Articles | Volume 18, issue 19
https://doi.org/10.5194/gmd-18-6737-2025
© 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/gmd-18-6737-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
02 Oct 2025
Model evaluation paper |
| 02 Oct 2025
| 02 Oct 2025
Evaluation of ozone and its precursors using the Multi-Scale Infrastructure for Chemistry and Aerosols Version 0 (MUSICAv0) during the Michigan–Ontario Ozone Source Experiment (MOOSE)
Noribeth Mariscal
Department of Civil and Environmental Engineering, Wayne State University, Detroit, Michigan 48202, USA
Louisa K. Emmons
Atmospheric Chemistry Observations and Modeling Laboratory, National Center for Atmospheric Research, Boulder, Colorado 80305, USA
Duseong S. Jo
Department of Earth Science Education, Seoul National University, Seoul, 08826, South Korea
Ying Xiong
College of Environment and Climate, Institute for Environmental and Climate Research, Guangdong-Hong Kong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Jinan University, Guangzhou, 511443, China
Laura M. Judd
NASA Langley Research Center, Hampton, Virginia 23666, USA
Scott J. Janz
NASA Goddard Space Flight Center, Greenbelt, Maryland 20771, USA
Jiajue Chai
Department of Chemistry, State University of New York College of Environmental Science and Forestry, Syracuse, New York 13210, USA
Department of Civil and Environmental Engineering, Wayne State University, Detroit, Michigan 48202, USA
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Carley D. Fredrickson, Scott J. Janz, Lok N. Lamsal, Ursula A. Jongebloed, Joshua L. Laughner, and Joel A. Thornton
Atmos. Meas. Tech., 18, 3669–3689, https://doi.org/10.5194/amt-18-3669-2025, https://doi.org/10.5194/amt-18-3669-2025, 2025
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We present an analysis of high-resolution remote sensing measurements of nitrogen-containing trace gases emitted by wildfires. The measurements were made using an instrument on the NASA ER-2 aircraft in the summer of 2019. We find that time-resolved fire intensity is critical to quantify trace gas emissions over a fire's entire lifespan. These findings have implications for improving air pollution forecasts downwind of wildfires using computer models of atmospheric chemistry and meteorology.
Prajjwal Rawat, James H. Crawford, Katherine R. Travis, Laura M. Judd, Mary Angelique G. Demetillo, Lukas C. Valin, James J. Szykman, Andrew Whitehill, Eric Baumann, and Thomas F. Hanisco
Atmos. Meas. Tech., 18, 2899–2917, https://doi.org/10.5194/amt-18-2899-2025, https://doi.org/10.5194/amt-18-2899-2025, 2025
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The Pandonia Global Network (PGN) consists of Pandora spectrometers that observe trace gases at a high time resolution to validate satellite observations and understand local air quality. To aid users, PGN assigns quality flags that assure scientifically valid data but eliminate large amounts of data appropriate for scientific applications. A new method based on contemporaneous data in two independent observation modes is proven using complementary ground-based and airborne observations.
Xinyue Shao, Yaman Liu, Xinyi Dong, Minghuai Wang, Ruochong Xu, Joel A. Thornton, Duseong S. Jo, Man Yue, Wenxiang Shen, Manish Shrivastava, Stephen R. Arnold, and Ken S. Carslaw
EGUsphere, https://doi.org/10.5194/egusphere-2025-1526, https://doi.org/10.5194/egusphere-2025-1526, 2025
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Highly Oxygenated Organic Molecules (HOMs) are key precursors of secondary organic aerosols (SOA). Incorporating the HOMs chemical mechanism into a global climate model allows for a reasonable reproduction of observed HOM characteristics. HOM-SOA constitutes a significant fraction of global SOA, and its distribution and formation pathways exhibit strong sensitivity to uncertainties in autoxidation processes and peroxy radical branching ratios.
Ngoc Thi Nhu Do, Kengo Sudo, Akihiko Ito, Louisa K. Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
Geosci. Model Dev., 18, 2079–2109, https://doi.org/10.5194/gmd-18-2079-2025, https://doi.org/10.5194/gmd-18-2079-2025, 2025
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Understanding historical isoprene emission changes is important for predicting future climate, but trends and their controlling factors remain uncertain. This study shows that long-term isoprene trends vary among Earth system models mainly due to partially incorporating CO2 effects and land cover changes rather than to climate. Future models that refine these factors’ effects on isoprene emissions, along with long-term observations, are essential for better understanding plant–climate interactions.
Min Huang, Gregory R. Carmichael, Kevin W. Bowman, Isabelle De Smedt, Andreas Colliander, Michael H. Cosh, Sujay V. Kumar, Alex B. Guenther, Scott J. Janz, Ryan M. Stauffer, Anne M. Thompson, Niko M. Fedkin, Robert J. Swap, John D. Bolten, and Alicia T. Joseph
Atmos. Chem. Phys., 25, 1449–1476, https://doi.org/10.5194/acp-25-1449-2025, https://doi.org/10.5194/acp-25-1449-2025, 2025
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We use model simulations along with multiplatform, multidisciplinary observations and a range of analysis methods to estimate and understand the distributions, temporal changes, and impacts of reactive nitrogen and ozone over the most populous US region that has undergone significant environmental changes. Deposition, biogenic emissions, and extra-regional sources have been playing increasingly important roles in controlling pollutant budgets in this area as local anthropogenic emissions drop.
Xinyue Shao, Minghuai Wang, Xinyi Dong, Yaman Liu, Stephen R. Arnold, Leighton A. Regayre, Duseong S. Jo, Wenxiang Shen, Hao Wang, Man Yue, Jingyi Wang, Wenxin Zhang, and Ken S. Carslaw
EGUsphere, https://doi.org/10.5194/egusphere-2024-4135, https://doi.org/10.5194/egusphere-2024-4135, 2025
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This study uses a global chemistry-climate model to investigate how new particle formation (NPF) from highly oxygenated organic molecules (HOMs) contributes to cloud condensation nuclei (CCN) in both preindustrial (PI) and present-day (PD) environments, and its impact on aerosol indirect radiative forcing. The findings highlight the crucial role of biogenic emissions in climate change, providing new insights for carbon-neutral scenarios and enhancing understanding of aerosol-cloud interactions.
Jerome D. Fast, Adam C. Varble, Fan Mei, Mikhail Pekour, Jason Tomlinson, Alla Zelenyuk, Art J. Sedlacek III, Maria Zawadowicz, and Louisa Emmons
Atmos. Chem. Phys., 24, 13477–13502, https://doi.org/10.5194/acp-24-13477-2024, https://doi.org/10.5194/acp-24-13477-2024, 2024
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Aerosol property measurements recently collected on the ground and by a research aircraft in central Argentina during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) campaign exhibit large spatial and temporal variability. These measurements coupled with coincident meteorological information provide a valuable data set needed to evaluate and improve model predictions of aerosols in a traditionally data-sparse region of South America.
Xinyue Shao, Minghuai Wang, Xinyi Dong, Yaman Liu, Wenxiang Shen, Stephen R. Arnold, Leighton A. Regayre, Meinrat O. Andreae, Mira L. Pöhlker, Duseong S. Jo, Man Yue, and Ken S. Carslaw
Atmos. Chem. Phys., 24, 11365–11389, https://doi.org/10.5194/acp-24-11365-2024, https://doi.org/10.5194/acp-24-11365-2024, 2024
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Highly oxygenated organic molecules (HOMs) play an important role in atmospheric new particle formation (NPF). By semi-explicitly coupling the chemical mechanism of HOMs and a comprehensive nucleation scheme in a global climate model, the updated model shows better agreement with measurements of nucleation rate, growth rate, and NPF event frequency. Our results reveal that HOM-driven NPF leads to a considerable increase in particle and cloud condensation nuclei burden globally.
David P. Edwards, Sara Martínez-Alonso, Duseong S. Jo, Ivan Ortega, Louisa K. Emmons, John J. Orlando, Helen M. Worden, Jhoon Kim, Hanlim Lee, Junsung Park, and Hyunkee Hong
Atmos. Chem. Phys., 24, 8943–8961, https://doi.org/10.5194/acp-24-8943-2024, https://doi.org/10.5194/acp-24-8943-2024, 2024
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Until recently, satellite observations of atmospheric pollutants at any location could only be obtained once a day. New geostationary satellites stare at a region of the Earth to make hourly measurements, and the Geostationary Environment Monitoring Spectrometer is the first looking at Asia. These data and model simulations show how the change seen for one important pollutant that determines air quality depends on a combination of pollution emissions, atmospheric chemistry, and meteorology.
Haipeng Lin, Louisa K. Emmons, Elizabeth W. Lundgren, Laura Hyesung Yang, Xu Feng, Ruijun Dang, Shixian Zhai, Yunxiao Tang, Makoto M. Kelp, Nadia K. Colombi, Sebastian D. Eastham, Thibaud M. Fritz, and Daniel J. Jacob
Atmos. Chem. Phys., 24, 8607–8624, https://doi.org/10.5194/acp-24-8607-2024, https://doi.org/10.5194/acp-24-8607-2024, 2024
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Tropospheric ozone is a major air pollutant, a greenhouse gas, and a major indicator of model skill. Global atmospheric chemistry models show large differences in simulations of tropospheric ozone, but isolating sources of differences is complicated by different model environments. By implementing the GEOS-Chem model side by side to CAM-chem within a common Earth system model, we identify and evaluate specific differences between the two models and their impacts on key chemical species.
M. Omar Nawaz, Jeremiah Johnson, Greg Yarwood, Benjamin de Foy, Laura Judd, and Daniel L. Goldberg
Atmos. Chem. Phys., 24, 6719–6741, https://doi.org/10.5194/acp-24-6719-2024, https://doi.org/10.5194/acp-24-6719-2024, 2024
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NO2 is a gas with implications for air pollution. A campaign conducted in Houston provided an opportunity to compare NO2 from different instruments and a model. Aircraft and satellite observations agreed well with measurements on the ground; however, the latter estimated lower values. We find that model-simulated NO2 was lower than observations, especially downtown, suggesting that NO2 sources associated with the urban core of Houston, such as vehicle emissions, may be underestimated.
Wenfu Tang, Benjamin Gaubert, Louisa Emmons, Daniel Ziskin, Debbie Mao, David Edwards, Avelino Arellano, Kevin Raeder, Jeffrey Anderson, and Helen Worden
Atmos. Meas. Tech., 17, 1941–1963, https://doi.org/10.5194/amt-17-1941-2024, https://doi.org/10.5194/amt-17-1941-2024, 2024
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We assimilate different MOPITT CO products to understand the impact of (1) assimilating multispectral and joint retrievals versus single spectral products, (2) assimilating satellite profile products versus column products, and (3) assimilating multispectral and joint retrievals versus assimilating individual products separately.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
Geosci. Model Dev., 17, 1931–1955, https://doi.org/10.5194/gmd-17-1931-2024, https://doi.org/10.5194/gmd-17-1931-2024, 2024
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Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.
Wenfu Tang, Louisa K. Emmons, Helen M. Worden, Rajesh Kumar, Cenlin He, Benjamin Gaubert, Zhonghua Zheng, Simone Tilmes, Rebecca R. Buchholz, Sara-Eva Martinez-Alonso, Claire Granier, Antonin Soulie, Kathryn McKain, Bruce C. Daube, Jeff Peischl, Chelsea Thompson, and Pieternel Levelt
Geosci. Model Dev., 16, 6001–6028, https://doi.org/10.5194/gmd-16-6001-2023, https://doi.org/10.5194/gmd-16-6001-2023, 2023
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The new MUSICAv0 model enables the study of atmospheric chemistry across all relevant scales. We develop a MUSICAv0 grid for Africa. We evaluate MUSICAv0 with observations and compare it with a previously used model – WRF-Chem. Overall, the performance of MUSICAv0 is comparable to WRF-Chem. Based on model–satellite discrepancies, we find that future field campaigns in an eastern African region (30°E–45°E, 5°S–5°N) could substantially improve the predictive skill of air quality models.
Maria Val Martin, Elena Blanc-Betes, Ka Ming Fung, Euripides P. Kantzas, Ilsa B. Kantola, Isabella Chiaravalloti, Lyla L. Taylor, Louisa K. Emmons, William R. Wieder, Noah J. Planavsky, Michael D. Masters, Evan H. DeLucia, Amos P. K. Tai, and David J. Beerling
Geosci. Model Dev., 16, 5783–5801, https://doi.org/10.5194/gmd-16-5783-2023, https://doi.org/10.5194/gmd-16-5783-2023, 2023
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Enhanced rock weathering (ERW) is a CO2 removal strategy that involves applying crushed rocks (e.g., basalt) to agricultural soils. However, unintended processes within the N cycle due to soil pH changes may affect the climate benefits of C sequestration. ERW could drive changes in soil emissions of non-CO2 GHGs (N2O) and trace gases (NO and NH3) that may affect air quality. We present a new improved N cycling scheme for the land model (CLM5) to evaluate ERW effects on soil gas N emissions.
Xueying Liu, Yuxuan Wang, Shailaja Wasti, Wei Li, Ehsan Soleimanian, James Flynn, Travis Griggs, Sergio Alvarez, John T. Sullivan, Maurice Roots, Laurence Twigg, Guillaume Gronoff, Timothy Berkoff, Paul Walter, Mark Estes, Johnathan W. Hair, Taylor Shingler, Amy Jo Scarino, Marta Fenn, and Laura Judd
Geosci. Model Dev., 16, 5493–5514, https://doi.org/10.5194/gmd-16-5493-2023, https://doi.org/10.5194/gmd-16-5493-2023, 2023
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With a comprehensive suite of ground-based and airborne remote sensing measurements during the 2021 TRacking Aerosol Convection ExpeRiment – Air Quality (TRACER-AQ) campaign in Houston, this study evaluates the simulation of the planetary boundary layer (PBL) height and the ozone vertical profile by a high-resolution (1.33 km) 3-D photochemical model Weather Research and Forecasting-driven GEOS-Chem (WRF-GC).
Christine Wiedinmyer, Yosuke Kimura, Elena C. McDonald-Buller, Louisa K. Emmons, Rebecca R. Buchholz, Wenfu Tang, Keenan Seto, Maxwell B. Joseph, Kelley C. Barsanti, Annmarie G. Carlton, and Robert Yokelson
Geosci. Model Dev., 16, 3873–3891, https://doi.org/10.5194/gmd-16-3873-2023, https://doi.org/10.5194/gmd-16-3873-2023, 2023
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The Fire INventory from NCAR (FINN) provides daily global estimates of emissions from open fires based on satellite detections of hot spots. This version has been updated to apply MODIS and VIIRS satellite fire detection and better represents both large and small fires. FINNv2.5 generates more emissions than FINNv1 and is in general agreement with other fire emissions inventories. The new estimates are consistent with satellite observations, but uncertainties remain regionally and by pollutant.
Duseong S. Jo, Simone Tilmes, Louisa K. Emmons, Siyuan Wang, and Francis Vitt
Geosci. Model Dev., 16, 3893–3906, https://doi.org/10.5194/gmd-16-3893-2023, https://doi.org/10.5194/gmd-16-3893-2023, 2023
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A new simple secondary organic aerosol (SOA) scheme has been developed for the Community Atmosphere Model (CAM) based on the complex SOA scheme in CAM with detailed chemistry (CAM-chem). The CAM with the new SOA scheme shows better agreements with CAM-chem in terms of aerosol concentrations and radiative fluxes, which ensures more consistent results between different compsets in the Community Earth System Model. The new SOA scheme also has technical advantages for future developments.
Matthew S. Johnson, Amir H. Souri, Sajeev Philip, Rajesh Kumar, Aaron Naeger, Jeffrey Geddes, Laura Judd, Scott Janz, Heesung Chong, and John Sullivan
Atmos. Meas. Tech., 16, 2431–2454, https://doi.org/10.5194/amt-16-2431-2023, https://doi.org/10.5194/amt-16-2431-2023, 2023
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Satellites provide vital information for studying the processes controlling ozone formation. Based on the abundance of particular gases in the atmosphere, ozone formation is sensitive to specific human-induced and natural emission sources. However, errors and biases in satellite retrievals hinder this data source’s application for studying ozone formation sensitivity. We conducted a thorough statistical evaluation of two commonly applied satellites for investigating ozone formation sensitivity.
Wenfu Tang, Simone Tilmes, David M. Lawrence, Fang Li, Cenlin He, Louisa K. Emmons, Rebecca R. Buchholz, and Lili Xia
Atmos. Chem. Phys., 23, 5467–5486, https://doi.org/10.5194/acp-23-5467-2023, https://doi.org/10.5194/acp-23-5467-2023, 2023
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Globally, total wildfire burned area is projected to increase over the 21st century under scenarios without geoengineering and decrease under the two geoengineering scenarios. Geoengineering reduces fire by decreasing surface temperature and wind speed and increasing relative humidity and soil water. However, geoengineering also yields reductions in precipitation, which offset some of the fire reduction.
Gyo-Hwang Choo, Kyunghwa Lee, Hyunkee Hong, Ukkyo Jeong, Wonei Choi, and Scott J. Janz
Atmos. Meas. Tech., 16, 625–644, https://doi.org/10.5194/amt-16-625-2023, https://doi.org/10.5194/amt-16-625-2023, 2023
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This study discusses the morning and afternoon distribution of NO2 emissions in large cities and industrial areas in South Korea, one of the largest NO2 emitters around the world, using GeoTASO, an airborne remote sensing instrument developed to support geostationary satellite missions. NO2 measurements from GeoTASO were compared with those from ground-based remote sensing instruments including Pandora and in situ sensors.
Hao Guo, Clare M. Flynn, Michael J. Prather, Sarah A. Strode, Stephen D. Steenrod, Louisa Emmons, Forrest Lacey, Jean-Francois Lamarque, Arlene M. Fiore, Gus Correa, Lee T. Murray, Glenn M. Wolfe, Jason M. St. Clair, Michelle Kim, John Crounse, Glenn Diskin, Joshua DiGangi, Bruce C. Daube, Roisin Commane, Kathryn McKain, Jeff Peischl, Thomas B. Ryerson, Chelsea Thompson, Thomas F. Hanisco, Donald Blake, Nicola J. Blake, Eric C. Apel, Rebecca S. Hornbrook, James W. Elkins, Eric J. Hintsa, Fred L. Moore, and Steven C. Wofsy
Atmos. Chem. Phys., 23, 99–117, https://doi.org/10.5194/acp-23-99-2023, https://doi.org/10.5194/acp-23-99-2023, 2023
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We have prepared a unique and unusual result from the recent ATom aircraft mission: a measurement-based derivation of the production and loss rates of ozone and methane over the ocean basins. These are the key products of chemistry models used in assessments but have thus far lacked observational metrics. It also shows the scales of variability of atmospheric chemical rates and provides a major challenge to the atmospheric models.
Thibaud M. Fritz, Sebastian D. Eastham, Louisa K. Emmons, Haipeng Lin, Elizabeth W. Lundgren, Steve Goldhaber, Steven R. H. Barrett, and Daniel J. Jacob
Geosci. Model Dev., 15, 8669–8704, https://doi.org/10.5194/gmd-15-8669-2022, https://doi.org/10.5194/gmd-15-8669-2022, 2022
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We bring the state-of-the-science chemistry module GEOS-Chem into the Community Earth System Model (CESM). We show that some known differences between results from GEOS-Chem and CESM's CAM-chem chemistry module may be due to the configuration of model meteorology rather than inherent differences in the model chemistry. This is a significant step towards a truly modular Earth system model and allows two strong but currently separate research communities to benefit from each other's advances.
Longlei Li, Natalie M. Mahowald, Jasper F. Kok, Xiaohong Liu, Mingxuan Wu, Danny M. Leung, Douglas S. Hamilton, Louisa K. Emmons, Yue Huang, Neil Sexton, Jun Meng, and Jessica Wan
Geosci. Model Dev., 15, 8181–8219, https://doi.org/10.5194/gmd-15-8181-2022, https://doi.org/10.5194/gmd-15-8181-2022, 2022
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This study advances mineral dust parameterizations in the Community Atmospheric Model (CAM; version 6.1). Efforts include 1) incorporating a more physically based dust emission scheme; 2) updating the dry deposition scheme; and 3) revising the gravitational settling velocity to account for dust asphericity. Substantial improvements achieved with these updates can help accurately quantify dust–climate interactions using CAM, such as the dust-radiation and dust–cloud interactions.
Daniel L. Goldberg, Monica Harkey, Benjamin de Foy, Laura Judd, Jeremiah Johnson, Greg Yarwood, and Tracey Holloway
Atmos. Chem. Phys., 22, 10875–10900, https://doi.org/10.5194/acp-22-10875-2022, https://doi.org/10.5194/acp-22-10875-2022, 2022
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TROPOMI measurements offer a valuable means to validate emissions inventories and ozone formation regimes, with important limitations. Lightning NOx is important to account for in Texas and can contribute up to 24 % of the column NO2 in rural areas and 8 % in urban areas. Modeled NO2 in urban areas agrees with TROPOMI NO2 to within 20 % in most circumstances, with a small underestimate in Dallas (−13 %) and Houston (−20 %). Near Texas power plants, the satellite appears to underrepresent NO2.
Ka Ming Fung, Colette L. Heald, Jesse H. Kroll, Siyuan Wang, Duseong S. Jo, Andrew Gettelman, Zheng Lu, Xiaohong Liu, Rahul A. Zaveri, Eric C. Apel, Donald R. Blake, Jose-Luis Jimenez, Pedro Campuzano-Jost, Patrick R. Veres, Timothy S. Bates, John E. Shilling, and Maria Zawadowicz
Atmos. Chem. Phys., 22, 1549–1573, https://doi.org/10.5194/acp-22-1549-2022, https://doi.org/10.5194/acp-22-1549-2022, 2022
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Understanding the natural aerosol burden in the preindustrial era is crucial for us to assess how atmospheric aerosols affect the Earth's radiative budgets. Our study explores how a detailed description of dimethyl sulfide (DMS) oxidation (implemented in the Community Atmospheric Model version 6 with chemistry, CAM6-chem) could help us better estimate the present-day and preindustrial concentrations of sulfate and other relevant chemicals, as well as the resulting aerosol radiative impacts.
Siqi Ma, Daniel Tong, Lok Lamsal, Julian Wang, Xuelei Zhang, Youhua Tang, Rick Saylor, Tianfeng Chai, Pius Lee, Patrick Campbell, Barry Baker, Shobha Kondragunta, Laura Judd, Timothy A. Berkoff, Scott J. Janz, and Ivanka Stajner
Atmos. Chem. Phys., 21, 16531–16553, https://doi.org/10.5194/acp-21-16531-2021, https://doi.org/10.5194/acp-21-16531-2021, 2021
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Predicting high ozone gets more challenging as urban emissions decrease. How can different techniques be used to foretell the quality of air to better protect human health? We tested four techniques with the CMAQ model against observations during a field campaign over New York City. The new system proves to better predict the magnitude and timing of high ozone. These approaches can be extended to other regions to improve the predictability of high-O3 episodes in contemporary urban environments.
Xinxin Ye, Pargoal Arab, Ravan Ahmadov, Eric James, Georg A. Grell, Bradley Pierce, Aditya Kumar, Paul Makar, Jack Chen, Didier Davignon, Greg R. Carmichael, Gonzalo Ferrada, Jeff McQueen, Jianping Huang, Rajesh Kumar, Louisa Emmons, Farren L. Herron-Thorpe, Mark Parrington, Richard Engelen, Vincent-Henri Peuch, Arlindo da Silva, Amber Soja, Emily Gargulinski, Elizabeth Wiggins, Johnathan W. Hair, Marta Fenn, Taylor Shingler, Shobha Kondragunta, Alexei Lyapustin, Yujie Wang, Brent Holben, David M. Giles, and Pablo E. Saide
Atmos. Chem. Phys., 21, 14427–14469, https://doi.org/10.5194/acp-21-14427-2021, https://doi.org/10.5194/acp-21-14427-2021, 2021
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Wildfire smoke has crucial impacts on air quality, while uncertainties in the numerical forecasts remain significant. We present an evaluation of 12 real-time forecasting systems. Comparison of predicted smoke emissions suggests a large spread in magnitudes, with temporal patterns deviating from satellite detections. The performance for AOD and surface PM2.5 and their discrepancies highlighted the role of accurately represented spatiotemporal emission profiles in improving smoke forecasts.
Hao Guo, Clare M. Flynn, Michael J. Prather, Sarah A. Strode, Stephen D. Steenrod, Louisa Emmons, Forrest Lacey, Jean-Francois Lamarque, Arlene M. Fiore, Gus Correa, Lee T. Murray, Glenn M. Wolfe, Jason M. St. Clair, Michelle Kim, John Crounse, Glenn Diskin, Joshua DiGangi, Bruce C. Daube, Roisin Commane, Kathryn McKain, Jeff Peischl, Thomas B. Ryerson, Chelsea Thompson, Thomas F. Hanisco, Donald Blake, Nicola J. Blake, Eric C. Apel, Rebecca S. Hornbrook, James W. Elkins, Eric J. Hintsa, Fred L. Moore, and Steven Wofsy
Atmos. Chem. Phys., 21, 13729–13746, https://doi.org/10.5194/acp-21-13729-2021, https://doi.org/10.5194/acp-21-13729-2021, 2021
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The NASA Atmospheric Tomography (ATom) mission built a climatology of the chemical composition of tropospheric air parcels throughout the middle of the Pacific and Atlantic oceans. The level of detail allows us to reconstruct the photochemical budgets of O3 and CH4 over these vast, remote regions. We find that most of the chemical heterogeneity is captured at the resolution used in current global chemistry models and that the majority of reactivity occurs in the
hottest20 % of parcels.
Haipeng Lin, Daniel J. Jacob, Elizabeth W. Lundgren, Melissa P. Sulprizio, Christoph A. Keller, Thibaud M. Fritz, Sebastian D. Eastham, Louisa K. Emmons, Patrick C. Campbell, Barry Baker, Rick D. Saylor, and Raffaele Montuoro
Geosci. Model Dev., 14, 5487–5506, https://doi.org/10.5194/gmd-14-5487-2021, https://doi.org/10.5194/gmd-14-5487-2021, 2021
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Emissions are a central component of atmospheric chemistry models. The Harmonized Emissions Component (HEMCO) is a software component for computing emissions from a user-selected ensemble of emission inventories and algorithms. It allows users to select, add, and scale emissions from different sources through a configuration file with no change to the model source code. We demonstrate the implementation of HEMCO in several models, all sharing the same HEMCO core code and database library.
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
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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.
Jianfeng Li, Yuhang Wang, Ruixiong Zhang, Charles Smeltzer, Andrew Weinheimer, Jay Herman, K. Folkert Boersma, Edward A. Celarier, Russell W. Long, James J. Szykman, Ruben Delgado, Anne M. Thompson, Travis N. Knepp, Lok N. Lamsal, Scott J. Janz, Matthew G. Kowalewski, Xiong Liu, and Caroline R. Nowlan
Atmos. Chem. Phys., 21, 11133–11160, https://doi.org/10.5194/acp-21-11133-2021, https://doi.org/10.5194/acp-21-11133-2021, 2021
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Comprehensive evaluations of simulated diurnal cycles of NO2 and NOy concentrations, vertical profiles, and tropospheric vertical column densities at two different resolutions with various measurements during the DISCOVER-AQ 2011 campaign show potential distribution biases of NOx emissions in the National Emissions Inventory 2011 at both 36 and 4 km resolutions, providing another possible explanation for the overestimation of model results.
Wenfu Tang, David P. Edwards, Louisa K. Emmons, Helen M. Worden, Laura M. Judd, Lok N. Lamsal, Jassim A. Al-Saadi, Scott J. Janz, James H. Crawford, Merritt N. Deeter, Gabriele Pfister, Rebecca R. Buchholz, Benjamin Gaubert, and Caroline R. Nowlan
Atmos. Meas. Tech., 14, 4639–4655, https://doi.org/10.5194/amt-14-4639-2021, https://doi.org/10.5194/amt-14-4639-2021, 2021
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We use high-resolution airborne mapping spectrometer measurements to assess sub-grid variability within satellite pixels over urban regions. The sub-grid variability within satellite pixels increases with increasing satellite pixel sizes. Temporal variability within satellite pixels decreases with increasing satellite pixel sizes. This work is particularly relevant and useful for future satellite design, satellite data interpretation, and point-grid data comparisons.
Yaman Liu, Xinyi Dong, Minghuai Wang, Louisa K. Emmons, Yawen Liu, Yuan Liang, Xiao Li, and Manish Shrivastava
Atmos. Chem. Phys., 21, 8003–8021, https://doi.org/10.5194/acp-21-8003-2021, https://doi.org/10.5194/acp-21-8003-2021, 2021
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Secondary organic aerosol (SOA) is considered one of the most important uncertainties in climate modeling. We evaluate SOA performance in the Community Earth System Model version 2.1 (CESM2.1) configured with the Community Atmosphere Model version 6 with chemistry (CAM6-Chem) through a long-term simulation (1988–2019) with observations in the United States, which indicates monoterpene-formed SOA contributes most to the overestimation of SOA at the surface and underestimation in the upper air.
Fernando Chouza, Thierry Leblanc, Mark Brewer, Patrick Wang, Sabino Piazzolla, Gabriele Pfister, Rajesh Kumar, Carl Drews, Simone Tilmes, Louisa Emmons, and Matthew Johnson
Atmos. Chem. Phys., 21, 6129–6153, https://doi.org/10.5194/acp-21-6129-2021, https://doi.org/10.5194/acp-21-6129-2021, 2021
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The tropospheric ozone lidar at the JPL Table Mountain Facility (TMF) was used to investigate the impact of Los Angeles (LA) Basin pollution transport and stratospheric intrusions in the planetary boundary layer on the San Gabriel Mountains. The results of this study indicate a dominant role of the LA Basin pollution on days when high ozone levels were observed at TMF (March–October period).
Melinda K. Schueneman, Benjamin A. Nault, Pedro Campuzano-Jost, Duseong S. Jo, Douglas A. Day, Jason C. Schroder, Brett B. Palm, Alma Hodzic, Jack E. Dibb, and Jose L. Jimenez
Atmos. Meas. Tech., 14, 2237–2260, https://doi.org/10.5194/amt-14-2237-2021, https://doi.org/10.5194/amt-14-2237-2021, 2021
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This work focuses on two important properties of the aerosol, acidity, and sulfate composition, which is important for our understanding of aerosol health and environmental impacts. We explore different methods to understand the composition of the aerosol with measurements from a specific instrument and apply those methods to a large dataset. These measurements are confounded by other factors, making it challenging to predict aerosol sulfate composition; pH estimations, however, show promise.
Paul T. Griffiths, Lee T. Murray, Guang Zeng, Youngsub Matthew Shin, N. Luke Abraham, Alexander T. Archibald, Makoto Deushi, Louisa K. Emmons, Ian E. Galbally, Birgit Hassler, Larry W. Horowitz, James Keeble, Jane Liu, Omid Moeini, Vaishali Naik, Fiona M. O'Connor, Naga Oshima, David Tarasick, Simone Tilmes, Steven T. Turnock, Oliver Wild, Paul J. Young, and Prodromos Zanis
Atmos. Chem. Phys., 21, 4187–4218, https://doi.org/10.5194/acp-21-4187-2021, https://doi.org/10.5194/acp-21-4187-2021, 2021
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We analyse the CMIP6 Historical and future simulations for tropospheric ozone, a species which is important for many aspects of atmospheric chemistry. We show that the current generation of models agrees well with observations, being particularly successful in capturing trends in surface ozone and its vertical distribution in the troposphere. We analyse the factors that control ozone and show that they evolve over the period of the CMIP6 experiments.
Duseong S. Jo, Alma Hodzic, Louisa K. Emmons, Simone Tilmes, Rebecca H. Schwantes, Michael J. Mills, Pedro Campuzano-Jost, Weiwei Hu, Rahul A. Zaveri, Richard C. Easter, Balwinder Singh, Zheng Lu, Christiane Schulz, Johannes Schneider, John E. Shilling, Armin Wisthaler, and Jose L. Jimenez
Atmos. Chem. Phys., 21, 3395–3425, https://doi.org/10.5194/acp-21-3395-2021, https://doi.org/10.5194/acp-21-3395-2021, 2021
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Secondary organic aerosol (SOA) is a major component of submicron particulate matter, but there are a lot of uncertainties in the future prediction of SOA. We used CESM 2.1 to investigate future IEPOX SOA concentration changes. The explicit chemistry predicted substantial changes in IEPOX SOA depending on the future scenario, but the parameterization predicted weak changes due to simplified chemistry, which shows the importance of correct physicochemical dependencies in future SOA prediction.
Gillian D. Thornhill, William J. Collins, Ryan J. Kramer, Dirk Olivié, Ragnhild B. Skeie, Fiona M. O'Connor, Nathan Luke Abraham, Ramiro Checa-Garcia, Susanne E. Bauer, Makoto Deushi, Louisa K. Emmons, Piers M. Forster, Larry W. Horowitz, Ben Johnson, James Keeble, Jean-Francois Lamarque, Martine Michou, Michael J. Mills, Jane P. Mulcahy, Gunnar Myhre, Pierre Nabat, Vaishali Naik, Naga Oshima, Michael Schulz, Christopher J. Smith, Toshihiko Takemura, Simone Tilmes, Tongwen Wu, Guang Zeng, and Jie Zhang
Atmos. Chem. Phys., 21, 853–874, https://doi.org/10.5194/acp-21-853-2021, https://doi.org/10.5194/acp-21-853-2021, 2021
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This paper is a study of how different constituents in the atmosphere, such as aerosols and gases like methane and ozone, affect the energy balance in the atmosphere. Different climate models were run using the same inputs to allow an easy comparison of the results and to understand where the models differ. We found the effect of aerosols is to reduce warming in the atmosphere, but this effect varies between models. Reactions between gases are also important in affecting climate.
Benjamin Gaubert, Louisa K. Emmons, Kevin Raeder, Simone Tilmes, Kazuyuki Miyazaki, Avelino F. Arellano Jr., Nellie Elguindi, Claire Granier, Wenfu Tang, Jérôme Barré, Helen M. Worden, Rebecca R. Buchholz, David P. Edwards, Philipp Franke, Jeffrey L. Anderson, Marielle Saunois, Jason Schroeder, Jung-Hun Woo, Isobel J. Simpson, Donald R. Blake, Simone Meinardi, Paul O. Wennberg, John Crounse, Alex Teng, Michelle Kim, Russell R. Dickerson, Hao He, Xinrong Ren, Sally E. Pusede, and Glenn S. Diskin
Atmos. Chem. Phys., 20, 14617–14647, https://doi.org/10.5194/acp-20-14617-2020, https://doi.org/10.5194/acp-20-14617-2020, 2020
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This study investigates carbon monoxide pollution in East Asia during spring using a numerical model, satellite remote sensing, and aircraft measurements. We found an underestimation of emission sources. Correcting the emission bias can improve air quality forecasting of carbon monoxide and other species including ozone. Results also suggest that controlling VOC and CO emissions, in addition to widespread NOx controls, can improve ozone pollution over East Asia.
Steven T. Turnock, Robert J. Allen, Martin Andrews, Susanne E. Bauer, Makoto Deushi, Louisa Emmons, Peter Good, Larry Horowitz, Jasmin G. John, Martine Michou, Pierre Nabat, Vaishali Naik, David Neubauer, Fiona M. O'Connor, Dirk Olivié, Naga Oshima, Michael Schulz, Alistair Sellar, Sungbo Shim, Toshihiko Takemura, Simone Tilmes, Kostas Tsigaridis, Tongwen Wu, and Jie Zhang
Atmos. Chem. Phys., 20, 14547–14579, https://doi.org/10.5194/acp-20-14547-2020, https://doi.org/10.5194/acp-20-14547-2020, 2020
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A first assessment is made of the historical and future changes in air pollutants from models participating in the 6th Coupled Model Intercomparison Project (CMIP6). Substantial benefits to future air quality can be achieved in future scenarios that implement measures to mitigate climate and involve reductions in air pollutant emissions, particularly methane. However, important differences are shown between models in the future regional projection of air pollutants under the same scenario.
Benjamin A. Nault, Pedro Campuzano-Jost, Douglas A. Day, Hongyu Guo, Duseong S. Jo, Anne V. Handschy, Demetrios Pagonis, Jason C. Schroder, Melinda K. Schueneman, Michael J. Cubison, Jack E. Dibb, Alma Hodzic, Weiwei Hu, Brett B. Palm, and Jose L. Jimenez
Atmos. Meas. Tech., 13, 6193–6213, https://doi.org/10.5194/amt-13-6193-2020, https://doi.org/10.5194/amt-13-6193-2020, 2020
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Collecting particulate matter, or aerosols, onto filters to be analyzed offline is a widely used method to investigate the mass concentration and chemical composition of the aerosol, especially the inorganic portion. Here, we show that acidic aerosol (sulfuric acid) collected onto filters and then exposed to high ammonia mixing ratios (from human emissions) will lead to biases in the ammonium collected onto filters, and the uptake of ammonia is rapid (< 10 s), which impacts the filter data.
Laura M. Judd, Jassim A. Al-Saadi, James J. Szykman, Lukas C. Valin, Scott J. Janz, Matthew G. Kowalewski, Henk J. Eskes, J. Pepijn Veefkind, Alexander Cede, Moritz Mueller, Manuel Gebetsberger, Robert Swap, R. Bradley Pierce, Caroline R. Nowlan, Gonzalo González Abad, Amin Nehrir, and David Williams
Atmos. Meas. Tech., 13, 6113–6140, https://doi.org/10.5194/amt-13-6113-2020, https://doi.org/10.5194/amt-13-6113-2020, 2020
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This paper evaluates Sentinel-5P TROPOMI v1.2 NO2 tropospheric columns over New York City using data from airborne mapping spectrometers and a network of ground-based spectrometers (Pandora) collected in 2018. These evaluations consider impacts due to cloud parameters, a priori profile assumptions, and spatial and temporal variability. Overall, TROPOMI tropospheric NO2 columns appear to have a low bias in this region.
David S. Stevenson, Alcide Zhao, Vaishali Naik, Fiona M. O'Connor, Simone Tilmes, Guang Zeng, Lee T. Murray, William J. Collins, Paul T. Griffiths, Sungbo Shim, Larry W. Horowitz, Lori T. Sentman, and Louisa Emmons
Atmos. Chem. Phys., 20, 12905–12920, https://doi.org/10.5194/acp-20-12905-2020, https://doi.org/10.5194/acp-20-12905-2020, 2020
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We present historical trends in atmospheric oxidizing capacity (OC) since 1850 from the latest generation of global climate models and compare these with estimates from measurements. OC controls levels of many key reactive gases, including methane (CH4). We find small model trends up to 1980, then increases of about 9 % up to 2014, disagreeing with (uncertain) measurement-based trends. Major drivers of OC trends are emissions of CH4, NOx, and CO; these will be important for future CH4 trends.
Cited articles
Abdi-Oskouei, M., Carmichael, G., Christiansen, M., Ferrada, G., Roozitalab, B., Sobhani, N., Wade, K., Czarnetzki, A., Pierce, R. B., Wagner, T., and Stanier, C.: Sensitivity of Meteorological Skill to Selection of WRF-Chem Physical Parameterizations and Impact on Ozone Prediction During the Lake Michigan Ozone Study (LMOS), J. Geophys. Res.-Atmos., 125, e2019JD031971, https://doi.org/10.1029/2019JD031971, 2020.
Acdan, J. J. M., Pierce, R. B., Dickens, A. F., Adelman, Z., and Nergui, T.: Examining TROPOMI formaldehyde to nitrogen dioxide ratios in the Lake Michigan region: implications for ozone exceedances, Atmos. Chem. Phys., 23, 7867–7885, https://doi.org/10.5194/acp-23-7867-2023, 2023.
Akimoto, H.: Global Air Quality and Pollution, Science, 302, 1716–1719, https://doi.org/10.1126/science.1092666, 2003.
Anenberg, S. C., Achakulwisut, P., Brauer, M., Moran, D., Apte, J. S., and Henze, D. K.: Particulate Matter-Attributable Mortality and Relationships with Carbon Dioxide in 250 Urban Areas Worldwide, Sci. Rep., 9, 11552, https://doi.org/10.1038/s41598-019-48057-9, 2019.
Beirle, S., Borger, C., Dörner, S., Li, A., Hu, Z., Liu, F., Wang, Y., and Wagner, T.: Pinpointing Nitrogen Oxide Emissions from Space, Science Advances, 5, eaax9800, https://doi.org/10.1126/sciadv.aax9800, 2019.
Brasseur, G. P. and Jacob, D. J. .: Modeling of Atmospheric Chemistry, Cambridge University Press, https://doi.org/10.1017/9781316544754, 2017.
Brook, J. R., Makar, P. A., Sills, D. M. L., Hayden, K. L., and McLaren, R.: Exploring the nature of air quality over southwestern Ontario: main findings from the Border Air Quality and Meteorology Study, Atmos. Chem. Phys., 13, 10461–10482, https://doi.org/10.5194/acp-13-10461-2013, 2013.
Cassidy-Bushrow, A. E., Burmeister, C., Lamerato, L., Lemke, L. D., Mathieu, M., O'Leary, B. F., Sperone, F. G., Straughen, J. K., and Reiners, J. J.: Prenatal Airshed Pollutants and Preterm Birth in an Observational Birth Cohort Study in Detroit, Michigan, USA, Environ. Res., 189, 109845, https://doi.org/10.1016/j.envres.2020.109845, 2020.
Cede, A.: Manual for Blick Software Suite 1.8, Pandonia Global Network, https://www.pandonia-global-network.org/wp-content/uploads/2021/09/BlickSoftwareSuite_Manual_v1-8-4.pdf (last access: 29 August 2024), 2021.
Cede, A., Tiefengraber, M., Gebetsberger, M., and Spinei, E.: Pandonia Global Network Data Products Readme Document Version 1.8-8, https://www.pandonia-global-network.org/wp-content/uploads/2023/11/PGN_DataProducts_Readme_v1-8-8.pdf#page=3.23 (last access: 15 September 2025), 2023.
Chance, K., Liu, X., Miller, C. C., Abad, G. G., Huang, G., Nowlan, C., Souri, A., Suleiman, R., Sun, K., Wang, H., Zhu, L., Zoogman, P., Al-Saadi, J., Antuña-Marrero, J.-C., Carr, J., Chatfield, R., Chin, M., Cohen, R., Edwards, D., Fishman, J., Flittner, D., Geddes, J., Grutter, M., Herman, J. R., Jacob, D. J., Janz, S., Joiner, J., Kim, J., Krotkov, N. A., Lefer, B., Martin, R. V., Mayol-Bracero, O. L., Naeger, A., Newchurch, M., Pfister, G. G., Pickering, K., Pierce, R. B., Cárdenas, C. R., Saiz-Lopez, A., Simpson, W., Spinei, E., Spurr, R. J. D., Szykman, J. J., Torres, O., and Wang, J.: Tempo Green Paper: Chemistry, Physics, and Meteorology Experiments with the Tropospheric Emissions: Monitoring of Pollution Instrument, in: Sensors, Systems, and Next-Generation Satellites XXIII, Sensors, Systems, and Next-Generation Satellites XXIII, 56–67, https://doi.org/10.1117/12.2534883, 2019.
Cheng, K., Xie, M., Wang, Y., and Lu, Y.: Vertical Distribution, Diurnal Evolution, and Source Region of Formaldehyde During the Warm Season Under Ozone-Polluted and Non-Polluted Conditions in Nanjing, China, Remote Sensing, 16, 4313, https://doi.org/10.3390/rs16224313, 2024.
Cheng, P., Pour-Biazar, A., White, A. T., and McNider, R. T.: Improvement of summertime surface ozone prediction by assimilating Geostationary Operational Environmental Satellite cloud observations, Atmos. Environ., 268, 118751, https://doi.org/10.1016/j.atmosenv.2021.118751, 2022.
Computational and Information Systems Laboratory: Cheyenne: HPE/SGI XA System (NCAR Community Computing), https://doi.org/10.5065/D6RX99HX, 2019.
Computational and Information Systems Laboratory: Derecho: HPE Cray EX System (NCAR Community Computing), https://doi.org/10.5065/qx9a-pg09, 2023.
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.
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.
Crippa, M., Guizzardi, D., Muntean, M., Schaaf, E., Dentener, F., van Aardenne, J. A., Monni, S., Doering, U., Olivier, J. G. J., Pagliari, V., and Janssens-Maenhout, G.: Gridded emissions of air pollutants for the period 1970–2012 within EDGAR v4.3.2, Earth Syst. Sci. Data, 10, 1987–2013, https://doi.org/10.5194/essd-10-1987-2018, 2018.
Crippa, M., Solazzo, E., Huang, G., Guizzardi, D., Koffi, E., Muntean, M., Schieberle, C., Friedrich, R., and Janssens-Maenhout, G.: High resolution Temporal Profiles in the Emissions Database for Global Atmospheric Research, Sci. Data, 7, 121, https://doi.org/10.1038/s41597-020-0462-2, 2020.
Danabasoglu, G., Lamarque, J.-F., Bacmeister, J., Bailey, D. A., DuVivier, A. K., Edwards, J., Emmons, L. K., Fasullo, J., Garcia, R., Gettelman, A., Hannay, C., Holland, M. M., Large, W. G., Lauritzen, P. H., Lawrence, D. M., Lenaerts, J. T. M., Lindsay, K., Lipscomb, W. H., Mills, M. J., Neale, R., Oleson, K. W., Otto-Bliesner, B., Phillips, A. S., Sacks, W., Tilmes, S., van Kampenhout, L., Vertenstein, M., Bertini, A., Dennis, J., Deser, C., Fischer, C., Fox-Kemper, B., Kay, J. E., Kinnison, D., Kushner, P. J., Larson, V. E., Long, M. C., Mickelson, S., Moore, J. K., Nienhouse, E., Polvani, L., Rasch, P. J., and Strand, W. G.: The Community Earth System Model Version 2 (CESM2), J. Adv. Model. Earth Sy., 12, e2019MS001916, https://doi.org/10.1029/2019MS001916, 2020.
Darmenov, A. S. and da Silva, A. M.: The Quick Fire Emissions Dataset (QFED): Documentation of Versions 2.1, 2.2 and 2.4, NASA Global Modeling and Assimilation Office, Volume 38, https://ntrs.nasa.gov/citations/20180005253 (last access: 29 September 2025), 2015.
de Gouw, J. A., Parrish, D. D., Brown, S. S., Edwards, P., Gilman, J. B., Graus, M., Hanisco, T. F., Kaiser, J., Keutsch, F. N., Kim, S.-W., Lerner, B. M., Neuman, J. A., Nowak, J. B., Pollack, I. B., Roberts, J. M., Ryerson, T. B., Veres, P. R., Warneke, C., and Wolfe, G. M.: Hydrocarbon Removal in Power Plant Plumes Shows Nitrogen Oxide Dependence of Hydroxyl Radicals, Geophys. Res. Lett., 46, 7752–7760, https://doi.org/10.1029/2019GL083044, 2019.
Dix, B., Francoeur, C., Li, M., Serrano-Calvo, R., Levelt, P. F., Veefkind, J. P., McDonald, B. C., and de Gouw, J.: Quantifying NOx Emissions from U.S. Oil and Gas Production Regions Using TROPOMI NO2, ACS Earth Space Chem., 6, 403–414, https://doi.org/10.1021/acsearthspacechem.1c00387, 2022.
Du, Q., Faber, V., and Gunzburger, M.: Centroidal Voronoi Tessellations: Applications and Algorithms, SIAM Rev., 41, 637–676, https://doi.org/10.1137/S0036144599352836, 1999.
Dye, T. S., Roberts, P. T., and Korc, M. E.: Observations of Transport Processes for Ozone and Ozone Precursors during the 1991 Lake Michigan Ozone Study, American Meteorological Society, 1889, https://doi.org/10.1175/1520-0450(1995)034%3C1877:OOTPFO%3E2.0.CO;2, 1995.
ECCAD – Emissions of atmospheric Compounds and Compilation of Ancillary Data, https://eccad.aeris-data.fr/, last access: 15 September 2025.
Edwards, D. P., Martínez-Alonso, S., Jo, D. S., Ortega, I., Emmons, L. K., Orlando, J. J., Worden, H. M., Kim, J., Lee, H., Park, J., and Hong, H.: Quantifying the diurnal variation in atmospheric NO2 from Geostationary Environment Monitoring Spectrometer (GEMS) observations, Atmos. Chem. Phys., 24, 8943–8961, https://doi.org/10.5194/acp-24-8943-2024, 2024.
Elguindi, N., Granier, C., Stavrakou, T., Darras, S., Bauwens, M., Cao, H., Chen, C., Denier van der Gon, H. a. C., Dubovik, O., Fu, T. M., Henze, D. K., Jiang, Z., Keita, S., Kuenen, J. J. P., Kurokawa, J., Liousse, C., Miyazaki, K., Müller, J.-F., Qu, Z., Solmon, F., and Zheng, B.: Intercomparison of Magnitudes and Trends in Anthropogenic Surface Emissions From Bottom-Up Inventories, Top-Down Estimates, and Emission Scenarios, Earth's Future, 8, e2020EF001520, https://doi.org/10.1029/2020EF001520, 2020.
Emmons, L. K., Schwantes, R. H., Orlando, J. J., Tyndall, G., Kinnison, D., Lamarque, J.-F., Marsh, D., Mills, M. J., Tilmes, S., Bardeen, C., Buchholz, R. R., Conley, A., Gettelman, A., Garcia, R., Simpson, I., Blake, D. R., Meinardi, S., and Pétron, G.: The Chemistry Mechanism in the Community Earth System Model Version 2 (CESM2), J. Adv. Model. Earth Sy., 12, e2019MS001882, https://doi.org/10.1029/2019MS001882, 2020.
Fang, X., Shao, M., Stohl, A., Zhang, Q., Zheng, J., Guo, H., Wang, C., Wang, M., Ou, J., Thompson, R. L., and Prinn, R. G.: Top-down estimates of benzene and toluene emissions in the Pearl River Delta and Hong Kong, China, Atmos. Chem. Phys., 16, 3369–3382, https://doi.org/10.5194/acp-16-3369-2016, 2016.
Fiore, A. M., Jacob, D. J., Field, B. D., Streets, D. G., Fernandes, S. D., and Jang, C.: Linking Ozone Pollution and Climate Change: The Case for Controlling Methane, Geophys. Res. Lett., 29, 25-1–25-4, https://doi.org/10.1029/2002GL015601, 2002.
Fuhrer, J., Skärby, L., and Ashmore, M. R.: Critical Levels for Ozone Effects on Vegetation in Europe, Environ. Pollut., 97, 91–106, https://doi.org/10.1016/S0269-7491(97)00067-5, 1997.
Gaubert, B., Arellano Jr., A. F., Barré, J., Worden, H. M., Emmons, L. K., Tilmes, S., Buchholz, R. R., Vitt, F., Raeder, K., Collins, N., Anderson, J. L., Wiedinmyer, C., Martínez Alonso, S., Edwards, D. P., Andreae, M. O., Hannigan, J. W., Petri, C., Strong, K., and Jones, N.: Toward a Chemical Reanalysis in a Coupled Chemistry-Climate Model: An Evaluation of MOPITT CO Assimilation and Its Impact on Tropospheric Composition, J. Geophys. Res.-Atmos., 121, 7310–7343, https://doi.org/10.1002/2016JD024863, 2016.
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs, L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan, K., Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A., Silva, A. M. da, Gu, W., Kim, G.-K., Koster, R., Lucchesi, R., Merkova, D., Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert, S. D., Sienkiewicz, M., and Zhao, B.: The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), J. Climate, 30, 5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017.
Goldberg, D. L., de Foy, B., Nawaz, M. O., Johnson, J., Yarwood, G., and Judd, L.: Quantifying NOx Emission Sources in Houston, Texas Using Remote Sensing Aircraft Measurements and Source Apportionment Regression Models, ACS EST Air, 1, 1391–1401, https://doi.org/10.1021/acsestair.4c00097, 2024.
Granier, C., Darras, S., Denier van der Gon, H., Doubalova, J., Elguindi, N., Galle, B., Gauss, M., Guevara, M., Jalkanen, J.-P., Kuenen, J., Liousse, C., Quack, B., Simpson, D., and Sindelarova, K.: The Copernicus Atmosphere Monitoring Service global and regional emissions (April 2019 version), Copernicus Atmosphere Monitoring Service (CAMS) report, https://doi.org/10.24380/D0BN-KX16, 2019.
Guenther, A., Hewitt, C. N., Erickson, D., Fall, R., Geron, C., Graedel, T., Harley, P., Klinger, L., Lerdau, M., Mckay, W. A., Pierce, T., Scholes, B., Steinbrecher, R., Tallamraju, R., Taylor, J., and Zimmerman, P.: A Global Model of Natural Volatile Organic Compound Emissions, J. Geophys. Res.-Atmos., 100, 8873–8892, https://doi.org/10.1029/94JD02950, 1995.
Guenther, A. B., Jiang, X., Heald, C. L., Sakulyanontvittaya, T., Duhl, T., Emmons, L. K., and Wang, X.: The Model of Emissions of Gases and Aerosols from Nature version 2.1 (MEGAN2.1): an extended and updated framework for modeling biogenic emissions, Geosci. Model Dev., 5, 1471–1492, https://doi.org/10.5194/gmd-5-1471-2012, 2012.
Guevara, M., Jorba, O., Tena, C., Denier van der Gon, H., Kuenen, J., Elguindi, N., Darras, S., Granier, C., and Pérez García-Pando, C.: Copernicus Atmosphere Monitoring Service TEMPOral profiles (CAMS-TEMPO): global and European emission temporal profile maps for atmospheric chemistry modelling, Earth Syst. Sci. Data, 13, 367–404, https://doi.org/10.5194/essd-13-367-2021, 2021.
Hanna, S. R. and Chang, J. C.: Relations Between Meteorology and Ozone in the Lake Michigan Region, J. Appl. Meteorol. Clim., 34, 670–678, https://doi.org/10.1175/1520-0450(1995)034<0670:RBMAOI>2.0.CO;2, 1995.
Hayden, K. L., Sills, D. M. L., Brook, J. R., Li, S.-M., Makar, P. A., Markovic, M. Z., Liu, P., Anlauf, K. G., O'Brien, J. M., Li, Q., and McLaren, R.: Aircraft study of the impact of lake-breeze circulations on trace gases and particles during BAQS-Met 2007, Atmos. Chem. Phys., 11, 10173–10192, https://doi.org/10.5194/acp-11-10173-2011, 2011.
Herman, J., Cede, A., Spinei, E., Mount, G., Tzortziou, M., and Abuhassan, N.: NO2 Column Amounts from Ground-Based Pandora and MFDOAS Spectrometers using the Direct-Sun DOAS Technique: Intercomparisons and Application to OMI Validation, J. Geophys. Res.-Atmos., 114, D13307, https://doi.org/10.1029/2009JD011848, 2009.
Hoesly, R. M., Smith, S. J., Feng, L., Klimont, Z., Janssens-Maenhout, G., Pitkanen, T., Seibert, J. J., Vu, L., Andres, R. J., Bolt, R. M., Bond, T. C., Dawidowski, L., Kholod, N., Kurokawa, J.-I., Li, M., Liu, L., Lu, Z., Moura, M. C. P., O'Rourke, P. R., and Zhang, Q.: Historical (1750–2014) anthropogenic emissions of reactive gases and aerosols from the Community Emissions Data System (CEDS), Geosci. Model Dev., 11, 369–408, https://doi.org/10.5194/gmd-11-369-2018, 2018.
Huang, Y., Unger, N., Harper, K., and Heyes, C.: Global Climate and Human Health Effects of the Gasoline and Diesel Vehicle Fleets, GeoHealth, 4, e2019GH000240, https://doi.org/10.1029/2019GH000240, 2020.
Jacob, D. J.: Introduction to Atmospheric Chemistry, Princeton University Press, 280 pp., ISBN 9781400841547, 1999.
Jacob, D., Logan, J., Yevich, R., Gardner, G., Spivakovsky, C., Wofsy, S., Munger, J., Sillman, S., Prather, M., and Rogers, M.: Simulation of Summertime Ozone Over North America, J. Geophys. Res., 98, 14797–14816, https://doi.org/10.1029/93JD01223, 1993.
Jaffe, D. and Ray, J.: Increase in Surface Ozone at Rural Sites in the Western US, Atmos. Environ., 41, 5452–5463, https://doi.org/10.1016/j.atmosenv.2007.02.034, 2007.
Jo, D. S.: MUSICAv0 results for Jo et al. (2023) in JAMES, Zenodo [data set], https://doi.org/10.5281/zenodo.8044736, 2023.
Jo, D. S., Park, R. J., Kim, M. J., and Spracklen, D. V.: Effects of Chemical Aging on Global Secondary Organic Aerosol Using the Volatility Basis Set Approach, Atmos. Environ., 81, 230–244, https://doi.org/10.1016/j.atmosenv.2013.08.055, 2013.
Jo, D. S., Hodzic, A., Emmons, L. K., Tilmes, S., Schwantes, R. H., Mills, M. J., Campuzano-Jost, P., Hu, W., Zaveri, R. A., Easter, R. C., Singh, B., Lu, Z., Schulz, C., Schneider, J., Shilling, J. E., Wisthaler, A., and Jimenez, J. L.: Future changes in isoprene-epoxydiol-derived secondary organic aerosol (IEPOX SOA) under the Shared Socioeconomic Pathways: the importance of physicochemical dependency, Atmos. Chem. Phys., 21, 3395–3425, https://doi.org/10.5194/acp-21-3395-2021, 2021.
Jo, D. S., Emmons, L. K., Callaghan, P., Tilmes, S., Woo, J.-H., Kim, Y., Kim, J., Granier, C., Soulié, A., Doumbia, T., Darras, S., Buchholz, R. R., Simpson, I. J., Blake, D. R., Wisthaler, A., Schroeder, J. R., Fried, A., and Kanaya, Y.: Comparison of Urban Air Quality Simulations During the KORUS-AQ Campaign With Regionally Refined Versus Global Uniform Grids in the Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICA) Version 0, J. Adv. Model. Earth Sy., 15, e2022MS003458, https://doi.org/10.1029/2022MS003458, 2023.
Jones, P. W.: First- and Second-Order Conservative Remapping Schemes for Grids in Spherical Coordinates, Monthly Weather Review, 2204–2210, https://doi.org/10.1175/1520-0493(1999)127%3C2204:FASOCR%3E2.0.CO;2, 1999.
Judd, L. M., Al-Saadi, J. A., Janz, S. J., Kowalewski, M. G., Pierce, R. B., Szykman, J. J., Valin, L. C., Swap, R., Cede, A., Mueller, M., Tiefengraber, M., Abuhassan, N., and Williams, D.: Evaluating the impact of spatial resolution on tropospheric NO2 column comparisons within urban areas using high-resolution airborne data, Atmos. Meas. Tech., 12, 6091–6111, https://doi.org/10.5194/amt-12-6091-2019, 2019.
Judd, L. M., Al-Saadi, J. A., Szykman, J. J., Valin, L. C., Janz, S. J., Kowalewski, M. G., Eskes, H. J., Veefkind, J. P., Cede, A., Mueller, M., Gebetsberger, M., Swap, R., Pierce, R. B., Nowlan, C. R., Abad, G. G., Nehrir, A., and Williams, D.: Evaluating Sentinel-5P TROPOMI tropospheric NO2 column densities with airborne and Pandora spectrometers near New York City and Long Island Sound, Atmos. Meas. Tech., 13, 6113–6140, https://doi.org/10.5194/amt-13-6113-2020, 2020.
Lauritzen, P. H., Nair, R. D., Herrington, A. R., Callaghan, P., Goldhaber, S., Dennis, J. M., Bacmeister, J. T., Eaton, B. E., Zarzycki, C. M., Taylor, M. A., Ullrich, P. A., Dubos, T., Gettelman, A., Neale, R. B., Dobbins, B., Reed, K. A., Hannay, C., Medeiros, B., Benedict, J. J., and Tribbia, J. J.: NCAR Release of CAM-SE in CESM2.0: A Reformulation of the Spectral Element Dynamical Core in Dry-Mass Vertical Coordinates With Comprehensive Treatment of Condensates and Energy, J. Adv. Model. Earth Sy., 10, 1537–1570, https://doi.org/10.1029/2017MS001257, 2018.
Lawrence, D. M., Fisher, R. A., Koven, C. D., Oleson, K. W., Swenson, S. C., Bonan, G., Collier, N., Ghimire, B., van Kampenhout, L., Kennedy, D., Kluzek, E., Lawrence, P. J., Li, F., Li, H., Lombardozzi, D., Riley, W. J., Sacks, W. J., Shi, M., Vertenstein, M., Wieder, W. R., Xu, C., Ali, A. A., Badger, A. M., Bisht, G., van den Broeke, M., Brunke, M. A., Burns, S. P., Buzan, J., Clark, M., Craig, A., Dahlin, K., Drewniak, B., Fisher, J. B., Flanner, M., Fox, A. M., Gentine, P., Hoffman, F., Keppel-Aleks, G., Knox, R., Kumar, S., Lenaerts, J., Leung, L. R., Lipscomb, W. H., Lu, Y., Pandey, A., Pelletier, J. D., Perket, J., Randerson, J. T., Ricciuto, D. M., Sanderson, B. M., Slater, A., Subin, Z. M., Tang, J., Thomas, R. Q., Val Martin, M., and Zeng, X.: The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty, J. Adv. Model. Earth Sy., 11, 4245–4287, https://doi.org/10.1029/2018MS001583, 2019.
Lelieveld, J., Evans, J. S., Fnais, M., Giannadaki, D., and Pozzer, A.: The Contribution of Outdoor Air Pollution Sources to Premature Mortality on a Global Scale, Nature, 525, 367–371, https://doi.org/10.1038/nature15371, 2015.
Lemke, L. D., Lamerato, L. E., Xu, X., Booza, J. C., Reiners, J. J., Raymond III, D. M., Villeneuve, P. J., Lavigne, E., Larkin, D., and Krouse, H. J.: Geospatial Relationships of Air Pollution and Acute Asthma Events Across the Detroit–Windsor International Border: Study Design and Preliminary Results, J. Expo. Sci. Env. Epid., 24, 346–357, https://doi.org/10.1038/jes.2013.78, 2014.
Lichtig, P., Gaubert, B., Emmons, L. K., Jo, D. S., Callaghan, P., Ibarra-Espinosa, S., Dawidowski, L., Brasseur, G. P., and Pfister, G.: Multiscale CO Budget Estimates Across South America: Quantifying Local Sources and Long Range Transport, J. Geophys. Res.-Atmos., 129, e2023JD040434, https://doi.org/10.1029/2023JD040434, 2024.
Lin, J.-T., Youn, D., Liang, X.-Z., and Wuebbles, D. J.: Global Model Simulation of Summertime U.s. Ozone Diurnal Cycle and Its Sensitivity to PBL Mixing, Spatial Resolution, and Emissions, Atmos. Environ., 42, 8470–8483, https://doi.org/10.1016/j.atmosenv.2008.08.012, 2008.
Liu, F., Beirle, S., Zhang, Q., Dörner, S., He, K., and Wagner, T.: NOx lifetimes and emissions of cities and power plants in polluted background estimated by satellite observations, Atmos. Chem. Phys., 16, 5283–5298, https://doi.org/10.5194/acp-16-5283-2016, 2016a.
Liu, O., Li, Z., Lin, Y., Fan, C., Zhang, Y., Li, K., Zhang, P., Wei, Y., Chen, T., Dong, J., and de Leeuw, G.: Evaluation of the first year of Pandora NO2 measurements over Beijing and application to satellite validation, Atmos. Meas. Tech., 17, 377–395, https://doi.org/10.5194/amt-17-377-2024, 2024.
Liu, X., Ma, P.-L., Wang, H., Tilmes, S., Singh, B., Easter, R. C., Ghan, S. J., and Rasch, P. J.: Description and evaluation of a new four-mode version of the Modal Aerosol Module (MAM4) within version 5.3 of the Community Atmosphere Model, Geosci. Model Dev., 9, 505–522, https://doi.org/10.5194/gmd-9-505-2016, 2016b.
Mariscal, N.: Grid Information Files and Processed Datasets for Mariscal et al. (2025) in GMD, Zenodo [data set], https://doi.org/10.5281/zenodo.14625128, 2025.
Martínez-Alonso, S., Veefkind, J. P., Dix, B., Gaubert, B., Theys, N., Granier, C., Soulié, A., Darras, S., Eskes, H., Tang, W., Worden, H., de Gouw, J., and Levelt, P. F.: S-5P/TROPOMI-Derived NO Emissions From Copper/Cobalt Mining and Other Industrial Activities in the Copperbelt (Democratic Republic of Congo and Zambia), Geophys. Res. Lett., 50, e2023GL104109, https://doi.org/10.1029/2023GL104109, 2023.
Monks, P. S., Archibald, A. T., Colette, A., Cooper, O., Coyle, M., Derwent, R., Fowler, D., Granier, C., Law, K. S., Mills, G. E., Stevenson, D. S., Tarasova, O., Thouret, V., von Schneidemesser, E., Sommariva, R., Wild, O., and Williams, M. L.: Tropospheric ozone and its precursors from the urban to the global scale from air quality to short-lived climate forcer, Atmos. Chem. Phys., 15, 8889–8973, https://doi.org/10.5194/acp-15-8889-2015, 2015.
National Aeronautics and Space Administration and European Space Agency: Pandonia Global Network, https://www.pandonia-global-network.org/, last access: 15 September 2025.
Nowlan, C. R., Liu, X., Leitch, J. W., Chance, K., González Abad, G., Liu, C., Zoogman, P., Cole, J., Delker, T., Good, W., Murcray, F., Ruppert, L., Soo, D., Follette-Cook, M. B., Janz, S. J., Kowalewski, M. G., Loughner, C. P., Pickering, K. E., Herman, J. R., Beaver, M. R., Long, R. W., Szykman, J. J., Judd, L. M., Kelley, P., Luke, W. T., Ren, X., and Al-Saadi, J. A.: Nitrogen dioxide observations from the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument: Retrieval algorithm and measurements during DISCOVER-AQ Texas 2013, Atmos. Meas. Tech., 9, 2647–2668, https://doi.org/10.5194/amt-9-2647-2016, 2016.
Nowlan, C. R., Liu, X., Janz, S. J., Kowalewski, M. G., Chance, K., Follette-Cook, M. B., Fried, A., González Abad, G., Herman, J. R., Judd, L. M., Kwon, H.-A., Loughner, C. P., Pickering, K. E., Richter, D., Spinei, E., Walega, J., Weibring, P., and Weinheimer, A. J.: Nitrogen dioxide and formaldehyde measurements from the GEOstationary Coastal and Air Pollution Events (GEO-CAPE) Airborne Simulator over Houston, Texas, Atmos. Meas. Tech., 11, 5941–5964, https://doi.org/10.5194/amt-11-5941-2018, 2018.
Olaguer, E. P., Hu, Y., Kilmer, S., Adelman, Z. E., Vasilakos, P., Odman, M. T., Vaerten, M., McDonald, T., Gregory, D., Lomerson, B., and Russell, A. G.: Is There a Formaldehyde Deficit in Emissions Inventories for Southeast Michigan?, Atmosphere, 14, 461, https://doi.org/10.3390/atmos14030461, 2023a.
Olaguer, E. P., Su, Y., Stroud, C. A., Healy, R. M., Batterman, S. A., Yacovitch, T. I., Chai, J., Huang, Y., and Parsons, M. T.: The Michigan–Ontario Ozone Source Experiment (MOOSE): An Overview, Atmosphere, 14, 1630, https://doi.org/10.3390/atmos14111630, 2023b.
Pfister, G. G., Eastham, S. D., Arellano, A. F., Aumont, B., Barsanti, K. C., Barth, M. C., Conley, A., Davis, N. A., Emmons, L. K., Fast, J. D., Fiore, A. M., Gaubert, B., Goldhaber, S., Granier, C., Grell, G. A., Guevara, M., Henze, D. K., Hodzic, A., Liu, X., Marsh, D. R., Orlando, J. J., Plane, J. M. C., Polvani, L. M., Rosenlof, K. H., Steiner, A. L., Jacob, D. J., and Brasseur, G. P.: The Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICA), Bulletin of the American Meteorological Society, E1743–E1760, https://doi.org/10.1175/BAMS-D-19-0331.1, 2020.
Ramanathan, V. and Feng, Y.: On Avoiding Dangerous Anthropogenic Interference with the Climate System: Formidable Challenges Ahead, Proceeding of the National Academy of the Sciences, USA, 105, 14245–14250, https://doi.org/10.1073/pnas.0803838105, 2008.
Ramanathan, V., Crutzen, P., Kiehl, J., and Rosenfeld, D.: Aerosols, Climate, and the Hydrological Cycle, Science, 294, 2119–2124, https://doi.org/10.1126/science.1064034, 2002.
Schwantes, R. H., Emmons, L. K., Orlando, J. J., Barth, M. C., Tyndall, G. S., Hall, S. R., Ullmann, K., St. Clair, J. M., Blake, D. R., Wisthaler, A., and Bui, T. P. V.: Comprehensive isoprene and terpene gas-phase chemistry improves simulated surface ozone in the southeastern US, Atmos. Chem. Phys., 20, 3739–3776, https://doi.org/10.5194/acp-20-3739-2020, 2020.
Schwantes, R. H., Lacey, F. G., Tilmes, S., Emmons, L. K., Lauritzen, P. H., Walters, S., Callaghan, P., Zarzycki, C. M., Barth, M. C., Jo, D. S., Bacmeister, J. T., Neale, R. B., Vitt, F., Kluzek, E., Roozitalab, B., Hall, S. R., Ullmann, K., Warneke, C., Peischl, J., Pollack, I. B., Flocke, F., Wolfe, G. M., Hanisco, T. F., Keutsch, F. N., Kaiser, J., Bui, T. P. V., Jimenez, J. L., Campuzano-Jost, P., Apel, E. C., Hornbrook, R. S., Hills, A. J., Yuan, B., and Wisthaler, A.: Evaluating the Impact of Chemical Complexity and Horizontal Resolution on Tropospheric Ozone Over the Conterminous US With a Global Variable Resolution Chemistry Model, J. Adv. Model. Earth Sy., 14, e2021MS002889, https://doi.org/10.1029/2021MS002889, 2022.
Scott, R. W. and Huff, F. A.: Impacts of the Great Lakes on Regional Climate Conditions, J. Great Lakes Res., 22, 845–863, https://doi.org/10.1016/S0380-1330(96)71006-7, 1996.
Sicard, P., Agathokleous, E., Araminiene, V., Carrari, E., Hoshika, Y., De Marco, A., and Paoletti, E.: Should We See Urban Trees as Effective Solutions to Reduce Increasing Ozone Levels in Cities?, Environ. Pollut., 243, 163–176, https://doi.org/10.1016/j.envpol.2018.08.049, 2018.
Soulie, A., Granier, C., Darras, S., Zilbermann, N., Doumbia, T., Guevara, M., Jalkanen, J.-P., Keita, S., Liousse, C., Crippa, M., Guizzardi, D., Hoesly, R., and Smith, S. J.: Global anthropogenic emissions (CAMS-GLOB-ANT) for the Copernicus Atmosphere Monitoring Service simulations of air quality forecasts and reanalyses, Earth Syst. Sci. Data, 16, 2261–2279, https://doi.org/10.5194/essd-16-2261-2024, 2024.
Spinei, E., Whitehill, A., Fried, A., Tiefengraber, M., Knepp, T. N., Herndon, S., Herman, J. R., Müller, M., Abuhassan, N., Cede, A., Richter, D., Walega, J., Crawford, J., Szykman, J., Valin, L., Williams, D. J., Long, R., Swap, R. J., Lee, Y., Nowak, N., and Poche, B.: The first evaluation of formaldehyde column observations by improved Pandora spectrometers during the KORUS-AQ field study, Atmos. Meas. Tech., 11, 4943–4961, https://doi.org/10.5194/amt-11-4943-2018, 2018.
Stanier, C. O., Pierce, R. B., Abdi-Oskouei, M., Adelman, Z. E., Al-Saadi, J., Alwe, H. D., Bertram, T. H., Carmichael, G. R., Christiansen, M. B., Cleary, P. A., Czarnetzki, A. C., Dickens, A. F., Fuoco, M. A., Hughes, D. D., Hupy, J. P., Janz, S. J., Judd, L. M., Kenski, D., Kowalewski, M. G., Long, R. W., Millet, D. B., Novak, G., Roozitalab, B., Shaw, S. L., Stone, E. A., Szykman, J., Valin, L., Vermeuel, M., Wagner, T. J., Whitehill, A. R., and Williams, D. J.: Overview of the Lake Michigan Ozone Study 2017, Bulletin of the American Meteorological Society, E2207–E2225, https://doi.org/10.1175/BAMS-D-20-0061.1, 2021.
Tang, W., Emmons, L. K., Buchholz, R. R., Wiedinmyer, C., Schwantes, R. H., He, C., Kumar, R., Pfister, G. G., Worden, H. M., Hornbrook, R. S., Apel, E. C., Tilmes, S., Gaubert, B., Martínez-Alonso, S.-E., Lacey, F., Holmes, C. D., Diskin, G. S., Bourgeois, I., Peischl, J., Ryerson, T. B., Hair, J. W., Weinheimer, A. J., Montzka, D. D., Tyndall, G. S., and Campos, T. L.: Effects of Fire Diurnal Variation and Plume Rise on U.S. Air Quality During FIREX-AQ and WE-CAN Based on the Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICAv0), J. Geophys. Res.-Atmos., 127, e2022JD036650, https://doi.org/10.1029/2022JD036650, 2022.
Tang, W., Emmons, L. K., Worden, H. M., Kumar, R., He, C., Gaubert, B., Zheng, Z., Tilmes, S., Buchholz, R. R., Martinez-Alonso, S.-E., Granier, C., Soulie, A., McKain, K., Daube, B. C., Peischl, J., Thompson, C., and Levelt, P.: Application of the Multi-Scale Infrastructure for Chemistry and Aerosols version 0 (MUSICAv0) for air quality research in Africa, Geosci. Model Dev., 16, 6001–6028, https://doi.org/10.5194/gmd-16-6001-2023, 2023.
Taylor, K. E.: Summarizing Multiple Aspects of Model Performance in a Single Diagram, J. Geophys. Res.-Atmos., 106, 7183–7192, https://doi.org/10.1029/2000JD900719, 2001.
Tilmes, S., Hodzic, A., Emmons, L. K., Mills, M. J., Gettelman, A., Kinnison, D. E., Park, M., Lamarque, J.-F., Vitt, F., Shrivastava, M., Campuzano-Jost, P., Jimenez, J. L., and Liu, X.: Climate Forcing and Trends of Organic Aerosols in the Community Earth System Model (CESM2), J. Adv. Model. Earth Sy., 11, 4323–4351, https://doi.org/10.1029/2019MS001827, 2019.
Unger, N., Bond, T. C., Wang, J. S., Koch, D. M., Menon, S., Shindell, D. T., and Bauer, S.: Attribution of Climate Forcing to Economic Sectors, P. Natl. Acad. Sci. USA, 107, 3382–3387, https://doi.org/10.1073/pnas.0906548107, 2010.
University Corporation for Atmospheric Research: ESMCI/Community_Mesh_Generation_ Toolkit, https://github.com/ESMCI/Community_Mesh_Generation_Toolkit (last access: 15 September 2025), 2025.
University Corporation for Atmospheric Research: ESCOMP/CESM: https://github.com/ESCOMP/CESM, last access: 15 September 2025.
US Environmental Protection Agency: Green Book, US EPA, https://www3.epa.gov/airquality/greenbook/anayo_mi.html (last access: 1 April 2021).
US Environmental Protection Agency: Air Quality System Data Mart, https://www.epa.gov/outdoor-air-quality-data, last access: 15 September 2025.
Vermeuel, M. P., Novak, G. A., Alwe, H. D., Hughes, D. D., Kaleel, R., Dickens, A. F., Kenski, D., Czarnetzki, A. C., Stone, E. A., Stanier, C. O., Pierce, R. B., Millet, D. B., and Bertram, T. H.: Sensitivity of Ozone Production to NO and VOC Along the Lake Michigan Coastline, J. Geophys. Res.-Atmos., 124, 10989–11006, https://doi.org/10.1029/2019JD030842, 2019.
Wang, P., Chen, Y., Hu, J., Zhang, H., and Ying, Q.: Attribution of Tropospheric Ozone to NOx and VOC Emissions: Considering Ozone Formation in the Transition Regime, Environ. Sci. Technol., 53, 1404–1412, https://doi.org/10.1021/acs.est.8b05981, 2019.
Wang, J., Chen, Y., Liao, W., He, G., Tett, S. F. B., Yan, Z., Zhai, P., Feng, J., Ma, W., Huang, C., and Hu, Y.: Anthropogenic emissions and urbanization increase risk of compound hot extremes in cities, Nat. Clim. Chang., 11, 1084–1089, https://doi.org/10.1038/s41558-021-01196-2, 2021.
Wiedinmyer, C., Akagi, S. K., Yokelson, R. J., Emmons, L. K., Al-Saadi, J. A., Orlando, J. J., and Soja, A. J.: The Fire INventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning, Geosci. Model Dev., 4, 625–641, https://doi.org/10.5194/gmd-4-625-2011, 2011.
Wolfe, G. M., Kaiser, J., Hanisco, T. F., Keutsch, F. N., de Gouw, J. A., Gilman, J. B., Graus, M., Hatch, C. D., Holloway, J., Horowitz, L. W., Lee, B. H., Lerner, B. M., Lopez-Hilifiker, F., Mao, J., Marvin, M. R., Peischl, J., Pollack, I. B., Roberts, J. M., Ryerson, T. B., Thornton, J. A., Veres, P. R., and Warneke, C.: Formaldehyde production from isoprene oxidation across NOx regimes, Atmos. Chem. Phys., 16, 2597–2610, https://doi.org/10.5194/acp-16-2597-2016, 2016.
Wortman, S. E. and Lovell, S. T.: Environmental Challenges Threatening the Growth of Urban Agriculture in the United States, J. Environ. Qual., 42, 1283–1294, https://doi.org/10.2134/jeq2013.01.0031, 2013.
Xiong, Y., Chai, J., Mao, H., Mariscal, N., Yacovitch, T., Lerner, B., Majluf, F., Canagaratna, M., Olaguer, E. P., and Huang, Y.: Examining the Summertime Ozone Formation Regime in Southeast Michigan Using MOOSE Ground-Based HCHO/NO2 Measurements and F0AM Box Model, J. Geophys. Res.-Atmos., 128, e2023JD038943, https://doi.org/10.1029/2023JD038943, 2023.
Yan, S., Zhu, B., Shi, S., Lu, W., Gao, J., Kang, H., and Liu, D.: Impact of aerosol optics on vertical distribution of ozone in autumn over Yangtze River Delta, Atmospheric Chemistry and Physics, 23, 5177–5190, https://doi.org/10.5194/acp-23-5177-2023, 2023.
Short summary
The distribution of ozone (O3) and its precursors (NOx, VOCs) is explored using the chemistry–climate model MUSICAv0 and evaluated using measurements from the Michigan–Ontario Ozone Source Experiment. A custom grid of ~7 km was created over Michigan. A sector-based diurnal cycle for anthropogenic nitric oxide was included in the model. This work shows that grid resolution plays a more important role in relation to O3 precursors and that the diurnal cycle significantly impacts nighttime O3 formation.
The distribution of ozone (O3) and its precursors (NOx, VOCs) is explored using the...
