Articles | Volume 16, issue 8
https://doi.org/10.5194/gmd-16-2303-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-2303-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Comparison of ozone formation attribution techniques in the northeastern United States
Qian Shu
U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
Sergey L. Napelenok
CORRESPONDING AUTHOR
U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
William T. Hutzell
U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
Kirk R. Baker
U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
Barron H. Henderson
U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
Benjamin N. Murphy
U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
Christian Hogrefe
U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
Related authors
No articles found.
Anam M. Khan, Olivia E. Clifton, Jesse O. Bash, Sam Bland, Nathan Booth, Philip Cheung, Lisa Emberson, Johannes Flemming, Erick Fredj, Stefano Galmarini, Laurens Ganzeveld, Orestis Gazetas, Ignacio Goded, Christian Hogrefe, Christopher D. Holmes, László Horváth, Vincent Huijnen, Qian Li, Paul A. Makar, Ivan Mammarella, Giovanni Manca, J. William Munger, Juan L. Pérez-Camanyo, Jonathan Pleim, Limei Ran, Roberto San Jose, Donna Schwede, Sam J. Silva, Ralf Staebler, Shihan Sun, Amos P. K. Tai, Eran Tas, Timo Vesala, Tamás Weidinger, Zhiyong Wu, Leiming Zhang, and Paul C. Stoy
Atmos. Chem. Phys., 25, 8613–8635, https://doi.org/10.5194/acp-25-8613-2025, https://doi.org/10.5194/acp-25-8613-2025, 2025
Short summary
Short summary
Vegetation removes tropospheric ozone through stomatal uptake, and accurately modeling the stomatal uptake of ozone is important for modeling dry deposition and air quality. We evaluated the stomatal component of ozone dry deposition modeled by atmospheric chemistry models at six sites. We find that models and observation-based estimates agree at times during the growing season at all sites, but some models overestimated the stomatal component during the dry summers at a seasonally dry site.
Ioannis Kioutsioukis, Christian Hogrefe, Paul A. Makar, Ummugulsun Alyuz, Jessy O. Bash, Roberto Bellasio, Roberto Bianconi, Tim Buttler, Olivia E. Clifton, Philippe Cheung, Alma Hodzic, Richard Kranenburg, Aurelia Lupascu, Kester Momoh, Juan Luis Perez-Camaño, John Pleim, Young-Hee Ryu, Robero San Jose, Donna Schwede, Ranjeet Sokhi, and Stefano Galmarini
EGUsphere, https://doi.org/10.5194/egusphere-2025-1091, https://doi.org/10.5194/egusphere-2025-1091, 2025
Short summary
Short summary
Deposition is a key in air quality modelling. An evaluation of the AQMEII4 models is performed prior to analysing the different deposition schemes in relation to the LULC used. Such analysis is unprecedented. Among the results, LULC masks have to be harmonised and up-to-date information used in place of outdated and too course masks. Alternatively LULC masks should be evaluated and intercom pared when multiple model results are analysed.
Paul A. Makar, Philip Cheung, Christian Hogrefe, Ayodeji Akingunola, Ummugulsum Alyuz, Jesse O. Bash, Michael D. Bell, Roberto Bellasio, Roberto Bianconi, Tim Butler, Hazel Cathcart, Olivia E. Clifton, Alma Hodzic, Ioannis Kioutsioukis, Richard Kranenburg, Aurelia Lupascu, Jason A. Lynch, Kester Momoh, Juan L. Perez-Camanyo, Jonathan Pleim, Young-Hee Ryu, Roberto San Jose, Donna Schwede, Thomas Scheuschner, Mark W. Shephard, Ranjeet S. Sokhi, and Stefano Galmarini
Atmos. Chem. Phys., 25, 3049–3107, https://doi.org/10.5194/acp-25-3049-2025, https://doi.org/10.5194/acp-25-3049-2025, 2025
Short summary
Short summary
The large range of sulfur and nitrogen deposition estimates from air quality models results in a large range of predicted impacts. We used models and deposition diagnostics to identify the processes controlling atmospheric sulfur and nitrogen deposition variability. Controlling factors included the uptake of gases and aerosols by hydrometeors, aerosol inorganic chemistry, particle dry deposition, ammonia bidirectional fluxes, gas deposition via plant cuticles and soil, and land use data.
Diego Guizzardi, Monica Crippa, Tim Butler, Terry Keating, Rosa Wu, Jacek W. Kamiński, Jeroen Kuenen, Junichi Kurokawa, Satoru Chatani, Tazuko Morikawa, George Pouliot, Jacinthe Racine, Michael D. Moran, Zbigniew Klimont, Patrick M. Manseau, Rabab Mashayekhi, Barron H. Henderson, Steven J. Smith, Rachel Hoesly, Marilena Muntean, Manjola Banja, Edwin Schaaf, Federico Pagani, Jung-Hun Woo, Jinseok Kim, Enrico Pisoni, Junhua Zhang, David Niemi, Mourad Sassi, Annie Duhamel, Tabish Ansari, Kristen Foley, Guannan Geng, Yifei Chen, and Qiang Zhang
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-601, https://doi.org/10.5194/essd-2024-601, 2025
Preprint under review for ESSD
Short summary
Short summary
The global air pollution emission mosaic HTAP_v3.1 is the state-of-the-art database for addressing the evolution of a set of policy-relevant air pollutants over the past 2 decades. The inventory is made by the harmonization and blending of seven regional inventories, gapfilled using the most recent release of EDGAR (EDGARv8). By incorporating the best available local information, the HTAP_v3.1 mosaic inventory can be used for policy-relevant studies at both regional and global levels.
Christian Hogrefe, Stefano Galmarini, Paul A. Makar, Ioannis Kioutsioukis, Olivia E. Clifton, Ummugulsum Alyuz, Jesse O. Bash, Roberto Bellasio, Roberto Bianconi, Tim Butler, Philip Cheung, Alma Hodzic, Richard Kranenburg, Aurelia Lupascu, Kester Momoh, Juan Luis Perez-Camanyo, Jonathan E. Pleim, Young-Hee Ryu, Roberto San Jose, Martijn Schaap, Donna B. Schwede, and Ranjeet Sokhi
EGUsphere, https://doi.org/10.5194/egusphere-2025-225, https://doi.org/10.5194/egusphere-2025-225, 2025
Short summary
Short summary
Performed under the umbrella of the fourth phase of the Air Quality Model Evaluation International Initiative (AQMEII4), this study applies AQMEII4 diagnostic tools to better characterize how dry deposition removes pollutants from the atmosphere in regional-scale models. The results also strongly suggest that improvement and harmonization of the representation of land use in these models would serve the community in their future development efforts.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
Short summary
Short summary
Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
T. Nash Skipper, Emma L. D'Ambro, Forwood C. Wiser, V. Faye McNeill, Rebecca H. Schwantes, Barron H. Henderson, Ivan R. Piletic, Colleen B. Baublitz, Jesse O. Bash, Andrew R. Whitehill, Lukas C. Valin, Asher P. Mouat, Jennifer Kaiser, Glenn M. Wolfe, Jason M. St. Clair, Thomas F. Hanisco, Alan Fried, Bryan K. Place, and Havala O.T. Pye
Atmos. Chem. Phys., 24, 12903–12924, https://doi.org/10.5194/acp-24-12903-2024, https://doi.org/10.5194/acp-24-12903-2024, 2024
Short summary
Short summary
We develop the Community Regional Atmospheric Chemistry Multiphase Mechanism (CRACMM) version 2 to improve predictions of formaldehyde in ambient air compared to satellite-, aircraft-, and ground-based observations. With the updated chemistry, we estimate the cancer risk from inhalation exposure to ambient formaldehyde across the contiguous USA and predict that 40 % of this risk is controllable through reductions in anthropogenic emissions of nitrogen oxides and reactive organic carbon.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
Short summary
Short summary
This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Matthew J. Rowlinson, Mat J. Evans, Lucy J. Carpenter, Katie A. Read, Shalini Punjabi, Adedayo Adedeji, Luke Fakes, Ally Lewis, Ben Richmond, Neil Passant, Tim Murrells, Barron Henderson, Kelvin H. Bates, and Detlev Helmig
Atmos. Chem. Phys., 24, 8317–8342, https://doi.org/10.5194/acp-24-8317-2024, https://doi.org/10.5194/acp-24-8317-2024, 2024
Short summary
Short summary
Ethane and propane are volatile organic compounds emitted from human activities which help to form ozone, a pollutant and greenhouse gas, and also affect the chemistry of the lower atmosphere. Atmospheric models tend to do a poor job of reproducing the abundance of these compounds in the atmosphere. By using regional estimates of their emissions, rather than globally consistent estimates, we can significantly improve the simulation of ethane in the model and make some improvement for propane.
Christopher A. Emery, Kirk R. Baker, Gary M. Wilson, and Greg Yarwood
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-48, https://doi.org/10.5194/gmd-2024-48, 2024
Preprint withdrawn
Short summary
Short summary
We describe the Comprehensive Air quality Model with extensions (CAMx) and evaluate a model simulation during 2016 over nine U.S. climate zones. For ozone, the model statistically replicates measured concentrations better than most other past models and applications. For small inhalable particulates, the model replicates concentrations consistent with most other past models and applications subject to common uncertainties associated with sources, weather, and chemical interactions.
David de la Paz, Rafael Borge, Juan Manuel de Andrés, Luis Tovar, Golam Sarwar, and Sergey L. Napelenok
Atmos. Chem. Phys., 24, 4949–4972, https://doi.org/10.5194/acp-24-4949-2024, https://doi.org/10.5194/acp-24-4949-2024, 2024
Short summary
Short summary
This source apportionment modeling study shows that around 70 % of ground-level O3 in Madrid (Spain) is transported from other regions. Nonetheless, emissions from local sources, mainly road traffic, play a significant role, especially under atmospheric stagnation. Local measures during those conditions may be able to reduce O3 peaks by up to 30 % and, thus, lessen impacts from high-O3 episodes in the Madrid metropolitan area.
Elyse A. Pennington, Yuan Wang, Benjamin C. Schulze, Karl M. Seltzer, Jiani Yang, Bin Zhao, Zhe Jiang, Hongru Shi, Melissa Venecek, Daniel Chau, Benjamin N. Murphy, Christopher M. Kenseth, Ryan X. Ward, Havala O. T. Pye, and John H. Seinfeld
Atmos. Chem. Phys., 24, 2345–2363, https://doi.org/10.5194/acp-24-2345-2024, https://doi.org/10.5194/acp-24-2345-2024, 2024
Short summary
Short summary
To assess the air quality in Los Angeles (LA), we improved the CMAQ model by using dynamic traffic emissions and new secondary organic aerosol schemes to represent volatile chemical products. Source apportionment demonstrates that the urban areas of the LA Basin and vicinity are NOx-saturated, with the largest sensitivity of O3 to changes in volatile organic compounds in the urban core. The improvement and remaining issues shed light on the future direction of the model development.
Kelvin H. Bates, Mathew J. Evans, Barron H. Henderson, and Daniel J. Jacob
Geosci. Model Dev., 17, 1511–1524, https://doi.org/10.5194/gmd-17-1511-2024, https://doi.org/10.5194/gmd-17-1511-2024, 2024
Short summary
Short summary
Accurate representation of rates and products of chemical reactions in atmospheric models is crucial for simulating concentrations of pollutants and climate forcers. We update the widely used GEOS-Chem atmospheric chemistry model with reaction parameters from recent compilations of experimental data and demonstrate the implications for key atmospheric chemical species. The updates decrease tropospheric CO mixing ratios and increase stratospheric nitrogen oxide mixing ratios, among other changes.
Heather Simon, Christian Hogrefe, Andrew Whitehill, Kristen M. Foley, Jennifer Liljegren, Norm Possiel, Benjamin Wells, Barron H. Henderson, Lukas C. Valin, Gail Tonnesen, K. Wyat Appel, and Shannon Koplitz
Atmos. Chem. Phys., 24, 1855–1871, https://doi.org/10.5194/acp-24-1855-2024, https://doi.org/10.5194/acp-24-1855-2024, 2024
Short summary
Short summary
We assess observed and modeled ozone weekend–weekday differences in the USA from 2002–2019. A subset of urban areas that were NOx-saturated at the beginning of the period transitioned to NOx-limited conditions. Multiple rural areas of California were NOx-limited for the entire period but become less influenced by local day-of-week emission patterns in more recent years. The model produces more NOx-saturated conditions than the observations but captures trends in weekend–weekday ozone patterns.
Benjamin N. Murphy, Darrell Sonntag, Karl M. Seltzer, Havala O. T. Pye, Christine Allen, Evan Murray, Claudia Toro, Drew R. Gentner, Cheng Huang, Shantanu Jathar, Li Li, Andrew A. May, and Allen L. Robinson
Atmos. Chem. Phys., 23, 13469–13483, https://doi.org/10.5194/acp-23-13469-2023, https://doi.org/10.5194/acp-23-13469-2023, 2023
Short summary
Short summary
We update methods for calculating organic particle and vapor emissions from mobile sources in the USA. Conventionally, particulate matter (PM) and volatile organic carbon (VOC) are speciated without consideration of primary semivolatile emissions. Our methods integrate state-of-the-science speciation profiles and correct for common artifacts when sampling emissions in a laboratory. We quantify impacts of the emission updates on ambient pollution with the Community Multiscale Air Quality model.
Olivia E. Clifton, Donna Schwede, Christian Hogrefe, Jesse O. Bash, Sam Bland, Philip Cheung, Mhairi Coyle, Lisa Emberson, Johannes Flemming, Erick Fredj, Stefano Galmarini, Laurens Ganzeveld, Orestis Gazetas, Ignacio Goded, Christopher D. Holmes, László Horváth, Vincent Huijnen, Qian Li, Paul A. Makar, Ivan Mammarella, Giovanni Manca, J. William Munger, Juan L. Pérez-Camanyo, Jonathan Pleim, Limei Ran, Roberto San Jose, Sam J. Silva, Ralf Staebler, Shihan Sun, Amos P. K. Tai, Eran Tas, Timo Vesala, Tamás Weidinger, Zhiyong Wu, and Leiming Zhang
Atmos. Chem. Phys., 23, 9911–9961, https://doi.org/10.5194/acp-23-9911-2023, https://doi.org/10.5194/acp-23-9911-2023, 2023
Short summary
Short summary
A primary sink of air pollutants is dry deposition. Dry deposition estimates differ across the models used to simulate atmospheric chemistry. Here, we introduce an effort to examine dry deposition schemes from atmospheric chemistry models. We provide our approach’s rationale, document the schemes, and describe datasets used to drive and evaluate the schemes. We also launch the analysis of results by evaluating against observations and identifying the processes leading to model–model differences.
Bryan K. Place, William T. Hutzell, K. Wyat Appel, Sara Farrell, Lukas Valin, Benjamin N. Murphy, Karl M. Seltzer, Golam Sarwar, Christine Allen, Ivan R. Piletic, Emma L. D'Ambro, Emily Saunders, Heather Simon, Ana Torres-Vasquez, Jonathan Pleim, Rebecca H. Schwantes, Matthew M. Coggon, Lu Xu, William R. Stockwell, and Havala O. T. Pye
Atmos. Chem. Phys., 23, 9173–9190, https://doi.org/10.5194/acp-23-9173-2023, https://doi.org/10.5194/acp-23-9173-2023, 2023
Short summary
Short summary
Ground-level ozone is a pollutant with adverse human health and ecosystem effects. Air quality models allow scientists to understand the chemical production of ozone and demonstrate impacts of air quality management plans. In this work, the role of multiple systems in ozone production was investigated for the northeastern US in summer. Model updates to chemical reaction rates and monoterpene chemistry were most influential in decreasing predicted ozone and improving agreement with observations.
Christian Hogrefe, Jesse O. Bash, Jonathan E. Pleim, Donna B. Schwede, Robert C. Gilliam, Kristen M. Foley, K. Wyat Appel, and Rohit Mathur
Atmos. Chem. Phys., 23, 8119–8147, https://doi.org/10.5194/acp-23-8119-2023, https://doi.org/10.5194/acp-23-8119-2023, 2023
Short summary
Short summary
Under the umbrella of the fourth phase of the Air Quality Model Evaluation International Initiative (AQMEII4), this study applies AQMEII4 diagnostic tools to better characterize how dry deposition removes pollutants from the atmosphere in the widely used CMAQ model. The results illustrate how these tools can provide insights into similarities and differences between the two CMAQ dry deposition options that affect simulated pollutant budgets and ecosystem impacts from atmospheric pollution.
Monica Crippa, Diego Guizzardi, Tim Butler, Terry Keating, Rosa Wu, Jacek Kaminski, Jeroen Kuenen, Junichi Kurokawa, Satoru Chatani, Tazuko Morikawa, George Pouliot, Jacinthe Racine, Michael D. Moran, Zbigniew Klimont, Patrick M. Manseau, Rabab Mashayekhi, Barron H. Henderson, Steven J. Smith, Harrison Suchyta, Marilena Muntean, Efisio Solazzo, Manjola Banja, Edwin Schaaf, Federico Pagani, Jung-Hun Woo, Jinseok Kim, Fabio Monforti-Ferrario, Enrico Pisoni, Junhua Zhang, David Niemi, Mourad Sassi, Tabish Ansari, and Kristen Foley
Earth Syst. Sci. Data, 15, 2667–2694, https://doi.org/10.5194/essd-15-2667-2023, https://doi.org/10.5194/essd-15-2667-2023, 2023
Short summary
Short summary
This study responds to the global and regional atmospheric modelling community's need for a mosaic of air pollutant emissions with global coverage, long time series, spatially distributed data at a high time resolution, and a high sectoral resolution in order to enhance the understanding of transboundary air pollution. The mosaic approach to integrating official regional emission inventories with a global inventory based on a consistent methodology ensures policy-relevant results.
Havala O. T. Pye, Bryan K. Place, Benjamin N. Murphy, Karl M. Seltzer, Emma L. D'Ambro, Christine Allen, Ivan R. Piletic, Sara Farrell, Rebecca H. Schwantes, Matthew M. Coggon, Emily Saunders, Lu Xu, Golam Sarwar, William T. Hutzell, Kristen M. Foley, George Pouliot, Jesse Bash, and William R. Stockwell
Atmos. Chem. Phys., 23, 5043–5099, https://doi.org/10.5194/acp-23-5043-2023, https://doi.org/10.5194/acp-23-5043-2023, 2023
Short summary
Short summary
Chemical mechanisms describe how emissions from vehicles, vegetation, and other sources are chemically transformed in the atmosphere to secondary products including criteria and hazardous air pollutants. The Community Regional Atmospheric Chemistry Multiphase Mechanism integrates gas-phase radical chemistry with pathways to fine-particle mass. New species were implemented, resulting in a bottom-up representation of organic aerosol, which is required for accurate source attribution of pollutants.
James D. East, Barron H. Henderson, Sergey L. Napelenok, Shannon N. Koplitz, Golam Sarwar, Robert Gilliam, Allen Lenzen, Daniel Q. Tong, R. Bradley Pierce, and Fernando Garcia-Menendez
Atmos. Chem. Phys., 22, 15981–16001, https://doi.org/10.5194/acp-22-15981-2022, https://doi.org/10.5194/acp-22-15981-2022, 2022
Short summary
Short summary
We present a framework that uses a computer model of air quality, along with air pollution data from satellite instruments, to estimate emissions of nitrogen oxides (NOx) across the Northern Hemisphere. The framework, which advances current methods to infer emissions from satellite observations, provides observationally constrained NOx estimates, including in regions of the world where emissions are highly uncertain, and can improve simulations of air pollutants relevant for health and policy.
Sarah E. Benish, Jesse O. Bash, Kristen M. Foley, K. Wyat Appel, Christian Hogrefe, Robert Gilliam, and George Pouliot
Atmos. Chem. Phys., 22, 12749–12767, https://doi.org/10.5194/acp-22-12749-2022, https://doi.org/10.5194/acp-22-12749-2022, 2022
Short summary
Short summary
We assess Community Multiscale Air Quality (CMAQ) model simulations of nitrogen and sulfur deposition over US climate regions to evaluate the model ability to reproduce long-term deposition trends and total deposition budgets. A measurement–model fusion technique is found to improve estimates of wet deposition. Emission controls set by the Clean Air Act successfully decreased oxidized nitrogen deposition across the US; we find increasing amounts of reduced nitrogen to the total nitrogen budget.
Mengying Li, Shaocai Yu, Xue Chen, Zhen Li, Yibo Zhang, Zhe Song, Weiping Liu, Pengfei Li, Xiaoye Zhang, Meigen Zhang, Yele Sun, Zirui Liu, Caiping Sun, Jingkun Jiang, Shuxiao Wang, Benjamin N. Murphy, Kiran Alapaty, Rohit Mathur, Daniel Rosenfeld, and John H. Seinfeld
Atmos. Chem. Phys., 22, 11845–11866, https://doi.org/10.5194/acp-22-11845-2022, https://doi.org/10.5194/acp-22-11845-2022, 2022
Short summary
Short summary
This study constructed an emission inventory of condensable particulate matter (CPM) in China with a focus on organic aerosols (OAs), based on collected CPM emission information. The results show that OA emissions are enhanced twofold for the years 2014 and 2017 after the inclusion of CPM in the new inventory. Sensitivity cases demonstrated the significant contributions of CPM emissions from stationary combustion and mobile sources to primary, secondary, and total OA concentrations.
Elyse A. Pennington, Karl M. Seltzer, Benjamin N. Murphy, Momei Qin, John H. Seinfeld, and Havala O. T. Pye
Atmos. Chem. Phys., 21, 18247–18261, https://doi.org/10.5194/acp-21-18247-2021, https://doi.org/10.5194/acp-21-18247-2021, 2021
Short summary
Short summary
Volatile chemical products (VCPs) are commonly used consumer and industrial items that contribute to the formation of atmospheric aerosol. We implemented the emissions and chemistry of VCPs in a regional-scale model and compared predictions with measurements made in Los Angeles. Our results reduced model bias and suggest that VCPs may contribute up to half of anthropogenic secondary organic aerosol in Los Angeles and are an important source of human-influenced particular matter in urban areas.
Stefano Galmarini, Paul Makar, Olivia E. Clifton, Christian Hogrefe, Jesse O. Bash, Roberto Bellasio, Roberto Bianconi, Johannes Bieser, Tim Butler, Jason Ducker, Johannes Flemming, Alma Hodzic, Christopher D. Holmes, Ioannis Kioutsioukis, Richard Kranenburg, Aurelia Lupascu, Juan Luis Perez-Camanyo, Jonathan Pleim, Young-Hee Ryu, Roberto San Jose, Donna Schwede, Sam Silva, and Ralf Wolke
Atmos. Chem. Phys., 21, 15663–15697, https://doi.org/10.5194/acp-21-15663-2021, https://doi.org/10.5194/acp-21-15663-2021, 2021
Short summary
Short summary
This technical note presents the research protocols for phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4). This initiative has three goals: (i) to define the state of wet and dry deposition in regional models, (ii) to evaluate how dry deposition influences air concentration and flux predictions, and (iii) to identify the causes for prediction differences. The evaluation compares LULC-specific dry deposition and effective conductances and fluxes.
Syuichi Itahashi, Rohit Mathur, Christian Hogrefe, Sergey L. Napelenok, and Yang Zhang
Geosci. Model Dev., 14, 5751–5768, https://doi.org/10.5194/gmd-14-5751-2021, https://doi.org/10.5194/gmd-14-5751-2021, 2021
Short summary
Short summary
The Community Multiscale Air Quality (CMAQ) modeling system extended for hemispheric-scale applications (H-CMAQ) incorporated the satellite-constrained degassing SO2 emissions from 50 volcanos across the Northern Hemisphere. The impact on tropospheric sulfate aerosol (SO42−) is assessed for 2010. Although the considered volcanic emissions occurred at or below the middle of free troposphere (500 hPa), SO42− enhancements of more than 10 % were detected up to the top of free troposphere (250 hPa).
Xiaoyang Chen, Yang Zhang, Kai Wang, Daniel Tong, Pius Lee, Youhua Tang, Jianping Huang, Patrick C. Campbell, Jeff Mcqueen, Havala O. T. Pye, Benjamin N. Murphy, and Daiwen Kang
Geosci. Model Dev., 14, 3969–3993, https://doi.org/10.5194/gmd-14-3969-2021, https://doi.org/10.5194/gmd-14-3969-2021, 2021
Short summary
Short summary
The continuously updated National Air Quality Forecast Capability (NAQFC) provides air quality forecasts. To support the development of the next-generation NAQFC, we evaluate a prototype of GFSv15-CMAQv5.0.2. The performance and the potential improvements for the system are discussed. This study can provide a scientific basis for further development of NAQFC and help it to provide more accurate air quality forecasts to the public over the contiguous United States.
Benjamin N. Murphy, Christopher G. Nolte, Fahim Sidi, Jesse O. Bash, K. Wyat Appel, Carey Jang, Daiwen Kang, James Kelly, Rohit Mathur, Sergey Napelenok, George Pouliot, and Havala O. T. Pye
Geosci. Model Dev., 14, 3407–3420, https://doi.org/10.5194/gmd-14-3407-2021, https://doi.org/10.5194/gmd-14-3407-2021, 2021
Short summary
Short summary
The algorithms for applying air pollution emission rates in the Community Multiscale Air Quality (CMAQ) model have been improved to better support users and developers. The new features accommodate emissions perturbation studies that are typical in atmospheric research and output a wealth of metadata for each model run so assumptions can be verified and documented. The new approach dramatically enhances the transparency and functionality of this critical aspect of atmospheric modeling.
K. Wyat Appel, Jesse O. Bash, Kathleen M. Fahey, Kristen M. Foley, Robert C. Gilliam, Christian Hogrefe, William T. Hutzell, Daiwen Kang, Rohit Mathur, Benjamin N. Murphy, Sergey L. Napelenok, Christopher G. Nolte, Jonathan E. Pleim, George A. Pouliot, Havala O. T. Pye, Limei Ran, Shawn J. Roselle, Golam Sarwar, Donna B. Schwede, Fahim I. Sidi, Tanya L. Spero, and David C. Wong
Geosci. Model Dev., 14, 2867–2897, https://doi.org/10.5194/gmd-14-2867-2021, https://doi.org/10.5194/gmd-14-2867-2021, 2021
Short summary
Short summary
This paper details the scientific updates in the recently released CMAQ version 5.3 (and v5.3.1) and also includes operational and diagnostic evaluations of CMAQv5.3.1 against observations and the previous version of the CMAQ (v5.2.1). This work was done to improve the underlying science in CMAQ. This article is used to inform the CMAQ modeling community of the updates to the modeling system and the expected change in model performance from these updates (versus the previous model version).
Qian Shu, Benjamin Murphy, Jonathan E. Pleim, Donna Schwede, Barron H. Henderson, Havala O.T. Pye, Keith Wyat Appel, Tanvir R. Khan, and Judith A. Perlinger
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-129, https://doi.org/10.5194/gmd-2021-129, 2021
Preprint withdrawn
Short summary
Short summary
We have bridged the gap between dry deposition measurement and modeling by rigorous use of box and regional transport models and field measurements, but more efforts are needed. This study highlights that deviation among deposition schemes is most pronounced for small and large particles. This study better links model predictions to available real-world observations and incrementally reduces uncertainties in the magnitude of loss processes important for the lifecycle of air pollutants.
Karl M. Seltzer, Elyse Pennington, Venkatesh Rao, Benjamin N. Murphy, Madeleine Strum, Kristin K. Isaacs, and Havala O. T. Pye
Atmos. Chem. Phys., 21, 5079–5100, https://doi.org/10.5194/acp-21-5079-2021, https://doi.org/10.5194/acp-21-5079-2021, 2021
Short summary
Short summary
Volatile chemical products (VCPs) are an increasingly important source of anthropogenic reactive organic carbon emissions. Here, we develop VCPy, a new framework to model organic emissions from VCPs throughout the United States. At the national-level, VCPy emissions are broadly consistent with the US EPA’s 2017 National Emission Inventory, however county-level and categorical estimates can differ substantially. An observational evaluation indicates high fidelity in the methods employed here.
Yilin Chen, Huizhong Shen, Jennifer Kaiser, Yongtao Hu, Shannon L. Capps, Shunliu Zhao, Amir Hakami, Jhih-Shyang Shih, Gertrude K. Pavur, Matthew D. Turner, Daven K. Henze, Jaroslav Resler, Athanasios Nenes, Sergey L. Napelenok, Jesse O. Bash, Kathleen M. Fahey, Gregory R. Carmichael, Tianfeng Chai, Lieven Clarisse, Pierre-François Coheur, Martin Van Damme, and Armistead G. Russell
Atmos. Chem. Phys., 21, 2067–2082, https://doi.org/10.5194/acp-21-2067-2021, https://doi.org/10.5194/acp-21-2067-2021, 2021
Short summary
Short summary
Ammonia (NH3) emissions can exert adverse impacts on air quality and ecosystem well-being. NH3 emission inventories are viewed as highly uncertain. Here we optimize the NH3 emission estimates in the US using an air quality model and NH3 measurements from the IASI satellite instruments. The optimized NH3 emissions are much higher than the National Emissions Inventory estimates in April. The optimized NH3 emissions improved model performance when evaluated against independent observation.
Huiying Luo, Marina Astitha, Christian Hogrefe, Rohit Mathur, and S. Trivikrama Rao
Atmos. Chem. Phys., 20, 13801–13815, https://doi.org/10.5194/acp-20-13801-2020, https://doi.org/10.5194/acp-20-13801-2020, 2020
Short summary
Short summary
A new method is introduced to evaluate nonlinear, nonstationary modeled PM2.5 time series by decomposing decadal PM2.5 concentrations and its species onto various timescales. It does not require preselection of temporal scales and assumptions of linearity and stationarity. It provides a unique opportunity to assess the influence of each species on total PM2.5. The results reveal a phase shift in modeled EC/OC concentrations, indicating the need for improved model treatment of organic aerosols.
Amy E. Christiansen, Annmarie G. Carlton, and Barron H. Henderson
Atmos. Chem. Phys., 20, 11607–11624, https://doi.org/10.5194/acp-20-11607-2020, https://doi.org/10.5194/acp-20-11607-2020, 2020
Short summary
Short summary
We quantify differences in surface-level fine particle mass (PM2.5) chemical composition in relation to satellite-derived cloud flags and find significant differences between clear-sky and cloud days. The work suggests that future analysis in this area is warranted.
Cited articles
Atkinson, R.:
Atmospheric Chemistry of VOCS and NOx, Atmos. Environ., 34, 2063–2101, https://doi.org/10.1016/s1352-2310(99)00460-4, 2000.
Baker, K. R., Woody, M. C., Tonnesen, G. S., Hutzell, W., Pye, H. O. T., Beaver, M. R., Pouliot, G., and Pierce, T.:
Contribution of regional-scale fire events to ozone and PM2.5 Air Quality estimated by photochemical modeling approaches, Atmos. Environ., 140, 539–554, https://doi.org/10.1016/j.atmosenv.2016.06.032, 2016.
Bash, J. O., Baker, K. R., and Beaver, M. R.:
Evaluation of improved land use and canopy representation in BEIS v3.61 with biogenic VOC measurements in California, Geosci. Model Dev., 9, 2191–2207, https://doi.org/10.5194/gmd-9-2191-2016, 2016.
Booker, F., Muntifering, R., McGrath, M., Burkey, K., Decoteau, D., Fiscus, E., Manning, W., Krupa, S., Chappelka, A., and Grantz, D.:
The ozone component of Global Change: Potential Effects on agricultural and horticultural plant yield, product quality and interactions with invasive species, J. Integr. Plant Biol., 51, 337–351, https://doi.org/10.1111/j.1744-7909.2008.00805.x, 2009.
Burr, M. J. and Zhang, Y.:
Source apportionment of fine particulate matter over the Eastern U. S. Part I: Source sensitivity simulations using CMAQ with the brute force method, Atmos. Pollut. Res., 2, 300–317, https://doi.org/10.5094/apr.2011.036, 2011.
Butler, T., Lupascu, A., Coates, J., and Zhu, S.:
TOAST 1.0: Tropospheric Ozone Attribution of Sources with Tagging for CESM 1.2.2, Geosci. Model Dev., 11, 2825–2840, https://doi.org/10.5194/gmd-11-2825-2018, 2018.
Cohan, D. S. and Napelenok, S. L.:
Air Quality Response Modeling for Decision Support, Atmosphere, 2, 407–425, https://doi.org/10.3390/atmos2030407, 2011.
Cooper, O. R., Langford, A. O., Parrish, D. D., and Fahey, D. W.:
Challenges of a lowered U. S. Ozone Standard, Science, 348, 1096–1097, https://doi.org/10.1126/science.aaa5748, 2015.
Duncan, B. N., Yoshida, Y., de Foy, B., Lamsal, L. N., Streets, D. G., Lu, Z., Pickering, K. E., and Krotkov, N. A.:
The observed response of Ozone Monitoring Instrument (OMI) no2 columns to nox emission controls on power plants in the United States: 2005–2011, Atmos. Environ., 81, 102–111, https://doi.org/10.1016/j.atmosenv.2013.08.068, 2013.
Dunker, A. M., Yarwood, G., Ortmann, J. P., and Wilson, G. M.:
Comparison of source apportionment and source sensitivity of ozone in a three-dimensional air quality model, Environ. Sci. Technol., 36, 2953–2964, https://doi.org/10.1021/es011418f, 2002.
Emery, C., Tai, E., Yarwood, G., and Morris, R.:
Investigation into approaches to reduce excessive vertical transport over complex terrain in a regional photochemical grid model, Atmos. Environ., 45, 7341–7351, https://doi.org/10.1016/j.atmosenv.2011.07.052, 2011.
Emery, C., Jung, J., Koo, B., and Yarwood, G.:
Improvements to CAMx Snow Cover Treatments and Carbon Bond Chemical Mechanism for Winter Ozone, Final report for Utah Department of Environmental Quality, Division of Air Quality, Salt Lake City, UT, Ramboll US Corporation, http://www.camx.com/files/udaq_snowchem_final_6aug15.pdf (last access: 13 December 2019), 2015.
Emery, C., Koo, B., Hsieh, W. C., Wetland, A., Wilson, G., and Yarwood, G.:
Technical Memorandum for Updated Carbon Bond Chemical Mechanism, EPA Contract EPD12044, https://www.camx.com/files/emaq4-07_task7_techmemo_r1_1aug16.pdf (last access: 1 February 2023), 2016a.
Emery, C., Liu, Z., Koo, B., and Yarwood, G.:
Improved Halogen Chemistry for CAMx Modeling, Final report for Texas Commission on Environmental Quality, Ramboll US Corporation, https://wayback.archive-it.org/414/20210529060701/https://www.tceq.texas.gov/assets/public/implementation/air/am/contracts/reports/pm/5821661842FY1613-20160526-environ-CAMx_Halogens.pdf (last access: 13 December 2019), 2016b.
Gillani, N. V. and Pleim, J. E.:
Sub-grid-scale features of anthropogenic emissions of NOx and VOC in the context of regional Eulerian models, Atmos. Environ., 30, 2043–2059, https://doi.org/10.1016/1352-2310(95)00201-4, 1996.
Grewe, V., Tsati, E., and Hoor, P.:
On the attribution of contributions of atmospheric trace gases to emissions in atmospheric model applications, Geosci. Model Dev., 3, 487–499, https://doi.org/10.5194/gmd-3-487-2010, 2010.
Henderson, B. H., Akhtar, F., Pye, H. O. T., Napelenok, S. L., and Hutzell, W. T.:
A database and tool for boundary conditions for regional air quality modeling: description and evaluation, Geosci. Model Dev., 7, 339–360, https://doi.org/10.5194/gmd-7-339-2014, 2014.
Hidy, G. M. and Friedlander, S. K.:
The nature of the Los Angeles aerosol, Proceedings of the Second International Clean Air Congress, Washington, D.C., 6–11 December 1970, 391–404, https://doi.org/10.1016/b978-0-12-239450-8.50081-2, 1971.
Hong, S.-Y., Noh, Y., and Dudhia, J.:
A new vertical diffusion package with an explicit treatment of entrainment processes, Mon. Weather Rev., 134, 2318–2341, https://doi.org/10.1175/mwr3199.1, 2006.
Jacob, D. J. and Winner, D. A.:
Effect of climate change on air quality, Atmos. Environ., 43, 51–63, https://doi.org/10.1016/j.atmosenv.2008.09.051, 2009.
Jacquemin, B. and Noilhan, J.:
Sensitivity study and validation of a land surface parameterization using the HAPEX-MOBILHY data set, Bound.-Lay. Meteorol., 52, 93–134, https://doi.org/10.1007/bf00123180, 1990.
Jiménez, P.:
Ozone response to precursor controls in very complex terrains: Use of photochemical indicators to assess O3-nox-voc sensitivity in the northeastern Iberian Peninsula, J. Geophys. Res.-Atmos., 109, D20309, https://doi.org/10.1029/2004jd004985, 2004.
Karamchandani, P., Long, Y., Pirovano, G., Balzarini, A., and Yarwood, G.:
Source-sector contributions to European ozone and fine PM in 2010 using AQMEII modeling data, Atmos. Chem. Phys., 17, 5643–5664, https://doi.org/10.5194/acp-17-5643-2017, 2017.
Koo, B., Wilson, G. M., Morris, R. E., Dunker, A. M., and Yarwood, G.:
Comparison of source apportionment and sensitivity analysis in a particulate matter air quality model, Environ. Sci. Technol., 43, 6669–6675, https://doi.org/10.1021/es9008129, 2009.
Kwok, R. H. F., Napelenok, S. L., and Baker, K. R.:
Implementation and evaluation of PM2.5 Source Contribution Analysis in a photochemical model, Atmos. Environ., 80, 398–407, https://doi.org/10.1016/j.atmosenv.2013.08.017, 2013.
Kwok, R. H. F., Baker, K. R., Napelenok, S. L., and Tonnesen, G. S.:
Photochemical grid model implementation and application of VOC, NOx, and O3 source apportionment, Geosci. Model Dev., 8, 99–114, https://doi.org/10.5194/gmd-8-99-2015, 2015.
Lamsal, L. N., Duncan, B. N., Yoshida, Y., Krotkov, N. A., Pickering, K. E., Streets, D. G., and Lu, Z.:
U.S. NO2 trends (2005–2013): EPA Air Quality System (AQS) data versus improved observations from the Ozone Monitoring Instrument (OMI), Atmos. Environ., 110, 130–143, https://doi.org/10.1016/j.atmosenv.2015.03.055, 2015.
Lefohn, A. S., Shadwick, D. S., and Ziman, S. D.:
Peer reviewed: The Difficult Challenge of attaining EPA's new Ozone Standard, Environ. Sci. Technol., 32, 276A–282A, https://doi.org/10.1021/es983569x, 1998.
Li, Y., Lau, A. K.-H., Fung, J. C.-H., Zheng, J. Y., Zhong, L. J., and Louie, P. K.:
Ozone Source Apportionment (osat) to differentiate local regional and super-regional source contributions in the Pearl River Delta region, China, J. Geophys. Res.-Atmos., 117, D15305, https://doi.org/10.1029/2011jd017340, 2012.
Marmur, A., Unal, A., Mulholland, J. A., and Russell, A. G.:
Optimization-based source apportionment of PM2.5 incorporating gas-to-particle ratios, Environ. Sci. Technol., 39, 3245–3254, https://doi.org/10.1021/es0490121, 2005.
Paatero, P. and Tapper, U.:
Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values, Environmetrics, 5, 111–126, https://doi.org/10.1002/env.3170050203, 1994.
Pay, M. T., Gangoiti, G., Guevara, M., Napelenok, S., Querol, X., Jorba, O., and Pérez García-Pando, C.:
Ozone source apportionment during peak summer events over southwestern Europe, Atmos. Chem. Phys., 19, 5467–5494, https://doi.org/10.5194/acp-19-5467-2019, 2019.
Pleim, J. and Ran, L.:
Surface flux modeling for air quality applications, Atmosphere, 2, 271–302, https://doi.org/10.3390/atmos2030271, 2011.
Ramboll Environ:
Improved OSAT, APCA and PSAT Algorithms for CAMx, Final report for Texas Commission on Environmental Quality, Ramboll US Corporation, https://wayback.archive-it.org/414/20210529064528/https://www.tceq.texas.gov/assets/public/implementation/air/am/contracts/reports/pm/5825543880FY1511-20150817-improved_OSAT_APCA_PSAT_for_CAMx.pdf (last access: 18 December 2021), 2015.
Ramboll Environ:
Implementation of the Piecewise Parabolic Method for Vertical Advection in Comprehensive Air Quality Model with Extensions (CAMx), Final report for Texas Commission on Environmental Quality, Ramboll US Corporation, https://www.tceq.texas.gov/downloads/air-quality/research/reports/photochemical/5822231153028-20220616-ramboll-camx_ppm_implementation.pdf (last access: 10 January 2023), 2022.
Reitze Jr., A. W.:
Air Quality Protection Using State Implementation Plans-Thirty-Seven Years of Increasing Complexity, Vill. Envtl. L. J., 15, 209, https://digitalcommons.law.villanova.edu/elj/vol15/iss2/1 (last access: 10 January 2023), 2004.
Sarwar, G., Gantt, B., Schwede, D., Foley, K., Mathur, R., and Saiz-Lopez, A.:
Impact of enhanced ozone deposition and halogen chemistry on tropospheric ozone over the Northern Hemisphere, Environ. Sci. Technol., 49, 9203–9211, https://doi.org/10.1021/acs.est.5b01657, 2015.
Sarwar, G., Gantt, B., Foley, K., Fahey, K., Spero, T. L., Kang, D., Mathur, R., Foroutan, H., Xing, J., Sherwen, T., and Saiz-Lopez, A.:
Influence of bromine and iodine chemistry on annual, seasonal, diurnal, and background ozone: CMAQ simulations over the Northern Hemisphere, Atmos. Environ., 213, 395–404, https://doi.org/10.1016/j.atmosenv.2019.06.020, 2019.
Shu, L., Wang, T., Han, H., Xie, M., Chen, P., Li, M., and Wu, H.:
Summertime ozone pollution in the Yangtze River Delta of eastern China during 2013–2017: Synoptic impacts and source apportionment, Environ. Pollut., 257, 113631, https://doi.org/10.1016/j.envpol.2019.113631, 2020.
Shu, Q., Koo, B., Yarwood, G., and Henderson, B. H.:
Strong influence of deposition and vertical mixing on secondary organic aerosol concentrations in CMAQ and CAMx, Atmos. Environ., 171, 317–329, https://doi.org/10.1016/j.atmosenv.2017.10.035, 2017.
Shu, Q., Murphy, B., Schwede, D., Henderson, B. H., Pye, H. O. T., Appel, K. W., Khan, T. R., and Perlinger, J. A.:
Improving the particle dry deposition scheme in the CMAQ photochemical modeling system, Atmos. Environ., 289, 119343, https://doi.org/10.1016/j.atmosenv.2022.119343, 2022.
Sillman, S.:
The use of NOy, H2O2, and HNO3 as indicators for ozone-nox-hydrocarbon sensitivity in urban locations, J. Geophys. Res.-Atmos., 100, 14175, https://doi.org/10.1029/94jd02953, 1995.
Simon, H., Reff, A., Wells, B., Xing, J., and Frank, N.:
Ozone trends across the United States over a period of decreasing NOx and VOC emissions, Environ. Sci. Technol., 49, 186–195, https://doi.org/10.1021/es504514z, 2014.
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D., Duda, M. G., and Powers, J. G.:
A Description of the Advanced Research WRF Version 3 (No. NCAR/TN-475+STR), UCAR/NCAR, University Corporation for Atmospheric Research, https://doi.org/10.5065/D68S4MVH, 2008.
Smagorinsky, J.:
General circulation experiments with the primitive equations, Mon. Weather Rev., 91, 99–164, https://doi.org/10.1175/1520-0493(1963)091<0099:gcewtp>2.3.co;2, 1963.
Stein, U. and Alpert, P.: Factor Separation in Numerical Simulations, J. Atmos. Sci., 50, 2107–2115, https://doi.org/10.1175/1520-0469(1993)050<2107:FSINS>2.0.CO;2, 1993.
U.S. EPA:
CMAQ, Zenodo [code], https://doi.org/10.5281/zenodo.3585898, 2019.
U.S. EPA:
2016 Version 1 Technical Support Document, U.S. EPA, https://www.epa.gov/air-emissions-modeling/2016-version-1-technical-support-document (last access: 13 December 2022), 2021.
U.S. EPA:
CMAQ, Zenodo [code], https://doi.org/10.5281/zenodo.7218076, 2022a.
U.S. EPA:
CMAQ ISAM, Zenodo [code], https://doi.org/10.5281/zenodo.6266674, 2022b.
U.S. EPA: Air Quality System (AQS), U.S. EPA [data set], https://www.epa.gov/aqs, last access: 1 March 2022c.
Valverde, V., Pay, M. T., and Baldasano, J. M.:
Ozone attributed to Madrid and Barcelona on-road transport emissions: Characterization of plume dynamics over the Iberian Peninsula, Sci. Total Environ., 543, 670–682, https://doi.org/10.1016/j.scitotenv.2015.11.070, 2016.
Watson, J. G., Cooper, J. A., and Huntzicker, J. J.:
The effective variance weighting for least squares calculations applied to the mass balance receptor model, Atmos. Environ. (1967), 18, 1347–1355, https://doi.org/10.1016/0004-6981(84)90043-x, 1984.
WHO:
Global tuberculosis report 2013, World Health Organization, https://apps.who.int/iris/handle/10665/91355 (last access: 7 December 2022), 2013.
Yarwood, G., Morris, R. E., and Wilson, G. M.:
Particulate Matter Source Apportionment Technology (PSAT) in the CAMx Photochemical Grid Model, in: Air Pollution Modeling and Its Application XVII, edited by: Borrego, C. and Norman, A.-L., Springer, Boston, MA, 478–492, https://doi.org/10.1007/978-0-387-68854-1_52, 2007.
Yienger, J. J. and Levy, H.:
Empirical model of global soil-biogenic NOx emissions J. Geophys. Res.-Atmos., 100, 11447, https://doi.org/10.1029/95jd00370, 1995.
Zhang, L.:
A size-segregated particle dry deposition scheme for an atmospheric aerosol module, Atmos. Environ., 35, 549–560, https://doi.org/10.1016/s1352-2310(00)00326-5, 2001.
Zhang, L., Brook, J. R., and Vet, R.:
A revised parameterization for gaseous dry deposition in air-quality models, Atmos. Chem. Phys., 3, 2067–2082, https://doi.org/10.5194/acp-3-2067-2003, 2003.
Zhang, L., Jacob, D. J., Kopacz, M., Henze, D. K., Singh, K., and Jaffe, D. A.:
Intercontinental source attribution of ozone pollution at Western U. S. sites using an adjoint method, Geophys. Res. Lett., 36, https://doi.org/10.1029/2009gl037950, 2009.
Zhang, R., Cohan, A., Pour Biazar, A., and Cohan, D. S.:
Source apportionment of biogenic contributions to Ozone Formation over the United States, Atmos. Environ., 164, 8–19, https://doi.org/10.1016/j.atmosenv.2017.05.044, 2017.
Short summary
Source attribution methods are generally used to determine culpability of precursor emission sources to ambient pollutant concentrations. However, source attribution of secondarily formed pollutants such as ozone and its precursors cannot be explicitly measured, making evaluation of source apportionment methods challenging. In this study, multiple apportionment approach comparisons show common features but still reveal wide variations in predicted sector contribution and species dependency.
Source attribution methods are generally used to determine culpability of precursor emission...