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Walters WW, Pye HOT, Kim H, Hastings MG. Modeling the Oxygen Isotope Anomaly (Δ17O) of Reactive Nitrogen in the Community Multiscale Air Quality Model: Insights into Nitrogen Oxide Chemistry in the Northeastern United States. ACS ES&T AIR 2024; 1:451-463. [PMID: 38884197 PMCID: PMC11151734 DOI: 10.1021/acsestair.3c00056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 04/09/2024] [Accepted: 04/10/2024] [Indexed: 06/18/2024]
Abstract
Atmospheric nitrate, including nitric acid (HNO3), particulate nitrate (pNO3), and organic nitrate (RONO2), is a key atmosphere component with implications for air quality, nutrient deposition, and climate. However, accurately representing atmospheric nitrate concentrations within atmospheric chemistry models is a persistent challenge. A contributing factor to this challenge is the intricate chemical transformations involving HNO3 formation, which can be difficult for models to replicate. Here, we present a novel model framework that utilizes the oxygen stable isotope anomaly (Δ17O) to quantitatively depict ozone (O3) involvement in precursor nitrogen oxidesN O x = N O + N O 2 photochemical cycling and HNO3 formation. This framework has been integrated into the US EPA Community Multiscale Air Quality (CMAQ) modeling system to facilitate a comprehensive assessment of NO x oxidation and HNO3 formation. In application across the northeastern US, the model Δ17O compares well with recently conducted diurnal Δ17O(NO2) and spatiotemporal Δ17O(HNO3) observations, with a root mean square error between model and observations of 2.6 ‰ for Δ17O(HNO3). The model indicates the major formation pathways of annual HNO3 production within the northeastern US are NO+OH (46 %), N2O5 hydrolysis (34 %), and organic nitrate hydrolysis (12 %). This model can evaluate NO x chemistry in CMAQ in future air quality and deposition studies involving reactive nitrogen.
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Affiliation(s)
- Wendell W. Walters
- Department
of Chemistry and Biochemistry, University
of South Carolina, Columbia, South Carolina 29208, United States
- Office
of Research and Development, U.S. Environmental
Protection Agency, Durham, North Carolina 27703, United States
| | - Havala O. T. Pye
- Office
of Research and Development, U.S. Environmental
Protection Agency, Durham, North Carolina 27703, United States
| | - Heejeong Kim
- Department
of Earth, Environment, and Planetary Sciences, Brown University, Providence, Rhode Island 02912, United States
- Institute
at Brown for Environment and Society, Brown
University, Providence, Rhode Island 02912, United States
| | - Meredith G. Hastings
- Department
of Earth, Environment, and Planetary Sciences, Brown University, Providence, Rhode Island 02912, United States
- Institute
at Brown for Environment and Society, Brown
University, Providence, Rhode Island 02912, United States
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2
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Phelan JN, Van Houtven G, Clark CM, Buckley J, Cajka J, Hargrave A, Horn K, Thomas RQ, Sabo RD. Climate change could negate U.S. forest ecosystem service benefits gained through reductions in nitrogen and sulfur deposition. Sci Rep 2024; 14:10767. [PMID: 38730011 PMCID: PMC11087459 DOI: 10.1038/s41598-024-60652-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 04/25/2024] [Indexed: 05/12/2024] Open
Abstract
Climate change and atmospheric deposition of nitrogen (N) and sulfur (S) impact the health and productivity of forests. Here, we explored the potential impacts of these environmental stressors on ecosystem services provided by future forests in the contiguous U.S. We found that all stand-level services benefitted (+ 2.6 to 8.1%) from reductions in N+S deposition, largely attributable to positive responses to reduced S that offset the net negative effects of lower N levels. Sawtimber responded positively (+ 0.5 to 0.6%) to some climate change, but negatively (- 2.4 to - 3.8%) to the most extreme scenarios. Aboveground carbon (C) sequestration and forest diversity were negatively impacted by all modelled changes in climate. Notably, the most extreme climate scenario eliminated gains in all three services achieved through reduced deposition. As individual tree species responded differently to climate change and atmospheric deposition, associated services unique to each species increased or decreased under future scenarios. Our results suggest that climate change should be considered when evaluating the benefits of N and S air pollution policies on the services provided by U.S. forests.
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Affiliation(s)
| | | | - Christopher M Clark
- U.S. Environmental Protection Agency, Office of Research and Development, Washington, DC, USA
| | - John Buckley
- RTI International, 3040 E. Cornwallis Rd., RTP, NC, USA
| | - James Cajka
- RTI International, 3040 E. Cornwallis Rd., RTP, NC, USA
| | - Ashton Hargrave
- U.S. Department of Agriculture, Forest Service, National Forest System Washington Office, Fort Collins, CO, USA
| | - Kevin Horn
- Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute, Blacksburg, VA, USA
| | - R Quinn Thomas
- Department of Forest Resources and Environmental Conservation, Virginia Polytechnic Institute, Blacksburg, VA, USA
- Department of Biological Sciences, Virginia Polytechnic Institute, Blacksburg, VA, USA
| | - Robert D Sabo
- U.S. Environmental Protection Agency, Office of Research and Development, Washington, DC, USA
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3
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Clark CM, Phelan J, Ash J, Buckley J, Cajka J, Horn K, Thomas RQ, Sabo RD. Future climate change effects on US forest composition may offset benefits of reduced atmospheric deposition of N and S. GLOBAL CHANGE BIOLOGY 2023; 29:4793-4810. [PMID: 37417247 PMCID: PMC11166206 DOI: 10.1111/gcb.16817] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 04/26/2023] [Indexed: 07/08/2023]
Abstract
Climate change and atmospheric deposition of nitrogen (N) and sulfur (S) are important drivers of forest demography. Here we apply previously derived growth and survival responses for 94 tree species, representing >90% of the contiguous US forest basal area, to project how changes in mean annual temperature, precipitation, and N and S deposition from 20 different future scenarios may affect forest composition to 2100. We find that under the low climate change scenario (RCP 4.5), reductions in aboveground tree biomass from higher temperatures are roughly offset by increases in aboveground tree biomass from reductions in N and S deposition. However, under the higher climate change scenario (RCP 8.5) the decreases from climate change overwhelm increases from reductions in N and S deposition. These broad trends underlie wide variation among species. We found averaged across temperature scenarios the relative abundance of 60 species were projected to decrease more than 5% and 20 species were projected to increase more than 5%; and reductions of N and S deposition led to a decrease for 13 species and an increase for 40 species. This suggests large shifts in the composition of US forests in the future. Negative climate effects were mostly from elevated temperature and were not offset by scenarios with wetter conditions. We found that by 2100 an estimated 1 billion trees under the RCP 4.5 scenario and 20 billion trees under the RCP 8.5 scenario may be pushed outside the temperature record upon which these relationships were derived. These results may not fully capture future changes in forest composition as several other factors were not included. Overall efforts to reduce atmospheric deposition of N and S will likely be insufficient to overcome climate change impacts on forest demography across much of the United States unless we adhere to the low climate change scenario.
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Affiliation(s)
- Christopher M. Clark
- US Environmental Protection Agency, Office of Research and Development, Center for Public Health and Environmental Assessment, Washington DC
| | | | - Jeremy Ash
- US Department of Agriculture, US Forest Service, Region 8, Ashville, NC
| | | | - James Cajka
- RTI International, Research Triangle Park, NC
| | - Kevin Horn
- Virginia Polytechnical University, Department of Forest Resources and Environmental Conservation, Blacksburg, VA
| | - R. Quinn Thomas
- Virginia Polytechnical University, Department of Forest Resources and Environmental Conservation, Blacksburg, VA
| | - Robert D. Sabo
- US Environmental Protection Agency, Office of Research and Development, Center for Public Health and Environmental Assessment, Washington DC
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4
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Hogrefe C, Bash JO, Pleim JE, Schwede DB, Gilliam RC, Foley KM, Appel KW, Mathur R. An Analysis of CMAQ Gas Phase Dry Deposition over North America Through Grid-Scale and Land-Use Specific Diagnostics in the Context of AQMEII4. ATMOSPHERIC CHEMISTRY AND PHYSICS 2023; 23:8119-8147. [PMID: 37942278 PMCID: PMC10631556 DOI: 10.5194/acp-23-8119-2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
The fourth phase of the Air Quality Model Evaluation International Initiative (AQMEII4) is conducting a diagnostic intercomparison and evaluation of deposition simulated by regional-scale air quality models over North America and Europe. In this study, we analyze annual AQMEII4 simulations performed with the Community Multiscale Air Quality Model (CMAQ) version 5.3.1 over North America. These simulations were configured with both the M3Dry and Surface Tiled Aerosol and Gas Exchange (STAGE) dry deposition schemes available in CMAQ. A comparison of observed and modeled concentrations and wet deposition fluxes shows that the AQMEII4 CMAQ simulations perform similarly to other contemporary regional-scale modeling studies. During summer, M3Dry has higher ozone (O3) deposition velocities (Vd) and lower mixing ratios than STAGE for much of the eastern U.S. while the reverse is the case over eastern Canada and along the West Coast. In contrast, during winter STAGE has higher O3 Vd and lower mixing ratios than M3Dry over most of the southern half of the modeling domain while the reverse is the case for much of the northern U.S. and southern Canada. Analysis of the diagnostic variables defined for the AQMEII4 project, i.e. grid-scale and land-use (LU) specific effective conductances and deposition fluxes for the major dry deposition pathways, reveals generally higher summertime stomatal and wintertime cuticular grid-scale effective conductances for M3Dry and generally higher soil grid-scale effective conductances (for both vegetated and bare soil) for STAGE in both summer and winter. On a domain-wide basis, the stomatal grid-scale effective conductances account for about half of the total O3 Vd during daytime hours in summer for both schemes. Employing LU-specific diagnostics, results show that daytime Vd varies by a factor of 2 between LU categories. Furthermore, M3Dry vs. STAGE differences are most pronounced for the stomatal and vegetated soil pathway for the forest LU categories, with M3Dry estimating larger effective conductances for the stomatal pathway and STAGE estimating larger effective conductances for the vegetated soil pathway for these LU categories. Annual domain total O3 deposition fluxes differ only slightly between M3Dry (74.4 Tg/year) and STAGE (76.2 Tg/yr), but pathway-specific fluxes to individual LU types can vary more substantially on both annual and seasonal scales which would affect estimates of O3 damages to sensitive vegetation. A comparison of two simulations differing only in their LU classification scheme shows that the differences in LU cause seasonal mean O3 mixing ratio differences on the order of 1 ppb across large portions of the domain, with the differences generally largest during summer and in areas characterized by the largest differences in the fractional coverages of the forest, planted/cultivated, and grassland LU categories. These differences are generally smaller than the M3Dry vs. STAGE differences outside the summer season but have a similar magnitude during summer. Results indicate that the deposition impacts of LU differences are caused both by differences in the fractional coverages and spatial distributions of different LU categories as well as the characterization of these categories through variables like surface roughness and vegetation fraction in look-up tables used in the land-surface model and deposition schemes. Overall, the analyses and results presented in this study illustrate how the diagnostic grid-scale and LU-specific dry deposition variables adopted for AQMEII4 can provide insights into similarities and differences between the CMAQ M3Dry and STAGE dry deposition schemes that affect simulated pollutant budgets and ecosystem impacts from atmospheric pollution.
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Affiliation(s)
- Christian Hogrefe
- Center for Environmental Measurement and Modeling, US Environmental Protection Agency, 109 T.W. Alexander Dr., P.O. Box 12055, RTP, NC 27711, USA
| | - Jesse O. Bash
- Center for Environmental Measurement and Modeling, US Environmental Protection Agency, 109 T.W. Alexander Dr., P.O. Box 12055, RTP, NC 27711, USA
| | - Jonathan E. Pleim
- Center for Environmental Measurement and Modeling, US Environmental Protection Agency, 109 T.W. Alexander Dr., P.O. Box 12055, RTP, NC 27711, USA
| | - Donna B. Schwede
- Center for Environmental Measurement and Modeling, US Environmental Protection Agency, 109 T.W. Alexander Dr., P.O. Box 12055, RTP, NC 27711, USA
| | - Robert C. Gilliam
- Center for Environmental Measurement and Modeling, US Environmental Protection Agency, 109 T.W. Alexander Dr., P.O. Box 12055, RTP, NC 27711, USA
| | - Kristen M. Foley
- Center for Environmental Measurement and Modeling, US Environmental Protection Agency, 109 T.W. Alexander Dr., P.O. Box 12055, RTP, NC 27711, USA
| | - K. Wyat Appel
- Center for Environmental Measurement and Modeling, US Environmental Protection Agency, 109 T.W. Alexander Dr., P.O. Box 12055, RTP, NC 27711, USA
| | - Rohit Mathur
- Center for Environmental Measurement and Modeling, US Environmental Protection Agency, 109 T.W. Alexander Dr., P.O. Box 12055, RTP, NC 27711, USA
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Abstract
Atmospheric deposition processes are of primary importance for human health, forests, agricultural lands, aquatic bodies, and ecosystems. South-East Europe is still characterized by numerous hot spots of elevated sulfur deposition, despite the reduction in European emission sources. The purpose of this study is to discuss the results from two chemical transport models and observations for wet and dry depositions of sulfur (S), reduced nitrogen (RDN) and oxidized nitrogen (OXN) in Bulgaria in 2016–2017. The spatial distribution and the domain main deposition values by EMEP MSC-W (model of the MSC-W Centre of the Co-operative Programme for Monitoring and Evaluation of the Long-range Transmissions of Air Pollutants in Europe) and BgCWFS (Bulgarian Chemical Weather Forecast System) demonstrated S wet depositions to be higher than N depositions, and identified a rural area in south-east Bulgaria as a possible hot-spot. The chemical analysis of deposition samples at three sites showed a prevalence of sulfate in the western part of the country, and prevalence of Cl and Na at a coastal site. The comparison between modeled and observed depositions demonstrated that both models captured the prevalence of S wet depositions at all sites. Better performance of BgCWFS with an average absolute value of the normalized mean bias of 16% was found.
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6
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Hood RR, Shenk GW, Dixon RL, Smith SMC, Ball WP, Bash JO, Batiuk R, Boomer K, Brady DC, Cerco C, Claggett P, de Mutsert K, Easton ZM, Elmore AJ, Friedrichs MAM, Harris LA, Ihde TF, Lacher I, Li L, Linker LC, Miller A, Moriarty J, Noe GB, Onyullo G, Rose K, Skalak K, Tian R, Veith TL, Wainger L, Weller D, Zhang YJ. The Chesapeake Bay Program Modeling System: Overview and Recommendations for Future Development. Ecol Modell 2021; 465:1-109635. [PMID: 34675451 PMCID: PMC8525429 DOI: 10.1016/j.ecolmodel.2021.109635] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
The Chesapeake Bay is the largest, most productive, and most biologically diverse estuary in the continental United States providing crucial habitat and natural resources for culturally and economically important species. Pressures from human population growth and associated development and agricultural intensification have led to excessive nutrient and sediment inputs entering the Bay, negatively affecting the health of the Bay ecosystem and the economic services it provides. The Chesapeake Bay Program (CBP) is a unique program formally created in 1983 as a multi-stakeholder partnership to guide and foster restoration of the Chesapeake Bay and its watershed. Since its inception, the CBP Partnership has been developing, updating, and applying a complex linked modeling system of watershed, airshed, and estuary models as a planning tool to inform strategic management decisions and Bay restoration efforts. This paper provides a description of the 2017 CBP Modeling System and the higher trophic level models developed by the NOAA Chesapeake Bay Office, along with specific recommendations that emerged from a 2018 workshop designed to inform future model development. Recommendations highlight the need for simulation of watershed inputs, conditions, processes, and practices at higher resolution to provide improved information to guide local nutrient and sediment management plans. More explicit and extensive modeling of connectivity between watershed landforms and estuary sub-areas, estuarine hydrodynamics, watershed and estuarine water quality, the estuarine-watershed socioecological system, and living resources will be important to broaden and improve characterization of responses to targeted nutrient and sediment load reductions. Finally, the value and importance of maintaining effective collaborations among jurisdictional managers, scientists, modelers, support staff, and stakeholder communities is emphasized. An open collaborative and transparent process has been a key element of successes to date and is vitally important as the CBP Partnership moves forward with modeling system improvements that help stakeholders evolve new knowledge, improve management strategies, and better communicate outcomes.
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Affiliation(s)
- Raleigh R Hood
- Horn Point Laboratory, University of Maryland Center for Environmental Science, P.O. Box 775, Cambridge, MD 21613, USA
| | - Gary W Shenk
- USGS Chesapeake Bay Program Office, 410 Severn Avenue, Suite 109, Annapolis, MD, 21403, USA
| | - Rachel L Dixon
- Chesapeake Research Consortium, 645 Contees Wharf Road, Edgewater, MD 21037, USA
| | - Sean M C Smith
- University of Maine, School of Earth and Climate Sciences, Bryand Global Science Center, Orono, ME 04469, USA
| | - William P Ball
- Chesapeake Research Consortium, 645 Contees Wharf Road, Edgewater, MD 21037, USA
| | - Jesse O Bash
- Environmental Protection Agency, Center for Environmental Measurement and Modeling, 109 T.W. Alexander Drive, Durham, NC 27709, USA
| | - Rich Batiuk
- U.S. Environmental Protection Agency, Chesapeake Bay Program Office, 410 Severn Avenue, Suite 109, Annapolis, MD, 21403, USA
| | - Kathy Boomer
- The Nature Conservancy, 114 South Washington Street, Easton, MD 21601, USA
| | - Damian C Brady
- Darling Marine Center, University of Maine, 193 Clarks Cove Rd, Walpole, ME 04573, USA
| | - Carl Cerco
- #U.S. Army Corps of Engineers Waterways Experiment Station, P.O. Box 631, Vicksburg, MS 39180, USA
| | - Peter Claggett
- USGS Chesapeake Bay Program Office, 410 Severn Avenue, Suite 109, Annapolis, MD, 21403, USA
| | - Kim de Mutsert
- University of Southern Mississippi, Gulf Coast Research Laboratory, 703 East Beach Drive, Ocean Springs, MS 39564, USA
| | | | - Andrew J Elmore
- Appalachian Laboratory, University of Maryland Center for Environmental Science, 301 Braddock Rd, Frostburg, MD 21532, USA
| | - Marjorie A M Friedrichs
- Virginia Institute of Marine Science, William & Mary, 1375 Greate Rd, Gloucester Point, VA 23062, USA
| | - Lora A Harris
- Chesapeake Biological Laboratory, University of Maryland Center for Environmental Science, P.O. Box 38, Solomons, MD 20688, USA
| | - Thomas F Ihde
- Patuxent Environmental & Aquatic Research Laboratory, Morgan State University, 10545 Mackall Road, St. Leonard, MD 20685, USA
| | - Iara Lacher
- Smithsonian Conservation Biology Institute, 1500 Remount Rd, Front Royal, VA 22630 USA
| | - Li Li
- Department of Civil and Environmental Engineering, Penn State University, University Park, PA 16802, USA
| | - Lewis C Linker
- U.S. Environmental Protection Agency, Chesapeake Bay Program Office, 410 Severn Avenue, Suite 109, Annapolis, MD, 21403, USA
| | - Andrew Miller
- Department of Geography and Environmental Systems, University of Maryland Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA
| | - Julia Moriarty
- Institute for Arctic and Alpine Research, Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder CO 80309, USA
| | - Gregory B Noe
- Florence Bascom Geoscience Center, U.S. Geological Survey, 12201 Sunrise Valley Drive, MS926A, Reston, VA 20192, USA
| | - George Onyullo
- District of Columbia Department of Energy and Environment, 1200 First Street NE, Washington DC 20002, USA
| | - Kenneth Rose
- Horn Point Laboratory, University of Maryland Center for Environmental Science, P.O. Box 775, Cambridge, MD 21613, USA
| | - Katie Skalak
- National Research Program, U.S. Geological Survey, 12201Sunrise Valley Drive, Reston, VA 20192, USA
| | - Richard Tian
- USGS Chesapeake Bay Program Office, 410 Severn Avenue, Suite 109, Annapolis, MD, 21403, USA
| | - Tamie L Veith
- U.S. Department of Agriculture Agricultural Research Service, Pasture Systems and Watershed Management Research Unit, Building 3702, Curtin Road, University Park, PA 16802, USA
| | - Lisa Wainger
- Chesapeake Biological Laboratory, University of Maryland Center for Environmental Science, P.O. Box 38, Solomons, MD 20688, USA
| | - Donald Weller
- Smithsonian Environmental Research Center, 647 Contees Wharf Road, Edgewater, MD 21037, USA
| | - Yinglong Joseph Zhang
- Virginia Institute of Marine Science, William & Mary, 1375 Greate Rd, Gloucester Point, VA 23062, USA
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Kuo CP, Fu JS, Wu PC, Cheng TJ, Chiu TY, Huang CS, Wu CF, Lai LW, Lai HC, Liang CK. Quantifying spatial heterogeneity of vulnerability to short-term PM 2.5 exposure with data fusion framework. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 285:117266. [PMID: 33964553 DOI: 10.1016/j.envpol.2021.117266] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 04/25/2021] [Accepted: 04/26/2021] [Indexed: 06/12/2023]
Abstract
The current estimations of the burden of disease (BD) of PM2.5 exposure is still potentially biased by two factors: ignorance of heterogeneous vulnerabilities at diverse urbanization levels and reliance on the risk estimates from existing literature, usually from different locations. Our objectives are (1) to build up a data fusion framework to estimate the burden of PM2.5 exposure while evaluating local risks simultaneously and (2) to quantify their spatial heterogeneity, relationship to land-use characteristics, and derived uncertainties when calculating the disease burdens. The feature of this study is applying six local databases to extract PM2.5 exposure risk and the BD information, including the risks of death, cardiovascular disease (CVD), and respiratory disease (RD), and their spatial heterogeneities through our data fusion framework. We applied the developed framework to Tainan City in Taiwan as a use case estimated the risks by using 2006-2016 emergency department visit data, air quality monitoring data, and land-use characteristics and further estimated the BD caused by daily PM2.5 exposure in 2013. Our results found that the risks of CVD and RD in highly urbanized areas and death in rural areas could reach 1.20-1.57 times higher than average. Furthermore, we performed a sensitivity analysis to assess the uncertainty of BD estimations from utilizing different data sources, and the results showed that the uncertainty of the BD estimations could be contributed by different PM2.5 exposure data (20-32%) and risk values (0-86%), especially for highly urbanized areas. In conclusion, our approach for estimating BD based on local databases has the potential to be generalized to the developing and overpopulated countries and to support local air quality and health management plans.
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Affiliation(s)
- Cheng-Pin Kuo
- Department of Civil and Environmental Engineering, University of Tennessee Knoxville, Knoxville, TN, USA
| | - Joshua S Fu
- Department of Civil and Environmental Engineering, University of Tennessee Knoxville, Knoxville, TN, USA.
| | - Pei-Chih Wu
- Department of Green Energy and Environmental Resources, Chang Jung Christian University, Tainan, Taiwan; Environmental Research and Information Center, Chang Jung Christian University, Tainan, Taiwan
| | - Tain-Junn Cheng
- Departments of Neurology and Occupational Medicine, Chi-Mei Medical Center, Tainan, Taiwan
| | - Tsu-Yun Chiu
- Environmental Research and Information Center, Chang Jung Christian University, Tainan, Taiwan
| | - Chun-Sheng Huang
- Institute of Environmental and Occupational Health Sciences, National Taiwan University, Taipei, Taiwan
| | - Chang-Fu Wu
- Institute of Environmental and Occupational Health Sciences, National Taiwan University, Taipei, Taiwan; Department of Public Health, National Taiwan University, Taipei, Taiwan
| | - Li-Wei Lai
- Environmental Research and Information Center, Chang Jung Christian University, Tainan, Taiwan
| | - Hsin-Chih Lai
- Department of Green Energy and Environmental Resources, Chang Jung Christian University, Tainan, Taiwan; Environmental Research and Information Center, Chang Jung Christian University, Tainan, Taiwan
| | - Ciao-Kai Liang
- Department of Air Quality Protection and Noise Control, Environmental Protection Administration, Taiwan
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Toro C, Foley K, Simon H, Henderson B, Baker KR, Eyth A, Timin B, Appel W, Luecken D, Beardsley M, Sonntag D, Possiel N, Roberts S. Evaluation of 15 years of modeled atmospheric oxidized nitrogen compounds across the contiguous United States. ELEMENTA (WASHINGTON, D.C.) 2021; 9:10.1525/elementa.2020.00158. [PMID: 34017874 PMCID: PMC8128711 DOI: 10.1525/elementa.2020.00158] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Atmospheric nitrogen oxide and nitrogen dioxide (NO + NO2, together termed as NO X ) estimates from annual photochemical simulations for years 2002-2016 are compared to surface network measurements of NO X and total gas-phase-oxidized reactive nitrogen (NO Y ) to evaluate the Community Multiscale Air Quality (CMAQ) modeling system performance by U.S. region, season, and time of day. In addition, aircraft measurements from 2011 Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality are used to evaluate how emissions, chemical mechanism, and measurement uncertainty each contribute to the overall model performance. We show distinct seasonal and time-of-day patterns in NO X performance. Summertime NO X is overpredicted with bimodal peaks in bias during early morning and evening hours and persisting overnight. The summertime morning NO X bias dropped from between 28% and 57% for earlier years (2002-2012) to between -2% and 7% for later years (2013-2016). Summer daytime NO X tends to be unbiased or underpredicted. In winter, the evening NO X overpredictions remain, but NO X is unbiased or underpredicted overnight, in the morning, and during the day. NO X overpredictions are most pronounced in the Midwestern and Southern United States with Western regions having more of a tendency toward model underpredictions of NO X . Modeled NO X performance has improved substantially over time, reflecting updates to the emission inputs and the CMAQ air quality model. Model performance improvements are largest for years simulated with CMAQv5.1 or later and for emission inventory years 2014 and later, coinciding with reduced onroad NO X emissions from vehicles with newer emission control technologies and improved treatment of chemistry, deposition, and vertical mixing in CMAQ. Our findings suggest that emissions temporalization of specific mobile source sectors have a small impact on model performance, while chemistry updates improve predictions of NO Y but do not improve summertime NO X bias in the Baltimore/DC area. Sensitivity runs performed for different locations across the country suggest that the improvement in summer NO X performance can be attributed to updates in vertical mixing incorporated in CMAQv5.1.
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Affiliation(s)
- Claudia Toro
- U.S. Environmental Protection Agency, Ann Arbor, MI, USA
| | - Kristen Foley
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Heather Simon
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Barron Henderson
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Kirk R. Baker
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Alison Eyth
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Brian Timin
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Wyat Appel
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Deborah Luecken
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | | | | | - Norm Possiel
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Sarah Roberts
- U.S. Environmental Protection Agency, Ann Arbor, MI, USA
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9
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Burns DA, Bhatt G, Linker LC, Bash JO, Capel PD, Shenk GW. Atmospheric nitrogen deposition in the Chesapeake Bay watershed: A history of change. ATMOSPHERIC ENVIRONMENT (OXFORD, ENGLAND : 1994) 2021; 251:1-118277. [PMID: 34504390 PMCID: PMC8422878 DOI: 10.1016/j.atmosenv.2021.118277] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
The Chesapeake Bay watershed has been the focus of pioneering studies of the role of atmospheric nitrogen (N) deposition as a nutrient source and driver of estuarine trophic status. Here, we review the history and evolution of scientific investigations of the role of atmospheric N deposition, examine trends from wet and dry deposition networks, and present century-long (1950-2050) atmospheric N deposition estimates. Early investigations demonstrated the importance of atmospheric deposition as an N source to the Bay, providing 25%-40% among all major N sources. These early studies led to the unprecedented inclusion of targeted decreases in atmospheric N deposition as part of the multi-stakeholder effort to reduce N loads to the Bay. Emissions of nitrogen oxides (NOx) and deposition of wet nitrate, oxidized dry N, and dry ammonium ( NH 4 + ) sharply and synchronously declined by 60%-73% during 1995-2019. These decreases largely resulted from implementation of Title IV of the 1990 Clean Air Act Amendments, which began in 1995. Wet NH 4 + deposition shows no significant trend during this period. The century-long atmospheric N deposition estimates indicate an increase in total atmospheric N deposition in the Chesapeake watershed from 1950 to a peak of ~15 kg N/ha/yr in 1979, trailed by a slight decline of <10% through the mid-1990s, and followed by a sharp decline of about 40% thereafter through 2019. An additional 21% decline in atmospheric N deposition is projected from 2015 to 2050. A comparison of the Potomac River and James River watersheds indicates higher atmospheric N deposition in the Potomac, likely resulting from greater emissions from higher proportions of agricultural and urban land in this basin. Atmospheric N deposition rose from 30% among all N sources to the Chesapeake Bay watershed in 1950 to a peak of 40% in 1973, and a decline to 28% by 2015. These data highlight the important role of atmospheric N deposition in the Chesapeake Bay watershed and present a potential opportunity for decreases in deposition to contribute to further reducing N loads and improving the trophic status of tidal waters.
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Affiliation(s)
- Douglas A. Burns
- U.S. Geological Survey, Troy, NY, USA
- Corresponding author. (D.A. Burns)
| | - Gopal Bhatt
- Pennsylvania State University, Annapolis, MD, USA
| | - Lewis C. Linker
- U.S. Environmental Protection Agency, Chesapeake Bay Program Office, Annapolis, MD, USA
| | - Jesse O. Bash
- National Exposure Research Laboratory, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Paul D. Capel
- Department of Civil, Environmental, and Geo-Engineering, University of Minnesota, Minneapolis, MN, USA
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10
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Koplitz SN, Nolte CG, Sabo RD, Clark CM, Horn KJ, Thomas RQ, Newcomer-Johnson TA. The contribution of wildland fire emissions to deposition in the U S: implications for tree growth and survival in the Northwest. ENVIRONMENTAL RESEARCH LETTERS : ERL [WEB SITE] 2021; 16:10.1088/1748-9326/abd26e. [PMID: 33747119 PMCID: PMC7970516 DOI: 10.1088/1748-9326/abd26e] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
Ecosystems require access to key nutrients like nitrogen (N) and sulfur (S) to sustain growth and healthy function. However, excessive deposition can also damage ecosystems through nutrient imbalances, leading to changes in productivity and shifts in ecosystem structure. While wildland fires are a known source of atmospheric N and S, little has been done to examine the implications of wildland fire deposition for vulnerable ecosystems. We combine wildland fire emission estimates, atmospheric chemistry modeling, and forest inventory data to (a) quantify the contribution of wildland fire emissions to N and S deposition across the U S, and (b) assess the subsequent impacts on tree growth and survival rates in areas where impacts are likely meaningful based on the relative contribution of fire to total deposition. We estimate that wildland fires contributed 0.2 kg N ha-1 yr-1 and 0.04 kg S ha-1 yr-1 on average across the U S during 2008-2012, with maxima up to 1.4 kg N ha-1 yr-1 and 0.6 kg S ha-1 yr-1 in the Northwest representing over ~30% of total deposition in some areas. Based on these fluxes, exceedances of S critical loads as a result of wildland fires are minimal, but exceedances for N may affect the survival and growth rates of 16 tree species across 4.2 million hectares, with the most concentrated impacts occurring in Oregon, northern California, and Idaho. Understanding the broader environmental impacts of wildland fires in the U S will inform future decision making related to both fire management and ecosystem services conservation.
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Affiliation(s)
- Shannon N Koplitz
- Center for Environmental Measurement and Modeling, US EPA, Research Triangle Park, NC, United States of America
- Current address: Office of Air Quality Planning and Standards, US EPA, Research Triangle Park, NC, United States of America
| | - Christopher G Nolte
- Center for Environmental Measurement and Modeling, US EPA, Research Triangle Park, NC, United States of America
| | - Robert D Sabo
- Center for Public Health and Environmental Assessment, US EPA, Washington, DC, United States of America
| | - Christopher M Clark
- Center for Public Health and Environmental Assessment, US EPA, Washington, DC, United States of America
| | - Kevin J Horn
- Department of Forest Resources and Environmental Conservation, Virginia Tech, Blacksburg, VA, United States of America
| | - R Quinn Thomas
- Department of Forest Resources and Environmental Conservation, Virginia Tech, Blacksburg, VA, United States of America
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11
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Henneman LRF, Shen H, Hogrefe C, Russell AG, Zigler CM. Four Decades of United States Mobile Source Pollutants: Spatial-Temporal Trends Assessed by Ground-Based Monitors, Air Quality Models, and Satellites. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:882-892. [PMID: 33400508 PMCID: PMC7983042 DOI: 10.1021/acs.est.0c07128] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
On-road emissions sources degrade air quality, and these sources have been highly regulated. Epidemiological and environmental justice studies often use road proximity as a proxy for traffic-related air pollution (TRAP) exposure, and other studies employ air quality models or satellite observations. To assess these metrics' abilities to reproduce observed near-road concentration gradients and changes over time, we apply a hierarchical linear regression to ground-based observations, long-term air quality model simulations using Community Multiscale Air Quality (CMAQ), and satellite products. Across 1980-2019, observed TRAP concentrations decreased, and road proximity was positively correlated with TRAP. For all pollutants, concentrations decreased fastest at locations with higher road proximity, resulting in "flatter" concentration fields in recent years. This flattening unfolded at a relatively constant rate for NOx, whereas the flattening of CO concentration fields has slowed. CMAQ largely captures observed spatial-temporal NO2 trends across 2002-2010 but overstates the relationships between CO and elemental carbon fine particulate matter (EC) road proximity. Satellite NOx measures overstate concentration reductions near roads. We show how this perspective provides evidence that California's on-road vehicle regulations led to substantial decreases in NO2, NOx, and EC in California, with other states that adopted California's light-duty automobile standards showing mixed benefits over states that did not adopt these standards.
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Affiliation(s)
- Lucas RF Henneman
- George Mason University Department of Civil, Environmental, and Infrastructure Engineering, Fairfax, VA
| | - Huizhong Shen
- Georgia Institute of Technology School of Civil and Environmental Engineering, Atlanta, GA
| | - Christian Hogrefe
- Atmospheric Dynamics and Meteorology Branch; Atmospheric and Environmental Systems Modeling Division; CEMM, ORD, U.S. EPA; Research Triangle Park, NC
| | - Armistead G Russell
- Georgia Institute of Technology School of Civil and Environmental Engineering, Atlanta, GA
| | - Corwin M Zigler
- University of Texas Department of Statistics and Data Sciences and Department of Women’s Health, Austin, TX
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12
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Lu X, Yuan D, Chen Y, Fung JCH, Li W, Lau AKH. Estimations of Long-Term nss-SO 42- and NO 3- Wet Depositions over East Asia by Use of Ensemble Machine-Learning Method. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2020; 54:11118-11126. [PMID: 32808770 DOI: 10.1021/acs.est.0c01068] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Wet deposition of non-sea-salt sulfate (nss-SO42-) and nitrate (NO3-), derived from anthropogenic emissions of SO2 and NOx, exerts adverse effects on ecosystems. In this work, an ensemble back-propagation neural network was proposed to estimate the long-term wet depositions of nss-SO42- (2005-2017) and NO3- (2001-2014) over East Asia in 10 km resolution. The R2 values for the 10-fold cross-validation of annual wet depositions of nss-SO42- and NO3- were 0.90 and 0.85, respectively. The hotspots of the wet deposition of these two acidic species span southwestern, central, and eastern China. The molar ratio of NO3- to nss-SO42- increased in 10 out of 12 analyzed East Asian countries from 2005 to 2014, which indicates that the acidity in rainwater shifts from the sulfur type to nitrogen type over most of the regions. The wet deposition on the four ecosystems (forest, grassland, cropland, and freshwater body) was also analyzed. Results showed that the nss-SO42- wet deposition on 25.5% of freshwater bodies in 2015 and NO3- wet deposition on 21.7% of grassland in 2014 exceeded the ecosystem empirical critical loads (25 kg/ha sulfate and 2 kg N/ha) in East Asia. Thus, more stringent and regionally collaborative sulfur and nitrogen emission-control measures are urgently needed to protect the ecosystem of East Asia.
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Affiliation(s)
- Xingcheng Lu
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong 999077, China
| | - Dehao Yuan
- Department of Mathematics, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong 999077, China
| | - Yiang Chen
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong 999077, China
| | - Jimmy C H Fung
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong 999077, China
- Department of Mathematics, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong 999077, China
| | - Wenkai Li
- Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-Sen University, Guangzhou 510275, China
| | - Alexis K H Lau
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong 999077, China
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Ran L, Yuan Y, Cooter E, Benson V, Yang D, Pleim J, Wang R, Williams J. An Integrated Agriculture, Atmosphere, and Hydrology Modeling System for Ecosystem Assessments. JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS 2020; 11:4645-4668. [PMID: 34122728 PMCID: PMC8193828 DOI: 10.1029/2019ms001708] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
UNLABELLED We present a regional-scale integrated modeling system (IMS) that includes Environmental Policy Integrated Climate (EPIC), Weather Research and Forecast (WRF), Community Multiscale Air Quality (CMAQ), and Soil and Water Assessment Tool (SWAT) models. The centerpiece of the IMS is the Fertilizer Emission Scenario Tool for CMAQ (FEST-C), which includes a Java-based interface and EPIC adapted to regional applications along with built-in database and tools. The SWAT integration capability is a key enhanced feature in the current release of FEST-C v1.4. For integrated modeling demonstration and evaluation, FEST-C EPIC is simulated over three individual years with WRF/CMAQ weather and N deposition. Simulated yearly changes in water and N budgets along with yields for two major crops (corn grain and soybean) match those inferred from intuitive physical reasoning and survey data given different-year weather conditions. Yearlong air quality simulations with an improved bidirectional ammonia flux modeling approach directly using EPIC-simulated soil properties including NH3 content helps reduce biases of simulated gas-phase NH3 and NH4 + wet deposition over the growing season. Integrated hydrology and water quality simulations applied to the Mississippi River Basin show that estimated monthly streamflow and dissolved N near the outlet to the Gulf of Mexico display similar seasonal patterns as observed. Limitations and issues in different parts of the integrated multimedia simulations are identified and discussed to target areas for future improvements. PLAIN LANGUAGE SUMMARY Computer modeling tools with land-water-air processes are important for understanding nutrient cycling and its negative impacts on air and water quality. We have developed an integrated modeling system that includes agriculture, atmosphere, and hydrology components. The centerpiece of the system is a computer system that includes an agricultural ecosystem model and tools used to connect different modeling components. The agricultural system can conduct simulations for 42 types of grassland and cropland with the influence of site, soil, and management information along with weather and nitrogen deposition from the atmosphere component. An air quality computer model then uses information from the agricultural model, such as how much ammonia is in the soil, to predict how much ammonia gets in the air. Then, the watershed hydrology and water quality model uses the information from the agricultural and atmospheric models to understand the influence of agriculture and atmosphere on water quality. The paper demonstrates and evaluates the integrated modeling system on issues mainly related to N cycling. The system performs reasonably well in comparison with survey and observation data given the configured modeling constraints. The paper also identifies and discusses the advantages and limitations in each part of the system for future applications and improvements.
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Affiliation(s)
- L. Ran
- U.S. Environmental Protection Agency, NC, USA
| | - Y. Yuan
- U.S. Environmental Protection Agency, NC, USA
| | - E. Cooter
- U.S. Environmental Protection Agency, NC, USA
| | - V. Benson
- Benson Consulting, Columbia, MO, USA
| | - D. Yang
- University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - J. Pleim
- U.S. Environmental Protection Agency, NC, USA
| | - R. Wang
- Department of Land, Air, and Water Resources, University of California, Davis, CA, USA
| | - J. Williams
- Blackland Research and Extension Center, Texas A&M University, Temple, TX, USA
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14
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Campbell PC, Bash JO, Nolte CG, Spero TL, Cooter EJ, Hinson K, Linker L. Projections of Atmospheric Nitrogen Deposition to the Chesapeake Bay Watershed. JOURNAL OF GEOPHYSICAL RESEARCH. BIOGEOSCIENCES 2019; 12:3307-3326. [PMID: 33868882 PMCID: PMC8048095 DOI: 10.1029/2019jg005203] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Accepted: 10/07/2019] [Indexed: 05/24/2023]
Abstract
Atmospheric deposition is among the largest pathways of nitrogen loading to the Chesapeake Bay Watershed (CBW). The interplay between future climate and emission changes in and around the CBW will likely shift the future nutrient deposition abundance and chemical regime (e.g., oxidized vs. reduced nitrogen). In this work, a Representative Concentration Pathway (RCP) from the Community Earth System Model is dynamically downscaled using the Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) model coupled to the agro-economic Environmental Policy Integrated Climate (EPIC) model. The relative impacts of emission and climate changes on atmospheric nutrient deposition are explored for a recent historical period and a period centered on 2050. The projected regional emissions in CMAQ reflect current federal and state regulations, which use baseline and projected emission years 2011 and 2040, respectively. The historical simulations of 2-m temperature and precipitation have cool and dry biases, and temperature and precipitation are projected to both increase. Ammonium wet deposition agrees well with observations, but nitrate wet deposition is underpredicted. Climate and deposition changes increase simulated future ammonium fertilizer application. In the CBW at 2050, these changes (along with widespread decreases in anthropogenic nitrogen oxide and sulfur oxide emissions, and relatively constant NH3 emissions) decrease total nitrogen deposition by 21%, decrease annual average oxidized nitrogen deposition by 44%, and increase reduced nitrogen deposition by 10%. These results emphasize the importance of decreased anthropogenic emissions on the control of future nitrogen loading to the Chesapeake Bay in a changing climate.
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Affiliation(s)
- Patrick C Campbell
- National Academies/National Research Council (NRC) Fellowship Participant at National Exposure Research Laboratory, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA
| | - Jesse O Bash
- National Exposure Research Laboratory, U.S. Environmental Protection Agency Research Triangle Park, North Carolina, USA
| | - Christopher G Nolte
- National Exposure Research Laboratory, U.S. Environmental Protection Agency Research Triangle Park, North Carolina, USA
| | - Tanya L Spero
- National Exposure Research Laboratory, U.S. Environmental Protection Agency Research Triangle Park, North Carolina, USA
| | - Ellen J Cooter
- National Exposure Research Laboratory, U.S. Environmental Protection Agency Research Triangle Park, North Carolina, USA
| | - Kyle Hinson
- Chesapeake Bay Research Consortium, Edgewater, Maryland, USA
| | - Lewis Linker
- U.S. Environmental Protection Agency Chesapeake Bay Program Office, Annapolis, Maryland, USA
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15
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Walker JT, Beachley G, Amos HM, Baron JS, Bash J, Baumgardner R, Bell MD, Benedict KB, Chen X, Clow DW, Cole A, Coughlin JG, Cruz K, Daly RW, Decina SM, Elliott EM, Fenn ME, Ganzeveld L, Gebhart K, Isil SS, Kerschner BM, Larson RS, Lavery T, Lear GG, Macy T, Mast MA, Mishoe K, Morris KH, Padgett PE, Pouyat RV, Puchalski M, Pye HOT, Rea AW, Rhodes MF, Rogers CM, Saylor R, Scheffe R, Schichtel BA, Schwede DB, Sexstone GA, Sive BC, Sosa Echeverría R, Templer PH, Thompson T, Tong D, Wetherbee GA, Whitlow TH, Wu Z, Yu Z, Zhang L. Toward the improvement of total nitrogen deposition budgets in the United States. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 691:1328-1352. [PMID: 31466212 PMCID: PMC7724633 DOI: 10.1016/j.scitotenv.2019.07.058] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2019] [Revised: 07/02/2019] [Accepted: 07/04/2019] [Indexed: 06/10/2023]
Abstract
Frameworks for limiting ecosystem exposure to excess nutrients and acidity require accurate and complete deposition budgets of reactive nitrogen (Nr). While much progress has been made in developing total Nr deposition budgets for the U.S., current budgets remain limited by key data and knowledge gaps. Analysis of National Atmospheric Deposition Program Total Deposition (NADP/TDep) data illustrates several aspects of current Nr deposition that motivate additional research. Averaged across the continental U.S., dry deposition contributes slightly more (55%) to total deposition than wet deposition and is the dominant process (>90%) over broad areas of the Southwest and other arid regions of the West. Lack of dry deposition measurements imposes a reliance on models, resulting in a much higher degree of uncertainty relative to wet deposition which is routinely measured. As nitrogen oxide (NOx) emissions continue to decline, reduced forms of inorganic nitrogen (NHx = NH3 + NH4+) now contribute >50% of total Nr deposition over large areas of the U.S. Expanded monitoring and additional process-level research are needed to better understand NHx deposition, its contribution to total Nr deposition budgets, and the processes by which reduced N deposits to ecosystems. Urban and suburban areas are hotspots where routine monitoring of oxidized and reduced Nr deposition is needed. Finally, deposition budgets have incomplete information about the speciation of atmospheric nitrogen; monitoring networks do not capture important forms of Nr such as organic nitrogen. Building on these themes, we detail the state of the science of Nr deposition budgets in the U.S. and highlight research priorities to improve deposition budgets in terms of monitoring and flux measurements, leaf- to regional-scale modeling, source apportionment, and characterization of deposition trends and patterns.
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Affiliation(s)
- J T Walker
- U.S. Environmental Protection Agency, Office of Research and Development, Durham, NC, United States of America.
| | - G Beachley
- U.S. Environmental Protection Agency, Office of Air and Radiation, Washington, DC, United States of America
| | - H M Amos
- AAAS Science and Technology Policy Fellow hosted by the U.S. Environmental Protection Agency, Office of Research and Development, Washington, DC, United States of America
| | - J S Baron
- U.S. Geological Survey, Fort Collins Science Center, Fort Collins, CO, United States of America
| | - J Bash
- U.S. Environmental Protection Agency, Office of Research and Development, Durham, NC, United States of America
| | - R Baumgardner
- U.S. Environmental Protection Agency, Office of Research and Development, Durham, NC, United States of America
| | - M D Bell
- National Park Service, Air Resources Division, Lakewood, CO, United States of America
| | - K B Benedict
- Colorado State University, Department of Atmospheric Science, Fort Collins, CO, United States of America
| | - X Chen
- U.S. Environmental Protection Agency, Office of Research and Development, Durham, NC, United States of America
| | - D W Clow
- U.S. Geological Survey, Colorado Water Science Center, Denver, CO, United States of America
| | - A Cole
- Environment and Climate Change Canada, Air Quality Research Division, Toronto, ON, Canada
| | - J G Coughlin
- U.S. Environmental Protection Agency, Region 5, Chicago, IL, United States of America
| | - K Cruz
- U.S. Department of Agriculture, National Institute of Food and Agriculture, Washington, DC, United States of America
| | - R W Daly
- U.S. Environmental Protection Agency, Office of Research and Development, Durham, NC, United States of America
| | - S M Decina
- University of California, Department of Chemistry, Berkeley, CA, United States of America
| | - E M Elliott
- University of Pittsburgh, Department of Geology & Environmental Science, Pittsburgh, PA, United States of America
| | - M E Fenn
- U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station, Riverside, CA, United States of America
| | - L Ganzeveld
- Meteorology and Air Quality (MAQ), Wageningen University and Research Centre, Wageningen, Netherlands
| | - K Gebhart
- National Park Service, Air Resources Division, Fort Collins, CO, United States of America
| | - S S Isil
- Wood Environment & Infrastructure Solutions, Inc., Newberry, FL, United States of America
| | - B M Kerschner
- Prairie Research Institute, University of Illinois, Champaign, IL, United States of America
| | - R S Larson
- Wisconsin State Laboratory of Hygiene, University of Wisconsin, Madison, WI, United States of America
| | - T Lavery
- Environmental Consultant, Cranston, RI, United States of America
| | - G G Lear
- U.S. Environmental Protection Agency, Office of Air and Radiation, Washington, DC, United States of America
| | - T Macy
- U.S. Environmental Protection Agency, Office of Air and Radiation, Washington, DC, United States of America
| | - M A Mast
- U.S. Geological Survey, Colorado Water Science Center, Denver, CO, United States of America
| | - K Mishoe
- Wood Environment & Infrastructure Solutions, Inc., Newberry, FL, United States of America
| | - K H Morris
- National Park Service, Air Resources Division, Lakewood, CO, United States of America
| | - P E Padgett
- U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station, Riverside, CA, United States of America
| | - R V Pouyat
- U.S. Forest Service, Bethesda, MD, United States of America
| | - M Puchalski
- U.S. Environmental Protection Agency, Office of Air and Radiation, Washington, DC, United States of America
| | - H O T Pye
- U.S. Environmental Protection Agency, Office of Research and Development, Durham, NC, United States of America
| | - A W Rea
- U.S. Environmental Protection Agency, Office of Research and Development, Durham, NC, United States of America
| | - M F Rhodes
- D&E Technical, Urbana, IL, United States of America
| | - C M Rogers
- Wood Environment & Infrastructure Solutions, Inc., Newberry, FL, United States of America
| | - R Saylor
- National Oceanic and Atmospheric Administration, Air Resources Laboratory, Oak Ridge, TN, United States of America
| | - R Scheffe
- U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Durham, NC, United States of America
| | - B A Schichtel
- National Park Service, Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, United States of America
| | - D B Schwede
- U.S. Environmental Protection Agency, Office of Research and Development, Durham, NC, United States of America
| | - G A Sexstone
- U.S. Geological Survey, Colorado Water Science Center, Denver, CO, United States of America
| | - B C Sive
- National Park Service, Air Resources Division, Lakewood, CO, United States of America
| | - R Sosa Echeverría
- Centro de Ciencias de la Atmosfera, Universidad Nacional Autónoma de México, Mexico
| | - P H Templer
- Boston University, Department of Biology, Boston, MA, United States of America
| | - T Thompson
- AAAS Science and Technology Policy Fellow hosted by the U.S. Environmental Protection Agency, Office of Policy, Washington, DC, United States of America
| | - D Tong
- George Mason University. National Oceanic and Atmospheric Administration, Air Resources Laboratory, College Park, MD, United States of America
| | - G A Wetherbee
- U.S. Geological Survey, Hydrologic Networks Branch, Denver, CO, United States of America
| | - T H Whitlow
- Cornell University, Department of Horticulture, Ithaca, NY, United States of America
| | - Z Wu
- U.S. Environmental Protection Agency, Office of Research and Development, Durham, NC, United States of America
| | - Z Yu
- University of Pittsburgh, Department of Geology & Environmental Science, Pittsburgh, PA, United States of America
| | - L Zhang
- Environment and Climate Change Canada, Air Quality Research Division, Toronto, ON, Canada
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Walker JT, Bell MD, Schwede D, Cole A, Beachley G, Lear G, Wu Z. Aspects of uncertainty in total reactive nitrogen deposition estimates for North American critical load applications. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 690:1005-1018. [PMID: 31302534 PMCID: PMC7724635 DOI: 10.1016/j.scitotenv.2019.06.337] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Revised: 06/20/2019] [Accepted: 06/21/2019] [Indexed: 06/07/2023]
Abstract
Determination of the amount of reactive nitrogen (Nr) deposition in excess of the ecosystem critical load (CL) requires an estimate of total deposition. Because the CL exceedance is used to inform policy decisions, uncertainty in both the CL and the exceedance itself must be understood. In this paper we review the state of the science with respect to the sources of uncertainty in total Nr deposition budgets used for CL assessments in North America and put forth recommendations for research and monitoring to improve deposition measurements and models. In the absence of methods to rigorously quantify uncertainty in total Nr deposition, a simple weighted deposition uncertainty metric (WDUM) is introduced as a tool for scientists and decision makers to use in assessing CL exceedances. Maps of the WDUM applied to National Atmospheric Deposition Program (NADP) Total Deposition (TDep) estimates show greater uncertainty in areas of the U.S. where dry deposition makes a larger contribution to the deposition budget, particularly ammonia (NH3) in agricultural areas and oxidized nitrogen (NOx) in urban areas. Organic N deposition is an important source of uncertainty over much of the U.S. Our analysis illustrates how the WDUM can be used to assess spatial patterns of deposition uncertainty and inform actions to improve deposition budgets for CL assessments at the local scale.
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Affiliation(s)
- John T Walker
- U.S. EPA, Office of Research and Development, Durham, NC, United States of America.
| | - Michael D Bell
- National Park Service, Air Resources Division, Lakewood, CO, United States of America
| | - Donna Schwede
- U.S. EPA, Office of Research and Development, Durham, NC, United States of America
| | - Amanda Cole
- Environment and Climate Change Canada, Air Quality Research Division, Toronto, ON, Canada
| | - Greg Beachley
- U.S. EPA, Office of Air Programs, Washington, DC, United States of America
| | - Gary Lear
- U.S. EPA, Office of Air Programs, Washington, DC, United States of America
| | - Zhiyong Wu
- U.S. EPA, Office of Research and Development, Durham, NC, United States of America
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17
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Senthilkumar N, Gilfether M, Metcalf F, Russell AG, Mulholland JA, Chang HH. Application of a Fusion Method for Gas and Particle Air Pollutants between Observational Data and Chemical Transport Model Simulations Over the Contiguous United States for 2005-2014. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16183314. [PMID: 31505818 PMCID: PMC6765984 DOI: 10.3390/ijerph16183314] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/14/2019] [Revised: 09/02/2019] [Accepted: 09/04/2019] [Indexed: 11/24/2022]
Abstract
Accurate spatiotemporal air quality data are critical for use in assessment of regulatory effectiveness and for exposure assessment in health studies. A number of data fusion methods have been developed to combine observational data and chemical transport model (CTM) results. Our approach focuses on preserving the temporal variation provided by observational data while deriving the spatial variation from the community multiscale air quality (CMAQ) simulations, a type of CTM. Here we show the results of fusing regulatory monitoring observational data with 12 km resolution CTM simulation results for 12 pollutants (CO, NOx, NO2, SO2, O3, PM2.5, PM10, NO3−, NH4+, EC, OC, SO42−) over the contiguous United States on a daily basis for a period of ten years (2005–2014). An annual mean regression between the CTM simulations and observational data is used to estimate the average spatial fields, and spatial interpolation of observations normalized by predicted annual average is used to provide the daily variation. Results match the temporal variation well (R2 values ranging from 0.84–0.98 across pollutants) and the spatial variation less well (R2 values 0.42–0.94). Ten-fold cross validation shows normalized root mean square error values of 60% or less and spatiotemporal R2 values of 0.4 or more for all pollutants except SO2.
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Affiliation(s)
- Niru Senthilkumar
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Mark Gilfether
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Francesca Metcalf
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Armistead G Russell
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - James A Mulholland
- School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Howard H Chang
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA.
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