0.05% by weight
8 (wt %) in light distillates such as diesel fuel, to 1.5 wt % in heavy fuel oils, and from 0.5 to 2.0 wt % in
9 coal, as surveyed by the United Kingdom Air Quality Expert Group (2004).
10 On-road mobile source emissions constitute the largest type of emissions from all transportation
11 sources. Significant variability attaches to these emissions. For example, the ratio of NO2 to total NOX in
12 exhaust gases in primary emissions ranges from 1 to 3% from gasoline engines tested on dynamometers
August 2008
2-6
DRAFT-DO NOT QUOTE OR CITE
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1 (Heeb, 2008; Milliard, 1979). On the other hand, some European studies have reported NO2 to NOX ratios
2 > 15% from gasoline vehicles based on integrated measurements from Tedlar bags (Lenner, 1987; Soltic,
3 2003). However, subsequent studies suggesting that NO-to-NO2 conversion will occur within a bag
4 sample of diluted exhaust if not properly handled have led groups performing these measurement to
5 revise their measurement techniques to avoid use of Tedlar bag samples (Alvarez, 2008). As a result,
6 dynamometer-based measurements generally indicate that in the absence of post-tailpipe transformation,
7 NO2 comprises, at most, only a few percent of the total NOx in current-generation gasoline engine
8 exhaust.
9 The emissions ratio ranges between 5 and 12% from heavy-duty diesel truck engines, although
10 some emission control devices used for diesel engines in Europe increase the fraction of exhaust NOX
11 emitted as NO2 to > 20% (Carslaw, 2005; Carslaw, 2005; Carslaw, 2007; Kessler, 2006). In the U.S., on-
12 road experiments with diesel engines propelling heavy buses in congested urban areas like New York City
13 have shown that engines equipped with emissions control devices similar to those in the European studies
14 increased the NO2 to NOX ratio from -10% before addition of the new controls to -30% after controls
15 were added (Shorter, 2005). In a second type of experiment in a different setting, Kittelson et al.
16 (Kittelson, 2006) used an on-road laboratory to sample exhaust plumes of a truck equipped with the
17 European-style emissions control device under highway cruise conditions and found the NO2-to-NOx
18 ratios for this exhaust under highway cruise conditions ranged from 59 to 70%. The wide range revealed
19 by comparing these two studies illustrates the significant differences in NOx exhaust under different
20 conditions of engine load and ambient temperature.
21 As for other combustion sources, NO2-to-NOx emissions ratios for compressed natural gas engines
22 range between 5 and 10%, and between 5 and 10% from most stationary sources. The NO2-to-NOx ratios
23 in emissions from turbine jet engines are as high as 35% during taxi and takeoff (U.S. Environmental
24 Protection Agency, 1996).
25 In addition to NO and NO2, mobile sources emit other forms of oxidized N including nitrous acid
26 (HNO2); measured ratios of HNO2 to NOX range from a low of 0.3% in the Caldecott Tunnel, San
27 Francisco, CA (Kirchstetter, 1996), up to as much as 0.5 and 1.0% in studies in the United Kingdom
28 (U.K. Air Quality Expert Group, 2004).
29 Marine transport represents an additional source of NOX in the U.S., especially for coastal cities
30 with large ports, but constitutes a larger source in Europe where it is expected to represent more than 60%
31 of land-based NOX sources (U.K. Air Quality Expert Group, 2004).
32 The anthropogenic sources of NOX are distributed with height such that some, like on-road mobile
33 sources, are nearer to ground level than others, like the emissions stacks from EGUs and some industrial
34 emitters. Emissions height is an important consideration because the prevailing winds aloft are generally
35 stronger than those at the surface. The result is that emissions from elevated sources can be distributed
August 2008 2-7 DRAFT-DO NOT QUOTE OR CITE
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1 over a wider area than those emitted at the surface and hence can be diluted to lower mixing ratios than
2 those emitted nearer their sources.
2.2.2. Major Biogenic Sources
2.2.2.1. Soils
3 Nitrification and denitrification processes in soils produce two gas-phase intermediates, NO and
4 N2O, which can evolve from soil microbes before reaching their reaction endpoint, N2. N2O is not among
5 the nitrogen oxides important for urban and regional air quality either for human health concerns or
6 environmental effects because its reaction potential on these spatio-temporal scales in the troposphere is
7 insignificant. As a result, NO from soil metabolism is the prime, but not exclusive, form of atmospheric
8 NOx from the biosphere relevant to this ISA.
9 Biogenic NOX emissions are predominately the result of incomplete bacterial denitrification and
10 nitrification processes, as described above. Denitrification is a reduction process performed by particular
11 groups of heterotrophic bacteria having the ability to use nitrate ion (NO3 ) as an electron acceptor during
12 anaerobic respiration, thereby converting NO3 in soils and water to gas-phase forms (Firestone, 1989). At
13 low O2 concentrations, these microbial communities may use NO3 , nitrite (NO2 ), or N2O as alternative
14 electron acceptors to O2 (Davidson, 1995).
15 The basic outlines of these reaction pathways are known, but uncertainty remains concerning the
16 conditions favoring production of the various products of the NO3 transformations. Groups of aerobic
17 bacteria use most NH4+ in soils as an energy source, oxidizing it to NO2 and then NO3. Oxidized N
18 products from nitrification may undergo denitrification and thus also drive production of NOx- Some
19 bacteria are known to be nitrifiers and denitrifiers and can change depending on environmental
20 conditions, including high loadings of exogenous N.
21 Soil emissions of NOX can be increased by agricultural practices and activities, including the use of
22 synthetic and organic fertilizers, production of N-fixing crops, cultivation of soils with high organic
23 content, and the application of livestock manure to croplands and pasture. All of these practices directly
24 add exogenous N to soils, of which a portion will then be converted to NO or N2O on the pathway to full
25 conversion to N2. Additionally, indirect additions of N to soils can also result in NOX emissions from
26 agricultural and non-agricultural systems. Indirect additions include processes by which atmospheric NOX
27 is deposited directly to a region or N from applied fertilizer or manure volatilizes to NH3 and is oxidized
28 to NOX and then is ultimately re-deposited onto soils as NH4NO3, HNO3, or NOX (EPA, 2006).
29 N metabolism in soils is strongly dependent on soil substrate concentrations and physical
30 conditions. Where N is limiting, it is efficiently retained and little gas-phase N is released; where N is in
August 2008 2-8 DRAFT-DO NOT QUOTE OR CITE
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1 excess of demand, N emissions increase. As a consequence, soil NO emissions are highest from fertilized
2 agricultural lands and tropical soils (Davidson, 1997; Williams, 1992). In addition, temperature, soil
3 moisture, and O2 concentrations control both the rates of reaction and the partitioning between NO and
4 N2O. In flooded soils where O2 concentrations are low, N2O is the dominant soil N gas; as soils dry, more
5 O2 diffuses in and NO emissions increase. In very dry soils, microbial activity is inhibited and emissions
6 of both N2O and NO decrease.
7 Emission rates of NO from cultivated soils depend largely on fertilization levels and soil
8 temperature. Production of NO from agriculture results from the oxidation of NH3 emitted both by
9 livestock and by soils after fertilization with NH4NO3. Estimates of biogenic N emissions are far less
10 certain than those of anthropogenic emissions sources. Uncertainty on the order of a factor of 3 or more is
11 introduced by the variation within biomes to which fertilizer is applied, such as between shortgrass and
12 tallgrass prairie for example (Davidson, 1997; Williams, 1992; Yienger, 1995). The contribution of soil
13 emissions to the global NOX budget is approximately 10% (Finlayson-Pitts, 2000; Van Aardenne, 2001;
14 Seinfeld, 1998), but NOx emissions from fertilized fields are highly variable. Soil NO emissions can be
15 estimated from the fraction of the applied fertilizer N emitted as NOX, for example, but the flux depends
16 strongly on land use type and temperature. Estimates of globally averaged fractional-applied N lost as NO
17 varies from a low of 0.3% (Skiba, 1997) up to 2.5% (Yienger, 1995).
18 The spatial scales of these N fluxes are also significant. Local contributions to soil NOX can be
19 much greater than the global average, particularly in summer, and especially where corn is grown
20 extensively. Approximately 60% of total NOx emitted by soils in the U.S. occurs in the U.S. central corn
21 belt. Nitrification of fertilizer NH3 to NO3 in aerobic soils appears to be the dominant pathway to soil
22 NOx emissions, but the mass and chemical form of N applied to soils, the vegetative cover, the
23 temperature and soil moisture characteristics, and the agricultural practices such as tillage all influence
24 the amount of fertilizer N converted and released as NOx. On sub-national scales these emissions can be
25 large and highly variable. Williams et al. (1992) estimated that NOX from soils in Illinois was ~l/4 as
26 large as the total NOX emissions from industrial and commercial processes in that state. In Iowa, Kansas,
27 Minnesota, Nebraska, and South Dakota—states with smaller human populations than Illinois—soil
28 emissions may, in fact, dominate the NOX budget.
29 Emissions of NOx from soils often peak in summer when ozone (O3) formation is also at a
30 maximum. The significance of agricultural emission sources of NO and NH3 among other air pollutants
31 was described in detail in a recent National Research Council report (NRC, 2002). That report
32 recommended immediate implementation of best management practices to control these emissions, and
33 called for additional research to quantify the magnitude of emissions and the effects of agriculture on air
34 quality. The effects of such changes in management practice can be dramatic: Civerolo and Dickerson
August 2008 2-9 DRAFT-DO NOT QUOTE OR CITE
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1 (1998) reported that the use of no-till cultivation techniques on a fertilized cornfield in Maryland reduced
2 NO emissions by a factor of 7.
2.2.2.2. Live Vegetation
3 Extensive work on N inputs from the atmosphere to forests was conducted in the 1980s as part of
4 the Integrated Forest Study, summarized by Johnson and Lindberg (1992). As noted below and in Chapter
5 3, our understanding of NO2 exchange with vegetation suggests that NO2 should be emitted from foliage
6 when ambient concentrations are below the compensation point of ~1 ppb. However, Lerdau et al. (2000)
7 noted that current understanding of the global distribution of NOx is not consistent with the large source
8 that would be expected in remote forests if NO2 emissions were significant when atmospheric
9 concentrations were below the 1 ppb compensation point.
2.2.2.3. Biomass Burning
10 During biomass burning, N is derived mainly from fuel N and not from atmospheric N2, since
11 temperatures required to fix atmospheric N2 are likely to be found only in the flaming crowns of the most
12 intense boreal forest fires. N is present in plants mostly as amine (NH2) groups in amino acids. During
13 combustion, N is released in many forms, mostly unidentified and presumably as N2, leaving very little N
14 remaining in the fuel ash. Emissions of NOx are estimated to be ~0.2 to 0.3% of the total biomass burned
15 (e.g., Radke, 1991; Andreae, 1991). The most abundant NOX species in biomass burning plumes is NO,
16 emissions of which account for ~10 to 20% of the total fuel N loadings (Lobert, 1991); other N-
17 containing species such as NO2, nitriles, and NH3 together account for a similar amount. Westerling et al.
18 (2006) noted that the frequency and intensity of wildfires in the western U.S. increased substantially since
19 1970, lending added importance to consideration of all NOX emissions from this sector.
2.2.2.4. Lightning
20 Annual global production of NO by lightning is the most uncertain source of atmospheric N. In the
21 last decade, literature values of the global average production rate ranged from 2 to 20 Tg N/yr. Most
22 recent estimates, however, are in the range of 3 to 8 Tg N/yr. This large and persistent uncertainty stems
23 from several factors: (1) a wide range of as much as 2 orders of magnitude in NO production rates per
24 meter of flash length; 2) uncertainty over whether cloud-to-ground (CG) and intracloud (1C) flashes
25 produce substantially different NO levels; 3) the global average flash rate; and (4) the ratio of the number
26 of 1C to CG flashes.
27 Estimates of the NO concentration produced per flash have been made from theoretical
28 considerations (e.g.,, Price, 1997), laboratory experiments (e.g.,, Wang, 1998), and field experiments (e.g.,
August 2008 2-10 DRAFT-DO NOT QUOTE OR CITE
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1 Huntrieser, 2002; Huntrieser, 2007, 93018; Stith, 1999), and with a hybrid method of cloud-resolving
2 model simulations, observed lightning flash rates, and measurements of NO concentrations in cloud
3 anvils (e.g., DeCaria, 2000; 2005; Ott, 2007). A series of midlatitude and subtropical thunderstorm events
4 were simulated with the model of DeCaria et al. (2005) and the derived NO production per CG flash was,
5 on avg, 500 moles/flash, while production per 1C flash was 425 moles/flash on avg (Ott, 2006). The
6 hybrid method had earlier been used by Pickering et al. (1998) who showed that only ~5 to 20% of the
7 total NO produced by lightning in a given storm exists in the planetary boundary layer (PEL) at the end of
8 a thunderstorm event, thereby reducing its importance as a direct emissions source to the urban and
9 regional troposphere.
2.2.3. Anthropogenic and Biogenic Sources of N20
10 N2O has an atmospheric lifetime (T) of -114 years, resulting from its having effectively no
1 1 chemistry in the lower troposphere on urban and regional scales. The chief N2O loss pathway (with a
12 quantum yield of ~1) is the photodissociation process
Reaction 3
1 3 driven by the short wavelength UV present only in the stratosphere.
14 However, N2O is also a GHG with a global warming potential (GWP) on the conventional 100-
1 5 year time horizon of -296; i.e., 1 molecule of N2O is nearly 300 times more effective at trapping heat in
16 the atmosphere than 1 molecule of carbon dioxide (CO2) over a 100-year period (EPA, 2002) (Houghton,
17 2001). The high GWP of N2O results from its combination of direct and indirect radiative forcing climate
1 8 effects in the stratosphere. By comparison, the primary climate effects of NO and NO2 are indirect and
1 9 result from their role in promoting the production of O3 (P(O3)) in the troposphere and, to a lesser degree,
20 in the lower stratosphere where NOX has positive radiative forcing effects. Additional complications for
21 calculating NOX GWPs arise because NOX emissions from high-altitude aircraft are also likely to
22 decrease methane (CH4) concentrations, a negative radiative forcing effect (Houghton, 1996), and
23 because pNO3 transformed from NOX also have negative radiative forcing effects. The EPA does not
24 calculate GWPs for total NOX or SOX or for the other atmospheric constituents for which no agreed-upon
25 method exists to estimate the contributions from these gases that are short-lived in the atmosphere, have
26 strong spatial variability, or have only indirect effects on radiative forcing.
27 Thus, because there are no tropospheric reactions or effects to consider, N2O is not a significant
28 component of NOX for the purposes of this ISA. However, the role of N2O as an intermediate product
29 along with NO from the complex soil metabolism described in Section 2.2.2. 1 means that a brief
August 2008 2-1 1 DRAFT-DO NOT QUOTE OR CITE
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1 description of its emissions strengths and its component part of the total budget of U.S. GHGs will be
2 useful, and so appears just below.
3 N2O is a contributor to the total U.S. GHG budget, with 6.5% of total GHG on a Tg CO2
4 equivalents basis (CO2e) in 2005 (EPA, 2007). CO2, by comparison, accounted for 83.9% in that same
5 year, and CH4 for 7.4% (EPA, 2007). Although atmospheric concentrations of N2O have increased
6 globally by -18% to a current value of ~315 ppb due to Western industrialization since 1750 C.E.
7 (Hofmann, 2004), there is considerable interannual variation in N2O emissions which remains largely
8 unexplained (Houghton, 2001). N2O emissions in the U.S., for example, decreased by 2.8%, or 13.4 Tg
9 CO2e, between 1990 and 2005 (EPA, 2007).
10 N2O is produced by biological processes occurring in the soil and water and by a variety of
11 anthropogenic activities in the agricultural, energy, industrial, and waste management sectors. The chief
12 anthropogenic activities producing N2O in the U.S. are agricultural soil management, fuel combustion in
13 motor vehicles, manure management, production of adipic acid (nylon) and HNO3, wastewater treatment,
14 and stationary fuel combustion.
15 N2O emissions from anthropogenic activities in the U.S. were 386.7 Tg CO2e/yr between 1990 and
16 2004 (EPA, 2007). These emissions resulted from the fuel combustion, industrial practices, and
17 stimulation of biogenic sources through agricultural practices enumerated above. In 2005, N2O emissions
18 from mobile sources were 38.0 Tg CO2e, or -8% of the U.S. N2O emissions total (EPA, 2007). In the
19 period between 1990 and 1998, control technologies on mobile sources reduced on-road vehicle NO and
20 NO2 emissions at the expense of increasing N2O emissions by 10%. The overall reduction in N2O mobile
21 source emissions between 1998 and 2005 (when totals were last available), however, has been 13% owing
22 to more efficient controls used after 1998.
23 Biogenic production of N2O stimulated through soil management accounted for > 75% of all U.S.
24 N2O emissions in 2005 (EPA, 2007). N2O emissions from these sources have shown no significant long-
25 term trend, because the biogenic emitters are highly sensitive to the concentrations and forms of N
26 applied to soils, and these applications have been largely constant (EPA, 2007).
27 Aquatic sources of N2O may also be stimulated by environmental conditions. In some ocean areas,
28 large areas of surface water can become depleted in O2, allowing active denitrification in open water, and
29 potentially increasing N2O emissions as described in Section 2.2.2. In addition, oceanic N2O can also
30 arise from denitrification in marine sediments, particularly in nutrient rich areas such as those of estuaries.
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2.3. Sources and Emissions of Tropospheric SOx
1 Emissions of SO2, the chief component of SOX, are due mostly to combustion of fossil fuels by
2 EGUs and industrial processes with transportation-related sources making smaller but significant
3 contributions.
2.3.1. Major Anthropogenic Sources
4 Table 2-1 shows that for 2002, fossil fuel combustion at EGUs accounted for -66% of total SO2
5 emissions in the U.S., or 11.31 Tg of the total 16.87 Tg. All transportation sources accounted for ~5% of
6 the total U.S. SO2 emissions in 2002, or 0.76 Tg. On-road vehicles produced -40% of the transportation-
7 related total SO2 emissions in 2002, with off-road diesel and marine traffic together accounting for the
8 remainder. Thus, most SO2 emissions originate from point sources having well-known locations and
9 identifiable fuel streams.
10 Since nearly all S in fuels is released in volatile components, either SO2 or SO3, during
11 combustion, total S emissions from these point sources can be computed from the known S content in fuel
12 stocks with greater accuracy than can total NOX emissions from point sources. However, just as for the
13 NOX emissions totals described above, total SOX emissions estimates are national-scale averages and so
14 can not accurately reflect the contribution of local sources to selected environmental exposures to SOX at
15 specific locations and times. To refine those national estimates, county-level average SO2 emissions for
16 2001 are shown in Figure 2-5; normalized emissions intensities per square mile like those shown above
17 for NOx are shown for SO2 in Figure 2-6.
18 Figure 2-6 illustrates the west-to-east increasing gradient in SO2 emissions densities, with most
19 counties east of the Mississippi River in warmer colors (greater emissions densities) than most counties in
20 the West. The upper end of the SO2 emissions density distribution represented includes many counties in
21 the eastern U.S.—primarily in the Ohio River Valley—with 2001 SO2 emissions densities significantly
22 greater than 20. Examples of these high densities (in tons per square mile) are: Hillsborough County, FL,
23 80; Grant County, WV, 156; Indiana County, PA, 190; Washington County, OH, 273; and Armstrong
24 County, PA, 292. In these counties, SO2 emissions were due mostly to EGU fuel combustion, as shown in
25 Table 2-2. For the EGU emissions densities in Figure 2-7, and the total SO2 densities in Figure 2-6, the
26 upper end of the density distribution compresses a wide range (see Table 2-2). Thus, for the five counties
27 considered above, non-EGU emissions were < 5% of total SO2 emissions in Washington County, OH,
28 and < 1% in Indiana County, PA, Armstrong County, PA, and Grant County, WV. Hillsborough County,
29 FL, is an exception, where 17% of the 2001 SO2 emissions density came from non-EGU sources, the
30 largest of which was chemical and allied product manufacturing.
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2001 County Emissions (1000 Tons per Year) of Sulfur Dioxide
0 >0-0.05 0.05-0.11 0.11-0.31
0.31-1.5 BB 1.5-12 BB 121
Source: U.S. EPA (2006)
Figure 2-5.2001
county-level total
U.S. 862 emissions.
2001 County Emissions Density (Tons per sq mi ) of Sulfur Dioxide
0.54-2,7
>OH3.069
Z7-20
0.069-0.17
20+
0.17-0.54
Source: U.S. EPA (2006)
Figure 2-6.2001
county-level total
U.S. S02 emissions
densities (tons per
square mile).
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2001 County Emissions Density (Tons per sq.mi.) of Sulfur Dioxide
0 jO-0.000098 O.OQDOSa-O.OOtl O.OOH -0.045
0045-13 • 13-57 • 57+
Source: U.S. EPA (2006)
Figure 2-7.2001
county-level SCb
emissions densities
(tons per square
mile) from EGUs.
Table 2-2. Total
County
Hillsborough, FL
Grant, WV
Indiana, PA
Washington, OH
Armstrong, PA
and non-EGU S(>2 emissions densities for selected U.S. counties, 2001 .
S02
Emissions
Density
(tons/mi2)
80
156
190
273
292
Non-EGU
Emissions
Density
Fraction (%)
17
<1
<1
<5
<1
1 Although on-road mobile sources in 2001 contributed < 5% to SC>2 emissions totals on the national
2 scale, their fraction of county-level emissions densities varies widely. Generally, however, on-road mobile
3 source SC>2 emissions reflect the west-to-east increasing gradient in the densities of both total SC>2
4 emissions and U.S. population, as shown in Figure 2-8. In areas such as Wayne County, MI, and Bronx
5 County, NY, for example, 2001 SO2 emissions densities from on-road mobile sources were 3 and 8.8 tons
6 per square mile out of totals of 98 and 160 tons per square mile, respectively, total SO2. In other areas like
7 Dallas County, TX, and DeKalb County, GA, however, the on-road fraction of total SO2 emissions
8 densities in 2001 was substantially greater: 1.5 out of the total 4.1 tons per square mile in Dallas County,
9 and 3.5 out of the total 6.5 tons per square mile in DeKalb County.
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2001 County Emissions Density (Tons per sq.mi.) of Sulfur Dioxide
0
0.057-0.14
>0-0.0065
0.14-0,32
0.0065-0.022
0.32 +
0.022-0.057
Source: U.S. EPA (2006)
Figure 2-8.2001
county-level 862
emissions densities
(tons per square
mile) from on-road
mobile sources.
Source: US EPA Offiet ol Air and Radiation. NEI DalolxrM
Thursday, July 10. 2DOB
2001 County Emissions Density (Tons per sq.mi.) of Sulfur Dioxide
0.067-0.18
>0-0.016
0.18-0.5
0.016-0.041
0.5+
0.041-0.087
Source: U.S. EPA (2006)
Figure 2-9.2001
county-level 862
emissions densities
(tons per square
mile) from off-road
mobile and other
transportation
sources.
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1 An additional source of SO2 emissions of concern in particular locations not immediately obvious
2 from national-scale averages and totals are transit and in-port activities in areas with substantial shipping
3 traffic (Wang, 2007). Because of the importance of these SO2 emissions, the ports of Long Beach and Los
4 Angeles, CA, for example, are part of a Sulfur Emissions Control Area in which S contents of fuels are
5 not to exceed 1.5%. Figure 2-9 shows SO2 emissions densities combined for all non-road transportation-
6 related emitters in which coastal areas with ports and shipping routes, such as the Mississippi River, are
7 easily discerned. In Los Angeles County, CA, for example, off-road transportation including shipping and
8 port traffic contributed 1.4 of the total 4.1 tons of SO2 per square mile in 2001; in King County (including
9 the city of Seattle), WA, the off-road transportation fraction was 42% of the total SO2 emissions density,
10 or 1.2 of the total 2.8 tons per square mile. Emissions density data at finer scales more specific to the
11 ports are not available in the routine emissions inventories and some confusion attends estimates of the
12 actual SO2 loads from these sources. Modeling studies by Vutukuru (2008) for southern California ports,
13 for example, have shown that ships contribute >1 ppb to the 24-h avg SO2 concentration in Long Beach,
14 CA, with < 10% of that, or ~100s of ppt farther inland.
2.3.2. Major Biogenic Sources
15 The major biogenic sources of SO2 are volcanoes, biomass burning, and dimethylsulfide (DMS)
16 oxidation over the oceans. Although SO2 constitutes a relatively minor fraction of 0.005% by volume of
17 total volcanic emissions (Holland, 1978), concentrations in volcanic plumes can be in the range of several
18 to tens of ppm. The ratio of hydrogen sulfide (H2S) to SO2 is highly variable in volcanic gases,
19 typically < 1, as in the Mount St. Helens eruption in the Washington Cascade Range (46.20 N, 122.18 W,
20 summit 2549 m asl) (Turco, 1983). However, in addition to being degassed from magma, H2S can be
21 produced if ground waters, especially those containing organic matter, come into contact with volcanic
22 gases. In this case, the ratio of H2S to SO2 can be > 1. H2S produced this way would more likely be
23 emitted through side vents than through eruption columns (Pinto, 1989). Primary particulate sulfate
24 (pSO4) is a component of marine aerosol and is also produced by wind erosion of surface soils.
25 Since 1980, the Mount St. Helens volcano has been a variable source of SO2. Its major effects came
26 in the explosive eruptions of 1980, which primarily affected the northern part of the mountainous western
27 half of the U.S. The Augustine volcano near the mouth of the Cook Inlet in southwestern Alaska (59.363
28 N, 153.43 W, summit 1252 m asl) has had variable SO2 emissions since its last major eruptions in 1986.
29 Volcanoes in the Kamchatka peninsula of the eastern region of Siberian Russia do not significantly affect
30 surface SO2 concentrations in northwestern North America. The most serious effects from volcanic SO2 in
31 the U.S. occur on the island of Hawaii. Nearly continuous venting of SO2 from Mauna Loa and Kilauea
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1 produces SO2 in such large amounts that > 100 km downwind of the island, levels of SO2 can exceed
2 30 ppb (Thornton, 1993).
3 Emissions of SO2 from burning vegetation are generally in the range of 1 to 2% of the biomass
4 burned (e.g.,, Levine, 1999). S is bound in amino acids in vegetation, and -50% of this organically-bound
5 S is released during combustion, leaving the remainder in the ash (Delmas, 1982). Gas-phase emissions
6 are mainly in the form of SO2, with much smaller amounts of H2S and carbonyl sulfide (OCS). The ratio
7 of reduced S species such as H2S to more oxidized forms like SO2 increases as the fire conditions change
8 from flaming to smoldering phases of combustion because emissions of reduced species are favored by
9 the lower temperatures and decreased O2 availability.
10 SO2 is also produced by the photochemical oxidation of reduced S compounds such as
11 dimethylsulfide (CH3-S-CH3, or DMS), H2S, carbon disulfide (CS2), OCS, methyl mercaptan
12 (CH3-S-H), and DMS (CH3-S-S-CH3). The sources for these compounds are mainly biogenic (see
13 Table 2-1). Emissions of reduced S species are associated typically with marine organisms living either in
14 pelagic or coastal zones and with anaerobic bacteria in marshes and estuaries. Emissions of DMS from
15 marine plankton represent the largest single source of reduced S species to the atmosphere (Berresheim,
16 1995). Other sources such as wetlands and terrestrial plants and soils account for < 5% of the DMS global
17 flux, with most of this coming from wetlands.
18 Other than OCS, which is lost mainly by photolysis with a T of ~6 months, SOX species are lost
19 mainly by reaction with OH" and NO3 , and are relatively short-lived, with T ranging from a few hours to
20 a few days. Reaction with NO3 at night most likely represents the major loss process for DMS and
21 methyl mercaptan. Although the mechanisms for the oxidation of DMS are not known with certainty,
22 excess SO42 in marine aerosol appears related mainly to production of SO2 from the oxidation of DMS.
23 Emissions of SOx from natural sources are small compared to industrial emissions within the U.S. (see
24 Table 2-1). However, important exceptions occur locally as the result of volcanic activity, wildfires, and
25 in certain coastal zones as described above.
26 Because OCS is relatively long-lived, it can survive oxidation in the troposphere and be transported
27 upward into the stratosphere. Crutzen (1976) proposed that its oxidation to SO42 in the stratosphere
28 serves as the major source of the stratospheric aerosol layer. However, Myhre et al. (2004) proposed that
29 SO2 transported upward from the troposphere by deep convection is the most likely source, since the flux
30 of OCS is too small to account for current atmospheric loadings. In addition, in situ measurements of the
31 isotopic composition of S in stratospheric SO42 do not match those of OCS (Leung, 2002). Thus, in
32 addition to biogenic OCS, anthropogenic SO2 emissions could be important precursors to the formation of
33 the stratospheric aerosol layer.
34 The coastal and wetland sources of DMS have a dormant period in the fall and winter from plant
35 senescence. Marshes die back in fall and winter, so DMS emissions from them are lower, and lower light
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1 levels in winter at mid-to-high latitudes lessen phytoplankton growth also tend to lower DMS emissions.
2 Western coasts at mid-to-high latitudes have lower actinic flux to drive photochemical production and
3 oxidation of DMS. Freezing at mid and high latitudes affects the release of biogenic S gases, particularly
4 in the nutrient-rich regions around Alaska. Transport of SC>2 from regions of biomass burning seems to be
5 limited by heterogeneous losses that accompany convective processes that ventilate the surface layer and
6 the lower boundary layer (Thornton, 1996).
7 Reduced S species are also produced by several anthropogenic industrial sources: DMS is used in
8 petroleum refining and in petrochemical production processes to control the formation of coke and CO;
9 and it is used to control dusting in steel mills, and in a range of organic syntheses; as a food flavoring
10 component; and can also be oxidized by natural or artificial means to dimethyl sulfoxide, a widely-used
11 industrial solvent.
2.4. NHx Emissions
12
13
14
15
16
17
18
NH3 can be emitted from or deposited to soils, water, or vegetation depending on the ratio of
atmospheric NH3 concentration to the compensation point of the underlying surface. The compensation
point, %, generally is governed by the form, concentration, and acidity of N at the surface of exchange,
and hence changes over time as these variables change. For most of the year, large areas of the U.S. are
very near the nominal % of 1 ug/m3, with the result that the NH3 air-surface flux is very often highly
dynamic. Figure 2-10 and Figure 2-11 show county-level annual total NH3 emissions for 2001 in tons,
and the spatially normalized county-level emissions in tons per square mile, respectively.
Source: U.S. EPA (2006)
Figure 2-10.2001
county-level total
U.S. NHs emissions.
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Source: U.S. EPA (2006)
Figure 2-11.2001
county-level total
U.S. NHs emissions
densities.
1 Total emissions of NH3 on a national scale show a strikingly different pattern from those of NOx or
2 SO2 as comparison of these figures to their NOX and SOX analogs above illustrates. Anthropogenic NH3
3 emissions from mobile sources are small since the three-way catalysts used in motor vehicles emit only
4 small amounts of NH3 as a byproduct during the reduction of NOX; in 2002, this totaled -8% of the
5 national NH3 total of ~3.7m short tons. Stationary combustion sources including EGUs make even
6 smaller contributions to emissions of NH3 because their efficient combustion favors NOX formation and
7 NH3 is produced during combustion largely by inefficient, low-temperature burning. In 2002, the total
8 from all stationary source fuel combustion processes amounted to < 2% of total NH3 emissions and
9 chemical production added only -0.7% more. For these reasons, NH3 emissions totals are dominated by
10 biogenic production from agriculture, chiefly from livestock management and fertilizer applications to
11 soils. In 2002, these sources accounted for -86% of U.S. total emissions.
12 As with NOX and SOX emissions, however, these national-scale emissions totals obscure important
13 variability at finer scales. To illustrate this point, Figures 2-13 through 2-15 show county-level NH3
14 emissions densities separately for emissions from on-road mobile sources, EGUs, and miscellaneous and
15 biogenics, respectively.
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Source: U.S. EPA (2006)
Figure 2-12.2001
county-level NHs
emissions densities
from on-road mobile
sources.
Source: U.S. EPA (2006)
Figure 2-13.2001
county-level NHs
emissions densities
from EG Us.
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Source: U.S. EPA (2006)
Figure 2-14.2001
county-level NHs
emissions densities
from miscellaneous
and biogenic
sources
2.5. Evaluating Emissions Inventories
1 Emissions inventories are very complex and highly changeable conjoined forms built from
2 measurements and production and transfer rates, some of which are measured directly, others indirectly,
3 and others merely assumed, and with model predictions. National-scale emissions inventories like the
4 ones illustrated in county-level maps have uncertainties embedded in them owing to unknown emission
5 factors, unknown and varying emission rates, generalized or depleted profiles, and the like. Substantial
6 effort is applied at national, state, and local scales to test these terms in the final product emissions totals,
7 and to assure their quality.
8 One means for evaluating emissions inventories has been to compare predictions in the inventories
9 to measured long-term trends, or to ratios of pollutants in ambient air. Comparisons of emissions model
10 predictions with observations have been performed in a number of environments. Very often emissions
11 inventories for NOX and SOX are evaluated in relation to CO emissions because the low reactivity of CO
12 on urban and regional scales means it can be treated as largely conserved on these scales. Using the
13 distinction between mobile sources which emit NOX and CO but little SO2, and power plants which emit
14 NOX and SO2 but little CO, Stehr et al. (2000) evaluated emissions estimates for the eastern U.S. Results
15 indicated that coal combustion contributes 25 to 35% of the total area NOX emissions in rough agreement
16 with the U.S. EPA NEI (EPA, 1997). Studies using ratios of CO concentrations to NOX concentrations,
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1 and concentrations of nonmethane organic compounds (NMOC) to NOX carried out in the early 1990s in
2 tunnels and ambient air indicated that emissions of CO and NMOC were systematically underestimated in
3 emissions inventories at that time. More details are available in the Air Quality Criteria for Carbon
4 Monoxide (EPA, 2000).
5 These reconciliation studies depend on the assumption that NOx emissions are predicted correctly
6 by emissions factor models which are merely mean and aggregate descriptions of the highly variable U.S.
7 mobile source fleet. Roadside remote sensing data have indicated that > 50% of non-methane hydro-
8 carbons (NMHC) and CO emissions are produced by less than 10% of vehicles (Stedman, 1991),
9 typically the poorly maintained "super-emitters."
10 Parrish et al. (1998) and Parrish and Fehsenfeld (2000) proposed methods to derive emission rates
11 by examining measured ambient ratios among individual volatile organic compounds (VOCs), NOX, and
12 NOY. Typically, strong correlations exist among measured values for these species because emission
13 sources are geographically collocated, even when individual sources are different. Correlations can be
14 used to derive emissions ratios between species, including adjustments for the effect of photochemical
15 aging. Examples of this type include using correlations between CO and NOY (e.g.,, Parrish, 1991),
16 between individual VOC species and NOY (Arnold, 2007; Goldan, 1995, 2005) and among various VOC
17 species (McKeen, 1993, 1996). Many of these studies were summarized in Trainer et al. (2000), Parrish
18 et al. (1998), and Parrish and Fehsenfeld (2000).
19 Other methods for emissions evaluation exist. Buhr et al. (1992) derived emission estimates from
20 principal component analysis (PCA) and other statistical methods. Goldstein and Schade (2000) also used
21 species correlations to identify the relative effects of anthropogenic and biogenic emissions. Chang et al.
22 (1996;, 1997) and Mendoza-Dominguez and Russell (2000) used inverse modeling to derive emission
23 rates in conjunction with results from chemical-transport models (CTMs).
24 A decadal field study of ambient CO at a rural site in the eastern U.S. (Hallock-Waters, 1999)
25 indicated a downward trend consistent with the downward trend in estimated emissions over the period
26 1988 to 1999 (EPA, 2000), even when the global downward trend was taken into account. Measurements
27 at two urban areas in the U.S. confirmed the decrease in CO emissions (Parrish, 2002). That study also
28 indicated that the ratio of CO to NOX emissions decreased by approximately a factor of 3 over 12 years.
29 NEI estimates (EPA, 1997) indicated a much smaller decrease in this ratio, suggesting that NOX
30 emissions from mobile sources may have been underestimated or increasing or both. Parrish et al. (2002)
31 concluded that O3 photochemistry in U.S. urban areas may have become more NOx-limited over the past
32 decade. (See Section 2.6.2.1 for a discussion of NOX and its role in enhancing and limiting O3 formation.)
33 Results from some of these recent emissions evaluation studies have been mixed, with some studies
34 showing agreement to within ±50% (EPA, 2000). However, Pokharel et al. (2002) employed remotely
3 5 sensed emissions from on-road vehicles and fuel use data to estimate emissions in Denver. Their
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1 calculations indicated a continual decrease in CO, hydrocarbons (HC), and NO emissions from mobile
2 sources over the 6-year study period, 1996 through 2001. Inventories based on the ambient data were 30
3 to 70% lower for CO, 40% higher for HC, and 40 to 80% lower for NO than those predicted by the
4 MOBILE6 on-road mobile source emissions model (see http://www.epa.gov/otaq/m6.htm for information
5 on MOBILE6).
6 Satellite data also have proved useful for optimizing estimates of emissions of NO2 (Leue, 2001;
7 Martin, 2003; Jaegle, 2005). Satellite-borne instruments such as the Global Ozone Monitoring
8 Experiment (GOME) (see Martin, 2003 and references therein) and the Scanning Imaging Absorption
9 Spectrometer for Atmospheric Chartography (SCIAMACHY) (see Bovensmann, 1999) retrieve
10 tropospheric columns of NO2 that can then be combined with model-derived T of NOX to yield emissions
11 of NOX.
12 Top-down inference of NOx emission inventories from the satellite observations of NO2
13 concentrations columns by mass balance requires at minimum three pieces of information: (1) the
14 retrieved tropospheric NO2 column; 2) the ratio of tropospheric NOX to NO2 in the columns; and (3) the
15 NOX t against reaction losses to stable chemical reservoirs. (See the discussion of these chemical
16 reservoirs in Section 2.6). A photochemical model has been used to provide information on the latter two
17 pieces of information. The method is most often applied to land surface emissions, excluding lightning.
18 Tropospheric NO2 columns are largely insensitive to lightning NOX emissions since most of the lightning
19 NOx in the upper troposphere is present as NO at the time of the satellite measurements (Ridley, 1996),
20 owing to the slower reactions of NO with ©3 at the altitude where lightning production is most prevalent.
21 Using satellite data, Bertram et al. (2005) found clear signals in the SCIAMACHY observations of
22 short, intense NOx pulses following springtime fertilizer application and subsequent precipitation over
23 agricultural regions of the western U.S. For the agricultural region in north-central Montana, they
24 calculated an annual SCIAMACHY top-down estimate that is 60% greater than a commonly-used model
25 of soil NOX emissions by Yienger and Levy (1995).
26 Jaegle et al. (2005) applied additional information on the spatial distribution of emissions and fire
27 activity to partition NOX emissions into sources from fossil fuel combustion, soils, and biomass burning.
28 Global a posteriori estimates of soil NOX emissions were 68% larger than the a priori estimates. Large
29 increases were found for the agricultural region of the western U. S. during summer, increasing total U.S.
30 soil NOx emissions by a factor of 2.
31 Martin et al. (2006) retrieved tropospheric NO2 columns for May 2004 to April 2005 from the
32 SCIAMACHY satellite instrument to derive top-down NOX emissions estimates via inverse modeling
33 with the GEOS-Chemistry global chemical transport model (see http://www.as.harvard.edu/ctm/geos/ for
34 more information on GEOS-Chem). The top-down emissions were combined with a priori information
3 5 from a bottom-up emission inventory with error weighting to achieve an improved a posteriori estimate of
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1 the global distribution of surface NOx emissions. Their a posteriori inventory improved GEOS-Chem
2 simulations of NOX, peroxyacetyl nitrate (PAN), and HNO3 as compared against airborne in situ
3 measurements over and downwind of New York City. Their a posteriori inventory showed lower NOX
4 emissions from the Ohio River Valley in summer than winter, reflecting recent controls on NOx emissions
5 from electric utilities there. Their a posteriori global inventory was highly consistent with the NEI 99 (R2
6 = 0.82, bias = 3%); however, it was 68% greater than a recent inventory by Streets et al. (2003) for East
7 Asia for the year 2000.
8 Significant uncertainties attach to estimates of the magnitude and spatial and temporal variability of
9 NH3 emissions. A strong seasonal pattern should be evident in NH3 emissions profiles to correspond with
10 the overwhelmingly agricultural sources of NH3 and strong seasonal temperature differences in NH3
11 volatility, for example, but this pattern has not appeared in previous emissions factors and inventories.
12 The magnitude of these temporal differences is large: Heber et al. (2001) showed that NH3 flux from two
13 swine finishing buildings were -70% higher in June than in fall and winter months, and Aneja et al.
14 (2000) found fluxes from hog waste lagoons ~80 to 90% higher in summer as compared to winter.
15 The value of inverse modeling techniques using large-scale Eulerian air quality models (AQMs)
16 has been successfully demonstrated for several aspects of emissions inventories; see, for example,
17 Mendoza-Dominguez and Russell (2000;, 2001; Mendoza-Dominguez, 2001), Gilliland et al. (2001;,
18 2001;, 2003) and Finder et al. (2006) have worked extensively with Kalman filter inverse modeling and
19 the U.S. EPA Community Multiscale Air Quality (CMAQ) modeling system (Byun, 1999) to reduce
20 uncertainties specifically in NH3 emissions. NH3 is an especially good case for emissions estimate
21 evaluation with inverse modeling techniques because the modeled response in NH4+ wet deposition is
22 strongly linear with changes in NH3 emissions. Correcting the NH3 emissions estimates was also shown
23 to be an essential step for reasonable model-prediction of other N compounds (Gilliland, 2003). Results
24 can be highly significant. For example: the a posteriori R value of CMAQ predictions against measured
25 west NH4+ concentrations from the National Atmospheric Deposition Program (NADP) cites in the U.S.
26 was 0.98, increased from the a priori value of 0.12. Pinder et al. (2004) provided the first farm-level
27 model for NH3 emissions from dairy cattle, and this has been coupled with the seasonally varying
28 fertilizer inventory for NH3 from Goebes et al. (2003) and with the inverse modeling results of Gilliland
29 et al. (2003) to correct the NEI NH3 emissions totals. The estimate of Gilliland et al. (2003) was that the
30 annual NEI NH3 was -37% too high to optimize modeled wet NH4+ concentration. Following earlier
31 work by Gilliland and others in this vein, U.S. EPA (EPA, 2002), in fact, reported its intention to decrease
32 total NH3 emissions in the NEI by 23% by altering emissions factors for nondairy cows and swine.
33 Holland et al. (2005) estimated wet and dry deposition of NHX based on measurements over the
34 CONUS and reported that NH3 emissions in the 1999 NEI
35 (http://www.epa.gov/ttn/chief/net/1999inventory.html) were underestimated by a factor of ~2 or 3.
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Possible reasons for this error included under-representation of deposition monitoring sites in populated
areas and the neglect of off-shore transport in the NEI. The use of fixed deposition velocities (Vd) not
reflective of local conditions at the time of measurement introduces additional uncertainty into estimates
4 of dry deposition to which NH3 is particularly sensitive.
2.6. NOx-SOx-NHx Chemistry in the Troposphere
2.6.1. Introduction
5 NOX, VOCs, and CO are precursors in the formation of O3 and other elements of photochemical
6 smog and PM. The role of NOX in P(O3), mechanisms for transporting the NOX and VOC O3 precursors,
7 factors controlling P(O3) efficiency, methods for calculating O3 from its NOX and VOC precursors, and
8 methods for measuring and estimating NOY were all reviewed in Chapter 2, Section 2.2 of the Air Quality
9 Criteria Document for Ozone and Related Photochemical Oxidants (O3 AQCD) (EPA, 2006) and are
10 available in numerous texts (Seinfeld, 1998; Jacob, 2000; Jacobson, 2002). Hence, these are only briefly
11 recounted here with special reference to the secondary NOX and SOX NAAQS.
12 Important compounds, reactions, and cycles are schematized in Figure 2-15. Figure 2-15 also
13 illustrates that NO2, itself an oxidant, can react to form other photochemical oxidants including organic
14 nitrates (RONO2) like the PANs shown in Figure 2-15, and can react with toxic compounds like the
15 poly cyclic aromatic hydrocarbons (PAHs) to form nitro-PAHs, some of which demonstrate greater
16 toxicity than either reactant alone. NO2 can also be further oxidized to FINO3 and can contribute in that
17 form to the acidity of cloud, fog, and rain water and can form ambient pNO3.
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Long range transport to remote
regions at low temperatures
NIV "°3<<
,N\/
nitrosamines,
nitre-phenols, etc
Inorganic
Nitrates
emissions
Figure 2-15. Schematic diagram of the cycle of reactive oxidized N species in the atmosphere. NOv
refers to all the species shown within the inner and outer box; NOx to NO and NOa (in the inner
box); to all the species outside of the inner box. IN refers to inorganic particulate species (e.g.,
sodium (Na+), calcium (Ca++)), MPP to multiphase processes, hv to a solar photon and R to an
organic radical. Particle-phase RONOa are formed from the species shown on the right side. For the
purposes of this EPA document, "NOx" is defined as the group of all N-containing compounds
inside the large dashed-line box, the same group generally termed "NOv" by atmospheric
scientists.
1 The only gas-phase forms of SOX of interest in tropospheric chemistry are SO2 and SO3. SO3 can
2 be emitted from the stacks of power plants and factories; however, it reacts extremely rapidly with H2O in
3 the stacks or immediately after release into the atmosphere to form sulfuric acid (H2SO4). H2SO4 in turn
4 mainly condenses onto existing particles when particle loadings are high, or nucleates to form new
5 particles under lower concentration conditions. Thus, of the gas-phase SOX species, only SO2 is emitted in
6 the tropospheric boundary layer at concentrations of concern for environmental exposures.
7 NH3, the gas-phase precursor for NH4+, plays a key role in neutralizing acidity in ambient particles
8 and in cloud, fog, and rain water. NH3 is also involved in the ternary nucleation of new particles and
9 reacts with gas-phase HNO3 to form NH4NO3, and with SO42 to form ammonium bisulfate (NH4HSO4)
10 and ammonium sulfate ((NH4)2SO4), three significant components of N and S deposition across the
11 landscape. The NOx-SO2-NHx cycles and phase-changes are schematized in Figure 2-16.
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Gas-phase products
Secondary Organic
aerosol
Droplet Phase
Source: Adapted from Meng et al. (1997) and Warneck and used courtesy of
R. Mathur and R. Dennis, U.S. EPA /ORD / NERL / ASMD.
Figure 2-16. The combined
NOx+SOx+NHx System showing
how atmospheric fates and
lifetimes of reduced and oxidized N
components are linked.
2.6.2. NOx Chemistry
x is emitted by combustion sources mainly as NO with ~5 to 10% NO2. The rapid
2 photochemical cycle in the troposphere linking NO and NO2 involves photolysis of NO2 by UV-A
3 radiation to yield NO and a ground-state oxygen atom, O(3P)
Reaction 4
4 O(3P) can then combine with molecular oxygen (O2) to form O3; and, colliding with any molecule from
5 the surrounding air (M = N2, O2, etc.), the newly formed O3 molecule transfers excess energy and is
6 stabilized by
Reaction 5
7 Reaction 5 is the only significant reaction for forming O3 in the troposphere.
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NO and O3 react to reform NO2
NO + O3 -» NO2 + O2
Reaction 6
2 Reaction 6 is responsible for O3 decreases and NO2 increases found near sources of NO like highways.
3 The falloff of NO2 with distance from a road depends on wind speed and direction, and the local structure
4 of turbulent mixing, temperature through the temperature dependence of Reaction 6 and the UVA-flux
5 (through Reaction 4).
6 Oxidation of reactive VOCs leads to formation of reactive radical species that allow conversion of
7 NO to NO2 without participation of O3 as in Reaction 7
NO H°2' R°2 > NO2
Reaction 7
8 O3, therefore, can accumulate as NO2 photolyzes as in Reaction 4, followed by Reaction 5. Specific
9 mechanisms for the oxidation of a number of VOCs were discussed in the O3 AQCD (EPA, 2006).
10 It is often convenient to speak about families of chemical species defined in terms of members that
11 interconvert rapidly on time scales shorter than those for formation or destruction of the family as a
12 whole. For example, an "odd oxygen" (Ox) family can be defined as
Ox = 1L(O(3P) + O(}D) + O3 + NO2)
Reaction 8
13 In much the same way, NOX is sometimes referred to as "odd nitrogen." Hence, we see that production of
14 Ox occurs by the schematic Reaction 7 while the sequence of reactions given by Reaction 4 through
15 Reaction 6 represents no net production of Ox. (Definitions of species families and methods for
16 constructing families are discussed in Jacobson (1999) and references therein.) Other families including
17 N-containing species used later in this chapter are
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NOZ = ^HNO2 + HNO4 + NO, + 2NO2O5 + PAN(CH,CHO -OO-NO2)
other organic nitrates + halogen nitrates + participate nitrates
and
NOY = NOX + NOZ + MONO.
and
HOX=OH+HO2
I NOZ refers to the sum of all oxidation products of NOX, but not the original NO and NO2.
2 The reaction of NO2 with O3 leads to the formation of NO3
Reaction 9
3 However, NO3 reacts rapidly, having a T of ~5 s during the photochemically most active period of the day
4 near local solar noon, by two pathways (Atkinson, 1992)
NOi + hv -
~J A*\^J. IS / \J f
Reaction 10
NO3 + hv -* NO2 + O(3P)(900/<))
Reaction 11
5 Because of this, NO3 concentrations remain low during daylight hours but can increase after sunset
6 to nighttime concentrations of 5 * 107 to 1 x 1010 molecules/cm3 or 2 to 430 parts per trillion (ppt) over
7 continental areas influenced by anthropogenic emissions of NOX (Atkinson, 1986). At night, NO3, rather
8 than OH, is most often the primary oxidant in polluted tropospheric systems. Moreover, NO3 can combine
9 with NO2 to form dinitrogen pentoxide (N2O5)
NO3 + NO2 < M >N2O5
Reaction 12
10 and N2Os both photolyzes and thermally decomposes back to NO2 and NO3 during the day; however,
11 N2Os can accumulate during the night to ppb levels in polluted urban atmospheres.
12 The tropospheric chemical removal processes forNOx include reaction of NO2 with OH and
13 hydrolysis of N2O5 in aqueous aerosol solutions if there is no organic coating. Both of these reactions
14 produce HNO3
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OH + NO 2 ——
Reaction 13
N2O5 2 > 2HNO3
Reaction 14
1 The gas-phase reaction of OH with NO2 (Reaction 13) is one of the major and ultimate removal
2 processes for NOX in the troposphere. This reaction removes OH and NO2 in one step and competes with
3 HC for OH in areas characterized by high NOX concentrations such as urban centers. The T for conversion
4 of NOX to HNO3 in the PEL at 40 N latitude ranges from ~ 4 hours in July to ~ 16 hours in January. The
5 corresponding range in T at 25 N latitude is between 4 and 5 hours, while at 50 N latitude, HNOs T ranges
6 from about 4 to 20 hours (Martin, 2003).
7 In addition to gas-phase HNOs, Golden and Smith (2000) have shown on the basis of theoretical
8 studies that pernitrous acid (HOONO) is also produced by the reaction of NO2 and OH; however, this
9 production channel most likely represents a minor yield ~ 15% at the surface (Jet Propulsion Laboratory,
10 2003). Pernitrous acid will also thermally decompose and photolyze.
1 1 Gas-phase HNO3 formed from Reaction 13 and Reaction 14 undergoes wet and dry deposition to
12 the surface and uptake by ambient aerosol particles. In addition to uptake of HNO3 on particles and in
13 cloud drops, it photolyzes and reacts with OH
HNO3 + hv-*OH + NO 2
Reaction 15a
HNO3 + hv^O + HNO2
Reaction 15b
HNO3 + hv^H + NO3
Reaction 15c
14 and
HNO3 + OH^> NO3 + H2O
Reaction 16
15 (Margitan, 1982) established that Reaction 15a has a quantum yield of ~1, with only very small
16 contributions from the two other possible photolytic pathways. The T of HNOs with respect to these two
1 7 reactions is long enough for HNOs to act somewhat as a reservoir species for NOX during long-range
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1 transport, contributing in this way to NO2 levels in areas remote from the source region of the NOX that
2 formed this HNO3.
3 Geyer and Platt (2002) concluded that Reaction 14 constituted about 10% of the removal of NOX at
4 a site near Berlin, Germany during spring and summer. However, Dentener and Crutzen (1993) estimated
5 20% in summer and 80% of P(HNC>3) in winter. A modeling study by Tonnesen and Dennis (2000)
6 reported 16 to 31 % of summer HNOs production from Reaction 14. The importance of Reaction 14 could
7 be much higher during winter than during summer because of the much lower concentration of OH and
8 the enhanced stability of N2Os due to lower temperatures and UV flux. Recent work in the northeastern
9 U.S. indicates that this reaction proceeds at a faster rate in power plant plumes than in urban plumes
10 (Brown, 2006; Brown, 2006; Frost, 2006).
11 OH also reacts with NO to produce nitrous acid (HNO2).
OH+NO——
Reaction 17
12 In sunlight, HNO2 is rapidly photolyzed back to the original reactants.
HNO2 + hv -> OH + NO
Reaction 18
13 Reaction 17 is, however, a negligible source of HNO2, which is formed mainly by multiphase processes.
14 At night, heterogeneous reactions of NO2 in aerosols or at Earth's surface result in accumulation of HNO2
15 (Lammel, 1996; Jacob, 2000; Sakamaki, 1983; Pitts, 1984; Svensson, 1987; Jenkin, 1988; Lammel, 1988;
16 Notholt, 1992; Notholt, 1992; Harris, 1982), which can be a source of morning OH to drive P(O3).
17 HO2 can react with NO2 to produce pernitric acid (HNO4)
HO 2 + NO2 + M-> HNO4 + M
Reaction 19
18 which then can thermally decompose and photolyze back to its original reactants. The acids formed in
19 these gas-phase reactions are all water soluble; thus, they can be incorporated into cloud drops and in the
20 aqueous phase of particles.
21 A broad range of organic N compounds are directly emitted by combustion sources or formed in
22 the atmosphere from NOX emissions. Organic N compounds include the PANs, nitrosamines, nitro-PAHs,
23 and the more recently identified nitrated quinones. Oxidation of VOCs produces organic peroxy radicals
24 (RO2). Reaction of RO2 radicals with NO and NO2 produces RONO2 and peroxynitrates (RO2NO2)
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RO2 + NO — —
Reaction 20
RO2 + NO2 — -
Reaction 21
1 Reaction 20 is a minor branch for the reaction of RO2 with NO; the major branch produces RO and NO2,
2 as discussed in the next section. However, the RONO2 yield increases with carbon number (Atkinson,
3 2000).
4 The most important family of these organic nitrates is the PANs, the dominant member of the
5 broader family of peroxyacyl nitrates which includes peroxypropionyl nitrate (PPN) of anthropogenic
6 origin, and peroxymethacrylic nitrate (MPAN) produced from isoprene oxidation. The PANs are formed
7 by the combination reaction of acetyl peroxy radicals with NO2
CH3C(O)-OO + NO 2 -> CH3C(O}OONO2
Reaction 22
8 where the acetyl peroxy radicals are formed mainly during the oxidation of ethane (C2H6) along with
9 acetaldehyde. Acetaldehyde (CH3CHO) can be photolyzed or react with OH to yield acetyl radicals
CH3-C(O)H + hv^> CH3-C(O) + H
Reaction 23
CH3-C(O)H + OH^ CH3-C(O) + H2O
Reaction 24
10 Acetyl radicals then react with O2 to yield acetyl peroxy radicals.
CH3-C(O) + <92 + M-> CH3C(O)-OO + M
Reaction 25
11 However, acetyl peroxy radicals will react with NO in areas of high NO concentrations
CH3(CO)-OO + M? -» CH3(CO)-O + NO2
12 and the acetyl-oxy radicals will then decompose
Reaction 26
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CH3(CO)-O -> CH3 + CO2
Reaction 27
1 Thus, formation of PAN is favored at conditions of high ratios of NO2 to NO which are most typically
2 found under low total NOX conditions. The PANs both thermally decompose and photolyze back to their
3 reactants with T on the order of a few hours during warm sunlit conditions: T with respect to thermal
4 decomposition range from ~1 hour at 298 K, to -2.5 days at 273 K, up to several weeks at 250 K. Thus,
5 PANs can provide a reversible sink of NOX at cold temperatures and high solar zenith angles, allowing
6 release of NO2 as air masses warm. The PANs are also removed by uptake to vegetation (Sparks, 2003;
7 Teklemariam, 2004). RO2NO2 produced by Reaction 21 are thermally unstable and most have very short T
8 of < 100 s owing to thermal decomposition back to the original reactants. They are thus not effective
9 permanent sinks of NOX.
2.6.2.1. Oa Formation
10 O3 is unlike most other air pollution species whose rates of formation vary directly with the
11 emissions of their precursors in that P(O3) changes nonlinearly with the concentrations of its precursors.
12 At the low NOx concentrations found in most environments ranging from remote continental areas to
13 rural and suburban areas downwind of urban centers, net P(O3) increases with increasing NOxlevels. At
14 the high NOx concentrations found in downtown metropolitan areas especially near busy streets and
15 roadways and in power plant plumes, net destruction of O3 by titration reaction with NO dominates.
16 Between these two regimes is a transition stage in which P(O3) shows only a weak dependence on NOx.
17 In the high NOx concentration regime, NO2 scavenges OH (Reaction 13) which would otherwise oxidize
18 VOCs to produce HO2, which in turn would oxidize NO to NO2 (Reaction 7). In the low NOX
19 concentration regime, VOC oxidation generates, or at least does not consume, free radicals, and P(O3)
20 varies directly with NOX levels. Sometimes the terms "VOC-limited" and "NOx-limited" are used to
21 describe these two regimes; also, the terms NOx-limited and NOx-saturated are used (e.g.,, Jaegle, 2001).
22 OH chemistry initiates HC oxidation and behaves similarly to that for O3 with respect to NOX
23 concentrations (Hameed, 1979; Pinto, 1993; Poppe, 1993; Zimmermann, 1993). These considerations
24 introduce a high degree of uncertainty into attempts to relate changes in O3 concentration to emissions of
25 precursors. Note that in a NOx-limited or NOx-sensitive regime, P(O3) is not insensitive to radical
26 production or the flux of solar UV photons; rather, P(O3) is more sensitive to the NOX concentrations. For
27 example, global tropospheric O3 is sensitive to CH4, even though the troposphere is predominantly NOx-
28 limited.
29 Various analytical techniques have been proposed that use ambient NOx and VOC measurements
30 to derive information about P(O3) and particular instantiations of this O3-NOx-VOC sensitivity. The
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1 National Research Council (NRC) (NRC, 1992); previously suggested that P(O3) in individual urban
2 areas could be understood in terms of measurements of ambient NOX and VOC during the early morning.
3 With this approach, the summed VOC-to-NOx unweighted by chemical reactivity is used to determine
4 whether conditions are NOx sensitive or VOC sensitive. However, the technique is inadequate to
5 characterize P(O3) because it omits many factors important for P(O3), including: (1) the effect of biogenic
6 VOCs, because they are mostly absent during early morning hours; 2) important individual differences in
7 the ability of VOCs to generate free radicals, rather than just from total VOC, and other differences in
8 Os-forming potential for individual VOCs (Carter, 1995); 3) the effect of multiday transport; and (4)
9 general changes in photochemistry as air moves downwind from urban areas (Milford et al., 1994).
10 Jacob et al. (1995) used a combination of field measurements and a CTM to show that P(O3)
11 changed from NOx-limited to NOx-saturated as seasons changed from summer to fall at a monitoring site
12 in Shenandoah National Park, VA. Photochemical P(O3) generally occurs together with production of
13 other species including HNO3, RONO2, and hydrogen peroxide (H2O2). The relative rates of P(O3) and
14 the production of these other species vary depending on photochemical conditions and can be used to
15 provide information about particular O3 precursor sensitivities.
16 The transition stage between NOx-limited and NOx-saturated is not clearly demarcated with regard
17 to NOX concentrations, but is highly spatially and temporally heterogeneous. In the upper troposphere,
18 responses to NOX additions from commercial aircraft have been found which are very similar to these in
19 the lower troposphere. Briihl et al. (2000) found that the NOX concentrations for determining net P(O3) or
20 destruction are highly sensitive to the radical sources included in model calculations. Inclusion of only
21 CH4 and CO oxidation led to a decrease in net P(O3) in the North Atlantic flight corridor due to NO
22 emissions from aircraft. However, inclusion of acetone photolysis shifted the maximal P(O3) to higher
23 NOX concentrations, thereby reducing or eliminating areas in which P(O3) rates decreased due to the
24 aircraft NOX emissions.
25 Trainer et al. (1993) suggested that the slope of the regression line between O3 concentration and
26 NOZ concentration can be used to estimate the rate of P(O3) per NOX consumed; this relationship is also
27 known as the O3 production efficiency (OPE). Ryerson et al. (1998;, 2001) used measured correlations
28 between O3 and NOZ to identify different rates of O3 production in plumes from large point sources.
29 These relationships were further characterized and tested against surface concentrations with predictions
30 from a large-scale Eulerian air quality model by Dennis et al. (2001), and Arnold, et al. (2003).
31 Sillman (1995) and Sillman and He (2002) identified several secondary reaction products that show
32 different correlation patterns for NOx-limited conditions and NOx-saturated conditions. The most
33 important correlations are for O3 versus NOY, O3 versus NOZ, O3 versus HNO3, and H2O2 versus HNO3.
34 The correlations between O and NOy, and O3 and NOZ are especially important because measurements of
35 NOy concentrations are more widely available than of other species. Ratios of measured O3 versus NOZ
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1 shown in Figure 2-17 have distinctly different patterns in different locations. In rural areas and in smaller
2 urban areas such as Nashville, TN, O3 shows a strong correlation with NOZ concentrations and a
3 relatively steep slope to the regression line. By contrast, in Los Angeles O3 concentration also increased
4 with NOz, but the rate of increase was lower and the O3 concentration for a given NOz concentration was
5 generally lower. The heterogeneity of these patterns was tested in surface data at several special research
6 sites in the southeastern U.S. and with predictions from U.S. EPA's CMAQ modeling system (Arnold,
7 2001;, 2003).
250
S3
a.
a.
200
150
100
Figure 2-17. Measured values of Os
and NOz (NOY - NOX). Measured
during the afternoon at rural sites in
the eastern U.S. (gray circles) and
in urban areas and urban plumes
associated with Nashville, TN (gray
dashes), Paris, FR (black diamonds)
and Los Angeles, CA (Xs).
NOZ (ppb)
8 The difference between NOx-limited and NOx-saturated regimes is also reflected in measurements
9 of H2O2 concentrations. P(H2O2) takes place by self-reaction of photochemically generated HO2 so H2O2
10 concentrations show a strong seasonal variance with values > 1 ppb limited mainly to summer months
11 when photochemistry is most active (Kleinman, 1991). H2O2 is produced in abundance only when O3 is
12 produced under NOx-limited conditions; when the photochemistry is NOx-saturated, much less H2O2 is
13 produced, owing to decreased availability of free HO2 to self-combine. In addition, increasing NOX
14 concentrations tend to slow P(H2O2) under NOx-limited conditions. Differences between these two
15 regimes are also related to the preferential P(SO4) 2~ during summer and to inhibition of SO42 and H2O2
16 production during winter (Stein, 2003). Measurements in the rural eastern U.S. (Jacob, 1995), in
17 Nashville (Sillman, 1998), and in Los Angeles (Sakugawa, 1989) show large differences in H2O2
18 concentrations, likely due in part to differences in NOx availability at these locations. More details on
19 P(O3) are given in the ISA for NO^-Health Criteria (EPA, 2008a).
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2.6.2.2. Multiphase Interactions
1 Warneck (1999) constructed a box model describing the chemistry of the oxidation of NO2
2 including the interactions of N species and minor processes in sunlit cumulus clouds. The relative
3 contributions of different reactions to the oxidation of NO2 to NOs 10 min after cloud formation are given
4 in Table 2-3. Where the two columns show the relative contributions with and without transition metal
5 ions. Oxidation of NO2 as delineated in Table 2-3 occurs mainly in the gas phase within clouds, implying
6 that gas-phase oxidation of NO2 by OH predominates.
Table 2-3. Relative contributions of various gas and aqueous phase reactions to aqueous NOs
formation within a sunlit cloud, 10 minutes after cloud formation.
Reaction
% of Total3
% of Total »
Gas Phase
OH + N02 + M
Aqueous Phase
N205g + H20
N03- + Cl-
N03- + S0#-
N03- + HCOO-
HN04 + SO#-
HOONO + N03"
03 + N02-
57.7
8.1
<0.1
0.7
0.6
31.9
0.8
<0.1
67.4
11.2
0.1
1.0
0.8
20.5
<0.1
<0.1
a In the absence of transition metals.
b In the presence of iron and copper ions.
Source: Adapted from Warneck (1999).
7 Recent laboratory studies on SO42 and organic aerosols indicate that the reaction probability
8 yN2O5 is in the range of 0.01 to 0.05 (Kane, 2001; Hallquist, 2003; Thornton, 2003). Tie et al. (2003)
9 found that a value of 0.04 in their global model gave the best simulation of observed NOX over the Arctic
10 in winter. Using aircraft measurements over the northeastern U.S., Brown et al. (Brown, 2006) found that
11 yN2O5 on the surfaces of particles depends strongly on their SO42 content. They found that yN2O5 was
12 highest (0.017) in regions where the aerosol SO42 concentration was highest and lower elsewhere
13 (< 0.0016). This result contrasts with that of Dentener and Crutzen (1993) who concluded that yN2O5
14 would be independent of aerosol composition based on a value for yN2O5 of 0.1, implying that the
15 heterogeneous hydrolysis of N2O5 would be saturated for typical ambient aerosol surface areas. The
16 importance of this reaction to tropospheric chemistry depends on the value of yN2Os. If it is 0.01 or lower,
17 loss of NOy and formation of pNOs becomes difficult to explain, especially during winter. A decrease in
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1 N2O5 concentration retards removal of NOX by leaving more NO2 available for reaction, and thus
2 increases P(O3).
3 Based on the consistency between measurements of NOY partitioning and gas-phase models, Jacob
4 (2000) considered it unlikely that HNO3 is recycled to NOx in the lower troposphere in significant
5 concentrations. However, only one of the reviewed studies (Schultz, 2000) was conducted in the marine
6 troposphere and none was conducted in the marine boundary layer (MBL). An investigation over the
7 equatorial Pacific reported discrepancies between observations and theory (Singh, 1996), which might be
8 explained by HNO3 recycling. It is important to recognize that both Schultz et al. (2000) and Singh et al.
9 (1996) involved aircraft sampling at altitude which, in the MBL, can significantly under-represent sea salt
10 aerosols and thus most total NO3 (defined to be HNO3 + pNO3) and large fractions of NOY in marine air
11 (see, Huebert, 1996). Consequently, some caution is warranted in interpreting constituent ratios and NOY
12 budgets based on these data.
13 Recent work in the Arctic has quantified significant photochemical recycling of total NO3 to NOX
14 and attendant perturbations of OH chemistry in snow (Honrath, 2000; Dibb, 2002; Domine, 2002) which
15 suggest the possibility that similar multiphase pathways could occur in aerosols. As mentioned above,
16 NO3 is photolytically reduced to NO2 (Zafiriou, 1979) in acidic sea salt solutions (Anastasio, 1999).
17 Further photolytic reduction of NO2 to NO (Zafiriou, 1979) could provide a possible mechanism for
18 HNO3 recycling. Early experiments reported production of NOX during the irradiation of artificial
19 seawater concentrates containing NO3 (Petriconi, 1972). Based on the above, HNO3 recycling in sea salt
20 aerosols is potentially important and warrants further investigation. Other possible recycling pathways
21 involving highly acidic aerosol solutions and soot are reviewed by Jacob (2000).
22 Stemmler et al. (2006) studied the photosensitized reduction of NO2 to HNO2 on humic acid films
23 using radiation in the UV-A through the visible spectral regions. They also found evidence for reduction
24 occurring in the dark, reactions which may occur involving surfaces containing partly oxidized aromatic
25 structures. For example, Simpson et al. (2006) found that aromatic compounds constituted -20% of
26 organic films coating windows in downtown Toronto. They calculated p(HNO2) rates compatible with
27 observations of high HNO2 concentrations in a variety of environments. The photolysis of HNO2 formed
28 this way could account for up to 60% of the integrated source of OH in the PEL. A combination of high
29 NO2 concentrations and surfaces of soil and buildings and other structures exposed to diesel exhaust
30 would then be conducive to P(HNO2) and, hence, to high OH concentrations.
31 Ammann et al. (1998) reported the efficient conversion of NO2 to HNO2 on fresh soot particles in
32 the presence of water, and suggested that interaction between NO2 and soot particles may account for
33 high concentrations of HNO2 observed in urban environments. Conversion of NO2 to HNO2 and the
3 4 subsequent photolysis of HNO2 to NO + OH (Reaction 18) would constitute a NOx catalyzed O3 sink
3 5 involving snow. High HNO2 levels can lead to the rapid rise in OH shortly after sunrise, accelerating
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1 photochemical smog formation. Prolonged exposure to ambient oxidizing agents appears to deactivate
2 this process. Broske et al. (2003) studied the interaction of NO2 on secondary organic aerosols and
3 concluded that the uptake coefficients were too low for this reaction to be an important source of HNO2 in
4 the troposphere.
5 Choi and Leu (1998) evaluated interactions of HNO3 on the model black carbon soot Degussa
6 FW2, graphite, hexane, and kerosene soot, finding that HNO3 decomposed to NO2 and H2O at higher
7 HNO3 surface coverages, i.e.,/>HNO3 = 10~4 Torr while none of the soot models used were reactive at
8 />HNO3 = 5 x 10~7 Torr or at temperatures below 220 K. They concluded that aircraft soot in the upper
9 troposphere and lower stratosphere was unlikely to decrease HNOs concentrations.
10 Heterogeneous production on soot at night is believed to be the mechanism by which HNO2
11 accumulates to provide an early morning source of HOX in high NOX environments (Harrison, 1996;
12 Jacob, 2000). HNO2 has been frequently observed to accumulate to levels of several ppb overnight, and
13 this has been attributed to soot chemistry (Harris, 1982; Calvert, 1994; Jacob, 2000).
14 Longfellow et al. (1999) observed formation of HNO2 when CIL,, propane, hexane, and kerosene
15 soot were exposed to NO2 and suggested that this reaction may account for some part of the unexplained
16 high levels of HNO2 observed in urban areas. However, without specific details of the surface area,
17 porosity, and amount of soot available for this reaction, reactive uptake values cannot be estimated
18 reliably. Longfellow, et al. (1999) noted that soot and NO2 are produced in close proximity during
19 combustion, and that large quantities of HNO2 have been observed in aircraft plumes.
20 Saathoff et al. (2001) studied the heterogeneous loss of NO2, HNO3, NO3/N2O5, HO2/HO2NO2 on
21 soot aerosol using a large aerosol chamber. Reaction periods of up to several days were monitored and
22 results used to fit a detailed model. Saathoff et al. (2001) derived reaction probabilities at 294 K and 50%
23 RH for NO2, NO3, HO2, and HO2NO2 deposition to soot, HNO3 reduction to NO2, and N2O5 hydrolysis.
24 When these probabilities were included in photochemical box model calculations of a 4-day smog event,
25 the only noteworthy influence of soot was a 10% reduction in the second day maximum O3 concentration
26 for a soot loading of 20 (ig/m3. Note that this loading is roughly a factor of 10 greater than any observed
27 black carbon loadings in U.S. urban areas, even during air pollution episodes.
28 Muiioz and Rossi (2002) conducted Knudsen cell studies of HNO3 uptake on black and grey
29 decane soot produced in lean and rich flames, respectively and observed HNO2 as the chief species
30 released following HNO3 uptake on gray soot, with NO and traces of NO2 from black soot. They
31 concluded that these reactions would have relevance only in special situations in urban settings where
32 soot and HNO3 are present in high concentrations simultaneously.
33 The biosphere also interacts with NOX through HC emissions and their subsequent reactions to
34 form multi-functional RONO2, of which isoprene nitrates are an important class. Isoprene reacts with OH
35 to form a radical that adds NO2 to form a hydroxyalkyl nitrate. The combination of OH and NO3
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1 functional groups makes these compounds especially soluble with low vapor pressures and they likely
2 deposit rapidly (Shepson, 1996; Treves, 2000). Many other unsaturated HCs react by analogous routes.
3 Observations at Harvard Forest show a substantial fraction of total NOY not accounted for by NO, NO2
4 and PAN, and attribute the missing fraction to RONO2 (Munger, 1998; Horii, 2006). Furthermore, the
5 total NOY flux there exceeds the sum of FŁNO3, NOX, and PAN, which implies that the RONO2 are a
6 substantial fraction of N deposition. Other observations that show evidence of hydoxyalkyl nitrates
7 include those of Grossenbacher et al. (2001) and Day et al. (2003).
8 HNO2 formation on vegetative surfaces at night has long been observed based on measurements of
9 positive gradients (Harrison, 1994). Surface reactions of NO2 enhanced by moisture have been proposed
10 to explain these results. Production was evident at sites with high ambient NO2 concentrations; at low
11 NO2 concentrations, uptake of HNO2 exceeded the source. Daytime observations of HNO2 when rapid
12 photolysis depletes ambient concentrations to very low levels implies large sources of photo-induced
13 HNO2 could be present at a variety of forested sites where measurements have been made. Emissions
14 rates ranging from 200-1800 ppt/h have been estimated (Zhou, 2003; Zhou, 2002), which are ~20 times
15 faster than all nighttime sources of HNO2 formation. Reliable estimates to extend this emissions rate
16 nationwide have not been made. Additional evidence of light-dependent reactions to produce HNO2
17 comes from discovery of a HNO2 artifact in pyrex sample inlet lines exposed to ambient light. Either
18 covering the inlet or washing it eliminated the HNO2 formation (Zhou, 2002). Similar reactions might
19 serve to explain observations of UV-dependent production of NOx in empty foliar cuvettes exposed to
20 ambient air (Hari, 2003; Raivonen, 2003).
21 Production of HNO2 in the dark is currently believed to occur via a heterogeneous reaction
22 involving NO2 on wet surfaces (Jenkin, 1988; Pitts, 1984; He, 2006; Sakamaki, 1983), with a mechanism
23 that is first-order in both NO2 and H2O (Kleffmann, 1998; Svensson, 1987) despite the stoichiometry.
24 However, the molecular pathway of the mechanism is still under debate. Jenkin et al. (1988) postulated a
25 H2O-NO2 water complex reacting with gas phase NO2 to produce HNO2, which is inconsistent with the
26 formation of an N2O4 intermediate leading to HNO2 as proposed by Finlayson-Pitts et al. (2003). Another
27 uncertainty is whether the reaction forming HNO2 is dependent on water vapor (Svensson, 1987; Stutz,
28 2004) or water adsorbed on surfaces (Kleffmann, 1998). Furthermore, the composition of the surface and
29 the available amount of surface or surface-to-volume ratio can significantly influence the HNO2
30 production rates (Kaiser, 1977; Kleffmann, 1998; Svensson, 1987), which may explain the difference in
31 the rates observed between laboratory and atmospheric measurements.
32 There is no consensus on a chemical mechanism for photo-induced HNO2 production. Photolysis
33 of HNO3 or NO3 absorbed on ice or in surface water films has been proposed (Honrath, 2002; Ramazan,
34 2004; Zhou, 2001; Zhou, 2003), but alternative pathways include NO2 interaction with organic surfaces
35 such as humic substances (George, 2005; Stemmler, 2006). Note that either NO3 photolysis or
August 2008 2-40 DRAFT-DO NOT QUOTE OR CITE
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1 heterogeneous reaction of NO2 are routes for recycling deposited NOX back to the atmosphere in an
2 active form. NO3 photolysis would return N that heretofore was considered irreversibly lost, while surface
3 reactions between NO2 and water films or organic molecules would decrease the effectiveness of
4 observed NO2 deposition if the HNO2 were re-emitted.
Halogen Chemistry
5 Four decades of observational data on O3 in the troposphere have revealed numerous anomalies not
6 easily explained by gas-phase HOX-NOX photochemistry. The best-known example is the dramatic
7 decrease in ground-level O3 during polar sunrise due to multiphase catalytic cycles involving inorganic Br
8 and Cl radicals (Barrie, 1988; Martinez, 1999; Foster, 2001). Other examples of anomalies in tropospheric
9 O3 at lower latitudes include O3 concentrations < 10 ppb in the MBL and overlying free troposphere (FT)
10 at times over large portions of the tropical Pacific (Kley, 1996) as well as post-sunrise O3 decreases over
11 the western subtropical Pacific Ocean (Nagao, 1999), the temperate Southern Ocean (Galbally, 2000), and
12 the tropical Indian Ocean (Dickerson, 1999). The observed O3 depletions in near-surface marine air are
13 generally consistent with the model-predicted volatilization of Br2, BrCl, and C12 from sea salt aerosols
14 through autocatalytic halogen "activation" mechanisms (see e.g., 1996; Von Glasow, 2002) involving
15 these aqueous-phase reactions
HOBr + Br- + H+ -> Br2 + H2O
Reaction 28
HOCL + Br- + //+-> BrCl + H2O
Reaction 29
HOC I + Cl- + //+-» C12 + H2O
Reaction 30
16 In polluted marine regions at night, the heterogeneous reaction
N2O5 + C7--> C1NO2 + NO3-
Reaction 31
17 may also be important (Finlayson-Pitts, 1989; Behnke, 1997; Erickson, 1999). Br2, BrCl, C12, and C1NO2
18 volatilize and photolyze in sunlight to produce atomic Br and Cl. The acidification of sea salt aerosol via
19 incorporation of HNO3 and other acid leads to volatilization of HC1 (Erickson, 1999)
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NO3-
Reaction 32
1 and the corresponding shift in phase partitioning can accelerate deposition flux to the surface of total
2 pNO3 (Russell, 2003; Fischer, 2006).
3 The set of N reactions with aerosol salts in marine atmospheres sketched briefly here was reviewed
4 in detail by De Haan et al. (De Haan, 1999). This chemistry remains important not only for halogen
5 cycling and atmospheric oxidation reactions (Andreae, 1997), but also because through them NO3 can be
6 shifted from gas-phase HNOs or from fine-mode aerosol after dissociation of NH4NO3, for example, to
7 coarse-mode particles, thereby enhancing the potential for local N deposition to coastal regions. The
8 actual areal extent of N deposition resulting from gas-to-particle NOs conversion, however, is a complex
9 function of local wind speeds, as shown by Pryor and S0rensen (2000): with moderate winds of 3.5-10
10 m/s, gas-phase HNOs Vd exceeded that of an average NaNOs particle, whereas at higher and lower wind
1 1 speeds the reverse was true. This means that as a result of gas-to-particle NO3 conversion, under
12 commonly moderate winds, less N would be deposited locally and more would be available for transport
1 3 and deposition in a larger area of extent.
14 In polluted coastal regions where HC1 from Reaction 33 often exceeds 1 ppb, significant additional
1 5 atomic CF is produced (Singh, 1988; Keene, 2007).
HC1 +OH -^Cl +H2O
Reaction 33
1 6 Following production, Br and Cl atoms catalytically destroy O3
X + O3 -» XO + O2
Reaction 34
HO2-*HOX+O2
Reaction 35
HOX+hv^OH
Reaction 36
where X = Br and Cl.
17
1 8 Formation of Br and Cl nitrates via
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XO + NO 2 -> XNO3
Reaction 37
1 and the subsequent reaction of XNO3 with sea salt and sulfate aerosols
XNO3 + H2O -> BOX + H+ + NO3-
Reaction 38
2 and
XNO3 + Y-^XY+ NO3-
Reaction 39
3 where Y = Cl, Br, or I accelerates conversion of NOX to pNO3 and thereby contributes indirectly to net O3
4 destruction (Sander, 1999; Vogt, 1999; Pszenny, 2004).
5 Most XNO3 reacts via Reaction 38 on sea salt whereas Reaction 39 is more important on pSO4.
6 Partitioning of HC1 on pSO4 following Henry's Law provides Cl for Reaction 39 to form BrCl. Product
7 NO3 from both Reaction 38 and Reaction 39 partitions with the gas-phase HNO3 following Henry's Law.
8 Because most aerosol size fractions in the MBL are near equilibrium with respect to HNO3 (Erickson,
9 1999; Keene, 2004), both pSO4 and sea salt aerosol can sustain the catalytic removal of NOx and re-
10 activation of Cl and Br with no detectable change in composition. The photolytic reduction of NO3 in sea
1 1 salt aerosol solutions recycles NOx to the gas phase (Pszenny, 2004). Halogen chemistry also affects O3
12 indirectly by altering OH-to-HO2 ratios through the steps of Reactions 33 through 34 (e.g.,, Stutz, 1999;
13 Bloss, 2005).
14 In addition to O3 destruction via Reaction 34, atomic Cl" oxidizes HCs primarily via H abstraction
15 to form HC1 vapor and organic products (Jobson, 1994; Pszenny, 2006). The enhanced supply of odd-H
16 radicals from HC oxidation leads to net P(O3) in the presence of sufficient NOX (Pszenny, 1993).
17 Available evidence suggests that Cl~ chemistry may be a significant net source for O3 in polluted coastal
1 8 urban air (Tanaka, 2003; e.g.,, Finley, 2006).
19 An analogous autocatalyic O3 destruction cycle involving multiphase I chemistry also operates in
20 the marine atmosphere (Alicke, 1999; Vogt, 1999; McFiggans, 2000; Ashworth, 2002). In this case, the
21 primary source of I is believed to be either photolysis of CH2I2, other I-containing gases (Carpenter, 1999;
22 Carpenter, 2003), or perhaps I2 (Saiz-Lopez, 2004; McFiggans, 2005; McFiggans, 2004) emitted by
23 micro-and macro flora. Sea salt and pSO4 provide substrates for multiphase reactions that sustain the
24 catalytic I-IO cycle. The reaction of IO with NO2 followed by uptake of INO3 into aerosols accelerates
25 conversion of NOx to pNO3, contributing to net O3 destruction and changing the deposition of N
26 compounds as described above.
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2.6.2.3. Nitro-PAH Formation
1 Nitro-PAHs are generated from incomplete combustion processes through electrophilic reactions of
2 PAHs in the presence of NO2 (International Agency for Research on Cancer (IARC) (1989), 1989; World
3 Health Organization (WHO), 2003 (2003); structures for example nitro-PAHs are shown in Figure 2-18.
4 Among combustion sources, diesel emissions have been identified as the major source of nitro-PAHs in
5 ambient air (Bezabeh, 2003; Gibson, 1983; Schuetzle, 1983; Tokiwa, 1986). Direct emissions of nitro-
6 PAHs in PM vary with type of fuel, vehicle maintenance, and ambient conditions.
2-nitronaphthalene 9-nitroanthracene
Figure 2-18. Structures of some nitro-PAHs.
2-nitrofluoranthene 6-nitrobenzo(a)pyrene
7 In addition to being directly emitted, nitro-PAHs are formed from both gas-phase and
8 heterogeneous reactions of PAHs with gaseous N pollutants (Arey, 1998; Arey, 1986; Perrini, 2005; Pitts,
9 1987; Sasaki, 1997; Zielinska, 1989). Different isomers of nitro-PAHs are formed through different
10 formation processes. For example, the most abundant nitro-PAH in diesel particles is 1-nitropyene (1NP),
11 followed by 3-nitrofluoranthene (3NF) and 8-nitrofluoranthene (8NF) (Bezabeh, 2003; Gibson, 1983;
12 Schuetzle, 1983; Tokiwa, 1986; Zielinska, 1989). However, in ambient particulate organic matter (POM),
13 2-nitrofluoranthene (2NF) is the dominant compound, followed by 1NP and 2-nitropyrene (2NP) (Arey,
14 1989; Arey, 1989; Bamford, 2003; Reisen, 2005), although 2NF and 2NP are not directly emitted from
15 primary combustion emissions. Reaction mechanisms for various nitro-PAH formation processes are
16 schematized in Figure 2-19.
17 The dominant process for the formation of nitro-PAHs in the atmosphere is gas-phase reaction of
18 PAHs with OH in the presence of NOX (Arey, 1986, 1998; Atkinson, 1994; Ramdahl, 1986; Sasaki,
19 1997). The postulated reaction mechanism of OH with PAHs involves addition of OH at the site of
20 highest electron density of the aromatic ring, for example, the 1-position for pyrene (PY) and the 3-
21 position for fluoranthene (FL), followed by addition of NO2 to the OH-PAH adduct and elimination of
22 water to form the nitroarenes (as in Figure 2-19) (Arey, 1986; Atkinson, 1990; Pitts, 1987). After
23 formation, nitro-PAHs with low vapor pressures (such as 2NF and 2NP) immediately migrate to particles
24 under ambient conditions (Fan, 1995; Feilberg, 1999). The second order rate-constants for the reactions of
25 OH with most PAHs range from 10~10 to 10~12/cm/molecule/s at 298 K with the yields ranging from -0.06
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1 to ~5% (Atkinson, 1994). 2NF and 2NP have been found to be the most abundant nitro-PAHs formed via
2 reactions of OH with gaseous PY and FL, respectively, in ambient air.
H OH
11
Figure 2-19. Formation of 2NP from the reaction
of OH with gaseous PY.
2NP
3 The concentrations for most nitro-PAHs found in ambient air are much lower than 1 pg/m3, except
4 NNs, 1NP, and 2NF, which can be present at several pg/m3. These concentrations are lower by as much as
5 a factor of 2 to 1000 than their parent PAHs; however, nitro-PAHs are much more toxic than PAHs
6 (Durant, 1996; Grosovsky, 1999; Salmeen, 1982; Tokiwa, 1998; Tokiwa, 1986), and are present on
7 particles with a mass median diameter < 0.1 (im, perhaps altering their delivery to susceptible organisms
8 in the environment.
9 Additional information on nitro-PAHs is included in Chapter 2 and Annex B of the latest ISA for
10 Oxides ofNO^-Human Health Criteria (EPA, 2008a).
2.6.3. SOx Chemistry
Gas phase oxidation of SO2 is initiated by the reaction
SO2 +OH
M
Reaction 40
12 followed by
+HO
2
SO + H2
Reaction 41
Reaction 42
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1 Because the saturation vapor pressure of H2SO4 is extremely low, it will be removed rapidly by
2 transfer to the aqueous phase of aerosol particles and cloud droplets. Depending on atmospheric
3 conditions and the concentrations of other ambient particles and gas-phase species that can participate in
4 new particle formation, it can also nucleate to form new particles. Rate coefficients for the reactions of
5 SC>2 with either HC>2 or NO3 (Jet Propulsion Laboratory, 2003) are too low to be significant.
6 SC>2 is chiefly but not exclusively primary in origin; it is also produced by the photochemical
7 oxidation of reduced sulfur compounds such as dimethyl sulfide (CH3-S-CH3), hydrogen sulfide (H2S),
8 carbon disulfide (€82), carbonyl sulfide (OCS), methyl mercaptan (CH3-S-H), and dimethyl disulfide
9 (CH3-S-S-CH3) which are all mainly biogenic in origin. Their sources are discussed in Section 2.3.2 just
10 above. Table 2-4 lists the atmospheric lifetimes of reduced sulfur species with respect to reaction with
11 various oxidants. Except for OCS, which is lost mainly by photolysis (r~6 months), these species are lost
12 mainly by reaction with OH and NO3.
13 Because OCS is relatively long-lived in the troposphere, it can be transported upwards into the
14 stratosphere.
15
16
17
18
19
Table 2-4. Atmospheric lifetimes of S02 and reduced sulfur species with respect to reaction with
OH, NOs, and Cl radicals.
S02
CH3-S-CH3
H2S
CS2
OCS
CH3-S-H
CH3-S-S-CH3
OH
kx1012
1.6
5.0
4.7
1.2
0.0019
33
230
T
7.2 d
2.3d
2.2 d
9.6 d
17y
8.4 h
1.2h
NOs
kx1012 T
NA
1.0 1.1-h
NA
< 0.0004 >116d
< 0.0001 >1.3y
0.89 1.2h
0.53 2.1-h
CL
kx1012
NA
400
74
< 0.004
< 0.0001
200
NA
T
29 d
157 d
Nr
Nr
58 d
1 Rate coefficients were taken from JPL Chemical Kinetics Evaluation No. 14 (Jet Propulsion Laboratory, 2003)
NA = Reaction rate coefficient not available.
OH = 1 x 106/cm
N03 = 2.5x108/cm
Cl= 1 x 103/cm
Nr = Rate coefficient too low to be relevant as an atmospheric loss mechanism. Rate coefficients were calculated at 298 K and 1 atmosphere.
Source: Seinfeld and Pandis (1998)
Crutzen (1976) proposed that its oxidation serves as the major source of SO42 in the stratospheric
Junge layer, (1961) during periods when volcanic plumes do not reach the stratosphere. However, the flux
of OCS into the stratosphere is probably not sufficient to maintain this stratospheric aerosol layer. Myhre
et al. (2004) proposed instead that SO2 transported upwards from the troposphere is the most likely source
since the upward flux of OCS is too small to sustain observed SO42 loadings in the Junge layer.
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1 In addition, in situ measurements of the isotopic composition of S do not match those of OCS (Leung,
2 2002).
3 Reaction with NO3 at night most likely represents the major loss process for DMS and methyl
4 mercaptan, although the mechanisms are not well understood. Initial attack by NO3 and OH" involves H
5 atom abstraction, with a smaller branch leading to OH" addition to the S atom. The OH" addition branch
6 increases in importance as temperatures decrease, becoming the major pathway below temperatures of
7 285 K (Ravishankara, 1997). The adduct may either decompose to form methanesulfonic acid (MSA) or
8 undergo further reactions in the main pathway to yield dimethyl sulfoxide (Barnes, 1991). Following H
9 atom abstraction from DMS, the main reaction products include MSA and SO2. The ratio of MSA to SO2
10 is strongly temperature dependent, varying from about 0.1 in tropical waters to about 0.4 in Antarctic
11 waters (Seinfeld, 1998). SO42 in excess of that expected from sea salt aerosols is related mainly to the
12 production of SO2 from the oxidation of DMS. These transformations among atmospheric S compounds
13 are summarized in Figure 2-20.
Source: Adapted from Berresheim et al. (1995).
Figure 2-20. Transformations of
sulfur compounds in the
atmosphere.
14
15
16
17
2.6.3.1. Multi-phase SOx Chemistry
The major S species in clouds are hydrogen sulfite (HSO3 ) and the sulfite ion (SO32 ). Both are
derived from the dissolution of SO2 in water, and are grouped together as S(IV); bisulfate ion (HSO4 )
and SO42 are grouped together as S(VI). The chief species capable of oxidizing S(IV) to S(VI) in cloud
water are O3, H2O2 or organic peroxides, OH", and ions of transition metals such as iron (Fe), manganese
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1 (Mn) and copper (Cu) in the presence of O2. The basic mechanism of the aqueous phase oxidation of SO2
2 has long been studied and can be found in numerous texts on atmospheric chemistry; see for example,
3 Seinfeld and Pandis (1998), Finlayson-Pitts and Pitts (1999, Jacob (1999, and Jacobson (2002). Following
4 Jacobson (2002, the steps involved in the aqueous phase oxidation of SO2 can be summarized as: (1)
5 dissolution of SO2
Reaction 43
6 and (2) formation and dissociation of H2SO3
SO2 (aq) + H2O(aq} O H2 SO3 O H+ + HSO3 '^>2H + + SO3 2-
Reaction 44
7 In the pH range commonly found in rainwater, pH 2 to 6, the most important reaction converting S(IV) to
8 S(VI) is
HSO3 ~ + H2O2 + H+ <^> SO4 2~ +H2O + 2H
9 as SO32 is much less abundant than HSO3 .
10 Another pathway to aqueous-phase oxidation of S(IV) is reaction with O3
HSO3~ + O3 + OfT^ SO42~ + H2O + O2
Reaction 45
Reaction 46
11 But while the gas-phase reaction of SO2 with O3 is slow, the rate coefficient for Reaction 46 in the
12 aqueous phase is rapid, and increases up to a value of ~5 x 10-3 with increasing pH between 1 and 3
13 (Finlayson-Pitts, 2000). Major pathways for the aqueous-phase oxidation of S(IV) to S(VI) as a function
14 of pH are shown in Figure 2-21.
15 For pH up to about 5.3, H2O2 is the dominant oxidant converting S(IV) to S(VI), while at pH > 5.3,
16 O3 becomes dominant, followed by Fe(III), using characteristic values found in Seinfeld and Pandis
17 (1998). However, differences in concentrations of oxidants result in differences in the pH at which this
18 transition occurs. It should also be noted that the oxidation of SO2 by O3 and O2 tends to be self-limiting:
19 as SO42 is formed, the pH decreases and the rates of these reactions decrease. Higher pH levels are
20 expected to be found mainly in marine aerosols. However, in marine aerosols, the CFcatalyzed oxidation
21 of S(IV) may be more important (Zhang, 1991; Hoppel, 2005). Because NH4+ is so effective in
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1 neutralizing acidity, it, too, affects the rate of oxidation of S(IV) to S(VI) and the rate of dissolution of
2 SO2 in particles and cloud droplets.
3
1CT6
10'8
10-10
10-1
10-1
10-16
10'1
Figure 2-21. Comparison of aqueous-phase
oxidation paths. The rate of conversion of S(IV)
to S(VI) is shown as a function of pH. Conditions
assumed are: [SCfyg)] = 5 ppb; [NCfyg)] = 1 ppb;
[H202(g)] = 1 ppb; [Osfaj] = 50 ppb; [Fe(lll)(aq)] = 0.3
2345
PH
4 A comparison of the relative rates of oxidation by gas and aqueous phase reactions by Warneck
5 (1999) indicates that on average only ~ 20% of SO2 is oxidized by gas-phase reactions; the remainder is
6 oxidized by aqueous phase reactions. Warneck's box model (1999) describing the chemistry of the
7 oxidation of SO2 and NO2 includes interactions of S species and minor processes in sunlit cumulus
8 clouds. The relative contributions of different reactions to the oxidation of S(IV) species to S(VI) 10 min
9 after cloud formation are given in Table 2-5. The two columns show the relative contributions with and
10 without transition metal ions. As can be seen from Table 2-5, SO2 within a cloud (gas + cloud drops) is
11 oxidized mainly by H2O2 in the aqueous phase, while and the gas-phase oxidation by OH is small by
12 comparison. A much smaller contribution in the aqueous phase is made by methyl hydroperoxide
13 (CH3OOH) because it is formed mainly in the gas phase and its Henry's Law constant is several orders of
14 magnitude smaller that of H2O2. After H2O2, HNO4 is the major contributor to S(IV) oxidation.
15 The values shown in Table 2-5 here and Table 2-3 above for NO3 indicate that gas-phase oxidation
16 accounts for only ~ 20% of SO2 oxidation but ~ 90% of NO2 oxidation.
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Table 2-5. Relative contributions of various reactions to the total S(IV) oxidation rate within a sunlit
cloud, 10 min after cloud formation.
Reaction
% of Total '
% of Total b
Gas Phase
OH + N02 + M
Aqueous Phase
I\l205g + H20
NOa + CI-
N03 + S032-
NOs + HCOO-
HN04 + S032-
HOONO + NOs-
03 + N02-
57.7
8.1
<0.1
0.7
0.6
31.9
0.8
<0.1
67.4
11.2
0.1
1.0
0.8
20.5
<0.1
0.1
a In the absence of transition metals.
b In the presence of iron and copper ions.
Source: Adapted from Warneck (1999).
1 In areas away from strong pollution sources, the SO2 T is ~7 days, based on measurements of the
2 rate constant for Reaction 41 (Jet Propulsion Laboratory, 2003) and a nominal OH concentration of
3 106/cm3. However, the mechanism of SO2 oxidation at a particular location depends on local
4 environmental conditions. For example, near stacks, oxidants such as OH are depleted and almost no SO2
5 is oxidized in the gas phase. Further downwind, as the plume is diluted with background air, the gas phase
6 oxidation of SO2 increases in importance. Finally, even further downwind when conditions in the plume
7 can become more oxidizing than in background air, the SO2 oxidation rate could exceed that in
8 background air. SO2 in the PEL is also removed from the atmosphere by dry deposition to moist surfaces,
9 resulting in an atmospheric T with respect to dry deposition of ~ 1 day to 1 week. Wet deposition of S
10 naturally depends on the variable nature of rainfall, but in general results in a T of SO2 ~7 days, too. These
11 two processes, oxidation and deposition, lead to an overall T of SO2 in the atmosphere of 3 to 4 days.
12 Multiphase chemical transformations involving inorganic halogenated compounds effect changes in
13 the multiphase cycling of SOX in ways analogous to their effects on NOX. Oxidation of dimethylsulfide
14 (CH3)2S by BrO produces dimethylsulfoxide (CH3)2SO (Barnes, 1991; Toumi, 1994), and oxidation by Cl
15 leads to formation of SO2 (Keene, 1996). (CH3)2SO and SO2 are precursors for methanesulfonic acid
16 (CH3SO3H) and H2SO4. In the MBL, virtually all H2SO4 and CH3SO3H vapor condenses onto existing
17 aerosols or cloud droplets, which subsequently evaporate, thereby contributing to aerosol growth and
18 acidification. Unlike CH3SO3H, H2SO4 also has the potential to produce new particles (Korhonen, 1999;
19 Kulmala, 2000), which in marine regions is thought to occur primarily in the FT.
20 Excepting H2SO4, inorganic particles are solid at low RH, and their composition determines their
21 deliquescence thresholds for forming saturated aqueous solutions. Crystallization is not simply the reverse
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1 of deliquescence but is a process subject to hysteresis; see the NaCl+Na2SO4 example in Figure 2-22, and
2 Tang and Munkelwitz (1993) for deliquescence RH points of other inorganic particles.
4.5
04.0
5 3.5
0>
O>
« 3.0
6
"> o c
82-5
5
J> 2.0
o
m
CL 1.5
1.0
• deliquescence i
o efflorescence /
predicted
measured
0.50 0.65 0.60 0.65 0.70 0.75
Relative Humidity
0.80
0.85
0.90
Source: Pandis, 2004, in McMurry et al., 2004.
Figure 2-22. Relative humidity (RH)
effects on deliquescence and
efflorescence points for a
NaCI+Na2$04 particle, indicating
deliquescence at ~72% RH and re-
crystallization at -52% RH. Points
are measurements from Tang
(1997); solid line is aerosol
thermodynamic model prediction of
(Ansari, 2000).
3 Particles with several components behave similarly to the example of Na2SO4 but with more
4 complex curves and generally have deliquescence RH points below these of their constituent components
5 (Wexler, 1991).
6 Saiz-Lopez et al. (2004) estimated that observed levels of BrO at Mace Head Atmospheric
7 Research Station in Ireland would oxidize (CH3)2S ~6 times faster than OH and thereby substantially
8 increase P(H2SO4) and other condensible S species in the MBL. SO2 is also scavenged by deliquesced
9 aerosols and oxidized to H2SC>4 in the aqueous phase by several strongly pH-dependent pathways
10 (Chameides, 1992; Keene, 1998; Vogt, 1996). Model calculations indicate that oxidation of S(IV) by O3
11 dominates in fresh, alkaline sea salt aerosols, whereas oxidation by hypohalous acids, primarily HOC1,
12 dominates in moderately acidic solutions. Additional non-sea salt (nss) pSC>4 is generated by SO2
13 oxidation in cloud droplets (Clegg, 1998). Ion-balance calculations indicate that most of the nss pSO4 in
14 short-lived sea salt size fractions accumulates in acidic aerosol solutions or in acidic aerosols processed
15 through clouds or both (e.g.,, Keene, 2004). The production, cycling, and associated radiative effects of S-
16 containing aerosols in marine and coastal air are regulated in part by chemical transformations involving
17 inorganic halogens (Von Glasow, 2002). These transformations include: dry-deposition fluxes of nss pSO4
18 in marine air dominated, naturally, by the sea salt size fractions (Huebert, 1996; Turekian, 2001) HC1
19 phase partitioning that regulates sea salt pH and associated pH-dependent pathways for S(IV) oxidation
20 (Keene, 2002; Pszenny, 2004) and potentially important oxidative reactions with reactive halogens for
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1 (CH3)2S and S(IV). However, both the absolute magnitudes and relative importance of these processes in
2 MBL S cycling are poorly understood.
3 Iodine chemistry has been linked to ultrafine particle bursts at Mace Head (O'Dowd, 2002;
4 O'Dowd, 1999). Observed bursts coincide with the elevated IO concentration and are characterized by
5 particle concentrations increasing from background levels to up to 300,000/cm3 on a time scale of seconds
6 to minutes. This newly identified source of marine aerosol would provide additional aerosol surface area
7 for condensation of SOx and thereby presumably diminish the potential for nucleation pathways
8 involving H2SO4. However, a subsequent investigation in polluted air along the New England, USA coast
9 found no correlation between periods of nanoparticle growth and corresponding concentrations of I
10 oxides (Fehsenfeld, 2006).
11
12
13
2.6.4. NHx Interactions
Figure 2-17 above illustrated the central role NH3 can play in the atmospheric chemistry of NOX
and SOx- This results in part from its being the most common soluble base in the atmosphere and a range
of chemical reactions. OH attack on NH3 proceeds by
NH3 + OH ->NH2 +H2O
= 1.6x
molec/cm/s
Reaction 47
Reaction 48
14 The fate of the NH2 radical is not known with certainty, but in polluted atmospheres can be
NH2 + O3 ->NH, NHO, NO
NH2 + NO2
NH2 + NO2 ->N2O + H2O
Reaction 49
Reaction 50
Reaction 51
15 However, with typical OH concentration of 1 to 2 x 106/cm3, the T of NH3 against the initial reaction is ~
16 30 to 70 days, sufficiently long that this is a small sink compared to NH3 uptake by cloud droplets where
17 it is reduced to NH4+
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NH3(g) + H2O <-> NH3-H2O(aq) <-> NH4 + OH
Reaction 52
1 Gas-phase NH3 also reacts with gas-phase FiNO3 to form particulate NH4NO3
NH3 + HNO3 <-> NH4NO3
Reaction 53
2 and with aqueous-phase H2SO4 to from particulate and aqueous-phase NH4HSO4 and (NFi4)2SO4
NH3(g) + H2SO4(l) ->NH4HSO4 (s,l)
Reaction 54
NH3(g) +NH4HSO4(l) -*(NH4)2SO4(s,l)
Reaction 55
3 These products are of special note because submicron pNH4HSO4 and (pNH4)2SO4 can act as
4 cloud condensation nuclei, but the H2SO4+H2O system does not readily undergo nucleation without
5 addition of NH4+ (Coffman, 1995; Kulmala, 2007). They are also of note because Reaction 53 and
6 Reaction 54 are not reversible under typical ambient conditions while Reaction 52 resulting in creation of
7 NH4NO3 is reversible. The pNO4NO3 is in a thermodynamic equilibrium with NH4+ and FiNO3 in the gas
8 phase such that lower temperatures shift the equilibrium toward greater production of pNH4NO3 and
9 away from the gas phase. Higher RH also shifts the equilibrium toward liquid-phase pNH4NO3. For these
10 reasons, and because gas-phase NH3 will neutralize SO42 preferentially first, pNH4NO3 can only form
11 when an excess of gas-phase NH3 first exists.
12 Along with HNO3 and H2SO4, NH3 can be limiting in the formation of secondary atmospheric
13 particles containing NO3 and SO42 . Measurements and thermodynamics models office and condensed-
14 phase precursors have been used to predict the limiting reactant under different atmospheric conditions
15 (Watson, 1994; Blanchard, 2000; Dennis, 2001). Figure 2-23 shows results from one application of this
16 technique from Blanchard et al. (2000) with isopleths of NO3 as predicted from total (gas and particulate
17 phase) HNO3 and NH3, with 25 ug/m3 SO42 and 2 ug/m3 total Cl. Formation of pNO3 is limited by total
18 NH3 availability but not HNO3 where isolines are vertical. NO3 exists predominately in the condensed
19 phase where isolines are horizontal, and formation is not limited by NH3 there. These relationships have
20 also been confirmed in field measurements like those reported for NO3 aloft in Arnold and Luke (2007).
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O)
o
o
O
80-
60-
40-
20-
-•= 0
0 10 20 30 40
Total Ammonia Concentration, jig/m3
Source: Adapted from Blanchard et al. (2000).
Figure 2-23. Predicted isolines of participate NOs
concentrations (ug/m3) as a function of total
HMOs and NH3 at 293 K and 80 percent relative
humidity, and with 25 ug/m3 S042" and 2 ug/m3
total Cl.
1 Changing RH and particle water content also changes the partitioning between gas and condensed
2 phases for semivolatile species like atmosphere NOs; see Figure 2-24 for the example of NH4NO3.
o
51
NH,(g) + HN03(g) » NH4NO3
35 40 45 50 55 60 65 70 75
Relative Humidity (%)
Source: Pandis, 2004, in McMurry et al., 2004.
Figure 2-24. Predicted particulate N03
concentration as a function of relative humidity
for a typical environment. Actual measured
values depend on aging characteristics of the
particle.
3 The phase partitioning of NH3 with deliquesced aerosol solutions is controlled primarily by the
4 thermodynamic properties of the system
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~[NH3aq\~[NH4+] +KW/[H+]
Reaction 56
1 where KH and Kb are the temperature-dependent Henry's Law and dissociation constants (62 M/atm) (1.8
2 x 1(T5 M), respectively, for NH3, and Kw is the ion product of water (1.0 x l(T14 M) (Chameides, 1984).
3 For a given NHX concentration, increasing aqueous concentrations of particulate FT will shift the
4 partitioning of NH3 towards the condensed phase. Consequently, under the more polluted conditions
5 characterized by higher pSO4 concentration, ratios of gaseous NH3 to particulate NH4+ decrease (Smith,
6 2007). It also follows that in marine air, where aerosol acidity varies substantially as a function of particle
7 size, NH3 partitions preferentially to the more acidic submicron size fractions (e.g., (Keene, 2004; Smith,
8 2007).
9 Because the dry Vd of gaseous NH3 to the surface is substantially greater than that for the
10 submicron pSO4 size factions with which most particulate NH4+ is associated, dry deposition fluxes of
11 total NH3 are dominated by the gas-phase fraction (Russell, 2003; Smith, 2007). Consequently,
12 partitioning with acidic pSO4 effectively increases the atmospheric lifetime of total NH3 against dry
13 deposition.
14 This shift has important consequences for NH3 cycling in the atmosphere and potential ecological
15 effects. In coastal New England during summer, air transported from rural eastern Canada contains
16 relatively low concentrations of nss pSO4 and total NH3 (Smith, 2007). Under these conditions, the
17 roughly equal partitioning of total NH3 between the gas and particulate phases sustains substantial dry
18 deposition fluxes of total NH3 with a median value of 10.7 (iM/m2/day to the coastal ocean. In contrast,
19 heavily polluted air transported from the industrialized midwestern U.S. contains median concentrations
20 of nss pSO4 and total NH3 a factor of ~3 greater. Under these conditions, > 85% of total NH3 partitions to
21 the acidic pSO4 size fractions and, consequently, the median dry-deposition flux of total NH3 is 30%
22 lower than that under the cleaner northerly flow regime. The relatively longer atmospheric T of total NH3
23 against dry deposition under more polluted conditions implies that, on average, total NH3 would
24 accumulate to higher atmospheric concentrations under these conditions and also be subject to
25 atmospheric transport over longer distances. Consequently, the importance of NHX removal via wet
26 deposition would also increase. Because of the inherently sporadic character of precipitation, greater
27 heterogeneity may exist in NH3 deposition fields and any potential biological responses downwind of
28 major S-emission regions.
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2.6.5. Transport-related Effects
1 Convective processes and small-scale turbulence transport pollutants both upward and downward
2 throughout the planetary boundary layer and the free troposphere. NOx, SOx, VOCs, and CO can be
3 transported vertically by convection into upper part of the mixed layer on one day, then transported
4 overnight as a layer of elevated mixing ratios, perhaps by a nocturnal low-level jet, and then entrained
5 into a growing convective boundary layer downwind and brought back to the surface.
6 Because NO and NO2 are only slightly soluble, they can be transported over longer distances in the
7 gas phase than can more soluble species which can be depleted by deposition to moist surfaces, or taken
8 up more readily on aqueous surfaces of particles. During transport, they can be transformed into reservoir
9 species such as HNO3, PANs, and N2O5. These species can then contribute to local NOX concentrations in
10 remote areas. For example, it is now well established that PAN decomposition provides a major source of
11 NOX in the remote troposphere (Staudt, 2003). PAN decomposition in subsiding air masses from Asia
12 over the eastern Pacific could make an important contribution to O3 and NOx enhancement in the U.S.
13 (Kotchenruther, 2001; Hudman, 2004). Further details about mechanisms for transporting O3 and its
14 precursors were described at length in O3 AQCD (2006).
15 Major episodes of high pollution concentrations in the eastern United Sates and in Europe are often
16 associated with slow moving high-pressure systems. High-pressure systems during the warmer seasons
17 are associated with subsidence, resulting in warm, generally cloudless conditions with light winds. The
18 subsidence results in stable conditions near the surface, which inhibit or reduce the vertical mixing of
19 NOX, SOX, VOCs and CO. Photochemical activity is enhanced because of higher temperatures and the
20 availability of sunlight.
21 However, it is becoming increasingly apparent that transport of O3 and NOX and VOC from distant
22 sources can provide significant contributions to local O3 concentrations even in areas where there is
23 substantial photochemical production. A number of transport phenomena occur either in the upper
24 boundary layer or in the FT which can contribute to high O3 concentrations at the surface. These
25 phenomena include stratospheric-tropospheric exchange (STE), deep and shallow convection, low-level
26 jets, and the so-called "conveyor belts" that serve to characterize flows around frontal systems.
27 Crutzen and Gidel (1983), Gidel (1983), and Chatfield and Crutzen (1984) hypothesized that
28 convective clouds played an important role in rapid atmospheric vertical transport of trace species and
29 first tested simple parameterizations of convective transport in atmospheric chemical models. At nearly
30 the same time, evidence was shown of venting the boundary layer by shallow, fair weather cumulus
31 clouds (e.g.,, Greenhut, 1986; Greenhut, 1984). Field experiments were conducted in 1985 which resulted
32 in verification of the hypothesis that deep convective clouds are instrumental in atmospheric transport of
33 trace constituents (Dickerson, 1987). Once pollutants are lofted to the middle and upper troposphere, they
34 typically have a much longer chemical T and with the generally stronger winds at these altitudes, they can
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1 be transported large distances from their source regions. Transport of NOX from the boundary layer to the
2 upper troposphere by convection tends to dilute concentrations and extend the NOX i from less than 24
3 hours to several days. Photochemical reactions occur during this long-range transport. Pickering et al.
4 (1990) demonstrated that venting of boundary layer NOx by convective clouds (both shallow and deep)
5 causes enhanced P(O3) in the FT. NOx at the surface can often increase P(O3) efficiency. Therefore,
6 convection aids in the transformation of local pollution into a contribution to global atmospheric
7 pollution. Downdrafts within thunderstorms tend to bring air with less NOx from the middle troposphere
8 into the boundary layer. Lightning produces NO which is directly injected chiefly into the middle and
9 upper troposphere. As described in Section 2.2.2.4 the total global production of NO by lightning remains
10 uncertain, but is on the order of 10% of the total.
11 The first unequivocal observations of deep convective transport of boundary layer pollutants to the
12 upper troposphere were documented by Dickerson et al. (1987). Instrumentation aboard three research
13 aircraft measured CO, O3, NO, NOX, NOY, and HCs in the vicinity of an active mesoscale convective
14 system near the border of Oklahoma and Arkansas during the 1985 PRE-STORM experiment. Anvil
15 penetrations about two hours after maturity found greatly enhanced mixing ratios inside the cloud of all of
16 the aforementioned species compared with outside it. NO mixing ratios in the anvil averaged 3 to 4 ppb,
17 with individual 3-min observations reaching 6 ppb; boundary layer NOX was typically 1.5 ppb or less
18 outside the cloud. Therefore, the anvil observations represent a mixture of boundary layer NOX and NOX
19 contributed by lightning. Luke et al. (1992) summarized the air chemistry data from all 18 flights during
20 PRE-STORM by categorizing each case according to synoptic flow patterns. Storms in the maritime
21 tropical flow regime transported large amounts of CO, 0$, and NOy into the upper troposphere with the
22 midtroposphere remaining relatively clean. During frontal passages a combination of stratiform and
23 convective clouds mixed pollutants more uniformly into the middle and upper levels.
24 Prather and Jacob (1997) and Jaegle et al. (1997) noted that precursors of HOx are also transported
25 to the upper troposphere by deep convection, in addition to the primary pollutants. The HOX precursors of
26 most importance are water vapor, formaldehyde, H2O2, acetaldehyde, and acetone.
27 Over remote marine areas, the effects of deep convection on trace gas distributions differ from
28 those over moderately polluted continental regions. Chemical measurements taken by the NASA ER-2
29 aircraft during the Stratosphere-Troposphere Exchange Project (STEP) off the northern coast of Australia
30 show the influence of very deep convective events. Between 14.5 and 16.5 km on the February 2-3, 1987
31 flight, chemical profiles that included pronounced maxima in CO, water vapor, and CCN, and minima of
32 NOY, and O3 (Pickering, 1993). Trajectory analysis showed that these air parcels likely were transported
33 from convective cells 800-900 km upstream. Very low marine boundary layer mixing ratios of NOY and
34 O3 in this remote region were apparently transported upward in the convection. A similar result was noted
35 in Central Equatorial Pacific Experiment (CEPEX'; see, Kley, 1996) and in Indian Ocean Experiment
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1 (INDOEX; see (De Laat, 1999) where a series of ozonesonde ascents showed very low upper tropospheric
2 O3 following deep convection. It is likely that similar transport of low O3 concentrations tropical marine
3 boundary layer air to the upper troposphere occurs in thunderstorms along the east coast of Florida. Deep
4 convection occurs frequently over the tropical Pacific. Low O3 concentrations and low NOx convective
5 outflow likely will descend in the subsidence region of the subtropical eastern Pacific, leading to some of
6 the cleanest air that arrives at the west coast of the U.S.
7 The discussion above relates to the effects of specific convective events. Observations have also
8 been conducted by NASA aircraft in survey mode, in which the regional effects of many convective
9 events can be measured. The Subsonic Assessment Ozone and Nitrogen Oxides Experiment (SONEX)
10 field program in 1997 conducted primarily upper tropospheric measurements over the North Atlantic. The
11 regional effects of convection over North America and the Western Atlantic on upper tropospheric NOX
12 were pronounced (Crawford, 2000; Allen, 2000).
13 Thunderstorm clouds are optically very thick, and, therefore, have major effects on radiative fluxes
14 and photolysis rates. Madronich (1987) provided modeling estimates of the effects of clouds of various
15 optical depths on photolysis rates. In the upper portion of a thunderstorm anvil, photolysis is likely to be
16 enhanced by a factor of 2 or more due to multiple reflections off the ice crystals. In the lower portion and
17 beneath the cloud, photolysis is substantially decreased. With enhanced photolysis rates, the NO-to-NO2
18 ratio in the upper troposphere is driven to larger values than under clear-sky conditions.
19 Thunderstorm updraft regions, which contain copious amounts of water, are regions where efficient
20 scavenging of soluble species can occur (Balkanski, 1993). NO2 itself is not very soluble and therefore
21 wet scavenging is not a major removal process for it. However, a major NOx reservoir species, HNO3 is
22 extremely soluble. Very few direct field measurements of the amounts of specific trace gases that are
23 scavenged in storms are available. Pickering et al. (Pickering, 2001) used a combination of model
24 estimates of soluble species that did not include wet scavenging and observations of these species from
25 the upper tropospheric outflow region of a major line of convection observed near Fiji. Over 90% of the
26 NOX in the outflow air appeared to have been removed by the storm; about 50% of acetaldehyde and
27 about 80% of formaldehyde had been lost.
2.7. Sampling and Analysis Techniques
2.7.1. Methods for Relevant Gas-Phase N Species
28 Separate sections here on field-deployed measurement techniques focus on current methods and
29 promising new technologies so no attempt is made to cover development of these methods or methods no
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1 longer in widespread use. Rather, the descriptions in this chapter concern chiefly the Federal Reference
2 Methods and Federal Equivalent Methods (FRM and FEM, respectively). More detailed discussions of
3 the FRM, FEM, and other, newer methods including issues about their field use is found in (Clemitshaw,
4 2004; McClenny, 2000; Parrish, 2000;, 1996; EPA, 2008; Edgerton, 2006; Edgerton, 2007).
2.7.1.1. NO and N02
5 NO can be measured reliably using the principle of gas-phase chemiluminescence (CL) induced by
6 the reaction of NO with O3 at low pressure. Modern commercial NOX analyzers have sufficient sensitivity
7 and specificity for adequate measurement in urban and many rural locations (EPA, 1993; U.S.
8 Environmental Protection Agency, 2006). Research grade CL instruments have been compared under
9 realistic field conditions to spectroscopic instruments, and the results indicate that both methods are
10 reliable (at concentrations relevant to smog studies) to better than 15 percent with 95 percent confidence.
11 Response times are on the order of 60 s (e.g.,, Crosley, 1996). Near-source, urban, and rural and remote
12 concentrations of NO are routinely measured using CL. However, Cardelino and Chameides (2000)
13 reported that measured NO concentrations during the afternoon was frequently at or below the operational
14 limit of detection (LOD), ~1 ppb, of the regulatory NOX instruments even in large metropolitan regions
15 such as Washington, DC, Houston, TX, and New York, NY, where NOx concentrations from mobile
16 sources would be high.
17 The FRM for NO2 also makes use of this NO detection technique using a prerequisite step to
18 reduce NO2 to NO on the surface of a molybdenum oxide (MoOx) substrate heated to -340 EC. Because
19 the FRM monitor cannot detect NO2 directly, the NO2 level is determined as the difference between the
20 sample passed over the heated MoOx substrate (the NOX total) and the sample not so reduced (the NO
21 alone). Reduction of NO2 to NO on the MoOx substrate is not specific to NO2; hence, the CL analyzers
22 are subject to varying interferences produced by the presence in the sample of the other oxidized N
23 compounds (the NOz species shown in the outer box of Figure 2-15). This interference is often termed a
24 "positive artifact" in the NO2 concentration estimate, since the presence of NOz always results in an over-
25 estimate of the NO2 concentration in the reported measurement. This interference by NOz compounds has
26 long been known (Fehsenfeld, 1987; EPA, 2008; Steinbacher, 2007, 2006JD007971;, 2007;, 2007;
27 Rodgers, 1989; Crosley, 1996; Nunnermacker, 1998; Parrish, 2000; McClenny, 2002,. These studies have
28 relied on intercomparisons of measurements using the FRM and other techniques for measuring NO2. The
29 sensitivity of the FRM to potential interference by individual NOZ compounds is variable and also
30 depends in part on characteristics of individual monitors, such as the design of the instrument inlet, the
31 temperature and composition of the reducing substrate, and on the interactions of atmospheric species
32 with the reducing substrate. Only recently have attempts been made to systematically quantify the
33 magnitude and variability of the interference by NOZ species in ambient measurements of NO2. Dunlea
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1 et al. (2007;, 2007) found an average of-22% of ambient NO2 (~9 to 50 parts per billion [ppb])
2 measured in Mexico City was due to interference from NOZ compounds; that is to say, the actual NO2
3 concentration was -22% lower than what was reported at monitors using the difference technique.
4 Comparable levels of NO2 are found in many locations in the U.S., but the same comparison for distinct
5 places in the U.S. is difficult to make because significant uncertainty remains in determining the
6 concentrations of the higher oxidation NOz products since they are not routinely measured. Dunlea et al.
7 (2007;, 2007) compared NO2 measured using the conventional chemiluminescent instrument with other
8 (optical) techniques. The main sources of interference were HNOs and various organic nitrates (RONO2)
9 which can be converted to NO on the catalyst with varying rates of efficiency. In this study, the efficiency
10 of conversion on the catalyst — that is, how much of the compound introduced to the catalyst was
11 converted to NO — was estimated to be -38% for HNO3; for PAN, -95% and - 95% for other RONO2.
12 Peak interference (over-estimation) in the reported estimate of NO2 concentrations from the presence of
13 NOZ compounds of up to 50% was found during afternoon hours and was associated with O3 and NOZ
14 compounds such as HNO3 and the alkyl and multifunctional alkyl nitrates.
15 In a study in rural Switzerland, Steinbacher et al. (2007, 2006) compared measurements of NO2
16 continuously measured using a conventional NOX monitor and measurements in which NO2 was
17 photolyzed to NO. They found the conventional technique using catalytic reduction overestimated the
18 reported NO2 concentration using the photolytic technique on average by 10% during winter and 50%
19 during summer.
20 Another approach to estimating the measurement interference is to use model calculations in
21 conjunction with known data on the reduction efficiencies of NOz species on the MoOx converters as
22 described above. Lamsal et al. (2008) used the conversion efficiencies noted above along with output for
23 NOy species from the GEOS-Chem CTM to derive seasonal correction factors for the ambient monitoring
24 data across the U.S. These factors range from < 10% in winter in the East to > 80% in the West, with the
25 highest values found during summer in relatively unpopulated areas. Lamsal et al. (2008) also used these
26 corrected data to determine the feasibility of using satellite data to supplement ground based data.
27 However, the current generation of satellite monitors are in low earth orbit and so the NO2 values are
28 restricted to time of satellite overpass in early afternoon. Future generations of geostationary satellites are
29 planned that will obtain more continuous data across the U.S. throughout the day.
30 Calculations using CMAQ for the Mid-Atlantic region in a domain extending from Virginia to
31 southern New Jersey were made at much higher spatial resolution than the GEOS-Chem simulations (see
32 http://www.mde.state.md.us/Programs/AirPrograms/air_planning/index.asp). The daily average
33 interference for an episode during the summer of 2002 estimated using model-derived concentration
34 fields for NOz species and using the conversion efficiencies for NOz species given above, ranged from
35 -20% in Baltimore to -80% in Madison, VA. Highest values were found during the afternoon, when
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1 photochemical activity is highest and production and accumulation of the higher oxidized NOZ
2 compounds is greatest, and lowest values during the middle of the night when photochemistry stops. The
3 model calculations showed episode averages of the NOZ/NO2 ratio ranging from 0.26 to 3.6 in rural
4 Virginia; the highest ratios were in rural areas, and lowest were in urban centers closer to sources of fresh
5 NOx emissions. (The capabilities of three-dimensional CTMs such as GEOS-CHEM and CMAQ and
6 issues associated with their use are presented below.)
7 On the whole, the current method of determining ambient NOx and then reporting NO2
8 concentrations by subtraction of NO is subject to a consistently positive interference by NOx oxidation
9 products, chiefly HNOs and PAN as well as other oxidized N-containing compounds, though the
10 magnitude of this positive bias is largely unknown and can be changing rapidly. Measurements of these
11 higher-order oxidation products in urban areas are sparse. Concentrations of these oxidation products are
12 expected to peak in the afternoon because of the continued oxidation of NO2 emitted during the morning
13 rush hours and during conditions conducive to photochemistry in areas well downwind of sources,
14 particularly during summer.
15 Within the urban core of metropolitan areas, where many of the ambient monitors are sited close to
16 strong NOX sources such as motor vehicles on busy streets and highways, the positive artifacts due to the
17 NO2 oxidation products are much smaller on a relative basis, typically <.10%. Conversely, the positive
18 artifacts are larger in locations more distant from NOX sources where NO2 concentrations are lowest and
19 could exceed 50%. Therefore, variable, positive artifacts associated with measuring NO2 using the
20 Federal Reference Method (FRM) severely hamper its ability to serve as an accurate and precise indicator
21 of NO2 concentrations at the typical ambient levels generally encountered outside of urban cores where
22 they would be most relevant for environmental exposures.
23 NO has also been successfully measured in ambient air with direct spectroscopic methods; these
24 include two-photon laser-induced fluorescence (TPLIF), tunable diode laser absorption spectroscopy
25 (TDLAS), and two-tone frequency-modulated spectroscopy (TTFMS). These were reviewed thoroughly
26 in the 2008 NO2 ISA for human health. The spectroscopic methods demonstrate excellent sensitivity and
27 selectivity for NO with detection limits on the order of 10 ppt for integration times of 1 min.
28 Spectroscopic methods compare well with the CL method for NO in controlled laboratory air, ambient air,
29 and heavily polluted air (e.g.,, Walega, 1984; Kireev, 1999; Gregory, 1990). These spectroscopic methods
30 remain in the research arena due to their complexity, size, and cost, but are essential for demonstrating
31 that CL methods are reliable for monitoring NO concentrations involved in Q^ formation, from around 20
3 2 ppt to several hundred of ppb.
33 There are approaches to measuring NO2 not affected by the artifacts mentioned above. For
34 example, NO2 can be photolytically reduced to NO with an efficiency of-70% as used in the Steinbacher
35 et al. (2007, 2006 study. Ryerson et al. (2000) developed a gas-phase CL method using a photolytic
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1 converter based on a Hg lamp with increased radiant intensity in the region of peak NO2 photolysis (350
2 to 400 nm) and producing conversion efficiencies of 70% or more in less than 1 s. Metal halide lamps
3 with conversion efficiency of about 50% and accuracy on the order of 20% (Nakamura, 2003) have been
4 used. Because the converter produces little radiation at wavelengths less than 350 nm, interferences from
5 HNOs and PAN are minimal. This method requires additional development to ensure its cost effectiveness
6 and reliability for extensive field deployment. The relatively low and variable conversion efficiency of
7 this technique would necessitate more frequent calibration. Optical methods such as those using
8 differential optical absorption spectroscopy (DOAS) or laser induced fluorescence (LIF) are also
9 available. However, these particular methods are more expensive than either the FRM monitors or
10 photolytic reduction technique and require specialized expertise to operate. Moreover, the DOAS obtains
11 an area-integrated measurement rather than a point measurement. Cavity attenuated phase shift (CAPS)
12 monitors are an alternative optical approach that is potentially less costly than DOAS or LIF (Kebabian,
13 2007; Kebabian, 2007). However, this technique is not highly specific to NO2 and is subject to
14 interference by other species absorbing at 440 nm, such as the 1,2-dicarbonyl compounds. The extent of
15 this interference and the potential of the CAPS technique for extensive field deployment have not been
16 evaluated.
17 A DOAS system manufactured by OPSIS is designated as a FEM for measuring NO2. DOAS
18 systems can also be configured to measure NO, HONO, and NO3 radicals. Typical detection limits are 0.2
19 to 0.3 ppb for NO, 0.05 to 0.1 ppb forNO2, 0.05 to 0.1 ppb for HONO, and 0.001 to 0.002 ppb forNO3,
20 at path lengths of 0.2, 5, 5, and 10 km, respectively. The obvious advantage compared to fixed point
21 measurements is that concentrations relevant to a much larger area are obtained, especially if multiple
22 targets are used. At the same time, any microenvironmental artifacts are minimized over the long path
23 integration. However, comparisons to other measurements made at point not a real location are difficult.
24 A major limitation in this technique had involved inadequate knowledge of absorption cross sections.
25 Harder et al. (1997) conducted an experiment in rural Colorado involving simultaneous measurements of
26 NO2 by DOAS and by photolysis followed by chemiluminescence. They found differences of as much as
27 110% in clean air from the west, but for NO2 mixing ratios in excess of 300 ppt, the two methods agreed
28 to better than 10%. Stutz et al. (2000) cites two intercomparisons of note. NO was measured by DOAS,
29 by photolysis of NO2 followed by chemiluminescence, and by LIF during July 1999 as part of the SOS in
30 Nashville, TN. On average, the three methods agreed to within 2%, with some larger differences likely
31 caused by spatial variability over the DOAS path. In another study in Europe, and a multi-reflection set-
32 up over a 15 km path, negated the problem of spatial averaging here agreement with the CL detector
33 following photolytic conversion was excellent (slope = 1.006 ± 0.005; intercept = 0.036 ± 0.019; r = 0.99)
34 over a concentration range from about 0.2 to 20 ppb.
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1 The paucity of specific in situ NO2 measurements motivates the inference of ground level NO2
2 concentrations from satellite measurements of tropospheric NO2 columns. This prospect would take
3 advantage of the greater sensitivity of tropospheric NO2 columns to NOX in the lower troposphere than in
4 the upper troposphere as discussed earlier. Tropospheric NO2 columns show a strong correlation with in
5 situ NO2 measurements in northern Italy (Ordonez, 2006). Quantitative calculation of surface NO2
6 concentrations from a tropospheric NO2 column requires information on the relative vertical profile.
7 Comparison of vertical profiles of NO2 in a CTM (GEOS-Chem) versus in situ measurements over and
8 downwind of North America shows a high degree of consistency (Martin, 2004; Martin, 2006; Martin,
9 2004; Martin, 2006), suggesting that CTM could be used to infer the relationship between surface NO2
10 concentrations and satellite observations of the tropospheric NO2 column.
11 Table 2-6 contains an overview of the three satellite instruments that are used retrieve tropospheric
12 NO2 columns from measurements of solar backscatter. All three instruments are in polar sun-synchronous
13 orbits with global measurements in the late morning and early afternoon. The spatial resolution of the
14 measurement from SCIAMACHY is 7 times better than that from Ozone Monitoring Instrument
15 (GOME), and that from Ozone Monitoring Instrument (OMI) is 40 times better than that from GOME.
16 Figure 2-25 shows tropospheric NO2 columns retrieved from SCIAMACHY. Pronounced
17 enhancements are evident over major urban and industrial emissions. The high degree of spatial
18 heterogeneity over the southwestern U.S. provides empirical evidence that most of the tropospheric NO2
19 column is concentrated in the lower troposphere. Tropospheric NO2 columns are more sensitive to NOx
20 in the lower troposphere than in the upper troposphere (Martin, 2002). This sensitivity to NOx m the
21 lower troposphere is due to the factor of 25 decrease in the NO2 to-NO ratio from the surface to the upper
22 troposphere (Bradshaw, 1999) that is driven by the temperature dependence of the NO + Oj, reaction.
23 Martin et al. (2004) integrated in situ airborne measurements of NO2 and found that during summer the
24 lower mixed layer contains 75% of the tropospheric NO2 column over Houston and Nashville. However,
25 it should be noted that these measurements are also sensitive to surface albedo and aerosol loading.
Table 2-6. Satellite instruments used to retrieve tropospheric NCh columns.
Instrument
GOME
SCIAMACHY
OMI
Coverage
1995-2002
2002-
2004-
Typical U.S.
Measurement Time
10:30-1 1:30 AM
10:00-1 1:00 AM
12:45-1:45 PM
Typical Resolution (km)
320 x 40
30x60
13x24
Return Time (days)1
3
6
1
Instrument Overview
Burrows etal. (1999)
Bovensmann et al. (1999)
Level! et al. (2006)
1 Return time is reported here for cloud-free conditions. Note that due to precession of the satellite's orbit, return measurements are close to but not made over the same location. In
practice, clouds decrease observation frequency by a factor of 2.
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Table 2-7. Characteristics of principal airsheds for reduced-N deposition.
Watershed
Principal Red-N Airshed
Area (km2)
Red-N Area as % of
Ox-N Area
% Red-N Deposition Explained
by Airshed Emissions
Airshed NHs Emission as % of
E. North American Emissions
Chesapeake Bay
Pamlico Sound
Apalachee Bay
668,000
406,000
310,000
64%
61%
70%
55%
60%
45-50% est.
11%
6.8%
4.3%
345678
SCIAMACHYTropospheric NOL (1015 moleccm ~2)
Source: Martin etal. (2006).
Figure 2-25. Tropospheric NO? columns (molecules N02/cm2) retrieved from the SCIAMACHY
satellite instrument for 2004-2005.
2.7.1.2. NOY
1 Commercially available NOx monitors have been converted to NOy monitors by moving the
2 MoOx converter to interface directly with the sample inlet. Because of losses on inlet surfaces and
3 differences in the efficiency of reduction of NOz compounds on the heated MoOx substrate, NOx cannot
4 be considered as a universal surrogate for NOy. However, in settings close to relatively high-
5 concentration, fresh emissions like those during urban rush hour, most of the NOY is present as NOX.
6 Measurements of total NOY characterize the entire suite of oxidized N compounds to which humans are
7 exposed. Reliable measurements of NOY and NO2, especially at the low concentrations observed in many
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1 areas remote from sources are also crucial for evaluating the performance of three-dimensional, chemical
2 transport models of oxidant and acid production in the atmosphere.
3 Gold-catalyzed CO or H2 reduction or conversion on heated MoOx have been used to reduce total
4 NOy to NO before detection by CL (Fehsenfeld, 1987; Crosley, 1996). Both techniques offer generally
5 reliable measurements, with response times on the order of 60 s and a linear dynamic range demonstrated
6 in field intercomparisons from ~10 ppt to 10s of ppb. Under some conditions, hydrogen cyanide (HCN),
7 NH3, alkyl nitrates (RNO2), and acetonitrile (CH3CN) can be converted to NO; but at normal
8 concentrations and humidity, and when converter temperature is closely monitored, these are minor
9 interferants. Thermal decomposition followed by LIF has also been used for NOy detection. In field
10 comparisons, instruments based on these two principles generally showed good agreement (Day, 2002)
11 with experimental uncertainty estimated to be on the order of 15 to 30%.
2.7.1.3. HN03
12 A major issue to be considered when measuring NOX and NOY is the possibility that FŁNO3, a
13 major component of NOY, is sometimes lost in inlet tubes and not measured (Luke, 1998; Parrish, 2000).
14 This problem is especially critical if measured NOY is used to identify NOx-limited versus NOx-saturated
15 conditions. The problem is substantially alleviated although not necessarily completely solved by using
16 much shorter inlets on NOy monitors than on NOX monitors and by the use of surfaces less likely to take
17 up HNO3. The correlation between O3 and NOY differs for NOx-limited versus NOx-saturated locations,
18 but this difference is driven primarily by differences in the ratio of O3 to FINO3. If HNO3 were omitted
19 from the NOY measurements, then the measurements would represent a severely biased estimate and their
20 use would be problematic.
21 Accurate measurement of HNO3 has presented a long-standing analytical challenge. To understand
22 why, it is useful to consider the major factors that control HNO3 partitioning between the gas and
23 deliquesced-particulate phases in ambient air
fC K
HN03(g)^[HN03(aq)] ~[H+]+[N03-]
Reaction 57
24 where KH is the Henry's Law constant in M/atm and Ka is the acid dissociation constant in M. Thus, the
25 primary controls on HNO3 phase partitioning are its thermodynamic properties, aerosol liquid water
26 content (LWC), solution pH, and kinetics. Aerosol LWC and pH are controlled by the relative mix of
27 acids and bases in the system, the hygroscopic properties of condensed compounds, and meteorological
28 conditions, chiefly RH, temperature, and pressure.
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1 In the presence of chemically distinct aerosols of varying acidities (e.g., super-(im, predominantly
2 sea salt; and sub-(im, predominantly pSO4), HNO3 should partition preferentially to the less-acidic
3 particles, and observations are consistent with this (see. e.g.,, Huebert, 1996; Keene, 1998). The kinetics
4 of this phase partitioning are controlled by atmospheric concentrations of HNO3 vapor and pNO3, and the
5 size distribution and T of the particles against deposition. Sub-(im diameter aerosols typically equilibrate
6 with the gas phase in seconds to minutes while super-(im aerosols require hours to a day or more see, e.g.,
7 Meng and Seinfeld (1996) and Erickson et al. (1999). Consequently, smaller aerosol size fractions are
8 typically close to thermodynamic equilibrium with respect to HNO3, whereas larger size fractions, for
9 which T against deposition range from hours to a few days, are often undersaturated (e.g.,, Keene, 1998;
10 Erickson, 1999).
11 Methods used widely for measuring HNO3 include standard filterpacks configured with nylon or
12 alkaline-impregnated filters (see, e.g.,, Goldan, 1983; Bardwell, 1990), annular denuders like EPA method
13 IP-9, and standard mist chambers (e.g.,, Talbot, 1990). Samples from these instruments are typically
14 analyzed by ion chromatography. Intercomparisons of these measurement techniques by Hering et al.
15 (1988), Tanner et al. (1989), and Talbot et al. (1990) reported differences on the order of a factor of 2 or
16 more. In part, this variance is due to nonsystematic sampling error. When chemically distinct aerosols
17 with different pHs, for example, sea salt and pSO4, mix together on a bulk filter, the acidity of the bulk
18 mixture will be greater than that of the less-acidic aerosols with which most of the NO3 is associated.
19 This change in pH may cause the bulk mix to be supersaturated with respect to HNO3 leading to
20 volatilization and, thus, to a positive measurement bias in HNO3 sampled downstream. Alternatively,
21 when undersaturated super-(im size fractions like sea salt accumulate on a bulk filter and chemically
22 interact over time with HNO3 in the sample air stream, scavenging may lead to a negative bias in the
23 HNO3 sampled downstream. Because the magnitude of both effects will vary as functions of the overall
24 composition and thermodynamic state of the multiphase systems, the combined influence can cause net
25 positive or net negative measurement bias in data with unknown frequencies. Pressure drops across
26 particle filters can also lead to artifact volatilization and associated positive bias in HNO3 concentrations
27 measured downstream.
28 Recently, sensitive HNO3 measurements based on the principle of chemical ionization mass
29 spectroscopy (CIMS) have been reported; see, e.g., Huey et al. (1998), Mauldin et al. (1998), Furutani and
30 Akimoto (2002), and Neuman et al. (2002). The CIMS relies on selective formation of ions such as
31 SiF5~ • HNO3 or HSO4 • HNO3 followed by detection via mass spectroscopy. Two CIMS techniques and a
32 filter pack technique were intercompared in Boulder, CO (Fehsenfeld, 1998). Results indicated agreement
33 to within 15% between the two CIMS instruments and between the CIMS and filterpack methods under
34 relatively clean conditions with HNO3 mixing ratios between 50 and 400 ppt. In more polluted air, the
3 5 filterpack technique generally yielded higher values than the CIMS, suggesting that interactions between
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1 chemically distinct particles on bulk filters is a more important source of bias in polluted continental air.
2 Differences were also greater at lower temperature when pNO3 corresponded to relatively greater
3 fractions of total NO3.
4 Three semi-continuous methods for detecting HNO3 were tested against the annular denuder filter
5 pack (ADS) integrated collection technique at the Tampa Bay Regional Atmospheric Chemistry
6 Experiment (BRACE) Sydney research station ~20 km downwind of the Tampa, Florida, urban core
7 (Arnold, 2007). The semi-continuous instruments included: two slightly differing implementations of the
8 NOy-NOv* (total oxides of nitrogen minus that total denuded of HNO3) denuder difference technique,
9 one from the NOAA Air Resources Lab (ARL), and one from Atmospheric Research and Analysis, Inc.
10 (ARA); the parallel plate wet diffusion scrubber online ion chromatography technique from Texas Tech
11 University (TTU); and the chemical ionization mass spectrometer from the Georgia Institute of
12 Technology (GIT). Twelve hour ADS samples were collected by the University of South Florida (USF).
13 Results for 10 min samples computed from the various higher sampling frequencies of each semi-
14 continuous instrument showed good agreement (R2 > 0.7) for afternoon periods of the highest production
15 and accumulation of HNO3. Further, agreement was within ± 30% for these instruments even at HNO3
16 concentrations < 0.30 ppb. The USF ADS results were biased low, however, by 44%, on average,
17 compared to the corporate 12 h aggregated means from the semi-continuous methods, and by >600% for
18 the nighttime samples; ADS results were below the corporate mean maximum HNO3 concentration by
19 >30% as well. The four instruments using semi-continuous methods, by contrast, were all within 10% of
20 each other's 12 h mean mixing ratios. While only ARA employed a formal minimum detection limit at
21 0.050 ppb, error analysis with the other techniques established that at the same level of precision, TTU's
22 effective limit was approximately the same as ARA's and that ARL's limit was 0.030 ppb; analysis for
23 GIT showed no apparent effective limit at the levels of HNO3 encountered in this field study. The
24 importance of sample inlet height for HNO3 measurements was indirectly shown through comparison to
25 previous field work at this site when sample inlet heights ranged from 1.5-10 m and produced systematic
26 discrepancies in HNO3 concentrations correlated with height of more than a factor of 2.
2.7.1.4. Other Nitrates
27 Methods for sampling and analysis of RONO2 in the atmosphere have been reviewed by Parrish
28 and Fehsenfeld (2000). PAN, PPN, and MPAN are typically measured using a gas chromatograph
29 followed by electron capture detectors (GC-ECD) (see, e.g.,, Gaffhey, 1998), although other techniques
30 such as Fourrier Transform InfraRed (FTIR) analysis can also be used. Field measurements made using
31 GC-ECD have reported a total uncertainty of ±5 ppt + 15% (1998). Additional descriptions of specific
32 techniques for RONO2 and some of the issues involved with using data taken with them appear in Section
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1 2.10, accompanying descriptions of the methods used routinely to monitor ambient air concentrations and
2 deposition amounts of RONO2, and in the ISA for NOX—Health Criteria (EPA, 2008a).
2.7.1.5. NH3
3 Because NH3 plays a key role in the atmospheric chemistry of particle formation, several methods
4 have been developed for ambient and higher-level concentrations; see, for example, (Appel, 1988;
5 Allegrini, 1991; Genfa, 1989; Williams, 1992; Wyers, 1993; Mennen, 1996; Asman, 1998; Pryor, 2001;
6 Schwab, 2007; Fehsenfeld, 2002). Measurement of NH3 is made difficult by its chemistry, whereby it
7 forms strong H bonds with itself and water, and can be lost either partly reversibly (i.e., with hysteresis)
8 or irreversibly to many instrument surfaces. Moreoever, the range of atmospheric NH3 extends over 4 or 5
9 orders of magnitude. Because of these challenges, many NH3 techniques remain "research-grade" with
10 steep requirements of time, care, and technical experience. However, U.S. EPA has proposed to include
11 ambient NH3 measurements in its new National Core (NCore) monitoring network (EPA, 2005) and this
12 has motivated additional development and testing of NH3 monitors.
13 The U.S. EPA Environmental Technology Verification (ETV) Program's Advanced Monitoring
14 Systems (AMS) Center, has verified the performance of seven ambient NH3 monitors1 for use at confined
15 animal feeding operations (CAFOs). In collaboration with the U.S. Department of Agriculture (USDA),
16 the AMS Center verified the seven ambient NH3 monitors (see Table 2-8) in two phases of testing, each at
17 separate CAFOs. Phase I was conducted at a swine finishing farm, and Phase II was conducted at a cattle
18 feedlot. These sites were selected to provide realistic testing conditions and a wide range of NH3
19 concentrations. Table 2-9 summarizes some of the performance data for the individual technologies. (The
20 full verification reports can be found at http://www.epa.gov/nrmrl/std/etv/vt-ams.html under ambient NH3
21 sensors category.)
22 Ambient NH3 monitors utilize a wide range of analytical methods. These methods include direct
23 detection by spectroscopic techniques or indirect detection of NH3 using selective membrane permeation
24 with conductivity detection, catalytic conversion with CL detection, treatment with a chemical dopant
25 followed by ion mobility detection, or other techniques. Ambient NH3 monitors also can provide
26 specialized features that can be valuable in specific uses, such as long-term monitoring or determining
27 NH3 fluxes and emission rates.
28 For example, monitors that collect high-speed, sub-second response time NH3 concentration data
29 can be used with simultaneous three-dimensional windspeed and direction data to determine NH3 flux.
30 Alternatively, open-path monitors can be used to calculate emission rates from CAFOs, since these
31 monitors measure the average NH3 concentration over a 1 to 100 meter path. Some monitors also are
32 suitable for long-term monitoring, since they can be operated without user intervention for weeks at a
33 time.
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Table 2-8. Verified ambient NH3 monitors.
Technology Name
Description
Aerodyne Research, Inc. QC-TILDAS
Bruker Daltonics OPAG 22 Open-Path Gas
Analyzer
Molecular Analytics lonPro-IMSNHa Analyzer
Omnisens SA TGA310 NHb Analyzer
Pranalytica, Inc. NitroluxTM 1000 Ambient NHb
Analyzer
Mechatronics Instruments BV AiRRmonia NHb
Analyzer
Thermo Electron Corp. Model 17C NHb
Analyzer
An infrared laser spectrometer, based on pulsed quantum cascade laser technology; continuous measurement
A broadband, open-path, Fourier transform infrared spectrometer for remote sensing continuous measurement
An ion mobility spectrometer; continuous measurement
A trace gas analyzer that uses photoacoustic spectrometry; continuous measurement
A resonant photoacoustic spectrometer with a line-tunable C02 laser; continuous measurement
A single-point monitor composed of a membrane diffusion sampler, a detector block with a diffusion membrane, and two conductivity
cells; continuous measurement
A CL analyzer that uses NO and ozone (Oa) reactions; time-averaged measurement
Table 2-9. Performance characteristics of the 7 EPA ETV tested NHs methods.
Vendor3 Testing
A
B
C
D
E
F
G
Phase I &
Phase II
Phase I &
Phase II
Phase I &
Phase II
Phase II
Phase II
Phase II
Phase I &
Phase II
Average
Relative
Accuracy1"
3.7 to 10.5%
2.4 to 34%
10 to 44%
2.2%
18.3%
26%
4.7 to 10%
Relative
Precision1"
0.3%
0.7 to 2.1%
0.2 to 1.3%
0.9%
1.0%
1.8%
1.9 to 2.5%
Response
Time (95%)
3 to 76 min
8 to 20 min
1 to 32 min
2 to 2.6 min
2.5 to 17 min
4 to 14 sec
0.8 to 66 sec
Linearity
Slope Intercept
0.90 to 1.03 -24(0-0.6
1.02 to 1.28 -2.4 to 136
0.716to 1.25 -58.5to167
0.966 15.9
0.815 1.08
0.583 24.9
0.840 to 0.962 -8.8 to 35
Comparability0
r2
1.000
0.9957 to
0.9999
0.9854 to
0.9997
1.000
1.000
0.9144
0.9989to
0.9998
Slope
0.86to1.20
0.41to1.18
0.646to1.83
1.15
1.565
Not reported
0.984 to 1.09
Intercept
-0.5 to 16
-1.4 to 58
-6.7 to 21. 6
-4.1
-16.5
Not reported
-9.5 to 14.4
r2
0.984 to 0.990
0.538 to 0.9755
0.9794 to
0.9842
0.994
0.994
Not reported
0.9943to
0.9982
'" Because the ETV Program does not compare technologies, the performance results shown in this table do not identify the vendor associated with each result and are not in the same
order as the list of technologies in Table 2-8.
b A result of 0% indicates perfect accuracy or precision.
0 The comparability of the verified technology with a standard reference method was established by comparing the average NH3 sensors readings with time-integrated NHb samples
collected using citric-acid-coated denuders. The reference samples were collected based on procedures described in the EPA Compendium Method IO-4.2, Determination of Reactive
Acidic and Basic Gases and Acidity of Fine Particles (<2.5 urn). Comparability between the NHb sensors results and the reference method results with respect to ambient air was
assessed by linear regression using the reference method NHb concentrations as the independent variable and results from the NHb sensor as the dependent variable.
1 In addition to the elevation by EPA, ETV, a laboratory-based intercomparison of real-time ambient
2 NH3 instruments was conducted and reported by Schwab et al., (2007) with seven instruments using six
3 methods. The methods were these: the tunable diode laser (TDL) absorption spectrometer, the wet
4 scrubbing long-path absorption photometer (LOPAP), the wet effusive diffusion denuder (WEDD), the
5 ion mobility spectrometer (IMS), the Nitrolux laser acousto-optical absorption analyzer, and a modified
6 CL analyzer. Schwab et al. (2007) reported that all instruments performed well and agreed to within
7 -25% of the expected calibration value, with the exception of the CL analyzer which suffered from
8 problems related to its MoOx conversion of NOZ to NO. (Work with a modification of this technique has
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1 been continuing with the Aerosol Research Inhalation Epidemiology Study (ARIES); see Blanchard and
2 Hidy (2003).
3 Instrument response time is known to be a crucial feature for ambient NH3 measurements, and
4 Schwab et al. (2007) showed response time to be sensitive to measurement history as well as the sample
5 handling materials. Shortest response was for the TDL; the Nitrolux and IMS and WEDD instruments had
6 unacceptably long time responses under some environmental conditions which rendered correlations
7 across instruments meaningless. The TDL and LOPAP reported values closest to delivered concentration
8 values; the IMS exhibited bias of- +25%; the Nitrolux bias was —25%. Schwab et al. (2007) concluded
9 that sub-ppb ambient NH3 measurements can be taken reliably with some of these instruments, but that
10 special care must still be exercised to ensure high-quality data.
11 These and other recent intercomparisons of ambient NH3 instruments have confirmed that no single
12 technique has yet been identified for automated, fast-response, low-concentration, high-quality
13 continuous data.
2.7.2. Methods for Relevant Gas-phase S Species
14 Currently, ambient SO2 is measured using instruments based on pulsed fluorescence. The UV
15 fluorescence monitoring method for atmospheric SO2 was developed to improve upon the flame
16 photometric detection (FPD) method for SO2, which in turn had displaced the pararosaniline wet
17 chemical method for SO2 measurement. The pararosaniline method is still the FRM for atmospheric SO2,
18 but is rarely used because of its complexity and slow response, even in its automated forms. Both the UV
19 fluorescence and FPD methods are designated as FEMs by the EPA, but UV fluorescence has largely
20 supplanted the FPD approach because of the UV method's inherent linearity, sensitivity, and the absence
21 of consumables, such as the H gas needed for the FPD method.
22 The LOD for a non-trace-level SO2 analyzer is 10 ppb (CFR, 2006). However, most commercial
23 analyzers report operational detection limits of ~3 ppb. This concentration is very near the current
24 ambient annual average concentration of SO2 of ~4 ppb.
25 SO2 molecules absorb ultraviolet (UV) light at one wavelength and emit UV light at longer
26 wavelengths. This fluorescence involves excitation of the SO2 molecule to a higher energy (singlet)
27 electronic state. Once excited, the molecule decays non-radiatively to a lower energy electronic state from
28 which it then decays to the original, or ground, electronic state by emitting a photon of light at a longer
29 wavelength (i.e., lower energy) than the original, incident photon. The process can be summarized by the
30 following equations
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SO2 +hvj -»SO2*
SO2*-»SO2+hv2
Reaction 58
Reaction 59
1 where SC>2* represents the excited state of SC>2, hvi, and hv2 represent the energy of the excitation and
2 fluorescence photons, respectively, and hv2 < hvi. The intensity of the emitted light is proportional to the
3 number of SC>2 molecules in the sample gas. Additional information is found in the 2008 ISA for SO2
4 human health effects.
2.7.2.1. Positive Interference
5 Luke (1997) reported the positive artifacts of a modified pulsed fluorescence detector generated by
6 the co-existence of NO, €82, and a number of highly fluorescent aromatic HCs such as benzene, toluene,
7 o-xylene, m-xylene, p-xylene, m-ethyltoluene, ethylbenzene, and 1,2,4-trimethylbenzene. The positive
8 artifacts could be reduced by using a HC "kicker" membrane. At a flow rate of 300 standard cc/min and a
9 pressure drop of 645 torr across the kicker, the interference from ppm levels of many aromatic HCs was
10 eliminated entirely. More details appear in the ISA for SOX—Health Criteria (EPA, 2008b).
2.7.2.2. Negative Interference
11 Nonradiative deactivation (quenching) of excited SO2 molecules can occur from collisions with
12 common molecules in air, including N, O2, and water. During collisional quenching, the excited SO2
13 molecule transfers energy, kinetically allowing the SO2 molecule to return to the original lower energy
14 state without emitting a photon. Collisional quenching results in a decrease in the SO2 fluorescence and
15 results in the underestimation of SO2 concentration in the air sample. The concentrations of N2 and O2 are
16 constant in the ambient air, so quenching from those species at a surface site is also constant, but the
17 water vapor content of air can vary. Luke (1997) reported that the response of the detector could be
18 reduced by about 7% and 15% at water vapor mixing ratios of 1 and 1.5 mole percent (RH = 35 to 50% at
19 20-25 °C and 1 atm for a modified pulsed fluorescence detector (Thermo Environmental Instruments,
20 Model 43s). At very high SC>2 concentrations, reactions between electronically excited SC>2 and ground
21 state SC>2 to form SOj, and SO might occur (Calvert, 1978) However, this possibility has not been
22 examined.
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2.7.2.3. Other Methods
1 A more sensitive SO2 measurement method than the UV-fluorescence method was reported by
2 Thornton et al. (2002) using of an atmospheric pressure ionization mass spectrometer. The high
3 measurement precision and instrument sensitivity were achieved by adding isotopically labeled SO2
4 (34S16O2) continuously to the manifold as an internal standard. Field studies showed that the method
5 precision was belter than 10% and the limit of SO2 can be measured by LIF at around 220 nm (Matsumi,
6 2005). Because the laser wavelength is alternately tuned to an SO2 absorption peak at 220.6 and trough at
7 220.2 nm, and the difference signal at the two wavelengths is used to extract the SO2 concentration, the
8 technique eliminates interference from either absorption or fluorescence by other species and has high
9 sensitivity (5 ppt in 60 s).
10 SO2 can also be measured by the same DOAS instrument that can measure NO2. Photoacoustic
11 techniques have been employed for SO2 detection, but they generally have detection limits suitable only
12 for source monitoring (Gondal, 1997; Gondal, 2001).
13 CIMS techniques for SO2 have been shown to have high sensitivity, 10 ppt or better, with
14 uncertainty of-15% when a charcoal scrubber is used for zeroing and the sensitivity is measured with
15 isotopically labeled 34SO2 (Hanke, 2003; Hennigan, 2006; Huey, 2004).
2.7.3. Methods for Relevant Aerosol-phase N and S Species
16 SO42 is commonly present in PM2 5. Most PM2 5 samplers have a size-separation device to
17 separate particles so that only those particles approximately 2.5 (im or less are collected on the sample
18 filter. Air is drawn through the sample filter at a controlled flow rate by a pump located downstream of the
19 sample filter. The systems have two critical flow rate components for the capture of fine particulate:
20 (1) the flow of air through the sampler must be at a flow rate that ensures that the size cut at 2.5 (im
21 occurs; and (2) the flow rate must be optimized to capture the desired amount of particulate loading with
22 respect to the analytical method detection limits.
23 When using the system described above to collect pSO4 sampling artifacts can occur because of:
24 (1) positive sampling artifact for pSO4, NOs, and particulate ammonium due to chemical reaction; and (2)
25 negative sampling artifact for NOs and ammonium due to the decomposition and evaporation.
26 Several traditional and new methods could be used to quantify elemental S collected on filters:
27 energy dispersive X-ray fluorescence, synchrotron induced X-ray fluorescence, proton induced X-ray
28 emission (PIXE), total reflection X-ray fluorescence, and scanning electron microscopy. Energy
29 dispersive X-ray fluorescence (EDXRF) (Method IO-3.3, EPA, 1997; see 2004 PM CD for details) and
30 PIXE are the most commonly used methods. Since sample filters often contain very small amounts of
31 particle deposits, preference is given to methods that can accommodate small sample sizes and require
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1 little or no sample preparation or operator time after the samples are placed into the analyzer. X-ray
2 fluorescence (XRF) meets these needs and leaves the sample intact after analysis so it can be submitted
3 for additional examinations by other methods as needed. To obtain the greatest efficiency and sensitivity,
4 XRF typically places the filters in a vacuum which may cause volatile compounds (nitrates and organics)
5 to evaporate. As a result, species that can volatilize such as ammonium nitrate and certain organic
6 compounds can be lost during the analysis. The effects of this volatilization are important if the PTFE
7 filter is to be subjected to subsequent analyses of volatile species.
8 Polyatomic ions such as SO42 , NO3, and ammonium are quantified by methods such as ion
9 chromatography (1C) (an alternative method commonly used for ammonium analysis is automated
10 colorimetry). All ion analysis methods require a fraction of the filter to be extracted in deionized distilled
11 water for SO42 and NaCO3/NaHCO3 solution for NO3 and then filtered to remove insoluble residues
12 prior to analysis. The extraction volume should be as small as possible to avoid over-diluting the solution
13 and inhibiting the detection of the desired constituents at levels typical of those found in ambient PM2 5
14 samples.
15 Continuous methods for the quantification of aerosol sulfur compounds first remove gaseous sulfur
16 (e.g., SO2, H2S) from the sample stream by a diffusion tube denuder followed by the analysis of
17 particulate sulfur (Cobourn, 1978; Durham, 1978; Huntzicker, 1978; Mueller, 1980; Tanner, 1980).
18 Another approach is to measure total sulfur and gaseous sulfur separately by alternately removing
19 particles from the sample stream. Particulate sulfur is obtained as the difference between the total and
20 gaseous sulfur (Kittelson, 1978). The total sulfur content is measured by a flame photometric detector
21 (FPD) by introducing the sampling stream into a fuel-rich, hydrogen-air flame (e.g.,, Farwell, 1976;
22 Stevens, 1969) that reduces sulfur compounds and measures the intensity of the CL from electronically
23 excited sulfur molecules (S2*). Sensitivities for particulate sulfur as low as 0.1 (ig/m3, with time
24 resolution ranging from 1 to 30 min, have been reported. Continuous measurements of particulate sulfur
25 content have also been obtained by on-line XRF analysis with resolution of 30 min or less (Jaklevic,
26 1981). During a field-intercomparison study of five different sulfur instruments, Camp et al. (1982) four
27 out of five FPD systems agreed to within ± 5% during a 1-week sampling period.
28 There are two major PM speciation ambient air-monitoring networks in the U.S.: the Chemical
29 Speciation Network (CSN, which now includes the former Speciation Trends Network [STN]), and the
30 Interagency Monitoring of Protected Visual Environments (IMPROVE) network. The current CSN
31 samplers sample on a l-in-3 days cycle using three filters: (1) Teflon for equilibrated mass and elemental
32 analysis including elemental S; 2) a FiNO3-denuded nylon filter for ion analysis including NO3 and SO42 ,
33 (3) a quartz-fiber filter for elemental and organic carbon (EC and OC, respectively). The IMPROVE
34 sampler, which collects two 24-h samples per week, simultaneously collects one sample of PM10 on a
35 Teflon filter, and three samples of PM2 5 on Teflon, nylon, and quartz filters. PM2 5 mass concentrations
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1 are determined gravimetrically from the PM2 5 Teflon filter sample. The PM2 5 Teflon filter sample is also
2 used to determine concentrations of selected elements. The PM2 5 nylon filter sample, which is preceded
3 by a denuder to remove acidic gases, is analyzed to determine NO3 and pSO4 concentrations. Finally, the
4 PM2 5 quartz filter sample is analyzed for OC and EC using the thermal-optical reflectance (TOR) method
5 for IMPROVE and thermal-optical transmittance (TOT) for CSN, though this network is in a transition
6 stage to TOR.
7 In a side-by-side comparison of two of the chief aerosol monitoring techniques, PM2 5 mass and
8 major contributing species were moderately well correlated among the different methods with r > 0.8
9 (Hains, 2007). Agreement was good for total mass, SO42 , OC, total carbon (TC), and NH4+, while NO3
10 and black carbon (BC) showed less-good fits. Based on reported uncertainties, however, even daily
11 concentrations of PM2 5 mass and major contributing species were often significantly different at the 95%
12 confidence level. The CSN methods reported generally higher values of PM2 5 total mass and of
13 individual species than did the IMPROVE-like ones.
2.7.3.1. Artifacts
14 The reaction of SO2 and other acid gases with basic coarse particles on the filter leads to formation
15 of nonvolatile pSO4, pNO3, and Cl salts. These positive artifacts lead to the overestimates of the
16 concentrations of PM total mass and SO42 and likely NO3 as well. These problems were largely
17 overcome by changing to quartz fiber or Teflon filters and by the separate collection of the PM2 5 fraction.
18 However, the possible reaction of acidic gases with basic coarse particles remains a possibility, especially
19 with PM10 and PM10.2.5 measurements. These positive artifacts could be effectively eliminated by
20 removing acidic gases in the sampling line with denuders coated with NaCl or Na2CO3.
21 Positive sampling artifacts also occur during measurement of pNH4. The reaction of NH3 with
22 acidic particles
2NH3 + H2SO4 ->• (NH4)2SO4
Reaction 60
23 either during sampling or during transportation, storage, and equilibration could lead to an overestimation
24 of pNH4 concentrations. Techniques have been developed to overcome this problem, including using a
25 denuder coated with hydrofluoric, citric, or phosphoric acid to remove NH3 during sampling and to
26 protect the collected PM from NH3 (Suh, 1992; Suh, 1994; Brauer, 1991; Koutrakis, 1988; Koutrakis,
27 1988; Possanzini, 1999; Winberry, 1999; Keck, 2006). Positive artifacts for pNH4 can also develop during
28 sample handling due to contamination with NH3 emitted directly from human sweat, breath, and tobacco
29 smoking to form (NH4)2SO4 or NH4HSO4 if the filter is improperly handled (Sutton, 2000).
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1 Although pSO4 is relatively stable on a Teflon filter, it is now well known that volatilization losses
2 of pNO3 occur during sampling. For pNO3, the effect on the accuracy of atmospheric measurements from
3 these volatilization losses is more significant for PM2 5 than for PM10, partly because NO3 contributes a
4 smaller fraction to PMi0 and partly because NOX is present in a non-volatile form such as NaNO3, in the
5 coarse mode.
6 Sampling artifacts resulting from the loss of pNO3 species represents a significant problem in areas
7 such as southern California that experience high total NO3 loadings. Hering and Cass (1999) discussed
8 errors in PM2 5 mass measurements owing to the volatilization of pNO3 using data from two field
9 measurement campaigns conducted in southern California: (1) the Southern California Air Quality Study
10 (SCAQS) (Lawson, 1990); and (2) the 1986 California Institute of Technology (CalTech) study (Solomon,
11 1992). In both studies, side-by-side sampling of PM2 5 was conducted with one sampler collecting
12 particles directly onto a Teflon filter and a second using an MgO-coated denuder (Appel, 1981) to remove
13 gaseous HNO3, followed by a nylon filter to absorb the evaporating HNO3. In both studies, the PM2 5
14 mass lost from NH4NO3 volatilization represented a significant fraction of the total PM2 5 mass, and these
15 losses were greater during summer than fall: 17% (summer) versus 9% (fall) during SCAQS, and 21%
16 (summer) versus 13% (fall) during CalTech. With regard to percentage loss of pNO3, as contrasted to
17 percentage loss of mass discussed above, (Hering, 1999) found that the amount of pNO3 remaining on the
18 Teflon filter samples was, on average, 28% less than that on the HNO3-denuded nylon filters.
19 Hering and Cass (1999) also analyzed these data by extending the evaporative model developed by
20 Zhang and McMurry (1987). The extended model used by Hering and Cass (1999) takes into account the
21 dissociation of collected particulate ammonium nitrate on Teflon filters into HNO3 and NH3 via three
22 mechanisms: (1) the scrubbing of HNO3 and NH3 in the sampler inlet (John, 1988 showed that clean
23 PMio inlet surfaces serve as an effective denuder for HNO3; 2) the heating of the filter substrate above
24 ambient temperature by sampling; and (3) the pressure drop across the Teflon filter. For the sampling
25 systems modeled, the flow-induced pressure drop was measured to be less than 0.02 atm, and the
26 corresponding change in vapor pressure was 2%, so losses driven by pressure drop were not considered to
27 be significant in this work. Losses from Teflon filters were found to be higher during the summer than
28 during the winter, higher during the day compared to night, and reasonably consistent with modeled
29 predictions.
30 Finally, during the SCAQS (Lawson, 1990), particulate samples also were collected using a Berner
31 impactor and greased Tedlar substrates in size ranges from 0.05 to 10 (im in aerodynamic diameter. The
32 Berner impactor PM2 5 NO3 values were much closer to those from the denuded nylon filter than those
33 from the Teflon filter, the impactor NO3 values being ~2% lower than the nylon filter NO3 for the fall
34 measurements and ~7% lower for the summer measurements. When the impactor collection was
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1 compared to the Teflon filter collection for a nonvolatile species (sulfate), the results were in agreement.
2 Chang et al. (2000) discuss reasons for reduced loss of NO3 from impactors.
3 Brook and Dann (1999) observed much higher NO3 losses during a study in which they measured
4 particulate NO3 in Windsor and Hamilton, Ontario, Canada, by three techniques: (1) a single Teflon filter
5 in a dichotomous sampler, (2) the Teflon filter in an annular denuder system (ADS), and (3) total NO3
6 including both the Teflon filter and the nylon back-up filter from the ADS. The Teflon filter from the
7 dichotomous sampler averaged only 13% of the total NO3, whereas the Teflon filter from the ADS
8 averaged 46% of the total NO3. The authors concluded that considerable NO3 was lost from the
9 dichotomous sampler filters during handling, which included weighing and XRF measurement in a
10 vacuum.
11 Kim et al. (1999) also examined NO3-sampling artifacts by comparing denuded and non-denuded
12 quartz and nylon filters during the PM10 Technical Enhancement Program (PTEP) in the California South
13 Coast Air Basin. They observed negative NO3 losses for most measurements; however, for a significant
14 number of measurements, they observed positive NO3 artifacts. Kim et al. (1999) pointed out that random
15 measurement errors make it difficult to measure true amounts of NO3 loss.
16 Diffusion denuder samplers, developed primarily to measure particle strong acidity (Koutrakis,
17 1988; Koutrakis, 1992), also can be used to study NO3 volatilization. Measurements were made with two
18 versions of the Harvard-EPA Annular Denuder System (HEADS) for which HNO3 vapor was removed by
19 a Na2CO3-coated denuder and the remaining pNO3 was reported either as the sum of nonvolatile NO3
20 collected on a Teflon filter and volatized NO3 collected on a Na2CO3-coated filter downstream of the
21 Teflon filter (full HEADS), or on aNylon filter downstream of the Teflon filter (Nylon HEADS). The full
22 HEADS consistently underestimated the total pNO3 by -20% compared to the Nylon HEADS.
23 This comparison technique was then used to measure loss of pNO3 from Teflon filters in seven
24 U.S. cities. (Babich, 2000). Babich et al. (2000) found significant NO3 losses in Riverside, CA,
25 Philadelphia, PA, and Boston, MA, but not in Bakersfield, CA, Chicago, IL, Dallas, TX, or Phoenix, AZ,
26 where measurements were made only during winter.
27 Negative sampling artifacts due to decomposition and volatilization are also significant for pNH4
28 more often when it appears as N^NOs since (NH^SC^ is much more stable. The presence and
29 deposition of N^NOs is highly sensitive to environmental factors such as temperature, relative humidity,
30 acidity of aerosols, as well as to filter type (Spurny, 1999; Keck, 2005). Any change in these parameters
31 during the sampling period influences the position of the equilibrium between the particle and gas phases.
32 Keck and Wittmaack (2005) observed that at temperatures < 0 EC, acetate-NO3, quartz fiber, and Teflon
33 filters could properly collect pNH4, NH3, and Cl; but at temperatures > 0 EC, the salts were lost from
34 quartz fiber and Teflon filters, more so at higher temperatures and with no significant difference between
35 quartz fiber and Teflon filters. The salts were lost completely from denuded quartz fiber filters at
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1 temperatures above -20 EC, and from non-undenuded quartz fiber and Teflon filters at temperatures
2 above -25 EC. It is anticipated that current sampling techniques underestimate pMij levels due to
3 volatilization, but fine particle mass contains many acidic compounds, and, as consequence, a fraction of
4 volatilized NH4+ in the form of NH3 can be retained on the Teflon filter by reactions with them. Owing to
5 these positive and negative interference effects, the magnitude of pNH4 remains largely unknown.
6 However, techniques have been applied to pNH4 sampling to correct its concentrations due to evaporation
7 using a backup filter coated with hydrofluoric acid, citric acid, or phosphorous acid to absorb the
8 evaporated NH4 as NH3.
9 Volatile compounds can also leave the filter after sampling and prior to filter weighing or chemical
10 analysis. Losses of NO3, NH4, and Cl from glass and quartz-fiber filters that were stored in unsealed
11 containers at ambient air temperatures for 2 to 4 weeks prior to analysis exceeded 50% (Witz, 1990).
2.7.3.2. Other Methods
12 An integrated collection and vaporization cell was developed by Stolzenburg and Hering (2000)
13 that provides automated, 10-min resolution monitoring of fine-particulate NO3. In this system, particles
14 are collected by a humidified impaction process and analyzed in place by flash vaporization and CL
15 detection of the evolved NOX. In field tests in which the system was collocated with two FRM samplers,
16 the automated pNO3 sampler results followed the results from the FRM, but were offset lower. The
17 system also was collocated with a HEADS and a SASS speciation sampler (MetOne Instruments). In all
18 these tests, the automated sampler was well correlated to other samplers with slopes near 1, ranging from
19 0.95 for the FRM to 1.06 for the HEADS and correlation coefficients ranging from 0.94 to 0.996. During
20 the Northern Front Range Air Quality Study in Colorado (Watson, 1998), the automated pNO3 monitor
21 captured the 12-min variability in pNO3 concentrations with a precision of approximately ± 0.5 (ig/m3
22 (Chow, 1998). A comparison with denuded filter measurements followed by 1C analysis (Chow, 1999)
23 showed agreement within ±0.6 (ig/m3 for most of the measurements, but exhibited a discrepancy of a
24 factor of two for the periods of high pNO3 concentrations. More recent intercomparisons took place
25 during the 1997 Southern California Ozone Study (SCOS97) in Riverside, CA. Comparisons with 14 days
26 of 24-h denuder-filter sampling gave a correlation coefficient of R2 = 0.87 and showed no significant
27 bias. As currently configured, the system has a detection limit of 0.7 (ig/m3 and a precision of 0.2 (ig/m3.
28 The extent to which sampling artifacts for pNH4+ have been adequately addressed in the current
29 networks is not clear. Recently, new denuder-filter sampling systems have been developed to measure
30 pSO42~, pNO3, and pNH4+ with an adequate correction of NH/ sampling artifacts. The denuder-filter
31 system, Chembcomb Model 3500 speciation sampling cartridge developed by Rupprecht & Patashnick
32 Co, Inc. could be used to collect NO3, SO42 , and ammonium simultaneously. The sampling system
33 contains a single-nozzle size-selective inlet, two honeycomb denuders, the aerosol filter and two backup
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1 filters (Keck, 2005). The first denuder in the system is coated with 0.5% sodium carbonate and 1%
2 glycerol and collects acid gases such as HC1, SO2, HNO2, and HNO3. The second denuder is coated with
3 0.5% phosphoric acid in methanol for collecting NH3. Backup filters collect the gases behind denuded
4 filters. The backup filters are coated with the same solutions as the denuders. A similar system based on
5 the same principle was applied by Possanzini et al. (1999). The system contains two NaClcoated annular
6 denuders followed by other two denuders coated with NaCO3/glycerol and citric acid, respectively. This
7 configuration was adopted to remove HNO3 quantitatively on the first NaCl denuder. The third and forth
8 denuder remove SC>2 and NH3, respectively. A polyethylene cyclone and a two-stage filter holder
9 containing three filters is placed downstream of the denuders. Aerosol fine particles are collected on a
10 Teflon membrane. A backup nylon filter and a subsequent citric acid impregnated filter paper collect
11 dissociation products HNO3 and NH3 of Nlr^NOs evaporated from the filtered particulate matter.
2.8. Methods to Compute NOx and SOx Concentrations,
Chemical Interactions, and Deposition
2.8.1. CTMs
12 CTMs are the prime tools used to compute the interactions among NOX, SOX, other pollutants and
13 their precursors, the transport and transformation of air toxics, the production of secondary aerosols, the
14 evolution of the particle size distribution, and deposition of pollutants. CTMs are driven by emissions
15 inventories for primary species such as NOX, SOX, NH3, and primary PM, and by meteorological fields
16 produced by other numerical prediction models. Meteorological quantities such as winds and
17 temperatures are taken from operational analyses, reanalyses, or weather circulation models. In most
18 cases, these are off-line meteorological analyses, meaning that they are not modified by radiatively active
19 species generated by the air quality model (AQM).
20 Emissions of precursor compounds can be divided into anthropogenic and biogenic source
21 categories, and biogenic sources can be further divided into biotic (vegetation, microbes, animals) and
22 abiotic (biomass burning, lightning) categories as presented above. However, the distinction between
23 biogenic sources and anthropogenic sources is often difficult to make, as human activities affect directly
24 or indirectly emissions from what would have been considered biogenic sources during the preindustrial
25 era. Thus, emissions from plants and animals used in agriculture have been referred to as anthropogenic
26 or biogenic in different applications. Wildfire emissions may be considered to be biogenic, except that
27 forest management practices may have led to the buildup of fuels on the forest floor, thereby altering the
28 frequency and severity of forest fires.
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1 The initial conditions, or starting concentration fields of all species computed by a model, and the
2 boundary conditions, or concentrations of species along the horizontal and upper boundaries of the model
3 domain throughout the simulation, must be specified at the beginning of the simulation. Both initial and
4 boundary conditions can be estimated from models or data or, more generally, model+data hybrids.
5 Because data for vertical profiles of most species of interest are sparse, results of model simulations over
6 larger, usually global, domains are often used. As might be expected, the influence of boundary conditions
7 depends on the T of the species under consideration and the time scales for transport from the boundaries
8 to the interior of the model.
9 Each of the model components described above has associated uncertainties and the relative
10 importance of these uncertainties varies with the modeling application. The largest errors in
11 photochemical modeling are still thought to arise from the meteorological and emissions inputs to the
12 model (Russell, 2000). Within the model itself, horizontal advection algorithms are still thought to be
13 significant source of uncertainty (see e.g.,, Chock, 1994), though more recently, those errors are thought
14 to have been reduced (see e.g.,, Odman, 1996). There are also indications that problems with mass
15 conservation continue to be present in photochemical and meteorological models (see e.g.,, Odman, 1999)
16 and can result in significant simulation errors. The effects of errors in initial conditions can be minimized
17 by including several days spin-up time in a simulation to allow the model to be driven by emitted species
18 before the simulation of the period of interest begins.
19 While the effects of poorly specified boundary conditions propagate through the model's domain,
20 the effects of these errors remain undetermined. Because many meteorological processes occur on spatial
21 scales which are smaller than the model grid spacing (either horizontally or vertically) and thus are not
22 calculated explicitly, parameterizations of these processes must be used and these introduce additional
23 uncertainty.
24 Specific uncertainty also arises in modeling the chemistry of NOx transformations because they are
25 strongly nonlinear. Thus, the volume of the grid cell into which emissions are injected is important
26 because, for example, O3 production or loss depends in a complicated way on the concentrations of NOX
27 and OH as explained above. Use of ever-finer grid spacing allows more valid separations of regions of
28 high NOx concentrations from low NOx regions and from regions were NOx concentrations are optimal
29 for P(O3).
30 The use of grid spacing fine enough to resolve the chemistry in individual power-plant plumes is
31 too demanding of computer resources for this to be attempted in most simulations. Instead,
32 parameterizations of the effects of sub-grid-scale processes such as these must be developed, else serious
33 errors can result if emissions are allowed to mix through an excessively large grid volume before the
34 chemistry step in a model calculation is performed. In light of the significant differences between
35 atmospheric chemistry taking place within and outside of a power plant plume identified by Ryerson et al.
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1 (1998), inclusion of a separate module for treating large, tight plumes can be useful. Because the
2 photochemistry of NOX transformation is nonlinear, emissions correctly modeled in a tight plume may be
3 incorrectly modeled in a more dilute plume. Fortunately, it appears that the chemical mechanism used to
4 follow a plume's development need not be as detailed as that used to simulate the rest of the domain, as
5 the inorganic reactions are the most important in the plume (see e.g.,, Kumar, 1996).
6 Because the chemical production and loss terms in the continuity equations for individual species
7 are coupled, the chemical calculations must be performed iteratively until calculated concentrations
8 converge to within some preset criterion. The number of iterations and the convergence criteria chosen
9 also can introduce error.
10 CTMs have been developed for application over a wide range of spatial scales ranging up from
11 neighborhood to global. CTMs are used to: (1) obtain better understanding of the processes controlling
12 the formation, transport, and destruction of gas- and particle-phase criteria and hazardous air pollutants;
13 2) understand the relations between concentrations of secondary pollutant products and concentrations of
14 their precursors such as NOX and VOCs and the factors leading to acid deposition and possible damage to
15 biota; 3) understand relations among the concentration patterns of various pollutants that may exert
16 adverse effects; and (4) evaluate how changes in emissions propagate through the atmospheric system to
17 secondary products and deposition.
18 Global-scale CTMs are used to address issues associated with climate change and stratospheric O3
19 depletion, and to provide boundary conditions for the regional-scale models. The CTMs include
20 simplified mathematical descriptions of atmospheric transport, the transfer of solar radiation through the
21 atmosphere, chemical reactions, and removal to the surface by turbulent motions and precipitation for
22 pollutants emitted into the model domain. The upper boundaries of the CTMs extend anywhere from the
23 top of the mixed layer to the mesopause at ~80 km in order to obtain more realistic boundary conditions
24 for problems involving stratospheric dynamics.
25 CTMs in current use mostly have one of two forms. The first, grid-based or Eulerian air quality
26 models subdivide the region to be modeled or the modeling domain into a three-dimensional array of grid
27 cells. Spatial derivatives in the species continuity equations are cast in finite-difference form over this
28 grid and a system of equations for the concentrations of all the chemical species in the model are solved
29 numerically at each grid point. Finite element Eulerian models also exist and have been exercised, but less
30 frequently. Time dependent continuity or mass conservation equations are solved for each species
31 including terms for transport, chemical production and destruction, and emissions and deposition (if
32 relevant), in each cell. Chemical processes are simulated with ordinary differential equations, and
33 transport processes are simulated with partial differential equations. Because of a number of factors such
34 as the different time scales inherent in different processes, the coupled, nonlinear nature of the chemical
35 process terms, and computer storage limitations, all of the terms in the equations are not solved
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1 simultaneously in three dimensions. Instead, operator splitting, in which terms in the continuity equation
2 involving individual processes are solved sequentially, is used.
3 In the second common CTM formulation, trajectory or Lagrangian models, a number of
4 hypothetical air parcels are specified as following wind trajectories. In these models, the original system
5 of partial differential equations is transformed into a system of ordinary differential equations.
6 A less common approach is to use a hybrid Lagrangian/Eulerian model, in which certain aspects of
7 atmospheric chemistry and transport are treated with a Lagrangian approach and others are treaded in an
8 Eulerian manner (see e.g.,, Stein, 2000).
9 Each approach has its advantages and disadvantages. The Eulerian approach is more general in that
10 it includes processes that mix air parcels and allows integrations to be carried out for long periods during
11 which individual air parcels lose their identity. There are, however, techniques for including the effects of
12 mixing in Lagrangian models such as FLEXPART (e.g.,, Zanis, 2003), ATTILA (Reithmeier, 2002), and
13 CLaMS (McKenna, 2002).
2.8.1.1. Global Scale
14 The importance of global transport of O3 and O3 precursors and their contribution to regional O3
15 levels in the U.S. is now apparent. There are at present on the order of 20 three-dimensional global
16 models developed by various groups to address problems in tropospheric chemistry. These models resolve
17 synoptic meteorology, O3-NOX-CO-HC photochemistry, have parameterizations for wet and dry
18 deposition, and parameterize sub-grid scale vertical mixing processes such as convection. Global models
19 have proven useful for testing and advancing scientific understanding beyond what is possible with
20 observations alone. For example, they can calculate quantities of interest that cannot be measured directly,
21 such as the export of pollution from one continent to the global atmosphere or the response of the
22 atmosphere to future perturbations to anthropogenic emissions.
23 Global simulations are typically conducted at a horizontal resolution of 200 km2 or more.
24 Simulations of the effects of transport from long-range transport link multiple horizontal resolutions from
25 the global to the local scale. Finer resolution will only improve scientific understanding to the extent that
26 the governing processes are more accurately described at that scale. Consequently, there is a critical need
27 for observations at the appropriate scales to evaluate the scientific understanding represented by the
28 models.
29 During the recent IPCC-AR4 tropospheric chemistry study coordinated by the European Union
30 Atmospheric Composition Change: the European Network of excellence (ACCENT), 26 atmospheric
31 CTMs were used to estimate the impacts of three emissions scenarios on global atmospheric composition,
32 climate, and air quality in 2030 (Dentener, 2006). All models were required to use anthropogenic
33 emissions developed at IIASA (Dentener, 2005) and GFED version 1 biomass burning emissions (Van der
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1 Werf, 2003) as described in Stevenson et al. (2006). The base simulations from these models were
2 evaluated against a suite of present-day observations. Most relevant to this assessment report are the
3 evaluations with ozone, NO2, and N deposition (Stevenson, 2006; van Noije, 2006; Dentener, 2006),
4 which are summarized briefly below.
5 An analysis of the standard deviation of zonal mean and tropospheric column 03 reveals large
6 inter-model variability in the tropopause region and throughout the polar troposphere, likely reflecting
7 differences in model tropopause levels and the associated stratospheric injection of 03 to the troposphere
8 (Stevenson, 2006). Ozone distributions in the tropics also exhibit large standard deviations (-30%),
9 particularly as compared to the mid-latitudes (-20%), indicating larger uncertainties in the processes that
10 influence ozone in the tropics: deep tropical convection, lightning NOX, isoprene emissions and
11 chemistry, and biomass burning emissions (Stevenson, 2006).
12 Stevenson et al., (2006) found that the model ensemble mean (MEM) typically captures the
13 observed seasonal cycles to within one standard deviation. The largest discrepancies between the MEM
14 and observations include: (1) an underestimate of the amplitude of the seasonal cycle at 30°-90°N with a
15 10 ppb overestimate of winter ozone, possibly due to the lack of a seasonal cycle in anthropogenic
16 emissions or to shortcomings in the stratospheric influx of O3, and (2) an overestimate of O3 throughout
17 the northern tropics. However, the MEM was found to capture the observed seasonal cycles in the
18 southern hemisphere, suggesting that the models adequately represent biomass burning and natural
19 emissions.
20 The mean present-day global ozone budget across the current generation of CTMs differs
21 substantially from that reported in the IPCC Third Assessment Report (TAR), with a 50% increase in the
22 mean chemical production (to 5100 Tg CVyr), a 30% increase in the chemical and deposition loss terms
23 (to 4650 and 1000 Tg CVyr, respectively) and a 30% decrease in the mean stratospheric input flux (to 550
24 Tg CVyr) (Stevenson, 2006). The larger chemical terms as compared to the IPCC TAR are attributed
25 mainly to higher NOX (as well as an equatorward shift in distribution) and isoprene emissions, although
26 more detailed schemes and/or improved representations of photolysis, convection, and stratospheric-
27 tropospheric exchange may also contribute (Stevenson, 2006).
28 A subset of 17 of the 26 models used in the Stevenson et al. (2006) study was used to compare with
29 three retrievals of NO2 columns from the GOME instrument (van Noije, 2006) for the year 2000. The
30 higher resolution models reproduce the observed patterns better, and the correlation among simulated and
31 retrieved columns improved for all models when simulated values are smoothed to a 5° x 5° grid,
32 implying that the models do not accurately reproduce the small-scale features of NO2 (van Noije, 2006).
33 Van Noije et al. (2006) suggest that variability in simulated NO2 columns may reflect model differences
34 in OH distributions and the resulting NOx lifetimes, as well as differences in vertical mixing which
35 strongly affect partitioning between NO and NO2. Overall, the models tend to underestimate
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1 concentrations in the retrievals in industrial regions (including the eastern U.S.) and overestimate them in
2 biomass burning regions (van Noije, 2006).
3 Over the eastern U.S. and in industrial regions more generally, the spread in absolute column
4 abundances is generally larger among the retrievals than among the models, with the discrepancy among
5 the retrievals particularly pronounced in winter (van Noije, 2006), suggesting that the models are biased
6 low, or that the European retrievals may be biased high as the Dalhousie SAO retrieval is closer to the
7 model estimates. The lack of seasonal variability in fossil fuel combustion emissions may contribute to a
8 wintertime model underestimate (van Noije, 2006) manifested most strongly over Asia. In biomass
9 burning regions, the models generally reproduce the timing of the seasonal cycle of the retrievals, but tend
10 to overestimate the seasonal cycle amplitude, partly due to lower values in the wet season, which may
11 reflect an underestimate in wet season soil NO emissions (van Noije, 2006; Jaegle, 2004; Jaegle, 2005).
2.8.1.2. Regional Scale
12 Major modeling efforts within the EPA center on the Community Multiscale Air Quality modeling
13 system (CMAQ) (Byun, 1999; Byun, 2006). A number of other modeling platforms using Lagrangian and
14 Eulerian frameworks have been reviewed in the 2006 AQCD for 03 (EPA, 2006) and in Russell and
15 (2001;, 2000). The capabilities of a number of CTMs designed to study local- and regional-scale air
16 pollution problems were summarized by Russell and Dennis (2000). Evaluations of the performance of
17 CMAQ are given in Arnold et al. (2003, Eder and Yu, (2006, Appel et al. (2005), and Fuentes and Raftery
18 (2005). The domain of CMAQ can extend from several hundred km to the entire hemisphere. In addition,
19 both of these classes of models allow resolution of the calculations over specified areas to vary. CMAQ is
20 most often driven by the MM5 mesoscale meteorological model (Seaman, 2000), though it may be driven
21 by other meteorological models RAMS. Simulations of pollution episodes over regional domains have
22 been performed with a horizontal resolution as low as 1 km, and smaller calculations over limited
23 domains have been accomplished at even finer scales. However, simulations at such high resolutions
24 require better parameterizations of meteorological processes such as boundary layer fluxes, deep
25 convection and clouds (Seaman, 2000), as well as finer-scale emissions. Finer spatial resolution is
26 necessary to resolve features such as urban heat island circulation; sea, bay, and land breezes; mountain
27 and valley breezes, and the nocturnal low-level jet, all of which can affect pollutant concentrations.
28 The most common approach to setting up the horizontal domain is to nest a finer grid within a
29 larger domain of coarser resolution. However, there are other strategies such as the stretched grid (e.g.,,
30 Fox-Rabinovitz, 2002) and the adaptive grid. In a stretched grid, the grid's resolution continuously varies
31 throughout the domain, thereby eliminating any potential problems with the sudden change from one
32 resolution to another at the boundary. Caution should be exercised in using such a formulation, because
33 certain parameterizations (such as for convection) valid on a relatively coarse grid scale may not be valid
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1 on finer scales. Adaptive grids are not fixed at the start of the simulation, but instead adapt to the needs of
2 the simulation as it evolves (e.g.,, Hansen, 1994). They have the advantage that they can resolve processes
3 at relevant spatial scales. However, they can be very slow if the situation to be modeled is complex.
4 Additionally, if adaptive grids are used for separate meteorological, emissions, and photochemical
5 models, there is no reason a priori why the resolution of each grid should match, and the gains realized
6 from increased resolution in one model will be wasted in the transition to another model. The use of finer
7 horizontal resolution in CTMs will necessitate finer-scale inventories of land use and better knowledge of
8 the exact paths of roads, locations of factories, and, in general, better methods for locating sources and
9 estimating their emissions.
10 The vertical resolution of these CTMs is variable, and usually configured to have higher resolution
11 near the surface and decreasing aloft. Because the height of the boundary layer is of critical importance in
12 simulations of air quality, improved resolution of the boundary layer height would likely improve air
13 quality simulations. Additionally, current CTMs do not adequately resolve fine scale features such as the
14 nocturnal low-level jet in part because little is known about the nighttime boundary layer.
15 CTMs require time-dependent, three-dimensional wind fields for the period of simulation. The
16 winds may be generated either by a model using initial fields alone or with four-dimensional data
17 assimilation to improve the model's performance; i.e., model equations can be updated periodically
18 "nudged" to bring results into agreement with observations. Modeling efforts typically focus on
19 simulations of several days' duration, the typical time scale for individual 03 episodes; but longer term
20 modeling series of several months or multiple seasons of the year are now common. The current trend in
21 modeling applications is towards annual simulations. This trend is driven in part by the need to belter
22 understand observations of periods of high wintertime PM (e.g.,, Blanchard, 2002) and the need to
23 simulate 03 episodes occurring outside of summer.
24 Chemical kinetics mechanisms (a set of chemical reactions) representing the important reactions
25 occurring in the atmosphere are used in CTMs to estimate the rates of chemical formation and destruction
26 of each pollutant simulated as a function of time. Unfortunately, chemical mechanisms that explicitly treat
27 the reactions of individual reactive species are too computationally demanding to be incorporated into
28 CTMs for regulatory use. So, for example, are very extensive "master mechanisms" (Derwent, 2001)
29 includes approximately 10,500 reactions involving 3603 chemical species (Derwent, 2001), but "lumped"
30 mechanisms that group compounds of similar chemistry together, are used. The chemical mechanisms
31 used in existing photochemical O3 models contain significant uncertainties that may limit the accuracy of
32 their predictions; the accuracy of each of these mechanisms is also limited by missing chemistry. Because
33 of different approaches to the lumping of organic compounds into surrogate groups, chemical
34 mechanisms can produce somewhat different results under similar conditions. The CB-IV chemical
35 mechanism (Gery, 1989), the RADM II mechanism (Stockwell, 1990), the SAPRC (e.g.,, Wang, 2000;
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1 Wang, 2000; Carter, 2007) and the RACM mechanisms can be used in CMAQ. Jimenez et al. (2003)
2 provide brief descriptions of the features of the main mechanisms in use and they compared
3 concentrations of several key species predicted by seven chemical mechanisms in a box model simulation
4 over 24 h. The average deviation from the average of all mechanism predictions for 03 and NO over the
5 daylight period was less than 20%, and was 10% for NO2 for all mechanisms. However, much larger
6 deviations were found for HNO3, PAN, HO2, H2O2, ethylene (C2H4), and isoprene (CsH8). An analysis
7 for OH radicals was not presented. The large deviations shown for most species imply differences
8 between the calculated lifetimes of atmospheric species and the assignment of model simulations to either
9 NOx-limited or radical quantity limited regimes between mechanisms. Gross and Stockwell (2003) found
10 small differences between mechanisms for clean conditions, with differences becoming more significant
11 for polluted conditions, especially for NO2 and organic peroxy radicals. Faraji et al. (2005) found
12 differences of 40% in peak 1 h O3 in the Houston-Galveston-Brazoria area between simulations using
13 SAPRAC and CB4. They attributed differences in predicted O3 concentrations to differences in the
14 mechanisms of oxidation of aromatic HCs.
15 CMAQ and other state-of-the-science CTMs incorporate processes and interactions of aerosol-
16 phase chemistry (Mebust, 2003). There have also been several attempts to study the feedbacks of
17 chemistry on atmospheric dynamics using meteorological models, like MM5 (e.g., (e.g.,, Grell, 2000; Liu,
18 2001; Lu, 1997; Park, 2001). This coupling is necessary to simulate accurately feedbacks such as may be
19 caused by the heavy aerosol loading found in forest fire plumes (Lu, 1997; Park, 2001), or in heavily
20 polluted areas. Photolysis rates in CMAQ can now be calculated interactively with model produced O3,
21 NO2, and aerosol fields (Binkowski, 2007).
22 Spatial and temporal characterizations of anthropogenic and biogenic precursor emissions must be
23 specified as inputs to a CTM. Emissions inventories have been compiled on grids of varying resolution
24 for many HCs, aldehydes, ketones, CO, NH3, and NOx- Emissions inventories for many species require
25 the application of algorithms for calculating the dependence of emissions on physical variables such as
26 temperature and to convert the inventories into formatted emission files which can be used by a CTM. For
27 example, preprocessing of emissions data for CMAQ is done by the Spare-Matrix Operator Kernel
28 Emissions (SMOKE) system. For many species, information concerning the temporal variability of
29 emissions is lacking, so long-term (e.g., annual or O3-season) averages are used in short-term, episodic
30 simulations. Annual emissions estimates are often modified by the emissions model to produce emissions
31 more characteristic of the time of day and season. Significant errors in emissions can occur if
32 inappropriate time dependence or a default profile is used. Additional complexity arises in model
33 calculations because different chemical mechanisms can include different species, and inventories
34 constructed for use with another mechanism must be adjusted to reflect these differences. This problem
35 also complicates comparisons of the outputs of these models because one chemical mechanism may
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1 produce some species not present in another mechanism yet neither prediction may agree with the
2 measurements.
2.8.1.3. Sub-regional Scale
3 The grid spacing in regional chemistry transport models of between 1 and 12 km2 is usually too
4 coarse to resolve spatial variations on the neighborhood scale. The interface between regional scale
5 models and models of personal exposure described is provided by smaller scale dispersion models.
6 Several models could be used to simulate concentration fields near roads, each with its own set of
7 strengths and weaknesses. For example, AERMOD
8 (http://www.epa.gov/scramOO l/dispersion_prefrec.htm) is a steady-state plume model that was formulated
9 as a replacement to the ISC3 dispersion model. In the stable boundary layer (SBL), it assumes the
10 concentration distribution to be Gaussian in both the vertical and horizontal. In the convective boundary
11 layer, the horizontal distribution is also assumed to be Gaussian, but the vertical distribution is described
12 with a bi-Gaussian probability density function (pdf). AERMOD has provisions to be applied to flat and
13 complex terrain, and multiple source types (including, point, area and volume sources) in both urban and
14 rural areas. It incorporates air dispersion based on planetary boundary layer turbulence structure and
15 scaling concepts, and is meant to treat both surface and elevated sources and simple and complex terrain
16 in rural and urban areas. The dispersion of emissions from line sources like highways is treated as the sum
17 of emissions from a number of point sources placed side by side. However, emissions are usually not in
18 steady state and there are different functional relationships between buoyant plume rise in point and line
19 sources. It should be remembered that NO2 is largely secondary in nature as it is produced by Reaction 6.
20 However, AERMOD does not have provision for including secondary sources. The more appropriate use
21 of AERMOD would be to simulate the total of NO and NO2, or NOX.
22 There are non-steady state models that incorporate plume rise explicitly from different types of
23 sources. For example, CALPUFF (http://www.src.com/calpuff/calpuff 1 .htm) is a non-steady-state puff
24 dispersion model that simulates the effects of time- and space-varying meteorological conditions on
25 pollution transport, transformation, and removal and has provisions for calculating dispersion from
26 surface sources. However, it should be noted that neither model was designed to treat the dispersion of
27 emissions from roads or to include secondary sources. In using either model, the user would have to
28 specify dispersion parameters that are specific to traffic. The distinction between a steady-state and time
29 varying model might not be important for long time scales; however for short time scales, the temporal
30 variability in traffic emissions could result in underestimation of peak concentration and exposures.
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2.8.1.4. Modeling Effects of Convection for Chemical Transport
1 The effects of deep convection can be simulated using cloud-resolving models, or in regional or
2 global models in which the convection is parameterized. The Goddard Cumulus Ensemble (GCE) model
3 (Tao, 1993) has been used by Pickering et al. (1991;, 1992;, 1992;, 1993;, 1996), Scala et al. (1990),
4 and Stenchikov et al. (1996) in the analysis of convective transport of trace gases. The cloud model is
5 nonhydrostatic and contains a detailed representation of cloud microphysical processes. Two- and three-
6 dimensional versions of the model have been applied in transport analyses. The initial conditions for the
7 model are usually from a sounding of temperature, water vapor and winds representative of the region of
8 storm development. Model-generated wind fields can be used to perform air parcel trajectory analyses
9 and tracer advection calculations.
10 Such methods were used by Pickering et al. (1992) to examine transport of urban plumes by deep
11 convection. Transport of an Oklahoma City plume by the 10-11 June 1985 PRE-STORM squall line was
12 simulated with the 2-D GCE model. This major squall line passed over the Oklahoma City metropolitan
13 area, as well as more rural areas to the north. Chemical observations ahead of the squall line were
14 conducted by the PRE-STORM aircraft. In this event, forward trajectories from the boundary layer at the
15 leading edge of the storm showed that almost 75% of the low level inflow was transported to altitudes
16 exceeding 8 km. Over 35% of the air parcels reached altitudes over 12 km. Tracer transport calculations
17 were performed for CO, NOx, O3, and HCs. Rural boundary layer NOx was only 0.9 ppb, whereas the
18 urban plume contained about 3 ppb. In the rural case, mixing ratios of 0.6 ppb were transported up to 11
19 km. Cleaner air descended at the rear of the storm lowering NOx at the surface from 0.9 to 0.5 ppb. In the
20 urban plume, mixing ratios in the updraft core reached 1 ppb between 14 and 15 km. At the surface, the
21 main downdraft lowered the NOX mixing ratios from 3 to 0.7 ppb.
22 Regional chemical transport models have been used for applications such as simulations of
23 photochemical O3 production, acid deposition, and fine PM. Walcek et al. (1990) included a
24 parameterization of cloud-scale aqueous chemistry, scavenging, and vertical mixing in the chemistry
25 model of (Chang, 1987). The vertical distribution of cloud microphysical properties and the amount of
26 sub-cloud-layer air lifted to each cloud layer are determined using a simple entrainment hypothesis
27 (Walcek, 1986). Vertically integrated O3 formation rates over the northeast U. S. were enhanced by -50%
28 when the in-cloud vertical motions were included in the model.
29 Wang et al. (1996) simulated the 10-11 June 1985 PRE-STORM squall line with the NCAR/Penn
30 State Mesoscale Model (MM5) (Grell, 1994; Dudhia, 1993). Convection was parameterized as a sub-grid-
31 scale process in MM5 using the Kain and Fritsch (1993) scheme. Mass fluxes and detrainment profiles
32 from the convective parameterization were used along with the 3-D wind fields in CO tracer transport
33 calculations for this convective event.
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1 Convective transport in global chemistry and transport models is treated as a sub-grid-scale process
2 that is parameterized typically using cloud mass flux information from a general circulation model or
3 global data assimilation system. While GCMs can provide data only for a "typical" year, data assimilation
4 systems can provide "real" day-by-day meteorological conditions, such that CTM output can be compared
5 directly with observations of trace gases. The NASA Goddard Earth Observing System Data Assimilation
6 System (GEOS-1 DAS and successor systems; Schubert, 1993; Bloom, 1996; Bloom, 2005) provides
7 archived global data sets for the period 1980 to present, at 2° x 2.5° or better resolution with 20 layers or
8 more in the vertical. Deep convection is parameterized with the Relaxed Arakawa-Schubert scheme
9 (Moorthi, 1992) in GEOS-1 and GEOS-3 and with the Zhang and McFarlane (1995) scheme in GEOS-4.
10 Pickering et al. (1995) showed that the cloud mass fluxes from GEOS-1 DAS are reasonable for the 10-
11 11 June 1985 PRE-STORM squall line based on comparisons with the GCE model (cloud-resolving
12 model) simulations of the same storm. In addition, the GEOS-1 DAS cloud mass fluxes compared
13 favorably with the regional estimates of convective transport for the central U.S. presented by Thompson
14 et al. (1994). However, Allen et al. (1997) have shown that the GEOS-1 DAS overestimates the amount
15 and frequency of convection in the tropics and underestimates the convective activity over midlatitude
16 marine storm tracks.
17 Global models with parameterized convection and lightning have been run to examine the roles of
18 these processes over North America. Lightning contributed 23% of upper tropospheric NOY over the
19 SONEX region according to the UMD-CTM modeling analysis of Allen et al. (2000). During the summer
20 of 2004 the NASA Intercontinental Chemical Transport Experiment - North America (INTEX-NA) was
21 conducted primarily over the eastern two-thirds of the U.S., as a part of the International Consortium for
22 Atmospheric Research on Transport and Transformation (ICARTT). Deep convection was prevalent over
23 this region during the experimental period. Cooper et al. (Cooper, 2006) used a particle dispersion model
24 simulation for NOx to show that 69-84% of the upper tropospheric Oj, enhancement over the region in
25 summer 2004 was due to lightning NOX. The remainder of the enhancement was due to convective
26 transport of O3 from the boundary layer or other sources of NOX. Hudman et al. (2007) used a GEOS-
27 Chem model simulation to show that lightning was the dominant source of upper tropospheric NOX over
28 this region during this period. Approximately 15% of North American boundary layer NOX emissions
29 were shown to have been vented to the free troposphere over this region based on both the observations
30 and the model.
2.8.2. Computed Deposition
31 Wet and dry deposition are important removal processes for pollutants on urban and regional scales
32 and so are included in CTMs. The general approach used in most models is the resistance-in-series
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1 method described above and represented in Reaction 61. This approach works for a range of substances,
2 although it is inappropriate for species with substantial re-emissions from the surface or for species where
3 deposition to the surface depends on concentrations at the surface itself. The approach is also modified
4 somewhat for aerosols in that the terms Rb and Rc are replaced with a surface Vd to account for
5 gravitational settling.
= Ł> \~1
Reaction 61
aerodynamic
Atmospheric
Resistances
Canopy
Resistances
Source: Courtesy of Thomas Pierce, USEPA / ORD / NERL / Atmospheric Modeling Division.
Figure 2-26. Schematic of the resistance-in-
series analogy for atmospheric deposition.
Function of wind speed, solar radiation, plant
characteristics, precipitation/moisture, and
soil/air temperature.
Resistance analogy for the deposition of atmospheric pollutants
6 where Ra, Rb, and Rc represent the resistance due to atmospheric turbulence, transport in the fluid sublayer
7 very near the elements of surface such as leaves or soil, and the resistance to uptake of the surface itself as
8 shown in Figure 2-26.
9 Weseley and Hicks (2000) listed several shortcomings of the then-current knowledge of dry
10 deposition. Among those shortcomings were difficulties in representing dry deposition over varying
11 terrain where horizontal advection plays a significant role in determining the magnitude of Ra and
12 difficulties in adequately determining Vd for extremely stable conditions such as those occurring at night;
13 see the discussion by Mahrt (1998) 1998, for example. Under optimal conditions, when a model is
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1 exercised over a relatively small area where dry deposition measurements have been made, models still
2 generally showed uncertainties on the order of ±30% (see e.g.,, Massman, 1994; Brook, 1996; Padro,
3 1996). Wesely and Hicks (2000) concluded that an important result of those comparisons was that the
4 level of sophistication of most dry deposition models was relatively low, and that deposition estimates,
5 therefore, must rely heavily on empirical data. Still larger uncertainties exist when the surface features in
6 the built environment are not well known or when the surface comprises a patchwork of different surface
7 types, as is common in the eastern U.S.
2.8.2.1. N Deposition and Flux with Biota
8 Several reactive N are species are deposited to vegetation, among them, HNO3, NO2, and PAN and
9 other RONO2.
10 Field observations based on concentration gradients of HNO3 and using eddy covariance
11 techniques demonstrate rapid deposition that approaches the aerodynamic limit (as constrained by
12 atmospheric turbulence) in the Wesely and Lesht (1989) formulation based on analogy to resistance.
13 Surface resistance to HNO3 uptake by vegetation is negligible. Deposition rates are independent of leaf
14 area or stomatal conductance, implying that deposition occurs to branches, soil, and the leaf cuticle as
15 well as leaf surfaces. The HNO3 Vd typically exceeds 1 cm/s and exhibits a diel pattern controlled by
16 turbulence characteristics of midday maxima and lower values at night in the more-stable boundary layer.
17 NO2 interaction with vegetation is more difficult to understand than that for HNO3, in part because
18 very fast measurements of NO2 flux are confounded by the rapid interconversion of NO, NO2, and O3
19 (Gao, 1991). Application of 15N-labeled NO2 demonstrates thatNO2 is absorbed and metabolized by
20 foliage (Siegwolf, 2001; Mocker, 1998; Segschneider, 1995; Weber, 1995). Exposure to NO2 induces
21 activation of NO3 reductase (Weber, 1995; Weber, 1998), a necessary enzyme for assimilating oxidized N.
22 Understanding of NO2 interactions with foliage is largely based on leaf cuvette and growth chamber
23 studies which expose foliage or whole plants to controlled NO2 concentrations and measure the fraction
24 of NO2 removed from the chamber air. A key finding is that the fit of NO2 flux to NO2, has a non-0
25 intercept, implying a compensation point or internal concentration. In studies at very low NO2
26 concentrations, emission from foliage is observed (Teklemariam, 2006). Evidence for a compensation
27 point is not solely based on the fitted intercept. The NO2 uptake rate to foliage is clearly related to
28 stomatal conductance. Internal resistance is variable, and may be associated with concentrations of
29 reactive species such as ascorbate in the plant tissue that react with NO2 (Teklemariam, 2006). Foliar NO2
30 emissions show some dependence on N content (Teklemariam, 2006). Internal NO2 appears to derive
31 from plant N metabolism.
32 Two approaches to modeling NO2 uptake by vegetation are the resistance-in-series analogy which
33 considers flux (F) as the product of concentration (C) and Vd, related to the sum of aerodynamic,
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1 boundary layer, and internal resistances (Ra, Rb, and Rc, respectively); by convention, positive fluxes are
2 in the direction of from the atmosphere to foliage. Note that this approach is the method most often used
3 to predict deposition in AQMs, that of Wesely and Lesht (1989), as described above. These terms are
4 related as shown in Equations 59 above and 60
F=CVd
Reaction 62
5 Typically, the NO2 Vd is less than that for 03 due to the surface's generally higher resistance to
6 NO2 uptake, consistent with NO2's lower reactivity.
7 Alternatively, NO2 exchange with foliage can be modeled from a physiological standpoint where
8 the flux from the leaf (J) is related to the stomatal conductance (gs) and a concentration gradient between
9 the ambient air and interstitial air in the leaf (Ca-C,). This approach best describes results for exchange
1 0 with individual foliage elements, and is expressed per unit leaf or needle area. While this approach
1 1 provides linkage to leaf physiology, it is not straightforward to scale up from the leaf to the ecosystem
Reaction 63
12 This model implicitly associates the compensation point with a finite internal concentration.
13 Typically observed compensation points are ~1 ppb; values of internal NO2 concentrations are consistent
14 with metabolic pathways that include NOX. In this formulation, the uptake will be linear with NO2, which
15 is typically measured in foliar chamber studies.
16 Several studies have shown the UV dependence of NO2 emissions, which implies some photo-
17 induced surface reactions to release NO2. Rather than model this as a UV-dependent internal
1 8 concentration, it would be more realistic to add an additional term to account for emission that is
1 9 dependent on light levels and other surface characteristics
J=gs(Ca-Ci)=Js(UV)
Reaction 64
20 The mechanisms for surface emission are discussed below. Measurement of NO2 flux is
21 confounded by the rapid interconversion of NO, NO2, and O3 (Gao, 1991).
22 PAN is phytotoxic and absorbed at the leaf. Observations based on inference from concentration
23 gradients and rates of loss at night (Shepson, 1992; Schrimpf, 1996) and from leaf chamber studies
24 (Teklemariam, 2004) have indicated that uptake of PAN is slower than that of O3; however, recent work
25 in coniferous canopies with direct eddy covariance PAN flux measurements indicated a Vd more similar
26 to that of O3. Uptake of PAN is under stomatal control, has non-zero deposition at night, and is influenced
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1 by leaf wetness (Turnipseed, 2006). On the other hand, flux measurements determined by gradient
2 methods over a grass surface showed a Vd closer to 0.1 cm/s, with uncertainty on the order of a factor of
3 10 (Doskey, 2004). Whether the discrepancies are methodological or indicate intrinsic differences
4 between different vegetation is unknown. Uptake of PAN is a smaller loss process than its thermal
5 decomposition in all cases.
6 The biosphere also interacts with NOx through HC emissions and their subsequent reactions to
7 form multi-functional RONO2. Formation of the hydroxyalkyl nitrates occurs after OH attack on VOCs.
8 In one sense, this mechanism is simply an alternate pathway for OH to react with NOx to form a rapidly
9 depositing species. If VOC were not present, OH would be available to react with NO2 when it is present
10 toformHNO3.
11 Isoprene nitrates are an important class of RONO2. Isoprene reacts with OH to form a radical that
12 adds NO2 to form the hydroxyalkyl nitrate. The combination of hydroxyl and NO3 functional group
13 makes these compounds especially soluble with low vapor pressures, so they likely deposit rapidly
14 (Shepson, 1996; Treves, 2000). Many other unsaturated HCs react by analogous routes. Observations at
15 Harvard Forest show a substantial fraction of the total of all gas-phase forms of oxidized N (category
16 label is NOY) not accounted for by NO, NO2 and PAN, which is attributed to the RONO2 (Horii, 2006;
17 Munger, 1998). Furthermore, the total NOY flux exceeds the sum of HNO3, NOX, and PAN, which
18 implies that the RONO2 are a substantial fraction of the total N deposition. Other observations showing
19 evidence of hydoxyalkyl nitrates include those of Grossenbacher et al. (2001) and Day et al. (2003).
20 Formation of the hydroxyalkyl nitrates occurs after VOC + OH reaction. In some sense, this
21 mechanism is just an alternate pathway for OH to react with NOx to form a rapidly depositing species. If
22 VOC were not present, OH would be available to react with NO2 when it is present instead to form
23 HNO3.
24 HNO2 formation on vegetative surfaces at night has long been observed based on measurements of
25 positive gradients (Harrison, 1994). Surface reactions of NO2 enhanced by moisture were proposed to
26 explain these results. Production was evident at sites with high ambient NO2; at low concentration, uptake
27 of HNO2 exceeded the source. Daytime observations of HNO2 when rapid photolysis is expected to
28 deplete ambient concentrations to very low levels implies a substantial source of photo-induced HNO2
29 formation at a variety of forested sites where measurements have been made. Estimated source strengths
30 are 200 to 1800 ppt/h in the surface layer (Zhou, 2003; Zhou, 2002), which is ~20 times faster than all
31 nighttime sources.
32 HNO2 sources could be important to HOX budgets as HNO2 is rapidly photolyzed by sunlight to
33 OH and NO. Additional evidence of light-dependent reactions to produce HNO2 comes from discovery of
34 a HNO2 artifact in pyrex sample inlet lines exposed to ambient light. Either covering the inlet or washing
35 it eliminated the HNO2 formation (Zhou, 2002). Similar reactions might serve to explain observations of
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1 UV-dependent production of NOX in empty foliar cuvettes that had been exposed to ambient air (Hari,
2 2003; Raivonen, 2003).
3 Production of HNO2 in the dark is currently believed to occur via a heterogeneous reaction
4 involving NO2 on wet surfaces (He, 2006; Pitts, 1984; Sakamaki, 1983; Jenkin, 1988; Pitts, 1984), and it
5 is proposed that the mechanism has first-order dependence in both NO2 and H2O (Kleffmann, 1998;
6 Svensson, 1987) despite the stoichiometry. However, the molecular pathway of the mechanism is still
7 under debate. Jenkin et al. (1988) postulated a H2ONO2 water complex reacting with gas phase NO2 to
8 produce HNO2, which is inconsistent with the formation of an N2C>4 intermediate leading to HNO2 as
9 proposed by Finlayson-Pitts et al. (2003). Another uncertainty is whether the reaction forming HNO2 is
10 dependent on water vapor (Svensson, 1987; Stutz, 2004; Svensson, 1987; Stutz, 2004) or water adsorbed
11 on surfaces (Kleffmann, 1998). Furthermore, the composition of the surface and the available amount of
12 surface or surface-to-volume ratio can significantly influence the HNO2 production rates (Kaiser, 1977;
13 Kleffmann, 1998; Svensson, 1987), which may explain the difference in the rates observed between
14 laboratory and atmospheric measurements.
15 There is no consensus on a chemical mechanism for photo-induced HNO2 production. Photolysis
16 of HNO3 or NO3 absorbed on ice or in surface water films has been proposed (Honrath, 2002; Ramazan,
17 2004; Zhou, 2001; Zhou, 2003). Alternative pathways include NO2 interaction with organic surfaces such
18 as humic substances (Stemmler, 2006; George, 2005). Note that either NO3 photolysis or heterogeneous
19 reaction of NO2 are routes for recycling deposited nitrogen oxides back to the atmosphere in an active
20 form. NO3 photolysis would return N that heretofore was considered irreversibly deposited, surface
21 reactions between NO2 and water films or organic molecules would decrease the effectiveness of
22 observed NO2 deposition if the HNO2 were re-emitted.
2.8.3. Air Quality Model Evaluation
23 Urban and regional air quality is determined by a complex system of coupled chemical and
24 physical processes including emissions of pollutants and pollutant precursors, complex chemical
25 reactions, physical transport and diffusion, and wet and dry deposition. NOX in these systems has long
26 been known to act nonlinearly in P(O3) and other secondary pollutants (Dodge, 1977), to extend over
27 multiple spatial and temporal scales, and to involve complicated cross-media environmental issues such
28 as acidic or nutrient deposition to sensitive biota and degradation of visibility.
29 NOy species emitted and transformed from NOx emissions control the production and fate of O3
30 and aerosols by sustaining or suppressing OH cycling. Correctly characterizing the interrelated NOy and
31 OH dynamics for O3 formation and fate in the polluted troposphere depends on new techniques using
32 combinations of several NOY species for diagnostically probing the complex atmospheric dynamics in
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1 typical urban and regional airsheds. Dennis (2002) provides more detail on measurement requirements for
2 diagnostic model evaluation.
3 Because of the complexity of these atmospheric processes, compensating errors in a model's
4 physical, chemical, or numerical representations can produce cases of model output that appears right, but
5 for the wrong reasons. That is to say, there are cases where the model solution coheres with expectations
6 and often even with values measured in situ from field campaigns, but where these solutions have been
7 produced through unrevealed errors that, in essence, off-set opposing effects, balancing or buffering the
8 final model predictions. The model performance evaluation statistics that have historically been computed
9 for summary descriptors like bias, gross error, and peak prediction accuracy for individual species alone
10 cannot distinguish these difficult, but frequently encountered, conditions. The regulatory use of models to
11 predict future effects of potential control strategies means that there are no direct tests for these significant
12 model applications. However, avoiding the potential costly errors in predicting possible effects from
13 mandated controls, as described above, requires an accurate appraisal of the type, magnitude, and extent
14 of these controls. Thus, model credibility and user confidence in model-predicted effects related to such
15 controls and effects can be established only by diagnostically probing process and mechanism
16 representations in the model, and then checking these where possible against analogous tests of
17 photochemical dynamics in ambient atmospheres.
18 Arnold et al. (1998) described a model evaluation methodology that distinguished several types of
19 AQM testing. Two components of that methodology were: (1) operational testing to judge the
20 performance and overall behavior of a model over specific attributes; and (2) diagnostic testing to help
21 reveal potential compensating error in model inputs or processing. Diagnostic testing is in situ testing of
22 model components using data that emphasize atmospheric processes, often with mass balance techniques,
23 special species ratios, and process rate and reaction rate information not typically stored by the model for
24 output. Some of these probes have been developed through process-oriented studies using theoretical
25 assumptions, model-derived explanations, and results from instrumented models ranging from one-
26 dimensional box models to the full 4-dimensional photochemical modeling system (Tonnesen, 2000).
27 Additional information on instrumenting AQMs for diagnostic analysis with model process and reaction
28 rate information is found in Dennis et al. (2002); information pertaining to the specific implementation of
29 these techniques in CMAQ is found in (Gipson, 1999); and results from application of diagnostic probes
30 to modeling experiments are found in Arnold and Dennis (2006;, 2003).
31 Evaluation results from a recent U.S. EPA exercise of CMAQ in the Tampa Bay airshed are
32 presented here as an example of the present level of skill of state-of-the-science AQMs for predicting
33 atmospheric concentrations of the relevant NOX, SOX, and NHX species for this NAAQS assessment.
34 This modeling series exercised CMAQ version 4.4 and with the University of California at Davis (UCD)
35 sectional aerosol module in place of the standard CMAQ modal module and as driven by meteorology
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1 from MM5 v3.6 and with NEI emissions as augmented by continuous emissions monitoring data where
2 available. The CTM was run with 21 vertical layers for the month of May 2002. For this evaluation,
3 CMAQ-UCD was run in a one-way nested series of three domains with 32 km, 8 km, and 2 km horizontal
4 grid spacings.
5 Depictions of the 8 km and 2 km domains used here zoomed over the central Tampa area are shown
6 in Figure 2-27 and Figure 2-28.
8KM RESOLUTION: ZOOMED2
Figure 2-27.8 km southeast U.S.
CMAQ doma Function of wind
speed, solar radiation, plant
characteristics, precipitation/
moisture, and soil/air temperature
in zoomed over Tampa Bay.
2KM RESOLUTION; ZOOMED2
Figure 2-28.2 km southeast U.S.
CMAQ domain zoomed over Tampa
Bay.
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2.8.3.1. Ground-based Comparisons of Photochemical Dynamics
1 Errors in the NOx concentrations in the model most likely from on-road emissions (Figure 2-29)
2 affected NOX predations, but CMAQ-UCD's general responses were reasonable. The model also
3 replicated well anthropogenic and biogenic VOC emissions; see Figure 2-30 and Figure 2-31,
4 respectively. After initial errors leading to underprediction in the first 21 days, CMAQ's predictions of
5 hourly PM2 5 concentrations and trends over the whole month also replicated the observed concentrations
6 well; see Figure 2-32.
J.
Morning drive-time NOX loadings low
Early collapse of boundary layer enhances |10>
late afternoon and evening overpredictions
Figure 2-29. Hourly averages for 1-
31 May, 2002, CMAQ 8 km and 2 km
results and measured
concentrations of NO (a), NCh (b),
and total NOx (c).
Magnitude and most ethene plumes well captured
by CMAO--UCD
Figure 2-30. May 2002 daily
concentrations and 8 km
CMAQ predictions for
ethene at Sydney, FL.
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Isoprene levels and timing very well captured
byCMAQ--UCD
Figure 2-31. May 2002 daily
concentrations and 8 km CMAQ
predictions for isoprene at Sydney,
FL
vMjJ* " «T '•»'•'
l!-fc) 11-Hl. U-tt,; IS-«)
PM2.5 total mass mostly underpredicted before
21 May. but trends are well captured
Figure 2-32. Observed hourly PIVk.s
concentrations at St. Petersburg,
FL and results from CMAQ 8 km.
CMAO--UCD tracks the photochemical systems across
the response surface very well, but does not move
them far enough into the most NOx-limited space
Effects of the generalized NOx overpredictions, and a
slight Os underprediction on the few highest days, are
evident here
Figure 2-33. Observed and modeled
ratios of Os to NOx. Diel curves
from hourly averages over 1-31
May, 2002 (a), and distribution of 03
to NOx ratio values binned to show
fractions of total daylight hours, 1-
31,2002.
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1 The P(O3) efficiency curves in the model agreed well with those observed at Sydney; see Figure
2 2-33. However, tests of CH2O (Figure 2-34) and H2O2 (Figure 2-35) seemed to indicate an error in the
3 model's OH chemistry related to these radical reservoir species since both were substantially and
4 systematically different from the observations at the ground-based Sydney site. These species have
5 historically been very difficult to model well, however, and the overall excellent agreement of CMAQ-
6 UCD to production curves in relation to NOx processing mean that this error was likely restricted to these
7 species and of limited influence in the overall model solutions and for this evaluation.
8 km and 2 km CHiO mixing ratios are low nearly
every hour, often by more than a factor of two during
the photochemically-active part of the day
Model CH20 production is beneath the curve relative
to NOz production in the world, too
Figure 2-34. Observed and CMAQ 8
km and 2 km predicted
formaldehyde concentrations.
Hourly averages from each day, 1-
31 May, 2002 (a), and formaldehyde
concentrations as a function of NOz
concentrations (b).
Model H2O? mixing ratios are too flat against the
Sydney observations, missing nearly every
maximum and minimum value
But the overall reduction trend over the month is
replicated in both the 8 km and 2km solutions
I.
Figure 2-35. Hourly concentrations
of H peroxide, observed and
predicted by CMAQ 8 km and 2 km,
1-31 May, 2002 at Sydney, FL
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1 NO3 aerosols play a crucial and complex role in the health of aquatic and estuarine ecosystes. Gas-
2 phase NO3 replacement of Cl~ on sea salt particles is often favored thermodynamically; and the
3 deposition velocity Vd of the coarse particle NO3 formed through this replacement is more than an order
4 of magnitude greater than for fine particle NO3 . Over open bodies of salt water such as the Gulf of
5 Mexico and Tampa Bay, NO3 from this reaction dominates dry deposition, and is estimated to be of the
6 same order as NO3 wet deposition.
7 However, aerosol NO3 concentrations are driven, buffered, and altered by a wide range of
8 photochemical gas-phase reactions, heterogeneous reactions, and aerosol dynamics, making them
9 especially difficult to model well. Because aerosol NO3 is derived mostly from gas-phase HNO3 and will
10 interact with Na+, Cl~, NH4+, and SO42 , all these species and the physical parameters governing their
11 creation, transport, transformation, and fate must be accurately replicated to predict NO3 with high
12 fidelity. This has historically been a difficult problem for numerical process models, owing not least to the
13 pervasive dearth of reliable ambient measurements of NO3~in its various forms. Normalized mean error
14 (NME) for the large-scale Eulerian CTM-predicted pNO3 has typically been on the order of a factor of 3
15 greater than the NME for pSO4 (Odman, 2002; Pun, 2003).
16 SO42 , NH4+, Na+, and Cl~ were all predicted to within a factor of two and with no significant bias
17 during the photochemical day in the 8 km CMAQ-UCD solution, although a significant bias in Na+ and
18 Cr was evident in the 2 km solution for two near water sites. This grid-size dependent bias is still being
19 explored. Size segregation maxima were correct to within two size bins every day for which there were
20 observations for both SO42~and NH4+ (0.2 to 1.0 urn), and Na+ and Cl" (2.0 to 10.0 urn). Cl"
21 concentrations were greatly overpredicted during dark hours, but were nearer to observed values during
22 the photochemical day. CMAQ performance for HNO3 and NH3 are shown in Figure 2-36 and Figure
23 2-37, respectively.
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HNOs. like aerosol NOs", is underpredicted, but
is closer than NOa
Diurnal cycle is correct, if peaks sometimes
overpredicted
Low nighttime predictions in part from NjOs y - 0
2 km emphasizes overprecfction peaks, but
mostly very similar to 8 km
ittv l&.Ma-s &Msy
Figure 2-36. Hourly and CMAQ-
predicted HMOs concentrations at
Sydney, FL, 1-31 May, 2002.
8 km and 2 km solutions strongly self-similar
Most diurnal patterns captured; the very few
exceptionally large peaks not replicated
Figure 2-37. Hourly and CMAQ-
predicted NH3 concentrations at
Sydney, FL, 1-31 May, 2002.
1 Overall, CMAQ-UCD was found to be operationally sound in this evaluation of its 8 km and 2 km
2 solutions for the Tampa Bay airshed using the ground-based and aloft data from the May 2002 field
3 intensive. Moreover, results from diagnostic tests of the model's photochemical dynamics were generally
4 in excellent agreement with results from the ambient atmosphere. However, CMAQ-UCD was biased low
5 in this application for total NC>3~and for NOs" present as gas-phase HNOs. In addition, the model was
6 biased low for the radical reservoir species CH2O and H2C>2, though this bias appeared to have been
7 limited to these species. Performance of the new UCD aerosol module was judged to be entirely adequate,
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1 allocating aerosols by chemical makeup to the appropriate size fractions. Model performance for fine-
2 mode aerosols was also judged to be fully adequate.
2.8.3.2. Deposition with CTMs
3 Both wet and dry deposition are highly parameterized in CTMs. While all current models
4 implement resistance schemes for dry deposition, the Vd generated from different models can vary highly
5 across terrains (Stevenson, 2006). The accuracy of wet deposition in global CTMs is tied to spatial and
6 temporal distribution of model precipitation and the treatment of chemical scavenging. Dentener et al.
7 (Dentener, 2006) compared wet deposition across 23 models with available measurements around the
8 globe. Source: Dentener et al. (2006).
9 Figure 2-38 and Source: Dentener et al. (2006).
10 Figure 2-39 extract results of a comparison of the 23-model mean versus observations over the
11 eastern U.S. for pNOs and pSC>4 deposition, respectively. The mean model results were strongly
12 correlated with the observations (r > 0.8), and usually capture the magnitude of wet deposition to within a
13 factor of 2 over the eastern U.S. Dentener et al. (2006) concluded that 60 to 70% of the participating
14 models captured the measurements to within 50% in regions with quality controlled observations. This
15 study then identified world regions receiving > 1000 mg N/m2/yr, which they defined as the critical load,
16 and found that 20% of non-crop, natural vegetation in the U.S. is exposed to N deposition in excess of
17 that amount (Dentener, 2006).
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600
400
200
Am. model. 227 Aus Mea 195 r 082 a-226
2 param fit y *51 1 + 090x
I param fit: y = 10Sx
Percentage within ± 50% 74.8
200 400
Measurement
Source: Dentener et al. (2006).
Figure 2-38. Scatter plot of total nitrate
(HMOs plus aerosol nitrate) wet deposition
(mg N/m2/yr) of the mean model versus
measurements for the North American
Deposition Program (NADP) network.
Dashed lines indicate factor of 2. The gray
line is the result of a linear regression
6oo fitting through 0.
1000
800
600
400
200
' • • • 5 * •'
' • 1
/ • ft • •! y •' •
' S m •"
• / • '••"* •
Ave model: 383 Ave, Mess: 322 r: 0.87 n = 225
7 paranfir y = 114.0+077x
1 param fi:: y = 1.00s
pgiufrildfc|ttwilhiii± 50%. 66.0
200
400 600
Measurement
800
1000
Source: Dentener et al. (2006).
Figure 2-39. Scatter plot of total SCV" wet
deposition (mg S/m2/yr) of the mean model
versus measurements for the North
American Deposition Program (NADP)
network. Dashed lines indicate factor of 2.
The gray line is the result of a linear
regression fitting through 0.
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2.8.4. Computing Atmospheric Deposition to Specific Locations
1 Inputs of new N, i.e., non-recycled, exogenous N mostly anthropogenic in origin, are often key
2 factors controlling primary productivity in N-sensitive estuarine and coastal waters (Paerl, 2000).
3 Increasing trends in urbanization, agricultural intensity, and industrial expansion have led to increases in
4 N deposited from the atmosphere on the order of a factor of 10 in the previous 100 years (Swackhamer,
5 2004). Direct fluxes of atmospheric N to ocean and gulf waters along the northeast and southeast U.S. are
6 now roughly equal to or exceed the load of new N from riverine inputs at 11, 5.6, and 5.6 kg N/ha for the
7 northeast Atlantic coast of the U.S., the southeast Atlantic coast of the U.S., and the U.S. eastern Gulf of
8 Mexico, respectively (Paerl, 2002).
9 This N deposition takes different forms physically and chemically. Physically, deposition can be
10 direct, with the loads resulting from air pollutants depositing directly to the surface of a body of water,
11 usually a large body of water like an estuary or lake. In addition, there is an indirect deposition
12 component derived from deposition of N or S air pollutants to the rest of the watershed, both land and
13 water, of which some fraction is transported through runoff, rivers, streams, and groundwater to the
14 waterbody of concern.
15 Direct and indirect deposition to watersheds depend on air pollutant concentrations in the airshed
16 above the watershed. The shape and extent of the airshed is quite different from that of the watershed. In a
17 watershed, everything that falls in its area, by definition, flows into a single body of water. An airshed, by
18 contrast, is a theoretical concept that defines the source area containing the emissions contributing a given
19 level, often 75%, to the deposition in a particular watershed or to a given waterbody. Hence, airsheds are
20 modeled domains containing the sources estimated to contribute a given level of deposition from each
21 pollutant of concern. The principal NOX airsheds and corresponding watersheds for several regions in the
22 eastern U.S. are shown in Figure 2-40.
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Airshed extents developed and used courtesy of Robin Dennis, EPA/ORD/NERL/Atmospheric Modeling Division.
Figure 2-40. Principal airsheds and watersheds for oxides of nitrogen for estuaries. Hudson/Raritan
Bay; Chesapeake Bay; Pamlico Sound; and Altamaha Sound (listed from north to south).
1 N inputs have been studied in several east and Gulf Coast estuaries owing to concerns about
2 eutrophication there. N from atmospheric deposition in these locations is estimated to be 10 to 40% of the
3 total input of N to many of these estuaries, and could be higher for some. Estimates of total N loadings to
4 estuaries or to other large-scale elements in the landscape are then computed using measurements of wet
5 and dry N deposition where these are available and interpolated with or without a set of air quality model
6 predictions such as the Extended Regional Acid Deposition Model (Ext-RADM) (Mathur, 2003 Dennis,
7 1990; Dennis, 2001; Mathur, 2000; Dennis, 1997). Ext-RADM has been shown to capture spatial and
8 seasonal variations in N deposition, to predict the constituent deposition species correctly, and to simulate
9 the chemistry and physics relating reduced and oxidized forms of N with high validity.
10 Extensive evaluation by Mathur and Dennis (2003) of the performance of the Ext-RADM showed
11 that model-predicted ambient levels, gas-to-particle partitioning ratios, and deposition totals were in good
12 agreement with available measurements, having R2 for both annual and seasonal totals in the range of 0.4
13 to 0.7 for most species. Ext-RADM correctly predicted that most particles in the eastern U.S. are fully
14 neutralized, further demonstrating that most modeled chemistry is correct as judged against
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1 measurements. Experiments with Ext-RADM to characterize atmospheric conditions over the eastern U.S.
2 in the period at the end of the 1980s and early 1990s showed that the model predicted that reduced N
3 species were contributed 47 ± 8% of total N wet deposition, in excellent agreement with the number
4 inferred from measurements, 43 ± 9%.
5 Table 2-10 lists several waterbodies for which atmospheric N inputs have been computed and
6 ratioed to total N loads. The contribution from the atmosphere ranges from a low of 2-8% for the
7 Guadalupe Estuary in South Texas to highs of-38% in the New York Bight and the Albemarle-Pamlico
8 Sound in North Carolina.
Table 2-10. Atmospheric
Waterbody
Albemarle-Pamlico Sounds
Chesapeake Bay
Delaware Bay
Long Island Sound
Narragansett Bay
New York Bight
N loads relative to total N
Total N Load
(million kg/yr)
23
170
54
60
5
164
loads in selected
Atmospheric N Load
(million kg/yr)
9
36
8
12
0.6
62
great waters.*
Percent Load from the Atmosphere
38
21
15
20
12
38
Based on ADN loads from the watershed only (excluding direct N deposition to the bay surface):
Waquoit Bay, MA
0.022
0.0065
29
Based on ADN directly to the waterbody (excluding ADN loads from the watershed):
Delaware Inland Bays
Flanders Bay, NY
Guadalupe Estuary, TX
Massachusetts Bays
Narragansett Bay
Newport River Coastal Waters, NC
Potomac River, MD
Sarasota Bay, FL
Tampa Bay, FL
1.3
0.36
4.2-15.9
22-30
9
0.27-0.85
35.5
0.6
3.8
0.28
0.027
0.31
1.6-6
0.4
0.095-0.68
1.9
0.16
1.1
21
7
2-8
5-27
4
>35
5
26
28
ADN = atmospheric deposition of N
Source: "Table from Deposition of Air Pollutants to the Great Waters-3rd Report to Congress (EPA, 2000)
9 The North Carolina case is a particularly rich example of computing defined airsheds and
10 characterizing the contributions from oxidized and reduced forms of N to underlying water bodies; see the
11 summary reported by Dennis and Mathur (2001). The Albemarle-Pamlico principal N airsheds were
12 computed to be 665,600 km2 for oxidized N, and 406,400 km2 for reduced N; these are factors of 25 and
13 15, respectively, larger than the watershed drainage area. NO emissions from within the oxidized N
14 principal airshed was estimated to explain 63% of all oxidized N deposition to the Albemarle-Pamlico
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1 system, very similar to the total of 60% of all reduced N deposition accounted for by NH3 emissions in
2 the reduced N principal airshed. The regional component to these computed N deposition totals varied
3 with the form of N such that local NH3 emissions inside North Carolina were estimated to account for
4 45% (hence, 55% left from the regional component) of the total reduced N deposition, while local NO
5 and NO2 emissions accounted for only 20% of the oxidized N deposition total (hence, leaving a regional
6 component of 80%).
Table 2-11. Natural and anthropogenic sources of atmospheric N compounds.
Chemical Form Sources (in approximate order of importance)
Reduced N Agricultural
NHs/ NUr Livestock waste (volatilized NHa)
Chemical fertilizers (volatilized NHs)
Bio mass burning
Dust from deforestation and land clearing
Urban and Rural (non-agricultural)
Wastewater treatment (volatilized NHi)
Fossil fuel combustion (from automobile catalytic converters)
Natural
Bio mass burning (forest and grass fire)
Decomposition of organic matter
Dust and aerosols
Volcanism
Oxidized Nitrogen Urban and Rural (non-agricultural)
NO, N02, NOf- Fossil fuel combustion
Mobile and stationary engines
Powerplants and industrial
Natural
Bio mass burning
Lightning
Photolysis of N20 (air, land, water)
Dust and aerosols generated by storms
Microbially mediated volatilization
Organic Nitrogen Agricultural
(Dissolved and Particulate) Dust and volatilization of wastes*
Urban and Rural (non-agricultural)
Dust or aerosols*
Natural
Atmospheric photochemical and lighting
Biological production in oceans*
* = possible, but little known about sources (the major chemical forms of atmospheric N compounds are the reduced, oxidized, and organic forms)
Source: Swackhameret al. (2004).
7 Chemically, N deposited from the atmosphere directly or indirectly can be present as an oxide or in
8 reduced form as NH3 and NH4+ or as dissolved or particulate organic N; see the listing in Table 2-11 for a
9 division of these and an approximate ranking of source strengths. NO and NO2, chiefly from fossil fuel
10 combustion, dominate total N pollution in the U.S. at ~50 to 75% of the total; see the descriptions of this
11 chemistry in Section 2.6.2 and of sources above.
12 CAFOs and other intensified agricultural production methods have resulted in greatly increased
13 volumes of animal wastes, of which 30 to 70% may be emitted as NH3 (Whitall, 2001). The increase in
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1 reduced N deposition in the U.S. measured as increased NH4+ deposition correlates well with the local
2 and regional increases in this agricultural intensity (Whitall, 2001). Moreover, the increases in NH4+
3 deposition in the U.S. track the effects in Europe where animal operations have dominated agricultural
4 production for much of the previous 100 years and where NH4+ is the dominant form of N deposited from
5 the atmosphere (Holland, 1999). Tables 2-11 and 2-12 list several important watersheds and their
6 respective oxidized (Table 2-12) and reduced (Table 2-13) airsheds. Airsheds for oxidized N tend to be
7 larger than those for reduced N owing to differences in the transport and deposition of NOx and NHX
8 described above in Section 2.6.
9 Considerable uncertainty attaches to estimates of the third form of atmospherically derived N,
10 organic N, in part because convenient methods for measurement and analysis are not widely available; see
11 Table 2-11. Intensive studies at individual sites have shown, however, that for the North Carolina coast,
12 for example, 30% of rain water N and deposition consisted of organic N, 20-30% of which was then
13 available to primary producers on time scales of hours to days (Peierls, 1997).
Table 2-12. Characteristics of oxidized-nitrogen airsheds.
Watershed
Casco Bay
Great Bay
Narragansett Bay
Long Island Sound
Hudson/Raritan Bay
Barnegat Bay
Delaware Bay
Delaware Inland
Bays
Chesapeake Bay
Pamlico Sound
Winyah Bay
Charleston Harbor
St. Helena Sound
Altamaha
Tampa Bay
Apalachee Bay
Apalachicola Bay
Mobile Bay
Lake Pontchartrain
Barataria-
Terrebonne
Size Size Factor Over Watershed
(km2) Area
624,000
547,000
595,200
905,600
912,000
505,600
729,600
326,400
1,081,600
665,600
886,400
806,400
588,800
678,400
256,000
441,600
812,800
992,000
659,200
409,600
244
214
138
22
22
361
22
584
6.5
25
19
20
48
18
45
31
16
8.7
17
55
% Ox-N Deposition Airshed NOx Emissions as % of E. North
Explained America
47
60
73
70
62
67
75
52
76
63
69
56
59
68
76
50
69
68
63
63
10
13
18
23
25
16
26
12
34
18
24
18
11
13
5
9
17
17
11
8
Efficiency of Deposition % dep. per
%emiss.
4.7
4.6
4.1
3.0
2.5
4.2
2.9
4.3
2.2
3.5
2.9
3.1
5.4
5.2
15.2
5.6
4.1
4.0
5.7
7.9
Source: http://www.epa.gov/AMD/Multimedia/characteristicsTable.html. Table generated by Robin Dennis, NOAA/USEPA.
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Table 2-13. Characteristics of principal airsheds for reduced-N deposition.
Watershed
Chesapeake Bay
Pamlico Sound
Apalachee Bay
Principal Red-N Airshed
Area (km2)
668,000
406,000
310,000
Red-N Area as % of OX-N
Area
64%
61%
70%
% Red-N Deposition Explained by
Airshed Emissions
55%
60%
45-50% est.
Airshed NHs Emission as % of
E. North American Emissions
11%
6.8%
4.3%
Source: http://www.epa.gov/AMD/Multimedia/reducedTable.html; Table generated by Robin Dennis, NOAA-ARL/ USEPA-NERL.
2.8.5. PRB Concentrations of NOx and SOx
1 Background concentrations of NOx and SOx used for purposes of informing decisions about
2 NAAQS are referred to as PRB concentrations. PRB concentrations are those concentrations that would
3 occur in the U.S. in the absence of anthropogenic emissions in continental North America (defined here as
4 the U.S., Canada, and Mexico). PRB concentrations include contributions from natural sources
5 everywhere in the world and from anthropogenic sources outside these three countries. Biogenic
6 emissions from agricultural activities are not considered in the formation of PRB concentrations.
7 Background levels so defined facilitate separation of pollution levels that can be controlled by U.S.
8 regulations (or through international agreements with neighboring countries) from levels that are
9 generally uncontrollable by the U.S. EPA assesses risks to human health and environmental effects from
10 NO2 and SO2 levels in excess of these PRB concentrations.
11 The MOZART-2 global model of tropospheric chemistry (Horowitz, 2003) is used to diagnose the
12 PRB contribution to NOX and SOX levels and to total (wet plus dry) deposition. The model setup for the
13 present-day simulation has been published in a series of papers from a recent model intercomparison
14 (Dentener, 2006; Dentener, 2006; Shindell, 2006; Stevenson, 2006; van Noije, 2006).
15 Background SO2 concentrations are orders of magnitude smaller, < 10 ppt overmuch of the
16 CONUS as shown in the middle panel of Figure 2-44. Maximum PRB SO2 concentrations are 30 ppt. In
17 the Northwest where there are geothermal sources of SO2, the contribution of PRB to total SO2 is 70 to
18 80%. However, excepting this, PRB contributes < 1% to present-day SO2 concentrations in surface air as
19 shown in the bottom panel Figure 2-44.
20
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Total
1ZO°W
100°W
< 0.50 2.80 5.10 7.40 9.70
12.00
ppb
Background
120°W
ioo°w
so°w
< 0.01
0.06
0.11
0.15
0.20
0.25
ppb
Percent Background Contribution
120°W
100°W
so°w
10
20
3D
40
50
Figure 2-41. Annual mean concentrations of H02 (ppb) in surface air over the U.S. in the present-day
(upper panel) and policy relevant background (middle panel) MOZART-2 simulations. The bottom
panel shows the percentage contribution of the background to the present-day concentrations.
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Total
120°W
0.01
1.21
2.41
3.BO
4.SO
B.OO
ppb
Background
120°W
ioo°w
BO°W
< D.001 O.OOB 0.011 0.015
0.020
0.025
ppb
Percent Background Contribution
< i 5 10 15 20 25
Figure 2-42. Annual mean concentrations of SOa (ppb) in surface air over the U.S. in the present-day
(upper panel) and policy relevant background (middle panel) MOZART-2 simulations. The bottom
panel shows the percentage contribution of the background to the present-day concentrations.
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1 The spatial pattern of NOY (defined in the model as HNO3 + NH4NO3 + NOX + HO2NO2 +
2 RONO2) in wet and dry deposition is shown in Figure 2-45. The upper panel of this figure shows that
3 highest values are found in the eastern U.S. in and downwind of the Ohio River Valley. The pattern of N
4 deposition in the PRB simulation shown in the Figure 46 middle panel, however, shows maximum
5 deposition centered over Texas and in the Gulf Coast region, reflecting a combination of N emissions
6 from lightning in the Gulf region, biomass burning in the Southeast, and from microbial activity in soils
7 with maxima in central Texas and Oklahoma. The bottom panel of Figure 2-45 shows that the PRB
8 contribution to N deposition is < 20% over the eastern U.S., and typically < 50% in the western U.S.
9 where NOy deposition is already lower at 25 to 50 mg N/m2/yr.
10 Present-day deposition of SO2 and pSO4 is largest in the Ohio River Valley, due to coal-burning
11 power plants in that region, while background deposition is typically at least an order of magnitude
12 smaller; see Figure 2-46. Over the eastern U.S., the background contribution to SOX deposition is < 10%,
13 and it is even smaller, < 1%, where present-day SOX deposition is highest. The contribution of PRB to S
14 deposition is highest in the western U.S. at > 20% because of the geothermal sources of SO2 and
15 oxidation of DMS in the surface of the eastern Pacific.
16 Figure 2-47 shows results from MOZART-2 discussed above as compared with those from another
17 tropospheric chemistry model, GEOS-Chem (Bey, 2001), which was previously used to diagnose PRB O3
18 concentrations (Fiore, 2003; EPA, 2006). In both models, the surface PRB NOX concentrations tend to
19 mirror the distribution of soil NO emissions, which are highest in the Midwest. The NO emissions in
20 GEOS-Chem are greater than those in MOZART-2 by nearly a factor of 2 reflecting different assumptions
21 regarding the contribution to soil NO emissions largely through fertilizer, since GEOS-Chem total soil
22 NO emissions are actually higher than MOZART-2 at 0.07 versus 0.11 Tg N over the U.S. in July. Even
23 with the larger PRB soil NO emissions, however, surface NOX concentrations in GEOS-Chem are
24 typically < 500 ppt.
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Total
120°W
ao°w
50
290
530
770
1010
1250
120°W
25
Background
ioo°w
BO°W
45
65
105
125
Percent Background Contribution
< 5 14 23 32 41 50
Figure 2-43. Annual mean concentrations of wet and dry deposition of HMOs, NH4N03, NOx, H02N02,
and organic nitrates (mg N/m2/yr) in surface air over the U.S. in the present-day (upper panel) and
policy relevant background (middle panel) MOZART-2 simulations. The bottom panel shows the
percentage contribution of the background to the present-day concentrations.
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Total
120°W
so°w
100
800
1500
2200
2900
3600
Background
120°W
ioo°w
so°w
10
16
22
28
34
40
Percent Background Contribution
130°W
ioo°w
ao°w
10
20
30
40
50
Figure 2-44. Annual mean concentrations of SOx deposition (SO? + pS04) (mg S/m2/yr) in surface air
over the U.S. in the present-day (upper panel) and policy relevant background (middle panel)
MOZART-2 simulations. The bottom panel shows the percentage contribution of the background to
the present-day concentrations.
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VOZART-2 SOIL NO
COS 15 2B
< D 3. 11 IS 23 2B
GEOS-Cn&m
MOZART-2 Swface MO^ JUL
-.T!J
Figure 2-45. July mean soil NO emissions (upper panels; 1 x 109 molecules/cm2/s) and surface PRB
NOx concentrations (lower panels; ppt) over the U.S. from MOZART-2 (left) and GEOS-Chem (right)
model simulations in which anthropogenic Os precursor emissions were set to zero in North
America.
1 First, the role of PRB in contributing to NO2 and SO2 concentrations in surface air is considered.
2 Figure 2-41 shows the annual mean NO2 concentration in surface air in the base case simulation (top
3 panel) and from the PRB simulation (middle panel), along with the percentage contribution of the
4 background to the total base case NO2 concentrations (bottom panel). Maximum concentrations in the
5 base case simulation occur along the Ohio River Valley and in the Los Angeles basin just as they do in
6 reported measurements; see the section on emissions and concentrations above. While present-day
7 concentrations are often > 5 ppb, PRB is < 300 ppt over most of the CONUS and < 100 ppt in the eastern
8 U.S. The distribution of PRB (middle panel of Figure 2-42) largely reflects the distribution of soil NO
9 emissions, with some local enhancements due to biomass burning such as is seen in western Montana. In
10 the northeastern U.S., where present-day NO2 concentrations are highest, PRB contributes < 1% to the
11 total concentrations.
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1 The spatial pattern of present-day SO2 concentrations over the CONUS is similar to that of NO2,
2 with highest concentrations of > 5 ppb along the Ohio River Valley; see the upper panel Figure 2-43.
3 It is also instructive to consider measurements of SO2 at relatively remote monitoring sites, i.e.,
4 ones located in sparsely populated areas not subject to obvious local sources of pollution. Berresheim
5 et al. (1993) used a type of atmospheric pressure ionization mass spectrometer (APIMS) at Cheeka Peak,
6 WA (48.30N, 124.62W, 480 m asl), in April 1991 during a field study for DMS oxidation products: SO2
7 concentrations there ranged from 20 to 40 ppt. Thornton et al. (Thornton, 2002) have also used an APIMS
8 with an isotopically labeled internal standard to determine background SO2 levels and found 25 to 40 ppt
9 in northwestern Nebraska in October 1999 at 150m above ground using the NCAR C-130. These values
10 are comparable to remote central south Pacific convective boundary layer SO2 (Thornton, 1999).
11 In summary, the PRB contribution to NOX and SOX over the CONUS is very small, except for SO2
12 in areas with volcanic activity.
2.9. Ambient Monitoring and Reported Concentrations of
Relevant N and S Species
13 Observational systems supporting air quality and related assessments include routine regulatory
14 networks, deposition networks, intensive field studies, remote sensing systems, sondes, aircraft
15 campaigns, satellites, and focused fixed site special purpose networks. Major networks currently
16 operating are emphasized; reference to other networks that have been discontinued, or that were only
17 intended for a specific operating period, is also provided. The focus is on routinely operating North
18 American air quality networks with limited coverage of European and international efforts relevant to
19 North American assessments.
20 The scope of network coverage is broad and relatively shallow, reflecting intent to describe the
21 observational foundation enabling integration of spatial scales, environmental media, and pollutant
22 categories. In addition to fixed-site, surface-based air quality networks, systems providing total Earth
23 column and vertical gradient information meteorological programs are included as well as operations
24 designed to address climate forcing gases and aerosols, long range transport and stratospheric ozone.
25 Cursory descriptions of recent intensive field campaigns are included to further foster integration of
26 multiple observation platforms and air quality modeling platforms.
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2.9.1. Routine Air Monitoring Networks in North America
1 Routine ambient air and deposition monitoring networks in North America provide more than 3000
2 fixed platforms measuring numerous gaseous species and aerosol properties. Many of these long-standing
3 network systems were initialized after the 1970 CAA, subsequent CAA amendments, NAAQS reviews
4 and National Academy of Sciences (NAS) recommendations resulting in periodic step enhancements to
5 these routine networks. Examples include CASTNet and the National Atmospheric Deposition Program
6 (NADP) addressing acidification; the Photochemical Assessment Monitoring Stations (PAMS) in
7 response to persistent O3 pollution and to monitor O3 precursors including NOX; and the PM2 5 network.
8 Table 2-14 lists the networks, sponsoring agencies, site densities, dates of operation, locations, and
9 measurement parameters.
Table 2-1 4.
Network
Major routine operating air monitoring networks.5
Lead
Federal NumDer |njtjated Measurement Parameters
. of Sites
Agency
Location of Information and/or Data
State/Local/Federal Networks
NCore—National Core Monitoring EPA
Network
SLAMS—State and Local Ambient EPA
Monitoring Stations
STN—PM25 Speciation Trends EPA
Network
PAMS—Photochemical EPA
Assessment Monitoring Network
IMPROVE—Interagency Monitoring NPS
of Protected Visual Environments
CASTNet—Clean Air Status and EPA
Trends Network
GPMP—Gaseous Pollutant NPS
Monitoring Network
POMS—Portable Ozone Monitoring NPS
Stations
Passive Ozone Sampler Monitoring NPS
Program
NADP/NTN—National Atmospheric USGS
Deposition Program / National
Trends Network
NADP/MDN—National Atmospheric None
Deposition Program / Mercury
Deposition Network
AIRMoN—National Atmospheric NOAA
Deposition Program / Atmospheric
Integrated Research Monitoring
Network
IADN—Integrated Atmospheric EPA
Deposition Network
NAPS—National Air Pollution Canada
Surveillance Network
75
-3000
300
75
2008
1978
1999
1994
110 plus
67 protocol
sites
33
43
200+
1987
1987
2002
1995
03, N0/N02/N0v, S02, CO, http://www.epa.gov/ttn/amtic/monstratdoc.htm
PM25/PMio-2.52, PM25Speciation,
NHa, HNOa, surface meteorology3
03, N0x/N02, S02, PM25/PMio, CO, Pb http://www.epa.gov/ttn/airs/airsaqs/aqsweb/aqswebhome.htm
PM25, PM25 speciation, major ions,
metals
03, NOx/NOy, CO, speciated VOCs,
carbonyls, surface meteorology and
upper air
PM25/PMio, major ions, metals, light
extinction, scattering coefficient
Os, S02, major ions, calculated dry
deposition, wet deposition, total
deposition for S/N, surface
meteorology
Os, N0x/N0/N02, S02, CO, surface
meteorology, (plus enhanced
monitoring of CO, NO, NOx, NOv, and
S02 plus canister samples for VOC at
three sites)
Os, surface meteorology, with
CASTNet-protocol filter pack (optional)
S042~, NOs, ammonium, nitric acid,
sulfur dioxide
Os dose (weekly)
http://www.epa.gov/ttn/airs/airsaqs/aqsweb/aqswebhome.html
http://www.epa.qov/ttn/airs/airsaqs/aqsweb/aqswebhome.htm
http://vista.cira.colostate.edu/IMPROVE/
http://www.epa.gov/castnet/
http://www2.nature.nps.qov/air/Monitorinq/network.cfmtfdata
http://www2.nature.nps.gov/air/studies/port03.cfm
http://www2.nature.nps.gov/air/Studies/Passives.cfm
1978 Major ions from precipitation chemistry http://nadp.sws.uiuc.edu/
90+ 1996 Mercury from precipitation chemistry http://nadp.sws.uiuc.edu/mdn/
8 1984 Major ions from precipitation chemistry http://nadp.sws.uiuc.edu/AIRMoN/
20 1990 PAHs, PCBs, and organoch brine
compounds are measured in air and
precipitation samples
152+ 1969 S02, CO, 03, NO, N02, NOx, VOCs,
SVOCs, PMio, PM25, TSP, metals
http://www.epa.gov/glnpo/monitoring/air
http://www.etcentre.org/NAPS/
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Network
Precipitation Monitoring Network
Mexican Metropolitan Air Quality
Network
Air Toxics Monitoring Networks
NATTS— National Air Toxics Trends
Station
State/Local Air Toxics Monitoring
Monitoring Network
Tribal Monitoring Networks
Tribal Monitoring
Industry/Research Networks
New Source Permit Monitoring
Monitoring Network
ARIES /SEARCH— Aerosol
Research Inhalation Epidemiology
Study / Southeastern Aerosol
Research and Characterization
Study experiment
SOS - SERON— Southern Oxidant
Study - Southeastern Regional
Oxidant Networks
National/Global Radiation Networks
RadNet— formerly Environmental
Radiation Ambient Monitoring
System (ERAMS)
SASP— Surface Air Sampling
Program
NEWNET Neighborhood
Environmental Watch Network
Test Ban Treaty
Other Networks
UV Index— EPA Sunwise Program
UV Net— Ultraviolet Monitoring
Program
UV-B Monitoring and Research
Program
SURFRAD— Surface Radiation
Budget Network
PRIMENet— Park Research &
Intensive Monitoring of Ecosystems
NETwork
BioWatch
Lead
Federal
Agency
Canada
Mexico
EPA
EPA
EPA
EPA
None
None
None
EPA
EPA
DHS
DOE
DOE
EPA
EPA
USDA
NOAA
NPS
No details
Number
of Sites
29
93
23
250+
34
120+
variable
9
8
-40
200+
41
26
80
-50 U.S.
cities
21
35
7
14
Initiated
2002
777
2005
1987
1998-
2005
1995
variable
1980
1992
1990
1973
1963
1993
1996
2002
2002
1992
1993
1997
Measurement Parameters
03, NO, N02, NOymass, PM2s
speciation, major ions for particles and
trace gases, precipitation chemistry for
major ions
03, NOx, CO, S02, PMio, TSP
VOCs, Carbonyls, PMio metals4, Hg
VOCs, Carbonyls, PMio metals4, Hg
CDDs, CDFs, dioxin-like PCBs
03, N0x/N02, S02, PM25/PMio, PAN,
NHs, PM2s, PMio and coarse fraction
CO, Pb
03, N0x/N02, S02, PM25/PMio, CO Pb
03, NOx, PM25/PMio, CO, S02, Pb,
VOCs, surface meteorology
03, N0/N02/N0y, S02, CO,
PM25/PMio, PM2s speciation, major
ions, NHs, HNOs, scattering coefficient,
surface meteorology
Os, NO, NOy, VOCs, CO, surface
meteorology
Radionuclides and radiation
89Sr, 90Sr, naturally occurring
radionuclides, 7Be, 210Pb
Ionizing gamma radiation, surface
meteorology
Radionuclides and noble gases
Calculated UV radiation index
Ultraviolet solar radiation (UV-B and
UV-A bands)
UV-B radiation
Solar and infrared radiation, direct and
diffuse solar radiation,
photosynthetically active radiation,
UVB, spectral solar, meteorological
parameters
Ozone, wet and dry deposition,
visibility, surface meteorology, and
ultraviolet radiation
Location of Information and/or Data
http://www.msc.ee. gc.ca/capmon^ndex e.cfm
See CEC, 19977
http://www.epa.gov/ttn/airs/airsags/agsweb/agswebhome.htm
http://www.epa.gov/ttn/airs/airsags/agsweb/agswebhome.htm
http://cfpub2.epa. gov/ncea/cfm/recordisplav.cfm?deid=22423
http://www.epa.gov/ttn/airs/airsaqs/aqsweb/aqswebhome.htmm
Contact specific industrial facilities
http://hrm.radian.com/houston/how/index.htm
http://www.atmospheric-
research.com/studies/SEARCH/index.html
http://www.ncsu.edu/sos/pubs/sos3/State of SOS 3.pdf
http://www.epa.gov/enviro/html/erams/
http://www.eml.doe.gov/databases/sasp/
http://newnet.lanl.gov/stations.asp
http://www.clw.org/archive/coalition/briefv3n14.htm
http://www.epa.gov/sunwise/uvindex.html
http://www.epa.gov/uvnet/access.html
http://uvb.nrel.colostate.edu/UVB/isp/uvb climate network.isp
http://www.srrb.noaa.gov/surfrad/index.html
http://www.forestrv.umt.edu/research/MFCES/programs/primenet/
1 Two important ambient air networks focused on environmental welfare effects were established in
2 the mid-1980s. The Interagency Agency Monitoring of Protected Visual Environments (IMPROVE)
3 network with >100 sites in National Parks and other remote locations is used primarily to assess visibility
4 impairment, but has provided a reliable long-term record of PM mass and major speciation components
5 and served as a model for the later deployment of STN; see Figure 2-46. STN (now part of CSN) has
6 provided an urban complement to characterize aerosol composition; see Figure 2-47. Additional, minor
7 networks identified in Figure 2-46 include those of the state and local air agencies deployed since the
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1 mid-1980s measuring a variety of aerosol- and gas-phase, hazardous air pollutants (HAPs) at -200
2 locations, and a modest National Air Toxics Trends (NATTS) network of 23 sites.
Ambient Air Monitoring Stations in the United States
NATTS
PM,5Speciation
PAMS
CASTNet
•ove
Lead
CO
Figure 2-46. Aggregate map of the majority routine U.S. monitoring stations illustrating relatively
broad coverage across the continental U.S. with noted spatial gaps in low populated areas.
3 CASTNET was established in the early 1990s to track changes in dry deposition of major inorganic
4 ions and gaseous precursors associated with the CAA Title IV reductions in S and N, designed to address
5 surface water acidification in eastern North America. Complementing ongoing precipitation
6 measurements from NADP, CASTNET (see Figure 2-46) has provided a valuable source of model
7 evaluation data for many of the large regional scale applications since the 1990s.
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Upper Midwest
Industrial Midwest
Northeast
02 03 04 05 06
Southern CA
02 03 04 05 06
: IZI Sulfate ~~
I Nitrate
I Elemental
I Organic carbon
02 03 04 05 06
^•Crustal
Source: 2006 EPA Air Quality Trends Report (www.epa.gov/air/airtrends/index.html).
Figure 2-47. Trends in regional chemical composition of PIVk.s aerosols based on urban speciation
sites and averaged over the entire 2006 sampling period.
I Deployment of the PAMS and the PM2 5 networks from the early 1990s through 2002 markedly
2 enhanced the spatial, temporal, and compositional attributes of gases and aerosols, partially supporting
3 user needs beyond NAAQS compliance (e.g., public reporting and forecasting of adverse air quality;
4 implementation efforts including air quality model evaluation, and source apportionment and pattern
5 (spatial and temporal) analysis of precursor species).
NCore Measurements
Level 2: - 75 Multi-
pollutant (MP)
Sites/'Core Species"
Plus Leveraging From
PAMS,
Speciation Program,
Air Toxics
A'.lrlr!
^A
Level 1. 3-10 Master
Sites Comprehensive
Measurements,
Advance Methods
Serving Science and
Technology Transfer
Needs
YTT\
/ Level 3 V"
ium "Core" Level 2 Measurements
Single Pollutant
Sites (e.g.> 500
sites each for O,
and PM!5 and
related spatial
Mapping Support
Continuous NO,NOV.SO2.CO.PM2 5.
PM10/PMc, O3 Meteorology (T.RH.WS.WO);
Integrated PM; 6 FRM, HNO3. NH3,
Figure 2-48. Original 3-tiered NCore design (left) and proposed site locations for Level 2 multiple
pollutant sites.
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1 A new multiple pollutant-monitoring network, NCore was begun in 2006. When finally
2 implemented in 2009, NCore will provide a minimum of 75 Level 2 sites (Figure 2-48) in most major
3 urban areas and important transport corridor and background locations. NCore will include a variety of
4 trace gas, aerosol mass and speciation measurements which are intended to support multiple data user
5 needs (e.g., air quality model evaluation, long-term epidemiological studies). In addition to establishing a
6 multiple pollutant measurement framework, the NCore sites are intended to provide a backbone of central
7 location sites that can be complemented by additional (existing and new) stations to address more specific
8 spatial resolution requirements.
2.9.1.1. Pollutant Categories
Inorganic Gas-phase Species
9 The majority of U.S. sites measuring the criteria gases O3, NOX, SO2, and CO are incorporated
10 within the State and Local Air Monitoring Systems (SLAMS) networks. Most of the SLAMS sites are
11 located in populated urban locations with a variety of siting requirements typically intended to site for
12 high concentration locations resulting in an emphasis on downwind (from urban center) locations for O3,
13 center-city locations for NOx, roadway intersection and canyon type locations for CO, and proximity to
14 major power generating facilities for SO2. Most monitoring platforms include multiple sensors to improve
15 efficiency of network operations and adding interpretive value.
16 Measurements of NOY, HNO3, and NH3 are useful in a variety of ways important for assessing
17 NOx and SOx environmental pollution effects; some of these ways include: (1) evaluation of emissions
18 inventories; 2) inputs to and sources of evaluation for numerical and observation-based models; and
19 (3) establishing baseline N budgets for watershed and field accountability assessments. NOY, HNO3, and
20 NH3, together with true NO2 and pNFL,, are significant components of the total N budget but remain
21 poorly characterized at the national scale. In largest part, a lack of reliable, cost effective continuous
22 measurement methods has hindered deployment of instruments for HNO3 and NH3. In the U.S., the
23 SEARCH network of eight sites is the only source of routine, continuous ambient air measurements of
24 NOY together with NH3 and HNO3; see discussions in Blanchard and Hidy (2003) and Zhang et al, 2006.
25 CASTNET recently has deployed a network of inexpensive passive NH3 samplers which have promise
26 for characterizing broad spatial patterns, with extended averaging times beyond 24 h. This is a significant
27 development since most other NH3 sampling is focused on high source regions in agricultural settings
28 designed to improve emission factors for NH3, resulting in very limited NH3 characterization of ambient
29 environments.
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Particulate Matter Mass
1 Nearly 1500 PM2 5 gravimetric sites were established before 2000 to determine nonattainment
2 status of counties throughout the U.S. following the 1997 promulgation of the PM2 5 particulate matter
3 standard. The network has evolved to add over 500 continuous PM2 5 monitors and a reduction of 24-h
4 gravimetric samplers below 1000 sites (see Figure 2-49) that support air quality forecasting and public
5 notification of adverse air quality using the Air Quality Index (AQI), a generalized indicator of exposure
6 concern linked to the NAAQS (http://www.epa.gov/airnow/). While this expansion of continuous PM2 5
7 sites adds spatial coverage of highly temporally resolved information, the mix of instrument types
8 compromises data harmonization across sites and geographic areas with different operational
9 characteristics.
:->%;A ^4'"'
^ij-'-v,-i:/^:
^JyftfeC
••^.iii^^'-f
h.^r^^F
*-•«. \ /" '
^ V«^ . PM,, FRWFEM Situ
< \ Ozone Sites
IX CD
Andersen BAM
Correlated Radiance Nephelometet
Me! One BAM
POMS
TEOM
Figure 2-49. Maps illustrating breadth of PMa.s FRM and FEM and Os network (left); and PM2.5
continuous samplers (right).
Particulate Matter Speciation
10 IMPROVE has provided nearly a two-decade record of major components including SO42~, NO3~,
11 OC and EC, and trace metals of PM2 5 aerosols in pristine areas of the U.S. Over 300 speciation sites were
12 added from 2000-2002 in urban areas of the U.S. to assist assessment efforts related to the PM2.s
13 standard. This network (see Figure 2-50) across rural areas has been a widely used resource across
14 disciplines (exposure/epidemiological, atmospheric science communities), organizations (academia,
15 industry, government agencies), and several spatial scales of interest (long-range hemispheric transport to
16 near source).
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C2?-
Speciation SLAMS
IMPROVE
Speciation Trends Sites
Continuous Speciation Sites with Multiple Measurements
Figure 2-50. Locations of chemical speciation sites delineated by program type.
1 The speciation networks typically collect a 24-h sample once every 3 or 6 days. CASTNET
2 provides weekly averaged measurements of major ions including SO42 , NO3 , calcium (Ca2+), sodium
3 (Na+), potassium (K+), NH4+, and magnesium (Mg2+) integrated over all aerosol sizes by means of open-
4 face filter packs. Daily, 24-h speciated samples often requested by health effects researchers is limited to
5 fewer than five sites in the U.S. and Canada. Similarly, a small and variable number of sites, fewer than
6 10 most years, provide near-continuous speciation data, usually limited to some combination of pSO4,
7 pNOs, and EC and OC. In addition, the 22 NATTS sites include aetholometers measuring semi-
8 continuous light absorption, often used as a surrogate for EC.
9 The EPA PM Supersites Program (Wittig, 2006, 92821) provided highly time-resolved aerosol
10 measurements at 8 cities in the U.S. for a mix of time periods between 1999 and 2004. Depending on
1 1 location and time period, a number of different instrument configurations were deployed ranging from
12 additional spatial coverage of standard speciation sites to systems capturing near-continuous size-
13 distributed chemical composition profiles.
14 The SEARCH program, funded since 1998 and EPRI and Southern Company, has provided
1 5 continuous, semi-continuous and integrated data on a wide variety of species from eight highly
16 instrumented paired research sites in the Southeastern U.S. in Alabama, Florida, Georgia and Mississippi
17 (see descriptions in Hansen (2003). At present, the suite of measurements made at all sites includes: (1)
18 24-hr PM25 filter samples, analyzed for mass, ions, (SO4, NO3, NH4+), OC, EC, and elements as measured
19 by XRF; 2) two 24-h coarse mass ions, and XRF elements; 3) 24-h gaseous NH3 as collected with an
20 annular denuder for continuous (minute-to-hourly) PM2 5 mass, OC, EC, NH4+, NOs and SO42 ; 4) light-
21 scattering and light absorption; 5) continuous O3, NO2, NOY, NO3", CO, and SO2; 6) continuous 10-m
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1 meteorological parameters: wind speed, wind direction, temperature, relative humidity, solar radiation,
2 barometric pressure, and precipitation.
Precipitation-based Networks
3 Precipitation chemistry is the primary link between atmospheric and terrestrial and aquatic systems.
4 The NADP (http ://nadp. sws.uiuc.edu/) oversees a network of more than 250 sites (see Figure 2-51) where
5 most of the major ions key to aquatic chemistry addressing acidification and eutrophication effects are
6 measured. The NADP includes the Mercury Deposition Network (MDN) of ~90 sites and 7 Atmospheric
7 Integrated Research Monitoring Network (AIRMoN) sites providing greater temporal resolution.
8 The joint Canadian and U.S. Integrated Atmospheric Deposition Network (IADN)
9 (http ://www.msc-smc.ec .gc .ca/iadn/indexe .html) includes a mix of master and satellite stations across
10 the Great Lakes where both precipitation and ambient air are sampled for a range of toxics compounds.
11 The IADN emphasizes many of the more persistent organic compounds including polychlorinated
12 biphenyl compounds, pesticides, dioxins, and toxic metals such as lead (Pb), cadmium (Cd), arsenic (As),
13 and selenium (Se).
2.9.2. Intensive Field Campaigns
14 Intensive field campaigns of relatively short duration supplement routine longer term monitoring
15 networks by enhancing spatial, temporal, and compositional distribution of atmospheric species to better
16 elucidate physical/chemical processes relevant to the fate, transport and removal of secondarily formed
17 gases and aerosols. Typically, these campaigns utilize some combination of aircraft studies, high time
18 resolved instrumentation and advanced analytical methods (in-situ and laboratory) all complementing
19 routine ground based measurements, which usually do not address reactive gaseous species, aerosol size
20 distributions, organic chemistry characterization and vertically stratified data.
21 There has been a long history of intensive field campaigns starting with the Regional Air Pollution
22 Study (RAPS) in the 1970s which formed the basis evaluating the early photochemical gridded Eulerian
23 airshed models used in acid deposition and 03 assessments. Landmark campaigns in the U.S. through the
24 1980s and 1990s such as the Southern California Air Quality Study (SCAQS) (Lawson, 1990), the San
25 Joaquin Valley Air Quality Study (SJAQS)/Atmospheric Utility Signatures, Predictions, and Experiments
26 (AUSPEX) (Roth, 1988) and the Southern Oxidant Study (SOS) (Cowling and Furiness, 2000) were
27 reviewed as part of the 2000 NARSTO O3 assessment (Wittig, in press). Over the last decade there have
28 been a series of field campaigns focusing on characterization of surface level aerosols through the PM
29 Supersites program (Solomon et al., 2007). While the early campaigns focused on urban environments,
30 the Eulerian Model Evaluation Field Study (EMEFS) and SOS during the early 1990s shifted focus
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1 toward regional spatial scales consistent with the dominant air pollution concerns (acid rain and ozone) of
2 the time. In addition to addressing urban areas of concern such as Houston, TX, and Los Angeles, CA,
3 more recent campaigns have extended spatial scales beyond regional studies to address oceanic transport
4 and a variety of air pollution issues across the Northern Hemisphere, recognizing the importance of far
5 ranging source regions and continental scale atmospheric processes. Some of these campaigns include
6 local and regional studies for the northeast and southeast U.S., portions of Texas, and central and southern
7 California; intercontinental studies including those for transport across Atlantic, Pacific, and Indian Ocean
8 areas. A variety of federal and state entities have served as lead agencies forthese studies. Table 2-15
9 provides a listing of studies conducted since the mid-1990s with well-known campaigns as far back as the
10 1960s identified in footnotes.
.. J Prtc)pitJl)«n ^
Air O Air
Oxtff't o Ozone
ul«U Mjtttf Q Mjtl»rt* P
NlbCQtfl * A20l*
™&° cn"^ "'S^^^W""'"""'
S.^'^^^3^™^
«»3!!rBBv'*v™
" "|pj?3,.. J""a°°'
n-*—* Monitoring Stations
1^3^ a.-
nc»***J| """"I»I^E™
^^^M^d Port
. •
• .4 • I ..Ł"",*.,, oNADP/NTNIw-d.po.rf.cn)
. . . .*.." :«*^ 'NADP/MDN (mercury depo.,l,0r|
• . •*•*** «TIMEATM|iurfacevic*eroodil»)
"•• • *. A * .* I • CASTNET |*y depotihorv-ceaie)
^*- • • • • EcdogKal Rmaurcflt
.
• • •.-1At,d,c Surface Waters
• .
* ••
•« CltBi I Arc».
-5* CSHighly Eulroph'C Eiluonei
Cr,
Figure 2-51. Routinely operating North American precipitation and surface water networks. Upper
left, Canadian Air and Precipitation Monitoring Network (CAPMON); Upper right, Integrated
Atmospheric Monitoring Deposition Network (IADN); Bottom, National Atmospheric Deposition
Monitoring Program (NADP) with Time/LTM surface chemistry sites.
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Table 2-15. Air monitoring networks/campaigns for non-routine special intensive studies.
1
2
3
4
5
6
7
8
9
10
11
Lead
Agency1
Texas
Number ..,.,. Measurement
of Sites lmtlated Parameters
17 2006 03, NOx, NOy, S02,
haze, visibility, CO,
VOC, solar radiation,
surface meteorology,
upper air
Location of Information and/or
Data
http://www.utexas.edu/
research/ceer/texaqsll/PDF/
12-12-04_Projected_SurfaceSites
Jbl.pdf
Notes
Researchers from universities, state and federal agencies, private industry, and local
governments are joining forces to conduct a major field study to address air quality
issues in the eastern half of Texas. The study, planned for a period extending from Apr
2005 through Oct 2006, will examine regional ozone formation, transport of ozone and
ozone precursors, meteorological and chemical modeling, issues related to ozone
formation by highly reactive emissions, and partial late matter formation. It is anticipated
that the information from the study will be the scientific basis used for developing State
Implementation Plans (SIPs) for ozone (with concentrations averaged over 8 h),
regional haze, and, if necessary, for fine particulate matter (partial late matter less than
2.5 microns in diameter, PM2s.
NOAA 1 ship, 2006 03, NO, N02, NOv,
•) „;„„,, VOCs, C02, CO, S02,
2alrCmft HN03,NH3, other
reactive pollutants,
aerosols, meteoro-
logical parameters and
upper air
NOAA 3 aircraft 2006 03, NO, N02, NOy,
VOCs, C02, CO, S02,
HN03,NH3, other
reactive pollutants,
aerosols, meteoro-
logical parameters,
altitude — NOAA
aircraft
httrj://esrl.noaa.gov/csd/2006/
For TexAQS 2006, the NOAA air quality component will investigate, through airborne
and sea-based measurements, the sources, and processes that are responsible for
photochemical pollution and regional haze during the summertime in Texas. The focus
of the study will be the transport of ozone and ozone precursors within the state and the
impact of the long-range transport of ozone or its precursors.
http://cbud1.arc.nasa.gov/intex-b/ The export of air pollutants from urban to regional and global environments is a major
concern because of wide-ranging potential consequences for human health, cultivated
and natural ecosystems, visibility degradation, weather modification, changes in
radiative forcing, and tropospheric oxidizing capacity. During the spring of 2006 a highly
integrated atmospheric field experiment was performed over and around North
America. The Megacity Initiative: Local and Global Research Observations (MILAGRO),
http://www.eol.ucar.edu/projects/milagro/, resulted through a highly coordinated
collaboration between NSF (through MIRAGE-Mex), DOE (through MAX-Mex), NASA
(through INTEX-B) and a variety of research institution in the U.S. and Mexico and
involved ground and air borne activities centered on Mexico City, Mexico during March
2006. MILAGRO goals were greatly facilitated and enhanced by a number of
concurrent and coordinated national and international field campaigns and global
satellite observations.
1 EPA— Environmental Protection Agency; NASA — National Aeronautics and Space Administration; NOAA — National Oceanic and Atmospheric Administration; NPS — National Park
Service\NSF — National Science Foundation; UCSD — University of California San Diego (Scripts Institution of Oceanography)
2This study is part of the Central California Air Quality Studies (CCAQS) which comprise the California Regional Particulate Air Quality Study (CRPAQS) and the Central California
Ozone Study (CCOS). CCAQS is a multi-year effort of meteorological and air quality monitoring, emission inventory development, data analysis, and air quality simulation modeling.
Prior studies in California included: Southern California Ozone Study (SCOS97) — 1997; Integrated Monitoring Study (IMS95) —1995; San Joaquin Valley Air Quality Study (SJVAQS)
— 1990; SARMAP Ozone Study —1990; Southern California Air Quality Study (SCAQS) — 1987.
Historically, there have been many other field studies in the 1960s - 1990s that are not reflected in this Table that involve both fixed monitoring sites and aircraft; well known examples
include Regional Air Pollution Study (RAPS), Large Power Plant Effluent Study (LAPPES), Northeast Corridor Regional Modeling Program (NECRMP), Northeast Regional Oxidant
Study (NEROS), Persistent Ebvated Pollutant Episode (PEPE), and Lake Michigan Ozone Study (LMOS).
A synthesis of key findings and lessons learned from major field campaigns conducted over the last
two decades would elevate exposure of these programs to a wider audience potentially generating support
to enhance and sustain atmospheric process and model evaluation studies which are important
complements to routine ground based and satellite observation platforms. While the NARSTO database
(http://eosweb.larc.nasa.gov/PRODOCS/narsto/Table_narsto.html) provides access to raw data for various
field campaigns, coverage of campaigns beyond North America must be acquired from other sources. The
National Aeronautics and Space Agency (NASA) 's Atmospheric Data Science Center
(http://eosweb.larc.nasa.gov/) also provides access to some of the more recent field campaigns. These
web services would benefit potential users by providing intermediate descriptions of the scopes
(locations, time frames, measurement systems and models) of these campaigns, including key objectives
and finding.
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2.9.3. Satellite-Based Air Quality Observing Systems
1 An extensive array of satellite-based systems (see Table 2-16 and Table 2-17) with the capability of
2 measuring atmospheric column total species has been established by U.S. and European Satellite
3 programs lead by NASA and the National Oceanic and Atmospheric Administration (NOAA) in the U.S.
4 and the European Space Agency (ESA). A suite of satellites including Aqua, Aura, CALIPSO, OCO,
5 Glory, as well as NOAA-17, NOAA-18 and NPOESS, have either been launched since about the year
6 2000 or have other near-term proposed launch dates. Collectively, the remote sensing techniques for
7 measuring columns and/or profiles of aerosols (AOD), O3, CO, CO2, CH4, SO2, NO2, chlorinated
8 fluorocarbon compounds (CFCs), other pollutants, and atmospheric parameters such as temperature and
9 H2O content. Most of these satellites have a near-polar orbit allowing for two passes per day over a given
10 location. When taken together, a group of six satellites (Aqua, Aura, CALIPSO, OCO, as well as
11 CloudSat and PARASOL) coined the A-Train is being configured to fly in a formation that crosses the
12 equator a few minutes apart at around 1330 local time to give a comprehensive picture of earth weather,
13 climate, and atmospheric conditions.
14 Satellite imagery offers the potential to cover broad spatial areas; however, an understanding of
15 their spatial, temporal and measurement limitations is necessary to determine how these systems
16 complement ground based networks and support air quality management assessments.
Table 2-16. Satellite-based air quality observing systems.1'4
Instrument
OLS (Operational
Linescan System)
BUV (Backscatter
Ultraviolet Spectrometer)
SBUV (Solar Backscatter
Ultraviolet Spectrometer)
TOMS (Total Ozone
Mapping Spectrometer)
LIMS (Limb Infrared
Monitor of the
Stratosphere
ATMOS (Atmospheric
Trace Molecule
Spectra scopy)
CLAES (Cryogenic Limb
Array Eta Ion
Spectrometer)
Satellite ^
DMSP DOD
satellites
Nimbus 4 NASA
Nimbus 7 NASA
Nimbus? NASA
Meteor 3 Earth-
Probe
Nimbus 7 NASA
Spacelab 3 NASA
ATLAS -1,2,3
UARS NASA
Initiated
1962?
1970-
1980
1978-
1993
1978-
1993
1991-
1994
1996
1978-
1979
1985,
1992,
1993,
1994
1991-
1993
Measurement °rbit* ,
Parameters DHorlzo"tal
Resolution
Identify fires and smoke Polar Imagery
plume only
03, C09, S02 Sun
synchronous
03, S02 Polar
03, S02, Aerosols Polar~100km
03, HNOs, N02, Polar
03, CFCb, CF2Cl2,
CION02, HCI, HF, CO,
CH4, HCN, HN03, NO,
N02,N20s, Aerosols
03, CFCb, CF2Cl2 CION02,
CH4, HN03, NO, N02,
N20, N20s, Aerosols
Location of Information and/or Data
http://www.af.mii/f actsheets/factsheet.asp?fslD=94
http://nssdc.gsfc.nasa.gov/database/MasterCatalog?sc=1970-025A
http://iwockv.gsfc.nasa.gov/n7toms/nimbus7tech.html
http://toms.gsfc.nasa.gov/fltmodel/spacecr.html
http://lims.gats-inc.com/about lims.html
http://remus.ipl.nasa.gov/atmos/sl3.html
http://umpgal.gsfc.nasa.gov/
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Instrument
HALOE (Halogen
Occultation Experiment)
ISAMS (Improved
Stratospheric and
Mesospheric Sounder)
MLS (Microwave Limb
Sounder)
GOES Imager
(Geostationary
Operational
Environmental Satellites)
GOES Sounder
(Geostationary
Operational
Environmental Satellites)
AVHRR (Advanced Very
High Resolution
Radiometer)
SBUV/2 (Solar
Backscattered Ultraviolet
Radiometer Model 2)
MOPITT (Measurement
of Pollution in the
Troposphere)
MISR (Multi-angle
Imaging
SpectroRadiomenter)
MODIS (Moderate
Resolution Imaging
Spectroradio meter)
AIRS (Atmospheric
Infrared Sounder)
HIRDLSfHigh
Resolution Dynamics
Limb Sounder)
MLS (Microwave Limb
Sounder)
OMI (Ozone Monitoring
Instrument)
TES (Total Emission
Spectrometer)
CALIPSO (Cloud-Aerosol
Lidar & Infrared
Satellite
Platform3
UARS
UARS
UARS
GOES-10
GOES-12
GOES-10
GOES-12
NOAA-15
NOAA-16
NOAA-172
NOAA-16
NOAA-172
EOS Terra
EOS Terra
EOS Terra
EOS Aqua
EOS Aqua
EOS Aura
EOS Aura
EOS Aura
EOS Aura
CALIPSO
Lead
Federal
Agency
NASA
NASA
NASA
NOAA
NOAA
NOAA
NOAA
NASA
NASA
NASA
NASA
NASA
NASA
NASA
NASA
NASA
Initiated
1991-
2005
1991-
1992
1991-
1999
1994
1994
1998
2000
1999
1999
1999
2002
2002
2004
2004
2004
2004
2005
Measurement
Parameters
03, HCI, HF, CH4, NO,
N 02, Aerosols
03, CO, CH4, N02, N20,
N20s Aerosols
03, CIO, CH3CN, HN03,
S02
Fire products for
WF_ABBA (imagery) and
GASP (aerosol optical
depth)
Total column Oi
Aerosol optical depth,
particle size information
and vegetation/ drought
index products related to
air quality through fires
Total and profile Oi from
surface to top of
atmosphere in ~5 km thick
Umkehr layers
CO, CH4
Aerosol properties and
plume height information
near the vicinity of fires
Os, aerosol optical depth,
particle size information,
fine particle fraction, and
forest fires
Total column ozone,
surface temperature,
temperature and moisture
vertical profiles, (plus
under development are CO
and C02 total column, Oi
vertical distribution, and
CH4 distribution)
03, CFCb, CF2Cl2,
CION02, CH4, HN03, N02,
N20, N205,
03, BrO, CIO, HOCI, HCI,
CO, HCN, CH3CN, HN03,
N20, OH, H02, S02
03, BrO, OCIO, HCHO,
N02.S02 and aerosol
03, NOy, CO, S02, CH4
Aero sol optical depth,
backscatter, extinction
Orbit &
Horizontal
Resolution
Geostationary
Geostationary
Polar
4km
Polar
Polar
22 x 22 km2
Polar ~1 km
Polar
1km
Polar
50km
Aerosols
Polar
Polar
Polar 26x42
km
Polar 0.3x0.3
km2
Location of Information and/or Data
http://umpgal. gsfc.nasa.gov/
http://umpgal.gsfc.nasa.gov/
http://umpgal.gsfc.nasa.gov/
http://www.nesdis.noaa.gov/
http://cimss.ssec.wisc.edu/goes/goesmain.htmltfsndrinfo
http://noaasis.noaa.gov/NOAASIS/ml/avhrr.html
http://www2.ncdc.noaa.gov/docs/podug/html/c4/sec4-4.htm
http://www.eos.ucar.edu/mopitt/
http://www-misr.ipl.nasa.gov/mission/introduction/welcome.html
http://modarch.gsfc.nasa.gov/index.php
http://www-airs.ipl.nasa.gov/
Polar http://aura.gsfc.nasa.gov/index.html
http://aura.gsfc.nasa.gov^ndex.html
12 x 24 km2 http://aura.gsfc.nasa.gov/index.html
http://aura.gsfc.nasa.gov^ndex.html
http://www-calipso.larc.nasa.gov/about/
Pathfinder Satellite
Observations)
OMPS
Ozone
Mapping and
Profiling Suite
NPOESS-
Preparatory
Project
NOAA 2006
Total column and vertical Polar
profile ozone data
http://www.ipo.noaa.gov/Proiects/npp.html
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Instrument
VIIRS (Visible Infrared
Imaging Radiometer
Suite)
Orbiting Carbon
Observatory
APS & TIM (Aerosol
Polarimetry Sensor &
Total Irradiance Monitor)
Satellite
Platform3
NPOESS-
Preparatory
Project
OCO
Glory
Lead
Federal
Agency
NOAA
NASA
NASA
...... Measurement
lmtlated Parameters
2006 Aerosol optical depth
2008 C02
2008 Black carbon soot, other
aerosols, total solar
irradiance, cloud images
Sun- synchronous, circular
Orbit &
Horizontal
Resolution
Polar
Polar
Low Earth
Orbit
Location of Information and/or Data
http://www.ipo. noaa.gov/Proiects/nrjp. html
http://oco.ipl.nasa.gov/
http://glorv.gsfc.nasa.gov/
1Non-U.S. satellite systems are not included in table at this time.
2As of 3/15/06 the operational satellite platforms may need to include NOAA-18.
3CALIPSO — Cloud-Aerosol Lidar & Infrared Pathfinder Satellite Observations
DMSP— Defense Meteorological Satellite Program
EOS — Earth Observing System
GOES — Geostationary Operational Environmental Satellites
NOAA — National Oceanic and Atmospheric Administrationl
NPOESS — National Polar-orbiting Operational Environmental Satellite System
OCO — Orbiting Carbon Observatory
UARS — Upper Atmosphere Research Satellite
4See the following table for additional information on NASA satellites, instrument systems, pollutants measured, and data availability:
Table 2-17. Key atmospheric chemistry and dynamics data sets at the NASA Goddard DAAC.
Missions
Instruments
Data Period
Spectral Region
Bands
03
BrO
CFCb
CF2Cl2
CIO
OCIO
CION02
HOCI
HCI
HF
HCHO
CO
cm
CH3CN
HCN
Nimbus 4
BUV SBUV
Apr Nov
70- 78-
May May
77 '93
255- 255-
380 nm 340 nm
13 13
• •
Nimbus 7
TOMS LIMS
Nov Oct
78- 78-
Present May
79
309- 6.2-
360 15 ^m
312-
380 nm
6 6
• •
Nimbus?
Meteor 3
ADEOS 1
Earth-Probe
ATMOS
'85, '92,
'93, '94
2.98-15 ^m
16
•
•
•
•
•
•
•
•
•
Nimbus?
CLAES HALOE
Oct '91- Oct '91-
May'93 Present
3.5- 2.43-
12.7 Mm 10.25 Mm
9 8
• •
•
•
•
•
•
• •
Space lab 3,
ATLAS 1,2,
3
SAMS
Sep '91-
Jul'92
4.6-
16. 6 ^m
8
•
•
•
UARS
MLS GOME
Sep April
'91- '95-
Jul Present
'99
63, 240-
183, 790 nm
205
GHz
3 3072
• •
•
•
•
•
•
ERS-2
MODIS
Mar
'00-
Present
0.4-
14^m
36
•
Terra Aqua
AIRS OMI
Sep Jul '04-
'02- Present
Present
0.4-1.1, 270-
3.74- 500 nm
15. 4 ^m
2382 1560
• •
•
•
•
•
•
Aqua
HIRDLS MLS
Jul '04- Jul '04-
Present Present
6.12- 118,190,
17.76 ^m 240,640
GHz, 2.5
THz
22 5
• •
•
•
•
•
•
•
•
•
•
•
Aura
TES*
Jul '04-Present
3.2-15.4 Mm
12
•
•
•
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Missions
HN03
NO
N02
N20
N205
OH
l-liO/ l-li imiHitw
h2U/ nUmlQIly
S02
Aerosols
Cloud
Temperature
Geopotential Height
Reflectance
Nimbus 4
• •
• •
• •
Nimbus?
•
•
•
•
•
•
•
•
Nimbus?
Meteor 3
ADEOS 1
Earth-Probe
•
•
•
•
•
•
Nimbus?
•
• •
• •
•
•
• •
• •
Space lab 3,
ATLAS 1,2,
3
•
•
•
•
•
UARS
•
•
• •
•
•
ERS-2
•
•
•
•
Terra Aqua
•
•
•
• •
•
•
• •
Aqua
• •
•
• •
•
•
•
•
•
• •
• •
Aura
•
•
•
Please note that the Table above does not contain parameters from all sensors and products. Also available from the GES DAAC are many more Atmospheric and Earth Sciences data
products from AIRS, AMSU-A, MSB, MODIS, SeaWiFS, OCTS, CZCS, TRMM (PR, TMI, VIRS), TOVS Pathfinder, Data Assimilation Model (GEOS-1, GEOS-DAS, CPC/ACDB), UARS
(HRDI, WINDII, SOLSTICE, SUSIM, PEM), SORCE, several Field Campaigns, and Interdisciplinary data sets consisting of 70 geophysical Earth Sciences parameters. TOMS & SBUV
reprocessed data (version-8) are now available on DVD-ROM. The MLS and OMI-Aura products & Visualization tools are now available from GES DISC.
Source: Aura instrument TES' is archived at the NASA Langley Atmospheric Sciences Data Center (http://eosweb.larc.nasa.gov/) http://disc.gsfc.nasa.gov/.
2.9.3.1. Satellite Coverages
1 The near polar orbiting tracks of most satellites performing trace gas measurements provides wide
2 spatial coverage of reasonable horizontal (10-50 km) resolution, but delivers only twice-daily snapshots
3 of a particular species. Consequently, temporal patterns of pollutants as well as a time-integrated measure
4 of pollutant concentrations cannot be delineated explicitly through satellite measurements alone. The
5 geostationary satellite platforms such as the GOES systems of NOAA do provide near-continuous
6 coverage of physical parameters for weather tracking and forecasting purposes. There are proposed
7 campaigns within NASA and across partnership Federal agencies to deploy geostationary platforms with
8 measurement capabilities for trace gases and aerosols to enhance space based characterization of
9 tropospheric air quality (Fishman, 1987).
10 Polar orbiting satellites typically provide horizontal spatial resolution between 10 and 100 km,
11 depending on the angle of a particular swath segment. Spatial resolution less than 10 km is possible with
12 geostationary platforms. Characterization of elevated pollutants delivered by satellite systems
13 complements of our ground based in-situ measurement networks - especially considering that a
14 considerable fraction of pollutant mass resides well above Earth's surface. With few exceptions, satellite
15 data typically represents a total atmospheric column estimate. For certain, important trace gases (e.g.,
16 NO2, SO2, CH2O) and aerosols, the majority of mass resides in the boundary layer of the lower
17 troposphere, enabling associations linking column data to surface concentrations or emissions fields. For
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1 example, reasonable correlations, especially in the Eastern U.S., have been developed between
2 concentrations from ground level PM2 5 stations and aerosol optical depths (AOD) from NASA's
3 Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua and Terra satellites (Engel-
4 Cox, 2004); see the example in Figure 2-52. The Infusing Satellite Data into Environmental Applications
5 (IDEA; http://idea.ssec.wisc.edu/) site provides daily displays and interpretations of MODIS and surface
6 air quality data. The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO)
7 satellite (discussed below) provides some ability to resolve aerosol vertical gradients.
-120 -110 -100 -90 -80 -70
-08 -06 -04 -0.2 0 02 04 0.6 0.8 1
Source: Engel-Cox et al. (Engel-Cox, 2004).
Figure 2-52. Correlation surfaces between MODIS AOD and hourly PIVh.s surface sites from April-
September 2002.
GOMS
GEOS CHEM
Source: Abbot et al. (2003) and Palmer et al. (2006)
Figure 2-53. Comparisons between GEOSchem global model and GOME derived formaldehyde
fields (left); Summer 2006 OMI column HCHO and translation to isoprene emission estimates (right).
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2.9.3.2. Measurement Issues
1 Most satellite air quality observations are based on spectroscopic techniques typically using
2 reflected solar radiation as a broad source of UV through IR electromagnetic radiation (LIDAR aboard
3 CALIPSO does utilize an active laser as the radiation source). While the science of satellite based
4 measurements of trace gases and aerosols is relatively mature, interferences related to surface reflections,
5 cloud attenuation and overlapping spectra of nearby species require adequate filtering and accounting for
6 in processing remote signals. For example, aerosol events episodes associated with clouds often are
7 screened out in developing in applications involving AOD characterizations through MODIS.
8 Correlations between AOD and surface aerosols generally are better in the eastern U.S. relative to the
9 West because due to excessive surface light scattering from relatively barren land surfaces.
10 Use of satellite data in air quality management assessments. Satellite data, particularly fire and
11 smoke plume observations and GOES meteorological data, support various air quality forecasting efforts
12 servicing public health advisories. Forecasting is driven by characterizing the environment in current and
13 immediate-future time frames, on the order of 1 to 3 days. Air quality assessments require greater
14 confidence in a systems response behavior to longer term, and usually much greater, changes in
15 emissions, land use and meteorology; which requires greater confidence in formulation of numerous
16 physical and chemical processes. Despite these differences, research and application products originally
17 catalyzed by forecasting objectives generally overlap well with retrospective air quality assessment needs,
18 the focus of this discussion.
19 Launched in 2004, NASA's Aura satellite mission (http://www.nasa.gov/mission_pages/
20 aura/spacecraft/index.html) deploys sensors potentially capable of measuring all criteria gases, CH4,
21 CH2O, HNO3, N2O, H2O vapor, OH and HO2 and AOD - a multiple pollutant space based complement to
22 the NCore multiple pollutant ground based network and intensive field campaigns. NASA's Orbiting
23 Carbon Observatory (OCO), scheduled to be launched in 2008, will be dedicated to tracking CO2 levels
24 which currently are captured on the Aqua based Atmospheric Infrared Sounder (AIRS) instrument. The
25 Aqua, Terra, Aura and OCO all are part of NASA's Earth Observation System (EOS).
26 Satellite data for CO, NO2, and CH2O as shown in Figure 2-53, as an indicator for biogenic
27 isoprene, have been used for improving emission inventories (Fu, 2006; Martin, 2006; Martin, 2003). As
28 longer-term records are developed, satellite imagery offers another means of checking progress of major
29 emission strategy plans as well as illustrating emissions growth in developing parts (East Asia) of the
30 world as shown in Figure 2-54 and Figure 2-55.
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i «
-•- Ohio: Satellite
-A- Ohio : Emission inventory
• New Yor* : Satellite
-A- New Yo'k . Fmiss or> inventory
0
-10
-20
-30
-40
A VC NO2
[molec crn"2 yr'1
6.0 10"
4.0 10"
2.0 10"
0.0 10°°
J-2.0 10'"
1-4.0 10"
-150 -120 -90 -60 -30 0 30
Longitude
90 120 150
Source: Kim et al. (2006) and Richter et al. (2005).
Figure 2-54. Superimposed eastern U.S. emission and combined GOME and SCIAMACHY NOa
1997-2002 trends (left); GOME N02 trends from 1995-2002 (right). Clear evidence of reductions in
Midwest U.S. and European NOx emissions, and increased NOx generated in eastern Asia.
Source: Husar (2005; http://capiton.wustl.edu/CAPITA/)
Figure 2-55. 2004 OMI NOa column images aggregated for all Fridays (left) and Sundays (right)
indicating weekend/weekday patterns associated with reduced Sunday emissions.
2.9.4. European Air Monitoring Networks
1 Extensive air monitoring networks have also been implemented in Europe. In addition to the
2 programs discussed above, many European-based programs are served by centralized organization
3 structures linked to international efforts such as Convention on Long Range Transport of Air Pollution
4 (LRTAP) (http : //www.unece . org/env/lrtap/) and the underlying technical assessment body, the Co-
5 operative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in
6 Europe (EMEP). The Global Atmospheric Watch (GAW) program
7 (http://www.wmo.int/pages/prog/arep/gaw/gaw home en.html) under the World Meteorological
8 Organization (WMO) provides quality assurance guidelines and data access to an important body of air
9 quality measurements relevant to assessing intercontinental pollution transport and climate forcing
10 phenomena. The Norwegian Institute for Air Research (NILU)
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1 (http://www.nilu.no/index.cfm?ac=topics&folder id=4572&lan id=3). maintains a database for much of
2 the European based networks. These programs are noted not only as resources for large spatial scale
3 environmental assessments, but also as examples of coordination and data harmonization that could be
4 extended or replicated for North American purposes. The MOZAIC aircraft atmospheric chemistry
5 vertical profile measurements illustrate the close linkage between European observation systems and air
6 quality modeling and process formulation studies. European-based efforts in deposition monitoring
7 relevant to sensitive ecosystems preceded efforts in North America and continue to lead the International
8 community in coordinated efforts in sustaining science based measurement programs.
9 Table 2-18 includes combined contributions from all countries ranging from a few sites to tens of
10 sites per country. Measurements for a variety of air pollutants are addressed including O3, heavy metals,
11 persistent organic pollutants (POPs), PM, VOCs, and deposition from acidifying and eutrophying
12 compounds.
Table 2-18. International and European air monitoring programs.
Network
i j . Number ......
Lead Agency Ofsjtes lmtlated
Measurement Parameters
Location of Information and/or Data
EMEP- UNECE
Co-operative Programmed for
Monitoring and Evaluation of the
Long-range Transmission of Air
Pollutants in Europe (encompasses
networks for -37 European countries
and organizations)
EUROTRAC—The European International
Experiment on the Transport and Executive
Transformation of Environmentally Committee
Relevant Trace Constituents over (European
Europe Countries)
270 1977 Acidifying / Eutrophying Compounds (precipitation): http://www.nilu.no/proiects/ccc/emepdata.html
S042", NOs, NH4, trace elements, pH, acidity
(air): S02, NCfe, HMOs, NHs, PMio, Plvbs, major ions
03 Heavy Metals precipitation, major ions, PM25,
PMio, Hg, wet deposition POPs precipitation, air,
deposition Particulate Matter PM25, PMio, EC, OC,
TC, BCVOCHCs, Carbonyls
??? 1986 EUROTRAC programs performed analyses utilizing http://www.gsf.de/eurotrac/index what is.html
data from existing or specially designed monitoring
networks in order to:
1. elucidate the chemistry and transport of ozone
and other photo-oxidants in the troposphere, e.g.,
TOR—30 0-j stations and ALPTRAC—15 snow-
monitoring sites
2. identify processes leading to the formation of
acidity in the atmosphere, particularly those
involving aerosols and clouds.
3. understand uptake and release of atmospheric
trace substances by the biosphere.
EUROTRAC-2 — The EUREKA International
project on the transport and chemical Scientific
transformation of trace constituents Secretariat
in the troposphere over Europe; (European
second phase. Subprojects: Countries and EU)
-AEROSOL
- BIATEX-2
-CAPMAN
-CMD
- EXPORT-E2
-GENEMIS
- GLOREAM
-LOOP
- MEPOP
-PROCLOUD
- SATURN
-TOR-2
-TRAP45
-TROPOSAT
1996 EUROTRAC-2 programs performed analyses
utilizing data from existing monitoring networks in
order to: support the further development of
abatement strategies within Europe by providing an
improved scientific basis for the quantification of
source-receptor relationships for photo-oxidants
and acidifying substances.
http://www.gsf.de/eurotrac/index what is.html
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2.9.5. Ambient Concentrations of Relevant N Compounds
2.9.5.1. NO and N02
1 Species concentrations described in this section were taken from two types of networks described
2 in Section 2.9 above: (1) the mostly urban networks designed and maintained for NAAQS attainment
3 demonstrations; and (2) the mostly rural and remote networks designed and operated to comply with a
4 range of requirements for protection of landscapes and views.
5 Figure 2-56 shows the distribution of monitoring sites for NO2 across the U.S. Data for ambient
6 NO2 are not collected or collected at very few sites over large areas of the U.S. Few cities have more than
7 two monitors and several large cities, including Seattle, WA, have none. Note that the number of NO2
8 monitors has been decreasing in the U.S. as ambient average concentrations have fallen to a few tenths of
9 the level of the NAAQS. There were, for example, 375 NO2 monitors identified in mid-2006, but only
10 280 in November 2007.
Figure 2-56. Location of ambient-level N02 monitors for NAAQS compliance in 2007. Shaded states
have N02 monitors; unshaded states have none.
11 Criteria for siting ambient monitors for NAAQS pollutants are given in the SLAMS / NAMS /
12 PAMS Network Review Guidance (EPA, 1998). As might be expected, criteria for siting monitors differ
13 by pollutant. NO2 monitors are meant to be representative of several scales: middle, or several city blocks,
14 300 to 500 m; neighborhood, or 0.5 to 4 km; and urban, or 4 to 50 km. Middle- and neighborhood-scale
15 monitors are used to determine highest concentrations and source effects, while neighborhood- and urban-
16 scale monitors are used for monitoring population exposures. As can be seen, there is considerable
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1 overlap between monitoring objectives and scales of representativeness. The distance of neighborhood-
2 and urban-scale monitor inlets from roadways increases with traffic volume and can vary from 10 to
3 250 m away from roadways as traffic volume increases. Where the distance of an inlet to a road is shorter
4 than the value in this range for the indicated traffic volume on that road, that monitor is classified as
5 middle scale. Vertically, the inlets to NC>2 monitors can be set at a height from 2 to 15m.
6 Figure 2-57 shows box plots of ambient concentrations of NC>2 measured at all monitoring sites
7 located within MSAs or urbanized areas in the U.S. from 2003 through 2005. As can be seen, mean NC>2
8 concentrations are ~15 ppb for averaging periods ranging from a day to a year, with an interquartile range
9 (IQR) of 10 to 25 ppb. However, the average of the daily 1-h max NC>2 concentration over this 3-year
10 period is ~30 ppb. These values are about twice as high as the 24-h avg. The highest maximum hourly
11 concentration (-200 ppb) found during the period of 2003 to 2005 was more than a factor often greater
12 than the overall mean 24-h concentrations. The ratio of the 99th percentile concentration to the mean
13 ranges from 2.1 for the 1-year avgs to 3.5 for the 1-h avgs.
100
90
•g.
k—T201 *—Jan *—Ji2!
* MAX
1-h max 1-h 24-h 2 week
1-year
Figure 2-57. Ambient concentrations of N02 measured at all monitoring sites located within
Metropolitan Statistical Areas in the U.S. from 2003 through 2005. * max; • mean
14 Because ambient NO2 monitoring data are so sparse across the U.S. and are particularly so in rural
15 areas, it would not be appropriate to use these data in constructing a map of NO2 concentrations across the
16 continental U.S. The short T of NO2 with respect to conversion to NOZ species and the concentrated
17 nature of NO2 emissions result in steep gradients and low concentrations away from major sources that
18 are not adequately captured by the existing monitoring networks. Model predictions might be more useful
19 for showing large-scale features in the distribution of NO2 and could be used in conjunction with the
20 values shown in Figure 2-57 to provide a more complete picture of the variability of NO2 across the U.S.
21 Monthly avg NC>2 concentrations for July and January 2002 calculated using EPA's CMAQ model are
22 shown in Figure 2-58. (A description of the capabilities of CMAQ and other three-dimensional CTMs is
23 given in Section 2.8) The high variation in NC>2 concentrations of at least a factor of 10 is apparent in
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1 these model estimates. As expected, the highest NO2 concentrations are seen in large urban regions, such
2 as the Northeast Corridor, and lowest values are found in sparsely populated regions located mainly in the
3 West. NO2 concentrations tend to be higher in January than in July.
January 2002
Min = 0.019 at (11), Max = 45.966 al (23,46)
July 2002
Min = 0.012 at (6,4), Max = 40.802 at (23,46)
Figure 2-58. Monthly average N02 concentrations for January 2002 (left panel) and July 2002 (right
panel) calculated by CMAQ (36 X 36 km horizontal resolution).
4 Trends in NO2 concentrations across the U.S. from 1990 to 2006 are shown in Figure 2-59. The
5 white line shows the mean values and the upper and lower borders of the shaded areas represent the 10th
6 and 90th percentile values. Information on trends at individual, local air monitoring sites can be found at
7 www.epa.gov/airtrends/nitrogen.html.
0.06
. 0.05 H
170 sites
National Standard
90 percent of sites are below this line.
10 percent of sites are below this line.
90 92 94 96 98 00 02 04
1990 to 2006: 30% decrease
06
Figure 2-59. Nationwide trend in NOa concentrations. The white line shows the mean values, and
the upper and lower borders of the green (shaded) areas represent the 10th and 90th percentile
values. The current NAAQS of 0.53 ppm is shown with the dotted line. Information on trends at local
air monitoring sites can be found atwww.epa.gov/airtrends/nitrogen.html.
8 Concentrations were substantially higher during earlier years in selected locations and contributed
9 in those years to the "brown clouds" observed in many cities. Residents in Chattanooga, TN, for example,
10 were exposed more than 30 years ago to high levels of NO2 from a munitions plant (Shy, 1980). Annual
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1 mean NO2 concentrations there declined from -102 ppb in 1968 to ~51 ppb in 1972. There was a strike at
2 the munitions plant in 1973 and levels declined to -32 ppb. With the implementation of control strategies,
3 values dropped further. In 1988, the annual mean NO2 concentration varied from -20 ppb in Dallas, TX
4 and Minneapolis, MN to 61 ppb in Los Angeles, CA. However, New York City, with the second-highest
5 annual mean concentration in the U.S. in 1988, the mean NO2 concentration was 41 ppb.
6 In contrast to most urban areas in the U.S., in other countries, NO2 concentrations have increased.
7 For example, annual mean NO2 concentrations in central London increased during the 1980s from
8 -25 ppb in 1978 to -40 ppb in 1989 at the background measurement site and from -35 to -45 ppb at the
9 roadside site. Corresponding NO concentrations increased from -20 ppb to -40 ppb at the background
10 site and from -125 to -185 ppb at the roadside site (Elsom, 2002d. Increased use of motor vehicles may
11 have contributed to much of these increases in NO2 levels.
12 The month-to-month variability in 24-h avg NO2 concentrations at two sites in Atlanta, GA, is
13 shown in Figure 2-60. (Similar plots of variability at other individual sites in selected urban areas are
14 shown in Figure 2-61 through Figure 2-68; these cities were chosen to represent regions with large
15 populations and, hence, large emissions from on-road vehicles and combustion for energy production, the
16 two largest sources of NO and NO2.)
August 2008 2-137 DRAFT-DO NOT QUOTE OR CITE
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a. Atlanta, GA.
SUBURBAN
o
1
o
o
0.09-
0.08-
0.07
0.06-
0.05-
0.04-
0.03-
0.02-
0.01-
0.00-
site id=130890002 poc=1
= Natural Spline Fit w/ 9 df
01/01/2003 07/01/2003 01/01/2004 07/01/2004 01/01/2005 07/01/2005 01/01/2006
Sample Date (mm/dd/yyyy)
site id=131210048poc=1
b. Atlanta, GA. URBAN and CENTER CITY
0.09;
__ 0.08-
Q. 0.07
a.
~ 0.06-
•S 0.05
2
•Ł 0.04-
o) :
" 0.03-
O
O 0.02-
0.01 - J
0.00 i
01/01/2003 07/01/2003 01/01/2004 07/01/2004 01/01/2005 07/01/2005 01/01/2006
Sample Date (mm/dd/yyyy)
Figure 2-60. Time series of 24-h avg N02 concentrations at individual sites in Atlanta, GA from 2003
through 2005. A natural spline function (with 9 degrees of freedom) was fit and overlaid to the data
(dark solid line).
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a. New York, NY.
SUBURBAN
b New York, NY. URBAN and CENTER CITY
Q.
ŁL
01/01/2003 07/01/2003 01/01/20W 07/01/2004 01/01/2005 07/0112005 01/01/2006 01/01/2003 07/01/2003 01/01/2004 07/01/2004 01/01/2005 07/01/2005 01/01/2006
Sample Date (mm/dd/yyyy)
Sample Date (mm/dd/yyyy)
c. New York, NY. URBAN and CENTER CITY
d. New York, NY. URBAN and CENTER CITY
—' 0.06
C
.O 005
2 004
g 003
O 0.02
O
001
000
01/01/2003 07/01/2003 01/D1/2004 07/01/2004 01/01/2005 07/01/2005 01/01(2006 01/01/2003 07/01/2003 01/01/2004 07/01/2004 01/01/2005 07/01/2006 01/01/2006
Sample Date (mm/dd/yyyy)
Sample Date (mm/dd/yyyy)
e. New York, NY. URBAN and CENTER CITY
01*1/2003 07101/2003 01/01/3004 07/01/2004 01/01/2005 07«01/2005 01/01/2006
Sample Date (mm/dd/yyyy)
Source: U.S. EPA AQS, 2007
Figure 2-61. Time series of 24-h avg N02 concentrations at individual sites in New York City from
2003 through 2005. A natural spline function (with 9 degrees of freedom) was fit and overlaid to the
data (dark solid line).
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a. Chicago, IL.
RURAL
b. Chicago, IL.
SUBURBAN
0.07-
006-
eid = 171971011 poc« 1
|->«. = fraiurai Spline Fuwfldf]
kk —ilk kfr- tt^.t
^FmffF ''-^
01/01*2003 07/01*2003 01/01(2004 07(01/2004 01/01(2005 07/01/2005 01/01/2006 01/01/2003 07/01(2003 01/01/2004 07/01(2004 01/01*2005 07/01/2005 01/01/2006
Sample Date (mm/dd/yyyy)
Sample Date (mm/dd/yyyy)
c. Chicago, IL.
SUBURBAN
d. Chicago, IL.
SUBURBAN
J'1'01,vCj3 07(01/2003 01/01/2004 07/01/2004 01/01/2005 07/01/2005 01/01/2006
01/DV2003 07/01/2003 01/01/2004 07/01/2004 01/01/2005 07/01(2005 01/01/2006
Sample Date (mm/dd/yyyy)
Sample Date (mm/dd/yyyy)
e. Chicago, IL.
SUBURBAN
f. Chicago, IL.
URBAN and CENTER CITY
01(01/2003 07/01/2003 01/01/2004 07/01/2004 01/01/2005 07/01(2005 01(01/2006 01/01/2003 07/01/2003 01/01/2004 07/01(2004 01/01(2005 07/01/2005 01/01/2006
Sample Date (mm/dd/yyyy)
Sample Date (mm/dd/yyyy)
g. Chicago, IL. URBAN and CENTER CITY
I °07
•S 0.06
O 0.05
2 0.04-
0.01
0.00-
01/0-;2003 07/01/2003 01/01/2004 07/01/2004 01/01(2005 07/01/2005 O1.'01'20{
Sample Date (mm/dd/yyyy)
Figure 2-62. Time series of 24-h avg N02 concentrations at individual sites in Chicago, IL from 2003
through 2005. A natural spline function (with 9 degrees of freedom) was fit and overlaid to the data
(dark solid line).
August 2008
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a. Baton Rouge, LA.
SUBURBAN
siteid=221210001 poc=1
= Natural Spline Fit w/ 9 df
0.09-
0.08^
0.07-
0.06-
0.05-
0.04-
0.03-
0.02-
0.01-
0,00-
01/01/2003 07/01/2003 01/01/2004 07/01/2004 01/01/2005 07/01/2005 01/01/2006
Sample Date (mm/dd/yyyy)
b. Baton Rouge, LA.
URBAN and CENTER CITY
site id=220330009 poc=1
0.09:
0.08-
I. 0.07-
~ 0.06:
•S 0.05:
•g 0.04 •;
| 0.03:
O
O 0.02:
0.01^
0.00;
01/01/2003 07/01/2003 01/01/2004 07/01/2004 01/01/2005 07/01/2005 01/01/2006
Sample Date (mm/dd/yyyy)
Figure 2-63. Time series of 24-h avg N02 concentrations at individual sites in Baton Rouge, LA from
2003 through 2005. A natural spline function (with 9 degrees of freedom) was fit and overlaid to the
data (dark solid line).
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a. Houston, TX.
SUBURBAN
b. Houston, TX.
SUBURBAN
007-
0.06-
005-
0.04
003-
0.02-
00'.
0.00:
01/01/2004 07/01/2004 01/01/2005 07(01/2005
Sample Date (mm/dd/yyyy)
01(01/2006 07/Q1/2CG5
Sample Date (mm/dd/yyyy)
c. Houston, TX.
SUBURBAN
d. Houston, TX.
SUBURBAN
01/01/2005 07/01/2005
'1/2003 07/01/2003 01/01/2004 07/01/2004 D1/01/2005 07/B1/2005
Sample Date (mm/dd/yyyy)
Sample Date (mm/dd/yyyy)
e. Houston, TX.
URBAN and CENTER CITY
0.07
0,06
0.05
0.04-
0.03
0.02
0.01
0.00'
07/01/2003 01/01/2004 07/01/2004 01/01/2005 07/01/2005
Sample Date (mm/dd/yyyy)
f. Houston, TX.
URBAN and CENTER CITY
a, °07'
c.
—' 006
C
.9 005
"5
Ł 004-
g 003-
C
O 002-
o
00!-
COO-
01/01/2003 07/01/2003 01/01/2004 07/01'2004 01/01/2005 07/01(2005
Sample Date (mm/dd/yyyy)
g. Houston, TX. URBAN and CENTER CITY
01(01/2003 07/01/2003 01/01/2004 07/01/2004 01/01/2005 07/01/2005
Sample Date (mm/dd/yyyy)
Figure 2-64. Time series of 24-h avg N02 concentrations at individual sites in Houston, TX from
2003 through 2005. A natural spline function (with 9 degrees of freedom) was fit and overlaid to the
data (dark solid line).
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a. Los Angeles, CA.
SUBURBAN
b. Los Angeles, CA.
SUBURBAN
07/01/2003 01/01/2004 07/01.2CB4 01/01/2005 07/01/2005 01(01/2006
Sample Date (mm/dd/yyyy)
01(01/2003 07(01/2003 01(01/2004 07/0112004 01/01/2005 07/01/2005 01101/2006
Sample Date (mm/dd/yyyy)
c. Los Angeles, CA.
SUBURBAN
d. Los Angeles, CA.
SUBURBAN
01/01/2003 07/01/2003 01/01/2004 07/01/2004 01/01/2005
Sample Date (mm/dd/yyyy)
01/01/2003 07/01/2003 01/01/2004 07/01/2004 01/01/2005 07/01/2005
Sample Date (mm/dd/yyyy)
e. Los Angeles, CA.
SUBURBAN
f. Los Angeles, CA.
Q1/0iy2003 07/01/2003 01/01/2004 Q7/01/20D4 01/01/2005 07/01/2005
Sample Date (mm/dd/yyyy)
SUBURBAN
Sample Date (mm/dd/yyyy)
g. Los Angeles, CA.
SUBURBAN
h. LOS Angeles, CA. URBAN and CENTER CITY
0.09-
0.08-
0.07-
0.05-
COS-
CM-
0.03-
002-
0.01-
ODD-
ieid = OB03780t2poc =
07/01/2003 01/012004 07(01/2004 01/01/2005 07/01/2005
Sample Date (mm/dd/yyyy)
01(01/2003 07/01/2003 01/01(2004 07/01/2004 01/01/2005 07/01/2005
Sample Date (mm/dd/yyyy)
Figure 2-65. Time series of 24-h avg N02 concentrations at individual sites in Los Angeles, CA from
2003 through 2005. A natural spline function (with 9 degrees of freedom) was fit and overlaid to the
data (dark solid line).
August 2008
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i. Los Angeles, CA. URBAN and CENTER CITY
j. Los Angeles, CA. URBAN and CENTER CITY
01W2003 07/01/2003 OMH/200* 07/01/2004 01/01/2005 Q7ffl1/2QCS 0101/3006 01J0112003 07/OU2003 01/01J2004 07'01'ZOM 01/011X105 07/01/2005
Sample Date (mm/ddfyyyy) Sample Date (mm/dd/yyyy)
k. LOS Angeles, CA, URBAN and CENTER CITY
LOS Angeles, CA. URBAN and CENTER CITY
§
0
OW1OOB 07/01OW3
01W30H CU/OKZOIB OWtf20C6
Sample Date (mm/dd/yyyy)
orxnaon own/sow OT«M(!OM OHMMOS 07«iaoos munasxe
Sample Date (mm/dd/yyyy)
m. LOS Angeles, CA. URBAN and CENTER CITY
n. LOS Angeles, CA. URBAN and CENTER CITY
a
D.
avmaaa 07/01/2103 o«n/2ow 07/01/2001 01/01/2006 07/oi«x» 01/01/2006
Sample Date (mm/dd/yyyy]
07ffl1S003 OKD1/20M CS7B1/2C04 01KHM05
Sample Date (mm/dd/yyyy)
Figure 2-66. Time series of 24-h avg N02 concentrations at individual sites in Los Angeles, CA from
2003 through 2005. A natural spline function (with 9 degrees of freedom) was fit and overlaid to the
data (dark solid line).
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a. Riverside, CA.
RURAL
b. Riverside, CA.
SUBURBAN
fkfail flidfr I iMJJfa 1t(JBi
.^.--^1*!-'*-"—<--.-A.^J*-- '-.-'-i^ *.. ~ J-
01(01(2003 07(01(2003 OKOM2004 07;OiraOM 01)01(2005 07)01)2005 01(01(2008
01(01(2003 07(01(2003 01(01)2004 07)01)2004 01(01(2005 07(01(2005 01BK2006
Sample Date (mm/dd/yyyy)
Sample Date (mm/dd/yyyy)
c. Riverside, CA.
SUBURBAN
d. Riverside, CA.
SUBURBAN
01.«1(20TO 07)01(2003 01 (01(2001 07(01(2004 01(01(2005 07)0112005
01(01(2003 07(01(2003 01(01)2004 07)01(2004 01(01(2005 07)01(2005 01(01(2005
Sample Date (mm/dd/yyyy)
Sample Date (mm/dd/yyyy)
Figure 2-67. Time series of 24-h avg N02 concentrations at individual sites in Riverside, CA from
2003 through 2005. A natural spline function (with 9 degrees of freedom) was fit and overlaid to the
data (dark solid line).
August 2008
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e. Riverside, CA.
SUBURBAN
f. Riverside, CA.
SUBURBAN
a. uu'
Q.
— 005
a ri = 060712002 pDC = 1
01(01/2003 07/0112003 01(01/2004 07/01(2004 01(01/2005 07/01(2005 01(01(2006
005^
004-
003-
002-
0.01. |
0.00-
01(01(2003 07)01/2003 01/01/2004 07/01/2KM 01/01(2005 07/OU200S 0«)1(2006
Sample Date (mm/dd/yyyy)
Sample Date (mm/dd/yyyy)
g. Riverside, CA.
0.09-
SUBURBAN
h Riverside. CA URBAN and CENTER CITY
01(01/2003 07/01(2003 01(01(2004 07/01(2004 01101(2005 07/010005 Olffll/2006
000-
01(01/2003 07/0112003 0101/2004 07/01(2004 01/01(2005 07/01(2005 01(01(2006
Sample Date (mm/dd/yyyy)
Sample Date (mm/dd/yyyy)
i. Riverside, CA. URBAN and CENTER CITY
01/01/2C03 07/01/2003 01KH/20W Q7WF20M 01/01/2006 07/01/2006 01/01/2006
Sample Date (mm/dd/yyyy)
Source: EPA (2003)
Figure 2-68. Time series of 24-h avg N02 concentrations at individual sites in Riverside, CA from
2003 through 2005. A natural spline function (with 9 degrees of freedom) was fit and overlaid to the
data (dark solid line).
1 Strong seasonal variability exists in NC>2 concentrations in the data shown above. Higher
2 concentrations are found during winter, consistent with the generally lower PEL depths in winter. Lower
3 concentrations are found during summer, consistent with PEL depths and increased rates of
4 photochemical oxidation of NC>2 to NOz. Note also the day-to-day variability in NC>2 concentration,
August 2008
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DRAFT-DO NOT QUOTE OR CITE
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1 which also tends to be larger during the winter. There appears to be a somewhat regular pattern for the
2 other southern cities examined with their winter maxima and summer minima.
3 Monthly maxima tend to be found from late winter to early spring in Chicago, IL, and New York,
4 NY, with minima occurring from summer through the fall. However, in Los Angeles and Riverside, CA,
5 monthly maxima tend to occur from autumn through early winter, with minima occurring from spring
6 through early summer. Mean and peak NC>2 concentrations during winter can be up to a factor of two
7 greater than those during the summer at sites in Los Angeles.
8 The diurnal variability in NC>2 concentrations at the same two sites in the Atlanta metropolitan area
9 shown in Figure 2-60 is illustrated in Figure 2-69. As can be seen from these figures, NC>2 typically
10 exhibits daily maxima during the morning rush hours, although they can occur at other times of day. In
11 addition, there are differences between weekdays and weekends. At both Atlanta sites, NO2
12 concentrations are generally lower and the diurnal cycles more compressed on weekends than on
13 weekdays. The diurnal variability of NO2 at these sites is typical of that observed at other urban sites.
14 Monitor siting plays a role in determining diurnal variability in the sense that monitors located farther
15 from traffic will measure lower concentrations and show a flatter overall distribution of data compared to
16 monitors located closer to traffic.
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0}
o
c:
o
0
A, Atlanta, GA Suburban
-E -15
Q.
a.
.9 .10-
•i-*
fa
.05-
.00
Weekday B. Atlanta, GA Suburban Weekend
.15;
.10
.05'
II
5 6 Q !
0246
10 12 14 16 18 20 22 24
Hour
0 2 4 6 8 10 12 14 16 18 20 22 24
Hour
C. Atlanta, GA Urban & City Center Weekday D. Atlanta, GA Urban & City Center Weekend
-=- ,15, , .15-
Q.
Q.
o
o
o .10
I
.05
X
„ x x x x „
*xx X*S*
m
XX
.10
.05
0 2 4 6 8 10 12 14 16 18 20 22 24 0 2 4 6 8 10 12 14 16 18 20 22 24
Hour Hour
Figure 2-69. Mean hourly N02 concentrations on weekdays and weekends measured at two sites in
Atlanta, GA. A and B refer to a suburban site, and C and D refer to a site classified as urban and
city center.
2.9.5.2. NOY and NOz
1 Data for individual NOY species are much less abundant than for either oxides of nitrogen or for
2 total NOY. Data for several NOY species are collected typically only as part of research field studies, e.g.,
3 the Southern Oxidant Study (SOS), Texas Air Quality Study (TexAQS I and TexAQS II) in the U.S. As a
4 result, this information is simply not available for a large number of areas in the U.S.
PANs
5 At warm temperatures, the concentration of PAN forms a photochemical steady state with its
6 radical precursors on a timescale of roughly 30 min. This steady state value increases with the ambient
7 concentration of O3 (Sillman, 1990). O3 and PAN may show different seasonal cycles, because they are
8 affected differently by temperature. Ambient O3 increases with temperature, driven in part by the
9 photochemistry of PAN. The atmospheric T of PAN decreases rapidly with increasing temperature due to
10 thermal decomposition. Based on the above, the ratio of O3 to PAN is expected to show seasonal changes,
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1 with highest ratios in summer, although there is no evidence from measurements. Measured ambient
2 concentrations show a strong nonlinear association between PAN and O3 (Pippin, 2001; Roberts, 1998);
3 see Figure 2-70. Moreover, uncertainty in the relationship between O3 and PAN grows as the level of
4 PAN increases.
0 1000 2000 3000 4000 0 1000 2000 3000 4000 5000
PAN (pptv)
Source: Roberts et al. (1998)
Figure 2-70. Measured Os (ppb) versus PAN (pptv by volume) in Tennessee, including (a) aircraft
measurements, and (b, c, and d) suburban sites near Nashville.
5 Measurements and models show that PANs in the U.S. includes major contributions from both
6 anthropogenic and biogenic VOC precursors (Horowitz et al., 1998(Roberts, 1998). Measurements in
7 Nashville during the 1999 summertime Southern Oxidants Study (SOS) showed PPN and MPAN
8 amounting to 14% and 25% of PANs, respectively (Roberts, 2002). Measurements during the TexAQS
9 2000 study in Houston indicated PAN concentrations of up to 6.5 ppb (Roberts, 2003). PAN
10 measurements in southern California during the SCOS97-NARSTO study indicated peak concentrations
11 of 5-10 ppb, which can be contrasted to values of 60-70 ppb measured back in 1960 (Grosjean, 2003).
12 Vertical profiles measured from aircraft over the U.S. and off the Pacific coasts typically show PAN
13 concentrations above the boundary layer of only a few hundred ppt, although there are significant
14 enhancements associated with long-range transport of pollution plumes from Asia (Kotchenruther, 2001;
15 Roberts, 2004).
16 Observed ratios of PAN to NO2 as a function of NOx at a site at Silwood Park, Ascot, Berkshire,
17 UK are shown in Figure 2-71 United Kingdom Air Quality Expert Group (U.K. Air Quality Expert Group,
18 2004). As can be seen there is a very strong inverse relation between the ratio and the NOx concentration,
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1 indicating photochemical oxidation of NOX has occurred in aged air masses and that PAN can make a
2 significant contribution to measurements of NO2 especially at low levels of NO2. It should be noted that
3 these ratios will likely differ from those found in the U.S. because of differences in the composition of
4 precursor emissions, the higher solar zenith angles found in the UK compared to the U.S., and different
5 climactic conditions. Nevertheless, these results indicate the potential importance of interference from
6 these compounds in measurements of NO2.
0.20 -
0.15
CS
O
0.10
0.05
0.00
20
40 60
[NOX] (ppb)
80 100
Source: U.K. Air Quality Expert Group (2004).
Figure 2-71. Ratios of PAN to N02 observed at Silwood Park, Ascot, Berkshire, U.K. from July 24 to
August 12, 1999. Each data point represents a measurement avgd over 30 minutes.
HN02
7 Measurements of HNO2 in urban areas are extremely limited; however, data from Stutz et al.
8 (2004) and Wang and Lu (2006) indicate that levels of HNO2 are <1 ppb even under heavily polluted
9 conditions, with the highest levels found during the night and just after dawn and the lowest values found
10 in the afternoon. However, data collected in the U.K. (U.K. Air Quality Expert Group, 2004; Lammel,
1 1 1996) and in the U.S. (Kirchstetter, 1996) indicate that HNO2-to-NOx ratios could be of the order of -5%
12 in motor vehicle emissions. These results indicate that HNO2 levels in traffic could be comparable to
13 those of NO2. Several field studies conducted at ground level (Hayden, 2003, near Boulder CO; Williams,
14 1987) and aircraft flights (Singh, 2007, over Eastern North America), have found much higher
1 5 concentrations than NOx concentrations in relatively unpolluted rural air.
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1 Measurements of HNO2 in urban areas are very limited; however, data from Stutz et al., (2004) and
2 Wang and Lu, (Wang, 2006) indicate that HNO2 concentrations are < 1 ppb even under heavily polluted
3 conditions (with the highest levels found during the night and just after dawn and lowest values found in
4 the afternoon). Several field studies such as Hayden et al. (2003) in rural Quebec, Williams et al.
5 (Williams, 1987) near Boulder, CO, and Singh et al. (Singh, 2007) in aircraft flights over eastern North
6 America have also found much higher levels of NOz compounds than NOx in relatively unpolluted rural
7 air.
8 Calculations with CMAQ for the mid-Atlantic region in a domain from Virginia to southern New
9 Jersey showed that the highest HNO3 and RONO2 concentrations occur during mid-afternoon, consistent
10 with their formation by photochemical processes also producing O3. Model simulations of an O3 episode
11 in July 2002 made for the Maryland State O3 Implementation Plan (SIP) showed episode averages of the
12 ratio of the further-oxidized N species like HNO3 to NO2 ranging from 0.26 to 3.6 in rural Virginia, with
13 the highest ratios in rural areas and lowest ratios in urban centers nearer the sources of fresh NOX
14 emissions.
15 The ratio of HNO2 to NO2 as a function of NOX measured at a curbside site in a street canyon in
16 London, UK is shown in Figure 2-72, where HNO2 is labeled HONO. The ratio is highly variable,
17 ranging from about 0.01 to 0.1, with a mean -0.05. As NO2 constitutes several percent of motor vehicle
18 emissions ofNOx, the above implies that emissions of HNO2 represent a few tenths of a percent of
19 mobile NOX emissions. A similar range of ratios have been observed at other urban sites in the United
20 Kingdom (Lammel, 1996).
0.3
0.2 i
;
o
200
400 600
[NOXJ (ppb)
800
1000
Source: UK AQEG (2004).
Figure 2-72. Ratios of HN02 to N02 observed in a street canyon (Marylebone Road) in London, U.K.
from 11 a.m. to midnight during October 1999. Data points reflect 15-min average concentrations of
HONO and N02.
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HN03 and N03
1 Data for concentrations of HNO3 and NO3 in urban areas in the U.S. are sparse. The most
2 geospatially intensive set of data for any HNO3 were taken as part of the Children's Health Study for
3 which gas-phase HNO3 was measured at 12 sites in southern California from 1994 through 2001 (Alcorn,
4 2004). Two week avg concentrations ranged from <1 ppb to >10 ppb, with the highest HNO3
5 concentrations and highest ratio of HNO3 to NO2, -0.2, was found downwind from central Los Angeles in
6 the San Bernardino during summer, as one would expect for this more oxidized N product.
7 HNO3 data have also been reported from the SEARCH network of four pairs (eight total sites) of
8 urban and rural sites in the southeastern U.S using increasingly sophisticated methods since 1998; see
9 Zhang et al. (Zhang, 2006). Concentrations of HNO3 in this area have ranged from <1 ppb to >10 ppb.
10 Maps of ambient concentrations from CASTNET data for rural and remote areas are available
11 below. The CASTNET ambient concentration maps were produced with Arclnfo using an inverse distance
12 weighting (IDW) interpolation technique. Using IDW, the surface is most influenced by the nearest point
13 values and less so by more distant points. CASTNET sites within 400 km of each grid point were used in
14 the computation. As noted above, thin data coverage complicates interpretation of these maps and renders
15 them most useful as heuristic guides to large areas of possible differences. Strict quantitative values
16 should not be imputed to areas away from the measurement sites.
17 Ranges of years in the chart represent 3-year averages. For example, 2004-2006 is the average
18 concentration of 2004, 2005 and 2006, as calculated from gridded output for each of the years. The three
19 annual grids from the 3-year period were averaged to derive the mean concentration of the 3-year period.
20 Only sites meeting completeness criteria for at least two of the three years of the averaging period were
21 included.
22 Figure 2-73 shows annual avg concentrations for gas-phase HNO3 from CASTNet for the years
23 2004 through 2006. (White areas on the maps are areas where monitoring sites are absent and no
24 information is available.) Because HNO3 is produced mostly as a secondary product from emitted NO the
25 regions of higher concentrations HNO3 are geographically similar to those of high concentration NO and
26 NO2, the northeast corridor and southern California.
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-2.5
t3.0
3.5
>4.0
Source: CASTNET, USEPA/CAMD 7/30/07
Figure 2-73. Annual average gas-phase HMOs concentrations, 2004-2006.
1 Because they have the same precursor reactants in NO and NO2, elevated O3 concentrations are
2 often associated with elevated HNO3 concentrations. However, HNO3 can be produced in significant
3 quantities in winter, even when O3 concentrations are low. The ratio between O3 and HNO3 also shows
4 great variation in air pollution events, with NOx-saturated environments having much lower ratios of O3
5 to HNO3 (Ryerson, 2001). pNO3 is formed primarily by the combination of NO3 supplied by HNO3 with
6 NH3, and may be limited by the availability of either reactant. NO3 is expected to correlate loosely with
7 O3, whereas NH3 is not expected to correlate with O3. 2003 annual avg concentrations of pNO3 from U.S.
8 EPA's STN (CSN) at several locations are shown in Figure 2-74 along with estimated of the fraction
9 contributed locally. (A concentration of 1 (ig/m3 reported here corresponds to -0.40 ppb NO3 .)
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Nitrates
Fresno
Missoula
Salt Lake City
Tulsa
St. Louis
Birmingham
Indianapolis
Atlanta
Cleveland
Charlotte
Richmond
Baltimore
New York City
WEST
EAST
Q Regional
Contribution
• Local
Contribution
2 4 6 8 10 12
Annual Average Concentration
of Nitrates, ug/m3
Source: EPA (2004).
Figure 2-74. Concentrations of participate N03 measures as part of the EPA's speciation network. 1
pg/m3 -0.40 ppb equivalent gas phase concentration for NOr. (Note: Regional concentrations are
derived from the rural IMPROVE monitoring network, http://vista.cira.colostate.edu/improve.
1 Thus, annual average pNO3 can account for several ppb of NOY, with the higher values in the
2 West. There is a strong seasonal variation, which is especially pronounced in western areas where there is
3 extensive wood burning in the winter resulting in a larger fractional contribution of local sources. Areas in
4 the East where there are topographic barriers might be expected to show higher fractional contributions
5 from local sources than other eastern areas that are influenced by regionally dispersed sources. Figure
6 2-76 shows a map of annual avg NOs concentrations in the years 2004 to 2006 produced from CASTNet
7 measurements of ambient concentrations. This maps indicates at least qualitatively that maximum
8 concentrations are found in areas of maximum NO and NC>2 emissions.
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0.5
1.0
-1.5
-2.0
[2.5
:
>4.0
>4.0
Source: CASTNET, USEPA/CAMD 7/30/07
'
Figure 2-75. Annual average gas-phase NOs concentrations, 2004-2006.
1 However, depending on the acidity of the particles, which in turn depends strongly on their SC>42
2 and NH4+ contents, higher pNO3 concentrations could be found in coarse mode particles PM10_2.5 than in
3 PM2 5 samples. The average pNO3 content of PM2 5 and PM10 is typically ~1% in the eastern U.S.; and
4 15.7% and 4.5% in the western U.S. (EPA, 1996). These values suggest that most of the pNO3 was in the
5 PM2.s size fraction in the studies conducted in the western U.S., but pNO3 in the studies in the eastern
6 U.S. was mainly in the PM10_2.5 size fraction.
2.9.5.3. Nitro-PAHs
7 Nitro-PAHs are widespread and found even in high altitude, relatively unpolluted environments
8 (Schauer, 2004) but there are differences in composition and concentration profiles both within and
9 between sites (rural vs. urban) as well as between and within urban areas (Albinet, 2006; Soderstrom,
10 2005; Naumova, 2003, 89234; Naumova, 2002), with some differences in relative abundances of nitro-
11 and oxo-PAHs also reported. Source attribution has remained largely qualitative with respect to
12 concentrations or mutagenicity (Eide, 2002). The spatial and temporal concentration pattern for the nitro-
13 PAHs may differ from that of the parent compounds because concentrations of the latter are dominated by
14 direct emission from local combustion sources. These emissions results in higher concentrations during
15 atmospheric conditions more typical of wintertime when mixing heights tend to be low. The
16 concentrations of secondary nitro-PAHs are elevated under conditions that favor hydroxyl and NO3
17 radical formation, i.e., during conditions more typical of summertime, and are enhanced downwind of
18 areas of high emission density of parent PAHs and show diurnal variation (Fraser, 1998; Reisen, 2005;
19 Kameda, 2004). Nitro-napthalene concentrations in Los Angeles, CA varied between about 0.15 to almost
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1 0.30 ng/m3 compared to 760 to 1500 ng/m3 for napthalene. Corresponding values for Riverside, CA were
2 0.012 to more than 0.30 ng/m3 for nitro-napthalene and 100 to 500 ng/m3 for napthalene. Nitro-pyrene
3 concentrations in LA varied between approximately 0.020 to 0.060 ng/m3 compared to 3.3 to 6.9 ng/m3
4 pyrene, whereas corresponding values for Riverside were 0.012 to 0.025 ng/m3 and 0.9 to 2.7 ng/m3.
2.9.5.4. NH3
5 Section 2.7.1.5 above established that a successful real-time continuous monitoring technique for
6 ambient NH3 has not been identified; and, of at least equal importance, Section 2.4 above described the
7 severely limiting unknowns related to NH3 emissions on national and local scales. With these important
8 lacunae, estimates of NH3 concentrations at any scale for the U.S. must be constructed and interpreted
9 with caution. It is possible, for example, to rank NH3 concentrations by land use types from the few
10 special field campaigns where it was measured as Walker et al. (Walker, 2004) did for agricultural, non-
11 agricultural, and urban types; see Table 2-19. This table shows the enormous range in NH3 concentrations
12 by season and land use type, from a low of 0.02 (ig/m3 in summer over alpine tundra on Niwot Ridge,
13 CO, (Rattray and Sievering, 2001) to 11.0 (ig/m3 over fertilized lands in Wekerom in the central
14 Netherlands (Buijsman, 1998).
15 A preliminary draft U.S. national-scale, county-level NH3 map was created by the U.S. EPA using
16 emissions data from the widely-used Carnegie Mellon University (CMU) NH3 emissions model, version 3
17 (see, Finder, 2007) for a description and application information) and an empirical relationship between
18 emissions and ambient concentration derived from field measurements over five different land use types
19 in North Carolina covering the range of expected NH3 emissions densities. In the CMU emissions model
20 used for this analysis, fertilized soils were included but NH3 emissions from natural (non-fertilized soils)
21 was not because of overwhelmingly large uncertainties in their emissions factors. Emissions from mobile
22 sources are included in this analysis, although uncertainties in those values are also large. And emissions
23 from a small number of counties having very low emissions rates was set to missing because their
24 extremely low values invalidated determination of densities in those counties. The CMU-derived county-
25 level NH3 emissions map is show in Figure 2-76. Differences in the techniques for estimating NH3
26 emissions and the very large uncertainties in NH3 emissions factors and totals complicate direct, fine-
27 scale comparisons to other NH3 emissions maps. However, both the magnitude and areal extent of the
28 emissions map here compare very favorably to the U.S. EPANEI database NH3 emissions map shown in
29 Section 2.4 above.
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Table 2-19. Ambient NH3 concentrations summarized by study.
Concentration (jjgm3)
3.0
11.0
10.48
0.65-1.2
0.26
0.34
0.02
0.62-1.47
0.29
0.22
0.21
0.16
0.21
0.23
0.63
4.75
0.38-1.49
0.63-0.72
1.18
"Buijsmanetal. (1998).
bMcCullochetal. (1998).
cPryoretal. (2001).
dTarnayetal. (2001).
e Rattray and Sievering (2001)
'Anejaetal. (1998).
fl|_angfordetal(1992).
hl_eferetal. (1999)
McCurdyetal. (1999).
i Sickles etal. (1990).
kl_eadereretal. (1999).
Land Use
Agricultural
Agricultural
Agricultural
Agricultural
Agricultural
Non-agricultural
Non-agricultural
Non-agricultural
Non-agricultural
Non-agricultural
Non-agricultural
Non-agricultural
Non-agricultural
Non-agricultural
Non-agricultural
Non-agricultural
Urban
Urban
Urban
Comment
Low NHs emissions
Moderate NHa emissions "
Fallb
Spring °
Winter0
High elevation, summer and fall d
High elevation, summer e
High elevation, summer'
High elevation, summer $
Coastal, summers
Forest, summer 'i
Forest h
Wetland, summer a
Wetland, summer a
Desert, summer a
Grassland, summer a
Pittsburgh, PA; summer
Research Triangle Park, NC; fall i
Vinton, VA; summer k
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kg/sq. km/yr
26 - 50
I I 61 - 150
151 -20Q
201 - 300
301 - 430
I | 401 - 600
| | 601 - 800
| [801-1,000
| J 1.001 -1500
H 1,501 -2,000
| | 2,001 - 2,500
| | 2,501 - 5,000
| 5,001 - 7,500
[ [7,501-12,000
Source: J. Walker, USEP/VORD/NRMRL
Figure 2-76. County-scale NHs emissions densities from the CMU inventory model.
| | 063-065
| 0.66-0.68
I | 0.69-0,72
Q^| 0.73 - 0.77
| | 0.78-0.84
| | 0.85 - 0.91
| | 0.92 - 0.99
I | 1.00-1 09
| 1.10-1.22
| | 1.23-1.36
HI 1.37-1.56
| J 1 57-2.25
|. | 2.26 - 3.50
| | 3 51 - 5 00
501-6.50
Source: J. Walker, USEP/VORD/NRMRL
Figure 2-77. Estimated county-scale ambient NHs concentrations.
2.9.5.5. NH4N03
1 The IMPROVE network is the premier source of data about the spatial and temporal patterns of
2 rural and remote pNOs in the U.S. Data about urban pNOs and other particles comes primarily from the
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1 collection of networks now termed the Chemical Speciation Network (CSN), which includes the U.S.
2 EPA Speciation Trends Network (STN) and others (Jayanty, 2003). Although IMPROVE began and still
3 functions primarily to characterize visibility impairments in protected areas, the network has been
4 expanded several times since its inception to include coverage of remote areas in central and western
5 states of the U.S. to better understand regional components of particulate pollution. Except where noted,
6 information in this section was derived form the IMPROVE IV Report (DeBell, 2006) with data displays
7 created with data and tools available at http://vista.cira.colostate.edu/views/. Much of these data and
8 conclusions are also to appear in Pitchford et al., 2008.
9 The IMPROVE Network monitors the major fine particle components pSO4, NO3, crustal, EC and
10 OC, and coarse mass concentration computed as the concentration difference PM10 minus PM2 5. An
11 implicit assumption is that most of the pNO3 is present as NH4NO3 in the PM2 5 size range. One
12 component of the Big Bend Regional Aerosol and Visibility Observational (BRAVO) Study, conducted at
13 Big Bend National Park, TX, in the summer and fall of 1999, entailed use of detailed measurements of
14 aerosol chemical composition, size distribution, water growth, and optical properties to characterize the
15 aerosol and assess the relationships among aerosol physical, chemical, and optical properties (Schichtel,
16 et al., 2004). Fine pNO3 accounted for <5% of the mass concentration in these samples and was present
17 mostly as NaNO3. Approximately 67% of the pNO3, again inferred to be NaNO3, was found in the coarse
18 mode where it comprised -8% of the mass concentration.
19 A year-long special study of coarse particle speciation was conducted at nine IMPROVE remote
20 area monitoring sites during 2003 and 2004 to provide additional information about the geographic and
21 seasonal variations in coarse particle composition; see Malm, et al. 2007. The same sampling and
22 analytical methodologies procedures were used for the PM10 samples as are routinely used on the
23 IMPROVE PM2 5 samples. The IMPROVE coarse particle speciation study did not include NH4+ analysis,
24 so pNO3 was assumed again to be NH4NO3. As expected crustal minerals were the largest contributors to
25 coarse mass overall at -60%, and organic particles contributed significantly at -25% of coarse mass. On
26 average, pNO3 was the third largest contributor to coarse mass at -8% on average for the nine monitoring
27 sites. The sites with the highest coarse pNO3 concentrations were the two in California (San Gorgonio,
28 0.74ug/m3 and Sequoia, 0.69ug/m3) where fine pNO3 were also high on average (2.66ug/m3 and
29 2.14ug/m3 respectively). Brigantine, a coastal site in NJ had the highest fraction of total coarse pNO3 at
30 36%. The authors speculated that Brigantine's pNO3 was likely NaNO3, the result of HNO3 reactions with
31 sea-salt NaCl. The nine-site average fraction of total coarse pNO3 was 26%.
32 Figure 2-78 shows maps of remote NH4NO3 for two years selected to demonstrate the additional
33 information available after expansion of the IMPROVE network into the central U.S. The locations of
34 monitoring sites supplying the data shown as color contours are shown as dot on the maps. Concentration
3 5 contour maps generally carry the caution that their isolines are provided merely to guide visual
August 2008 2-159 DRAFT-DO NOT QUOTE OR CITE
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1 similarities among sites reporting similar values, and should not be read to suggest any quantitative
2 spatial interpolation where sites do not exist. These plots, showing the so-called Midwest pNO3 "bulge"
3 illustrate why that caution is always warranted.
Figure 2-78. IMPROVE network measured annual averaged ammonium N03 concentration for 2000
(left) and for 2004 (right), (maps produced by VIEWS)
4 Prior to 2001 no IMPROVE or any other remote-area aerosol speciation monitoring sites exited in
5 the central states between northern MN and MI to the north and AK and KY to the south. The lack of
6 monitoring over such a large region in the center of the country hid the largest regional distribution of
7 particulate matter dominated by NH4NO3, previously thought to be a phenomenon isolated to CA.
8 However, with fewer than 6 years of complete data for this region, insufficient information exists to test
9 for long-term trends.
10 Combining IMPROVE and CSN data makes possible comparison of urban pNO3 to surrounding
11 remote-area regional values. These are shown as paired color contour maps for IMPROVE and
12 IMPROVE plus CSN in Figure 2-79. EPA (2004b) used the pairing of IMPROVE and CSN monitoring
13 sites at 13 selected areas to separate local and regional contributions to the major contributors of PM2 5, as
14 shown for pNO3 in Figure 2-80.
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A STN Site
• IMPROVE Site
• IMPROVE Urban Site
00
Puerto Rico /
Virgin Islands
Figure 2-79. IMPROVE and CSN (labeled STN) monitored mean ammonium nitrate concentrations
for 2000 through 2004.
Nitrates
Fresno
Missoula
Salt Lake City
Tulsa
St. Louis
Birmingham
Indianapolis
Atlanta
Cleveland
Charlotte
Richmond
Baltimore
New York City
LZ
I WEST
LJ ^SJ
I
1C
I]
1 O RagioNdl
1 1 Contribution
• Local
Contribution
Annual Average Concentration
o1 Nitrates, ug/m3
Source: EPA, 2004b.
Figure 2-80. Regional and local
contributions to annual average
PM2.5 by pNOs for select urban
areas based on paired IMPROVE
and CSN monitoring sites.
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1 Urban pNO3 concentrations in Western states are in general more than a factor of 2 greater than the
2 remote-area regional concentrations. For the Central Valley of California and Los Angeles areas, the
3 urban excess NH4NO3 exceed regional concentrations by amounts ranging from 2ug/m3 to 12ug/m3. In
4 the region of the recently identified Midwest pNO3 bulge, the urban concentrations were less than twice
5 the background concentrations for an annual urban excess of about lug/m3. Northeast and southeast of the
6 Midwest NO3 bulge, annual urban pNO3 were ~lug/m3 or less above the remote-area regional
7 concentrations, with warmer southern locations tending to have smaller concentrations of both regional
8 and urban excess pNO3.
9 Holland et al. (1999) developed NOx emissions trends from 1989 to 1995 and compared them to
10 corresponding trends in total N (pNO3 + gas-phase HNO3) for the states in the U.S. between LA and MN
11 and East of that line based on data from 34 rural CASTNet dry deposition monitoring sites. They reported
12 a decrease in total N median values of ~8% associated with a decrease of 5.4% in non-biogenic NOx
13 emissions. Because of the form of total N assumed in this analysis, it is not possible to determine whether
14 this change is larger for HNO3 or pNO3. For situations with limited gas-phase NH3 or with elevated
15 temperatures, it may be assumed that the trend in total N is principally in FŁNO3 with no net change in
16 pNO3. Where NH3 concentrations are substantially in excess of those required to neutralize pSO4 and
17 where temperatures are lower, this trend may be assumed to be reversed.
18 Potential causes of the Midwest pNO3 bulge can be examined through comparison of the pNO3
19 areal extent to that of NOX and NH3 emissions. Figure 88 shows a map of the annual average pNO3
20 concentrations (top) with a map of NH3 emissions (bottom). The spatial extent of NH3 emissions in the
21 Midwest is strikingly similar to that of pNO3 concentrations, each having regional maxima centered on
22 Iowa. NO and NO2 emissions are high over a broad region of the country associated with the larger
23 population densities and greater numbers of fossil fueled EGUs to the east of the Midwest pNO3 bulge.
24 While both NH3 and HNO3 are needed to form NH4NO3, the maps suggest the Midwest NO3 bulge is due
25 primarily to the abundance of free NH3, defined as the amount beyond that required to neutralize the
26 acidic pSO4. By contrast, the region East of the Midwest NO3 bulge might be expected to have excess
27 HNO3 given greater emissions of NO and NO2, but apparently has a deficiency of free NH3. The few
28 eastern monitoring sites with locally high pNO3 (near southern PA) are located within a small region of
29 high density animal agricultural sites identified as a high NH3 emissions region in Figure 88. Note that
30 California's South Coast and Central Valley have both high NH3 and NO and NO2 emissions, explaining
31 its own high pNO3 concentration.
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Figure 2-81. Maps of spatial patterns for average annual particulate N03 measurements (top), and
for NHs emissions for April 2002 from the WRAP emissions inventory (bottom).
1 Importantly, although the Midwest pNO3 bulge was not apparent before measurements were made
2 in its region, air quality modeling using national-scale emissions data predicted it as early as 1996 as done
3 with CMAQ applications for the U.S. EPA Western Regional Air Partnership (http://www.wrapair.org).
4 Figure 89 shows the CMAQ-predicted average pNO3 concentration for the month of January 1996 (left
5 panel) and the model-predicted sensitivities of pNO3 to a 50% decrease in NH3 emissions. Reductions in
6 magnitude of ~3 ug/m3 in the heart of the Midwest NO3 bulge and in areal extent are predicted as a result
7 of the NH3 emissions decrease.
CMAQ Jan Avg Nitrate
8 Layers
k-CCTM_a2b1_36.combine.01 .avg
CMAQ Jan Avg Nitrate- 50% NH3 Red.
8 Layers
o-CCTM a2b9 36.combine.01.avg
12.000 90
10.500
9.000
7.500
6.000
4.500
3.000
1.500
0.000 ,
ug/m3
12.00090
10.500
9.000
7.500
6.000
1.500
3.000
1.500
0.000
13? ug/m3
January 1,1996 1:00:00
Min- 0.000 at (5,90), Max- 11.025 at (13,44)
January 1,1996 1:00:00
Min- 0.000 at (5,90), Max- 10.577 at (115,40)
Figure 2-82. CMAQ simulation of January monthly averaged particulate N03 concentration using
1996 emissions (left), and for a 50% decrease in NH3 emissions (right). Source: U.S. EPA / WRAP.
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1 Several example monitoring locations distributed across the northern and southern portions of the
2 Western U.S. have been selected to illustrate the attribution results from air quality simulation modeling
3 by source region and source type for pNO3. They include Olympic National Park (NP), WA; Yellowstone
4 NP, WY; and Badlands NP, SD across the north, and San Gorgonio Wilderness (W), CA; Grand Canyon
5 NP, AZ and Salt Creek W, NM across the south. Pie diagrams of pNO3 attribution results by source region
6 for each of these sites are shown in Figure 90. Based on these sites, 25% or less of the pNO3 in remote
7 areas of the Pacific coastal states is from outside of the U.S. (Pacific Offshore and Outside of the
8 Domain). The Outside of the Domain values are derived by simulating the fate of the boundary condition
9 concentrations, which for the WRAP air quality modeling were obtained using output from the GEOS-
10 CHEM global air quality model (Fiore, 2003).
2002
Nitrate 1.6 ua/m3
2002
Nitrate 0.6 ua/m3
2002
Nitrate 1.2 ua/m3
(b)
WRAP
| Pacific Offshore
CENRAP
Eastern U.S.
Canada
Mexico
Outside Domain
2002
Nitrate 1.5 ua/m3
2002
Nitrate 0.4 ua/m3
2002
Nitrate 0.5 uci/m3
Figure 2-83. Particulate N03 source attribution by region using CAMx modeling for six western
remote area monitoring sites. Top left to right Olympic NP, WA; Yellowstone NP, WY; Badlands NP,
SD; bottom left to right San Gorgonio W, CA; Grand Canyon NP, AZ; and Salt Creek W, NM. WRAP
includes ND, SD, WY, CO, NM and all states further west. CENRAP includes all states east of WRAP
and west of the Mississippi River including MN. Eastern U.S. includes all states east of CENRAP.
The Pacific Offshore extends 300km to the west of CA, OR, and WA. Outside Domain refers to the
modeling domain, which extend hundreds of kilometer into the Pacific and Atlantic Oceans and
from Hudson Bay Canada to just north of Mexico City.
11 By comparison, the pNO3 is much more from domestic regional emission sources, with ~60 to
12 -80% being from emissions within the WRAP region. For the west coast sites -25% of pNO3 is from a
13 combination of Pacific Offshore emissions (i.e. marine shipping) and Outside Domain regions. Canadian
14 emissions are responsible for -10 to 30% of pNO3, but Mexican emissions do not contribute appreciably
15 to pNO3 for the three southern sites. Motor vehicles are the largest contributing NO+NO2 source category
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1 responsible for pNO3 for these six WRAP sites, with a combination of point, area and wildfire source
2 categories also contributing from ~10 to 50% of the WRAP regional emissions.
2.9.6. Ambient Concentrations of Relevant S Compounds
2.9.6.1. S02 and S042~ Near Urban Areas
3 SO2 data collected from the SLAMS and National Air Monitoring Stations (NAMS) networks show
4 that the decline in SO2 emissions from EGUs has improved air quality. There has not been a single
5 monitored exceedance of the SO2 annual ambient air quality standard in the U.S. since 2000 (EPA,
6 2006b). EPA's trends data (www.epa.gov/airtrends) reveal that the national composite average SO2 annual
7 mean ambient concentration decreased by 48% from 1990 to 2005, with the largest single-year reduction
8 coming in 1994-1995 (EPA, 2006b).
9 In 2007, there were -500 SO2 monitors reporting values to the EPA Air Quality System database
10 (AQS). Trace level SO2 monitoring is currently required at the approximately 75 proposed NCore sites, as
11 noted in CFR 40 Part 58 Appendices C and D. Continued operation of existing State and Local Air
12 Monitoring Sites (SLAMS) for SO2 using FRM or FEM is required until discontinuation is approved by
13 the EPA Regional Administrator. Where SLAMS SO2 monitoring is required, at least one of the sites must
14 be a maximum concentration site for that specific area.
15 Figures 91 through 96 illustrate the 2005 geospatial locations of monitors for SO2, NO2, CO, PM10,
16 PM2 5, and 03. These locations, sited in several cities in six states, were selected as relevant for SO2
17 environmental effects to complement measurements from rural and remote CASTNet sites and to be near
18 large sources of SO2. For each state, map A of each figure shows locations of each monitor for all six
19 pollutants; map B of each figure shows only the SO2 monitor locations. Totals for each monitor type are
20 included. These figures demonstrate the important point that not all SO2 monitors in any Consolidated
21 Metropolitan Statistical Area (CMSA) are co-located with monitors for other pollutants. Two examples
22 are given below.
23 Table 2-20 lists the totals for all criteria air pollutant monitors (except Pb) in California, as well as
24 the subset of these monitors in San Diego County. At each of the four sites where SO2 was measured,
25 NO2, CO, PMio, PM2 5, and O3 were also measured, with the exception of PM2 5 at one site (AQS ID
26 060732007) in Otay Mesa, CA. Table 2-21 lists the totals for all criteria air pollutant monitors (except Pb)
27 in Ohio, as well as the subset of in Cuyahoga County.
28 In Cuyahoga County, PM10 and PM2 5 were measured at all four sites where SO2 was also
29 measured in 2005, but Oj, and CO were not measured at any of those four sites; NO2 was only measured
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1 at one site (AQS ID 39050060) near Cleveland's city center and ~0.5 km from the intersection of
2 Interstate Highways 77 and 90.
Table 2-20. Monitor counts for California and San Diego County, 2005.
California (all)
San Diego County
S02
35
4
N02
105
9
Os
176
10
CO PMio PM2.5
86 177 97
6 7 7
Table 2-21. Monitor counts for Ohio and Cuyahoga County, 2005.
S02 N02 03 CO PMio PM2.5
Ohio (all) 31 4 49 15 49 49
Cuyahoga County 423467
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Highwa
y
Interstate
Federal
Monitor Location
+
A
V
o
c
ti
CO (86)
NO; (105)
O, (176)
PM.j (177)
PM25(177)
SO2 (35)
San Diego «
Source- US EPA Office of Air and Radeon AQS Database
Figure 2-84. Criteria pollutant
monitor locations (A) and SOa
monitor locations (B), California,
2005. Shaded counties have at
least one monitor.
Highway
— Interstate
Federal
State
Monitor Location
+
A
V
O
D
a
CO (15)
NO2 (4)
03 (49)
PM10 (49)
PM; 5 (49)
S02(31)
Source- US EPA Office of Ait and Radiation AQS Database
Figure 2-85. Criteria pollutant
monitor locations (A) and 862
monitor locations (B), Ohio,
2005. Shaded counties have at
least one monitor.
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Highway
— Interstate
Federal
State
Monitor Location
* CO (20)
A N02(13)
V 03 (45)
O PM,o (67)
U PMZ5(16)
ft SO2 (7)
Figure 2-86. Criteria pollutant monitor
locations (A) and 862 monitor locations (B),
Arizona, 2005. Shaded counties have at
least one monitor.
Source. US EPA Office of Ait and Radiation AOS Database
Highway
Interstate
Federal
State
Monitor Location
-i- CO (25)
A NOj (29)
V 03 (47)
O PM,0 (46)
0 PM25(49)
* SO2 (42)
Figure 2-87. Criteria pollutant monitor
locations (A) and 862 monitor locations (B),
Pennsylvania, 2005. Shaded counties have
at least one monitor.
Source; US EPA Office of Air and Radiation AQS Database
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Buffalo
Highway
Interstate
Federal
State
+ C0(11)
A N02 (9)
V 03(34)
O PM,0(10)
D PM25(28)
•a S02 (25)
Figure 2-88. Criteria pollutant monitor
locations (A) and SOa monitor locations (B),
New York, 2005. Shaded counties have at
least one monitor.
Source: US EPA Office of Air and Radiation AQS Database
Highway
Interstate
Federal
State
Monitor Location
+
A
V
0
D
i?
CO (5)
N02(13)
03 (16)
PM,0(11)
PM25(22)
SO2(10)
Figure 2-89. Criteria pollutant monitor
locations (A) and 862 monitor locations (B),
Massachusetts, 2005. Shaded counties
have at least one monitor.
Source- US EPA Office of Air and Radiation AQS Database
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1 The regional distribution of SO2 and SO42 concentrations through the CONUS are shown in Table
2 2-22. In and around most individual CMSAs, the trends are also toward lower SO2 levels. Table 2-22
3 shows that many annual and even 1-h mean concentrations for the years 2003 through 2005 were
4 consistently at or below the operating LOD of ~3 ppb for the standard sensitivity UV fluorescence SC>2
5 monitors deployed in the regulatory networks; the aggregate mean value over all 3 years and all sites in
6 and around the CMSAs was just above the LOD at ~4 ppb, and was identical to the 1-h and 24-h means.
Table 2-22. Regional distribution of 862 and S042~ ambient concentrations, averaged for 2003-05.
S02(ppb)
Mid-Atlantic 3.3
Midwest 2.3
Northeast 1.2
Southeast 1.3
Concentration
S042- (Mg/m3)
4.5
3.8
2.5
4.1
Table 2-23. Distributions of temporal averaging inside and
Averaging Time n ^^
Monitor Locations , ,- ,,, -,-
1-h Max Concentration
Inside CMSAs 332405 13 111 3
Outside CMSAs 53417 13 1111
1-h Avg Concentration
Inside CMSAs 7408145 4 1111
Outside CMSAs 1197179 4 1111
24-h Avg Concentration
Inside CMSAs 327918 4 1111
Outside CMSAs 52871 4 1111
Annual Avg Concentration
Inside CMSAs 898 4 1111
Outside CMSAs 143 4 1111
Aggregate 3-yr Avg Concentration, 2003-2005
Inside CMSAs 283 4 1112
Outside CMSAs 42 4 1112
outside CMSAs.
Percentiles
30 50 70 75 90 95 99
4 7 13 16 30 45 92
25 10 13 31 51 116
1 2 4 5 10 15 34
1 2 3 3 7 13 36
2 3 5 6 10 13 23
1 2 3 4 8 12 25
2 4 5 6 8 10 12
2 3 4 5 8 9 13
3 3 5 5 8 10 12
2 3 4 5 8 9 13
Max
714
636
714
636
148
123
15
14
14
13
* Values are ppb
** CMSA = Consolidated Metropolitan Statistical Area
7 To be sure, the max 1-h concentration observed at some sites in and around some CMSAs still
8 exceeded the mean by a large margin, with max 1-h values of > 600 ppb. However, the 50th percentile
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1 maximum value outside CMSAs, 5 ppb, was only slightly greater than the 1-h, 24-h, and annual mean
2 value, 4 ppb. The 50th percentile maximum value inside CMSAs, 7 ppb, was 75% greater than these
3 longer-term averages, reflecting heterogeneity in source strength and location. In addition, even with 1-h
4 max values of > 600 ppb, the maximum annualized mean value for all CMSAs was still < 16 ppb, which
5 is below the current annual primary SC>2 NAAQS.
6 The strong west-to-east increasing gradient in SC>2 emissions described above is well-replicated in
7 the observed concentrations in individual CMSAs. For example, Table 2-23 shows the mean annual
8 concentrations from 2003-2005 for the 12 CMSAs with four or more SC>2 regulatory monitors. Values
9 ranged from a reported low of ~1 ppb in Riverside, CA and San Francisco, CAto a high of ~12 ppb in
10 Pittsburgh, PA and Steubenville, OH, in the highest SO2 source region.
11 The Pearson correlation coefficients (r) for multiple monitors in these CMSAs were generally very
12 low for all cities, especially at the lower end of the observed concentration ranges, and even negative at
13 the very lowest levels on the West Coast; see Table 2-24. This reflects strong heterogeneity in SO2
14 ambient concentrations even within any one CMSA. At higher concentrations, the r values were also
15 higher. In some CMSAs, this heterogeneity may result from meteorological effects, whereby a generally
16 well-mixed subsiding air mass containing one or more SC>2 plumes with relatively high concentration
17 would be more uniformly spread than faster-moving plumes with lower concentrations. However,
18 instrument error may also play a role, because the highest r values, i.e., those > 0.7, correspond to the
19 highest SC>2 concentrations, i.e., > 6 and > 10 ppb. Since the lowest SC>2 concentrations are at or below
20 the operating LOD, and demonstrate the lowest correlation across monitors that share at least some air
21 mass characteristics most of the year, the unbiased instrument error in this range may be confounding
22 interpretation of any possible correlation. This could be because the same actual ambient value would be
23 reported by different monitors (with different error profiles) in the CMSA as different values in this
24 lowest concentration range.
25 To better characterize the extent and spatiotemporal variance of SO2 concentrations within each of
26 the CMSAs having four or more SC>2 monitors, the means, minima, and maxima were computed from
27 daily mean data across all available monitors for each month for the years 2003 through 2005. Because
28 many of these CMSAs with SO2 monitors also reported SO42 , it is possible to compute the degree of
29 correlation between SO2, the emitted species, and SO42 , the most prominent oxidized product from SO2.
30 SO42 values, however, while averaged over all available data at each site are generally available at their
31 monitoring sites on a schedule of only 1 in 3 days or 1 in 6 days. Furthermore, SO2 and SO42 monitors
32 are not all co-located throughout the CMSAs. For each of the five example CMSAs in Figure 2-11
33 through Figure 2-15, monthly aggregated values are depicted from daily means of: (a) the monthly mean,
34 minimum, and maximum SC>2 concentrations; b) the monthly mean, minimum and maximum SO42
35 concentrations; and (c) a scatterplot of SC>2 versus SO42 concentrations.
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Table 2-24. Range of mean annual 862 concentrations and
areas having at least four regulatory monitors, 2003-2005.
CMSA (# Monitors)
Philadelphia, PA
Washington, DC
Jacksonville, FL
Tampa, FL
Pittsburgh, PA
Steubenville, OH
Chicago, IL
Salt Lake City, UT
Phoenix, AZ
San Francisco, CA
Riverside, CA
Los Angeles, CA
Pearson correlation coefficients
Mean S02
Concentration
(PRb)
3.6-5.9
3.2-6.5
1.7-3.4
2.0-4.6
6.8-12
8.6-14
2.4-6.7
2.2-4.1
1.6-2.8
1.4-2.8
1.3-3.2
1.4-4.9
in urban
Pearson
Correlation
Coefficient
0.37-0.84
0.30-0.68
-0.03-0.51
-0.02-0.18
0.07-0.77
0.11-0.88
0.04-0.45
0.01-0.25
-0.01-0.48
-0.03-0.60
-0.06-0.15
-0.16-0.31
1 Moving across the CONUS from highest to lowest SO2 concentrations, first consider Steubenville,
2 OH (Figure 97), where the area of highest SO2 concentrations of all 12 CMSAs with more than four
3 monitors, all monthly mean SO2 concentrations (a) were substantially < 30 ppb, though max daily means
4 in some months were often > 60 ppb, or even > 90 ppb. SO42 data (b) at Steubenville were insufficient to
5 make meaningful comparisons, though the 12 months of available SO42 data suggest no correlation with
6 SO2 (c).
7 Next, consider Philadelphia, PA (Figure 98). SO2 in Philadelphia, PA (a) is present at roughly one-
8 half the monthly mean concentrations in Steubenville, OH, and demonstrates a strong seasonality with
9 SO2 concentrations peaking in winter. By contrast, SO42 concentrations in Philadelphia peak in the three
10 summer seasons, with pronounced wintertime minima. This seasonal anticorrelation still contains
11 considerable monthly scatter, however.
12 Los Angeles, CA (Figure 99) presents a special case, since its size and power requirements place a
13 larger number of SO2 emitters near it than would otherwise be expected on the West Coast.
14 Concentrations of SO2 demonstrate weak seasonality in these 3 years, with summertime means of ~3 to 4
15 ppb, and maxima generally higher than wintertime ones, though the highest means and maxima occur
16 during the winter of 2004-2005. SO42 at Los Angeles shows stronger seasonality, most likely because the
17 longer summer days of sunny weather allow for additional oxidation of SO2 to SO42 than would be
18 available in winter. Weak seasonal effects in SO2 likely explain the complete lack of correlation between
19 SO2 and SO42 here.
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CO
B-
4
fr
SO, (ppft)
Figure 2-90. Steubenville, OH, 2003-2005. (a) Monthly mean, minimum, and maximum 862
concentrations, (b) Monthly mean, minimum, and maximum S042~ concentrations, (c) Monthly mean
S042" concentrations as a function of SOi concentrations.
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-a
Q.
•>
I
f
Ł
o
I
J;
fit
SO; (PPb)
Figure 2-91. Philadelphia, 2003-2005. (a) Monthly mean, minimum, and maximum SOa
concentrations, (b) Monthly mean, minimum, and maximum S042~ concentrations, (c) Monthly mean
S042" concentrations as a function of SOa concentrations.
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E
en
J'
0 " *
Figure 2-92. Los Angeles, 2003-2005. (a) Monthly mean, minimum, and maximum 862
concentrations, (b) Monthly mean, minimum, and maximum S042~ concentrations, (c) Monthly mean
S042" concentrations as a function of SCb concentrations.
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1
III
I
8'
I-
w
M
r
K
-.
1:
--
J»
o
(
S02 (ppb)
Figure 2-93. Riverside, CA, 2003-2005. (a) Monthly mean, minimum, and maximum SCh
concentrations, (b) Monthly mean, minimum, and maximum S042~ concentrations, (c) Monthly mean
S042" concentrations as a function of 862 concentrations.
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s
f
I
111!
•ml
it
20 25
SQi (Kb)
1
2
3
4
Figure 2-94. Phoenix, 2003-2005. (a) Monthly mean, minimum, and maximum 862 concentrations.
(b) Monthly mean, minimum, and maximum S042~ concentrations, (c) Monthly mean SCU2"
concentrations as a function of SCh concentrations.
The Riverside, CA CMSA (Figure 100) presents the strongest example among the 12 examined for
this study of correlation between SO2 and SO42 , though even here the R2 value is merely 0.3. Seasonal
peaks are obvious in summertime for SO2 and SO42 , both at roughly one-half the ambient concentrations
seen in Los Angeles. This is very likely due to Riverside's geographic location just downwind of the
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1 regionally large electric generating utility sources near Los Angeles and the prevailing westerly winds in
2 summer. Again, as with Los Angeles, the summertime peaks in SO42 are most likely due to the
3 combination of peaking SO2 and favorable meteorological conditions allowing more complete oxidation.
4 Phoenix, AZ was the CMSA with the lowest monthly mean SC>2 and SO42 concentrations
5 examined here (Figure 100). In Phoenix, nearly all monthly mean SC>2 values were at or below the
6 regulatory monitors' operating LOD of ~3 ppb. SO42 concentrations were equivalently low, roughly one-
7 half the concentrations seen in Riverside, CA, for example. The monthly mean data show strong
8 summertime peaks for even these very low-level SO42 observations, which, at ~1 to 3 (ig/m3, were
9 generally one-half of those in Philadelphia. This suggests some seasonality in SC>2, though anticorrelated
10 with SO42 ; however, the trend is very weak, as the correlation scatterplot shows.
2.9.6.2. 862 and SC>42~ in rural and remote areas
11 The mean annual concentrations of SC>2 and SO42 from CASTNet's long-term monitoring sites can
12 be compared using two 3-year periods, 1989-1991 and 2003-2005, shown in Figure 101 for SO2 and
13 Figure 102 for SO42 .
14 From 1989 through 1991 the highest ambient mean concentrations of SC>2 and SO42 were observed
15 in western Pennsylvania and along the Ohio River Valley: > 20 (ig/m3 (~8 ppb) SO2 and > 15 (ig/m3
16 SO42 . As with SO2, in the years since the ARP controls were enacted, both the magnitude of SO42
17 concentrations and their areal extent have been significantly reduced, with the largest decreases again
18 along the Ohio River Valley.
19 The IMPROVE network monitors the major fine particle components including SO42 , NOs,
20 crustal, elemental, and organic carbon plus coarse mass concentration defined as PM10 minus PM2 5. An
21 implicit assumption is that most of the pSO4 is present as (NH4)2SO4. Much of the information contained
22 below is based on particulate elemental S used to infer the (NH4)2SO4 levels. A discussion of IMPROVE
23 S-to-pSO4 history and trends is available (Eldred, 2001). As with data from IMPROVE used above for
24 pNOs, and except where noted, information in this section was derived form the IMPROVE IV Report
25 (DeBell, 2006) with data displays created with data and tools available at
26 http://vista.cira.colostate.edu/views/. Much of these data and conclusions are also to appear in Pitchford et
27 al., 2008.
28 One component of the Big Bend Regional Aerosol and Visibility Observational (BRAVO) Study,
29 conducted at Big Bend National Park, TX in the summer and fall of 1999, entailed use of detailed
30 measurements of aerosol chemical composition, size distribution, water growth, and optical properties to
31 characterize the aerosol and assess the relationship between aerosol physical, chemical, and optical
32 properties. (Schichtel, et al., 2004). Fine-mode ammoniated pSO4 during the BRAVO Study was -50% of
33 the fine particle mass concentration.
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1
2
3
4
In contrasts to results seen for pNO3, additional monitoring sites in the U.S. midwestern states
produced no surprises for (NH4)2SO4 or areal extent. Figure 103 shows highest (NH4)2SO4 concentrations
in the mid-Atlantic and upper southern U.S. states where annual concentrations ranged from ~3 ug/m3 to
~6 ug/m3. The (NH4)2SO4 concentrations in most western U.S. states was <~1 ug/m3.
Soume: CASTNET
USHWCAMD oirzim
Figure 2-95. Annual mean ambient 862 concentration, 1989 through 1991 (top), and 2003 through
2005 (bottom).
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Source: castitBl
USFFA/rAMD IO06AM
: CASTNET
LISEP.4/C-1MD07/27/OT
Figure 2-96. Annual mean ambient S042~ concentration, 1989 through 1991 (top), and 2003 through
2005 (bottom).
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ug/m3
ig/m3
Figure 2-97. IMPROVE network measured annual averaged pS04 concentration for 2000 (top) and
for 2004 (bottom). Note difference in scale.
1 Combining IMPROVE and CSN data makes possible comparison of urban pSO4 to surrounding
2 remote-area regional values. These are shown as paired color contours maps for IMPROVE and
3 IMPROVE plus CSN in Figure 104. EPA (2004b) used the pairing of IMPROVE and CSN monitoring
4 sites at 13 selected areas to separate local and regional contributions to the major contributors of PM2 5, as
5 shown for pSO4 in Figure 105.
6 As shown in Figures 104 and 105, annual-averaged urban pSO4 were in general not significantly
7 greater than the regional values, with urban excess pSO4 generally <~0.5 (ig/m3. Exceptions to the general
8 case appear in Texas and Louisiana where urban excess pSO4 were >lug/m3. Urban contributions were a
9 larger fraction of the total pSO4 in western U.S. states because the regional levels were much lower there
10 than in eastern ones The modest additional pSO4 associated with urban areas suggests that most pSO4 is a
11 regionally distributed pollutant, and that IMPROVE and CSN monitoring sites can be used together to
12 enhance our ability to delineate pSO4 spatial distributions. Note, for example, that the additional data
13 from urban sites shown in Figure 105 extends to the north and south of the high pSO4 loading shown in
14 Figure 104 over Tennessee and Kentucky, as well as the high loadings over southern PA, eastern WV, and
15 northern VA. The small area decrease in pSO4 evident on these maps between the two eastern high
16 concentrations regions may not be real, but cannot be verified without speciation monitoring sites in
17 southern OH, KY, WV, and VA. U.S. EPA (2004b) estimates of the contribution of local sources to pSO4
18 were made for the same cities included for pNO3 shown above; see Figure 106. The east-west divide in
19 both concentration and the regional contribution to pSO4 is strongly apparent here.
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Hawaii
IMPROVE Site
IMPROVE Urban Site
Puerto Rico /
Virgin Islands
Figure 2-98. IMPROVE mean ammonium S042~ concentrations for 2000 through 2004.
° Alaska
Hawaii
I
^~
if
VS A STN Site
^
*">
IMPROVE Site
IMPROVE Urban Site
•
Puerto Rico /
Virgin Islands
Figure 2-99. IMPROVE and CSN (labeled STN) monitored mean ammonium S042~ concentrations for
2000 through 2004.
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Sulfates
Fresno
Missoula
Salt Lake City
Tulsa
St. Louis
Birmingham
Indianapolis
Atlanta
Cleveland
Charlotte
Richmond
Baltimore
New York City
^
~n
i i
WEST
EAST
ii
ii
II D Regional
II Contribution
D Local
II
2 4 6 8 10 12
Annual Average Concentration
o1 Su Hates, ug/m3
Source: From EPA, 2004b.
Figure 2-100. Regional and local contributions to annual average PIVk.s by pS04 for select urban
areas based on paired IMPROVE and CSN monitoring sites.
1 Source attribution of the pSO4 contribution to haze at Big Bend NP, TX was a primary motivation
2 for the BRAVO Study. Schichtel, et al. (2005) showed that during the four-month field monitoring study
3 (July through October, 1999) SO2 emissions sources in the U.S. and Mexico were responsible for -55%
4 and -38% of the pSO4 respectively. Among U.S. source regions, TX was responsible for -16%, Eastern
5 U.S. - 30%, and the Western U.S. -9%. A large coal fired power plant, the Carbon facility in Mexico just
6 south of Eagle Pass, TX was responsible for about -19%, making it the largest single contributor.
7 Modeling for a three day pollution episode in September 1996 in the California South Coast Air
8 Basin (SCAB) and for another episode in January 1996 in the Jan Joaquin Valley (SJV) by Ying and
9 Kleeman (2006) has shown -80% of pSO4 for both regions are derived from upwind sources, with most
10 of the remaining local contributions associated with diesel and high-sulfur fuel combustion. Kleeman, et
11 al. (1999) using a combination of measurements and modeling showed that the upwind pSO4 source
12 region for the SCAB was over the Pacific Ocean, and this was confirmed by measurements on Santa
13 Catalina Island. Moreover, these particles subsequently grew with accumulation of additional secondary
14 aerosol material, principally NH3NO3 as they traversed the SCAB. The majority of the HNO3 that forms
15 pNO3 in the SCAB is from diesel and gasoline combustion (-63%), while much of the NH3 is from
16 agricultural sources (-40%) and catalyst equipped gasoline combustion (-16%) and upwind sources
17 (-18%). In the SJV most of the HNO3 that forms pNO3 is from upwind sources (-57%) with diesel and
18 gasoline combustion contributing most of the rest (30%), while much of the NH3 is from upwind sources
19 (-39%) and a combination of area, soil and fertilizer sources (-52%).
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1 Using a regression analysis to find the dependence of pSO4 concentration measured over a three
2 year period (2000-2002) at 84 western IMPROVE monitoring sites on the modeled transport trajectories
3 to the sites for each sample period, Xu et al. (2006) were able to infer the source regions that supplied
4 pSC>4 in the Western U.S. Among the source regions included in this analysis is the near-coastal Pacific
5 Ocean (i.e. a 300 km zone off the coast of California, Oregon, and Washington states). Up to 50% of the
6 pSO4 measured at Southern California monitoring sites is associated with this source region. As shown in
7 Figure 107 the zone of impact from this source region includes large regions of California, Arizona, and
8 Nevada. The authors make the case that high S content fuel used in marine shipping and port emissions
9 may be largely responsible. As a result, the Western Regional Air Partnership (WRAP) RPO emissions
10 inventory was modified to include marine shipping and a Pacific Offshore source region was added to
11 source attribution by air quality simulation modeling.
(a)
Contrlbu*l»n or UM PacHK C«rt It 3Llfat» Cantwririltcn
0.1-0.2
U2-0*
0 + -O.S
OJ-O.t
C>.S- \.4
Figure 2-101. Contributions of the Pacific Coast area to the (NH4)2S04 (ug/m3) at 84 remote-area
monitoring sites in Western U.S. based on trajectory regression (dots denote locations of the
IMPROVE aerosol monitoring sites). From Xu, et al. (2006).
12 The SO42 attribution results of the WRAP air quality modeling (available from http://wrapair.org)
13 are largely in line with these empirical results, finding that the Pacific Offshore source region contributed
14 somewhat smaller amounts than reported by Xu et al.,(2006) with concentrations at the peak impact site
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1 in California of -45% compared to 50% by the regression analyses and even greater differences for more
2 distant monitoring sites.
002
Sulfate 1.1 ua/m3
Sulfate O.B ua/m3
102
Sulfate 1.2 ua/m3
(a)
WRAP
Pacific Offshore
CENRAP
Eastern U.S.
Canada
Mexico
Outside Domain
2002
Sulfate 0.8 ua/m3
2002
Sulfate 0.5 uci/m3
2002
Sulfate 1.4 ua/m3
Figure 2-102. pS04 source attribution by region using CAMx modeling for six western remote area
monitoring sites. Top left to right Olympic NP, WA; Yellowstone NP, WY; Badlands NP, SD; bottom
left to right San Gorgonio W, CA; Grand Canyon NP, AZ; and Salt Creek W, NM. WRAP includes ND,
SD, WY, CO, NM and all states further west. CENRAP includes all states east of WRAP and west of
the Mississippi River including MN. Eastern U.S. includes all states east of CENRAP. The Pacific
Offshore extends 300km to the west of CA, OR, and WA. Outside Domain refers to the modeling
domain, which extend hundreds of kilometer into the Pacific and Atlantic Oceans and from Hudson
Bay Canada to just north of Mexico City.
3 Several example monitoring locations distributed across the northern and southern portions of the
4 Western U.S. have been selected to illustrate the attribution results from the WRAP air quality simulation
5 modeling by source region and source type for pSO4. They include Olympic National Park (NP), WA;
6 Yellowstone NP, WY; and Badlands NP, SD across the north, and San Gorgonio Wilderness (W), CA;
7 Grand Canyon NP, AZ and Salt Creek W, NM across the south. Pie diagrams of the pSO4 attribution
8 results by source region for each of these sites are shown in Figure 108. Based on these sites, >50% of the
9 pSO4 in remote areas of the Pacific coastal states is from outside of the U.S. (Pacific Offshore and
10 Outside of the Domain). The Outside of the Domain values are derived by simulating the fate of the
11 boundary condition concentrations, which for the WRAP air quality modeling were obtained using output
12 from the GEOS-CHEM global air quality model (Fiore, 2003). The pSO4 fraction from the region labeled
13 Outside of Domain is approximately uniform throughout the western U.S. with site-to-site variation in the
14 fraction mostly caused by the variations in the total SO42 concentration. The more northerly sites have
15 effects from Canadian emissions, while the southern sites have impacts from Mexican emissions. Half of
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1 the Salt Creek, NM, pSO4 is from the domestic source emissions further to the east (CENRAP and
2 Eastern U.S.), which also contribute about 20% to Badland pSO4 concentrations. A breakout of the
3 emission sources from within the WRAP region by source type (not shown) has most of the emissions
4 from point sources, with the combination of motor vehicle, area and wildfire emissions contributing from
5 a few percent at the furthest eastern sites to about half at San Gorgonio.
2.10. Deposition of N and S Species
6 As established in Sections 2.2 and 2.3 above, total emissions of NOx and SOx have decreased
7 substantially in the last 35 years. Between 1970 and 2005, NOX emissions fell from 26.9 million tons per
8 year (Mt/yr) to 19 Mt/yr, and SO2 emissions fell from 31.2 to 15 Mt/yr. These decreases in emissions led
9 to correlative decreases in N and S concentrations, described just above in Section 2.9, and in atmospheric
10 deposition of N and S species across the landscape; see the trends summarized in Figure 109. Importantly,
11 however, these very recent decreases in deposition still leave current deposition amounts which are a
12 factor of 2 greater than in pre-industrial times for NO3 and NFLj, and a factor of 5 greater for SO42 ,
13 according to modeling experiments by Luo et al. (2007).
25
!= 2
:!! 20
^ a 15
^3 O
If
S S1Q
-------
1 measured rainfall at the site. Dry deposition is inferred from the measured ambient air concentrations of
2 the chemical multiplied by the dry deposition rate obtained from an inferential model of linked resistances
3 to derive species and location-dependent Vd. (See the CASTNET QAPP for more information on methods
4 of computing their deposition totals). Note that NH3 is not included in these total N estimates because it is
5 not currently measured in these networks.
6 Data in this section are presented to show deposition across the landscape; finer-scale data and
7 maps of sensitive and vulnerable regions and ecosystems are presented in other sections. Data presented
8 in the maps and charts represent 3-yr averages. For example, "89-91" is the average total deposition of
9 1989, 1990, and 1991 for a given site. Only sites having valid total deposition for at least two of the three
10 years are shown and in some instances, sites only met this criterion for one of the two reporting periods.
11 Because of differences like these, direct site-by-site comparisons are not possible everywhere.
2.10.1. Nitrogen
12 For the years 2004-2006, mean N deposition was greatest in the Ohio River basin, specifically in
13 the states of Indiana and Ohio, with values as high as 9.2 and 9.6 kg/ha/yr, respectively; see Figure 110.
14 Recent work by Elliott et al. (2007) using 515N to trace deposition totals and isolate them to point to
15 mobile source type shows that for 33 NADP/NTN sites, in the East and Upper Midwest, spatial
16 distributions 515N concentrations were strongly correlated with NOX emissions from point sources, and
17 that wet NO3-deposition at the 33 sites considered was strongly associated with NOX emissions from the
18 surrounding point sources. N deposition is lower in other parts of the East, including the Southeast and in
19 northern New England. In the central U.S., Kansas and Oklahoma reported the highest deposition, 7.0 and
20 6.5 kg/ha/yr, respectively. N deposition is generally much lower in the western U.S., where it is highest in
21 urban areas in southern California and Denver, 4.8 and 3.3 kg ha/yr, respectively. It should be noted,
22 however, that large portions of the U.S. west of the Mississippi River are poorly covered by the current
23 deposition monitoring networks as the location icons on these maps make clear. Hence, the actual degree
24 of heterogeneity and magnitude of real deposition in much of the West is largely unknown.
25 Because NOX emissions decreased by -25% between 1990 and 2005, recent N deposition is lower
26 compared with average deposition for the years 1989 to 1991. For 1989 to 1991, several recording
27 stations in the Ohio River basin reported average annual deposition rates in excess of 10 kg ha/yr. Data
28 are lacking, however, for much of the central and western U.S. and little can be said for changes between
29 the two reporting periods in these areas for the reasons given above. The greatest mass of N deposition
30 primarily occurred as wet NOs and NH4+, followed in importance by dry HNOs, dry NH4+, and dry
31 see Figure 111. Although most deposition for both reporting periods occurred as wet deposition, there
32 were some exceptions, including parts of California where N deposition was primarily dry.
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SOUKC: USEPA/CASTNETNADP/NTN
ii iv> y • ' *
(kg/ha)
15
fr—10
F5
DDryN
DwetN
USHPA/CAMD 08/30/07
USEPA,'CAMD 10/06/04
Figure 2-104. Total average yearly wet and dry inorganic N deposition, excepting NHs, for 2004-2006
(top) and 1989-1991 (bottom).
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71 4.6 Inorg. N
' (kg/ha)
15
A—10
Souice: USEPA/CASTNETNADP/NTN
*5.7 **«,!
Figure 2-105. Total average yearly inorganic nitrogen deposition by species, excepting NHs, for
2004-2006 (top) and 1989-1991 (bottom).
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1 Figure 2-104 and Figure 2-105 show maps of wet deposition from NADP's data and IDW
2 interpolation technique. NO3 concentration and wet deposition amounts track dry deposition in locations
3 where the two monitoring networks overlap. Thus NO3 ambient concentration and deposition are highest
4 in the upper Ohio River Valley, excepting the significant large pNO3 deposition in excess of 6 kg/ha/yr
5 where NADP has a substantial number of monitors, CASTNet does not; see the description of the middle-
6 westNO3 "bulge" in Section 2.9.5.2.
I WetNOa
(kg/ha)
Source: NADP, USEPA, CAMD 7/19/07
Figure 2-106. N0s~ concentration in
NADP wet deposition samples,
2004-2006.
Source: NADP, USEPA, CAMD 7/19/07
Figure 2-107. Average NOs"
concentration in NADP wet
deposition samples, 2004-2006.
2.10.1.1. Example of NOa and HMOs Deposition and Flux Data from Harvard Forest
Harvard Forest is a rural site in central Massachusetts, where ambient NOX, NOY, and other
pollutant concentrations and fluxes of total NOY have been measured since 1990 (Munger, 1996).
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1 An intensive study in 2000 used a TDLAS to measure NO2 and HNO3 Absolute concentrations of
2 HNO3 were measured, and the flux inferred based on the dry deposition inferential method that uses
3 momentum flux measurements to compute a Vd and derives an inferred flux (Wesely, 1977; Hicks, 1987).
4 Direct eddy covariance calculations for HNOs were not possible because the atmospheric variations were
5 attenuated by interaction with the inlet walls despite very short residence time and use of fluorinated
6 silane coatings to make the inlet walls more hydrophobic. NO response was adequate to allow both
7 concentration and eddy covariance flux determination. Simultaneously, NO and NOy eddy covariance
8 fluxes were determined with two separate O3 CL detectors, one equipped with a H2_gold catalyst at the
9 inlet to convert all oxidized N compounds to NO. Additionally, the measurements include concentration
10 gradients for NO, NO2, and O3 over several annual cycles to examine their vertical profiles in the forest
11 canopy.
12 Overall, the results show typical NO2 concentrations of 1 ppb under clean-air conditions and mean
13 concentrations up to 3 ppb at night and 1 ppb during daytime for polluted conditions. Net positive fluxes
14 (emission) of NO2 were evident in the daytime and negative fluxes (deposition) were observed at night
15 (Figure 114). NO fluxes were negative during the daytime and near zero at night.
NW
sw
Source: Horii et al. (Horn, 2004).
Figure 2-108. Diel cycles of median concentrations (upper panels) and fluxes (lower panels) for the
Northwest clean sector, left panels) and Southwest (polluted sector, right panels) wind sectors at
Harvard Forest, April-November, 2000, for [NO], [N02], and [Os/10]. NO and Os were sampled at a
height of 29 m, and N02 at 22 m. Vertical bars indicate 25th and 27th quartiles for NO and N02
measurements. N02 concentration and nighttime deposition are enhanced under southwesterly
conditions, as are Os and the morning NO maximum.
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Simple Model
100 - NO,
80-
,§ 60-
.9>
as
40-
20
NO;
0- !
NO .'
-+•
0.0 0.2 0.4 0.6 0.8 1.0-2-1 0 1 2
Concentration (nmol mol'1) Flux (nmol moM cm s"1)
Source: Horii (Horn, 2002).
Figure 2-109. Simple NOx photochemical canopy model outputs. Left panel, concentrations of NO
(dashed) and N02 (solid); right, fluxes of NO (dashed) and N02 (solid). Symbols indicate
measurement heights for NO (29m) and N02 (22m) at Harvard Forest. The model solves the
continuity equation for NO concentration at 200 levels, d/dz(-Kc[dNO/dz]) = PNO'LNO, where PNO =
[N0]/t1, LNO = [N0]/t2, and zero net deposition or emission of NOx is allowed. NOx (NO + N02) is
normalized to 1ppb. t1 = 70s in this example. Due to the measurement height difference, observed
upward N02 flux due to photochemical cycling alone should be substantially larger than observed
downward NO flux attributable to the same process.
FN02 (night) = F9+ l/0 [NO2] + a [NO2]2
E -5- -
o
Va= -0.08 ±0.03 (ens'1)
s = -0 013 - 0.001 (nnol"' mol cm s')
-10-
-15-
-20-
10 15 20
[N02] (nmol mo)-1)
25
30
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Source: Horii et al. (2004).
Figure 2-110. Hourly (dots) and median nightly (pluses) NCh flux vs. concentration, with results of
least squares fit on the hourly data (curve). The flux is expressed in units of concentration times
velocity (nmol/mol/cm/s) in order to simplify the interpretation of the coefficients in the least
squares fit. Pressure and temperature corrections have been taken into account in the conversion
from density to mixing ratio.
1 After accounting for the time of the NO-NO2 null cycle during the measurement sampling period,
2 the net NOX flux can be derived. Overall, there was a net deposition of NOX during the night and
3 essentially zero flux in the day, with large variability in the magnitude and sign of individual flux
4 observations. For the periods with NO2 > 2 ppb, deposition was always observed. These canopy-scale
5 field observations are consistent with a finite compensation point for NO2 in the canopy that offsets foliar
6 uptake or even reverses it when concentrations are especially low. At concentrations above the
7 compensation point, NOX is absorbed by the canopy. Examination of concentration profiles corroborates
8 the flux measurements (Figure 117). During daytime for low-NOx conditions, there is a local maximum
9 in the concentration profile near the top of the canopy where O3 has a local minimum, which is consistent
10 with foliar emission or light-dependent production of NOX in the upper canopy. Depletion is evident for
11 both NOx and O3 near the forest floor. Air reaching the ground has passed through the canopy where
12 uptake is efficient and the vertical exchange rates near the ground are slow. At night, the profiles generally
13 decrease with decreasing height above the ground, showing only uptake. At higher concentrations, the
14 daytime NOx concentrations are nearly constant through the canopy; no emission is evident from the
15 sunlit leaves.
16 Figure 118 compares observed fluxes of all the observed species. The measured NOx and estimated
17 PAN fluxes are small relative to the observed total NOY flux. In clean air, HNO3 accounts for nearly all
18 the NOY flux and the sum of all measured species is about equal to the NOY concentration. However, in
19 polluted conditions, unmeasured species are up to 25% of the NOY, and HNO3 fluxes cannot account for
20 all the total NOY flux observed. These unmeasured NOY species likely are hydroxyalkyl nitrates and
21 similar compounds rapidly deposited to surfaces but not routinely measured; see the descriptions of
22 measurement techniques and challenges (Section 2.3). The deposition of HNO3 and multifunctional
23 RONO2 are the largest elements of the measured N dry deposition budget. Two key areas of remaining
24 uncertainty are the production of HNO2 over vegetation and the role of very reactive biogenic VOCs.
25 FINO2 is important because its photolysis is a source of OH radicals, and its formation may represent an
26 unrecognized mechanism to regenerate photochemically active NOx from NO3 that had been considered
27 terminally removed from the atmosphere; see the discussion in Section 2.3 above on the atmospheric
28 chemistry of NOX and the role of oxidized N compounds in atmospheric N transport.
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NOX PROFILES
30-
Canopy
Top — *• 25-
20-
O)
'o>
5 -
o -
30-
Canopy
Top - ' 25 -
— . 20-
E.
1 15
10-
5 -
o -
xo
_xc
// -
x'o
xo
N02 //NO,,
xo
_x o
/'/
x -c^-°
Night Low NOx 0
o
1
0
o
/o,
O
>«
3.70 0.75 0.80 O.B5 15 20 25 30
X O
X O
x' o
X O
/
X O
X O
. /
# 8
Day Low NOx o
o
\
o
°>.
/
o
o
0'°
30-
25-
20-
15
10-
5
0
30-
25
20-
15-
10-
5 -
o -
K
K
y.
j®
»
>o-
Night High NOx 0
/
1
o
o
o
y
3.4 3.8 4.2 4.6 14 16 18 20 22 24
X O
1
.1 \.
X O
\
X O
; /
• ! /•
X O
X O
^x o
/ /
X" O"^"
Day High NOx o
o
„
1
I
O
^
0.65 0.70 075 0.8028 30 32 34 36 42 44 4.6 4.8 5.0 22 23 24 25 26 27 28
Concentration (nmol mol'1)
Concentration (nmol mol"1)
Source: Horii et al. (2004).
Figure 2-111. Averaged profiles at Harvard Forest give some evidence of some N02 input near the
canopy top from light-mediated ambient reactions, or emission from open stomates.
2.10.2. Sulfur
1 For the most recent 3-year reporting period available (2004 to 2006), mean S deposition was
2 greatest in the eastern U.S. east of the Mississippi River, with the highest deposition of 21.3 kg/ha/yr in
3 the Ohio River basin; see Figure 119. Most recording stations throughout the Ohio River basin report
4 3-year total S deposition averages >10 kg/ha/yr and many other stations in the East report deposition >5
5 kg/ha/yr. Data are sparse for the central and west U.S., but, where available, indicate lower values than in
6 most of the East, ranging from 4.1 to 5.3 kg/ha/yr. Total S deposition in the U.S. west of the 100th
7 meridian is lower, with all recording stations reporting <2 kg/ha/yr and many reporting <1.0 kg/ha/yr.
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Summer 2000
NW
sw
j;
0
o
2.
12
0.8
0.0
-5
NO
NtV+HNOPAN
i ™N (•«.) x
FNO (paiarn.) T
FNO
FHNO.tDDIM)
r (e.c.)
-25
Source: Horii et al. (2006).
Figure 2-112. Summer (June-August) 2000 median concentrations (upper panels), fractions of NOy
(middle panels), and fluxes (lower panels) of NOv and component species separated by wind
direction (Northwest on the left and Southwest on the right). Vertical lines in the flux panels show
25th and 75th quartiles of F(NOv) and F(HNOs); negative fluxes represent deposition; F(NOx) is
derived from eddy covariance F(NO) and F(N02) measurements (corrected for photochemical
cycling), F(HN02) is inferred, and F(NOv) was measured by eddy covariance. The sum of NOx, HMOs,
and PAN accounts for all of the NOy concentration and flux for Northwesterly (unpolluted
background) flows, whereas up to 50% of NOy and F (NOy) under Southwesterly flows are in the
form of reactive nitrogen species whose fluxes are not measured or estimated here.
1 These values can also be compared to S deposition totals from 1989-1991 in Figure 119. Station-
2 by-station comparisons between averaging periods are difficult because some stations do not have
3 sufficient data to report a mean for the sampling period. There are, however, clear regional decreases in S
4 deposition across the country. S deposition for 1989-1991 (the earliest 3 year reporting period available)
5 is almost uniformly greater than for the most recent three-year average (2004-2006). Deposition since
6 1989-1991 has declined throughout the Ohio River basin (from a previous high of 25.4 kg ha/yr), New
7 England, and the Mid-Atlantic, consistent with the -48% decrease in SO2 emissions nationwide between
8 1990 and 2005. Very little coverage for the western and central U.S. was available for the 1989-2001
9 reporting period, but sites with data show a similar decrease. Figure 120 shows that for both the 1989-
10 1991 and 2004-2006 reporting periods, S was primarily deposited as wet SC>42 followed by a smaller
11 proportion as dry SC>2 and a much smaller proportion as dry SC>42 .
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» « TotalS
.9 (kg/ha)
DwetS
IlDryS
5.2
Stance: OSEPA/CASTNHTNADP/NTN
USEPA/CAMD O&'JO/CT?
WetS
DDryS
Source: USEPAyCASTNET NADP*1TN
USKPA/CAMD 10/06/04
Figure 2-113. Total average yearly wet and dry sulfur deposition for 2004-2006 (top) and 1989-1991
(bottom).
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IlDrySOa
Dry S043-
I] Dry SOs
• Dry S042
Figure 2-114. Total average yearly sulfur deposition by species for 2004-2006 (top) and 1989-1991
(bottom).
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2.11. Summary
2.11.1. Emissions and Atmospheric Concentrations
1 Total anthropogenic NO and NO2 emissions in the U.S. in 2001 were -23.19 Tg. Combustion
2 chemistry at EGUs contributed -22% of this total, and transportation-related sources contributed -56%.
3 Ambient annual NOX concentrations have decreased -35% in the period 1990-2005 to current annual
4 average concentrations of-15 ppb.
5 Biogenic NOX sources are substantially smaller than anthropogenic ones and include biomass
6 burning, lightning, and soils. The NO and N2O emitted from soils as intermediate products from
7 denitrification can evolve either naturally or as stimulated by addition of N containing fertilizers to crops
8 and other soil management practices. N2O, another member of the oxides of N family of chemicals, is
9 also a minor contributor to total U.S. GHG emissions: -6.5% on a Tg CO2e basis in 2005, and its U.S.
10 emissions decreased -3% in the period 1990-2005, though there remains considerable interannual
11 variation in this value.
12 Concentrations of NO2 in the CONUS from biogenic sources in the U.S., Canada, and Mexico and
13 from all sources elsewhere in the world are defined as policy-relevant background concentrations. On an
14 annual average basis these concentrations are calculated to be <300 ppt over most of the CONUS and
15 <100 ppt in the eastern U.S. where NO emissions are greatest. The 24-h ambient NO2 levels in CMSAs
16 where most of the regulatory monitors are located and where most anthropogenic emissions originate
17 were, on average, <20 ppb with a 99% percentile value <50 ppb for the years 2003-2005. Annual-average
18 NO2 concentrations over the CONUS are calculated to be <5 ppb for nearly all urban and rural and remote
19 sites.
20 NO and N2O can be emitted from soils as intermediate products from denitrification, either
21 naturally; or as stimulated by addition of N containing fertilizers to crops and other soil management
22 practices. N2O is a minor contributor to total U.S. GHG emissions: -6.5% on a Tg CO2e basis in 2005,
23 and its U.S. emissions decreased -3% in the period 1990-2005, though there remains considerable
24 interannual variation in this value.
25 On a national scale, energy production at EGUs accounted for -66% of total SO2 emissions in the
26 U.S. in 2001-2002; -5% of total SO2 is emitted by transportation-related sources, with on-road vehicles
27 accounting for -40% of the transportation fraction, and off-road diesel and marine traffic together
28 accounting for the remainder. As with NOX, emissions of SOX have been significantly reduced in recent
29 years: ambient annual SOX concentrations have decreased -50% in the period 1990-2005 and now stand
30 at - 4 ppb for both aggregate annual and 24-h average concentrations nationwide.
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1 Annual-average policy-relevant background SO2 concentrations in the U.S. are <10 ppt over most
2 of the CONUS, or <1% of observed SO2 concentrations everywhere except areas in the Pacific Northwest
3 where geogenic SO2 sources are particularly strong.
4 NH3 emissions are chiefly from livestock and from soils as stimulated by addition of N-containing
5 fertilizers to crops and other soil management practices. Confined animal feeding operations and other
6 intensified agricultural production methods over a period of many decades have resulted in greatly
7 increased volumes of animal wastes high in N; 30 to 70% of these wastes may be emitted as NH3. These
8 increases in NH3 emissions, and the consequent increases in ambient NH3 concentrations and NH4+
9 concentration and deposition, are highly correlated geospatially with the local and regional increases in
10 agricultural intensity. However, estimates of total NH3 emissions on national and sub-national scales
11 range widely owing to three complex issues: (1) the high spatial and temporal variability in NH3
12 emissions; 2) the high uncertainty in the magnitude of those emissions; and (3) the lack of real-time,
13 reliable, ambient NH3 monitoring techniques. Nonetheless, U.S. national NH3 emissions totals have been
14 calculated, taking into account these three drivers of uncertainty; for 2001-2002 the national NH3
15 emissions total from the NEI and as corrected by means described in Section 2.5 and Section 0 was -4.08
16 Tg/yr.
2.11.2. Field Sampling and Analysis
17 The coverage of the networks is very thin over large expanses of the interior U.S. and especially so
18 west of the 100th meridian. This assessment concludes that this thorough-going lack of monitored sites
19 increases the likelihood that significant exposure from deposition is now occurring at current atmospheric
20 concentrations where no measurements are available, as predicted in numerical experiments with large-
21 scale, first-principles models of atmospheric chemistry and physics and deposition, and as measured at
22 some few special experimental sites.
23 The instrumentation deployed at present in the routine monitoring networks for determination of
24 gas-phase NOX and SO2 concentrations is likely adequate for determining compliance with the current
25 NAAQS standards. But in application for determining environmental effects, all these methods have
26 important limitations which make them inadequate for fully characterizing the state of the atmosphere at
27 present, for correctly representing the complex heterogeneity of N and S deposition across the landscape,
28 and for realistically apportioning the contributions of reduced and oxidized forms of atmospheric N and S
29 in driving observed biological effects at a national scale.
30 For example, routine NO2 measurements by CL are contaminated by unknown and varying
31 concentrations of higher-order oxidized N species, including gas-phase HNO3, important as in itself for N
32 deposition to the biosphere and also as a precursor to pNO3. Moreover, dry deposition of NO, NO2, and
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1 PANs is not estimated in the dry deposition networks, but could account for as much as 30% of total dry
2 oxidized N deposition in areas near strong NOX sources. This would include estuaries and other wetlands
3 near large urban areas.
4 As concerns SC>2, the present-day ambient annual avg SC>2 concentrations are very near or even
5 below the operating limit of detection of most of the FRM monitors in the largest regulatory network.
6 This produces irresolvable uncertainty in these data which may be important for environmental effects
7 from S compounds since they result in some cases from exposure at these current low concentrations
8 Routine field sampling techniques for NH3 are at present limited to integrated values from several
9 days to one week because higher frequency semi-continuous methods are not yet sufficiently robust to
10 deploy for routine operation in national networks. Estimates for the contribution of NH3 to the total N
11 deposition budget range as high as 30% of total N, and perhaps the dominant source of reduced N.
12 Moreover, routine national-scale sampling and analysis for particulate-phase NO3~, SO42 , and NH4+ are
13 subject to positive and negative errors, chiefly from the loss or production of constituent species on the
14 surface of the filter used for the long time-integrated measurement.
15 This assessment concludes that the aggregate effect of these uncertainties and errors very likely is
16 to underestimate total N and S atmospheric deposition and subsequent biological exposures.
2.11.3. Deposition of N and Sulfur
17 Increasing trends in urbanization, agricultural intensity, and industrial expansion during the
18 previous 100 years have produced a nearly 10-fold increase in N deposited from the atmosphere. NOX,
19 chiefly from fossil fuel combustion, often dominates total N pollution in the U.S. and comprises -50 to
20 75% of the total N atmospheric deposition.
21 For the period 2004-2006, the routine monitoring networks report the mean N deposition in the
22 U.S. was greatest in the Ohio River Valley, specifically in Indiana and Ohio, with values as high as 9.2
23 and 9.6 kg/ha/yr, respectively. N deposition was lower in other parts of the East, including the Southeast
24 and northern New England. In the central U.S., Kansas and Oklahoma reported the highest deposition: 7.0
25 and 6.5 kg/ha/yr, respectively.
26 Estimated N deposition from measurements primarily occurred in the form of wet NO3 and NH4,
27 followed with decreasing amounts of dry HNO3, dry NH/t, and dry NO3. Although deposition in most
28 areas of the U.S. occurred in wet form, there were some exceptions, including parts of California where N
29 deposition was primarily dry. Data are very sparse for the central U.S. between the 100th meridian and the
30 Mississippi River; but, where available, N deposition values there were lower than in most of the eastern
31 U.S., ranging from 4.1 to 5.3 kg N/ha/yr.
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1
2
3
4
5
6
7
Table 2-25. Regional changes in
1989-1991 and 2003-2005.
Measurement
Wet S042~ deposition
Wet SCU2~ concentration
Ambient sulfur dioxide concentration
Ambient SCU2~ concentration
Wet inorganic N deposition
Wet NO3 concentration
Ambient 3 concentration
Total ambient 3 concentration (3 + Nitric acid)
* Percent change is estimated from raw measurement data,
wet and dry N and S atmospheric concentrations and deposition,
Unit Region
kg/ha Mid-Atlantic
Midwest
Northeast
Southeast
mg/L Mid-Atlantic
Midwest
Northeast
Southeast
ug/m3 Mid-Atlantic
Midwest
Northeast
Southeast
ug/m3 Mid-Atlantic
Midwest
Northeast
Southeast
kg/ha Mid-Atlantic
Midwest
Northeast
Southeast
mg/L Mid-Atlantic
Midwest
Northeast
Southeast
ug/m3 Mid-Atlantic
Midwest
Northeast
Southeast
ug/m3 Mid-Atlantic
Midwest
Northeast
Southeast
Average
1989-1991
27
23
23
18
2.4
2.3
1.9
1.3
13
10
6.8
5.2
6.4
5.6
3.9
5.4
5.9
6.0
5.3
4.3
1.5
1.4
1.3
0.8
0.9
2.1
0.4
0.6
3.5
4.0
2.0
2.2
Average
2003-2005
20
16
14
15
1.6
1.6
1.1
1.1
8.4
5.8
3.1
3.4
4.5
3.8
2.5
4.1
5.5
5.5
4.1
4.4
1.0
1.2
0.9
0.7
1.0
1.8
0.5
0.7
3.0
3.5
1.7
2.1
Percent
Change*
-24
-32
-36
-19
-33
-30
-40
-21
-34
-44
-54
-35
-30
-33
-36
-24
-8
-8
-23
+2
-29
-14
-33
-9
+5
-14
+20
+17
-14
-12
-13
-5
not rounded; some of the measurement data used to calculate percentages may be at or below detection limits.
Source: CASTNET and the National Atmospheric Deposition Program / National Trends Network (NADP/NTN)
For the period 2004-2006, mean S deposition in the U.S. was greatest east of the Mississippi River
with the highest deposition amount, 21.3 kg S/ha/yr, in the Ohio River Valley where most recording
stations reported three-year averages >10 kg S/ha/yr. Numerous other stations in the East reported S
deposition >5 kg S/ha/yr. Total S deposition in the U.S. west of the 100th meridian is relatively low, with
all recording stations reporting less than 2 kg S/ha/yr and many reporting less than 1.0 kg S/ha/yr.
S was primarily deposited in the form of wet SO42 followed in decreasing order by a smaller
proportion of dry SO2 and a much smaller proportion of deposition as dry SO42 . However, these S data in
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1 the western U.S., like those for N deposition, are derived from measurements in networks with many
2 fewer nodes in the West than in the East.
3 Table 2-25 lists separate concentration and deposition totals for wet and dry N and S species in 4
4 sub-regions of the U.S. as annual averages for the years 1989-1991 and 2003-2005 as a summary of the
5 foregoing data.
6 Estimates of total N loadings to estuaries, or to other large-scale elements in the landscape, are
7 computed using the measurements of wet and dry N deposition (as reported above) where these are
8 available, and then can be interpolated with or without a set of air quality model predictions to determine
9 the relative contribution from the atmosphere of various species of reduced and oxidized N. Measurement
10 and modeling experiments like these have shown that atmospheric inputs of reactive N directly to the
11 surface of some coastal waters are essentially equal to or greater than those contained in riverine flow in
12 the absence of deposition and may contribute from 20 to >50% of external N loadings to these systems.
13 For example, atmospheric N inputs to the northeast Atlantic coast of the U.S., the southeast Atlantic coast
14 of the U.S., and the eastern Gulf of Mexico have been estimated to be 11, 5.6, and 5.6 kg N/ha'yr,
15 respectively. More specifically and at finer spatial scales, atmospheric N loads to great waters and
16 estuaries in the U.S. have been estimated to range from 2 to 8% for Guadalupe Bay, TX on the lowest end
17 to -72% for the Catherines-Sapelo estuary at the highest end. At Chesapeake Bay, atmospheric N is
18 estimated to contribute up to 30% of total N and 14% of the NFLj loadings to the Bay.
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Chapter 3. Ecological and
Other Welfare Effects
1 This chapter is organized into four sections. The introduction (Section 3.1) frames the organizing
2 principle of this chapter and several basic concepts of ecology. A discussion of acidification is presented
3 in Section 3.2. N enrichment is discussed in Section 3.3. Lastly, other welfare effects are presented in
4 Section 3.4, including interactions between sulfur (S) deposition and mercury (Hg) methylation and direct
5 gas-phase injury to vegetation.
3.1. Introduction to Ecological Concepts
3.1.1. Critical Loads as an Organizing Principle for Ecological Effects
of Atmospheric Deposition
6 This chapter uses the critical loads concept as an organizing principle. The components that are
7 necessary to develop a critical load provide a conceptual framework for linking atmospheric pollutants to
8 ecological endpoints that indicate impairment. The generally accepted definition of a critical load of
9 atmospheric pollutant deposition emerged from a pair of international workshops held in the late 1980s
10 (Nilsson, 1986; Nilsson, 1988). The workshop participants defined a critical load as:
11 "A quantitative estimate of an exposure to one or more pollutants below
12 which significant harmful effects on specified sensitive elements of the
13 environment do not occur according to present knowledge."
14 The development of a quantitative critical load estimate requires a number of steps. An illustrative
15 example of the eight general steps is shown in Table 3-1. A more detailed description of these steps is
16 given in Annex D.
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Table 3-1. An example of the matrix of information that must be considered in the definition and
calculation of critical loads (see discussion in text). Note that multiple alternative biological
indicators, critical biological responses, chemical indicators, and critical chemical limits could be
used.
1) Disturbance
2) Receptor
3) Biological
indicator
4) Critical
biological
response
5) Chemical
indicator
6) Critical
chemical
limit
7) Atmospheric
pollutant
8) Critical
pollutant load
Acidification
Forest
Sugar
Maple
Failure to
reproduce
Soil % Base
Saturation
10%
S04, N03,
NH4
???
Norway
Spruce
Seedling
death
Soil Ca/Al
ratio
1,0
S04, NO3,
NH4
???
Lake
Brook trout
Presence
absence
Lakewater
ANC
0 ueq/L
S04, N03,
NH4
???
Fish species
richness
Species
loss
Lakewater
ANC
50 |jeq/L
SO4, N03,
NH4
???
Eutrophication
Grassland
Species
diversity
Species
loss
Soil C/N
ratio
20
NO3, NH4
???
Lake
Primary
productivity
Excess
productivity
Lakewater
NO3
10|jeq/L
NO3, NH4
???
1 This chapter presents information with a focus on the following questions:
2 • What is the disturbance?
3 • What receptors are affected?
4 • What indicator organisms are (or previously were) present and observable?
5 • What chemical indicators are changing and can be measured?
6 • What atmospheric pollutant is driving the changes in the chemical indicators?
7 It is important to recognize that there is no single "definitive" critical load for a natural resource.
8 Critical loads estimates reflect the current state-of-knowledge and policy priorities. Changes in scientific
9 understanding may include, for example, new dose-response relationships; better resource maps and
10 inventories; larger survey datasets; continuing time-series monitoring; improved numerical models.
11 Changes in the policy elements may include: new mandates for resource protection; focus on new
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1 pollutants; and inclusion of perceived new threats that may exacerbate the pollutant effects (e.g., climate
2 change).
3 This procedure can result in calculation of multiple critical loads for a given pollutant at a single
4 location. The multiple solutions derive from the nested sequence of disturbances, receptors, and biological
5 indicators that must be considered for a given pollutant. Multiple critical load values may also arise from
6 an inability to agree on a single definition of "significant harm." Calculation of critical loads for multiple
7 definitions of "harm" may be deemed useful in subsequent discussions of the analysis and in the decision-
8 making steps that may follow critical load calculation.
9 Finally, there is the inescapable heterogeneity of all natural environments. Consider soils, for
10 instance. The high spatial variability of soils almost guarantees that for any reasonably sized soil-based
11 "receptor" that might be defined in a critical load analysis, there will be a continuum of critical load
12 values for any indicator chosen. The range of this continuum of values may be narrow enough to be
13 ignored; nevertheless, there is an a priori expectation in any critical load analysis that multiple values (or
14 a range of values) will result from the analysis. Given the heterogeneity of ecosystems affected by N and
15 S deposition, examples of published critical load values for a variety of endpoints and locations in the
16 U.S. are presented here (see Section 3.3.7).
3.1.2. Ecosystem Scale, Function, and Structure
17 Information presented in this ISA was collected at multiple scales, ranging from the physiology of
18 a given species to population, community, and ecosystem-level investigations. For the purpose of this
19 assessment, "ecosystem" is defined as a functional entity consisting of interacting groups of living
20 organisms and their abiotic (chemical and physical) environment. Ecosystems cover a hierarchy of spatial
21 scales and can comprise the entire globe, biomes at the continental scale, or small, well-circumscribed
22 systems such as a small pond.
23 Ecosystems have both structure and function. Structure may refer to a variety of measurements
24 including the species richness, abundance, community composition and biodiversity as well as landscape
25 attributes. Competition among and within species and their tolerance to environmental stresses are key
26 elements of survivorship. When environmental conditions shift, for example, by the presence of
27 anthropogenic air pollution, these competitive relationships may change and tolerance to stress may be
28 exceeded. Function refers to the suite of processes and interactions among the ecosystem components and
29 their environment that involve nutrient and energy flow as well as other attributes including water
30 dynamics and the flux of trace gases. Plant processes including photosynthesis, nutrient uptake,
31 respiration, and carbon (C) allocation, are directly related to functions of energy flow and nutrient
32 cycling. The energy accumulated and stored by vegetation (via photosynthetic C capture) is available to
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1 other organisms. Energy moves from one organism to another through food webs, until it is ultimately
2 released as heat. Nutrients and water can be recycled. Air pollution alters the function of ecosystems when
3 elemental cycles or the energy flow is altered. This alteration can also be manifested in changes in the
4 biotic composition of ecosystems.
3.1.3. Ecosystem Services
5 Ecosystem structure and function may be translated into ecosystem services. Ecosystem services
6 identify the varied and numerous ways that ecosystems are important to human welfare. Ecosystems
7 provide many goods and services that are of vital importance for the functioning of the biosphere and
8 provide the basis for the delivery of tangible benefits to human society. Hassan et al. (2005) define these
9 to include supporting, provisioning, regulating, and cultural services:
10 • Supporting services are necessary for the production of all other ecosystem services. Some
11 examples include biomass production, production of atmospheric O2, soil formation and
12 retention, nutrient cycling, water cycling, and provisioning of habitat. Biodiversity is a
13 supporting service that is increasingly recognized to sustain many of the goods and services
14 that humans enjoy from ecosystems. These provide a basis for three higher-level categories of
15 services.
16 • Provisioning services, such as products (cf. Gitay, 2001), i.e., food (including game, roots,
17 seeds, nuts and other fruit, spices, fodder), fiber (including wood, textiles), and medicinal and
18 cosmetic products (including aromatic plants, pigments).
19 • Regulating services that are of paramount importance for human society such as (a) C
20 sequestration, (b) climate and water regulation, (c) protection from natural hazards such as
21 floods, avalanches, or rock-fall, (d) water and air purification, and (e) disease and pest
22 regulation.
23 • Cultural services that satisfy human spiritual and aesthetic appreciation of ecosystems and their
24 components.
25 Wetlands also offer key ecosystem services such as sequestering carbon, providing habitats,
26 regulating flood, maintaining water quality, and stabilizing coastal slope (EPA, 1993).
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3.2. Ecological Effects of Acidification
3.2.1. Effects on Major Biogeochemical Processes
1 Acidifying deposition has altered major biogeochemical processes in the U.S. by increasing the S
2 (Figure 3-1) and N content of soils, accelerating SO42 and NO3 leaching from soil to drainage water,
3 depleting base cations (especially Ca and Mg) from soils, and increasing the mobility of Al. The extent of
4 soil acidification is a critical factor that regulates virtually all acidification-related ecosystem effects from
5 S and N deposition. Soil acidification occurs in response to both natural factors and acidifying deposition.
6 To best integrate the effects of acidifying deposition, this assessment starts with a description of the
7 effects on soils and major biogeochemical processes within ecosystems, then summarizes the chemical
8 and biological effects on terrestrial, transitional, and aquatic ecosystems. More detailed information on
9 acidification effects is provided in Annex B.
Little or no S Deposition
Major Fluxes
High S Deposition to Base-Poor Ecosystem
Low S Adsorption on Soil Hi9h S Adsorption on Soil
Simplified Description
Base cation supply to soil from
deposition and weathering is
stable.
Base cation losses to soil water
and surface water are replaced
by the external supply from
weathering and BC deposition.
Base cation uptake into
vegetation is recycled.
Inorganic rnonomeric Al is not
mobilized to drainage water.
Simplified Description
Increased S deposition is often
accompanied by increased base
cation deposition.
Sulfate leaches through soil to
drainage water if it is not
adsorbed to soil.
Sulfate flux is partially
neutralized by flux of BC and Al,
from soil to drainage water.
Over time, soils can become
depleted of BCf and drainage
water enriched in Al, and hT, both
of which can be toxic to plant
roots and aquatic biota.
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Figure 3-1. Illustration of major fluxes of ions associated with S-driven acidification of drainage
water. The upper diagram represents ion fluxes in the absence of S deposition. The two lower
diagrams illustrate changes to these fluxes in response to S deposition on two types of soils, with
(right) and without (left) substantial S adsorption on soil. Effects are most pronounced under high
deposition with little adsorption, and include increased leaching of base cations (contributes to soil
acidification), H (reduced pH), and Ah (toxic to many plant roots and aquatic species). Larger fluxes
are represented by thicker arrows.
3.2.1.1. Soil Acidification
1 Soil acidification is the loss of base cations plus the accumulation of acidic cations such as
2 hydrogen (FT) and aluminum (AF+) in the soil; this happens when a proton donor is added to the soil. Soil
3 acidification is a natural process. Such natural acidity is contributed by carbonic acid, organic acids, and
4 plant cation uptake (Turner, 1990; Charles, 1991). However, the donor can also be a mineral acid, such as
5 HNO3 and H2SO4, the common components of acid rain that result from NOX and SOX air pollution.
6 Decreases in soil pH attributable to acidifying deposition have been documented in the U.S. (Johnson,
7 1994; Johnson, 1994; Bailey, 2005; Sullivan, 2006). Effects in the Eastern U.S. appear to have been
8 limited mainly to the Northeast and portions of the Appalachian Mountains in both hardwood and
9 coniferous forests. Soil acidification has also likely occurred in localized areas of mixed conifer forest and
10 chaparral vegetation in, and near, the Los Angeles Basin, in response to locally high levels of atmospheric
11 dry N deposition (Fenn, 2003; Fenn, 2003).
12 To evaluate soil acidification, the soil must be considered in terms of the surface organic layer (the
13 primary rooting zone), of which the Oa horizon (or in some studies the O horizon, which combines the Oe
14 and Oa horizons) is an important component (See Figure 3-2). In addition, the mineral soil including the
15 A and/or B horizon, which lie below the Oa horizon and are primarily comprised of mineral matter, must
16 be considered.
17 Acidifying deposition can have a direct effect on soil pH. However, net uptake of nutrient cations
18 by vegetation can also generate acidity within the soil, and a considerable amount of natural organic
19 acidity is produced in the Oa horizon through the partial decomposition of organic matter. This process
20 can decrease the pH of soil water in the Oa horizon well below the lowest pH values measured in
21 acidifying deposition (Krug, 1985; Lawrence, 1995). Oa-horizon soils under coniferous vegetation are
22 strongly acidified by organic acids and are unlikely to have experienced a lowering of pH as a result of
23 acidifying deposition (Johnson, 1992; Lawrence, 1995). Soils influenced by the growth of hardwood
24 species tend to have surface horizons that are less acidic naturally and are, therefore, more susceptible to
25 decreased pH in the Oa horizon from acidifying deposition. By taking up larger amounts of Ca from the
26 soil, hardwoods can acidify lower soil horizons more than conifers even though they enrich surface
27 horizons with Ca via litterfall (Alban, 1982).
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Source: http://soils.usda.gov/education/resources/
Figure 3-2. Diagram illustrates
"ideal" soil horizons to which many
soils conform. Each main horizon is
denoted by a capital letter: 0)
Organic matter: Litter layer of plant
residues in relatively undecom-
posed form. A) Surface soil: Layer
of mineral soil with most organic
matter accumulation and soil life.
This layer is depleted of iron, clay,
aluminum, organic compounds, and
other soluble constituents. B)
Subsoil: This layer accumulates
iron, clay, aluminum and organic
compounds. C) Substratum: Layer
of unconsolidated soil parent
material. This layer may accumulate
the more soluble compounds that
bypass the "B" horizon.
1 Several studies document declines in soil pH within the Oa/A horizons and the upper B horizon in
2 sensitive regions of the U.S. over the past several decades (Johnson, 1994; Johnson, 1994; Drohan, 1997;
3 Bailey, 2005). These declines have been attributed at least partly to acidifying deposition (Bailey, 2005).
4 In summary, soil acidification is a natural process, which is often exacerbated by acidifying
5 deposition. Natural acidification is particularly pronounced in coniferous forests. Acidifying deposition
6 can contribute to soil acidification, with consequent effects on the availability of nutrient cations in soil
7 and the chemistry of drainage water that flows from soil into streams and lakes. More detailed
8 descriptions of soil acidification are provided by van Breemen et al. (1983) and Binkley and Richter
9 (1987).
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3.2.1.2. Sulfur Accumulation and S042~ Leaching
1 Most acidification-related consequences of atmospheric S and N deposition in the U.S. are caused
2 by SO42 (Sullivan, 2000; Driscoll, 2001). The mobility within the watershed of SO42 , derived from
3 atmospheric S deposition, is a key factor governing many aspects of soil and water acidification at
4 locations in the U.S. that are affected by acidifying deposition.
5 Upon deposition to the Earth's surface, S may be assimilated by vegetation or microbes,
6 accumulate in the soil or act as a mobile ion and leach out of the soil. When a given area is affected by
7 acidifying deposition, S deposition levels are typically much higher than plant demand for S and
8 consequently almost all deposited S is transported to the soil where it may accumulate and is available for
9 leaching as SO42 . SO42 acts as a mobile anion at many locations in the U.S. that receive high levels of S
10 deposition, notably the glaciated Northeast and Upper Midwest, where much of the deposited S leaches
11 through soils into streams and lakes. SO42 leaching leads to most of the ecological effects from
12 atmospheric S deposition because it is accompanied by leaching of cations, and this contributes to
13 acidification of soil, soil water, and surface water.
14 Over time, sustained SO42 leaching and associated soil acidification contribute to pronounced
15 changes in soils in some areas. When S is transported from soils to surface waters in the form of SO42 , an
16 equivalent amount of cations, or countercharge, is also transported. When the countercharge is provided
17 by base cations, the base saturation of the soil is reduced as the acidity of the soil water is neutralized.
18 However, this process acidifies the soil, thereby decreasing the soil's capacity to neutralize additional
19 acidity deposited from the atmosphere and prevent acidification of soil water, and by connection, surface
20 water. As the base cations become depleted, the countercharge provided by acidic cations (H and
21 inorganic Al) increases, sometimes resulting in toxic conditions for plant roots and aquatic organisms
22 (Turner, 1990; Charles, 1991).
23 In the U.S., there are some regional trends of soil accumulation, retention, and leaching of S that
24 are discussed below.
Southeast
25 Accumulation of atmospherically deposited S in soil has resulted from anion adsorption and
26 incorporation of S into organic matter through biological assimilation. Such retention of S can
27 temporarily reduce SO42 leaching and cause a delay in ecosystem recovery in response to decreases in S
28 deposition, as some accumulated S is slowly released from the soil into drainage water. S adsorption on
29 soil is especially pronounced in the Southeastern U.S. Under continued loading of S deposition, it is
30 expected that many southeastern watersheds will exhibit a gradual decrease in the extent of S adsorption
31 in the future. This will likely contribute to further acidification of some streams, even under substantially
32 reduced levels of S deposition (Turner, 1990; Elwood, 1991; Sullivan, 2004).
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Northeast
1 In the Northeast, the accumulation of a portion of the historic legacy of atmospheric S deposition in
2 soil was demonstrated by a positive relationship between wet deposition of SO42 and concentrations of
3 total S in the forest floor of 12 red spruce stands (Driscoll, 2001). However, net loss of S from soils now
4 appears to be occurring in a number of Northeastern watersheds in response to decreased levels of
5 atmospheric S deposition. The potential for net mineralization of stored S might affect recovery of
6 drainage waters (Novak, 2007; Likens, 2002; Gbondo-Tugbawa, 2002). Where leaching of previously
7 stored S occurs, it delays soil and surface water chemical recovery from acidification (Driscoll, 2001).
8 Weathering contributes substantial S in some watersheds (Shanley, 2005). Uncertainties in
9 estimates of ecosystem S fluxes, such as weathering and dry deposition, and the difficulty in discerning
10 the effects of net SO42 desorption and net S mineralization make it difficult to predict when S outputs in
11 the northeastern U.S. will no longer exceed inputs. Recent research results, based on experimental
12 reduction of S inputs, suggest that this process will occur on a decadal timescale (Martinson, 2005;
13 Morth, 2005). The long-term role of C-bonded S adds further uncertainty because enhancement of S
14 mineralization by a warming climate could also affect S retention and release from soil (Knights, 2000;
15 Driscoll, 2001).
16 In summary, atmospheric S deposition alters soil chemistry through the following mechanisms:
17 (1) sustained SO42 leaching and associated changes in soil chemistry, and (2) accumulation of S in the
18 soil through physical/chemical adsorption and biological assimilation. The recent evidence of net loss of
19 S from soils at a number of sites in the Northeast is a likely response to recent decreases in atmospheric S
20 inputs (Driscoll, 2001). The gradual loss of previously accumulated S is further contributing to continued
21 SO42 leaching and soil acidification.
3.2.1.3. N Accumulation and NOs" Leaching
22 The scope of this section is the role of N deposition in the process of acidification. This assessment
23 divides the effects of N deposition into the two broad categories of acidification and N nutrient
24 enrichment effects. The latter is discussed in Section 3.3. N deposition may cause acidification of
25 ecosystems via three main mechanisms: (1) excess accumulation in soils followed by increased rates of
26 nitrification by microbes, (2) change in base cation status of soils caused by NO3 leaching, and (3)
27 increased growth of vegetation causing increased cation uptake.
Nitrification and Accumulation
28 Atmospherically deposited N accumulates in soil through incorporation of N into organic matter.
29 Accumulation is either documented or suggested to occur across large areas of the U.S. (Aber, 2003).
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1 Direct evidence for such accumulation has been found in the Northeastern U.S. and in Colorado.
2 Increased accumulation of N in soil is suggested, for example, by a positive correlation between
3 atmospheric deposition levels and total N concentration in the Oa soil horizon at red spruce sites in New
4 York, Vermont, New Hampshire, and Maine (Driscoll, 2001). Mass balance studies also show soil N
5 retention (e.g.,, Campbell, 2005). Further evidence that atmospheric deposition has increased the
6 availability of N in soil is provided by the strong negative correlation between atmospheric N deposition
7 and the C:N ratio of the Oa soil horizon across the northeastern U.S. (Aber, 2003).
8 The nitrification process is mediated by autotrophic bacteria that derive energy by reducing NH4+
9 to NO3 . Nitrification produces acidity in the form of HNO3 as a byproduct. The HNO3 produced
10 contributes to the acidification of soils and surface waters. If the C:N ratio of soils falls below about 20 to
11 25, nitrification is stimulated and net nitrification and associated production of acidity occurs in soils
12 (Aber, 2003; Emmett, 1998). This process often results in elevated NO3 concentration in soil waters and
13 surface waters (Aber, 2003; Ross, 2004). Thus, data collected from streams and lakes can yield important
14 information about processes that occur in the soil. N saturation refers to the condition when N inputs from
15 atmospheric deposition and other sources exceed the biological requirements of the ecosystem. Excess N
16 supply reduces competition between plants and heterotrophic microbes for NH4+ to the point that net
17 nitrification occurs (Aber, 2003; Aber, 1998).
Leaching
18 In many upland forested areas in the U.S., a large fraction of the N received in atmospheric
19 deposition is retained in soil or in plant biomass. Nevertheless, elevated NO3 concentration in surface
20 waters during the growing season is common and widespread in the U.S. (Charles, 1991). High
21 concentrations of NO3 in lakes and streams, indicative of ecosystem N saturation in most natural
22 systems, have been found at a variety of locations throughout the U.S. (Stoddard, 1994) EPA, 2004). In
23 general, atmospheric deposition of 8 to 10 kg N/ha/yr or more, results in NO3 leaching to surface waters
24 in the Eastern U.S. Lower N deposition levels (less than 5 kg N/ha/yr) may lead to NO3 leaching in the
25 mountainous West because of colder temperatures, shorter growing season, little soil development,
26 extensive exposed bedrock, and rapid melting of large snowpacks (Baron, 1994; Williams, 1996).
27 NO3 leaching usually contributes to the leaching of base cations from soils to surface waters.
28 Although concentrations of NO3 are typically less than SC>42 in drainage waters in most ecosystems in
29 the U.S., concentrations of NO3 in some streams are high enough to suggest a substantial role for NO3
30 in base cation loss from soil, particularly during periods of high soil-water NO3 flux during the non-
31 growing season (Van Miegroet, 1992; Cook, 1994).
32 The relationship between atmospheric N deposition and NO3 leaching from forest ecosystems is
33 often modified by land-use history, current land-use, land disturbance, tropospheric ozone levels, and
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1 climate. The N retention capacity of soils is highly dependent on land-use history and its effects on N
2 cycling and pool sizes. For example, the removal of trees reduces the amount of N in the watershed and
3 enhances the demand of vegetative regrowth for added N. This effect results in little or no NO3 leaching
4 and can last for decades to more than a century (Goodale, 2000). NO3 leaching is also affected by current
5 land use (U.S. EPA 2006). In the northeastern U.S., concentrations of N in streams of upland forested
6 watersheds tend to be considerably lower than in streams draining watersheds with other land uses (Aber,
7 1997; Aber, 2003). Perhaps the most noteworthy effect of urban land use on processes of nutrient
8 enrichment from N deposition concerns the transport of NO3 to N-limited estuarine and near-coastal
9 waters. This topic is discussed in Section 0. In agricultural, and especially in forested areas, it is generally
10 expected that most atmospherically deposited N is taken up by terrestrial vegetation. This is usually not
11 the case in urban landscapes, although it is sometimes possible. Due to the relatively large impervious
12 surface area in the urban landscape (e.g., buildings, roads, parking lots), a higher percentage of
13 precipitation is routed directly to surface waters, with less opportunity for vegetative uptake of deposited
14 N.
15 Climatic factors also play an important role in determining the extent of NO3 leaching. In
16 particular, temperature and moisture have large effects on N cycling and NO3 leaching. Murdoch et al.
17 (1998) found that, for at least one site, annual mean NO3 concentrations in stream water were not related
18 to annual wet N deposition, but rather, were positively correlated with mean annual air temperature. This
19 pattern was likely due partly to the fact that microbial processes responsible for NO3 production are very
20 sensitive to temperature. Fluctuations in microbial immobilization and mineralization in response to
21 climatic variability affect NO3 losses to drainage waters.
22 Long-term data sets also suggest that climate may affect patterns of NO3 loss. Many of the
23 original (sampled periodically since the early 1980s) long-term monitoring lakes in the Adirondack
24 Mountains showed increased NO3 leaching from terrestrial ecosystems throughout the 1980s, which was
25 followed by a decline during the 1990s (Driscoll, 2003; Driscoll, 2003). Decreasing stream NO3
26 concentrations during the 1990s were also observed in the Catskill Mountains and in New Hampshire
27 (Driscoll, 2003; Driscoll, 2003). There was not a substantial change in N emissions or deposition in the
28 Northeast region over that period. Climatic factors, increases in atmospheric CO2, and interactions with
29 increasing availability of dissolved OC have been proposed as possible contributing factors for regional
30 decreases in NO3 in drainage water during the 1990s, but the driver of this decadal scale pattern remains
31 under investigation. Snowmelt and rain-on-snow, along with soil freezing, can influence N cycling in cold
32 climates (Eimers, 2007; Campbell, 2005; Park, 2003).
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3.2.1.4. Base-Cation Leaching
1 Acidifying deposition has been shown to be an important factor causing decreases in
2 concentrations of exchangeable base cations in soil. Loss of base cations from soil is a natural process.
3 Under conditions of low atmospheric deposition of S and N the limited mobility of anions associated with
4 naturally derived acidity (organic acids and carbonic acid) controls the rate of base cation leaching. Inputs
5 of S and N in acidifying deposition enhance inputs of strong acid anions that can accelerate natural rates
6 of base-cation leaching (Cronan, 1978; Lawrence, 1999).
7 Leaching of base cations from watershed soils to surface waters is a mechanism that (1) depletes
8 essential plant nutrients from soil; and (2) limits the extent of surface water acidification in response to
9 acidifying deposition. When SO42 and NO3 leaching occur in equal magnitude to base cation leaching,
10 the drainage water is not acidified. However, in the process of neutralizing the acidity of drainage water,
11 base cation release from soil causes depletion of the base saturation of the soil. Soil base saturation
12 expresses the concentration of exchangeable bases (Ca, Mg, potassium [K], sodium [Na]) as a percent of
13 the total cation exchange capacity (which includes exchangeable hydrogen ion and inorganic Al). Once
14 base cations in the soil become depleted, Al is moved from soil into drainage water, with potentially
15 harmful consequences for sensitive terrestrial plants and aquatic organisms throughout the food web.
16 In the 1990s, data were published supporting the occurrence of base cation depletion from soils in
17 the U.S. (Lawrence, 1999; Lawrence, 1995; Lawrence, 1997), although decreases in exchangeable Ca
18 concentrations had earlier been identified in European soils through repeated sampling. Recent data reveal
19 that decreases in concentrations of exchangeable base cations and base saturation in the Oa and B soil
20 horizons have occurred over the past several decades in the eastern U.S. and most studies attribute this
21 change to the effects of acidifying deposition. For example, the most thorough soil re-sampling study in
22 the U.S. was conducted in northwestern Pennsylvania by Bailey et al. (2005). This study showed that
23 between 1967 and 1997 pronounced decreases, attributed largely to acidifying deposition, were measured
24 in exchangeable Ca and Mg concentrations in Oa/A horizons and throughout the B horizon. Similarly,
25 data compiled by Sullivan et al. (2006;, 2006) suggested decreases in base saturation of B-horizon soils
26 in the Adirondack Mountains between the mid-1980s and 2003. Depletion of base cations contributes to
27 soil acidification and influences the ability of watershed soils to support acid-sensitive vegetation and to
28 neutralize acidity in future acidifying deposition. Both plant uptake of cations, for example via forest
29 regrowth subsequent to logging or land use conversion, and acidifying deposition can acidify soils
30 (Johnson, 1990; Trettin, 1999) Richter and Markewitz 2001,.
31 Upslope decreases in exchangeable soil base cation concentrations were found to be positively
32 correlated with higher S deposition in the Catskill Mountains (Lawrence, 1999). Furthermore, declines in
33 soil exchangeable pools of base cations have been documented in New Hampshire (Likens, 1996) and
34 Norway (Kirchner, 1995). In summary, leaching of base cations associated with acidifying deposition is
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1 occurring in sensitive regions in the U.S. Base cation loss increases the sensitivity of the watershed to
2 further acidifying deposition. Watersheds that were capable of fully neutralizing a particular level of
3 acidifying deposition in the past may no longer be capable of fully neutralizing that level today or at some
4 time in the future because of the cumulative effect of acidifying deposition on soil base saturation. Where
5 the availability of exchangeable base cations is limited, the leaching of potentially toxic inorganic Al into
6 soil and surface waters can result.
3.2.1.5. Aluminum Leaching
7 If soil base saturation is 20 to 25%, or lower, acidifying deposition can mobilize inorganic Al,
8 which can lead to the leaching of this potentially toxic form of Al into soil waters and surface waters
9 (Reuss, 1985; Cronan, 1990). This is an extremely important effect of acidifying deposition because some
10 forms of inorganic monomeric Al, including A13+ and various hydroxide species, are toxic to tree roots,
11 fish, algae, and aquatic invertebrates (see Section 3.2.3). In fact, fish mortality in response to surface
12 water acidification is usually attributable to Al toxicity. Increased concentrations of exchangeable
13 inorganic Al in the mineral soil have been identified through repeated sampling in the U.S. and Europe
14 over periods ranging from 17 years to 41 years in studies by Billet et al. (Billett, 1990), Falkengren-
15 Grerup and Eriksson (Falkengren-Grerup, 1990), Bailey et al. (2005), and Lawrence et al. (1995). In areas
16 of Europe with excessively high acidic deposition levels, evidence of Al depletion in the mineral soil has
17 also been found (Mulder, 1989; Lapenis, 2004), but Al depletion has not been documented in the U.S.
18 Acidifying deposition is an important cause of increased mobilization of inorganic Al from soils to
19 streams and lakes (Turner, 1990). Acidifying deposition introduces mineral acidity associated with anions
20 that are more mobile than those from organic matter. If the release of base cations from the soil is
21 insufficient to neutralize the inputs of sulfuric and nitric acid, then Al that had previously been deposited
22 by normal soil development in the upper mineral soil is mobilized. Al may also be mobilized by organic
23 acids. However, acidifying deposition mobilizes Al in inorganic forms, and in doing so increases the
24 amount of exchangeable inorganic Al within the B horizon and results in transport of inorganic Al into
25 soil waters and surface waters (Driscoll, 1984; Driscoll, 1985). Inorganic Al is minimally soluble at pH
26 about 6.0, but solubility increases steeply at pH values below about 5.5. This distinction between organic
27 and inorganic forms of Al is important because organic Al is not toxic, whereas inorganic Al is toxic to a
28 variety of plants and aquatic organisms (Baker, 1982; Baldigo, 1997; Joslin, 1988; Joslin, 1989)(Section
29 3.2.3.1). Discussions in this document of inorganic Al in solution refer to dissolved, rather than particulate
30 or colloidal, forms. These dissolved inorganic Al species are often collectively called inorganic
31 monomeric Al (cf, (Driscoll, 1984).
32 Recovery of soil chemistry will require a decrease in exchangeable Al concentrations and Al
33 leaching. It is unclear what length of time would be required to decrease soil exchangeable Al
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1 concentrations to levels characteristic of unpolluted systems. Furthermore, in most cases it is unclear
2 whether exchangeable Al concentrations are continuing to increase, remaining stable, or decreasing.
3 Predictions of trends in exchangeable Al concentrations remain uncertain because of our incomplete
4 understanding of mechanisms through which mineral matter and organic matter interact to control
5 dissolved Al concentrations. Possible changes in the dynamics of soil organic matter that could be
6 expected from climate change add further uncertainty to predictions of future change in exchangeable Al
7 concentrations in soils.
8 In summary, the natural downward movement and deposition of Al within the upper soil profile is
9 altered by acidifying deposition if the release of base cations is insufficient to buffer atmospheric inputs
10 of acidity. Rather than be deposited as an alumino-organic complex, Al mobilized by acidifying
11 deposition tends to remain in solution in inorganic forms that can be transported out of the soil and into
12 surface waters. Depletion of exchangeable base cations generally precedes the mobilization of inorganic
13 Al; therefore, as base cation concentrations in drainage water decrease, inorganic Al concentrations may
14 increase. Increases in concentrations of inorganic Al have been documented at several locations in base-
15 cation depleted soils in the U.S. and Europe. In soils with base saturation values less than about 15 to
16 20%, the ratio of exchangeable Ca to Al is typically low in upper mineral soils (Lawrence, 1995).
3.2.1.6. Episodic Acidification
17 The status of surface water chemistry can be examined and reported as chronic condition or
18 episodic condition. Chronic condition refers to annual average conditions, which are often represented as
19 summer and fall chemistry for lakes and as spring baseflow chemistry for streams. Episodic condition
20 refers to conditions during rainstorms or snowmelt when proportionately more drainage water is routed
21 through upper soil horizons, which tend to provide less neutralization of atmospheric acidity as compared
22 with deeper soil horizons. Surface water chemistry exhibits lower pH and acid neutralizing capacity
23 (ANC) during episodes than during baseflow conditions.
24 One of the most significant effects of acidifying deposition on surface water chemistry is the short-
25 term change in chemistry termed "episodic acidification." While natural processes contribute to seasonal
26 and short-term increases in the acidity of surface waters, research from several regions in the U.S.
27 indicates that acidifying deposition likely has substantially increased the magnitude, frequency, and
28 biological effects of episodic acidification events. Many streams that exhibit chemical conditions during
29 base flow (relatively stable flows that occur between storms) that is suitable for aquatic biota, are subject
30 to occasional episodic acidification with adverse consequences. During such episodes, both stream flow
31 and water chemistry can change markedly (Figure 3-3). Episodic acidification can cause declines in pH
32 and ANC, and most significantly, increases in inorganic Al concentrations in stream waters of the
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1 Northeast, Pennsylvania, and in the central Appalachian Mountain region (Charles, 1991). Episodic
2 decreases in pH and ANC have been documented throughout the country (Wigington et al, 1990).
3 The EPA's Episodic Response Project (ERP) confirmed the chemical and biological effects of
4 episodic pH and ANC depressions in lakes and streams in parts of the eastern U.S. The ERP illustrated the
5 processes of episodic acidification and the role played by SC>42 and especially NOs attributable to
6 atmospheric deposition in the episodic acidification of surface waters. The ERP also clearly showed that
7 the episodic chemical response that has the greatest effect on aquatic biota is increased inorganic Al
8 concentration (Wigington Jr., 1996). During drought periods, atmospherically deposited S that has been
9 stored in wetland soils in reduced form can be reoxidized and mobilized by heavy rains. This remobilized
10 S, as SO42 , has been shown to contribute to episodic acidification of receiving waters in southeastern
11 Canada and the northeastern U.S. (Eimers, 2007; Eimers, 2002; Mitchell, 2006).
12 Aquatic biota vary greatly in their sensitivity to episodic decreases in pH and increases in inorganic
13 Al in waters having low Ca concentration. Baker et al. (1990a) concluded that episodes are most likely to
14 affect biota if the episode occurs in waters with pre-episode pH above 5.5 and minimum pH during the
15 episode of less than 5.0. The most thorough characterization of episodic variation in stream chemistry in
16 the U.S. was conducted through the ERP, in which 13 low-order streams (watershed areas less than
17 24 km2) in the Adirondack and Catskill regions of New York and the Appalachian Plateau in Pennsylvania
18 were monitored from 1988 to 1990 (Wigington Jr., 1996). About 10% of the acid episodes involved
19 decreases in ANC of up to 200 (ieq/L, decreases in pH of up to one unit, and increases in concentrations
20 of inorganic Al of up to 15 (iM (Wigington Jr., 1996). Results showed that acid episodes reduced the size
21 offish populations and eliminated acid-sensitive species if median high-flow pH was less than 5.2 and
22 inorganic Al concentration exceeded 3.7 (iM, despite the relatively short duration of episodes (Baker,
23 1996).
24 Results from the ERP demonstrated that episodic acidification can have long-term adverse effects
25 on fish populations. Streams with suitable chemistry during low flow, but low pH and high inorganic Al
26 levels during high flow, had substantially lower numbers and biomass of brook trout than were found in
27 non-acidic streams (Wigington Jr., 1996).
28 In many regions, the most severe acidification of surface waters generally occurs during spring
29 snowmelt (Charles, 1991). Stoddard et al. (2003) found that, on average, the difference between spring
30 and summer ANC during baseflow in New England, the Adirondacks, and the Northern Appalachian
31 Plateau was about 30 (ieq/L during the period 1990 to 2000 (see Figure 3-4). This implies that lakes and
32 streams in these regions would need to recover to chronic ANC values above 30 (ieq/L before they could,
33 on average, be expected to not experience acidic episodes (Stoddard, 2003). However, the estimate of
34 30 (ieq/L is certain to be low because the comparison was made with non-episodic sampling in spring,
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1 expressed as average spring ANC. ANC measured during episodic spring events would be expected to be
2 lower than average ANC during spring.
3
^ o
E JB
6
5 -
4 -
3 -
2 -
1 -
0
10
-10 -
-20 -
-30
5.0 -
4.8 -
4.6 -
16 -
12 -
8 -
4 -
0
80
60 -
40 -
20 -
0
5/7/90
5/14/955000
Time
5/21/90
5/28/90
Source: Driscoll etal. (2001b)
Figure 3-3. Results of an in situ
bioassay during a period of
episodic acidification in Buck
Creek, Adirondack Mountains, in
spring 1990. (a) discharge, (b) acid
neutralizing capacity, (c) pH, (d)
concentration of inorganic
monomeric aluminum, and (e)
cumulative percentage of mortality
of brook trout over time.
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DRAFT-DO NOT QUOTE OR CITE
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200
150 -
o-
CD
3.
O
100 -
E
3
E
U)
c
'l_
a
V)
c
m
a>
New England Lakes
O Adirondack Lakes
O Appalachian Streams
50 100 150
Mean Summer ANC (peq/L)
200
Source: Stoddard et al. (2003).
Figure 3-4. Relationship between
mean summer acid neutralizing
capacity (ANC) and the mean of
minimum spring ANC values at
long-term monitoring lake and
stream sites in New England, the
Adirondacks, and the Northern
Appalachian Plateau.
1 The most important factor governing watershed sensitivity to episodic acidification is the pathway
2 followed by snowmelt water and storm-flow water through the watershed. The routing of water as it flows
3 through a watershed determines the degree of contact with acidifying or neutralizing materials and
4 therefore influences (along with soils and bedrock characteristics) the amount of episodic acidification
5 that occurs. In any given watershed, surface water ANC may vary in time depending upon the proportion
6 of the flow that has contact with ANC supplying substrate; in general, the more subsurface contact, the
7 higher the surface water ANC (Turner, 1990). This pattern can be attributed in part to higher base
8 saturation and (in some watersheds) greater SO42 adsorption capacity in subsurface soils. It may also
9 relate to the accumulation in the upper soil horizons of acidic material derived from atmospheric
10 deposition and decay processes (Lynch, 1989; Lynch, 1989; Turner, 1990).
11 Streams having acidic episodes show significantly higher fish mortality and other aquatic
12 community changes as compared with streams in which ANC remains above zero (Wigington, 1993).
13 Results from in situ bioassay studies from across the Eastern U.S. show that acidic episodes (with
14 associated low pH and elevated inorganic Al concentrations, and high streamwater discharge) caused
15 rapid fish mortality under some conditions (Baker, 1996; Bulger, 1999)Driscoll et al., 2001b). For
16 example, streams with suitable conditions during low flow, but moderate-to-severe episodic acidification
17 during high flow, had higher fish mortality in bioassays, higher net downstream movement of brook trout
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1 during events, and lower brook trout abundance and biomass compared to streams that did not experience
2 appreciable episodic acidification. These episodically affected streams lacked the more acid-sensitive fish
3 species (blacknose dace and sculpin). Movement of trout into refugia (areas with higher pH and lower
4 inorganic Al) during episodes only partially mitigated the adverse effects of episodes (Baker, 1996).
5 Consideration of episodic acidification greatly increases the extent and degree of estimated effects
6 for acidifying deposition on surface waters. In the Northeast, inclusion of episodically acidified water
7 bodies in regional assessments substantially increases estimates of the extent of surface water
8 acidification. For example, baseflow samples collected from 1991 to 1994 through the EPA Temporally
9 Integrated Monitoring of Ecosystems (TIME) Program indicated that 10% of the 1,812 lakes larger than 1
10 ha surface area in the Adirondack region could be considered chronically acidic (fall index ANC values
11 less than 0 (ieq/L), but that an additional 31% of these lakes had fall index ANC values less than 50 (ieq/L
12 and were, therefore, estimated to be susceptible to episodic acidification (Driscoll, 2001).
13 Lawrence (2002) estimated the extent of episodically acidified stream reaches in a Catskill, NY
14 watershed (area = 85 km2) using an index site at the base of the watershed that became episodically
15 acidified at high flows. Upstream sites with a lower base flow ANC than the index site at the same date
16 and time were found to have a high likelihood of becoming episodically acidified. Base flow sampling of
17 122 upstream sites indicated that approximately 16% of the total upstream reaches had chronic ANC less
18 than 10 (ieq/L, but that 66% of the stream reaches had episodic ANC less than 10 (ieq/L.
19 In the Southeast, a recent study by Deviney et al. (2006) within Shenandoah National Park,
20 Virginia used hourly ANC predictions over short time periods to compute recurrence intervals of annual
21 water-year minimum ANC values for periods of 6, 24, 72, and 168 h. They extrapolated the results to the
22 rest of the Shenandoah National Park catchments using catchment geology and topography to stratify
23 watershed response patterns. On the basis of the models, they concluded that a large number of
24 Shenandoah National Park streams had 6- to 168-h periods of low ANC values, which may stress
25 resident fish populations (Deviney, 2006). Specifically, on the basis of a 4-year recurrence interval,
26 approximately 23% of the land area (44% of the catchments) can be expected to have conditions that are
27 classified with respect to brook trout response categories (Bulger, 1999) as indeterminate (ANC 20 to 50),
28 episodically acidic (ANC 0 to 20) or chronically acidic (ANC less than 0) for 72 continuous hours. Many
29 catchments were predicted to have successive years of ANC values sufficiently low as to potentially
30 extirpate some aquatic species (Deviney, 2006). The authors of the study reported that smaller catchments
31 are more vulnerable to episodic acidification than larger catchments underlain by the same bedrock.
32 Results from a study of six intensively monitored sites in the Park demonstrated a clear pattern of larger
33 episodic ANC depressions in streams having higher median ANC than in streams with lower ANC.
34 However, streams with low median ANC typically experienced decreases that resulted in minimum ANC
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1 values associated with toxicity to biota. These low ANC conditions were more likely to occur in streams
2 underlain by siliclastic bedrock than in those with granitic or basaltic bedrock.
3 In the West, episodic acidification is an especially important issue for surface waters throughout
4 high-elevation areas. Where soils are sparse, as in alpine regions, most snowpack N is flushed to surface
5 waters early in the snowmelt period. Even though there is evidence through use of isotopic tracers that
6 much of the N was cycled microbially, snowpack N has been reported to cause temporary acidification of
7 alpine streams (Williams, 2000; Campbell, 2002). Snowmelt-related temporary acidification of alpine
8 lakes and streams and associated effects have been reported in the Rocky Mountains (Brooks, 1996;
9 Williams, 1996) and Sierra Nevada (Johannessen, 1978; Stoddard, 1995).
10 There have been no studies in the U.S. to determine if either the severity or frequency of episodic
11 acidification has lessened in response to recent decreases in acidifying deposition over the past three
12 decades. In a study of two streams in Nova Scotia (Laudon, 2002) noticeable trends in ANC during
13 different phases of storm hydrographs from 1983 to 1998 were generally not detected other than during
14 the peak-flow phase of one stream (an increase of 0.87 (ieq/L).
15 In summary, the vast majority of water chemistry data for acid-sensitive lakes and streams in the
16 U.S. were collected at low stream flow. It is well known, however, that water chemistry changes with
17 season and with weather. Water chemistry is most stressful to aquatic biota (lowest pH and ANC; highest
18 inorganic Al concentration) during high flow following snowmelt and rainstorms. During such conditions,
19 stream chemistry can be toxic to species that thrive under chemical conditions more typical of base flow.
20 The EPA's ERP and other more localized studies have quantified the effects of episodes on fish. Episodes
21 are driven by hydrological processes, but the acidification that occurs is largely a result of acidifying
22 deposition, especially in cases where inorganic Al has been mobilized. Consideration of such variability
23 in water chemistry is critical for accurate assessment of the extent, magnitude, and biological effects of
24 surface water acidification. The biological effects of changes in surface water chemistry are discussed in
25 greater detail in Section 3.2.3.2.
3.2.2. Terrestrial Ecosystems
26 The changes in major biogeochemical processes and soil conditions described above contribute to a
27 series of effects on terrestrial ecosystems. These changes are manifest in both chemical and biological
28 effects that can include reduced soil base saturation, altered key element ratios, changes in plant
29 productivity, reduced stress tolerance of sensitive plant species, and in some cases, increased mortality of
30 canopy trees. Specific chemical indicators of change can be used to assess sensitivity to, and effects from,
31 acidifying deposition. In the U.S., terrestrial effects of acidification are best described for forested
32 ecosystems, with supportive information on other plant communities, including shrubs and lichens.
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3.2.2.1. Chemical Effects
1 There are several chemical indicators that provide useful information about the acid-base status of
2 soils and its influence on terrestrial vegetation. These include (1) soil base saturation, (2) Ca:Al ratio, and
3 (3) C:N ratio (see Table 3-2). Each chemical indicator provides insight into the level to which the
4 ecosystem has acidified and may be susceptible to associated biological effects. These chemical indicators
5 may also be used to monitor the extent of acidification or recovery that occurs in forest ecosystems as
6 deposition rates of S and N change. As such, several chemical indicators and possible effect thresholds
7 have been developed and applied in conjunction with efforts to estimate critical loads. The critical loads
8 approach is discussed in more detail in Section 3.1.2.
Table 3-2. Examples of chemical indicators of effects from acidifying deposition to terrestrial
ecosystems.
Examples of Chemical Indicators
Soil base saturation
Soil solution Ca:AI ratio
Soil C:N ratio
Example Possible Effect Threshold
10-20%
1.0
20-25
References
Lawrence et al. (Lawrence, 2005)
Driscolletal. (Driscoll, 2001)
Cronan et al. (Cronan, 1990)
Cronan and Grigal (Cronan, 1995)
Aberetal. (2003)
Soil Base Saturation
9 In soils with a base saturation less than about 15 to 20%, exchange ion chemistry is dominated by
10 Al (Reuss, 1983). Under this condition, responses to sulfuric and nitric acid inputs largely involve the
11 release and mobilization of inorganic Al through cation exchange. This is the form of Al that interferes
12 with uptake of Ca by plant roots and is also toxic to many forms of aquatic biota (Cronan, 1995; Baker,
13 1990).
14 The soil O horizon tends to have a much higher base saturation than the underlying mineral soil,
15 despite having lower pH due to organic acidity. The base saturation of the B horizon is in a Spodosol can
16 be sensitive to base cation depletion from leaching by SC>42 and NOs , and is therefore useful for
17 assessing base status with regard to acidifying deposition. Little direct work has been done to relate soil
18 base saturation to forest health, but Cronan and Grigal (1995) determined that base saturation values
19 below about 15% in the B horizon of forests in the northeastern U.S. could lead to effects from Al stress.
20 Lawrence et al. (1995) also observed pronounced decreases in diameter growth of Norway spruce in
21 northwestern Russia, where base saturation decreased from 30% to 20% in the upper 10 cm of the B
22 horizon over a period of 3 7 years.
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1 Base saturation values less than 10% predominate in the soil B horizon in the areas in the U.S.
2 where soil and surface water acidification from acidifying deposition have been most pronounced,
3 including conifer and hardwood forests in the Adirondack Mountains (Sullivan, 2006), red spruce forests
4 throughout the Northeast (David, 1996, hardwood forests in the Allegheny Plateau (Bailey, 2004, and
5 conifer and hardwood forests in the southern Appalachian Mountains (Sullivan, 2003). In a study of sugar
6 maple decline throughout the Northeast, Bailey et al. (2004) found threshold relationships between base
7 cation availability in the upper B soil horizon and sugar maple mortality at Ca saturation less than 2%,
8 and Mg saturation less than 0.5% (Bailey et al., 2004). The authors concluded that base saturation varied
9 as a function of topography, geologic parent material, and acidifying deposition.
Aluminum Concentration in Soil Solution: Calcium to Aluminum Ratio
10 Al may be toxic to tree roots. Plants affected by high Al concentration in soil solution often have
11 reduced root growth, which restricts the ability of the plant to take up water and nutrients, especially Ca
12 (Parker, 1989). Ca is well known as an ameliorant for Al toxicity to roots in soil solution, as well as to
13 fish in a stream. However, because inorganic Al tends to be increasingly mobilized as soil Ca is depleted,
14 elevated concentrations of inorganic Al tend to occur with low levels of Ca in surface waters. Mg, and to
15 a lesser extent Na and K, have also been associated with reduced Al toxicity.
16 Dissolved Al concentrations in soil solution at spruce-fir study sites in the southern Appalachian
17 Mountains frequently exceed 50 (iM and sometimes exceed 100 (iM (Johnson, 1991; Joslin, 1992A1996).
18 All studies reviewed by Eagar et al. (1996) showed a strong correlation between Al concentrations and
19 NO3 concentrations in soil solution. They surmised that the occurrence of periodic large pulses of NO3
20 in solution were important in determining Al chemistry in the soils of southern Appalachian Mountain
21 spruce-fir forests.
22 The negative effect of Al mobilization on Ca uptake by tree roots was proposed by Shortle and
23 Smith (1988), and substantial evidence of this relationship has accumulated over the past two decades
24 through field studies (McLaughlin, 1992; Schlegel, 1992; Minocha, 1997; Shortle, 1997; Kobe, 2002) and
25 laboratory studies (Sverdrup and Warfvinge, 1993; see also review of (Cronan, 1995). Based on these
26 studies, it is clear that high inorganic Al concentration in soil water can be toxic to plant roots. The toxic
27 response is often related to the concentration of inorganic Al relative to the concentration of Ca, expressed
28 as the molar ratio of Ca to inorganic Al in soil solution. As a result, considerable effort has been focused
29 on determining a threshold value for the ratio of Ca to Al that could be used to identify soil conditions
3 0 that put trees under physiological stress.
31 From an exhaustive literature review, Cronan and Grigal (1995) estimated that there was a 50% risk
32 of adverse effects on tree growth if the molar ratio of Ca to Al in soil solution was as low as 1.0. They
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1 estimated that there was a 100% risk for adverse effects on growth at a molar ratio value below 0.2 in soil
2 solution.
3 The information available to define levels of risk for the Ca:Al ratio is complicated by differences
4 in natural soil conditions. As a result of these complications, the risk levels for the ratio defined in
5 laboratory experiments have not necessarily been successfully applied to field conditions. For example,
6 Johnson et al. (Johnson, 1994;, 1994) reported Ca:Al ratios above 1.0 through most of 4 years in the Oa
7 and B horizons of a high-elevation red spruce stand experiencing high mortality. In the 3-year study of
8 DeWitt et al. (2001), Al additions lowered molar Cato inorganic Al ratios in soil solutions of a Norway
9 spruce stand below 0.5, but the authors found no response other than reduced Mg concentrations in
10 needles in the third year, which was a possible precursor to damage.
11 In summary, a molar ratio of Ca to Al in soil solution can be used as a general index that suggests
12 an increasing probability of stress to forest ecosystems as the ratio decreases. The ratio value of 1.0 is
13 proposed as a general damage threshold, but cannot be interpreted as a universally applicable threshold in
14 all natural systems. Tree species vary widely in their sensitivity to Al stress (See Figure 3-5). In addition,
15 Al concentrations in soil solution often exhibit pronounced spatial and temporal variability that is difficult
16 to relate to root activity. Finally, the form of Al present in solution plays an important role in determining
17 toxicity. For example, organically complexed Al, which predominates in upper, organic-rich soil horizons,
18 is essentially nontoxic (Baker, 1982; Cronan, 1995).
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Transpiration
FUNCTION
Membrane integrity
Stomatal regulation
Enzyme activation
Carbohydrate metabolism
Cold hardiness
Defense/chemical-physical
1
GROWTH
Cell division
Cell wall synthesis
Stress tolerance
1
STRUCTURE
Canopy integrity
Leaf form
Wood quality
Tree height
Physiological Processes
H+ I Deposition
Cytoplasm
Cell Wall
Ca
Leaching
Throughfall
Root xylem and cortex
»
Ca.AI
Leaching
Biogeochemical Processes
Source: Fenn et al. (2006)
Figure 3-5. Diagram based on Fenn et al. (Fenn, 2006) shows indicators of forest physiological
function, growth and structure that are linked to biogeochemical cycles through processes that
control rates of Ca supply. Calcium affects plant physiological processes that influence growth
rates and the capacity of plants to resist environmental stresses such as extremes of temperature,
drought, insects, and diseases. Therefore, acidifying deposition, which can deplete soil Ca or
interfere with Ca uptake through mobilization of soil Al, is a concern for maintenance of forest
health.
Soil N: Carbon to N Ratio
1 Mechanisms of retention and release of N in forest ecosystems are not fully understood, but the
2 adverse effects of nitrification and associated acidification and cation leaching have been consistently
3 shown to occur only in soils with a C:N ratio below about 20 to 25 (Aber, 2003; Ross, 2004) .This
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1 observation makes the C:N ratio especially useful because N mineralization and nitrification rates are
2 difficult to measure directly under natural conditions. All available measurement approaches disturb the
3 soil and often cause artificially high rates. Therefore, field measurement provides a relative index rather
4 than a realistic quantitative rate (Ross, 2004). Approaches for measuring N mineralization and
5 nitrification also are subject to high degrees of variability, both temporally (hourly to seasonal) and
6 spatially (down to the sub meter level). Measurements of total OC and N however, are less variable in
7 space and time and are therefore more straightforward to document than N mineralization and nitrification
8 rates. Also, ratios of C to N in the forest floor are inversely related to acidifying deposition levels,
9 although the relationship is stronger for hardwood stands than conifer stands (Aber, 2003). In summary,
10 these factors make the C:N ratio a reliable and relatively straightforward measure for identifying forest
11 ecosystems that may be experiencing soil acidification and base leaching as a result of N input and
12 increased nitrification.
Summary of Biogeochemistry and Chemical Effects
13 The evidence is sufficient to infer a causal relationship between acidifying deposition and
14 changes in biogeochemistry related to terrestrial ecosystems. The strongest evidence for a causal
15 relationship comes from studies of forested ecosystems, with supportive information on other plant
16 communities, including shrubs and lichens; grasslands are likely less sensitive to acidification than
17 woodlands. Soil acidification occurs in response to inputs of sulfuric acid (H2SC>4) and nitric acid
18 (HNOs); the effect can be neutralized by weathering or base cation exchange. Soil acidification is a
19 natural process, but is often accelerated by acidifying deposition. Acidifying deposition is important in
20 decreasing concentrations of exchangeable base cations in soils. The limited mobility of anions associated
21 with naturally derived acidity (organic acids and carbonic acid) controls the rate of base cation leaching
22 from soil under conditions of low atmospheric deposition of S and N. Because inputs of S and N in
23 acidifying deposition provide anions that are more mobile in the soil environment than anions of naturally
24 derived acids, these mineral acid anions can accelerate natural rates of base-cation leaching.
25 Nitrification is mediated by autotrophic bacteria that derive energy by reducing NH4+ to NO3 .
26 Nitrification produces acidity in the form of HNO3 as a byproduct. The HNO3 produced contributes to the
27 acidification of soils and surface waters.
28 There are three useful indicators of chemical changes and acidification effects on terrestrial
29 ecosystems, showing consistency and coherence among multiple studies: soil base saturation, Al
30 concentration in soil water, and soil C:N ratio.
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1 • Soil base saturation is the concentration of exchangeable bases as a percent of the total soil
2 cation exchange capacity. Once base saturation decreases to a critical level (approximately 15-
3 20%), inputs of H2SC>4 and HNOs are increasingly buffered by release of inorganic Al through
4 cation exchange.
5 • Aluminum is toxic to some tree roots. Plants affected by high inorganic Al concentrations in
6 soil solution often have reduced root growth, which restricts the ability of the plant to take up
7 water and nutrients, especially calcium (Ca) (Parker, 1989).
8 • The C:N ratio of soil is used to indicate alterations to the N biogeochemical cycle. If the C:N
9 ratio of soils falls below about 20 to 25, nitrification is stimulated and net nitrification and
10 associated production of acidity occurs in soils.
3.2.2.2. Biological Effects
11 Acidifying deposition can affect terrestrial ecosystems via direct effects on plant foliage and
12 indirect effects associated with changes in soil chemistry. Biological effects of acidification on terrestrial
13 ecosystems are generally attributable to Al toxicity and decreased ability of plant roots to take up base
14 cations (especially Ca) and water from the soil (Cronan, 1995). Acidifying deposition to acid-sensitive
15 soils can cause soil acidification, increased mobilization of inorganic Al from soil to drainage water, and
16 depletion of the pool of stored base cations in the soil. Effects on the soil and direct effects of acidifying
17 deposition on foliage can influence the response of plants to climatic stresses such as drought and cold
18 temperature. They can also influence the sensitivity of plants to other stresses, including insect pests and
19 disease (Joslin, 1992).
20 The combined effects of acidifying deposition and other stressors on terrestrial vegetation are
21 typically measured using indices such as percent dieback of canopy trees, dead tree basal area (as a
22 percent), crown vigor index, and fine twig dieback (see Table 3-3). Each of these variables has a rating
23 system used to quantify forest condition and relate the variables to foliar and soil nutrient concentrations.
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Table 3-3. Example biological effects indicators in terrestrial ecosystems.
Indicator Species Example of Health Indices References
n . n ... , , , Shortleetal. (Shortle, 1997)
Red spruce Percent dieback of canopy trees DeHayes etal. (1999)
Basal area dead sugar maple (as %)
Sugarmaple Crown vigor index
Fine twig dieback
1 The effects of acidifying deposition on the health, vigor, and productivity of terrestrial ecosystems
2 in the U.S. are best documented in spruce-fir and northern hardwood forests of the eastern U.S. Some
3 information is also available for individual species such as red spruce, sugar maple, and some species of
4 lichen. In the western U.S., the health of ponderosa pine and Jeffrey pine has been affected by air
5 pollution, but such effects have largely been attributed to ozone exposure, not acidifying deposition.
Health, Vigor, and Reproduction of Tree Species in Forests
6 Both coniferous and deciduous forests throughout the eastern U.S. are experiencing gradual losses
7 of base cation nutrients from the soil due to accelerated leaching from acidifying deposition. This change
8 in base cation nutrient availability may reduce the quality of forest nutrition over the long term. Evidence
9 suggests that red spruce and sugar maple in some areas in the eastern U.S. have experienced declining
10 health as a consequence of acidifying deposition. Existing information regarding the effects of acidifying
11 deposition on these two forest tree species is summarized below and reference is made to specific health
12 indicators where such information is available.
Red Spruce
13 Red spruce (Picea rubens) is a conifer that occurs mainly in the Northeastern U.S. and at scattered
14 high-elevation sites in the Appalachian Mountains (see Figure 3-6). Red spruce dieback or decline has
15 been observed across high elevation landscapes of the northeastern, and to a lesser extent, southeastern
16 U.S. At high elevations in the Adirondack and Green Mountains, more than 50% of the canopy red spruce
17 trees died during the 1970s and 1980s. In the White Mountains, about 25% of the canopy spruce died
18 during that same period. Dieback of red spruce has also been observed in mixed hardwood-conifer stands
19 at relatively low elevations in the western Adirondack Mountains, an area that receives high inputs of
20 acidifying deposition (Shortle, 1997); acidifying deposition has been implicated as a causal factor
21 (DeHayes, 1999). The frequency of freezing injury to red spruce needles has increased over the past
22 40 years, a period that coincided with increased emissions of S and N oxides and increased acidifying
23 deposition (DeHayes, 1999).
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1 From the 1940s to 1970s, red spruce growth also declined at high elevation in the Southeastern
2 U.S. (McLaughlin et al, 1987; and Zelaker, 1992; Eager et al., 1996), as emissions of both NOX and SO2
3 increased to maxima of about 25 and 30 million tons/yr, respectively. The growth decline in Great Smoky
4 Mountains National Park in North Carolina and Tennessee started earlier at higher elevations (around the
5 1940s and 1950s) and was steeper, while the growth decline developed at lower elevation sites 20 years
6 later. After the 1980s, red spruce growth increased substantially at both the higher- and lower-elevation
7 sites, corresponding to a decrease in SC>2 emissions in the U.S. (to about 20 million tons/yr by 2000),
8 while nitrogen oxide emissions held fairly steady (at about 25 million tons/yr). Annual emissions of S
9 plus nitrogen oxides explained about 43% of the variability in red spruce tree ring growth between 1940
10 and 1998. Climatic variability accounted for about 8% of the growth variation for that period. At low
11 elevation, changes in radial growth could be explained by climatic variables only, and there was no
12 correlation with national S plus nitrogen oxide emissions trends. Recent reductions in S oxide emissions
13 may have changed growth trajectories (Webster, 2004).
Source: Little (19711 http://esp.cr.usqs.qou/data/atlas/little/
Figure 3-6. Distribution of red
spruce (rose) and sugar maple
(green) in the eastern U.S. These
two tree species have experienced
adverse effects in portions of their
ranges that have been attributed to
acidification from acidifying
deposition. Tree distribution data
were obtained from Little's Ranges.
14 The observed dieback in red spruce has been linked, in part, to reduced cold tolerance of red spruce
15 needles, caused by acidifying deposition. Results of controlled exposure studies showed that acidic mist
16 or cloud water reduced the cold tolerance of current-year red spruce needles by 3 to 10 °C (DeHayes,
17 1999). There is a significant positive association between cold tolerance and foliar Ca in trees that exhibit
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1 foliar Ca deficiency. The membrane-associated pool of Ca, although a relatively small fraction of the total
2 foliar Ca pool, strongly influences the response of cells to changing environmental conditions. The plant
3 plasma membrane plays an important role in mediating cold acclimation and low-temperature injury
4 (EPA, 2004). The studies of DeHayes et al. (DeHayes, 1999) suggested that direct acidifying deposition
5 on red spruce needles preferentially removes membrane-associated Ca. More recently, a link has been
6 established between availability of soil Ca and winter injury (Hawley, 2006)based on an experimental
7 addition of Ca at the Hubbard Brook Experimental Forest, New Hampshire. This study demonstrated that
8 Ca depletion from soil was associated with winter injury of red spruce foliage during 2003 when winter
9 injury was unusually high throughout the region (see Figure 3-6).
10 In summary, the weight of evidence suggests that changes in soil chemistry have contributed to
11 high mortality rates and decreasing growth trends of red spruce trees in some areas over the past three
12 decades (Sullivan et al., 2002a). In forests where this has occurred, which are mainly located at high
13 elevation, changes in red spruce growth rates are attributable, at least in part, to base cation deficiencies
14 related to decreased availability of Ca and increased availability of Al as a result of acidifying deposition
15 effects on soils. Important factors appear to include depletion of base cations in upper soil horizons by
16 acidifying deposition, Al toxicity to tree roots, and accelerated leaching of base cations from foliage as a
17 consequence of acidifying deposition. Recent studies also show improvements in red spruce growth with
18 decreasing emissions of SO2 in the U.S. (Webster, 2004).
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(A)
I
ppressed.
Trtr irmvn class
MI.-I :-.-•:-.
lirr.-,-,.,.-
nt_L;i-addition
ns
Tree crown r
I
Interned i.. i e. stipptt s^d.
and undcrstory
Source: Hawley et al. (2006)
Figure 3-7. Mean (± standard error) of current-year red spruce needle winter injury in reference and
calcium-addition watersheds and among crown classes, expressed as foliar injury (A) and bud
mortality (B). Watershed means were either not significantly different (ns) or statistically different
at p < 0.05 (*) or p < 0.01 (**) based on nested analyses of variance.
Sugar Maple
1 Sugar maple (Acer saccharum) is the deciduous tree species of the Northeastern U.S. that is most
2 commonly associated with adverse acidification-related effects of S and N deposition, though other base
3 cation accumulating hardwoods may also be at risk (Driscoll et al., 200Ib). Sugar maple is distributed
4 throughout the northeastern U.S. and central Appalachian Mountain region as a component of the
5 northern hardwood forest Figure 3-6.
6 A conceptual view of the interactions of acidifying deposition and other stressors in sugar maple
7 decline is provided in Figure 3-8. Several studies, mainly in Pennsylvania, have hypothesized that sugar
8 maple decline is linked to the occurrence of relatively high levels of acidifying deposition and base-poor
9 soils (Horsley et al., 2000; Bailey et al., 2004; Hallett et al., 2006; Moore and Ouimet, 2006).
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1 Acidifying deposition may be contributing to episodic dieback of sugar maple in the Northeast
2 through depletion of nutrient cations from marginal soils (Figure 3-8). Horsley et al. (2000) found that
3 dieback at 19 sites in northwestern and northcentral Pennsylvania and southwestern New York was
4 correlated with combined stress from defoliation and soil deficiencies of Mg and Ca. Dieback occurred
5 predominately on ridgetops and on upper slopes, where soil base cation availability was much lower than
6 occurred in the deeper soils found on middle and lower slopes (Bailey et al., 2004). A long-term decrease
7 in soil pH since 1960 (0.78 pH unit decrease in the O horizon, and 0.23 pH unit decrease in the A horizon)
8 in Pennsylvania hardwood forests has been documented, along with decreases in soil Ca and Mg
9 concentrations. Declining sugar maples were shown to be deficient in foliar Ca and Mg (Drohan, 1997).
10 More recent research has strengthened understanding of the role of cation nutrition in sugar maple health
11 at a regional scale across a broad range of conditions (Hallett et al., 2006).
12 Drohan et al. (2002) investigated differences in soil conditions in declining versus non-declining
13 sugar maple plots in northern Pennsylvania from the U.S. Department of Agriculture (USD A) Forest
14 Service's Forest Inventory and Analysis (FIA) program. Soils in plots with declining sugar maple tended
15 to have lower base cation concentrations and pH, and Ca:Al ratio less than 1. Regressions between foliar
16 and soil chemistry showed that foliar nutrition was highly correlated with the chemistry of the upper 50
17 cm of soil (Drohan et al., 2002).
18 Juice et al. (Juice, 2006) added Ca to watershed 1 (Wl) at HBEF in October 1999 sufficient to raise
19 the pH of the O;e soil horizon from 3.8 to 5.0 and the Oa horizon from 3.9 to 4.2. Subsequently, they
20 measured the response of sugar maples to the Ca fertilization. Foliar Ca of canopy sugar maples increased
21 markedly and foliar Mn declined. By 2005, crown condition was much healthier then in the untreated
22 reference watershed (W6). The density of sugar maple seedlings increased significantly following high
23 seed production in 2000 and 2002. In addition, sugar maple germinants were 50% larger on Wl and
24 mycorrhizal colonization of seedlings was much higher in the treated watershed (22.47% of root length)
25 as compared with the reference watershed (4.4%) (Juice, 2006).
26 In general, evidence indicates that acidifying deposition in combination with other stressors is a
27 likely contributor to the decline of sugar maple trees that occur at higher elevation, on geologies
28 dominated by sandstone or other base-poor substrate, and that have base-poor soils having high
29 percentages of rock fragments (Drohan, 2002). Such site conditions are representative of the kinds of
30 conditions expected to be most susceptible to adverse effects of acidifying deposition because of probable
31 low initial base cation pools and high base cation leaching losses.
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Source: Hallettetal. (2006).
Figure 3-8. Conceptual diagram outlining the current understanding of sugar maple decline.
Positive and negative signs indicate the nature of the correlative relationship between variables.
Other Forest Ecosystems
2 Loss of base cations, specifically Ca2+, has also been implicated in increased susceptibility of
3 flowering dogwood (Cornus floridd) to its most destructive disease, dogwood anthracnose (Figure 3-9).
4 Flowering dogwood is a dominant understory species of hardwood forests in the Eastern U.S.
5 (Holzmueller et al. 2006), with important ecosystem functions as a food source for numerous species of
6 animals, and as a large contributor to available Ca in forest litter. It is also recognized as a significant
7 cultural and aesthetic resource throughout its range. Since dogwood anthracnose, a mostly fatal disease,
8 was first reported in 1976 in New York State, it has spread over a large portion of the species' range,
9 generally resulting in mortality greater than 90% in affected stands. Pacific dogwood (Cornus nutallii) is
10 similarly affected, but because its abundance within its range was much lower before the disease first
11 appeared, the effect has received less notice. Susceptibility to the disease, and disease severity in stands,
12 appear dependent on several factors, including acid deposition and various edaphic characteristics and
13 meteorological conditions.
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Reprinted with permission from (E. Holzmueller [ex: Holzmueller et al 2006]) (Journal of Forestry) (Volume, pages).
Figure 3-9. Native range of flowering dogwood (Cornus florida) (dk. gray) and the documented
range of dogwood anthracnose in the eastern U.S. (red). 2002 data from the U.S. Forest Service.
1 In 1990 and 1991, Britton and Berang (Britton, 1996) exposed 200 potted dogwood plants to
2 simulated acid rain (SAR) at 4 levels of pH between 2.5 and 5.5. The plants were then placed among
3 natural stands showing symptoms of the disease. In both years, there was a fourfold increase in
4 percentage of leaf area affected from the plants treated with SAR at a pH of 5.5 to those treated with SAR
5 at apH of 2.5. In 1992 and 1993, four combinations of SAR with a pH of 2.5 or 5.5 were applied
6 separately to the foliage and the soil before inoculation. The percent of leaf area affected was
7 approximately two to four times greater for plants grown in soil treated with acidic SAR, regardless of
8 foliar treatment, suggesting that the worsening of anthracnose damage by acid deposition occurs mostly
9 through soil effects.
10 In a study of the effects of Ca, K, and Mg on dogwood density in forest stands, and on resistance to
11 anthracnose in containerized dogwood plants, Holzmueler et al. (2007) found a strong relation between
12 soil available cations, particularly Ca2+, and dogwood density in Great Smoky Mountains National Park,
13 where dogwood anthracnose has resulted in significant damage. The mortality of potted dogwood plants
14 fertilized with solutions varying in Ca2+, K+, or Mg2+ concentration, and exposed to anthracnose, was both
15 greatest and most rapid when Ca2+ was deficient, but not when K+ and Mg2+ were deficient.
16 Data on the possible effects of S and N deposition on the acid-base characteristics of forests in the
17 U.S., other than the spruce-fir and northern hardwood forest ecosystems, are limited. Ponderosa pine
18 (Pinusponderosd) seedlings exposed to acidic precipitation (pH 5.3, 4.4, 3.5 of 1:1 NHO3:H2SO4)
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1 showed no significant changes in growth (Temple et al., 1992). Perm et al. (2003a) reported that
2 deposition of 20 to 35 kg N/ha/yr contributed to increased NO3 leaching and soil acidity and decreased
3 base saturation in southern California forest ecosystems, but they did not report quantitative measures of
4 growth. Baron et al. (2000) showed that small differences in the N deposition between the east (3 to 5 kg
5 N/ha/yr) and the west (1 to 2 kg N/ha/yr) side of the Rocky Mountains were associated with significant
6 declines in foliar Mg levels and increased foliar N:Mg and N:Ca ratios in old-growth stands of
7 Engelmann spruce (Picea engelmanii). It is not known if such changes in nutrient ratios affect the health
8 or growth of these forests.
9 Despite the evidence for effects of acidifying deposition on the health and vigor of some terrestrial
10 plant communities, we found a lack of scientific literature directly documenting species loss, reduced
11 biodiversity, or adverse effects on threatened and endangered species. A notable exception is the effect of
12 acidifying deposition on lichen abundance and diversity within forest communities (Lichens are discussed
13 in Section 3.2.2.2.3). In Eastern North America and central Europe, areas that receive relatively high
14 levels of acidifying deposition and high atmospheric concentrations of SO2, N oxides, and reduced N
15 have experienced noticeable reductions in cyanolichen abundance on both coniferous and deciduous trees
16 (Richardson and Cameron, 2004). Effects on lichen species biodiversity are also likely (McCune, 1988;
17 Van Haluwyn and Van Herk, 2002). In London, epiphyte diversity, including a majority of the lichen taxa,
18 declined in areas where NO exceeded 40 (ig/m3 and total N oxides exceeded 70 (ig/m3.
Health and Biodiversity of Other Plant Communities
Shrubs
19 Forest trees are not the only vascular plants that are potentially sensitive to acidifying deposition.
20 Available data suggest that it is possible, or perhaps likely, that a variety of shrub and herbaceous species
21 are sensitive to base cation depletion and/or Al toxicity. However, conclusive evidence is generally
22 lacking.
23 Research in Europe has illustrated a shift from shrub to grass dominance in heathlands in response
24 to acidifying deposition. However, such effects are probably more related to the nutrient enrichment
25 effects of N deposition than to the acidification effects of S and N deposition. (See further discussion in
26 Section 3.3.3.1). In summary, whereas some evidence suggests that effects on shrubs and perhaps
27 herbaceous plants are possible, data in the U.S. are insufficient to support the use of shrub or herbaceous
28 plant species as indicators of the acidification-related effects of acidifying deposition at this time.
Lichens
29 Typically, lichens and bryophytes are among the first components of the terrestrial ecosystem to be
30 affected by acidifying deposition. Vulnerability of lichens to increased N input is generally greater than
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1 that of vascular plants (Fremstad et al., 2005). Even in the Pacific Northwest, which receives uniformly
2 low levels of N deposition, changes from acid-sensitive and N-sensitive to pollution-tolerant and
3 nitrophillic lichen taxa are occurring in some areas (Fenn et al., 2003a). Lichens remaining in areas
4 affected by acidifying deposition were found by Davies et al. (2007) to contain almost exclusively the
5 families Candelariaceae, Physciaceae, and Teloschistaceae.
6 Effects of SC>2 exposure on lichens includes reduced photosynthesis and respiration, damage to the
7 algal component of the lichen, leakage of electrolytes, inhibition of N fixation, reduced K absorption, and
8 structural changes (Fields, 1988; Farmer et al., 1992). In response to reductions after the 1970s in SC>2
9 exposure and acidifying deposition in London, lichen diversity increased dramatically (Hawksworth,
10 2002). However, the recovery of lichens in response to reduced S and N inputs is inconsistent.
11 Improvement for bryophytes has been reported to occur in 1 year by Power et al., (2006) and Mitchell
12 et al., (2004), 5 years by Gordon et al., (2001), and 49 years by Strengbom et al., (2001).
13 Scott (1989a,b) concluded that the S:N exposure ratio was as important as pH in causing toxic
14 effects on lichens, based on experiments on Cladina rangiferina and C. stellaris. Thus, it is not clear to
15 what extent acidity may be the principal stressor under high levels of air pollution exposure. The toxicity
16 of SO2 to several lichen species is greater under acidic conditions than under neutral conditions. The
17 effects of excess N deposition to lichen communities are discussed in Section 3.3.3.1.5.
Grasslands
18 Due to structural differences and their lower canopy, grasslands are thought to be less sensitive to
19 acidification than woodlands (Blake et al., 1999; Kochy and Wilson, 2001). Among grasslands, those with
20 calcareous soils will be less sensitive than those with acidic soils (Bobbink et al., 1998). Most literature
21 on the effects of atmospheric S and N deposition on grasslands documents effects of fertilization from N
22 deposition, not acidification. Such fertilization effects are discussed in Section 3.3.3.1.2.
Arctic and Alpine Tundra
23 The possible effects of acidifying deposition on arctic and alpine plant communities are also of
24 concern. Especially important in this regard is the role of N deposition in regulating ecosystem N supply
25 and plant species composition (See further discussion of such effects in Section 3.2.2). Soil acidification
26 and base cation depletion in response to acidifying deposition have not been documented in arctic or
27 alpine terrestrial ecosystems in the U.S. Such ecosystems are rare and spatially limited in the eastern U.S.,
28 where acidifying deposition levels have been high. These ecosystems are more widely distributed in the
29 western U.S. and throughout much of Alaska, but acidifying deposition levels are generally low in these
30 areas. Key concerns are for listed threatened or endangered species and species diversity. However, for
31 most rare, threatened, or endangered herbaceous plant species, little is known about their relative
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1 sensitivities to acidification from atmospheric deposition inputs. Although plant species diversity of arctic
2 and alpine ecosystems is highly valued, it is difficult to document changes in this parameter in response to
3 acidifying deposition.
Summary of Biological Effects
4 The evidence is sufficient to infer a causal relationship between acidifying deposition and
5 Changes in terrestrial biota. The strongest evidence for a causal relationship comes from studies of
6 terrestrial systems exposed to elevated levels of acidifying deposition that show reduced plant health,
7 reduced plant vigor, and loss of terrestrial biodiversity. Consistent and coherent evidence from multiple
8 species and studies shows that acidifying deposition can affect terrestrial ecosystems by causing direct
9 effects on plant foliage and indirect effects associated with changes in soil chemistry. Biological effects of
10 acidification on terrestrial ecosystems are generally attributable to aluminum toxicity and decreased
11 ability of plant roots to take up base cations. There are several indicators of stress to terrestrial vegetation
12 (see Table 3-3) including percent dieback of canopy trees, dead tree basal area (as a percent), crown vigor
13 index, and fine twig dieback.
Species Level
14 • Changes in soil chemistry (depletion of soil base cations, Al toxicity to tree roots, leaching of
15 base cations into drainage water) have contributed to high mortality rates and decreasing
16 growth trends of red spruce trees (Picea rubens) in some areas of the Eastern U.S. over the
17 past three decades.
18 • Acidifying deposition, in combination with other stressors, is a likely contributor to the decline
19 of sugar maple (Acer saccharum) trees that occur at higher elevation, in some portions of the
20 eastern U.S., on geologies dominated by sandstone or other base-poor substrate, and that have
21 base-poor soils.
22 • Lichens and bryophytes are among the first species affected by acidifying deposition in the
23 terrestrial ecosystem. Effects of SO2 on lichens include reduced photosynthesis and respiration,
24 damage to the algal component of lichen, leakage of electrolytes, inhibition of N fixation,
25 reduced potassium (K) absorption and structural changes.
26 • Data are insufficient to draw general conclusions for other species.
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Community Level
1 Species loss and reduced biodiversity of forests, shrubs, and meadow plant communities may
2 occur, but have not been clearly demonstrated in the U.S.
3.2.3. Aquatic Ecosystems
3.2.3.1. Chemical Effects
3 The changes in major biogeochemical processes and soil conditions caused by acidifying
4 deposition have significant ramifications for the water chemistry and biological functioning of associated
5 surface waters. Surface water chemistry indicates the adverse effects of acidification on the biotic
6 integrity of fresh water ecosystems. Because surface water chemistry integrates the sum of soil and water
7 processes that occur upstream within a watershed, it also reflects the results of watershed-scale terrestrial
8 effects, including N saturation, forest decline, and soil acidification (Stoddard, 2003). Thus, water
9 chemistry integrates and reflects changes in soil and vegetative properties and biogeochemical processes.
10 The effects on aquatic ecosystems can be described by changes in several chemical effects
11 indicators such as: SO42 concentration, NO3 concentration, base cation concentration, pH, ANC, and
12 inorganic Al. All of these are of interest, and each can provide useful information regarding both
13 sensitivity to surface water acidification and the level of acidification that has occurred. Importantly, these
14 chemical changes can occur over both long- and short-term timescales. Short-term (hours or days)
15 episodic changes in water chemistry have perhaps the most significant biological effects. The
16 acidification effects on aquatic biota are most commonly evaluated using either Al or pH as the primary
17 chemical indicator (Table 3-4). ANC is also used because it integrates overall acid status and because
18 surface water acidification models do a better job projecting ANC than pH and inorganic Al
19 concentrations. However, ANC does not relate directly to the health of biota. The usefulness of ANC lies
20 in the association between ANC and the surface water constituents that directly contribute to or
21 ameliorate acidity-related stress, in particular pH, Ca, and inorganic Al. The base cation surplus
22 (Lawrence, 2007) is an alternate index that integrates acid-base status. It is based on a measurement of
23 ANC (calculated from the charge balance of ionic concentrations in water) and also accounts for the
24 influence of natural organic acidity.
25 A synoptic illustration of the national patterns of surface water alkalinity in the conterminous U.S.
26 is provided in Figure 3-10. Alkalinity is the most readily available measure of the sensitivity of lakes and
27 streams to acidifying deposition. Although the actual sensitivity of a water body depends on many
28 watershed characteristics and processes, the low-alkalinity areas on the map indicate where sensitive
29 surface waters are most likely to be found. The map is based on data from approximately 39,000 lake and
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1 stream sites and the associations of the data values with factors such as land use, physiography, geology,
2 and soils.
Table 3-4. Examples
ecosystems.
Chemical Indicator
Surface water pH
Surface water AN C
Inorganic Al
'^ '
1
of chemical indicators of effects from acidifying deposition to aquatic
Examples of Potential Thresholds Reference
5.0-6.0 Baker etal. (1990)
0-50|jeq/L Bulger etal. (1999)
Wigington Jr. etal. (1996)
2-4|jmol/L Driscoll etal. (2001)
Baldigo et al. (2007)
FSJ t -"-ft • %ffi
•
i
Total
^ Alkalinity
3m •• -(r
T «^ ' Cj .- ' /^s^H' * '0 lixi
W;
,,™
T ™ «o
« 0 ln> t"! XD
Ajben Eqiul Area pr<^ec[lon
Source: Omernik, J.M et al. 1988.
Figure 3-10. Surface water alkalinity in the conterminous U.S. Shading indicates the range of
alkalinity within which the mean annual values of most of the surface waters of the area fall.
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Surface Water S042-
1 Measurements of SO42 concentration in surface water provide important information on the extent
2 of cation leaching in soils and how SO42 concentrations relate to ambient levels of atmospheric S
3 deposition. Assessments of acidifying deposition effects dating from the 1980s to the present have shown
4 SO42 to be the primary anion in most, but not all, acid-sensitive waters in the U.S. (Driscoll, 1985;
5 Driscoll, 1988; Driscoll, 2001) Webb et al., 2004). In an analysis representative of over 10,000 acid-
6 sensitive lakes in the Northeast, inorganic anions represented the majority of negative (anionic) charge in
7 83% of the lakes, and in this group of lakes, 82% of the total negative charge was due to SO42 (Driscoll,
8 1988; Driscoll, 2001). In contrast, naturally derived organic anions represented an average of 71% of total
9 negative charge in the 17% of lakes in which organic anions predominated (Driscoll, 1988; Driscoll,
10 2001).
11 Atmospheric deposition of S is widely acknowledged as causing changes in concentrations of
12 SO42 in surface water. No long-term data sets exist to document changes in SO42 in surface waters since
13 the onset of the Industrial Revolution. One of the longest-running monitoring programs exists at the
14 Hubbard Brook Experimental Forest in New Hampshire. Surface water data from this Long-Term
15 Ecological Research site have been used to develop historic estimates of SO42 concentrations using the
16 Photosynthesis and EvapoTranspiration-BioGeoChemical (PnET-BGC) model (Gbondo-Tugbawa, 2002).
17 Results from Hubbard Brook suggest that acidifying deposition has contributed to a nearly four-fold
18 increase in stream SO42 concentration between 1850 and 1970 (Driscoll, 1988; Driscoll, 2001).
19 Long-term data in other regions suggest similar trends in some cases. For example, a study of
20 seven streams in the Catskill region of New York, Stoddard (1991) identified increasing trends in SO42
21 concentrations from 1952-54 to 1970 in three streams and no trend in the four other streams.
22 As emissions and deposition of S have declined over approximately the last 30 years, surface water
23 concentrations of SO42 have decreased in most regions in the eastern U.S. For example, Stoddard et al.
24 (2003) found that surface waters monitored in EPA's Long-Term Monitoring program showed consistent
25 decreases in SO42 concentrations from 1990 to 2000 in New England lakes (1.77 (ieq/L/yr), Adirondack
26 lakes (2.26 (ieq/L/yr), Appalachian streams (2.27 (ieq/L/yr) and Upper Midwest lakes (3.36 (ieq/L/yr).
27 The only exception to the pattern of decreasing SO42 concentration in surface waters during this period
28 was for streams in the Blue Ridge Mountain region of Virginia, which showed a significant increase in
29 SO42 concentrations (0.29 (ieq/L/yr) during this period. The increasing trend in Virginia streams is
30 presumably the result of decreased S adsorption on soils and net desorption from the soil in response to
31 decreased S deposition.
32 In summary, available data indicate a pattern of increasing concentrations of SO42 in surface
33 waters before the year of peak S emissions in the early 1970s, followed by widespread decreasing trends
34 in SO42 concentrations after the peak (with the only exception being the Blue Ridge Mountain region in
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1 Virginia). On this basis, continued decreases in S emissions would be expected to result in further
2 decreases in SO42 concentrations in surface waters, although the rate of response is variable and some
3 model results suggest that recovery may be delayed as accumulated S leaches from watersheds, even as
4 emissions and deposition decline.
Surface Water NOs"
5 As described in the previous section, the acidification potential of atmospherically deposited S is
6 primarily a function of the extent of SO42 anion mobility in watershed soils and drainage waters.
7 Similarly, acidification of soil water and surface water from atmospheric N deposition is largely governed
8 by the mobility of the NO3 anion. Both oxidized and reduced N deposition can contribute to the NO3
9 flux in drainage water. Once N is deposited, processes within the N cycle, including microbial
10 assimilation, plant uptake, and loss to denitrification act to limit the extent of NO3 leaching. In contrast,
11 processes such as mineralization, nitrification, fixation, and atmospheric deposition contribute to the
12 NO3 flux and increase the likelihood that substantial leaching of NO3 in drainage water will occur. Such
13 leaching of NO3 is required in order for N deposition to cause N saturation, surface water acidification,
14 or base cation leaching and depletion. Ultimately, the balance of these processes in the N cycle will
15 determine the extent to which such effects will be manifested.
16 Whereas SO42 is generally considered the dominant agent of surface water acidification in affected
17 regions of the U.S., NO3 plays a large role in acidification of surface waters in some regions, particularly
18 during snowmelt and rainstorms. Prior to the mid-1980s, atmospheric deposition effects research in the
19 U.S. focused almost exclusively on S. Within the 1980 to 1990 National Acid Precipitation Assessment
20 Program (NAPAP) research program, relatively little attention was paid to N research.
21 Release of NO3 from soil to surface waters may affect nutrient relationships and biological
22 neutralization processes in aquatic ecosystems to a greater extent than SO42 (Kelly, 1987) Bukaveckas
23 and Shaw, 1998; Momen et al., 2006). The importance of NO3 as an agent of acidification varies by
24 region. Driscoll and Newton, (Driscoll, 1985) found that NO3 concentrations in 20 lakes in the early
25 1980s in the Adirondack region of New York averaged 12% of SO42 concentrations, whereas Lovett et al.
26 (2000) found that baseflow NO3 concentrations in 1994-97 were an average of 37% of SO42
27 concentrations in 39 streams in the Catskill region of New York. Murdoch and Stoddard (1993)
28 demonstrated the importance of NO3 during high-flow conditions in Catskill streams in which
29 concentrations periodically equaled or exceeded SO42 concentrations. Average concentrations of NO3 in
30 most southeastern streams tend to be considerably less than SO42 concentrations (Webb et al., 2004).
31 However, Cook et al. (1994) documented very high NO3 concentrations in stream water at high elevation
32 in the Great Smoky Mountains in North Carolina.
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1 Surface water NO3 concentration trends vary by region and over time. Several regions in the
2 Northeastern U.S. showed increased NO3 concentrations during the 1980s. For example, in the Catskill
3 Mountains of New York all 16 streams for which data were available showed increasing trends in NO3
4 concentration during that period. A similar increase in NO3 concentration was reported for Adirondack
5 lakes in the 1980s (Stoddard, 1999). These increasing trends in NO3 concentration were initially
6 attributed to N saturation in response to atmospheric deposition (Aber, 1998).
7 More recent information on NO3 trends during the 1990s, when atmospheric N deposition was
8 relatively stable, suggest that the relationship between atmospheric N deposition and surface water NO3
9 concentrations is complex. During the 1990s, the only significant change occurred in the two regions with
10 the highest ambient surface water NO3 concentrations: lakes in the Adirondack Mountains and streams in
11 the Northern Appalachian Plateau (Figure 3-11). Both exhibited small but significant downward trends in
12 NO3 concentration during the 1990s. The long-term record of dissolved inorganic N (which is largely
13 NO3 ) concentrations at the Hubbard Brook Experimental Forest showed a similar pattern: high
14 concentrations in the late 1960s and 1970s, followed by decreases to minimum values in the mid-1990s
15 (Aber, 2002). Across New England and the Upper Midwest, where ambient surface water concentrations
16 are much lower than in the Adirondack Mountains and Northern Appalachian Plateau (Figure 3-11), NO3
17 concentrations in surface waters were unchanged during the 1990s. The Ridge/Blue Ridge province
18 registered a small, but significant, decrease in NO3 concentration during the 1990s, but interpretation of
19 trends for NO3 in this region was complicated by an outbreak of gypsy moths, which consumed foliage
20 and caused large increases in the concentration of NO3 in soil water and stream water in affected
21 watersheds (Eshleman, 1998).
22 Efforts to explain the complex patterns in NO3 concentrations under conditions of reasonably
23 stable atmospheric N deposition have focused on both terrestrial and aquatic N cycling. Goodale et al.
24 (Goodale, 2003) reported that lower NO3 concentrations measured in the 1990s at streams in New
25 Hampshire could not be accounted for by differences in stream flow or forest succession, but inter-annual
26 climate variation was proposed as a possible cause. In the Adirondacks, Driscoll et al., (Driscoll, 2007)
27 proposed that increased concentrations of atmospheric CO2 may have resulted in a fertilization effect that
28 increased N assimilation. Studies by Mitchell et al. (1996) and Murdoch et al. (1998) provide some
29 evidence of climate effects on trends in NO3 concentrations in surface waters in the Northeast. In
30 particular, a region-wide spike in NO3 concentrations followed an unusually cold December that may
31 have disrupted soil N cycling processes (Mitchell, 1996). Murdoch et al. (1998) also found that mean
32 annual air temperature was strongly related to average annual NO3 concentration during most years in a
33 Catskill watershed with elevated NO3 concentrations in stream water.
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Regional Trends, 1990-2000
(in lakes and streams)
Sulfate (|jeq/L/yr)
Nitrate (|jeq/L/yr)
ANC (|Jeq/L/yr)
Hydrogen Ion (|jeq/L/yr)
Base Cations (|jeq/L/yr)
DOC (mq/L/yr)
Aluminum (peq/Uyr)
-1 o 1
Slope of Trend
New England Lakes
Adirondack Lakes
Northern Appalachian Streams
Upper Midwest Lakes
Ridge and Blue Ridge Streams
Source: Stoddard et al. (2003)
Figure 3-11. Summary of regional
trends in surface water chemistry
from 1990 to 2000 in regions
covered by the Stoddard et al.
(2003) report.
1 Processes within lakes may have also played a role in the measured trends in Adirondack lakes (Ito
2 et al., 2005, 2007). In a study of 30 of the 48 long-term monitoring lakes investigated by Driscoll et al.
3 (Driscoll, 2003; Driscoll, 2007) and Momen et al. (2006) found that concentrations of dissolved NOs
4 were inversely correlated with concentrations of chlorophyll a in 11 lakes, and that chlorophyll a was
5 increasing in concentration in 9 lakes. The increase in pH observed in most of these lakes may have
6 stimulated productivity so that N assimilation by plankton increased (Momen et al., 2006).
7 In summary, NOs contributes to the acidity of many lakes and streams in the eastern U.S. that have
8 been affected by acidifying deposition, especially during spring months and under high-flow conditions.
9 Nevertheless, there is little or no apparent relationship between recent trends in N deposition and trends in
10 NO3 concentrations in surface waters in the eastern U.S. This observation is in sharp contrast to observed
11 responses for S deposition and SO42 concentrations. These results likely reflect the complexities of N use
12 within terrestrial and aquatic ecosystems. Uptake of atmospherically deposited N by plants and
13 microorganisms in the terrestrial environment precludes drainage water acidification and base cation
14 leaching that would be caused if excess N leached as NO3 from the terrestrial to aquatic ecosystems.
15 While great uncertainty exists, and the timescales of N saturation may be longer than previously
16 considered (e.g., centuries rather than decades), the long-term retention of N deposited in forested regions
17 and consequent dampening of deposition effects on surface waters is unlikely to continue indefinitely
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1 (Aber, 2003) and spatial patterns across the Northeastern U.S. are consistent with atmospheric N
2 deposition contributing to elevated NO3 leaching.
Surface Water Base Cations
3 The results from several studies in the Eastern U.S. suggest that base cation concentrations in
4 surface waters increased during the initial phases of acidification into the 1970s. This trend reversed and
5 base cations decreased in response to decreasing SO42 and NO3 concentrations. For example, the study
6 of Likens et al. (Likens, 1996) evaluated trends in base cation concentrations in stream water in relation to
7 long-term trends in SO42 plus NO3 for the Hubbard Brook Experimental Forest. This record showed an
8 approximately linear increasing relationship between concentrations of base cations and SO42 plus NO3
9 from 1964 to 1969, then a reversal in 1970 and a decreasing trend up to 1994. The slope of the phase with
10 increasing cation concentrations was steeper than the slope for the phase with decreasing cation
11 concentrations. Regional declines in base cation concentrations were measured in the Long-Term
12 Monitoring project from 1990 to 2000 for lakes in New England, the Adirondack Mountains, and the
13 Upper Midwest (Figure 3-11). The study of Lawrence et al. (1999) showed decreased concentrations of
14 base cations at a rate that exceeded decreases in (SO42 plus NO3 ) in Catskill Mountain streams from
15 1984 to 1997. In streams within western Virginia and in Shenandoah National Park, concentrations of
16 base cations did not exhibit significant trends from 1988 to 2001, perhaps due to the influence of S
17 adsorption to soil on stream water SO42 concentrations.
18 In some surface waters, interpretation of the effects of, and changes in, the concentration of base
19 cations and ANC is complicated by the influence of naturally occurring organic acidity. The base cation
20 surplus provides an approach for distinguishing between the effects of organic acidity and acidifying
21 deposition (Lawrence, 2007). Base cation surplus is defined as the difference between the summed
22 concentrations of base cations (Ca, Mg, Na, K) and strongly acidic inorganic anions (SO42 , NO3 ,
23 chloride), plus an estimate of the strongly acidic organic anions estimated from dissolved organic C and
24 an assumed charge density. These strongly acidic organic anions are dissociated at low pH, and function
25 essentially as mineral acid anions in terms of their effect on ANC. The calculated base cation surplus is
26 similar to the calculated ANC, but explicitly accounts for strongly acidic organic acids. When the base
27 cation surplus is plotted against inorganic Al concentration, a distinct threshold for Al mobilization occurs
28 at a base cation surplus value that closely approximates 0, regardless of the dissolved OC concentration
29 (Lawrence, 2007). This threshold provides an unambiguous reference point for evaluating the effects of
30 acidifying deposition on mobilization of inorganic Al. To date, this calculated variable has only been used
31 in one large-scale assessment of acidifying deposition effects on surface waters (Lawrence, 2007).
32 In summary, decreases in base cation concentrations in surface water in the Eastern U.S. over the
33 past two to three decades are ubiquitous and are closely tied to trends in SO42 concentrations. In most
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1 regions, rates of decrease for base cations have been similar to those for SO42 plus NO3 , with the
2 exception of streams in Shenandoah National Park, Virginia, which are affected by decreases in
3 SO42~adsorption in soils. Decreasing trends of base cation concentrations do not necessarily indicate
4 further acidification or recovery of surface waters, but may indicate either lower base cation leaching
5 rates in soils or depletion of base cations from the soil system.
Surface Water pH
6 Surface water pH is a commonly used as an indicator of acidification. The pH of water quantifies
7 the hydrogen ion concentration, which is toxic to many forms of aquatic life. In addition, pH correlates
8 with other biologically important components of surface water acid-base chemistry, including ANC,
9 inorganic Al, Ca concentration, and organic acidity. Low pH can have direct toxic effects on aquatic
10 species (Driscoll, 2001). Threshold pH levels for adverse biological effects have been summarized for a
11 variety of aquatic organisms (Haines and Baker, 1986; Baker et al., 1990a). Common reference values for
12 pH, below which adverse biological effects are anticipated, are 6.0, 5.5, and 5.0. The effects of low pH are
13 specific to the study organism and depend also upon the concentrations of other chemicals in the water,
14 notably inorganic Al and Ca. Species-specific effects are discussed in more detail in Section 3.2.3.2.
15 Long-term past changes in surface water pH have been inferred for lakes in the Adirondacks
16 through paleolimnological studies (Charles et al., 1989; Sullivan et al., 1990; Cumming et al., 1992,
17 1994). These studies of algal remains in lake sediments for regionally representative Adirondack lakes
18 suggested that about 25 to 35% of the Adirondack lakes that are larger than 4 ha have acidified since
19 preindustrial time. An estimated 80% of the Adirondack lakes that had ambient pH less than 5.2 in the
20 mid-1980s were inferred to have experienced declines in pH and ANC since the previous century. About
21 30 to 45% of the lakes with ambient pH between 5.2 and 6.0 have also acidified. The results suggest that
22 the low-ANC lakes of the southwestern Adirondacks acidified the most since preindustrial time.
23 Additional information regarding long-term changes in surface water pH has been gained through
24 site-specific dynamic modeling. For example, by applying the PnET-BGC model to the long-term stream
25 chemistry record at the Hubbard Brook Experimental Forest, Gbondo-Tugbawa et al. (2002) estimated
26 that past stream pH (circa 1850) was probably about 6.3, compared with values just above 5.0 in 2000
27 (Driscoll, 2007).
28 In recent decades, measurements of pH have been routinely collected in surface waters in the U.S.
29 where effects of acidifying deposition have been monitored, but there has been a long-standing reliance
30 on titrated ANC as the primary chemical measurement for evaluation of surface water acidification.
31 Overall, between 1980 and 2000 most studies reported slight increases in surface water pH, including
32 lakes in the Adirondack Mountains (rate variable) (Driscoll, 2007) and southern New England (0.002 pH
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1 units per year) (Warby, 2005), and streams in the Catskill/Poconos region of New York and Pennsylvania
2 (0.008 pH units per year) (Warby, 2005).
3
Adirondack Survey
October 2003
Median DOC = 743 umol L
Adirondack Survey
March 2004
Median DOC = 411 umol I/1
Winnisook Stream
2001-2004
Median DOC = 211 umol L'1
slope = -0.16
x intercept = 2.0
r2 = 0.69
-100 -50
50 100 150 200
Base Cation Surplus (ueq L~1)
Source: Lawrence et al. (Lawrence, 2007)
Figure 3-12. Concentration of inorganic Al in Adirondack streams as a function of the calculated
base cation surplus.
4 Through frequent monitoring from 1990 to 2000, Stoddard et al. (2003) found a decrease in
5 hydrogen ion (0.19 (ieq/L/yr) that was similar to the rate of change observed in the same Adirondack
6 lakes by Driscoll et al. (Driscoll, 2007) from 1992 to 2004 (0.18 (ieq/L). Stoddard et al. (2003) also
7 reported an increase in the hydrogen ion concentration of Appalachian streams (0.08 (ieq/L/yr) and Upper
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1 Midwest lakes (0.01 (ieq/L/yr). No trends were found in New England lakes in this study (see Figure
2 3-11).
3 In summary, increasing trends in pH (decreasing hydrogen ion concentration) in surface waters in
4 the Northeastern U.S. were common through the 1990s up to 2004, but many exceptions occur, and
5 overall, the rates of change have been small. Driscoll et al. (Driscoll, 2001; Driscoll, 2001; Driscoll, 2007)
6 attributed the limited pH recovery of lakes in acid-sensitive regions to three factors: (1) The levels of
7 acid-neutralizing base cations in surface waters have decreased markedly because of the depletion of
8 available base cations from the soil, and to a lesser extent, a reduction in atmospheric inputs of base
9 cations; 2) As forests mature, their requirements for N decrease, and they are expected to increasingly lose
10 NO3 as forests develop; and (3) Sulfur has accumulated in the soil under previous conditions of high
11 atmospheric S deposition and is now being gradually released to surface water as SO42 , even though S
12 deposition has decreased.
Surface Water ANC
13 The most widely used measure of surface-water acidification is ANC, which is often determined by
14 Gran titration (titrated ANC). This measurement is the primary chemical indicator for assessing past
15 effects of acidifying deposition, and the recovery expected from decreasing atmospheric deposition
16 (Bulger, 2000; Stoddard, 2003). Titrated ANC is useful because it reflects the ANC of the complete
17 chemical system, which is typically reduced by acidifying deposition in acid-sensitive landscapes.
18 In contrast to surface water pH, ANC is more stable and it reflects sensitivity and effects of
19 acidification in a linear fashion across the full range of ANC values. Therefore, ANC is the preferred
20 indicator variable for surface water acidification. Both titrated and calculated ANC values are commonly
21 determined in studies aimed at resource characterization or long-term monitoring.
22 Bulger et al. (1999) defined ANC response categories for brook trout in Virginia as less than zero
23 (chronic damage likely), 0 to 20 (ieq/L (episodic damage likely), 20 to 50 (ieq/L (likelihood of damage
24 not determined), and greater than 50 (ieq/L (brook trout not sensitive). ANC less than 0 (ieq/L is of
25 significance because waters at or below this level have limited capacity to neutralize acid inputs. Surface
26 waters with ANC < 50 (ieq/L have been termed "extremely acid sensitive" (Schindler, 1988), are prone to
27 episodic acidification in some regions (DeWalle, 1987) Eshleman, 1988), and may be susceptible to
28 future chronic acidification at current or increased rates of acidifying deposition. Baker et al. (1990c) used
29 ANC cutoffs of 0, 50, and 200 (ieq/L for reporting on national lake and stream population estimates.
30 In assessing changes in surface water ANC, it is important to distinguish between acidic waters and
31 acidified waters. "Acidic" describes a condition that can be measured (i.e., Gran ANC less than or equal
32 to 0). It may be due either to the effects of acidifying deposition, or to other causes such as the presence
33 of organic acidity or the weathering of S-containing minerals in the watershed. "Acidified" refers to the
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1 consequences of the process of acidification (a decrease in ANC observed through time). It does not
2 require that the water body be acidic, and does not imply a particular cause for the change in chemistry.
3 The term "anthropogenically acidified" implies that human activity was responsible for the increase in
4 acidity that occurred.
5 Some of the most detailed studies of ANC have been conducted in the Adirondack Mountains.
6 Model simulations suggested that none of the lakes in the Adirondack target lake population identified by
7 EPA's Environmental Monitoring and Assessment Program (EMAP) were chronically acidic or had ANC
8 less than 20 (ieq/L under preindustrial conditions, but that by 1980 there were hundreds of such lakes
9 (Table 3-5). Many lakes were estimated to have had preindustrial ANC below 50 (ieq/L, but this estimate
10 more than doubled by 1990. Based on Model of Acidification of Groundwater in Catchments (MAGIC)
11 model outputs extrapolated to the regional population of Adirondack lakes larger than 1 ha that currently
12 have ANC below 200 (ieq/L, maximum past acidification occurred by about 1980 or 1990, with median
13 ANC of the lake population of about 61 (ieq/L (reduced from a median of 92 (ieq/L estimated for the
14 preindustrial period). Changes in ANC produced an increase in not only the percentage of lakes that were
15 chronically acidic, but also in those that were deemed likely to experience episodic acidification and its
16 associated short-term changes in water chemistry (Sullivan et al, in press).
Table 3-5. Estimates of change in number and proportion of acidic surface waters in acid-sensitive
regions of the North and East, based on applying current rates of change in Gran ANC to past
estimates of population characteristics from probability surveys.
Results of Regional Survey
Region
New England
Adirondacks
N. Appalachians
Ridge/Blue Ridge
Upper Midwest
Population
Size
6,834 lakes
1830 lakes
42,426 km
32,687 km
8,574 lakes
Number
Acidic1
386 lakes
238 lakes
5,014km
1,634km
251 lakes
% Acidic2
5.6%
13.0%
11.8%
5.0%
2.9%
Time Period of
Estimate
1991-94
1991-94
1993-94
1987
1984
Rate of ANC
change3
+0.3
+0.8
+0.7
-o.o
+1.0
Results of Monitoring during 1990s
Estimated Number
Acidic in 2000
374 lakes
149 lakes
3,600 km
1,634km
80 lakes
% Acidic in 2000 %(
5.5%
8.1%
8.5%
5.0%
0.9%
Change in Number
f Acidic Systems
-2%
-38%
-28%
0%
-68%
1 Number of lakes/streams with Gran ANC < 0 in past probability survey by EPA (data collected at "Time Period of Estimate," in column 5).
2 Percent of population (from Column 2) with Gran ANC < 0 in past probability survey (data collected at "Time Period of Estimate," in column 5).
3 Based on regional trends presented in the Stoddard et al. (2003) report, in |jeq/L/yr, for the 1990s.
17
18 In other regions, responses to reduced levels of acidifying deposition required by the Clean Air Act
19 (CAA) and other emissions control legislation were reported by Stoddard et al. (2003). They found
20 tendencies during the 1990s toward increasing surface water Gran ANC in all of the glaciated regions of
21 the eastern U.S. (i.e., New England, Adirondacks, and Northern Appalachian Plateau) and Upper
22 Midwest, and decreasing Gran ANC in the Ridge/Blue Ridge province. Changes in ANC were relatively
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1 modest compared with observed reductions in SO42 concentrations in surface waters. The regional
2 increases in the Adirondacks, Northern Appalachian Plateau, and Upper Midwest were statistically
3 significant (Table 3-6). Median increases of about +1 (ieq/L/yr in the Northern Appalachian Plateau,
4 Adirondacks, and Upper Midwest represent significant trends towards ecological recovery from
5 acidification (Stoddard, 2003). Estimated change in the number of acidic surface waters decreased during
6 the 1990s in all regions investigated by Stoddard et al. (2003), except the Ridge and Blue Ridge Provinces
7 in the mid-Appalachian Mountains (Table 3-5). For other regions, the change in number of acidic systems
8 ranged from -2% in New England to -68% in the Upper Midwest.
Table 3-6. Regional trend results for long-term monitoring lakes and streams for the period 1990
through 2000 (values are median slopes for the group of sites in each region).
Region
New England Lakes
Adirondack Lakes
Appalachian Streams
Upper Midwest Lakes
Ridge/Blue Ridge Streams
S042- (jJeq/L/yr)
-1.77"
-2.26"
-2.27*
-3.36"
+0.29"
NOs" (jjeq/L/yr)
+0.01ns
-0.47"
-1.37"
+0.02ns
-0.07"
Base Cations
[Ca + Mg] (jjeq/Uyr)
-1.48"
-2.29"
-3.40"
-1.42"
-0.01ns
Gran ANC (jjeq/L/yr)
+0.11ns
+1.03"
+0.79*
+1.07"
-0.07ns
Hydrogen (jjeq/L/yr)
-0.01ns
-0.19"
-0.08*
-0.01*
+0.01ns
DOC (mg/L/yr)
+0.03*
+0.06**
+0.03ns
+0.06**
NA
Aluminum (jjg/L/yr)
+0.09ns
-1.12"
+0.56ns
-0.06ns
NA
ns Regional trend not significant (p > 0.05)
* p < 0.05
" p < 0.01
NA = insufficient data.
9
10 In summary, ANC is the most widely used measure of acid sensitivity, acidification, and chemical
11 recovery of surface waters in response to changes in acidifying deposition. ANC can be measured in the
12 laboratory by Gran titration or calculated on the basis of the difference between the base cation sum and
13 the mineral acid anion sum. Acidic waters are defined as those having ANC less than or equal to
14 zero (ieq/L. Lake and stream ANC values decreased throughout much of the 20th century in a large
15 number of acid-sensitive lakes and streams throughout the Eastern U.S. This effect has been well
16 documented in monitoring programs, paleolimnological studies, and model simulations. Since about 1990
17 the ANC of many affected lakes and streams have shown some increase, but such increases have been
18 relatively modest.
Surface Water Aluminum
19 The concentration of inorganic Al in surface waters is an especially useful indicator of acidifying
20 deposition effects because (1) it is widely toxic, and (2) it generally does not leach from the terrestrial
21 soils to surface waters in the absence of acidifying deposition (Driscoll, 1998; Lawrence, 2007), with
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1 exceptions such as acid mine drainage and relatively rare geologic deposits. Lawrence et al. (1995)
2 showed that strong organic acid anions can contribute to the mobilization of inorganic Al in combination
3 with SO42 and NO3 , but in the absence of geologic S, the presence of inorganic Al in surface waters is
4 an ambiguous indication of acidifying deposition effects.
5 Considerable work was done to define pH sensitivity ranges for a wide variety of aquatic
6 organisms, but when pH values fall below approximately 5.5, inorganic Al generally becomes the greater
7 health risk to biota. Although organically complexed Al (organic Al) can occur in surface waters as a
8 result of natural soil and hydrologic processes, this form of Al is not harmful to aquatic life (Gensemer
9 and Playle, 1999). Inorganic Al, however, has been found to be toxic to plant and animal species
10 throughout the food web (Gensemer and Playle, 1999).
11 Earlier studies demonstrated reduced growth and survival of various species offish (Baker, 1982;
12 Baker, 1996) at inorganic Al concentrations between approximately 2 and 7.5 (imol/L. Most recently,
13 20% mortality of young -of-the year brook trout was documented in situ during a 30-day period with a
14 median inorganic Al concentration of 2 (imol/L (Baldigo, 2007). This study estimated that 90% mortality
15 would occur over 30 days with a median inorganic Al concentration of 4.0 (imol/L.
16 The development of methods to fractionate Al into organic and inorganic forms (Driscoll, 1984)
17 Sullivan et al., 1986) resulted in collection of a considerable amount of data on Al concentrations in
18 surface waters in the 1980s, but most of this sampling was done either once or for a limited period of time
19 (Driscoll, 1985; Driscoll, 1987; Lawrence, 1987; Cronan et al., 1990). Available long-term trend
20 information for inorganic Al is limited. In Adirondack lakes, inorganic Al concentrations decreased
21 slightly (e.g., by 0.02 (JVI/yr to 0.18 (iM/yr; Driscoll et al., 2007a) or remained unchanged between 1982
22 and 2004 (Stoddard, 2003) Driscoll et al., 2007a). There was no trend in inorganic Al for this period in
23 New England lakes, Appalachian streams, or Midwest lakes. Monthly stream chemistry monitoring at the
24 Hubbard Brook Experimental Forest showed decreases in inorganic Al concentrations at four locations
25 along the reference stream for the experimental forest from 1982 to 2000, but no trends at two other
26 locations along this stream (Palmer, 2004).
27 Most recently, Lawrence et al. (in press) found that 49 of 195 streams (25%) in the western
28 Adirondack region had inorganic Al concentrations above 2.0 (iM during August base flow. Although
29 there is not a clear benchmark value above which inorganic Al is toxic to aquatic biota, 2 (iM is generally
30 recognized as a reasonable threshold for biological effects at a variety of trophic levels (Driscoll et al.,
31 200Ib; Baldigo, 2007).
32 In summary, inorganic Al is an important chemical indicator of the effects of acidifying deposition
33 on surface water. It has well-documented effects on aquatic biota at specific thresholds. Limited data
34 suggest that acid-sensitive regions of the Northeastern U.S. have elevated inorganic Al concentrations
35 which have been induced by years of acidifying deposition and which pose a threat to aquatic life.
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1 Concentrations have decreased slightly in some surface waters in the Northeastern U.S. during the last
2 two decades in response to decreased levels of acidifying deposition.
Quantification of Acidification
3 Changes in the acid-base status of soils and drainage waters operate on different time scales. Most
4 temperate forest soils have high exchangeable acidity, and relatively small changes in the acidity of
5 precipitation input would not be expected to have a large effect on soil acidity (Krug, 1983; Turner, 1990).
6 Therefore, recent soil acidification in affected areas appears to have been modest (c.f,, Sullivan, 2006),
7 and projected recovery of soil acid-base chemistry in response to future decreases in acidifying deposition
8 is expected to be limited (c.f,, Gbondo-Tugbawa, 2002; Sullivan, 2006). In contrast, changes in the
9 chemistry of drainage water in response to changes in acidifying deposition can occur more rapidly. This
10 is because drainage water can become acidified by the leaching of a mobile acid anion such as SO42 or
11 NO3 even if the acidity of the soil is not measurably affected (Seip, 1980; Reuss, 1986; Turner, 1990). In
12 areas (including the Northeastern U.S.) where S adsorption on soils is minimal, and therefore where SC>42
13 is highly mobile, changes in S deposition input have been shown to cause changes in the ANC and base
14 cation concentrations in lakes and streams over a time period of years to decades (Driscoll, 2003).
15 One way to quantify acidification dose-response relationships is to calculate the changes in various
16 ionic constituents in solution that occur in response to changes in mineral acid anion (SO42 and NO3 )
17 concentrations due to changes in acidifying deposition input. As [SO42~ + NO3~] increases or decreases in
18 solution, equivalent changes must also occur in the concentration of other anions (i.e., bicarbonate
19 [HCO3 ], organic acid anion [RCOCT]) or cations (i.e., hydrogen [fT] inorganic Al [AF+], sum of base
20 cations [SBC]) to maintain the charge balance. Typically, the largest counteracting change is in SBC. It is
21 generally assumed that most of the base cation change is due to Ca2+ and Mg2+. In acid-sensitive waters,
22 additional changes can occur in ANC (which can be expressed as [HCO3 -fT]), AF+, and/or RCOCT)
23 (Husar, 1991). Henriksen (1984) presented evidence for Norwegian lakes, suggesting that base cation
24 release accounted for up to a maximum of 40% of the added mineral acid anions. This proportional
25 change in base cations relative to SC>42 or [SC>42 + NO3 ] is called the F-factor:
26 Subsequently, diatom reconstructions for Adirondack lakes suggested higher F-factors, generally ranging
27 from 0.4 to greater than 1.0 (Sullivan, 1990).
28 Sullivan and Eilers (1994) compiled available data on proportional changes in SBC, ANC, and
29 AF+, relative to the observed or estimated change in [SC>42 + NO3 ]. Their analysis included: 1) measured
30 short-term ( < 20 yr) changes in drainage water chemistry in response to ambient or experimental
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1 increases or decreases in S deposition loading, 2) results of space-for-time substitution analyses, 3) results
2 of diatom inferences of past lake chemistry, and 4) MAGIC model hindcast and forecast simulations.
3 Results indicated a wide range in the estimated proportional changes in SBC as a percent of change in
4 [SC>42 + NOs ]. Estimated F-factors generally ranged from about 0.5 to 1.0, although some watersheds in
5 Norway and in the western U.S. showed F-factors as low as about 0.25. The estimated proportional
6 change in ANC was typically less than 0.3, and change in AF+ was smaller. Quantitative data were not
7 available for the organic acid anion response, but this response is also expected to generally be relatively
8 small. More recent PnET-BGC simulations for Adirondack lakes were in close agreement with the diatom
9 results Figure 3-13; Zhai, 2008), ranging from about 0.4 to 1.0.
1.5
1.0 -
o
•G
CO
0.5 -
0.0
F= -10 * ANC +0.005*ANC+0.52
R2=0.62
-50
50 100 150 200 250
ANC (ueq/L)
Source: Zhai etal. (Zhai, 2008)
Figure 3-13. F-factors calculated from PnET-BGC model results for the period 1850 to 1980 as a
function of simulated ANC in 1980 for 44 EMAP lakes in the Adirondack region of New York.
10 Measured, modeled, and inferred changes in surface water chemistry in areas that have experienced
11 relatively short-term (less than three decades) changes in acid deposition loading are available from many
12 sources. Process model hindcasts and paleolimnological reconstructions of pre-industrial surface water
13 chemistry provide insight into the extent to which individual lakes and streams have acidified over the
14 longer term. Evaluation of acidification effects from assessment of current conditions is generally not
15 helpful. This is because lakes and streams vary with respect to their expected chemistry (i.e., ANC or pH)
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1 in the absence of acidifying deposition. In many regions, pre-disturbance lake and stream ANC values
2 below 50 ueq/L and pH below 6.0 appear to have been common; in some cases, ANC below 0 and pH
3 below 5.0 also occurred. The common occurrence of lakes and streams that were naturally low in ANC
4 and pH prior to the advent of acidifying deposition is further complicated by the fact that disturbances
5 other than air pollution have contributed to further changes in acid-base status, including both ANC and
6 pH increases and decreases. Such disturbances have included logging, fire, forest regrowth, erosion, road-
7 building, forest insect infestation and disease, and other land-disturbing activities and events. Current
8 surface water chemistry is a complex function of inherent sensitivity (which to some degree was reflected
9 in pre-disturbance chemistry), levels of acidifying deposition (historic and current), and the effects of
10 other disturbance s.
11 Dose-response functions may in some cases be similar from water body to water body within a
12 defined region. For example, model simulations conducted for the NAPAP Integrated Assessment
13 (NAPAP, 1991) reported by Sullivan et al. (1992) found that, although substantial variability was found in
14 projected future change in ANC among the modeled Adirondack watersheds, there was a highly
15 consistent relationship between median change in acidifying deposition and projected median change in
16 ANC over 50 years. Each 1 kg/ha/yr change in future S deposition caused approximately a 3.5 ueq/L
17 change in simulated lakewater ANC (see Figure 3-14). Results of MAGIC model hindcast simulations
18 suggested that all of the Adirondack lakes modeled for NAPAP (NAPAP, 1991) had acidified (decreased
19 in pH or ANC) since pre-industrial times. The median and range of estimated changes in ANC were -46
20 ueq/L and -31 to -84 respectively. None of the lakes were inferred to have been acidic (ANC < 0) in pre-
21 industrial times. The minimum simulated pre-industrial values were pH 5.4 and ANC = 30 ueq/L
22 (Sullivan, 1994).
23 Historical changes in Adirondack lakewater chemistry inferred from measurements in diatoms
24 suggested somewhat more conservative estimates of historical acidification. From these data, Sullivan
25 (1990) and Sullivan et al. (1990) concluded :
26 • the "median" Adirondack lake had not acidified;
27 • acidification was generally limited to lakes that had ambient ANC during the 1980s less than
28 about 50 ueq/L (or pH less than about 6.0);
29 • approximately 15% of the Adirondack lakes were inferred to have acidified by more than 0.28
30 pH units;
31 • the median historical acidification (expressed as A ANC - A Alj) of lakes that were acidic
32 (ANC < 0) at the time of sampling was -37 ueq/L;
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1
2
approximately 3% of the Adirondack lakes were acidic in pre-industrial times, compared to
14% in the 1980s.
Source: Sullivan etal. 1992
-8 -6-4-20 2 4
Median Change in Sulfur Deposition (kg/ha/yr)
Figure 3-14. Median and range of
projected change in ANC (ueq/L) of
Adirondack lakes for 50-year
MAGIC simulations versus median
future change in sulfur deposition
(kg/ha/yr) for each deposition
scenario (points on each line
correspond to -50%, -30%, -20%,
0%, +20%, +30% change from
current deposition).
3 These paleolimnological estimates suggested that Adirondack lakes that were acidic in the 1980s
4 had decreased a median of about 4 ueq/L in [ANCG - Al;] for each kg/ha/yr change in S deposition. This
5 was slightly more than one-half of the median historical rate of acidification projected by MAGIC
6 (7 ueq/L of calculated ANC for each kg/ha/yr) for acidic Adirondack lakes (Sullivan, 1992).
7 In comparing estimates, derived from different approaches, of past and future changes in
8 Adirondack lakewater chemistry in response to acidifying deposition, it is important to consider several
9 factors (Sullivan, 1992):
10 • Chemical changes estimated from paleolimnology or monitoring data incorporate all
11 influences on the acid-base chemistry of lakewater, including land use, disturbances, and
12 climatic differences. Model estimates commonly include only postulated or estimated changes
13 in acidifying deposition as having influenced the lakewater chemistry. Because watershed
14 disturbances generally cause an increase in surface water ANC, they may partially explain the
15 more conservative estimates of diatom-inferred acidification compared with MAGIC model
16 estimates of acidification.
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1 • The use of a process-based model for hindcasting requires assumptions regarding historical
2 deposition of all major ions. In addition to uncertainties regarding historical sulfur deposition
3 levels, base cation deposition has also likely changed by an unknown amount, and the degree
4 to which sulfur and base cation deposition have been coupled is unclear (Driscoll, 1989; Chen,
5 1989).
6 • Organic acids may have exerted a greater influence on lakewater pH during pre-industrial
7 times than they do currently because DOC and organic acid anion concentrations may have
8 decreased in response to increased organic acid protonation and increased concentrations of Al
9 (Aimer, 1974; Krug, 1983; Davis, 1985; Kingston, 1990).
10 • Data sets from different points in time are often not directly comparable because of differences
11 in ANC definition or pH measurement. For example, the calculated ANC used by MAGIC
12 differs from titrated ANC (ANCG) used to calibrate paleolimnological transfer functions and
13 reported in surveys. The differences are due to the partially counteracting influences of Al and
14 organic acids on ANCG and their omission from calculated ANC. These differences can be
15 appreciable for acidic and low-ANC waters (Sullivan, 1989).
16 There is not a clear definable relationship between atmospheric S deposition and ecological effects.
17 A given amount of S deposition can cause a wide range of ecological responses, from no ecological effect
18 to varying levels of adverse ecological effect. These can include changes in community composition, loss
19 of sensitive species, reduced biological diversity, and altered ecosystem functions. Such effects can occur
20 in both aquatic and terrestrial ecosystems. The observed wide range of responses within and among
21 regions is attributable to varying ecosystem sensitivity. Some soils (notably in many watersheds in the
22 southeastern U.S.) have the capacity to adsorb substantial quantities of S, with essentially no acidification
23 of drainage water. Nevertheless, there is a finite limit to this S adsorption capacity, and under continual
24 high S deposition loading, the adsorptive capacity of soil will eventually become depleted.
25 In addition to differences in S adsorption capacity of soils, watersheds also differ in their sensitivity
26 to acidification effects as a consequence of differing sensitivity of the species that make up the local
27 biological community. Some species of fish, aquatic insects, and mollusks, for example, are highly
28 sensitive to adverse effects from low pH and high inorganic Al concentrations; others are less sensitive.
29 Finally, watersheds differ in the size of the soil base cation pool available to neutralize deposited mineral
30 acidity. Some watersheds have sufficient quantities of base cations in their soils such that drainage waters
31 will remain well buffered, even under relatively high S deposition loads, for many decades or longer.
32 Other watersheds had relatively low base cation supply during preindustrial times due to low weathering
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1 rates of the underlying geology, and the base cation supply may have been further depleted by past
2 acidifying deposition.
3 As a consequence of these, and other, differences in sensitivity to S inputs, watersheds differ in the
4 extent to which they acidify in response to a given amount of S deposition and they also differ in the
5 extent to which that acidification translates to biological effects. Thus, one cannot specify a level of S
6 deposition that would be likely to cause adverse effects across the landscape. Sensitivity differs from
7 watershed to watershed.
8 Despite these differences in watershed sensitivity to acidification, it is possible to place bounds on
9 the amount of acidification that has occurred in response to a given change in S deposition. Such
10 quantitative estimates of acidification have been derived using watershed models of acidification
11 response. Modeling results summarized in Table 3-7 illustrate a wide range in the model estimates of past
12 acidification of acid-sensitive lakes and streams in the eastern U.S.
Table 3-7. Model estimates of long-terms S deposition load required to achieve certain surface
water quality criteria (ANC above 0, 20, or 50 eq/L) in different endpoint years (approximately 2040
or 2100) and estimates of historic acidification in response to S deposition.
Region
Adirondacks, NY
Adirondacks, NY
Adirondacks, NY
Adirondacks, NY
Adirondacks, NY
Adirondacks, NY
Shenandoah NP,
VA
Shenandoah NP,
VA
Loch Vale, Rocky
Mt. N.P., CO
Loch Vale, Rocky
Mt. N.P., CO
Resource Description
Median of population of lakes within
region having current ANC < 200
ueq/L
Median of population of lakes within
region having current ANC < 200
ueq/L
10th percentile of lakes within region
having current ANC < 200 ueq/L
10th percentile of lakes within region
having current ANC < 200 ueq/L
25th percentile of lakes within region
having current ANC < 200 ueq/L
25th percentile of lakes within region
having current ANC < 200 ueq/L
Median of streams on siliciclastic
lithology
Most sensitive stream
The Loch
Andrews Creek
Deposition Load (kg S/ha/yr) to Maintain
Surface Water ANC Above1
Approach ° H«l'L 20 ueq/L 50 ueq/L
In the Year
2040/2100 2040/2100 2040/2100
MAGIC
PnET-
BGC
MAGIC
PnET-
BGC
MAGIC
PnET-
BGC
MAGIC 15/12 8/9 <0/3
MAGIC 9/9 8/6 <0/1
MAGIC 11.1/ND 7.8/ND 2.8/ND
MAGIC 8.1/ND 4.6/ND <0/ND
Estimate of Acidification (AANC)
Since Pre-lndustrial Period
(ueq/L)
25
27
39
62
36
39
71
69
28
Reference
(Sullivan etal.
2006, 2007)
(Sullivan etal.
2006)
(Sullivan etal.
2006, 2007)
(Sullivan etal.
2006)
(Sullivan etal.
2006, 2007)
(Sullivan etal.
2006)
Sullivan etal.
(2008)
Sullivan et al.
(2008)
(Sullivan etal.
2005)
(Sullivan et al.
2005)
13
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Summary of Biogeochemistry and Chemical Effects
1 The evidence is sufficient to infer a causal relationship between acidifying deposition and
2 changes in biogeochemistry related to aquatic ecosystems. The strongest evidence for a causal
3 relationship comes from studies of changes in surface water chemistry including concentrations of SC>42 ,
4 NOs , inorganic Al, and Ca, surface water pH, sum of base cations, ANC, and base cation surplus. Surface
5 water chemistry integrates the sum of upstream soil and water processes and reflects the results of
6 watershed-scale terrestrial effects of S and N deposition including, N saturation, forest decline, and soil
7 acidification (Stoddard, 2003). In many cases, surface water chemistry indicates the effects of
8 acidification on biotic species and communities found in fresh water ecosystems.
9 Surface water chemistry can be examined and reported as chronic chemistry or episodic chemistry.
10 Chronic chemistry refers to annual average conditions, which are often represented as summer and fall
11 chemistry for lakes and as spring baseflow chemistry for streams. Episodic chemistry refers to conditions
12 during rainstorms or snowmelt when proportionately more drainage water is routed through upper soil
13 horizons, which tend to provide less neutralizing of atmospheric acidity as compared with deeper soil
14 horizons. Surface water chemistry has lower pH and ANC during storm runoff or snowmelt than during
15 baseflow conditions. One of the most important effects of acidifying deposition on surface water
16 chemistry is the short-term change in chemistry that is termed "episodic acidification." Some streams may
17 have chronic or average chemistry that is suitable for aquatic biota, but be subject to occasional episodic
18 acidification with lethal consequences. Episodic declines in pH and ANC are nearly ubiquitous in
19 drainage waters throughout the Eastern U.S. caused partly by acidifying deposition and partly by natural
20 processes.
21 Acidification effects on aquatic biota are often evaluated using measures of either Al or pH. ANC is
22 also used because it is an indicator of buffering capacity (although ANC does not relate directly to the
23 health of biota). The usefulness of ANC lies in the association between ANC and the surface water
24 constituents that directly contribute to or ameliorate acidity-related stress, in particular pH, Ca, and
25 inorganic Al.
SO42~, NO3~, and Base Cations
26 Changes in water chemistry resulting from acidifying deposition typically include changes in
27 SO42 , NO3 , and base cation concentrations. Each plays an important role in the acid-base chemistry of
28 water, but none are directly toxic at concentrations commonly encountered in natural waters.
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1 • SO42 is the primary inorganic anion found in most acid sensitive waters. Continued decreases
2 in S emissions should cause further decreases in SO42 concentrations in surface waters.
3 However the rate of decrease in surface water SO42 concentrations may be delayed as
4 accumulated S leaches from watershed soils in some regions of the country, especially the
5 Blue Ridge Mountains.
6 • The importance of NO3 as an agent of acidification varies by region, but it is particularly
7 important during periods of high hydrologic flow from soils to streams such as those that occur
8 during snowmelt and rain runoff. The relationship between N deposition and surface water
9 NO3 concentration is complex and involves the terrestrial and aquatic cycling of N and other
10 elements. NO3 contributes to the acidity of many lakes and streams in the eastern U.S., but
11 there is no apparent relationship between recent trends in N deposition and trends in NO3
12 concentrations in these surface waters (in contrast to observed responses for S deposition and
13 SO42 concentrations). This suggests that the time scales of N saturation may be longer than
14 previously considered (e.g., centuries rather than decades). Nevertheless, long-term retention
15 of N deposited in forested regions and consequent dampening of deposition effects on surface
16 waters is unlikely to continue indefinitely (Aber, 2003).
17 • Decreases in base cation concentrations in Eastern U.S. surface waters over the past two to
18 three decades are ubiquitous and are closely tied to trends in SO42 concentrations. Rates of
19 base cation depletion have been similar to those for SO42 plus NO3 in most areas
20 (Shenandoah National Park is a notable exception). Decreasing trends in base cation
21 concentrations do not necessarily indicate further acidification or recovery of surface waters,
22 but may indicate either lower base cation leaching rates in soils or depletion of base cations
23 from the soil system.
pH, Acid Neutralizing Capacity, and Aluminum
24 Acidification of surface water causes changes in pH, ANC, and inorganic aluminum concentration.
25 Low pH and high inorganic aluminum concentration can be directly toxic to aquatic biota.
26 • The pH of freshwater streams and lakes is a common measure used to link acidification to
27 adverse effects on aquatic biota. Decreases in pH below values of 6.0 typically result in species
28 loss of benthic invertebrates, plankton species, and fish. A number of synoptic surveys
29 indicated loss of species diversity and absence of several fish species in the pH range of 5.0 to
30 5.5. If pH decreases to lower values, there is a greater likelihood that more aquatic species
31 could be lost without replacement, resulting in decreased richness and diversity. (See the
32 following discussion on biota).
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1 • ANC reflects the difference between base cations and anions of strong acids in solution and is
2 the most widely used measure of acid sensitivity, acidification, and chemical recovery of
3 surface waters in response to changes in acidifying deposition. Acidic waters are defined as
4 those having ANC equal to or below zero. Waters with ANC of < 50 (ieq/L are considered
5 "extremely acid sensitive" (Schindler, 1988) and are vulnerable to episodic acidification
6 (DeWalle et al., 1987; Eshleman, 1988. Lake and stream ANC values decreased throughout
7 much of the 20th century in a large number of acid-sensitive lakes and streams throughout the
8 Eastern U.S. Since about 1990, the ANC of many affected lakes and streams has increased
9 slightly. The number of acidic surface waters has decreased in some areas of the Northeast, but
10 not in the mid-Appalachian Mountains.
11 • Dissolved inorganic Al is an important chemical indicator of the effects of acidifying
12 deposition on surface water because it is toxic to aquatic life and generally does not leach from
13 soils in the absence of acidification. When pH falls below approximately 5.5, inorganic Al
14 generally becomes a greater health risk to biota. Limited data suggest that acid-sensitive
15 regions of the Northeastern U.S. have elevated inorganic Al concentrations in surface waters
16 induced by years of acidifying deposition, posing a threat to aquatic life. Concentrations have
17 decreased slightly in some surface waters in the northeastern U.S. during the last two decades
18 in response to decreased levels of acidifying deposition.
3.2.3.2. Biological Effects
19 Aquatic effects of acidification have been well studied in the U.S. and elsewhere at various trophic
20 levels. These studies indicate that aquatic biota have been affected by acidification at virtually all levels of
21 the food web in acid sensitive aquatic ecosystems. Effects have been most clearly documented for fish,
22 aquatic insects, other invertebrates, and algae.
23 Biological effects are primarily attributable to a combination of low pH and high inorganic Al
24 concentration. Such conditions occur more frequently during rainfall and snowmelt that cause high flows
25 of water and less commonly during low-flow conditions, except where chronic acidity conditions are
26 severe. Biological effects of episodes include reduced fish condition factor, changes in species
27 composition, and declines in aquatic species richness across multiple taxa, ecosystems and regions. These
28 conditions may also result in direct mortality as was shown from results of in situ bioassays (Van Sickle et
29 al. 1996). High concentrations of Ca, and to a lesser extent other base cations, can lessen the toxicity of
30 low pH and high inorganic Al concentration where they occur (Baker et al., 1990).
31 Biological effects in aquatic ecosystems can be divided into two major categories: (1) effects on
32 health, vigor, and reproductive success; and (2) effects on biodiversity. The first category includes
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1 changes in biological indicators such as individual condition factor and recruitment success. The latter
2 can be described by changes in species composition and taxonomic richness.
3 The following sections define concepts used to measure and evaluate acidification-related effects
4 on aquatic biota. We present measures of changes in (1) health, vigor, and reproductive success, and (2)
5 biodiversity for fish. Finally, the general effects literature is summarized for phytoplankton, zooplankton,
6 benthic invertebrates, amphibians, and fish-eating birds. Specific reference is made to the biological
7 indicators outlined above where such information exists.
Measures of Health, Vigor, and Reproductive Success
8 There are few measures of the effects of acidification on the health, vigor, and reproductive success
9 of aquatic species. Condition factor is one measure of sublethal acidification stress that has been used to
10 quantify effects of acidification on an individual fish. Condition factor is an index that describes the
11 relationship between fish weight and length. Expressed as fish weight/length3, multiplied by a scaling
12 constant, this index reflects potential depletion of stored energy (Everhart and Youngs, 1981; Goede and
13 Barton, 1990; Dennis, 1995). Condition factor is interpreted as depletion of energy resources such as
14 stored liver glycogen and body fat in response to increased stress at sublethal levels (Goede and Barton,
15 1990). Fish with higher condition factor are more robust than fish having low condition factor. Field
16 studies have shown lower condition factor in fish found in more acidic streams (Dennis, 1995).
Measures of Biodiversity
17 Species composition refers to the mix of species that are present in a particular ecosystem.
18 Acidification alters species composition in aquatic ecosystems. There are a number of species common to
19 many oligotrophic waters that are sensitive to acidifying deposition and that cannot survive, compete, or
20 reproduce in acidic waters. In response to small to moderate changes in acidity, acid-sensitive species are
21 often replaced by other more acid-tolerant species, resulting in changes in community composition, but
22 little or no change in total community abundance or biomass. The extent of alteration of surface water
23 biological community composition increases as surface waters become more acidic. There is also a
24 common pattern of lower community diversity with increased acidification.
25 One important tool that aids in the determination of effects on species composition is the Acid
26 Stress Index (ASI) developed by Baker et al. (1990a). This index uses fish bioassay survival data to
27 predict the probability offish survival expressed as a percent mortality. Separate ASI models were
28 developed for tolerant, intermediate, and sensitive fish species.
29 Taxonomic richness is a metric that is commonly used to quantify the effects of an environmental
30 stress on biota. It can be applied at various taxonomic levels. For example, the number offish species
31 present in a lake or stream can be used as an index of acidification (cf. Bulger, 1999). Similarly,
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1 acidification effects on aquatic insects can be evaluated on the basis of the number of families or genera
2 of mayflies (order Ephemeroptera) (Sullivan, 2003). In the latter cases, the mayfly order was selected for
3 study because it includes a number of genera and species having varying degrees of sensitivity to
4 acidification.
5 Decreases in ANC and pH and increases in inorganic Al concentration have been shown to
6 contribute to declines in species richness and abundance of zooplankton, macroinvertebrates, and fish
7 (Schindler, 1985; Keller, 1995). Species richness is positively correlated with pH and ANC (Rago and
8 Wiener, 1986; Baker et al., 1990b) primarily because of the elimination of acid-sensitive species at lower
9 pH and ANC (Schindler, 1985). Interpretation of species richness can be difficult because more species
10 tend to occur in larger lakes and streams as compared with smaller ones, irrespective of acidity (Sullivan,
11 2003). Nevertheless, decreases in species richness have been observed for all major trophic levels of
12 aquatic organisms (Baker et al., 1990a), even after adjusting for lake size (Harvey and Lee, 1982; Frenette
13 et al., 1986; Rago and Wiener, 1986; Schofield, 1987) Matuszek and Beggs, 1988).
Health, Vigor, and Reproductive Success of Fish
14 Fish populations in acidified streams and lakes of Europe and North America have declined, and
15 some have been eliminated as a result of atmospheric deposition of acids and the resulting changes in
16 water quality (Baker et al., 1990a). A variety of water chemistry variables, including inorganic Al,
17 dissolved OC, and Ca, along with the timing and magnitude of episodic fluctuations in toxic acid and
18 inorganic Al concentrations, are related to the degree to which surface water acidification influences fish
19 survival in natural systems (Baker et al., 1990c; Gagen et al., 1993; Siminon et al., 1993; Van Sickle et al.,
20 1996; Baldigo, 1997).
21 The effects of acidification on the health, vigor, and reproductive success are manifested through a
22 range of physiological effects on individual life stages and fish species. The primary mechanism for the
23 toxic effects of low pH and elevated inorganic Al on fish involves disruption of normal ion regulation at
24 the gill surface, resulting in increased rates of ion loss and inhibition of ion uptake (McWilliams and
25 Potts, 1978; Leivestad, 1982; Wood and McDonald, 1987; Bergman et al., 1988). Additional effects might
26 include (1) disruption of Ca metabolism (Peterson and Martin-Robichaud, 1986; Gunn and Noakes, 1987;
27 Reader et al., 1988), and (2) decreased hatching success (Runn et al., 1977; Peterson et al., 1980; Haya
28 and Waiwood, 1981; Waiwood and Haya, 1983).
29 There is marked variability among species, and among life stages within species, in the specific
30 levels of pH and inorganic Al that produce measurable responses. In general, early life stages are more
31 sensitive to acidic conditions than the young-of-the-year, yearlings, and adults (Baker, 1985; Johnson,
32 1987; Baker et al., 1990a). Also, small fish, especially swim-up fry, are probably less mobile and less able
33 to avoid exposure to adverse chemical conditions than the relatively larger adults (Baker, 1996).
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1 Here, effects are described by life stage. Several studies have shown that the earliest reproductive
2 stages are highly sensitive to low pH. The processes of oogenesis and fertilization in fish are especially
3 sensitive (Muniz, 1991; Havas et al, 1995), most likely due to adverse effects on the female spawner. For
4 instance, Beamish (1976) reported that reduced serum and plasma Ca in female fish in acidified Canadian
5 lakes caused a higher probability of failure in producing viable eggs. Depletion of Ca from bone and
6 increased numbers of females with unshed eggs have also been linked to acidification at this life stage (cf
7 Rosseland, 1986; Muniz, 1991).
8 After fertilization, the embryo seems to be susceptible to acidic waters throughout the whole period
9 of development, although periods shortly after fertilization and prior to hatching seem to be most critical
10 (Rosseland, 1986). The susceptibility of the embryo can be the result of direct exposure to elevated
11 hydrogen ion concentrations and also to the toxic effects of inorganic Al at intermediate pH-values. Low
12 pH in the surrounding water also results in pH-depression inside the egg, leading to either prolongation of
13 hatching or to reduced hatching success (Rosseland, 1986). Eggs lying in gravel on stream and lake beds
14 are, to some extent, protected from exposure to rapid changes in pH (Gunn and Keller, 1984b; Lacroix,
15 1985). Nevertheless, they can experience high mortality during periods of acid runoff, such as snowmelt
16 (Gunn and Keller, 1984a). Yellowstone cutthroat trout (O. c. bouveri) were exposed to 7-day pH
17 depressions by Farag et al. (1993). Of the four life stages studied, eggs were most sensitive to low pH.
18 Eggs exposed for seven days to pH 5.0 test water showed a statistically significant reduction in survival
19 compared with eggs exposed for seven days to pH 6.5 water. Survival of alevin and swim-up larvae were
20 significantly reduced from near 100% at pH 6.5 to near 0% at pH 4.5. Intermediate pH values (6.0, 5.5) in
21 all cases showed reduced survival compared with the control (6.5), but not by statistically significant
22 amounts (p > 0.05).
23 Emergent alevins show susceptibility to the adverse effects of inorganic Al and hydrogen ion that
24 increases with age (Baker, 1982). Rosseland (1986) indicated that this increasing sensitivity results from
25 changes that take place in the respiratory system. Shortly after hatching, alevins still respire through their
26 skin but gradually gills become the primary organ of gas and ion exchange. Gills are the locus for
27 interference of hydrogen ion and inorganic Al with iono-regulatory exchange.
28 Woodward et al. (1989) exposed cutthroat trout (Oncorhynchus clarM) from the Snake River in
29 Wyoming to pH depressions from pH 4.5 to 6.5 in the laboratory and found that reductions in pH from 6.5
30 to 6.0 in low-Ca water (70 (ieq/L) did not affect survival, but did reduce growth of swim-up larvae. The
31 eggs, alevin, and swim-up larval stages showed significantly higher mortality at pH 4.5 than at pH 6.5.
32 Mortality was also higher at pH 5.0 than at pH 6.5, but only statistically higher for eggs. The authors
3 3 concluded that the threshold for effects of acidity on greenback cutthroat trout in the absence of inorganic
34 Al was pH 5.0 (Woodward, 1991).
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1 In juvenile, young-of-year and adult fish there is an energy cost in maintaining physiological
2 homeostasis; the calories used to respond to stress are a part of the fish's total energy budget and are
3 unavailable for other functions, such as growth and reproduction (Schreck, 1981, 1982; Wedemeyer et al.,
4 1990). Observed differences in condition factor may occur because maintenance of internal chemistry in
5 the more acidic streams would require energy that otherwise would be available for growth and weight
6 gain (Dennis and Bulger, 1999; Sullivan et al., 2003). The energy costs to fish for active iono-
7 osmoregulation can be substantial (Farmer and Beamish, 1969; Bulger, 1986).
8 Prominent physiological disturbances to fish exposed to acid waters are iono- and osmoregulatory
9 failure, acid-base regulatory failure, and respiratory and circulatory failure. Most of these effects can be
10 directly attributed to effects on gill function or structure. The acute toxicity of low pH in acidic waters
11 results in the loss of Ca from important binding sites in the gill epithelium, which reduces the ability of
12 the gill to control membrane permeability (McDonald, 1983; Havas, 1986; Exley and Phillips, 1988). Al
13 has been shown to accumulate on the gill surface when fish are exposed to water having high inorganic Al
14 concentration.
15 Cumulative sublethal physiological effects can be expressed by changes in condition factor.
16 Condition factor has been developed and applied mainly for blacknose dace. This fish species is widely
17 distributed in Appalachian Mountain streams and is moderately tolerant of low pH and ANC, relative to
18 other fish species in the region. However, the condition factor concept is probably applicable to other
19 species as well. Condition factor may be a useful metric for many species in aquatic ecosystems that are
20 only marginally affected by acidification. Bulger et al. (1999) observed a positive relationship between
21 dace condition factor and pH in streams in Shenandoah National Park. Dennis and Bulger (1995) found a
22 reduction in the condition factor for blacknose dace in waters near pH 6.0. The four populations with the
23 lowest condition factor had mean habitat pH values within or below the range of critical pH values at
24 which Baker and Christensen (1991) estimated that negative population effects are likely for the species.
25 The mean condition factor offish from the study stream with the lowest ANC was about 20% lower than
26 that of the fish in best condition. In addition to effects on blacknose dace, condition factor, reduced
27 growth rates have been also attributed to acid stress in a number of other fish species, including Atlantic
28 salmon (Salmo salaf), chinook salmon (Oncorhynchus tshawytscha), lake trout (Salvelinus namaycush),
29 rainbow trout (Oncorhynchus mykiss), brook trout, brown trout (Salmo trutta), and arctic char (Salvelinus
30 alpines) (Baker et al., 1990a).
31 In summary, some studies have been conducted on changes in the health, vigor, and reproductive
32 success offish exposed to water having low pH and high inorganic Al concentration. Blacknose dace
33 have been most thoroughly studied regarding the sublethal effects of acidity on fish condition. Effects
34 tend to vary by life stage; early life stages tend to be particularly sensitive. Adverse effects often involve
35 disruption of gill function, partly due to Al toxicity.
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Fish Biodiversity
1 Biodiversity loss is a predictable consequence of acidification and there are abundant examples of
2 this in North America and Europe, mostly focused on fish (cf. Bulger, 2000). Population-level fish
3 response to acidification is primarily through recruitment failure, a result of increased mortality of early
4 life stages or indirect effects through the food chain (loss of prey species). Changes in inorganic Al, pH,
5 and Ca most likely have the greatest influence on fish community structure. These changes in water
6 chemistry can alter species composition and species richness, both of which are components of
7 biodiversity.
8 By 1990, it was well established that changes in pH in the range of 4.0 to 6.5 could cause
9 significant adverse biological effects on fish community composition. As described above, the toxicity of
10 low pH was, in most cases, the result of impaired body salt regulation. Decreased water pH inhibited the
11 active uptake of Na+ and Cl and stimulated the passive loss of these ions from the bloodstream (Baker
12 et al., 1990a). Species vary in terms of their sensitivity to such disruptions of physiological condition.
13 The response offish to pH, ANC, and inorganic Al is not uniform across species. A number of
14 synoptic surveys indicated loss of species diversity and absence of several fish species in the pH range of
15 5.0 to 5.5. If pH is lower, there is a greater likelihood that more fish species could be lost without
16 replacement, resulting in decreased richness and diversity. In general, populations of salmonids are not
17 found at pH levels less than 5.0, and smallmouth bass (Micropterus dolomieu) populations are usually not
18 found at pH values less than about 5.2 to 5.5. Bioassay experiments using brook trout eggs and fry have
19 demonstrated greater mortality in chronically acidic stream water as compared to water having higher
20 ANC.
21 The ASI is an index of acidification that uses fish bioassay survival data fitted to a regression
22 model of exposure to water chemistry (pH, Al, and Ca) to predict the probability offish survival.
23 Approximate ASI reference levels were reported by Baker et al. (1990c) for various fish species, based on
24 logistic regression offish presence as a function of the sensitive, intermediate, and tolerant ASI values for
25 brown bullhead (Ameiurus nebulosus), brook trout, lake trout, and common shiner (Luxilus cornutus).
26 Fish species richness is an important indicator of acidification response, in part because the public
27 tends to place relatively high value on fisheries. As discussed in the previous section, lakes and streams
28 having pH below about 5.0 or ANC below about 0 generally do not support fish. There is often a positive
29 relationship between pH and number offish species, at least for pH values between about 5.0 and 6.5, or
30 ANC values between about 0 and 50 to 100 (ieq/L (Bulger, 1999; Cosby, 2006)Sullivan et al., 2006a).
31 Such observed relationships are complicated, however, by the tendency for smaller lakes and streams,
32 having smaller watersheds, to also support fewer fish species, irrespective of acid-base chemistry. This
33 pattern may be due to a decrease in the number of available niches as stream or lake size decreases.
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1 Nevertheless, fish species richness is relatively easily determined and is one of the most useful indicators
2 of biological effects of surface water acidification.
3 Some of the most in-depth studies of the effects of acid stress on fish species richness have been
4 conducted in the streams in Shenandoah National Park, Virginia and the lakes in the Adirondack
5 Mountains, New York. These regions are examined in detail below. However, note that effects on fish
6 species richness have also been documented in acid-sensitive streams of the Catskill Mountains of
7 southeastern New York (Stoddard, 1991) and the Appalachian Mountains from Pennsylvania to Tennessee
8 and South Carolina (SAMAB, 1996; Bulger, 1999; Bulger, 2000).
9 The Shenandoah National Park Fish in Sensitive Habitats (FISH) Project evaluated the effects of
10 streamwater acidification on fish communities in streams in Shenandoah National Park (Bulger,
11 1995)Dennis et al., 1995; Dennis, 1995)MacAvoy and Bulger, 1995). A statistically robust relationship
12 between stream ANC and fish species richness was documented. Numbers offish species were compared
13 among 13 Shenandoah National Park streams spanning a range of pH and ANC conditions. There was a
14 highly significant (p < 0.0001) relationship between stream acid-base status (during the 7-year period of
15 record) and fish species richness among the 13 streams. The streams with the lowest ANC hosted the
16 fewest species (Figure 3-15). The 3-year FISH study of stream acidification demonstrated negative
17 effects on fish from both chronic and episodic acidification (Bulger, 1999). Bulger et al. (1999) concluded
18 that the most important cause of the observed decline in species richness with decreasing ANC was acid
19 stress from acidification. However, an additional causal factor may have been a decrease in the number of
20 available aquatic niches when moving from downstream locations (which are seldom low in pH and
21 ANC) to upstream locations (which are often low in pH and ANC in this region; Sullivan et al., 2003).
22 South of Shenandoah National Park, the effects of surface water acidification on fish species
23 richness have been studied in some detail in the St. Marys River in Virginia. Fish species richness was
24 closely associated with surface water acid-base chemistry. The number offish species in the St. Marys
25 River within the wilderness declined from 12 in 1976 to 4 in 1998. Three of the four species present in
26 1998 (brook trout, blacknose dace, fantail darter [Etheostoma flabellare} are tolerant of low pH and are
27 typically the only fish species present in streams having similar levels of acidity in nearby Shenandoah
28 National Park (Bulger, 1999).
29 Dynamic water chemistry model projections have been combined with biological dose-response
30 relationships to estimate declines in fish species richness with acidification. A relationship derived from
31 the Shenandoah National Park data was used by Sullivan et al. (2003), along with stream ANC values
32 predicted by the MAGIC model to provide estimates of the expected number offish species in each of the
33 modeled streams for the past, present and future chemical conditions simulated for each stream. Results
34 suggest that historical loss of species had been greatest in the streams located on the most sensitive
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1 geological class (siliciclastic bedrock; 1.6 species lost), with fewer lost species on granitic bedrock and
2 basaltic bedrock (average of 0.4 species lost).
9
8
7
6
'o
= 2
I
*
i
M I ft
fflt I ttl
-25 0 25 50 75 100 125 150 175 200 225 250 275 300
Average ANC (peq/L)
Source: Redrawn from Bulger etal. (1999)
Figure 3-15. Number of fish species as a function of mean stream ANC among 13 streams in
Shenandoah National Park, Virginia. Values of ANC are means based on quarterly measurements,
1987-1994. The regression analysis showed a highly significant relationship (p < 0.0001) between
mean stream ANC and number of fish species. Streams having ANC consistently < 50 peq/L had
three or fewer species.
3 In the Adirondack Mountains, lakewater acidification and the associated elevated concentrations of
4 inorganic Al have adversely affected fish populations and communities in sensitive areas (Baker and
5 Schofield, 1982; Johnson, 1987; Schofield, 1987) Baker et al., 1990b; Siminon et al., 1993). Of the 53
6 fish species recorded in Adirondack lakes by the Adirondack Lakes Survey Corporation, about half (26
7 species) were absent from lakes with pH below 6.0. Among the absent species were several important
8 recreational species (Baker et al., 1990b), plus ecologically important minnows that serve as forage for
9 sport fish. Fully 346 of 1,469 lakes surveyed supported no fish at all at the time of the survey. These lakes
10 were significantly lower in pH, dissolved Ca, and ANC, and had higher concentrations of inorganic Al
11 than lakes hosting one or more species offish (Gallagher, 1990). Among lakes with fish, there was an
12 unambiguous relationship between the number offish species and lake pH, ranging from about one
13 species per lake for lakes having pH less than 4.5 to about six species per lake for lakes having pH higher
14 than 6.5 (Baker et al., 1990b; Driscoll et al., 200la).
15 High-elevation lakes are more likely to be fishless than larger lakes at low elevation (Gallagher,
16 1990). This observation has been attributed to the fact that high elevation lakes tend to have poor access
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1 for fish immigration, poor fish spawning substrate, or low pH, or they may be susceptible to periodic
2 winter kills. Small, high-elevation Adirondack lakes with fish also had significantly higher pH compared
3 with fishless high-elevation lakes; acidity is likely to play an important role in the absences offish from
4 such lakes (Driscoll et al, 200Ib).
5 Sullivan et al. (2006a) developed a relationship between fish species richness and ANC class for
6 Adirondack lakes. Under chronically acidic conditions (summer index or annual average
7 ANC < 0 (ieq/L), Adirondack lakes are generally without fish. There was a marked increase in mean
8 species richness with increases in ANC up to values of approximately 50 to 100 (ieq/L (Figure 3-16). The
9 asymptote for the fish species equation was 5.7 species. This analysis suggests that there could be loss of
10 fish species with decreases in ANC below approximately 50 to 100 (ieq/L. The response functions from
11 Shenandoah National Park (Figure 3-15) and the Adirondack Mountains (Figure 3-16) are generally
12 similar at low ANC values, below about 100 ueq/L. Fish species richness was somewhat higher in
13 Shenandoah National Park at higher ANC values. The reasons for this difference are not known.
14-
0)
0.
w
12-
10-
8-
6-
o 4-
-4-
i l
-200
-100
100
200
300
400
500
ANCdjeq/L)
Source: Sullivan etal.(2006a)
Figure 3-16. Number of fish species per lake versus acidity status, expressed as ANC, for
Adirondack lakes. The data are presented as mean (filled circles) and range (bars) of species
richness within 10 peq/L ANC categories, based on data collected by the Adirondack Lakes Survey
Corporation.
14 The absence offish from a given lake or stream in an area that experiences surface water
15 acidification does not necessarily imply that acidification is responsible for the absence of fish. For
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1 example, results of fisheries research in the Adirondacks has indicated that many Adirondack lakes
2 always had marginal spawning habitat for brook trout (Schofield, 1993). However, multivariate regression
3 of the presence or absence of brook trout in Adirondack waters produced a ranking of factors that
4 appeared to influence the presence of brook trout when biological factors (stocking, presence of
5 associated species, presence of competitors) were excluded from the analysis. Among contributing
6 factors, including silica (Si), ANC, dissolved OC, substrate type, and distance to the nearest road, pH
7 ranked first as a predictor of brook trout presence (Christensen et al., 1990). The results of this analysis
8 supported the conclusion that 1990 levels of pH and related variables restricted the distribution offish in
9 some Adirondack lakes.
10 In summary, acidic conditions characterized by low pH, low ANC, and high inorganic Al exert
11 considerable influence on the fish species composition of sensitive surface waters, particularly in the
12 eastern U.S. Low pH and ANC, and high inorganic Al concentrations, contribute to loss of the most acid-
13 sensitive fish species. Species richness is a common indicator used to reflect the effects of water
14 acidification on aquatic biota. This index is most often applied to fish. Few or no fish species are found in
15 lakes and streams that have very low ANC (near zero) and low pH (near 5.0). The number of fish species
16 generally increases at higher ANC and pH values. This relationship is complicated, to some extent, by the
17 tendency of smaller lakes and streams (which are more likely to have low ANC and pH) to host fewer fish
18 species, regardless of acid-base chemistry. Nevertheless, available data strongly suggest that acid stress is
19 a major factor governing the observed relationship between fish species richness and surface water
20 acidity.
Summary of Biological Effects
21 The evidence is sufficient to infer a causal relationship between acidifying deposition and
22 Changes in aquatic biota. The strongest evidence for a causal relationship comes from studies of aquatic
23 systems exposed to elevated levels of acidifying deposition that support fewer species of fishes,
24 macroinvertebrates, and diatoms. Although there are few studies of the response of higher trophic levels
25 to pH changes resulting from acidifying deposition, piscivorous birds are known to be affected by
26 acidifying deposition. Consistent and coherent evidence from multiple species and studies shows that
27 acidification can result in the loss of acid-sensitive species, and more species are lost with greater
28 acidification. Biological effects are linked to changes in water chemistry including ANC, pH, and Al.
29 Decreases in ANC and pH and increases in inorganic Al concentration contribute to declines in taxonomic
30 richness of zooplankton, macroinvertebrates, and fish. Chemical changes can occur over both long- and
31 short-term time scales, with additional effects on biological systems. Short-term (hours or days) episodic
32 changes in water chemistry can have biological effects, including reduced fish condition factor, changes
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1 in species composition, and declines in aquatic species richness across multiple taxa, ecosystems and
2 regions.
Species
3 • Logistic regression modeling showed that the occurrence of two piscivorous birds (common
4 loons and common mergansers) is positively related to the pH of lakes in the Algoma region of
5 Ontario. Model estimates suggested that the number of lakes projected to be suitable for
6 supporting breeding pairs and broods of these bird species increased with increasing lake pH.
7 • High levels of acidification (to pH values below 5) virtually eliminate all mayflies,
8 crustaceans, and mollusks from some streams.
9 "In general, populations of salmonid fish are not found at pH levels less than 5.0, and
10 smallmouth bass (Micropterus dolomieu) populations are usually not found at pH values less
11 than 5.5 to 5.2.
12 • Twenty percent mortality of young-of-the year brook trout was documented during a 30-day
13 period with a median inorganic Al concentration of 2 (imol/L (Baldigo, 2007). It was estimated
14 that 90% mortality would occur over 30 days with a median inorganic Al concentration of
15 4.0nmol/L.
Community
16 Community-level effects were observed in the Adirondacks and Shenandoah National Park where
17 taxonomic richness is lower in lakes and streams having low ANC and pH.
18 • Decreases in pH and increases in inorganic Al concentrations have reduced the species
19 richness of plankton, invertebrates, and fish in acid-affected surface waters.
20 • Invertebrate taxa that are most sensitive to acidification include mayflies, amphipods, snails,
21 and clams.
22 • In the Adirondacks, a positive relationship exists between the pH and ANC in lakes and the
23 number of fish species present in those lakes. A number of synoptic surveys indicated
24 suggested loss of species diversity and absence of several sensitive fish species in the pH range
25 of 5.0 to 6.0.
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1 "In Shenandoah National Park streams, the fish species richness decreased with decreasing
2 stream ANC. On average, richness is lower by one fish species for every 21 (ieq/L decrease in
3 ANC.
4 • Short-term episodes of acidification are particularly harmful to aquatic biota. Early life stages
5 are more sensitive to acidic conditions than the young-of-the-year, yearlings, and adults.
6 Episodes are most likely to affect biota if the water had pre-episode pH above 5.5 and
7 minimum pH during the episode of less than 5.0. Episodic acidification can have long-term
8 adverse effects on fish populations.
3.2.4. Most Sensitive and Most Affected Ecosystems and Regions
3.2.4.1. Characteristics of Sensitive Ecosystems
9 The principal factor governing the sensitivity of terrestrial and aquatic ecosystems to acidification
10 from S and N deposition is geology (particularly surficial geology). Geologic formations having low base
11 cation supply generally underlie the watersheds of acid-sensitive lakes and streams. Bedrock geology has
12 been used in numerous acidification studies (e.g., Bricker, 1989); Stauffer, 1990; Stauffer and Wittchen,
13 1991; Vertucci and Eilers, 1993; Sullivan et al., 2007). Other factors contribute to the sensitivity of soils
14 and surface waters to acidifying deposition, including topography, soil chemistry, land use, and
15 hydrologic flowpath.
16 Several studies have confirmed the importance of geology in regulating terrestrial and aquatic
17 ecosystem sensitivity to acidification, and highlighted other key factors responsible for terrestrial and
18 aquatic sensitivity to acidifying deposition throughout the southeastern U.S. Sensitive terrestrial
19 ecosystems include high-elevation spruce-fir forests dominated by relatively nonreactive bedrock in
20 which base cation production via weathering is limited (Elwood, 1991). Soils in such areas tend to have
21 thick organic horizons, high organic matter content in the mineral horizons, and low pH 2. Because of the
22 largely nonreactive bedrock, base-poor litter and organic acid anions produced by the conifers, high
23 precipitation, and high leaching rates, soil base saturation in these high-elevation forests tends to be below
24 about 10% and the soil cation exchange complex is generally dominated by Al (Johnson, 1992)Eagar
25 etal., 1996).
26 Galloway (Galloway, 1996) further attributed forest soil sensitivity to acidification in the
27 southeastern U.S. to atmospheric deposition level, soil age, weathering rate, and S adsorption capacity.
28 Moncoulon et al. (2004) suggested that forest ecosystem sensitivity to acidification varies mainly with
29 weathering rate. In a review of 241 ecosystem types in France (classified by pedologic and geologic
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1 characteristics), the ecosystems most susceptible to acidification were those with low weathering rates
2 and thus limited buffering capacity (Moncoulon et al, 2004).
3 In hardwood forests, species nutrient needs, soil conditions, and additional stressors work together
4 to determine sensitivity to acidifying deposition. Stand age and successional stage also can affect the
5 susceptibility of hardwood forests to acidification effects. In northeastern hardwood forests, older stands
6 exhibit greater potential for Ca depletion in response to acidifying deposition than younger stands. Thus,
7 with the successional change from pin cherry (Prunus pensylvanica), striped maple (Acer pensylvanicum),
8 white ash (Fraxinus americana), yellow birch and white birch (Betula papyrifera) in younger stands to
9 beech and red maple in older stands, there is an increase in sensitivity to acidification (Hamburg et al.,
10 2003).
11 Land use influences watershed sensitivity to acidification mainly through disturbance and
12 consequent exposure of S-bearing minerals to oxidation, loss of base cations through erosion and timber
13 harvesting, and change in N status of the forest through timber management. Each of these types of
14 activity can influence the relative availability of mobile mineral acid anions (SO42 , NO3 ) in soil solution
15 and base cations (Ca, Mg, K, Na) on the soil ion exchange sites and in drainage water.
16 The movement of water through the soils into a lake or stream, and the interchange between
17 drainage water and the soils and sediments, strongly regulate the type and degree of watershed response
18 to acidic inputs (Sullivan, 2000). Surface waters in the same setting can have different sensitivities to
19 acidification depending on the relative contributions of near-surface drainage water and deeper
20 groundwater (Eilers et al., 1983; Chen et al., 1984; Driscoll et al., 1991).
21 Movement of a strong acid anion, such as SC>42 or NOs , through an acidic soil can mobilize ET
22 and A13+ because these cations are available on soil exchange sites. There is no time lag in this exchange
23 reaction and it is instantly reversible if input of strong acid anions is ceased (Turner, 1990). It is necessary,
24 however, for appreciable mobilization of ET and A13+ that the soil be acidic, either naturally or because of
25 soil acidification from acidifying deposition.
26 In summary, lakes and streams in the U.S. that are sensitive to episodic and chronic acidification in
27 response to SOX, and to a lesser extent NOX, deposition tend to occur at relatively high elevation in areas
28 that have base-poor bedrock, high relief, and shallow soils. For example, in the Southern Appalachian
29 region, Sullivan et al. (2002a, 2007) determined that underlying bedrock geology dominated by sandstone
30 or related rock types and elevations greater than 1000 m (3250 ft) could be used to identify landscapes in
31 the region most likely to contain acidic streams.
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3.2.4.2. Extent and Distribution of Sensitive Ecosystems
Surface Waters
1 Several regions of the U.S. contain appreciable numbers of lakes and streams with low ANC (less
2 than about 50 (ieq/L), including portions of the Northeast (especially New England, the Adirondacks, and
3 the Catskill Mountains), Southeast (the Appalachian Mountains and northern Florida), Upper Midwest,
4 and western U.S. (Charles, 1991). The Adirondack and Appalachian Mountains, and to a lesser extent the
5 Upper Midwest, include many acidified surface waters that have been affected by acidifying deposition.
6 Portions of northern Florida also contain many acidic and low-ANC lakes and streams, although the role
7 of acidifying deposition in these areas is less clear. The Western U.S. contains many of the surface waters
8 most susceptible to potential acidification effects, but with the exception of the Los Angeles Basin and
9 surrounding areas, the levels of acidifying deposition in the West are low in most areas, acidic surface
10 waters are rare, and the extent of chronic surface water acidification that has occurred to date has likely
11 been very limited.
12 Several national assessments were conducted to estimate the distribution and extent of surface
13 water acidity in the U.S. During summer baseflow of 2004, the EPA conducted a National Wadeable
14 Stream Assessment (WSA) survey of 1,392 randomly selected sites across the conterminous 48 U.S. to
15 assess the ecological condition of wadeable streams (EPA, 2006c). Because this sampling was conducted
16 during baseflow in the summer (which exhibits the least acidic conditions of the year) only the most
17 chronically acidified streams were identified as acidic. Therefore, the extent of potential seasonal
18 acidification was underestimated by this approach (Lawrence et al., in press). Overall, less than 1% of the
19 1,020,000 km of stream in the target population (based on the 1:100,000-scale U.S. Geological Survey
20 (USGS) map blue line network) was acidic due to acidifying deposition. No acidic streams were observed
21 in the Mountainous West, Xeric West, Upper Midwest, Northern Plains, Southern Plains, or Temperate
22 Plains ecoregions. Acidic streams attributable to acidifying deposition were found in the Northern
23 Appalachians (2.8% of 96,100 km of stream), and the Southern Appalachians (1.8% of 287,000 km). Very
24 low ANC (0-25 (ieq/L) streams likely exposed to episodic acidification were found in the Northern
25 Appalachians (2.7% of 96,100 km of stream), the Coastal Plain (6.3% of 119,000 km), and the
26 Mountainous West (0.6% of 204,000 km).
27 Even though the WSA had over 1,300 sample sites, it was still a very coarse sample of the nation's
28 streams with respect to acidifying deposition effects, which are only observed in spatially restricted
29 subpopulations. More precise survey estimates of the effects of surface water acidification were made in
30 the National Surface Water Survey (NSWS) in the mid 1980s. By statistically selecting representative
31 lakes and streams in each surveyed region, the NSWS estimated chemical conditions of 28,300 lakes and
32 56,000 stream reaches (Baker et al., 1990c). The NSWS concluded that 4.2% of lakes larger than 4 ha and
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1 2.7% of stream segments in the acid-sensitive regions of the eastern U.S. were acidic. The NSWS
2 documented the status and extent of surface water acid-base chemistry during probability surveys of lakes
3 and streams conducted from 1984 through 1988 in the major acid sensitive regions of the U.S. (Linthurst
4 et al., 1986a; Landers et al, 1987; Kaufmann et al, 1988).
5 The stream component of the NSWS, the National Stream Survey (NSS), was focused in the
6 northern and southern Appalachians and Coastal Plain of the Eastern U.S. (Kaufmann et al., 1991). The
7 NSS included 500 stream reaches selected from 1:250,000 scale USGS topographic maps using a
8 systematic, randomized sample. Study reaches were sampled at both the upstream and downstream end of
9 each selected reach. Population estimates were made for chemistry at both reach ends and for stream
10 length by interpolating chemical results between reach ends.
11 Overall, out of the estimated 57,000 stream reaches in the NSS, after excluding streams acidic due
12 to acid mine drainage, 6.2% of the upstream and 2.3% of the downstream reach ends were acidic during
13 spring baseflow (Kaufmann et al., 1991). After interpolation, this corresponded to 2.7% of the
14 201,000 km of stream in the study region. In acidic and low-ANC NSS reaches, ANC usually increased
15 with downstream distance. Acidic (ANC < 0) streams were located in the highlands of the Mid-Atlantic
16 Region (southern New York to southern Virginia, 2320 km), in coastal lowlands of the Mid-Atlantic
17 (2530 km), and in Florida (461 km). Acidic streams were rare (less than 1%) in the highlands of the
18 Southeast and Piedmont. Inorganic monomeric Al concentrations were highest in acidic streams of the
19 Mid-Atlantic Highlands, where over 70% of the acidic streams had inorganic Al greater than 3.7 (iM
20 (100 (ig/L), a concentration above which deleterious biological effects have frequently been reported.
21 Anion composition of the NSS stream samples was examined to evaluate the most probable
22 sources of stream acidity in acidic and low-ANC sites (Baker et al., 1991; Herlihy et al., 1991). Acidic
23 streams that had minimal organic influence (organic anions constituted less than 10% of total anions), and
24 SC>42 and NOs concentrations indicative of evaporative concentration of atmospheric deposition, were
25 classified as acidic due to acidifying deposition. These acidic streams were located in small (< 30 km2)
26 forested watersheds in the Mid-Atlantic Highlands (an estimated 1980 km of stream length) and in the
27 Mid-Atlantic Coastal Plain (1250 km). Acidic streams affected primarily by acidifying deposition but also
28 influenced by naturally occurring organic anions accounted for another 1210 km of acidic stream length
29 and were mainly located in the New Jersey Pine Barrens, plateau tops in the Mid-Atlantic and Southeast
30 Highlands, and the Florida Panhandle. The total length of streams that were identified as acidic due to
31 acid mine drainage in the NSS (4590 km) was about the same as the total length of acidic streams likely
32 affected by acidifying deposition (4455 km). Acidic streams whose acid anion composition was
33 dominated by organics were mainly located in Florida and the Mid-Atlantic Coastal Plain. In Florida,
34 most of the acidic streams were organic-dominated, whereas about half of the acidic streams in the Mid-
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1 Atlantic Coastal Plain were organic-dominated. Organic-dominated acidic streams were not observed in
2 the Mid-Atlantic or Southeast Highlands.
3 Stoddard et al. (2003) presented a map of acid-sensitive regions of the eastern U.S. where lakes and
4 streams occur that are likely to be affected by acidifying deposition (Figure 3-17). The map shows
5 considerable overlap with the areas of high interest identified by Baker et al. (1990c). Surface waters in
6 most other regions of the U.S. are not sensitive to the effects of acidification due largely to the nature of
7 the local geology (Stoddard, 2003). An exception is the region surrounding the Los Angeles Basin, which
8 receives high N deposition ( > 20 kg N/ha/yr in some areas) and includes streams with very high
9 concentrations ( > 50 (ieq/L; Bytnerowicz and Fenn, 1996; Fenn and Poth 1999, 2001).
Acid Sensitive Regions of the Northern and Eastern United States
s
fF\
Source: Stoddard et al. (2003).
Figure 3-17. Regions of the eastern U.S. that contain appreciable numbers of lakes and streams that
are sensitive to acidification from acidifying deposition.
10 In addition to the large water chemistry databases developed by the EPA that help to identify the
11 spatial distribution of acid-sensitive and acid-affected surface waters in the U.S., there are also some
12 important supplemental regional databases in New England, the Adirondacks, the mid-Appalachian
13 region, the Florida Panhandle, the Upper Midwest, and the Western U.S. Results from these studies are
14 summarized in the following paragraphs.
New England
15 For the New England region, results from EPA's TIME program indicate that 5.6% of the regional
16 lake population (386 lakes) in New England exhibited ANC < 0 (ieq/L during the period 1991 to 1994.
17 This result is similar to the Environmental Monitoring and Assessment Program (EMAP) findings, which
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1 indicate that 5% of lakes in New England had ANC values less than 0 (ieq/L. The EMAP survey was a
2 probability based survey representative of lakes with surface area greater than 1 ha(l,812 lakes). The
3 survey was conducted during low-flow summer conditions, and the results therefore likely reflect the
4 highest ANC values for the year. The EMAP analysis also estimated that an additional 10% of the
5 population had low ANC values, between 0 and 50 (ieq/L, and were probably sensitive to episodic
6 acidification (Driscoll et al., 200Ib).
Adirondacks
1 A study by Driscoll et al. (200 Ib) used EMAP data from 1991 to 1994 to evaluate the extent of
8 acidic lakes in the Adirondacks for that period. Results from the survey indicate that 10% of the
9 population of Adirondack lakes were chronically acidic (ANC values of less than 0) and 31% were
10 sensitive to episodic acidification (ANC values between 0 and 50) during the study period (Driscoll et al.,
11 2001b).
12 The Adirondack Lake Survey Corporation conducted a comprehensive survey of Adirondack lakes
13 greater than 0.2 ha in surface area between 1984 and 1987 (Baker et al., 1990b). Of the 1,489 lakes
14 surveyed, 24% had summer pH values below 5.0, 27% were chronically acidic (ANC < 0) and an
15 additional 21% were probably susceptible to episodic acidification (ANC between 0 and 50; Driscoll
16 etal.,2007a).
Mid-Appalachian Region
17 A compilation of survey data from the mid-Appalachians yields a consistent picture of the acid-
18 base status of streams. In the subpopulation of upland forested streams, which comprises about half of the
19 total stream population in the mid-Appalachian area, data from various local surveys showed that 5% to
20 20% of the streams were acidic and about 25 to 50% had ANC < 50 (ieq/L (Herlihy et al., 1993). NSS
21 estimates for the whole region showed that there were 2330 km of acidic streams and 7500 km of streams
22 with ANC < 50 (ieq/L. In these forested reaches, 12% of the upstream reach ends were acidic and 17%
23 had pH < 5.5. SO42 from atmospheric deposition was the dominant source of acid anions in acidic mid-
24 Appalachian streams.
25 Cosby et al., (Cosby, 2006) provided a detailed characterization of streamwater acid-base chemistry
26 in Shenandoah National Park, Virginia, which has been the most thoroughly studied area within the mid-
27 Appalachian Mountain region with respect to acidification from acidifying deposition. Based on MAGIC
28 model simulations and extrapolation using landscape characteristics, Cosby et al. (Cosby, 2006)
29 developed maps showing the distribution of streamwater conditions in the Park for the preindustrial past,
30 current conditions, and anticipated future conditions.
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Florida Panhandle
1 According to the EPA's Eastern Lakes Survey conducted in 1984, 75% of the Florida Panhandle
2 lakes were acidic at that time, as were 26% of the lakes in the northern peninsula. Most of the acidic lakes
3 were clear water (dissolved OC < 400 (iM) seepage lakes in which the dominant acid anions were
4 chloride and SO42 . Most of the acidic and low-ANC lakes were located in the Panhandle and northcentral
5 lake districts. Acidic streams were located in the Panhandle and were mildly acidic (mean pH 5.0) and
6 extremely dilute, with very low sea salt-corrected sum of base cations (mean 21 (ieq/L) and sea salt-
7 corrected SO42 concentrations (mean 16 (ieq/L). One-fourth of these acidic Panhandle streams were
8 organic-dominated but the remaining sites all had dissolved OC < 2 mg/L. Inorganic monomeric Al
9 concentrations in these acidic streams were very low (mean 11 (ig/L). In these low dissolved OC, low
10 ANC Panhandle streams, it was suggested that the degree of SO42 and NOs retention in soil was an
11 important control on streamwater ANC (Baker et al., 1990c).
Upper Midwest
12 Based on the Eastern Lakes Survey, the Upper Midwest has a large population of lakes having
13 ANC < 200 (ieq/L, (Linthurst et al., 1986a,b); only 6% of the lakes had ANC < 50 (ieq/L. Groundwater
14 recharge lakes (those having Si concentration less than 1 mg/L, indicating little groundwater input)
15 constituted 71% of the seepage lakes in the Upper Midwest, and were more frequently low in pH and
16 ANC. Five percent were acidic and 9% had pH < 5.5. Nearly 90% of Upper Midwestern lakes that had
17 ANC < 50 (ieq/L were in the groundwater recharge category (Baker et al., 1991). Such lakes tend to be
18 susceptible to acidification from acidifying deposition.
19 Acidic lakes in the Upper Midwest are primarily small, shallow, seepage lakes that have low
20 concentrations of base cations and Al and moderate SO42 concentrations. Organic anions, estimated by
21 both the Oliver et al. (1983) method and the anion deficit, tend to be less than half the measured SO42
22 concentrations in the acidic lakes (Eilers, 1988, but much higher in many of the drainage lakes that are
23 less sensitive to acidification from acidifying deposition.
West
24 Landers et al. (1987) identified subregions in the West with acid-sensitive lakes, based on results of
25 EPA's Western Lakes Survey. The surface water chemistry data for the West indicate that the Sierra
26 Nevada and Cascade Mountains constitute the mountain ranges with the greatest number of sensitive lake
27 resources. Surface waters in this region are among the most poorly buffered surface waters in the U.S.
28 (Landers et al., 1987; Melack and Stoddard, 1991). The hydrologic cycle is dominated by the annual
29 accumulation and melting of a dilute, mildly acidic snowpack.
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1 Many Cascade and Rocky Mountain lakes are highly sensitive to potential acidifying deposition
2 effects (Nelson, 1991; Turk and Spahr, 1991). It does not appear that chronic acidification has occurred to
3 any significant degree, although episodic acidification has been reported for lakes in the Colorado Front
4 Range (Williams and Tonnessen, 2000).
5 Along the eastern edge of the Continental Divide in Colorado and southeastern Wyoming,
6 Musselman et al. (1996) conducted a synoptic survey of surface water chemistry in the mountainous areas
7 that are exposed to relatively high (by western standards) deposition of N. A total of 267 high-elevation
8 lakes situated in watersheds having a high percentage of exposed bedrock or glaciated landscape were
9 selected for sampling. None of the lakes were chronically acidic (ANC < 0), although several had
10 ANC < 10 neq/L, and more than 10% of the lakes had ANC < 50 (ieq/L.
Forest Ecosystems
11 No systematic national survey of terrestrial ecosystems in the U.S. has been conducted to
12 determine the extent and distribution of terrestrial ecosystem sensitivity to acidifying deposition. The
13 scarcity of information on sensitive terrestrial ecosystems is due in part to sparse soils data. In general,
14 forest ecosystems of the Adirondack Mountains of New York, Green Mountains of Vermont, White
15 Mountains of New Hampshire, the Allegheny Plateau of Pennsylvania, and high-elevation forests in the
16 southern Appalachians are considered to be the regions most sensitive to terrestrial acidification effects
17 from acidifying deposition.
18 One national and a few regional efforts have been undertaken to characterize forest sensitivity to
19 acidifying deposition using a critical loads approach. In this context, acid-sensitive soils are those which
20 contain low levels of exchangeable base cations and low base saturation. On a broad national scale,
21 McNulty et al. (McNulty, 2007) used a simple mass balance equation and available national databases to
22 estimate forest soil critical acidic loads (for wet and dry deposition of S and N) and exceedences for forest
23 soils. Exceedences are pollutant loads that are greater than the estimated critical load for that location.
24 They found that approximately 15% of forest soils in the U.S. receive acidifying deposition that exceeds
25 the estimated critical load of wet and dry deposition of S and N by more than 250 eq ha/yr (McNulty,
26 2007). The areas where exceedences reach this level could be considered to represent those areas that are
27 likely most sensitive to continued high levels of acidifying deposition. Thus, there is not a national survey
28 of soil sensitivity to acidification, but there are approaches available with which to identify areas likely to
29 include sensitive soils.
30 Note that the McNulty et al. (McNulty, 2007) paper represents the beginning of an iterative process
31 to identify more precise critical loads for terrestrial acidity. The authors note that the actual area in
32 exceedence of the forest soil critical acid load may be higher than the mapped estimates for several
33 reasons (McNulty, 2007). First, their estimated total deposition did not include cloud deposition. Second,
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1 base cation deposition to near-coastal areas was not corrected for marine aerosol contributions. Third, the
2 1-km squared grid size of the mapping resulted in averaging of soil and deposition data, which removed
3 extreme values from the analysis (McNulty, 2007). The authors take care to describe their results as
4 "preliminary" and note that a more systematic analysis of model-predicted and measured forest soil
5 critical acid load exceedance is needed before this approach can be used as a tool for identifying areas of
6 potential forest health concern (McNulty, 2007). For these reasons, and because of the significant
7 uncertainty associated with many of the large national databases used in the analysis, the appropriate use
8 of this information is not for the actual determination of critical loads at specific locations or for
9 predictions of forest health effects, but rather for increased understanding of relative differences in forest
10 soil sensitivity at a national scale. In general, the Northeast, the Southern Appalachians, parts of Florida
11 and the Upper Midwest have the highest proportion of soils that exceed the estimated critical acid loads
12 by at least 250 eq ha/yr and could, therefore, be termed vulnerable. Where the exceedances are highest,
13 forest soils are likely most sensitive to continued effects from acidifying deposition.
14 At a regional scale, Pardo et al. (Pardo, 2007) calculated critical loads of S and N deposition to
15 forests in Great Smoky Mountains National Park (GSMNP) based on available data. A simple mass
16 balance model and the Very Simple Dynamic model (VSD) were used to calculate a critical load for
17 acidity (N+S) and N nutrient. The authors concluded that current deposition exceeded the critical load at
18 all four sites evaluated (2 high elevation spruce-fir sites, a mid-high elevation beech site, and a lower
19 elevation mixed hardwood site). The exceedance for S + N deposition ranged from 150 eq/ha/yr for the
20 low elevation mixed hardwood site to 2300 eq/ha/yr at the upper spruce-fir site. The maximum acceptable
21 deposition of N ranged from 200 eq/ha/yr (3 kg/ha/yr) for the low elevation mixed hardwood site to 500
22 eq/ha/yr (7 kg/ha/yr) at the upper spruce-fir site.
23 Another approach to identification of sensitive forest lands is to map the distribution of tree species
24 thought to be most sensitive to adverse effects. The effects of acidifying deposition are particularly well
25 documented for red spruce trees (Johnson, 1992; Cronan, 1995; Joslin, 1992; Johnson, 1994) that occur in
26 the northeastern U.S. and southern Appalachian Mountains (Table 3-6 shows the distribution). In the
27 Northeast, red spruce grows at elevations from near sea level to about 1,400 m. In the Appalachian
28 Mountains, spruce-fir forests are generally found at relatively high elevation, for example above about
29 1400 m in the southern portion of the range (SAMAB, 1996). Northern hardwood forests have also been
30 identified as forest resources experiencing air pollution effects. Effects are best documented for sugar
31 maples, which are broadly distributed across the northern hardwood forests in the northeastern U.S.
32 (Figure 3-6 shows the distribution). The areas where sugar maples appear to be at greatest risk are along
33 ridges and where this species occurs on nutrient-poor soils.
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Model Simulations
1 In the eight-state Southern Appalachian Mountains region, Sullivan et al. (2005) modeled future
2 effects of atmospheric S and N deposition on aquatic resources. Modeling was conducted with the
3 MAGIC model for 40 to 50 sites within each of three physiographic provinces, stratified by stream water
4 ANC class. The model runs were based on three emissions control strategies (A2, Bl, and B3). A2 is the
5 base case that represents best estimates for air emission controls under regulations for which
6 implementation strategies were relatively certain at the time of the study (about the year 2000), including
7 the acid rain controls under Title IV of the 1990 Amendments to the CAA, the 1-h ozone (O3) standard,
8 NOX reductions required under EPA's call for revised State Implementation Plans (SIPs), and several
9 highway vehicle and fuel reductions. The Bl and B3 strategies assumed progressively larger emissions
10 reductions, targeted only to the eight states in the southern Appalachian Mountains region, but covering
11 all emissions sectors.
12 The results for the portion of the region south of Virginia and West Virginia suggest that the
13 percentages of streams having ANC below zero and below 20 (ieq/L will actually increase through the
14 year 2040 under all except the most restrictive emissions control strategies (Sullivan et al., 2005). Most
15 simulated changes in stream water ANC from 1995 to 2040 were rather modest, given the very large
16 estimates of future decrease in S deposition. Few modeled streams showed projected change in ANC of
17 more than about 20 (ieq/L (Sullivan et al., 2005). Some of the largest changes were simulated for some of
18 the streams that were most acidic in 1995. For such streams, however, even relatively large increases in
19 ANC would still result in stream water having negative ANC, and therefore little biological improvements
20 would be expected from the simulated improvement in chemistry (Sullivan et al., 2005).
21 Sullivan et al. (2002b) used the NuCM model to evaluate potential changes in soil chemistry in
22 response to acidifying deposition in the southern Appalachian Mountains. The results suggest that spruce-
23 fir forests in the region are likely to experience decreased Ca:Al ratios in soil solution under virtually all
24 strategies of reduced future acidifying deposition considered. This result was partly because SO42
25 adsorption in soils is likely to decline, even with dramatically reduced S deposition. In addition, many
26 spruce-fir forests in the region are N-saturated, and continued N deposition at moderate or high levels
27 would be expected to contribute to elevated NO3 concentrations in soil water, which could further
28 enhance base cation leaching and mobilization of Al from soils to soil solution.
29 In the Adirondacks, model results produced by several studies suggest that the trend of increasing
30 lakewater ANC for the most acid-sensitive lakes might not continue in coming decades. These results are
31 discussed above in the Adirondack case study.
32 In a regional application of PnET-BGC, Chen and Driscoll (2005) analyzed 60 DDRP (Direct
33 Delayed Response Project) lake watersheds within northern New England under three future emissions
34 reduction scenarios. Most of the lakes had surface water ANC values greater than 50 (ieq/L in 1984 and
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1 were therefore not considered chronically acidic. The authors reported that ANC was projected to increase
2 under all three scenarios, with greater rates of recovery occurring with deeper emissions reductions. Soil
3 improvements were slow and modest under all scenarios. Simulations suggested that 80% of the northern
4 New England sites and 60% of the Maine sites will have soil base saturation below 20% in 2050 (Chen
5 and Driscoll, 2005). They concluded that the decreases in SC>42 and NOs concentrations in surface water
6 were coupled with nearly stoichiometric decreases in base cation concentrations. Simulated improvements
7 in ANC in response to reduced acidifying deposition were minor. Therefore, while further declines in
8 atmospheric deposition in S and N will bring some improvements, most ecosystems in the study were not
9 expected to recover to background conditions by 2050.
10 Bulger et al. (2000) developed model-based projections using the MAGIC model to evaluate the
11 potential effect of reductions in S deposition of 40% and 70% from 1991 levels using data from streams
12 in and near Shenandoah National Park. Projections were based on four brook trout stream categories:
13 Suitable, ANC > 50 (leq/L; Indeterminate, ANC 20 to 50 (leq/L; Marginal, ANC 0 to 20 (leq/L; and
14 Unsuitable, ANC < 0 (ieq/L. Three scenarios of future acidifying deposition were modeled: constant
15 deposition at 1991 levels, 40% reduction from 1991 deposition levels, and 70% reduction from 1991
16 deposition levels. Based on observed 1991 ANC values, approximately 30% of all trout streams in
17 Virginia were marginal or unsuitable for brook trout because they were either episodically (24%) or
18 chronically (6%) acidic. In addition, another 20% of the streams were classified as indeterminate, and
19 brook trout in these streams may or may not have been affected. Based on the model simulations, 82% of
20 these streams would not have been acidic prior to the onset of acidifying deposition and would likely have
21 been suitable for brook trout.
22 The model projections suggested that neither the 40% nor the 70% reductions in acidifying
23 deposition would increase the number of streams that were suitable for brook trout above the ambient
24 50%. In fact, the results suggested that a 70% reduction in deposition would be needed in the long term
25 just to maintain the number of streams that were considered suitable for brook trout. Because of the length
26 of time required to restore buffering capacity in watershed soils, most of the marginal or unsuitable
27 streams were expected to remain marginal or unsuitable for the foreseeable future.
28 Results of modeling studies for lakes and streams in the Adirondack Mountains and in Shenandoah
29 National Park are presented in the case study sections of this report.
3.2.4.3. Levels of Deposition at Which Effects are Manifested
30 The effects of S and N deposition are manifested at a range of deposition levels, depending on the
31 inherent sensitivity of the natural resources, as described in the previous sections, and the historical
32 deposition loading. The intersection among current deposition loading, historic loading, and sensitivity
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1 defines the ecological vulnerability to the adverse effects of acidification. Few studies in the U.S. have
2 defined deposition levels that are associated with effects over large areas.
3 Some degree of surface water acidification, and perhaps also of soil acidification, can occur at very
4 low levels of S deposition (only a few kg/ha/yr). These highly sensitive areas are characterized by very
5 low levels of exchangeable base cations and soil base saturation. They provide limited neutralization of
6 acidic drainage water.
7 Effects levels for N deposition can be established based on changes to stream and soil chemistry
8 that signal alteration of nutrient cycling, causing NO3 leaching. Analyses have been conducted in the
9 northeastern U.S. and Europe to examine the relationships between N deposition and NO3 leaching to
10 surface waters. The relationship between measured wet deposition of N and streamwater output of NO3
11 was evaluated by Driscoll et al. (1989) for sites in North America (mostly eastern areas), and augmented
12 by Stoddard (1994). The resulting data showed a pattern of N leaching at wet inputs greater than
13 approximately 5.6 kg N/ha/yr. Aber et al. (2003) concluded that loss of NO3 to surface waters during the
14 growing season in forested watersheds often occurs above a threshold of total (wet plus dry) atmospheric
15 N deposition of about 8 to 10 kg N/ha/yr.
16 The effects of N addition on forests have been shown to be wide-ranging. Additions of 25 kg
17 N/ha/yr to spruce plots in Vermont (ambient bulk deposition 5.4 kg N/ha/yr), in which net nitrification did
18 not occur prior to treatment, triggered net nitrification in the second year of treatment (McNulty et al.,
19 1996). Similar results were seen in Colorado, where additions of 25 kg N/ha/yr to old-growth spruce plots
20 in Loch Vale watershed (ambient bulk deposition 4 to 5 kg N/ha/yr) doubled N mineralization rates and
21 stimulated nitrification. In marked contrast to these results, concentrations of NO3 plus NH4+ were not
22 detected until the seventh year in hardwood plots in Harvard Forest, Massachusetts, which received
23 additions of 150 kg N/ha/yr (Magill et al., 2004). Concentrations of NO3 plus NH4+ in hardwood plots
24 receiving 50 kg N/ha/yr were not yet detectable in the 15th year of treatment.
25 Many of the changes in plant species composition, species diversity, and nitrification and
26 mineralization rates in response to atmospheric N deposition are associated with nutrient N fertilization,
27 rather than acidification. They are discussed in more detail in Section 3.3.
Chemical Response
28 As discussed in Section 3.2.1.6, surface water chemistry has responded to changes in emissions and
29 deposition of S over the past two to three decades and most recently also decreases in N. Monitoring data
30 collected within EPA's Long-Term Monitoring (LTM) and TIME projects, as well as other monitoring
31 programs, has been key to understanding chemical responses. See discussion of major monitoring
32 programs in Annex B. Surface water chemistry monitoring data generated through TIME and LTM
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1 (Stoddard, 2003) suggest that the following important changes in lake and stream chemistry have
2 occurred over the past one to two decades in the eastern U.S.:
3 • SO42 concentration has decreased as a percentage of total ion concentration in surface waters.
4 • ANC has increased modestly in three of the five regions studied.
5 • Dissolved OC and associated natural organic acidity increased, perhaps toward more natural
6 pre-disturbance concentrations, as surface water acidity contributed from acidifying deposition
7 has decreased.
8 • Inorganic Al concentrations appear to have decreased slightly in some sensitive aquatic
9 systems.
10 The significant decreases in surface water SO42 concentration which have been observed in many
11 areas have not necessarily brought large changes in the acidity of lakes and streams. For example, the
12 decline in Adirondack lakewater SO42 during the 1980s was charge-balanced by a nearly equivalent
13 decrease in concentrations of base cations in many of the low-ANC lakes, and this limited the increase in
14 ANC and pH that occurred in response to lower SO42 concentrations. Overall, improvements in
15 lakewater acid-base chemistry since 1990 have been measurable but modest. Similar patterns have been
16 observed in most other regions. There are currently no data in the U.S. that indicate increases in soil pH
17 associated with recent declines in acidifying deposition levels.
18 Declines in SC>2 and NOx emissions have brought about measurable improvements in streamwater
19 chemistry in sensitive regions of the U.S. since 1990. However, model forecasts suggest that a reversal in
20 chemical recovery could occur in many sensitive ecosystems under current emissions and deposition
21 levels and that further reductions beyond those required by the 1990 Amendments to the Clean Air Act
22 may be needed to prevent continued adverse effects and to support biological recovery of terrestrial and
23 aquatic ecosystems (see discussion in Section 3.2.4.5.3).
Biological Response
24 Biological recovery can occur only if chemical recovery is sufficient to allow survival and
25 reproduction of acid-sensitive plants and animals. The time required for biological recovery is uncertain.
26 For terrestrial ecosystems, it may be decades after soil chemistry is restored because of the long life of
27 many plant species and the complex interactions of soil, roots, microbes, and soil biota. For aquatic
28 systems, research suggests that stream macroinvertebrate populations may recover relatively rapidly
29 (within approximately 3 years), whereas lake populations of zooplankton recover more slowly (Gunn and
30 Mills, 1998).
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1 Table 3-8 contains a general summary of pH levels at which biological changes are typically
2 manifested. Nevertheless, for aquatic ecosystems, there is currently no theoretical basis on which to
3 predict the pathway and timing of biological recovery. Biological recovery of previously acidified surface
4 waters can lag behind chemical recovery because of such factors as (1) limits on dispersal and
5 recolonization, (2) barriers imposed by water drainage patterns (Jackson and Harvey, 1995), (3) the
6 influence of predation (h et al., 1995), and (4) other environmental stressors (Gunn et al., 1995; Havas
7 et al., 1995; Jackson and Harvey, 1995; McNicol et al., 1995; Yan et al., 1996a,b). Full biological
8 recovery may take decades from the onset of chemical recovery. The results of biological recovery
9 research from the Sudbury region of Canada and several experimental lakes is summarized below.
Table 3-8. General summary of biological changes anticipated with surface water acidification,
expressed as a decrease in surface water pH.
PH
Decrease
General Biological Effects
6.5 to 6.0 Small decrease in species richness of plankton and benthic invertebrate communities resulting from the loss of a few highly acid-sensitive species, but no measurable
change in total community abundance or production.
Some adverse effects (decreased reproductive success) may occur for highly acid-sensitive fish species (e.g., fathead minnow, striped bass).
6.0 to 5.5 Loss of sensitive species of minnows and dace, such as fathead minnow and blacknose dace; in some waters, decreased reproductive success of lake trout and walleye,
which are important sport fish species in some areas.
Visual accumulation of filamentous green algae in the near-shore zone of many lakes and in some streams.
Distinct decrease in species richness and change in species composition of plankton and benthic invertebrate communities, although little if any change in total
community abundance or production.
Loss of some common invertebrate species from zooplankton and benthic communities, including many species of snails, clams, mayflies, and amphipods, and some
crayfish.
5.5 to 5.0 Loss of several important sport fish species, including lake trout, walleye, rainbow trout, and smallmouth bass, as well as additional nongame species such as creek
chub.
Further increase in the extent and abundance of filamentous green algae in lake near-shore areas and streams.
Continued shift in species composition and decline in species richness of plankton, periphyton, and benthic invertebrate communities; decreases in total abundance and
biomass of benthic invertebrates and zooplankton may occur in some waters.
Loss of several additional invertebrate species common in surface waters, including all snails, most species of clams, and many species of mayflies, stoneflies, and other
benthic invertebrates.
Inhibition of nitrification.
5.0 to 4.5 Loss of most fish species, including most important sport fish species such as brook trout and Atlantic salmon. A few fish species are able to survive and reproduce in
water below pH 4.5 (e.g., central mudminnow, yellow perch, and in some waters, largemouth bass).
Measurable decline in the whole-system rates of decomposition of some forms of organic matter, potentially resulting in decreased rates of nutrient cycling.
Substantial decrease in number of species of plankton and benthic invertebrates and further decline in species richness of plankton and periphyton communities;
measurable decrease in total community biomass of plankton and benthic invertebrates of most waters.
Loss of additional species of plankton and benthic invertebrate species, including all clams and many insects and crustaceans.
Reproductive failure of some acid-sensitive species of amphibians, such as spotted salamanders, Jefferson salamanders, and the leopard frog.
10
11
12
13
The Sudbury region of Ontario, Canada has been important for studying both the chemical and
biological effects of S deposition. Mining and smelting of copper-nickel ore began in the 1880s. By the
1950s and 1960s, SC>2 emissions from the mining and smelting operations peaked at over 5,000 tons/day
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1 and extensive acidification of nearby surface waters was documented (Beamish and Harvey, 1972).
2 Emissions of SO2 then decreased during the 1970s to less than one-third of the peak values. S emission
3 reductions resulted in improved water quality in many lakes (Keller and Pitblado, 1986; Keller et al.,
4 1986), and some fisheries recovery was also documented (Gunn and Keller, 1990; Keller and Yan, 1991).
5 Griffiths and Keller (1992) found changes in the occurrence and abundance of benthic invertebrates that
6 were consistent with a direct effect of reduced lakewater acidity. A more recent assessment of recovery of
7 ecosystems in Canada provided further evidence of biological recovery, but also showed that the spatial
8 extent of recovery was limited to lakes that had been severely acidified by the Sudbury smelter (Jeffries
9 et al., 2003). Research at Sudbury clearly documented that chemical recovery of lakes was possible upon
10 reduced emissions and deposition of S, and also that biological recovery, involving multiple trophic
11 levels, could follow. Major findings of the research at Sudbury and elsewhere are summarized below.
Phytoplankton
12 Studies of phytoplankton recovery from experimental acidification indicate that there is an increase
13 in phytoplankton species richness and diversity as pH increases. In Lake 223 in the Experimental Lakes
14 area of Ontario, there was little increase in phytoplankton diversity as pH changed from 5.0 to 5.8 but a
15 strong recovery of diversity at pH above 6 (Findlay and Kasian, 1996). In Lake 302S, profound change
16 began at pH 5.5; phytoplankton assemblages at pH below 5.5 resembled acidified lakes.
Zooplankton
17 Zooplankton recovery in response to experimental de-acidification has been reported for lakes in
18 Ontario, Canada and Minnesota. Zooplankton recovery in experimentally acidified Lake 223 as pH
19 returned back to 6.1 was reported by Malley and Chang (Malley, 1995). Species diversity that had been
20 reduced during the acidification phase had partially returned to pre-acidification levels. Rotifers had
21 recovered less than crustaceans.
22 One decade after cessation of the experimental acidification of Little Rock Lake in Wisconsin,
23 recovery of the zooplankton community was complete (Frost et al., 2006). Recovery did not follow the
24 same trajectory as the initial acidification, however, indicating a substantial hysteresis in zooplankton
25 community recovery. About 40% of the zooplankton species in the lake exhibited a lag of 1 to 6 years to
26 recover to levels that occurred in the neutral reference basin.
Benthic Invertebrates
27 There has been some research conducted on the recovery of benthic invertebrate communities in
28 surface waters exhibiting chemical recovery from acidification. In Scotland, Soulsby et al. (1995)
29 reported an increase in acid-sensitive mayflies in some streams that showed recent ANC increases.
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1 However, no increases in invertebrates were observed in the most acidic streams despite observed
2 increases in ANC. They suggested that further acidifying deposition reductions and sufficient time for
3 reversal of soil acidification may be required before aquatic biotic recovery can occur. The extent to
4 which benthic invertebrates in streams in the U.S. may have recovered in response to any recent increases
5 that may have occurred in stream ANC and pH is not known.
Fish
6 Fish populations have recovered in acidified lakes when the pH and ANC have been increased
7 through liming or reduction of acidifying deposition (Hultberg and Andersson, 1982; Beggs and Gunn,
8 1986; Dillon et al., 1986; Keller and Pitblado, 1986; Raddum et al., 1986; Gunn et al., 1988; Kelso and
9 Jeffries, 1988). The timing offish recovery is uncertain and probably depends heavily on dispersion.
10 Stocking could accelerate fish population recovery (Driscoll et al., 200Ib). Limitations on dispersal and
11 recolonization can hamper biological recovery from acidification.
12 Continued periodic episodic acidification might hamper biological recovery of a lake or stream that
13 is experiencing improvement in chronic chemistry. If fish move into refugia during episodes of low pH
14 and then return, behavioral avoidance would reduce the overall effect of episodic acidification on fish
15 populations. If fish move out of the stream system in response to acidic episodes, as suggested by Baker
16 et al. (1996), and do not return or return in smaller numbers, then the population level effects of episodic
17 acidification would be greater than predicted based on mortality tests alone.
18 Baker et al. (1990a) used field-based models to test the potential for biological recovery. For each
19 species considered, the current presence or absence of the species was analyzed as a function of the water
20 quality variables associated with acidification (e.g., pH, Al, Ca, ANC, and DOC) using maximum
21 likelihood logistic regression (Reckhow et al., 1987). The results from the various models were compared
22 to their prediction of the change in the number of Adirondack lakes with unsuitable acid-base chemistry,
23 given a 50% decrease or a 30% increase in S deposition relative to the existing conditions at the time of
24 the Eastern Lakes Survey (1984). Most of the models provided similar results and suggest that a 30%
25 increase in S deposition would increase the unsuitable fish habitat in Adirondack DDRP lakes by 15% to
26 28% for brook trout, lake trout, and common shiner. A 50% decrease in S deposition was projected to
27 increase suitable habitat by 8% to 18%.
Waterfowl
28 Few studies have been conducted on the recovery of higher trophic level organisms such as birds
29 (Table 3-9). However, breeding distribution for the common goldeneye (Bucephala clangula), an
30 insectivorous duck, may be affected by changes in acidifying deposition (Longcore, 1993). Similarly,
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1 reduced prey diversity and quantity have been observed to create feeding problems for nesting pairs of
2 loons on low-pH lakes in the Adirondacks (Parker, 1988).
Table 3-9. Studies that either did or did not yield evidence that acidifying deposition affected certain
species of birds.
Species
Common loon
Arctic loon
Common
merganser
Belted kingfisher
Osprey
Black duck
Common
goldeneye
Ring-necked duck
Eurasian dipper
Eastern kingbird
Tree swallow
Diet/
Foraging
YES NO
X
X
X
X
X
X
Breeding
Distribution
YES NO
X
X
X
X
X
xb
X
X
X
X
Reproductive
Measures
YES NO
X
X
X
xb
X
X
X
X
X
X
Reference
Alvo et al. (1988); Parker (1988); Wayland and McNicol (1990); Blancher and McNicol (1991); DesGranges and Houde
(1989);Blair(1990)
Eriksson (1987)
McNicol etal. (1987b)
Goriup(1989)
Eriksson (1983); Eriksson (1986)
Hunter et al. (1986); DesGranges and Darveau (1985); Rattner et al. (1987); Harasmis and Chu (1987)
McNicol et al. (1987b); DesGranges and Darveau (1985)
McAuley and Longcore (1988a,b)
Ormerod et al. (1985, 1986); Ormerod and Tyler (1987)
Glooschenko etal. (1986)
Blancher and McNicol (1988, 1991); St. Louis et al. (1990)
b Effect was beneficial
o
4 Logistic regression modeling with measured pH and species occurrence data for acid-sensitive
5 lakes in the Algoma region of Ontario showed that the occurrences of fish, common loons, and common
6 mergansers were positively related to lake water pH (McNicol, 2002). Predictions of common loon and
7 merganser recovery for this area were made using the Waterfowl Acidification Response Modeling
8 System (WARMS) under varying S emissions control scenarios targeted for 2010 (McNicol, 2002). The
9 number of lakes projected to be suitable for supporting breeding pairs and broods increased with Lake pH
10 and stricter emissions controls (McNicol, 2002). Marginal improvements in fish-eating bird habitat were
11 predicted to occur by 2010, with more significant improvements expected under hypothetical S emissions
12 reductions of 50% and 75% for lakes with pH below 6.5 ((McNicol, 2002). Fundamental to the predicted
13 improvement of these fish-eating bird populations is the expected increase in food availability with lake
14 pH recovery.
3.2.4.4. Acidification Case Study #1: Adirondack Region of New York
15 In this and the following section, case studies are presented for two of the most thoroughly studied
16 regions of the U.S. that are known to have been affected by acidification from atmospheric S and N
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1 deposition. Studies in these regions have focused on both chemical and biological effects, and have
2 included extensive model simulations of past acidification and projections of the likelihood of future
3 recovery as deposition levels decline. The Adirondack Mountain region is perhaps the most thoroughly
4 studied region in the world with respect to surface water acidification. Large numbers of Adirondack
5 lakes have been acidified over the past century, and many of those now show signs of chemical recovery.
6 Shenandoah National Park contains many acidified and acid-sensitive streams. Sensitivity in this region is
7 strongly controlled by geology and the extent to which deposited S is adsorbed to soils. These two case
8 studies are intended to be illustrative of the types of research that has been conducted and what that
9 research has revealed.
General Description of Region
10 The Adirondack Mountains are in northeastern New York State and are densely forested, have
11 abundant surface waters, and have 46 peaks that extend up to 1600 m in elevation. The Adirondack Park
12 has long been a nationally important recreation area for fishing, hiking, boating, and other outdoor
13 activities.
14 The Adirondacks, particularly the southwestern Adirondacks, are sensitive to acidifying deposition
15 because they receive high precipitation, have shallow base-poor soils, and are underlain by igneous
16 bedrock with low weathering rates (Driscoll et al., 1991). The Adirondacks are among the most severely
17 acid-affected regions in North America (Landers et al., 1988; Driscoll et al., 2003b). It has long been used
18 as an indicator of the response of forest and aquatic ecosystems to U.S. policy on atmospheric emissions
19 of SO2 and N oxides (EPA, 1995b; NAPAP, 1998; GAO, 2000).
Rates of Acidifying Deposition
20 Current rates of wet deposition of S and N in the western Adirondacks remain among the highest in
21 the nation. Spatial patterns in wet deposition of S and N from 1988 to 1999 were developed by Ito et al.
22 (2002), using data from 24 precipitation and 4 wet deposition monitoring stations. Results from this effort
23 suggest that wet S deposition ranged from 2.3 to 12.9 kg S/ha/yr and wet NO3-N deposition rates ranged
24 from 1.7 to 5.1 kg N/ha/yr (Ito etal., 2002) (Figure 3-18). In general, deposition rates are highest in the
25 southwestern Adirondacks and decrease to the northeast. Rates of dry deposition are less well known, but
26 probably constitute 25% to 50% or more of total wet deposition (Sullivan et al., 2006a)/
27 Deposition trends have changed with the implementation of federal and state emissions control
28 regulations. For example, by 1990 average wet S deposition in the Adirondack region had declined by
29 approximately 30% from its peak in the 1970s (Sullivan, 1990). Deposition of S has continued to decline
30 (Figure 3-19)and (Figure 3-20) in response to implementation of the Clean Air Act Amendments of 1990.
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1 Until recently, wet N deposition had been fairly consistent over the previous two decades. N deposition
2 now appears to be decreasing (http ://nadp. sws.uiuc.edu/).
Annual S04 Deposition (kg S04/ha-yr)
6.9 -10.4
10.4-13.9
13.9-17.4
| 17.4-21.0
| ] 21.0-24.5
| 24.5-28.0
| 28.0-31.6
31.6-35.1
I 35.1 -38.6
I Not estimated
Annual NO3 Deposition (kg NO3/ha-yr)
[ 7.6-9.3
j 9.3-10.9
~ 10.9-12.6
12.6-14.2
14.2-15.9
15.9-17.6
17.6-19.2
19.2-20.9
20.9-22.5
Not estimated
Source: Itoetal. (2002)
Figure 3-18. Spatial patterns in predicted wet S042" and N03 deposition in the Adirondack Park
during the period 1988 to 1999.
Soil Retention and Leaching of Sulfur and N
3 As discussed in Section 3.2.4.4, acidifying deposition has resulted in the accumulation of S and N
4 in Adirondack soils. Although input-output budgets for S developed in the 1980s suggested that the
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1 amount of S exported was approximately equal to the S inputs from atmospheric deposition, more recent
2 studies show that watershed loss of SO42 now exceeds atmospheric S deposition inputs (Driscoll, 1998).
3 This pattern suggests that decades of atmospheric S deposition have resulted in the accumulation of S in
4 forest soils. With recent declines in atmospheric S deposition and a possible warming-induced
5 enhancement of S mineralization from soil organic matter, previously retained S is gradually being
6 released to surface waters (Driscoll, 1998). This release of SC>42 from soils could contribute to a delay in
7 the recovery of surface waters in response to SC>2 emissions controls.
8 N dynamics are quite different from those of S. Because N is a growth-limiting nutrient for many
9 forest plants, retention in forest ecosystems under low levels of air pollution is generally high and NOs
10 loss to streams is relatively low (Aber, 2003). However, recent research suggests that N has accumulated
11 in soils over time in the Adirondacks and that some forests have exhibited declining retention of N inputs
12 (Driscoll et al., 2003a,c). The result has been increased leaching of NO3 to surface waters. The extent
13 and degree of leaching appear to be linked to climatic variation, land-use history, and vegetation type (see
14 Section 3.2.1.3).
I
CO
S
30
25
20
15
10
Huntington Forest Annual Sulfur Wet Deposition
y = -0.4233X + 860.39
R2=0.6192
1975 1979 1983 1987 1991 1995 1999 2003
Year
Source: Sullivan etal.(2006a)
Figure 3-19. Measured wet deposition of sulfur at the Huntington Forest NADP/NTN monitoring
station.
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1 The leaching of both SO42 and NO3 into drainage water has contributed to the displacement of
2 cations from soil, acidification of surface waters (Driscoll et al., 200 la), and the associated chemical and
3 biological effects discussed below.
Soil Acidification and Base Cation Depletion
4 Atmospherically deposited hydrogen ions can directly affect soil pH. Net uptake of nutrient cations
5 by vegetation can also generate acidity within the soil, and a considerable amount of natural organic
6 acidity is produced in the Oa horizon through the partial decomposition of organic matter and uptake of
7 nutrient cations. In the only repeated soil sampling in the U.S. in which the original sampling predated
8 acidifying deposition, Johnson et al. (1994) found significantly higher soil pH values in 1930 than in 1984
9 in the Oa horizon of Adirondack soils that had an initial pH of 4.0-5.5, but no decrease in pH in soils with
10 an initial pH of < 4.0. Johnson et al. (1994) also documented a decrease in exchangeable Ca
11 concentrations in both the O (combined Oa and Oe horizons) and B horizons from 1930 to 1984. The
12 decrease in soil pH and Ca concentrations was attributed to a combination of acidifying deposition and
13 changing vegetation dynamics.
1850
1900
1950
Year
2000
2050
2100
Source: Sullivan etal.(2006b)
Figure 3-20. Estimated time series of S deposition at one example watershed in the southwestern
Adirondack Mountains. Table used by Sullivan et al. (2006b) as input to the MAGIC model for
projecting past and future changes in lakewater chemistry attributable to acidifying deposition.
Future deposition estimates were based on three emissions control scenarios (Base Case [solid
line], Moderate Additional Controls [dotted line], Aggressive Additional Controls [dashed line]).
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1 In a statistically based regional assessment of changes in soil-exchange chemistry, Sullivan et al.
2 (Sullivan, 2006) found that base saturation and exchangeable Ca concentrations in the Adirondack region
3 appeared to have decreased in the B horizon between the mid 1980s and 2003 in watersheds of lakes with
4 acid-neutralizing capacity less than 200 (ieq/L. Although this study did not involve repeated sampling of
5 the same sites, the comparison could be made on a regional basis because the sampling locations were
6 selected randomly in both the mid 1980s and in 2003, and a large and similar number of sites were
7 included in both samplings.
Effects of Acidifying Deposition on Adirondack Surface Water Chemistry
8 The Adirondack Lake Survey Corporation conducted a comprehensive survey of Adirondack lakes
9 greater than 0.2 ha in surface area between 1984 and 1987 (Baker et al., 1990b). Of the 1,489 lakes
10 surveyed, 24% had summer pH values below 5.0, 27% were chronically acidic (ANC < 0) and an
11 additional 21% were probably susceptible to episodic acidification (ANC between 0 and 50; Driscoll
12 etal., 2007a).
13 In addition to low pH and ANC, many acidic surface waters in the Adirondacks are characterized
14 by high concentrations of inorganic Al. For example, a study of 12 sub-basins in the watershed of the
15 North Branch of the Moose River by Driscoll et al. (1987b) determined that the concentration of
16 inorganic Al in lakewater was higher in lakes having pH below 6.0. Recently, Lawrence et al. (2007)
17 determined that 66% of 188 streams sampled in the western Adirondack region during snowmelt in 2004
18 had measurable concentrations of inorganic Al, an indicator of acidification by acidifying deposition.
19 Historical changes in lakewater chemistry from the mid-1800s to recent times have been estimated
20 for the Adirondacks using paleolimnological techniques. Fossil remains of diatoms and chrysophytes in
21 sediment cores have been used to reconstruct chemical histories. The PIRLAI and II projects
22 (Paleoecological Investigation of Recent Lake Acidification) used the remains of diatoms preserved in
23 lake sediments to estimate historical changes in lakewater chemistry across the Adirondack region. The
24 PIRLA-II project focused on lakes that are 4 ha or larger that represented a subpopulation of 675
25 Adirondack lakes. The results from these analyses suggest that nearly all lakes with estimated
26 preindustrial pH less than 6.0 had acidified between 0.3 and 1.0 pH units during the 20th century. Based
27 on an analysis of data from Cumming et al. (1992) and Baker et al. (1990b), low-pH lakes were
28 uncommon or rare in the preindustrial Adirondacks; the number of lakes with pH less than 5.5 had at least
29 doubled by the mid 1980s and the number with pH less than 5.0 had increased by 5 to 10 times.
30 The PIRLA results are generally consistent with projections from model hindcasts. Sullivan et al.
31 (2006a) modeled past changes in the acid-base chemistry of 70 Adirondack lake watersheds, including 44
32 that were statistically selected to be representative of the approximately 1,320 Adirondack lake
33 watersheds that have lakes larger than 1 ha and deeper than 1 m and that have ANC < 200 (ieq/L. Model
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1 hindcasts were constructed using both the MAGIC and PnET-BGC models. Based on MAGIC model
2 outputs, maximum past acidification occurred by about 1980 or 1990, with a median ANC for the study
3 population of about 61 (ieq/L (reduced from a median of 92 (ieq/L estimated for the preindustrial period).
4 By 1990, 10% of the population target lakes had decreased in ANC to below -16 (ieq/L and 25% had
5 ANC < 28 (ieq/L. The model simulations coupled with population-level extrapolations suggest that none
6 of the target lakes were chronically acidic (had ANC < 0 (ieq/L) under preindustrial conditions, but that
7 by 1980 there were about 204 chronically acidic Adirondack lakes.
8 PnET-BGC model simulations generated output that was generally similar to results provided by
9 MAGIC model simulations. Results from PnET-BGC suggest that none of the lakes in the Adirondack
10 population had preindustrial ANC below 20 (ieq/L. By 1990, there were 289 lakes having
11 ANC < 20 (ieq/L and 217 chronically acidic (ANC < 0 (ieq/L) lakes according to PnET-BGC simulations.
12 There were 202 lakes in the population simulated to have had preindustrial ANC below 50 (ieq/L, and this
13 number increased 2.8 times by 1980 under the PnET-BGC simulations.
14 Zhai et al. (2008) reported PnET-BGC hindcasts for the 44 EMAP lakes. They report that simulated
15 median values of pH, ANC, and soil percent base saturation were 6.63, 67.7 (ieq/L, and 12.3%,
16 respectively, in 1850 compared to current measured values of 5.95, 27.8 (ieq/L, and 7.9%. They also
17 calculated F factors for the PnET-BGC model projections of historical acidification. The F-factor
18 (Henriksen, 1984; Husar et al., 1991) reflects the proportion of the increase in lakewater SO42 plus NO3
19 concentration that is charge balanced by an equivalent increase in base cation concentrations. The
20 remaining proportion (1-F) is attributed to increase in the potentially toxic cations, hydrogen ions and
21 inorganic Al. Based on PnET-BGC hindcast simulations, F-factors for the EMAP lakes ranged from 0.3 to
22 slightly over 1.0, with a mean value of 0.7 (Figure 3-13). The F-factor increased with ambient lakewater
23 ANC. These results are in close agreement with paleolimnological analyses reported by Sullivan et al.
24 (Sullivan, 1990), which showed historic F-factors for Adirondack lakes ranging from about 0.5 to above
25 1.0.
Biological Effects
26 The Adirondack region has a rich aquatic biota dataset from which to examine relationships among
27 lake water chemistry and species abundance, composition, and richness. In general, there tends to be a
28 negative relationship in Adirondack lakes between pH, ANC, and inorganic Al chemical variables and the
29 diversity and abundance offish (Baker and Laflen, 1983; Baker et al., 1990c; Havens et al., 1993) Figure
30 3-16 phytoplankton, and zooplankton (Confer et al., 1983; Siegfried et al., 1989) (Table 3-10).
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Table 3-10. Observed relationships between zooplankton species richness and lakewater ANC
in the Adirondack Mountains.
Taxonomic Group
Total zooplankton
Crustaceans
Rotifers
Equation
Richness =15.65 + 0.089 ANC
Richness = 6.35 + 0.028 ANC
Richness = 9.04 + 0.053 ANC
R2
0.46
0.47
0.30
P
0.001
0.001
0.001
1
2 Through the Adirondack Lakes Survey, 1,469 lakes were sampled between 1984 and 1987,
3 representing 80% of the estimated population of Adirondack lakes larger than 1 ha in area (Whittier et al.,
4 2002). The goal of the survey was to characterize the biological, physical, and chemical characteristics of
5 the lakes and evaluate the relationships between fish communities and water chemistry. The major results
6 were reported by Baker et al. (1990b). Key findings are:
7 • Seventy-six percent of the lakes had fish; 24% (346 lakes) were fishless.
8 • The most common fish caught were native acid-tolerant species: brown bullhead, brook trout,
9 and white sucker.
10 "As pH decreases, fish diversity also decreases. The average number offish species declines
11 from six fish species in lakes with pH higher than 6.5 to two or fewer fish species in lakes with
12 pH of 5.0 or less.
13 • As pH decreases, the number of fishless lakes increases. Few lakes with pH of 5.5 or higher
14 are fishless. Below pH 5.0, approximately 75% of the lakes are fishless.
15 Researchers in the Adirondacks were among the first in the U.S. to demonstrate that fish mortality
16 increases during acid episodes, which are common to lakes and streams in the Adirondacks during spring
17 runoff. Driscoll et al. (Driscoll, 1987) documented surface water chemistry changes associated with
18 periods of high flow. They found that pH and ANC decreased substantially during hydrological episodes
19 and inorganic Al concentrations commonly exceeded thresholds harmful to fish. These relationships were
20 further documented by the Episodic Response Project as shown in the example for Bald Mountain Brook
21 in the Adirondacks (Wigington Jr., 1996). Work by Van Sickle et al. (1996) and others linked these
22 chemical changes to fish mortality in small streams. They determined that blacknose dace were highly
23 sensitive to low pH and could not tolerate inorganic Al concentrations above about 3.7 (iM for extended
24 periods of time. After 6 days of exposure to high inorganic Al, dace mortality increased rapidly to nearly
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1 100% (Van Sickle et al., 1996). Brook trout were less sensitive, but still showed high mortality during
2 many acid episodes.
3 Several efforts have been made to link changes in fish populations with historical changes in water
4 chemistry associated with acidifying deposition. Among the most widely cited is the work of Baker et al.
5 (1990b; Baker, 1996). They analyzed 988 Adirondack Lake Survey lakes for which data existed for the
6 period before 1970 and for the 1980s. Of the 2,824 fish populations confirmed by pre-1970 surveys, 30%
7 had apparently been lost by the 1980s (Baker et al., 1990b). An estimated 23% of the fish population
8 losses were related to acidifying deposition. This relationship was strengthened by evidence from the
9 PIRLA projects. In the 32 lakes that had both historic fish data and paleolimnological chemical
10 reconstructions, the lakes that had acidified the most or that were originally the most acidic were the same
11 ones that were judged to have lost fish populations (Baker et al., 1996).
Recent Trends in Surface Water Chemistry and Projections of Future Change
12 Several studies have been conducted to analyze trends in lake chemistry in the Adirondacks.
13 Driscoll et al. (Driscoll, 2003) evaluated changes from 1982 to 2000 in the original 16 Adirondack LTM
14 lakes and from 1992 to 2000 in the complete set of 48 Adirondack LTM lakes. They found that nearly all
15 study lakes showed marked decreases in SC>42 concentration over the period of record and several lakes
16 showed declines in NO3 concentration. Data for one example monitoring lake are given in Figure 3-21.
17 They found that 7 of the 16 original monitoring lakes showed a statistically significant increase in ANC
18 (Figure 3-22), with a mean rate of increase of 0.78 (ieq/L/yr (Driscoll, 2003). Twenty-nine of the group of
19 48 lakes showed increasing ANC trends from 1992 to 2000 with a mean rate of increase of 1.60 (ieq/L/yr
20 (Driscoll, 2003). The authors attributed this recent increase in ANC to declines in both SO42 and NO3
21 concentrations (Driscoll, 2003).
22 Despite these recent improvements in lake water chemistry in the Adirondack Long-Term
23 Monitoring lakes, 34 of the 48 lakes still had mean ANC values less than 50 (ieq/L in 2000, including 10
24 lakes with ANC less than 0 (ieq/L. Thus, current chemistry data suggest that most of these lakes exhibit
25 chemical conditions that continue to pose a risk to aquatic biota. Model projections of future acid-base
26 chemistry of lakes in the Adirondack Mountains under three scenarios of future atmospheric emissions
27 controls were presented by Sullivan et al. (2006b) to evaluate the extent to which lakes might be expected
28 to continue to increase in ANC in the future. Estimated levels of S deposition at one representative
29 watershed are shown in Figure 3-20 for the hindcast period and in the future under the three emissions
30 control scenarios. Model simulations for 44 statistically selected Adirondack lakes using the MAGIC and
31 PnET-BGC models were extrapolated to the regional lake population. Cumulative distribution frequencies
32 of ANC response projected by MAGIC are shown in Figure 3-23 for the past (1850), peak acidification
33 period (approximately 1990), and future (2100). Results for the future are given for each of the scenarios.
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Darts lake ^Adirondacks)
ISO
160 -
d 140 -
^ 120 -
s inn -
80
_ 8°
20 -
0
1t>0 -
110-
120 -
1DO -
3D
0
-20
-40
6.5
G.O
55
6.0
4.5
40
6
0 d
O o>
Q E
Source: Stoddard et al. (2003)
Figure 3-21. Time series data for S042",
N03, base cations [Ca plus Mg], Gran ANC,
pH, and dissolved OC in one example
Long-Term Monitoring Lake in the
Adirondack Park. Shaded box indicates
time period of analyses reported by
Stoddard et al. (2003).
1/1/32 1/1/84 1/1/86 1/1/88 1/1/90 1/1/92 1/1/94 1/1/96 1/1/98 1/1/00 1/1/02
1 Forecasting results suggested that the ongoing trend of increasing lakewater ANC for the most
2 acid-sensitive lakes would not continue under future emissions and deposition levels anticipated as of
3 2003 (Base Case Scenario). The numbers of Adirondack lakes having ANC below 20 and below 50 (ieq/L
4 were projected to increase between 2000 and 2100 under that scenario, and the number of chronically
5 acidic Adirondack lakes (i.e., ANC less than 0) was projected to stabilize at the level reached in 2000.
6 This projected partial reversal of chemical recovery of acid-sensitive lakes was due to a continuing
7 decline in the simulated pool of exchangeable base cations in watershed soils. Simulations suggested that
8 re-acidification might be prevented with further reductions in emissions and deposition.
9 Chen and Driscoll (2004) applied the PnET-BGC model to DDRP lake watersheds in the
10 Adirondacks. The model was applied to three future emissions scenarios: base case, moderate emissions
11 reductions, and aggressive emissions reductions. A case study for Indian Lake in the Adirondacks
12 illustrated that larger reductions in deposition caused greater decreases in SC>42 and base cation
13 concentrations in lake water and greater recovery in pH and ANC. Within the full population of lake-
14 watersheds, some showed decreasing ANC and pH values from 1990 to 2050 even under the moderate
15 and aggressive reduction scenarios. By 2050 to 2100, however, nearly all lakes were simulated to
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1 experience increasing ANC and pH. The modeled soil base saturation increased very slowly over the
2 modeled time period compared to changes in surface water chemistry. For 95% of the lake-watersheds
3 studied, simulated soil base saturation remained below 20% in 2100 under all emissions scenarios.
S04-
N03-
N03-
CB-
ANC-
H* •
AL,-
(n)
(16)
(9)
(16)
(16)
(8)
(11)
(9)
j
u
HE
_l
n
EC
Min -Met
in - Max
3
1
-5
-4
-3 -2 -1 0
Change in Lake Chemistry
Source: Driscoll et al. (Driscoll, 2003)
Figure 3-22. Mean rates of change in solute concentration in 16 lakes of the Adirondack Long-Term
monitoring (ALTM) program from 1982 to 2000. Minimum, mean, and maximum changes in
concentrations and number of lakes showing significant trends are shown. All values are
in peq/L/yr, except for concentrations of inorganic monomeric aluminum (Ah), which are expressed
in pM/yr.
Multipollutant Interaction: Biological Mercury Hotspots in the Adirondacks
4 The Adirondacks has been identified as a region at risk from the combined effects of acidifying
5 deposition and Hg deposition (Driscoll, 2007). The relationship between atmospheric deposition of S and
6 enhanced Hg methylation is discussed in Section 3.4. In general, the solubility of Hg increases with
7 increasing sulfide concentrations in anoxic waters through complexation reactions, potentially increasing
8 the pool of Hg available for methylation (Benoit et al., 2003; Driscoll, 2007). Evers et al. (2007)
9 identified a biological Hg hotspot in the western Adirondacks based on Hg concentrations in yellow perch
10 and common loons. Mean yellow perch Hg concentrations in the Adirondack hotspot were 1.5 to 2.5
11 times higher than the EPA and U.S. Food and Drug Administration's reference dose used for fish
12 consumption advisories (Evers et al., 2007). The authors hypothesized that the occurrence of the
13 biological hotspot was due in part to the combination of high Hg deposition and sensitive water
14 chemistry, such as low ANC and pH, which is associated with both natural acidity and the long-term
15 effects of acidifying deposition (Evers et al., 2007). Driscoll et al. (Driscoll, 2007) concluded that
16 watersheds sensitive to Hg deposition tend to be forested, have an abundance of wetlands, contain
17 shallow hydrologic flow paths and low nutrient concentrations, and are affected by acidifying deposition.
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MAGIC Model Estimates of ANC Distribution
Adirondack Lakes with ANC <
Predicted ANC ((jeq/L)
Source: Sullivan et al. (Sullivan, 2006)
Figure 3-23. Simulated cumulative frequency distributions of lakewater ANC at three dates for the
population of Adirondack lakes, based on MAGIC model simulations reported by Sullivan et al.,
2006. Conditions for the year 2100 are presented for three emissions control scenarios: Base Case,
Moderate Additional Controls, and Aggressive Additional Controls. (See Figure 3-15)
3.2.4.5. Acidification Case Study #2: Shenandoah National Park, Virginia
1 Shenandoah National Park is located along the crest of the Blue Ridge Mountains in Virginia. Air
2 pollution within Shenandoah National Park, including S and N deposition and O3 concentration, is higher
3 than in most other national parks in the U.S. Measured wet S deposition in the park has ranged from 8 to
4 10 kg S/ha/yr in the early 1980s to near 6 kg S/ha/yr since 2000 (Figure 3-24). Dry S deposition may be
5 nearly as high as wet deposition (Sullivan, 2003). Most acidification effects in the park have been linked
6 with S deposition.
7 The sensitivity of streams in the park to acidification from acidifying deposition is determined
8 mainly by the types of rocks found beneath the stream and the characteristics of the watershed soils that
9 surround it. If the underlying geology is Si-based (siliclastic lithology), the soil and water in the
10 watershed generally have poor ability to neutralize acids deposited from the atmosphere. About one-third
11 of the streams in the park are located on this type of geology. Model estimates using the MAGIC model
12 suggest that such streams have typically lost most of their natural ANC, largely in response to a century of
13 industrial emissions and acidifying deposition. As a consequence, stream pH values in many streams are
14 low, especially during winter and spring. Prior to human-caused air pollution, most streams in
15 Shenandoah National Park probably had pH above about 6. Many park streams on siliclastic lithology
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1 currently have pH as low as about 5 (Sullivan, 2003; Cosby, 2006). Other predominant lithologies in the
2 park include granite-based (granitic) lithologies typically characterized by intermediate ANC streams, and
3 basalt-based (basaltic) lithologies typically characterized by relatively high stream ANC (Cosby,
4 2001)Sullivan et al., 2004, 2007, (Sullivan, 2008).
5 The effects of acidifying deposition on Shenandoah National Park streams have been studied for
6 over 25 years by the Shenandoah Watershed Study, the longest-running watershed study program in any
7 of the national parks (Cosby, 2006) see http://swas.evsc.virginia.edu). This program has determined that
8 the high rate of atmospheric deposition of S, combined with naturally low contributions from some rock
9 types of Ca and other base cations (that serve to neutralize acidity), are the most important causes of low
10 stream water ANC in many park streams. Some park streams can also become temporarily acidic for short
11 periods (hours to days) during rainstorms or snowmelt.
12.0
10.0-
I
i
8.0-
«! 6.0-
o
D,
3
V)
4.0-
2.0-
0.0
O
\ \ \ \ \ \ ' • \
1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006
Year
Source: Sullivan et al. (Sullivan, 2003).
Figure 3-24. Wet sulfur deposition
for the period of record at the Big
Meadows NADP/NTN monitoring
station in Shenandoah National
Park.
12 The acidification of streams in the Park is linked to effects that are occurring in the watershed soils.
13 Over time, the ability of soils to adsorb S, thereby effectively negating S's potential to acidify water, is
14 decreasing due to the long term accumulation of SO42 on soil adsorption sites in response to a legacy of
15 acidifying deposition. In addition, the amount of stored Ca and Mg in the soil is gradually declining in
16 response to acidifying deposition. Therefore, streams are expected to acidify more in the future than they
17 have so far, relative to the amount of acidifying deposition received. This prognosis is consistent with
18 recent analysis of national lake and stream response to reductions in air pollution emissions (Stoddard,
19 2003). Unlike a number of other regions of the country, streams in the region that includes Shenandoah
20 National Park are generally not recovering from acidification.
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1 A great deal of research has been conducted in the park on the effects of S and N deposition on soil
2 and water acidification. This park was a major site of early research on acidification processes (cf.
3 Galloway, 1983). This early work provided much of the foundation for development of the MAGIC
4 model (Cosby et al., 1985), which has been the most widely used dynamic watershed acid-base chemistry
5 model worldwide for the past two decades.
6 Although research on many aspects of acidification effects science has been conducted in the park,
7 it has been particularly noteworthy for studies on episodic acidification; biological effects of stream
8 acidification; and dynamic modeling of acidification, recovery, and critical loads. Research within
9 Shenandoah National Park on each of these topics is discussed below.
Episodic Acidification
10 A number of studies of episodic acidification have been conducted in streams within Shenandoah
11 National Park. Eshleman and Hyer (2000) estimated the contribution of each major ion to observed
12 episodic ANC depressions in Paine Run, Staunton River, and Piney River during a 3-year period. During
13 the study, 33 discrete storms were sampled and water chemistry values were compared between
14 antecedent baseflow and the point of minimum measured ANC (near peak discharge). The relative
15 contribution of each ion to the ANC depressions was estimated using the method of Molot et al. (1989),
16 which normalized the change in ion concentration by the overall change in ANC during the episode. At
17 the low-ANC (~0 (ieq/L) Paine Run site on siliciclastic bedrock, increases in NO3 and SO42 , and to a
18 lesser extent organic acid anions, were the primary causes of episodic acidification. Increases in base
19 cations tended to compensate for most of the increases in acid anion concentration. ANC declined by 3 to
20 21 (ieq/L (median 7 (ieq/L) during the episodes studied.
21 At the intermediate-ANC (-60 to 120 (ieq/L) Staunton River site on granitic bedrock, increases in
22 SO42 and organic acid anions, and to a lesser extent NO3 , were the primary causes of episodic
23 acidification. Base cation increases compensated these changes to a large degree, and ANC declined by 2
24 to 68 (ieq/L during the episodes (median decrease in ANC was 21 (ieq/L).
25 At the high-ANC (~ 150 to 200 (ieq/L) Piney River site on basaltic (69%) and granitic (31 %)
26 bedrock, base cation concentrations declined during episodes (in contrast with the other two sites where
27 base cation concentrations increased). SC>42 and NO3 concentrations usually increased. The change in
28 ANC during the episodes studied ranged from 9 to 163 (ieq/L (median 57 (ieq/L) (Eshleman and Hyer,
29 2000). Changes in base cation concentrations during episodes contributed to changes in the ANC of Paine
30 Run, had little effect in Staunton River, and contributed to decreases in ANC in Piney River.
31 The most acidic conditions in Shenandoah National Park streams occur during high-flow periods,
32 in conjunction with storm or snowmelt runoff. There are several different mechanisms of episodic
33 acidification in operation in these streams, depending at least in part on the bedrock geology of the stream
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1 watershed. The relative importance of the major processes that contribute to episodic acidification varies
2 among the streams, in part as a function of baseflow stream water ANC which is largely controlled by
3 bedrock geology. S-driven acidification was an important contributor to episodic loss of ANC at all three
4 study sites, probably because S adsorption by soils occurs to a lesser extent during high-flow periods.
5 This is due, at least in part, to diminished contact between drainage water and potentially adsorbing soil
6 surfaces along the shallow flow paths. Dilution of base cation concentrations during episodes, which is an
7 acidifying process, was most important at the high-ANC site.
8 Thus, episodic acidification of streams in Shenandoah National Park can be attributed to a number
9 of causes, including dilution of base cations and increased concentrations of sulfuric, nitric, and organic
10 acids (Eshleman et al., 1995; Hyer et al., 1995). For streams having low pre-episode ANC, episodic
11 decreases in pH and ANC and increases in toxic Al concentrations can have adverse effects on fish
12 populations. However, not all of the causes of episodic acidification are related to acidifying deposition.
13 Base-cation dilution and increase in organic acid anions during high-flow conditions are natural
14 processes. The contribution of N, indicated by increased NO3 concentrations, has evidently been (at least
15 for streams in the park) related to forest defoliation by the gypsy moth (Webb et al., 1995; Eshleman
16 et al., 1998). Significant contributions of H2SO4, indicated by increased SO42 concentrations during
17 episodes in some streams, is an effect of atmospheric deposition and the dynamics of S adsorption on
18 soils (Eshleman and Hyer, 2000).
19 A recent study by Deviney et al. (Deviney, 2006) used hourly ANC predictions over short time
20 periods to compute recurrence intervals of annual water-year minimum ANC values for periods of 6, 24,
21 72, and 168 h. They extrapolated the results to the rest of the catchments using catchment geology and
22 topography. On the basis of the models, they concluded that many streams in the park have 6- to 168-h
23 periods of low ANC values, which may stress resident fish populations (Deviney, 2006). Specifically, on
24 the basis of a 4-year recurrence interval, approximately 23% of the land area (44% of the catchments) can
25 be expected to have conditions for 72 continuous hours that are indeterminate with respect to brook trout
26 suitability (ANC 20 to 50), episodically acidic (ANC 0 to 20), or chronically acidic (ANC less than 0).
27 Many catchments were predicted to have successive years of low-ANC values potentially sufficient to
28 extirpate some species (Deviney, 2006). The authors of the study reported that smaller catchments are
29 more vulnerable to adverse effects of episodic acidification than larger catchments underlain by the same
30 bedrock. Catchments with similar topography and size are more vulnerable if underlain by less basaltic
31 and carbonate bedrock.
Biological Effects of Acidification
32 A robust relationship between acid-base status of streams and fish species richness
33 was documented in Shenandoah National Park in the 3-year Fish in Sensitive Habitats (FISH) study
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1 (Bulger, 1999). Numbers offish species were compared among 13 streams spanning a range of pH and
2 ANC conditions. There was a highly significant (p < 0.0001) relationship between stream acid-base status
3 (during the 7-year period of record) and fish species richness among the 13 streams. The streams with the
4 lowest ANC hosted the fewest species (Figure 3-15). This study demonstrated biological differences in
5 low- versus high-ANC streams, including species richness, population density, condition factor, age, size,
6 and field bioassay survival. Of particular note was that both episodic and chronic mortality occurred in
7 young brook trout exposed in a low-ANC stream, but not in a high-ANC stream (MacAvoy and Bulger,
8 1995), and that blacknose dace (Rhinichthys atratulus) in low-ANC streams were in poor condition
9 relative to blacknose dace in higher-ANC streams (Dennis, 1995).
10 Bulger et al. (Bulger, 1999) observed a positive relationship between condition factor and pH in
11 streams in Shenandoah National (Figure 3-25). Dennis and Bulger (1995) also found a reduction in
12 condition factor for blacknose dace in waters near pH 6.0. The four populations depicted in (Figure 3-25)
13 with the lowest condition factor had mean habitat pH values within or below the range of critical pH
14 values at which Baker and Christensen (1991) estimated that negative population effects for blacknose
15 dace are likely for the species. The mean condition factor of fish from the study stream with the lowest
16 ANC was about 20% lower than that of the fish in best condition. Comparisons with the work of
17 Schofield and Driscoll (1987) and Baker et al. (1990b) suggest that pH values in the low-pH streams are
18 also near or below the limit of occurrence for blacknose dace populations in the Adirondack region of
19 New York (Sullivan, 2003).
20 MacAvoy and Bulger (1995) used multiple bioassays over 3 years in one of the low-ANC streams
21 as part of the FISH project to determine the effect of stream baseflow and acid episode stream chemistry
22 on the survival of brook trout eggs and fry. Simultaneous bioassays took place in mid- and higher-ANC
23 reference streams. Acidic episodes, with associated low pH and elevated inorganic Al concentrations and
24 high streamwater discharge, caused rapid fish mortality in the low-ANC stream, while the test fish in the
25 higher-ANC stream survived (Bulger, 1999).
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y = 1.194x + 1.519, r =.777
5.4
5.6
5.8
6 6.2 6.4
mean pH
6.6
6.8
7.2
Source: Bulger et al. (Bulger, 1999)
Figure 3-25. Length-adjusted
condition factor (K), a measure of
body size in blacknose dace
(Rhinichthys atratulus) compared
with mean stream pH among 11
populations (n = 442) in
Shenandoah National Park. Values
of pH are means based on quarterly
measurements, 1991-94; Kwas
measured in 1994. The regression
analysis showed a highly
significant relationship (p < 0.0001)
between mean stream pH and body
size, such that fish from acidified
streams were less robust than fish
from circumneutral streams.
Modeling of Acidification, Recovery, and Critical Loads
1 Dynamic models have been used in Shenandoah National Park to help determine whether the
2 changes in surface water chemistry that have occurred over the past one to two decades will continue and
3 whether they will reach levels needed to support biological recovery. The most commonly used models
4 are described in Annex B, and details of these analyses are discussed below. In general, model forecasts
5 indicated that under base case conditions (those expected under existing or anticipated emissions controls)
6 surface water ANC in the southern Appalachians (and also in parts of the Adirondacks) would be likely to
7 decline in the future. In terms of soil chemistry, projected future improvements in both regions appear to
8 be slow and in most cases do not reach a base saturation of 20% or more within the next 100 years.
9 MAGIC model simulations for streams in Shenandoah National Park by Sullivan et al. (Sullivan,
10 2003) suggested that acidifying deposition would have to be decreased substantially to improve and
11 maintain acid-sensitive streams at levels of ANC that would be expected to protect against ecological
12 harm. In addition, it took a long time for these streams to acidify in the past; because of complexities
13 related to soil conditions, it will take even longer for them to recover in the future. To protect against
14 chronic acidity in the year 2100, with associated probable lethal effects on brook trout, S deposition to the
15 most geologically sensitive siliciclastic lithology watersheds in the park will have to be kept below about
16 9 kg/ha/yr for the next 100 years (Sullivan et al., 2007a). Prior to the Industrial Revolution, most
17 streamwater in the Park had ANC higher than about 50 (ieq/L. To promote ANC recovery to 50 (ieq/L in
18 the future, to protect against general ecological harm, S deposition to Si-based (siliciclastic) watersheds in
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1 the park will have to be kept below about 6 kg/ha/yr. Some watersheds will likely not recover streamwater
2 ANC to values above 50 (ieq/L over the next century even if S deposition is reduced to zero (Sullivan
3 etal.,2007a).
4 Simulation and mapping of watershed responses to historical changes in acidifying deposition
5 (from preindustrial to current) by Cosby et al. (Cosby, 2006) suggest that large areas of Shenandoah
6 National Park have suffered deterioration of both soil and stream conditions. The changes in soil
7 condition have been relatively modest up to the present time, with areas in the southern district of the park
8 moving from classification of "moderate concern" (watershed average mineral soil percent base saturation
9 10% to 20%; the historical baseline) to "elevated concern" (average mineral soil percent base saturation
10 5% to 10%) as a result of leaching of base cations from the soils in response to S deposition. Simulation
11 results indicated that deterioration in stream conditions has been more severe than for soil conditions,
12 with large areas in the southern district and some smaller areas in the central and northern districts
13 moving from "moderate concern" (average stream ANC 50 to 100 (ieq/L) to "elevated concern" (average
14 stream ANC 0 to 50 (ieq/L). Neither soil nor stream conditions have shown any improvement from 1980
15 to the present in response to the decline in acidifying deposition over the last 25 years.
16 Simulation and mapping of watershed responses to predicted future changes in acidifying
17 deposition by Cosby et al. (Cosby, 2006) were developed following EPA methods for preparation of
18 emissions inventory inputs into air quality modeling for policy analysis and rule making purposes. These
19 alternate emissions scenarios were based on existing emission control regulations and several proposed
20 alternatives. The model output suggested that the responses of soil conditions to changes in S deposition
21 are expected to be relatively slow. In the short term (by the year 2020), neither improvement nor further
22 deterioration is likely to be observed in soil condition regardless of the future deposition scenario
23 considered. However, model results suggested that constant deposition at 1990 levels would produce
24 worsening soil conditions in the park by the year 2100 with the development of areas of "acute concern"
25 (average percent soil base saturation below 5%) in the southern district. Although the scenarios of
26 possible reduced future deposition did not produce worsening soil conditions, neither did they indicate
27 any improvement in soil condition, even in the long term.
28 Simulated responses of stream conditions were more rapid than those of soils. In the short term (by
29 the year 2020), constant deposition at 1990 levels would likely produce further deterioration in stream
30 condition. The scenarios of future deposition reductions failed to reverse the deterioration of stream
31 condition that has occurred during the last century. In the long term (by year 2100), the effects of the
32 deposition reduction scenarios begin to diverge. The moderate S deposition reduction scenario (69%
33 reduction from 1990 values) did not produce improvement in stream chemistry relative to current
34 conditions. The larger deposition reduction scenario (75%), by contrast, produced modest improvements
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1 in stream chemistry by 2100. However, even the relatively large S deposition reductions of this scenario
2 did not result in a simulated return of stream conditions to the preindustrial state.
3 To develop projections of probable past and future responses of aquatic biota to changing S
4 deposition in Shenandoah National Park, the MAGIC model was coupled by Sullivan et al. (2003) with
5 several empirical models that linked biological response to past and future model projections of water
6 quality. Unlike MAGIC, which is a geochemical, process-based model, the biological effects estimates
7 were based on observed empirical relationships rooted in correlation and expressed as linear relationships.
8 Correlation does not necessarily imply causality, but an observed pattern of covariation between variables
9 does provide a quantitative context for extrapolation. In this case, the projections did not require
10 extrapolation beyond the observed ranges of observations, and therefore the projections were statistically
11 robust. To the extent that the observed empirical relationships used in the coupled models do in fact
12 reflect the effects of acid stress on aquatic biota, the projections were also biologically robust.
13 Dynamic water chemistry model projections were combined with biological dose-response
14 relationships to estimate declines in fish species richness with acidification. A relationship derived from
15 the data in Figure 2-107 was used by Sullivan et al. (2003) with stream ANC values predicted by the
16 MAGIC model to provide estimates of the expected number offish species in each of the modeled
17 streams for the past, present, and future chemical conditions simulated for each stream. The coupled
18 geochemical and biological model predictions were evaluated by comparing the predicted species
19 richness in each of the 13 streams with the observed number of species that occur in each stream. The
20 agreement between predicted and observed species numbers was good, with a root mean squared error in
21 predicted number of species across the 13 streams of 1.2 species. The average error was 0.3 species,
22 indicating that the coupled models were unbiased in their predictions. Model reconstructions of past
23 species richness in the streams suggested that historical loss of species had been greatest in the streams
24 located on the most sensitive geological class (siliciclastic). The average number of species lost from
25 streams on the three bedrock types examined were estimated as 1.6 species on siliciclastic bedrock; 0.4
26 species on granitic bedrock; and 0.4 species on basaltic bedrock. In the case of the siliciclastic streams,
27 the projected past changes were much larger than the average error and root mean squared error of the
28 coupled models, suggesting that the projections were reasonably robust.
3.3. Nutrient Enrichment Effects from N Deposition
29 The ecological effects caused by atmospheric deposition of reactive N (Nr) are the main focus of
30 this section. As discussed previously, the scope of this ISA includes assessment of evidence for all forms
31 of N compounds that contribute to nutrient enrichment. The present context, the various chemical forms
32 of N can be divided into two groups: nonreactive (N2 gas) and Nr. Nonreactive N2 gas composes 80% of
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1 the total mass of the Earth's atmosphere, but it is not biologically available until transformed into to
2 reactive forms of N. Reactive N includes all biologically and chemically active N compounds in the
3 Earth's atmosphere and biosphere (Galloway, 2003). The Nr group includes inorganic reduced forms (e.g.,
4 NH3 and NH4+), inorganic oxidized forms (e.g., NOx, HNOs, N2O, NOs ), and organic N compounds
5 (e.g., urea, amine, proteins, nucleic acids) (Galloway, 2003). Atmospheric N deposition may be composed
6 of numerous chemical species besides oxides, all of which contribute to ecosystem nutrient enrichment.
7 The ISA evaluates the nutrient effects of nitrogen oxides in combination with all other forms of Nr
8 deposition.
9 This assessment focuses on the effects of atmospheric N deposition. Agricultural lands are
10 excluded from this discussion of ecosystems sensitive to nutrient enrichment effects of N deposition
11 because crops are routinely fertilized with amounts of N (100 to 300 kg/ha) that far exceed air pollutant
12 inputs even in the most polluted areas (EPA, 1993). These high rates of fertilization can contribute to
13 ground water NO3 contamination and eutrophication of some surface waters, especially estuaries.
14 However, assessment of the environmental effects of agricultural N fertilization is beyond the scope of
15 this assessment.
16 Organisms in their natural environment are commonly adapted to a specific regime of nutrient
17 availability. Change in the availability on one important nutrient, such as N, may result in imbalance in
18 ecological stoichiometry, with effects on ecosystem processes, structure and function (Sterner, 2002). In
19 general, ecosystems that are most responsive to nutrient enrichment from atmospheric N deposition are
20 those that receive high levels of deposition relative to non-anthropogenic N loading, those that are N-
21 limited, or those that contain species that have evolved in nutrient-poor environments.
22 The following discussion of N-nutrient deposition begins with the N cascade, which provides a
23 conceptual foundation for discussing the effects of Nr on the structure and function of ecosystems.
24 Subsequent sections include the effects of N deposition on: N cycling, C cycling, biogenic GHG
25 emissions, and biodiversity effects, and as well as the characterization of sensitive ecosystems and regions
26 in the U.S. Information is presented for ecosystems in which atmospheric deposition dominates total Nr
27 input (i.e. many terrestrial ecosystems) and ecosystems in which atmospheric deposition constitutes a
28 small proportion of total Nr load (e.g. some wetlands and estuarine ecosystems).
3.3.1. Reactive Nitrogen and the N Cascade
29 N is one of the most important nutrients in practically all ecosystems (Vitousek, 1991, and is often
30 limiting. It is mainly because of its importance as a limiting nutrient that N deposition from air pollution
31 causes ecological problems. N is required by all organisms because it is a major constituent of both the
32 nucleic acids that determine the genetic character of all living things and the enzymes and proteins that
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1 drive the metabolism of every living cell (Sterner, 2002; Galloway, 1998; Galloway, 2002). It is of critical
2 importance in plant metabolism and it often governs the utilization of phosphorus (P), potassium (K) and
3 other nutrients.
4 An increase in global Nr has occurred over the past century, largely due to three main causes: (1)
5 widespread cultivation of legumes, rice, and other crops that promote conversion of N2 gas to organic N
6 through biological N fixation; 2) combustion of fossil fuels, which converts both atmospheric N2 and
7 fossil N to NOx; and (3) synthetic N fertilizer production via the Haber-Bosch process, which converts
8 nonreactive N2 to Nr to sustain food production and some industrial activities (Galloway, 2002; Galloway,
9 2003). Food production accounts for much of the conversion from N2 to Nr, and accounts for geographic
10 redistribution of N as food is shipped to meet population demands and often returned to the environment
11 via waste water.
12 Reactive N accumulates in the environment on local, regional, and global scales (Galloway, 1998)
13 (Galloway, 2002; Galloway, 2003). This accumulation occurs in the atmosphere, soil, and water
14 (Galloway, 2002, with a multitude of effects on humans and ecosystems (Galloway, 1998; Rabalais,
15 2002)Van Egmond et al., 2002; Townsend et al., 2003). The sequence of transfers, transformations, and
16 environmental effects is referred to as the "N cascade" (See Figure 3-26) (Galloway, 2002, 2003).
17 In general, the results of the N cascade and the various transformations in the N cycle can be both
18 beneficial and detrimental to humans and to ecosystems (Galloway, 2002; Galloway, 2003). Among the
19 most important effect of atmospheric N deposition are aquatic eutrophication and changes in the structure
20 of terrestrial plant communities, disruptions in nutrient cycling, increased soil emissions of nitrous oxide
21 (N2O; a potent greenhouse gas), accumulation of N compounds in the soil, soil-mediated effects of
22 acidification (see Section 3.2), and increased susceptibility of plants to stress factors (Aber, 1989; Aber,
23 1998; Bobbink, 1998; Driscoll, 2003; Fenn, 1998).
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Food production
[\rfcs
W
A // People
\ 7 (food; fiber)
•J
' Agroecosystem
NHX effects
Crop Animal
11 organic
Soil
Forests &
grasslands
effects
Plant
Soil
NO,
NO,
N2O
(terrestrial)
Coastal
effects
The
Nitrogen
Groundwater effects
aquatic)
Aquatic Ecosystem
Source: Galloway et al. (Galloway, 2003)
Figure 3-26. Illustration of the N cascade showing the movement of the human-produced reactive
nitrogen (Nr) as it cycles through the various environmental reservoirs in the atmosphere,
terrestrial ecosystems, and aquatic ecosystems.
3.3.2. N Enrichment Effects on N Cycling
1 Given the complexity of the N cycle, the goal of creating a broadly applicable and well-tested
2 predictive model of these interactions has not yet been fully achieved. There is scientific information with
3 which to make generalizations about how ecological and biogeochemical processes respond to Nr
4 deposition. Significant scientific advancements in recent years have included refinement of theoretical
5 foundations of nutrient limitation, development and improvement of analytical technologies, and
6 improved understanding of the role of Nr in regulating or influencing the cycling of other elements,
7 especially C (see Section 3.3.3). Central to this understanding is the basic process of N cycling in
8 terrestrial, transitional, and aquatic ecosystems.
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Deposition
/
Plant
Utilization
,Y
Photosynthesis
w
X
X
X
N^
N
Animal
Proteins
Process altered by
nitrogen saturation
Source: Garner (1994)
Figure 3-27. N cycle (dotted lines indicated processes altered by N saturation).
1 The key steps in the N cycle are outlined in Figure 3-27 include N fixation, assimilation,
2 mineralization (conversion of organic N to simple inorganic forms), nitrification (conversion of reduced
3 inorganic N to oxidized inorganic N), and denitrification (the reduction of NO3 to NO, N2O, and N2 gas
4 by microbes under anaerobic conditions). These steps generally require biologically mediated
5 transformations. Key organisms involved in transforming N from one form to another include plants and
6 microbes.
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1 In addition to direct effects on the ecosystem where it is deposited, N can be exported from the
2 system and cause environmental effects (eutrophication or acidification) in other ecosystem
3 compartments. The two principal mechanisms for N export or loss from ecosystems are leaching and
4 denitrification. Leaching removes N from terrestrial or transitional ecosystems, but adds it to aquatic
5 ecosystems. Thus, an export from one ecosystem becomes an import to another. Denitrification removes
6 N from terrestrial, transitional, and aquatic ecosystems and adds it to the atmosphere (Davidson, 2000;
7 Seitzinger, 2006). Although denitrification provides a pathway for removing excess Nr from ecosystems,
8 incidental production of NO and N2O during denitrification is of concern due to the roles of NO as a
9 precursor in the production of ozone (O3), and N2O as a potent greenhouse gas (see Section 3.3.4 for N
10 deposition effects on biogenic N2O flux). Here we discuss leaching and denitrification in addition to other
11 fundamentals of N cycling in terrestrial, transitional, and aquatic ecosystems.
3.3.2.1. Terrestrial Ecosystems
12 Nr deposition has a potentially important effect on terrestrial ecosystems throughout large areas of
13 the U.S. The availability of N to plants in soil is largely controlled by the process of N mineralization, or
14 the microbial conversion from organic N to simple amino acids and then to inorganic forms such as NH4+
15 and NO3 (Schimel and Bennett, 2004). The two-step, aerobic, microbial process of autotrophic
16 nitrification converts NH4+ to NO3 . Nitrification is an acidifying process, releasing 2 mol hydrogen ion
17 (fT) permolNH4+ converted to NO3 (Reuss, 1986) see Section 3.2 and Annex C for the effects of
18 acidifying deposition). As the N cycle becomes enriched through cumulative N addition, N becomes more
19 abundant, competition among organisms for N decreases, net nitrification rates often increase, and NO3
20 can leach from the ecosystem (Aber, 1989; Aber, 2003).
21 Numerous experimental 15N-addition studies have been conducted as a way of understanding how
22 N cycles through terrestrial ecosystems. These studies have shown that trees typically take up only a
23 small fraction of added 15N; the vast preponderance is retained in the soil (e.g., Tietema et al., 1998;
24 Nadelhoffer et al., 1999; Providoli et al., 2005; Templer et al., 2005). This pattern persists even a decade
25 after 15N application (Nadelhoffer et al., 2004), but these experiments have been criticized for applying
26 15N directly to the soil surface, thereby precluding direct canopy uptake of N from wet, dry, or gaseous
27 deposition (Sievering, 1999; Sievering et al., 2000). Canopy 15N experiments are now underway, but have
28 not yet been published. Comparisons of rates of N deposition in throughfall and in total deposition
29 suggest that forest canopies can take up an average of 16% of total atmospheric N input (Lovett, 1992),
30 but this interception can be considerably higher (up to 90%) in some N-limited forests with large epiphyte
31 loads (e.g., Klopatek et al., 2006). Of that N from deposition that is retained in vegetation, it remains
32 unclear how much of it is used in photosynthetic enzymes (e.g., Bauer et al., 2004).
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1 N in forest ecosystems is stored primarily in the soil, and soil N often exceeds 85% of the total
2 ecosystem N (cf Bormann et al., 1977; Cole and Rapp, 1981). Most soil N is contained in organic matter,
3 typically bound in humic material or organo-mineral complexes that are resistant to microbial
4 degradation. This N is not directly available for biological uptake by plants or microbes or for leaching
5 loss into ground water or surface water.
6 Only what is termed the mineralizable, or labile, pool of N in the soil is considered to be
7 biologically active (Aber, 1989). Bioavailable N often controls photosynthesis and net primary
8 productivity (NPP) (e.g., Field and Mooney, 1986). Plants obtain N from the soil by absorbing NH4+,
9 NO3 , or simple organic N compounds through their roots, or N is taken up by symbiotic organisms (e.g.,
10 fungi, bacteria, cyanobacteria) in plant roots (cf. Lilleskov et al., 2001; Schimel and Bennett, 2004). Plant
11 roots, nitrifying bacteria, and microbial decomposers within the soil utilize, and compete for, this
12 available soil N pool. Plant uptake of N can be energetically costly, as NO3 must be reduced to NH4+,
13 and NH4+ fixed into amino acids before N can be used in plant processes. Some species reduce NO3 in
14 their leaves, taking advantage of excess energy from photosynthesis, whereas other species are restricted
15 to the more energy expensive approach of reducing NO3 in their roots.
N Saturation
16 The term N-saturation refers to the condition whereby the input of N to the ecosystem exceeds the
17 requirements of terrestrial biota, and consequently an elevated fraction of the incoming N leaches from
18 soils to surface waters. The original description of N saturation by Aber et al. (Aber, 1989) described four
19 stages. It was revised by Stoddard (1994) and Aber et al. (1998) Figure 3-28. In Stage 0, N inputs are low
20 and there are strong N limitations on growth. Stage 1 is characterized by high N retention and a
21 fertilization effect of added N on tree growth. Stage 2 includes the induction of nitrification and some
22 NO3 leaching, though growth may still be high. In Stage 3 tree growth declines, nitrification and NO3
23 loss continue to increase, but N mineralization rates begin to decline. While not all terrestrial ecosystems
24 move through the stages of N saturation at the same rate or in response to the same N loading, several
25 experimental N addition studies and a survey of 161 spruce-fir stands along a N deposition gradient
26 support the concept of N saturation progressing from the onset of increase in net nitrification and NO3
27 leaching loss to the eventual decline in tree growth and increase in tree mortality (Aber, 1998).
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V)
+J
'E
200 -,
150 _
N Mineralization
Foliar N-
> ioo H
50 -
Source: Aberetal. (1998)
Figure 3-28. Schematic illustration of the response of temperate forest ecosystems to long-term,
chronic N additions. Changes from initial hypotheses of Aber et al. (Aber, 1989) include the
reduction in N mineralization in stage 3 and the addition of foliar Ca:AI and Mg:N ratios.
1 Decades of atmospheric deposition of N have increased the availability of NO3 and NH4+ in some
2 terrestrial ecosystems to levels where excess N availability results in net nitrification and associated NO3
3 leaching in drainage water. Severe symptoms of N saturation have been observed (1) in the northern
4 hardwood watersheds at Fernow Experimental Forest near Parsons, West Virginia (Peterjohn, 1996), (2)
5 in high-elevation, nonaggrading spruce-fir ecosystems in the Appalachian Mountains (Cook, 1994), (3)
6 throughout the northeastern U.S. (Aber, 1989; Aber, 1998) and (4) lower-elevation eastern forests
7 (Edwards and Helvey, 1991; Peterjohn et al., 1996; Adams et al., 1997, 2000).
8 Mixed conifer forests and chaparral watersheds with high smog exposure in the Los Angeles Air
9 Basin also are N-saturated and exhibit the highest stream water NO3 concentrations documented within
10 wildlands in North America (Bytnerowicz and Fenn, 1996; Fenn, 1998). In general, it is believed that
11 deciduous forest stands in the eastern U.S. have not progressed toward N-saturation as rapidly or as far as
12 coniferous stands. Deciduous forests may have a greater capacity for N retention than coniferous forests.
13 In addition, deciduous forests tend to be located at lower elevation and receive lower atmospheric inputs
14 of N. Many deciduous forests have higher rates of N uptake and greater N requirement than coniferous
15 forests (Aber, 1998).
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N0s~ Leaching
1 Two of the primary indicators of N enrichment in forested watersheds are the leaching of NO3 in
2 soil drainage waters and the export of NO3 in stream water, especially during the growing season (2. The
3 concentration of NO3 in surface water provides an indication of the extent to which N deposited
4 atmospherically or otherwise leaches from the terrestrial ecosystem.
5 In most upland forested areas in the U.S., most N received in atmospheric deposition is retained in
6 soil (Nadelhoffer et al., 1999). Several different data compilations indicate that 80% to 100% of N
7 deposition is retained or denitrified within terrestrial ecosystems that receive less than about 10 kg
8 N/ha/yr (Dise and Wright, 1995; Sullivan, 2000; MacDonald et al., 2002; Aber, 2003; Kristensen et al.,
9 2004). In general, because much of the atmospherically deposited N is retained within the terrestrial
10 ecosystem or denitrified during export, a relatively small fraction of this N reaches downstream estuaries
11 (Castro, 2001)Alexander et al., 2002; Seitzinger, 2002; van Breemen, 2002).
12 Despite retention of most atmospheric N deposition within the terrestrial environment, N-related
13 adverse effects on aquatic life do occur (Driscoll, 2003). For example, although 70% to 88% of
14 atmospheric N deposition was retained in the Catskill Mountains watersheds in upstate New York, fish
15 populations could not be sustained because high NO3 concentrations in stream water during high flows
16 caused the concentrations of inorganic Al to exceed the toxicity threshold (Lawrence, 1999).
17 In an analysis of data collected during the mid- to late 1990s from lakes and streams throughout the
18 northeastern U.S., Aber et al. (2003) suggested that nearly all N deposition is retained or denitrified in
19 northeastern watersheds that receive less than about 8 to 10 kg N/ha/yr. An analysis of N deposition to
20 forestland in the northeastern U.S. based on Ollinger et al. (1993) suggested that approximately 36% of
21 the forests in the region received 8 kg N/ha/yr or more and may therefore be susceptible to elevated NO3
22 leaching (Driscoll, 2003).
23 Aber et al. (2003) further found that surface water NO3 concentrations exceeded 1 (ieq/L in
24 watersheds receiving about 9 to 13 kg N/ha/yr of atmospheric N deposition Figure 3-29. The lakes and
25 streams found to have high NO3 concentration were those receiving N deposition above this range, but
26 responses were variable among those receiving high N deposition. Above this range, mean NO3 export
27 increased linearly with increasing deposition at a rate of 0.85 kg NO3 kg N/ha/yr for every 1 kg N/ha/yr
28 increase in deposition, although there was considerable variability in N retention among watersheds at
29 higher rates of deposition (Figure 3-30) (Aber, 2003).
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Summer (n = 350)
Spring (n = 212)
8 10 12 6 8 10
Estimated N deposition (kg per ha per yr)
12
Source: Aberetal. (2003).
Figure 3-29. Surface water N0s~ concentrations as a function of N deposition at the base of each
watershed in summer and spring. N deposition to the whole watershed may be 2 to 6 kg N/ha/yr
greater than at the base.
1 In other studies, the isotopic signature of 18O in stream-water NO3 indicates that only a small
2 percentage of the incoming NO3 from atmospheric deposition leached directly to drainage waters (e.g.,
3 Spoelstra et al., 2001; Burns and Kendall, 2002; Pardo, 2004). The rest of the NO3 that leached from the
4 terrestrial ecosystem was cycled by biota in soils or streams prior to being exported. That cycled N may
5 have originated in atmospheric deposition, but its first origin was not identified.
6 In general, field experiments have shown that NO3 leaching can be induced by chronic addition of
7 N (Edwards et al., 2002; Kahl et al., 1999; Norton et al., 1999; Kahl et al., 1993; Peterjohn et al., 1996;
8 See Table 3-11). Several N-exclusion studies in Europe demonstrated that decreases in N deposition
9 produced immediate reductions in NO3 leaching from forest stands (Gundersen et al., 1998; Quist et al.,
10 1999). At a regional scale, the leaching transport of N from terrestrial to freshwater systems has important
11 implications beyond its impact on upland lakes and streams, because N exports can ultimately also
12 contribute to the eutrophication of coastal ecosystems (Howarth, 1996)Driscoll et al., 2003c).
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12 -
55 9 H
a.
CO
0)
Q.
6 -
o
N deposition (kg per ha per yr)
90% -
c
g
'•^
gj
•S 70% -
c
o
'c
re
0 50% -
_c
30% -
^^6>° ° °
ON. ^^
°o^^ o °o
o R ""-•. °
o
-------
1 temporal heterogeneity inherent in the denitrification process (Davidson and Seitzinger, 2006). Additional
2 information on measurement techniques is available in Annex C.
3 Denitrification is accomplished by facultative anaerobic denitrifying bacteria, and occurs only
4 under anaerobic conditions, in the presence of sufficient NO3 and organic C. Hence, most terrestrial
5 denitrification occurs in "hotspots," that is, in sporadically wet places or times or in anaerobic soil
6 microsites (McClain et al., 2003; Seitzinger, 2006). The high organic matter content of terrestrial soils
7 provides an ample supply of C, and so the factors that typically limit rates of denitrification in terrestrial
8 ecosystems are rates of NO3 supply and the occurrence of anaerobic conditions. (See Annex C for
9 additional studies and Section 3.3.4 for an analysis of N deposition effects on N2O flux from terrestrial
10 and wetland ecosystems)
11 Using a simple model of the fate of global N inputs to terrestrial ecosystems, Seitzinger et al.
12 (Seitzinger, 2006) estimated that denitrification in terrestrial soils removed 46% (124 Tg/yr) of global N
13 inputs from all sources (N deposition, fertilizer, and N fixation). Half of this denitrification (66 Tg/yr) was
14 estimated to have occurred in agricultural systems. However, this model assumed that all N entering
15 terrestrial systems was leached as NO3 if it was not taken up by plants. Hence, the model overestimated
16 the potential for denitrification by the extent to which N accumulated in soils or ground water (Seitzinger,
17 2006).
Foliar N Concentration
18 The concentration of N in plant foliage, especially in forest trees, can provide an indicator of
19 nutrient enrichment (McNeil et al., 2007; Table 3-11). This indicator may be especially relevant because
20 there is a potential to acquire regional-scale data on foliar N through remote sensing techniques. This
21 allows rapid assessment of N status across large land areas. The N content in tissue of some plant species
22 varies in proportion to N inputs (Baddeley et al., 1994; Hyvarinen and Crittenden, 1998; Pitcairn et al.,
23 2003). Similarly, species typical of nutrient-poor environments tend to accumulate the amino acid
24 arginine in plant tissue (van Dijk and Roelofs, 1988), and arginine concentration therefore varies in
25 proportion to N inputs. Foliar N and foliar arginine concentrations both provide good indices of N
26 deposition effects.
27 There is an interaction between N content and insects, increases N content has been shown to
28 increase palatability to defoliating insects and therefore increasing the extent of defoliation (Nordin et al.,
29 1998; Forkner and Hunter, 2000).
Soil Carbon-to-N Ratio
30 The N and C cycles are tightly coupled in forest soils. For example, NO3 leaching has been
31 correlated with forest floor C:N. Nitrification and NO3 leaching rates are generally low on sites having
August 2008 3-113 DRAFT-DO NOT QUOTE OR CITE
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1 soil C:N ratios above about 22 to 25 (Lovett et al., 2002; Ross, 2004). The C:N ratio of the forest floor
2 can be changed by N deposition over time, although it is difficult to detect a change over time against
3 background spatial heterogeneity (Aber, 2003). The forest floor C:N ratio has been used as an indicator of
4 ecosystem N status in mature coniferous forests (Table 3-11).
Table 3-11. Summary biogeochemical indicators of N addition to terrestrial ecosystems.
Region/Country
White Mountains of
New Hampshire
Europe
Northeast US
Continental Divide
in Colorado
Europe
Adirondacks
Scotland
Vermont
Colorado
Colorado
Harvard Forest, MA
Harvard Forest, MA
Maine and West
Virginia
Endpoint
Soil C:N Ratio
Nitrification
Soil C:N Ratio
NCr Leaching
Soil C:N Ratio
Nitrification
Soil C:N
Foliar C:N
Mineralization Soil
%N
Foliar N:Mg Foliar
N:P
Foliar [N]
Foliar [N]
Foliar [N]
Nitrification
Mineralization
Nitrification Foliar
[N] Organic Soil
Horizon [N]
Mineralization
Nitrification
Soil [N03-]
Soil [NH4+]
Soil [N03-]
Soil [NH41
NOa" Leaching
Observations
Observational: field relationships between soil C:N ratio and canopy lignin:N ratio and high
spectral resolution remote sensing data to predict spatial patterns in C:N. Remote-sensed data
were obtained from NASA's Airborne Visible and Infrared Imaging Spectrometer (AVIRIS)
instrument. Preliminary regional estimates of soil C:N ratio suggested that 63% of the land area
in the region had C:N below 22, which was suggested as a critical threshold for the onset of
nitrification. Below C:N = 22, increasing, but variable, rates of nitrification were found
Observation and Modeling: data from 160 sites across Europe was used to determine that NO-f
leaching occurs in n with soil C:N ratio above 30
Observational: in a compilation of soil C:N and nitrification data from 250 plots showed a
statistically significant but weak correlations between either soil C:N or nitrification and annual N
deposition rate. However, across plots, nitrification increased sharply as C:N ratio (by mass)
decreased below about 22.
Deposition Gradient: Comparison of Engleman spruce (Picea englemanii) forest stands east (3
to 5 kg N/ha/yr) and west (1 to 2 kg N/ha/yr) slopes of the Continental Divide in Colorado. The
higher N deposition on the east slope was due to agricultural and urban areas of the South
Platte River Basin. East slope sites showed lower soil organic horizon C:N ratio, lower foliar C:N
ratio, higher potential net mineralization, and higher percent N, N:Mg ratio, and N:P ratio in
foliage. These results suggested that even moderate levels of N deposition input can cause
measurable changes in spruce forest biogeochemistry.
Observation and Modeling: data from 160 sites across Europe was used to determine NO-f
leaching occurs with foliar N <13 mg N/g
Deposition gradient: observe that eight of nine major canopy tree species had increased foliar N
in response to a gradient of N deposition. Species specific differences were strongly related to
two functional traits that arise from within-leaf allocations of N resources: leaf mass per area
and shade tolerance.
Deposition gradient: Total tissue N and arginine concentrations were closely correlated with
both atmospheric NHs concentration and estimated N deposition (r2 > 0.97 and > 0.78,
respectively)
Field addition: Additions of 25 kg N/ha/yr to spruce plots (ambient bulk deposition 5.4 kg
N/ha/yr), in which net nitrification did not occur prior to treatment, triggered net nitrification in the
second year of treatment, whereas nitrification was not triggered until the third year in plots
receiving 19.8 kg N/ha/yr
Field addition: Additions of 25 kg N/ha/yr to plots in Loch Vale watershed (ambient bulk
deposition -4-5 kg N/ha/yr) doubled N mineralization rates and stimulated nitrification, while the
addition of the same amount to plots receiving ambient bulk deposition of -2.0 kg N/ha/yr in
Fraser Experimental Forest elicited no microbial response but significantly increased foliar and
organic soil horizon N
Deposition gradient: A comparison study of plots across a depositional gradient found
mineralization rates to be higher where N deposition ranged from 3 to 5 kg N/ha/yr than where
N deposition ranged from 1 to 2 kg N/ha/yr, with measurable nitrification rates at sites with the
highest deposition amounts
Field Addition: which exhibited elevated concentrations of N03~ plus NHfin soil water after 1
year of 150 kg N/ha/yr doses, and after 5 years of 50 kg N/ha/yr doses
Field Addition: In plots that received additions of 150 kg N ha-1 yr , elevated concentrations
were detected on the seventh year. In plots receiving 50 kg N/ha/yr, elevated soil concentrations
were not observed after 15 years of treatment.
Field Addition: Additions of N to watersheds in Maine (25 kg N/ha/yr) and West Virginia (35.5 kg
N/ha/yr), which were releasing N03~ to surface waters prior to the additions, resulted in
substantial increases in N03~ concentrations in soil water and stream water within the first
Forest Type/
Species
Coniferous
Forests
Engleman Spruce
(Picea
Englemanii)
Coniferous
Forests
Northern
Hardwood
Three Moss
Species In A
Mixed Woodland
Spruce Forest
Old-Growth
Spruce
Old-Growth
Spruce
Pinus Resinosa
Hardwood Plots
Hardwood
Reference
Ollingeretal. (2002)
Kristensen et al.
2004
Aber et al. 2
Rueth and Baron
(2002)
Kristensen et al.
2004
McNiel et al. 2007
Pitcairn et al. (2003)
(McNultyetal.,
1996).
Rueth et al (Rueth,
2003)
Rueth and Baron,
(2002).
Magilletal.,2004
Magilletal.,2004
(Kahletal., 1993;
Peterjohnetal.,
1996).
treatment year
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Region/Country
Fernow
Experimental
Forest, WV
Bear Brook, ME
Fernow
Experimental
Endpoint
NOs" Leaching
Ca Leaching
N03~ Leaching
N Retention
N03~ Leaching
Observations
Observational: N saturation observed. Progressive increases in streamwater NOf and Ca
concentrations were measured at the Fernow Experimental Forest in the 1970s and 1980s).
This watershed has received higher N deposition (average throughfall input of 22 kg ha/yr of N
in the 1980s) than is typical for low-elevation areas of the eastern U.S., however (Eagaretal.,
1996), and this may help to explain the observed N saturation.
Field Addition: Ammonium SCU2" ([NFU^SCU) fertilization of a forested watershed resulted in
long-term increases in NCr concentration in stream water and high annual export of N,
although the fertilized catchment retained 80% of N inputs, mostly in soil
Field Addition: to (NFU^SCU fertilization caused NOf leaching
Forest Type/
Species
Lower-Elevation
Eastern Forests,
Especially In
West Virginia
Reference
(Edwards and
Helvey, 1991;
Peterjohnetal.,
1996; Adams etal,
1997, 2000)
(Kahletal., 1999;
Norton etal, 1999).
(Edwards etal,
2002)
Forest, WV
greater Los N Saturation
Angeles area, CA
Sierra Nevada and NCr Leaching
San Bernardino,
CA
San Bernardino N Saturation
Mountains, CA
San Bernardino DIN Export
Mountains, CA
Rocky Mountain N Retention
alpine catchments
Observational: plant communities exposed to air pollution received sufficiently high levels of
atmospheric N deposition to be N saturated. Symptoms of N saturation were evident in mixed
conifer or chaparral sites receiving atmospheric deposition of 20 to 25 kg N/ha/yr or higher.
Critical load for increased N03~ leaching calculated as 17 kg N/ha/yr
Chaparral And
Mixed Conifer
Fennetal. (1996)
Mixed Conifer Fennel, al. (Fenn,
Forests 1998)
Deposition gradient: over the range of 12.1-31.7 kg N/ha/yr, the ecosystem was N saturated, as Coniferous Forest Fenn et al, 2000
evidenced by high streamwater N03~ concentration (151 and 65 ueq/L at upper and lower ends,
respectively, of Devil Canyon West Fork
Deposition gradient: over the range of 11-40kg N/ha/yr, dissolved inorganic N (DIN) export was Mixed Forest-
scale dependent, with highest export occurring in watersheds of ~ 150/ha. Differences attributed Chaparral,
to temporal asynchrony between N availability and biological demand Hardwood,
Coniferous
Results from several studies suggest that the capacity of Rocky Mountain alpine catchments to
sequester N is exceeded at input levels less than 10 kg N/ha/yr
Miexnerand Fenn,
2004
Baron etal. (Baron,
1994) Williams and
Tonnessen, 1999
Disturbance and stand age effects on N retention
1 The varying degree of N assimilation, leaching and microbial transformation often reflect
2 differences in N status among treatment sites. These variations have most often been attributed to
3 disturbance history, dating back a century or more (Goodale, 2001). Sites which have undergone
4 disturbances that cause loss of soil N, such as logging, fire, and agriculture, tend to be most effective at
5 retaining atmospheric and experimental inputs of N. Fire causes substantial N losses from ecosystems
6 (see Table 3-12). Timber harvest contributes to nutrient removal from the ecosystem via biomass export
7 and acceleration of leaching losses (Bormann et al., 1968; Mann et al., 1988). In particular, logging
8 contributes to loss of N and Ca2+ from the soil (Tritton et al., 1987; Latty, 2004). N retention capability
9 often decreases with stand age, which suggests that older forests are more susceptible than younger
10 forests to becoming N-saturated (Hedin et al., 1995). Aber et al. (1998) surmised that land use history
11 may be more important than cumulative atmospheric deposition of N in determining the N status of a
12 forest ecosystem. See Annex D for a more detailed discussion of how disturbance affects N cycling.
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Table 3-12. Effects of fire on nutrient concentrations in forests in Nevada and California
Region/Country
End point
Observations
Grassland type/ species
Reference
LakeTahoe Basin, nutrient Field measurement: Compared runoff from fixed plots within wildfire-burned and
Nevada concentration in unburned areas in both summer and winter seasons. Wildfire increased the
runoff frequency and magnitude of elevated nutrient in discharge runoff for all 3
parameters studied: NOa N, ammonium nitrogen, phosphate P. The mobilization
of nutrients was increased due to wildfire, but the lack of 0 horizon material
(surface organic layer of mineral soils) after burning may ultimately reduce
discharge concentrations over time
Lake Tahoe, leaching, N Field measurement: Fire and post-fire erosion caused large and statistically
Nevada concentrations in significant losses of C, N, P, S, Ca, and Mg from the forest floor; Before the
forest floor and soil burn, there were no significant differences in leaching, but during the first winter
after the fire, soil solution concentrations of NFU* NCr, ortho-P, and
(especially) SCU2" were elevated in the burned area, and resin lysimeters
showed significant increases in the leaching of NFU* and mineral N. The
leaching losses of mineral N were much smaller than the losses from the forest
floor and A11 horizons. The major short-term effects of wildfire were on
leaching, whereas the major long-term effect was the loss of N from the forest
floor and soil during the fire.
Sierra Nevada, forest floor and Field experiment: investigated the effect of forest thinning treatments and
California nutrient content, soil prescribed burning on carbon, N, ortho-P, and SCU2" in the forest floor organic
chemical properties, layer and surface soil mineral horizons. The study included a prescribed fire and
and soil leaching three timber harvest treatments: whole-tree thinning (WT) cut-to-length thinning
(CTL), and no harvest (CONT). There were no statistically significant effects of
burning on soil C, N, C:N ratio, Bray-extractable P, exchangeable Ca2*, K* or
Mg2* Burning had no significant effect on soil solution pH, ortho-P, SCU2", N03~,
or NH4* as measured by ceramic cup lysimeters and no effect on the cumulative
leaching of ortho-P, NO-j-, or NHU* as measured by resin lysimeters. Prescribed
fire had little impact on total and soluble nutrients in the upper mineral soil layer.
Loss of N capital from the forest floor appears to be the major effect of
prescribed burning.
Sierra Nevada, nutrient budget of Field measurement/Modeling: effects of fire, post-fire salvage logging, and
California C, N, Ca, P, K, S, revegetation on nutrient budgets were estimated for a site that burned in a
Mg wildfire in 1981. 2 decades after the fire, the shrub ecosystem contained less C
and more N than the adjacent forest ecosystem. C was exported in biomass
during salvage logging and will not be recovered until forest vegetation occupies
the site again. Most N was lost via volatilization during the fire rather than in
post-fire salvage logging (assuming that foliage and 0 horizons were
combusted). Comparison of the pre-fire and present day N showed the lost N
was rapidly replenished in 0 horizons and mineral soils, probably due to N-
fixation by snowbush. No differences in ecosystem P, K, or S contents or in soil
extractable P or S between the shrub and forested plots. K* Ca2*, and Mg2*
were greater in shrub than in adjacent forested soils. The large increase in Ca
resulted from either the release of Ca from non-exchangeable forms in the soil
or the rapid uptake and recycling of Ca by post-fire vegetation.
Little Valley, C and N loss Field measurement/ Modeling: On an ecosystem level, the fire consumed
Nevada approximately equal percentages of C and N (12 and 9%, respectively), but a
greater proportion of aboveground N (71%) than C(21%). Salvage logging was
the major factor of C lost, and C lost will not be replenished until forest
vegetation is reestablished. N2 fixation by Ceanothus velutinus in the post-fire
shrub vegetation appears to have more than made up for N lost by gasification
in the fire over the first 16 yr, and may result in long-term increases in C stocks
once forest vegetation takes over the site. N loss from the fire equaled > 1,000
years of atmospheric N deposition and > 10,000 years of N leaching at current
rates. Calculations of C and N losses from theoretical wildfires in the IFS sites
show similar patterns to those in Little Valley. Calculated losses of N in most of
the IFS sites would equal many centuries of leaching. Conceptual models of
biogeochemical cycling in forests need to include episodic events such as fire.
C and N loss Field measurement: The quantities of C and N volatilized from the forest floor by
prescription fire in the Sierra Nevada were measured at three sites: Marlene,
Sawtooth andSpooner. Glosses calculated by the weight method were 6.12,
7.39, and 17.8 mg C/ha at the Sawtooth, Marlene, and Spooner sites. N losses
calculated by the weight method were 56.2, 60.8, and 362 kg N/ha, at the
Sawtooth, Marlene, and Spooner sites, respectively. N volatilization during
prescribed fire is the dominant mechanism of N loss from these systems.
N. Lake Tahoe,
Nevada;
Truckee, California
(Tahoe National
Forest);
Glenbrook, Nevada
(Lake Tahoe
Jeffery pine, white fir, sugar pine, Sierra
chinquapin, currant, and snow brush,
bitterbrush
Soils: Cagwin series
Sierra Nevada mixed conifer forest: Jeffrey
pine (Pinus Jeffrey!), white fa (Abies
concolor), sugar pine (Pinus lambertiana)
and incense-cedar (Calocedrus
decurrens). Understory vegetation: green
leaf manzanita (Arctostaphylos patula),
snowbrush (Ceanothus velutinus). Soils-
Cagwin series: coarse, loamy sand
Jeffery pine (PinusJeffrey!) forest
Miller etal.
(2006)
Murphy et
al. (2006)
Murphy et
al. (2006a)
110-130 year old Jeffery pine (Pinus
Jeffrey!)
Johnson et
al. (2005)
Jeffery pine (PinusJeffrey!) Mesic forests in
the Integrated Forest Study (IFS).
Johnson et
al. (2004)
Marlene: Jeffery pine, white fir, snowbrush,
squawcarpet, green leaf manzanita,
pinemat manzanita, soil: Cagwin series
Sawtooth: Jeffery and Ponderosa pine,
soil: Kyburz series
Spooner: mixed confer, red fir, white fir,
snowbrush and manzanita, soil: Tahoma
series
Caldwell et
al. (2002)
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3.3.2.2. Wetland Ecosystems
1 N dynamics in wetland ecosystems vary in time, with type of wetland and with environmental
2 factors, especially water availability (Howarth, 1996). A wetland can act as a source, sink, or transformer
3 of atmospherically deposited N (Devito, 1989) and these functions can vary with season and with
4 hydrological conditions. Vegetation type, physiography, local hydrology, and climate all play significant
5 roles in determining source and sink N dynamics in wetlands (Devito, 1989; Koerselman, 1993) Arheimer
6 and Wittgren, 1994; Mitchell, 1996).
N Fixation and Mineralization
7 N fixation and mineralization are two mechanisms by which N becomes available for plants. It is
8 documented that ecosystems may derive substantial amounts of new N inputs via ^-fixation (Hurd et al.
9 2001). N mineralization has been shown to increase with N addition, and this can cause an increase in
10 wetland N export to adjacent surface water (Groffman, 1994). Drought has been shown to inhibit
11 mineralization and nitrification in soils leading to a decrease in NO3 concentration (Foster et al. 1992).
12 However, drying may stimulate mineralization upon re-wetting (Keift et al. 1987). A laboratory study
13 showed that within 24 h of re-wetting, extractable NO3 concentration in dried peat increased
14 approximately 7-fold as compared to continuously moist peat (Watmough et al. 2004).
N0s~ Leaching
15 Leaching losses from wetlands are rarely considered separately from leaching losses from upland
16 terrestrial environments and the wet environments that occur in upland catchments. That is, when
17 leaching losses from terrestrial ecosystems are quantified based on stream exports, estimated leaching
18 losses implicitly include the net loss of NO3 from both terrestrial ecosystems and adjacent wetlands.
19 Leaching losses of NO3 in water derived directly from wetlands are often small because of NO3 removal
20 by denitrification. However, hydrologic flowpaths that deliver water to streams by bypassing wetland
21 soils can deliver substantial quantities of NO3~-rich water from terrestrial uplands.
Denitrification
22 Transitional ecosystems can remove significant quantities of NO3 from water because they
23 represent a convergence of conditions of NO3 , C>2, and C that are requisite for denitrification.
24 Denitrification is frequently optimized when NO3 from more oxic upland areas passes through wet, often
25 C-rich and anoxic wetlands. In some cases NO3 concentration was found to be a better predictor of
26 denitrification rates than soil moisture (Groffman 1994), and there is evidence that in some cases
27 denitrification is limited by C and NO3 supply in wetlands(Ashby et al. 1998).
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1 Denitrification has been studied in riparian zone ecosystems (Lowrance, 1992; Pinay et al, 1993,
2 2000; Watts and Seitzinger, 2001; Hefting et al., 2003) and seems to be related to C availability.
3 Generally, riparian soils that are both rich in organic matter and anaerobic have high denitrification
4 potential. Where riparian soils are aerobic, however, nitrification, rather than denitrification, can be the
5 dominant process (Stevens et al., 1997).
Table 3-13. Summary of N cycling studies for wetlands.
Region/Country
Endpoint
Observations
Wetland Type /
Species
Reference
Adirondock Mountains, NY
N sources used by vegetation Isotopic tracer: Surface waters in forested watersheds. The study estimated N2 fixation by fllnus incana
speckled alder in five wetlands by the 15N natural abundance method and by acetylene
reduction using a flow-through system. The study of alder-dominated wetlands showed
that alder derived >85% of leaf N from N-fixation at an estimated rate of 43 kg N/ha/yr
Conclusion: speckled alder in wetlands of northern New York State relies heavily on N2
fixation to meet N demands, and symbiotic N2 fixation in speckled alders adds substantial
amounts of N to alder-dominated wetlands in the Adirondack Mountains. These additions
may be important for watershed N budgets, where alder-dominated wetlands occupy a
large proportion of watershed area
Rhode Island
Catskill Mountain soils
Adirondack Mountains, NY,
Archer Creek Watershed
Michigan, Smith Creek
Denitrification
denitrification
denitrification
denitrification
Observational: the highest rates of denitrification (4 to 135 kg N/ha/yr) were observed in
very poorly drained soils on nutrient-rich parent material, with lower rates (1.2 to 5.3 kg
N/ha/yr) in soils that were better drained or less nutrient-rich.
Field Addition: Higher rates of denitrification per unit area associated with soils with higher
organic matter content and water-filled pore spaces. Instantaneous NOf concentration did
not correlate with denitrification rate, suggesting that the rates of N03~ supply through
microbial production or hydrologic transport were more important than in situ NOf
concentration. Denitrification was most stimulated by amendments with glucose alone or
glucose plus NCb", suggesting limitation by labile C and NCb" supply.
Ecological gradient: Changes in stream N were measured in one riparian wetland and one
beaver meadow: Strong effects of peatlands on local N concentrations, but little effect of
peatlands on adjacent stream chemistry, since peatland ground water contributed little to
streamflow.
Field additions/measurement Over a two-year period > 1400 individual samples of
subsurface waters were analyzed.
Both spatial patterns of water chemistry and additions of labile C to demonstrate that the
supply of degradable C from shallow flowpaths limited rates of N03~ removal via
denitrification in near-stream zones. Thus, the immediate near-stream region may be
especially important for determining the landscape-level function of many riparian
wetlands.
peatlands
Riparian wetlands
Hurdetal. (Hurd, 2001)
Groffman (1994)
Ashbyetal. (1998)
McHale et al. (2004)
Hedinetal. (1998)
6 N deposition may stimulate biogenic emissions if the N supply is limiting the rate of denitrification
7 in wetland soils via (2006 and Ross, 2005). Previous studies suggest that elevated N inputs to wetlands
8 will often increase the rate of denitrification (Dierberg and Brezonik, 1983; Broderick et al., 1988;
9 Cooper, 1990). This process increases the contribution of nitrous greenhouse gasses to the atmosphere,
10 but limits other environmental effects that are typically associated with increased N supply to soils and
11 drainage waters.
12 In a review of the effects of riparian zones on NOs removal from ground water, Hill (1996)
13 concluded that there are large losses of NOs to denitrification within riparian zones. However, there are
14 important limitations to the generalization that riparian wetlands prevent the leaching of NOs to streams.
15 Not all water entering streams passes directly through adjacent riparian zones, and denitrification in deep
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1 subsurface flowpaths is often limited by the supply of labile C. In addition, not all stream water passes
2 through riparian zones, and large amounts of water may follow flowpaths beneath organic-rich riparian
3 zones, allowing significant transport of NO3 to streams (McHale et al. 2004). The supply of degradable
4 C from shallow flowpaths has been shown to limit rates of NO3 removal via denitrification in near-
5 stream zones (Hedin et al. 1998).
6 In summary, wetland soils can be hotspots of NO3 removal by denitrification in anoxic sites rich in
7 NO3 and labile C, but denitrification rates can be limited by suboptimal conditions of any single
8 biogeochemical factor, and deep water flowpaths can bypass wetland denitrification altogether (see Table
9 3-13).
3.3.2.3. Freshwater Aquatic Ecosystems
10 As previously noted, a large fraction of atmospheric N deposition is retained in most forests.
11 Nevertheless, the fraction that does leach to streams can make a substantial contribution to total N inputs
12 to downstream rivers and estuaries, especially in the eastern U.S. (Driscoll et al. 2003).
NOs" Leaching
13 The predominant chemical consequences of excess atmospheric and non-atmospheric N loading to
14 the watershed of fresh surface waters are: (1) elevated NO3 concentration in surface water; and (2) NO3
15 leaching downstream. The concentration of NOs m surface water can serve as a chemical indicator of N
16 input in excess of ecosystem requirements, and has relevance with respect to acidification and
17 eutrophication effects on surface water.
18 The relationship between wet deposition of N and stream water output of NO3 was evaluated by
19 Driscoll et al. (Driscoll, 1989) for sites in North America (mostly eastern areas), and augmented by
20 Stoddard (1994). The data showed a pattern of N leaching at wet inputs greater than approximately 5.6 kg
21 N/ha/yr, which probably corresponds with a total N deposition input of about 8 to 10 kg/ha/yr. In the
22 Northeast, a survey of 230 lakes and streams documented NO3 concentrations ranging from less than 2
23 up to 42 (ieq/L, with the highest median values occurring in the Adirondacks (Aber, 2003) (Figure 3-31).
24 In the western U.S., NO3 concentrations of freshwater ecosystems have been shown to increase
25 with proximity to urban areas. Results from the Western Lake Survey (WLS) (Eilers, 1987), document
26 enhanced N concentrations in high elevation lakes adjacent to and downwind of urban centers (Fenn
27 et al., 2003a), such as those found in the Sierra Nevada and Colorado Front Range (see Figure 3-32). For
28 example, NO3 concentrations in streamwater during the growing season in the Sierra Nevada were
29 reported to range from 4 to 19 (ieq/L (Fenn et al., 2003b). Concentrations above 10 (ieq/L are generally
30 considered high.
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Mean annual NO3 ~ (umol per L)
O 0-10.5
O 10.5-21.0
• 21.0-31.5
• 31.5-42.0
ADK CAT VT HN ME
(n = 66) (n+48) (n+74) (n = 14)
Source: Aberetal. (2003).
Figure 3-31. Mean annual N0s~ concentrations in 230 lakes and streams across the northeastern
U.S. Inset indicates the median, quartile, and 90% range of mean annual N0s~ in the Adirondacks
(ADK), the Catskills (CAT), Vermont (VT), New Hampshire (NH), and Maine (ME).
1 An interesting example from the Colorado Front Range indicates that lakes on the eastern and
2 western slopes can experience significantly different levels of NOs . A survey of 44 lakes east and west of
3 the Continental Divide indicated that lakes on the western side of the Continental Divide averaged
4 6.6 (ieq/L of NOs , whereas lakes on the eastern side of the divide averaged 10.5 (ieq/L of NOs
5 concentration. NO3 concentrations above 15 (ieq/L have commonly been measured in lakes on the
6 eastern slope of the Front Range, suggesting some degree of N saturation (Baron, 1992), and extreme
7 values as high as 40 (ieq/L have also been reported (Campbell et al., 2000). Williams et al. (1996b)
8 concluded that N-saturation is occurring throughout high-elevation catchments of the Colorado Front
9 Range. Many lakes in the Colorado Front Range have chronic NO3 concentrations greater than 10 (ieq/L
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1 and concentrations during snowmelt are frequently much higher, due at least in part to leaching from
2 tundra, exposed bedrock, and talus areas.
3 In the Unita Mountains of Utah and the Bighorn Mountains of central Wyoming, 19% of the lakes
4 included within the Western Lakes Survey had NOs concentrations greater than 10 (ieq/L. This pattern
5 suggests that N deposition in these areas may have exceeded the capability of these lakes to assimilate N.
6 It is unknown if these concentrations of NOs represent effects from anthropogenic sources or if this
7 constituted a natural condition associated with inhibited NOs assimilation in cold alpine environments.
Lake nitrate
concentratio
(|jeq per L)
0-2
• 2-6
• 6-12
• 12-20
• 20-33
Cities*
Source: Fenn et al. (2003a)
Figure 3-32. N0s~ concentrations in high-elevation lakes in western North America. Stars represent
cities with a population greater than 100,000.
8
9
10
11
12
13
Denitrification
Denitrification in freshwater aquatic ecosystems has been studied in small streams most
intensively, though some work has also been done at larger scales. N is cycled rapidly within streams,
especially small streams with large relative areas for contact with benthic surfaces and hyporheic zones.
For example, Peterson et al. (2001) found that 15N-NH4+ added to streams of various sizes was taken up
most rapidly in the smallest streams, and that these headwater streams exported less than 50% of their
added NH4+. Nevertheless, the long-term fate of this removed or transformed and recycled N is more
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1 difficult to assess. Mulholland et al. (2004) found that addition of 15N-NO3 to a headwater stream at
2 Walker Branch, TN, indicated a mean uptake length of 35 m under ambient conditions. The uptake length
3 extended three-fold (i.e., reduced uptake) under a modest fertilization treatment, which employed NO3
4 addition of approximately 500 (ig N/L. Direct measurements of denitrification of added 15N indicated that
5 denitrification accounted for 16% of the NO3 loss under the ambient treatment, and only 1% of NO3
6 uptake under the fertilized treatment. Nearly all of the denitrification occurred as reduction to N2 gas
7 rather than to N2O.
8 Hyporheic losses of NO3 to denitrification may be largely controlled by supplies of labile
9 dissolved organic carbon (DOC). Bernhardt and Likens (2002) found that adding 6 mg/L of DOC as
10 acetate to a small stream at Hubbard Brook, NH, reduced stream NO3 concentrations from ~5
11 to < 1 (imol/L. In experimental mesocosms designed to mimic hyporheic flowpaths of a small river in the
12 Catskill Mountains, NY, Sobczak et al. (2003) found that adding just 0.5 to 1.0 mg/L DOC from leaf litter
13 resulted in the net consumption of nearly all of the 40 (imol/L NO3 in solution. Acetylene block
14 measurements indicated that the majority of this NO3 loss was due to microbial assimilation rather than
15 denitrification, consistent with the isotopic tracer results of Mulholland et al. (2004).
16 At large spatial scales, water residence time is the variable most frequently identified as a controller
17 of N loss from aquatic ecosystems examined. Examples include lakes of various sizes (Howarth, 1996)
18 and large river basins spanning the northeastern U.S. (Seitzinger, 2002). Compiling N loss data sets from
19 a wide range of aquatic ecosystems, Seitzinger et al. (Seitzinger, 2006) found that water residence time
20 alone explained 56% of the variance in rates of N loss across lakes, rivers, estuaries, and continental
21 shelves, from fast-flowing river reaches (residence time of h) with 0% to 15% N loss to century-scale
22 turnover lakes that eventually incur 80% to 100% N loss.
N Transport Downstream: Urbanization and Determination of N Sources
23 The transport of N via rivers and streams represents an important source of N to downstream
24 ecosystems. The transport and loss of N is determined by the net balance of delivery of N by direct
25 atmospheric deposition and from upland terrestrial and associated transitional ecosystem sources, minus
26 the uptake and gaseous loss of that N during transport. Alexander et al. (Alexander, 2002) and 2007)
27 showed -70% of the N in headwater streams in from N deposition and the net transport of N from
28 headwater streams is between 40-65% of the total N flux to lower order streams. Numerous studies have
29 illustrated correlations between water quality or ecological conditions and various measures of the extent
30 of urbanization, such as human population density or percent impervious surface (Hachmoller et al.,
31 1991; Charbonneau and Kondolf, 1993; Johnson et al., 1997; Thorne et al., 2000; Alberti et al., 2007; see
32 additional discussion of urbanization in Annex C). In many higher order streams and estuaries,
33 atmospheric N combines with fertilizer N in agricultural areas and with N from wastewater treatment
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1 facilities in urban areas, and the role of atmospheric deposition in residential and urban ecosystems is
2 rarely addressed (see Section 3.3.2.4 for additional discussion of inputs to estuaries).
3 In lowland areas, other terrestrial sources of N, such as fertilizer, livestock waste, septic effluent,
4 and wastewater treatment plant outflow, are often become much more important than in upland areas. In
5 lowland areas, it is difficult to determine the percent of atmospheric N that leaches to drainage water
6 because there are other ill-defined sources of N to drainage waters. In Table 3-14 studies are summarized
7 that address how atmospheric deposition of N to the estuary surfaces and to the terrestrial watershed
8 interact with the other anthropogenic sources of N to make up the total anthropogenic N load to the
9 system.
Table 3-14. Summary of N deposition effects on leaching in freshwater aquatic ecosystems.
Region/Country
New England
Neuse Estuary,
NC
Chesapeake Bay
system
Chesapeake Bay
system
Endpoint Observations
N sources in Modeling: Application of the statistical model SPARROW (SPAf ally Referenced Regression On Watershed
rivers and attributes) showed that first-order headwaters contributed 65%, 55%, and 40% of the N flux to 2nd, 4th, and
streams higher-ordered catchments, respectively. Atmospheric deposition accounted for almost 70% of the total simulated
N load to these headwater streams.
water [N] Observational: trends in N and P concentrations from 1998 to 2002 could be explained mainly by a combination
N sources of climate, management policies, and urban/agricultural development. Nutrient loading reductions did occur in
response to imposed management practices in the watershed, but they were affected by increases in human and
livestock population in the watershed. Thus, goals for estuarine and coastal nutrient loading reduction must
consider the influence of within-watershed development
Watershed N Modeling: The Choptank tributary of the Chesapeake Bay had become eutrophic over the last 50-1 00 years.
sources Systematic monitoring of nutrient inputs began in 1970, and there have been 2-5-fold increases in nitrogen (N)
and P inputs during 1970-2004 due to sewage discharges, fertilizer applications, atmospheric deposition, and
changes in land use. Hydrochemical modeling and land-use yield coefficients suggest that current input rates are
4- 20 times higher for N and P than under forested conditions existing 350 yr ago. The Choptank watershed
(1756 km2) is dominated by agricultural land use (62%), with only 5% urban development. 02 concentration in
bottom waters of the Patuxent estuary is consistently below 3 mg/L in summer; 02 levels have been steadily
decreasing in the Choptank estuary over the past two decades and now approach 3 mg/L in wet years
Watershed N Modeling: The Patuxent watershed (2260 km2) is dominated by forest (64%), with significant urban land use
sources coverage (16%) and less intensive agricultural development (20%). Sewage is a major cause of nutrient
enrichment. The low N: P of sewage inputs to the Patuxent results in an N-limited, P-saturated system, whereas
the Choptank is primarily limited by N, but with P limitation of phytoplankton during spring river flows. Reduced
eutrophication in dry years suggests that both estuaries will respond to significant decreases in nutrients
Ecosystem
Type/
Species
Rivers
Watershed/
estuary
Watershed/
estuary
Watershed/
estuary
Reference
Alexander
et al. (2002,
2007)
Burkholder
et al. (2006)
Fisher etal.
(Fisher, 1998)
2006
Fisher etal.
(Fisher,
1998), 2006
3.3.2.4. Estuarine and Coastal Marine Ecosystems
10 Estuaries and coastal marine environments tend to be N-limited, and many currently receive high
11 levels of N input from human activities (Vitousek, 1991; Howarth, 1996). The nature and extent of the
12 impacts on estuarine and coastal environments is, in part, related to the export of N from upland systems
13 to coastal environments, as discussed in previous sections. Denitrification is the primary mechanism of N
14 output from the estuary and back to the atmosphere (See Annex C). Important environmental effects
15 include increased algal blooms, depletion of dissolved O2 in bottom waters, and reduction in fisheries and
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1 sea grass habitats (Valiela and Costa, 1988; Valiela et al., 1990; Boynton et al, 1995; Paerl, 1995, 1997;
2 Howarth, 1996). The general process of estuarine eutrophication is depicted in Figure 3-33.
40-,
Overall eutrophic condition
No Problem /low Moderate low Moderate Moderate high
High
Few symptoms occur Symptoms occur Symptoms occur Symptoms occur Symptoms occur
at more than episodically and/or less regularly less regularly and/or periodically or
over a small to and/or over a over a medium to persistently and/or
medium area. medium area extensive area. over an extensive area.
Key ro symbols:
^ Submerged aquatic
J vegetation
Chlorophyll a
Nuisance/toxic
blooms
Macroalgae
O
Dissolved oxygen
Source: Brickeretal. (2007)
Figure 3-33. A conceptualization of the relationship between overall eutrophic conditions,
associated eutrophic symptoms, and influencing factors (N loads and susceptibility). Overall
eutrophic condition was assessed for estuaries throughout the U.S.
3 There is broad scientific consensus that N-driven eutrophication of shallow estuaries in the U.S.
4 has increased over the past several decades and that environmental degradation of coastal ecosystems is
5 now a widespread occurrence (Paerl, 2001). For example, the frequency of phytoplankton blooms and the
6 extent and severity of hypoxia have increased in the Chesapeake Bay (Officer, 1984) Pamlico estuary in
7 North Carolina (Paerl et al., 1998), and along the continental shelf adjacent to the Mississippi and
8 Atchafalaya River discharges to the Gulf of Mexico (Eadie et al., 1994). A recent national assessment of
9 eutrophic conditions in estuaries found that 65% of the assessed systems had moderate to high overall
10 eutrophic conditions (Bricker, 2007). Estuaries with high overall eutrophic conditions were generally
11 those that received the greatest N loads from all sources, including atmospheric and land-based sources
12 (Bricker, 2007). The relative importance of the various N sources varies from estuary to estuary.
13 Atmospheric sources are proportionately more important to estuaries that exhibit large surface area
14 relative to watershed drainage area, and in those estuaries that drain watersheds dominated by natural
15 ecosystems rather than agricultural or urban lands (Boyer et al., 2002).
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Assessing the contribution of atmospheric Nr deposition to total Nr loading
1 In the estuaries and coastal ecosystems in the U.S. that experience varying levels of N over-
2 enrichment, the importance of atmospheric deposition as a cause of eutrophication is determined by the
3 relative contribution of atmospheric versus non-atmospheric sources of N input.
4 Anthropogenic sources of N to estuarine and coastal ecosystems include atmospheric deposition,
5 wastewater discharge, agricultural runoff, and urban runoff. Valigura et al. (2000) estimated that direct
6 atmospheric deposition to the estuary surface generally constitutes at least 20% of the total N load for
7 estuaries that occupy more than 20% of their watershed. EPA (1999b) estimated that between 10% and
8 40% of the total N input to estuaries in the U.S. is typically derived from atmospheric deposition. NRC
9 (2000) concluded that EPA (1999a) underestimated the importance of atmospheric deposition as a
10 contributor to the total N load.
11 Estimates of the relative contribution of each major source have been developed by using the
12 Watershed Assessment Tool for Evaluating Reduction Scenarios for Nitrogen (WATERS-N) model
13 (Castro, 2002; Castro, 2002). Driscoll et al. (Driscoll, 2003) estimated annual net anthropogenic N inputs
14 to eight large watersheds in the Northeast for the year 1997. Input values of total atmospheric plus non-
15 atmospheric anthropogenic N ranged from 14 kg N/ha/yr in the watershed of Casco Bay in Maine to
16 68 kg N/ha/yr in the watershed of Massachusetts Bay (Driscoll, 2003). In all eight watersheds, net import
17 of N in food for humans (input into estuaries as wastewater) was the largest anthropogenic input.
18 Atmospheric deposition was estimated to be the second largest anthropogenic N input, ranging from 5 to
19 10 kg N/ha/yr, or ll%to 36% of the total inputs, with four watersheds ranging from 34% to 36%
20 (Driscoll, 2003). These results are broadly consistent with estimates by Boyer et al. (2002), who used a
21 similar N budgeting approach for 16 large northeastern U.S. river basins and reported that N deposition
22 contributes approximately 31% of the total N load to large river basins, although this fraction varies
23 regionally (Boyer et al., 2002). Boyer et al. (2002) considered only the portions of each basin above
24 USGS gauging stations, which often occurred above large population centers. Hence, the Driscoll et al.
25 (Driscoll, 2003) budgets included regions with greater human food consumption than those considered by
26 Boyer etal. (2002).
27 Castro and Driscoll (2002) studied 10 estuaries along the U.S. east coast and found total
28 atmospheric N inputs (watershed runoff plus direct deposition to the surface of estuary) accounted for 15-
29 42% of the total N inputs. Simulated reductions of atmospheric N deposition by 25% and 50% of current
30 deposition rates reduced the contribution made by atmospheric N deposition to the total N loads by 1-6%
31 and 2-11%, respectively. Overall, results from the simulated reductions suggested that considerable
32 reductions ( > 25%) in atmospheric N deposition were needed to significantly reduce the contribution
33 made by atmospheric N deposition to the total N loads. In a later study, Driscoll et al. (Driscoll, 2003)
34 estimated that the implementation of aggressive controls on both mobile N emissions sources and electric
August 2008 3-125 DRAFT-DO NOT QUOTE OR CITE
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1 utilities would produce an estimated reduction in estuarine loading in Casco Bay, ME of 13% (Driscoll,
2 2003).
•4W, N in food
1 1 I Atmospheric N deposition
Fertilizer N
80 T I I N in feed
• N fixation
Northeast
Mid-Atlantic
Source: Driscoll et al. (Driscoll, 2003)
Figure 3-34. Estimated anthropogenic N inputs to the estuaries of the northeastern U.S., in kg/ha/yr.
3 One the challenges in determining the contribution of atmospheric N deposition to estuaries is
4 estimating the inputs from upstream river basins. Smith et al. (1997) applied the SPAtially Referenced
5 Regressions on Watershed Attributes (SPARROW) model to streamwater chemistry data from the
6 National Stream Quality Accounting Network in order to evaluate NOs leaching in large river basins.
7 Leaching losses of N in large river systems provide important sources of N to estuaries and coastal marine
8 waters. Smith et al. (1997) concluded that much of the U.S. probably exports less than 5 kg N/ha/yr, but
9 that N export in watersheds of the northeastern U.S. is probably higher. For the watersheds that export
10 more than 10 kg N/ha/yr, Smith et al. (1997) concluded that fertilizer was the largest source of N (48%),
1 1 followed by atmospheric deposition (18%). In this analysis, fertilizer used for human food production was
12 considered to be the ultimate source of N contributed to waterways through waste water treatment plants.
13 If the analysis of N sources to estuarine water is restricted to only nonpoint sources of N, atmospheric
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1 deposition is often considered to be the largest individual source ((Howarth, 1996; Jaworski, 1997)Smith
2 et al., 1997; NRC, 2000; Howarth, 2007).
3 Overall, these estimates of the relative importance of atmospheric deposition, compared to non-
4 atmospheric sources of N, typically involve many assumptions regarding dry deposition, riverine fluxes,
5 and the relationship between human populations and wastewater inputs. Thus, such estimates entail
6 considerable uncertainty. It is clear, however, that the relative contribution of atmospheric deposition to
7 total N loading varies with the atmospheric N deposition level, land use, watershed and estuary areas, and
8 hydrological and morphological estuarine characteristics. It is also clear that atmospheric deposition is
9 generally an important contributor to the overall N load that stimulates eutrophication of estuaries in the
10 eastern U.S. (Paerl, 2001; Boyer et al., 2002; Driscoll, 2003). See Annex C for an additional discussion of
11 estuarine N budgets.
3.3.2.5. Summary of N, Effects on Biogeochetnical Cycling of N and Associated
Chemical Indicators
Terrestrial Ecosystems
12 The evidence is sufficient to infer a causal relationship between Nr deposition and the
13 alteration of biogeochemical cycling of N in terrestrial ecosystems. The main source of new Nr to
14 ecosystems is atmospheric deposition. Nr deposition disrupts the nutrient balance of ecosystem. The
15 chemical indicators that are typically measured are summarized in Table 3-11 and include: NO3 leaching,
16 C:N ratio, N mineralization, nitrification, denitrification, foliar N and soil water NO3 and NH4+. Values
17 for these indicators that represent a threshold for the onset of a related biogeochemical or biological effect
18 are also summarized. Note that N saturation does not need to occur to cause adverse effects on terrestrial
19 ecosystems. However, in some regions N saturation is a plausible mechanism of net nitrification and
20 associated NO3 leaching in drainage water. Substantial leaching of NO3 from forest soils to streamwater
21 can acidify downstream waters (see Section 3.2) and deplete soils of nutrient base cations, especially Ca
22 and Mg (Likens, 1998).
23 Aber et al. (2003) suggested that nearly all N deposition is retained or denitrified in northeastern
24 watersheds that receive less than about 8 to 10 kg N/ha/yr. Aber et al. (2003) further found that surface
25 water NO3 concentrations exceeded 1 (ieq/L in watersheds receiving about 9 to 13 kg N/ha/yr of
26 atmospheric N deposition (see Section 0). The lakes and streams found to have high NO3 concentration
27 were those receiving N deposition above this range, but responses were variable among those receiving
28 high N deposition. Above this range, mean NO3 export increased linearly with increasing deposition at a
29 rate of 0.85 kg NO3 kg N/ha/yr for every 1 kg N/ha/yr increase in deposition, although there was
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1 considerable variability in N retention among watersheds at higher rates of deposition (see Section
2 3.3.2.4) (Aber, 2003).
Wetlands
3 The evidence is sufficient to infer a casual relationship between Nr deposition and the
4 alteration of biogeochemical cycling of N in wetlands. Nr deposition contributes to total N load in
5 wetlands. The chemical indicators that are typically measured include: NO3 leaching, N mineralization,
6 and denitrification. N dynamics in wetland ecosystems are variable in time and with type of wetland and
7 environmental factors, especially water availability (Howarth, 1996). A wetland can act as a source, sink,
8 or transformer of atmospherically deposited N (Devito, 1989) and these functions can vary with season
9 and with hydrological conditions. Vegetation type, physiography, local hydrology, and climate all play
10 significant roles in determining source/sink N dynamics in wetlands (Devito, 1989; Koerselman, 1993)
11 Arheimer and Wittgren, 1994; Mitchell, 1996).
12 N mineralization has been shown to increase with N addition, and this can cause an increase in
13 wetland N export to adjacent surface water (Groffman, 1994). In general, leaching losses of NO3 in
14 water derived directly from wetlands are often small because of NO3 removal by denitrification.
15 Previous studies suggest that elevated N inputs to wetlands will often increase the rate of denitrification
16 (Dierberg and Brezonik, 1983; Broderick et al., 1988; Cooper, 1990). This process limits environmental
17 effects that are typically associated with increased N supply to soils and drainage waters; but increases the
18 contribution of greenhouse gasses to the atmosphere. Denitrification appears to be negligible in wetland
19 environments that are typically nutrient (including N) poor, such as some bogs and fens (Morris, 1991).
Freshwater aquatic
20 The evidence is sufficient to infer a casual relationship between Nr deposition and the
21 alteration of biogeochemical cycling of N in freshwater ecosystems. Nr deposition is the main source
22 of N to headwater streams, higher order streams and high elevation lakes. The predominant chemical
23 indicator is NO3 concentration in surface waters. Recent evidence documents examples of lakes and
24 streams that are limited by N and show symptoms of eutrophication in response to N addition. Elevated
25 surface water NO3 concentrations occur in both the eastern and western U.S.
Estuaries and coastal marine
26 The reviewed evidence is sufficient to infer a casual relationship between Nr deposition and
27 the biogeochemical cycling of N in estuaries and coastal marine waters. The contribution of
28 atmospheric Nr deposition to total N load is calculated for some estuaries and can be greater than
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1 40%. It is unknown if atmospheric deposition alone is sufficient to cause eutrophication. In general,
2 estuaries tend to be N-limited, and many currently receive high levels of N input from human activities to
3 cause eutrophication (Vitousek, 1991; Howarth, 1996). The most widespread chemical indicator of
4 eutrophication is dissolved O2.
3.3.3. N Deposition Effects on Productivity and C Budgets
3.3.3.1. Terrestrial Ecosystems
5 The following section discusses the mechanisms by which atmospheric N deposition alters C
6 cycling in terrestrial ecosystems. Although predicted values of atmospheric [CC^] in the future may alter
7 the interaction between N and terrestrial C cycling (Hyvonen, 2007);Norby et al. 1988; Schindler and
8 Bayley 1993), this topic is beyond the scope this review.
9 Because N availability often limits rates of net primary production in temperate terrestrial
10 ecosystems (Vitousek, 1991, there is an implicit link between the C and N cycles (Figure 3-35). Over 50%
11 of plant N is used for photosynthetic enzymes. Because N is necessary for photosynthesis, rates of
12 photosynthesis and net primary productivity (NPP) typically correlate with metrics of N availability such
13 as leaf N content and net N mineralization rate (Field, 1986); Reich et al., 1997a, b; Smith et al., 2002). A
14 meta-analysis of 126 N addition experiments evaluated N limitation of NPP in terrestrial ecosystems by
15 evaluating aboveground plant growth in fertilized to control plots (LeBauer, 2008). The results showed
16 that most ecosystems are N limited with an average 29% growth response to N. The response ratio was
17 significant within temperate forests, tropical forests, temperate grasslands, tropical grasslands, wetlands,
18 and tundra, but not deserts (LeBauer, 2008).
19 However, it can be difficult to directly apply the results of fertilizer studies to the question of
20 chronic N deposition effects on ecosystems. Most fertilization studies do not mimic the long-term N
21 loading profile of atmospheric N additions. Most studies add N in a large pulse at one time, rather than
22 chronic N loads of smaller amounts over time as are delivered by atmospheric deposition. Ecosystem
23 growth response to a pulse of 100 kg N/ha at one time may not the be same as 10 kg N/ha/yr for 10 years,
24 although the net load is the same. In addition, climate, ozone and even atmospheric CO2 concentrations
25 can also affect ecosystem C dynamics (Ollinger, 2002) Nowak et al. 2003).
26 Unfortunately, few studies have isolated the effect of chronic N deposition on plant growth and
27 ecosystem C balances. It is difficult to untangle the effects of climate, disease and land use from N
28 deposition effects. Therefore to address this question, we rely on fertilization studies, modeling, gradient
29 studies, and time-trend analyses.
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1 Carbon accumulation in terrestrial ecosystems occurs in the plants and in the soil. C cycling is a
2 complex process that can be quantified into ecosystem C budgets on the basis of net ecosystem
3 productivity (NEP), defined as gross primary productivity (GPP) after subtracting the ecosystem
4 respiration (vegetative + heterotrophic respiration). Factors that may increase terrestrial CC>2 sinks on a
5 regional scale are increased NPP, and decreased respiration of CC>2 from leaf or soil processes. These two
6 mechanisms may be altered by atmospheric deposition of N, tropospheric ozone exposure, increased CC>2
7 concentrations, land-use change and factors associated with climate warming (Myneni et al., 1997;
8 Melillo et al., 2002, Beedlow et al. 2004, Schimel et al. 2001, Caspersen et al. 2001). This adds to the
9 uncertainty regarding the sources and sinks in the terrestrial biosphere (Houghton 2003). It should be
10 noted that it is not known whether present terrestrial C sequestration can be sustained, in view of limits of
11 forest re-growth, nutrient availability and uncertainty about changes in the frequency of disturbances such
12 as fire (Scholes and Noble 2001; Schimel et al. 2001).
Forests
C Allocation Interactions with Stressors
13 Addition of Nr is believed to decrease resistance to drought stress because plants balance their
14 allocations of sunlight and nutrients in order to grow above ground to maximize light and C capture and
15 to grow below ground to maximize capture of water and other nutrients, including N (Sterner and Elser,
16 2002). Fertilization with N often causes trees to allocate less photosynthate to roots than shoots (Minnich
17 et al., 1995). Because shoot growth is more enhanced than root growth, the water supply from the roots
18 can become insufficient during periods of drought to support water loss via transpiration (Fangmeier
19 et al., 1994; Krupa, 2003). Smaller root systems also cause greater susceptibility to windthrow. For
20 example, in Switzerland, the amount of trees uprooting during a strong storm event was significantly
21 correlated with base saturation and N concentration in the leaves (positively) in Beech trees (Braun et al.
22 2003). Across Europe, soil acidification and soil N content since the 1980s have accentuated the storm
23 sensitivity due to changes in root architecture, including more superficial roots and loss of root
24 ramification (Nilsson et al. 2004; Godbold et al., 2003; Puhe, 2003; Braun, 2003).
25 Deposition of Nr is also believed to reduce frost hardiness of plants (Dueck et al., 1990). This is
26 likely because the addition of Nr prolongs the growth phase of the plants during autumn and delays winter
27 hardiness. This can cause detrimental effects if the first frost occurs early in the autumn period (Cape
28 et al., 1991). Plant shoots also appear to be more susceptible to pathogenic fungal infection under high N
29 status or changed nutrient balance such as an increase in the ratio of N to K+ (Ylimartimo, 1991; Krupa,
30 2003). As opposed to shoot diseases, addition of Nr has been found to reduce mycorrhizal fungus
31 colonization of roots (see more detailed discussion in Section 3.3.5.1).
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Above-ground processes
1 There is substantial evidence that N additions to trees cause increased leaf-level photosynthetic
2 rates. However, the potential for N deposition to increase above-ground C biomass it is limited for
3 reasons related to the biogeochemical cycling of N (see more detailed discussion in Section 3.3.2.1).
4 Briefly, C:N stoichiometry of the forest ecosystem compartments determines the C response to N
5 deposition. Only a small portion of added N is taken up by vegetation, thus only a small portion of N
6 contributes to C capture by trees (Nadelhoffer et al., 1999). A recent study reported that tree biomass (e.g.,
7 foliage, woody tissue, and fine roots) accumulated 7 to 16% of N additions (Nadelhoffer et al., 2004). N
8 may be immobilized in the soil, leached out before biological assimilation, or, upon the addition of N,
9 some other factor may become limiting to growth (e.g., water or other nutrients). Even though only a
10 portion of N deposition is incorporated into vegetation, the general result of additional N is an increase in
11 leaves, wood, and root biomass (Nilsson and Wiklund, 1995).
C02
CO..
photosynthesis
autotrophic •Ł
respiration 3
1 O
uptake
Nitrification/denitrification
mycorrhiza
i
heterotrophic
respiration Litter
1 coarse woody debris
I !
N deposition
>tf immolation Soi|mmera|N * N fixation
'*
mineralization
[ICICIUUUJJIIII,
respiration
decomposition
Soil organic matter
mineralization
Nleachln9
Figure 3-35. Interactions between the carbon and N cycles.
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Table 3-1 5.
Region/Country
Europe
Norway
Sweden
Bear Brook, ME,
U.S.
Fernow
Experimental
Forest, WV, U.S.
Harvard Forest,
MA, U.S.
Summary of
Endpoint
forest Biomass
growth (tree ring
increments)
growth (stem
volume)
growth (basal area)
growth
mortality
N effects on forest carbon cycling.
Observations
Modeling: using growing stock of large forest regions over an entire country as empirical data,
the authors determine forest biomass is accumulating, largely in response to increases in
forest area and improved management, but other possible mechanisms of growth
enhancement (including N) cannot be ruled out
Deposition gradient: A comprehensive analyses of regional forest growth trends analyzed tree
increment cores from more than 31,000 plots. In this study, growth increased during the 1960s
and 1970s and then declined in the 1990s, especially in southern regions exposed to the
highest rates of N deposition
Field addition: chronic fertilization at 30 kg N/ha/yr continued to stimulate stemwood
production even after 30 years, whereas a higher application (90 kg N/ha/yr) decreased stem
volume growth, and an intermediate application (60 kg N/ha/yr) had little positive or negative
effect relative to the control plots
Field Addition: basal area increment of sugar maple was enhanced 13 to 104% by addition of
25 kg N/ha/yr as ammonium SCU2~ ((NHU^SCU), whereas red spruce was not significantly
affected.
Field addition: The application of 35 kg N/ha/yr as (Mm) 2SCU enhanced growth of (Prunus
serotina) and yellow poplar (Liriodendron tulipifera) during the first 7 years, but led to reduced
growth of these species relative to control trees in years 9 through 12, with no change in red
maple or sweet birch (Betula lenta)
Field addition: chronic N addition levels of 50 and 150kg N/ha/yr for 15 years caused a 31%
and 54% decrease, respectively, in red pine growth. As red pine has died, striped maple
(Acer pensylvanicum), black cherry, and black birch (Betula lenta) have increased their
Forest type/
species
Forests from Austria,
Finland, Sweden,
France, Germany ,
and Switzerland
boreal forest (Picea
abies and Pinus
sylvestris)
Boreal forest
Scots pine forest
sugar maple and red
spruce
black cherry, yellow
poplar, red maple,
sweet birch
red pine, striped
maple, black cherry,
black birch
Reference
Kauppietal.,
1992; Spiecker
etal., 1996
Nellemann and
Thomsen, 2001
Hogbergetal.,
2006
Elvir etal., 2003
DeWalleetal.,
2006
Magi II etal., 2004
northeastern U.S. live basal area
Harvard Forest,
MA, U.S.
Ysselsteyn.The
Netherlands
growth
mortality
root production
growth
root production
Southern CA, U.S.
CA, U.S.
CA, U.S.
California
California
North Carolina and
Virginia
N- saturation-
reduced soil base
saturation, and lack
of a growth response
Growth
contributions to annual litterfall production.
Field addition: In a high-elevation red spruce-balsam fir (Abies balsamea) forest in the, N red spruce-balsam fir
fertilization over 1 4 years led to a decrease in live basal area (LBA) with increasing N
additions. In control plots, LBA increased by 9% over the course of the study, while LBA
decreased by 18% and 40% in plots treated, respectively, with 15.7kg N/ha/yr and 31. 4 kg
N/ha/yr.
Field addition: N fertilization of a 50-year-old red-oak/red maple stand largely stimulated old red-oak, red
productivity, although the drought in 1995 induced significant mortality in small red maple maple
trees. Fine root biomass was slightly, but not significantly, lower in highly fertilized stands
relative to controls in both red pine and oak/maple ecosystems
Field addition and deposition exclusion: improvements in wood accumulation rate, root Coniferous- Picea
production, and mycorrhizal associations occurred when a "clean roof" was installed at the site abies, Picea
receiving the highest rate of N deposition (>40 kg N/ha/yr). Decreased production of fine roots sitchesis,
may predispose N-fertilized plants to be more sensitive to intermittent drought, as well as to Pseudotsuga
nutrient depletion exacerbated by acid deposition. menziesii, Pinus
sylvestris
Observational: Areas of chaparral and mixed conifer forests that receive very high levels of chaparral and mixed
dry N deposition in southern California have experienced significant environmental change conifer
over the past several decades
Observational: Some southern California forests experience N deposition up to 45 kg N/ha/yr, mixed conifers;
and that increased N deposition caused increased growth of Jeffrey and ponderosa pine Jeffrey and
stands. ponderosa pine
growth (productivity)
and mortality
litter accumulation,
above-ground woody
biomass, fire
susceptibility
growth
Observational: high inputs of reactive N appear to exhibit decreases in productivity and Conifer forests
increases in mortality (Fenn, 1998).
Field addition: N fertilization has been shown to cause increased litter accumulation and C Ponderosa pine
storage in above-ground woody biomass, which in turn may lead to increased susceptibility to
more severe fires.
increased N deposition caused increased growth for Jeffrey (Pinusjeffreyi) and ponderosa mixed conifers
pine (Pinus ponderosa) stands,
growth (basal area), Deposition gradient: Results from a study of 46 forest plots on six sites in North Carolina and American beech,
foliar chemistry, Virginia dominated by American beech, sugar maple, and yellow birch suggested that N sugar maple, and
nitrification and deposition is associated with changes in basal area, foliar chemistry, and nitrification and yellow birch
mineralization mineralization rates. Growth rates for the three tree species were similar at the lowest rates of
N deposition, and then diverged as N deposition increased, with growth of yellow birch and
American beech decreasing at the high N deposition loads. These differential growth rates
have the potential to affect forest structure and biodiversity
(McNulty et al.,
2005)
Magill et al., 2004
Boxman et al.,
1998b Emmett
et al. (Emmett,
1998)
Fennetal., 1996,
2003a
Takemoto et al.,
2001
(Fenn, 1998)
Fenn et al., 2003a
Takemoto et al.
(Takemoto, 2001)
Boggs et al., 2005
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Region/Country
California, Sequoia
National Park
Michigan
Endpoint
growth
ANPP and surface
soil organic matter
Observations
Field addition: Aspen (Populus tremuloides) have been reported to show positive growth
effects from fertilization at N deposition rates as low as 10 kg N/ha/yr
Field addition: Chronic N fertilization (30 kg N/ha/yr) for 20 years caused significant increases
in ANPP by 10% and surface soil organic matter (0-10 cm) by 26%
Forest type/
species
Aspen
Sugar maple
Reference
Bytnerowicz
(Bytnerowicz,
2002)
Pregitzer et al.
2008
1 In order to understand the effects of added N to forest ecosystems, it is helpful to examine the
2 results of modeling projects and experimental N additions. Experimental N additions to forest ecosystems
3 have elicited positive growth responses in some, but certainly not all, organisms (Emmett, 1999; Elvir
4 et al., 2003; DeWalle et al., 2006; Hogberg et al., 2006). Forest growth enhancement, to the extent that it
5 occurs, can potentially exacerbate other nutrient deficiencies, such as Ca, Mg, or K. Multiple long-term
6 experiments have demonstrated transient growth increases followed by increased mortality, especially at
7 higher rates of fertilization (Elvir et al., 2003; Magill et al., 2004; McNulty et al., 2005; Hogberg et al.,
8 2006).
^ 10
E
E
Q)
E
"ro
'o
c
ro
o
9 -
8 -
7 -
6 -
5 -
4 -
3 -
2
O > 15 Kg N/ha/yr (n = 1183)
• 7 -15 kg N/ha/yr (n = 2389)
A < 7 kg N/ha/yr (n = 28034)
1940
1950
1960
1970
Year
1980
1990 2000
Source: Nellemann and Thomsen (2001)
Figure 3-36. Mean 5-year radial increment from 31,606 core samples from Picea abies during the
period 1945 to 1996 for three atmospheric N deposition zones (high, medium, and low wet N-
deposition in 1990), respectively. Note that the decline in radial increment after 1975 corresponds
with the peak in exceedances for critical loads for the same areas. The increase and subsequent
decline from 1965-1996 is significant (p < 0.01) using Kruskal-Wallis analysis with Dunn's tests.
S.E.s are all below 5% or 1-3.5 mm increment.
9 Experimental N addition studies on forest ecosystems show a range of responses in terms of
10 mortality and productivity. In general, moderate to high additions of N led to either no significant change
11 in growth rates or transient growth increases followed by increased mortality, especially at higher rates of
12 fertilization (Elvir et al., 2003; Magill et al., 2004; McNulty et al., 2005; Hogberg et al., 2006; Table
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1 3-15). An additional line of evidence comes from the experimental N removal studies: removal of N and S
2 from throughfall increased tree growth in Europe (Beier et al., 1998; Boxman et al., 1998).
3 Decreased growth and increased mortality have more commonly been observed in high-elevation
4 coniferous stands than in lower elevation hardwood forests, and these differences have been partially
5 attributed to higher inputs of N at higher elevation and to response characteristics of coniferous, as
6 opposed to deciduous, trees (Aber et al., 1998). Conifer forests that receive high inputs of Nr appear to
7 exhibit decreases in productivity and increases in mortality (Fenn, 1998). For example, fertilization
8 experiments at Mount Ascutney, VT suggested that N saturation may lead to the replacement of slow-
9 growing spruce-fir forest stands by fast-growing deciduous forests that cycle N more rapidly (McNulty
10 etal., 1996, 2005).
Below-ground processes
11 Soils contain the largest near-surface reservoir of terrestrial C, with more than 50% of C captured
12 annually by plants may be allocated below ground (Kubiske and Godbold, 2001). Therefore,
13 understanding the factors that control soil C storage and turnover is essential for understanding the C
14 cycle and sequestration. Although there remains considerable uncertainty in the potential response of soil
15 C to increases in reactive N additions (Neff et al., 2002), a meta-analysis by Johnson and Curtis (2001)
16 suggested that N fertilization caused an 18% increase in soil carbon content.
17 There is also evidence of a relationship between N deposition and root production Nadelhoffer
18 (2000) argued that it is likely that N deposition functions to decrease forest fine-root biomass but to
19 stimulate fine-root turnover and production. However, very high levels of N ( > 100 kg N/ha/yr)
20 decreased root life span of Pinusponderosa (Johnson et al., 2000).
21 Litter fall is usually the dominant source of soil organic C and a substantial source of organic N.
22 Decomposition of litter fall is often facilitated by heterotrophic bacteria and mycorrhizae. The quantity of
23 litter has been shown to increase with elevated N deposition (Schulze et al., 2000), with the result of
24 increased microbial metabolism in soil. It is also well demonstrated that increased N availability reduces
25 the ratio of C:N in leaf tissue. In turn, lower C:N in leaf litter has been shown to cause faster initial rates
26 of decomposition (Melillo et al., 1982), however the biochemistry of the leaf tissue is also important and
27 higher N litter can actually decompose more slowly in the long-term (Berg 2000). Under higher
28 decomposition rates, N bound by leaf organic matter is released over a shorter period and lead to lower N
29 retention by the soil (De vries 2006). A 10-year experiment that investigated decomposition in 21 sites
30 from 7 biomes found net N release from leaf litter is predominantly driven by the initial N concentration
31 and mass remaining regardless of climate, edaphic conditions, or biota (Parton et al., 2007). A recent
32 meta-analysis by Knorr et al. (2005) indicated that, as expected, litter decomposition was stimulated by
33 additional N deposition, however only at sites with low ambient N deposition ( < 5 kg N/ha/yr).
August 2008 3-134 DRAFT-DO NOT QUOTE OR CITE
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1 Additional N deposition reduced decomposition at sites with moderate levels of N deposition (5 to 10 kg
2 N/ha/yr).
3 Soil respiration is the dominant source by which plant-assimilated C is returned to the atmosphere
4 via CC>2. Changes in the magnitude of soil CC>2 efflux due to changes in environmental conditions will
5 likely influence the global atmospheric CC>2 budget (Schlesinger and Andrews, 2000). The effects of N
6 addition on soil respiration are mixed; reductions at high levels of N (Lu, 1998, Bowden et al., 2004), no
7 effect (Vose et al., 1995), and increases (Griffin et al., 1997; Mikan et al., 2000) all have been observed.
8 At the Harvard Forest LTER Site Chronic Nitrogen Amendment Study, N additions increased soil
9 respiration for hardwood stand, but not for pine stand during the first year of fertilization. However,
10 continued N additions over a decade caused a 40% decrease in soil respiration for both stands and that
11 was attributed mostly to a decrease in microbial respiration (Bowden et al., 2004).
Regional Trends in NEPandNEE
12 An analysis of > 100 young and mature forest stands from around the world indicated that annual
13 values of CC>2 exchange varied from approximately -100 to 250 g C/m2/yr for boreal forests and 250 to
14 700 g C/m2/yr for temperate forests (Malhi et al., 1999). Net ecosystem exchange (NEE), defined as the
15 difference between NPP and heterotrophic respiration, was positive when the forest was a sink that took
16 up CO2. Townsend et al. (1996) and Holland et al. (1997) modeled the impact of NOY and NHX
17 deposition on ecosystem C budgets by combining estimates of emissions with three dimensional transport
18 models. They used spatially explicit estimates of N inputs and climate data as drivers for a process-based
19 biogeochemical model to simulate ecosystem C dynamics globally. Their simulations predicted that CO2
20 C uptake due to NOY deposition on land surfaces ranged from 0.3 to 1.4 Pg C uptake/yr (Townsend et al.,
21 1996; Holland et al., 1997; Holland and Lamarque, 1997). The model allowed for variations in the degree
22 of ecosystem N retention. The highest C uptake was calculated when trees were assumed to uptake 80%
23 of N inputs, which is a likely overestimation because field studies suggested trees only took up a small
24 portion (7-16%) of N deposition.
25 Analyses of satellite observations of canopy greenness over the last 20 years across North America
26 suggests enhancement of NEP in some regions, corresponding to observed changes in climate and forest
27 management. Few such changes were observed in the northeastern U.S., where rates of N deposition are
28 relatively high (Hicke et al., 2002). In another study, evaluation of tree growth rates in five states
29 (Minnesota, Michigan, Virginia, North Carolina, and Florida) found little evidence for growth
30 enhancement due to any factor examined, including N deposition, carbon dioxide (CO2) fertilization, or
31 climate change (Caspersen et al., 2000). Potential effects of N deposition on boreal forests of North
32 America are of concern in part due to the large size of this terrestrial biome. Climate warming and N
33 deposition may increase NPP and C sequestration in the boreal forest, but may also stimulate
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1 decomposition of soil organic matter, potentially leading to a net loss of C from the ecosystem
2 (Kirschbaum, 1994; Makipaa et al., 1999).
3 A recent European study suggested that N deposition increased forest growth (Magnani, 2007), but
4 these findings have been disputed. Magnani et al. (Magnani, 2007) reported a strong correlation between
5 estimated average long-term NEP and estimated 1990 wet N deposition (Holland et al. 2005) for 20 forest
6 stands mostly in western Europe and the conterminous U.S. The authors reported that when confounding
7 effects of disturbance were factored out, carbon sequestration was found to be increased by moderate N
8 deposition (estimated up to 9.8 kg N/ha/yr). However, this study did not evaluate forest stands that receive
9 higher levels of N deposition that may be showing negative symptoms of N saturation. Several responses
10 to this study have been critical of the methods and conclusions have been published (De Schrijver et al
11 2008, De Vries et al. 2008, Sutton et al. 2008). For example, Sutton et al. (2008) re-analyzed the data
12 from Magnani et al. (Magnani, 2007) and concluded the NEP response to N response reported by
13 Magnani et al. (2008) was implausibly high (725 kg C/wet-deposited N). After considering the
14 uncertainties in wet and dry N deposition and climate variability, Sutton et al. (2008) reported the
15 estimated NEP response to N deposition was 68 kg C/ deposited N. Sutton et al (2008) concluded that N
16 deposition remains an important driver of NEP, but did not find support that the NEP was overwhelmingly
17 driven by N deposition.
18 EPA conducted a meta-analysis of 17 observations from 9 studies in U.S. forests to examine the
19 impact of N fertilization on forest ecosystem C content (EC). Here EC was defined as the sum of C
20 content of vegetation, forest floor and soil (Johnson et al. 2006). To avoid possible confounded variability
21 caused by site conditions, this meta-analysis only included studies of which control and treatment sites
22 experienced same climatic, soil and vegetation conditions. Studies on N nutrient effects along a
23 deposition gradient, such as Magnani et al. (Magnani, 2007), were not included. EPA's meta-analysis
24 revealed that while there was a great deal of variation in response, overall N addition increased EC by 6%
25 for U.S. forest ecosystems (see Figure 3-37). Different from Magnani et al. (Magnani, 2007), this study
26 did not find any correlation between the amount of N addition and the response magnitudes of EC.
27 However, it is uncertain if short term C accumulation may lead to long term C sequestration. N
28 fertilization could reduce the capacity of ecosystem to sequester decay resistant soil C. Giardina et al.
29 (Giardina, 2004) found that although N fertilization significantly increased plant production, the C flux
30 moving to mineral soil was reduced by 22% in a humid tropical forest in Hawaii. Mycorrhizal biomass
31 comprises a substantial carbon pool - represent up to 15% of soil organic matter in some ecosystems
32 (Vogt et al. 1982). A meta-analysis by (Treseder, 2004) suggested that mycorrhizal abundance decreased
33 15% under N fertilization.
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17 -
I /
i_
E '
i s-
c
o
"ro
<5 2 -
n
o
1 -
n -
/
I
__
1 ft
I *
-
1
Ł
^
^
<
C
»
mean response ratio
H coniferous
^^%i deciduous
r
%
\
'$
2
\
i
9
!
i"
/
/
!
/
i
*5
/
/
/
/
/
/
-
p
__
0.8
0.9
1.0 1.1
response ratio
1.2
1.3
Figure 3-37. Effects of N addition on forest ecosystem C content. The bars show the distribution of
the number of studies categorized by vegetation type. The dot with error bars shows the overall
mean response ratio with 95% Cl.
Arctic Tundra
\ Arctic tundra is adapted to cold temperature, short growing season, high soil moisture, and
2 periodically low soil O2 level. In general, arctic tundra plants respond to reduced N availability by
3 changing the allocation of biomass to favor root growth (Bloom, 1985) or changing the efficiency with
4 which N is used or stored (Chapin, 1980).
5 Mack et al. (2004) examined C and N pools in a long-term fertilization experiment at the arctic
6 Long-Term Ecological Research site near Toolik Lake, AK. Fertilized plots in moist acidic tundra
7 received 10 g N and 5 g N/m2/yr from 1981 to 2000. This is approximately 5 to 8 times the annual soil N
8 uptake requirement for above-ground production in the ecosystem. Two decades of fertilization shifted
9 community composition from graminoid tundra dominated by the tussock-forming sedge, Eriophorum
10 vaginatum, to shrub tundra dominated by Betula nana (Shaver et al., 2001). Consequently, this greatly
11 increased above-ground NPP, but had a larger effect on decomposition than on plant production, resulting
12 in a net loss of almost 2,000 g C/m2 from this ecosystem over 20 yr (p < 0.04). Carbon storage increased
13 above ground because of the accumulation of woody shrub biomass and litter, but this was offset by a
14 larger decrease of C in below-ground pools due to a pronounced decrease in the C contained in deep
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1 organic ( > 5 cm depth) and upper mineral soil layers. This study clearly showed that increased nutrient
2 availability enhanced decomposition of below-ground C pools in deep soil layers more than it increased
3 primary production, leading to a substantial net loss of C from this ecosystem.
4 The key process responsible for the C loss was identified as increased deep soil C decomposition in
5 response to increased nutrient availability. The authors noted that increasing temperatures may amplify
6 these effects and further stimulate C losses from high-latitude systems. As temperature rises, the amount
7 of N released due to a 3 to 7 EC increase in mean annual temperature (MAT) is likely to range in
8 magnitude from 7 to 9.4 g N/m2/yr, respectively (Mack et al., 2004). This will cause species shifts in the
9 vegetation community from tussock to increased shrub abundance and lead to decreased ecosystem C
10 storage. Finally, the decreased soil moisture and increased depth of thaw with temperatures rise are
11 predicted to have a positive effect on decomposition (Shaver, 2001), releasing more CO2.
Grasslands
Below-ground Factors
12 An investigation by Neff et al. (2002) of long-term effects (10 years) of N deposition (10 kg
13 N/ha/yr) in a dry meadow ecosystem indicated that N additions significantly accelerated decomposition of
14 soil C fractions with decadal turnover times while further stabilizing soil C compounds in mineral -
15 associated fractions with multi-decadal to century lifetimes. Despite these changes in the dynamics of
16 different soil pools, no significant changes in bulk soil C were observed, highlighting a limitation of the
17 single-pool approach for investigating soil C responses to changing environmental conditions (Neff et al.,
18 2002). The authors noted that it remains to be seen if the effects that were caused by relatively high,
19 decadal-term fertilizer additions are similar to those which would arise from lower, longer-term additions
20 of N to natural ecosystems from atmospheric deposition.
Interactions with Fire
21 Several lines of evidence suggest that Nr deposition may be contributing to greater fuel loads and
22 thus altering the fire cycle in a variety of ecosystem types (Fenn et al., 2003a). Invasive grasses, which
23 can be favored by high N deposition, promote a rapid fire cycle in many locations (D'Antonio and
24 Vitousek, 1992). The increased productivity of flammable understory grasses increases the spread of fire
25 and has been hypothesized as one mechanism for the recent conversion of CSS to grassland in California
26 (Minnich and Dezzani, 1998).
27 High grass biomass has also been associated with increased fire frequency in the Mohave Desert
28 (Brooks, 1999; Brooks and Esque, 2002; Brooks et al., 2004). This effect is most pronounced at higher
29 elevation, probably because the increased precipitation at higher elevation contributes to greater grass
30 productivity. Increased N supply at lower elevation in arid lands can only increase productivity to the
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1 point at which moisture limitation prevents additional growth. Fire was relatively rare in the Mojave
2 Desert until the past two decades, but now fire occurs frequently in areas that have experienced invasion
3 of exotic grasses (Brooks, 1999).
3.3.3.2. Wetlands
Above-ground processes
4 The 1993 NOx AQCD showed that N applications, ranging from 7 to 3120 kg N/ha/yr, stimulated
5 standing biomass production by 6-413% (U.S. EPA, 1993). However, the magnitude of the changes in
6 primary production depended on soil N availability and limitation of other nutrients. The degree of N
7 limitation to growth is varied among wetlands across the U.S. (Bedford, 1999).
8 The genus Sphagnum dominates ombrotrophic bogs and some nutrient poor fens in the Northern
9 US and Canada. These mosses efficiently capture atmospheric deposition with retention rates between
10 50-90%, much of the variation due to the depth of the water Table (Aldous 2002a). Studies conducted on
11 4 species of Sphagnum in Maine (2 to 4 kg N/ha/yr ambient deposition) and New York (10 to 13 kg
12 N/ha/yr ambient deposition) document that higher N deposition resulted in higher tissue N concentrations
13 (Aldous 2001) and greater NPP (Aldous 2002a), but lower bulk density (Aldous 2002a). A study of
14 Sphagnum fuscum in six Canadian peatlands showed a weak, although significant, negative correlation
15 between NPP and N deposition when deposition levels were greater than 3 kg N/ha/yr (y = 150-3.4x,
16 p=0.04, R2=0.01) (Vitt et al. 2003). A study of 23 ombrotrophic peatlands in Canada with deposition
17 levels ranging from 2.7 to 8.1 kg N/ha/yr showed peat accumulation increases linearly with N deposition
18 (y = 2.84x +0.67, r2 =0.32, P < 0.001), however in recent years this rate has begun to slow indicating
19 limited capacity for N to stimulate accumulation (Moore et al. 2004).
20 Primary production of plant species from intertidal wetlands typically increases with N addition,
21 however most studies apply fertilizer treatments that are several orders of magnitude larger than
22 atmospheric deposition (Mendelssohn 1979, Wigand et al. 2003, Tyler et al. 2007, Darby and Turner
23 2008). In comparison, N loads brought by tidal water and ground water (565-668 kg N/ha/yr) are much
24 larger than N depositing directly to the surface of coastal marshes, which suggested that direct N
25 deposition may have limited impacts on this ecosystem (Morris 1991). On the other hand, indirect
26 atmospheric deposition that is N deposited to the watershed and transported via surface or ground water,
27 could be the major sources of the total N load to coastal marshes. For example, model calculation
28 suggested that the contribution from the atmosphere (36 million kg N/yr) was about 21-30% of the total
29 N loading (170 million kg N/yr) in Chesapeake Bay waters (EPA 2000). Therefore 30% of the N delivered
30 to wetlands via estuarine tides would originate from atmospheric deposition. Future studies are needed to
31 determine the role of indirect atmospheric N deposition on the nutrient budget of intertidal wetlands.
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Below-ground Processes
1 Bragazza et al. (2006) investigated the decomposition rates of recently formed litter peat samples
2 collected in nine European countries under a natural gradient of atmospheric N deposition from 2 to
3 20 kg/ha/yr. They found enhanced decomposition rates for material accumulated under higher
4 atmospheric N supplies resulted in higher carbon dioxide (CO2) emissions and dissolved organic carbon
5 release. The increased N availability favored microbial decomposition (i) by removing N constraints on
6 microbial metabolism and (ii) through a chemical amelioration of litter peat quality with a positive
7 feedback on microbial enzymatic activity. Although some uncertainty remains about whether decay-
8 resistant Sphagnum will continue to dominate litter peat, the data indicated that, even without such
9 changes, increased N deposition poses a serious risk to the valuable peatland C sinks.
Reduced vs. Oxidized N
10 The form of added N may regulate wetland response to N deposition. Experimental applications of
11 NO3 appear to have been less effective at stimulating wetland plant productivity than applications of
12 NH4+ (EPA, 1993). This may reflect higher rates of denitrification in response to the added NO3 ,
13 suggesting the importance of competition between plants and microbes for bioavailable N. Plants appear
14 to compete more successfully for NH4+ and microbes to compete more successfully for NO3 . An
15 important caveat expressed by U.S. EPA (1993), however, was that the results of relatively short-term N
16 fertilization experiments are not necessarily good predictors of long-term wetland community responses
17 to increased N inputs.
NEE of grassland, tundra and wetlands
18 In the meta-analysis of 16 observations from 9 publications on the relationship between N addition
19 and C sequestration of non-forest ecosystems, N addition had no significant effect on NEE of non-forest
20 ecosystems (Figure 3-38). N limitation to NPP is globally distributed and therefore plant productivity is
21 normally enhanced by N addition. A meta-analysis by Lebauer and Treseder (LeBauer, 2008) indicated
22 that N fertilization increased aboveground NPP (ANPP) in all non-forest ecosystems except for desert.
23 However, N addition also has been observed to stimulate ecosystem C loss. For example, N fertilization
24 stimulated soil organic carbon decomposition in arctic tundra. Increasing N deposition led to higher C
25 loss in temperate peatlands (See Section 3.3.3.2). In an agricultural experiment site, Khan et al. (Khan,
26 2007) observed that 40 to 50 years N fertilization resulted in a net decline in soil C despite massive
27 residue C incorporation. This meta-analysis indicated that N addition had no significant impact on C
28 sequestration in non forest ecosystems, which may be due to C gain via NPP was exceeded by C loss via
29 heterotrophic respiration.
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16 -
0)
.0
C
.0
H— »
cc
CD
W
.Q
O
2 -
1 -
mean response ratio
grassland
tundra
wetland
0.4
0.6
0.8
1.2
1.4
1.6
response ratio
Figure 3-38. Effects of N addition on NEE of non-forest ecosystems. The bars show the distribution
of the number of studies categorized by vegetation type. The dot with error bars shows the overall
mean response ratio with 95% Cl.
3.3.3.3. Freshwater Aquatic
1 N deposition effects on productivity are discussed here. The biogeochemical cycles of N, P and C
1 are linked in freshwater ecosystems (Figure 3-39), therefore N additions alter the balance of all three
3 cycles. In N-limited aquatic systems, atmospheric inputs of N increase productivity and alter biological
4 communities, especially phytoplankton. The results of numerous publications addressing the experimental
5 additions of N are tabulated in Annex C. Evidence that altered productivity leads to altered community
6 structure is discussed in Section 3.3.5.
7 Generally, the dose-response data for aquatic organisms such as those cited below are expressed in
8 concentration units, as mg/L or (imol/L of N, for example. Such concentration data cannot be directly
9 related to ecosystem exposure, which is generally expressed in such units as kg N/ha. This is because N
10 deposition can result in widely varying concentrations of N compounds (especially NO3 ) in water. For
11 convenience, a concentration of 1 mg/L of N (as, for example, in the case of NO3~-N or NH4+-N) is equal
12 to71.4(imol/Lor71.4(ieq/LofNO3"orNH4+.
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N-limitation
1 A freshwater lake or stream must be N-limited in order to be sensitive to N-mediated
2 eutrophication. There are many examples of fresh waters that are N-limited or N and P co-limited (e.g.,
3 (Elser, 1990; Fenn et al., 2003a; Tank and Dodds, 2003; Bergstrom et al., 2005; Baron, 2006; Bergstrom
4 and Jansson, 2006). Recently, a comprehensive study of available data from the northern hemisphere
5 surveys of lake along gradients of N deposition show increased inorganic N concentration and
6 productivity to be correlated with atmospheric N deposition (Bergstrom and Jansson, 2006). The results
7 are unequivocal evidence of N limitation in lakes with low ambient inputs of N, and increased N
8 concentrations in lakes receiving N solely from atmospheric N deposition (Bergstrom and Jansson, 2006).
9 These authors suggested that the majority of lakes in the northern hemisphere may have originally been
10 N-limited, and that atmospheric N deposition has changed the balance of N and P in lakes so that P-
11 limitation is generally observed today. If this is correct, the role of atmospheric N deposition as an
12 influence on aquatic primary production may have been underestimated throughout the entire history of
13 limnology.
CO,
Terrestrial input
CO,
respiration
deposition
C02
rvTTT.ii.ii./ tl
C02
W
1
CD
Gt
"^.u:;:^ ^".I",I,"."_"."^T^:; :i, resoiration r.
uptake
=fjg rrirnar
excretion JfP^uce
k
\nts decomposition
Figure 3-39. N cycle in freshwater ecosystem.
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1 Recent research (e.g., Wolfe et al., 2001, 2003, 2006; Lafrancois(Lafrancois, 2003; Das, 2005)
2 (Saros, 2005) has provided additional evidence indicating that N deposition has played an important role
3 in influencing the productivity of oligotrophic, high-elevation lakes in the western U.S. and Canada, and
4 the Canadian arctic. There is evidence suggesting historical N-limitation of some lakes based on
5 paleolimnological studies conducted in mountainous regions of the western U.S. that have been the
6 recipient of elevated levels of N, but not S, deposition over background values (see Section 3.3.4).
7 Interactions between N and P loading are discussed in Annex C.
8 Productivity investigations have included gradient studies in which the relationship between lake N
9 concentration and primary productivity (reported as chlorophyll a, NPP, or an index such as the lake
10 chemistry ratio of dissolved inorganic N [DIN] to total P, DIN:TP) was surveyed and correlated with
11 atmospheric N deposition. Productivity studies have also included lake and stream bioassays in which N
12 was added to waters in field or laboratory in order to measure the response. The most common, and
13 easiest to document, indicators of change in algal productivity are measures of the concentration of
14 chlorophyll a and water clarity. However, clarity is also strongly influenced by erosional inputs of fine
15 sediment to the lake or stream system. Chlorophyll a concentration is generally more directly tied to algal
16 productivity than is water clarity.
Phytoplankton Biomass
17 Studies have shown an increase in lake phytoplankton biomass with increasing N deposition in
18 several regions, including the Snowy Range in Wyoming (Lafrancois, 2003), the Sierra Nevada
19 Mountains in California (Sickman et al., 2003), and across Europe (Bergstrom and Jansson, 2006).
20 Gradient studies of undisturbed northern temperate, mountain, or boreal lakes that receive low levels of
21 atmospheric N deposition found strong relationships between N-limitation and productivity where N
22 deposition was low, and P and N+P limitations where N deposition was higher (Fenn et al., 2003a;
23 Bergstrom et al., 2005; Bergstrom and Jansson, 2006).
24 Bergstrom and Jansson (2006) concluded the eutrophication caused by inorganic N deposition
25 indicates that phytoplankton biomass in a majority of lakes in the northern hemisphere is limited by N in
26 their natural state. Chemical data from 3,907 lakes and phytoplankton biomass data from 225 lakes from
27 Swedish monitoring programs showed a clear north-south gradient of increasing lake concentrations and
28 algal productivity related to the pattern of increasing N deposition input (Bergstrom et al., 2005). The
29 lowest productivity was found at sites where wet N deposition was about 1.3 kg N/ha/yr; increasing
30 productivity occurred at greater than 2.2 kg N/ha/yr (Bergstrom et al., 2005). Although these lakes are all
31 in Sweden, the study size and the strong correlation between productivity and atmospheric N deposition
32 makes the results likely relevant to North American audiences.
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1 Experiments conducted with mesocosms in lakes where NO3 was below the detection level found
2 a strong response in phytoplankton biomass with additions of N (bringing concentrations to ~1.0 mg N/L)
3 and even stronger responses to additions of N plus P, but not P alone (Lafrancois, 2004). The reverse was
4 also found in Colorado Front Range lakes with ambient NOs concentrations of ~1.0 mg/L: productivity
5 increased with additions of N plus P or P only, but not NOs alone (Lafrancois, 2004).
6 A meta-analysis of enrichment bioassays in 62 freshwater lakes of North America, including many
7 of the studies described above, found algal growth enhancement from N amendments to be common in
8 slightly less than half the studies (Elser, 1990). There was a mean increase in phytoplankton biomass of
9 79% in response to N enrichment (average of 46.3 (ieq/L N) (Elser, 1990). This meta-analysis was
10 recently repeated with a much large data set and similar results (Elser, 2007). Freshwater enrichment
11 bioassay studies from 990 separate studies worldwide were gleaned from the literature. The In-
12 transformed response ratio (RRX), a frequently used effect metric in ecological meta-analysis, was equal
13 at about 0.3 for N and P experiments with stream benthos (periphyton) bioassays, and approximately
14 equal at about 0.2 for lake phytoplankton. There was a stronger response to P than N in lake benthos
15 studies, but the RRX for N was still about 0.3, showing that many sites increased productivity when
16 fertilized with N alone (Elser, 2007).
Table 3-16. Summary of additional evidence of N effects on productivity of freshwater ecosystems.
Region
Lake
Tahoe,
CA
Endpoint
productivity water
clarity
Observation
Long-term (28 years) measurements showed that primary productivity has doubled, while water clarity
has declined, mostly as a result of atmospheric N deposition
Ecosystem
Type
lake
Reference
Goldman (Goldman,
1988); Jassbyetal.
(Jassby, 1994)
Alaska primary production N amendment experiments with 6.4 |jM N to elicited responses throughout the ecosystem, including small arctic (Benstead et al., 2005).
funaal biomass enhanced primary production, enhanced fungal biomass and elevated leaf litter decomposition rates, streams
decomposition rates
benthic
macroinvertebrate
and a fourfold to sevenfold greater benthic macroinvertebrate abundance
17
18
19
20
21
22
23
Chlorophyll a
The most widely used index of biological change in response to nutrient addition is measurement
of chlorophyll a concentration in water. Surveys and fertilization experiments show increased inorganic N
concentration and aquatic ecosystem productivity (as indicated by chlorophyll a concentration) to be
strongly related. For example, a series of in situ meso- and microcosm N amendment experiments more
than 30 years ago showed increases in lake algal productivity. Lake 226S in Ontario's Experimental Lake
District (ELD) showed doubling of average epilimnetic chlorophyll a over five years of fertilization.
However, because the response to P fertilization was much greater, the effects of N received less attention
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1 (Schindler, 1980). Other ELD lakes that had relatively low N to P concentration ratios experienced 3 to 10
2 times greater increases in chlorophyll a than Lake 226S (Schindler, 1980) f
3 Similar experiments at Castle Lake, California, the Snowy Range of southern Wyoming, and
4 Alaskan arctic foothill lakes yielded measurable increases in chlorophyll a and primary productivity with
5 N amendments (Axler and Reuter, 1996; Levine and Whalen, 2001; Nydick et al., 2003, 2004a;
6 Lafrancois, 2004).
Periphyton Biomass
7 N effects have been observed in periphyton which grows on rocks or sediment in lakes and streams
8 where there is sufficient light for photosynthesis. We found no studies that documented resource
9 requirements for periphyton, although several papers described stimulated growth with N amendments
10 from ecosystems throughout the U.S. (Annex C), including streams in Alaska, Arizona, Iowa, Texas,
11 Minnesota, Missouri, and lakes in California, Colorado, and Massachusetts. Growth stimulation occurred
12 with N additions ranging from 8 to 50 (iM/L, or with exposure to 0.5 M N concentrations on agar
13 substrate (e.g., Bushong and Bachmann, 1989; Allen and Hershey, 1996; Wold and Hershey, 1999; Smith
14 and Lee, 2006). Additional lake bioassay experiments that enriched the water column down into the
15 sediments found enhancement of periphyton growth on bioassay container walls in experiments in
16 California, Wyoming, and Massachusetts (Axler and Reuter, 1996; Nydick et al., 2004b; Smith and Lee,
17 2006). Strong N limitation of benthic algae has also been inferred in streams of Arizona (Grimm and
18 Fisher, 1986), California (Hill and Knight, 1988), Missouri (Lohman et al., 1991), and Montana (Lohman
19 and Priscu, 1992; Smith and Nicholas, 1999).
Trophic Status Indices
20 Nutritional responses of aquatic ecosystems to atmospheric N deposition are heavily dependent on
21 surface water P concentrations. Thus, chemical ratios of N to P can be very useful in evaluating
22 eutrophication potential. A series of papers, described below, has been published exploring nutrient
23 limitations and offering indices that describe the trophic state of freshwaters. Valuable insights have been
24 gained from several indices, including total N to total P (TN:TP), dissolved inorganic N to total P
25 (DIN:TP), dissolved inorganic N to total dissolved P (DIN:TDP), dissolved inorganic N to soluble
26 reactive P (DIN:SRP), and dissolved inorganic N to the ratio of chlorophyll a to total P (DIN:[chl a:TP]).
27 While there are publications that compare the effectiveness of some of these indices, it appears that
28 different indices are useful for different purposes; we make no attempt to favor one over another.
29 Algal growth was reported to be limited at DIN:TP values between 5 and 20 (Schindler, 1980)
30 Grimm and Fisher, 1986; Morris and Lewis, 1988; Downing and McCauley, 1992; Bergstrom and
31 Jansson, 2006). When DIN:TP ratios are greater than reference values, growth stimulation, N and P
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1 colimitation, or P limitation commonly occurs (Sickman et al., 2003b). In a Swedish lake survey, N-
2 limitation occurred in lakes where the DIN:TP ratio was less than 7 (concentrations < 33 (iM N/L). Co-
3 limitation of both N and P were found in lakes with DIN:TP ratio between 8 and 10, and P-limitation at
4 DIN:TP values greater than 10. This corresponds roughly to N concentrations of 45 to 80 (iM N/L for co-
5 limited lakes, and concentrations > 80 (iM N/L for P-limited lakes (Bergstrom et al., 2005). Other
6 thresholds for N-limitation were reported in the literature to occur at DIN:SRP ratios < 4 (Lohman and
7 Priscu, 1992) and < 10 (Wold and Hershey, 1999).
8 Bergstrom et al. (2005) reported a new index, (DIN:[chl a:TP]) to indicate the eutrophication of
9 lakes from N deposition. The choice of DIN/[chl a:TP] was based on whole lake experiments in Sweden
10 (Jansson et al., 2001) and permits the assessment of a possible eutrophication effect of N deposition
11 independent of differences in P input between lakes in different regions. These researchers found that the
12 mean chl a:TP ratios increased more than three times from low N to high N deposition areas, indicating
13 that N deposition contributed to eutrophication.
Freshwater summary
14 The productivity of many freshwater ecosystems is currently limited by the availability of N.
15 European and North American lakes may have been N-limited before human-caused disturbance, and
16 remote lakes may have remained N-limited until slight increases in atmospheric N deposition brought
17 about an increase in phytoplankton and periphyton biomass and induced P limitation. Increases in algal
18 biomass are associated with changes in algal assemblages that favor certain species over others. These
19 effects are described below in the discussion of biodiversity.
3.3.3.4. Estuarine and Marine
20 In coastal marine ecosystems, the nutrients most commonly associated with phytoplankton growth
21 are N, P, and Si (see Annex C for interactions between hydrology and nutrient cycling). Interactions
22 among the supplies of these nutrients can affect phytoplankton species composition in ways that might
23 impact ecosystem function (Riegman, 1992; Paerl, 2001). The relative proportions of these nutrients are
24 important determinants of primary production, food web structure, and energy flow through the
25 ecosystem (Dortch, 1992; Justic, 1995; Justic, 1995; Turner, 1998). There is a strong scientific consensus
26 that N is the principal cause of coastal eutrophication in the U.S. (NRC, 2000). On average, human
27 activity has likely contributed to a sixfold increase in the N flux to the coastal waters of the U.S., and N
28 now represents the most significant coastal pollution problem (Howarth et al., 2002; Howarth and
29 Marino, 2006). Atmospheric deposition is responsible for a portion of the N input.
30 Ecological effects of accelerated estuarine eutrophication and climatic perturbations such as
31 droughts, floods, and hurricanes are often expressed most closely at the level of the primary producers.
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1 Phytoplankton can be divided into functional groups that reflect ecological change, for example:
2 chlorophytes, cryptophytes, cyanobacteria, diatoms, and dinoflagellates (Pinckney et al, 2001).
3 These groups have the added benefit that their relative abundances are reflected in photopigment
4 indicators which can be easily measured in the laboratory (Paerl, 2003). Changes in phytoplankton
5 community composition, which may affect food web interactions, can have important effects on nutrient
6 cycling. For example, if the growth of phytoplankton species that are more readily grazed by zooplankton
7 (i.e., diatoms) is favored, trophic transfer will occur in the water column from diatoms to fish and nutrient
8 export will take place as fish move to the ocean. However, if the phytoplankton that are favored by
9 nutrient addition and disturbance are not readily grazed (i.e., cyanobacteria and dinoflagellates), trophic
10 transfer will be poor. In that case, more unconsumed algal biomass will settle to the bottom where it can
11 contribute to O2 consumption and associated hypoxia (Paerl, 2003).
12 In order to evaluate the impacts of eutrophication, five biological indicators were used in the recent
13 national assessment of estuary trophic condition: chlorophyll a, macroalgae, dissolved O2, nuisance/toxic
14 algal blooms, and submerged aquatic vegetation (SAV) (Bricker, 2007) (Figure 3-40). Each of these
15 indicators is discussed below and/or within the biodiversity section of this document (see Section 3.3.5.4).
N limitation
16 Estuaries and coastal waters tend to be N-limited and are therefore inherently sensitive to increased
17 N loading (D'Elia et al., 1986; Howarth, 2006). There is a scientific consensus that N-driven
18 eutrophication of shallow estuaries has increased over the past several decades and that environmental
19 degradation of coastal ecosystems is now a widespread occurrence (Paerl, 2001). For example, the
20 frequency of phytoplankton blooms and the extent and severity of hypoxia have increased in the
21 Chesapeake Bay (Officer, 1984) and Pamlico estuaries in North Carolina (Paerl et al., 1998) and along the
22 continental shelf adj acent to the Mississippi and Atchafalaya rivers discharges to the Gulf of Mexico
23 (Eadie et al., 1994). It is partly because many estuaries and near-coastal marine waters are degraded by N
24 enrichment that they are highly sensitive to potential adverse impacts from N addition from atmospheric
25 deposition.
26 N enrichment of marine and estuarine waters can alter the ratios among nutrients and affect overall
27 nutrient limitation. The sensitivity of estuarine and coastal marine waters to eutrophication from
28 atmospheric N deposition depends on the supply of, and relative availability of, N and P. At upstream
29 freshwater locations in Chesapeake Bay, P is often the limiting nutrient (Larson et al., 1985). At the
30 transition between fresh water and salt water, N and P may be co-limiting, whereas the saltwater
31 environments of the outer bay are usually N-limited (Fisher, 1998) Rudek et al., 1991). Nutrient limitation
32 varies in space and over time, in response to changes in discharge and temperature that interact with
33 estuarine morphology and hydrology (Paerl et al., 2006).
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Primary symptoms
Description
Chlorophyll a
(Phytoplankron)
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 eutroph ic 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.
Source: Brickeretal. (2007)
Figure 3-40. Description of the eutrophic symptoms included in the national estuary condition
assessment.
1 The data for 92 worldwide coastal marine sites analyzed by Smith (2006), for which measurements
2 of both total N and total P were available, illustrated that about half of the sites had total nitrogen
3 (TN):total phosphorus (TP) above the Redfield ratio, which is commonly used to evaluate nutrient
4 limitation in freshwater (TN:TP = 16). As was emphasized in earlier work on nutrient limitation in fresh
5 waters by Redfield (1958) and Reiners (1986), elemental stoichiometry is a fundamental property of life
6 that probably stems from the shared phylogenetic histories of marine and freshwater autotrophs (Sterner
7 and Elser, 2002; Smith, 2006).
8 In general, the scientific community is at an early stage in development of an understanding of the
9 effects of anthropogenic activities on the stoichiometry of nutrient loading to estuaries and marine waters
10 (Turner, 2002) Dodds, 2006). Changes in nutrient stoichiometry in estuarine and marine ecosystems could
11 alter algal assemblages and cascade to higher trophic levels (Frost et al., 2002).
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Low Moderate High
Chlorophyll a
0 200 400
I Kilometers
] Miles
0 100 200
on A •
^H High: symptoms occur periodically or persistently and/or over an extensive area.
i i Moderate high: symptoms occur less regularly and/or over a medium to extensive area.
i i Moderate: symptoms occur less regularly and/or over a medium area.
^M Moderate low: symptoms occur episodically and/or over a small to medium area.
^^H Low: few symptoms occur at more than minimal levels.
I I Unknown: insufficient data for analysis.
Change in eutrophic condition since 1999 assessment
A Symptoms improved since 1999 assessment.
O No change in symptoms since 1999 assessment.
V Symptoms worsened since 1999 assessment.
D Insufficient data to show trend
Source: Brickeretal. (2007)
Figure 341. A high chlorophyll a rating was observed in a large number of the nation's estuaries.
White squares indicate that data were not available for a particular estuary.
Chlorophyll a
1 Chlorophyll a concentration in estuarine or marine water is an indicator of total phytoplankton
2 biomass. It can signal an early stage of water quality degradation related to nutrient loading. High
3 concentration of chlorophyll a suggests that algal biomass is sufficiently high that it might contribute to
4 low dissolved O2 concentration due to increased decomposition of dead algae. In the national estuary
5 condition assessment, high chlorophyll a concentration was the most widespread documented symptom of
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1 eutrophication (Bricker, 2007) (see Figure 3-41). Half of the estuaries for which there were available data
2 exhibited high chlorophyll a concentration (Bricker, 2007).
3 San Francisco Bay, California is an example of an estuary that has experienced considerable
4 increases in chlorophyll a concentrations in recent years. Phytoplankton biomass in much of the bay has
5 increased by more than 5% per year from 1993 to 2004. During this time, modeled primary production
6 has doubled and nutrient loading is identified as one of eight possible causes (Cloern et al., 2006).
Macroalgal Abundance
7 Macroalgae are generally referred to collectively as seaweed. Macroalgal blooms can contribute to
8 loss of important SAV by blocking the penetration of sunlight into the water column. Although
9 macroalgal data for estuaries in the U.S. were generally sparse, the national estuary condition assessment
10 reported that conditions were moderate or high for 33 of the estuaries evaluated (Bricker, 2007).
Dissolved 62
11 The decomposition of organic matter associated with increased algal abundance consumes
12 dissolved O2 and can reduce dissolved O2 concentrations in eutrophic waters to levels that cannot support
13 aquatic life. Decreased dissolved O2 can lead to development of hypoxic or anoxic zones that are
14 inhospitable to fish and other life forms. Perhaps the most important environmental effect of N input to
15 coastal waters is the development of hypoxia. The largest zone of hypoxic coastal water in the U.S. has
16 been documented in the northern Gulf of Mexico on the Louisiana-Texas continental shelf. During
17 midsummer, this hypoxic zone has regularly been larger than 16,000 km2 (Rabalais, 1998). The timing,
18 duration, and spatial extent of hypoxia in this case are related mostly to the nutrient flux from the
19 Mississippi River (Justic, 1997; Justic, 1993; Rabalais, 1996; Lohrenz, 1997; Paerl, 2001).
20 Although impacts on dissolved O2 can be quite severe in the areas where they are manifested, the
21 national assessment reports that the severity of dissolved O2 impacts related to eutrophication are
22 relatively limited in many of the systems assessed (Bricker, 2007). In the shallow estuary of Long Island
23 Sound, the existence of extended periods of low dissolved O2 is a notable problem, and atmospheric
24 deposition is considered to comprise a significant fraction of the total N loading. Dissolved O2 levels
25 below 3 mg/L are common, and levels below 2 mg/L also occur. During some years, portions of the Long
26 Island Sound bottom waters become anoxic ( < 1 mg/L) (Bricker, 2007) (Figure 3-42).
Nuisance/Toxic Algal Blooms
27 Nuisance or toxic algal blooms reflect the proliferation of a toxic or nuisance algal species that
28 negatively affects natural resources or humans. Such blooms can release toxins that kill fish and shellfish
29 and pose a risk to human health. Unlike the other indicators of estuarine eutrophication, the role of
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1 nutrients in stimulating toxic algal blooms is less clear. Of the 81 estuary systems for which data were
2 available, 26 exhibited a moderate or high symptom expression for nuisance or toxic algae (Bricker,
3 2007).
% of years stations
recorded hypoxia
CDO
10-20
20-30
}0-
-------
1 authors did agree N deposition remains an important driver of NEPav, but did not support the NEPav was
2 overwhelmingly driven by N deposition. NCEA conducted a meta-analysis to examine the impact of N
3 fertilization on forest ecosystem C content, defined as the sum of C content of vegetation, forest floor and
4 soil (Johnson et al. 2006) and found that N addition increased ecosystem C by 6%.
5 Nr addition causes alterations to the C cycle of Tundra, however there is no evidence linking
6 deposition to Tundra ecosystem C dynamics. Mack et al. (2004) examined C and N pools in a long-term
7 fertilization experiment at the arctic Long-Term Ecological Research site near Toolik Lake, AK. This
8 study clearly showed that increased nutrient availability enhanced decomposition of below-ground C
9 pools in deep soil layers more than it increased primary production, leading to a substantial net loss of C
10 from this ecosystem.
11 Nr deposition causes alteration to the C cycle in freshwater wetlands. In Sphagnum-dominated
12 ombrotrophic bogs, higher N deposition resulted in higher tissue N concentrations (Aldous 2001) and
13 greater NPP (Aldous 2002a), but lower bulk density (Aldous 2002a). A study of 23 ombrotrophic
14 peatlands in Canada with deposition levels ranging from 2.7 to 8.1 kg N/ha/yr showed peat accumulation
15 increases linearly with N deposition (y = 2.84x +0.67, r2 =0.32, P < 0.001), however in recent years this
16 rate has begun to slow indicating limited capacity for N to stimulate accumulation (Moore et al. 2004).
17 Soil respiration has been studied in European countries under a natural gradient of atmospheric N
18 deposition from 2 to 20 kg/ha/yr. They found enhanced decomposition rates for material accumulated
19 under higher atmospheric N supplies resulted in higher CC>2 emissions from soil. Primary production of
20 plant species from intertidal wetlands typically increases with N addition, however most studies apply
21 fertilizer treatments that are several orders of magnitude larger than atmospheric deposition (Mendelssohn
22 1979, Wigand et al. 2003, Tyler et al. 2007, Darby and Turner 2008).
23 Nr deposition causes alteration to the C cycle in freshwater aquatic ecosystems. Numerous studies
24 investigate the relationship between lake N concentration and primary productivity (reported as
25 chlorophyll a, NPP, or an index such as the lake chemistry ratio of dissolved inorganic N [DIN] to total P,
26 DIN:TP) and atmospheric Nr deposition. N addition experiments of lake and stream bioassays in which N
27 was added to waters in field or laboratory in order to measure the response. Gradient studies of
28 undisturbed northern temperate, mountain, or boreal lakes that receive low levels of atmospheric N
29 deposition found strong relationships between N-limitation and productivity where N deposition was low,
30 and P and N+P limitations where N deposition was higher (Fenn et al., 2003a; Bergstrom et al., 2005;
31 Bergstrom and Jansson, 2006).
32 The evidence is sufficient to infer a casual relationship between Nr deposition and alteration
33 to the biogeochemical cycling of C. Estuaries and coastal waters tend to be N-limited and are therefore
34 inherently sensitive to increased atmospheric N loading (D'Elia et al., 1986; Howarth, 2006). This is at
35 least partly because denitrification by microbes found in estuarine and marine sediments releases much of
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1 the added N inputs back into the atmosphere (Vitousek, 1997). However, other limiting factors occur in
2 some locations and during some seasons. Levels of N limitations are affected by seasonal patterns. N-
3 limited conditions are likely to be found during the peak of annual productivity in the summer.
3.3.4. Biogenic Nitrous Oxide and Methane Flux
4 Methane (CH4) and nitrous oxide (N2O) are greenhouse gases (GHGs) contributing to global
5 warming. Although atmospheric concentrations of CH^ (1774 ppb) and N2O (319 ppb) are much lower
6 than CO2 (379 ppm), their global warming potential is 23 and 296 times that of CO2 respectively. Human
7 activities have dramatically increased atmospheric concentration of CH4 by 48% and N2O by 18% since
8 pre-industrial times (IPCC 2007). The continuing increase of those GHGs concentrations have been
9 shown to threaten human and ecosystem health.
10 Anthropogenic N deposition to natural ecosystem is a primary component of global changes
11 (UNEP 2007). Additional N input not only changes global N cycle, but also has profound impacts on
12 biogeochemical processes associated with GHGs emission (Vitousek, 1997; Dalai, 2003; Bodelier, 2004).
13 In the following section, the impacts of N addition on CH4 and N2O emissions were reviewed and
14 quantitatively synthesized by meta-analysis. Further details on this meta-analysis including study site,
15 exosystem type, N addition level, form of N fertilizer, experimental conditions, relationship between N
16 addition and CIL, flux, are in included Annex C.
3.3.4.1. Methane
17 Atmospheric CH4 originates mainly (70-80%) from biogenic sources (Le Mer, 2001). Methane is
18 produced in anaerobic environment by methanogenic bacteria during decomposition of organic matter.
19 Once produced in soil, CH4 can be then released to the atmosphere or oxidized by methanotrophical
20 bacteria in aerobic zone (Le mer and Roger 2001). Methane production and oxidation processes occur
21 simultaneously in most ecosystems. Wetland soils are generally CH^t sources, accounting for about 20%
22 of global CH4 emission (see Annex C for a more detailed discussion of methane in wetlands). Non-
23 flooded upland soils are the most important biological sink for CH4, consuming about 6% of the
24 atmospheric CH4 (Le mer and Roger 2001). Numerous researches have demonstrated that N is an
25 important regulatory factor for both CH4 production and oxidation (Bodelier, 2004).
26 EPA conducted a meta-analysis, including 61 observations from 27 publications, to evaluate the
27 relationship between N addition and CH4 flux. Details on those publications, including study site,
28 ecosystem type, N addition level, form of N fertilizer, experimental condition, are given in Annex C. The
29 impact of N addition on CH4 source and sink strength were estimated by CH4 emission and CH4 uptake
30 respectively. The result suggested that N addition significantly increased CH4 emission by 115% for
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1 grasslands and wetlands (Figure 3-43). This response ratio did not differ among vegetation type, N
2 addition level, form of N fertilizer and experiment condition.
5
response ratio
Figure 3-43. Effects of N addition on biogenic ChU emission. The bars show the distribution of the
number of studies categorized by ecosystem type. The dot with error bars shows the overall mean
response ratio with 95% Cl.
3 Overall, N addition significantly reduced CH4 uptake by 38% (Figure 3-44). Ecosystem type, N
4 form and experiment condition influenced the degree of CH4 uptake response to N addition (Figure 3-45).
5 Methane uptake was reduced for all ecosystems, but this inhibition was significant only for coniferous
6 and deciduous forest, with a reduction of 28% and 45%, respectively (Figure 3-45).
7 All forms of N fertilizer except urea were shown to reduce CH4 uptake (Figure 3-45). Several
8 possible mechanisms have been proposed to explain the inhibition in CH4 oxidation by N addition.
9 Besides the oxidation of CH4, methane monooxygenase (MMO) can convert NH4+ to NOs", and NH4+
10 therefore usually inhibits CH4 oxidation by competing for MMO (Bodelier, 2004). Methanotrophic
1 1 bacteria are sensitive to osmotic stress induced by salts. Inhibition of CFLt uptake by nitrogenous salts
12 (e.g. KNO3, NH4C1, NH4NO3) and non-nitrogenous salts (e.g. K2SO4, KC1 and NaCl) has been observed
13 in field and laboratory studies (King and Schnell 1998; Bodelier, 2004). Other mechanisms, such as
14 toxicity of nitrite (NO2 ) produced by nitrification or denitrification processes, may also involve in the
15 inhibition of CH4 oxidation (Schnell and King 1994).
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_Q
O
A~7
*+/
8 -
6 -
4 -
2 -
n -
s
_s
1 A
jra
*5S
M
^
1
1
4
1
1
I
1
,
• mean response ratio
i i coniferous
ESSSS2 deciduous
ESS3 tropical forest
^^ grassland
1=1 heathland
i nrrrn tundra
tntm wetland
m i
n n H
0.0
0.2 0.4
0.6 0.8 1.0
response ratio
1.2 >1.4
Figure 3-44. Effects of N addition on biological CH4 uptake. The bars show the distribution of the
number of studies categorized by ecosystem type. The dot with error bars shows the overall mean
response ratio with 95% Cl.
coniferous (18)
deciduous (10)
grassland (7)
wetland (6)
tropical forest (2)
heathland (3)
NH4N03 (27)
NH4+ (8)
urea (5)
N03- (5)
field (36)
incubation (11)
vegetation
I • 1
—• 1
I •
N form
experimental condition
I • 1
0.2 0.4 0.6 0.8 1.0
response ratio
1.2
1.4
Figure 3-45. Effects of N addition on biological CH4 uptake. The data are expressed as the mean
response ratio with 95% confident intervals. The numbers of studies included are indicated in
parentheses.
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1 The mean response ratio of CH4 uptake from laboratory incubation studies was significantly lower
2 than that from field studies (Figure 3-45). This difference could be due to that the spatially and chemically
3 heterogeneous field conditions resulted in large experimental errors (Crill, 1994; Weitz, 1999) Gulledge
4 and Schimel 2000). Also laboratory microcosms were characterized by a closed and incomplete N cycle,
5 where N loss by leaching was very small and no plant competed for N with soil microbes. Therefore, N
6 addition may result in stronger impacts on microbial processes under laboratory condition than under field
7 condition
8 Several laboratory incubation studies found that CH4 uptake rates decreased with increasing N
9 input (Schnell and King 1994; King and Schnell 1998). This meta-analysis did not find significant
10 correlation between the amount of N addition and the response ratio of CH4 production/consumption
11 (Figure 3-45). The lack of dose response relationship is probably because CH4 production is influenced
12 by multiple interactions of soil N content, soil moisture, pH and temperature et al (Le Mer and Roger
13 2001), and varies greatly over small spatial and temporal scales (IPCC 2001).
3.3.4.2. Nitrous oxide
14 Biogenic sources are the dominating contributors ( > 90%) to atmospheric N2O. Terrestrial soil is
15 the largest source of atmospheric N2O, accounting for 60% of global emissions (IPCC 2001). Nitrous
16 oxide production in soil is mainly governed by microbial nitrification and denitrification (Dalai, 2003).
17 The contribution of each process to the total N2O production varies with environmental conditions.
18 Denitrifying bacteria reduce NO3 or NO2 into N2O or N2 under anaerobic condition. In submerged soils
19 such as wetland soil, denitrification should be the dominant contributing process to N2O emission
20 (Conrad 1996). Increasing NO3 input generally increases denitrification rate under suitable condition of
21 temperature and organic C supply. High soil NO3 concentrations also inhibit N2O reducing to N2 and
22 result in high N2O/N2 ratio (Dalai, 2003). Under aerobic environment, autotrophic nitrifying bacteria
23 obtain energy by reducing NH4+. Nitrous oxide is an intermediate product of the oxidation of NH4+ to
24 NO2 or decomposition of NO2 . The increase in N2O emission following NH4+ addition has been
25 observed in many lab and field experiments (Aerts and Toet 1997; Aerts and Caluwe 1999; Keller et al
26 2005).
EPA conducted a meta-analysis on the effects of N addition on N20 emission from non-agricultural
ecosystems, including 99 observations from 30 publications. N addition normally enhanced N20 emission,
but some studies also observed N20 emission was decreased by N addition (Skiba et al. 1999; Borken et al.
2002; Ambus et al. 2006; Ambus and Robertson 2006; Curtis et al 2006). Although some natural ecosystem
can be a N20 sink (Chapuis-Lardy et al. 2007), very limited publications assessed the impact of N addition on
N20 uptake. Thus, only changes in N20 production were estimated in this meta-analysis. Overall, the results
of the meta-analysis indicated that N addition increased N20 emission by 215%
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ro
CD
99 -
20 -
15 -
10 -
5 -
mean response ratio
coniferous
deciduous
ITTTmi tropical forest
desert
grassland
heathland
wetland
0.37 1.00 2.72 7.39
response ratio
20.09 54.60 > 148.41
1 Figure 3-46). The response of N2O emission was influenced by ecosystem type, the form and the
2 amount of the N addition (Figure 3-47).
99 -
20 -
15 -
0)
- 10
5 -
n
mean response ratio
coniferous
deciduous
imrrn tropical forest
desert
grassland
heathland
wetland
0.37
1.00
2.72 7.39
response ratio
20.09
54.60 > 148.41
Figure 3-46. Effects of N addition on biogenic N20 emission. The bars show the distribution of the
number of studies categorized by vegetation type. The dot with error bars shows the overall mean
response ratio with 95% Cl.
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1 Compared to other ecosystems, tropical forest emitted more N2O under N enrichment condition
2 (+735%) (Figure 3-47). This greater response may be because tropical forests are often P limited rather
3 than N limited (IPCC 2001). Hall and Matson (1999) measured N2O emission after adding N fertilizer in
4 two tropical rainforests in Hawaii. They found that N2O emission from P-limited sites was 54 times
5 greater in the short term N addition experiment and 8 times greater in the chronic N addition experiment
6 compared to that from N-limited sites. The P-limited soil had higher inorganic N concentration than the
7 N-limited soil (Hall and Matson 1999), which increased N availability to the nitrifying and denitrificating
8 bacteria. However, climatic conditions, especially temperature and precipitation, could also be the key
9 factors to drive N2O emission from tropical forest ecosystem.
10 NO3 caused a higher stimulation (+494%) on N2O emission than NH4+ did (+95%) (Figure 3-47),
11 which was consistent with the previous field studies (Keller, 1988; Wolf and Russow 2000; Russow et al.
12 2008). By adding 15N labeled NO3 and NH4+to soil, Russow et al. 2008 found that N2O was mainly
13 emitted by denitrification and the contribution of denitrification to the total N2O production increased
14 from 54% in soil with normal SOM content to 76% in soil with high SOM.
15 The Intergovernmental Panel on Climate Change (IPCC) issued a guideline for national GHGs
16 inventories of biogenicN20 (IPCC 2000). In this guideline, the default N2O emission factor is 1.25% for
17 N fertilizer applied to agricultural fields (i.e. 1.25% of the amount of N applied to a field will be emitted
18 to the atmosphere as N2O). Several studies have questioned the validity of this emission factor. Some
19 studies suggested a much lower emission factor, such as 0.25% for rice paddy field (Yan et al. 2003) and
20 0.02% for semi-arid regions (Barton et al. 2008), while others found the amount of N2O emission was not
21 clearly related to the amount of N addition (FAO/IFA 2001; Akiyama et al. 2005; Barnard et al. 2005).
22 EPA compiled ambient N2O emission data from 36 studies and did not find any correlation between N2O
23 emission and the level of N deposition (Figure 3-48). In this meta-analysis, although the mean response
24 ratio increased with the amount of N addition, the difference among the three levels (< 75, 75-150
25 and > 150 kg N/ha/yr) were not significant (Figure 3-47). The weak correlation is probably due to that the
26 effect of N addition on N2O emission is affected by many other biotic and abiotic factors such as fertilizer
27 type, vegetation, temperature, soil drainage et al. (Dalai, 2003).
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coniferous (34)
deciduous (17)
grassland (22)
wetland (19)
tropical forest (11)
heathland (3)
NH4N03 (47)
NH4+ (19)
N03- (21)
urea (9)
<75 (30)
75-150(19)
>150 (24)
vegetation
N form
N addition level
01 2 3 4 5 6 7 8 9 10 11 12 13 14 15 1660
response ratio
Figure 3-47. Effects of N addition on biogenic N20 emission. The data are expressed as the mean
response ratio with 95% confident intervals. The numbers of studies included are indicated in
parentheses.
6 -
>,
'ra
D) 4-
E
-------
3.3.4.3. Summary
1 Integrating 160 observations across 57 independent studies, this meta-analysis suggested that N
2 addition tended to increase CH4 emission, reduce CH4 uptake and increase N2O emission. Overall, N
3 deposition may result in higher CH4 and N2O concentrations in atmosphere and exacerbate global
4 warming, but the response magnitudes were influenced by many environmental factors, such as
5 vegetation type, N form, and climate.
6 The evidence is sufficient to infer a casual relationship between Nr deposition and the
7 alteration of biogeochemical flux of Cm in terrestrial ecosystems. N addition ranging from 10 to 560
8 kg N/ha/yr reduced CH4 uptake by 38% across all ecosystems (Figure 3-44), but this inhibition was
9 significant only for coniferous and deciduous forest, with a reduction of 28% and 45%, respectively
10 (Figure 3-45).
The evidence is sufficient to infer a casual relationship between Nr deposition and the alteration of
biogeochemical flux of N20 in terrestrial ecosystems. Overall, the results of the meta-analysis discussed in
section 3.3.4 indicated that N addition ranging from 10 to 560 kg N/ha/yrd. increased N20 emission by 215%
99 -
J> 20
E
ro
CD
15 -
10 -
5 -
I
mean response ratio
coniferous
deciduous
ITTTmi tropical forest
desert
grassland
heathland
wetland
0.37
1.00
2.72 7.39
response ratio
20.09
54.60 > 148.41
11 Figure 3-46). The response of N2O emission to N for coniferous forest, deciduous forest and
12 grasslands was significant (Figure 3-47).
13 The evidence is sufficient to infer a casual relationship between Nr deposition and the
14 alteration Of N20 flux in wetland ecosystems. In the meta-analysis of 19 observations from studies that
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1 evaluated the effects of N additions ranging from 15.4 to 300 N kg N/ha/yrN addition was shown to
2 increase the production of N2O by 207% (Figure 3-47).
3 The evidence is sufficient to infer a casual relationship between Nr deposition and the
4 alteration Of CH4 flux in wetland ecosystems. Wetlands are generally net sources of CH4, but some
5 wetlands can be net sinks depending on environmental conditions such as drainage and vegetation (Crill,
6 1994) Saarnio et al. 2003). The meta-analysis indicated that N addition, ranging from 30 to 240 N kg
7 N/ha/yr, increased CH4 production by 115% from the source wetlands (Figure 3-43, but had no significant
8 impact on CH4 uptake of the sink wetlands (Figure 3-45).
3.3.5. Species Composition, Species Richness and Biodiversity
9 A common response to environmental stress is the tendency for the more sensitive species to
10 decrease in abundance, or to be eliminated, while the more tolerant species increase in abundance
11 (Woodwell, 1970). Species composition and species richness, as well as impacts on rare or threatened
12 species, indicate changes to biodiversity. The ecological consequences of changing species composition,
13 richness and/or biodiversity can be profound. Selective removal of certain species can result in an
14 impairment of ecosystem function, change in community structure and food web dynamics, and decrease
15 in species richness and diversity. Such changes in species composition can occur in response to N
16 addition to terrestrial, aquatic, and transitional ecosystems.
17 Weis et al. (2006) presented an overview of potential biodiversity loss from N enrichment. A
18 survey by Stohlgren et al. (1999) of variables that contribute to species richness and invasibility of sites
19 found positive relationships of soil N with species richness and numbers of nonnative plant species. The
20 implication of this work is that N fertilization alters competitive interactions that may cause native species
21 to be lost, with subsequent decrease in species richness.
22 Alteration of plant productivity and growth by N deposition (see Section 3.3.3) causes a cascading
23 effect on the competitive interactions among species. Atmospheric deposition of N is expected to benefit
24 those species that are best able to take advantage of the increased nutrient availability. Other species may
25 experience decreased growth, reproduction and population size, because they are out-competed by species
26 that are more successful under conditions of enhanced N availability. Numerous studies evaluate
27 ecosystem response to levels of N addition that far exceed the range of N deposition levels in the U.S.
28 This assessment focuses on the information most relevant to the review of the NAAQS, therefore research
29 conducted at N loading levels that greatly exceed current conditions ( > 150 kg N/ha/yr) are excluded
30 from the discussion.
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3.3.5.1. Terrestrial Ecosystem Biodiversity
1 Atmospheric inputs of N can alleviate deficiencies and increase growth of some plants at the
2 expense of others. Thus, N deposition can alter competitive relationships among terrestrial plant species
3 and therefore alter species composition and diversity (Ellenberg, 1987; Kenk, 1988) EPA, 1993b).
4 Wholesale shifts in species composition are easier to detect in short-lived ecosystems such as annual
5 grasslands, in the forest understory, or mycorrhizal associations than for long-lived forest trees where
6 changes are evident on a decadal, or longer, time scale. Note species shifts and ecosystem changes can
7 occur even if the ecosystem does not exhibit signs of N saturation.
Forests
Trees
8 There is very little information on the effect of N deposition on the biodiversity of overstory trees
9 in the U.S. However, the altered growth rates caused by N enrichment have the potential to affect forest
10 structure and biodiversity. The life span of many trees is lOOyrs or more, therefore observation of how
11 growth rates effect biodiversity within established forests are difficult to observe on a decadal time scale.
12 N deposition has been observed to cause tree invasion into grasslands, also called forest
13 encroachment. A study of the northern edge of the Great Plains (southern Canada), showed that increasing
14 N deposition over a range of 8 to 22 kg N/ha/yr to aspen-dominated forest and boreal forest caused an
15 increase forest expansion into the grasslands (Kotchy and Wilson 2001). The following mechanisms have
16 been document to facilitate forest encroachment. Due to their height, trees and shrubs can intercept more
17 airborne particulate N than grasses and they should therefore benefit most from N deposition (Kellman &
18 Carty 1986; Binkley 1995). Fertilization also increases the water-use efficiency of woody invaders (Bert
19 et al 1997) and this may enable them colonize temperate grasslands on dry, coarsely textured soils.
20 Accelerated N cycling following deposition (Hogbom & Hogberg 1991; Berendse 1994; Carreiro et al.
21 2000) decreases competition for N and increases competition for light (Wilson & Tilman 1991), and may
22 give further advantage to tall or fast growing trees (Aerts 1999). Overall, therefore, increased deposition
23 rates may result in a self-maintaining positive feedback that allows trees to establish in grasslands (Wilson
24 1998).
Understory Herbaceous Plants and Shrubs
25 Studies in Europe have generally been based on natural gradients, whereas findings in the U.S.
26 have mostly been based on experimental N addition. The negative effects of increasing N deposition on
27 herbaceous plants were reviewed by Gilliam (Gilliam, 2006). Reported effects include (a) species shifts
28 towards nitrophilous and more acid-tolerant plant species along a deposition gradient from 6 to 20 kg
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1 N/ha/yr in Swedish oak forests; b) a decline in abundance and cover of ericaceous shrubs along a
2 deposition gradient from < 3 to > 12 kg N/ha/yr in the boreal forest in Sweden; and (c) a decline in
3 herbaceous cover under hardwoods following 3 years of N additions applied as (NH4)2SO4 at rates
4 ranging from 14 to 28 kg N/ha/yr. The decline in herbaceous cover in the latter study was attributed to
5 increased shading by ferns, and the effect was more pronounced at sites that experienced lower ambient
6 atmospheric N inputs.
7 Van Breemen and Van Dijk (1988) noted that over the previous several decades of N deposition the
8 composition of plants in forest herb layers in The Netherlands had shifted toward species commonly
9 found in N-rich areas. Brunet et al. (1998) and Falkengren-Grerup (1998) reported the effects of excessive
10 N deposition on mixed-oak forest vegetation along a depositional gradient. Results of this study suggest
11 that N deposition had affected non-woody vegetation directly by increased N availability and, indirectly,
12 by accelerating soil acidity. Time series studies indicated that 20 of the 30 non-woody plant species that
13 were associated most closely with high N deposition had increased in abundance in those areas in Europe
14 that received high N deposition.
15 Mixed results have been reported in other studies. Research at Fernow Experimental Forest, West
16 Virginia, indicated that application of 35 kg N/ha/yr applied as (NH4)2SO4 for 6 years had no significant
17 impact on the herbaceous layer in an Appalachian hardwood forest (Gilliam et al., 2006). Fernow has
18 been the recipient of high levels of N deposition for decades, raising the possibility that the herbaceous
19 layer responded long ago to changes in N availability.
Mycorrhizal and Microbial Diversity
20 Mycorrhizal and microbial biodiversity can also be affected by N enrichment. Relationships among
21 plant roots, mycorrhizal fungi, and microbes are critical for N cycling and for the growth and health of
22 plants. Mycorrhizal fungal diversity has been shown to be associated with above-ground plant
23 biodiversity and ecosystem productivity (Wall, 1999) and to be adversely affected by increased N
24 availability (Egerton-Warburton, 2000). The loss of mycorrhizal function has been hypothesized as a key
25 process contributing to reduced N uptake by vegetation and increased NOs mobility from soil into
26 drainage water under conditions of high N supply (EPA, 2004).
27 Progressive decline in ectomycorrhizal fungal species richness in Alaskan coniferous forest (white
28 spruce \Picea glauca] dominant) occurred along a local N deposition gradient, from 1 to 20 kg N/ha/yr,
29 downwind from an industrial complex (Lilleskov et al., 2002). Ectomycorrhizal fungal communities are
30 important in tree nutrition, and ectomycorrhizal fungal trees tend to be dominant in N-limited forest
31 ecosystems.
32 N fertilization at rates of 54 and 170 kg N/ha/yr (as NH4NO3) led to a decline in ectomycorrhizal
33 fungal diversity and species composition in an oak savanna at Cedar Creek Natural History Area in
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1 Minnesota (Avis et al., 2003). In the reference plots, five species collectively accounted for more than
2 40% cover versus four plant species in the lower N addition plots. In the higher N addition plots, a single
3 plant species accounted for more than 40% cover.
4 Compton et al. (2004) investigated the effects of 11 years of experimental N addition on forest soil
5 microbial ecology. Experimental N addition decreased the C content of microbial biomass in the O
6 horizon of both experimental forest stands, based on chloroform fumigation-extraction. In addition, the
7 use of N-containing substrates by microbes appeared to be reduced by N addition in the pine stand, but
8 not in the hardwood stand. In addition, the use of N-containing substrates by microbes appeared to be
9 reduced by N addition in the pine stand, but not in the hardwood stand. The mechanisms responsible for
10 such changes are not clear (Arnebrandt et al., 1990; Compton et al., 2004). It is possible that added N has
11 both direct (nutrient) and indirect (soil chemistry, organic matter quality, and quantity) effects on
12 microbial ecology. Effects can be manifested on mycorrhizal fruiting body abundance, hyphal networks,
13 and community composition (Lilleskov et al., 2002; Frey et al., 2004).
Grasslands
14 Reduced biodiversity in response to N deposition is reported for grasslands in the U.S. and Europe.
15 Clark and Tilman (2008) recently evaluated the effects of chronic N deposition over 23 years in
16 Minnesota prairie-like successional grasslands and in a native savanna grassland, each originally
17 dominated by a species-rich mixture of native C4 grasses and forbs.(Cedar Creek Long Term Ecological
18 Research Site, Minnesota). Experimental N addition ranged from 10 to 95 kg N/ha/yr above ambient
19 atmospheric N deposition (6 kg N/ha/yr). The N addition rate reduced plant species numbers by 17%
20 relative to controls receiving ambient N deposition. Moreover, species numbers were reduced more per
21 unit of added N at lower addition rates and relative species number was reduced at all addition levels.
22 This suggests that chronic but low-level N deposition may decrease diversity below the lowest addition
23 levels tested (the critical load was calculated as 5.3 kg N/ha/yr with an inverse prediction interval of 1.3-
24 9.8 kg N/ha/yr). A second experiment showed that a decade after cessation of N addition, relative plant
25 species number, although not species abundances, had recovered, demonstrating that some effects of N
26 addition are reversible.
27 Change in species composition in response to N deposition has been observed regardless of soil
28 type in European grasslands. Such effects have been found in calcareous, neutral, and acidic
29 environments, species-rich heaths, and montane-subalpine grasslands (Stevens et al., 2004; Bobbink,
30 1992; Bobbink, 1998; Bobbink, 1998). A transect of 68 acid grasslands across Great Britain, covering the
31 lower range of ambient annual N deposition (5 to 35 kg N/ha/yr), indicates that long-term, chronic N
32 deposition significantly reduced plant species richness. Species richness declined as a linear function of
August 2008 3-164 DRAFT-DO NOT QUOTE OR CITE
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1 the rate of inorganic N deposition, with a reduction of one species per 4-m2 quadrant for every 2.5 kg
2 N/ha/yr of chronic N deposition.
3 Grasslands are well known to respond to increased N availability through changes in growth rates
4 of both native and exotic species. Under high N supply, exotic grasses often out-compete other species,
5 and cause changes in plant community composition (Lowe, 2002). A summary of studies which have
6 show altered plant community composition or growth rates of plant species that have implications for
7 community composition is in Table 3-17. Increased availability of N to grasses can also affect herbivores
8 that feed on grasses by altering food quality, quantity, and phenology, and also perhaps by changing the
9 relationships between herbivores and their predators (Throop and Lerdau, 2004).
Table 3-17. Summary of N effects on grassland biodiversity.
Region/Country
Endpoint
Observations
Grassland Type/ Species
Reference
San Francisco Bay Area, Bay Checkerspot Observation: Serpentinitic soils sustain support native grasses that support
CA Populations populations of the endangered Bay Checkerspot butterfly. Several lines of
evidence indicate that dry N deposition is responsible for grass invasion and
subsequent decline of the butterfly population, however this relationship is
uncertain.
Colorado Growth Greenhouse experiment: they tested the response of grassland species to
increased N aval labi lity (0,10, 40, 70, or 100 kg N/ha/yr) over 75 days. All of
the grass species exhibited increased growth with increased N availability.
Native species did not consistently grow better at low N levels than the exotic
species. Two of the exotic grasses exhibited the greatest increase in growth,
while another of the exotics exhibited the smallest increase in growth.
Plant Research Growth and Field Addition: N additions in (0.1,1, 3 mmol N addition for 80 days), caused
Laboratory, University of Tissue Quality species-specific growth and plant tissue quality changes. Ci grasses (Elymus
Illinois at Chicago virginicus L, E. Canadensis L.) showed a greater positive growth response to
N additions than C4 grasses (Andropogon geradii Vitmanm, Schizachyrium
scoparium Michx.) and forbs (Solidago nemoralis Ait, S. rigida L.). Species
with smaller initial biomass exhibited the greatest increase in biomass, with a
sevenfold to eightfold increase in S. nemoralis and Ł canadensis and only a
threefold increase in S. rigida.
Jasper Ridge Biological Species Richness Field addition: 70 kg N/ha/yr over three years led to decreased to a decline in
Preserve in California and Diversity total species richness, species diversity decreased by 5% and all three N-
fixing forbs disappeared.
Lund University, Lund, Growth Greenhouse experiment: Sand-solution experiments studying how growth
Southern Sweden was effected by N concentrations of 50, 250 and 1250 |jM in a simulated acid
forest soil solution, similar to naturally occurring soil solutions is Southern
Sweden. 46% of grasses displayed a significantly greater biomass at 250
than at 50 |jM N as compared with only 7% for the herbs. Some species
attained their highest biomass at 1250 |jM N and others at 50 |jM N. Grasses
grew better than herbs in response to experimental addition of N. At the
highest experimental N deposition rates, growth was limited for most species
by the supply of nutrients other than N.
Minnesota, Cedar Creek Species Field addition: N enrichment over a 12-year period on 162 plots using a N
Natural History Area Composition addition gradient from 0 to 30 g m-2 year-1. Plots initially dominated by native
warm-season grasses shifted to low-diversity mixes of species dominated by
cool-season grasses at all but the lowest rates of N addition. Grasslands with
high N retention and C storage rates were the most vulnerable to loss of
species and major shifts in N cycling in response to experimental
N enrichment.
Serpentine Grasslands
Bay Checkerspot Butterfly
(Euphydryas Editha Bayensis)
Weiss (1999)
Two North American Native Species Lowe et al.
(Blue Grama And Western (2002)
Wheatgrass) and Four Exotic Species
(Cheatgrass, Leafy Spurge, Canada
Thistle, and Russian Knapweed)
Tallgrass Prairie
Lane and
BassiriRad
(2002)
Nine Annual Species: Avena Barbata, (Zavaleta
Bromus Hordeaceus, Lolium et al., 2003)
Multitorum, Avena Fatua, Bromus
Diandrus, Anagallis Arvensis,
Geranium Dissectum Erodium Botrys,
Vicia Sativa, and one Biennial
Species, Crepis Vesicaria
15 Herb and 13 Grass Species
Falkengren-
Grerup
(1998)
Three N-Limited Minnesota Wedin and
Grasslands with Varying Successional Tilman
Age, Species Composition, and Total (1996)
SoilC
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Region/Country
Endpoint
Observations
Grassland Type/ Species
Reference
San Francisco Bay Area,
CA
Jasper Ridge Biological
Preserve in California
Jasper Ridge Biological
Preserve in California
Michigan old field
Brookhaven Nat. Lab.,
Long Island, New York
and the Sciences
greenhouse facility,
SUNY, Stony Brook, NY
Species
Composition
Npp
Herbivory, Leaf
Tissue N And
Growth Rates
Biomass
Vegetative and
Seed Biomass
and Decreased
Root: Shoot
Ratios
Observational: N deposition levels of 10 to 15 kg N/ha/yr, exotic nitrophilous
grasses have been reported to have displaced native grass species, likely
due to greater N availability from deposition and from the cessation of
grazing, which previously exported N out of the system
Field addition: 70 kg N/ha/yr applied as (CaN03>2 increased NPP by 30%
Field addition: 70 kg N/ha/yr applied as (CaN03>2 caused altered herbivory by
gastropod which differed by species ( J., t and no change), 5 out of 6 species
had increased leaf tissue, 5 out of 6 species had increased growth rates
Field addition: 120 kg N/ha/yr applied as NFUNOa pellets had a significant
positive growth effect on annual dicot biomass but no significant growth effect
on annual grass biomass.
Field additions and Greenhouse experiment: N addition to common ragweed
(Ambrosia artemisifolia) led to increased vegetative and seed biomass and
decreased root: shoot ratios. N deposition may indirectly affect biomass
production and allocation through affecting insect herbivory. The particularly
strong influence of both herbivory and N deposition on A. artemisiifolia
reproduction suggests potential population and community-level
consequences.
Grasslands
Grasslands
Grasslands
Grasslands
Ambrosia Artemisiifolia (Common
Ragweed) and two of its Insect
Herbivores; a Leaf Beetle, Ophraella
Communa Lesage (Coleoptera:
Chrysomelidae), and an Aphid,
Uroleucon Tuataiae Olive (Hemiptera:
Aphididae)
Fenn et al.
(2003a)
Shawetal.
(2003)
Cleland et al.
(2006)
Huberty et al.
(1998)
Throop
(2005)
Region /
Country
Europe
Nora/ay
Endpoint
forest Biomass
growth (tree ring
increments)
Observations
Modeling: using growing stock of large forest regions over an entire country as empirical data, the
authors determine forest biomass is accumulating, largely in response to increases in forest area
and improved management, but other possible mechanisms of growth enhancement (including N)
cannot be ruled out
Deposition gradient: A comprehensive analyses of regional forest growth trends analyzed tree
increment cores from more than 31,000 plots. In this study, growth increased during the 1960s
and 1970s and then declined in the 1990s, especially in southern regions exposed to the highest
rates of N deposition (Figure 4.3-7)
Forest type /
species
Forests from Austria,
Finland, Sweden,
France, Germany ,
and Switzerland
boreal forest (Picea
abies and Pinus
sylvestris)
Reference
Kauppietal.,
1992; Spiecker
etal., 1996
Nellemann and
Thomsen, 2001
Sweden
Bear Brook,
ME, U.S.
Fernow
Experimental
Forest, WV,
U.S.
Harvard Forest,
MA, U.S.
northeastern
U.S.
Harvard Forest,
MA, U.S.
Ysselsteyn.The
Netherlands
growth (stem volume) Field addition: chronic fertilization at 30 kg N/ha/year continued to stimulate stemwood production
even after 30 years, whereas a higher application (90 kg N/ha/year) decreased stem volume
growth, and an intermediate application (60 kg N/ha/year) had little positive or negative effect
relative to the control plots
growth (basal area) Field Addition: basal area increment of sugar maple was enhanced 13 to 104% by addition of
25 kg N/ha/year as ammonium S042~ ((NH4)2S04), whereas red spruce was not significantly
affected.
growth
mortality
live basal area
growth
mortality
root production
growth
root production
Boreal forest
Scots pine forest
sugar maple and red
spruce
black cherry, yellow
poplar, red maple,
sweet birch
Field addition: The application of 35 kg N/ha/year as (NH4>2S04 enhanced growth of (Prunus
serotina) and yellow poplar (Liriodendron tulipifera) during the first 7 years, but led to reduced
growth of these species relative to control trees in years 9 through 12, with no change in red
maple or weet birch (Betula lenta)
Field addition: chronic N addition levels of 50 and 150kg N/ha/year for 15 years caused a 31% red pine, striped
and 54% decrease, respectively, in red pine growth. As red pine has died, striped maple maple, black cherry,
(Acer pensylvanicum), black cherry, and black birch (Betula lenta) have increased their black birch
contributions to annual litterfall production.
Field addition: In a high-elevation red spruce-balsam fir (Abies balsamea) forest in the, N red spruce-balsam fir
fertilization over 14 years led to a decrease in live basal area (LBA) with increasing N additions. In
control plots, LBA increased by 9% over the course of the study, while LBA decreased by 18%
and 40% in plots treated, respectively, with 15.7kg N/ha/year and 31.4 kg N/ha/year.
Field addition: N fertilization of a 50-year-old red-oak/red maple stand largely stimulated old red-oak, red
productivity, although the drought in 1995 induced significant mortality in small red maple trees. maple
Fine root biomass was slightly, but not significantly, lower in highly fertilized stands relative to
controls in both red pine and oak/maple ecosystems
Field addition and deposition exclusion: improvements in wood accumulation rate, root Coniferous- Picea
production, and mycorrhizal associations occurred when a "clean roof" was installed at the site abies, Picea
receiving the highest rate of N deposition (>40 kg N/ha/year). Decreased production of fine roots sitchesis,
may predispose N-fertilized plants to be more sensitive to intermittent drought, as well as to Pseudotsuga
nutrient depletion exacerbated by acid deposition. menziesii, Pinus
sylvestris
Hogbergetal.,
2006
Elviretal., 2003
DeWalleetal.,
2006
Magi II etal.,
2004
(McNultyetal.,
2005)
Magi II etal.,
2004
Boxman et al.,
1998b Emmett
et al. Emmett
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Region /
Country
Endpoint
Observations
Forest type /
species
Reference
Southern CA,
U.S.
CA, U.S.
CA, U.S.
California
California
North Carolina
and Virginia
California,
Sequoia
National Park
Michigan
N- saturation- Observational: Areas of chaparral and mixed conifer forests that receive very high levels of dry N
reduced soil base deposition in southern California have experienced significant environmental change over the
saturation, and lack past several decades
of a growth response
Growth Observational: Some southern California forests experience N deposition up to 45 kg N/ha/year,
and that increased N deposition caused increased growth of Jeffrey and ponderosa pine stands.
growth (productivity) Observational: high inputs of reactive N appear to exhibit decreases in productivity and increases
and mortality in mortality (Fenn, 1998).
litter accumulation, Field addition: N fertilization has been shown to cause increased litter accumulation and C
above-ground woody storage in above-ground woody biomass, which in turn may lead to increased susceptibility to
biomass, fire more severe fires.
susceptibility
growth increased N deposition caused increased growth for Jeffrey (Pinus Jeffrey!) and ponderosa pine
(Pinus ponderosa) stands,
growth (basal area), Deposition gradient: Results from a study of 46 forest plots on six sites in North Carolina and
foliar chemistry, Virginia dominated by American beech, sugar maple, and yellow birch suggested that N
nitrification and deposition is associated with changes in basal area, foliar chemistry, and nitrification and
mineralization mineralization rates. Growth rates for the three tree species were similar at the lowest rates of
N deposition, and then diverged as N deposition increased, with growth of yellow birch and
American beech decreasing at the high N deposition loads. These differential growth rates have
the potential to affect forest structure and biodiversity
growth Field addition: Aspen (Populus tremuloides) have been reported to show positive growth effects
from fertilization at N deposition rates as low as 10 kg N/ha/year
ANPP and surface Field addition: Chronic N fertilization (30 kg N/ha/year) for 20 years caused significant increases
soil organic matter in ANPP by 10% and surface soil organic matter (0-1 Ocm) by 26%
chaparral and mixed Fennetal.,
conifer 1996,2003a
mixed conifers; Jeffrey Takemoto et al.,
and ponderosa pine 2001
Conifer forests
Ponderosa pine
mixed conifers
Fenn et al.
(Fenn,1998)
Fennetal.,
2003a
Takemoto et al.
(2001)
American beech,
sugar maple, and (2005)
yellow birch
Aspen
Sugar maple
Bytnerowicz,
(2002)
Pregitzer et al.
(2008)
1 Not all studies have shown an effect of N addition on species richness or diversity. In old
2 agricultural fields in Michigan, increased N deposition changed neither the successional timing nor the
3 gain or loss of species numbers (Huberty et al., 1998). A lack of response in species richness may have
4 been due to application of mid-growing season fertilization in the experimental design. Huberty and
5 colleagues (1998) suggested that N additions may change the dominance structure instead of the species
6 composition, of these successional old-field communities. Other studies in Michigan on successional
7 grasslands showed no response to N application of 10 kg N/m2/yr, equivalent to about 2.5 times ambient
8 deposition rates (Ambus and Robertson, 2006).
Arid and Semi-Arid Land Ecosystems
9 Some arid, and semi-arid ecosystems in the southwestern U.S. are considered sensitive to N
10 enrichment effects and receive high levels of atmospheric N deposition. However, water is generally more
11 limiting than N in these systems. Nevertheless, enhanced N may play a role in the observed invasion of
12 some exotic plant species and associated changes in ecosystem function, especially where water supply is
13 adequate.
14 In semi-arid ecosystems, results from several N fertilization experiments showed (1) increased
15 biomass of nonnative plant species over native species, (2) decreased soil moisture under some
16 conditions, and (3) increased fire risk where dense mats of grasses replaced shrub cover (See Table 3-18).
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1 Much of the arid land data are from the coastal sage scrub (CSS) communities of southern
2 California, down-wind of the Los Angeles Basin, where dry N deposition is very high. The CSS
3 community in California has been declining in land area and in shrub density over about the past 60 years
4 and is being replaced in many areas by Mediterranean annual grasses (Padgett and Allen, 1999; Padgett
5 et al., 1999). N deposition is considered a possible cause or contributor to this ecosystem alteration. More
6 than 30 kg N/ha/yr of atmospheric N is deposited to portions of the Los Angeles Air Basin (Bytnerowicz
7 and Fenn, 1996). The CSS community is of particular interest because about 200 sensitive plant species
8 and several federally listed threatened or endangered animal species are found in the area.
9 Native shrub and forb seedlings in the CSS community are unable to compete with dense stands of
10 exotic grasses, and thus are gradually replaced by the grasses, especially following disturbances such as
11 fire (Eliason and Allen, 1997; Yoshida, 2001; Cione et al., 2002). Biodiversity impacts have also been
12 documented for microbial communities in coastal sage scrub ecosystems. It has been hypothesized that
13 the decline in coastal sage shrub species could be linked to the decline of the arbuscular mycorrhizal
14 community (Egerton-Warburton, 2000).
Table 3-18. Summary of N effects on arid and semi-arid ecosystems.
Region/Country
Endpoint
Observations
Ecosystem Type/
species
Reference
Southeast Idaho species
composition
and cover
southern California Plant
community
southern California Plant
community
southern California response of
native and
nonnative
plants.
southern California plant root-to-
shoot growth
ratios
southern California response of
native and
nonnative
plants.
Field addition: 6 or 12 kg N/ha/yr applied as NFUNOa for 6 years (in addition to ambient sagebrush (Artemisia
inputs of 1.3 to 1.4kg N/ha/yr) resulted in a decrease in soil moisture caused by shifts in tridentata) steppe
plants species composition and cover. However, there were no effects on perennial grass ecosystem
cover in response to experimental N additions
Observational: Dry N deposition is above 30 kg N/ha/yr in some places. Native shrub and coastal sage scrub
forb seedlings in this plant community are unable to compete with dense stands of exotic
grasses, and thus are gradually replaced by the grasses, especially following disturbances
such as fire
Greenhouse and deposition gradient experiments: N deposition is considered a possible
cause or contributor to declining shrub density over about the past 60 years and is being
replaced in many areas by Mediterranean annual grasses
coastal sage scrub
Greenhouse experiment: N (as 5.4 g/L NHUCI or 10g/L KNOs) was added to obtain soil N coastal sage scrub
concentrations of 2, 20, 40, and 80 |jg/g. The grasses demonstrated a 1.5-to 2.5-fold
growth increase when soil N levels increased from 20 to 40 |jg/g. To achieve a comparable
growth increase, shrubs required higher soil N levels (between 20 and 80 |jg/g). These lab
experiments agree with observations in the field, where exotic grasses, especially once
established, have replaced native shrubs under elevated N deposition.
Greenhouse experiment: Changes in plant root-to-shoot growth ratios were observed in the coastal sage scrub
plant community, which is composed largely of the drought-resistant deciduous shrubs
Artemisia californica, Encelia farinosa, and Eriogonum fasciculatum.
Observational: more than 30 kg N/ha/yr of atmospheric N is deposited to this ecosystem in coastal sage scrub
portions of the Los Angeles Air Basin). Decreases in the diversity of native plants paralleled
increases in exotic grass biomass.
(Inouye, 2006).
Eliason and Allen,
1997; Yoshida and
Allen (Yoshida,
2001); Cione etal.,
2002).
Allen etal., 1998;
Padgett and Allen,
1999; Padgett etal.,
1999).
Padgett and Allen,
1999
(Padgett and Allen,
1999; Padgett etal.,
1999).
(Bytnerowicz and
Fenn, 1996
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Region/Country
Colorado Plateau
Joshua Tree
National Park,
California
Joshua Tree
National Park,
California
Western U.S.
San Francisco Bay
area
Endpoint
response of
native and
nonnative
plants.
response of
native and
nonnative
plants.
response of
native and
nonnative
plants.
Fire cycle
response of
native and
nonnative
plants
Observations
Field addition: For 2 years, plots were treated with 0, 10, 20, or 40 kg N/ha/yr as a KNOs
solution. Galleta (Hilaria jamesii) and Indian ricegrass (Oryzopis hymenoides) showed no
increase in leaf photosynthesis or tiller size, but ricegrass showed a 50% increase in tiller
density in the second year at the 20 and 40 kg N/ha/yr application levels. For both species,
the increased N application hastened the onset of water stress. Unexpectedly, a non-native
species, Russian thistle (Salsola iberica) showed a rapid growth response to the highest
fertilization rate in the first summer, when rainfall was above average. The authors
suggested that the timing and amount of N deposition could facilitate noxious weed
invasion and thus change community composition in
Deposition gradient: 18 locations, chosen to cover the dominant vegetation types
(Creosote Bush Scrub, Joshua Tree Woodland, Pinyon Juniper Woodland), were sampled
for atmospheric concentrations of NO, NOj, NHb, and soil [N]. The relationship between
reactive atmospheric N concentrations and soil N were
consistent in most sites. Observations along the N gradient did not reveal a clear
relationship between non-native grass cover and soil N concentration up to 20 |jg/g.
Field addition: was applied at levels of 5 and 30 kg N/ha/yr at four sites over a 2-year
period. Low-elevation sites were dominated by creosote bush scrub and higher-elevation
sites by pinyon-juniper woodland. Non-native grass biomass increased significantly at three
of four treatment sites that received 30 kg N/ha/yr, but not at the sites that received 5 kg
N/ha/yr. A soil N concentration of 23 |jg/g was conservatively considered the low threshold
for significant plant N response based on this fertilization study.
Observational: Vegetative changes stimulated by nutrient enrichment from N deposition
may affect the frequency and severity of subsequent disturbance. Several lines of evidence
suggest that N deposition may be contributing to greater fuel loads, thus altering the fire
cycle in a variety of ecosystem types. Invasive grasses, which can be favored by high N
deposition, promote a rapid fire cycle in many locations
Observational: N deposition levels of 10 to 15 kg N/ha/yr, exotic nitrophilous grasses have
displaced native grass species, likely due to greater N availability from deposition and from
the cessation of grazing, which previously exported N out of the system. Since this change
in species composition, populations of the rare and threatened bay checkerspot butterfly
(Euphydryas editha bayensis) have declined greatly. It has been hypothesized that the
response of the butterfly has been due to the vegetative changes.
Ecosystem Type/
species
arid grassland
arid grassland
arid grassland
arid grassland
grasslands dominated by
exotic annuals such as
wild oat (Avena fatua),
brome (Bromus mollis),
and ryegrass (Lolium
multiflorum).
Reference
(Schwinningetal.,
2005)
(Allen etal., 2007).
Allen et al. (2007)
(Fennel al.,2003a)
(Fennel al.,2003a).
Mycorrhizal and Microbial Diversity
1 It has been hypothesized that the decline in coastal sage shrub species in California could be linked
2 to the decline of the arbuscular mycorrhizal community (Egerton-Warburton, 2000). They discerned a
3 shift in arbuscular mycorrhizal community composition with decreased species richness and diversity
4 along a deposition gradient (2 to 57 (ig N/g as soil NOs ). These shifts in mycorrhizal fungal communities
5 may facilitate replacement of native plant communities by Mediterranean annual grasslands. Larger-
6 spored fungal species (Scutellospora and Gigaspora) have decreased in number due to a failure to
7 sporulate, with a concomitant proliferation of small-spored species. This pattern suggests selective
8 pressure favoring the smaller spored species of fungi (Egerton-Warburton, 2000), and that N enrichment
9 of the soil might alter the arbuscular mycorrhizal species composition and diversity.
Desert Ecosystems
10 Some desert ecosystems in the southwestern U.S. are considered sensitive to N enrichment effects
11 and receive high levels of atmospheric N deposition. However, water is generally more limiting than N in
12 these systems. Nevertheless, N deposition can stimulate plant growth and cause the observed invasion of
13 some exotic plant species and associated changes in ecosystem function, especially where water supply is
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1 adequate. The majority of evidence is from field additions of N, levels ranging from 10-100 kg N/ha/yr
2 (Table 3-19).
3 Fertilization experiments in the Mojave Desert showed that increased levels of N deposition could
4 favor the establishment of nonnative species where the non-natives are already prevalent (Brooks, 2003).
5 There is also evidence that N deposition decreases the growth of desert legumes (Baez et al., 2007). A link
6 between N deposition and decrease in legumes has been found across other North American sites (Suding
7 et al., 2005). The effect on legumes may be attributable to the fact that legumes, which are N fixers, often
8 compete better under low N supply.
9 There is evidence from the desert ecosystems that N accumulates during periods of drought, and
10 that more N is immobilized during periods of high precipitation (Stursova et al., 2006). Thus, where water
11 and N appear to be co-limiting factors, the observed pattern of higher rates of N deposition during months
12 with higher precipitation may result in a stronger fertilization effect than if N deposition were
13 independent of precipitation (Hooper and Johnson, 1999; Asner et al., 2001; Knapp and Smith, 2001;
14 McLain and Martens, 2006).
Table 3-19. Summary of N effects on desert ecosystems.
Region/Country
End point
Reference
Chihuahuan Desert
Jornada basin, New
Mexico
Chihuahuan Desert,
Mojave Desert
Growth Field addition: 20 kg N/ha/yr addition in one season showed blue gramma (Bouteloua gracilis) was blue gramma
response of favored over black gramma (Bouteloua eriopoda), the current dominant species and black
native species gramma
Growth Field addition: black grama and another dominate species, creosote bush (Larrea tridentate) did not black grama
response of significantly increase biomass after experimental additions of 25 kg N/ha/yr, but did after additions of and creosote
native species 100 kg N/ha/yr bush
Growth
response of
native species
Native vs. non-
native
Field addition: Additions of 100kg N/ha/yr over about a decade, resulted in percent soil N that was Grasses and
15-61% higher, extractable NCb- that was 25-175% higher, and extractable NFU that was 247- legumes
1721% higher compared to control plots (Stursova et al, 2006). The resultant biologic effects were a
30% increase in cover of warm season grasses and a 52% reduction in cover of legu mes (Baez
etal, 2007).
Field addition: At application rates of 32 kg N/ha/yrr over 2 years, both density and biomass of non-
native plants increased (54% increased biomass), while native species biomass declined by about
39%. Plant responses were influenced by rainfall events rather than by average annual rainfall, with
the annual plants thriving in a year when high rainfall events triggered germination.
grasses
(Baezetal.,
2007).
(Ettershanketal.,
1978; Fisher etal,
(1998)
Stursova etal.,
2006; Baez etal,
2007
(Brooks, 2003)
Great Basin Desert,
sites near Mono Lake,
CA
Mojave desert
Mojave and Sonoran
deserts.
Growth and
seed viability
growth
response
Navtive vs.
non-native
Field addition: Sarcobatus vermiculatus, a desert shrub found demonstrated a twofold to threefold
increase in stem growth, a 2.5 to 4 fold increase in viable seed production, and a 17% to 35%
increase in leaf N with N additions. N was applied in March and November as NHUNOs, at a
cumulative addition rate of 233.6 g N per plant.
Field addition: The shrub Larrea tridentata showed no increased growth response to N additions (at
10 and 40 kg N/ha/yras CaNCb) but did respond to increased water
Observational: Invasive annuals showed a greater response to elevated N than native species, and
have recently invaded. Though their invasion is correlated with greater N deposition, no causation
Sarcobatus
vermiculatu
Larrea
tridentata
Drenovsky and
Richards, 2005
(Barker etal,
2006).
Fennetal,
2003a).
has been established.
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Lichens
1 Lichens are frequently used as indicators of air pollution and atmospheric deposition levels (see
2 Annexes A and C for an additional discussion). In addition to being good subjects for biomonitoring, they
3 constitute important components of the forest ecosystem by contributing to biodiversity, regulating
4 nutrient and hydrological cycles, and providing habitat elements for wildlife (McCune and Geiser, 1997).
5 Little is known about the mechanisms that control growth and resource partitioning in lichens,
6 which are complex symbiotic systems comprised of a fungus (mycobiont) and a green alga and/or
7 cyanobacterium (photobionts) (Palmqvist, 2000); Sundberg et al, 2001). Organic compounds required for
8 growth are produced via photobiont photosynthesis. Production is strongly coupled with N utilization.
9 The non-photosynthetic fungus comprises much of the lichen biomass and requires N for protein
10 synthesis, nucleic acids and fungal cell wall (chitin) synthesis (Palmqvist et al., 1998). Carbon and N
11 uptake must be balanced for coordinated development of lichen thalli (Sundberg et al., 2001).
12 Lichens can be classified on the basis of their response to atmospheric pollution. Nitrophytic
13 lichens occur in areas that receive high atmospheric N deposition; acidophytic lichens are prevalent in
14 areas that receive low N input (Rouss 1999, Van Herk 2001, Gaio-Oliveira et al. 2005). Lichens differ
15 with respect to N requirements. Many lichens that have a cyanobacterial photobiont are N-fixing, whereas
16 those with a green algal photobiont are dependent on atmospheric deposition for their N supply.
17 N-fixing lichen species are particularly affected by N deposition (Dahlman et al., 2002).
18 Cyanobacteria have been shown to grow on either NO3 or NH4+ sources when administered at non-toxic
19 concentrations. More rapid growth was observed with NH4+ fertilization as compared with NO3
20 fertilization (von Riickert and Giani, 2004). Amonium is more easily assimilated; both NO3 and nitrite
21 must first be reduced to NH4+ prior to assimilation (von Riickert and Giani, 2004).
22 Lichens with a green algal photobiont are solely dependent on atmospheric deposition as a source
23 of N. However, a buildup of N within the thallus can lead to toxicity. Lichens exhibit varying degrees of
24 sensitivity to increasing N deposition, owing to diverse mechanisms of responding to high N supply by
25 reducing N uptake or assimilating N into non-toxic forms such as arginine (Gaio-Oliverira et al., 2001;
26 Gaio-Oliverira et al., 2005; Dahlman et al., 2003).
27 Lichens that contain a cyanobacterial photobiont appear to be more sensitive to adverse effects
28 from atmospheric N deposition than most other lichens (Hallingback, 1991; Hallingback and Kellner,
29 1992). In Sweden, the proportion of cyanobacterial lichens that has disappeared or is threatened is three
30 times as large as the corresponding proportion of lichens having green algal photobionts (Hallingback,
31 1991). Low pH may be the most important effect of air pollution on Peltigera aphthosa in Sweden.
32 Nevertheless, there is some indication that NH4+ in combination with SO42 is more detrimental than low
33 pHper se (Hallingback and Kellner, 1992). The decline of lichens containing cyanobacteria in parts of
34 northern Europe has been associated with N deposition in the range of 5 to 10 kg N/ha/yr (Bobbink et al.,
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1 1998). In fact, epiphytic cyanobacteria-containing lichens may be among the most sensitive species in
2 humid forested ecosystems to atmospheric N deposition (Hallingback, 1991; Bobbink et al., 1998).
3 Epiphytic macro lichens (those that grow attached to trees or other plants) exhibit different
4 sensitivities to atmospheric pollutants, with some species being adversely impacted at air pollution levels
5 that may not be considered high relative to other sensitive receptors. Particularly sensitive genera include
6 Alectoria, Bryoria, Ramalina, Lobaria, Pseudocyphellaria, Nephroma, and Usnea (McCune and Geiser,
7 1997; Blettetal, 2003).
8 Community composition of epiphytic lichens in the U.S. can be altered by relatively small
9 increases in N deposition (Fenn et al., 2003a). Most epiphytic lichens meet their nutritional requirements
10 from atmospheric deposition and can store N in excess of their nutritional needs (van Herk, 1999). Early
11 work in the San Bernardino Mountains, California, lichen cover was inversely related to estimated
12 oxidant doses (Sigal, 1983). In recent analysis it has been determined that up to 50% of lichen species that
13 occurred in the region in the early 1900s have disappeared, with a disproportionate number of locally
14 extinct species being epiphytic cyanolichens (Nash, 1999 ; Fenn et al., 2003a). The calculated critical load
15 for lichen communities in mixed conifer forests in California is 3.1 kg/ha/yr (Fenn et al. 2008).
16 The Pacific Northwest retains widespread populations of pollution-sensitive lichens (Fenn et al.,
17 2003a). However, in urban areas, intensive agricultural zones, and downwind of major urban and
18 industrial centers in the Pacific Northwest, there are few air pollution-sensitive lichen species, such as
19 epiphytic cyanolichens, and high N concentrations have been measured in lichen tissue (Fenn et al.,
20 2003a). With N enrichment, especially around urban and agricultural areas, there is a shift towards weedy,
21 nitrophilous lichen species (Fenn et al., 2003a). Replacement of sensitive lichens by nitrophilous species
22 has undesirable ecological consequences. In late-successional, naturally N-limited forests of the Coast
23 Range and western Cascade Mountains, for example, epiphytic cyanolichens make important
24 contributions to mineral cycling and soil fertility (Pike, 1978; Sollins et al., 1980; Antoine, 2001), and
25 together with other large, pollution-sensitive macrolichens, are an integral part of the food web for
26 mammals, insects, and birds (McCune and Geiser, 1997). Sensitive lichen species appear to be negatively
27 affected by N inputs as low as 3 to 8 kg N/ha/yr (Fenn et al., 2003a). (A summary of additional
28 experiments on lichens is given by Table 3-20.)
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Table 3-20. Summary of
Region/Country
Netherlands
Scotland and northern
England
Umea, Vasterbotten,
Sweden
Sweden
Sweden
Pampulha reservoir
(Belo Horizonte, Brazil)
Sweden
Santo Antonio, near
Serra de Aire
Candeeiros Natural
Park, central Portugal
Endpoint
Species
richness
Community
composition
NH4+vs. N03
uptake rate
NUrvs. NOa
uptake
NH4+vs. N03
uptake
NH4+vs. NOa
growth
NH4*in
combination
with SCU2-
NH4* uptake
Physiological
responses
N effects on lichens.
Observations
Deposition gradient: Van Dobben, et al. (2001) recorded epiphytic lichen presence, tree bark
chemical composition, and atmospheric concentrations of S02, NCte and NHa at 123 sites along
depositional gradients. Relationships between atmospheric and bark chemistry and the
composition of the lichen vegetation were evaluated (ter Braak and Wiertz, 1994). Results showed
neearly all lichen species investigated were negatively effected by exposures to S02 and N02,
collectively decreasing lichen species richness. Of somewhat less importance were the ecological
factors such as bark pH, host tree species and tree diameter.
Deposition gradient: The authors suggested that the empirical critical load of N deposition for
protection of community composition of lichens and bryophytes was in the range of 1 1 to 1 8 kg
N/ha/yr
Isotopic tracer: In a study of 15N uptake in 1 4 lichen associations (for simplicity, designated as
"species"), found that NlVuptake was significantly greater, and to a higher extent passive, relative
to amino acid or N0~j- sources of N. Differences were also observed in NOr uptake, depending on
photobiont group; cyanobacterial lichens had a lower NOsr uptake rate than green algal lichens.
Morphology and microhabitat were not found to be associated with N uptake
The assimilation and allocation of externally added N was investigated for two N-fixing tripartite
(possessing both green algal and cyanobacterial phytobionts) lichen species, Peltigera aphthosa
and Nephroma articum. N uptake ranged from 2 to 27 percent of the 5 kg N/ha/yr that was applied
during the experiment over a 3 month period. Atmospheric deposition in this part of Sweden (~5 kg
N/ha/yr was about one-fourth the total experimental N application rate. NH4*was absorbed to a
greater extent than was N0~j-. In general, 15N levels of NHf treated thalli were about four times
higher than for NOr treated thalli. To some extent, this may reflect the increased energy
requirements of NOsr reduction as compared with NHU* assimilation (Raven etal., 1992) and/or the
adsorption of positively charged NH4*on the negatively charged functional groups present on
hyphal cell walls.
NH4*to be the preferred N source for the green algal foliose lichen Plathismatia glauca, followed by
glutamine and then NOr. This species responded to increased N availability by increasing growth
rate and C assimilation capacity through increased investment in the photobiont cells
Cyanobacteria have been shown to grow on either NOT or NhU* sources when administered at
non-toxic concentrations. More rapid growth was observed with NHf fertilization as compared with
NOr fertilization. Ammonium is more easily assimilated; both NOs and nitrite must first be reduced
to NH4*priorto assimilation
Low pH may be the most important effect of air pollution on Peltigera aphthosa in Sweden.
Nevertheless, there is some indication that NHf in combination with SCU2- is more detrimental than
low pH per se (Hallingback and Kellner, 1992).
Comparison of the physiological responses of two lichens to increased N supply. Uptake was
quantified using 15N labeled NhU*. Cholrophyll a and ergonsterol were used as indirect markers of
algal and fugal activity, respectively. The acidophytic lichen Evernia prunastri showed greater N
uptake from Nm*than the nitrophytic lichen Xanthoria parietina. In the acidophytic lichen, but not
the nitrophytic lichen, ergosterol concentrations decreased with increasing N uptake, and an
increase in the NhU* pool was also observed at the highest N doses (216 kg N/ha/yr, applied as
nine applications over a 2-month period). These differences can partially explain the higher
tolerance of X. parietina to high N deposition.
Ecosystem Type /
Species
Epiphytic lichens
Atlantic oak woods
Cyanobacterial
lichens and green
algal lichens
Peltigera aphthosa
and Nephroma
articum
Plathismatia
glauca, a foliose
lichen
Cyanobacteria
Peltigera aphthosa
Evernia prunastri
and Xanthoria
parietina
Reference
Van Dobben,
et al. (van
Dobben, 2001)
ter Braak and
Wiertz (1994)
Mitchell et al.
2005
Dahlmanetal
(2004)
Dahlmanetal,
2002
Palmqvist and
Dahlman
(2006)
von Rilckert
and Giani,
2004
Hallingback
and Kellner,
1992
Gaio-Oliveira
et al. 2005
Alpine
1 Herbaceous plants in alpine communities are considered very sensitive to changes in N deposition.
2 A combination of short growing season, strong seasonal variation in moisture and temperature, shallow
3 and poorly developed soils, steep terrain, sparse vegetation, and low rates of primary productivity
4 generally limit the N uptake and retention capacity of herbaceous plant species in alpine ecosystems
5 (Fisk, 1998) Burns, 2004). Alpine herbaceous plants are generally considered N-limited and changes in
6 alpine plant productivity and species composition have been noted in response to increased N inputs
7 (Vitousek, 1997; Bowman et al., 2006). See Table 3-21.
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1 Research on N enrichment effects on alpine and subalpine ecosystems in the Western U.S. has
2 mainly been limited to studies at the Loch Vale Watershed in Rocky Mountain National Park and the
3 Niwot Ridge LTER site, both located east of the Continental Divide in Colorado (see review by Burns,
4 2004). Changes in alpine plant species composition on Niwot Ridge have included increased cover of the
5 plant species that tend to be most responsive to N fertilization in some of the long-term monitoring plots
6 (Korb and Ranker, 2001; Fenn et al., 2003a). These changes are likely due to response to changes in N
7 deposition. However, the influences of climatic change, particularly changes in precipitation (Williams
8 et al., 1996), and pocket gopher disturbance (Sherrod and Seastedt, 2001) could not be ruled out as
9 contributors to vegetation change (Fenn et al., 2003a). Other environmental factors also affect the species
10 make-up of alpine ecosystems, but long-term experimental fertilization plots demonstrate a clear response
11 of alpine flora to N, including shifts toward graminoid plants that shade smaller flowering species, and
12 accompanying changes in soil N cycling (Bowman et al., 2006).
Table 3-21,
Region/Country
Niwot Ridge, CO
and Southern
Wyoming
Niwot Ridge, CO
Niwot Ridge, CO
, Summary of N effects on alpine ecosystems.
End point
Community shift
Plant foliage
productivity
species richness.
Species
composition
species diversity
plant biomass
tissue [N]
Observations
Field addition: 25 kg N/ha/yr added during summer caused a community shift
towards greater dominance of hairgrass (Deschampsia sp.) in wet alpine meadows,
but the increase in plant biomass (+67%) and plant N content (+107%) following N
fertilization was higher in graminoid-dominated dry meadows than in forb-dominated
wet meadows (+53% plant biomass, +64% standing N crop, respectively)
Field addition: Showed that 4 years of N addition to alpine vegetation at rates
ranging between 100 and 200 kg N/ha/yr (depending on the year) caused marginal
increases in alpine plant foliage productivity but reduced species richness.
Field addition: Additions of 20, 40, and 60 kg N/ha/yr (on top of ambient N
deposition near 5 kg N/ha/yr) over an 8-year period to a dry alpine meadow led to a
change in plant species composition, an increase in species diversity and plant
biomass, and an increase in tissue N concentration at all treatment levels within 3
years of application. Much of the response was due to increased cover and total
Ecosystem Type / Species
Wet and dry alpine meadow.alpine
tundra, talus, alpine and subalpine
forest— Englemann spruce, Bristlecone
pine, surface waters, algae,
amphibians
Wet and dry alpine tundra- sedge
Kobresia myosumides. Acomastylis
ross/7, Po/ygonum viviparurn Trifolium.
A.rossii and Deschumnpsia
caespitosa. D. caespitosa, Caltha
leptosepala, Sibbaldia procurnbens
and Trifolium parryi.
Dry alpine meadow
Reference
Bowman
etal. (1995);
Burns (2004).
Seastedt and
Vaccaro
(Seastedt,
2001)
Bowman
et al. (2006)
biomass of sedges (Carex spp.). There was a significant decrease in Kobresia
biomass with increasing N input. Vegetation composition appeared to respond at
lower N input levels than those that caused measurable changes in soil inorganic N
content. Changes in an individual species (Carexrupestris) were estimated to occur
at deposition levels near 4 kg N/ha/yr. Changes in the plant community, based on
the first axis of a detrended correspondence analysis, were estimated to occur at
deposition levels near 10 kg N/ha/yr. In contrast, increases in N03~ leaching, soil
solution N03~ concentration, and net nitrification occurred at levels above 20 kg
N/ha/yr. The authors concluded that changes in vegetation composition preceded
detectable changes in soil indicators of ecosystem response to N deposition.
Mycorrhizae across ecosystems
13 Microbial biodiversity can also be affected by N enrichment. Interactions between atmospherically
14 deposited N and terrestrial vegetation frequently occur in the rhizosphere. The rhizosphere includes the
15 soil that surrounds and is influenced by plant roots (Wall, 1999). Relationships among plant roots,
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1 mycorrhizal fungi, and microbes are critical for N cycling and for the growth and health of plants. The
2 plant provides shelter and C; the fungi and bacteria provide access to potentially limiting nutrients,
3 particularly N and P.
4 A meta-analysis of the effect of N and P fertilization on mycorrhize observed a 15% decrease in
5 mycorrhizal abundance due to N fertilization across 16 studies at 31 sites, covering a range of grassland,
6 shrubland, temperate and boreal forest ecosystems (Treseder, 2004). Declines in mycorrhizal abundance
7 were slightly higher at higher rates of N fertilization, but there was significant variation across all studies.
8 The loss of mycorrhizal function has been hypothesized as a key process contributing to reduced N uptake
9 by vegetation and increased NOs mobility from soil into drainage water (EPA, 2004).
NOs" versus NhV deposition
10 Plants also exhibit different degrees of response to NO3 versus NH4+ deposition. In general, fast-
11 growing annual species, including many agricultural crops, and fast growing pioneer trees such as birch
12 (Betula spp.) prefer NOs (Pearson and Stewart, 1993). Slow-growing perennial plant species generally
13 prefer NH4+. There are also many plant species which readily utilize both NOs and NH4+ (Krupa, 2003).
14 These include members of the family Ericaceae (e.g., Calluna, Erica, Vacciniuni), conifer trees, and
15 climax species such as Quercus and Fagus (Krupa, 2003).
3.3.5.2. Transitional Ecosystems
16 Wetlands in the U.S. support over 4200 native plant species, of which 121 are federally threatened
17 or endangered (http://plants.usda.gov/). Wetlands can be divided into three general categories based on
18 hydrology. Hydrologic pathways are often the same pathways of N input; therefore they are useful for
19 discussing the N sources and sensitivity to atmospheric N deposition. Nearly all new N comes from
20 atmospheric deposition in ombrotrophic bogs because they only receive water inputs via precipitation and
21 they develop where precipitation exceeds evapotranspiration and where there is some impediment to
22 drainage of the surplus water (Mitsch and Gosselink, 1986). Fens, marshes and swamps are characterized
23 by ground and surface water inputs that are often on the same order of magnitude as precipitation
24 (Koerselman 1989). Lastly, intertidal wetlands receive water from precipitation, ground/surface water and
25 marine/estuarine sources.
26 The balance of competition among plant species in some sensitive wetland ecosystems can be
27 altered by N addition, with resulting displacement of some species by others that can utilize the excess N
28 more efficiently (EPA, 1993). The sensitivity of wetlands is particularly important given that they contain
29 a disproportionately high number of rare plant species that have evolved under N-limited condition
30 (Moore et al., 1989) (See Annex D). In general these include the genus Isoetes sp., of which three species
31 are federally endangered; insectivorous plants like the endangered green pitcher Sarracenia oreophila;
August 2008 3-175 DRAFT-DO NOT QUOTE OR CITE
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1 and the genus Sphagnum, of which there are 15 species are listed as endangered by Eastern U.S. states.
2 Roundleaf sundew (Drosera rotundifolid) is also susceptible to elevated atmospheric N deposition
3 (Redbo-Torstensson, 1994). This plant is native to, and broadly distributed across, the U.S. and is
4 federally listed as endangered in Illinois and Iowa, threatened in Tennessee, and vulnerable in New York
5 (http ://plants .usda. gov/).
Freshwater wetlands
6 Peatlands and bogs are among the most vulnerable transitional ecosystems to adverse nutrient-
7 enrichment effects of N deposition (Krupa, 2003). The sensitivity of peatland Sphagnum species to
8 elevated atmospheric N deposition is well documented in Europe (Berendse et al, 2001; Tomassen et al.,
9 2004). Sphagnum squarrosum and S. fallax have been observed to be negatively affected by
10 experimentally elevated atmospheric N and S inputs in Europe (Kooijman and Bakker, 1994). The genus
11 Sphagnum dominates ombrotrophic bogs and some nutrient poor fens in the Northern US and Canada.
12 These mosses efficiently capture atmospheric deposition with retention rates between 50-90%, much of
13 the variation due to the depth of the water Table (Aldous 2002a). Studies conducted on 4 species of
14 Sphagnum in Maine (2 to 4 kg N/ha/yr ambient deposition) and New York (10 to 13 kg N/ha/yr ambient
15 deposition) document that higher N deposition resulted in higher tissue N concentrations (Aldous 2001)
16 and greater NPP (Aldous 2002a), but lower bulk density (Aldous 2002a). A study of Sphagnum fuscum in
17 six Canadian peatlands showed a weak, although significant, negative correlation between NPP and N
18 deposition when deposition levels were greater than 3 kg N/ha/yr (y = 150 - 3.4x, p=0.04, r2=0.01) (Vitt
19 et al. 2003). A study of 23 ombrotrophic peatlands in Canada with deposition levels ranging from 2.7 to
20 8.1 kg N/ha/yr showed peat accumulation increases linearly with N deposition (y = 2.84x +0.67, r2 =0.32,
21 P < 0.001), however in recent years this rate has begun to slow indicating limited capacity for N to
22 stimulate accumulation (Moore et al. 2004).
23 The sensitivity of peatland Sphagnum species to elevated atmospheric N deposition is well
24 documented in Europe (Berendse et al., 2001; Tomassen et al., 2004). Sphagnum squarrosum and S. fallax
25 have been observed to be negatively affected by experimentally elevated atmospheric N and S inputs in
26 Europe (Kooijman and Bakker, 1994). Roundleaf sundew (Drosera rotundifolid) is also susceptible to
27 elevated atmospheric N deposition (Redbo-Torstensson, 1994). This plant is native to, and broadly
28 distributed across, the U.S. and is federally listed as endangered in Illinois and Iowa, threatened in
29 Tennessee, and vulnerable in New York.
30 Sarracenia purpurea is a long lived (30-50 years) northern pitcher plant and widely distributed in
31 bogs, fens and swamps across Canada and the eastern U.S. (Ellison, 2002). S. purpurea has adapted to
32 nutrient poor environments and very sensitive to increasing N input. In a study of S. purpurea in Vermont
33 and Massachusetts, Ellison and Gotelli (Ellison, 2002) conducted a series of N enrichment experiments by
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1 augmenting N availability to leaves with 0, 0.1 and 1 mg N/L NH4+ solution for one growing season.
2 Population growth rates, estimated by demographic survey, were positive for 0 and 0.1 mg N/L additions
3 (equal to atmospheric deposition of 0-1.4 kg N/ha/yr)1 and negative for 1 mg N/ L additions (equivalent
4 to 10-14 kg N/ha/yr)* (Gotelli and Ellison 2006). Based on the annual demographic rates, a non
5 stationary matrix model forecasted that the extinction risk within the next 100 years increased
6 substantially if N deposition rate increase (1-4.7%) from the rate of 4.5-6.8 kg N/ha/yr (Gotelli and
7 Ellison 2002).
8 Increasing N availability not only reduced population growth of S. purpurea, also dramatically
9 altered plant morphology. S. purpurea produces carnivorous leaves (pitcher) and photosynthesis efficient
10 leaves (phyllodia). N enrichment was shown to stimulate the photosynthesis rate and increase the
11 production of phyllodia relative to pitcher (Ellison, 2002). The field N deposition simulation experiment
12 (ranged from 0-35 kg N/ha/yr)* revealed a positive linear relationship between N deposition level and
13 relative keel size (keel width/total width). This correlation was supported by the field surveys of 26 sites
14 across Massachusetts and Vermont (Ellison, 2002), and 39 sites across Canada and eastern U.S. (Ellison
15 et al. 2004). The relative kneel size of northern pitcher plant increased with increasing NH4+
16 concentration in soil water, and may be used as bio indicator (log [NH4+] = -1.57 + 1.78x relative keel
17 size).
18 In wet heathlands in Europe, changes in plant species composition have been attributed to elevated
19 atmospheric N deposition (Roem and Berendse, 2000). Diverse plant communities have been replaced by
20 monospecific stands Dutch wet heathlands (Aerts and Berendse, 1988; Houdijk et al., 1993). In other
21 studies, wetland species such as Calluna vulgaris can successfully compete with grasses even at relatively
22 high rates of N deposition, as long as the vegetative canopies are closed (Aerts et al., 1990). However, N
23 deposition causes nutrient imbalances, and increased plant shoot-to-root ratio, and therefore increases in
24 the sensitivity of shrubs to drought stress, frost stress, and attack by insect pests (Heil and Diemont,
25 1983). These can result in gaps in the canopy of the shrub layer, which can then be readily invaded by
26 grasses that are more efficient in using the additional N and therefore gain a competitive advantage
27 (Krupa, 2003).
Riparian wetlands
28 Marler et al. (2001) evaluated the potential impacts of experimentally elevated stream water
29 nutrient concentrations on three riparian wetland tree species: Fremont cottonwood (Populus fremontii),
1 N treatments were selected to represent annual N deposition measured at the nearest monitoring sites of National Atmospheric Deposition
Program (NADP). The unit of N treatments reported in the publication was precipitation-weighted mean concentrations (mg N/ L), from which
we calculated the level of deposition (kg N/ha/yr) using the equation: Deposition= Precipitation-Weighted Mean Concentrations x Annual
Precipitation. More detailed information on nitrogen deposition is available on the NADP website: http://nadp.sws.uiuc.edu/sites/ntnmap.asp?
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1 Goodding willow (Salix gooddingii), and exotic saltcedar (Tamarix ramosissima) in the riparian zone of
2 the Salt River near Phoenix, Arizona. The results from this 43-day experiment showed that growth of all
3 three riparian plant species responded positively to increased nutrient supply (treatment 3 and 4) (Marler
4 et al., 2001). The exotic and invasive salt cedar showed the greatest increases in biomass at high nutrient
5 supply. Other studies have also found that exotic plant species often respond more rapidly than native
6 vegetation to increased nutrient supply (Milberg et al., 1999; Paschke et al., 2000). This experiment was
7 conducted to simulate impacts of wastewater effluent on riparian zones, and N additions were therefore
8 very large nutrient supply to riparian systems via atmospheric N deposition in the U.S. is more typically
9 in the range of treatments in this experiment that showed minimal response to N addition.
Intertidal wetlands
10 Wetland eutrophication could significantly damage the structure and function of coastal marshes. N
11 enrichments were shown to facilitate the invasion of nonnative species (Tyler et al. 2007); shift the
12 competition between native species (Mendelssohn. 1979; Wigand et al. 2003; Grain 2007); increase
13 herbivore damage on plants (Bertness et al. 2008); stimulate evapotranspiration (Howes et al. 1986);
14 change microbial community and pore water chemistry (Caffrey et al. 2007); and alter carbon allocation
15 between root and shoot (Darby and Turner 2008). The majority of N fertilization experiments add levels
16 of N orders of magnitude above that expected by atmospheric deposition. A summary of experiments at
17 addition levels below 400 kg N/ha/yr is given in Table 3-22.
Table 3-22. Summarized responses of coastal marshes ecosystem to N fertilization. The Table
includes studies in which the lowest fertilization treatment is below 400 kg N/ha/yr, a value at the
higher end of the range that includes direct and indirect N deposition.
Site
Species
Responses
N enrichment
Reference
Walden Creek (NC) Spartina alterniflora Field addition: 1) increased the growth of short Spartina, but
had no effect on tall Spartina; 3) biomass production of short
Spartina increased linearly with N addition; 2) ammonium
showed higher growth stimulation on short Spartina than N03
does
0,280,560,1120kg
N/ha/yr
Mendelssohn et al. 1979
Narragansett Bay (Rl)
Great Sippewissett
Marsh (MA)
Spartina patens;
Spartina alterniflora
Spartina alterniflora
Field addition: 1) decreased the density and extent of S patens;
2) decreased the extent of tall S. alterniflora increased with
Field addition: increased live above ground biomass, leaf area
coverage, evapotranspiration
N gradient from 9 to
3282 kg N/ha/yr
396 kg N/ha/yr
Wigand et al. 2003
Howes etal. 1986
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3.3.5.3. Freshwater Aquatic Ecosystems
Paleolimnological studies
1 The paleolimnological method of taxonomic identification of fossil diatoms in lake sediments has
2 been augmented in recent years with cell counts and pigment concentrations of chlorophyll and
3 chlorophyll derivatives, rendering inferences about trophic state from proxies preserved in sediments
4 more robust than before (Das, 2005). Paleolimnological studies of mountain lakes that have only been
5 disturbed by atmospheric deposition and climate change have reported changes in diatom species
6 assemblages, increases in cell numbers, and pigment-inferred increases in whole lake primary production.
7 These inferred changes have been coincident with regional surrogates for increased N deposition. Such
8 changes have included increases in human population, industrial animal production, and fossil fuel
9 combustion emissions (Wolfe et al., 2001, 2003; Saros, 2003; Das, 2005). In most, but not all, of these
10 studies, the observed changes in ecology were inconsistent with changes in climate and more concordant
11 with effects from increased atmospheric N deposition.
12 Available data suggest that the increases in total N deposition do not have to be large in order to
13 elicit an ecological effect. For example, a hindcasting exercise determined that the change in Rocky
14 Mountain National Park lake algae that occurred between 1850 and 1964 was associated with an increase
15 in wet N deposition that was only about 1.5 kg N/ha (Baron, 2006). Similar changes inferred from lake
16 sediment cores of the Beartooth Mountains of Wyoming also occurred at about 1.5 kg N/ha deposition
17 (Saros, 2003). Pre-industrial inorganic N deposition is estimated to have been only 0.1 to 0.7 kg N/ha
18 based on measurements from remote parts of the world (Galloway, 1995) Holland et al., 1999). In the
19 western U.S., pre-industrial, or background, inorganic N deposition was estimated by Holland et al.
20 (1999) to range from 0.4 to 0.7 kg N/ha/yr.
Bioassay, mesocosm, and laboratory experiment
21 Bioassay, mesocosm, and laboratory experiments have been conducted on algae (both
22 phytoplankton and periphyton), invertebrates, amphibians, and fish, in order to determine effects of N on
23 sensitive aquatic organisms (see Annex C). Some freshwater algae are particularly sensitive to the effects
24 of added nutrient N and experience shifts in community composition and biodiversity with increased N
25 deposition. For example, two species of diatom, Asterionella formosa and Fragilaria crotonensis, now
26 dominate the flora of at least several alpine and montane Rocky Mountain lakes and sharp increases have
27 occurred in Lake Tahoe (Interlandi and Kilham, 1998; Baron, 2000; Wolfe et al., 2001, 2003; Saros, 2003;
28 Saros, 2005). The timing of this shift has varied, with changes beginning in the 1950s in the southern
29 Rocky Mountains and in the 1970s or later in the central Rocky Mountains (Figure 3-49). These species
August 2008 3-179 DRAFT-DO NOT QUOTE OR CITE
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1 are opportunistic algae that have been observed to respond rapidly to disturbance and slight nutrient
2 enrichment in many parts of the world (See Annex D for additional discussion).
3 Further evidence for the relationship between N enrichment and algal changes has been provided
4 by N addition studies that include in situ mesocosm studies (McKnight et al., 1990; Lafrancois, 2004;
5 Saros, 2005) and in situ incubations in large lakes (Interlandi and Kilham, 1998). Differences in resource
6 requirements allow some species to gain competitive advantage over others upon nutrient addition,
7 causing changes in species composition (Wolfe et al., 2001, 2003; Lafrancois, 2004; Saros, 2005). A
8 summary of these experiments is given in Table 3-23. This is in keeping with findings of Interlandi and
9 Kilham (2001), who demonstrated that maximum species diversity was maintained when N levels were
10 low ( < 3 (iM) in lakes in the Yellowstone National Park region.
11 The implication of this research is that species diversity declines with increasing availability of N.
12 In studies of lake sediment diatom remains, typical oligotrophic species such as Aulacoseria perglabra,
13 Cyclotella steligera, and Achnanthes spp. declined coincident with the rise in dominance of A. formosa
14 and F. crotonensis (Wolfe et al., 2001, 2003).
/ / X XX ,
0,0
1.0
2,0
3,0
4,0
5,0
6,0
7,0
C 9,0
o 10,0
*•" 11,0
5 12,0
O. 13,0
a> 14,0
Q 150
16,0
17.0
18.0
19.0
20.0
21.0
22.0
23.0
24.0
X c/ o/ XX o^ ^
^^™
.
•
'
H
1
1
1 1 1 1 1
20 40 60 80 100
_
__
-
.
•
i
i
20
—
^_
^H
•
1
1 III
20 40 60
•
^
•
i
l— 1
20
I
•
—
_^
^
^H
^^
•-n
20
••
HHHHHjjjII
—
^^"
^^^B
^^^^m
10 12
,
C
• ilUUU
4 AOA
^^^
1 1
2 4
Source: Saros et al. (Saros, 2003)
Figure 3-49. Diatom assemblage sediment patterns in Emerald Lake, WY.
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1 Community shifts in phytoplankton other than diatoms have also been observed under conditions
2 of elevated N availability (Lafrancois, 2004). For example, a positive correlation between the proportion
3 of the phytoplankton comprised of chrysophytes and the concentration of NO3 in lake water was found in
4 a survey of 15 Snowy Range lakes (Lafrancois, 2003). Chlorophytes, like the two diatom species
5 identified above, generally have a preference for high concentrations of N and are able to rapidly
6 dominate the flora when N concentrations increase (Findlay et al., 1999). This occurs in both
7 circumneutral and acidified waters (Wilcox and Decosta, 1982; Findlay et al., 1999).
8 In summary, survey data and fertilization experiments demonstrate that increase in algal
9 productivity, as well as species changes and reductions in biodiversity, have occurred at sensitive high
10 elevation lakes in the western U.S. in response to increased availability of N.
Table 3-23. N effects on species composition and biodiversity
Region
Snowy Range,
Wyoming
End point
Community shifts in
phytoplankton
Observation
Mesocosm experiment: correlation between the
proportion of the phytoplankton comprised of
Ecosystem type
lakes
Reference
Lafrancois et al. (Lafrancois,
2003)
chrysophytes and the concentration of NCr in lake water
was found in a survey of 15 lakes. Chrysophytes were
favored in lakes having lower N and cyanophytes and
chlorophytes favored in lakes having higher N
Beartooth Mountains of Diatom community
Montana-Wyoming
Colorado Front Range Community shifts in
phytoplankton
Lake Tahoe, CA
Community shifts in
phytoplankton
Rocky Mountain Lakes, growth
Colorado
Yellowstone National growth
Park, Wyoming
Paleo and observational: evaluation of resource lakes
requirements for dominant diatom species with
paleolimnological reconstructions and contemporary
surveys of the flora of seven lakes. Results reinforced the
likelihood that recent increases in dominant diatom
numbers have been the result of N enrichment rather
than climatic change
Paleo: Sediment cores showed increasing representation lakes
of mesotrophic diatoms in recent times, as compared with
pre-development conditions
Paleo: there has been a sharp increase in the ratio of lake
araphidinate pennate to centric diatoms since about 1950
(largely due increases in Fragilaria crotenensis),
associated with increased N loading to the lake. Jassby
et al. (Jassby, 1994) showed that atmospheric deposition
supplies most of the N to Lake Tahoe.
In situ mesocosm: incubations the growth of the diatom A. Diatoms
formosa has been stimulated with N amendments during
from 6.4 to 1616 |jM N
In situ incubations in large lakes: stimulated F. crotonensi. lakes
This publication did not reveal how much N was added to
the incubations
The N requirements for A. formosa and F. crotonensis Alpine lakes
were determined to be 0.041 |jM and 0.006 |jM,
respectively, and higher concentrations stimulated growth
Saras et al. (Saras, 2005)
Wolfe etal., 2001
Goldman (Goldman, 1988)
McKnight etal., 1990;
Interlandi and Kilham, 1998
Michel et al., 2006
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3.3.5.4. Estuarine and Marine Ecosystems
1 In coastal ecosystems, eutrophication can cause changes in marine biodiversity and species
2 composition. Phytoplankton production and community composition in estuarine and marine
3 environments also respond to differences in the form of atmospheric N input. Major algal functional
4 groups, including diatoms, dinoflagellates, cyanobacteria, and chlorophytes, may show different
5 responses to changing mixtures of added N (Paerl et al., 2002). Differential phytoplankton responses, in
6 turn, may cause changes in the species composition of zooplankton, herbivous fish, and higher trophic
7 levels of aquatic biota.
Phytoplankton
8 In addition to causing increased phytoplankton biomass, as indicated by chlorophyll a
9 measurements (see Section 3.3.3.4), excess N can contribute to changes in phytoplankton species
10 composition. High loadings of N and P can also increase the potential for Si limitation, with associated
11 changes in diatoms. Such changes to the phytoplankton community can also affect higher trophic levels.
12 For example, Officer and Ryther (1980) and Turner et al. (Turner, 1998) suggested that a shift in the Si-to-
13 N atomic ratio to less than 1 would alter the marine food web. Specifically, the diatom-to-zooplankton-to-
14 higher tropic level ratios would decrease, whereas flagellated algae (including those that often contribute
15 to hypoxia) would increase (Paerl, 2001).
16 Changes in phytoplankton species abundances and diversity have been further documented through
17 in situ bioassay experiments such as the results reported by Paerl et al. (Paerl, 2003) for the Neuse River
18 Estuary in North Carolina. Effects were species-specific and varied dramatically depending on whether,
19 and in what form, N was added. The findings illustrate the potential impacts of N additions on
20 phytoplankton community structure (see Figure 3-50).
21 Changing phytoplankton community composition has numerous potential ecological ramifications,
22 including modifications to the ecosystem food web and nutrient dynamics. For example, if the nutrient
23 mix favors species that are not readily grazed (e.g., cyanobacteria, dinoflagellates), trophic transfer will
24 be poor and relatively large amounts of unconsumed algal biomass will settle to the bottom, which could
25 stimulate decomposition, O2 consumption, and the potential for hypoxia (Paerl, 2003).
Reduced vs. Oxidized N
26 The form of N input to coastal aquatic ecosystems has an important influence on its effects.
27 Atmospheric deposition of reduced N has increased relative to oxidized N in the eastern U.S., and this
28 trend is expected to continue in the future under existing emissions controls. Such patterns can influence
29 marine eutrophication responses. Some studies suggest that large diatoms tend to dominate coastal waters
30 when NOs is supplied (Stolte, 1994; Paerl, 2001), whereas smaller diatom species have a greater
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1 preference for NH4+ uptake. Thus, ongoing trends of decreasing NO3 deposition and increasing
2 deposition might lead to changes in species distributions and size distributions of phytoplankton, with
3 cascading effects on trophic structure and biogeochemical cycling (Paerl, 2001).
4 Not all studies have found different levels of algal response depending on the form of N applied.
5 For example, Richardson et al. (2001) examined the effects of different forms of N application (NOs ,
6 NH4+, urea) on the structure and function of estuarine phytoplankton communities in mesocosm
7 experiments in the Neuse River Estuary, NC. Even though NH4+ is more readily taken up by
8 phytoplankton in this estuary than is NOs (Twomey, 2005), results of the Richardson et al (2001) study
9 suggested that phytoplankton community structure was determined more by the hydrodynamics of the
10 system than by the form of N available for growth.
11 Twomey et al. (2005) measured Neuse River Estuary phytoplankton uptake rates of NH4+, NO3 ,
12 and urea. Ammonium was the dominant form of N taken up, contributing about half of the total N uptake
13 throughout the estuary. Uptake varied spatially; in particular NO3 uptake declined from 33% of the total
14 uptake in the upper estuary to 11% and 16%, respectively in the middle and lower estuary. Urea uptake
15 contributed least to the total in the upper estuary (16%) but comprised 45 and 37% of the total N uptake in
16 the middle and lower estuary. Therefore, N budgets based only on inorganic forms may seriously
17 underestimate the total phytoplankton uptake (Twomey, 2005).
Submerged Aquatic Vegetation (SAV)
18 SAV provides important nursery grounds to many estuarine fish. There are few data documenting
19 the long-term response of SAV in coastal ecosystems to N loading. The national assessment (Bricker,
20 2007) suggested that only a small fraction of the estuary systems evaluated reported high severity of SAV
21 loss. Most of those that did report moderate or high loss were located in the Mid-Atlantic region.
22 However, where SAV loss is a problem, the results can be severe, and there is evidence suggesting a
23 correlation with increases in N loading. For example, at Waquoit Bay, Massachusetts, Valiela et al. (1990)
24 reported a strong negative relationship between modeled N loading and measured eelgrass area based on
25 measurements of eelgrass coverage from 1951 to 1992.
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400 n
350 -
0>
™ 300
• Centritractus
O Ankistrodesmus
| Unidentified dinoflageliate
| Closterium
Q Comphosphaeria
250 -
o>
a
w 200 -
O
100 -
50 .
Source: Paerl etal. (Paerl, 2003)
Figure 3-50. Microscopic counts of phytoplankton species composition in the Neuse River Estuary,
NC following 36-h in situ bioassays to manipulate available forms of N. Treatments included a
control (unamended estuarine water sample), all nutrients (N, P, vitamins, trace metals, and Si), all
with urea as the N form, all with ammonium (NH4+) as the N form, all with N0s~ as the N form, and all
with no N. Bars represent the mean density of cells present (three replicate counts for each
treatment).
3.3.5.5. Summary
Terrestrial
1 The evidence is sufficient to infer a causal relationship between N deposition on the
2 alteration of species richness, species composition and biodiversity in terrestrial ecosystems. The
3 ecological effects of N deposition were described for a variety of taxa and ecosystem types including:
4 forests, grasslands, arid and semi-arid, deserts, lichens, alpine, and mycorrhizae. The most sensitive
5 terrestrial taxa are lichens. Empirical evidence indicates that lichens in the U.S. are adversely affected by
6 deposition levels as low as 3/ha/yr. Among the most sensitive ecosystems are Alpine ecosystems;
7 alteration of plant cover of an individual species (Carex rupestrls) in Alpine communities were estimated
8 to occur at deposition levels near 4 kg N/ha/yr and modeling indicates that deposition levels near 10 kg
9 N/ha/yr alter plant community assemblages.
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Wetland
1 The evidence is sufficient to infer a causal relationship between Nr deposition and the
2 alteration of species richness, species composition and biodiversity in wetland ecosystems. The
3 effect of N deposition on wetland ecosystems depends on the fraction of rainfall in its total water budget
4 and the sensitivity to N deposition was suggested as: bogs > fens > intertidal wetlands (Morris, 1991).
5 Excess N deposition can cause shifts in wetland community composition by altering competitive
6 relationships among species, which potentially leads to effects such as decreasing biodiversity, increasing
7 non-native species establishment and increasing the risk of extinction for sensitive and rare species.
8 Wetlands contain a high number of rare plant species (Moore et al., 1989; EPA, 1993; Bedford and
9 Godwin, 2003). High levels of atmospheric N deposition increase the risk of decline and extinction of
10 these species that are adapted to low N conditions. In general these include the genus Isoetes sp., of which
11 three species are federally endangered; insectivorous plants like the endangered green pitcher Sarracenia
12 oreophila; and the genus Sphagnum, of which there are 15 species are listed as endangered by Eastern
13 U.S. states. Roundleaf sundew (Drosera rotundifolid) is also susceptible to elevated atmospheric N
14 deposition (Redbo-Torstensson, 1994). This plant is native to, and broadly distributed across, the U.S. and
15 is federally listed as endangered in Illinois and Iowa, threatened in Tennessee, and vulnerable in New
16 York (http://plants.usda.gov/). In the U.S., Sarraceniapurpurea can be used as a biological indicator of
17 local N deposition in some locations (Ellison, 2002).
Freshwater Aquatic
18 The evidence is sufficient to infer a causal relationship between Nr deposition and the
19 alteration of species richness, species composition and biodiversity in freshwater aquatic
20 ecosystems. Evidence from multiple lines of research and experimental approaches support this
21 observation, including paleolimnological reconstructions, bioassays, mesocosm and laboratory
22 experiments. Increased N deposition can cause a shift in community composition and reduce algal
23 biodiversity. Elevated N deposition results in changes in algal species composition, especially in sensitive
24 oligotrophic lakes.
25 In the west, a hindcasting exercise determined that the change in Rocky Mountain National Park
26 lake algae that occurred between 1850 and 1964 was associated with an increase in wet N deposition that
27 was only about 1.5 kg N/ha (Baron, 2006). Similar changes inferred from lake sediment cores of the
28 Beartooth Mountains of Wyoming also occurred at about 1.5 kg N/ha deposition (Saros, 2003).
29 Some freshwater algae are particularly sensitive to added nutrient N and experience shifts in
30 community composition and biodiversity with increased N deposition. For example, two species of
31 diatom (a group of algae), Asterionella formosa and Fragilaria crotonensis, now dominate the flora of at
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1 least several alpine and montane Rocky Mountain lakes and sharp increases have occurred in Lake Tahoe
2 (Interlandi and Kilham, 1998; Baron, 2000)Wolfe et al., 2001, 2003; Saros, 2003; Saros, 2005). The
3 timing of this shift has varied, with changes beginning in the 1950s in the southern Rocky Mountains and
4 in the 1970s or later in the central Rocky Mountains. These species are opportunistic algae that have been
5 observed to respond rapidly to disturbance and slight nutrient enrichment in many parts of the world.
Estuarine Aquatic
6 The evidence is sufficient to infer a causal relationship between Nr deposition and the alteration of
7 species richness, species composition and biodiversity in estuarine ecosystems. Increased N deposition
8 can cause shifts in community composition, reduced hypolimnetic DO, reduced biodiversity, and
9 mortality of submerged aquatic vegetation. The form of deposited N can significantly affect
10 phytoplankton community composition in estuarine and marine environments. Small diatoms are more
11 efficient in using NO3 than NH4+. Increasing NH4+ deposition relative to NO3 in the eastern U.S. favors
12 small diatoms at the expense of large diatoms. This alters the foundation of the food web. Submerged
13 aquatic vegetation is important to the quality of estuarine ecosystem habitats because it provides habitat
14 for a variety of aquatic organisms, absorbs excess nutrients, and traps sediments. Nutrient enrichment is
15 the major driving factor contributing to declines in submerged aquatic vegetation coverage. The Mid-
16 Atlantic region is the most heavily impacted area in terms of moderate or high loss of submerged aquatic
17 vegetation due to eutrophication. Indicators to assess the eutrophic condition of estuarine and coastal
18 waters are given in the following table:
3.3.6. Nr Deposition Effects on N0s~ Toxicity
19 NO3 in freshwater at extremely high concentrations can have direct adverse effects on many life
20 stages offish, as well as on invertebrates and amphibians. These effects occur at levels that are typically
21 more than 30 times higher than those that would commonly be attributable to atmospheric deposition, and
22 therefore NO3 concentration has not been defined as a primary biological indicator. These effects are
23 described in Annex C.
3.3.7. Critical Loads and Other Quantified Relationships between
Deposition Levels and Ecological Effects
24 This section highlights a variety of sensitive chemical and biological receptors that have been used
25 in developing critical loads for nutrient effects of N deposition on natural ecosystems. Sensitive receptors
26 for effects of excess nutrient N deposition on surface water could include water chemistry, productivity,
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1 and the response of important taxa. Key sensitive receptors for assessing impacts on soil include soil
2 chemistry and soil solution chemistry. Sensitive receptors for flora include macro-lichens and vascular
3 plant species that are adapted to nutrient-poor environments. In some cases, the chemical receptors may
4 be easier to characterize, although they likely also reflect important biological changes that may be more
5 difficult to document. Background information on critical loads is presented in Annex C.
6 The ecological indicators that are used for critical loads are considered important aspects of the
7 ecosystem. Perturbation of these endpoints is ecologically adverse. Empirical models of critical loads for
8 nutrient-N have been in use in Europe for some time (e.g., UNECE, 2004). Efforts have begun to develop
9 empirical relationships in the U.S.
3.3.7.1. Empirical Critical Loads for Europe
10 Within the United Nations Economic Commission for Europe (UNECE) Long Range
11 Transboundary Air Pollution (LRTAP) convention, empirical procedures have been developed to set
12 critical loads for atmospheric N deposition to protect against effects caused by nutrient enrichment.
13 Empirical critical loads of N deposition for natural and semi-natural terrestrial and wetland ecosystems
14 were first presented in a background document for the 1992 LRTAP workshop on critical loads held at
15 Lokeberg, Sweden (Bobbink, 1992). A number of European expert workshops have taken place in order
16 to reach agreement among specialists regarding the impacts of N deposition on various ecosystems and
17 related critical loads (Nilsson, 1988; Bobbink, 1992; Hornung, 1995; Bobbink et al., 1996; Achermann,
18 2003).
19 Information from the period 1996-2002 on the effects of increased N deposition on the structure
20 and function of natural and semi-natural ecosystems in Europe was evaluated in Bobbink et al. 2003. The
21 updated N critical loads were discussed and approved by full consensus at the November 2002 expert
22 meeting held under the LRTAP Convention in Berne (Switzerland, (Achermann, 2003). Values for areas
23 with low N deposition were updated by a CLRTAP workshop on critical loads of N in low-deposition
24 areas (Stockholm, Sweden, March 2007) and adopted by ICP M&M and WGE in 2007. The resulting
25 values are given in Table 3-24.
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Table 3-24. Biological indicators for the effects of elevated N deposition and related empirical
critical loads for major ecosystem types (according to the eunis classification) occurring in Europe.
Ecosystem Type
Biological Effect Indicators
Empirical Critical Load
(kg N/ha/yr)
Grasslands and tall forb habitats (E)
Sub-atlantic semi-dry calcareous grassland
Non-mediterranean dry acid and neutral closed
grassland
Inland dune grasslands
Low and medium elevation hay meadows
Mountain hay meadows
Moist and wet oligotrophic grasslands
Alpine and subalpine meadows
Moss and lichen dominated mountain summits
Increased mineralization, nitrification and N leaching; increased tall grasses; decreased diversity
Increase in nitrophilous graminoids, decline of typical species
Decrease in lichens, increase in biomass, accelerated succession
Increased tall grasses, decreased diversity
Increase in nitrophilous graminoids, changes in diversity
Increase in tall graminoids, decreased diversity, decrease in bryophytes
Increase in nitrophilous graminoids, changes in diversity
Effects on bryophytes and lichens
15-25
10-20
10-20
20-30
10-20
10-25
10-15
5-10
Heathland habitats (F)
Northern wet heaths
Dry heaths
Arctic, alpine, and subalpine scrub habitats
Decreased heather dominance, transition heather to grass, decline in lichens and mosses
Transition heather to grass, decline in lichens
Decline in lichens, mosses, and evergreen shrubs
10-20
10-20
5-15
Coastal habitat (B)
Shifting coastal dunes
Coastal stable dune grasslands
Coastal dune heaths
Moist to wet dune slacks
Increased biomass, increased N leaching
Increase in tall grasses, decreased prostrate plants, increased N leaching
Increase in plant production, increased N leaching, accelerated succession
Increase in biomasss and tall graminoids
10-20
10-20
10-20
10-25
Mire, bog, and fen habitats (D)
Raised and blanket bogs
Poor fens
Rich fens
Mountain rich fens
Changed species composition, N saturation of Spagnum
Increased sedges and vascular plant, negative effects on mosses
Increase in tall graminoids, decreased diversity, decrease of characteristic mosses
Increase in vascular plants, decrease in bryophytes
5-10
10-20
15-35
15-25
Forest habitats (G)
Mycorrhizae
Ground vegetation
Lichens and algae
Reduced sporocarp production, reduced below ground species composition
Changed species composition, increased nitrophilous species; increased susceptibility to
parasites (insects, fungi, virus)
Increase in algae; decrease in lichens
10-20
10-15
10-15
Source: Adapted from Achermann and Bobbink (2003).
3.3.7.2. U.S.
1 Efforts have begun to develop empirical relationships in the U.S., particularly for western
2 ecosystems, however there is currently no published national assessment of empirical critical loads for N
3 in the U.S., nor is there an assessment for the continent of North America. Table 4-4 summarizes
4 publications of deposition levels and related ecological effects, presenting critical load levels when
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1 reported in the original publication. Table 4-4 includes N levels at which effects are manifested in
2 terrestrial and freshwater ecosystems that have been documented through N addition and deposition
3 gradient studies. Several important studies from Europe published after the assessment by Bobbink et al.
4 are included in addition to some publications from Asia. Dose-response relationships between N and
5 environmental indicators are given in Table 3-25.
6 In terrestrial ecosystems, the reported effect levels range from 4 to 5 kg N/ha/yr for changes in the
7 abundance of individual sensitive alpine plant species, to 20 kg N/ha/yr for community level changes in
8 alpine plant communities. Clark and Tilman (2008) calculate the CL for the onset of reduced relative
9 species number in grasslands to be 5.3 kg N/ha/yr with a 95% inverse prediction interval of 1.3-9.8 kg
10 N/ha/yr. A critical load of 3.1 kg N/ha/yr is considered protective of lichen communities in the West (Fenn
11 et al. 2008).
12 Differences in the levels at which increased nitrification and NO3 leaching have been observed in
13 eastern and western watersheds. For example, Rueth (2002) observed increased rates of nitrification in
14 old-growth forests in Colorado at approximately 5 kg N/ha/yr, whereas Aber et al. (2003) associated the
15 onset of NO3 leaching in eastern forests with deposition levels of 7 to 10 kg N/ha/yr. The critical load for
16 NO3 leaching in Western chapparal ecosystems is 17 kg N/ha/yr (Fenn et al. 2008).
17 There is evidence that freshwater wetlands in the U.S. and Canada that are dominated by
18 Sphagnum sp. are affected by N deposition. Most evidence documents N retention, peat accumulation and
19 changes in NPP, and is not sufficient to quantify a critical load. The suggested critical load for protecting
20 the population health of northern pitcher plant is 10-14 kg N/ha/yr (Ellison, 2002)Gotelli and Ellison
21 2006). There are no publications suggesting critical loads for coastal marsh ecosystems.
Table 3-25. Summary of dose-response curves for N deposition and ecological indicators.
Ecosystems
Deposition range
(kg N/ha2/yr)
Effect
Indicator
Study region
Response curve
Reference
N deposition
Forest 1-75
Forest
2-8'
*wet deposition only
Forest 0-50
•throughfall N
Nutrient N leaching
enrichment
Acidification/
Nutrient
enrichment
Acidification/
Nutrient
enrichment
%N in the Oa horizon
Soil solution N03-N
65 forest sites
across Europe
12 red spruce stands
across the
northeastern US
104 European
monitoring site
Y=0.48xX-2.17(r2=0.69;
P<0.001)
Y: N leaching(kg N/ha2/yr)
X: total inorganic N deposition (kg
N/ha2/yr)
Y=0.097xX+1.03(r2=0.63)
Y: N content in the Oa horizon (%)
X: wet inorganic N deposition (kg
N/ha2/yr)
Conifers: Y=0.06e0.132x (r2=0.59
P=0.0001)
Deciduous: Y=0.018e0.266x
(r2=0.65P=0.0001)
Y: N03- concentration in soil water
(avagesJan 1996 to Jan. 1998)
(mg N /L)
X: throughfall N deposition
(averages 1993-1997) (kg
N/ha2/yr)
Dise and Wright
(Lawrence, 2007)
(1995)
Driscoll et al.
(Driscoll, 2001)
Gundersen et al.
(Gundersen,
2006)
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Ecosystems
Deposition range
(kg N/ha2/yr)
Effect
Indicator
Study region
Response curve
Reference
Forest
0-40
•throughfall N
Acidification/
Nutrient
enrichment
Soil solution N03-N
Forest
0-25
"Bulk precipitation N
Acidification/
Nutrient
enrichment
Forest
Relation between throughfall
and bulk precipitation N input
Forest
Forest
0-40
•throughfall N
0-40
•throughfall N
Grassland 5-35
Lakes
Lakes
Surface
water
Surface
water
Stream
water
Stream
water
1-16*
*wet deposition only
1-16*
*wet deposition only
Acidification/
Nutrient
enrichment
Acidification/
Nutrient
enrichment
Acidification/
Nutrient
enrichment
Nutrient
enrichment
Nutrient
enrichment
3.1 to 17.6* Nutrient
* Net anthropogenic nitrogen enrichment
inputs (NANI)
4-12
5-13
5-13
Acidification/
Nutrient
enrichment
Acidification/
Nutrient
enrichment
Acidification/
Nutrient
enrichment
Soil solution N03-N
Foliage N
C:N organic layer
Species richness
water [DIN]
Chla:Tot-P
104 European
monitoring site
104 European
monitoring site
104 European
monitoring site
104 European
monitoring site
104 European
monitoring site
68 acid grasslands
across UK
4296 lakes across
USA, Canada and
Europe
515 lakes across
USA, Canada and
Europe
Riverine exports of anthropogenic 16 watersheds from
N Maine to Virginia
Surface water [NOs-
N export
Inorganic N retention
220 lakes and
streams across the
northeastern US
83 lakes and
streams across the
northeastern US
83 lakes and
streams across the
northeastern US
Conifers: log(Y)=0.06X-1.2 (r2=0.59
P=0.0001)
Broadleaves:log(Y)=0.12X-1.8
(r2=0.65P=0.0001)
Y: NOs- concentration in soil water
(averages Dec 1995 to Feb. 1998)
(mg N/L)
X: Throughfall N deposition
(averages 1993-1997) (kg
N/ha2/yr)
Conifers: log(Y)=0.09X-1.3 (r2=0.32
P<0.0001)
Broadleaves:log(Y)=0.09X-1.18
(r2=0.16P=0.02)
Y: NCb- concentration in soil water
(avagesDec1995toFeb. 1998)
(mg N/L)
X: Bulk precipitation N deposition
(averages 1993-1997) (kg
N/ha2/yr)
Conifers: Y=1.8X-2.3(r2=0.65
P<0.0001)
Broadleaves: Y=0.86X-4.9 (r2=0.32
P=0.0008)
Y: Throughfall N deposition
(averages 1993-1997) (kg
N/ha2/yr)
X: Bulk precipitation N deposition
(averages 1993-1997) (kg
N/ha2/yr)
Conifers: Y=0.14X+12.7(r2=0.40
P<0.0001)
Y: Foliage N concentration (mg/g)
X: Throughfall N deposition
(averages 1993-1997) (kg
N/ha2/yr)
Conifers: Y=-0.21X+31.5(r2=0.19
P=0.0002)
Broadleaves: Y= -0.48X+32.3
(r2=0.14P=0.036)
Y: C:N organic layer
X: Throughfall N deposition
(averages 1993-1997) (kg
N/ha2/yr)
Y=23.3-0.408 xX(r2=0.70;
P<0.0001)
Y: plant species richness
X: total inorganic N deposition (kg
N/ha2/yr)
logY=1.34xlogX-1.55(r2=0.70;
P<0.001)
Y: water DIN (ug/L)
X: wet deposition (kg N km-2yr-1)
LogY=1.03x|n(logX)-1.43
(r2=0.52; P<0.001)
Y: Chi a : Tot-P
X: wet deposition (kg N km-2yr-1)
Y=(0.00087xQ-0.096) x NANI -
101
Y: Riverine N flux (kg N km-2/yr)
Q: rivine discharge
NANI: Net anthropogenic N inputs
(N km-2/yr)
Summer: Y=2.5xX-14.4(r2=0.30,
P<0.001)
Spring: Y=6.7xX-40.7 (r2=0.38,
P<0.001)
Y: N03-concentration in water
(umol/L)
X: N deposition (kg N/ha2/yr)
Y=0.85xX-5.8 (r2=0.56, P=0.01)
Y: N03-export (kg N/ha2/yr)
X: N deposition (kg N/ha2/yr)
Y=-0.07xX+1.44(r2=0.50, P=0.01)
Y: inorganic N retentions (kg
N/ha2/yr)
X: N deposition (kg N/ha2/yr)
Kristensen et al.
(Kristensen, 2006)
Kristensen et al.
2006
Kristensen et al.
2006
Kristensen et al.
2006
Kristensen et al.
2006
Stevens et al.
2004
Bergstrom and
Jansson 2006
Bergstrom and
Jansson 2006
Howarth et al.
2006
Aberetal. (2003)
Aber et al. (2003)
Aberetal. (2003)
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Ecosystems
Estuary
Peatland
Peatland
Peatland
Peatland
Spruce
forest
Deposition range
(kg N/ha2/yr)
8-24*
*N loads from atmospheric
deposition, human waster
water and fertilization
application
0-160
2-20
2-20
2.7 to 8.1 kgN/ha/yr
5 to 30 kg N/ha/yr
Effect
Nutrient
enrichment
Acidification/
Nutrient
enrichment
Nutrient
enrichment
Nutrient
enrichment
Nutrient
enrichment
Nutrient
enrichment
N20 flux
Indicator
Eelgrass area (ha)
NPP of Sphagnum fuscum
Decomposition of litter collected
from the field and incubated and
constant temperature
Decomposition of litter collected
from the field and incubated and
constant temperature
Showed N accumulation
increases linearly with N
deposition
showed a significant and positive
correlations between increasing N
deposition and increasing N20
flux
Study region
Waquoit Bay
8 bogs in North
America and Europe
12 bogs from 9
European countries
12 bogs from 9
European countries
23 ombrotrophic
peatlands in Canada
2 sites in Germany
and Ireland
Response curve
Y=-1.9xX + 50.7(r2=0.89)
Y: Eelgrass area (ha)
X: modeled N load (kg N/ha2/yr)
Y=831*e-0.185x-48(r2=0.73,
P<0.01)
Y: difference between NPP of
Sphagnum fuscum under
augmented N and control treatment
(gm-2yr-1);
X: N deposition (kg N/ha2/yr)
Y= 0.98*0.21 ln(x)(r2 =0.75, P
<0.01 ) four days incubation
Y= 0.49*0. 11ln(x)(r2= 0.73,
P<0.01) 10 days incubation
Y= N deposition (g m-2/yr)
X= C02 emission (mg/g/h)
Y=4.3*2.4ln(x)(r2=0.61,P=0.01)
Y= N deposition (g m-2/yr)
X= DOC concentration (mg/g)
y = 3.50x +0.64, r2 =0.29, P<0.001
Y= N wet deposition (g m-2/yr)
X= N accumulation in soil (g m-2/yr)
y= 4.7 + 1. 4x,r2 = 0.38, P< 0.001
Y= N wet deposition (mmol m-2)
X= N20 flux rates (|jg N20-Nm-
2/h)
Reference
Driscoll et al. 2003
Vittetal. 2003
Bragazza et al.
(2006)
Bragazza et al.
(2006)
Moore et al. 2004
Butterbach-Bahl
etal., 1998
3.3.8. Characterization of Sensitivity and Vulnerability
3.3.8.1. Extent and Distribution of Sensitive and Vulnerable Ecosystems
1 In general, ecosystems that are most responsive to nutrient enrichment from atmospheric N
2 deposition are those that receive high levels of N loading, are N-limited, or contain species that have
3 evolved in nutrient-poor environments. Species that are adapted to low N supply will often be more
4 readily outcompeted by species that have higher N demand when the availability of N is increased (Aerts,
5 1990; Tilman and Wedin, 1991; Krupa, 2003). As a consequence, some native species can be eliminated
6 by Nr deposition (Ellenberg, 1985; Falkengren-Grerup, 1986, 1989; Roelofs, 1986; Stevens et al., 2004).
7 Note the terms "low" and "high" are relative to the amount of bioavailable N in the ecosystem and the
8 level of deposition.
9 The following discussion of sensitive ecosystems is organized into three ecosystem categories:
10 terrestrial, transitional, and aquatic. Case studies are intended to highlight ecosystems and/or regions
11 where there are many publications documenting the effects of N deposition, thus they can provide
12 sufficient data for quantitative risk assessment.
Terrestrial
13 Most terrestrial ecosystems are N-limited, therefore they are sensitive to perturbation caused by N
14 additions (LeBauer, 2008). Little is known about the full extent and distribution of the terrestrial
15 ecosystems in the U.S. that are most sensitive to adverse impacts caused by nutrient enrichment from
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1 atmospheric N deposition. Effects are most likely to occur where areas of relatively high atmospheric N
2 deposition intersect with N-limited plant communities. The factors that govern the vulnerability of
3 terrestrial ecosystems to nutrient enrichment from N deposition include the degree of N-limitation, rates
4 and form of N deposition, elevation, species composition, length of growing season, and soil N retention
5 capacity.
6 Regions and ecosystems in the western U.S. where N enrichment effects have been documented in
7 terrestrial ecosystems are shown on Figure 3-51 (Fenn et al., 2003a). The alpine ecosystems of the
8 Colorado Front Range (see case study), chaparral watersheds of the Sierra Nevada, lichen and vascular
9 plant communities in the San Bernadino Mountains (see case study) and the Pacific Northwest, and the
10 southern California coastal sage scrub community are among the most sensitive terrestrial ecosystems.
11 In the eastern U.S., the degree of N saturation of the terrestrial ecosystem is often assessed in terms
12 of the degree of NO3 leaching from watershed soils into ground water or surface water. Stoddard (1994)
13 estimated the number of surface waters at different stages of saturation across several regions in the
14 eastern U.S. Of the 85 northeastern watersheds examined, 40% were in N-saturation Stage 0, 52% in
15 Stage 1, and 8% in Stage 2 (stages are defined in Section 3.3.2.1). Of the northeastern sites for which
16 adequate data were available for assessment, those in Stage 1 or 2 were most prevalent in the Adirondack
17 and Catskill Mountains. Effects on individual plant species have not been well studied in the U.S. More is
18 known about the sensitivity of particular plant communities. Based largely on results obtained in more
19 extensive studies conducted in Europe, it is expected that the more sensitive terrestrial ecosystems include
20 hardwood forests, alpine meadows, arid and semi-arid lands, and grassland ecosystems.
Transitional
21 About 107.7 million acres of wetlands are widely distributed in the conterminous U.S., 95 percent
22 of which are freshwater wetlands and 5 percent are estuarine or marine wetlands (U.S. FWS 2005; Figure
23 3-52). At one end of the spectrum, ombrotrophic bogs are very sensitive to Nr deposition because they
24 receive exogenous nutrients exclusively from precipitation, and the species in them are adapted to low
25 levels of N (Shaver and Melillo 1984, Bridgham et al. 1995, 1996). Intertidal wetlands are at the other end
26 of the spectrum; in these ecosystems marine/estuarine water sources generally exceed atmospheric inputs
27 by one or two orders of magnitude (Morris, 1991). Data are not available with which to evaluate the
28 extent to which wetlands in the U.S. have been affected by nutrient enrichment from N deposition.
29 Wetlands are widely distributed, including some areas that receive moderate to high levels of
30 N deposition.
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2,3
River
O City (.50,000)
^•1 Lake
^H National Forest/National Park
Ecological effects
Aquatic:
1. N enrichment or eutrophication of lakes
2. Elevated nitrate levels in runoff
incipient stages), 4
2, 3, 4, 5, 6, 7
(circumstantial evidence, see'text),
Terrestrial:
3. N enrichment or N saturation (e.g.soil, vegetation, & water are N enriched:
increased fluxes of nitrogenous trace gases)
4. Altered plant communities in response to N enrichment
5. Physiological perturbation of plants: combined effects of ozone and N deposition
6. Impacts on lichen communities.
7. Evidence that threatened and endangered species impacted
8. Decreased diversity of mycorrhizal communities
9. Forest expansion into grasslands (preliminary evidence for)
A Plot with lichen community affected by air pollution with a major N deposition component
High-elevation lake with elevated nitrate, reportedly from N deposition
Available data indicate elevated N deposition, but ecological effects have not been studied.
Source: Fenn et al. (2003a)
Figure 3-51. Map of the western U.S. showing the primary geographic areas where N deposition
effects have been reported. Eutrophication effects are more widespread and of greater importance
than acidification effects in western North America. Areas where effects of air pollution on lichen
communities have been reported in California are represented by pink triangles. The plots in
northcentral Colorado where lichen community changes were observed are exposed to emissions
of both N and sulfur (S) from two large power plants in Craig and Haydens, Colorado (Peterson and
Neitlich, 2001). The areas shown in red in Oregon and Washington (lichen communities affected by
N deposition) are kriged data (Geiser and Neitlich, 2007). Only lakes at an elevation greater than
1000 m and with a N03 concentration of more than 5 peq/L (measured in fall surveys or on an
annual volume-weighted basis) are shown in this figure. Other high-elevation lakes in the West also
had elevated N03 concentrations, but were excluded because N sources other than N deposition
may have contributed to the elevated concentrations of N03.
1 Peat-forming bog ecosystems are among the most sensitive transitional ecosystems to the effects of
2 N deposition. In the conterminous U.S., peat-forming bogs are most common in areas that were glaciated,
3 especially in portions of the Northeast and Upper Midwest (EPA, 1993a). In Alaska, these ecosystems are
4 common in poorly drained locations throughout the state.
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Source: NLOD 2001
Source: Data were obtained from the National Land Cover Data (NLCD) (2001) (http://www.mrlc.gou/)
Figure 3-52. Map of location of wetlands in the eastern U.S. Woody wetlands are coded blue and
emergent herbaceous wetlands are coded red.
1 Nutrient concentrations in wetland waters associated with the Great Lakes suggest that coastal
OO
2 Great Lakes wetlands are N-limited. Hill et al. (2006) found that more wetlands were N- than P-limited at
3 each of the five Laurentian Great Lakes. This result is consistent with the apparent N-limitation of most
4 North American marsh lands (Bedford et al., 1999). Nutrient loading to lakeshore wetlands is a concern
5 throughout the lower lakes (Lakes Erie, Ontario, and the southern part of Lake Michigan) and in some
6 localized areas of the upper lakes (Hill et al., 2006). Both agricultural and atmospheric sources of
7 nutrients contribute to this stress.
8 Coastal marsh ecosystems, unlike bog ecosystems, often receive large N inputs in tidal water,
9 groundwater, and surface runoff. Atmospheric inputs to these systems are important because any N
10 addition has the potential to contribute to eutrophication of coastal marshes and nearby marine and
11 estuarine ecosystems (Paerl, 2002; Galloway, 2003). At many locations, especially along the Atlantic and
12 Gulf coasts, atmospheric N inputs probably contribute to eutrophication problems in coastal marshes
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1 either by direct deposition to the wetland or from marine water inputs of N that originated from
2 atmospheric deposition.
Freshwater Aquatic
3 Aquatic systems in which N has been observed to influence ecological processes either receive
4 extremely high inputs (e.g., Dumont et al., 2005), or have very low initial N concentrations, and respond
5 rapidly to additional inputs (Baron, 2000) Bergstrom and Jansson, 2006). Eutrophication effects on
6 freshwater ecosystems from atmospheric deposition of N are of great concern in lakes and streams that
7 have very low productivity and nutrient levels and that are located in remote areas. In more productive
8 freshwaters, nutrient enrichment from N deposition usually does not stimulate productivity or community
9 changes because P is more commonly the limiting nutrient. Also, in many places with even minor levels
10 of human disturbance, nutrient enrichment with both N and P from non-atmospheric sources is common.
11 Thus, eutrophication effects from N deposition are most likely to be manifested in undisturbed, low-
12 nutrient surface waters such as those found in the higher elevation areas of the western U.S. The most
13 severe eutrophication from N deposition effects is expected downwind of major urban and agricultural
14 centers.
15 High concentrations of lake or streamwater NO3 , indicative of ecosystem saturation, have been
16 found at a variety of locations throughout the U.S., including the San Bernardino and San Gabriel
17 Mountains within the Los Angeles Air Basin (Fenn et al., 1996), the Front Range of Colorado (Baron,
18 1994) Williams et al., 1996a), the Allegheny Mountains of West Virginia (Gilliam et al., 1996), the
19 Catskill Mountains of New York (Murdoch, 1992; Stoddard, 1994, the Adirondack Mountains of New
20 York (Wigington Jr., 1996, and the Great Smoky Mountains in Tennessee (Cook, 1994). All of these
21 regions, except Colorado, received more than about 10 kg N/ha/yr atmospheric deposition of N
22 throughout the 1980s and 1990s. In contrast, the Front Range of Colorado receives up to about 5 kg
23 N/ha/yr of total (wet plus dry) deposition (Sullivan et al., 2005), less than half of the total N deposition
24 received at many of these other locations.
25 High concentrations of NO3 in surface waters in the western U.S. are not widespread. NO3
26 concentrations during the fall sampling season were low in most western lakes sampled in the Western
27 Lakes Survey. Only 24 sampled lakes were found to have NO3 concentrations greater than 10 (ieq/L. Of
28 those, 19 lakes were situated at high elevation, most above 3,000 m (Eilers, 1987). Other effects on
29 aquatic ecosystems in the west are summarized in Table 3-26.
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Table 3-26. changes in aquatic ecosystems associated with elevated N loadings in the Western U.S.
Ecological or Environmental
Impact
Location
Level of Uncertainty
Possibility of Broader
Occurrence (at other sites)
Reference
Effects in Aquatic Systems
Elevated NOf in runoff; most
severe in southern California and in
chaparral catchments in the
southwestern Sierra Nevada
N enrichment and shifts in diatom
communities in alpine lakes
Reduced lake water clarity and
increased algal growth
Increased NCr concentrations in
high-elevation lakes
Transverse ranges of southern
California; low-elevation
catchments in the Sierra Nevada;
high-elevation catchments in the
Colorado Front Range
Colorado Front Range; Lake Tahoe
(California/Nevada border)
Lake Tahoe (California/Nevada
border); high-elevation lakes
throughout central and southern
Sierra Nevada
Well-documented response
It is unclear how widespread
this phenomenon is outside
the ecosystems listed,
because there is littler
information from low-elevation
systems in the Sierra Nevada
and elsewhere.
Documented for two lakes east of These effects seem likely in
the Continental Divide and Lake other N-enriched lakes but
Tahoe have not been investigated.
Well-documented response; N
and P deposition believed to be
important factors
Several regions, mainly downwind
of urban centers
Fairly well established from lake
surveys, but more data needed
for improved definition of
frequency and severity
Lake Tahoe is an unusual
case because of its renowned
lake clarity; extent of
occurrence elsewhere in
northern Sierra Nevada is
unknown.
Evidence suggests that urban
plumes and agricultural
emissions affect lake NCr
levels. There is also evidence
of impacts on low-elevation
lakes.
Williams etal. (1996b), Fenn and Poth
(1999), Fennelal.(2003a)
Baron et al. (2000), Wolfe et al.
(2001), Goldman (1988)
Jassby et al. (1994), Sickman et al.
(2003)
Figure 2, Sickman et al. (2002)
1 There is some evidence suggesting that reductions in atmospheric N deposition could decrease the
2 extent of eutrophication in at least some of the Great Lakes. It has generally been believed that the
3 Laurentian Great Lakes are P-limited (Schelske, 1991; Downing and McCauley, 1992; Rose and Axler,
4 1998). Water quality in the open waters of these lakes has been improving in recent years in response to
5 controls on point sources of P (Nicholls et al., 2001). Work by Levine et al. (1997), however, suggested a
6 more complicated pattern of response to nutrient addition for Lake Champlain. They added nutrients to in
7 situ enclosures and measured indicators of P status, including alkaline phosphatase activity and
8 orthophosphate turnover time. Although P appeared to be the principal limiting nutrient during summer, N
9 addition also resulted in algal growth stimulation. P sufficiency appeared to be as common as P
10 deficiency. During spring, phytoplankton growth was not limited by P, N, or Si, but perhaps by light or
11 temperature (Levine et al., 1997).
Estuarine and Coastal Aquatic
12 N is an essential nutrient for estuarine and marine fertility. However, excessive N contributions can
13 cause habitat degradation, algal blooms, toxicity, hypoxia (reduced dissolved O2), anoxia (absence of
14 dissolved O2), reduction of sea grass habitats, fish kills, and decrease in biodiversity (Paerl, 2002, Valiela
15 and Costa, 1988; Valiela et al., 1990; Boynton et al., 1995; Paerl, 1995, 1997; Howarth, 1996). Each of
16 these potential impacts carries ecological and economic consequences. Ecosystem services provided by
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1 estuaries include fish and shellfish harvest, waste assimilation, and recreational activities (Costanza et al.,
2 1997).
A.
3
4
5
6
7
8
9
10
Low Moderate ModerateModerate High
low high
0 200 400
I Kilometers
1 Miles
0 100 200
^H High: symptoms occur periodically or persistently and/or over an extensive area.
i i Moderate high: symptoms occur less regularly and/or over a medium to extensive area.
i i Moderate: symptoms occur less regularly andfor over a medium area.
^•1 Moderate low: symptoms occur episodically and/or over a small to medium area.
^H Low: few symptoms occur at more than minimal levels,
i i Unknown: insufficient data for analysis.
Change in eutrophic condition since 1999 assessment
A Symptoms improved since 1 999 assessment.
O No change in symptoms since 1999 assessment.
V Symptoms worsened since 1999 assessment.
O Insufficient data to show trend
Source: Brickeretal. (2007
Estuaries and coastal waters tend to be N-limited and are therefore inherently sensitive to increased
atmospheric N loading (D'Elia et al., 1986; Howarth, 2006). The national estuary condition assessment
conducted by Bricker et al. (2007) found that the most impacted estuaries occurred in the mid-Atlantic
region and the estuaries with the lowest symptoms of eutrophication were in the North Atlantic. N over-
enrichment is a major environmental problem for coastal regions of the U.S., especially in the eastern and
Gulf Coast regions. Of 138 estuaries examined by Bricker et al. (1999) 44 were identified as showing
symptoms of nutrient over-enrichment. Estuaries are among the most biologically productive ecosystems
on Earth and provide critical habitat for an enormous diversity of life forms, especially fish. Of the 23
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1 estuaries examined in the Northeast, 61% were classified as moderately to severely degraded (Bricker,
2 1999). Other regions had mixtures of low, moderate, and high degree of eutrophication (See Figure 2-53).
3 The estuaries with the greatest extent of eutrophication corresponded with conditions related to
4 both the degree of N loading and the inherent sensitivity of the estuary, as influenced by morphology and
5 water flushing dynamics (see Annex C for a discussion of estuarine sensitivity). The most eutrophic
6 estuaries were generally those that had large watershed-to-estuarine surface area, high human population
7 density, high rainfall and runoff, low dilution, and low flushing rates (Bricker, 2007).
Figure 3-53. Overall eutrophication condition on a national scale.
8 Bricker et al. (2007) evaluated the future outlook of the nations estuaries based on population
9 growth and future management plans. They predicted that trophic conditions would worsen in 48
10 estuaries, stay the same in 11, and improve in only 14 by the year 2020. Between 1999 and 2007, an equal
11 number of estuary systems have improved their trophic status as have worsened. The assessed estuarine
12 surface area with high to moderate/high eutrophic conditions have stayed roughly the same, from 72% in
13 1999 (Bricker, 1999) to 78% in the recent assessment (Bricker, 2007).
14 Studies linking changes in estuary nutrient status to atmospheric N deposition have been limited,
15 though it is noted that many states are addressing atmospheric inputs as part of their development of Total
16 Maximum Daily Load plans to address estuarine water quality impairments, including those associated
17 with low dissolved O2. In an effort to evaluate the contribution of atmospheric N deposition to the future
18 reduction in N loading to estuaries, Castro and Driscoll (Castro, 2002) reported model calculations that
19 suggested that considerable reductions (more than 25%) in atmospheric N deposition will be needed to
20 reduce the contribution made by atmospheric N deposition to the total N loads to their study estuaries in
21 the northeastern U.S. A simulated reduction in atmospheric deposition of 25% of ambient deposition rates
22 reduced the contribution made by atmospheric deposition to the total estuarine N loads by only 1% to 6%
23 (Castro, 2002). In a later study, Driscoll et al. (2003b) estimated that reduction of both mobile N
24 emissions sources and electric utilities would produce an estimated reduction in estuarine N loading in
25 Casco Bay, Maine of 13% (Driscoll et al., 2003). Casco Bay receives the lowest atmospheric and non-
26 atmospheric N loading per unit area of watershed (4 kg N/ha/yr) of the eight estuaries in the northeastern
27 U.S. evaluated by Driscoll et al. (2003) (Figure 3-34).
Case Study: Alpine and Subalpine Communities of the Eastern Slope of the Rocky Mountains
28 Some alpine plant communities occur in areas that receive moderately elevated atmospheric N
29 deposition; especially those proximal to urban areas (see Annex C for a map). Because alpine plant
30 species are typically adapted to low nutrient availability, they often are sensitive to effects from N
31 enrichment.
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1 Research on N enrichment effects on alpine and subalpine ecosystems in the western U.S. has been
2 limited mainly to studies at the Loch Vale Watershed in Rocky Mountain National Park and the Niwot
3 Ridge Long-Term Ecosystem Research site; both located east of the Continental Divide in Colorado (see
4 review by Burns, 2004). Research has been conducted in this region on both the terrestrial and aquatic
5 effects of nutrient enrichment.
Terrestrial Effects
6 Changes in biomass production and NO3 leaching are indicative of effects on the health and vigor
7 of plants in alpine and subalpine ecosystems. Biomass production responses of alpine communities to
8 increased N deposition are dependent on moisture regimes (Fisk, 1998) and are driven by shifts in species
9 composition. In a fertilization experiment, the addition of 25 kg N/ha/yr during summer caused a
10 community shift towards greater dominance of hairgrass (Deschampsia sp.) in wet alpine meadows, but
11 the increase in plant biomass (+67%) and plant N content (+107%) following N fertilization was higher in
12 graminoid-dominated dry meadows than in forb-dominated wet meadows (+53% plant biomass, +64%
13 standing N crop, respectively) (Bowman et al., 1995; Burns, 2004).
14 Alteration of plant productivity and species richness has been observed in fertilization experiments.
15 Seastedt and Vaccaro (Seastedt, 2001) showed that four years of N addition to alpine vegetation at rates
16 ranging between 100 and 200 kg N/ha (depending on the year) caused marginal increases in plant foliage
17 productivity but reduced species richness. In a follow-up study at Niwot Ridge additions of 20, 40, and
18 60 kg N/ha/yr (on top of ambient N deposition near 5 kg N/ha/yr) over an 8-year period to a dry alpine
19 meadow led to an increase in plant biomass, and an increase in tissue N concentration at all treatment
20 levels within three years of application. Much of the response was due to increased cover and total
21 biomass of sedges (Carex spp.}. There was a significant decrease in Kobresia myosuroides with increasing
22 N input.
23 High elevation alpine zones exhibit a relatively low capacity to sequester atmospheric deposition of
24 N because of steep slopes, shallow soils, sparse vegetation, short growing season and other factors
25 (Baron, 1994; Williams et al., 1996a). Results from several studies suggest that the capacity of Rocky
26 Mountain alpine catchments to sequester N is exceeded at deposition levels less than 10 kg N/ha/yr
27 (Baron, 1994; Williams and Tonnessen, 2000). The changes in plant species that occur in response to N
28 deposition in the alpine zone can result in further increased leaching of NO3 from the soils, because the
29 plant species favored by higher N supply are often associated with greater rates of N mineralization and
30 nitrification than the preexisting species (Bowman et al., 1993, 2006; Steltzer and Bowman, 1998;
31 Suding, 2006).
32 Effects of Nr deposition to alpine terrestrial ecosystems in this region include community-level
33 changes in plants, lichens, and mycorrhizae. Alpine plant communities are sensitive to changes in species
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1 composition in response to added N (Bowman, 1995; Seastedt, 2001). Plant species composition likely
2 responds at lower N input levels than those that cause measurable changes in soil inorganic N content. For
3 example, Bowman et al. (2006) conducted a N-addition experiment in the Colorado Front Range with 20,
4 40, or 60 kg N/ha/yr. Experimental sites were monitored for 8 years along with a control site that received
5 about 5 kg N/ha/yr total ambient deposition. Changes in plant species composition associated with the
6 treatments occurred within 3 years of the initiation of the experiment, and were significant at all levels of
7 N addition.
8 Using changes of individual species abundance and ordination scores to evaluate critical load, the
9 critical load for total N deposition was estimated for change in individual species to be 4 kg N/ha/yr and
10 for overall community change to be 10 kg N/ha/yr (Bowman et al., 2006). In contrast, increases in NO3
11 leaching, soil solution inorganic NO3~, and net nitrification were detectable at levels above 20 kg N/ha/yr
12 (Bowman et al., 2006). These results indicate that changes in plant species composition may be detectable
13 at lower N deposition rates than the level at which the traditional soil indicators signal ecosystem
14 responses to N deposition. This response suggests that changes in species composition are probably
15 ongoing in alpine dry meadows of the Front Range of the Colorado Rocky Mountains at current
16 atmospheric N deposition levels. This research also demonstrated that long-term experimental fertilization
17 plots illustrate a clear response of alpine flora to N addition, including shifts toward graminoid plants that
18 shade smaller flowering species, and accompanying changes in soil N cycling (Bowman et al., 2006).
19 Changes in alpine plant species composition have also been documented on Niwot Ridge, where
20 increased cover of plant species that are most responsive to N fertilization has occurred in some of the
21 long-term monitoring plots (Korb and Ranker, 2001; Fenn et al., 2003a). These changes have probably
22 developed in response to changes in N deposition. However, the influences of climatic change,
23 particularly changes in precipitation (Williams et al., 1996a), and pocket gopher disturbance (Sherrod and
24 (Seastedt, 2001) could not be ruled out (Fenn et al., 2003a). The altered N cycling provided the potential
25 for replacement of some native plant species by more competitive, faster growing native species
26 (Bowman and Steltzer, 1998; Baron, 2000) Bowman, 2000).
Aquatic Effects
27 Rocky Mountain National Park has been the site of research addressing the effects of N deposition
28 on algal species abundance in freshwater lakes. Wolfe et al. (2001) analyzed sediments from Sky Pond
29 and Lake Louise, two small alpine lakes located at more than 3300 m elevation on the east slope of the
30 Colorado Front Range in Rocky Mountain National Park. Prior to 1900, the diatom flora was typical of
31 oligotrophic Rocky Mountain lakes, dominated by such species as Aulacoseira distorts, A. perglabra,
32 Fragilaria pinnata, F. construens, and various Achnanthes spp. The mesotrophic planktonic species
33 Astrionella formosa and Fragilaria crotonensis were present in trace frequencies, but became common
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1 elements of the diatom flora during the 20th century. Between 1950 and 1970, A. formosa became the
2 dominant taxa in both lakes. It is known from studies in other locations as an opportunistic alga that
3 responds rapidly to disturbance and nutrient enrichment (Renberg et al., 1993; Anderson et al., 1995;
4 Reavie and Smol, 2001). This shift in diatom species is apparently the result of environmental
5 stimulation, rather than recent colonization, as evidenced by the presence of these mesotrophic taxa in the
6 older sediment record.
CO o^
Ł ,_
CO CD
(D >
CD 03
O "0-
50 r
40
30
20
10
treatment x year P < 0.01
N added:
A
Source: Bowman et al. (2006)
Figure 3-54. Changes in plant species composition associated with N addition treatments in an
alpine dry meadow of the Colorado Front Range. Within 3 years of the initiation of the experiment,
statistically significant changes in the cover of Carex rupestris occurred at all treatment levels.
7 Additional corroborative evidence for the linkage between atmospheric N deposition and the
8 observed diatom shifts in these alpine lakes is provided by the results of laboratory (Interlandi and
9 Kilham, 1998) and in-lake (McKnight et al., 1990) N addition experiments. In both sets of experiments,
10 growth of A. formosa and F. crotonensis was accelerated by experimental N addition. The post-1950
11 period of rapid shifts in diatom species composition in Sky Pond and Lake Louise corresponded with
12 intensification of agricultural practices, animal husbandry, and population growth in adjacent regions to
13 the east of Rocky Mountain National Park (Wolfe et al., 2001). Nevertheless, N deposition at that time
14 was estimated to be low, probably less than 2 kg N/ha/yr (Baron, 2006).
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Case Study: Chesapeake Bay
1 Chesapeake Bay is the largest estuary in the U.S. and one of the most sensitive to N inputs
2 (Bricker, 1999; Howarth, 2007). Eutrophication effects have been pronounced in Chesapeake Bay
3 (Howarth, 2007) and it is perhaps the best known example in the U.S. of human activities leading to
4 accelerated estuarine eutrophication and its associated negative effects. In the recent national assessment
5 of eutrophic conditions in estuaries, the Chesapeake Bay stands out as a system with both physical
6 features and N loading levels that make it particularly vulnerable to eutrophication (Bricker, 2007).
7 The role of atmospheric N deposition in estuary eutrophication in the U.S. was ignored until Fisher
8 and Oppenheimer (1991) suggested that it could constitute up to 40% of the total N inputs to the
9 Chesapeake Bay. Although their analysis was preliminary, and has been updated by more conservative
10 estimates (e.g., Boyer et al, 2002; Boyer and Howarth, 2002), it served to focus attention on the role of
11 atmospheric deposition as an important contributor to the overall budget of estuaries in the eastern U.S. N
12 inputs to the Chesapeake Bay have increased substantially over the last 50 to 100 years. The increase is
13 attributed to rapid acceleration of the use of chemical fertilizers in agriculture, the increasing human
14 population density and associated wastewater discharge, and rising atmospheric N emissions within the
15 airshed and consequent deposition within the Chesapeake Bay watershed. Atmospheric deposition of N is
16 currently estimated to contribute about one-fourth of the total N loading to Chesapeake Bay (Boyer et al.
17 2002; Howarth, 2007).
18 Human activities have increased the susceptibility of the Chesapeake Bay to the effects of
19 atmospheric N deposition. For example, the filling in of wetlands and deforestation for agricultural and
20 urban development, have reduced the ability of natural ecosystem processes to remove or trap nutrients,
21 thereby further accelerating nutrient delivery to the bay. In addition, diseases and over-harvesting led to a
22 dramatic decline of the once highly abundant eastern oyster, seriously reducing the natural filtering of
23 algae and other organic matter from the water column.
24 As a result of these changing conditions, eutrophic symptoms intensified in the Chesapeake Bay
25 from the mid-1950s to the mid-1980s. The most apparent symptoms were (1) high production of algae,
26 (2) increasingly turbid water, (3) major declines in SAV abundance and species, and (4) increasingly
27 worsening anoxia and hypoxia (Boesch et al., 2001). The recent national estuary condition assessment
28 (Bricker, 2007) reported that chlorophyll a, dissolved O2, nuisance/toxic algal blooms, and SAV rated
29 "high" in Chesapeake Bay in terms of severity of effects associated with eutrophication. In addition,
30 macroalgae and toxic algal bloom conditions have worsened since the previous national assessment in
31 1999 (Bricker, 1999; Bricker, 2007).
32 Concentrations of chlorophyll a in the surface mixed layer have increased tenfold in the seaward
33 regions of the bay and one-and-one-half- to twofold elsewhere, paralleling estimates of increased loading
34 of N and P to the bay since 1945 (Harding and Perry, 1997).
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1 SAV began to decline as a result of nutrient enrichment during the mid-1960s, disappearing entirely
2 from the Patuxent and lower Potomac Rivers. By 1980, many areas of the bay that once contained
3 abundant SAV beds had none or only very small remnants left (Orth and Moore, 1984). Research
4 indicated that the major driving factor in the decline of SAV was nutrient enrichment, which was causing
5 excessive growth of algae in the water column and on SAV leaf blades (epiphytic algae). This algal
6 growth decreased light availability to the submerged plants to the point that they could not survive (Kemp
7 et al., 1983; Twilley et al., 1985).
8 There is an annual cycle of O2 depletion in the Chesapeake Bay that begins as the water starts to
9 warm in spring, and O2 depletion accelerates during and following the spring freshet. The spring
10 accumulation of algal biomass is more than sufficient to create conditions for O2 depletion and summer
11 anoxia (Malone, 1991, 1992). Hypoxia (very low dissolved O2 concentration ~ < 2mg/L) and anoxia
12 (absence of dissolved O2) generally occur from May through September, with the most severe conditions
13 observed in mid-summer. Seasonal hypoxia has been a feature of the Chesapeake Bay since deforestation
14 during the colonial period (Cooper and Brush, 1991; Malone, 1991), but evidence suggests an increase in
15 the extent of the problem in recent decades (Officer, 1984) Malone, 1991). Estuarine eutrophication is
16 sometimes accompanied by increases in the populations of species of algae, often cyanobacteria that
17 produce toxins. Such chemicals can affect people, fish, shellfish, and other organisms. Blooms of algae
18 that produce toxins in Chesapeake Bay have become more extensive over approximately the past decade
19 (Bricker, 2007).
20 In 1983, EPA, District of Columbia, and states of Virginia, Maryland, and Pennsylvania signed the
21 first Chesapeake Bay Agreement, which established the Chesapeake Bay Program—a voluntary
22 government partnership that directs and manages bay cleanup efforts. Scientific findings from the
23 program led to the signing of the second Chesapeake Bay Agreement in 1987, in which it was agreed to
24 reduce by 40% the N and P entering the Chesapeake Bay by the year 2000. Point source reductions have
25 been most successful, especially for P. Between 1985 and 1996, emissions from P point sources were
26 reduced by 58% and N by 15%. Nonpoint source reductions have been slower, largely because nonpoint
27 sources of nutrients are more difficult to control. Nonpoint source emissions of N and P have been
28 reduced by only 7% and 9%, respectively (Boesch et al., 2001). Strategies to reduce nonpoint source
29 nutrients include changes such as adoption of better agricultural practices, reduction of atmospheric N
30 deposition, enhancement of wetlands and other nutrient sinks, and control of urban sprawl.
Case Study: San Bernardino
31 The San Bernardino Mountains lie east of the Los Angeles Air Basin in California. Pollutants
32 generated in the greater LA metropolitan area are transported 60-100 km downwind and affect mid-
33 elevation forests in the San Bernardino Mountains and the San Gorgonio Class I Wilderness area. The
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1 primary source of air pollution is fossil fuel combustion. Approximately half of the air pollution in the LA
2 air basin is generated from mobile sources including trucks, trains, cars, ships, and buses (South Coast Air
3 Quality Management District). On the western end of the San Bernardino Mountains, nearly half of the N
4 deposition is in reduced forms (Fenn and Poth, 2004), most of which is believed to originate from dairy
5 farms in the Chino/Norco area.
6 In the San Bernardino Mountains, a wide variety of N species (NO, NO2, HNO3, HNO2, NO3 ) are
7 deposited to vegetation and soil surfaces, in gaseous, wet, and dry forms. Ammonium (NH4 +) can also be
8 transported moderate distances from feedlots for cattle and poultry (Bytnerowicz, 2002). Along a west to
9 east gradient in the San Bernardino Mountains, throughfall N deposition goes from averaging 71 kg
10 N/ha/yr at Camp Paivika (nearer to the pollutant sources), to 9 kg N/ha/yr at Barton Flats (farther from the
11 sources), 45 km east of Camp Paivika (Breiner et al., 2007, Fenn et al. 2008). These throughfall
12 measurements were made using ion exchange resin columns that measure total NO3 and NH4+ deposition
13 from precipitation, plus fog or dry deposition that has been scavenged by the overstory pine canopy and
14 then washed through the canopy (Fenn and Poth 2004). Throughfall N deposition using this method is
15 also available for seven other sites within the San Bernardino Mountains (Fenn et al. 2008).
16 Several key ecological endpoints in the mixed conifer forests of the San Bernardino Mountains
17 have been linked to anthropogenic N deposition. Because air pollution has been high since 1945 in the LA
18 air basin (Lee et al., 2003), N deposition is in excess of plant and microbial demand (Fenn et al., 1996).
19 The cardinal symptom of excess N is the export of high NOs levels in streamwater (see 3.3.2.1), which is
20 well demonstrated for areas with N deposition above 17 kg/ha/yr in the San Bernardino and San Gabriel
21 Mountains (Breiner et al., 2007; Fenn and Poth; 1999; Michalski et al., 2004; Riggan et al., 1985, Fenn et
22 al. 2008). Other indicators of excess N in the ecosystem include lowered litter C:N and elevated emissions
23 of NO and N2O from the soil (see 3.3.4.2, which have been observed at the more polluted sites in the San
24 Bernardino Mountains (Fenn et al. 1996; Fenn & Poth 2001; Fenn et al. 2008). Lichen communities in the
25 San Bernardino Mountains have also been dramatically changed by the disappearance of up to 50% of the
26 species that occurred in the region in the early 1900s, due to N pollution (Fenn et al 2003, (Nash, 1999). A
27 disproportionate number of the locally extinct lichen species are cyanolichens. N deposition has also been
28 tentatively linked to reduction in fine root biomass in ponderosa pine (Pinusponderosa C. Lawson) at
29 three sites (Grulke et al. 1998, Fenn et al. 2008). However, ozone is also believed to contribute to
30 decreased C allocation to fine roots (Grulke et al 1998), and could be a confounding factor (see below).
31 Recently, Fenn et al. 2008 have used the linkages between N deposition and effects described above to
32 calculate empirical and simulated (i.e. DayCent, Simple Mass Balance for N as a nutrient) critical loads
33 for N deposition for California mixed conifer forests.
34 The effects of high N deposition in the forests of San Bernardino Mountains are compounded by
35 the high ozone exposures that have occurred throughout the past 65 years. For example, from west to east,
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1 O3 concentrations were high at Camp Paivika (80 ppb/hr, averaged over 24 hr, from April 15 through
2 October 15, from 1993 through 1995; Grulke et al., 1998), moderately high (72 to 74 ppb/hr) 5 km further
3 east near Rim Forest, and moderate (62-64 ppb/hr) 45 km east of Camp Paivika at Barton Flats. Both O3
4 exposure and N deposition reduce foliar retention (Grulke and Balduman, 1999) and alter tissue chemistry
5 of both needles and litter (Poth and Fenn, 1998). In addition, confounding factors such as drought and fire
6 suppression add to the complexity of ecosystem response (Arbaugh et al., 2003; Minnich et al., 1995;
7 Takemoto et al., 2001). Extensive crown injury measurements have also been made, linking ambient O3
8 exposure data to chlorotic mottle and needle retention (Arbaugh et al., 1998). Ozone exposure and N
9 deposition reduce carbon allocation to stems and roots (Grulke et al., 1998a, 2001), further predisposing
10 trees to drought stress, windthrow, root diseases, and insect infestation (Takemoto et al., 2001). Recently,
11 Grulke et al. 2008 reported that various lines of phenomenological and experimental evidence indicate
12 that N deposition and ozone pollution contribute to the susceptibility of forests to wildfire in the San
13 Bernardino Mountains by increasing stress due to drought, weakening trees, and predisposing them to
14 bark beetle infestation. Figure 3-5 5 shows the multiple factors contributing to susceptibility to wildfires in
15 the San Bernardino Mountains.
Rapid population increase.
Change in land use
Fire suppression,
Reduced
Increased Os & N
/ X
Increased tree
Kdensifi cation
Direct mortality
Increased tree
susceptibility to
drought stress
J
Increased litter .4-
\
Increased success
of bark beetle,
Increased susceptibility
to fire
Increased fire starts.
Continued fire suppression
= WILDFIRE
Source: Grulke et al. (2008)
Figure 3-55. Diagram of multiple factors contributing to forest susceptibility to wildfire.
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3.3.9. Ecosystem Services
1 This evidence reviewed in this ISA supports that Nr deposition affects ecosystem services in the
2 following categories (defined by Hassan et al. 2005)(Hassan, 2005):
3 • Supporting: nutrient cycling, biodiversity
4 • Provisioning: forest yields, fishing yields in estuaries
5 • Regulating: climate (e.g. C sequestration, N2O emission, CH4 flux), water quality, fire
6 frequency and intensity
7 • Cultural: swimming, boating, biodiversity
8 At this time, no peer-reviewed publication has focused on the ecosystem services affected by N
9 deposition. However, some valuation studies have addressed the effects of N enrichment from multiple
10 sources (see Annex F). In general, both ecosystem structure and function play essential roles in providing
11 goods and services (Daily, 1997). Ecosystem processes provide diverse benefits including absorption and
12 breakdown of pollutants, cycling of nutrients, binding of soil, degradation of organic waste, maintenance
13 of a balance of gases in the air, regulation of radiation balance and climate, and fixation of solar energy
14 (Westman, 1977; Daily, 1997; World Resources Institute, 2000). These ecological benefits, in turn,
15 provide economic benefits and values to society (Costanza et al., 1997; Pimentel et al., 1997). Goods such
16 as food crops, timber, livestock, fish, and drinking water have market value that can be easily quantified.
17 The values of ecosystem services such as flood-control, wildlife habitat, cycling of nutrients, and removal
18 of air pollutants are more difficult to measure (Goulder and Kennedy, 1997).
19 Particular concern has developed within the past decade regarding the consequences of decreasing
20 biological diversity (Hooper and Vitousek, 1997; Chapin et al., 1998; Ayensu et al., 1999; Wall, 1999;
21 Tilman, 2000). Human activities that decrease biodiversity also alter the complexity and stability of
22 ecosystems, and change ecological processes. In response, ecosystem structure, composition and function
23 can be affected (Table 3-27) (Pimm, 1984; Tilman and Downing, 1994; Tilman, 1996; Chapin et al., 1998;
24 Levlin, 1998; Peterson et al., 1998; Daily, 1999; Wall, 1999). Biodiversity is an important consideration at
25 all levels of biological organization, including species, individuals, populations, and ecosystems. Human-
26 induced changes in biotic diversity and alterations in the structure and functioning of ecosystems are the
27 two most dramatic ecological trends of the past century (Vitousek, 1997; EPA, 2004), and the deposition
28 of nutrient N from the atmosphere contributes to both.
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Table 3-27. Primary Goods and Services Provided by Ecosystems
Ecosystem
Goods
Services
Coastal Ecosystems Fish and shellfish
Fish meat (animal feed)
Seaweeds (for food and industrial use)
Salt
Genetic resources
Forest Ecosystems Timber
Fuel wood
Drinking and irrigation water
Fodder
Non timber products (vines, bamboos, leaves, etc.)
Food (honey, mushrooms, fruit, and other edible plants;
game)
Genetic resources
Freshwater Drinking and irrigation water
Fish
Hydroelectricity
Genetic resources
Grassland Livestock (food, game, hides, and fiber)
Ecosystems Drinking and irrigation water
Genetic resources
Moderate storm impacts (mangroves, barrier islands)
Provide habitat and breeding areas/hatcheries/nurseries for wildlife (marine and terrestrial)
Maintain biodiversity
Dilute and treat wastes
Provide harbors and transportations routes
Provide human and wildlife habitat
Provide employment
Contribute aesthetic beauty and provide recreations
Remove air pollutants, emit 02
Cycle nutrients
Maintain array of watershed functions (infiltration, purification, flow control, soil stabilization)
Maintain biodiversity
Sequester atmospheric carbon
Moderate weather extremes and impacts
Generate soil
Provide employment
Provide human and wildlife habitat
Contribute aesthetic beauty and provide recreation
Buffer water flow (control timing and volume)
Dilute and carry away wastes
Cycle nutrients
Maintain biodiversity
Provide aquatic habitat
Provide transportation corridor
Provide employment
Contribute aesthetic beauty and provide recreation
Maintain array of watershed functions (infiltration, purification, flow control, and soil
stabilization)
Cycle nutrients
Remove air pollutants and emit Cte
Maintain biodiversity
Generate soil
Sequester atmospheric carbon
Provide human and wildlife habitat
Provide employment
Contribute aesthetic beauty and provide recreations
Source: World Resources Institute (2000).
3.4. Other welfare effects
1 This section includes the non-acidification effects of sulfur and direct phytotoxic effects of gas-
2 phase NOX and SOX on vegetation. Materials and structures damage caused by NOX and SOX is addressed
3 in Annex E.
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3.4.1. Non-acidification Effects of Sulfur
1 As discussed in Section 3.2, a number of environmental effects are associated with S deposition, in
2 particular soil and water acidification. However, S deposition also contributes to nutrient enrichment,
3 toxicity, and has secondary effects on the cycling and bioavailability of Hg, a highly neurotoxic
4 contaminant. High concentrations of SO2 can harm vegetation by causing foliar injury, decreasing plant
5 growth, and eliminating sensitive plant species, although atmospheric concentrations of SO2 are seldom
6 high enough to cause these effects on vegetation at ambient air pollution levels in the U.S. The
7 biogeochemical cycling of S is closely linked with the cycling of other important elements, including C,
8 N, P, Al, and Hg. Therefore, S deposition can influence the cycling of these elements in ways that
9 influence nutrient availability or contaminant toxicity. In particular, current research suggests that S
10 deposition influences the cycling of Hg in transitional and aquatic ecosystems by stimulating
11 SO42~-reducing bacteria, which are responsible for the bulk of Hg methylation, a key process that
12 increases the bioavailability of Hg.
3.4.1.1. Biological Role of Sulfur
Effects on Plants
13 S is an essential plant nutrient. Low dosages of S serve as a fertilizer, particularly for plants
14 growing in S-deficient soil (Hogan, 1998). A certain level of foliar SO42ls necessary for adequate plant S
15 nutrition (Johnson, 1998; Marschner, 1995, and S deficiency has been shown to occur at foliar SC>42
16 levels below 80 (ig/g in Pinus radiata (Turner, 1980). Nevertheless, the annual increment of S in
17 vegetation is usually small compared to atmospheric deposition and leaching fluxes. Plants require similar
18 levels of S and P, but S is generally available in much higher concentrations in soil. Storage of S in
19 vegetation is of minor significance in the retention or loss of S in most forests (Mitchell, 1992; Johnson,
20 1998).
21 Atmospheric deposition is an important component of the S cycle. This is true not only in polluted
22 areas where atmospheric deposition is very high, but also in areas of low S deposition. Biochemical
23 relationships between S and N are involved in plant protein synthesis and metabolism. S deficiency
24 reduces NO3 reductase and glutamine synthetase activity. N uptake in forests, therefore, could be loosely
25 regulated by S availability, but SC>42 additions in excess of needs do not necessarily lead to injury
26 (Turner, 1980; Hogan, 1998). Current levels of S deposition throughout much of the United States exceed
27 the capacity of most plant communities to immobilize the deposited S (Johnson, 1984; Lindberg, 1992). S
28 excesses associated with acidic deposition have been found (Shriner, 1978; Meiwes, 1981); Johnson et al.,
29 1982
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1 S deficiency in forest soil is rare, but has been reported in remote areas that receive very low levels
2 of atmospheric S deposition and that have inherently low S levels in soil (Kelly, 1972) (Turner, 1990;
3 Turner, 1977; Turner, 1990) Schnug, 1997). In such cases, atmospheric S deposition might be taken up by
4 vegetation, with little SO42 leaching. Within areas of the U.S. influenced by acidic deposition, this is not
5 expected to be a common phenomenon. To some extent, plant uptake of S is determined by the
6 availability of N. This is because most S in plant tissue is in protein form, with a specific S:N ratio
7 (Turner, 1990; Turner, 1977; Turner, 1990; Johnson, 1982)
8 Sulfur plays a critical role in agriculture, and is an essential component of fertilizers (Ceccotti,
9 1997). It is particularly important for plants growing in S-deficient soil (Hogan, 1998). The most
10 important source of S to vegetation is SO42 , which is taken up from the soil by plant roots (Marschner,
11 1995). There are few field demonstrations of foliar SO42 uptake (Krupa, 1986; Krupa, 1999; EPA, 2004).
12 Rather, SO42 in throughfall is often enriched above levels in precipitation. The relative importance of the
13 contribution of foliar leachate versus prior dry-deposited SO42 particles to this enrichment is difficult to
14 quantify (Cape, 1992). The major factor controlling the movement of S from the soil into vegetation is the
15 rate of release through microbial decomposition of S from organic to inorganic forms (May, 1972)EPA,
16 1982, 1993; Marschner, 1995).
17 Sulfur deposition can also have direct effects on plants via nutrient enrichment pathways. Sulfur is
18 an essential nutrient for protein synthesis in plants. Adequate S supply for sustaining plant health is 0.01%
19 to 0.05% in soils (Nriagu, 1978). SO42 is the dominant form of bioavailable S in soils. Plants can also
20 utilize volatile S compounds such as SO2 in the atmosphere to fulfill nutrient requirements (Rennenberg,
21 1984). This S is directly available for diffusive uptake through the leaf surface to support plant growth
22 (Jager, 1980, and can also become bioavailable in the soil for plant root uptake (Moss, 1978). However,
23 excess S inputs via atmospheric deposition can be toxic to plants and result in delayed flowering, reduced
24 growth, and mortality (Smith, 1981; Rennenberg, 1984; Roelofs, 1991) ; Smolders and Roelofs, 1996).
25 Plants that have exhibited reduced growth due to S toxicity have also been observed to have reduced
26 molybdenum (Mo) uptake and increased copper (Cu), manganese (Mn), and zinc (Zn) uptake (Gupta and
27 Munro, 1969; Gupta and Mehla, 1980). The threshold level of S toxicity is variable among species (Mudd
28 and Kozlowski, 1975).
29 Koch et al. (1990) found that hypoxia and high levels of sulfide (>1 mM) limited wetland plant
30 growth by inhibiting nutrient uptake. Sulfide toxicity to plants (e.g., Carex spp. Juncus acutiflorus,
31 Galium palustre, Gramineae) has also been observed in wetland mesocosm experimentally enriched with
32 SO42 (Lamers et al., 1998). Biomass regrowth was significantly reduced for these species for both 2 and
33 4 mmol/L SO42 treatments (Lamers et al., 1998). Van der Welle (2007) also showed that increased SO42
34 loading had negative effects on aquatic macrophytes (Stratiotes aloides and Elodea nuttallii), via sulfide
35 toxicity. Though S. aloides was native to the study region (The Netherlands) of Van der Welle et al.
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1 (2007), it is considered a noxious invasive plant in the U.S. However, E. nuttallii is native to the U.S.,
2 widely distributed across 33 states, and is considered threatened in Kentucky and a species of concern in
3 Tennessee (http://plants .usda.gov/). Negative impacts from elevated rates of atmospherically deposited
4 SO42 on this species could be of concern. It is important to note, however, that the SO42 concentrations
5 reported in these studies were much higher than would generally be expected to occur in regions of the
6 U.S. exposed to elevated atmospheric S deposition.
7 Iron (Fe) concentrations can influence the level of sulfide toxicity in wetland sediments (Smolders
8 et al., 2001; Lamers et al., 2002). Free sulfide produced through SO42 reduction is able to bind with Fe,
9 forming insoluble Fe sulfide (FeS). If sufficient Fe is present, this complexation can reduce or eliminate
10 sulfide toxicity to plants by removing the free sulfide from solution. Van der Welle et al. (2007) confirmed
11 the role of Fe in buffering against sulfide toxicity to plants by observing no toxic effects when sufficient
12 Fe was available to precipitate free sulfide.
13 However, the formation of FeS can disrupt, or compete with, Fe phosphate (FePO4) complexation,
14 resulting in P release and potential undesirable eutrophication effects on downstream receiving waters
15 (Caraco et al., 1989; Smolders et al., 2003). Iron(III) hydroxides and iron(III) phosphates are reduced in
16 anaerobic soils and highly insoluble FeS is formed, increasing phosphate (PO43 ) mobility and
17 bioavailability in surface waters (Smolders et al., 2006). This process has been termed "internal
18 eutrophication" since P is mobilized from within the system and is not contributed from an external
19 source (Roelofs, 1991). Increased nutrient availability via SO42 -induced P release from wetland
20 sediments can result in changes in aquatic vegetation community composition. Rooted aquatic
21 macrophytes can be out-competed by non-rooting floating species and filamentous algae (Smolders et al.,
22 2003). If Fe is available in high enough concentrations, it can prevent P release from saturated soils with
23 high S loading by providing adequate Fe to bind with sulfide without releasing P (Van Der Welle et al.,
24 2007).
25 The observation that NO3 addition decreases P release in wetland enclosures provides further
26 indication that S-induced P release is related to redox conditions and microbial dynamics in the soil
27 profile (Lucassen et al., 2004). Sufficiently high NO3 concentrations can prevent SO42 reduction, and
28 subsequent interruption of Fe-P binding, by maintaining redox status above that suitable for SO42
29 reduction (Lucassen et al., 2004). In the absence of a sufficient supply of NO3 to act as a redox buffer,
30 SO42 will undergo reduction and potentially trigger the internal eutrophication mechanism described
31 above (Lucassen et al., 2004). It is important to note that the majority of research on the topic of internal
32 eutrophication of has occurred in Dutch peatlands that have historically experienced much larger N
33 loading than those in the U.S., making it difficult to extrapolate these findings to U.S. systems.
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Effects on Methane-producing Microbes
1 Increased atmospheric S deposition and its impacts on microbial community structure can also
2 affect methane (CH4) emissions from saturated soils. Early investigation into the effects of elevated pore
3 water SO42 concentrations on CH4 emissions from wetland soils involved the application of a single
4 large dose of SO42 (Fowler, 1995). Methane production was observed to be suppressed (40% less than
5 the control) three weeks after the addition of SO42 . This was followed by a 4-week recovery period, after
6 which CH4 production had returned to pre-treatment levels. These results led to the hypothesis that large
7 single addition of SO42 , as applied by Fowler (Fowler, 1995), only stimulate SO42~-reducing bacterial
8 (SRB) activity for a short time. Fowler concluded that studies that more closely approximated long-term
9 SO42 loading, as with atmospheric S deposition, were necessary. Dise and Verry (2001) and Gauci et al.
10 (2002) showed that smaller and more numerous SO42 additions sustained CH4 emission suppression in
11 wetland soils. These studies more closely approximated SO42 enrichment associated with acidic
12 deposition. These results provided support to the hypothesis that continuous elevated SO42 deposition, as
13 encountered in areas affected by acidic deposition, contributes to sustained suppression of CH4 emissions
14 from wetland soils.
15 Gauci et al. (2004) considered both methods of SO42 addition (a single large dose versus numerous
16 small doses) in the same experiment. Rates of SO42 addition ranged between 15 and 100 kg S/ha/yrto
17 wetland soils previously exposed to 4 kg S/ha/yr of atmospheric S deposition. They observed that CH4
18 emissions from these wetland soils were almost equally suppressed under each treatment, and that each
19 treatment experienced the same CH4 emission "recovery" as found in the single-dose Fowler et al. (1995)
20 study. The two main conclusions from Gauci et al. (2004) were that 15 kg S/ha/yr is either at or above the
21 rate of S deposition required to achieve maximum CH4 emission suppression, and that a single large dose
22 of S has similar effects on CH4 emission suppression as do numerous smaller doses. The authors observed
23 that CH4 emissions from treated soils recovered to levels that were observed from untreated soils during
24 the period of plant senescence. This led to the hypothesis that SRB will out-compete CH4 producing
25 bacteria under conditions of elevated S deposition and durSing vigorous plant growth when available C
26 substrate is limited, but that root exudates and root degradation during the period of plant senescence
27 provides adequate substrate to sustain both methanogenic and SRB bacteria populations. Although the
28 suppression of CH4 emissions can fluctuate based upon plant growth cycles, elevated S deposition is
29 considered to shift microbial community structure in favor of SRB over methanogenic bacteria, reducing
30 annual CH4 emissions from saturated soils (Granberg, 2001). However, climate change simulations
31 suggest that increased soil temperature may override the suppressive effect that elevated S deposition has
32 on CH4 emissions (Granberg, 2001; Gauci, 2004).
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3.4.1.2. Cycling and Storage of Sulfur
Terrestrial Ecosystems
1 Considerable effort was devoted in the 1980s to the computation of S budgets for watersheds and
2 forest plots, with the objective of evaluating S retention and release. These budgets were subject to
3 complications from fluxes that could not be measured directly, such as dry deposition and weathering, but
4 they generally indicated net S retention at sites south of the line of glaciation — a result attributed to net
5 adsorption of SO42 (Rochelle et al., 1987; Cappellato et al, 1998). During the 1990s, little or no decrease
6 in SC>42 concentration occurred in streams in the Ridge and Blue Ridge physiographic provinces, despite
7 regional decreases in atmospheric deposition of S (Webb et al., 2004), and no evidence of S addition from
8 mine drainage. This lack of response in stream chemistry has been generally attributed to a shift in S
9 equilibrium between the adsorbed and solution phases under conditions of decreased atmospheric inputs
10 of SC>42 . This interpretation is supported by a decrease in concentrations of adsorbed SC>42 from 1982 to
11 1990 in a Piedmont soil in South Carolina that received decreasing levels of S deposition during this
12 period (Markewitz et al., 1998). This same soil also experienced an increase in adsorbed SO42 from 1962
13 to 1972 (Markewitz et al., 1998). The only published S budget more recent than 1992 for an unglaciated
14 site in the U.S. (Castro, 2000) also suggested a net release of SO42 . This upland Maryland watershed
15 released 1.6 times more SO42 than measured in throughfall in 1996-97.
16 Numerous S budgets were compiled in the 1980s for glaciated sites, and results generally indicated
17 that inputs approximately equaled outputs on an annual basis (Rochelle and Church, 1987). The
18 observation of little or no S retention at glaciated sites was attributed to relatively low SO42 adsorption
19 capacity in soils. Balanced S budgets in glaciated regions implied that decreases in atmospheric
20 deposition of S would lead directly to decreases in SO42 leaching. The strong correlation between recent
21 decreases in both atmospheric S deposition and SO42 concentrations in surface waters is widely
22 recognized to be a result of this direct linkage (Stoddard, 2003). Nevertheless, considerable evidence also
23 indicates that S inputs in glaciated ecosystems do not behave conservatively, but instead are cycled in part
24 through microbial and plant biomass (David et al., 1987; Alewell and Gehre, 1999;(Likens, 2002). As a
25 result, large quantities of S are stored in organic forms within the soil. David et al. (1987) found that
26 annual S deposition (wet plus dry) at a site in the central Adirondack region of New York was about 1%
27 of the organic S pool in the soil. Houle et al. (Houle, 2001) estimated that annual S deposition at 11 sites
28 in North America ranged from 1% to 13% of the organic S pool in soil.
29 The S cycle in forest ecosystems can be represented as a series of input, uptake, and output terms
30 (Figure 3-56). Some of the fluxes illustrated in this schematic drawing can be measured in the field,
31 including wet deposition, litterfall, and throughfall. Other fluxes must be calculated or estimated, which
32 involves considerable uncertainty (Johnson, 1998).
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WET DEPOSITION
TRANSLOCATION
DRY DEPOSITION
LITTERFALL
ROOT DEATH
AND DECAY -s^.
FOLIAR LEACHING
—THROUGHFALL
FOREST \ REDUCTION AND
FLOOR J VOLATILIZATION
DECOMPOSITION
MINERALIZATION
SOIL \ ^., ^ . ~
ORGANIC L SOLUBLE'
s r \ so
IMMOBILIZATION
SOIL
MINERAL
S
2' -S
ORGANIC S
INORGANIC S MINUS SO42- -S
Source: Johnson (1984).
Figure 3-56. Representation of the S
cycle in forest ecosystems.
1 Perhaps the most important uncertainty concerns the amount of dry deposition, which can be substantial
2 (Lindberg, 1990).
3 Atmospheric deposition is an important part of the S cycle, including in areas that are not exposed
4 to appreciable air pollution levels. In fact, although agricultural S and geologic S (especially associated
5 with mining activities) can be locally important or dominant, atmospheric S inputs may constitute the
6 major source of S input to many terrestrial ecosystems (Probert, 1983; Johnson, 1998).
7 Much of the organic S stored in soil is in C-bonded forms that are relatively unreactive, but can be
8 oxidized by bacteria or mineralized to SC>42 under oxic conditions, which are typically found in
9 moderately well drained to well drained soils (Johnson, 1998). Carbon-bonded S in forest soils can be
10 found in a variety of organic S compounds, including amino acids, sulfolipids, and sulfonic acids.
11 Carbon-bonded S can also be found in humic material in the form of aliphatic and aromatic structures
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1 (Likens, 2002). Furthermore, strong correlations have been shown between levels of atmospheric
2 deposition of S and concentrations of S in soil (Driscoll et al., 2001; Novak et al., 2005). Long-term
3 increases in concentrations of total S in soils that are at least partially attributable to increases in organic S
4 have also been documented (Knights, 2000; Lapenis, 2004), although the study of Houle et al. (Houle,
5 2001) did not find a relation between these factors. A Swedish "clean roof study also provides some
6 insight into the role of organic S in possibly delaying chemical recovery from acidification due to S
7 deposition (Morth, 2005). After 9 years of application of pre-industrial levels of S deposition, the amount
8 of SO42 in runoff still exceeded inputs by 30%. Most of the S in runoff was attributed to mineralization
9 of organic S in the O horizon.
10 Thus, research on the effects of atmospheric S deposition on soils has indicated pronounced
11 changes in soils from sustained SO42 leaching, and accumulation of S through physical/chemical
12 adsorption and biological assimilation. The recent evidence of net loss of S from soils at a number of sites
13 is likely a response to decreased atmospheric inputs. The gradual loss of previously accumulated S
14 contributes to continued SO42 leaching. Uncertainties in estimates of ecosystem fluxes such as
15 weathering and dry deposition, and complications in discerning the effects of desorption from
16 mineralization make it difficult to predict when S outputs will no longer exceed inputs as levels of S
17 deposition continue to decline. Research based on experimental reduction of S inputs suggests that this
18 process will occur on a decadal time scale (Martinson, 2005; Morth, 2005). The long-term role of C-
19 bonded S adds further uncertainty because enhancement of S mineralization by a warming climate could
20 also affect S retention and release (Knights, 2000)Driscoll et al., 2001). This process can be microbially
21 catalyzed, and bacteria are generally more active at higher temperature.
Transitional Ecosystems
22 Transitional ecosystems exert important controls on watershed S budgets, especially in watersheds
23 that contain extensive wetland development. Sulfur storage in wetland soils provides an important
24 buffering system that restricts chronic SO42 leaching to surface waters. Input-output studies of bogs in
25 Massachusetts (Hemond, 1980), Ontario (Urban and Bayley, 1986), and Minnesota (Urban and
26 Eisenreich, 1988) suggested more than 50% retention of atmospheric S inputs. However, oxidation of S
27 that was previously stored in wetland soils can provide an important episodic source of SO42 to
28 downstream surface waters. Thus, the presence of wetlands in a watershed can either temporarily increase
29 or decrease the flux of SO42 to surface waters, and these differences are largely determined by changes in
30 hydrology and redox conditions in wetland soils. Overall, wetlands act as sinks for S because of microbial
31 SO42 reduction and sequestering of reduced S as sulfide minerals and organic S.
32 Changes in S flux that are controlled by processes in transitional ecosystems can have important
33 effects on surface water chemistry. For example, reduction of SO42 in sediments by assimilatory and
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1 dissimilatory processes is an important source of acid neutralizing capacity (ANC) to lakes having long
2 hydraulic residence time, and a likely source also to beaver ponds and wetlands. In-lake ANC production
3 is mostly due to S retention from microbial SO42 reduction (Schindler, 1986; Brezonik et al., 1987;
4 Turner, 1990). It is unlikely, however, that the changes in S flux caused by wetlands and ponds in a
5 watershed would be large enough to have any direct non-acidification effects on biota. More likely, the
6 major non-acidification effects of wetland influence on S cycling relate to changes in Hg methylation in
7 wetland soils. This is discussed in Section 3.4.1.4. Other changes can also occur, including enhanced
8 release of N and P from wetland soils.
9 Some of the organic S in wetlands can be converted to reduced S gasses, including dimethylsulfide
10 and hydrogen sulfide (under acidic conditions), and released to the atmosphere. Up to 30% of the
11 atmospheric deposition of S in remote areas may be derived from release of reduced S gasses from
12 wetlands (Nriagu, 1987). Thus, wetland processes can have important effects on local atmospheric S
13 deposition and trace gas emissions.
Aquatic Ecosystems
14 In aquatic ecosystems that are sensitive to acidification from atmospheric S deposition, SO42 is
15 generally highly mobile within the ecosystem. Acid-sensitive streams tend to be relatively fast-flowing,
16 high-gradient, low-order streams that exhibit high SO42 mobility. Acid sensitive lakes tend to be
17 relatively small, headwater lakes with short hydraulic residence times (weeks to months). In such streams
18 and lakes, most of the SO42 contributed by inflowing ground and surface waters is directly flushed
19 through the ecosystem and emerges as outflow.
20 However, larger streams, streams that flow through series of ponds (i.e., beaver ponds) or lakes,
21 and especially larger lakes, tend to have longer hydraulic residence, and provide opportunity for microbial
22 S reduction in sediments. This S reduction can have important effects on the concentration of SO42 in
23 drainage water, and results in the generation of ANC. The importance of sediment reactions to the acid-
24 base chemistry of surface water depends mainly on the flux rate of material across the sediment-water
25 interface and the amount of time that water remains in contact with the sediment (Kelly, 1987) Baker and
26 Brezonik, 1988; Turner, 1990). In some lakes having long water residence times, about half of the input
27 SO42 is retained in lake sediments (Kelly, 1987; Baker and Brezonik, 1988).
28 Sulfur is an essential nutrient for algae and planktonic bacteria. Nevertheless, S concentration in
29 most lakes is well above the limiting concentration for algal productivity, and therefore biotic S uptake in
30 the water column is not a quantitatively important part of the S cycle in acid-sensitive lakes (Turner,
31 1990).
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3.4.1.3. Export of Sulfur
Terrestrial Ecosystems
1 In order for atmospherically deposited S to exert influence on drainage water, with the range of
2 associated environmental effects that can occur, it must be exported as SO42 from the soil. If the
3 incoming S in atmospheric deposition is retained in the vegetation or soil compartments, it will not be
4 available to affect soil water or surface water downstream within the watershed. In areas of S deposition,
5 almost all deposited S moves into the soil and can then be exported from the terrestrial ecosystem or
6 adsorbed on soil. In most parts of the U.S., most deposited S is exported in drainage water. In much of the
7 southeastern U.S., however, S adsorption on soil substantially limits S export (See discussion in
8 Annex B).
Transitional Ecosystems
9 When saturated, wetland soils act as sinks for incoming S via SO42 reduction. Sulfide is produced
10 through this process and sequestered in anoxic wetland sediments (Mitsch and Gosselink, 2000).
11 However, it has been observed that wetlands can act as sources of SO42 to downstream drainage waters
12 during storm events that follow prolonged periods of drought (Dillon and LaZerte, 1992; Devito and Hill,
13 1999; Eimers, 2002; Jeffries et al., 2002; Laudon et al, 2004; Mitchell, 2006). The mechanism has been
14 described as follows. SO42 is produced through oxidative processes in wetland sediments when they are
15 exposed to atmospheric O2 as the water Table falls during periods of drought. This newly formed SO42 is
16 mobile, and therefore can be flushed from the wetland into streams or lakes when the water table rises as
17 more typical hydrologic conditions resume. This flush of SO42 can result in episodic acidification of
18 downstream surface waters (Laudon et al., 2004) and potentially prolong the chemical recovery of surface
19 water ANC as S deposition declines (Aherne et al., 2006).
20 Much of the supporting research on this topic has been performed within the boreal watersheds of
21 Ontario, Canada (Dillon and LaZerte, 1992; Devito and Hill, 1997; Jeffries et al., 2002; Aherne et al.,
22 2004; Laudon et al., 2004). A Sphagnum-conifer wetland within the Plastic Lake watershed in Ontario
23 was determined to be a source of SO42 to downstream drainage waters after extended periods of
24 summertime drought (Dillon and LaZerte, 1992). Comparisons of stream water chemistry were made
25 between the wetland inlet and the wetland outlet, which drains a watershed consisting entirely of upland
26 soils. The results showed little difference between SO42 concentrations in the wetland inlet and outlet
27 during typical hydrologic conditions. However, SO42 concentrations in the outlet increased by up to a
28 factor of five during storm events that followed extended periods of drought. This occurred during 4
29 separate years.
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1 The majority of the study watersheds in the Plastic Lake region of Ontario, Canada have
2 consistently exported more SO42 than was atmospherically deposited on an annual basis over an 18-year
3 period (Eimers, 2002). This observation suggests either the existence of an internal watershed SO42
4 source, or an underestimation of S deposition. It is possible that dry deposition is underestimated (Likens
5 et al., 1990; Edwards et al., 1999), but a variety of potential watershed sources of additional S have also
6 been proposed in areas that are sensitive to atmospheric S deposition, including:
7 • weathering of S-containing minerals (Baron, 1995)
8 • desorption of SO42 previously adsorbed to soils when S deposition was higher (Driscoll et al.,
9 1995; Mitchell, 1996)
10 • mineralization of S previously incorporated into organic matter (Driscoll et al., 1998)
11 • drought-related oxidation and release of S stored in wetlands and riparian soils (Dillon and
12 LaZerte, 1992; Dillon et al., 1997)
13 Underestimation of dry deposition was not considered to be a significant issue for the Canadian
14 study watersheds (Eimers, 2002). Furthermore, mineral weathering is not considered a significant source
15 of SO42 in that region, due to the low S content of the bedrock (Neary et al., 1987). Reoxidation and
16 mobilization of S stored in wetland sediments was considered the most likely explanation for the
17 observed higher SO42 outputs for those watersheds that contain a significant proportion of wetland. Other
18 mechanisms, including increased soil SO42 desorption and/or increased S mineralization in response to
19 decreased S deposition inputs, may explain the SO42 input/output imbalance observed in watersheds
20 containing little or no wetland area (Alewell and Gehre, 1999; Eimers, 2002). Jeffries et al. (1995, 2002)
21 determined that within the Turkey Lakes watershed in western Ontario wetland, reoxidation and SO42
22 remobilization mechanism can delay lake acidification recovery by as much as 6 years.
23 Wetland S transformations have been incorporated into state-of-the-science modeling to better
24 describe climate-induced acidification effects on lake water chemistry (Aherne et al., 2004, 2006). A
25 wetland component to the MAGIC model was developed and tested for its ability to predict observed
26 stream water SO42 fluxes from the Plastic Lake watershed (Aherne et al., 2004). This model was then
27 used to investigate acidification recovery under two different climate scenarios: (1) an "average climate"
28 scenario consisting of long-term (most recent 20 years) monthly precipitation and runoff and (2) a
29 "variable climate" scenario that included sequential repetition of the measured monthly precipitation and
30 runoff for the preceding 20 years. The average climate scenario did not include any significant drought
31 periods, whereas the variable climate scenario included several periods of summer drought.
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1 Model results under the average climate scenario suggested that chemical recovery of lake water
2 would occur, with ANC reaching 40 (ieq/L by 2020 and 50 (ieq/L by 2080. However, the variable climate
3 scenario projected that recovery would be greatly reduced. ANC recovery by 2080 was estimated to only
4 reach 2.6 (ieq/L. The authors acknowledged that reiterating the past 20 years of climate under the variable
5 climate scenario was somewhat arbitrary. Nevertheless, results suggested that climate effects on the
6 cycling of S can modify chemical recovery of lake water from acidification in watersheds that are
7 wetland-influenced.
Aquatic Ecosystems
8 Export of S from surface waters is controlled primarily by retention in sediments through microbial
9 SO42 reduction. In-stream and in-lake biological demand for S is generally a very small component of
10 the S input levels in areas affected by atmospheric S deposition. Sulfur reduction can be an important
11 process regulating S export from aquatic ecosystems, mainly in waters that exhibit long hydraulic
12 retention. Sulfur reduction in lake and pond sediments can also be closely associated with Hg
13 methylation. Therefore, the dynamics of S storage and export can influence the bioavailability of Hg to
14 fish, piscivorous wildlife, and humans who consume large quantities offish.
3.4.1.4. Sulfur and Methylation of Mercury
15 Hg has long been established to be a potent neurological, reproductive, and developmental toxin
16 that accumulates at progressively higher concentrations in higher trophic levels (biomagnification). For
17 the protection of human health, the USEPA set the fish tissue criterion for MeHg at 0.3 ug/g. This has
18 resulted in 2,436 fish consumption advisories for Hg in 2004, 2,682 in 2005 and 3,080 in 2006. Forty-
19 eight states, 1 territory, and 2 tribes have issued mercury advisories. Eighty percent of all advisories have
20 been issued, at least in part, because of mercury. Most of the new Hg advisories issued in 2005 and 2006
21 were in Wisconsin (293), Michigan (46), New York (36) and Minnesota (32). In 2005, American Samoa,
22 Kansas, Oklahoma and Utah started issuing Hg advisories, and Iowa started in 2006. In 2006, a total of
23 14,177,175 lake acres and 882,963 river miles were under advisory for mercury. As of July 2007, 23
24 states have issued statewide advisories for mercury in freshwater lakes and/or rivers.
25 The biogeochemical cycle of Hg is closely tied to that of sulfur (S), and the presence of SO42 in
26 wetlands and lake sediments is essential for entry of Hg into the food web. Hg is taken up by living
27 organisms, and bioaccumulates, in the methylmercury (MeHg) form. SRB are the main agent of Hg
28 methylation in the environment, and changes in SC>42 deposition have been shown to result in
29 commensurate changes in both Hg methylation, and Hg levels in fish.
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Effects of Mercury in Aquatic Biota
1 Adverse effects of Hg, including behavioral, reproductive, neurochemical, and hormonal effects,
2 have been demonstrated in piscivorous mammals and birds (USEPA, 1996; Scheuhammer et al., 2007),
3 and MeHg has been shown to be the form in which Hg accumulates in tissue offish and piscivorous
4 species (Bloom, 1992; Becker and Bigham, 1995; Harris et al., 2003; Scheuhammer et al., 2007).
5 Exposure offish and wildlife to Hg occurs primarily through the diet. Top predatory, especially
6 piscivorous, animals feeding on aquatic food chains are at greatest risk for Hg accumulation and toxicity
7 (Scheuhammer et al., 2007). Wildlife living in inland lake habitats tends to accumulate higher tissue
8 concentrations of Hg than those living in coastal habitats (Frederick et al., 2002; Evers et al., 2005).
9 Available data suggest that numerous wild populations offish, birds, and mammals experience
10 MeHg exposures that are high enough to cause substantial reproductive, behavioral or health impairment.
11 Reproduction is the component of response that appears to be most affected (Scheuhammer et al., 2007).
12 In fish, exposure to MeHg can affect growth, reproductive ability, morphological characteristics, and
13 feeding efficiency. Examples of studies documenting the effects of MeHg on fish include Friedmann et al.
14 (1996), who investigated the effects of low-level (0.137 (ig Hg/g) and high-level (0.987 (ig Hg/g) dietary
15 Hg concentrations (as MeHg) on hatchery juvenile walleye (Stizostedion vitreum). These experimental Hg
16 exposures were chosen to reflect dietary Hg concentrations commonly encountered in North American
17 lakes and streams. Results showed impaired fish growth and impaired gonad development in males. Fjeld
18 et al. (1998) exposed grayling (Thymallus thymallus) embryos to varying concentrations of MeHg (0.16,
19 0.8, 4.0, and 20 (ig Hg/L) during their first 10 days of development. This exposure resulted in body tissue
20 MeHg concentrations of 0.09, 0.27, 0.63, and 3.80 (ig Hg/g respectively. Morphological deformities were
21 observed in fish exposed to the highest level of MeHg. Samson and Shenker (2000) also observed
22 morphological disturbance in zebrafish (Danio rerio) at embryonic MeHg exposure levels of 20 and
23 30 (ig CH3HgCl/L. Other fish such as mummichog (Fundulus heteroditus) and rainbow trout
24 (Oncorhynchus mykiss) have also been observed to suffer teratogenic effects such as cyclopia, tail
25 flexures, cardiac malformations, jaw deformities, twinning, and axial coiling from embryonic MeHg
26 exposure (Samson and Shenker, 2000). Fish survival and subsequent population status can be jeopardized
27 as a result of exposure to MeHg. Fathead minnows (Pimephales promelas) showed impaired feeding
28 efficiency after exposure to both 6.79 and 13.57 (ig HgCVL (Grippo and Heath, 2003). Reduced feeding
29 efficiency and competitive ability was also observed in grayling exposed to 0.8 to 20 (ig Hg/L as embryos
30 (Fjeld etal., 1998).
Role of Sulfur in the Biogeochemical Cycle of Mercury
31 The global cycle of Hg has atmospheric, aquatic, edaphic, and biotic components. In the
32 atmosphere, Hg is transported locally, regionally, and globally, depending on speciation. Both elemental
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1 and oxidized forms are found in soil and aquatic environments, but the oxidized form is more prevalent.
2 MeHg is the form that is found in tissues (Figure 3-57). SRB are the main agent of Hg methylation in the
3 environment. Although Hg methylation in watersheds has been shown to occur through other processes,
4 their contribution to MeHg loads is negligible in comparison to that of SRB-mediated methylation.
5 Addition of SO42 has been demonstrated to stimulate mercury methylation by SRB in studies spanning
6 scales from the culture of isolated bacteria, to the experimental amendment of entire lakes. Those studies
7 have included addition of SO42 at rates corresponding to observed deposition.
Hg-S
complexes ~ reducing
bacteria
Figure 3-57. Simplified cycle of Mercury, showing the role of Sulfur. Arrows are not proportional
with actual rates.
8 SRB are commonly found in anoxic wetland and lake bottom sediments (Compeau, 1985; Gilmour,
9 1991; Gilmour, 1992). Under increased SC>42 availability, their number and activity increase. The
10 mechanisms for Hg methylation, as mediated by SRB, have been discussed by Choi et al. (Choi, 1994),
11 Ekstrom et al. (Ekstrom, 2003), and Ekstrom and Morel (Ekstrom, 2004). Abiotic mechanisms
12 responsible for Hg methylation have been discussed by Weber (Weber, 1993), Hintelmann and Evans
13 (Hintelmann, 1997), and Siciliano et al. (Siciliano, 2005). Studies demonstrating the response of SRB-
14 mediated methylation to SO42 in pure cultures include King et al. (King, 2000), Benoit et al. (2001a), and
15 Benoit et al. (200 Ib). This response has also been established in samples of soil and sediments (Compeau,
16 1985; Gilmour, 1992) Harmon et al., 2004), and in experimental manipulations in wetlands and lakes
17 (Branfireun et al., 1999; Branfireun et al., 2001; Benoit et al., 2003; Frost et al., 1999; Harmon et al.,
18 2004; Jeremiason et al., 2006; Watras, 2006)Wiener et al., 2006).
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1 Evidence regarding the importance of SRB in MeHg production was provided by Compeau and
2 Bartha (Compeau, 1985), and Gilmour et al. (Gilmour, 1992), who showed that MeHg production was
3 substantially reduced with addition of a known SRB inhibitor (Na2MoO4). This is also in agreement with
4 observations of SRB-mediated Hg methylation in salt marsh sediments (Compeau, 1985). The work of
5 Gilmour et al. (Gilmour, 1992) considered anoxic lake bottom sediments, rather than wetland sediments.
6 However, anoxia is also common in freshwater wetland sediments, where SO42 addition has also been
7 observed to enhance Hg methylation (Branfireun, 1999; Harmon, 2004; Jeremiason, 2006). Accumulation
8 of sulfidic forms of S in sediments, also resulting from SRB activity, has been shown to diminish the
9 availability of S to SRBs, and thus net Hg methylation (Gilmour et al., 1998; Benoit et al., 1998; Benoit et
10 al., 2001; Benoit et al., 1999a; Benoit et al., 1999b; King et al., 2001).
11 Gilmour et al. (1992) investigated MeHg production within anoxic sediments of a reservoir located
12 in central Massachusetts. Elevated MeHg production with SO42 addition was measured in both
13 experimental laboratory slurries (Figure 3-58b) (Gilmour, 1992) and intact sediment cores. The
14 background SO42 concentration in the experimental sediment slurries was 60 (ieq/L. SO42 additions of 0,
15 100, 200, and 400 (ieq/L were applied to these samples in the presence of 50 mg/L of Hg as HgC12. The
16 rate of production and the final concentration of MeHg increased in proportion to the initial SO42
17 concentration. Furthermore, SO42 concentrations decreased during the experiment (Figure 3-58a);
18 Gilmour, 1992), suggesting that SO42 reduction had occurred. MeHg production within isolated lake
19 bottom sediment cores was also enhanced across a gradient of SO42 addition (3 to 1040 (imol sodium
20 SO42 [Na2SO4]; Figure 3-59). Sediment MeHg production was most enhanced when SO42 concentration
21 was above about 60 (ieq/L, with increased production from a pre-treatment background MeHg
22 concentration of 0.26 ng/g to approximately 7.0 to 8.5 ng/g. These results suggest maximum MeHg
23 production at SO42 concentrations between about 200 and 400 (ieq/L, although optimal conditions for
24 methylation are likely to vary with other factors that influence SO42 reduction. SO42 concentrations in
25 the range of these experiments (about 60 to 200 (ieq/L) are often found in waters affected by S deposition
26 in the U.S.
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o
to
250 n
150-
100-
50
0
B
0)
I
0)
0)
c
8
6 -
4 -
2 -
Added SO43- |jM
O—O 0
•—• 50
A—A 100
200
i
o
\
5
10
15
Days
I
20
I
25
I
30
I
35
i
o
5
I
10
15
Days
i i
20 25 30 35
Source: Gilmour et al. (Gilmour, 1992).
Figure 3-58. (A) S042~ and (B) methylmercury (MeHg) concentrations as a function of time in
sediment slurries made from Quabbin Reservoir littoral sediments. Each delta point represents the
average value from three separate incubations and the associated standard error.
Interacting factors
1 Many studies have also shown an association between low lake water pH and high Hg
2 concentrations in fish (Grieb et al., 1990; Suns and Hitchin, 1990; Driscoll et al., 1994; Kamman et al.,
3 2004). Hrabik and Watras (Hrabik, 2002) found that decreases in fish Hg concentration in an
4 experimentally de-acidified lake basin exceeded those in the reference lake basin by a factor of two over a
5 6-year period of experimental de-acidification. The association between low pH and high Hg
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1 accumulation in fish suggests a response of methylation to pH, but although SRB activity does respond to
2 pH (Kelly, 2003), quantification of the interactive effects of pH with SO42 in the environment has only
3 been tentative.
4 Other interacting factors, mainly Fe, P, and dissolved organic matter, have been identified, but very
5 incompletely quantified (Munthe et al., 2007; Watras and Morrison, 2008). Driscoll et al. (2007)
6 developed indicators of Hg sensitivity using two stratified, random-probability surveys of northeastern
7 lakes combined with the survey data sets of Chen et al. (2005). This analysis showed that lakes with Hg
8 levels above the EPA criterion of 0.3 (ig/g in yellow perch had significantly higher dissolved OC, and
9 lower pH, ANC, and total P than lakes with fish Hg concentrations below 0.3 (ig/g (Driscoll et al., 2007).
10 Based on the probability surveys, they calculated that about 20% of lakes in the region had total P
11 concentrations above 30 (ig/L and yellow perch Hg concentrations below 0.3 (ig/g. In the remaining 80%
12 of lakes, 75% had yellow perch Hg concentrations exceeding 0.3 (ig/g when surface water dissolved OC
13 levels exceeded 4.0 mg C/L, a pH of less than 6.0, or an ANC of less than 100 (ieq/L. Most Hg in the
14 water column of freshwaters is bound to organic matter, either to dissolved OC or to suspended
15 particulate matter. Therefore, total Hg and MeHg concentrations are often positively correlated with
16 dissolved OC in lake waters (Mierle and Ingram, 1991; Driscoll et al., 1994; EPA, 1996). Dissolved OC,
17 in turn, has an important influence on pH. Thus, several interrelated factors seem to affect Hg loading in
18 tissue. For example, Driscoll et al. (1995) found one or more yellow perch exceeding the 0.5 (ig/g action
19 level in 14 of 16 Adirondack study lakes despite wide ranges in pH (to above 7) and ANC (to above
20 200 (ieq/L) (Mierle, 1990). Driscoll et al. (1994) concluded that the most obvious factor regulating the
21 concentration and availability of both total Hg and MeHg in Adirondack lakes is dissolved OC. They
22 found increased fish Hg concentrations with increasing dissolved OC up to dissolved OC concentrations
23 of about 8 mg/L, followed by lower concentrations in the highly dystrophic Rock Pond (dissolved OC =
24 26 mg/L). They hypothesized that dissolved OC may bind with MeHg at very high dissolved OC
25 concentration, limiting the bioavailability of the Hg. In addition, calculations made by Driscoll et al.
26 (1995) with the Hg Cycling Model suggested that increases in dissolved OC result in increasing
27 concentrations of Hg in biota, but decreases in the bioconcentration factor of Hg in fish tissue. Because
28 the transport of Hg to Adirondack lakes appeared to be linked to dissolved OC production from wetlands
29 within the watersheds of the study lakes, Driscoll et al. (1995) concluded that dissolved OC is important
30 in regulating Hg concentrations in the lakes, and ultimately the supply to fish. In a peatland experiment
31 testing the effects of various sources of organic C, Mitchell et al. (2008) demonstrated that while SO42 is
32 required for methylation of Hg, the addition of some sources of C greatly enhanced the process. The
33 combinations of C and SO42 additions that enhanced methylation in the experiment corresponded to the
34 combinations present in MeHg 'hot spots' within watersheds that include peatlands.
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8 -
6 -
0>
o
c
d)
i
o
4 -
2 -
Artificial
O Natural
I
10
I I I I I
50
MM S043-
100
500
1 '
1000
Figure 3-59. Methylmercury produced in sediment cores incubated two weeks under artificial lake
water containing 3-1040 pM Na2$04. Error bars represent standard error between two replicate
cores. Data from cores incubated under natural water are shown individually. The average MeHg
concentration in unamended Purgee sediments sampled in July was 0.26 ± 0.01 ng/g (n = 2).
1 Several researchers have suggested that the export of Hg from terrestrial watersheds to lakes may
2 be controlled in large part by the nature of watershed soils and the transport of naturally occurring organic
3 acids (Mierle, 1990; Meili, 1991; Mierle and Ingram, 1991; Engstrom et al., 1994). This suggestion is
4 based partly on the fact that dissolved organic matter strongly binds with Hg, and partly on the observed
5 positive correlation between Hg accumulation in lake sediments and the ratio of the watershed area to the
6 lake area in relatively undisturbed watersheds (r2 = 0.91; r2 = 0.91) (Engstrom et al., 1994). Engstrom
7 et al. (1994) concluded that Hg export from the terrestrial watershed to lake water may be explained by
8 factors regulating the export of fulvic and humic matter and by watershed area. They based this
9 conclusion on the close correlation between Hg concentration and humic matter in surface waters, the
10 observation that peak concentrations of both Hg and dissolved organic matter tend to occur during periods
11 of high runoff, and the experimental determination that Hg transport occurs primarily in upper soil
12 horizons.
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Ecosystems Characteristics Conducive to Methylation
1 S deposition is most likely to result in enhanced Hg methylation in regions that receive relatively
2 high levels of atmospheric Hg and S deposition and that exhibit characteristics conducive to methylation.
3 These include low ANC and low pH surface waters, with large upstream or adjoining wetlands
4 (Scheuhammer and Blancher, 1994; Chen et al., 2005; Scheuhammer et al., 2007). Such sensitive
5 ecosystems are prevalent in portions of the northeastern U.S. and southeastern Canada. Studies of Hg
6 concentration in feathers, blood, and eggs of the common loon (Gavia immef) indicate decreasing
7 concentrations from west to east in this region (Evers et al., 1998, 2003). This pattern is in general
8 agreement with patterns of deposition of both Hg and S.
9 Wetland environments have been shown to be significant areas of MeHg production and sources of
10 export to downstream receiving waters (St. Louis et al., 1994). Wetland MeHg production has been
11 measured at rates 26 to 79 times higher than in upland areas of a Canadian boreal forest (wetland: 1.84 to
12 5.55 mg/ha/yr"; upland: 0.07 mg/ha/yr) (St. Louis et al., 1994). Watersheds containing 14.0% to 16.3%
13 wetland yielded 5 to 14 times more MeHg than upland catchments that lacked wetlands (St. Louis et al.,
14 1994). In the same region, St. Louis et al. (1996) found that all watersheds were net sinks for total Hg, but
15 that watersheds containing wetlands regularly exported MeHg (St. Louis et al., 1996). However, MeHg
16 export from these watersheds was not directly proportional to percent wetland coverage, indicating that
17 other variables are also involved in the major processes that regulate MeHg production and export. In
18 particular, the level of atmospheric Hg deposition and the acid-base chemistry of drainage water may be
19 important.
20 Branfireun et al. (1996) measured highest peat and pore water MeHg concentrations in wetland
21 areas that exhibited characteristics of a poor fen environment (i.e., interaction with nutrient-poor ground
22 water). St. Louis et al. (1996) observed that high water yield resulted in high MeHg export. Thus, the
23 proportion of upland to wetland land area within a watershed was not the only control on MeHg export,
24 but wetland type and annual water yield also played important roles (St. Louis et al., 1996).
25 As noted by Munthe et al. (2007), multiple hydrological, chemical, and biological characteristics of
26 watersheds determine the movement of Hg between compartments. With regards to MeHg, however, the
27 chemical and biological characteristics of the lake compartment may be more critical: comparing two
28 remote lakes, one a seepage lake, and the other a drainage lake, Watras and Morrison (2008) found that
29 although wetland MeHg export was the dominant external source of MeHg to the drainage lake, in-lake
30 methylation remained four- to seven-fold greater than loading from the wetland. Likewise, Harris et al.
31 (2007) demonstrated, using traceable stable isotopes of Hg in a whole ecosystem experiment, that nearly
32 all of the increase in fish MeHg came from Hg deposited to the lake surface, with less than 1% of Hg
33 deposited to the watershed being exported to the lake, in any form.
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1 Regardless, methylation of Hg occurs in anoxic sediments that contain a sufficient C source to
2 support SO42~-reducing bacterial activity along with an adequate supply of SO42 for SRB-mediated SO42
3 reduction. These conditions are found in lake and pond bottom sediments (Gilmour, 1992), freshwater
4 wetland sediments (Branfireun et al., 1999; Harmon et al., 2004; Jeremiason et al., 2006), and salt mash
5 sediments (Compeau, 1985). Such wetland systems, expected to exhibit high levels of Hg methylation,
6 can be found throughout the U.S.
7 In a 1998 preliminary national survey of 106 sites from 21 basins across the U.S., Krabbenhoft et
8 al. (1999) examined the relations of total Hg and MeHg in water, sediment and fish, and concluded that
9 wetland density was the single most important factor controlling MeHg production at the basin scale.
10 Four study basins along the east coast of the U.S. had the greatest methylation efficiency, while
11 nationwide, sub-basins characterized as mixed agriculture and forest cover types had the highest
12 methylation efficiency. A recent study of biological Hg hotspots in the northeastern U.S. and southeastern
13 Canada (Evers et al., 2007) analyzed more than 7,300 observations of Hg levels in seven species from
14 three major taxonomic groups to quantify the spatial heterogeneity in tissue Hg concentrations. Using
15 published effect thresholds for Hg tissue concentrations, they identified five known and nine possible
16 biological Hg hotspots. They reported that two of the biological hotspots, located in the Adirondack
17 Mountains of New York and south-central Nova Scotia, occur in areas with relatively low to moderate
18 atmospheric Hg deposition and high landscape sensitivity, as determined by the abundant forest and
19 wetland cover as well as the acidic surface water conditions (Evers et al., 2007). Using data collected by
20 the Northeastern Ecosystem Research Cooperative (NERC) initiative (Evers and Clair, 2005) to examine
21 the link between Hg deposition and biotic Hg, Driscoll et al. (2007) concluded that "forested regions with
22 a prevalence of wetland and unproductive surface waters," which are common in the northeastern US,
23 "promote high concentrations of Hg in freshwater biota." In contrast, in a study of over 600 randomly
24 selected streams and rivers throughout the western U.S., Peterson et al. (2007) found little relationship
25 between fish tissue Hg concentrations and surface water pH, SO42 , or dissolved OC. They attributed the
26 lack of a relationship to the fact that low pH (<7) and high dissolved OC systems were rare in the West.
27 The major factors controlling fish tissue Hg concentrations in western streams and rivers were fish size
28 and feeding group, not water chemistry. Likewise, a 1999 survey of high altitude western lakes with both
29 low Hg and low MeHg (Krabbenhoft et al., 2002) identified high pH and elevated rates of photo-
30 demethylation as the likely causes for low net methylation. Water clarity and high sunlight exposure were
31 cited as sources of enhanced photo degradation of MeHg.
S deposition and MeHg in fish
32 As shown by Harris et al. (2007), the response offish MeHg to changes in Hg deposition can occur
33 on a time scale of less than a year. In their comprehensive synthesis of information on all elements of the
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1 connection between environmental Hg loading, and Hg in fish, Munthe et al. (2007) concluded that
2 several interacting factors are expected to affect the speed and magnitude of the changes in fish
3 contamination that result from changes in Hg loading. As indicated previously, numerous studies have
4 ascertained that SC>42 supply is a principal driver of MeHg production, and Hrabik and Watras (Hrabik,
5 2002) showed that decreased deposition of both Hg and SC>42 are followed by MeHg decrease in fish.
6 Drevnick et al. (Drevnick, 2007), however, were able to establish an explicit linkage between S deposition
7 and fish Hg, by verifying that even in the absence of change in Hg deposition, changes in S deposition
8 alone result in commensurate changes in MeHg accumulation in fish.
3.4.1.5. Summary
9 The most important non-acidification effect of S deposition in areas of the U.S. that receive high
10 levels of S deposition is the influence of S supply on Hg methylation. The extent of methylation governs
11 the bioavailability of Hg to biota. High concentrations of MeHg in fish can constitute an important health
12 concern for people who consume large quantities offish and can affect the health and reproduction of
13 piscivorous wildlife, including the common loon, bald eagle (Haliaeetus leucocephalus), and river otter
14 (Lutra canadensis). Hg methylation occurs mostly in wetland soils and bottom sediments of lakes and
15 ponds. S deposition to these ecosystems can enhance S reduction and Hg methylation processes. Although
16 S can also be directly toxic to terrestrial vegetation, levels of S in ambient air pollution and levels of S
17 deposition commonly found in the U.S. are generally not high enough to cause substantial direct adverse
18 effects on plants.
3.4.1.6. S Nutrient Enrichment Case Study: Interactive Effects of S and Hg in Little
Rock Lake, Wl
19 Little Rock Lake is an 18-ha precipitation-dominated seepage lake located in a forested and
20 undisturbed catchment of northcentral Wisconsin. The extensive experimental work conducted at Little
21 Rock Lake was described by Hrabik and Watras (2002). The research at Little Rock Lake provides
22 considerable insight into the interactions of S and Hg in the lake, and also bioaccumulation of Hg in fish
23 in freshwater ecosystems.
24 In 1984, the lake was divided into two basins by placing an impermeable curtain across a narrow
25 lake section. One of the basins was experimentally acidified from pH 6.1 to 4.7 by mixing H2SO4 into the
26 surface water over a period of 6 years (Watras, 1989). The other basin was left undisturbed to serve as a
27 reference. Beginning in 1990, the treated basin was left to de-acidify naturally.
28 Hg accumulation in yellow perch showed significant declines in fish in both the experimental and
29 reference basins between 1994 and 2000, commensurate with declines in atmospheric deposition of Hg.
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1 Fish Hg concentrations in the experimental basin were 57% higher in 1994 than in 2000, whereas
2 concentrations were 36% higher in the reference basin (Hrabik, 2002). The authors determined that half
3 of the decrease in fish Hg concentration was attributable to lakewater de-acidification and the other half
4 was associated with regional declines in atmospheric Hg deposition. In the reference basin, which had
5 higher pH and exhibited a lower rate of de-acidification, 15% of the decrease in fish Hg concentration
6 was due to de-acidification (Hrabik, 2002).
7 These findings were consistent with the hypothesis that SO42 and newly added Hg synergistically
8 contribute to enhanced bioaccumulation of Hg in fish. In subsequent analyses, Watras et al. (Watras,
9 2006) found that maximum CH3Hg+ concentrations in hypolimnetic waters were directly correlated with
10 the SO42 deficit (mean epilimnetic SO42 concentration - minimum hypolimnetic SO42 concentration)
11 and they observed a correlation between CH3Hg+ and lakewater SO42 concentrations. The tracking of
12 external loads of Hg and S, and internal loads of Hg and CH3Hg+ suggested a tight biogeochemical
13 connection among atmospheric deposition, SO42 reduction, and Hg methylation. However, these
14 relationships did not fully explain the observed large inter-annual variability in CH3Hg+ accumulation.
15 The variability appeared to be influenced by OC, terrestrial runoff and temperature.
16 The results from the Little Rock Lake acidification experiment suggest that S deposition plays an
17 important role in the accumulation and methylation of Hg in freshwater ecosystems, and that acid
18 deposition and Hg deposition have a disproportionately larger effect together than either would have
19 separately (Watras, 2006).
3.4.2. Direct Phytotoxic Effects of Gaseous N and S on Vegetation
20 This section is intended to provide a brief overview of the exposure and phytotoxic effects of
21 gaseous N and S compounds on vegetation. This recognizes that the major focus of this review is the
22 effect of acidifying deposition and N deposition on ecosystems. However, direct effects of gaseous N and
23 S could augment the effects of deposition on vegetation and effects of gaseous N and S may occur in
24 some areas.
25 The effects of gaseous pollutants such as SO2, NO2, NO, HNO3 and O3 on vegetation have been
26 studied since the 1950s and 1960s. Methodologies have been developed to study these effects in the lab,
27 greenhouse, and in the field. The methodologies to study gaseous pollutants effects on vegetation have
28 been recently reviewed in the O3 AQCD (EPA, 2006). A thorough description of the methodologies used
29 to expose vegetation to gaseous pollutants can be found in Section AX9.1 of the O3 AQCD (EPA, 2006)
30 and Section 9.2 in the 1993 NO2 AQCD (EPA, 1993).
31 Uptake of gaseous pollutants in a vascular plant canopy is a complex process involving adsorption
32 to surfaces (leaves, stems, and soil) and absorption into leaves. These pollutants penetrate into leaves
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1 primarily in gaseous form through the stomata, although there is evidence for limited pathways via the
2 cuticle. Pollutants must be transported from the bulk air to the leaf boundary layer in order to get to the
3 stomata. Although the transport of pollutants through a boundary layer into the stomata region is known
4 to be important, and even rate limiting in many cases of low wind velocity, its description has been
5 defined from aeronautical concepts and usually relates to smooth surfaces that are not typical of leaf-
6 surface morphology; however, it is nearly the only treatment available (Gates, 1968). Once through the
7 boundary layer, the gas must enter the leaf through the stomata. The entry of gases into a leaf is dependent
8 upon the physical and chemical processes of gas phase and surfaces as well as the stomatal aperture. The
9 aperture of the stomata is controlled largely by the prevailing environmental conditions, such as humidity,
10 temperature, and light intensity. When the stomata are closed, as occurs under dark or drought conditions,
11 resistance to gas uptake is very high and the plant has a very low degree of susceptibility to injury (Figure
12 3-60). The stomatal control of uptake of gaseous pollutants is described in more detail in AX9.2 of the O3
13 AQCD (EPA, 2006a) and Section 9.3.1.5 of the oxides of N AQCD (EPA, 1993a). It should be noted that
14 unlike higher plants, mosses and lichens do not have a protective cuticle barrier to gaseous pollutants, a
15 major reason for their sensitivity to gaseous S and N.
3.4.2.1. Direct Phytotoxic Effects of S02 on Vegetation
16 It has been known since the early 1900s that exposure of plants to SO2 can cause damage and death
17 (Wislicenus, 1914). The large sources of SO2 were ore smelters. Sulfides in the ore were oxidized during
18 smelting and resulted in large releases of SO2. Emissions from large ore smelters in the U.S. and Canada
19 resulted in large areas denuded of vegetation surrounding these facilities (Swain 1949; Thomas 1951).
20 Much of the damage to the vegetation was due to acute effects of high concentrations of SO2. However,
21 as early as 1923 researchers recognized that SO2 might reduce plant growth without acute symptoms of
22 foliar injury (Stoklasa, 1923). In the 1950s through the early 1980s, there was much research on the
23 effects of lower levels of SO2 as well as the interaction with other pollutants such as Oj, and NO2. Since
24 then, there has been much less research on the effects of SO2 on vegetation, especially in the U.S., due to
25 the decreasing ambient concentrations of SO2. The effects of SO2 on vegetation are summarized below.
26 Currently, SO2 is the only criteria pollutant with a secondary NAAQS distinct from the primary
27 standard. This standard is to protect acute foliar injury resulting from SO2 exposure. The standard is a 3-h
28 average of 0.50 ppm and was promulgated in 1970 to protect against acute foliar injury in vegetation. The
29 last AQCD for ecological effects of SOX was completed in 1982 and concluded that controlled
30 experiments and field observations supported retaining this secondary standard (EPA, 1982a,b).
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Light
03, NOX, SOX
Cuticle
Epidermis
Pallisade
Mesophyll
Spongy
Mesophyll
Epidermis
Cuticle1
C0=[C02]--"
Guard Cell
03, NOX, SOX
Vascular
System
Figure 3-60. The microarchitecture of a dicot leaf. While details among species vary, the general
overview remains the same. Light that drives photosynthesis generally falls upon the upper (adaxial
leaf surface. C02, SOx, NOx, and Os gases generally enter through the stomata on the lower
(abaxial) leaf surface, while water vapor exits through the stomata (transpiration).
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Acute foliar injury usually happens with hours of exposure, involves a rapid absorption of a toxic
dose and involves collapse or necrosis of plant tissues. Another type of visible injury is termed chronic
injury and is usually a result of variable SO2 exposures over the growing season. After entering the leaf,
SO2 is converted to sulfite and bisulfite, which may be oxidized to SO42 . SO42 is about 30 times less
toxic than sulfite and bisulfite. The conversion of sulfite and bisulfite to SO42 results in net fT production
in the cells. Kropff (1991) proposed that the appearance of SO2-induced leaf injury was likely due to a
disturbance of intracellular pH regulation. Kropff (1991) pointed out several studies that the pH of
homogenates only shifted towards greater acidity when plants were lethally damaged from long-term SO2
exposures (Grill 1971; Jager and Klein, 1977; Thomas et al., 1944). The appearance of foliar injury can
vary significantly between species and growth conditions affecting stomatal conductance. Currently there
is not regular monitoring for SO2 foliar injury effects in the U.S.
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, the effects of foliar injury vary among species and growing
environment. The 1982 SO2 AQCD summarized the concentration-response information available at the
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1 time (EPA, 1982a). Effects on growth and yield of vegetation were associated with increased SO2
2 exposure concentration and time of exposure. However, that document concluded that more definitive
3 concentration-response studies were needed before useable exposure metrics could be identified. Because
4 of falling ambient SC>2 concentrations and focus on 03 vegetation effects research, few studies have
5 emerged to better inform a metric and levels of concern for effects of SC>2 on growth and productivity of
6 vegetation.
7 Since the 1982 SC>2 AQCD was published, several studies have investigated a number of different
8 effects of SC>2 effects on plants. Most recent research has been performed in areas of Europe where
9 ambient SC>2 concentrations are generally higher than in the U.S. A brief summary of some of the major
10 studies are presented in Table 3-28.
11 SO2 is considered to be the primary factor causing the death of lichens in many urban and industrial
12 areas, with fruticose lichens being more susceptible to SO2 than many foliose and crustose species
13 (Hutchinson et al., 1996). Damage caused to lichens in response to SO2 exposure includes reduced
14 photosynthesis and respiration, damage to the algal component of the lichen, leakage of electrolytes,
15 inhibition of N fixation, reduced K+ absorption, and structural changes (Farmer et al., 1992; Belnap et al.,
16 1993; Hutchinson et al., 1996). Significant reductions in lichen photosynthesis have been measured at
17 concentrations as low as 91 ppb over 2-4 hours (Huebert et al., 1985, Sanz et al. 1992). Damage to the
18 algal component of the thallus is evidenced by its discoloration. The entire thallus dies soon after algal
19 cells are damaged (Hutchison et al., 1996). At higher levels, SC>2 deactivates enzymes by chemical
20 modification leading to reduced metabolic activity and loss of membrane integrity (Zeigler 1975 and
21 1977: Nieboer et al. 1976). It also binds to the central metal atoms of enzymes, adversely affecting
22 membrane function and cell osmolality. In addition, SC>2 competitively inhibits carbonate (HCOs) and
23 phosphate (H2PO4) interactions with enzymes (Hutchison et al., 1996). Low pH increases the toxicity of
24 SC>2 action (Farmer et al., 1992). The toxic effects of atmospheric deposition of SC>2 are lessened when
25 lichen are attached to a substrate, typically bark or rock, having high pH or superior buffering capacity
26 (Richardson and Cameron, 2004). Van Herk (2001) evaluated relationships between bark pH and air
27 pollution levels as two significant variables affecting epiphytic lichen composition, and concluded that
28 bark pH was the primary factor regulating the distribution of acidophilic species in The Netherlands. In
29 studies of unpolluted areas, differences in bark chemistry also affect the presence and distribution of
30 epiphytes (Farmer et al., 1992). Indirect effects on bark pH, caused by acidification and high SO2
31 concentrations, also affect lichen distribution (Farmer et al., 1992).
3.4.2.2. Direct Phytotoxic Effects of NO, N02 and Peroxyacetyl Nitrate (PAN)
32 It is well known that in sufficient concentrations nitric oxide (NO) and NO2 can have phytotoxic
33 effects on plants through decreasing photosynthesis and inducing visible foliar injury (EPA, 1993a). The
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1 1993 NOX AQCD concluded that concentrations of NO2 or NO in the atmosphere are rarely high enough
2 to have phytotoxic effects on vegetation (EPA, 1993a). Since the 1993 AQCD, very little new research
3 has been done on these phytotoxic effects to alter this conclusion. However, it is known that these gases
4 alter the N cycle in some ecosystems, especially in the western U.S., and contributing N saturation (Fenn
5 et al., 2003a;(Bytnerowicz, 1996). See Section 3.3 for a discussion of the nutrient effects of N.
6 In general, NO and NO2 enters leaves through stomata (Saxe, 1986). However, it has also been
7 shown that the leaf cuticle may be an important receptor for NO2 and there is evidence of transport of NO
8 and NO2 across isolated cuticles (Lendzian and Kerstians, 1988). Several studies have demonstrated that
9 plant canopies can directly assimilate N in the form of NO2, but canopy uptake of NO2 is generally small
10 relative to total plant uptake (Hanson et al 1989, Norby et al, 1989; nussbaum et al 1993; Ammann et al
11 199; segschneider et al 1993; vallano and sparks 2008; von ballmoos et al 1993). After entering the
12 leaves, NO2 dissolves in the extracellular water of the sub-stomatal cavity to form HNO2 and HNO3,
13 which then dissociate to form nitrite, NO3~, and protons (Bytnerowicz et al, 1998a). Both cell and
14 tonoplast membranes contain ATP-dependent FT pumps and the tonoplast pumps are strongly inhibited by
15 NO3 (Bytnerowicz et al, 1998a). If extra protons are deposited in vacuoles of the plant cells during
16 normal cellular regulation, then additional acidity will occur in combination with additional NO3~. This
17 combination can cause disruptions in cellular control (Taylor and MacLean, 1970). NO3 and nitrite are
18 metabolized to amino acids and proteins through a series of enzymatic reactions mainly involving NO3
19 and nitrite reductases (Amundson and MacLean 1982). The effectiveness of plants to reduce NO3 and
20 nitrite to amino acids and proteins determines the potential of the plant to detoxify NO and NO2
21 (Wellburn, 1990). Reduction of NO3 takes place outside of the chloroplast while the reduction of nitrite
22 is coupled with the light reactions of photosynthesis. Therefore, when leaves are exposed to NO and NO2
23 in the dark, highly phytotoxic levels of nitrite accumulate and may lead to greater toxicity to NO and NO2
24 at night (Amundson and MacLean, 1982). Exposure to NO produces both NO3 and nitrite in the leaves,
25 but the rate of NO3 accumulation is much slower than nitrite. Thus, plants exposed to high NO could be
26 at risk to elevated concentrations of nitrite (Wellburn, 1990). More detailed information on the cellular
27 effects of NO and NO2 can be found in the 1993 NOX AQCD.
28 The functional relationship between ambient concentrations of NO or NO2 and a specific plant
29 response, such as foliar injury or growth, is complex. Factors such as inherent rates of stomatal
30 conductance and detoxification mechanisms and external factors, including plant water status, light,
31 temperature, humidity, and the particular pollutant exposure regime, all affect the amount of a pollutant
32 needed to cause symptoms of foliar injury. Plant age and growing conditions, and experimental exposure
33 techniques also vary widely among reports of experimental exposures of plants to NO2. An analysis
34 conducted in the 1993 NOx AQCD of over 50 peer-reviewed reports on the effects of NO2 on foliar injury
35 indicated that plants are relatively resistant to NO2, especially in comparison to foliar injury caused by
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1 exposure to O3 (EPA, 1993a). With few exceptions, visible injury was not reported at concentrations
2 below 0.20 ppm, and these occurred when the cumulative duration of exposures extended to 100 hours or
3 longer. At 0.25 ppm, increased leaf abscission was reported on navel orange trees (Citrus sinensis L), but
4 only after exposures in excess of 1000 hours (Thompson et al. 1970). Green bean plants used as bio-
5 indicators of NO2 injury in Israel developed foliar injury symptoms when ambient concentrations
6 exceeded 0.5 ppm (Donagi and Goren 1979). Only when concentrations exceeded 1 ppm did injury occur
7 on most plants in less than one day (EPA, 1993a).
8 Reductions in rates of photosynthesis have been recorded in experimental exposures of plants to
9 both NO and NO2, but usually at concentrations significantly higher than would normally be encountered
10 in ambient air. For example, Sabaratnam et al. (1988) reported that soybean (Glycine max) exposed
11 7 hours/day for 5 days showed an increase in photosynthetic rates at a concentration of 0.2 ppm, but a
12 reduction in net photosynthesis at a concentration of 0.5 ppm. Short-term exposures of soybean to
13 0.6 ppm NO2 for 2 to 3 hours also had no effect on net photosynthesis (Carlson 1983). Most plants appear
14 to be more susceptible to NO than to NO2, as shown by Saxe (1986b), who exposed a variety of
15 horticultural plants raised in greenhouses (species ofHedera, Ficus, Hibiscus, Nephrolepis, and
16 Dieffenbachid) to both NO and NO2. Saxe (1986b) reported that reductions in net photosynthesis occurred
17 at doses of NO that were 22 times less than that for NO2. However, these reductions in net photosynthesis
18 required concentrations as high as 1 ppm NO for 12 hours to elicit a response in these plants.
19 Hundreds of studies have been conducted on the effects of NO2 on growth and yield of plants
20 mostly performed in the 1970s and 1980s. These studies varied widely in plant species, growing
21 conditions, exposure equipment, concentrations, durations, exposure regimes, and environmental
22 conditions during exposures. No clear dose-response relationships for exposure to NO2 and reductions in
23 growth and/or yield of plants have emerged from these experiments. Readers are referred to the analysis
24 of over 100 studies conducted in the 1993 NOX AQCD. A few key studies are highlighted in this section.
25 Several plant species appear to be susceptible to reductions in growth by relatively low concentrations of
26 NO2 (less than 0.2 ppm), particularly when exposed during low-light conditions. For example, nearly
27 continuous exposure to 0.1 ppm NO2 for eight weeks significantly reduced growth of Kentucky blue grass
28 (Poa pratensis L) (Ashenden and Williams 1979; Whitmore and Mansfield 1983). Eight species of tree
29 seedlings were exposed to 0.1 ppm NO2 for six hours/day for 28 days, resulting in reduced shoot or root
30 growth in two species, white ash (Fraxinus americana L.) and sweetgum (Liquidambar styraciflua L.),
31 reduced height growth in two clones of loblolly pine (Pinus taeda L.), and no effects on the other species
32 (Kress and Skelly 1982). No effects of NO2 at 0.1 ppm or lower were observed on numerous other
33 species, including potato (Solanum tuberosum L.), black poplar (Populus nigra L.), radish (Raphanus
34 sativus L.), soybean, or peas (Pisum sativum L.) (EPA, 1993a). No effects of NO2 were observed on
35 soybeans grown in field plots subjected to a series of 10 episodic exposures averaging 0.4 ppm for 2.5 or
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1 3 hours (Irving et al. 1982). Numerous studies have reported negative effects on growth of a variety of
2 plants exposed to 0.5 ppm NO2 and above (EPA, 1993a), but these concentrations are unrealistically high
3 relative to current ambient levels of NO2.
4 The 1993 NOx AQCD reviewed the extensive literature on the effects of NO2 in combination with
5 other gaseous air pollutants, particularly SO2 and O3 and concluded that combinations of pollutants can
6 cause reductions in photosynthesis or foliar injury at concentrations lower than those associated with NO2
7 acting alone, but the plant responses occur at concentrations much higher than are found in ambient air
8 (EPA, 1993a). In addition, the presence of NO2 in combination studies did not produce symptoms
9 different from those caused by the dominant pollutant, either SO2 or O3, so that a plant response produced
10 by combinations of NO2 with other air pollutants in the field would be difficult, if not impossible, to
11 distinguish from those of the other single pollutants (EPA, 1993a).
12 Since the 1993 NOx AQCD was completed most new research on NO2 exposure to vegetation has
13 taken place in Europe and other areas outside the US. For example, foliar NO3 reductase activity was
14 increased in Norway spruce (Picea abies) trees growing in near a highway with average exposures of
15 about 0.027 ppm compared to trees growing 1300 meters away from the highway with NO2 exposures
16 less than 0.005 ppm (Ammann et al. 1995). This was consistent with other studies on Norway spruce in
17 the field and laboratory (Ballomoos et al. 1993; Thoene et al 1991). Muller et al (1996) found that the
18 uptake rate of NO3 by roots of Norway spruce seedlings was decreased by the exposure to 0.1 ppm of
19 NO2 for 48 hours. Similarly, soybean plants grown in Australia had decreased NO3 uptake by roots and
20 reduced growth of plants exposed to 1.1 ppm of NO2 for 7 days (Qiao and Murray, 1998). In a Swiss
21 study, poplar cuttings exposed to 0.1 ppm for of NO2 for approximately 12 weeks resulted in decreased
22 stomatal density and increased specific leaf weight, but did not result in other effects such as leaf injury or
23 a change in growth (GunthardtGoerg, 1996). However, NO2 enhanced negative effects of ozone,
24 including leaf injury, on these poplars when the pollutants were applied in combination (Gunthardt-
25 Goerge et al 1996)(GunthardtGoerg, 1996 007D.
26 Peroxyacetyl nitrate (PAN) is a well-known photochemical oxidant, often co-occurring with O3
27 during high photochemical episodes, which has been shown to cause injury to vegetation (See reviews by
28 Cape, 2003, 1997; Kleindienst, 1994)(Smidt, 1994; Temple, 1983). Acute foliar injury symptoms
29 resulting from exposure to PAN are generally characterized as a glazing, bronzing, or silvering of the
30 underside of the leaf surface; some sensitive plant species include spinach, Swiss chard, lettuces, and
31 tomatoes. Petunias have also been characterized as sensitive to PAN exposures and have been used as
32 bioindicators of in areas of Japan (Nouchi et al., 1984). Controlled experiments have also shown
33 significant negative effects on the net photosynthesis and growth of petunia (Petunia hybrida L.) and
34 kidney bean (Phaseolus vulgaris L.) after exposure of 30 ppb of PAN for four hours on each of three
35 alternate days (Izuta et al., 1993). As mentioned previously, it is known that oxides of N, including PAN,
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1 could be altering the N cycle in some ecosystems, especially in the western U.S., and contributing
2 N saturation (Fenn et al., 2003a; Bytnerowicz, 1996) see Section 3.3). However, PAN is a very small
3 component of N deposition in most areas of the US. Although PAN continues to persist as an important
4 component of photochemical pollutant episodes, there is little evidence in recent years suggesting that
5 PAN poses a significant risk to vegetation in the U.S.
3.4.2.3. Direct Phytotoxic Effects of HN03
6 Relatively little is known about the direct effects of HNO3 vapor on vegetation. It has been
7 established that HNO3 has a very high deposition velocity compared to other pollutants and may be an
8 important source of N for plants (Hanson, 1991; Vose, 1990; Hanson, 1992). This deposition could
9 contribute to N saturation of some ecosystems close to sources of photochemical smog (Fenn, 1998). For
10 example, in mixed conifer forests of the Los Angeles basin mountain ranges HNO3 has been estimated to
11 provide 60% of all dry deposited N (Bytnerowicz, 1999b; Bytnerowicz, 1999a).
12 Norby et al. (Norby, 1989) reported that exposure of 75 ppb of HNO3 for one day increased nitrate
13 reductase activity in red spruce foliage. In another study, foliar nitrate reductase activity was also
14 increased in California black oak (Quercus kelloggi), canyon live oak (Quercus chrysolepis) and
15 pondersosa pine (Pinus ponderosd) seedlings exposed to HNO3 concentrations of 65 to 80 ppb for 24
16 hours (Krywult, 1997). Because the induction of nitrate reductase activity is a step in a process leading to
17 the formation of organic N compounds (amino acids), the nitrate from HNO3 could function as an
18 alternated source of N for vegetation (Callanni et al 1999). However, in plants under stress, the reduction
19 of nitrate to amino acids consumes energy needed for other metabolic processes.
20 At high ambient concentrations HNO3 can cause vegetation damage. Seedlings of ponderosa pine
21 and California black oak subjected to short-term exposures from 50-250 ppb of HNO3 vapor for 12 hours
22 showed deterioration of pine needle cuticle at 50 ppb in light (Bytnerowicz et al, 1998b). Oak leaves
23 appeared to be more resistant to HNO3 vapor, however, with 12-h exposures in the dark at 200 ppb
24 producing damage to the epicuticular wax structure (Bytnerowicz et al, 1998b). The observed changes in
25 wax chemistry caused by HNO3 and accompanying injury to the leaf cuticle (Bytnerowicz et al, 1998b)
26 may predispose plants to various environmental stresses such as drought, pathogens and other air
27 pollutants. Because elevated concentrations of HNO3 and ozone co-occur in photochemical smog
28 (Solomon et al. 1998), synergistic interactions between the two pollutants are possible (Bytnerowicz et al,
29 1998a).
30 It has been suspected that HNO3 may have caused a dramatic decline in lichen species in the Los
31 Angles basin (Nash, 1999). The suggestion was strengthened by transplant ofRamalina lichen species
32 from clean air habitats (Mount Palomar and San Nicolas Island) to analogous polluted habitats in the Los
33 Angeles basin and repeatedly observing death of the lichens over a few weeks in the summer
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1 (Boonpragob, 1991). Associated with this death was massive accumulation of H+ and NO3 by the lichen
2 thalli (Boonpragob, 1989). Recently, Riddell et al. (2008) exposed the healthy Ramalina menziesii thalli
3 to moderate (8-10 ppb) and high (10-14ppb) HNO3 in month-long fumigations and reported a significant
4 decline in chlorophyll content and carbon exchange capacity compared to thalli in control chambers.
5 Thalli treated with HNO3 showed visual signs of bleaching and by day 28 were clearly damaged and
6 dead. The damage may have occurred through several mechanisms including acidification of pigments
7 and cell membrane damage (Riddell, 2008). The authors concluded that Ramalina menziesii has an
8 unequivocally negative response to HNO3 concentrations common to ambient summer conditions in the
9 Los Angeles air basin and it is very likely that HNO3 has contributed to the dissappearance of this
10 sensitive lichen species from the Los Angeles air basin, as well as other locations with arid conditions
11 with high deposition loads (Riddell, 2008).
Table 3-28. Summary of recent studies of SCh exposure to plants.
Species
Exposure (Concentration, Duration [hours, days])
Endpoint(s)
Results
Reference
Scots pine (P/'nus
sylvestris L.)\ Norway
spruce (Picea abies
(L) Karat)
0, 50, 100,150,155 ppb S02 in growth chambers Concentrations of
simulating natural weather in Finland in early June. carbohydrates and
The S02 concentrations represented the range of secondary
hourly S02 concentrations in the vicinity of industrial components
areas in Finland.
Scots pine (P/'nus
sylvestris L); Norway
spruce (Picea abies
(L) Karst.)
Mature red spruce
(Picea rubens Sarg.)
Mature trees growing at a polluted (32 ppb SCte) and
low pollution (1 ppb SCte) sites in Finland. In addition,
seedlings were placed in the chambers and open-field
plots in mid-Sept. 1991 and fumigated 8 hours daily, 5
days a week from 19 September to 15 Nov 1991 and
from 19 May to 12 Oct 1992. Mean pollutant
concentrations in the fumigated chambers during the
8-h exposure periods were 5-6 ppb S02 and 7-8 ppb
N02. The mean pollutant concentrations not receiving
the particular pollutant were ~2 ppb S02 and 5 ppb
N02.
Branches were fumigated in late summer of 1990 and
1991 in Canada. Four S02 treatment levels (0, 100,
200, 400 ppb)
Response of needle
sulphur and N
concentrations
Net photosynthesis,
stomatal
conductance, visible
foliar injury
Exposure to S02 (100 and 155 ppb) reduced concentrations Kainulainen et
of glucose and fructose and increased concentrations of al.
sucrose in pine needles. By contrast, one spruce clone had (Kainulainen,
more glucose and fructose and less sucrose in needles 1995)
exposed to 100 ppb S02, but in other spruces no changes in
sugar concentrations were detected in different S02
exposures (50-155 ppb). Exposure to S02 had no effects on
concentrations of monoterpenes in pine or spruce needles.
Concentration of total resin acids was significantly smaller in
needles exposed to the greatest concentration of S02 (155
ppb), but no changes were detected in other exposures (50-
150 ppb) in either tree species. Concentrations of palustric
and neoabietic acids were affected by S02 in needles of pine
(155 ppb S02> and clonal spruces (100 ppb SCte). Exposure
to S02 did not affect foliar concentration of total phenolics in
pine and spruce seedlings. In exposure to 0, 50,100 and
150 ppb S02, total phenolic concentration of spruce roots
increased linearly with elevated S02 exposure level. By
contrast, one spruce clone had decreased concentrations of
phenolics in roots after exposure to 155 ppb S02.
Elevated concentrations of S were found in mature pine and Manninen et
spruce trees at polluted sites. The response of mature Scots al. (Manninen,
pine to S02 differed from that of mature Norway spruce. The 2000)
greater increase in the needle total S concentrations of pine
suggested more abundant stomatal uptake of S02 compared
to spruce. Mature pine was able to assimilate SCU2- derived
from S02 into organic S more effectively than mature spruce
at the high S and N deposition sites, whereas both pine and
spruce seedlings accumulated S under N02+S02 exposure.
Net photosynthesis and stomatal conductance were found to Meng et al.
decrease in direct proportion with cumulative foliar S02 (Meng, 1994
absorption. Needle injury was observed in sun branches
exposed to 200 and 400 ppb of S02 in 1990. Net
photosynthesis was depressed by S02 regardless of branch
position. Foliage subjected to high level S02 did not recover
from S02 damage 1 year after treatment: needles had fallen
off twigs and twig length of new foliage was reduced.
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Species
Exposure (Concentration, Duration [hours, days])
Endpoint(s)
Results
Reference
Scots pine (Pinus
sylvestris L); Norway
spruce (Picea abies
(L) Karst.)
European Beech
(Fagus sylvatica L),
Norway Spruce (Picea
abies (L) Karst.)
European Silver Fir
(Abies alba Mill.).
Norway spruce (Picea
abies (L.))
European Beech
(Fagus sylvatica L),
Norway Spruce (Picea
abies (L.) Karst.)
European Silver Fir
(Abies alba Mill.).
European Beech
(Fagus sylvatica L),
Norway Spruce (Picea
abies (L.) Karst.)
European Silver Fir
(Abies alba Mill.).
Norway spruce (Picea
abies L. Karst) and fir
seedlings (Abies aiba
Mill.)
Black sage (Salvia
mellifera) CA
sagebrush (Artemisia
californica) Eastern
Mojave buckwheat
(Eriogonum
asciculatum) CA
brittlebush (Encelia
californica)
Timothy grass
(Phleum pratense)
Mixed native prairie
Faba bean (Vicia
faba L)
Open-air experiment, Finland- trees were exposed to
F, N and S pollutants individually, or in mixtures, by
spraying F and N compounds in aqueous solution and
fumigating plants with gaseous S02, for 5 months in
each of 3 consecutive growing seasons. S02
concentration among the trees varied between 35 and
140 ppb S02, depending on velocity and direction of
the wind. Exact concentrations of S02 were not
Weekly concentrations of S02, (averaging 3-42 ppb)
and Oa (10-90 ppb) was applied to trees in open-top
chambers in Hohenheim, Germany, for almost five
years.
Weekly concentrations of S02, (averaging 3-42ppb)
and Oa (10-90 ppb) was applied to trees in open-top
chambers in Hohenheim, Germany, for almost five
years.
Weekly concentrations of S02, (averaging 3-42 ppb)
and 03 (10-90 ppb) was applied to trees in open-top
chambers in Hohenheim, Germany, for almost five
years
Root samples taken in five-year Hohenheim Long
Term Experiment in Germany from 2 tree groups.
Each group of trees consisted of three younger (10-
year-old) and five older (13-year-old) trees. Weekly
concentrations of S02, (averaging 3-42 ppb) and 03
(10-90 ppb) was applied to trees in open-top
chambers.
One- and two- year old seedlings exposed to low
levels of S02 and Oi in open-top chambers in five
year experiment 1983 through 1988 in Hohenheim,
Germany. S02 concentrations averaged weekly
between 3-42 ppb and Oi concentrations were
between 10-90 ppb.
S02 fumigation over 10 weeks, at 0, 50, 200, and 500
ppb, California
Exposure to 120 ppb S02 for 40 days.
Exposed grasses to a control (~7 ppb) and three
elevated levels of S02 (-21, 37, 64 ppb) over 5 year
study.
Experiment done in 3 different years (1986,1986,
1988). Seasonal mean elevated exposures of S02
were 58 ppb in 1985, 22 ppb in 1986 and 26 ppb in
1988. Ambient concentrations were 6 ppb in 1985,
3 ppb in 1986 and 3 ppb in 1988.
Visible symptoms,
pollutant
concentrations,
ultrastructure of
seedlings
Shoot length, leaf
surface area, dry
weight
Ectomycorrhizal
(EM) frequency, fine
root structure,
distribution of short
roots
Visible injury
Fine root and
mycorrhizae
production
Visible symptoms,
photosynthesis,
transpiration
Number of
inflorescences
Leaf production, leaf
senescence,dry
weight (LAR), leaf-
area ratio, specific
leaf area (SLA)
Root and rhizome S
concentrations,
biomass, primary
productivity, lichen
cover, population
Yield, leaf injury
Visible injury symptoms were most pronounced in Wulff et al.
combination exposures and whenever F was applied. (Wulff, 1996)
Visiblesymptoms correlated well with needle pollutant
concentrations. Exposure to F increased needle F contents
particularly when F was applied with S02 or NH4N03. This
suggests that a reduction in N or S02 emissions, in F
polluted areas, could improve the condition of conifers via
decreased accumulation of phytotoxic F in the needles.
Norway spruce needles accumulated 2-10 times as much S
and F as those of Scots pine. In both species, exposure to
S02 increased significantly the amount of cytoplasmic
vacuoles, suggesting detoxification of excess sulphate or low
pH. All exposures enhanced the accumulation of lipid bodies.
Both visible symptoms and ultrastructural changes pointed to
the more pronounced sensitivity of Norway spruce compared
to Scots pine.
Fumigation with S02 alone caused insignificant decreases of Billen et al.
shoot length, total dry weight, and needle surface of spruce (Billen, 1990)
and fir. Fir trees fumigated with S02 in combination with Os
showed lower rates of productivity compared to filtered
control treatments. Beech was not as affected by S02 than
with 0s or S 02+ 03.
S02 resulted in higher percentages of non-mycorrhizal short Blaschke
root tips, and decreased number of living short roots. EM (Blaschke,
percentage decreased by 38%on S02exposed roots. 1990)
In Jan to Feb 1985, after long frost, S02 treated fir showed Arndt et al.
development of tip necrosis, showing S02 inhibits frost (Arndt, 1990)
resistance. No clear visible effects were found due to S02
alone on beech or spruce.
In beech seedlings, S02 and S02 +0s resulted in reduced Wollmer and
fine root production by 35% and 55%, respectively. S02 had Kottke
no clear effect on fine root production in fir. S02 increased (Wollmer,
fine root production in spruce by 31%, but significantly 1990)
reduced relative frequency of mycorrhizae (-20).
The twigs did not exhibit any visible sign of injury due to S02 Schweizer and
treatments. Exposure of fir to S02 alone or in combination Arndt
with Oi resulted in a significant decrease in photosynthesis (Schweizer,
and transpiration. No changes either in photosynthesis or 1990)
transpiration were found in spruce under fumigation with S02
alone.
Decreased inflorescences were observed at 50 ppb S02 for Westman et al.
black sage, and at 200 ppb S02 for California sagebrush, (Westman,
Eastern Mojave buckwheat, and California brittlebush, with 1985)
progressive declines as S02 concentration increased.
Diminished leaf production and increased leaf senescence in Mansfield and
seedlings exposed to 120 ppb S02 at 35 days. Exposure to Jones
120 ppb S02 in seedlings over 40 days resulted in a 62% (Mansfield,
reduction in the dry weight of roots and 51% reduction in the 1985)
dry weight of shoots, as well as a significant decline in leaf-
area ratio and specific leaf area by the end of the
experiment.
Year-to-year S accumulation did not appear to occur over Laurenroth
the 5-year course of the treatment, though progressive and Milchunas
increases in root and rhizome S concentrations were Laurenroth
observed seasonally. No significant negative effects on
either above-ground net primary productivity or below-
ground biomass dynamics in grasses were observed, except
a decrease in biomass for Bromusjaponicus. Lichen cover
declined after 1 year of exposure at the low treatment level.
Exposure to elevated S02 resulted in leaf injury in all three Kropff (Kropff,
years. S02 exposure reduced yield by 17% in 1985, 7% in 1990)
1986 and 9% in 1988.
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Chapter 4. Summary and Conclusions
1 The previous chapters present the policy-relevant science pertaining to the emissions, atmospheric
2 transformation and transport, deposition and ecological effects of NOX and SOX. Ecological effects are
3 divided into the broad categories of ecosystem type which are typically studied: terrestrial, wetlands,
4 freshwater aquatic, and estuarine aquatic. Several NOX and SOX chemical species were considered
5 because of their complex multi-phase and multi-species in both the atmosphere and the biosphere. For
6 example, the atmospheric chemistry of NOX and SOx would be incomplete, for the purposes of this ISA,
7 if only gas-phase compounds were considered; therefore, descriptions of current ambient concentrations
8 and deposition amounts related to the particulate forms of N and S are given in Chapter 2. Similarly, the
9 roles of other atmospheric pollutants, including Hg, O3, NH3, and ammonium ion, and their interactions
10 with NOX and SOX in the atmosphere and production of demonstrable welfare effects are also considered.
4.1. Source to Dose
4.1.1. Relevant Chemical Families and Constituent Species
11 NOX is the name given to the family of chemical species containing oxidized N, chief among which
12 is N2O, NO2, HNO3, and PAN in the gas phase. And because it has a prominent role in moving N from the
13 atmosphere to the biosphere, particulate nitrate is included in this ISA as well even though it is not a
14 member of the oxidized N family of species as typical defined. Some of these oxidized N species are
15 directly emitted; others are formed as secondary products from the emitted species. Similarly, SOX is the
16 name for the family of chemical species containing oxidized S, including SO, SO2, SO3, and S2O;
17 however, of these gas-phase species, only SO2 is present in concentrations relevant for atmospheric
18 chemistry and environmental exposures. In addition, and as was the case with the NOX family of species,
19 particulate SO42 is included in this ISA because of its dominant role in transferring S species from the
20 atmosphere to the biosphere. Furthermore, this ISA includes extensive treatment of the reduced N
21 chemical species NH3 and NH4 — together given the chemical family name NHX — because NHX can
22 play a crucial role controlling the transfer of total N and S to the biosphere on many levels of spatial
23 extent. The most salient points from the foregoing chapters are summarized below.
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4.1.2. Emissions and Atmospheric Concentrations
1 Total anthropogenic NO and NO2 emissions in the U.S. in 2001 were -23.19 Tg. Combustion
2 chemistry at EGUs contributed -22% of these total and transportation-related sources, -56%. Ambient
3 annual NOX concentrations have decreased -35% in the period 1990-2005 to current annual average
4 concentrations of-15 ppb.
5 Biogenic NOX sources are substantially smaller than anthropogenic ones and include biomass
6 burning, lightning, and soils. The NO and N2O emitted from soils as intermediate products from
7 denitrification can evolve either naturally or as stimulated by addition of N containing fertilizers to crops
8 and other soil management practices. N2O, another member of the oxides of N family of chemicals, is
9 also a minor contributor to total U.S. GHG emissions: -6.5% on a Tg CO2e basis in 2005, and its U.S.
10 emissions decreased -3% in the period 1990-2005, though there remains considerable interannual
11 variation in this value.
12 Concentrations of NO2 in the CONUS from uncontrollable sources in the U.S. and elsewhere in the
13 world are <300 ppt over most of the CONUS and <100 ppt in the eastern U.S. on an annual average basis.
14 The 24-h ambient NO2 concentrations in CMSAs where most of the regulatory monitors are located and
15 where most anthropogenic emissions originate were, on average, <20 ppb with a 99 percentile value <50
16 ppb for the years 2003-2005. Annual-average NO2 concentrations over the CONUS are calculated to be
17 <5 ppb for nearly all urban and rural and remote sites.
18 On a national scale, energy production at EGUs accounted for -66% of total SO2 emissions in the
19 U.S. in 2001-2002; -5% of total SO2 is emitted by transportation-related sources, with on-road vehicles
20 accounting for -40 % of the transportation fraction, and off-road diesel and marine traffic together
21 accounting for the remainder. Ambient annual SOX concentrations have decreased -50% in the period
22 1990-2005 and now stand at -4 ppb for both aggregate annual and 24-h average concentrations nation-
23 wide.
24 Annual-average policy-relevant background SO2 concentrations in the U.S. from uncontrolled
25 sources here and elsewhere in the world are <10 ppt over most of the CONUS, or <1% of observed SO2
26 concentrations everywhere except areas in the Pacific Northwest where geogenic SO2 sources are
27 particularly strong.
28 NH3 emissions are chiefly from livestock and from soils as stimulated by addition of N-containing
29 fertilizers to crops and other soil management practices. Confined animal feeding operations and other
30 intensified agricultural production methods over a period of many decades have resulted in greatly
31 increased volumes of animal wastes high in N; 30 to 70% of these wastes may be emitted as NH3. This
32 increase in NH3 emissions, and the consequent increase in NH4+ concentration and deposition, correlates
33 well with the local and regional increases in agricultural intensity. However, there remain no reliably
34 consistent estimates of national average NH3 concentrations owing to three complex issues: (1) the high
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1 spatial and temporal variability in NH3 emissions; 2) the high uncertainty in the magnitude of those
2 emissions; and (3) the lack of real-time, ambient level NH3 monitoring techniques. Nonetheless, U.S.
3 national NH3 emissions totals have been calculated taking into account these three drivers of uncertainty;
4 for 2001-2002 that national NH3 emissions total was -4.08 Tg/yr.
4.1.3. Deposition of N and S
5 Increasing trends in urbanization, agricultural intensity, and industrial expansion during the
6 previous 100 years have produced a nearly 10-fold increase in N deposited from the atmosphere. NOX,
7 chiefly from fossil fuel combustion, often dominates total N pollution in the U.S. and comprises -50 to
8 75% of the total N atmospheric deposition.
9 For the period 2004-2006, the routine monitoring networks report the mean N deposition in the
10 U.S. was greatest in the Ohio River Valley, specifically in the states of Indiana and Ohio, with values as
11 high as 9.2 and 9.6 kg N/ha/yr, respectively. N deposition was lower in other parts of the East, including
12 the Southeast and in northern New England. In the central U.S., Kansas and Oklahoma reported the
13 highest deposition, 7.0 and 6.5 kg N/ha/yr, respectively.
14 N deposition primarily occurred in the form of wet NO3 and NFLt, followed with decreasing
15 amounts of dry HNO3, dry NH4+, and dry NO3. Although deposition in most areas of the U.S. occurred in
16 wet form, there were some exceptions, including parts of California where N deposition was primarily
17 dry. Data are very sparse for the central U.S. between the 100th meridian and the Mississippi River; but,
18 where available, N deposition values there are lower than most of the Eastern U.S., ranging from 4.1 to
19 5.3 kg N/ha/yr.
20 For the period 2004-2006, mean S deposition in the U.S. was greatest east of the Mississippi River
21 with the highest deposition amount, 21.3 kg S/ha/yr, in the Ohio River Valley where most recording
22 stations reported three-year averages >10 kg S/ha/yr. Numerous other stations in the East reported S
23 deposition >5 kg S/ha/yr. Total S deposition in the U.S. west of the 100th meridian is relatively low, with
24 all recording stations reporting less than 2 kg S/ha/yr and many reporting less than 1.0 kg S/ha/yr.
25 S was primarily deposited in the form of wet SO42 followed in decreasing order by a smaller
26 proportion of dry SO2 and a much smaller proportion of dry SO42 . However, these S data in the western
27 U.S., like those for N deposition, are derived from networks with many fewer nodes in the West than in
28 the East.
29 N from atmospheric deposition is estimated to comprise 10 to 40% of the total input of N to many
30 coastal estuaries, and could be higher for some. Estimates of total N loadings to estuaries, or to other
31 large-scale elements in the landscape, are then computed using measurements of wet and dry N deposition
32 where these are available, and then interpolated with or without a set of air quality model predictions.
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1 Atmospheric inputs of reactive N directly to the surface of coastal waters are essentially equal to or
2 greater than those contained in riverine flow in the absence of deposition and may contribute from 20 to
3 >50% of external N loadings to these systems: 11, 5.6, and 5.6 kg N/ha/yr for the northeast Atlantic coast
4 of the U.S., the southeast Atlantic coast of the U.S., and the eastern Gulf of Mexico, respectively.
5 Atmospheric N loads to great waters and estuaries in the U.S. are estimated to range from 2 to 8%
6 for Guadalupe Bay, TX on the lowest end to -72% for the Catherines-Sapelo estuary (Castro, 2003) at the
7 highest end.
8 At Chesapeake Bay, where N and S deposition and ecological effects have been extensively
9 studied, total atmospheric deposition of atmospheric NO3 is estimated to contribute from 20 to 30% of
10 total N and 14% of the NH4+ loadings to the Bay.
4.1.4. Field Sampling and Analysis
11 The instrumentation deployed at present in the routine regulatory monitoring networks for
12 determination of gas-phase NOX and SO2 concentrations are likely adequate for determining compliance
13 with the current NAAQS. But all these methods have important limitations which make them inadequate
14 for fully characterizing the state of the atmosphere at present, the complex heterogeneity of N and S
15 deposition across the landscape, and the roles of atmospheric N and S in driving observed biological
16 effects.
17 • Routine NO2 measurements by CL (the Federal Register Method) are contaminated by
18 unknown and varying concentrations of higher-order oxidized N species, including gas-phase
19 HNO3, important as in itself for N deposition to the biosphere and also as a precursor to pNO3.
20 Moreover, dry deposition of NO, NO2, and PANs is not measured, but could be as much as
21 30% of total dry oxidized N deposition in areas near strong NOX sources.
22 D The present-day ambient annual avg SO2 concentrations are very near or even below the
23 operating limit of detection of most of the FRM monitors in the largest regulatory. This
24 produces irresolvable uncertainty in these data which may be important for
25 environmental effects since they can be affected in some cases at these current low
26 concentrations.
27 D Routine field sampling techniques for NH3 are at present limited to integrated values—
28 from several days to one week—because higher frequency semi-continuous methods are
29 not yet sufficiently robust to deploy in regulatory networks. Estimates for the
30 contribution of NH3 to the total N deposition budget range as high as 30% of total N, and
31 perhaps the dominant source of reduced N.
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1 D Routine regulatory sampling and analysis for particulate-phase NO3 , SO42 , and NH4+ are
2 subject to positive and negative errors, chiefly from the loss or production of constituent
3 species on the surface of the filter used for the long time-integrated measurement.
4 • The coverage of the networks is very thin over large expanses of the interior U.S. and
5 especially so west of the 100th meridian. This assessment concludes that this lack of monitored
6 sites increases the likelihood that significant deposition is now occurring at current
7 atmospheric concentrations where no measurements are available, as predicted in numerical
8 experiments with large-scale, first-principles models of atmospheric chemistry and physics and
9 deposition or measured at some few selected special sites.
4.2. Acidification
10 Oxides of N and S act together to cause acidification of ecosystems. The principal factor governing
11 the sensitivity of terrestrial and aquatic ecosystems to acidification deposition is geology. Watersheds of
12 acid-sensitive lakes and streams have geologic formations with low base cation supply (Bricker, 1989;
13 Stauffer, 1990; Stauffer, 1991; Vertucci, 1993; Sullivan, 2007). Other factors contribute to the sensitivity
14 of soils and surface waters to acidifying deposition, including topography, vegetation, soil chemistry, land
15 use, and hydrologic flowpath. Regional and ecosystem vulnerability to acidification is from sensitivity
16 and exposure to atmospheric loading of NOx and SOx
4.2.1. Terrestrial
17 In the 1982 AQCD for SOX (U.S. EPA, 1982), foliar and root uptake pathways for sulfur oxides
18 were described in detail, as well as the role of S as a nutrient. Though small amounts of SO2 may be
19 beneficial, it was understood that large amounts and high frequency of SO2 exposure and S deposition can
20 be detrimental in the long term. At that time, there were no documented observations or measurements of
21 changes in natural terrestrial ecosystems that were directly attributed to acidic precipitation. This did not
22 necessarily indicate that no change was occurring.
23 The 1993 AQCD for NOx (U.S. EPA, 1993) documented few cases in which excessive atmospheric
24 N deposition was linked to soil acidification, although the process of soil acidification was already well
25 understood. Since the preparation of these assessments, direct links between NOX and SOX deposition and
26 many adverse affects associated with ecosystem loading have been reported.
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4.2.1.1. Biogeochemistry and Chemical Effects
1 The evidence is sufficient to infer a causal relationship between acidifying deposition and
2 changes in biogeochemistry related to terrestrial ecosystems. The strongest evidence for a causal
3 relationship comes from studies of forested ecosystems, with supportive information on other plant
4 communities, including shrubs and lichens Section 3.2.2.1. Grasslands are likely less sensitive to
5 acidification than woodlands. Soil acidification occurs in response to inputs of sulfuric acid and nitric
6 acid; the effect can be neutralized by weathering or base cation exchange. Soil acidification is a natural
7 process, but is often accelerated by acidifying deposition. Acidifying deposition is important in decreasing
8 concentrations of exchangeable base cations in soils. The limited mobility of anions associated with
9 naturally derived acidity (organic acids and carbonic acid) controls the rate of base cation leaching from
10 soil under conditions of low atmospheric deposition of S and N. Because inputs of S and N in acidifying
11 deposition provide anions that are more mobile in the soil environment than anions of naturally derived
12 acids, these mineral acid anions can accelerate natural rates of base-cation leaching.
13 Nitrification is mediated by autotrophic bacteria that derive energy by reducing NO3 to NH4+.
14 Nitrification produces acidity in the form of HNO3 as a byproduct, which contributes to the acidification
15 of soils and surface waters.
16 There are three useful indicators of chemical changes and acidification effects on terrestrial
17 ecosystems, with consistency and coherence seen among multiple studies (see Table 4-1) Soil Base
18 Saturation, Aluminum Concentration, and C:N Ratio.
19 • Soil base saturation is the concentration of exchangeable bases as a percent of the total soil
20 cation exchange capacity. Once base saturation decreases to a critical level (-15-20%), inputs
21 of H2SO4 and HNO3 are increasingly buffered by the release of inorganic Al through cation
22 exchange.
23 • Al is toxic to some tree roots. Plants affected by high inorganic Al concentrations in soil
24 solution often have reduced root growth, which restricts the ability of the plant to take up water
25 and nutrients, especially calcium (Parker, 1989).
26 • The C:N ratio of soil is used to indicate alterations to the N biogeochemical cycle. If the ratio
27 falls below about 20 to 25, nitrification is stimulated and net nitrification and associated
28 production of acidity occurs in soils.
29
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Table 4-1. Studies on chemical indicators of acidification to terrestrial ecosystems.
Reference Indicator
Soil Base Saturation
Reuss(1983) If base saturation is less than 15-20%, exchange ion chemistry is dominated by inorganic Al.
,,ggg, ^ Base saturations below about 15% in the soil B-horizon could lead to effects from Al stress.
Lawrence et al. (1995) Base saturation decreases from 30% to 20% in the upper soil B-horizon showed decreases in diameter growth of Norway spruce.
Bailey et al. (2004) At Ca saturation less than 2% and Mg saturation less than 0.5% in the upper soil B-horizon, sugar maple mortality was observed.
Aluminum Concentrations
Johnson etal. (1991)
Joslin and Wolfe I" s°ils ™th base saturation below about 20%, base cations reserves are so low that Al exchange dominates.
(1992)
. (1996)
There is a 50% risk of negative effects on tree growth if the molar ratio of Ca to Al in soil solution was 1.0. 100% risk for negative effects on growth at a molar
Cronan and Gngal ratio below 0.2.
(1995)
,qq., ' * '' Ca:AI ratios above 1.0 over the course of 4 years were found in a forest stand experiencing high mortality.
DeWitt et al. (2001) Ca:AI ratios below 0.5 in a Norway spruce stand showed reduced Mg concentrations in needles in the third year.
C:N Ratio
Aberetal. (2003)
Increased effects of nitrification occur only in soil with C:N ratio below about 20-25.
Ross et al. (2004)
4.2.1.2. Biological Effects
2 The evidence is sufficient to infer a causal relationship between acidifying deposition and
3 Changes in terrestrial biota. The strongest evidence for a causal relationship comes from studies of
4 terrestrial systems exposed to elevated levels of acidifying deposition that show reduced plant health,
5 reduced plant vigor, and loss of terrestrial biodiversity. In multiple studies, consistent and coherent
6 evidence shows that acidifying deposition can affect terrestrial ecosystems by causing direct effects on
7 plant foliage and indirect effects associated with changes in soil chemistry (Section 3.2.2.2). Biological
8 effects of acidification on terrestrial ecosystems are generally attributable to aluminum toxicity and
9 decreased ability of plant roots to take up base cations. There are several indicators of stress to terrestrial
10 vegetation (see Table 3-3), including percent dieback of canopy trees, dead tree basal area (as a percent),
11 crown vigor index, and fine twig dieback.
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Species Level
1 • Changes in soil chemistry (e.g., depletion of soil base cations, Al toxicity to tree roots,
2 leaching of base cations into drainage water) have contributed to high mortality rates and
3 decreasing growth trends of red spruce trees (Picea rubens) in some areas of the Eastern U.S.
4 over the past three decades (see Red Spruce, Section 3.2.2.2).
5 • Acidifying deposition, in combination with other stressors, is a likely contributor to the decline
6 of sugar maple (Acer saccharuni) trees that occur at higher elevation, in some portions of the
7 eastern U.S., on geologies dominated by sandstone or other base-poor substrate, and that have
8 base-poor soils (see Sugar Maple, Section 3.2.2.2).
9 • Lichens and bryophytes are among the first species affected by acidifying deposition in the
10 terrestrial ecosystem. Effects of SO2 on lichens include reduced photosynthesis and respiration,
11 damage to the algal component of lichen, leakage of electrolytes, inhibition of N fixation,
12 reduced potassium absorption, and structural changes.
13 • Data are insufficient to draw general conclusions for other species.
Community Level
14 • Species loss and reduced biodiversity of forests, shrubs, and meadow plant communities may
15 occur in response to acidifying deposition; however, such effects are likely more related to the
16 nutrient enrichment effects of N deposition.
4.2.1.3. Regional Vulnerability and Sensitivity
17 There has been no systematic national survey of terrestrial ecosystems to determine the extent and
18 distribution of terrestrial ecosystem sensitivity to the effects of acidifying deposition. However, one
19 preliminary national evaluation estimated that -15% of forest ecosystems in the U.S. exceeds the
20 estimated critical load of wet and dry deposition of S and N by > 250 eq/ha/yr (McNulty, 2007).
21 Forests of the Adirondack Mountains of New York, Green Mountains of Vermont, White
22 Mountains of New Hampshire, the Allegheny Plateau of Pennsylvania, and high-elevation forest
23 ecosystems in the southern Appalachians are the regions most sensitive to terrestrial acidification effects
24 from acidifying deposition (Section 3.2.4.2). It is unknown if terrestrial acidification in these areas is
25 continuing, or if recovery is occurring in response to recent reductions in acidifying deposition.
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4.2.2. Aquatic
1 In the 1982 AQCD for SOx (EPA, 1982), evidence on acidifying deposition and its role in the
2 acidification of aquatic ecosystems was assessed. The most vulnerable regions were identified, including
3 the Adirondack Mountains of New York. Significant changes occurred in aquatic ecosystems with
4 increasing acidity, particularly as the pH decreases below ~ 5.5. It was concluded that: a) changes in
5 community structure occur at all levels in the food web; b) bacterial decomposition is reduced and fungi
6 that feed on organic debris may become dominant in aquatic communities; c) organic matter accumulates
7 rapidly, tying up nutrients and limiting nutrient mineralization and cycling; d) phytoplankton productivity
8 may be reduced because of changes in nutrient cycling and increased acidity; e) biomass and total
9 productivity of benthic macrophytes and algae may increase, in part because of increased lake
10 transparency; and f) species diversity and total numbers of species of aquatic plants and animals
11 (especially invertebrates and fish species) are reduced, and acid-tolerant species predominate.
12 The 1993 AQCD for NOX (EPA, 1993) reflected a substantial increase in our knowledge of the role
13 of N deposition in the acidification of aquatic ecosystems. This was especially the case with respect to
14 episodic acidification, which is far more common than chronic acidification and has been well
15 documented for streams and lakes in the Eastern U.S. The most well-known examples are in the
16 Adirondack and Catskill Mountains of the Northeast, as well as in the Great Smoky Mountains of the
17 Southeast. Instances of episodic acidification were also reported in the Western U.S. but to a much lesser
18 extent than in the East.
Biogeochemistry and Chemical Effects
19 The evidence is sufficient to infer a causal relationship between acidifying deposition and
20 changes in biogeochemistry related to aquatic ecosystems. The strongest evidence for a causal
21 relationship comes from studies of changes in surface water chemistry including concentrations of SO42 ,
22 N(V, sum and surplus of base cations, ANC, inorganic Al, Ca, and surface water pH (see Section 3.2.2.1.
23 Surface water chemistry integrates the sum of upstream soil and water processes and reflects the results of
24 watershed-scale terrestrial effects of S and N deposition, including N saturation, forest decline, and soil
25 acidification (Stoddard, 2003). In many cases, surface water chemistry indicates the effects of
26 acidification on biotic species and communities found in fresh water ecosystems.
27 The status of surface water chemistry can be examined and reported as chronic chemistry or
28 episodic chemistry. Chronic chemistry refers to annual average conditions, which are often represented as
29 summer and fall chemistry for lakes, and as spring baseflow chemistry for streams. Episodic chemistry
30 refers to conditions during rainstorms or snowmelt when proportionately more drainage water is routed
31 through upper soil horizons, which tend to provide less neutralizing of atmospheric acidity as compared
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1 with deeper soil horizons. Surface water chemistry has lower pH and ANC during storm runoff or
2 snowmelt than during baseflow conditions. One of the most important effects of acidifying deposition on
3 surface water chemistry is the short-term change in chemistry that is termed "episodic acidification."
4 Some streams may have chronic or average chemistry that is suitable for aquatic biota, but be subject to
5 occasional episodic acidification with lethal consequences. Episodic declines in pH and ANC are nearly
6 ubiquitous in drainage waters throughout the Eastern U.S., caused partly by acidifying deposition and
7 partly by natural processes.
8 Acidification effects on aquatic biota are often evaluated using measures of either Al or pH. ANC is
9 also used because it is an indicator of buffering capacity (although ANC does not relate directly to the
10 health of biota). The usefulness of ANC lies in the association between ANC and the surface water
11 constituents that directly contribute to or ameliorate acidity-related stress, in particular pH, Ca, and
12 inorganic Al.
Sulfate, Nitrate, and Base Cations
13 Changes in water chemistry resulting from acidifying deposition typically include changes in
14 SO42 , NO3 , and base cation concentrations. Each plays an important role in the acid-base chemistry of
15 water; none are directly toxic at concentrations commonly encountered in surface waters Table 4-2.
16 • Sulfate is the primary inorganic anion found in most acid-sensitive waters. Continued
17 decreases in S emissions should cause further decreases in SO42 concentrations in surface
18 waters. However the rate of decrease in surface water SO42 concentrations may be delayed as
19 accumulated S leaches from watershed soils in some regions of the country, especially the
20 Blue Ridge Mountains.
21 • The importance of NO3 as an agent of acidification varies by region, but is particularly
22 important during periods of high hydrologic flow from soils to streams, such as those that
23 occur during snowmelt and rain runoff. The relationship between N deposition and surface
24 water NO3 concentration is complex and involves the terrestrial and aquatic cycling of N and
25 other elements. NO3 contributes to the acidity of many lakes and streams in the eastern U.S.
26 However, there is no apparent relationship between recent trends in N deposition and trends in
27 NO3 concentrations in these surface waters (in contrast to observed responses for S deposition
28 and SO42 concentrations). This suggests that the time scales of N saturation may be longer
29 than previously considered (e.g., centuries, rather than decades). Nevertheless, long-term
30 retention of N deposited in forested regions and consequent dampening of deposition effects
31 on surface waters is unlikely to continue (Aber, 2003).
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1 • Decreases in base cation concentrations in Eastern U.S. surface waters over the past two to
2 three decades are ubiquitous and are closely tied to trends in SO42 concentrations. Rates of
3 base cation depletion have been similar to those for SO42 plus NO3 in most areas
4 (Shenandoah National Park is a notable exception). Decreasing trends in base cation
5 concentrations do not necessarily indicate further acidification or recovery of surface waters,
6 but may indicate either lower base cation leaching rates in soils or depletion of base cations
7 from the soil system.
Acid Neutralizing Capacity, Aluminum, and pH
8 Acidification of surface water causes changes in ANC, Al concentration, and pH. Low pH and high
9 inorganic Al concentration can be directly toxic to aquatic biota Section 3.2.3.
10 • ANC reflects the difference between base cations and anions of strong acids in solution; it is
11 the most widely used measure of acid sensitivity, acidification, and chemical recovery of
12 surface waters in response to changes in acidifying deposition. Acidic waters are defined as
13 those having ANC equal to or below zero. Waters with ANC of < 50 (ieq/L are considered
14 "extremely acid-sensitive" (Schindler, 1988), and are vulnerable to episodic acidification
15 (DeWalle, 1987; Eshleman, 1988). Lake and stream ANC values decreased throughout much
16 of the 20th century in a large number of acid-sensitive lakes and streams throughout the
17 Eastern U.S. Since -1990, the ANC of many affected lakes and streams has increased slightly.
18 The number of acidic surface waters has decreased in some areas of the Northeast, but not in
19 the mid-Appalachian Mountains.
20 • Dissolved inorganic Al is an important chemical indicator of the effects of acidifying
21 deposition on surface water because it is toxic to aquatic life and generally does not leach from
22 soils in the absence of acidification. When pH falls below approximately 5.5, inorganic Al
23 generally becomes a greater health risk to biota. Limited data suggest that acid-sensitive
24 regions of the Northeastern U.S. have elevated inorganic Al concentrations in surface waters
25 induced by years of acidifying deposition, posing a threat to aquatic life. Concentrations have
26 decreased slightly in some surface waters in the northeastern U.S. during the last two decades
27 in response to decreased levels of acidifying deposition.
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1 • The pH of freshwater streams and lakes is a common measure used to link acidification to
2 adverse effects on aquatic biota. Decreases in pH below values of 6.0 typically result in species
3 loss of benthic invertebrates, plankton species, and fish. A number of synoptic surveys
4 indicated loss of species diversity and absence of several fish species in the pH range of 5.0 to
5 5.5. If pH decreases to lower values, there is a greater likelihood that more aquatic species
6 could be lost without replacement, resulting in decreased richness and diversity.
Table 4-2. Studies on chemical indicators of acidification in surface water.
Reference Indicator
Sulfate
Driscoll et al. Acidifying deposition at Hubbard Brook Experimental Forest in New Hampshire contributed to a nearly four-fold increase in stream SCU2~ concentration between
(2001) 1850 and 1970.
Stoddard et al. Widespread decreasing trends in SCU2~ concentrations were documented by EPA during the period 1990-2000 in the Eastern U.S. including New England lakes
(2003) (1.77 |jeq/L/yr), Adirondack lakes (2.26 |jeq/L/yr), Appalachian streams (2.27 |jeq/L/yr), and Upper Midwest lakes (3.36 |jeq/L/yr).
Nitrate
Driscoll and NO-j" concentrations in 20 Adirondack lakes in the early 1980 averaged 12% of SCU2~ concentrations.
Newton (1985)
Lovett et al. (2000) Baseflow NOf concentrations in 1994-97 were an average of 37% of SCU2' concentrations in 39 Catskill streams.
Murdoch and During high-flows in Catskill streams NCr concentrations periodically equaled or exceeded SCU2" concentrations.
Stoddard (1993)
Webb et al. (2004) Average concentrations of NCb" in most southeastern streams tend to be considerably less than SCU2' concentrations.
Cook et al. (1994) Very high NOf concentrations in streamwater were documented at high elevations in the Great Smoky Mountains in North Carolina.
Base Cations
Likens et al. (1996) Approximately linear increasing relationship between concentrations of base cations and S042~+ N03~ concentrations in Hubbard Brook streams from 1964 to
1969, then a reversal in 1970 and a decreasing trend up to 1994.
Lawrence et al. Decreasing concentrations of base cations at a rate that exceeded decreases in concentrations of S042~+ NCr in Catskill Mountain streams from 1984 to 1997.
(1998)
Acid Neutralizing Capacity
Sullivan et al. Model simulations suggest that none of the lakes in the Adirondack target lake population were chronically acidic or had ANC less than 20 |jeq/L under
(2006) preindustrial conditions. By 1980, there were hundreds of such lakes.
Stoddard et al. Tendencies during the 1990s toward increasing surface water Gran ANC in all glaciated regions of the Eastern U.S. (i.e., New England, Adirondacks, Northern
(2003) Appalachian Plateau) and Upper Midwest; and decreasing Gran ANC in the Ridge/Blue Ridge province.
Surface Water Aluminum
Gensemer and Found that organically complex aluminum (organic Al) can occur in surface waters as a result of natural soil and hydrologic processes, but this form of Al is not
Playle (1999) harmful to aquatic life.
Gensemer and Demonstrated that inorganic Al has been found to be toxic to plant and animal species throughout the food web.
Playle (1999)
Baldigo et al. 20% mortality of young-of-the-year brook trout during a 30-day period with a median inorganic Al concentration of 2 |_imol/L. 90% mortality occurs over 30 days
(2007) with a median inorganic Al concentration of 4.0 |jmol/L.
Lawrence et al. 49 of 195 streams (25%) in the Western Adirondack region had inorganic Al concentrations above 2.0 |jM during August base flow.
(2007)
_pH
Haines and Baker pH values for biological effects have been summarized for a variety of aquatic organisms; common threshold values for pH are 5.0, 5.5, and 6.0.
(1986)
Baker etal.
(1990a)
Charles et al. 25 to 35% of the Adirondack lakes larger than 4 ha have acidified since preindustrial time. An estimated 80% of the Adirondack lakes that had pH less than 5.2 in
(1989) the mid-1980s were inferred to have experienced large declines in pH and ANC since the previous century. About 30 to 45% of the lakes with pH between 5.2 and
Sullivan et al. 6.0 have also acidified.
(1990)
Gumming etal.
(1992;, 1994)
Gbondo-Tugbawa PnET-BGC modeling at Hubbard Brook estimated that past stream pH (circa 1850) was probably about 6.3, compared with just above 5.0 in 2000.
et al. (2002)
Stoddard et al. An increase in the hydrogen ion concentration of Appalachian streams (0.08 |jeq/L/yr) and Upper Midwest lakes (0.01 |jeq/L/yr) was reported. No trends were
(2003) found in New England lakes or Appalachian streams in this study.
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4.2.2.1. Biological Effects
1 The evidence is sufficient to infer a causal relationship between acidifying deposition and
2 Changes in aquatic biota. The strongest evidence for a causal relationship comes from studies of aquatic
3 systems exposed to elevated levels of acidifying deposition that support fewer species of fishes,
4 macroinvertebrates, and diatoms (Section 3.2.3.2). Although there are few studies of the response of
5 higher trophic levels to pH changes resulting from acidifying deposition, piscivorous birds are known to
6 be affected by acidifying deposition. Consistent and coherent evidence from multiple species and studies
7 shows that acidification can result in the loss of acid-sensitive species, and more species are lost with
8 greater acidification. Biological effects are linked to changes in water chemistry including ANC, Al, and
9 pH. Decreases in ANC and pH and increases in inorganic Al concentration contribute to declines in
10 taxonomic richness of zooplankton, macroinvertebrates, and fish. Chemical changes can occur over both
11 long- and short-term time scales, with additional effects on biological systems. Short-term (hours or days)
12 episodic changes in water chemistry can have biological effects, including reduced fish condition factor,
13 changes in species composition, and declines in aquatic species richness across multiple taxa, ecosystems
14 and regions.
Species
15 • Logistic regression modeling showed that the occurrence of two piscivorous birds (common
16 loons and common mergansers) is positively related to the pH of lakes in the Algoma region of
17 Ontario. Model estimates suggested that the number of lakes projected to be suitable for
18 supporting breeding pairs and broods of these bird species increased with increasing lake pH.
19 • High levels of acidification (to pH values below 5) virtually eliminate all mayflies,
20 crustaceans, and mollusks from some streams.
21 "In general, populations of salmonid fish are not found at pH levels less than 5.0, and
22 smallmouth bass (Micropterus dolomieu) populations are usually not found at pH values less
23 than 5.5 to 5.2.
24 • Twenty percent mortality of young-of-year brook trout were documented during a 30-day
25 period with a median inorganic Al concentration of 2 (imol/L (Baldigo, 2007). It was estimated
26 that 90% mortality would occur over 30 days with a median inorganic Al concentration of 4.0
27 (imol/L.
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Community
1 Community-level effects were observed in the Adirondacks and Shenandoah National Park where
2 taxonomic richness is lower in lakes and streams having low ANC and pH.
3 • Decreases in pH and increases in inorganic Al concentrations have reduced the species
4 richness of plankton, invertebrates, and fish in acid-affected surface waters.
5 "In the Adirondacks, a positive relationship exists between the pH and ANC in lakes and the
6 number of fish species present in those lakes. A number of synoptic surveys indicated
7 suggested loss of species diversity and absence of several sensitive fish species in the pH range
8 of 5.0 to 6.0 (Section 3.2.4.4).
9 "In Shenandoah National Park streams, the fish species richness decreased with decreasing
10 stream ANC. On average, richness is lower by one fish species for every 21 (ieq/L decrease in
11 ANC (Section 3.2.4.5).
12 • Short-term episodes of acidification are particularly harmful to aquatic biota. Early life stages
13 are more sensitive to acidic conditions than the young-of-the-year, yearlings, and adults.
14 Episodes are most likely to affect biota if the water had pre-episode pH above 5.5 and
15 minimum pH during the episode of less than 5.0. Episodic acidification can have long-term
16 adverse effects on fish populations.
Regional Vulnerability and Sensitivity
17 The effects of acidifying deposition have been assessed by several national surveys since the
18 1980s, including the National Surface Water Survey and the National Stream Survey in the mid-1980s,
19 the Wadeable Streams Assessment (WSA) in 2004, EPA's Long-Term Monitoring program beginning in
20 1983, and Temporally Integrated Monitoring of Ecosystems probability surveys beginning in 1991. These
21 surveys indicate that acidifying deposition has acidified surface waters in the southwestern Adirondacks,
22 New England uplands, low-silica eastern Upper Midwest, forested Mid-Atlantic Highlands, and Mid-
23 Atlantic Coastal Plain (Section 3.2.4.2).
24 The Northeast and mountainous West of the U.S. contain many of the surface waters most sensitive
25 to acidification. Levels of acidifying deposition in the West are low in most areas, acidic surface waters
26 are rare, and the extent of chronic surface water acidification that has occurred to date has been very
27 limited. However, episodic acidification does occur. In both the West and the Northeast, the most severe
28 acidification of surface waters generally occurs during spring snowmelt. On average, spring ANC values
29 of acid-sensitive surface waters in New England, the Adirondacks, and the northern Appalachian Plateau
30 were about 30 (ieq/L lower than summer values between 1990 and 2000. This implies that lakes and
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1 streams in these regions would need to recover to chronic ANC values above -30 (ieq/L or more before
2 they could be expected not to experience acidic episodes (Stoddard, 2003).
3 In 2004, the EPA conducted a national WSA survey and found that, overall, less than 1% of the
4 1,020,000 km of stream in the target population was acidic due to acidifying deposition. No acidic
5 streams were observed in the Mountainous West, Xeric West, Upper Midwest, Northern Plains, Southern
6 Plains, or Temperate Plains ecoregions. Streams that were acidified from acidifying deposition were
7 found in the Northern Appalachians (2.8% of 96,100 km of stream), and the Southern Appalachians (1.8%
8 of 287,000 km). Very low ANC (0 to 25 (ieq/L) streams, likely exposed to episodic acidification, were
9 found in the Northern Appalachians (2.7% of 96,100 km of stream), the Coastal Plain (6.3% of 119,000
10 km), and the Mountainous West (0.6% of 204,000 km). Stream surveys were not conducted in the
11 Adirondacks or New England.
12 It is important to address surface water recovery in response to reduced acidifying deposition over
13 the past few decades. The following summarizes recent regional trends in acidification recovery.
14 • About one-quarter to one-third of the lakes and streams that were chronically acidic during
15 summer in the 1980s were no longer chronically acidic in 2000. These improvements in water
16 chemistry are largely attributed to decreases in S deposition. Throughout the Northeastern US,
17 the concentration of SO42 in surface waters has decreased substantially in response to
18 decreased emissions and atmospheric deposition of S. Decreased SO42 concentrations of a
19 third or more in lakes and streams have been commonly observed.
20 • EPA's monitoring programs suggest that the following important changes in lake and stream
21 chemistry occurred during the 1990s in response to S and N emissions reductions: (1) SO42
22 concentration decreased as a percentage of total ion concentration in surface waters; 2) ANC
23 increased modestly in three of the five regions included in surface water efforts; 3) dissolved
24 organic carbon and associated natural organic acidity increased, perhaps toward more natural
25 pre-disturbance concentrations, as surface water acidity contributed from acidifying deposition
26 decreased; and (4) inorganic, and potentially toxic, Al concentrations appear to have decreased
27 slightly in some sensitive aquatic systems.
4.3. N Nutrient Enrichment
28 The majority of experiments that quantify the effects of N deposition levels on ecosystems (see
29 Table 4-4 and Table 3-25) either evaluate N addition or N gradients. Fertilization experiments often use
30 NFLjNOs or (NFL^SC^ additions and assume that these additions would simulate a wide spectra of
31 atmospheric reactive N (Nr) deposition scenarios. Deposition gradient experiments often do not
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1 adequately identify all components of Nr deposition. Therefore, publications addressing N additions or
2 deposition gradients often do not include data on all components of Nr.
3 In terrestrial ecosystems, Nr deposition causes accelerated growth rates in some species, altered
4 competitive interactions among species, and nutrient imbalances, ultimately affecting biodiversity. The
5 onset of these effects may be as low as 3 kg/ha/yr. N utilization is so fundamental to plant growth and
6 nutrient cycling that there are myriad linkages among atmospheric N deposition, other pollutants (e.g., O3,
7 S, CO2), environmental stressors (e.g., drought, pests, pathogens), and disturbance regimes (e.g., fire and
8 wind-throw).
9 In aquatic ecosystems, reactive N that is both leached from the soil and directly deposited can
10 pollute groundwater and surface water. This causes alteration of the diatom community at levels as low as
11 1.5 kg/ha/yr. Reactive N also promotes eutrophication in coastal ecosystems, ultimately reducing
12 biodiversity, in part due to depletion of O2 needed for the survival of many species of aquatic plants and
13 animals.
14 Factors that govern the sensitivity of terrestrial ecosystems to nutrient enrichment from N
15 deposition include the degree of N-limitation, rates and form of N deposition, elevation, climate, species
16 composition, length of growing season, and soil N retention capacity. Critical N loads are described for
17 European ecosystems (see Section 3.3.7.1). Little is known about the extent and distribution of the
18 terrestrial ecosystems in the U.S. that are most sensitive to the effects of nutrient enrichment from
19 atmospheric N deposition.
4.3.1. Terrestrial
20 The 1993 AQCD concluded that N deposition may cause large effects on terrestrial systems, and
21 the effect of N deposition should consider total N in the system rather than just the oxidized forms. N
22 deposited to an N-deficient ecosystem is generally expected to increase growth. If N is deposited on an
23 ecosystem with adequate N or saturated with N, NO3 leaching is expected to occur. Much of the
24 information presented in the 1993 document was based on results from studies of forest systems. N
25 saturation was known to be more common in older forests. Disturbances such as fire and harvesting
26 would push ecosystems to a state of lower N saturation. Fertilization was known to increase growth in N-
27 deficient forests in the short-term, but little was known about long-term effects of N fertilization and the
28 differential growth effects on various tree and herbaceous plant species. It was known that plants do not
29 necessarily benefit from added N. When N increases to the point that it is no longer limiting, deficiencies
30 of other nutrients can occur (Aber, 1989).
31 A few studies documented the deleterious effects of excessive N on tree growth and grassland
32 biodiversity. Alpine ecosystems were identified as particularly sensitive to N deposition. The studies
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1 published since the 1993 assessment generally support its conclusions, provide more information on the
2 long-term effects of N deposition, and expand the knowledge of effects to include more ecosystem and
3 species. A summary of quantified deposition and associated ecological effect is given in Table 4-4.
4.3.1.1. Biogeochemical effects
N cycling
4 The evidence is sufficient to infer a causal relationship between Nr deposition and the
5 alteration of biogeochemical cycling of N in terrestrial ecosystems (Section 3.3.2.1). The main source
6 of new Nr to ecosystems is atmospheric deposition. Nr deposition disrupts the nutrient balance of
7 ecosystem with numerous biogeochemical effects. The chemical indicators that are typically measured
8 include: nitrate leaching, C:N ratio, N mineralization, nitrification, denitrification, foliar N concentration,
9 and soil water NOs and NH4+ levels. Values for these indicators that represent a threshold for the onset of
10 a related biogeochemical or biological effect are also summarized. Note that N saturation does not need to
11 occur to cause adverse effects on terrestrial ecosystems. However, in some regions N saturation is a
12 plausible mechanism of net nitrification and associated NO3 leaching in drainage water. Substantial
13 leaching of NO3 from forest soils to streamwater can acidify downstream waters (see Section 3.2) and
14 deplete soils of nutrient base cations, especially Ca and Mg (Likens, 1998).
15 • Two of the primary indicators of N enrichment in forested watersheds are the leaching of NO3
16 in soil drainage waters and the export of NO3 in stream water, especially during the growing
17 season (Stoddard, 1994).
18 "In general, there is consistency and coherence among experimental evidence from field studies
19 that show NO3 leaching can be induced by chronic addition of N (Edwards, 2002; Kahl, 1999;
20 Norton, 1999; Kahl, 1993; Peterjohn, 1996). Several N-exclusion studies in Europe
21 demonstrated that decreases in N deposition produced immediate reductions in NO3 leaching
22 from forest stands (Gundersen, 1998; Quist, 1999).
23 • In upland forested areas in the U.S., most N received in atmospheric deposition is retained in
24 soil, and lesser amounts (7-16%) are retained in plant biomass (Nadelhoffer et al., 1999).
25 Several different data compilations indicate consistent and coherent results that found that 80%
26 to 100% of N deposition is retained or denitrified within terrestrial ecosystems that receive less
27 than about 8-10 kg N/ha/yr (Dise, 1995; Sullivan, 2000; MacDonald, 2002; Aber, 2003;
28 Kristensen, 2004).
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1 • Aber et al. (2003) found that surface water NO3 concentrations exceeded 1 (ieq/L in
2 watersheds receiving about 9 to 13 kg N/ha/yr of atmospheric N deposition. The lakes and
3 streams found to have high NO3 concentration were those receiving N deposition above this
4 range, but responses were variable among those receiving high N deposition. Above this range,
5 mean NO3 export increased linearly with increasing deposition at a rate of 0.85 kg NO3 kg
6 N/ha/yr for every 1 kg N/ha/yr increase in deposition, although there was considerable
7 variability in N retention among watersheds at higher rates of deposition (Aber, 2003).
8 • In the west, mixed conifer forests and chaparral watersheds with high smog exposure in the
9 Los Angeles Air Basin also are N-saturated and exhibit the highest stream water NO3
10 concentrations documented within wildlands in North America (Bytnerowicz, 1996) (Fenn,
11 1998). In the mixed conifer forests of the Sierra Nevada and San Bernardino mountains, the
12 critical load for increased NO3 leaching is calculated at 17 kg N/ha/yr.
13 • Activities or disturbances such as logging or fire that export large quantities of N from the site
14 alter future N availability and site propensity to achieve N saturation (c.f,, Chanasyk, 2003)
C cycling
15 The evidence is sufficient to infer a causal relationship between Nr deposition and the
16 alteration of biogeochemical cycling of C in terrestrial ecosystems (Section 3.3.3.1). The most
17 extensive evidence on the interactions between N deposition and C cycling is available for forest
18 ecosystems. Experimental N addition studies show a range of responses in terms of tree mortality and
19 productivity. In general, moderate to high additions of N lead to either no significant change in growth
20 rates or transient growth increases (generally at deposition rates lower than 10 kg N/ha/yr), followed by
21 increased mortality, especially at higher rates of fertilization (see Section 3.3.3.1).
22 Due to the complexity of interactions between the N and C cycling, the effects of N on C budgets
23 (quantified input and output of C to the ecosystem) are variable. Regional trends in NEP of forests have
24 been documented through models based on gradient studies (Magnani, 2007). There have been critiques
25 of the method and the magnitude of these reported effects (Sutton, 2008). N addition was found to slightly
26 increase ecosystem C in a meta-analysis that examined the effects of N fertilization ranging from 25.5 to
27 200 kg N/ha/yr on forest ecosystem C content (see Section 3.3.3.1). In the Western U.S., atmospheric N
28 deposition has been shown to cause increased litter accumulation and carbon storage in above-ground
29 woody biomass, which in turn may lead to increased susceptibility to more severe fires (Fenn, 2003).
30 Less is known regarding the effects of Nr deposition on C budgets of non-forest ecosystem. A meta-
31 analysis, including 16 observations from 9 publications, conducted to evaluate the relationship between N
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1 addition ranging from 16 to 320 kg N/ha/yr and C sequestration of non-forest ecosystems showed that N
2 addition has no significant effect on net ecosystem exchange of non-forest ecosystems.
3 N deposition also affects the patterns of C allocation because most growth occurs above ground.
4 This increases the shoot-to-root ratio, which can be detrimental to the plant because of decreased
5 resistance to environmental stressors, such as drought and windthrow (Minnich, 1995; Fangmeier, 1994;
6 Krupa, 2003; Braun, 2003).
N20 and CH4 flux
7 The evidence is sufficient to infer a causal relationship between Nr deposition and the
8 alteration of biogeochemical flux of N20 in terrestrial ecosystems (Section 3.3.4.2). Terrestrial soil is
9 the largest source of N2O, accounting for 60% of global emission (John, 2002). In a meta-analysis of 80
10 observations of terrestrial ecosystems with different N forms (NH4+, NO3 , NH4NO3, and urea) and
11 addition rates (10 to 562 kg N/ha/yr), N addition resulted in a two-fold increase in N2O emission
12 imbalance. There were no quantitative results for other effects. The response of N2O emission to N
13 addition for coniferous forest, deciduous forest and grasslands was significant (see Section 3.3.4.2).
14 The evidence is sufficient to infer a causal relationship between Nr deposition and the
15 alteration of biogeochemical flux of Cm in terrestrial ecosystems (Section 3.3.4.1). Non-flooded
16 upland soil is the largest biological sink for atmospheric CH4, consuming about 6% of the atmospheric
17 CH4 (Le mer and Roger 2001). A meta-analysis was performed on a data set of 41 observations including
18 four forms of N (NH4+, NO3 , NH4NO3 and urea) and the addition rates ranging from 10 to 560 kg
19 N/ha/yr. The results indicated that N addition reduced CH4 uptake, but this inhibition was significant only
20 for coniferous and deciduous forests (see Section 3.3.4.1).
4.3.1.2. Species richness, composition and biodiversity
21 The evidence is sufficient to infer a causal relationship between Nr deposition on the
22 alteration of species richness, species composition and biodiversity in terrestrial ecosystems. The
23 most sensitive terrestrial taxa are lichens. Empirical evidence indicates that lichens in the U.S. are
24 adversely affected by deposition levels as low as 3/ha/yr. Alpine ecosystem are also sensitive to N
25 deposition, changes in an individual species (Carex rupestris) were estimated to occur at deposition levels
26 near 4 kg N/ha/yr and modeling indicates that deposition levels near 10 kg N/ha/yr alter plant community
27 assemblages. A summary of N deposition effects are presented below, organized by ecosystem type.
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Lichens
1 There is consistent and coherent evidence to support that lichen communities are affected by
2 current levels of N deposition. Sensitive lichens are frequently used as indicators of air pollution and
3 atmospheric deposition levels. In addition to being good subjects for biomonitoring, they constitute
4 important components of the forest ecosystem by contributing to biodiversity, regulating nutrient and
5 hydrological cycles, and providing habitat elements for wildlife (McCune, 1997); see Section 3.3.5).
6 Lichens that contain a cyanobacterial photobiont appear to be more sensitive to adverse effects
7 from atmospheric N deposition than most other lichens (Hallingback, 1991; Hallingback, 1992). The
8 decline of lichens containing cyanobacteria in parts of northern Europe has been associated with N
9 deposition in the range of 5 to 10 kg N/ha/yr (Bobbink, 1998). In the U.S., lichen species are negatively
10 affected by N inputs as low as 3 to 8 kg/ha/yr (Fenn, 2003).
11 In the San Bernardino Mountains, California, up to 50% of lichen species that occurred in the
12 region in the early 1900s have disappeared (Nash, 1999; Fenn, 2003). The calculated critical load for
13 lichen communities in mixed conifer forests in California is 3.1 kg/ha/yr. (Fenn, 2008).
14 The Pacific Northwest retains widespread populations of pollution-sensitive lichens (Fenn, 2003).
15 In this area, lichen communities are beginning to show evidence of changes in response to increased N
16 pollution, including decreased distribution of sensitive lichen taxa, and their replacement with
17 nitrophilous species (Geiser, 2007).
Alpine Plant Communities
18 Consistent and coherent evidence indicates that alpine plant communities are among the most
19 sensitive terrestrial communities to nutrient-enrichment from atmospheric N deposition. Factors that
20 govern the sensitivity of alpine tundra to N deposition include low rates of primary production, short
21 growing season, low temperature, and wide variation in moisture availability in the alpine environment
22 (Bowman, 1994; Bowman, 1993; Fisk, 1998; Bowman, 2001). Alpine herbaceous plants are generally
23 considered N-limited and changes in alpine plant productivity and species composition have been noted in
24 response to increased N inputs (Vitousek, 1997; Bowman, 2006). Alpine plant communities have also
25 developed under conditions of low nutrient supply, in part because soil-forming processes are poorly
26 developed, and this also contributes to their N-sensitivity.
27 The Western U.S. contains extensive land areas that receive low levels of atmospheric N
28 deposition, interspersed with hot spots of relatively higher N deposition downwind of large metropolitan
29 centers and agricultural areas. Some of these areas of higher N deposition occur at high elevation. Results
30 from several studies suggest that the capacity of Rocky Mountain alpine catchments to sequester N is
31 exceeded at input levels less than 10 kg N/ha/yr (Baron, 1994; Williams, 1999). Changes in an individual
32 species (Carex rupestris) were estimated to occur at deposition levels near 4 kg N/ha/yr. Changes in the
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1 plant community, based on the first axis of a detrended correspondence analysis, were estimated to occur
2 at deposition levels near 10 kg N/ha/yr. (Bowman, 2006). In comparison, critical loads for alpine plant
3 communities in Europe are between 5-15 kg N/ha/yr (Bobbink, 1998).
Grasslands
4 Consistent and coherent evidence for reduced biodiversity in response to N deposition is reported
5 for grasslands in the U.S. and Europe. Clark and Tilman (2008) recently evaluated the effects of chronic
6 N addition over 23 years in Minnesota prairie-like successional grasslands and in native savanna
7 grassland and found species numbers declined at the lowest addition level (10 kg N/ha/yr added to 6 kg
8 N/ha/yr of ambient deposition). The authors calculated the critical load as 5.3 kg N/ha/yr with an inverse
9 prediction interval of 1.3-9.8 kg N/ha/yr.
10 Change in species composition in response to N deposition has been observed regardless of soil
11 type in European grasslands. Such effects have been found in calcareous, neutral, and acidic
12 environments, species-rich heaths, and montane-subalpine grasslands (Stevens, 2004; Bobbink, 1992;
13 Bobbink, 1998). A transect of 68 acid grasslands across Great Britain, covering the lower range of
14 ambient annual N deposition (5 to 35 kg N/ha/yr), indicates that long-term, chronic N deposition
15 significantly reduced plant species richness. Species richness declined as a linear function of the rate of
16 inorganic N deposition, with a reduction of one species per 4 m2 quadrat for every 2.5 kg N/ha/yr of
17 chronic N deposition. The empirical critical loads for ten different types of grasslands in Europe ranged
18 between 10 and 30 kg N/ha/yr, above which changes in species composition were documented to occur
19 (Achermann, 2003) (See Section 3.3.7.1).
20 In the San Francisco Bay area of California, which receives N deposition levels of 10 to 15 kg
21 N/ha/yr, exotic nitrophilous grasses have displaced native grass species, likely due to greater N
22 availability from deposition and from the cessation of grazing, which previously exported N out of the
23 system (Fenn, 2003).
Forests
24 In this assessment, forests include overstory trees, understory herbaceous plants and mycorrhizae.
25 There is very little information on the effect of N deposition on the biodiversity of overstory trees within
26 forests in the U.S. This is due to the long life span and slow growth of trees which makes such changes
27 difficult to detect. A study of the northern edge of the Great Plains (southern Canada), showed that
28 increasing N deposition over a range of 8 to 22 kg N/ha/yr to aspen-dominated forest and boreal forest
29 caused an increase forest expansion into the grasslands (Kochy, 2001). More is known concerning the
30 effects of N deposition on understory herbs, however most of the evidence is from Europe, where
31 alteration of species composition is known to occur over the gradient of N deposition ranging from 6 to
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1 20 kg N/ha/yr for acid tolerant species and a decline in the cover and abundance of ericaceous shrubs
2 along a gradient from 3 to 12 kg N/ha/yr (Gilliam, 2006). Loss of mycorrhizal diversity was recorded for
3 Alaskan coniferous forest over a gradient of 1 to 20 kg N/ha/yr, and addition studies from oak savanna
4 ecosystems in Minnesota show N addition decreases mycorrhizal diversity (Avis, 2003).
Arid and Semi-arid Grasslands
5 Alteration to arid and semi-arid plant communities resulting from experimental N fertilization have
6 been reported in the Colorado Plateau, Joshua Tree National Park in California, and the coastal sage scrub
7 community (CSS) of Southern California.
8 Results from several lines of evidence showed (1) increased biomass of non-native plant species
9 over native species, (2) decreased soil moisture under some conditions, and (3) increased fire risk where
10 dense grasses replaced shrub cover.
11 In some areas of the CSS of Southern California, dry N deposition may be upwards of 30 kg
12 N/ha/yr (Bytnerowicz, 1996). Native shrub and forb seedlings in this plant community are unable to
13 compete with dense stands of exotic grasses, and thus are gradually replaced by the grasses, especially
14 following disturbances such as fire (Eliason, 1997; Yoshida, 2001; Cione, 2002). The coastal sage shrub
15 community in California has been declining in land area and in shrub density for the past 60 years and is
16 being replaced in many areas by Mediterranean annual grasses (Allen, 1998; Padgett, 1999; Padgett,
17 1999). N deposition is considered apossible cause or contributor to this ecosystem alteration.
18 Egerton-Warburton and Allen (2000) discerned a shift in arbuscular mycorrhizal community
19 composition with decreased species richness and diversity along a deposition gradient (2 to 57 (ig N/g as
20 soil NO3 ). These shifts in mycorrhizal fungal communities may facilitate replacement of native plant
21 communities by Mediterranean annual grasslands in CSS.
22 Several lines of evidence suggest that Nr deposition may be contributing to greater fuel loads and
23 thus altering the fire cycle in a variety of ecosystem types (Fenn, 2003). Invasive grasses, which can be
24 favored by high N deposition, promote a rapid fire cycle in many locations (D'Antonio, 1992). The
25 increased productivity of flammable understory grasses increases the spread of fire and has been
26 hypothesized as one mechanism for the recent conversion of CSS to grassland in California (Minnich,
27 1998).
Deserts
28 Consistent and coherent evidence that N fertilization alters desert plant communities has
29 been reported in the Chihuahuan Desert, Jordana Basin, Mojave Desert, and the Great Basin.
30 N additions stimulate plant growth and cause the observed invasion of some exotic plant species and
31 associated changes in ecosystem function, especially where water supply is adequate. There is little
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1 evidence evaluating the effects of ambient deposition gradients. However there are numerous field
2 experiments that evaluate N addition levels ranging from 10-100 kg N/ha/yr. Deposition rates in the
3 Southwestern U.S. vary from a low of 1-4 kg N/ha/yr to as high as 30-90 kg N/ha/yr downwind of major
4 urban and agricultural areas (Fenn, 2003; Fenn, 2003). For example, parts of the Sonoran desert in and
5 around Phoenix, Arizona, receive between 7.5 and 30 kg N/ha/yr (Nilles, 2001).
6 Increased grass biomass has also been associated with increased fire frequency in the Mojave
7 Desert (Brooks, 1999; Brooks, 2002; Brooks, 2004). This effect is most pronounced at higher elevation,
8 probably because the increased precipitation at higher elevation contributes to greater grass productivity.
9 In some cases, precipitation may be a more limiting factor than N to plant growth in deserts. Increased N
10 supply at lower elevation in arid lands can only increase productivity to the point at which moisture
11 limitation prevents additional growth. It is observed that fire was relatively rare in the Mojave Desert until
12 the past two decades, but now fire occurs frequently in areas that have experienced invasion of exotic
13 grasses (Brooks, 1999).
4.3.2. Transitional
14 Anaerobic conditions of water-logged soils in wetlands result in slow decomposition of organic
15 matter and accelerated denitrification. N cycles of two types of wetland, ombrotrophic bogs and coastal
16 salt marshes, were discussed in 1993 AQCD for NOX. Ombrotrophic bogs are generally considered the
17 most sensitive to atmospheric N deposition because they are nutrient poor, with a closed N cycle in which
18 the predominant source of N is rainfall. The 1993 AQCD found that the three main ecological effects of N
19 deposition on wetland ecosystem are: (1) increasing primary production; 2) modifying microbial
20 processes; and (3) reducing biodiversity and altering ecosystem structure. The studies since 1993 support
21 and extend the conclusions in the 1993 AQCD, especially with regard to the effects of N deposition on
22 species diversity.
4.3.2.1. Biogeochemical Effects
23 The contribution of N deposition to total N load varies among wetland types. The more N
24 deposition accounts for total N load the more vulnerable the ecosystem is to N deposition For example, in
25 freshwater wetland ecosystems atmospheric deposition is the main source of N to the ecosystem while N
26 deposition is a minor source of N in many saltwater wetlands.
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N Cycling
1 The evidence is sufficient to infer a causal relationship between Nr deposition and the
2 alteration Of biogeOChemical Cycling Of N (Section 3.3.2.2). Nr deposition contributes to total N load in
3 wetlands. The chemical indicators that are typically measured include: nitrate leaching, N mineralization,
4 and denitrification. N dynamics in wetland ecosystems are variable in time and with type of wetland and
5 environmental factors, especially water availability (Howarth, 1996). A wetland can act as a source, sink,
6 or transformer of atmospherically deposited N (Devito, 1989) and these functions can vary with season
7 and with hydrological conditions. Vegetation type, physiography, local hydrology, and climate all play
8 significant roles in determining source/sink N dynamics in wetlands (Devito, 1989; Koerselman, 1993;
9 Arheimer, 1994; Mitchell, 1996).
10 N mineralization has been shown to increase with N addition, and this can cause an increase in
11 wetland N export to adjacent surface water (Groffman, 1994). In general, leaching losses of NO3 in
12 water derived directly from wetlands are often small because of NO3 removal by denitrification.
13 Elevated N inputs to wetlands will often increase the rate of denitrification (Dierberg, 1983) (Broderick,
14 1988; Cooper, 1990). This process limits environmental effects that are typically associated with
15 increased N supply to soils and drainage waters; however it increases the contribution of greenhouse
16 gasses to the atmosphere. Denitrification appears to be negligible in wetland environments that are
17 typically nutrient (including N) poor, such as some bogs and fens (Morris, 1991).
C Cycling
18 The evidence is sufficient to infer a causal relationship between Nr deposition and the
19 alteration Of biogeOChemical Cycling Of C. In numerous freshwater wetland ecosystems atmospheric
20 deposition is the main source of N to the ecosystem. In contrast, N deposition is a minor source of N in
21 many saltwater wetlands.
22 A meta-analysis that included wetlands with other non-forest ecosystems indicated no effect of N
23 deposition on overall net ecosystem exchange of carbon (See Section 3.3.3). In contrast, above and below
24 ground carbon exchange processes are affected by N deposition. In Sphagnum -dominated ombrotrophic
25 bogs, higher N deposition resulted in higher tissue N concentrations and greater NPP (Aldous, 2002;
26 Aldous, 2002), but lower bulk density. A study of 23 ombrotrophic peatlands in Canada with deposition
27 levels ranging from 2.7 to 8.1 kg N/ha/yr showed peat accumulation increases linearly with N deposition,
28 however in recent years this rate has begun to slow indicating limited capacity for N to stimulate
29 accumulation (Moore, 2004). Soil respiration has been studied in European countries under a natural
30 gradient of atmospheric N deposition from 2 to 20 kg/ha/yr. They found enhanced decomposition rates for
31 material accumulated under higher atmospheric N supplies resulted in higher carbon dioxide.
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1 In intertidal wetlands, primary production of plant species typically increases with N addition,
2 however most studies apply fertilizer treatments that are several orders of magnitude larger than
3 atmospheric deposition (Mendelssohn, 1979; Wigand, 2003; Tyler, 2007; Darby, 2008). N fertilization
4 experiments in salt marsh ecosystems show biomass stimulation from 6 to 413% with application rates
5 ranging from 7 to 3120 kg N/ha/yr (EPA, 1993).
6 Increases in biomass linked to N deposition, have also increased evapotranspiration (Howes, 1986).
7 This changed the soil water balance of water and may influence the direction of plant community
8 succession. Model results suggest 7 kg N/ha/yr is the threshold for an oligotrophic bog to become a
9 mesotrophic bog dominated by trees, as found in the 1993 NOx AQCD.
N20 and CH4 flux
10 The evidence is sufficient to infer a causal relationship between Nr deposition and the
11 alteration Of N20 flux in wetland ecosystems. In a meta-analysis, 19 observations, with different N
12 forms (NH4+, NO3 , NH4NO3, and urea) and addition rates (15.4 to 300 kg N/ha/yr), were included to
13 evaluate the effect of N addition on wetland N2O emission (see Section 3.3.4.2). The results indicated that
14 N addition increased the production of N2O by about two-fold.
15 The evidence is sufficient to infer a causal relationship between Nr deposition and the
16 alteration Of CH4 flux in wetland ecosystems. Wetlands are generally net sources of CH4, but some
17 wetlands can be net sinks depending on environmental conditions such as drainage and vegetation (Crill,
18 1994; Saarnio, 2003). A meta-analysis was performed on a data set of 17 observations to assess the effects
19 of N additions on CH4 fluxes (see Section 3.3.4.1). This data set included four forms of N (NH4+, NO3 ,
20 NH4NO3 and urea) and the addition rates ranged from 30 to 240 N kg N/ha/yr (see Section 3.3.4.1). The
21 results indicated that N addition increased CH4 production from the wetlands, but had no significant effect
22 on CH4 uptake of wetlands.
4.3.2.2. Biological Effects
23 The evidence is sufficient to infer a causal relationship between Nr deposition and the
24 alteration of species richness, species composition and biodiversity in wetland ecosystems
25 (Section 3.3.5.2). Wetlands contain a high number of rare plant species (Moore, 1989; EPA, 1993;
26 Bedford, 2003). Excess N deposition can cause shifts in wetland community composition by altering
27 competitive relationships among species, which potentially leads to effects such as decreasing
28 biodiversity, increasing non-native species establishment and increasing the risk of extinction for sensitive
29 and rare species.
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1 Changes in plant species composition caused by elevated atmospheric N deposition haven been
2 demonstrated in Europe. (Achermann, 2003) (see Table 3-24) evaluated the empirical evidence linking N
3 deposition to wetland species composition and biodiversity to develop the following critical loads: raised
4 and blanket bogs = 5-10 kg N/ha/yr, poor fens = 10-20 kg N/ha/yr, rich fens 15-35 kg N/ha/yr, mountain
5 rich fens 15-25 kg N/ha/yr, pioneer and low-mid salt marshes 30-40 kg N/ha/yr.
6 Some wetland species are adapted to low-N environments. High levels of atmospheric N deposition
7 increase the risk of decline and extinction of those sensitive species. In general these include the genus
8 Isoetes sp., of which three species are federally endangered; insectivorous plants like the endangered
9 green pitcher Sarracenia oreophila; and the genus Sphagnum, of which there are 15 species are listed as
10 endangered by Eastern U.S. states. Roundleaf sundew (Drosera rotundifolia) is also susceptible to
11 elevated atmospheric N deposition (Redbo-Torstensson, 1994). This plant is native to, and broadly
12 distributed across, the U.S. and is federally listed as endangered in Illinois and Iowa, threatened in
13 Tennessee, and vulnerable in New York (http://plants.usda.gov/). In the U.S., Sarracenia purpurea can be
14 used as a biological indicator of local N deposition in some locations (Ellison, 2002). S. purpurea is a
15 perennial pitcher plant native to Canada and the Eastern U.S. that grows in nutrient-poor peatlands and is
16 sensitive to changes in N availability. Based on the annual demographic rates, a non stationary matrix
17 model forecasted that the extinction risk within the next 100 years increased substantially if N deposition
18 rate increase (1-4.7%) from the rate of 4.5-6.8 kg N/ha/yr (Gotelli, 2002).
4.3.2.3. Regional vulnerability and sensitivity
19 • Bogs are among the most sensitive wetland ecosystems to N deposition. In the U.S., peat-
20 forming bogs are most common in areas that were glaciated, especially in portions of the
21 Northeast and Upper Midwest (EPA, 1993).
22 • N input and output rates of fens are intermediate between bogs and coastal marshes. N
23 deposition could drastically change species composition, increase primary productivity and
24 increase methane emission in fens (Pauli, 2002; Aerts, 1999).
25 • Atmospheric N inputs contribute to eutrophication problems in coastal marshes at many
26 locations. However marine inputs of N are typically higher than direct atmospheric input.
27 Models of sources of N to wetland ecosystems are not yet available.
28 • The effect of N deposition on wetland ecosystems depends on the fraction of rainfall in its total
29 water budget and the sensitivity to N deposition was suggested as: bogs (70-100%
30 rainfall) > fens (55-83% rainfall) > intertidal wetlands (10-20% rainfall) (Morris, 1991).
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4.3.3. Freshwater Aquatic
1 General conclusions of the 1993 AQCD for NOx indicated that productivity of fresh water is
2 usually limited by the availability of phosphorus (P). However, it was noted that high inputs of P from
3 anthropogenic sources could lead to N limitation occurring. The ratio of dissolved organic N to total
4 phosphorous (molar basis) was used as an indicator for nutrient limitation, with values less than 2
5 indicating N limitation. The proportions of N limited lakes show wide regional variation: Pacific
6 Northwest (27.7%), Upper Midwest (19%), Northeast (5%), Southeast (2.5%). All sub regions of the West
7 contain substantial numbers of N limited lakes.
4.3.3.1. Biogeochemical Effects
N Cycling
8 The evidence is sufficient to infer a causal relationship between Nr deposition and the
9 alteration of biogeochemical cycling of N in freshwater aquatic ecosystems (Section 3.3.2.3). Nr
10 deposition is the main source of N to headwater streams, lower order streams and high elevation lakes.
11 The predominant chemical indicator is NO3 concentration in surface waters. Recent evidence documents
12 examples of lakes and streams that are limited by N and show symptoms of eutrophication in response to
13 N addition. Elevated surface water NO3 concentrations occur in both the Eastern and Western U.S.
C Cycling
14 The evidence is sufficient to infer a causal relationship between Nr deposition and the
15 alteration of biogeochemical cycling of C in freshwater aquatic ecosystems (Section 3.3.3.3). if
16 growth of the autotrophic community of a freshwater stream is N-limited, then N addition will stimulate
17 C-capture via photosynthesis often altering the C cycle. Moreover, a freshwater lake or stream must be
18 N-limited in order to be sensitive to N-mediated eutrophication. There are many examples of fresh waters
19 that are N-limited or N and P co-limited (Elser, 1990; Fenn, 2003; Tank, 2003; Bergstrom, 2006;
20 Bergstrom, 2005; e.g.,, Baron, 2006) (See Annex C). (Bergstrom, 2006) concluded that the eutrophication
21 caused by inorganic N deposition indicates that phytoplankton biomass in the majority of lakes in the
22 northern hemisphere is limited by N in their natural state.
23 Numerous studies investigate the relationship between N concentration of freshwater and primary
24 productivity (reported as chlorophyll a, NPP, or an index such as the lake chemistry ratio of DIN:TP) and
25 atmospheric Nr deposition. Typically N addition experiments of lake and stream bioassays in which N
26 was added to waters in field or laboratory in order to measure the response are conducted. A meta-analysis
27 of enrichment bioassays in 62 freshwater lakes of North America found algal growth enhancement from
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1 N amendments to be common in slightly less than half the studies (Elser, 1990). Gradient studies of
2 undisturbed northern temperate, mountain, or boreal lakes that receive low levels of atmospheric N
3 deposition found strong relationships between N-limitation and productivity where N deposition was low,
4 and P and N+P limitations where N deposition was higher (Fenn, 2003; Bergstrom, 2006; Bergstrom,
5 2005). One such study in Sweden found, the lowest productivity occurred at sites where wet N deposition
6 was about 1.3 kg N/ha/yr; increasing productivity occurred at greater than 2.2 kg N/ha/yr (Bergstrom,
7 2005).
8 Overall, productivity of many freshwater ecosystems is currently limited by the availability of N.
9 European and North American lakes may have been N-limited before human-caused disturbance, and
10 remote lakes may have remained N-limited until slight increases in atmospheric N deposition brought
11 about an increase in phytoplankton and periphyton biomass and induced P limitation.
4.3.3.2. Biological Effects
12 The evidence is sufficient to infer a causal relationship between Nr deposition and the
13 alteration of species richness, species composition and biodiversity in freshwater aquatic
14 ecosystems (Section 3.3.5.3). Increased N deposition can cause a shift in community composition and
15 reduce algal biodiversity. Elevated N deposition results in changes in algal species composition,
16 especially in sensitive oligotrophic lakes.
17 In the West, a hindcasting exercise determined that the change in Rocky Mountain National Park
18 lake algae that occurred between 1850 and 1964 was associated with an increase in wet N deposition that
19 was only about 1.5 kg N/ha (Baron, 2006). Similar changes inferred from lake sediment cores of the
20 Beartooth Mountains of Wyoming also occurred at about 1.5 kg N/ha deposition (Saros, 2003).
21 Some freshwater algae are particularly sensitive to added nutrient N and experience shifts in
22 community composition and biodiversity with increased N deposition. For example, two species of
23 diatom (a group of algae), Asterionella formosa and Fragilaria crotonensis, now dominate the flora of at
24 least several alpine and montane Rocky Mountain lakes and sharp increases have occurred in Lake Tahoe
25 (Interlandi, 1998; Baron, 2000; Wolfe, 2001; Wolfe, 2003; Saros, 2003; Saros, 2005). The timing of this
26 shift has varied, with changes beginning in the 1950s in the southern Rocky Mountains and in the 1970s
27 or later in the central Rocky Mountains. These species are opportunistic algae that have been observed to
28 respond rapidly to disturbance and slight nutrient enrichment in many parts of the world.
29 Extremely high NO3 concentrations can have direct adverse effects on fish, invertebrates and
30 amphibians, but the concentrations required to elicit such effects are typically more than 30 times higher
31 than those that would commonly be attributable to atmospheric deposition. For example, mortality of
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1 rainbow trout eggs and fry occurred after 30-day incubations in concentrations greater than 79 (ig N/L;
2 adverse effects on amphibians and insects occur at even higher concentrations.
4.3.3.3. Regional Vulnerability and Sensitivity
3 Eutrophication effects on freshwater ecosystems from atmospheric deposition of N are of greatest
4 concern in lakes and streams that have very low productivity and nutrient levels and that are located in the
5 most undisturbed areas.
6 • In the Western U.S., high-elevation lakes are considered the most sensitive aquatic ecosystems
7 to N deposition. Some examples include the Snowy Range in Wyoming, the Sierra Nevada
8 Mountains, and Lake Tahoe in California, and the Colorado Front Range.
9 • The most severe eutrophication from N deposition effects are expected downwind of major
10 urban and agricultural centers.
4.3.4. Estuarine Aquatic
11 The 1993 AQCD for NOX concluded that the primary N nutrient addition effect on aquatic
12 ecosystems is eutrophication of estuarine and near-coastal marine waters, which results in an increase of
13 algal biomass and changes in community composition. Studies published since 1996 generally support the
14 conclusions of 1993 AQCD. The data for estimating the contribution of N deposition to the nutrient
15 budget of aquatic ecosystems were very sparse and mainly limited to the Chesapeake Bay before 1993.
16 The contribution of N deposition to estuarine eutrophication is now better understood in the Chesapeake
17 Bay and other estuaries.
18 A recent national assessment of eutrophic conditions in estuaries found that 65% of the assessed
19 systems had moderate to high overall eutrophic conditions and generally received the greatest N loads
20 from all sources, including atmospheric and land-based sources (Bricker, 2007). Estuarine and coastal
21 marine ecosystems experience a range of ecological problems associated with nutrient enrichment.
22 Because the productivity of estuarine and near shore marine ecosystems is generally limited by the
23 availability of Nr, excessive contribution of Nr from sources of water and air pollution can contribute to
24 eutrophication.
4.3.4.1. Biogeochemical effects
25 A recent national assessment of eutrophic conditions in estuaries found that 65% of the assessed
26 systems had moderate to high overall eutrophic conditions and generally received the greatest N loads
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1 from all sources, including atmospheric and land-based sources (Bricker, 2007). Estuarine and coastal
2 marine ecosystems experience a range of ecological problems associated with nutrient enrichment.
3 Because the productivity of estuarine and near shore marine ecosystems is generally limited by the
4 availability of Nr, excessive contribution of Nr from sources of water and air pollution can contribute to
5 eutrophication.
N Cycling
6 The evidence is sufficient to infer a causal relationship between Nr deposition and the
7 biogeochemical Cycling Of N (Section 3.3.2.4). N from atmospheric deposition is estimated to comprise
8 10% to 40% of the total input of N to many coastal estuaries, and could be higher for some. Atmospheric
9 N loads to great waters and estuaries in the U.S. are estimated to range from 2 to 8% for Guadalupe Bay,
10 TX on the lowest end to -72% for the Catherines-Sapelo estuary, GA (Castro, 2003) on the highest. At
11 Chesapeake Bay, where N and S deposition and ecological effects have been extensively studied, total
12 atmospheric deposition of atmospheric NO3 is estimated to contribute from 20% to 30% of total N and
13 14% of the NH4 loadings to the Bay.
14 Estimates of total N loadings to estuaries, or to other large-scale elements in the landscape are
15 computed using measurements of wet and dry N deposition where these are available and interpolated
16 with or without a set of air quality model predictions. Direct atmospheric inputs (directly to the water
17 surface) of reactive N to coastal waters are essentially equal to or greater than those contained in riverine
18 flow in the absence of deposition and may contribute from 20 to > 50% of external N loadings to these
19 systems: 11, 5.6, and 5.6 kg N/ha for the Northeast Atlantic coast of the U.S., the Southeast Atlantic coast
20 of the U.S., and the U.S. Eastern Gulf of Mexico, respectively.
21 It is unknown if atmospheric deposition alone is sufficient to cause eutrophication. In general,
22 estuaries tend to be N-limited, and many currently receive high levels of N input from human activities to
23 cause eutrophication (Vitousek, 1991; Howarth, 1996). The most widespread chemical indicator of
24 eutrophication is dissolved O2.
C Cycling
25 The evidence is sufficient to infer a causal relationship between Nr deposition and alteration
26 to the biogeochemical Cycling Of C (Section 3.3.3.4). Estuaries and coastal waters tend to be N-limited
27 and are therefore inherently sensitive to increased atmospheric N loading (D'Elia, 1986; Howarth, 2006).
28 This is at least partly because denitrification by microbes found in estuarine and marine sediments
29 releases much of the added N inputs back into the atmosphere (Vitousek, 1997). However, other limiting
30 factors occur in some locations and during some seasons. Levels of N limitations are affected by seasonal
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1 patterns. N-limited conditions are likely to be found during the peak of annual productivity in the
2 summer.
3 Excess N inputs will affect the Si:N ratio in water. If the Si:N ratio decreases below about 1, the
4 marine food web structure would be expected to change, with decreasing diatom-to-zooplankton-to-
5 higher tropic level ratios and increasing abundance of flagellated algae.
4.3.4.2. Biological Effects
6 The evidence is sufficient to infer a causal relationship between Nr deposition and the
7 alteration of species richness, species composition and biodiversity in estuarine ecosystems
8 (Section 3.3.5.4). Increased N deposition can cause shifts in community composition, reduced
9 hypolimnetic DO, reduced biodiversity, and mortality of submerged aquatic vegetation. The form of
10 deposited N can significantly affect phytoplankton community composition in estuarine and marine
11 environments. Small diatoms are more efficient in using NO3 than NH4+. Increasing NH4+ deposition
12 relative to NO3 in the Eastern U.S. favors small diatoms at the expense of large diatoms. This alters the
13 foundation of the food web. Submerged aquatic vegetation is important to the quality of estuarine
14 ecosystem habitats because it provides habitat for a variety of aquatic organisms, absorbs excess nutrients,
15 and traps sediments. Nutrient enrichment is the major driving factor contributing to declines in submerged
16 aquatic vegetation coverage. The Mid-Atlantic region is the most heavily impacted area in terms of
17 moderate or high loss of submerged aquatic vegetation due to eutrophication. Indicators to assess the
18 eutrophic condition of estuarine and coastal waters are given in the following table:
Table 4-3. Indicators of estuarine eutrophication.
Primary Symptom Description
Chlorophyll a Excess N input will stimulate primary productivity and chlorophyll a concentration indicates a
phytoplankton biomass
Macroalgal Abundance Macroalgal blooms were moderate or high for half of the nation's assessed estuaries (Bricker, 2007).
Macroalgal blooms can cause the loss of important submerged aquatic vegetation by blocking sunlight.
Dissolved 02 Dissolved 02 concentration decreases with increasing algal abundance under elevated N, because
microbes consume 02 as they decompose dead algae. Increased atmospheric N deposition could
stimulate the development of hypoxic or anoxic zones. The northern Gulf of Mexico is the largest
documented zone of hypoxic coastal water in U.S.
Nuisance/Toxic Algal Blooms Excess N input can cause nuisance or toxic algal blooms, which release toxins in the water that can
poison aquatic animals and threaten human health. About one third of the nation's assessed estuary
systems exhibited a moderate or high symptom expression for nuisance or toxic algae (Bricker, 2007).
Source: Bricker etal. (2007).
19
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4.3.4.3. Regional Vulnerability and Sensitivity
1 The most eutrophic estuaries were generally those that had large watershed-to-estuarine surface
2 area, high human population density, high rainfall and runoff, low dilution, and low flushing rates
3 (Bricker, 2007). The national estuary condition assessment conducted by Bricker et al. (2007) found the
4 most impacted estuaries occurred in the mid-Atlantic region and the estuaries with the lowest symptoms
5 of eutrophication were in the North Atlantic. Other regions had mixtures of low, moderate, and high
6 degree of eutrophication. The regional assessment results from the report of Bricker et al. (2007) are
7 summarized in Section 3.3.8.
8 The Chesapeake Bay is the largest estuary in U.S. Its watershed covers 64,299 square miles and the
9 surface area of the bay and its major tributaries is 4,479 square miles (Pyzik, 1982). The Chesapeake Bay
10 is perhaps the best-documented case study in the U.S. of the effects of human activities on estuarine
11 eutrophication. Recent studies (Boyer, 2002; Howarth, 2007) indicated that atmospheric deposition makes
12 a substantial contribution (about 25%) to the overall N budget of Chesapeake Bay. Human disturbances,
13 such as landscape changes, have exacerbated the negative impacts of N deposition by reducing N removal
14 and retention in the upper watershed region. Anthropogenic N inputs have substantially altered the trophic
15 condition of Chesapeake Bay over the last 50 to 100 years. Symptoms of eutrophication in the bay
16 include high algal production, low biodiversity, and large hypoxia and anoxia zones. Submerged aquatic
17 vegetation was once abundant in Chesapeake Bay, covering about 200,000 acres along the shallows and
18 shorelines. Increased nutrient inputs caused submerged aquatic vegetation declines since the mid-1960s
19 and had fallen to about 38,000 acres by 1984. Eutrophication has been implicated in declines and
20 disappearance of striped bass (Morone saxatilis) and blue crab (Callinectes sapidus) in Chesapeake Bay.
4.4. Direct Phytotoxic Effects
4.4.1. S02
21 The evidence is sufficient to infer a causal relationship between exposure to 862 and injury to
22 vegetation. The current secondary standard for SC>2 is a 3-h avg of 0.50 ppm, which is designed to
23 protect vegetation against acute foliar injury. There has been limited research on acute foliar injury since
24 the last SO2 AQCD and there is no clear evidence of acute foliar injury below the level of the current
25 standard.
26 Effects on growth and yield of vegetation are associated with increased SC>2 exposure concentration
27 and time of exposure. The 1982 SC>2 AQCD concluded that more definitive concentration-response
28 studies were needed before useable exposure metrics could be identified. Because of falling ambient SC>2
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1 concentrations and focus on O3 vegetation effects research, few studies been published that would help
2 develop a metric and define levels of concern for effects of SO2 on growth and productivity of vegetation.
3 The few new studies published support a causal link between exposure to SO2 and reduced vegetation
4 growth. However, the majority of these studies have been performed outside the US and at levels well
5 above ambient concentrations observed in the US.
4.4.2. NO, N02 and PAN
6 The evidence is sufficient to infer a causal relationship between exposure to NO, NCh and
7 PAN and injury to vegetation. It is well known that in sufficient concentrations NO, NO2 and PAN can
8 have phytotoxic effects on plants through decreasing photosynthesis and induction of visible foliar injury
9 (EPA, 1993). However, the 1993 NOX AQCD concluded that concentrations of NO, NO2 and PAN in the
10 atmosphere are rarely high enough to have phytotoxic effects on vegetation (EPA, 1993). Since the 1993
11 AQCD, very little new research has been done on these phytotoxic effects at concentrations currently
12 observed in the US.
4.4.3. HN03
13 The evidence is sufficient to infer a causal relationship between exposure to HNOs and
14 changes to vegetation. Experimental exposure of HNOs resulted in damage to the leaf cuticle of pine
15 and oak seedlings which may predispose those plants to other stressors such as drought, pathogens and
16 other air pollutants (Bytnerowicz, 1998; Bytnerowicz, 1998b). Several lines of evidence, including
17 transplant and controlled exposure studies, indicate that HNOs is likely contributing to the decline in
18 lichen species in the Los Angles basin (Boonpragob, 1991; Riddell, 2008; Nash, 1999). Current
19 deposition of HNOs is contributing to N saturation of some ecosystems close to sources of photochemical
20 smog (Fenn, 1998) such as the mixed conifer forests of the Los Angeles basin mountain (Bytnerowicz,
21 1999b; Bytnerowicz, 1999a).
4.5. Mercury Methylation
22 The evidence is sufficient to infer a causal relationship between S deposition and increased
23 methylation of Hg, in aquatic environments where the value of other factors is within adequate
24 range for methylation (Section 3.4.1.4). The main agent of Hg methylation is SO42 -reducing-bacteria,
25 and experimental evidence from laboratory to mesocosm scales has established that only inconsequential
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1 amounts of MeHg can be produced in the absence of SO42 . These experimental results are highly
2 coherent with one another, and with observational studies at larger scales. Mechanistic links have been
3 established between changes in SO42 and methylation of Hg, and changes in the amount of SO42 present
4 have been shown to be followed by commensurate changes in MeHg. Quantification of this response in
5 natural settings has proved difficult because of the presence of multiple interacting factors: in aquatic
6 environments where SO42 and Hg are present, the amount of MeHg produced has been shown to vary
7 with O2 content, temperature, pH, and supply of labile organic carbon. In watersheds where no effect of
8 changes in SO42 deposition have been recorded on methylation of Hg, one or several of those interacting
9 factors were not present in the amounts required for methylation to occur. Watersheds with conditions
10 known to be conducive to Hg methylation can be found in the Northeastern U.S. and Southeastern
11 Canada, but studies in other regions with significant Hg accumulation in biota have not been as extensive.
12 Mercury is a highly neurotoxic contaminant, and enters the food web in the methylated form.
13 MeHg is then concentrated in higher trophic levels, including fish eaten by humans, with undesirable
14 consequences for affected species, and for populations that consume large amounts offish. Once MeHg is
15 present, other variables influence how much of it accumulates in fish. Current evidence indicates that
16 increased S deposition very likely results in MeHg accumulation in fish.
Table 4-4. Summary of N deposition levels and corresponding ecological effects.
Type of Ecosys-
tem
U.S.
Coastal sage
scrub
Ambient N Deposi-
tion1
(kg N/ha/yr)
Level = 9.8 to 35 kg
N/ha/yr
N Additions
(kg N/ha/yr)
60 kg N/ha/yr; as
NH4N03 between
Biological and Chemical Effects
N addition caused a shift in arbuscular
mycorrhizal community composition
Study Site
California
Study Species Reference
Egerton-
Warburton
Coastal sage
scrub
Coastal sage
scrub
Desert
Species = nitrate as
(HN03/N03)
Measure = referred to
Padgett etal. (1999)
Level = not reported
Species = not reported
Measure = not reported
Jan. and March
1994,1995, 1996 in
two 30 kg N/ha/yr
applications
10ug/gNH4N03;
Or50ug/gN03-;
Or50ug/gNH4+
Level = Up to 30 kg 60 kg N/ha/yr; as
N/ha/yr NHUNOs
Species = not reported
Measure = referred to
Bytnerowiczetal. 1987;
Fenn et al. 2003b
Level = 30 kg N/ha/yr Two additions of 16
Species = not reported kg N/ha/yr, one as
Measure = referred to NHkNCb and one as
Bytnerowicz et al. 1987 an NPK treatment
with decreased species richness and
diversity promoting a shift from shrub
to grasslands
No evidence, that decline in native
coastal sage scrub and increase in
exotic grass is due to mycorrhizal
response to increased NCr
Soil inoculum from high N deposition
site caused native shrub growth
depression likely due to mycorrhizal
fungi response. Growth of exotic grass
may be promoted by soil inoculum
from high N deposition site.
N addition increased biomass of non-
native plants by -54%, decreased
native species biomass by about
-39%
Southern
California
Western
Riverside
County Multis-
pecies Reserve;
University of
California
Riverside
Botanical
Gardens
Mojave desert
Artemisia californica (native); Bromus
madritenis spp. Rubens (exotic)
Artemisia californica (native); Bromus
madritenis spp. Rubens (exotic)
and Allen
(2000)
Yoshida and
Allen (2001)
Siguenza et
al.(2006)
Creosote bush (Larrea tridentate),
invasive grasses Bromus madritensis
spp. Rubens, and Schismus spp.; and
the forb Erodium deuterium
Brooks (2003)
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Type of Ecosys-
tem
Desert
Forest
Forest
Forest
Forest (conifer-
ous)
Forest (mixed-
chaparral, hard-
wood, coniferous)
Forest (conifer-
ous)
Forest (chaparral)
Forest (conifer)
Ambient N Deposi-
tion1
(kg N/ha/yr)
Level = 1.71 to 2.45 kg
N/ha/yr
Species = NH4N03;
Measure = field study
for 16yrswith network
of six funnel precipita-
tion collectors
Level = 3.6 and 3.5 kg
N/ha/yr on east slope;
1 . 1 kg N/ha/yr on west
slope
Species = not reported
Measure = referred to
Williams etal 1998;
NADP 1999; Stottle-
myer etal 1997)
Level = 1-2 kg N/ha/yr
on west slope; 3-5 kg
N/ha/yr on east slope
Species = not reported
Measure = unspecified
Level = 1.2 to 23 kg
N/ha/yr dry dep and 0.8
to 45 kg N/ha/yrwet dep
Species = (for both) =
N03-andNH4+
Measure = various
citations
Level =
2 study sites:
CP= 18.8 kg N/ha/yr
BF= 2.9 kg N/ha/yr
Species = NOf and
NH4+
Measure = ion concen-
trations via liq. ion
chromatography and
colorimetrically via
Technicon TRAACS
800 autoanalyzer
Level = 1 1 to 40 kg
N/ha/yr
Species = NOf and
NH4+
Measure = ion ex-
change resin column
throughfall collectors
(Fenn et al. 2002)
Level = 8 kg N/ha/yr
and 82 kg N/ha/yr
Species = not reported
Measure = referred to
Fenn etal., 2002
Level = 35 kg N/ha/yr
Species = not reported
Measure = taking mean
of two methods (estima-
tion methods using data
in situ and published
data; NADP)
Level = 1.2 to 71.1 kg
N/ha/yr
Species = NOf and
NH4+
Measure = Throughfall
measurements; ion
exchange resin col-
umns (Fenn & Poth
2004)
N Additions
(kg N/ha/yr)
Long term experi-
ment: 100kg N/ha/yr
as granular NH4N 03
to10plots2x/yr
since Dec. 1995;
Single season
experiment: 20 kg
N/ha/yr to 40 plots
once
No addition
No addition
No addition
No addition
No addition
0,50, 150 kg N/ha/yr
annually from 1996
to 2002
No addition
No addition
Biological and Chemical Effects
Long term: increased the cover of
warm season grasses and decreased
the cover of legumes;
Short term: increased N lead to signifi-
cant plant community structure
change, especially in blue and black
grama grassland patch types
East side: low C:N, lignin:N, and high
N:MgandN:P
Increased foliar [N], soil %N,N
mineralization rates, Mg depletion, and
P enriched on East side stands; East
side lakes higher [NOs];
East side had decreased soil organic
horizon C/N and foliar C/N, and
increased foliar N concentration, foliar
N/Mg, foliar N/P and potential net
mineralization; Englemann spruce
forest biogeochemistry altered
N saturation observed at 25-45 kg
N/ha/yr of total inorganic N deposition.
Where N saturation occurred, high
NOr concentrations in streamwater,
soil, leaves; high NO emissions; high
foliar N:P.
Site nearest to urban area (Los Ange-
les) received much more N deposition,
as well as other pollutants (i.e. S
deposition), and received much more
fog, coinciding with much more wet
deposition of N in that site
Ecosystem was N saturated, as
evidenced by high streamwater NOi"
concentration, 151 and 65 ueq/L at
upper and lower ends, respectively, of
Devil Canyon West Fork
DIN export was scale dependent, with
highest export occurring in watersheds
of ~ 1 50-ha. Differences attributed to
temporal asynchrony between N
availability and biological demand
Tree mortality was 9% higher and
beetle activity 50 % higher for unfer-
tilized trees at the high deposition site
compared to the low pollution site.
Tree mortality and beetle activity
increased 8% and 20%, respectively
under highest N fertilization rates at
the low deposition site
Continued high export (~3 kg N/ha/yr)
of NO-f in stream water (15 yr) after
prescribed burn indicates that chapar-
ral ecosystem did not recover N-
retention capabilities after disturbance
Empirical critical load for adverse
impacts on lichen at 3.1 kg N/ha/yr.
Enhanced NOi" leaching calculated
with N deposition above 17 kg N/ha/yr.
Lowered litter C:N and increases foliar
N also observed at highly polluted
sites.
Study Site
Chihuahuan
Desert
Eastern vs.
Western slope
of Continental
D ivied in Rocky
Mtns.
Eastern vs.
Western slope
of Continental
D ivied in Rocky
Mtns.
California - Los
Angeles Air
Basin
San Bernardino
Mountains,
California
San Bernardino
Mountains, CA
San Bernardino
Mountains, CA
San Dimas
Experimental
Forest (40 km
NW of LA), San
Gabriel Moun-
tains, CA
California mixed
conifer forests
Study Species
Blue and black grama (Boute/oua
gracilis and Boute/oua eropoda, re-
spectively)
Englemann spruce
Voniferous forest
Mixed forest- chaparral, hardwood,
coniferous
Ponderosa pine
Chamise (Menostoma fasiculatum),
Ceanothus spp., live oak (Quercus
agrifolia)
Lichens, Ponderosa pine
Reference
Baez
et al.(2007)
Baron et al.,
(2000)
Rueth and
Baron (2002)
Bytnerowicz
and Fenn
(1996)
Fenn et
al.(2000)
Meixner and
Fenn (2004)
Jones etal.
(2004)
Meixner etal.
(2006)
Fenn et al.
(2008)
August 2008
4-35
DRAFT-DO NOT QUOTE OR CITE
-------
Type of Ecosys-
tem
Forest
Forest
Forest
Forest (alpine)
Forest
Forest (maple-
dominated hard-
wood)
Forest
Forest
Forest (herba-
ceous layer)
Forest (ectomy-
corrhiza)
Ambient N Deposi-
tion1
(kg N/ha/yr)
Level = 20 to 35 kg
N/ha/yr
Species = N03-
Measure = field studies
and NuCM, a nutrient
cycling model (Fenn et
al. 1996)
Level = 3.2 to 5.5 kg
N/ha/yr
Species = not reported
Measure = data from
Loch Vale, a
NADP/NTN monitoring
station and Campbell et
al. 2000
Level = 1.7 kg N/ha/yr
Species = not reported
Measure = referred to
Stottlemyer and Tro-
endle 1992, Stottlemyer
etal. 1997
Level = 50 kg N/ha/yr
Measure = referred to
Sievering et al. 1995;
Theodose and Bowman
1997 and Fisk etal.
(1998)
Level = 11. 5 to 25.4 kg
N/ha/yr
Species = N03~ and
NH4+
Measure = both the
TRAACS 800 Auto-
analyzer and vai 16
IMPROVE monitoring
sites and 1 1
NADP/NTN wet dep.
sites
Level = 5 to 8 kg
N/ha/yr
Species = not reported
Measure = NADP 2006
Level = 3.3 to 12.7 kg
N/ha/yr
Species = not reported
Measure = at NERC, 29
Jan 2003, compiled
data sets and used
them in stats model by
Ollinger etal 1993, or
used published values
Level = 5.4 kg N/ha/yr
Species = not reported
Measure = McNulty and
Aber, 1993
Level = 7 kg N/ha/yr
Species = not reported
Measure = Shepard et
al. 1989
Level = 3.5-7.8
kg/ha/yr N in wet
deposition
Species = not reported
Measure = NADP data
N Additions
(kg N/ha/yr)
No addition
25 kg N/ha/yr of
NH4N03
25 kg N/ha/yr of
NH4N03
200 kg N/ha/yr in
1993 and 1994;
No fertilizer in 1995;
100 kg N/ha/yr as
(NH4),S04in1996
and 1997
Nutrient amend-
ments consisted of a
mixture a mixture of
(NH4)JN03and
(NH4),S04fortheN
plots
No addition
30 kg N/ha/yr as
NaN03
No addition
15.7 to 31. 4 kg
N/ha/yr as NFUCI-N
or NaN03-N
14 and 28 kg N/ha/yr
as crystalline
(NH4)2S04
Greenhouse study: 3
rates of N applica-
tions (0, 35,
140 kg/ha).
Biological and Chemical Effects
Areas with higher deposition had
increased N0a~ leaching, increased
soil acidity, and decreased base cation
saturation.
N addition increased N concentration
in foliar and organic soil horizon
N addition doubled N mineralization
rates and stimulated nitrification
N deposition increased plant foliage
productivity but reduced species
richness. The reduction of species is
best explained by changes in soil
chemistry that resulted directly or
indirectly from N additions
Concentrations of N in lichen thallus
were highest at eastern and western-
most sites where N deposition was
highest, implicating both agricultural
(east) and urban (west) sources;
Arbuscular micorrhizal fungal biomass,
storage structures and lipid storage
declined in response to N addition
At deposition levels above approxi-
mately 7-10 kg N/ha/yr, stream N03~
concentration increase with increasing
deposition
Soil C:N and nitrification flux increased
with N deposition
N dep not significantly important with
foliar chemistry
Forest trees in plots receiving < 20 kg
N/ha/yr had high rate of growth initially
followed by a decline, and forests
trees in plots receiving > 25 kg N/ha/yr
showed moderate rates of decline.
N addition decreased herbaceous
cover under hardwoods
Ectomycorrhizal abundance and
richness declined along increasing N
deposition transect under pitch pine.
The decline in richness was signifi-
cantly correlated with the N deposition
rate. In greenhouse study, pine seed-
ling biomass was inversely related to
N addition.
Study Site
Southern
California
Fraser Experi-
mental Forest,
Colorado
Loch Vale
watershed ,
Colorado
Niwot Ridge,
Colorado
Columbia River
Gorge, OR/WA
Northern Michi-
gan
Northeastern
U.S.
Vermont
Adirondack
Park, New York
New Jersey
Pine Barrens
Study Species
Spruce
Old-growth spruce
Alpine tundra: sedge Kobresia myo-
sumides. Acomastylis rossii, Poly-
gonum viviparurn Trifolium. More mesic
tundra-A. rossii and Deschumnpsia
caespitosa. Snow bed- D.caespitosa,
Sibbaldia rocurnbens, Rifolium parryi
Lichens
Maple-dominated hardwood- Sugar
maple (Acer saccharum)
Red spruce
Hardwood
Pitch pine
Reference
Fenn et
al.(2003)
Rueth et al.
(2003)
Rueth
et al.(2003)
Seastedt and
Vaccaro
(2001)
Fenn at
al.(2007)
van Diepen et
al. (2007)
Aber et al.
(2003)
McNulty
etal.(1996)
Hurd et
al.(1998)
Dighton et
al.(2004)
August 2008
4-36
DRAFT-DO NOT QUOTE OR CITE
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Type of Ecosys-
tem
Forest
Forest
Forest (mixed
hardwood)
Forest
(mixedhardwood)
Forest (herba-
ceous layer)
Forest (herba-
ceous layer)
Forest
Forest (herba-
ceous layer)
Ambient N Deposi-
tion1
(kg N/ha/yr)
Level = Wet plus dry
deposition 600 eq ha/yr
for N and 900
equiv. /ha/yr for S
Species: not reported
Measure =Kahl et al.
1999
Level = 17 kg N/ha/yr
Species: not reported
Measure = referred to
Adams etal. 1993
Level = 17 kg N/ha/yr
Species = not reported
Measure = referred to
Adams etal. 1993
Level = 17 kg N/ha/yr
Species = not reported
Measure = referred to
Adams etal. 1993
Level = 17 kg N/ha/yr
Species = not reported
Measure = referred to
Adams etal. 1993
Level = 17 kg N/ha/yr
Species = not reported
Measure = referred to
Adams etal. 1993)
Level = 6.6 to 8 kg
N/ha/yr
Measure = regional
extrapolation from
NADP sites (Ollingeret
al., 1993) and estimates
from Mungeretal.
(1996).
Level = 6.6 to 8 kg
N/ha/yr
Measure = regional
extrapolation from
NADP sites (Ollingeret
al., 1993) and estimates
from Mungeretal.
1996.
N Additions
(kg N/ha/yr)
1800 equiv. -ha-
1-yr-1 for 10yrs
(bimonthly additions
of dry (NH4) S04 at
the rate of 300
equiv. NHU and
S042~/ha per appli-
cation)
35.5 kg N/ha/yrand
40.5 kg S/ha/yr
fertilized annually
(NH4)2S04(17yrs)
35 kg N/ha/yr
(NH4)2S04(16yrs)
35 kg N/ha/yr
(NH4)2S04(12yrs)
35 kg N/ha/yr
(NH4)2S04 (4 yrs)
35 kg N/ha/yr
(NH4)2S04 (6 yrs)
50 and 150kg
N/ha/yr for 15 yrs
50 and 150kg
N/ha/yr
Biological and Chemical Effects
After 1 0 yrs of treatment, basal area
increment of sugar maple was en-
hanced 13 to 104%, whereas red
spruce was not significantly affected.
The increase in sugar maple radial
growth was attributed to a fertilization
effect from the (NH4)2S04 treatment
N addition enhanced growth of black
cherry and yellow poplar during the
first 7 yrs, but reduced growth of these
species in yrs 9 to 12, with no change
in red maple or sweet birch
Possible declining growth vigor in red
maple, and to lesser extent black
cherry and tulip poplar. Observed
interspecific differences in growth and
plant nutrition responses suggest
eventual changes in species composi-
tion under increasing N saturation.
N addition altered response of N-
processing microbes to environmental
factors, becoming less sensitive to
seasonal changes in soil moisture and
temperature
Increased foliar N in overstory tree
species and Viola rotundifolia and
decreased foliar Ca2* and Mg2*, in
response to 4 yrs of treatment.
Nitrification rates were equally high in
soils of all watersheds; Results sup-
port earlier studies that high amounts
of ambient N deposition brought about
N saturation on untreated watersheds
at the Fernow Experimental Forest
no significant impact on the herba-
ceous layer under hardwoods
Mortality of red pine reached 56% in
15 yrs in the pine high N plot, and
biomass accumulation has stopped
altogether. The high N hardwood
stand shows increased aboveground
NPP, but excess N availability and a
severe drought in 1995 contributed to
mortality of 72% of red maple trees by
2002. Species importance and litterfall
patterns were altered in several plots
after 1995. Roots, foliage and wood
have diminished as net sinks for
added N, re-emphasizing the role of
soils in N retention concentrations of
NH4+ plus NOawere not detected in
soil water until the 15th yea r. Losses
of inorganic N remain high in the high
N plots (higher in pines than hard-
woods) and low N plots in the pine
stand also have measurable DIN
losses. Foliar and fine root N concen-
trations are elevated significantly
Following 7 yrs of N additions, density
and biomass of herb layer species had
declined by 80% and 90%
Study Site
Bear Brook,
Maine
Fernow Experi-
mental Forest,
West Virginia
Fernow Experi-
mental Forest,
West Virginia
Fernow Experi-
mental Forest,
West Virginia
Fernow Experi-
mental Forest,
West Virginia
Fernow Experi-
mental Forest,
West Virginia
Harvard Forest
Harvard Forest
Study Species
Sugar maple; red spruce
Mixed hardwood- red oak, red maple,
tulip poplar, black cherry, sweet birch
Mixed hardwood- red oak, red maple,
tulip poplar, black cherry, sweet birch
Mixed hardwood- red oak, red maple,
tulip poplar, black cherry, sweet birch
Viola rotundifolia Michx
Mixed hardwood
Red pine (Pinus resinosa Ait.), black
and red oak (Quercus velutina Q. rubra)
black birch (Betula lenta), red maple
(Acer mbrum), American beech (Fagus
grandifolia) and black cherry (Prunus
serotina)
Understoty of red pine
Reference
Elvir et al.
(2003)
DeWalle
et al.(2006)
May et al.
(2005)
Gilliam et
al.(2001)
Gilliam
etal.(1996)
Gilliam etal.
(2006)
Magi II
et al.(2004)
Rainey et al.
(Rainey,
1999)
August 2008
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DRAFT-DO NOT QUOTE OR CITE
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TypeofEcosys- Ambient N Deposi- NAdditions
tion1
(kg N/ha/yr)
Biological and Chemical Effects Study Site
Study Species
Reference
Forest (mixed
hardwood and
coniferous)
Grassland
Grassland
Grassland
Grassland
Grassland
Level = 6.6 to 8 kg
N/ha/yr
Measure = regional
extrapolation from
NADP sites (Ollingeret
al., 1993) and estimates
from Mungeretal.
1996.
Oak savanna Level = 5.3 kg N/ha/yr 54, and 170 kg
Species = not reported N/ha/yr 16-yr
Measure = NADP 2003 addition of NH4N03
Level = 6 kg N/ha/yr
Species = 58% NH4,
42%N03
Measure = CASTN35
for total inorganic (wet
plus dry) N deposition;
local wet deposition
from the on-site NADP
monitoring station
Level = not reported
Species = not reported
Measure = not reported
Level = 10-15 kg
N/ha/yr in San Jose
grasslands; 4-6 kg
N/ha/yr at peninsula
sites
Species = not reported
Measure = referred to
Blanchard et al, 1996
Level = 10-15 kg
N/ha/yr
Species = not reported
Measure =referred to
Weiss 1999
Level = not reported
Species = not reported
Measure = not reported
Grassland (alpine) Level =5 kg N/ha/yr
Species = not reported
Measure = not reported
50 and 150kg Wood production increased (hard- Harvard Forest
N/ha/yr. wood) and decreased (coniferous)
Calculated N budgets for the first 6 yr
showed extremely high N retention
(85-99%). Of the retained N, 50-83%
appears to be in the long-term, recal-
citrant soil pool.
Foliar N increased 25% (hardwood)
and 67% (coniferous); NOa leaching
increased continuously over 6-yr
study in coniferous forest, but was
unchanged in hardwood forest, most
(85-99%) of added N was retained,
primarily in recalcitrant soil pool
N addition decreased total ectomy- Minnesota
corrhizal fungal diversity by 50% and
changed species composition.
10, 20, 34, 54 or 95 Reduced relative number of species at Cedar Creek
kg N/ha/yr at three, every deposition level. Species num- Biological
five, five, seven and bers were reduced more per unit of Station, Minne-
nine yrs, respec- added N at lower addition rates, sola
lively from 1982 to suggesting that chronic but low-level N
2004 deposition may have a greater impact
on diversity than previously thought.
Chronic (23 yr) N addition (10 kg
N/ha/yr) reduced plant species num-
bers by 17% relative to controls
receiving ambient.
Critical load calculated at 5.3 kg/ha/yr
with an inverse prediction interval of
1.3-9.8 kg N/ha/yr
0, 54.4, and 272 kg Most of the forbs were lost from the Cedar Ck,
N/ha/yr NH4N03 high N plots, and two grass species, P. LTER, Minne-
added twice a yr for pratensis and A. repens, dominated. sola
18 yrs Loss of plant diversity in areas of high
N. Change in composition of soil
microbial community; increased
bacterial and decreased fungal fatty
acid methyl ester activity
No addition Dry N deposition from smog contrib- San Francisco
utes to grass invasion. Soil N limits Bay area,
grass invasion on serpentinitic solids. California
Grazing cattle select grasses over
forbs, and grazing lead to a net export
of N as cattle are removed for slaugh-
ter. Decreased populations of the bay
checkerspot butterfly due to invasion
of grasses after cattle grazing.
No addition N deposition displaced native grass San Francisco
species by exotic nitrophilous grasses. Bay area,
Low levels of soil N normally limit California
grass invasion in serpentinitic soils,
but in ungrazed areas with experi-
mental N fertilization or high N deposi-
tion, the introduced grasses crowd out
many native species.
70 kg N/ha/yr After three yrs, N deposition sup- Jasper Ridge
divided into a liquid pressed plant diversity, forb produc- Biological
Ca(N03)2 pulse with tion, and forb abundance in associa- Preserve,
the first autumn tion with enhanced grass production California
rains and a time-
release pellet
application (Osmo-
cote) in January of
each yr for 3 yrs.
20, 40, 60 kg N/ha/yr N deposition caused changes of plant Colorado Front
for 8 yrs species composition within 3 yrs of the Range
initiation of the experiment and were
significant at all levels of N addition.
Changes in net nitrification were
detectable at levels above 20 kg
N/ha/yr. N addition increased NO-f
leaching and NOi" concentration in
soil water
Red pine (Pinus resinosa Ait.) stand
and mixed hardwood stand
Magilletal.
(1997)
Native oak savannah: buroak (Quercus Avis et al.
macrocarpa Michaux) and pin oak (2003)
(Q.ellipsoidalis E.J. Hill), ectomycorrhi-
zal fungi
Species=rich mixture of native C4 Clark and
grasses and forbs (full list at Tilman (2008)
http://www.cedarcreek.umn.edu/)
ornamental grasses (Schizachyrium
scoparium- Little Bluestem)
Bradley et
al(2006)
Bay checkerspot butterfly/ serpentinitic Weiss (1999)
grasslands
Serpentinitic grasslands
Avena barbata, Bromushordeaceus,
Lolium multiflorum, Avena fatua, and
Bromus diandrus, Anagallis arvensis,
Geranium dissectum, Erodium botrys,
Vicia saliva, Crepis vesicaria
Alpine dry meadows
Fenn
et al.(2003)
Zavaleta
et al.(2003)
Bowman
et al.(2006)
August 2008
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Type of Ecosys-
tem
Grassland
Grassland
Grassland
Lake
Lake
Surface waters
Surface waters
Wetland (fresh-
water)
Coastal-Marine
Ambient N Deposi-
tion1
(kg N/ha/yr)
Level = 5 kg N/ha/yr
Measure =referred to
Sievering et al. 1995;
Theodose and Bowman
1997 and Fisketal.
(1998)
Level = not reported
Species = not reported
Measure = not reported
Level = 5 kg N/ha/yr
Measure =referred to
Sievering et al. 1995;
Theodose and Bowman
1997 and Fisketal.
(1998)
Estimated background
N deposition value of
0.5 kg N/ha/yr in 1900,
from a 19-yr record of
measured values from
Loch Vale (Colorado,
USA; NADP site C098)
the mean wet N-depo-
sition values was
estimated at 1.5kg
N/ha/yr
Level = 2 kg N/ha/yr
Measure = NAPD site
from 1981 through 1996
Level = 8-10 kg N/ha/yr
Measu re = NADP from
1982 to 1994
Level = 4.71 kg N/ha/yr
-200% increase in
NCb" loading from wet
deposition over the
prior decade, increasing
from 8 kg N/ha/yr for
1985-1987 to 16.5 kg
N/ha/yr 1990-1992
Species= not reported
Measure = NADP
Level = 10to14kg
N/ha/yr
N Additions
(kg N/ha/yr)
200 kg N/ha/yr In
1993 and 1994;
No fertilizer in 1995;
100 kg N/ha/yr as
(NH4)2S04in1996
and 1997;
As a mixture of
ammonium nitrate
((NH,)'NO,)and
ammonium SCU2"
((NHJSO,)
0, 10, 40, 70, and
100 kg N/ha/yr for
75 days
25 kg N/ha/yr with
biweekly additions of
2 g of NH4N03
dissolved in deion-
ized water for two
yrs
No addition
N additions in semi-
continuous labora-
tory bioassays of
mixed diatom
assemblages,
No addition
No addition
Hawley Bog: 2
treatments of 0.1 or
LOmgNFU N/L
every 2 weeks
between June 1 and
Sept 30 for 1998,
1999, and 2000
Discontinuously
diluted N limited
cultures, which were
pulsed with
NCrevery 3 days;
Biological and Chemical Effects
Increased plant biomass and tissue N
concentration
N addition increased growth. Native
species gained more height at every
level of N availability compared to
exotics
N addition caused a community shift
towards greater dominance of hair-
grass in wet alpine meadows.
Increasing N deposition caused a shift
in algae community composition
Increasing N shifted diatom species in
alpine lakes.
Chronic N deposition resulted in
increased N leaching.
A shift in from an N-limited system to
an N-saturated system. Many lakes
having (NO-j) concentrations greater
than 10 iequiv/L. Increasing atmos-
pheric deposition of N with elevation is
causing a change from N limitation to
P limitation in the highest-elevation
bristlecone pines
Negative population growth rate of
pitcher plant
Large diatoms became dominant when
nitrate was supplied as the only N
source once in 3 days sinking rate of
the nitrate grown population was
higher (0.12 m/day) than that of the
ammonium grown population (0
m/day). For natural systems, this
implies nitrate-controlled systems
production by larger algae is relatively
high. This may be an explanation for
the higher sedimentation rates of
organic material in coastal or oceanic
upwelling areas as compared to
ammonium-controlled (re generative)
systems. Specific nitrate uptake was
related to cell volume
Study Site
Niwot Ridge,
Colorado
Greenhouse
study
Niwot Ridge,
Colorado
Loch Vale,
Colorado
Baron
(2006)and
Beartooth Lake,
Minnesota
(Saras etal.
(2003)
Rocky Mountain
, Colorado
Eastern U.S./
New England
and Adirondack
lakes
Niwot
Ridge/Green
Lakes, Colorado
Front Range
Hawley Bog
(MA)
Molly Bog (VA)
Study Species
Alpine tundra: sedge Kobresia myo-
sumides. Acomastylis rossii, Poly-
gonum viviparurn Trifolium. More mesic
tundra-A.
Rossii and Deschumnpsia caespitosa.
Snow bed- D. caespitosa, Sibbaldia
procumbens, Trifolium parryi
Two N. American natives, Blue grama,
western wheatgrass, and Four exotics,
cheatgrass, leafy spurge, Canada
thistle, Russian knapweed
Alpine tundra: sedge Kobresia myo-
suroides. Acomastylis rossii, Poly-
gonum viviparurn Trifolium. More mesic
tundra-A.
Rossii and Deschumnpsia caespitosa.
Snow bed- D. caespitosa, Sibbaldia
procumbens, Trifolium
Algae
Diatoms-Stephanodiscusminutulus,
Stephunodiscus niugarue, and
Cyclotella bodanica.
Sarracenia purpurea
Marine phytoplankton (Stolte study)
Reference
Seastedt and
Vaccaro
(2001)
(Lowe, 2002)
Bowman
etal.(1995)
Burns,(2004).
(2006) Saras
et al.(2003)
Interlandi and
Kilham (1998)
Stoddard et
al. (1994)
Williams et
al.(1996)
Gotelli and
Ellison (2002)
Gotelli and
Ellison (2006)
Stolte et al.
(1994)
August 2008
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Type of Ecosys-
tem
Variable
Ambient N Deposi-
tion1
(kg N/ha/yr)
Variable
N Additions
(kg N/ha/yr)
60-120 kg N/ha/yr
(variable range
across 23 different
experiments)
Biological and Chemical Effects Study Site Study Species
Soil CEC and temperature were the Variable Variable
strongest contributors to multivariable
explanation of species richness
response to experimental N addition in
23 studies throughout the U.S. Greater
plant species loss was associated with
lower soil CEC, colder temperature
and larger production increases
Reference
Clark etal.
(2007)
China and Europe
Forest
Level = 3 kg N/ha/yr
Species = not reported
Measure = not reported
30 yrs of annual
additions of NHUNOa
in 3 treatments: N1
and N2 (34 and
68 kg N/ha/yr) and
20 yrs of N3 (108 kg
N/ha/yr), plus a
control
Stimulate stemwood production in all
levels of N addition until 7 yrs into
experiment; thereafter the second and
third treatments (with medium and
high N addition) decreased stemwood
production and the first treatment (the
lowest amount of N addition) contin-
ued to increase stemwood production
Northern Swe-
den
Scots pine
Hogberg
et al.(2006)
Forest (boreal)
Lake
Wetland
Wetland
Wetland
Level = 3-12 kg N/ha/yr
Species = not reported
Measure = MATCH
model of N-deposition
for 1996; surveys in
permanent plots in the
National Forest Inven-
tory
Level =
Wet DIN = 1.3-1 1kg
N/ha/yr
Total N = 1-4 and 9-18
kg N/ha/yr
Species = wet DIN and
total N
Measure = SEPAs use
of MATCH model
Level = 0.2 - 0.3 g
N/m2/a (2 - 3 kg
N/ha/yr)
Species = NH4+and
N03-
Measure = refers to
Ruoho-Airola et al.
1998
Level = not reported
Species = not reported
Measure = not reported
Level = 2 to 20 kg
N/ha/yr
Species = not reported
Measure = national
precipitation monitoring
programs of each
country and refer to the
3 yrs prior to peat
sampling in experiment
No addition
No addition
Cumulative addition
of 3 g N/m2/a (30 kg
N/ha/yr) as NH4N03
on six occasions
during growing
season
240 kg N/ha/yr as
NH4N03 applied in
field experiment
where 3 of 6 plots
received treatment
every 2 weeks for 2
yrs
No addition
N deposition decreased the abun-
dance and cover of ericaceous shrubs
Increased lake concentrations of
inorganic N caused P limitation in
summer and increased eutrophication
with increased lake algal productivity
Increased NH4NOa affected comp. of
moss layer, specifically decreasing
Sphagnum balticum, and caused
decrease in litter and an increase of a
Vaccinium species
N addition increased above ground
biomass and abundance of Deyeucia
angustifolia, stimulated C02 and CH4,
and N20 emissions from D. angustifo-
lia wetlands. N20 emissions signifi-
cantly influenced by N addition.
N deposition increased N increased
microbial activity, C02 emissions, and
dissolved organic carbon release.
Decomposition rates for material
accumulated under higher atmos-
pheric N supplies resulted in higher
carbon dioxide (CCte) emissions and
dissolved organic carbon release
Sweden Vaccinium species (Ericaceae) Strengbom et
al.(2003)
Sweden Bergstrom
et al.(2005)
Eastern Finland Sphagnum sp., Eriophorum vaginatum, Saarnio
Carex pauciflora, Vaccinium oxycoccos, etal. (2003)
Scheuchzeria palustris
Northeast China Deyeucia angustifolia Zhang et al.
(2007)
Nine European Species like Sphagnum Bragazza et
countries al.(2006)
1 Ambient N deposition information is divided into three categories:
Level = deposition rate
Species = chemical species of N that were measured
Measure = source of the deposition data reported (i.e. a monitoring network, reference to another publication, etc.)
August 2008
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Glossary
Acid Neutralizing Capacity (ANC)
A key indicator of the ability of water to neutralize acidifying inputs. This ability depends largely on
associated biogeochemical characteristics.
Acidification
The process of decreasing the pH of a system. Systems that can be acidified by atmospheric deposition of
acidic or acidifying compounds include lakes, streams, and forest soils.
Algae
Photosynthetic, often microscopic and planktonic, organisms occurring in aquatic ecosystems.
Algal bloom
A rapid and extreme increase of an algae population in a lake, river, or ocean.
Alpine
The biogeographic zone made up of slopes above the tree line, and characterized by the presence of rosette-
forming herbaceous plants and low, shrubby, slow-growing woody plants.
Anthropogenic
Resulting from human activity or produced by human beings.
Arid region
An area receiving < 250 mm precipitation per year.
Atmosphere
The gaseous envelope surrounding the Earth. The dry atmosphere consists almost entirely of nitrogen and
O2, together with trace gases including carbon dioxide and ozone.
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. A marked increase in the sensitivity of soils to changes in base saturation occurs at a threshold
of approximately 20%.
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Bioaccumulation
The gradual increase in accumulation of some compounds in organisms with increasingly higher trophic
levels.
Biodiversity
The total diversity of all organisms and ecosystems at various spatial scales (from genes to biomes).
Buffering capacity
The ability of a body of water and its watershed to resist changes in pH.
Carbon sequestration
The process of increasing the carbon content of a reservoir other than the atmosphere.
Catchment
An area that collects and drains rainwater.
Climate
Climate in a narrow sense is usually defined as the 'average weather', or more rigorously, as the statistical
description in terms of the mean and variability of relevant quantities over a period of time ranging from
months to thousands or millions of years. These quantities are most often surface variables such as
temperature, precipitation, and wind. Climate in a wider sense is the state, including a statistical
description, of the climate system. The generally accepted period of time is 30 years, as defined by the
World Meteorological Organization (WMO).
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 oxidized nitrogen (e.g., nitrate or nitrite) to gaseous nitrogen (e.g., N2ON2O or
N2N2), normally accomplished by denitrifying bacteria.
Dry deposition
The movement of gases and particles from the atmosphere to surfaces in the absence of precipitation (e.j
rain or snow) or occult deposition.
Ecological community
An assemblage of populations of different species, interacting with one another
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Ecosystem services
Ecological processes or functions having monetary or non-monetary value to individuals or society at large.
They may be classified as (i) supporting services such as productivity or biodiversity maintenance; ii)
provisioning services such as food, fibre, or fish; iii) regulating services such as climate regulation or
carbon sequestration; and (iv) cultural services such as tourism or spiritual and aesthetic appreciation.
Ecosystem
The interactive system formed from all living organisms and their abiotic (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.
Eutrophication
The enrichment of a waterbody with nutrients, resulting in increased productivity (of algae or aquatic
plants), and sometimes also decreased dissolved O2 levels.
Eutrophy
Eutrophy generally refers to a state of nutrient enrichment, but it is commonly used to refer to condition of
increased algal biomass and productivity, presence of nuisance algal populations, and a decrease in
dissolved O2 concentrations.
Evapotranspiration
The combined process of water evaporation from the Earth's surface and transpiration from vegetation.
Fen
A phase in the development of the natural succession from open lake, through reedbed, fen and carr, to
woodland as the peat develops and its surface rises.
Freshet
A great rise or overflowing of a stream caused by heavy rains or melted snow.
Greenhouse gas
Those atmospheric gasses that absorb and emit radiation emitted by the Earth's surface, the atmosphere,
and clouds within the infrared portion of the spectrum. This property causes the greenhouse effect. Water
vapor (H2OH2O), carbon dioxide (CO2), nitrous oxide (N2ON2O), methane (CH4), and ozone (O3O3) are the
primary greenhouse gases in the Earth's atmosphere. Besides these, the Kyoto Protocol also deals with the
greenhouse gases sulfur hexafluoride (SF6), hydrofluorocarbons (HFCs), and perfluorocarbons (PFCs).
Gross primary production
The total carbon fixed by plants through photosynthesis.
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Heathland
A wide-open landscape dominated by low-growing woody vegetations such as heathers and heathland
grasses. Heathlands generally occur on acidic, nutrient-poor, and often sandy and well-draining soils.
Hypoxic
Events that lead to a deficiency of O2.
Invasive species and invasive alien species
A species aggressively expanding its range and population density into a region in which it is not native,
often through outcompeting or otherwise dominating native species.
Leaching
The removal of soil elements or chemicals by water movement through the soil.
Lowland
In physical geography, lowland is any relatively flat area in the lower levels of regional elevation. The term
can be applied to the landward portion of the upward slope from oceanic depths to continental highlands, to
a region of depression in the interior of a mountainous region, to a plain of denudation, or to any region in
contrast to a highland.
Net ecosystem exchange (NEE)
The net flux of carbon between the land and the atmosphere, typically measured using eddy covariance
techniques. Positive values of NEE usually refer to carbon released to the atmosphere (i.e., a source), and
negative values refer to carbon uptake (i.e., a sink)
Net ecosystem production (NEP)
The difference between net primary production (NPP) and heterotrophic respiration (mostly decomposition
of dead organic matter) of that ecosystem over the same area. NEP = -NEE, with positive values indicating
a sequestration of atmospheric carbon in to biosphere.
Net primary production (NPP)
The gross primary production minus autotrophic respiration, i.e., the sum of metabolic processes for plant
growth and maintenance, over the same area.
Nitrification
The biological oxidation of ammonia to nitrite and then to nitrate. This process is primarily accomplished
by autotrophic nitrifying bacteria that obtain energy by reducing ammonium and/or nitrite to nitrate.
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Nitrogen mineralization
The conversion of organic nitrogen into plant-available inorganic forms (e.g. NH3 or NH4+NH4+) by
microorganisms.
Nitrogen-retention capacity
The length of time that an ecosystem can retain nitrogen in (?) organisms (e.g., plant or microbe) and soil-
organic matter. Nitrogen-retention capacity is highly affected by soil, vegetative, topographic, and land-use
factors.
Nitrogen saturation
The condition in which nitrogen inputs from atmospheric deposition and other sources exceed the
biological requirements of the ecosystem.
Occult deposition
The transmission of gases and particles from the atmosphere to surfaces by fog or mist.
Ombrotrophic bog
An acidic peat-accumulating wetland that is fed by rainwater (instead of groundwater) and, thus, especially
poor in nutrients.
PH
A measure of the relative concentration of hydrogen ions in a solution. The formula for calculating pH is:
pH = ~-logio[H+], where [H+] represents the hydrogen ion concentration in moles per liter. The pH scale
ranges from 0 to 14. A pH of 7 is neutral. A pH less than 7 is acidic and a pH greater than 7 is basic.
Phytoplankton
The plant forms of plankton. Phytoplankton are the dominant plants in the sea and are the basis of the entire
marine food web. These single-celled organisms are the principal agents of photosynthetic carbon fixation
in the ocean.
Primary Production
All forms of production accomplished by plants, also called primary producers. See GPP, NPP, and NEP.
Semi-arid regions
Regions of moderately low rainfall (100- and 250-mm precipitation per year), which are not highly
productive and are usually classified as rangelands.
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Sensitivity
The degree to which a system responds to pollution (e.g. acidification, n-nutrient enrichment, etc.). The
response may be direct (e.g., a change in growth following a change in the mean, range, or variability of N
deposition) or indirect (e.g., changes in growth due to alterations in competitive dynamics between species
or decreased biodiversity , themselves following N deposition).
Streamflow
Water flow within a river channel. A synonym for river discharge.
Surface runoff
The water that travels over the land surface to the nearest surface stream; runoff "of a drainage basin that has
not passed beneath the surface since precipitation.
Throughfall
The precipitation falling through the canopy of a forest and reaching the forest floor.
Trophic level
The position that an organism occupies in a food web.
Tundra
A treeless, level, or gently undulating plain characteristic of the Arctic, sub-Arctic regions and some alpine
regions characterized by low temperatures and short growing seasons.
Upland terrestrial ecosystem
Generally considered to be the ecosystems located at higher elevations directly above riparian zones and
wetlands. Vegetation in an upland ecosystem is not in contact with groundwater or other permanent water
sources.
Valuation
The economic or non-economic 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.
Vulnerability
Susceptibility to degradation or damage from adverse factors or influences. Vulnerability is a function the
exposure and its sensitivity.
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Effects on soils, water, crops, vegetation, man-made 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 (CAA 302(h)).
The transmission of gases and particles from the atmosphere to surfaces by rain or other precipitation.
Those areas that are inundated or saturated by surface or ground water at a frequency and duration
sufficient to support a prevalence of vegetation adapted to water-saturated soil conditions. Wetlands
include swamps, marshes, bogs, and similar areas.
The animal forms of plankton. They consume phytoplankton or other zooplankton.
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