Articles | Volume 25, issue 10
https://doi.org/10.5194/acp-25-5101-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-5101-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Surface ozone trend variability across the United States and the impact of heat waves (1990–2023)
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, USA
NOAA Chemical Sciences Laboratory, Boulder, CO, USA
Brian C. McDonald
NOAA Chemical Sciences Laboratory, Boulder, CO, USA
Colin Harkins
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, USA
NOAA Chemical Sciences Laboratory, Boulder, CO, USA
Owen R. Cooper
NOAA Chemical Sciences Laboratory, Boulder, CO, USA
Related authors
Yu Yan Cui, Ju-Mee Ryoo, Matthew S. Johnson, Kai-Lan Chang, Emma Yates, Owen R. Cooper, and Laura T. Iraci
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-571, https://doi.org/10.5194/essd-2024-571, 2025
Preprint under review for ESSD
Short summary
Short summary
Atmospheric observations show that free tropospheric ozone has increased across the Northern Hemisphere over the past three decades. The sources driving this increase remain unclear. In this study, we developed a source-receptor relationship database combining harmonized multiplatform ozone data and advanced atmospheric transport modeling. This database can identify emission regions responsible for ozone increases and can also be used to analyze other co-observed atmospheric constituents.
Roeland Van Malderen, Zhou Zang, Kai-Lan Chang, Robin Björklund, Owen R. Cooper, Jane Liu, Eliane Maillard Barras, Corinne Vigouroux, Irina Petropavlovskikh, Thierry Leblanc, Valérie Thouret, Pawel Wolff, Peter Effertz, Audrey Gaudel, David W. Tarasick, Herman G. J. Smit, Anne M. Thompson, Ryan M. Stauffer, Debra E. Kollonige, Deniz Poyraz, Gérard Ancellet, Marie-Renée De Backer, Matthias M. Frey, James W. Hannigan, José L. Hernandez, Bryan J. Johnson, Nicholas Jones, Rigel Kivi, Emmanuel Mahieu, Isamu Morino, Glen McConville, Katrin Müller, Isao Murata, Justus Notholt, Ankie Piters, Maxime Prignon, Richard Querel, Vincenzo Rizi, Dan Smale, Wolfgang Steinbrecht, Kimberly Strong, and Ralf Sussmann
EGUsphere, https://doi.org/10.5194/egusphere-2024-3745, https://doi.org/10.5194/egusphere-2024-3745, 2025
Short summary
Short summary
Tropospheric ozone is an important greenhouse gas and an air pollutant, whose distribution and time variability is mainly governed by anthropogenic emissions and dynamics. In this paper, we assess regional trends of tropospheric ozone column amounts, based on two different approaches of merging or synthesizing ground-based observations and their trends within specific regions. Our findings clearly demonstrate regional trend differences, but also consistently higher pre- than post-COVID trends.
Sebastian H. M. Hickman, Makoto Kelp, Paul T. Griffiths, Kelsey Doerksen, Kazuyuki Miyazaki, Elyse A. Pennington, Gerbrand Koren, Fernando Iglesias-Suarez, Martin G. Schultz, Kai-Lan Chang, Owen R. Cooper, Alexander T. Archibald, Roberto Sommariva, David Carlson, Hantao Wang, J. Jason West, and Zhenze Liu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3739, https://doi.org/10.5194/egusphere-2024-3739, 2025
Short summary
Short summary
Machine learning is being more widely used across environmental and climate science. This work reviews the use of machine learning in tropospheric ozone research, focusing on three main application areas in which significant progress has been made. Common challenges in using machine learning across the three areas are highlighted, and future directions for the field are indicated.
Audrey Gaudel, Ilann Bourgeois, Meng Li, Kai-Lan Chang, Jerald Ziemke, Bastien Sauvage, Ryan M. Stauffer, Anne M. Thompson, Debra E. Kollonige, Nadia Smith, Daan Hubert, Arno Keppens, Juan Cuesta, Klaus-Peter Heue, Pepijn Veefkind, Kenneth Aikin, Jeff Peischl, Chelsea R. Thompson, Thomas B. Ryerson, Gregory J. Frost, Brian C. McDonald, and Owen R. Cooper
Atmos. Chem. Phys., 24, 9975–10000, https://doi.org/10.5194/acp-24-9975-2024, https://doi.org/10.5194/acp-24-9975-2024, 2024
Short summary
Short summary
The study examines tropical tropospheric ozone changes. In situ data from 1994–2019 display increased ozone, notably over India, Southeast Asia, and Malaysia and Indonesia. Sparse in situ data limit trend detection for the 15-year period. In situ and satellite data, with limited sampling, struggle to consistently detect trends. Continuous observations are vital over the tropical Pacific Ocean, Indian Ocean, western Africa, and South Asia for accurate ozone trend estimation in these regions.
Kai-Lan Chang, Owen R. Cooper, Audrey Gaudel, Irina Petropavlovskikh, Peter Effertz, Gary Morris, and Brian C. McDonald
Atmos. Chem. Phys., 24, 6197–6218, https://doi.org/10.5194/acp-24-6197-2024, https://doi.org/10.5194/acp-24-6197-2024, 2024
Short summary
Short summary
A great majority of observational trend studies of free tropospheric ozone use sparsely sampled ozonesonde and aircraft measurements as reference data sets. A ubiquitous assumption is that trends are accurate and reliable so long as long-term records are available. We show that sampling bias due to sparse samples can persistently reduce the trend accuracy, and we highlight the importance of maintaining adequate frequency and continuity of observations.
Davide Putero, Paolo Cristofanelli, Kai-Lan Chang, Gaëlle Dufour, Gregory Beachley, Cédric Couret, Peter Effertz, Daniel A. Jaffe, Dagmar Kubistin, Jason Lynch, Irina Petropavlovskikh, Melissa Puchalski, Timothy Sharac, Barkley C. Sive, Martin Steinbacher, Carlos Torres, and Owen R. Cooper
Atmos. Chem. Phys., 23, 15693–15709, https://doi.org/10.5194/acp-23-15693-2023, https://doi.org/10.5194/acp-23-15693-2023, 2023
Short summary
Short summary
We investigated the impact of societal restriction measures during the COVID-19 pandemic on surface ozone at 41 high-elevation sites worldwide. Negative ozone anomalies were observed for spring and summer 2020 for all of the regions considered. In 2021, negative anomalies continued for Europe and partially for the eastern US, while western US sites showed positive anomalies due to wildfires. IASI satellite data and the Carbon Monitor supported emission reductions as a cause of the anomalies.
Haolin Wang, Xiao Lu, Daniel J. Jacob, Owen R. Cooper, Kai-Lan Chang, Ke Li, Meng Gao, Yiming Liu, Bosi Sheng, Kai Wu, Tongwen Wu, Jie Zhang, Bastien Sauvage, Philippe Nédélec, Romain Blot, and Shaojia Fan
Atmos. Chem. Phys., 22, 13753–13782, https://doi.org/10.5194/acp-22-13753-2022, https://doi.org/10.5194/acp-22-13753-2022, 2022
Short summary
Short summary
We report significant global tropospheric ozone increases in 1995–2017 based on extensive aircraft and ozonesonde observations. Using GEOS-Chem (Goddard Earth Observing System chemistry model) multi-decadal global simulations, we find that changes in global anthropogenic emissions, in particular the rapid increases in aircraft emissions, contribute significantly to the increases in tropospheric ozone and resulting radiative impact.
Kai-Lan Chang, Owen R. Cooper, Audrey Gaudel, Irina Petropavlovskikh, and Valérie Thouret
Atmos. Chem. Phys., 20, 9915–9938, https://doi.org/10.5194/acp-20-9915-2020, https://doi.org/10.5194/acp-20-9915-2020, 2020
Short summary
Short summary
We provide a statistical framework for detecting trends of multiple autocorrelated time series from sparsely sampled profile data. The result is a better and more consistent quantification of trend estimates of vertical profile data. The focus was placed on the long-term ozone time series from commercial aircraft and balloon-borne ozonesonde measurements. This framework can be applied to other trace gases in the atmosphere.
Rodrigo J. Seguel, Charlie Opazo, Yann Cohen, Owen R. Cooper, Laura Gallardo, Björn-Martin Sinnhuber, Florian Obersteiner, Andreas Zahn, Peter Hoor, Susanne Rohs, and Andreas Marsing
Atmos. Chem. Phys., 25, 8553–8573, https://doi.org/10.5194/acp-25-8553-2025, https://doi.org/10.5194/acp-25-8553-2025, 2025
Short summary
Short summary
We explored ozone differences between the Northern Hemisphere and Southern Hemispheres in the upper troposphere–lower stratosphere. We found lower ozone (with stratospheric origin) in the Southern Hemisphere, especially during years of severe ozone depletion. Sudden stratospheric warming events increased the ozone in each hemisphere, highlighting the relationship between stratospheric processes and ozone in the upper troposphere, where ozone is an important greenhouse gas.
Yu Yan Cui, Ju-Mee Ryoo, Matthew S. Johnson, Kai-Lan Chang, Emma Yates, Owen R. Cooper, and Laura T. Iraci
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-571, https://doi.org/10.5194/essd-2024-571, 2025
Preprint under review for ESSD
Short summary
Short summary
Atmospheric observations show that free tropospheric ozone has increased across the Northern Hemisphere over the past three decades. The sources driving this increase remain unclear. In this study, we developed a source-receptor relationship database combining harmonized multiplatform ozone data and advanced atmospheric transport modeling. This database can identify emission regions responsible for ozone increases and can also be used to analyze other co-observed atmospheric constituents.
Chelsea E. Stockwell, Matthew M. Coggon, Rebecca H. Schwantes, Colin Harkins, Bert Verreyken, Congmeng Lyu, Qindan Zhu, Lu Xu, Jessica B. Gilman, Aaron Lamplugh, Jeff Peischl, Michael A. Robinson, Patrick R. Veres, Meng Li, Andrew W. Rollins, Kristen Zuraski, Sunil Baidar, Shang Liu, Toshihiro Kuwayama, Steven S. Brown, Brian C. McDonald, and Carsten Warneke
Atmos. Chem. Phys., 25, 1121–1143, https://doi.org/10.5194/acp-25-1121-2025, https://doi.org/10.5194/acp-25-1121-2025, 2025
Short summary
Short summary
In urban areas, emissions from everyday products like paints, cleaners, and personal care products, along with non-traditional sources such as cooking, are increasingly important and impact air quality. This study uses a box model to evaluate how these emissions impact ozone in the Los Angeles Basin and quantifies the impact of gaseous cooking emissions. Accurate representation of these and other anthropogenic sources in inventories is crucial for informing effective air quality policies.
Roeland Van Malderen, Zhou Zang, Kai-Lan Chang, Robin Björklund, Owen R. Cooper, Jane Liu, Eliane Maillard Barras, Corinne Vigouroux, Irina Petropavlovskikh, Thierry Leblanc, Valérie Thouret, Pawel Wolff, Peter Effertz, Audrey Gaudel, David W. Tarasick, Herman G. J. Smit, Anne M. Thompson, Ryan M. Stauffer, Debra E. Kollonige, Deniz Poyraz, Gérard Ancellet, Marie-Renée De Backer, Matthias M. Frey, James W. Hannigan, José L. Hernandez, Bryan J. Johnson, Nicholas Jones, Rigel Kivi, Emmanuel Mahieu, Isamu Morino, Glen McConville, Katrin Müller, Isao Murata, Justus Notholt, Ankie Piters, Maxime Prignon, Richard Querel, Vincenzo Rizi, Dan Smale, Wolfgang Steinbrecht, Kimberly Strong, and Ralf Sussmann
EGUsphere, https://doi.org/10.5194/egusphere-2024-3745, https://doi.org/10.5194/egusphere-2024-3745, 2025
Short summary
Short summary
Tropospheric ozone is an important greenhouse gas and an air pollutant, whose distribution and time variability is mainly governed by anthropogenic emissions and dynamics. In this paper, we assess regional trends of tropospheric ozone column amounts, based on two different approaches of merging or synthesizing ground-based observations and their trends within specific regions. Our findings clearly demonstrate regional trend differences, but also consistently higher pre- than post-COVID trends.
Sebastian H. M. Hickman, Makoto Kelp, Paul T. Griffiths, Kelsey Doerksen, Kazuyuki Miyazaki, Elyse A. Pennington, Gerbrand Koren, Fernando Iglesias-Suarez, Martin G. Schultz, Kai-Lan Chang, Owen R. Cooper, Alexander T. Archibald, Roberto Sommariva, David Carlson, Hantao Wang, J. Jason West, and Zhenze Liu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3739, https://doi.org/10.5194/egusphere-2024-3739, 2025
Short summary
Short summary
Machine learning is being more widely used across environmental and climate science. This work reviews the use of machine learning in tropospheric ozone research, focusing on three main application areas in which significant progress has been made. Common challenges in using machine learning across the three areas are highlighted, and future directions for the field are indicated.
Audrey Gaudel, Ilann Bourgeois, Meng Li, Kai-Lan Chang, Jerald Ziemke, Bastien Sauvage, Ryan M. Stauffer, Anne M. Thompson, Debra E. Kollonige, Nadia Smith, Daan Hubert, Arno Keppens, Juan Cuesta, Klaus-Peter Heue, Pepijn Veefkind, Kenneth Aikin, Jeff Peischl, Chelsea R. Thompson, Thomas B. Ryerson, Gregory J. Frost, Brian C. McDonald, and Owen R. Cooper
Atmos. Chem. Phys., 24, 9975–10000, https://doi.org/10.5194/acp-24-9975-2024, https://doi.org/10.5194/acp-24-9975-2024, 2024
Short summary
Short summary
The study examines tropical tropospheric ozone changes. In situ data from 1994–2019 display increased ozone, notably over India, Southeast Asia, and Malaysia and Indonesia. Sparse in situ data limit trend detection for the 15-year period. In situ and satellite data, with limited sampling, struggle to consistently detect trends. Continuous observations are vital over the tropical Pacific Ocean, Indian Ocean, western Africa, and South Asia for accurate ozone trend estimation in these regions.
Kai-Lan Chang, Owen R. Cooper, Audrey Gaudel, Irina Petropavlovskikh, Peter Effertz, Gary Morris, and Brian C. McDonald
Atmos. Chem. Phys., 24, 6197–6218, https://doi.org/10.5194/acp-24-6197-2024, https://doi.org/10.5194/acp-24-6197-2024, 2024
Short summary
Short summary
A great majority of observational trend studies of free tropospheric ozone use sparsely sampled ozonesonde and aircraft measurements as reference data sets. A ubiquitous assumption is that trends are accurate and reliable so long as long-term records are available. We show that sampling bias due to sparse samples can persistently reduce the trend accuracy, and we highlight the importance of maintaining adequate frequency and continuity of observations.
Qindan Zhu, Rebecca H. Schwantes, Matthew Coggon, Colin Harkins, Jordan Schnell, Jian He, Havala O. T. Pye, Meng Li, Barry Baker, Zachary Moon, Ravan Ahmadov, Eva Y. Pfannerstill, Bryan Place, Paul Wooldridge, Benjamin C. Schulze, Caleb Arata, Anthony Bucholtz, John H. Seinfeld, Carsten Warneke, Chelsea E. Stockwell, Lu Xu, Kristen Zuraski, Michael A. Robinson, J. Andrew Neuman, Patrick R. Veres, Jeff Peischl, Steven S. Brown, Allen H. Goldstein, Ronald C. Cohen, and Brian C. McDonald
Atmos. Chem. Phys., 24, 5265–5286, https://doi.org/10.5194/acp-24-5265-2024, https://doi.org/10.5194/acp-24-5265-2024, 2024
Short summary
Short summary
Volatile organic compounds (VOCs) fuel the production of air pollutants like ozone and particulate matter. The representation of VOC chemistry remains challenging due to its complexity in speciation and reactions. Here, we develop a chemical mechanism, RACM2B-VCP, that better represents VOC chemistry in urban areas such as Los Angeles. We also discuss the contribution of VOCs emitted from volatile chemical products and other anthropogenic sources to total VOC reactivity and O3.
Matthew M. Coggon, Chelsea E. Stockwell, Lu Xu, Jeff Peischl, Jessica B. Gilman, Aaron Lamplugh, Henry J. Bowman, Kenneth Aikin, Colin Harkins, Qindan Zhu, Rebecca H. Schwantes, Jian He, Meng Li, Karl Seltzer, Brian McDonald, and Carsten Warneke
Atmos. Chem. Phys., 24, 4289–4304, https://doi.org/10.5194/acp-24-4289-2024, https://doi.org/10.5194/acp-24-4289-2024, 2024
Short summary
Short summary
Residential and commercial cooking emits pollutants that degrade air quality. Here, ambient observations show that cooking is an important contributor to anthropogenic volatile organic compounds (VOCs) emitted in Las Vegas, NV. These emissions are not fully presented in air quality models, and more work may be needed to quantify emissions from important sources, such as commercial restaurants.
Meng Li, Junichi Kurokawa, Qiang Zhang, Jung-Hun Woo, Tazuko Morikawa, Satoru Chatani, Zifeng Lu, Yu Song, Guannan Geng, Hanwen Hu, Jinseok Kim, Owen R. Cooper, and Brian C. McDonald
Atmos. Chem. Phys., 24, 3925–3952, https://doi.org/10.5194/acp-24-3925-2024, https://doi.org/10.5194/acp-24-3925-2024, 2024
Short summary
Short summary
In this work, we developed MIXv2, a mosaic Asian emission inventory for 2010–2017. With high spatial (0.1°) and monthly temporal resolution, MIXv2 integrates anthropogenic and open biomass burning emissions across seven sectors following a mosaic methodology. It provides CO2 emissions data alongside nine key pollutants and three chemical mechanisms. Our publicly accessible gridded monthly emissions data can facilitate long-term atmospheric and climate model analyses.
Davide Putero, Paolo Cristofanelli, Kai-Lan Chang, Gaëlle Dufour, Gregory Beachley, Cédric Couret, Peter Effertz, Daniel A. Jaffe, Dagmar Kubistin, Jason Lynch, Irina Petropavlovskikh, Melissa Puchalski, Timothy Sharac, Barkley C. Sive, Martin Steinbacher, Carlos Torres, and Owen R. Cooper
Atmos. Chem. Phys., 23, 15693–15709, https://doi.org/10.5194/acp-23-15693-2023, https://doi.org/10.5194/acp-23-15693-2023, 2023
Short summary
Short summary
We investigated the impact of societal restriction measures during the COVID-19 pandemic on surface ozone at 41 high-elevation sites worldwide. Negative ozone anomalies were observed for spring and summer 2020 for all of the regions considered. In 2021, negative anomalies continued for Europe and partially for the eastern US, while western US sites showed positive anomalies due to wildfires. IASI satellite data and the Carbon Monitor supported emission reductions as a cause of the anomalies.
Peeyush Khare, Jordan E. Krechmer, Jo E. Machesky, Tori Hass-Mitchell, Cong Cao, Junqi Wang, Francesca Majluf, Felipe Lopez-Hilfiker, Sonja Malek, Will Wang, Karl Seltzer, Havala O. T. Pye, Roisin Commane, Brian C. McDonald, Ricardo Toledo-Crow, John E. Mak, and Drew R. Gentner
Atmos. Chem. Phys., 22, 14377–14399, https://doi.org/10.5194/acp-22-14377-2022, https://doi.org/10.5194/acp-22-14377-2022, 2022
Short summary
Short summary
Ammonium adduct chemical ionization is used to examine the atmospheric abundances of oxygenated volatile organic compounds associated with emissions from volatile chemical products, which are now key contributors of reactive precursors to ozone and secondary organic aerosols in urban areas. The application of this valuable measurement approach in densely populated New York City enables the evaluation of emissions inventories and thus the role these oxygenated compounds play in urban air quality.
Haolin Wang, Xiao Lu, Daniel J. Jacob, Owen R. Cooper, Kai-Lan Chang, Ke Li, Meng Gao, Yiming Liu, Bosi Sheng, Kai Wu, Tongwen Wu, Jie Zhang, Bastien Sauvage, Philippe Nédélec, Romain Blot, and Shaojia Fan
Atmos. Chem. Phys., 22, 13753–13782, https://doi.org/10.5194/acp-22-13753-2022, https://doi.org/10.5194/acp-22-13753-2022, 2022
Short summary
Short summary
We report significant global tropospheric ozone increases in 1995–2017 based on extensive aircraft and ozonesonde observations. Using GEOS-Chem (Goddard Earth Observing System chemistry model) multi-decadal global simulations, we find that changes in global anthropogenic emissions, in particular the rapid increases in aircraft emissions, contribute significantly to the increases in tropospheric ozone and resulting radiative impact.
Ziwei Mo, Ru Cui, Bin Yuan, Huihua Cai, Brian C. McDonald, Meng Li, Junyu Zheng, and Min Shao
Atmos. Chem. Phys., 21, 13655–13666, https://doi.org/10.5194/acp-21-13655-2021, https://doi.org/10.5194/acp-21-13655-2021, 2021
Short summary
Short summary
There is a lack of detailed understanding of NMVOC emissions from the use of volatile chemical products (VCPs) in China. This study used a mass balance method to compile a long-term emission inventory for solvent use (including coatings, adhesives, inks, pesticides, cleaners and personal care products) in China during 2000–2017. The striking growth and recent trend of solvent use NMVOC emissions can give important implications for air quality modeling and NMVOC control strategies in China.
Benjamin A. Nault, Duseong S. Jo, Brian C. McDonald, Pedro Campuzano-Jost, Douglas A. Day, Weiwei Hu, Jason C. Schroder, James Allan, Donald R. Blake, Manjula R. Canagaratna, Hugh Coe, Matthew M. Coggon, Peter F. DeCarlo, Glenn S. Diskin, Rachel Dunmore, Frank Flocke, Alan Fried, Jessica B. Gilman, Georgios Gkatzelis, Jacqui F. Hamilton, Thomas F. Hanisco, Patrick L. Hayes, Daven K. Henze, Alma Hodzic, James Hopkins, Min Hu, L. Greggory Huey, B. Thomas Jobson, William C. Kuster, Alastair Lewis, Meng Li, Jin Liao, M. Omar Nawaz, Ilana B. Pollack, Jeffrey Peischl, Bernhard Rappenglück, Claire E. Reeves, Dirk Richter, James M. Roberts, Thomas B. Ryerson, Min Shao, Jacob M. Sommers, James Walega, Carsten Warneke, Petter Weibring, Glenn M. Wolfe, Dominique E. Young, Bin Yuan, Qiang Zhang, Joost A. de Gouw, and Jose L. Jimenez
Atmos. Chem. Phys., 21, 11201–11224, https://doi.org/10.5194/acp-21-11201-2021, https://doi.org/10.5194/acp-21-11201-2021, 2021
Short summary
Short summary
Secondary organic aerosol (SOA) is an important aspect of poor air quality for urban regions around the world, where a large fraction of the population lives. However, there is still large uncertainty in predicting SOA in urban regions. Here, we used data from 11 urban campaigns and show that the variability in SOA production in these regions is predictable and is explained by key emissions. These results are used to estimate the premature mortality associated with SOA in urban regions.
Chelsea E. Stockwell, Matthew M. Coggon, Georgios I. Gkatzelis, John Ortega, Brian C. McDonald, Jeff Peischl, Kenneth Aikin, Jessica B. Gilman, Michael Trainer, and Carsten Warneke
Atmos. Chem. Phys., 21, 6005–6022, https://doi.org/10.5194/acp-21-6005-2021, https://doi.org/10.5194/acp-21-6005-2021, 2021
Short summary
Short summary
Volatile chemical products are emerging as a large source of petrochemical organics in urban environments. We identify markers for the coatings category by linking ambient observations to laboratory measurements, investigating volatile organic compound (VOC) composition, and quantifying key VOC emissions via controlled evaporation experiments. Ingredients and sales surveys are used to confirm the prevalence and usage trends to support the assignment of water and solvent-borne coating tracers.
Zhen Qu, Daven K. Henze, Owen R. Cooper, and Jessica L. Neu
Atmos. Chem. Phys., 20, 13109–13130, https://doi.org/10.5194/acp-20-13109-2020, https://doi.org/10.5194/acp-20-13109-2020, 2020
Short summary
Short summary
We use satellite observations and chemical transport modeling to quantify sources of NOx, a major air pollutant, over the past decade. We find improved simulations of the magnitude, seasonality, and trends of NO2 and ozone concentrations using these derived emissions. Changes in ozone pollution driven by human and natural sources are identified in different regions. This work shows the benefits of remote-sensing data and inverse modeling for more accurate ozone simulations.
Kai-Lan Chang, Owen R. Cooper, Audrey Gaudel, Irina Petropavlovskikh, and Valérie Thouret
Atmos. Chem. Phys., 20, 9915–9938, https://doi.org/10.5194/acp-20-9915-2020, https://doi.org/10.5194/acp-20-9915-2020, 2020
Short summary
Short summary
We provide a statistical framework for detecting trends of multiple autocorrelated time series from sparsely sampled profile data. The result is a better and more consistent quantification of trend estimates of vertical profile data. The focus was placed on the long-term ozone time series from commercial aircraft and balloon-borne ozonesonde measurements. This framework can be applied to other trace gases in the atmosphere.
Cited articles
Arias, P., Bellouin, N., Coppola, E., Jones, R., Krinner, G., Marotzke, J., Naik, V., Palmer, M., Plattner, G.-K., Rogelj, J., Rojas, M., Sillmann, J., Storelvmo, T., Thorne, P., Trewin, B., Achuta Rao, K., Adhikary, B., Allan, R., Armour, K., Bala, G., Barimalala, R., Berger, S., Canadell, J., Cassou, C., Cherchi, A., Collins, W., Collins, W., Connors, S., Corti, S., Cruz, F., Dentener, F., Dereczynski, C., Di Luca, A., Diongue Niang, A., Doblas-Reyes, F., Dosio, A., Douville, H., Engelbrecht, F., Eyring, V., Fischer, E., Forster, P., Fox-Kemper, B., Fuglestvedt, J., Fyfe, J., Gillett, N., Goldfarb, L., Gorodetskaya, I., Gutierrez, J., Hamdi, R., Hawkins, E., Hewitt, H., Hope, P., Islam, A., Jones, C., Kaufman, D., Kopp, R., Kosaka, Y., Kossin, J., Krakovska, S., Lee, J.-Y., Li, J., Mauritsen, T., Maycock, T., Meinshausen, M., Min, S.-K., Monteiro, P., Ngo-Duc, T., Otto, F., Pinto, I., Pirani, A., Raghavan, K., Ranasinghe, R., Ruane, A., Ruiz, L., Sallée, J.-B., Samset, B., Sathyendranath, S., Seneviratne, S., Sörensson, A., Szopa, S., Takayabu, I., Tréguier, A.-M., van den Hurk, B., Vautard, R., von Schuckmann, K., Zaehle, S., Zhang, X., and Zickfeld, K.: Technical Summary, in: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Masson-Delmotte, V., Zhai, P., Pirani, A., Connors, S., Péan, C., Berger, S., Caud, N., Chen, Y., Goldfarb, L., Gomis, M., Huang, M., Leitzell, K., Lonnoy, E., Matthews, J., Maycock, T., Waterfield, T., Yelekci, O., Yu, R., and Zhou, B., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, https://doi.org/10.1017/9781009157896.002, 33–144, 2021. a
Bartusek, S., Kornhuber, K., and Ting, M.: 2021 North American heatwave amplified by climate change-driven nonlinear interactions, Nat. Clim. Change, 12, 1143–1150, https://doi.org/10.1038/s41558-022-01520-4, 2022. a
Berrocal, V. J., Gelfand, A. E., and Holland, D. M.: Assessing exceedance of ozone standards: a space-time downscaler for fourth highest ozone concentrations, Environmetrics, 25, 279–291, https://doi.org/10.1002/env.2273, 2014. a
Box, G. E. P. and Tiao, G. C.: Intervention analysis with applications to economic and environmental problems, J. Am. Stat. Assoc., 70, 70–79, https://doi.org/10.1080/01621459.1975.10480264, 1975. a, b, c, d
Buchholz, R. R., Park, M., Worden, H. M., Tang, W., Edwards, D. P., Gaubert, B., Deeter, M. N., Sullivan, T., Ru, M., Chin, M., Levy, R. C., Zheng, B., and Magzamen, S.: New seasonal pattern of pollution emerges from changing North American wildfires, Nat. Commun., 13, 2043, https://doi.org/10.1038/s41467-022-29623-8, 2022. a
Byrne, B., Liu, J., Bowman, K. W., Pascolini-Campbell, M., Chatterjee, A., Pandey, S., Miyazaki, K., van der Werf, G. R., Wunch, D., Wennberg, P. O., Roehl, C. M., and Sinha, S.: Carbon emissions from the 2023 Canadian wildfires, Nature, 633, 835–839, https://doi.org/10.1038/s41586-024-07878-z, 2024. a, b
Chai, T. and Draxler, R. R.: Root mean square error (RMSE) or mean absolute error (MAE)? – Arguments against avoiding RMSE in the literature, Geosci. Model Dev., 7, 1247–1250, https://doi.org/10.5194/gmd-7-1247-2014, 2014. a
Chang, K.-L., Petropavlovskikh, I., Cooper, O. R., Schultz, M. G., and Wang, T.: Regional trend analysis of surface ozone observations from monitoring networks in eastern North America, Europe and East Asia, Elementa: Science of the Anthropocene, 5, 50, https://doi.org/10.1525/elementa.243, 2017. a, b, c, d
Chang, K.-L., Schultz, M. G., Lan, X., McClure-Begley, A., Petropavlovskikh, I., Xu, X., and Ziemke, J. R.: Trend detection of atmospheric time series: Incorporating appropriate uncertainty estimates and handling extreme events, Elementa: Science of the Anthropocene, 9, 00035, https://doi.org/10.1525/elementa.2021.00035, 2021. a, b, c, d
Chang, K.-L., Cooper, O. R., Rodriguez, G., Iraci, L. T., Yates, E. L., Johnson, M. S., Gaudel, A., Jaffe, D. A., Bernays, N., Clark, H., Effertz, P., Leblanc, T., Petropavlovskikh, I., Sauvage, B., and Tarasick, D. W.: Diverging ozone trends above western North America: Boundary layer decreases versus free tropospheric increases, J. Geophys. Res.-Atmos., 128, 2022JD038090, https://doi.org/10.1029/2022JD038090, 2023a. a
Chang, K.-L., Schultz, M. G., Koren, G., and Selke, N.: Guidance note on best statistical practices for TOAR analyses, arXiv [preprint], https://doi.org/10.48550/arXiv.2304.14236, 2023b. a, b
Chang, K.-L., Cooper, O. R., Gaudel, A., Petropavlovskikh, I., Effertz, P., Morris, G., and McDonald, B. C.: Technical note: Challenges in detecting free tropospheric ozone trends in a sparsely sampled environment, Atmos. Chem. Phys., 24, 6197–6218, https://doi.org/10.5194/acp-24-6197-2024, 2024. a, b
Chen, C. W. S., Chan, J. S. K., Gerlach, R., and Hsieh, W. Y. L.: A comparison of estimators for regression models with change points, Stat. Comput., 21, 395–414, https://doi.org/10.1007/s11222-010-9177-0, 2011. a
Christiansen, A., Mickley, L. J., and Hu, L.: Constraining long-term NOx emissions over the United States and Europe using nitrate wet deposition monitoring networks, Atmos. Chem. Phys., 24, 4569–4589, https://doi.org/10.5194/acp-24-4569-2024, 2024. a, b
Clifton, O. E., Fiore, A. M., Correa, G., Horowitz, L. W., and Naik, V.: Twenty-first century reversal of the surface ozone seasonal cycle over the northeastern United States, Geophys. Res. Lett., 41, 7343–7350, https://doi.org/10.1002/2014GL061378, 2014. a, b
Cooper, O. R., Gao, R.-S., Tarasick, D., Leblanc, T., and Sweeney, C.: Long-term ozone trends at rural ozone monitoring sites across the United States, 1990–2010, J. Geophys. Res.-Atmos., 117, D22307, https://doi.org/10.1029/2012JD018261, 2012. a, b
Cooper, O. R., Parrish, D. D., Ziemke, J., Balashov, N. V., Cupeiro, M., Galbally, I. E., Gilge, S., Horowitz, L., Jensen, N. R., Lamarque, J.-F., Naik, V., Oltmans, S. J., Schwab, J., Shindell, D. T., Thompson, A. M., Thouret, V., Wang, Y., and Zbinden, R. M.: Global distribution and trends of tropospheric ozone: An observation-based review, Elementa: Science of the Anthropocene, 2, 000029, https://doi.org/10.12952/journal.elementa.000029, 2014. a
Cooper, O. R., Schultz, M. G., Schröder, S., Chang, K.-L., Gaudel, A., Benitez, G. C., Cuevas, E., Fröhlich, M., Galbally, I. E., Molloy, S., Kubistin, D., Lu, X., McClure-Begley, A., Nédélec, P., O'Brien, J., Oltmans, S. J., Petropavlovskikh, I., Ries, L., Senik, I., Sjöberg, K., Solberg, S., Spain, G. T., Steinbacher, M., Tarasick, D. W., Thouret, V., and Xu, X.: Multi-decadal surface ozone trends at globally distributed remote locations, Elementa: Science of the Anthropocene, 8, 23, https://doi.org/10.1525/elementa.420, 2020. a
Cooper, O. R., Chang, K.-L., Bates, K., Brown, S. S., Chace, W. S., Coggon, M. M., Gorchov-Negron, A. M., Middlebrook, A. M., Peischl, J., Piasecki, A., Schafer, N., Stockwell, C. E., Wang, S., Warneke, C., Zuraski, K., Miyazaki, K., Payne, V. H., Pennington, E. A., Worden, J. R., Bowman, K. W., and McDonald, B. C.: Early-season 2023 wildfires generated record-breaking surface ozone anomalies across the U. S. Upper Midwest, Geophys. Res. Lett., 51, e2024GL111481, https://doi.org/10.1029/2024GL111481, 2024. a, b, c, d, e
Dielman, T. E.: Least absolute value regression: recent contributions, J. Stat. Comput. Sim., 75, 263–286, https://doi.org/10.1080/0094965042000223680, 2005. a
Domeisen, D. I., Eltahir, E. A., Fischer, E. M., Knutti, R., Perkins-Kirkpatrick, S. E., Schär, C., Seneviratne, S. I., Weisheimer, A., and Wernli, H.: Prediction and projection of heatwaves, Nature Reviews Earth & Environment, 4, 36–50, https://doi.org/10.1038/s43017-022-00371-z, 2023. a
Edwards, P. M., Brown, S. S., Roberts, J. M., Ahmadov, R., Banta, R. M., Degouw, J. A., Dubé, W. P., Field, R. A., Flynn, J. H., Gilman, J. B., Graus, M., Helmig, D., Koss, A., Langford, A. O., Lefer, B. L., Lerner, B. M., Li, R., Li, S.-M., McKeen, S. A., Murphy, S. M., Parrish, D. D., Senff, C. J., Soltis, J., Stutz, J., Sweeney, C., Thompson, C. R., Trainer, M. K., Tsai, C., Veres, P. R., Washenfelder, R. A., Warneke, C., Wild, R. J., Young, C. J., Yuan, B., and Zamora, R.: High winter ozone pollution from carbonyl photolysis in an oil and gas basin, Nature, 514, 351–354, https://doi.org/10.1038/nature13767, 2014. a, b, c
European Commission: Directive 2008/50/EC of the European Parliament and of the Council of 21 May 2008 on ambient air quality and cleaner air for Europe, Official Journal of the European Union, http://data.europa.eu/eli/dir/2008/50/2015-09-18 (last access: 20 January 2025), 2015. a
Fasiolo, M., Wood, S. N., Zaffran, M., Nedellec, R., and Goude, Y.: qgam: Bayesian non-parametric quantile regression modelling in R, J. Stat. Softw., 100, 1–31, https://doi.org/10.18637/jss.v100.i09, 2020. a, b
Fiore, A., Oberman, J., Lin, M., Zhang, L., Clifton, O., Jacob, D. J., Naik, V., Horowitz, L., Pinto, J., and Milly, G.: Estimating North American background ozone in US surface air with two independent global models: Variability, uncertainties, and recommendations, Atmos. Environ., 96, 284–300, https://doi.org/10.1016/j.atmosenv.2014.07.045, 2014. a
Fiore, A. M., Hancock, S., Lamarque, J.-F., Correa, G., Chang, K.-L., Ru, M., Cooper, O. R., Gaudel, A., Polvani, L. M., Sauvage, B., and Ziemke, J. R.: Understanding recent tropospheric ozone trends in the context of large internal variability: A new perspective from chemistry-climate model ensembles, Environmental Research: Climate, 1, 025008, https://doi.org/10.1088/2752-5295/ac9cc2, 2022. a
Fitzenberger, B.: The moving blocks bootstrap and robust inference for linear least squares and quantile regressions, J. Econometrics, 82, 235–287, https://doi.org/10.1016/S0304-4076(97)00058-4, 1998. a
Fleming, Z. L., Doherty, R. M., von Schneidemesser, E., Malley, C. S., Cooper, O. R., Pinto, J. P., Colette, A., Xu, X., Simpson, D., Schultz, M. G., Lefohn, A. S., Hamad, S., Moolla, R., Solberg, S., and Feng, Z.: Tropospheric Ozone Assessment Report: Present-day ozone distribution and trends relevant to human health, Elementa: Science of the Anthropocene, 6, 12, https://doi.org/10.1525/elementa.291, 2018. a, b
Francoeur, C. B., McDonald, B. C., Gilman, J. B., Zarzana, K. J., Dix, B., Brown, S. S., de Gouw, J. A., Frost, G. J., Li, M., McKeen, S. A., Peischl, J., Pollack, I. B., Ryerson, T. B., Thompson, C., Warneke, C., and Trainer, M.: Quantifying methane and ozone precursor emissions from oil and gas production regions across the contiguous US, Environ. Sci. Technol., 55, 9129–9139, https://doi.org/10.1021/acs.est.0c07352, 2021. a, b
Gaudel, A., Cooper, O. R., Ancellet, G., Barret, B., Boynard, A., Burrows, J. P., Clerbaux, C., Coheur, P. F., Cuesta, J., Cuevas, E., Doniki, S., Dufour, G., Ebojie, F., Foret, G., Garcia, O., Muños, M. J. G., Hannigan, J. W., Hase, F., Huang, G., Hassler, B., Hurtmans, D., Jaffe, D., Jones, N., Kalabokas, P., Kerridge, B., Kulawik, S. S., Latter, B., Leblanc, T., Flochmoën, E. L., Lin, W., Liu, J., Liu, X., Mahieu, E., McClure-Begley, A., Neu, J. L., Osman, M., Palm, M., Petetin, H., Petropavlovskikh, I., Querel, R., Rahpoe, N., Rozanov, A., Schultz, M. G., Schwab, J., Siddans, R., Smale, D., Steinbacher, M., Tanimoto, H., Tarasick, D. W., Thouret, V., Thompson, A. M., Trickl, T., Weatherhead, E. C., Wespes, C., Worden, H. M., Vigouroux, C., Xu, X., Zeng, G., and Ziemke, J. R.: Tropospheric Ozone Assessment Report: Present-day distribution and trends of tropospheric ozone relevant to climate and global atmospheric chemistry model evaluation, Elementa: Science of the Anthropocene, 6, 12, https://doi.org/10.1525/elementa.273, 2018. a
Harkins, C., McDonald, B. C., Henze, D. K., and Wiedinmyer, C.: A fuel-based method for updating mobile source emissions during the COVID-19 pandemic, Environ. Res. Lett., 16, 065018, https://doi.org/10.1088/1748-9326/ac0660, 2021. a, b
Hodson, T. O.: Root-mean-square error (RMSE) or mean absolute error (MAE): when to use them or not, Geosci. Model Dev., 15, 5481–5487, https://doi.org/10.5194/gmd-15-5481-2022, 2022. a
Jaffe, D. A., Cooper, O. R., Fiore, A. M., Henderson, B. H., Tonnesen, G. S., Russell, A. G., Henze, D. K., Langford, A. O., Lin, M., and Moore, T.: Scientific assessment of background ozone over the US: Implications for air quality management, Elementa: Science of the Anthropocene, 6, 56, https://doi.org/10.1525/elementa.309, 2018. a
Jenkinson, A. F.: The frequency distribution of the annual maximum (or minimum) values of meteorological elements, Q. J. Roy. Meteor. Soc., 81, 158–171, https://doi.org/10.1002/qj.49708134804, 1955. a
Jiang, Z., McDonald, B. C., Worden, H., Worden, J. R., Miyazaki, K., Qu, Z., Henze, D. K., Jones, D. B., Arellano, A. F., Fischer, E. V., Zhu, L., and Boersma, K. F.: Unexpected slowdown of US pollutant emission reduction in the past decade, P. Natl. Acad. Sci. USA, 115, 5099–5104, https://doi.org/10.1073/pnas.1801191115, 2018. a, b, c
Jiang, Z., Zhu, R., Miyazaki, K., McDonald, B. C., Klimont, Z., Zheng, B., Boersma, K. F., Zhang, Q., Worden, H., Worden, J. R., Henze, D. K., Jones, D. B. A., van der Gon, H. A. C. D., and Eskes, H.: Decadal variabilities in tropospheric nitrogen oxides over United States, Europe, and China, J. Geophys. Res.-Atmos., 127, e2021JD035872, https://doi.org/10.1029/2021JD035872, 2022. a, b, c
Jin, X., Fiore, A., Boersma, K. F., Smedt, I. D., and Valin, L.: Inferring changes in summertime surface Ozone–NO x–VOC chemistry over US urban areas from two decades of satellite and ground-based observations, Environ. Sci. Technol., 54, 6518–6529, https://doi.org/10.1021/acs.est.9b07785, 2020. a
Jing, P., Lu, Z., and Steiner, A. L.: The ozone-climate penalty in the Midwestern US, Atmos. Environ., 170, 130–142, https://doi.org/10.1016/j.atmosenv.2017.09.038, 2017. a
Kleiber, C. and Zeileis, A.: Applied econometrics with R, Springer, https://doi.org/10.1007/978-0-387-77318-6, 2008. a
Koenker, R.: Quantile regression, vol. 38, Cambridge University Press, https://doi.org/10.1017/CBO9780511754098, 2005. a, b
Koenker, R., Chernozhukov, V., He, X., and Peng, L.: Handbook of quantile regression, CRC Press, https://doi.org/10.1201/9781315120256, 2017. a
Lahiri, S. N.: Resampling methods for dependent data, Springer, https://doi.org/10.1007/978-1-4757-3803-2, 2003. a
Langford, A. O., Senff, C. J., Alvarez, R. J., Aikin, K. C., Ahmadov, R., Angevine, W. M., Baidar, S., Brewer, W. A., Brown, S. S., James, E. P., McCarty, B. J., Sandberg, S. P., and Zucker, M. L.: Were wildfires responsible for the unusually high surface ozone in Colorado during 2021?, J. Geophys. Res.-Atmos., 128, e2022JD037700, https://doi.org/10.1029/2022JD037700, 2023. a, b, c, d, e
Li, S., Wang, H., and Lu, X.: Anthropogenic emission controls reduce summertime ozone–temperature sensitivity in the United States, Atmos. Chem. Phys., 25, 2725–2743, https://doi.org/10.5194/acp-25-2725-2025, 2025. a
Lin, M., Horowitz, L. W., Payton, R., Fiore, A. M., and Tonnesen, G.: US surface ozone trends and extremes from 1980 to 2014: quantifying the roles of rising Asian emissions, domestic controls, wildfires, and climate, Atmos. Chem. Phys., 17, 2943–2970, https://doi.org/10.5194/acp-17-2943-2017, 2017. a, b, c
Lu, X., Zhang, L., Yue, X., Zhang, J., Jaffe, D. A., Stohl, A., Zhao, Y., and Shao, J.: Wildfire influences on the variability and trend of summer surface ozone in the mountainous western United States, Atmos. Chem. Phys., 16, 14687–14702, https://doi.org/10.5194/acp-16-14687-2016, 2016. a
Lund, R. B., Beaulieu, C., Killick, R., Lu, Q., and Shi, X.: Good practices and common pitfalls in climate time series changepoint techniques: A review, J. Climate, 36, 8041–8057, https://doi.org/10.1175/JCLI-D-22-0954.1, 2023. a, b
Marsavin, A., Pan, D., Pollack, I. B., Zhou, Y., Sullivan, A. P., Naimie, L. E., Benedict, K. B., Juncosa Calahoranno, J. F., Fischer, E. V., Prenni, A. J., Schichtel, B. A., Sive, B. C., and Collett Jr., J. L.: Summertime ozone production at Carlsbad Caverns National Park, New Mexico: Influence of oil and natural gas development, J. Geophys. Res.-Atmos., 129, e2024JD040877, https://doi.org/10.1029/2024JD040877, 2024. a
Mastrandrea, M. D., Field, C. B., Stocker, T. F., Edenhofer, O., Ebi, K. L., Frame, D. J., Held, H., Kriegler, E., Mach, K. J., Matschoss, P. R., Plattner, G.-K., Yohe, G. W., and Zwiers, F. W.: Guidance note for lead authors of the IPCC fifth assessment report on consistent treatment of uncertainties, https://www.ipcc.ch/site/assets/uploads/2018/05/uncertainty-guidance-note.pdf (last access: 20 January 2025), 2010. a, b, c
Mazdiyasni, O. and AghaKouchak, A.: Substantial increase in concurrent droughts and heatwaves in the United States, P. Natl. Acad. Sci. USA, 112, 11484–11489, https://doi.org/10.1073/pnas.1422945112, 2015. a
McDonald, B. C., Dallmann, T. R., Martin, E. W., and Harley, R. A.: Long-term trends in nitrogen oxide emissions from motor vehicles at national, state, and air basin scales, J. Geophys. Res.-Atmos., 117, D00V18, https://doi.org/10.1029/2012JD018304, 2012. a, b
McDonald, B. C., McBride, Z. C., Martin, E. W., and Harley, R. A.: High-resolution mapping of motor vehicle carbon dioxide emissions, J. Geophys. Res.-Atmos., 119, 5283–5298, https://doi.org/10.1002/2013JD021219, 2014. a
McDonald, B. C., McKeen, S. A., Cui, Y. Y., Ahmadov, R., Kim, S.-W., Frost, G. J., Pollack, I. B., Peischl, J., Ryerson, T. B., Holloway, J. S., Graus, M., Warneke, C., Gilman, J. B., de Gouw, J. A., Kaiser, J., Keutsch, F. N., Hanisco, T. F., Wolfe, G. M., and Trainer, M.: Modeling ozone in the Eastern US using a fuel-based mobile source emissions inventory, Environ. Sci. Technol., 52, 7360–7370, https://doi.org/10.1021/acs.est.8b00778, 2018. a
McDuffie, E. E., Edwards, P. M., Gilman, J. B., Lerner, B. M., Dubé, W. P., Trainer, M., Wolfe, D. E., Angevine, W. M., deGouw, J., Williams, E. J., Tevlin, A. G., Murphy, J. G., Fischer, E. V., McKeen, S., Ryerson, T. B., Peischl, J., Holloway, J. S., Aikin, K., Langford, A. O., Senff, C. J., II, R. J. A., Hall, S. R., Ullmann, K., Lantz, K. O., and Brown, S. S.: Influence of oil and gas emissions on summertime ozone in the Colorado Northern Front Range, J. Geophys. Res.-Atmos., 121, 8712–8729, https://doi.org/10.1002/2016JD025265, 2016. a, b
Mills, G., Pleijel, H., Malley, C. S., Sinha, B., Cooper, O. R., Schultz, M. G., Neufeld, H. S., Simpson, D., Sharps, K., Feng, Z., Gerosa, G., Harmens, H., Kobayashi, K., Saxena, P., Paoletti, E., Sinha, V., and Xu, X.: Tropospheric Ozone Assessment Report: Present-day tropospheric ozone distribution and trends relevant to vegetation, Elementa: Science of the Anthropocene, 6, 47, https://doi.org/10.1525/elementa.302, 2018. a
Parks, S. A. and Abatzoglou, J. T.: Warmer and drier fire seasons contribute to increases in area burned at high severity in western US forests from 1985 to 2017, Geophys. Res. Lett., 47, e2020GL089858, https://doi.org/10.1029/2020GL089858, 2020. a
Peischl, J., Aikin, K. C., McDonald, B. C., Harkins, C., Middlebrook, A. M., Langford, A. O., Cooper, O. R., Chang, K.-L., and Brown, S. S.: Quantifying anomalies of air pollutants in 9 US cities during 2020 due to COVID-19 lockdowns and wildfires based on decadal trends, Elementa: Science of the Anthropocene, 11, 00029, https://doi.org/10.1525/elementa.2023.00029, 2023. a
Perkins, S. E. and Alexander, L. V.: On the measurement of heat waves, J. Climate, 26, 4500–4517, https://doi.org/10.1175/JCLI-D-12-00383.1, 2013. a, b, c, d
Perkins, S. E., Alexander, L. V., and Nairn, J. R.: Increasing frequency, intensity and duration of observed global heatwaves and warm spells, Geophys. Res. Lett., 39, L20714, https://doi.org/10.1029/2012GL053361, 2012. a
Porter, W. C., Heald, C. L., Cooley, D., and Russell, B.: Investigating the observed sensitivities of air-quality extremes to meteorological drivers via quantile regression, Atmos. Chem. Phys., 15, 10349–10366, https://doi.org/10.5194/acp-15-10349-2015, 2015. a
Putero, D., Cristofanelli, P., Chang, K.-L., Dufour, G., Beachley, G., Couret, C., Effertz, P., Jaffe, D. A., Kubistin, D., Lynch, J., Petropavlovskikh, I., Puchalski, M., Sharac, T., Sive, B. C., Steinbacher, M., Torres, C., and Cooper, O. R.: Fingerprints of the COVID-19 economic downturn and recovery on ozone anomalies at high-elevation sites in North America and western Europe, Atmos. Chem. Phys., 23, 15693–15709, https://doi.org/10.5194/acp-23-15693-2023, 2023. a
Rasmussen, D. J., Fiore, A. M., Naik, V., Horowitz, L. W., McGinnis, S. J., and Schultz, M. G.: Surface ozone-temperature relationships in the eastern US: A monthly climatology for evaluating chemistry-climate models, Atmos. Environ., 47, 142–153, https://doi.org/10.1016/j.atmosenv.2011.11.021, 2012. a
Razavi, S. and Vogel, R.: Prewhitening of hydroclimatic time series? Implications for inferred change and variability across time scales, J. Hydrol., 557, 109–115, https://doi.org/10.1016/j.jhydrol.2017.11.053, 2018. a
Reeves, J., Chen, J., Wang, X. L., Lund, R., and Lu, Q. Q.: A review and comparison of changepoint detection techniques for climate data, J. Appl. Meteorol. Clim., 46, 900–915, https://doi.org/10.1175/JAM2493.1, 2007. a
Rickly, P. S., Coggon, M. M., Aikin, K. C., Alvarez, R. J., Baidar, S., Gilman, J. B., Gkatzelis, G. I., Harkins, C., He, J., Lamplugh, A., Langford, A. O., McDonald, B. C., Peischl, J., Robinson, M. A., Rollins, A. W., Schwantes, R. H., Senff, C. J., Warneke, C., and Brown, S. S.: Influence of wildfire on urban ozone: An observationally constrained box modeling study at a site in the Colorado front range, Environ. Sci. Technol., 57, 1257–1267, https://doi.org/10.1021/acs.est.2c06157, 2023. a
Schnell, J. L. and Prather, M. J.: Co-occurrence of extremes in surface ozone, particulate matter, and temperature over eastern North America, P. Natl. Acad. Sci. USA, 114, 2854–2859, https://doi.org/10.1073/pnas.1614453114, 2017. a, b
Seguel, R. J., Castillo, L., Opazo, C., Rojas, N. Y., Nogueira, T., Cazorla, M., Gavidia-Calderón, M., Gallardo, L., Garreaud, R., Carrasco-Escaff, T., and Elshorbany, Y.: Changes in South American surface ozone trends: exploring the influences of precursors and extreme events, Atmos. Chem. Phys., 24, 8225–8242, https://doi.org/10.5194/acp-24-8225-2024, 2024. a
Seltzer, K. M., Shindell, D. T., Kasibhatla, P., and Malley, C. S.: Magnitude, trends, and impacts of ambient long-term ozone exposure in the United States from 2000 to 2015, Atmos. Chem. Phys., 20, 1757–1775, https://doi.org/10.5194/acp-20-1757-2020, 2020. a, b
Shi, X., Gallagher, C., Lund, R., and Killick, R.: A comparison of single and multiple changepoint techniques for time series data, Comput. Stat. Data An., 170, 107433, https://doi.org/10.1016/j.csda.2022.107433, 2022. a
Silvern, R. F., Jacob, D. J., Mickley, L. J., Sulprizio, M. P., Travis, K. R., Marais, E. A., Cohen, R. C., Laughner, J. L., Choi, S., Joiner, J., and Lamsal, L. N.: Using satellite observations of tropospheric NO2 columns to infer long-term trends in US NOx emissions: the importance of accounting for the free tropospheric NO2 background, Atmos. Chem. Phys., 19, 8863–8878, https://doi.org/10.5194/acp-19-8863-2019, 2019. a, b
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, 2015. a, b, c
Simon, H., Hogrefe, C., Whitehill, A., Foley, K. M., Liljegren, J., Possiel, N., Wells, B., Henderson, B. H., Valin, L. C., Tonnesen, G., Appel, K. W., and Koplitz, S.: Revisiting day-of-week ozone patterns in an era of evolving US air quality, Atmos. Chem. Phys., 24, 1855–1871, https://doi.org/10.5194/acp-24-1855-2024, 2024. a
Smith, R. L.: Extreme value analysis of environmental time series: an application to trend detection in ground-level ozone, Stat. Sci., 4, 367–377, https://doi.org/10.1214/ss/1177012400, 1989. a, b
Sorooshian, A., Arellano, A. F., Fraser, M. P., Herckes, P., Betito, G., Betterton, E. A., Braun, R. A., Guo, Y., Mirrezaei, M. A., and Roychoudhury, C.: Ozone in the Desert Southwest of the United States: A Synthesis of Past Work and Steps Ahead, ACS ES&T Air, 1, 62–79, https://doi.org/10.1021/acsestair.3c00033, 2024. a
Strode, S. A., Rodriguez, J. M., Logan, J. A., Cooper, O. R., Witte, J. C., Lamsal, L. N., Damon, M., Van Aartsen, B., Steenrod, S. D., and Strahan, S. E.: Trends and variability in surface ozone over the United States, J. Geophys. Res.-Atmos., 120, 9020–9042, https://doi.org/10.1002/2014JD022784, 2015. a, b
US EPA: Integrated Science Assessment for Ozone and Related Photochemical Oxidants, Federal Register 85 FR 21849, https://www.federalregister.gov/documents/2020/04/20/2020-08333/integrated-science-assessment-for-ozone-and-related-photochemical-oxidants (last access: 20 January 2025), 2020a. a
US EPA: Review of the Ozone National Ambient Air Quality Standards, https://www.govinfo.gov/content/pkg/FR-2020-12-31/pdf/2020-28871.pdf (last access: 20 January 2025), 2020b. a
US Federal Register: National Ambient Air Quality Standards for Ozone, https://www.federalregister.gov/documents/2015/10/26/2015-26594/national-ambient-air-quality-standards-for-ozone (last access: 20 January 2025), 2015. a
Weatherhead, E. C., Reinsel, G. C., Tiao, G. C., Meng, X.-L., Choi, D., Cheang, W.-K., Keller, T., DeLuisi, J., Wuebbles, D. J., Kerr, J. B., Miller, A. J., Oltmans, S. J., and Frederick, J. E.: Factors affecting the detection of trends: Statistical considerations and applications to environmental data, J. Geophys. Res.-Atmos., 103, 17149–17161, https://doi.org/10.1029/98JD00995, 1998. a
Wells, B., Dolwick, P., Eder, B., Evangelista, M., Foley, K., Mannshardt, E., Misenis, C., and Weishampel, A.: Improved estimation of trends in US ozone concentrations adjusted for interannual variability in meteorological conditions, Atmos. Environ., 248, 118234, https://doi.org/10.1016/j.atmosenv.2021.118234, 2021. a, b
WHO: Air quality guidelines: global update 2005: particulate matter, ozone, nitrogen dioxide, and sulfur dioxide, https://iris.who.int/bitstream/handle/10665/107823/9789289021920-eng.pdf?sequence=1 (last access: 20 January 2025), 2006. a
WHO: Review of evidence on health aspects of air pollution: REVIHAAP project: technical report, World Health Organization, Regional Office for Europe, https://iris.who.int/handle/10665/341712 (last access: 20 January 2025), 2013. a
Willmott, C. J. and Matsuura, K.: Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance, Clim. Res., 30, 79–82, https://doi.org/10.3354/cr030079, 2005. a
WMO: WMO Air Quality and Climate Bulletin No. 2, https://library.wmo.int/records/item/58736-no-2-september-2022 (last access: 20 January 2025), 2022. a
Wood, S. N.: Generalized additive models: an introduction with R, CRC Press, https://doi.org/10.1201/9781315370279, 2006. a, b
Wood, S. N. and Fasiolo, M.: A generalized Fellner–Schall method for smoothing parameter optimization with application to Tweedie location, scale and shape models, Biometrics, 73, 1071–1081, https://doi.org/10.1111/biom.12666, 2017. a
Wu, S., Mickley, L. J., Leibensperger, E. M., Jacob, D. J., Rind, D., and Streets, D. G.: Effects of 2000–2050 global change on ozone air quality in the United States, J. Geophys. Res.-Atmos., 113, D06302, https://doi.org/10.1029/2007JD008917, 2008. a
Yee, T. W.: Vector generalized linear and additive models: with an implementation in R, Springer, https://doi.org/10.1007/978-1-4939-2818-7, 2015. a
Youngman, B. D.: evgam: An R Package for Generalized Additive Extreme Value Models, J. Stat. Softw., 103, 1–26, https://doi.org/10.18637/jss.v103.i03, 2022. a
Zanis, P., Akritidis, D., Turnock, S., Naik, V., Szopa, S., Georgoulias, A. K., Bauer, S. E., Deushi, M., Horowitz, L. W., Keeble, J., Sager, P. L., O'Connor, F. M., Oshima, N., Tsigaridis, K., and van Noije, T.: Climate change penalty and benefit on surface ozone: a global perspective based on CMIP6 earth system models, Environ. Res. Lett., 17, 024014, https://doi.org/10.1088/1748-9326/ac4a34, 2022. a, b, c
Zoogman, P., Jacob, D. J., Chance, K., Liu, X., Lin, M., Fiore, A., and Travis, K.: Monitoring high-ozone events in the US Intermountain West using TEMPO geostationary satellite observations, Atmos. Chem. Phys., 14, 6261–6271, https://doi.org/10.5194/acp-14-6261-2014, 2014. a
Short summary
Exposure to high levels of ozone can be harmful to human health. This study shows consistent and robust evidence of decreasing ozone extremes across much of the United States over the period from 1990 to 2023, previously attributed to ozone precursor emission controls. Nevertheless, we also show that the increasing heat wave frequencies are likely to contribute to additional ozone exceedances, slowing the progress of decreasing the frequency of ozone exceedances.
Exposure to high levels of ozone can be harmful to human health. This study shows consistent and...
Altmetrics
Final-revised paper
Preprint