Articles | Volume 23, issue 11
https://doi.org/10.5194/acp-23-6271-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-23-6271-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Jun 2023
Research article |
| 07 Jun 2023
| 07 Jun 2023
Background nitrogen dioxide (NO2) over the United States and its implications for satellite observations and trends: effects of nitrate photolysis, aircraft, and open fires
John A. Paulson School of Engineering and Applied Sciences, Harvard
University, Cambridge, MA 02138, USA
Daniel J. Jacob
John A. Paulson School of Engineering and Applied Sciences, Harvard
University, Cambridge, MA 02138, USA
Viral Shah
John A. Paulson School of Engineering and Applied Sciences, Harvard
University, Cambridge, MA 02138, USA
now at: Global Modeling and Assimilation Office, NASA Goddard Space
Flight Center, Greenbelt, MD 20771, USA
now at: Science Systems and
Applications, Inc., Lanham, MD 20706, USA
Sebastian D. Eastham
Department of
Aeronautics and Astronautics, Laboratory for Aviation and the Environment, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
Joint Program on the Science and Policy of Global Change,
Massachusetts Institute of Technology, Cambridge, MA 02139, USA
Thibaud M. Fritz
Department of
Aeronautics and Astronautics, Laboratory for Aviation and the Environment, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
Loretta J. Mickley
John A. Paulson School of Engineering and Applied Sciences, Harvard
University, Cambridge, MA 02138, USA
Tianjia Liu
Department of Earth and Planetary Sciences, Harvard University,
Cambridge, MA 02138, USA
Yi Wang
Center for Global and Regional Environmental Research, Iowa
Technology Institute, The University of Iowa, Iowa City, IA 52242, USA
Department of Chemical and Biochemical Engineering, The University of
Iowa, Iowa City, IA 52242, USA
Center for Global and Regional Environmental Research, Iowa
Technology Institute, The University of Iowa, Iowa City, IA 52242, USA
Department of Chemical and Biochemical Engineering, The University of
Iowa, Iowa City, IA 52242, USA
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Hyerim Kim, Xi Chen, Jun Wang, Zhendong Lu, Meng Zhou, Gregory R. Carmichael, Sang Seo Park, and Jhoon Kim
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Atmospheric model gradients provide a meaningful tool for better understanding the underlying atmospheric processes. Adjoint modeling enables computationally efficient gradient calculations. We present the adjoint of the GEOS-Chem unified chemistry extension (UCX). With this development, the GEOS-Chem adjoint model can capture stratospheric ozone and other processes jointly with tropospheric processes. We apply it to characterize the Antarctic ozone depletion potential of active halogen species.
Tong Sha, Siyu Yang, Qingcai Chen, Liangqing Li, Xiaoyan Ma, Yan-Lin Zhang, Zhaozhong Feng, K. Folkert Boersma, and Jun Wang
Atmos. Chem. Phys., 24, 8441–8455, https://doi.org/10.5194/acp-24-8441-2024, https://doi.org/10.5194/acp-24-8441-2024, 2024
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Using an updated soil reactive nitrogen emission scheme in the Unified Inputs for Weather Research and Forecasting coupled with Chemistry (UI-WRF-Chem) model, we investigate the role of soil NO and HONO (Nr) emissions in air quality and temperature in North China. Contributions of soil Nr emissions to O3 and secondary pollutants are revealed, exceeding effects of soil NOx or HONO emission. Soil Nr emissions play an important role in mitigating O3 pollution and addressing climate change.
Zhendong Lu, Jun Wang, Yi Wang, Daven K. Henze, Xi Chen, Tong Sha, and Kang Sun
Atmos. Chem. Phys., 24, 7793–7813, https://doi.org/10.5194/acp-24-7793-2024, https://doi.org/10.5194/acp-24-7793-2024, 2024
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In contrast with past work showing that the reduction of emissions was the dominant factor for the nationwide increase of surface O3 during the lockdown in China, this study finds that the variation in meteorology (temperature and other parameters) plays a more important role. This result is obtained through sensitivity simulations using a chemical transport model constrained by satellite (TROPOMI) data and calibrated with surface observations.
Laura Hyesung Yang, Daniel J. Jacob, Ruijun Dang, Yujin J. Oak, Haipeng Lin, Jhoon Kim, Shixian Zhai, Nadia K. Colombi, Drew C. Pendergrass, Ellie Beaudry, Viral Shah, Xu Feng, Robert M. Yantosca, Heesung Chong, Junsung Park, Hanlim Lee, Won-Jin Lee, Soontae Kim, Eunhye Kim, Katherine R. Travis, James H. Crawford, and Hong Liao
Atmos. Chem. Phys., 24, 7027–7039, https://doi.org/10.5194/acp-24-7027-2024, https://doi.org/10.5194/acp-24-7027-2024, 2024
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The Geostationary Environment Monitoring Spectrometer (GEMS) provides hourly measurements of NO2. We use the chemical transport model to find how emissions, chemistry, and transport drive the changes in NO2 observed by GEMS at different times of the day. In winter, the chemistry plays a minor role, and high daytime emissions dominate the diurnal variation in NO2, balanced by transport. In summer, emissions, chemistry, and transport play an important role in shaping the diurnal variation in NO2.
Drew C. Pendergrass, Daniel J. Jacob, Yujin J. Oak, Jeewoo Lee, Minseok Kim, Jhoon Kim, Seoyoung Lee, Shixian Zhai, Hitoshi Irie, and Hong Liao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-172, https://doi.org/10.5194/essd-2024-172, 2024
Preprint withdrawn
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Atmos. Meas. Tech., 17, 2625–2636, https://doi.org/10.5194/amt-17-2625-2024, https://doi.org/10.5194/amt-17-2625-2024, 2024
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Methane is a potent greenhouse gas and a current high-priority target for short- to mid-term climate change mitigation. Detection of individual methane emitters from space has become possible in recent years, and the volume of data for this task has been rapidly growing, outpacing processing capabilities. We introduce an automated approach, U-Plume, which can detect and quantify emissions from individual methane sources in high-spatial-resolution satellite data.
Hannah Nesser, Daniel J. Jacob, Joannes D. Maasakkers, Alba Lorente, Zichong Chen, Xiao Lu, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Margaux Winter, Shuang Ma, A. Anthony Bloom, John R. Worden, Robert N. Stavins, and Cynthia A. Randles
Atmos. Chem. Phys., 24, 5069–5091, https://doi.org/10.5194/acp-24-5069-2024, https://doi.org/10.5194/acp-24-5069-2024, 2024
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We quantify 2019 methane emissions in the contiguous US (CONUS) at a ≈ 25 km × 25 km resolution using satellite methane observations. We find a 13 % upward correction to the 2023 US Environmental Protection Agency (EPA) Greenhouse Gas Emissions Inventory (GHGI) for 2019, with large corrections to individual states, urban areas, and landfills. This may present a challenge for US climate policies and goals, many of which target significant reductions in methane emissions.
Amy Christiansen, Loretta J. Mickley, and Lu Hu
Atmos. Chem. Phys., 24, 4569–4589, https://doi.org/10.5194/acp-24-4569-2024, https://doi.org/10.5194/acp-24-4569-2024, 2024
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In this work, we provide an additional constraint on emissions and trends of nitrogen oxides using nitrate wet deposition (NWD) fluxes over the United States and Europe from 1980–2020. We find that NWD measurements constrain total NOx emissions well. We also find evidence of NOx emission overestimates in both domains, but especially over Europe, where NOx emissions are overestimated by a factor of 2. Reducing NOx emissions over Europe improves model representation of ozone at the surface.
Xu Feng, Loretta J. Mickley, Michelle L. Bell, Tianjia Liu, Jenny A. Fisher, and Maria Val Martin
Atmos. Chem. Phys., 24, 2985–3007, https://doi.org/10.5194/acp-24-2985-2024, https://doi.org/10.5194/acp-24-2985-2024, 2024
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During severe wildfire seasons, smoke can have a significant impact on air quality in Australia. Our study demonstrates that characterization of the smoke plume injection fractions greatly affects estimates of surface smoke PM2.5. Using the plume behavior predicted by the machine learning method leads to the best model agreement with observed surface PM2.5 in key cities across Australia, with smoke PM2.5 accounting for 5 %–52 % of total PM2.5 on average during fire seasons from 2009 to 2020.
Sebastian D. Eastham, Guillaume P. Chossière, Raymond L. Speth, Daniel J. Jacob, and Steven R. H. Barrett
Atmos. Chem. Phys., 24, 2687–2703, https://doi.org/10.5194/acp-24-2687-2024, https://doi.org/10.5194/acp-24-2687-2024, 2024
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Emissions from aircraft are known to cause air quality impacts worldwide, but the scale and mechanisms of this impact are not well understood. This work uses high-resolution computational modeling of the atmosphere to show that air pollution changes from aviation are mostly the result of emissions during cruise (high-altitude) operations, that these impacts are related to how much non-aviation pollution is present, and that prior regional assessments have underestimated these impacts.
Kelvin H. Bates, Mathew J. Evans, Barron H. Henderson, and Daniel J. Jacob
Geosci. Model Dev., 17, 1511–1524, https://doi.org/10.5194/gmd-17-1511-2024, https://doi.org/10.5194/gmd-17-1511-2024, 2024
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Accurate representation of rates and products of chemical reactions in atmospheric models is crucial for simulating concentrations of pollutants and climate forcers. We update the widely used GEOS-Chem atmospheric chemistry model with reaction parameters from recent compilations of experimental data and demonstrate the implications for key atmospheric chemical species. The updates decrease tropospheric CO mixing ratios and increase stratospheric nitrogen oxide mixing ratios, among other changes.
Qindan Zhu, Bryan Place, Eva Y. Pfannerstill, Sha Tong, Huanxin Zhang, Jun Wang, Clara M. Nussbaumer, Paul Wooldridge, Benjamin C. Schulze, Caleb Arata, Anthony Bucholtz, John H. Seinfeld, Allen H. Goldstein, and Ronald C. Cohen
Atmos. Chem. Phys., 23, 9669–9683, https://doi.org/10.5194/acp-23-9669-2023, https://doi.org/10.5194/acp-23-9669-2023, 2023
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Nitrogen oxide (NOx) is a hazardous air pollutant, and it is the precursor of short-lived climate forcers like tropospheric ozone and aerosol particles. While NOx emissions from transportation has been strictly regulated, soil NOx emissions are overlooked. We use the airborne flux measurements to observe NOx emissions from highways and urban and cultivated soil land cover types. We show non-negligible soil NOx emissions, which are significantly underestimated in current model simulations.
Drew C. Pendergrass, Daniel J. Jacob, Hannah Nesser, Daniel J. Varon, Melissa Sulprizio, Kazuyuki Miyazaki, and Kevin W. Bowman
Geosci. Model Dev., 16, 4793–4810, https://doi.org/10.5194/gmd-16-4793-2023, https://doi.org/10.5194/gmd-16-4793-2023, 2023
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We have built a tool called CHEEREIO that allows scientists to use observations of pollutants or gases in the atmosphere, such as from satellites or surface stations, to update supercomputer models that simulate the Earth. CHEEREIO uses the difference between the model simulations of the atmosphere and real-world observations to come up with a good guess for the actual composition of our atmosphere, the true emissions of various pollutants, and whatever else they may want to study.
Nicholas Balasus, Daniel J. Jacob, Alba Lorente, Joannes D. Maasakkers, Robert J. Parker, Hartmut Boesch, Zichong Chen, Makoto M. Kelp, Hannah Nesser, and Daniel J. Varon
Atmos. Meas. Tech., 16, 3787–3807, https://doi.org/10.5194/amt-16-3787-2023, https://doi.org/10.5194/amt-16-3787-2023, 2023
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We use machine learning to remove biases in TROPOMI satellite observations of atmospheric methane, with GOSAT observations serving as a reference. We find that the TROPOMI biases relative to GOSAT are related to the presence of aerosols and clouds, the surface brightness, and the specific detector that makes the observation aboard TROPOMI. The resulting blended TROPOMI+GOSAT product is more reliable for quantifying methane emissions.
Daniel J. Varon, Daniel J. Jacob, Benjamin Hmiel, Ritesh Gautam, David R. Lyon, Mark Omara, Melissa Sulprizio, Lu Shen, Drew Pendergrass, Hannah Nesser, Zhen Qu, Zachary R. Barkley, Natasha L. Miles, Scott J. Richardson, Kenneth J. Davis, Sudhanshu Pandey, Xiao Lu, Alba Lorente, Tobias Borsdorff, Joannes D. Maasakkers, and Ilse Aben
Atmos. Chem. Phys., 23, 7503–7520, https://doi.org/10.5194/acp-23-7503-2023, https://doi.org/10.5194/acp-23-7503-2023, 2023
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We use TROPOMI satellite observations to quantify weekly methane emissions from the US Permian oil and gas basin from May 2018 to October 2020. We find that Permian emissions are highly variable, with diverse economic and activity drivers. The most important drivers during our study period were new well development and natural gas price. Permian methane intensity averaged 4.6 % and decreased by 1 % per year.
Zichong Chen, Daniel J. Jacob, Ritesh Gautam, Mark Omara, Robert N. Stavins, Robert C. Stowe, Hannah Nesser, Melissa P. Sulprizio, Alba Lorente, Daniel J. Varon, Xiao Lu, Lu Shen, Zhen Qu, Drew C. Pendergrass, and Sarah Hancock
Atmos. Chem. Phys., 23, 5945–5967, https://doi.org/10.5194/acp-23-5945-2023, https://doi.org/10.5194/acp-23-5945-2023, 2023
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We quantify methane emissions from individual countries in the Middle East and North Africa by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. We show that the ability to simply relate oil/gas emissions to activity metrics is compromised by stochastic nature of local infrastructure and management practices. We find that the industry target for oil/gas methane intensity is achievable through associated gas capture, modern infrastructure, and centralized operations.
Shixian Zhai, Daniel J. Jacob, Drew C. Pendergrass, Nadia K. Colombi, Viral Shah, Laura Hyesung Yang, Qiang Zhang, Shuxiao Wang, Hwajin Kim, Yele Sun, Jin-Soo Choi, Jin-Soo Park, Gan Luo, Fangqun Yu, Jung-Hun Woo, Younha Kim, Jack E. Dibb, Taehyoung Lee, Jin-Seok Han, Bruce E. Anderson, Ke Li, and Hong Liao
Atmos. Chem. Phys., 23, 4271–4281, https://doi.org/10.5194/acp-23-4271-2023, https://doi.org/10.5194/acp-23-4271-2023, 2023
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Anthropogenic fugitive dust in East Asia not only causes severe coarse particulate matter air pollution problems, but also affects fine particulate nitrate. Due to emission control efforts, coarse PM decreased steadily. We find that the decrease of coarse PM is a major driver for a lack of decrease of fine particulate nitrate, as it allows more nitric acid to form fine particulate nitrate. The continuing decrease of coarse PM requires more stringent ammonia and nitrogen oxides emission controls.
Nadia K. Colombi, Daniel J. Jacob, Laura Hyesung Yang, Shixian Zhai, Viral Shah, Stuart K. Grange, Robert M. Yantosca, Soontae Kim, and Hong Liao
Atmos. Chem. Phys., 23, 4031–4044, https://doi.org/10.5194/acp-23-4031-2023, https://doi.org/10.5194/acp-23-4031-2023, 2023
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Surface ozone, detrimental to human and ecosystem health, is very high and increasing in South Korea. Using a global model of the atmosphere, we found that emissions from South Korea and China contribute equally to the high ozone observed. We found that in the absence of all anthropogenic emissions over East Asia, ozone is still very high, implying that the air quality standard in South Korea is not practically achievable unless this background external to East Asia can be decreased.
Laura Hyesung Yang, Daniel J. Jacob, Nadia K. Colombi, Shixian Zhai, Kelvin H. Bates, Viral Shah, Ellie Beaudry, Robert M. Yantosca, Haipeng Lin, Jared F. Brewer, Heesung Chong, Katherine R. Travis, James H. Crawford, Lok N. Lamsal, Ja-Ho Koo, and Jhoon Kim
Atmos. Chem. Phys., 23, 2465–2481, https://doi.org/10.5194/acp-23-2465-2023, https://doi.org/10.5194/acp-23-2465-2023, 2023
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A geostationary satellite can now provide hourly NO2 vertical columns, and obtaining the NO2 vertical columns from space relies on NO2 vertical distribution from the chemical transport model (CTM). In this work, we update the CTM to better represent the chemistry environment so that the CTM can accurately provide NO2 vertical distribution. We also find that the changes in NO2 vertical distribution driven by a change in mixing depth play an important role in the NO2 column's diurnal variation.
Fangqun Yu, Gan Luo, Arshad Arjunan Nair, Sebastian Eastham, Christina J. Williamson, Agnieszka Kupc, and Charles A. Brock
Atmos. Chem. Phys., 23, 1863–1877, https://doi.org/10.5194/acp-23-1863-2023, https://doi.org/10.5194/acp-23-1863-2023, 2023
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Particle number concentrations and size distributions in the stratosphere are studied through model simulations and comparisons with measurements. The nucleation scheme used in most of the solar geoengineering modeling studies overpredicts the nucleation rates and particle number concentrations in the stratosphere. The model based on updated nucleation schemes captures reasonably well some aspects of particle size distributions but misses some features. The possible reasons are discussed.
Jing Wei, Zhanqing Li, Jun Wang, Can Li, Pawan Gupta, and Maureen Cribb
Atmos. Chem. Phys., 23, 1511–1532, https://doi.org/10.5194/acp-23-1511-2023, https://doi.org/10.5194/acp-23-1511-2023, 2023
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This study estimated the daily seamless 10 km ambient gaseous pollutants (NO2, SO2, and CO) across China using machine learning with extensive input variables measured on monitors, satellites, and models. Our dataset yields a high data quality via cross-validation at varying spatiotemporal scales and outperforms most previous related studies, making it most helpful to future (especially short-term) air pollution and environmental health-related studies.
Viral Shah, Daniel J. Jacob, Ruijun Dang, Lok N. Lamsal, Sarah A. Strode, Stephen D. Steenrod, K. Folkert Boersma, Sebastian D. Eastham, Thibaud M. Fritz, Chelsea Thompson, Jeff Peischl, Ilann Bourgeois, Ilana B. Pollack, Benjamin A. Nault, Ronald C. Cohen, Pedro Campuzano-Jost, Jose L. Jimenez, Simone T. Andersen, Lucy J. Carpenter, Tomás Sherwen, and Mat J. Evans
Atmos. Chem. Phys., 23, 1227–1257, https://doi.org/10.5194/acp-23-1227-2023, https://doi.org/10.5194/acp-23-1227-2023, 2023
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NOx in the free troposphere (above 2 km) affects global tropospheric chemistry and the retrieval and interpretation of satellite NO2 measurements. We evaluate free tropospheric NOx in global atmospheric chemistry models and find that recycling NOx from its reservoirs over the oceans is faster than that simulated in the models, resulting in increases in simulated tropospheric ozone and OH. Over the U.S., free tropospheric NO2 contributes the majority of the tropospheric NO2 column in summer.
Randall V. Martin, Sebastian D. Eastham, Liam Bindle, Elizabeth W. Lundgren, Thomas L. Clune, Christoph A. Keller, William Downs, Dandan Zhang, Robert A. Lucchesi, Melissa P. Sulprizio, Robert M. Yantosca, Yanshun Li, Lucas Estrada, William M. Putman, Benjamin M. Auer, Atanas L. Trayanov, Steven Pawson, and Daniel J. Jacob
Geosci. Model Dev., 15, 8731–8748, https://doi.org/10.5194/gmd-15-8731-2022, https://doi.org/10.5194/gmd-15-8731-2022, 2022
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Atmospheric chemistry models must be able to operate both online as components of Earth system models and offline as standalone models. The widely used GEOS-Chem model operates both online and offline, but the classic offline version is not suitable for massively parallel simulations. We describe a new generation of the offline high-performance GEOS-Chem (GCHP) that enables high-resolution simulations on thousands of cores, including on the cloud, with improved access, performance, and accuracy.
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.
Amy Christiansen, Loretta J. Mickley, Junhua Liu, Luke D. Oman, and Lu Hu
Atmos. Chem. Phys., 22, 14751–14782, https://doi.org/10.5194/acp-22-14751-2022, https://doi.org/10.5194/acp-22-14751-2022, 2022
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Understanding tropospheric ozone trends is crucial for accurate predictions of future air quality and climate, but drivers of trends are not well understood. We analyze global tropospheric ozone trends since 1980 using ozonesonde and surface measurements, and we evaluate two models for their ability to reproduce trends. We find observational evidence of increasing tropospheric ozone, but models underestimate these increases. This hinders our ability to estimate ozone radiative forcing.
Gonzalo A. Ferrada, Meng Zhou, Jun Wang, Alexei Lyapustin, Yujie Wang, Saulo R. Freitas, and Gregory R. Carmichael
Geosci. Model Dev., 15, 8085–8109, https://doi.org/10.5194/gmd-15-8085-2022, https://doi.org/10.5194/gmd-15-8085-2022, 2022
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The smoke from fires is composed of different compounds that interact with the atmosphere and can create poor air-quality episodes. Here, we present a new fire inventory based on satellite observations from the Visible Infrared Imaging Radiometer Suite (VIIRS). We named this inventory the VIIRS-based Fire Emission Inventory (VFEI). Advantages of VFEI are its high resolution (~500 m) and that it provides information for many species. VFEI is publicly available and has provided data since 2012.
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
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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.
William Atkinson, Sebastian D. Eastham, Y.-H. Henry Chen, Jennifer Morris, Sergey Paltsev, C. Adam Schlosser, and Noelle E. Selin
Geosci. Model Dev., 15, 7767–7789, https://doi.org/10.5194/gmd-15-7767-2022, https://doi.org/10.5194/gmd-15-7767-2022, 2022
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Understanding policy effects on human-caused air pollutant emissions is key for assessing related health impacts. We develop a flexible scenario tool that combines updated emissions data sets, long-term economic modeling, and comprehensive technology pathways to clarify the impacts of climate and air quality policies. Results show the importance of both policy levers in the future to prevent long-term emission increases from offsetting near-term air quality improvements from existing policies.
Lu Shen, Ritesh Gautam, Mark Omara, Daniel Zavala-Araiza, Joannes D. Maasakkers, Tia R. Scarpelli, Alba Lorente, David Lyon, Jianxiong Sheng, Daniel J. Varon, Hannah Nesser, Zhen Qu, Xiao Lu, Melissa P. Sulprizio, Steven P. Hamburg, and Daniel J. Jacob
Atmos. Chem. Phys., 22, 11203–11215, https://doi.org/10.5194/acp-22-11203-2022, https://doi.org/10.5194/acp-22-11203-2022, 2022
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We use 22 months of TROPOMI satellite observations to quantity methane emissions from the oil (O) and natural gas (G) sector in the US and Canada at the scale of both individual basins as well as country-wide aggregates. We find that O/G-related methane emissions are underestimated in these inventories by 80 % for the US and 40 % for Canada, and 70 % of the underestimate in the US is from five O/G basins, including Permian, Haynesville, Anadarko, Eagle Ford, and Barnett.
Zichong Chen, Daniel J. Jacob, Hannah Nesser, Melissa P. Sulprizio, Alba Lorente, Daniel J. Varon, Xiao Lu, Lu Shen, Zhen Qu, Elise Penn, and Xueying Yu
Atmos. Chem. Phys., 22, 10809–10826, https://doi.org/10.5194/acp-22-10809-2022, https://doi.org/10.5194/acp-22-10809-2022, 2022
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We quantify methane emissions in China and contributions from different sectors by inverse analysis of 2019 TROPOMI satellite observations of atmospheric methane. We find that anthropogenic methane emissions for China are underestimated in the national inventory. Our estimate of emissions indicates a small life-cycle loss rate, implying net climate benefits from the current
coal-to-gasenergy transition in China. However, this small loss rate can be misleading given China's high gas imports.
Daniel J. Jacob, Daniel J. Varon, Daniel H. Cusworth, Philip E. Dennison, Christian Frankenberg, Ritesh Gautam, Luis Guanter, John Kelley, Jason McKeever, Lesley E. Ott, Benjamin Poulter, Zhen Qu, Andrew K. Thorpe, John R. Worden, and Riley M. Duren
Atmos. Chem. Phys., 22, 9617–9646, https://doi.org/10.5194/acp-22-9617-2022, https://doi.org/10.5194/acp-22-9617-2022, 2022
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We review the capability of satellite observations of atmospheric methane to quantify methane emissions on all scales. We cover retrieval methods, precision requirements, inverse methods for inferring emissions, source detection thresholds, and observations of system completeness. We show that current instruments already enable quantification of regional and national emissions including contributions from large point sources. Coverage and resolution will increase significantly in coming years.
Daniel J. Varon, Daniel J. Jacob, Melissa Sulprizio, Lucas A. Estrada, William B. Downs, Lu Shen, Sarah E. Hancock, Hannah Nesser, Zhen Qu, Elise Penn, Zichong Chen, Xiao Lu, Alba Lorente, Ashutosh Tewari, and Cynthia A. Randles
Geosci. Model Dev., 15, 5787–5805, https://doi.org/10.5194/gmd-15-5787-2022, https://doi.org/10.5194/gmd-15-5787-2022, 2022
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Reducing atmospheric methane emissions is critical to slow near-term climate change. Globally surveying satellite instruments like the TROPOspheric Monitoring Instrument (TROPOMI) have unique capabilities for monitoring atmospheric methane around the world. Here we present a user-friendly cloud-computing tool that enables researchers and stakeholders to quantify methane emissions across user-selected regions of interest using TROPOMI satellite observations.
John R. Worden, Daniel H. Cusworth, Zhen Qu, Yi Yin, Yuzhong Zhang, A. Anthony Bloom, Shuang Ma, Brendan K. Byrne, Tia Scarpelli, Joannes D. Maasakkers, David Crisp, Riley Duren, and Daniel J. Jacob
Atmos. Chem. Phys., 22, 6811–6841, https://doi.org/10.5194/acp-22-6811-2022, https://doi.org/10.5194/acp-22-6811-2022, 2022
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This paper is intended to accomplish two goals: 1) describe a new algorithm by which remotely sensed measurements of methane or other tracers can be used to not just quantify methane fluxes, but also attribute these fluxes to specific sources and regions and characterize their uncertainties, and 2) use this new algorithm to provide methane emissions by sector and country in support of the global stock take.
Pinya Wang, Yang Yang, Huimin Li, Lei Chen, Ruijun Dang, Daokai Xue, Baojie Li, Jianping Tang, L. Ruby Leung, and Hong Liao
Atmos. Chem. Phys., 22, 4705–4719, https://doi.org/10.5194/acp-22-4705-2022, https://doi.org/10.5194/acp-22-4705-2022, 2022
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China is now suffering from both severe ozone (O3) pollution and heat events. We highlight that North China Plain is the hot spot of the co-occurrences of extremes in O3 and high temperatures in China. Such coupled extremes exhibit an increasing trend during 2014–2019 and will continue to increase until the middle of this century. And the coupled extremes impose more severe health impacts to human than O3 pollution occurring alone because of elevated O3 levels and temperatures.
Tia R. Scarpelli, Daniel J. Jacob, Shayna Grossman, Xiao Lu, Zhen Qu, Melissa P. Sulprizio, Yuzhong Zhang, Frances Reuland, Deborah Gordon, and John R. Worden
Atmos. Chem. Phys., 22, 3235–3249, https://doi.org/10.5194/acp-22-3235-2022, https://doi.org/10.5194/acp-22-3235-2022, 2022
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We present a spatially explicit version of the national inventories of oil, gas, and coal methane emissions as submitted by individual countries to the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. We then use atmospheric modeling to compare our inventory emissions to atmospheric methane observations with the goal of identifying potential under- and overestimates of oil–gas methane emissions in the national inventories.
Drew C. Pendergrass, Shixian Zhai, Jhoon Kim, Ja-Ho Koo, Seoyoung Lee, Minah Bae, Soontae Kim, Hong Liao, and Daniel J. Jacob
Atmos. Meas. Tech., 15, 1075–1091, https://doi.org/10.5194/amt-15-1075-2022, https://doi.org/10.5194/amt-15-1075-2022, 2022
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This paper uses a machine learning algorithm to infer high-resolution maps of particulate air quality in eastern China, Japan, and the Korean peninsula, using data from a geostationary satellite along with meteorology. We then perform an extensive evaluation of this inferred air quality and use it to diagnose trends in the region. We hope this paper and the associated data will be valuable to other scientists interested in epidemiology, air quality, remote sensing, and machine learning.
Lu Shen, Daniel J. Jacob, Mauricio Santillana, Kelvin Bates, Jiawei Zhuang, and Wei Chen
Geosci. Model Dev., 15, 1677–1687, https://doi.org/10.5194/gmd-15-1677-2022, https://doi.org/10.5194/gmd-15-1677-2022, 2022
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The high computational cost of chemical integration is a long-standing limitation in global atmospheric chemistry models. Here we present an adaptive and efficient algorithm that can reduce the computational time of atmospheric chemistry by 50 % and maintain the error below 2 % for important species, inspired by machine learning clustering techniques and traditional asymptotic analysis ideas.
Xiao Lu, Daniel J. Jacob, Haolin Wang, Joannes D. Maasakkers, Yuzhong Zhang, Tia R. Scarpelli, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Hannah Nesser, A. Anthony Bloom, Shuang Ma, John R. Worden, Shaojia Fan, Robert J. Parker, Hartmut Boesch, Ritesh Gautam, Deborah Gordon, Michael D. Moran, Frances Reuland, Claudia A. Octaviano Villasana, and Arlyn Andrews
Atmos. Chem. Phys., 22, 395–418, https://doi.org/10.5194/acp-22-395-2022, https://doi.org/10.5194/acp-22-395-2022, 2022
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We evaluate methane emissions and trends for 2010–2017 in the gridded national emission inventories for the United States, Canada, and Mexico by inversion of in situ and satellite methane observations. We find that anthropogenic methane emissions for all three countries are underestimated in the national inventories, largely driven by oil emissions. Anthropogenic methane emissions in the US peak in 2014, in contrast to the report of a steadily decreasing trend over 2010–2017 from the US EPA.
Kelvin H. Bates, Daniel J. Jacob, Ke Li, Peter D. Ivatt, Mat J. Evans, Yingying Yan, and Jintai Lin
Atmos. Chem. Phys., 21, 18351–18374, https://doi.org/10.5194/acp-21-18351-2021, https://doi.org/10.5194/acp-21-18351-2021, 2021
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Simple aromatic compounds (benzene, toluene, xylene) have complex gas-phase chemistry that is inconsistently represented in atmospheric models. We compile recent experimental and theoretical insights to develop a new mechanism for gas-phase aromatic oxidation that is sufficiently compact for use in multiscale models. We compare our new mechanism to chamber experiments and other mechanisms, and implement it in a global model to quantify the impacts of aromatic oxidation on tropospheric chemistry.
Sabour Baray, Daniel J. Jacob, Joannes D. Maasakkers, Jian-Xiong Sheng, Melissa P. Sulprizio, Dylan B. A. Jones, A. Anthony Bloom, and Robert McLaren
Atmos. Chem. Phys., 21, 18101–18121, https://doi.org/10.5194/acp-21-18101-2021, https://doi.org/10.5194/acp-21-18101-2021, 2021
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We use 2010–2015 surface and satellite observations to disentangle methane from anthropogenic and natural sources in Canada. Using a chemical transport model (GEOS-Chem), the mismatch between modelled and observed methane concentrations can be used to infer emissions according to Bayesian statistics. Compared to prior knowledge, we show higher anthropogenic emissions attributed to energy and/or agriculture in Western Canada and lower natural emissions from Boreal wetlands.
Shixian Zhai, Daniel J. Jacob, Jared F. Brewer, Ke Li, Jonathan M. Moch, Jhoon Kim, Seoyoung Lee, Hyunkwang Lim, Hyun Chul Lee, Su Keun Kuk, Rokjin J. Park, Jaein I. Jeong, Xuan Wang, Pengfei Liu, Gan Luo, Fangqun Yu, Jun Meng, Randall V. Martin, Katherine R. Travis, Johnathan W. Hair, Bruce E. Anderson, Jack E. Dibb, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jung-Hun Woo, Younha Kim, Qiang Zhang, and Hong Liao
Atmos. Chem. Phys., 21, 16775–16791, https://doi.org/10.5194/acp-21-16775-2021, https://doi.org/10.5194/acp-21-16775-2021, 2021
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Geostationary satellite aerosol optical depth (AOD) has tremendous potential for monitoring surface fine particulate matter (PM2.5). Our study explored the physical relationship between AOD and PM2.5 by integrating data from surface networks, aircraft, and satellites with the GEOS-Chem chemical transport model. We quantitatively showed that accurate simulation of aerosol size distributions, boundary layer depths, relative humidity, coarse particles, and diurnal variations in PM2.5 are essential.
Liam Bindle, Randall V. Martin, Matthew J. Cooper, Elizabeth W. Lundgren, Sebastian D. Eastham, Benjamin M. Auer, Thomas L. Clune, Hongjian Weng, Jintai Lin, Lee T. Murray, Jun Meng, Christoph A. Keller, William M. Putman, Steven Pawson, and Daniel J. Jacob
Geosci. Model Dev., 14, 5977–5997, https://doi.org/10.5194/gmd-14-5977-2021, https://doi.org/10.5194/gmd-14-5977-2021, 2021
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Atmospheric chemistry models like GEOS-Chem are versatile tools widely used in air pollution and climate studies. The simulations used in such studies can be very computationally demanding, and thus it is useful if the model can simulate a specific geographic region at a higher resolution than the rest of the globe. Here, we implement, test, and demonstrate a new variable-resolution capability in GEOS-Chem that is suitable for simulations conducted on supercomputers.
Zhen Qu, Daniel J. Jacob, Lu Shen, Xiao Lu, Yuzhong Zhang, Tia R. Scarpelli, Hannah Nesser, Melissa P. Sulprizio, Joannes D. Maasakkers, A. Anthony Bloom, John R. Worden, Robert J. Parker, and Alba L. Delgado
Atmos. Chem. Phys., 21, 14159–14175, https://doi.org/10.5194/acp-21-14159-2021, https://doi.org/10.5194/acp-21-14159-2021, 2021
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The recent launch of TROPOMI offers an unprecedented opportunity to quantify the methane budget from a top-down perspective. We use TROPOMI and the more mature GOSAT methane observations to estimate methane emissions and get consistent global budgets. However, TROPOMI shows biases over regions where surface albedo is small and provides less information for the coarse-resolution inversion due to the larger error correlations and spatial variations in the number of observations.
Lee T. Murray, Eric M. Leibensperger, Clara Orbe, Loretta J. Mickley, and Melissa Sulprizio
Geosci. Model Dev., 14, 5789–5823, https://doi.org/10.5194/gmd-14-5789-2021, https://doi.org/10.5194/gmd-14-5789-2021, 2021
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Chemical-transport models are tools used to study air pollution and inform public policy. However, they are limited by the availability of archived meteorology. Here, we describe how the GEOS-Chem chemical-transport model may now be driven by meteorology archived from a state-of-the-art general circulation model for past and future climates, allowing it to be used to explore the impact of climate change on air pollution and atmospheric composition.
Xuan Wang, Daniel J. Jacob, William Downs, Shuting Zhai, Lei Zhu, Viral Shah, Christopher D. Holmes, Tomás Sherwen, Becky Alexander, Mathew J. Evans, Sebastian D. Eastham, J. Andrew Neuman, Patrick R. Veres, Theodore K. Koenig, Rainer Volkamer, L. Gregory Huey, Thomas J. Bannan, Carl J. Percival, Ben H. Lee, and Joel A. Thornton
Atmos. Chem. Phys., 21, 13973–13996, https://doi.org/10.5194/acp-21-13973-2021, https://doi.org/10.5194/acp-21-13973-2021, 2021
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Halogen radicals have a broad range of implications for tropospheric chemistry, air quality, and climate. We present a new mechanistic description and comprehensive simulation of tropospheric halogens in a global 3-D model and compare the model results with surface and aircraft measurements. We find that halogen chemistry decreases the global tropospheric burden of ozone by 11 %, NOx by 6 %, and OH by 4 %.
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.
Yi Yin, Frederic Chevallier, Philippe Ciais, Philippe Bousquet, Marielle Saunois, Bo Zheng, John Worden, A. Anthony Bloom, Robert J. Parker, Daniel J. Jacob, Edward J. Dlugokencky, and Christian Frankenberg
Atmos. Chem. Phys., 21, 12631–12647, https://doi.org/10.5194/acp-21-12631-2021, https://doi.org/10.5194/acp-21-12631-2021, 2021
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The growth of methane, the second-most important anthropogenic greenhouse gas after carbon dioxide, has been accelerating in recent years. Using an ensemble of multi-tracer atmospheric inversions constrained by surface or satellite observations, we show that global methane emissions increased by nearly 1 % per year from 2010–2017, with leading contributions from the tropics and East Asia.
Hannah Nesser, Daniel J. Jacob, Joannes D. Maasakkers, Tia R. Scarpelli, Melissa P. Sulprizio, Yuzhong Zhang, and Chris H. Rycroft
Atmos. Meas. Tech., 14, 5521–5534, https://doi.org/10.5194/amt-14-5521-2021, https://doi.org/10.5194/amt-14-5521-2021, 2021
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Analytical inversions of satellite observations of atmospheric composition can improve emissions estimates and quantify errors but are computationally expensive at high resolutions. We propose two methods to decrease this cost. The methods reproduce a high-resolution inversion at a quarter of the cost. The reduced-dimension method creates a multiscale grid. The reduced-rank method solves the inversion where information content is highest.
Xu Feng, Haipeng Lin, Tzung-May Fu, Melissa P. Sulprizio, Jiawei Zhuang, Daniel J. Jacob, Heng Tian, Yaping Ma, Lijuan Zhang, Xiaolin Wang, Qi Chen, and Zhiwei Han
Geosci. Model Dev., 14, 3741–3768, https://doi.org/10.5194/gmd-14-3741-2021, https://doi.org/10.5194/gmd-14-3741-2021, 2021
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WRF-GC is an online coupling of the WRF meteorological model and GEOS-Chem chemical transport model for regional atmospheric chemistry and air quality modeling. In WRF-GC v2.0, we implemented the aerosol–radiation interactions and aerosol–cloud interactions, as well as the capability to nest multiple domains for high-resolution simulations based on the modular framework of WRF-GC v1.0. This allows the GEOS-Chem users to investigate the meteorology–atmospheric chemistry interactions.
Jing Wei, Zhanqing Li, Rachel T. Pinker, Jun Wang, Lin Sun, Wenhao Xue, Runze Li, and Maureen Cribb
Atmos. Chem. Phys., 21, 7863–7880, https://doi.org/10.5194/acp-21-7863-2021, https://doi.org/10.5194/acp-21-7863-2021, 2021
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This study developed a space-time Light Gradient Boosting Machine (STLG) model to derive the high-temporal-resolution (1 h) and high-quality PM2.5 dataset in China (i.e., ChinaHighPM2.5) at a 5 km spatial resolution from the Himawari-8 Advanced Himawari Imager aerosol products. Our model outperforms most previous related studies with a much lower computation burden in terms of speed and memory, making it most suitable for real-time air pollution monitoring in China.
David R. Lyon, Benjamin Hmiel, Ritesh Gautam, Mark Omara, Katherine A. Roberts, Zachary R. Barkley, Kenneth J. Davis, Natasha L. Miles, Vanessa C. Monteiro, Scott J. Richardson, Stephen Conley, Mackenzie L. Smith, Daniel J. Jacob, Lu Shen, Daniel J. Varon, Aijun Deng, Xander Rudelis, Nikhil Sharma, Kyle T. Story, Adam R. Brandt, Mary Kang, Eric A. Kort, Anthony J. Marchese, and Steven P. Hamburg
Atmos. Chem. Phys., 21, 6605–6626, https://doi.org/10.5194/acp-21-6605-2021, https://doi.org/10.5194/acp-21-6605-2021, 2021
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The Permian Basin (USA) is the world’s largest oil field. We use tower- and aircraft-based approaches to measure how methane emissions in the Permian Basin changed throughout 2020. In early 2020, 3.3 % of the region’s gas was emitted; then in spring 2020, the loss rate temporarily dropped to 1.9 % as oil price crashed. We find this short-term reduction to be a result of reduced well development, less gas flaring, and fewer abnormal events despite minimal reductions in oil and gas production.
Daniel J. Varon, Dylan Jervis, Jason McKeever, Ian Spence, David Gains, and Daniel J. Jacob
Atmos. Meas. Tech., 14, 2771–2785, https://doi.org/10.5194/amt-14-2771-2021, https://doi.org/10.5194/amt-14-2771-2021, 2021
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Satellites can detect methane emissions by measuring sunlight reflected from the Earth's surface and atmosphere. Here we show that the European Space Agency's Sentinel-2 twin satellites can be used to monitor anomalously large methane point sources around the world, with global coverage every 2–5 days and 20 m spatial resolution. We demonstrate this previously unreported capability through high-frequency Sentinel-2 monitoring of two strong methane point sources in Algeria and Turkmenistan.
Xiao Lu, Daniel J. Jacob, Yuzhong Zhang, Joannes D. Maasakkers, Melissa P. Sulprizio, Lu Shen, Zhen Qu, Tia R. Scarpelli, Hannah Nesser, Robert M. Yantosca, Jianxiong Sheng, Arlyn Andrews, Robert J. Parker, Hartmut Boesch, A. Anthony Bloom, and Shuang Ma
Atmos. Chem. Phys., 21, 4637–4657, https://doi.org/10.5194/acp-21-4637-2021, https://doi.org/10.5194/acp-21-4637-2021, 2021
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We use an analytical solution to the Bayesian inverse problem to quantitatively compare and combine the information from satellite and in situ observations, and to estimate global methane budget and their trends over the 2010–2017 period. We find that satellite and in situ observations are to a large extent complementary in the inversion for estimating global methane budget, and reveal consistent corrections of regional anthropogenic and wetland methane emissions relative to the prior inventory.
Joannes D. Maasakkers, Daniel J. Jacob, Melissa P. Sulprizio, Tia R. Scarpelli, Hannah Nesser, Jianxiong Sheng, Yuzhong Zhang, Xiao Lu, A. Anthony Bloom, Kevin W. Bowman, John R. Worden, and Robert J. Parker
Atmos. Chem. Phys., 21, 4339–4356, https://doi.org/10.5194/acp-21-4339-2021, https://doi.org/10.5194/acp-21-4339-2021, 2021
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We use 2010–2015 GOSAT satellite observations of atmospheric methane over North America in a high-resolution inversion to estimate methane emissions. We find general consistency with the gridded EPA inventory but higher oil and gas production emissions, with oil production emissions twice as large as in the latest EPA Greenhouse Gas Inventory. We find lower wetland emissions than predicted by WetCHARTs and a small increasing trend in the eastern US, apparently related to unconventional oil/gas.
Yuzhong Zhang, Daniel J. Jacob, Xiao Lu, Joannes D. Maasakkers, Tia R. Scarpelli, Jian-Xiong Sheng, Lu Shen, Zhen Qu, Melissa P. Sulprizio, Jinfeng Chang, A. Anthony Bloom, Shuang Ma, John Worden, Robert J. Parker, and Hartmut Boesch
Atmos. Chem. Phys., 21, 3643–3666, https://doi.org/10.5194/acp-21-3643-2021, https://doi.org/10.5194/acp-21-3643-2021, 2021
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We use 2010–2018 satellite observations of atmospheric methane to interpret the factors controlling atmospheric methane and its accelerating increase during the period. The 2010–2018 increase in global methane emissions is driven by tropical and boreal wetlands and tropical livestock (South Asia, Africa, Brazil), with an insignificant positive trend in emissions from the fossil fuel sector. The peak methane growth rates in 2014–2015 are also contributed by low OH and high fire emissions.
Inés Sanz-Morère, Sebastian D. Eastham, Florian Allroggen, Raymond L. Speth, and Steven R. H. Barrett
Atmos. Chem. Phys., 21, 1649–1681, https://doi.org/10.5194/acp-21-1649-2021, https://doi.org/10.5194/acp-21-1649-2021, 2021
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Contrails cause ~50 % of aviation climate impacts, but this is highly uncertain. This is partly due to the effect of overlap between contrails and other cloud layers. We developed a model to quantify this effect, finding that overlap with natural clouds increased contrails' radiative forcing in 2015. This suggests that cloud avoidance may help in reducing aviation's climate impacts. We also find that contrail–contrail overlap reduces impacts by ~3 %, increasing non-linearly with optical depth.
Susan S. Kulawik, John R. Worden, Vivienne H. Payne, Dejian Fu, Steven C. Wofsy, Kathryn McKain, Colm Sweeney, Bruce C. Daube Jr., Alan Lipton, Igor Polonsky, Yuguang He, Karen E. Cady-Pereira, Edward J. Dlugokencky, Daniel J. Jacob, and Yi Yin
Atmos. Meas. Tech., 14, 335–354, https://doi.org/10.5194/amt-14-335-2021, https://doi.org/10.5194/amt-14-335-2021, 2021
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This paper shows comparisons of a new single-footprint methane product from the AIRS satellite to aircraft-based observations. We show that this AIRS methane product provides useful information to study seasonal and global methane trends of this important greenhouse gas.
Yang Li, Loretta J. Mickley, and Jed O. Kaplan
Atmos. Chem. Phys., 21, 57–68, https://doi.org/10.5194/acp-21-57-2021, https://doi.org/10.5194/acp-21-57-2021, 2021
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Climate models predict a shift toward warmer, drier environments in southwestern North America. Under future climate, the two main drivers of dust trends play opposing roles: (1) CO2 fertilization enhances vegetation and, in turn, decreases dust, and (2) increasing land use enhances dust emissions from northern Mexico. In the worst-case scenario, elevated dust concentrations spread widely over the domain by 2100 in spring, suggesting a large climate penalty on air quality and human health.
Junfeng Wang, Jianhuai Ye, Dantong Liu, Yangzhou Wu, Jian Zhao, Weiqi Xu, Conghui Xie, Fuzhen Shen, Jie Zhang, Paul E. Ohno, Yiming Qin, Xiuyong Zhao, Scot T. Martin, Alex K. Y. Lee, Pingqing Fu, Daniel J. Jacob, Qi Zhang, Yele Sun, Mindong Chen, and Xinlei Ge
Atmos. Chem. Phys., 20, 14091–14102, https://doi.org/10.5194/acp-20-14091-2020, https://doi.org/10.5194/acp-20-14091-2020, 2020
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We compared the organics in total submicron matter and those coated on BC cores during summertime in Beijing and found large differences between them. Traffic-related OA was associated significantly with BC, while cooking-related OA did not coat BC. In addition, a factor likely originated from primary biomass burning OA was only identified in BC-containing particles. Such a unique BBOA requires further field and laboratory studies to verify its presence and elucidate its properties and impacts.
Viral Shah, Daniel J. Jacob, Jonathan M. Moch, Xuan Wang, and Shixian Zhai
Atmos. Chem. Phys., 20, 12223–12245, https://doi.org/10.5194/acp-20-12223-2020, https://doi.org/10.5194/acp-20-12223-2020, 2020
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Cloud water pH affects atmospheric chemistry, and acid rain damages ecosystems. We use model simulations along with observations to present a global view of cloud water and precipitation pH. Sulfuric acid, nitric acid, and ammonia control the pH in the northern midlatitudes, but carboxylic acids and dust cations are important in the tropics and subtropics. The acid inputs to many nitrogen-saturated ecosystems are high enough to cause acidification, with ammonium as the main acidifying species.
Ke Li, Daniel J. Jacob, Lu Shen, Xiao Lu, Isabelle De Smedt, and Hong Liao
Atmos. Chem. Phys., 20, 11423–11433, https://doi.org/10.5194/acp-20-11423-2020, https://doi.org/10.5194/acp-20-11423-2020, 2020
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Surface summer ozone increased in China from 2013 to 2019 despite new governmental efforts targeting ozone pollution. We find that the ozone increase is mostly due to anthropogenic drivers, although meteorology also plays a role. Further analysis for the North China Plain shows that PM2.5 continued to decrease through 2019, while emissions of volatile organic compounds (VOCs) stayed flat. This could explain the anthropogenic increase in ozone, as PM2.5 scavenges the radical precursors of ozone.
Xiao Lu, Lin Zhang, Tongwen Wu, Michael S. Long, Jun Wang, Daniel J. Jacob, Fang Zhang, Jie Zhang, Sebastian D. Eastham, Lu Hu, Lei Zhu, Xiong Liu, and Min Wei
Geosci. Model Dev., 13, 3817–3838, https://doi.org/10.5194/gmd-13-3817-2020, https://doi.org/10.5194/gmd-13-3817-2020, 2020
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This study presents the development and evaluation of a new climate chemistry model, BCC-GEOS-Chem v1.0, which couples the GEOS-Chem chemical transport model as an atmospheric chemistry component in the Beijing Climate Center atmospheric general circulation model. A 3-year (2012–2014) simulation of BCC-GEOS-Chem v1.0 shows that the model captures well the spatiotemporal distributions of tropospheric ozone, other gaseous pollutants, and aerosols.
Tong Sha, Xiaoyan Ma, Jun Wang, Rong Tian, Jianqi Zhao, Fang Cao, and Yan-Lin Zhang
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-760, https://doi.org/10.5194/acp-2020-760, 2020
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Most numerical models perform poorly on simulating the inorganic chemical components in PM2.5 (sulfate, nitrate, and ammonium (SNA)), generally underestimate sulfate but overestimate nitrate concentrations in haze events. Our work aims at investigating the role of cloud water in simulating SNA. We find that the uncertainties of cloud water can lead to model bias in simulating SNA, and can be reduced by constraining the modeled cloud water with MODIS satellite observations.
Cited articles
Airbus: Global Market Forecast 2022–2041, https://www.airbus.com/en/products-services/commercial-aircraft/market/global-market-forecast (last access: 26 May 2023), 2022.
Andersen, S. T., Carpenter, L. J., Reed, C., Lee, J. D., Chance, R.,
Sherwen, T., Vaughan, A. R., Stewart, J., Edwards, P. M., Bloss, W. J.,
Sommariva, R., Crilley, L. R., Nott, G. J., Neves, L., Read, K., Heard, D.
E., Seakins, P. W., Whalley, L. K., Boustead, G. A., Fleming, L. T., Stone,
D., and Fomba, K. W.: Extensive field evidence for the release of HONO from
the photolysis of nitrate aerosols, Sci. Adv., 9, eadd6266,
https://doi.org/10.1126/sciadv.add6266, 2023.
Bates, K. H. and Jacob, D. J.: A new model mechanism for atmospheric oxidation of isoprene: global effects on oxidants, nitrogen oxides, organic products, and secondary organic aerosol, Atmos. Chem. Phys., 19, 9613–9640, https://doi.org/10.5194/acp-19-9613-2019, 2019.
Belmonte Rivas, M., Veefkind, P., Eskes, H., and Levelt, P.: OMI tropospheric NO2 profiles from cloud slicing: constraints on surface emissions, convective transport and lightning NOx, Atmos. Chem. Phys., 15, 13519–13553, https://doi.org/10.5194/acp-15-13519-2015, 2015.
Boeing: Boeing Commercial Market Outlook 2022–2041, https://www.boeing.com/commercial/market/commercial-market-outlook/ (last access: 26 May 2023), 2022.
Boersma, K. F., Jacob, D. J., Bucsela, E. J., Perring, A. E., Dirksen, R.,
van der A, R. J., Yantosca, R. M., Park, R. J., Wenig, M. O., Bertram, T.
H., and Cohen, R. C.: Validation of OMI tropospheric NO2 observations during
INTEX-B and application to constrain NOx emissions over the eastern United
States and Mexico, Atmos. Environ., 42, 4480–4497,
https://doi.org/10.1016/j.atmosenv.2008.02.004, 2008.
Boersma, K. F., Vinken, G. C. M., and Eskes, H. J.: Representativeness errors in comparing chemistry transport and chemistry climate models with satellite UV–Vis tropospheric column retrievals, Geosci. Model Dev., 9, 875–898, https://doi.org/10.5194/gmd-9-875-2016, 2016.
Boersma, K. F., Eskes, H. J., Richter, A., De Smedt, I., Lorente, A., Beirle, S., van Geffen, J. H. G. M., Zara, M., Peters, E., Van Roozendael, M., Wagner, T., Maasakkers, J. D., van der A, R. J., Nightingale, J., De Rudder, A., Irie, H., Pinardi, G., Lambert, J.-C., and Compernolle, S. C.: Improving algorithms and uncertainty estimates for satellite NO2 retrievals: results from the quality assurance for the essential climate variables (QA4ECV) project, Atmos. Meas. Tech., 11, 6651–6678, https://doi.org/10.5194/amt-11-6651-2018, 2018.
Bows-Larkin, A., Mander, S. L., Traut, M. B., Anderson, K. L., and Wood, F.
R.: Aviation and Climate Change–The Continuing Challenge, in: Encyclopedia
of Aerospace Engineering, 1–11, 2016.
Brey, S. J. and Fischer, E. V.: Smoke in the City: How Often and Where Does
Smoke Impact Summertime Ozone in the United States?, Environ. Sci. Technol.,
50, 1288–1294, https://doi.org/10.1021/acs.est.5b05218, 2016.
Carter, T. S., Heald, C. L., Jimenez, J. L., Campuzano-Jost, P., Kondo, Y., Moteki, N., Schwarz, J. P., Wiedinmyer, C., Darmenov, A. S., da Silva, A. M., and Kaiser, J. W.: How emissions uncertainty influences the distribution and radiative impacts of smoke from fires in North America, Atmos. Chem. Phys., 20, 2073–2097, https://doi.org/10.5194/acp-20-2073-2020, 2020.
Castellanos, P., Boersma, K. F., Torres, O., and de Haan, J. F.: OMI tropospheric NO2 air mass factors over South America: effects of biomass burning aerosols, Atmos. Meas. Tech., 8, 3831–3849, https://doi.org/10.5194/amt-8-3831-2015, 2015.
Cattau, M. E., Wessman, C., Mahood, A., and Balch, J. K.: Anthropogenic and
lightning-started fires are becoming larger and more frequent over a longer
season length in the U.S.A, Global Ecol. Biogeogr., 29, 668–681,
https://doi.org/10.1111/geb.13058, 2020.
Choi, S., Joiner, J., Choi, Y., Duncan, B. N., Vasilkov, A., Krotkov, N., and Bucsela, E.: First estimates of global free-tropospheric NO2 abundances derived using a cloud-slicing technique applied to satellite observations from the Aura Ozone Monitoring Instrument (OMI), Atmos. Chem. Phys., 14, 10565–10588, https://doi.org/10.5194/acp-14-10565-2014, 2014.
Cooper, M. J., Martin, R. V., Henze, D. K., and Jones, D. B. A.: Effects of a priori profile shape assumptions on comparisons between satellite NO2 https://doi.org/10.5194/acp-20-7231-2020, 2020a.
Cooper, M. J., Martin, R. V., McLinden, C. A., and Brook, J. R.: Inferring
ground-level nitrogen dioxide concentrations at fine spatial resolution
applied to the TROPOMI satellite instrument, Environ. Res. Lett., 15,
104013, https://doi.org/10.1088/1748-9326/aba3a5, 2020b.
Dedoussi, I. C.: Implications of future atmospheric composition in
decision-making for sustainable aviation, Environ. Res. Lett., 16, 031002,
https://doi.org/10.1088/1748-9326/abe74d, 2021.
Dobber, M., Voors, R., Dirksen, R., Kleipool, Q., and Levelt, P.: The
High-Resolution Solar Reference Spectrum between 250 and 550 nm and its
Application to Measurements with the Ozone Monitoring Instrument, Solar
Phys., 249, 281–291, https://doi.org/10.1007/s11207-008-9187-7, 2008.
Dulitz, K., Amedro, D., Dillon, T. J., Pozzer, A., and Crowley, J. N.: Temperature-(208–318 K) and pressure-(18–696 Torr) dependent rate coefficients for the reaction between OH and HNO3, Atmos. Chem. Phys., 18, 2381–2394, https://doi.org/10.5194/acp-18-2381-2018, 2018.
Duncan, B. N., Yoshida, Y., de Foy, B., Lamsal, L. N., Streets, D. G., Lu,
Z., Pickering, K. E., and Krotkov, N. A.: The observed response of Ozone
Monitoring Instrument (OMI) NO2 columns to NOx emission controls on power
plants in the United States: 2005–2011, Atmos. Environ., 81, 102–111,
https://doi.org/10.1016/j.atmosenv.2013.08.068, 2013.
Duncan, B. N., Lamsal, L. N., Thompson, A. M., Yoshida, Y., Lu, Z., Streets,
D. G., Hurwitz, M. M., and Pickering, K. E.: A space-based, high-resolution
view of notable changes in urban NOx pollution around the world
(2005–2014), J. Geophys. Res.-Atmos., 121, 976–996,
https://doi.org/10.1002/2015JD024121, 2016.
EPA: Annual Average Emissions, Air Pollutant Emission Trends Data:
https://www.epa.gov/air-emissions-inventories/air-pollutant-emissions-trends-data (last access: 26 May 2023),
2021.
Fischer, E. V., Zhu, L., Payne, V. H., Worden, J. R., Jiang, Z., Kulawik, S. S., Brey, S., Hecobian, A., Gombos, D., Cady-Pereira, K., and Flocke, F.: Using TES retrievals to investigate PAN in North American biomass burning plumes, Atmos. Chem. Phys., 18, 5639–5653, https://doi.org/10.5194/acp-18-5639-2018, 2018.
Gelaro, R., McCarty, W., Suarez, 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., da
Silva, A. M., 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.
Gen, M., Liang, Z., Zhang, R., Go Mabato, B. R., and Chan, C. K.:
Particulate nitrate photolysis in the atmosphere, Environ. Sci.-Atmos., 2, 111–127, https://doi.org/10.1039/D1EA00087J, 2022.
Griffin, D., McLinden, C. A., Dammers, E., Adams, C., Stockwell, C. E., Warneke, C., Bourgeois, I., Peischl, J., Ryerson, T. B., Zarzana, K. J., Rowe, J. P., Volkamer, R., Knote, C., Kille, N., Koenig, T. K., Lee, C. F., Rollins, D., Rickly, P. S., Chen, J., Fehr, L., Bourassa, A., Degenstein, D., Hayden, K., Mihele, C., Wren, S. N., Liggio, J., Akingunola, A., and Makar, P.: Biomass burning nitrogen dioxide emissions derived from space with TROPOMI: methodology and validation, Atmos. Meas. Tech., 14, 7929–7957, https://doi.org/10.5194/amt-14-7929-2021, 2021.
He, T.-L., Jones, D. B. A., Miyazaki, K., Huang, B., Liu, Y., Jiang, Z.,
White, E. C., Worden, H. M., and Worden, J. R.: Deep Learning to Evaluate US
NOx Emissions Using Surface Ozone Predictions, J. Geophys. Res.-Atmos., 127, e2021JD035597,
https://doi.org/10.1029/2021JD035597, 2022.
HMS Science Team: Hazard Mapping System Fire and Smoke Product, NOAA [data set], https://www.ospo.noaa.gov/Products/land/hms.html (last access: 26 May 2023), 2003.
Holmes, C. D., Bertram, T. H., Confer, K. L., Graham, K. A., Ronan, A. C.,
Wirks, C. K., and Shah, V.: The Role of Clouds in the Tropospheric NOx
Cycle: A New Modeling Approach for Cloud Chemistry and Its Global
Implications, Geophys. Res. Lett., 46, 4980–4990,
https://doi.org/10.1029/2019GL081990, 2019.
Hudman, R. C., Moore, N. E., Mebust, A. K., Martin, R. V., Russell, A. R., Valin, L. C., and Cohen, R. C.: Steps towards a mechanistic model of global soil nitric oxide emissions: implementation and space based-constraints, Atmos. Chem. Phys., 12, 7779–7795, https://doi.org/10.5194/acp-12-7779-2012, 2012.
Jaeglé, L., Shah, V., Thornton, J. A., Lopez-Hilfiker, F. D., Lee, B.
H., McDuffie, E. E., Fibiger, D., Brown, S. S., Veres, P., Sparks, T. L.,
Ebben, C. J., Wooldridge, P. J., Kenagy, H. S., Cohen, R. C., Weinheimer, A.
J., Campos, T. L., Montzka, D. D., Digangi, J. P., Wolfe, G. M., Hanisco,
T., Schroder, J. C., Campuzano-Jost, P., Day, D. A., Jimenez, J. L.,
Sullivan, A. P., Guo, H., and Weber, R. J.: Nitrogen Oxides Emissions,
Chemistry, Deposition, and Export Over the Northeast United States During
the WINTER Aircraft Campaign, J. Geophys. Res.-Atmos.,
123, 12368–12393, https://doi.org/10.1029/2018JD029133, 2018.
Jaffe, D. A., O'Neill, S. M., Larkin, N. K., Holder, A. L., Peterson, D. L.,
Halofsky, J. E., and Rappold, A. G.: Wildfire and prescribed burning impacts
on air quality in the United States, J. Air Waste Manage. Assoc., 70,
583–615, https://doi.org/10.1080/10962247.2020.1749731, 2020.
Jiang, Z., McDonald Brian, C., Worden, H., Worden John, R., Miyazaki, K.,
Qu, Z., Henze Daven, K., Jones Dylan, B. A., Arellano Avelino, F., Fischer
Emily, 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.
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., Denier van der Gon, H. A. C., 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.
Jin, X., Zhu, Q., and Cohen, R. C.: Direct estimates of biomass burning NOx emissions and lifetimes using daily observations from TROPOMI, Atmos. Chem. Phys., 21, 15569–15587, https://doi.org/10.5194/acp-21-15569-2021, 2021.
Juncosa Calahorrano, J. F., Payne, V. H., Kulawik, S., Ford, B., Flocke, F.,
Campos, T., and Fischer, E. V.: Evolution of Acyl Peroxynitrates (PANs) in
Wildfire Smoke Plumes Detected by the Cross-Track Infrared Sounder (CrIS)
Over the Western U.S. During Summer 2018, Geophys. Res. Lett., 48,
e2021GL093405, https://doi.org/10.1029/2021GL093405, 2021.
Kasibhatla, P., Sherwen, T., Evans, M. J., Carpenter, L. J., Reed, C., Alexander, B., Chen, Q., Sulprizio, M. P., Lee, J. D., Read, K. A., Bloss, W., Crilley, L. R., Keene, W. C., Pszenny, A. A. P., and Hodzic, A.: Global impact of nitrate photolysis in sea-salt aerosol on NOx, OH, and O3 in the marine boundary layer, Atmos. Chem. Phys., 18, 11185–11203, https://doi.org/10.5194/acp-18-11185-2018, 2018.
Kim, J., Jeong, U., Ahn, M.-H., Kim, J. H., Park, R. J., Lee, H., Song, C.
H., Choi, Y.-S., Lee, K.-H., Yoo, J.-M., Jeong, M.-J., Park, S. K., Lee,
K.-M., Song, C.-K., Kim, S.-W., Kim, Y. J., Kim, S.-W., Kim, M., Go, S.,
Liu, X., Chance, K., Chan Miller, C., Al-Saadi, J., Veihelmann, B., Bhartia,
P. K., Torres, O., Abad, G. G., Haffner, D. P., Ko, D. H., Lee, S. H., Woo,
J.-H., Chong, H., Park, S. S., Nicks, D., Choi, W. J., Moon, K.-J., Cho, A.,
Yoon, J., Kim, S.-k., Hong, H., Lee, K., Lee, H., Lee, S., Choi, M.,
Veefkind, P., Levelt, P. F., Edwards, D. P., Kang, M., Eo, M., Bak, J.,
Baek, K., Kwon, H.-A., Yang, J., Park, J., Han, K. M., Kim, B.-R., Shin,
H.-W., Choi, H., Lee, E., Chong, J., Cha, Y., Koo, J.-H., Irie, H.,
Hayashida, S., Kasai, Y., Kanaya, Y., Liu, C., Lin, J., Crawford, J. H.,
Carmichael, G. R., Newchurch, M. J., Lefer, B. L., Herman, J. R., Swap, R.
J., Lau, A. K. H., Kurosu, T. P., Jaross, G., Ahlers, B., Dobber, M.,
McElroy, C. T., and Choi, Y.: New Era of Air Quality Monitoring from Space:
Geostationary Environment Monitoring Spectrometer (GEMS), B. Am. Meteorol. Soc., 101, 1–22, https://doi.org/10.1175/BAMS-D-18-0013.1, 2020.
Krotkov, N. A., McLinden, C. A., Li, C., Lamsal, L. N., Celarier, E. A., Marchenko, S. V., Swartz, W. H., Bucsela, E. J., Joiner, J., Duncan, B. N., Boersma, K. F., Veefkind, J. P., Levelt, P. F., Fioletov, V. E., Dickerson, R. R., He, H., Lu, Z., and Streets, D. G.: Aura OMI observations of regional SO2 and NO2 pollution changes from 2005 to 2015, Atmos. Chem. Phys., 16, 4605–4629, https://doi.org/10.5194/acp-16-4605-2016, 2016.
Krotkov, N. A., Lamsal, L. N., Marchenko, S. V., Bucsela, E. J., Swartz, W. H., Joiner J., and the OMI core team: OMI/Aura Nitrogen Dioxide (NO2) Total and Tropospheric Column 1-orbit L2 Swath 13×24 km V003, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://disc.gsfc.nasa.gov/datasets/OMNO2_003/summary (last access: 26 May 2023), 2019.
Lamsal, L. N., Krotkov, N. A., Vasilkov, A., Marchenko, S., Qin, W., Yang, E.-S., Fasnacht, Z., Joiner, J., Choi, S., Haffner, D., Swartz, W. H., Fisher, B., and Bucsela, E.: Ozone Monitoring Instrument (OMI) Aura nitrogen dioxide standard product version 4.0 with improved surface and cloud treatments, Atmos. Meas. Tech., 14, 455–479, https://doi.org/10.5194/amt-14-455-2021, 2021.
Laughner, J. L. and Cohen, R. C.: Direct observation of changing
NOx lifetime in North American cities,
Science, 366, 723–727, https://doi.org/10.1126/science.aax6832, 2019.
Laughner, J. L., Zhu, Q., and Cohen, R. C.: Evaluation of version 3.0B of the BEHR OMI NO2 product, Atmos. Meas. Tech., 12, 129–146, https://doi.org/10.5194/amt-12-129-2019, 2019.
Lee, D. S., Fahey, D. W., Skowron, A., Allen, M. R., Burkhardt, U., Chen,
Q., Doherty, S. J., Freeman, S., Forster, P. M., Fuglestvedt, J., Gettelman,
A., De León, R. R., Lim, L. L., Lund, M. T., Millar, R. J., Owen, B.,
Penner, J. E., Pitari, G., Prather, M. J., Sausen, R., and Wilcox, L. J.:
The contribution of global aviation to anthropogenic climate forcing for
2000 to 2018, Atmos. Environ., 244, 117834,
https://doi.org/10.1016/j.atmosenv.2020.117834, 2021.
Li, C., Xu, X., Liu, X., Wang, J., Sun, K., van Geffen, J., Zhu, Q., Ma, J.,
Jin, J., Qin, K., He, Q., Xie, P., Ren, B., and Cohen, R. C.: Direct
Retrieval of NOx
Vertical Columns from UV-Vis (390–495 nm) Spectral Radiances Using a Neural
Network, J. Remote Sens., 2022, 9817134, https://doi.org/10.34133/2022/9817134,
2022.
Liu, H. Y., Jacob, D. J., Bey, I., and Yantosca, R. M.: Constraints from
Pb-210 and Be-7 on wet deposition and transport in a global
three-dimensional chemical tracer model driven by assimilated meteorological
fields, J. Geophys. Res.-Atmos., 106, 12109–12128, https://doi.org/10.1029/2000jd900839,
2001.
Liu, M., Lin, J., Kong, H., Boersma, K. F., Eskes, H., Kanaya, Y., He, Q., Tian, X., Qin, K., Xie, P., Spurr, R., Ni, R., Yan, Y., Weng, H., and Wang, J.: A new TROPOMI product for tropospheric NO2 columns over East Asia with explicit aerosol corrections, Atmos. Meas. Tech., 13, 4247–4259, https://doi.org/10.5194/amt-13-4247-2020, 2020.
Lorente, A., Folkert Boersma, K., Yu, H., Dörner, S., Hilboll, A., Richter, A., Liu, M., Lamsal, L. N., Barkley, M., De Smedt, I., Van Roozendael, M., Wang, Y., Wagner, T., Beirle, S., Lin, J.-T., Krotkov, N., Stammes, P., Wang, P., Eskes, H. J., and Krol, M.: Structural uncertainty in air mass factor calculation for NO2 and HCHO satellite retrievals, Atmos. Meas. Tech., 10, 759–782, https://doi.org/10.5194/amt-10-759-2017, 2017.
Luo, G., Yu, F., and Schwab, J.: Revised treatment of wet scavenging processes dramatically improves GEOS-Chem 12.0.0 simulations of surface nitric acid, nitrate, and ammonium over the United States, Geosci. Model Dev., 12, 3439–3447, https://doi.org/10.5194/gmd-12-3439-2019, 2019.
Luo, G., Yu, F., and Moch, J. M.: Further improvement of wet process
treatments in GEOS-Chem v12.6.0: impact on global distributions of aerosols
and aerosol precursors, Geosci. Model Dev., 13, 2879-2903,
10.5194/gmd-13-2879-2020, 2020.
Marais, E. A., Jacob, D. J., Choi, S., Joiner, J., Belmonte-Rivas, M., Cohen, R. C., Beirle, S., Murray, L. T., Schiferl, L. D., Shah, V., and Jaeglé, L.: Nitrogen oxides in the global upper troposphere: interpreting cloud-sliced NO2 observations from the OMI satellite instrument, Atmos. Chem. Phys., 18, 17017–17027, https://doi.org/10.5194/acp-18-17017-2018, 2018.
Marais, E. A., Roberts, J. F., Ryan, R. G., Eskes, H., Boersma, K. F., Choi, S., Joiner, J., Abuhassan, N., Redondas, A., Grutter, M., Cede, A., Gomez, L., and Navarro-Comas, M.: New observations of NO2 in the upper troposphere from TROPOMI, Atmos. Meas. Tech., 14, 2389–2408, https://doi.org/10.5194/amt-14-2389-2021, 2021.
Martin, R. V., Chance, K., Jacob, D. J., Kurosu, T. P., Spurr, R. J. D.,
Bucsela, E., Gleason, J. F., Palmer, P. I., Bey, I., Fiore, A. M., Li, Q.,
Yantosca, R. M., and Koelemeijer, R. B. A.: An improved retrieval of
tropospheric nitrogen dioxide from GOME, J. Geophys. Res.-Atmos., 107, ACH 9-1–ACH 9-21, https://doi.org/10.1029/2001JD001027,
2002.
Martin, R. V., Jacob, D. J., Chance, K., Kurosu, T. P., Palmer, P. I., and
Evans, M. J.: Global inventory of nitrogen oxide emissions constrained by
space-based observations of NO2 columns, J. Geophys. Res.-Atmos., 108, ACH 5-1–ACH 5-12, https://doi.org/10.1029/2003JD003453, 2003.
McDuffie, E. E., Smith, S. J., O'Rourke, P., Tibrewal, K., Venkataraman, C., Marais, E. A., Zheng, B., Crippa, M., Brauer, M., and Martin, R. V.: A global anthropogenic emission inventory of atmospheric pollutants from sector- and fuel-specific sources (1970–2017): an application of the Community Emissions Data System (CEDS), Earth Syst. Sci. Data, 12, 3413–3442, https://doi.org/10.5194/essd-12-3413-2020, 2020.
Mebust, A. K., Russell, A. R., Hudman, R. C., Valin, L. C., and Cohen, R. C.: Characterization of wildfire NOx emissions using MODIS fire radiative power and OMI tropospheric NO2 columns, Atmos. Chem. Phys., 11, 5839–5851, https://doi.org/10.5194/acp-11-5839-2011, 2011.
Miyazaki, K., Eskes, H., Sudo, K., Boersma, K. F., Bowman, K., and Kanaya, Y.: Decadal changes in global surface NOx emissions from multi-constituent satellite data assimilation, Atmos. Chem. Phys., 17, 807–837, https://doi.org/10.5194/acp-17-807-2017, 2017.
Murray, L. T., Jacob, D. J., Logan, J. A., Hudman, R. C., and Koshak, W. J.:
Optimized regional and interannual variability of lightning in a global
chemical transport model constrained by LIS/OTD satellite data, J. Geophys. Res.-Atmos., 117, D20307,
https://doi.org/10.1029/2012JD017934, 2012.
Ott, L. E., Pickering, K. E., Stenchikov, G. L., Allen, D. J., DeCaria, A.
J., Ridley, B., Lin, R. F., Lang, S., and Tao, W. K.: Production of
lightning NOx and its vertical distribution calculated from
three-dimensional cloud-scale chemical transport model simulations, J.
Geophys. Res.-Atmos., 115, D04301, https://doi.org/10.1029/2009jd011880, 2010.
Palm, B. B., Peng, Q., Hall, S. R., Ullmann, K., Campos, T. L., Weinheimer,
A., Montzka, D., Tyndall, G., Permar, W., Hu, L., Flocke, F., Fischer, E.
V., and Thornton, J. A.: Spatially Resolved Photochemistry Impacts Emissions
Estimates in Fresh Wildfire Plumes, Geophys. Res. Lett., 48, e2021GL095443,
https://doi.org/10.1029/2021GL095443, 2021.
Palmer, P. I., Jacob, D. J., Chance, K., Martin, R. V., Spurr, R. J. D.,
Kurosu, T. P., Bey, I., Yantosca, R., Fiore, A., and Li, Q.: Air mass factor
formulation for spectroscopic measurements from satellites: Application to
formaldehyde retrievals from the Global Ozone Monitoring Experiment, J. Geophys. Res.-Atmos., 106, 14539–14550,
https://doi.org/10.1029/2000JD900772, 2001.
Peng, Q. Y., Palm, B. B., Fredrickson, C. D., Lee, B. H., Hall, S. R.,
Ullmann, K., Campos, T., Weinheimer, A. J., Apel, E. C., Flocke, F., Permar,
W., Hu, L., Garofalo, L. A., Pothier, M. A., Farmer, D. K., Ku, I. T.,
Sullivan, A. P., Collett, J. L., Fischer, E., and Thornton, J. A.:
Observations and Modeling of NOx Photochemistry and Fate in Fresh Wildfire
Plumes, ACS Earth Space Chem., 5, 2652–2667,
https://doi.org/10.1021/acsearthspacechem.1c00086, 2021.
Qu, Z., Jacob, D. J., Silvern, R. F., Shah, V., Campbell, P. C., Valin, L.
C., and Murray, L. T.: US COVID-19 Shutdown Demonstrates Importance of
Background NO2 in Inferring NOx Emissions From Satellite NO2 Observations,
Geophys. Res. Lett., 48, e2021GL092783,
https://doi.org/10.1029/2021GL092783, 2021.
Reed, C., Evans, M. J., Crilley, L. R., Bloss, W. J., Sherwen, T., Read, K. A., Lee, J. D., and Carpenter, L. J.: Evidence for renoxification in the tropical marine boundary layer, Atmos. Chem. Phys., 17, 4081–4092, https://doi.org/10.5194/acp-17-4081-2017, 2017.
Richards, N. K., Wingen, L. M., Callahan, K. M., Nishino, N., Kleinman, M.
T., Tobias, D. J., and Finlayson-Pitts, B. J.: Nitrate Ion Photolysis in
Thin Water Films in the Presence of Bromide Ions, J. Phys. Chem. A, 115, 5810–5821, https://doi.org/10.1021/jp109560j, 2011.
Richards, N. K., Anderson, C., Anastasio, C., and Finlayson-Pitts, B. J.:
The effect of cations on NO2 production from the photolysis of aqueous thin
water films of nitrate salts, Phys. Chem. Chem. Phys., 17,
32211–32218, https://doi.org/10.1039/C5CP05325K, 2015.
Rolph, G. D., Draxler, R. R., Stein, A. F., Taylor, A., Ruminski, M. G.,
Kondragunta, S., Zeng, J., Huang, H.-C., Manikin, G., McQueen, J. T., and
Davidson, P. M.: Description and Verification of the NOAA Smoke Forecasting
System: The 2007 Fire Season, Weather Forecast., 24, 361–378,
https://doi.org/10.1175/2008waf2222165.1, 2009.
Romer, P. S., Wooldridge, P. J., Crounse, J. D., Kim, M. J., Wennberg, P.
O., Dibb, J. E., Scheuer, E., Blake, D. R., Meinardi, S., Brosius, A. L.,
Thames, A. B., Miller, D. O., Brune, W. H., Hall, S. R., Ryerson, T. B., and
Cohen, R. C.: Constraints on Aerosol Nitrate Photolysis as a Potential
Source of HONO and NOx, Environ. Sci. Technol., 52, 13738–13746,
https://doi.org/10.1021/acs.est.8b03861, 2018.
Russell, A. R., Valin, L. C., and Cohen, R. C.: Trends in OMI NO2 observations over the United States: effects of emission control technology and the economic recession, Atmos. Chem. Phys., 12, 12197–12209, https://doi.org/10.5194/acp-12-12197-2012, 2012.
Scharko, N. K., Berke, A. E., and Raff, J. D.: Release of Nitrous Acid and
Nitrogen Dioxide from Nitrate Photolysis in Acidic Aqueous Solutions,
Environ. Sci. Technol., 48, 11991–12001, https://doi.org/10.1021/es503088x, 2014.
Shah, V., Jacob, D. J., Dang, R., Lamsal, L. N., Strode, S. A., Steenrod, S. D., Boersma, K. F., Eastham, S. D., Fritz, T. M., Thompson, C., Peischl, J., Bourgeois, I., Pollack, I. B., Nault, B. A., Cohen, R. C., Campuzano-Jost, P., Jimenez, J. L., Andersen, S. T., Carpenter, L. J., Sherwen, T., and Evans, M. J.: Nitrogen oxides in the free troposphere: implications for tropospheric oxidants and the interpretation of satellite NO2 measurements, Atmos. Chem. Phys., 23, 1227–1257, https://doi.org/10.5194/acp-23-1227-2023, 2023.
Silvern, R. F., Jacob, D. J., Travis, K. R., Sherwen, T., Evans, M. J.,
Cohen, R. C., Laughner, J. L., Hall, S. R., Ullmann, K., Crounse, J. D.,
Wennberg, P. O., Peischl, J., and Pollack, I. B.: Observed NO/NO2 Ratios in
the Upper Troposphere Imply Errors in NO-NO2-O3 Cycling Kinetics or an
Unaccounted NOx Reservoir, Geophys. Res. Lett., 45, 4466–4474,
https://doi.org/10.1029/2018GL077728, 2018.
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.
Simone, N. W., Stettler, M. E. J., and Barrett, S. R. H.: Rapid estimation
of global civil aviation emissions with uncertainty quantification,
Transport Environ., 25, 33–41,
https://doi.org/10.1016/j.trd.2013.07.001, 2013.
Travis, K. R., Jacob, D. J., Fisher, J. A., Kim, P. S., Marais, E. A., Zhu, L., Yu, K., Miller, C. C., Yantosca, R. M., Sulprizio, M. P., Thompson, A. M., Wennberg, P. O., Crounse, J. D., St. Clair, J. M., Cohen, R. C., Laughner, J. L., Dibb, J. E., Hall, S. R., Ullmann, K., Wolfe, G. M., Pollack, I. B., Peischl, J., Neuman, J. A., and Zhou, X.: Why do models overestimate surface ozone in the Southeast United States?, Atmos. Chem. Phys., 16, 13561–13577, https://doi.org/10.5194/acp-16-13561-2016, 2016.
Travis, K. R., Heald, C. L., Allen, H. M., Apel, E. C., Arnold, S. R., Blake, D. R., Brune, W. H., Chen, X., Commane, R., Crounse, J. D., Daube, B. C., Diskin, G. S., Elkins, J. W., Evans, M. J., Hall, S. R., Hintsa, E. J., Hornbrook, R. S., Kasibhatla, P. S., Kim, M. J., Luo, G., McKain, K., Millet, D. B., Moore, F. L., Peischl, J., Ryerson, T. B., Sherwen, T., Thames, A. B., Ullmann, K., Wang, X., Wennberg, P. O., Wolfe, G. M., and Yu, F.: Constraining remote oxidation capacity with ATom observations, Atmos. Chem. Phys., 20, 7753–7781, https://doi.org/10.5194/acp-20-7753-2020, 2020.
van der Werf, G. R., Randerson, J. T., Giglio, L., van Leeuwen, T. T., Chen, Y., Rogers, B. M., Mu, M., van Marle, M. J. E., Morton, D. C., Collatz, G. J., Yokelson, R. J., and Kasibhatla, P. S.: Global fire emissions estimates during 1997–2016, Earth Syst. Sci. Data, 9, 697–720, https://doi.org/10.5194/essd-9-697-2017, 2017.
van Geffen, J., Boersma, K. F., Eskes, H., Sneep, M., ter Linden, M., Zara, M., and Veefkind, J. P.: S5P TROPOMI NO2 slant column retrieval: method, stability, uncertainties and comparisons with OMI, Atmos. Meas. Tech., 13, 1315–1335, https://doi.org/10.5194/amt-13-1315-2020, 2020.
Vasilkov, A., Krotkov, N., Yang, E.-S., Lamsal, L., Joiner, J., Castellanos, P., Fasnacht, Z., and Spurr, R.: Explicit and consistent aerosol correction for visible wavelength satellite cloud and nitrogen dioxide retrievals based on optical properties from a global aerosol analysis, Atmos. Meas. Tech., 14, 2857–2871, https://doi.org/10.5194/amt-14-2857-2021, 2021.
Vinken, G. C. M., Boersma, K. F., Maasakkers, J. D., Adon, M., and Martin, R. V.: Worldwide biogenic soil NOx emissions inferred from OMI NO2 observations, Atmos. Chem. Phys., 14, 10363–10381, https://doi.org/10.5194/acp-14-10363-2014, 2014.
Wang, X., Dalton, E. Z., Payne, Z. C., Perrier, S., Riva, M., Raff, J. D.,
and George, C.: Superoxide and Nitrous Acid Production from Nitrate
Photolysis Is Enhanced by Dissolved Aliphatic Organic Matter, Environ. Sci.
Technol. Lett., 8, 53–58, https://doi.org/10.1021/acs.estlett.0c00806, 2021.
Wang, X., Jacob, D. J., Downs, W., Zhai, S., Zhu, L., Shah, V., Holmes, C. D., Sherwen, T., Alexander, B., Evans, M. J., Eastham, S. D., Neuman, J. A., Veres, P. R., Koenig, T. K., Volkamer, R., Huey, L. G., Bannan, T. J., Percival, C. J., Lee, B. H., and Thornton, J. A.: Global tropospheric halogen (Cl, Br, I) chemistry and its impact on oxidants, Atmos. Chem. Phys., 21, 13973–13996, https://doi.org/10.5194/acp-21-13973-2021, 2021.
Wang, Y., Wang, J., Xu, X., Henze, D. K., Qu, Z., and Yang, K.: Inverse modeling of SO2 and NOx emissions over China using multisensor satellite data – Part 1: Formulation and sensitivity analysis, Atmos. Chem. Phys., 20, 6631–6650, https://doi.org/10.5194/acp-20-6631-2020, 2020.
Wang, Y., Ge, C., Castro Garcia, L., Jenerette, G. D., Oikawa, P. Y., and
Wang, J.: Improved modelling of soil NOx emissions in a high temperature
agricultural region: role of background emissions on NO2 trend over the US,
Environ. Res. Lett., 16, 084061, https://doi.org/10.1088/1748-9326/ac16a3, 2021.
Wesely, M. L.: Parameterization of surface resistances to gaseous dry
deposition in regional-scale numerical-models, Atmos. Environ., 23,
1293–1304, https://doi.org/10.1016/0004-6981(89)90153-4, 1989.
Westerling, A. L.: Increasing western US forest wildfire activity:
sensitivity to changes in the timing of spring, Philos. T. Roy. Soc. B, 371, 20150178,
https://doi.org/10.1098/rstb.2015.0178, 2016.
Wilkerson, J. T., Jacobson, M. Z., Malwitz, A., Balasubramanian, S., Wayson, R., Fleming, G., Naiman, A. D., and Lele, S. K.: Analysis of emission data from global commercial aviation: 2004 and 2006, Atmos. Chem. Phys., 10, 6391–6408, https://doi.org/10.5194/acp-10-6391-2010, 2010.
Wingen, L. M., Moskun, A. C., Johnson, S. N., Thomas, J. L., Roeselová,
M., Tobias, D. J., Kleinman, M. T., and Finlayson-Pitts, B. J.: Enhanced
surface photochemistry in chloride–nitrate ion mixtures, Phys. Chem. Chem. Phys., 10, 5668–5677, https://doi.org/10.1039/B806613B, 2008.
Yang, K., Carn, S. A., Ge, C., Wang, J., and Dickerson, R. R.: Advancing
measurements of tropospheric NO2 from space: New algorithm and first global
results from OMPS, Geophys. Res. Lett., 41, 4777–4786,
https://doi.org/10.1002/2014GL060136, 2014.
Ye, C., Zhou, X., Pu, D., Stutz, J., Festa, J., Spolaor, M., Tsai, C.,
Cantrell, C., Mauldin, R. L., Campos, T., Weinheimer, A., Hornbrook, R. S.,
Apel, E. C., Guenther, A., Kaser, L., Yuan, B., Karl, T., Haggerty, J.,
Hall, S., Ullmann, K., Smith, J. N., Ortega, J., and Knote, C.: Rapid
cycling of reactive nitrogen in the marine boundary layer, Nature, 532,
489–491, https://doi.org/10.1038/nature17195, 2016.
Ye, C., Zhang, N., Gao, H., and Zhou, X.: Photolysis of Particulate Nitrate
as a Source of HONO and NOx, Environ. Sci. Technol., 51, 6849–6856,
https://doi.org/10.1021/acs.est.7b00387, 2017.
Zhai, S., Jacob, D. J., Wang, X., Liu, Z., Wen, T., Shah, V., Li, K., Moch,
J. M., Bates, K. H., Song, S., Shen, L., Zhang, Y., Luo, G., Yu, F., Sun,
Y., Wang, L., Qi, M., Tao, J., Gui, K., Xu, H., Zhang, Q., Zhao, T., Wang,
Y., Lee, H. C., Choi, H., and Liao, H.: Control of particulate nitrate air
pollution in China, Nat. Geosci., 14, 389–395, https://doi.org/10.1038/s41561-021-00726-z,
2021.
Zhang, J., Zhang, S., Zhang, X., Wang, J., Wu, Y., and Hao, J.: Developing a
High-Resolution Emission Inventory of China's Aviation Sector Using
Real-World Flight Trajectory Data, Environ. Sci. Technol., 56, 5743–5752,
https://doi.org/10.1021/acs.est.1c08741, 2022.
Zhang, R., Gen, M., Huang, D., Li, Y., and Chan, C. K.: Enhanced Sulfate
Production by Nitrate Photolysis in the Presence of Halide Ions in
Atmospheric Particles, Environ. Sci. Technol., 54, 3831–3839,
https://doi.org/10.1021/acs.est.9b06445, 2020.
Zhu, L., Val Martin, M., Gatti, L. V., Kahn, R., Hecobian, A., and Fischer, E. V.: Development and implementation of a new biomass burning emissions injection height scheme (BBEIH v1.0) for the GEOS-Chem model (v9-01-01), Geosci. Model Dev., 11, 4103–4116, https://doi.org/10.5194/gmd-11-4103-2018, 2018.
Zhu, Q., Laughner, J. L., and Cohen, R. C.: Lightning NO2 simulation over the contiguous US and its effects on satellite NO2 retrievals, Atmos. Chem. Phys., 19, 13067–13078, https://doi.org/10.5194/acp-19-13067-2019, 2019.
Short summary
We use the GEOS-Chem model to better understand the magnitude and trend in free tropospheric NO2 over the contiguous US. Model underestimate of background NO2 is largely corrected by considering aerosol nitrate photolysis. Increase in aircraft emissions affects satellite retrievals by altering the NO2 shape factor, and this effect is expected to increase in future. We show the importance of properly accounting for the free tropospheric background in interpreting NO2 observations from space.
We use the GEOS-Chem model to better understand the magnitude and trend in free tropospheric NO2...
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