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Foley KM, Pouliot GA, Eyth A, Aldridge MF, Allen C, Appel KW, Bash JO, Beardsley M, Beidler J, Choi D, Farkas C, Gilliam RC, Godfrey J, Henderson BH, Hogrefe C, Koplitz SN, Mason R, Mathur R, Misenis C, Possiel N, Pye HO, Reynolds L, Roark M, Roberts S, Schwede DB, Seltzer KM, Sonntag D, Talgo K, Toro C, Vukovich J, Xing J, Adams E. 2002-2017 anthropogenic emissions data for air quality modeling over the United States. Data Brief 2023; 47:109022. [PMID: 36942100 PMCID: PMC10023994 DOI: 10.1016/j.dib.2023.109022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 02/17/2023] [Accepted: 02/21/2023] [Indexed: 03/06/2023] Open
Abstract
The United States Environmental Protection Agency (US EPA) has developed a set of annual North American emissions data for multiple air pollutants across 18 broad source categories for 2002 through 2017. The sixteen new annual emissions inventories were developed using consistent input data and methods across all years. When a consistent method or tool was not available for a source category, emissions were estimated by scaling data from the EPA's 2017 National Emissions Inventory with scaling factors based on activity data and/or emissions control information. The emissions datasets are designed to support regional air quality modeling for a wide variety of human health and ecological applications. The data were developed to support simulations of the EPA's Community Multiscale Air Quality model but can also be used by other regional scale air quality models. The emissions data are one component of EPA's Air Quality Time Series Project which also includes air quality modeling inputs (meteorology, initial conditions, boundary conditions) and outputs (e.g., ozone, PM2.5 and constituent species, wet and dry deposition) for the Conterminous US at a 12 km horizontal grid spacing.
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Affiliation(s)
- Kristen M. Foley
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
- Corresponding authors. @kfoley7991
| | - George A. Pouliot
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
- Corresponding authors. @kfoley7991
| | - Alison Eyth
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Michael F. Aldridge
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Christine Allen
- General Dynamics Information Technology, 79 T.W. Alexander Drive, Research Triangle Park, NC 27709, United States
| | - K. Wyat Appel
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Jesse O. Bash
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Megan Beardsley
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - James Beidler
- General Dynamics Information Technology, 79 T.W. Alexander Drive, Research Triangle Park, NC 27709, United States
| | - David Choi
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Caroline Farkas
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Robert C. Gilliam
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Janice Godfrey
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Barron H. Henderson
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Christian Hogrefe
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Shannon N. Koplitz
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Rich Mason
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Rohit Mathur
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Chris Misenis
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Norm Possiel
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Havala O.T. Pye
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Lara Reynolds
- General Dynamics Information Technology, 79 T.W. Alexander Drive, Research Triangle Park, NC 27709, United States
| | - Matthew Roark
- General Dynamics Information Technology, 79 T.W. Alexander Drive, Research Triangle Park, NC 27709, United States
| | - Sarah Roberts
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Donna B. Schwede
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Karl M. Seltzer
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Darrell Sonntag
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Kevin Talgo
- General Dynamics Information Technology, 79 T.W. Alexander Drive, Research Triangle Park, NC 27709, United States
| | - Claudia Toro
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Jeff Vukovich
- US Environmental Protection Agency, 109 T.W. Alexander Drive, Research Triangle Park, NC 27711, United States
| | - Jia Xing
- School of Environment, State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing, China
| | - Elizabeth Adams
- University of North Carolina, Institute for the Environment, 100 Europa Drive, Suite 490, CB #1105, Chapel Hill, NC 27599, United States
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Baker KR, Lee SD, Lemieux P, Hudson S, Murphy BN, Bash JO, Koplitz SN, Nguyen TKV, Hao WM, Baker S, Lincoln E. Predicting wildfire particulate matter and hypothetical re-emission of radiological Cs-137 contamination incidents. Sci Total Environ 2021; 795:148872. [PMID: 34328919 PMCID: PMC9019821 DOI: 10.1016/j.scitotenv.2021.148872] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2021] [Revised: 07/01/2021] [Accepted: 07/02/2021] [Indexed: 06/13/2023]
Abstract
Radiological release incidents can potentially contaminate widespread areas with radioactive materials and decontamination efforts are typically focused on populated areas, which means radionuclides may be left in forested areas for long periods of time. Large wildfires in contaminated forested areas have the potential to reintroduce these radionuclides into the atmosphere and cause exposure to first responders and downwind communities. One important radionuclide contaminant released from radiological incidents is radiocesium (137Cs) due to high yields and its long half-life of 30.2 years. An Eulerian 3D photochemical transport model was used to estimate potential ambient impacts of 137Cs re-emission due to wildfire following hypothetical radiological release scenarios. The Community Multiscale Air Quality (CMAQ) model did well at predicting levels and periods of increased PM2.5 carbon due to wildfire smoke at routine surface monitors in California during the summer of 2016. The model also did well at capturing the extent of the surface mixing layer compared to aerosol lidar measurements. Emissions from a large hypothetical wildfire were introduced into the wildland-urban interface (WUI) impacted by a hypothetical radiological release event. While ambient concentrations tended to be highest near the fire, the highest population committed effective dose equivalent by inhalation to an adult from 137Cs over an hour was downwind where wind flows moved smoke to high population areas. Seasonal variations in meteorology (wind flows) can result in differential population impacts even in the same metropolitan area. Modeled post-incident ambient levels of 137Cs both near these wildfires and further downwind in nearby urban areas were well below levels that would necessitate population evacuation or warrant other protective action recommendations such as shelter-in-place. These results suggest that 1) the modeling system captures local to regional scale transport and levels of PM2.5 from wildfire and 2) first responders and downwind population would not be expected to be at elevated risk from the initial inhalathion exposure of 137Cs re-emission.
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Affiliation(s)
- Kirk R Baker
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA.
| | - Sang Don Lee
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Paul Lemieux
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Scott Hudson
- U.S. Environmental Protection Agency, Cincinnati, OH, USA
| | - Benjamin N Murphy
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Jesse O Bash
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Shannon N Koplitz
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | | | - Wei Min Hao
- Missoula Fire Sciences Laboratory, Rocky Mountain Research Station, US Forest Service, Missoula, MT, USA
| | - Stephen Baker
- Missoula Fire Sciences Laboratory, Rocky Mountain Research Station, US Forest Service, Missoula, MT, USA
| | - Emily Lincoln
- Missoula Fire Sciences Laboratory, Rocky Mountain Research Station, US Forest Service, Missoula, MT, USA
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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. Environ Res Lett 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] [What about the content of this article? (0)] [Affiliation(s)] [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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Marlier ME, Liu T, Yu K, Buonocore JJ, Koplitz SN, DeFries RS, Mickley LJ, Jacob DJ, Schwartz J, Wardhana BS, Myers SS. Fires, Smoke Exposure, and Public Health: An Integrative Framework to Maximize Health Benefits From Peatland Restoration. Geohealth 2019; 3:178-189. [PMID: 32159040 PMCID: PMC7007093 DOI: 10.1029/2019gh000191] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2019] [Revised: 06/04/2019] [Accepted: 06/04/2019] [Indexed: 05/08/2023]
Abstract
Emissions of particulate matter from fires associated with land management practices in Indonesia contribute to regional air pollution and mortality. We assess the public health benefits in Indonesia, Malaysia, and Singapore from policies to reduce fires by integrating information on fire emissions, atmospheric transport patterns, and population exposure to fine particulate matter (PM2.5). We use adjoint sensitivities to relate fire emissions to PM2.5 for a range of meteorological conditions and find that a Business-As-Usual scenario of land use change leads, on average, to 36,000 excess deaths per year into the foreseeable future (the next several decades) across the region. These deaths are largely preventable with fire reduction strategies, such as blocking fires in peatlands, industrial concessions, or protected areas, which reduce the health burden by 66, 45, and 14%, respectively. The effectiveness of these different strategies in mitigating human health impacts depends on the location of fires relative to the population distribution. For example, protecting peatlands through eliminating all fires on such lands would prevent on average 24,000 excess deaths per year into the foreseeable future across the region because, in addition to storing large amounts of fuel, many peatlands are located directly upwind of densely populated areas. We also demonstrate how this framework can be used to prioritize restoration locations for the Indonesian Peatland Restoration Agency based on their ability to reduce pollution exposure and health burden. This scientific framework is publicly available through an online decision support tool that allows stakeholders to readily determine the public health benefits of different land management strategies.
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Affiliation(s)
- Miriam E. Marlier
- The RAND CorporationSanta MonicaCAUSA
- Department of Ecology, Evolution, and Environmental BiologyColumbia UniversityNew YorkNYUSA
| | - Tianjia Liu
- Department of Earth and Planetary SciencesHarvard UniversityCambridgeMAUSA
| | - Karen Yu
- School of Engineering and Applied SciencesHarvard UniversityCambridgeMAUSA
| | - Jonathan J. Buonocore
- Center for Climate, Health, and the Global Environment, Harvard T.H. Chan School of Public HealthHarvard UniversityBostonMAUSA
| | - Shannon N. Koplitz
- Department of Earth and Planetary SciencesHarvard UniversityCambridgeMAUSA
| | - Ruth S. DeFries
- Department of Ecology, Evolution, and Environmental BiologyColumbia UniversityNew YorkNYUSA
| | - Loretta J. Mickley
- School of Engineering and Applied SciencesHarvard UniversityCambridgeMAUSA
| | - Daniel J. Jacob
- Department of Earth and Planetary SciencesHarvard UniversityCambridgeMAUSA
- School of Engineering and Applied SciencesHarvard UniversityCambridgeMAUSA
| | - Joel Schwartz
- Harvard T.H. Chan School of Public HealthHarvard UniversityBostonMAUSA
| | | | - Samuel S. Myers
- Harvard T.H. Chan School of Public HealthHarvard UniversityBostonMAUSA
- Harvard University Center for the EnvironmentHarvard UniversityCambridgeMAUSA
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5
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Baker KR, Koplitz SN, Foley KM, Avey L, Hawkins A. Characterizing grassland fire activity in the Flint Hills region and air quality using satellite and routine surface monitor data. Sci Total Environ 2019; 659:1555-1566. [PMID: 31096365 PMCID: PMC6704483 DOI: 10.1016/j.scitotenv.2018.12.427] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Revised: 12/28/2018] [Accepted: 12/28/2018] [Indexed: 06/09/2023]
Abstract
Prescribed grassland fires in the Flint Hills region of central Kansas and northern Oklahoma are a common tool for land management. Local to regional scale impacts on air quality from grassland fires in this region are not well understood, which is important as these types of prescribed fires may increase in the future to preserve broader areas of native grasses in the central U.S. Routine air quality and deposition measurements from sites in and near the Flint Hills were examined for coincident increases during periods of increased prescribed grassland fires. Prescribed fire activity in this region was quantified using satellite detections and multiple publicly available data products of area burned information. March and April comprise over half (41 to 93%) of all annual fire detections in the Flint Hills region seen from satellites between 2007 and 2018 excluding drought years. Annual total fire detections in this region range between 1 and 12 thousand and account for approximately 3% of all fire detections in the contiguous U.S. Annual acres burned ranged from 0.2 to 2 million acres based on U.S. EPA's National Emission Inventory, which accounts for 4 to 38% of grasslands in the area. A comparison of weekly standardized anomalies suggests a relationship between periods of increased grassland fire activity and elevated levels of PM2.5 organic carbon, elemental carbon, and potassium. Daily 1-hr maximum ozone (O3), ammonia (NH3), sulfur dioxide (SO2), and oxidized nitrogen gases measured at Konza Prairie also had increased levels when prescribed grassland fire activity was highest. This detailed characterization of prescribed fire activity in the Flint Hills and associated air quality impacts will benefit future efforts to understand changes in atmospheric composition due to changing land management practices.
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Affiliation(s)
- K R Baker
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA.
| | - S N Koplitz
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - K M Foley
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - L Avey
- U.S. Environmental Protection Agency, Lenexa, KS, USA
| | - A Hawkins
- U.S. Environmental Protection Agency, Lenexa, KS, USA
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6
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Kelly JT, Koplitz SN, Baker KR, Holder AL, Pye HOT, Murphy BN, Bash JO, Henderson BH, Possiel N, Simon H, Eyth AM, Jang C, Phillips S, Timin B. Assessing PM 2.5 Model Performance for the Conterminous U.S. with Comparison to Model Performance Statistics from 2007-2015. Atmos Environ (1994) 2019; 214:1-116872. [PMID: 31741655 PMCID: PMC6859642 DOI: 10.1016/j.atmosenv.2019.116872] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Previous studies have proposed that model performance statistics from earlier photochemical grid model (PGM) applications can be used to benchmark performance in new PGM applications. A challenge in implementing this approach is that limited information is available on consistently calculated model performance statistics that vary spatially and temporally over the U.S. Here, a consistent set of model performance statistics are calculated by year, season, region, and monitoring network for PM2.5 and its major components using simulations from versions 4.7.1-5.2.1 of the Community Multiscale Air Quality (CMAQ) model for years 2007-2015. The multi-year set of statistics is then used to provide quantitative context for model performance results from the 2015 simulation. Model performance for PM2.5 organic carbon in the 2015 simulation ranked high (i.e., favorable performance) in the multi-year dataset, due to factors including recent improvements in biogenic secondary organic aerosol and atmospheric mixing parameterizations in CMAQ. Model performance statistics for the Northwest region in 2015 ranked low (i.e., unfavorable performance) for many species in comparison to the 2007-2015 dataset. This finding motivated additional investigation that suggests a need for improved speciation of wildfire PM2.5emissions and modeling of boundary layer dynamics near water bodies. Several limitations were identified in the approach of benchmarking new model performance results with previous results. Since performance statistics vary widely by region and season, a simple set of national performance benchmarks (e.g., one or two targets per species and statistic) as proposed previously are inadequate to assess model performance throughout the U.S. Also, trends in model performance statistics for sulfate over the 2007 to 2015 period suggest that model performance for earlier years may not be a useful reference for assessing model performance for recent years in some cases. Comparisons of results from the 2015 base case with results from five sensitivity simulations demonstrated the importance of parameterizations of NH3 surface exchange, organic aerosol volatility and production, and emissions of crustal cations for predicting PM2.5 species concentrations.
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Affiliation(s)
- James T Kelly
- Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Shannon N Koplitz
- Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Kirk R Baker
- Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Amara L Holder
- Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Havala O T Pye
- Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Benjamin N Murphy
- Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Jesse O Bash
- Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Barron H Henderson
- Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Norm Possiel
- Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Heather Simon
- Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Alison M Eyth
- Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Carey Jang
- Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Sharon Phillips
- Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Brian Timin
- Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
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Baker KR, Woody MC, Valin L, Szykman J, Yates EL, Iraci LT, Choi HD, Soja AJ, Koplitz SN, Zhou L, Campuzano-Jost P, Jimenez JL, Hair JW. Photochemical model evaluation of 2013 California wild fire air quality impacts using surface, aircraft, and satellite data. Sci Total Environ 2018; 637-638:1137-1149. [PMID: 29801207 DOI: 10.1016/j.scitotenv.2018.05.048] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Revised: 05/03/2018] [Accepted: 05/04/2018] [Indexed: 06/08/2023]
Abstract
The Rim Fire was one of the largest wildfires in California history, burning over 250,000 acres during August and September 2013 affecting air quality locally and regionally in the western U.S. Routine surface monitors, remotely sensed data, and aircraft based measurements were used to assess how well the Community Multiscale Air Quality (CMAQ) photochemical grid model applied at 4 and 12 km resolution represented regional plume transport and chemical evolution during this extreme wildland fire episode. Impacts were generally similar at both grid resolutions although notable differences were seen in some secondary pollutants (e.g., formaldehyde and peroxyacyl nitrate) near the Rim fire. The modeling system does well at capturing near-fire to regional scale smoke plume transport compared to remotely sensed aerosol optical depth (AOD) and aircraft transect measurements. Plume rise for the Rim fire was well characterized as the modeled plume top was consistent with remotely sensed data and the altitude of aircraft measurements, which were typically made at the top edge of the plume. Aircraft-based lidar suggests O3 downwind in the Rim fire plume was vertically stratified and tended to be higher at the plume top, while CMAQ estimated a more uniformly mixed column of O3. Predicted wildfire ozone (O3) was overestimated both at the plume top and at nearby rural and urban surface monitors. Photolysis rates were well characterized by the model compared with aircraft measurements meaning aerosol attenuation was reasonably estimated and unlikely contributing to O3 overestimates at the top of the plume. Organic carbon was underestimated close to the Rim fire compared to aircraft data, but was consistent with nearby surface measurements. Periods of elevated surface PM2.5 at rural monitors near the Rim fire were not usually coincident with elevated O3.
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Affiliation(s)
- K R Baker
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA.
| | - M C Woody
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - L Valin
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - J Szykman
- U.S. Environmental Protection Agency, Hampton, VA, USA
| | - E L Yates
- NASA Ames Research Center, Moffett Field, CA, USA
| | - L T Iraci
- NASA Ames Research Center, Moffett Field, CA, USA
| | - H D Choi
- National Institute of Aerospace, NASA Langley Research Center, Hampton, VA, USA
| | - A J Soja
- National Institute of Aerospace, NASA Langley Research Center, Hampton, VA, USA
| | - S N Koplitz
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - L Zhou
- U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Pedro Campuzano-Jost
- Department of Chemistry & Biochemistry, CIRES, University of Colorado, Boulder, CO, USA
| | - Jose L Jimenez
- Department of Chemistry & Biochemistry, CIRES, University of Colorado, Boulder, CO, USA
| | - J W Hair
- NASA Langley Research Center, Hampton, VA, USA
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8
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Koplitz SN, Nolte CG, Pouliot GA, Vukovich JM, Beidler J. Influence of uncertainties in burned area estimates on modeled wildland fire PM 2.5 and ozone pollution in the contiguous U.S. Atmos Environ (1994) 2018; 191:328-339. [PMID: 31019376 PMCID: PMC6476193 DOI: 10.1016/j.atmosenv.2018.08.020] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Wildland fires are a major source of fine particulate matter (PM2.5), one of the most harmful ambient pollutants for human health globally. To represent the influence of wildland fire emissions on atmospheric composition, regional and global chemical transport models rely on emission inventories developed from estimates of burned area (i.e. fire size and location). While different methods of estimating annual burned area agree reasonably well in the western U.S. (within 20-30% for most years during 2002-2014), estimates for the southern U.S. can vary by more than a factor of 5. These differences in burned area lead to significant variability in the spatial and temporal allocation of emissions across fire emission inventory platforms. In this work, we implement wildland fire emission estimates for 2011 from three different products - the USEPA National Emission Inventory (NEI), the Fire Inventory of NCAR (FINN), and the Global Fire Emission Database (GFED4s) - into the Community Multiscale Air Quality (CMAQ) model to quantify and characterize differences in simulated PM and ozone concentrations across the contiguous U.S. (CONUS) due to the fire emission inventory used. The NEI is developed specifically for the U.S., while both FINN and GFED4s are available globally. We find that NEI emissions lead to the largest increases in modeled annual average PM2.5 (0.85 μg m-3) and April-September maximum daily 8-h ozone (0.28 ppb) nationally compared to a "no fire" baseline, followed by FINN (0.33 μg m-3 and 0.22 ppb) and GFED4s (0.12 μg m-3 and 0.17 ppb). Annual mean enhancements in wildland fire pollution are highest in the southern U.S. across all three inventories (over 4 μg m-3 and 2 ppb in some areas), but show considerable spatial variability within these regions. We also examine the representation of five individual fire events during 2011 and find that of the two global inventories, FINN reproduces more of the acute changes in pollutant concentrations modeled with NEI and shown in surface observations during each of the episodes investigated compared to GFED4s. Understanding the sensitivity of modeling fire-related PM2.5 and ozone in the U.S. to burned area estimation approaches will inform future efforts to assess the implications of present and future fire activity for air quality and human health at national and global scales.
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Affiliation(s)
- Shannon N. Koplitz
- US EPA Office of Research and Development, Research Triangle Park, North Carolina, USA
- Corresponding author:
| | - Christopher G. Nolte
- US EPA Office of Research and Development, Research Triangle Park, North Carolina, USA
| | - George A. Pouliot
- US EPA Office of Research and Development, Research Triangle Park, North Carolina, USA
| | - Jeffrey M. Vukovich
- US EPA Office of Air Quality Planning and Standards, Research Triangle Park, North Carolina, USA
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Koplitz SN, Jacob DJ, Sulprizio MP, Myllyvirta L, Reid C. Burden of Disease from Rising Coal-Fired Power Plant Emissions in Southeast Asia. Environ Sci Technol 2017; 51:1467-1476. [PMID: 28080047 DOI: 10.1021/acs.est.6b03731] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
Southeast Asia has a very high population density and is on a fast track to economic development, with most of the growth in electricity demand currently projected to be met by coal. From a detailed analysis of coal-fired power plants presently planned or under construction in Southeast Asia, we project in a business-as-usual scenario that emissions from coal in the region will triple to 2.6 Tg a-1 SO2 and 2.6 Tg a-1 NOx by 2030, with the largest increases occurring in Indonesia and Vietnam. Simulations with the GEOS-Chem chemical transport model show large resulting increases in surface air pollution, up to 11 μg m-3 for annual mean fine particulate matter (PM2.5) in northern Vietnam and up to 15 ppb for seasonal maximum 1 h ozone in Indonesia. We estimate 19 880 (11 400-28 400) excess deaths per year from Southeast Asian coal emissions at present, increasing to 69 660 (40 080-126 710) by 2030. 9000 of these excess deaths in 2030 are in China. As Chinese emissions from coal decline in coming decades, transboundary pollution influence from rising coal emissions in Southeast Asia may become an increasing issue.
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Affiliation(s)
- Shannon N Koplitz
- Department of Earth and Planetary Sciences, Harvard University , Cambridge, Massachusetts 02138 United States
| | - Daniel J Jacob
- John A. Paulson School of Engineering and Applied Sciences, Harvard University , Cambridge, Massachusetts 02138 United States
| | - Melissa P Sulprizio
- John A. Paulson School of Engineering and Applied Sciences, Harvard University , Cambridge, Massachusetts 02138 United States
| | | | - Colleen Reid
- Department of Geography, University of Colorado , Boulder, Colorado 80309 United States
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Marlier ME, DeFries R, Pennington D, Nelson E, Ordway EM, Lewis J, Koplitz SN, Mickley LJ. Future fire emissions associated with projected land use change in Sumatra. Glob Chang Biol 2015; 21:345-62. [PMID: 25044917 DOI: 10.1111/gcb.12691] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2013] [Accepted: 06/12/2014] [Indexed: 05/24/2023]
Abstract
Indonesia has experienced rapid land use change over the last few decades as forests and peatswamps have been cleared for more intensively managed land uses, including oil palm and timber plantations. Fires are the predominant method of clearing and managing land for more intensive uses, and the related emissions affect public health by contributing to regional particulate matter and ozone concentrations and adding to global atmospheric carbon dioxide concentrations. Here, we examine emissions from fires associated with land use clearing and land management on the Indonesian island of Sumatra and the sensitivity of this fire activity to interannual meteorological variability. We find ~80% of 2005-2009 Sumatra emissions are associated with degradation or land use maintenance instead of immediate land use conversion, especially in dry years. We estimate Sumatra fire emissions from land use change and maintenance for the next two decades with five scenarios of land use change, the Global Fire Emissions Database Version 3, detailed 1-km2 land use change maps, and MODIS fire radiative power observations. Despite comprising only 16% of the original study area, we predict that 37-48% of future Sumatra emissions from land use change will occur in fuel-rich peatswamps unless this land cover type is protected effectively. This result means that the impact of fires on future air quality and climate in Equatorial Asia will be decided in part by the conservation status given to the remaining peatswamps on Sumatra. Results from this article will be implemented in an atmospheric transport model to quantify the public health impacts from the transport of fire emissions associated with future land use scenarios in Sumatra.
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Affiliation(s)
- Miriam E Marlier
- Department of Ecology, Evolution and Environmental Biology, Columbia University, New York, NY, 10027, USA
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