Articles | Volume 14, issue 9
https://doi.org/10.5194/gmd-14-5487-2021
© Author(s) 2021. 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-14-5487-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
06 Sep 2021
Model description paper |
| 06 Sep 2021
| 06 Sep 2021
Harmonized Emissions Component (HEMCO) 3.0 as a versatile emissions component for atmospheric models: application in the GEOS-Chem, NASA GEOS, WRF-GC, CESM2, NOAA GEFS-Aerosol, and NOAA UFS models
John A. Paulson School of Engineering and Applied Sciences, Harvard
University, Cambridge, MA, USA
Daniel J. Jacob
John A. Paulson School of Engineering and Applied Sciences, Harvard
University, Cambridge, MA, USA
Elizabeth W. Lundgren
John A. Paulson School of Engineering and Applied Sciences, Harvard
University, Cambridge, MA, USA
Melissa P. Sulprizio
John A. Paulson School of Engineering and Applied Sciences, Harvard
University, Cambridge, MA, USA
Christoph A. Keller
Universities Space Research Association, Columbia, MD, USA
NASA Global Modeling and Assimilation Office, Greenbelt, MD, USA
Thibaud M. Fritz
Department of Aeronautics and Astronautics, Massachusetts Institute of
Technology, Cambridge, MA, USA
Sebastian D. Eastham
Department of Aeronautics and Astronautics, Massachusetts Institute of
Technology, Cambridge, MA, USA
Louisa K. Emmons
Atmospheric Chemistry Observations and Modeling Laboratory, National
Center for Atmospheric Research, Boulder, CO, USA
Patrick C. Campbell
Center for Spatial Information Science and Systems, Cooperative
Institute for Satellite Earth System Studies (CISESS), George Mason
University, Fairfax, VA, USA
NOAA Air Resources Laboratory Affiliate, College Park, MD, USA
Barry Baker
NOAA Air Resources Laboratory Affiliate, College Park, MD, USA
Joint Center for Earth Systems Technology (JCET), University of
Maryland Baltimore County, Baltimore, MD, USA
Rick D. Saylor
NOAA Air Resources Laboratory, Atmospheric Turbulence and Diffusion
Division, Oak Ridge, TN, USA
Raffaele Montuoro
Cooperative Institute for Research in Environmental Sciences, CU
Boulder, Boulder, CO, USA
NOAA Global Systems Laboratory, Boulder, CO, USA
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Hongyu Liu, Bo Zhang, Richard H. Moore, Luke D. Ziemba, Richard A. Ferrare, Hyundeok Choi, Armin Sorooshian, David Painemal, Hailong Wang, Michael A. Shook, Amy Jo Scarino, Johnathan W. Hair, Ewan C. Crosbie, Marta A. Fenn, Taylor J. Shingler, Chris A. Hostetler, Gao Chen, Mary M. Kleb, Gan Luo, Fangqun Yu, Mark A. Vaughan, Yongxiang Hu, Glenn S. Diskin, John B. Nowak, Joshua P. DiGangi, Yonghoon Choi, Christoph A. Keller, and Matthew S. Johnson
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Noribeth Mariscal, Louisa K. Emmons, Duseong S. Jo, Ying Xiong, Laura M. Judd, Scott J. Janz, Jiajue Chai, and Yaoxian Huang
EGUsphere, https://doi.org/10.5194/egusphere-2025-228, https://doi.org/10.5194/egusphere-2025-228, 2025
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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 played a more important role for O3 precursors, and the diurnal cycle significantly impacted nighttime O3 formation.
Tia R. Scarpelli, Elfie Roy, Daniel J. Jacob, Melissa P. Sulprizio, Ryan D. Tate, and Daniel H. Cusworth
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-552, https://doi.org/10.5194/essd-2024-552, 2025
Preprint under review for ESSD
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We present an update of the Global Fuel Exploitation Inventory (GFEI), a global inventory of methane emissions from oil, gas, and coal exploitation. GFEI v3 uses emissions as reported by countries in national inventories for 2020, and new infrastructure information, including a new dataset on coal mine locations. The goal of updating GFEI is to provide a more accurate spatial representation of the country-reported national inventories, allowing comparison with methane monitoring data.
Sarah E. Hancock, Daniel J. Jacob, Zichong Chen, Hannah Nesser, Aaron Davitt, Daniel J. Varon, Melissa P. Sulprizio, Nicholas Balasus, Lucas A. Estrada, María Cazorla, Laura Dawidowski, Sebastián Diez, James D. East, Elise Penn, Cynthia A. Randles, John Worden, Ilse Aben, Robert J. Parker, and Joannes D. Maasakkers
Atmos. Chem. Phys., 25, 797–817, https://doi.org/10.5194/acp-25-797-2025, https://doi.org/10.5194/acp-25-797-2025, 2025
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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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William J. Collins, Fiona M. O'Connor, Connor R. Barker, Rachael E. Byrom, Sebastian D. Eastham, Øivind Hodnebrog, Patrick Jöckel, Eloise A. Marais, Mariano Mertens, Gunnar Myhre, Matthias Nützel, Dirk Olivié, Ragnhild Bieltvedt Skeie, Laura Stecher, Larry W. Horowitz, Vaishali Naik, Gregory Faluvegi, Ulas Im, Lee T. Murray, Drew Shindell, Kostas Tsigaridis, Nathan Luke Abraham, and James Keeble
EGUsphere, https://doi.org/10.5194/egusphere-2024-3698, https://doi.org/10.5194/egusphere-2024-3698, 2024
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If reductions aren’t implemented to limit emissions of pollutants that produce ozone then we calculate that this will cause a warming of climate. We assess how the future warming from ozone is affected by changing meteorological variables such as clouds and atmospheric temperatures. We find that reductions in high cloud cover tend to slightly reduce the warming from ozone.
Vincent R. Meijer, Sebastian D. Eastham, Ian A. Waitz, and Steven R. H. Barrett
Atmos. Meas. Tech., 17, 6145–6162, https://doi.org/10.5194/amt-17-6145-2024, https://doi.org/10.5194/amt-17-6145-2024, 2024
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Aviation's climate impact is partly due to contrails: the clouds that form behind aircraft and which can linger for hours under certain atmospheric conditions. Accurately forecasting these conditions could allow aircraft to avoid forming these contrails and thus reduce their environmental footprint. Our research uses deep learning to identify three-dimensional contrail locations in two-dimensional satellite imagery, which can be used to assess and improve these forecasts.
Meghana Velagar, Christoph Keller, and J. Nathan Kutz
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-77, https://doi.org/10.5194/gmd-2024-77, 2024
Revised manuscript accepted for GMD
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We develop the data-driven method of dynamic mode decomposition for producing a robust and stable surrogate reduced order model of atmospheric chemistry dynamics. The model is computationally efficient, provides interpretable patterns of activity and produces uncertainty quantification metrics. It is ideal for forecasting of atmospheric chemistry in a computationally tractable manner.
Yujin J. Oak, Daniel J. Jacob, Nicholas Balasus, Laura H. Yang, Heesung Chong, Junsung Park, Hanlim Lee, Gitaek T. Lee, Eunjo S. Ha, Rokjin J. Park, Hyeong-Ahn Kwon, and Jhoon Kim
Atmos. Meas. Tech., 17, 5147–5159, https://doi.org/10.5194/amt-17-5147-2024, https://doi.org/10.5194/amt-17-5147-2024, 2024
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We present an improved NO2 product from GEMS by calibrating it to TROPOMI using machine learning and by reprocessing both satellite products to adopt common NO2 profiles. Our corrected GEMS product combines the high data density of GEMS with the accuracy of TROPOMI, supporting the combined use for analyses of East Asia air quality including emissions and chemistry. This method can be extended to other species and geostationary satellites including TEMPO and Sentinel-4.
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.
Irene C. Dedoussi, Daven K. Henze, Sebastian D. Eastham, Raymond L. Speth, and Steven R. H. Barrett
Geosci. Model Dev., 17, 5689–5703, https://doi.org/10.5194/gmd-17-5689-2024, https://doi.org/10.5194/gmd-17-5689-2024, 2024
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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.
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.
Brian Nathan, Joannes D. Maasakkers, Stijn Naus, Ritesh Gautam, Mark Omara, Daniel J. Varon, Melissa P. Sulprizio, Lucas A. Estrada, Alba Lorente, Tobias Borsdorff, Robert J. Parker, and Ilse Aben
Atmos. Chem. Phys., 24, 6845–6863, https://doi.org/10.5194/acp-24-6845-2024, https://doi.org/10.5194/acp-24-6845-2024, 2024
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Venezuela's Lake Maracaibo region is notoriously hard to observe from space and features intensive oil exploitation, although production has strongly decreased in recent years. We estimate methane emissions using 2018–2020 TROPOMI satellite observations with national and regional transport models. Despite the production decrease, we find relatively constant emissions from Lake Maracaibo between 2018 and 2020, indicating that there could be large emissions from abandoned infrastructure.
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
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Fine particles suspended in the atmosphere are a major form of air pollution and an important public health burden. However, measurements of particulate matter are sparse in space and in places like East Asia monitors are established after regulatory policies to improve pollution have changed. In this paper, we use machine learning to fill in the gaps. We train an algorithm to predict pollution at the surface from the atmosphere’s opacity, then produce high resolution maps of data without gaps.
Qindan Zhu, Rebecca H. Schwantes, Matthew Coggon, Colin Harkins, Jordan Schnell, Jian He, Havala O. T. Pye, Meng Li, Barry Baker, Zachary Moon, Ravan Ahmadov, Eva Y. Pfannerstill, Bryan Place, Paul Wooldridge, Benjamin C. Schulze, Caleb Arata, Anthony Bucholtz, John H. Seinfeld, Carsten Warneke, Chelsea E. Stockwell, Lu Xu, Kristen Zuraski, Michael A. Robinson, J. Andrew Neuman, Patrick R. Veres, Jeff Peischl, Steven S. Brown, Allen H. Goldstein, Ronald C. Cohen, and Brian C. McDonald
Atmos. Chem. Phys., 24, 5265–5286, https://doi.org/10.5194/acp-24-5265-2024, https://doi.org/10.5194/acp-24-5265-2024, 2024
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Volatile organic compounds (VOCs) fuel the production of air pollutants like ozone and particulate matter. The representation of VOC chemistry remains challenging due to its complexity in speciation and reactions. Here, we develop a chemical mechanism, RACM2B-VCP, that better represents VOC chemistry in urban areas such as Los Angeles. We also discuss the contribution of VOCs emitted from volatile chemical products and other anthropogenic sources to total VOC reactivity and O3.
Jack H. Bruno, Dylan Jervis, Daniel J. Varon, and Daniel J. Jacob
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.
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.
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.
Li Pan, Partha S. Bhattacharjee, Li Zhang, Raffaele Montuoro, Barry Baker, Jeff McQueen, Georg A. Grell, Stuart A. McKeen, Shobha Kondragunta, Xiaoyang Zhang, Gregory J. Frost, Fanglin Yang, and Ivanka Stajner
Geosci. Model Dev., 17, 431–447, https://doi.org/10.5194/gmd-17-431-2024, https://doi.org/10.5194/gmd-17-431-2024, 2024
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A GEFS-Aerosols simulation was conducted from 1 September 2019 to 30 September 2020 to evaluate the model performance of GEFS-Aerosols. The purpose of this study was to understand how aerosol chemical and physical processes affect ambient aerosol concentrations by placing aerosol wet deposition, dry deposition, reactions, gravitational deposition, and emissions into the aerosol mass balance equation.
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.
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.
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.
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.
Ruijun Dang, Daniel J. Jacob, Viral Shah, Sebastian D. Eastham, Thibaud M. Fritz, Loretta J. Mickley, Tianjia Liu, Yi Wang, and Jun Wang
Atmos. Chem. Phys., 23, 6271–6284, https://doi.org/10.5194/acp-23-6271-2023, https://doi.org/10.5194/acp-23-6271-2023, 2023
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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.
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.
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.
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.
Yunyao Li, Daniel Tong, Siqi Ma, Saulo R. Freitas, Ravan Ahmadov, Mikhail Sofiev, Xiaoyang Zhang, Shobha Kondragunta, Ralph Kahn, Youhua Tang, Barry Baker, Patrick Campbell, Rick Saylor, Georg Grell, and Fangjun Li
Atmos. Chem. Phys., 23, 3083–3101, https://doi.org/10.5194/acp-23-3083-2023, https://doi.org/10.5194/acp-23-3083-2023, 2023
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Plume height is important in wildfire smoke dispersion and affects air quality and human health. We assess the impact of plume height on wildfire smoke dispersion and the exceedances of the National Ambient Air Quality Standards. A higher plume height predicts lower pollution near the source region, but higher pollution in downwind regions, due to the faster spread of the smoke once ejected, affects pollution exceedance forecasts and the early warning of extreme air pollution events.
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.
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.
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.
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.
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.
Youhua Tang, Patrick C. Campbell, Pius Lee, Rick Saylor, Fanglin Yang, Barry Baker, Daniel Tong, Ariel Stein, Jianping Huang, Ho-Chun Huang, Li Pan, Jeff McQueen, Ivanka Stajner, Jose Tirado-Delgado, Youngsun Jung, Melissa Yang, Ilann Bourgeois, Jeff Peischl, Tom Ryerson, Donald Blake, Joshua Schwarz, Jose-Luis Jimenez, James Crawford, Glenn Diskin, Richard Moore, Johnathan Hair, Greg Huey, Andrew Rollins, Jack Dibb, and Xiaoyang Zhang
Geosci. Model Dev., 15, 7977–7999, https://doi.org/10.5194/gmd-15-7977-2022, https://doi.org/10.5194/gmd-15-7977-2022, 2022
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This paper compares two meteorological datasets for driving a regional air quality model: a regional meteorological model using WRF (WRF-CMAQ) and direct interpolation from an operational global model (GFS-CMAQ). In the comparison with surface measurements and aircraft data in summer 2019, these two methods show mixed performance depending on the corresponding meteorological settings. Direct interpolation is found to be a viable method to drive air quality models.
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.
Li Zhang, Raffaele Montuoro, Stuart A. McKeen, Barry Baker, Partha S. Bhattacharjee, Georg A. Grell, Judy Henderson, Li Pan, Gregory J. Frost, Jeff McQueen, Rick Saylor, Haiqin Li, Ravan Ahmadov, Jun Wang, Ivanka Stajner, Shobha Kondragunta, Xiaoyang Zhang, and Fangjun Li
Geosci. Model Dev., 15, 5337–5369, https://doi.org/10.5194/gmd-15-5337-2022, https://doi.org/10.5194/gmd-15-5337-2022, 2022
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The NOAA’s air quality predictions contribute to protecting lives and health in the US, which requires sustainable development and improvement of forecast systems. GEFS-Aerosols v1 has been developed in a collaboration between the NOAA research laboratories for operational forecast since September 2020 in the NCEP. The predictions demonstrate substantial improvements for both composition and variability of aerosol distributions over those from the former operational system.
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.
Xiaotian Xu, Xu Feng, Haipeng Lin, Peng Zhang, Shaojian Huang, Zhengcheng Song, Yiming Peng, Tzung-May Fu, and Yanxu Zhang
Geosci. Model Dev., 15, 3845–3859, https://doi.org/10.5194/gmd-15-3845-2022, https://doi.org/10.5194/gmd-15-3845-2022, 2022
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Mercury is one of the most toxic pollutants in the environment, and wet deposition is a major process for atmospheric mercury to enter, causing ecological and human health risks. High-mercury wet deposition in the southeastern US has been a problem for many years. Here we employed a newly developed high-resolution WRF-GC model with the capability to simulate mercury to study this problem. We conclude that deep convection caused enhanced mercury wet deposition in the southeastern US.
Patrick C. Campbell, Youhua Tang, Pius Lee, Barry Baker, Daniel Tong, Rick Saylor, Ariel Stein, Jianping Huang, Ho-Chun Huang, Edward Strobach, Jeff McQueen, Li Pan, Ivanka Stajner, Jamese Sims, Jose Tirado-Delgado, Youngsun Jung, Fanglin Yang, Tanya L. Spero, and Robert C. Gilliam
Geosci. Model Dev., 15, 3281–3313, https://doi.org/10.5194/gmd-15-3281-2022, https://doi.org/10.5194/gmd-15-3281-2022, 2022
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NOAA's National Air Quality Forecast Capability (NAQFC) continues to protect Americans from the harmful effects of air pollution, while saving billions of dollars per year. Here we describe and evaluate the development of the most advanced version of the NAQFC to date, which became operational at NOAA on 20 July 2021. The new NAQFC is based on a coupling of NOAA's operational Global Forecast System (GFS) version 16 with the Community Multiscale Air Quality (CMAQ) model version 5.3.1.
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.
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.
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.
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.
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 %.
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.
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.
Hyun Cheol Kim, Soontae Kim, Mark Cohen, Changhan Bae, Dasom Lee, Rick Saylor, Minah Bae, Eunhye Kim, Byeong-Uk Kim, Jin-Ho Yoon, and Ariel Stein
Atmos. Chem. Phys., 21, 10065–10080, https://doi.org/10.5194/acp-21-10065-2021, https://doi.org/10.5194/acp-21-10065-2021, 2021
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Global outbreaks of COVID-19 offer rare opportunities of natural experiments in emission control and corresponding responses of tropospheric chemistry. This study's novel approach investigates (1) isolating the pandemic's impact from natural and anthropogenic variations, (2) emission adjustment to reproduce real-time emissions, and (3) brute-force modeling to investigate Chinese economic activities. Results provide characteristics of the region's chemistry and emissions.
Jun Meng, Randall V. Martin, Paul Ginoux, Melanie Hammer, Melissa P. Sulprizio, David A. Ridley, and Aaron van Donkelaar
Geosci. Model Dev., 14, 4249–4260, https://doi.org/10.5194/gmd-14-4249-2021, https://doi.org/10.5194/gmd-14-4249-2021, 2021
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Dust emissions in models, for example, GEOS-Chem, have a strong nonlinear dependence on meteorology, which means dust emission strengths calculated from different resolution meteorological fields are different. Offline high-resolution dust emissions with an optimized global dust strength, presented in this work, can be implemented into GEOS-Chem as offline emission inventory so that it could promote model development by harmonizing dust emissions across simulations of different resolutions.
Xiaoyang Chen, Yang Zhang, Kai Wang, Daniel Tong, Pius Lee, Youhua Tang, Jianping Huang, Patrick C. Campbell, Jeff Mcqueen, Havala O. T. Pye, Benjamin N. Murphy, and Daiwen Kang
Geosci. Model Dev., 14, 3969–3993, https://doi.org/10.5194/gmd-14-3969-2021, https://doi.org/10.5194/gmd-14-3969-2021, 2021
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The continuously updated National Air Quality Forecast Capability (NAQFC) provides air quality forecasts. To support the development of the next-generation NAQFC, we evaluate a prototype of GFSv15-CMAQv5.0.2. The performance and the potential improvements for the system are discussed. This study can provide a scientific basis for further development of NAQFC and help it to provide more accurate air quality forecasts to the public over the contiguous United States.
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.
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.
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.
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.
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).
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.
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.
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.
Christoph A. Keller, Mathew J. Evans, K. Emma Knowland, Christa A. Hasenkopf, Sruti Modekurty, Robert A. Lucchesi, Tomohiro Oda, Bruno B. Franca, Felipe C. Mandarino, M. Valeria Díaz Suárez, Robert G. Ryan, Luke H. Fakes, and Steven Pawson
Atmos. Chem. Phys., 21, 3555–3592, https://doi.org/10.5194/acp-21-3555-2021, https://doi.org/10.5194/acp-21-3555-2021, 2021
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This study combines surface observations and model simulations to quantify the impact of COVID-19 restrictions on air quality across the world. The presented methodology removes the confounding impacts of meteorology on air pollution. Our results indicate that surface concentrations of nitrogen dioxide, an important air pollutant emitted during the combustion of fossil fuels, declined by up to 60 % following the implementation of COVID-19 containment measures.
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.
Youhua Tang, Huisheng Bian, Zhining Tao, Luke D. Oman, Daniel Tong, Pius Lee, Patrick C. Campbell, Barry Baker, Cheng-Hsuan Lu, Li Pan, Jun Wang, Jeffery McQueen, and Ivanka Stajner
Atmos. Chem. Phys., 21, 2527–2550, https://doi.org/10.5194/acp-21-2527-2021, https://doi.org/10.5194/acp-21-2527-2021, 2021
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Chemical lateral boundary condition (CLBC) impact is essential for regional air quality prediction during intrusion events. We present a model mapping Goddard Earth Observing System (GEOS) to Community Multi-scale Air Quality (CMAQ) CB05–AERO6 (Carbon Bond 5; version 6 of the aerosol module) species. Influence depends on distance from the inflow boundary and species and their regional characteristics. We use aerosol optical thickness to derive CLBCs, achieving reasonable prediction.
Bo Zhang, Hongyu Liu, James H. Crawford, Gao Chen, T. Duncan Fairlie, Scott Chambers, Chang-Hee Kang, Alastair G. Williams, Kai Zhang, David B. Considine, Melissa P. Sulprizio, and Robert M. Yantosca
Atmos. Chem. Phys., 21, 1861–1887, https://doi.org/10.5194/acp-21-1861-2021, https://doi.org/10.5194/acp-21-1861-2021, 2021
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We simulate atmospheric 222Rn using the GEOS-Chem model to improve understanding of 222Rn emissions and characterize convective transport in the model. We demonstrate the potential of a customized global 222Rn emission scenario to improve simulated surface 222Rn concentrations and seasonality. We assess convective transport using observed 222Rn vertical profiles. Results have important implications for using chemical transport models to interpret the transport of trace gases and aerosols.
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.
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.
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.
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.
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.
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.
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.
Wenfu Tang, Benjamin Gaubert, Louisa Emmons, Yonghoon Choi, Joshua P. DiGangi, Glenn S. Diskin, Xiaomei Xu, Cenlin He, Helen Worden, Simone Tilmes, Rebecca Buchholz, Hannah S. Halliday, and Avelino F. Arellano
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-864, https://doi.org/10.5194/acp-2020-864, 2020
Revised manuscript not accepted
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A specific demonstration of the potential use of correlative information from carbon monoxide to refine estimates of regional carbon dioxide emissions from fossil fuel combustion.
Robert J. Allen, Steven Turnock, Pierre Nabat, David Neubauer, Ulrike Lohmann, Dirk Olivié, Naga Oshima, Martine Michou, Tongwen Wu, Jie Zhang, Toshihiko Takemura, Michael Schulz, Kostas Tsigaridis, Susanne E. Bauer, Louisa Emmons, Larry Horowitz, Vaishali Naik, Twan van Noije, Tommi Bergman, Jean-Francois Lamarque, Prodromos Zanis, Ina Tegen, Daniel M. Westervelt, Philippe Le Sager, Peter Good, Sungbo Shim, Fiona O'Connor, Dimitris Akritidis, Aristeidis K. Georgoulias, Makoto Deushi, Lori T. Sentman, Jasmin G. John, Shinichiro Fujimori, and William J. Collins
Atmos. Chem. Phys., 20, 9641–9663, https://doi.org/10.5194/acp-20-9641-2020, https://doi.org/10.5194/acp-20-9641-2020, 2020
Sarah A. Strode, James S. Wang, Michael Manyin, Bryan Duncan, Ryan Hossaini, Christoph A. Keller, Sylvia E. Michel, and James W. C. White
Atmos. Chem. Phys., 20, 8405–8419, https://doi.org/10.5194/acp-20-8405-2020, https://doi.org/10.5194/acp-20-8405-2020, 2020
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The 13C : 12C isotopic ratio in methane (CH4) provides information about CH4 sources, but loss of CH4 by reaction with OH and chlorine (Cl) also affects this ratio. Tropospheric Cl provides a small and uncertain sink for CH4 but has a large effect on its isotopic ratio. We use the GEOS model with several different Cl fields to test the sensitivity of methane's isotopic composition to tropospheric Cl. Cl affects the global mean, hemispheric gradient, and seasonal cycle of the isotopic ratio.
Haipeng Lin, Xu Feng, Tzung-May Fu, Heng Tian, Yaping Ma, Lijuan Zhang, Daniel J. Jacob, Robert M. Yantosca, Melissa P. Sulprizio, Elizabeth W. Lundgren, Jiawei Zhuang, Qiang Zhang, Xiao Lu, Lin Zhang, Lu Shen, Jianping Guo, Sebastian D. Eastham, and Christoph A. Keller
Geosci. Model Dev., 13, 3241–3265, https://doi.org/10.5194/gmd-13-3241-2020, https://doi.org/10.5194/gmd-13-3241-2020, 2020
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Online coupling of meteorology and chemistry models often presents maintenance issues with hard-wired coding. We present WRF-GC, an one-way online coupling of the WRF meteorological model and GEOS-Chem atmospheric chemistry model for regional atmospheric chemistry and air quality modeling. Our coupling structure allows future versions of either parent model to be immediately integrated into WRF-GC. The WRF-GC model was able to well reproduce regional PM2.5 with greater computational efficiency.
Pablo E. Saide, Meng Gao, Zifeng Lu, Daniel L. Goldberg, David G. Streets, Jung-Hun Woo, Andreas Beyersdorf, Chelsea A. Corr, Kenneth L. Thornhill, Bruce Anderson, Johnathan W. Hair, Amin R. Nehrir, Glenn S. Diskin, Jose L. Jimenez, Benjamin A. Nault, Pedro Campuzano-Jost, Jack Dibb, Eric Heim, Kara D. Lamb, Joshua P. Schwarz, Anne E. Perring, Jhoon Kim, Myungje Choi, Brent Holben, Gabriele Pfister, Alma Hodzic, Gregory R. Carmichael, Louisa Emmons, and James H. Crawford
Atmos. Chem. Phys., 20, 6455–6478, https://doi.org/10.5194/acp-20-6455-2020, https://doi.org/10.5194/acp-20-6455-2020, 2020
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Air quality forecasts over the Korean Peninsula captured aerosol optical depth but largely overpredicted surface PM during a Chinese haze transport event. Model deficiency was related to the calculation of optical properties. In order to improve it, aerosol size representation needs to be refined in the calculations, and the representation of aerosol properties, such as size distribution, chemical composition, refractive index, hygroscopicity parameter, and density, needs to be improved.
Lu Shen, Daniel J. Jacob, Mauricio Santillana, Xuan Wang, and Wei Chen
Geosci. Model Dev., 13, 2475–2486, https://doi.org/10.5194/gmd-13-2475-2020, https://doi.org/10.5194/gmd-13-2475-2020, 2020
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Chemical mechanisms in air quality models tend to get more complicated with time, reflecting both increasing knowledge and the need for greater scope. This objectively improves the models but increases the computational burden. In this work, we present an approach that can reduce the computational cost of chemical integration by 30–40 % while maintaining an accuracy better than 1 %. It retains the complexity of the full mechanism where it is needed and preserves full diagnostic information.
Thibaud M. Fritz, Sebastian D. Eastham, Raymond L. Speth, and Steven R. H. Barrett
Atmos. Chem. Phys., 20, 5697–5727, https://doi.org/10.5194/acp-20-5697-2020, https://doi.org/10.5194/acp-20-5697-2020, 2020
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Aircraft exhaust drives formation of ozone and is a dominant anthropogenic influence in the upper troposphere. These impacts are mitigated by non-linear chemistry inside the aircraft plume, which cuts off part of the ozone production pathway and reduces the long-term impact of aircraft in a way which is not captured by current models. The ice clouds which form in aircraft exhaust ("contrails") also play a role, converting emitted nitrogen oxides into more stable forms such as nitric acid.
Li Pan, HyunCheol Kim, Pius Lee, Rick Saylor, YouHua Tang, Daniel Tong, Barry Baker, Shobha Kondragunta, Chuanyu Xu, Mark G. Ruminski, Weiwei Chen, Jeff Mcqueen, and Ivanka Stajner
Geosci. Model Dev., 13, 2169–2184, https://doi.org/10.5194/gmd-13-2169-2020, https://doi.org/10.5194/gmd-13-2169-2020, 2020
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Compared to anthropogenic emissions, emissions from wildfires are largely uncontrolled and unpredictable. Quantitatively describing wildfire emissions and their contributions to air pollution remains a substantial challenge for air quality forecasting efforts. In this study, we test the wildfire calculation algorithm used by the National Air Quality Forecasting Capability (NAQFC) by comparison with ground, satellite and flight measurements during the Southeast Nexus (SENEX) field experiment.
Rebecca H. Schwantes, Louisa K. Emmons, John J. Orlando, Mary C. Barth, Geoffrey S. Tyndall, Samuel R. Hall, Kirk Ullmann, Jason M. St. Clair, Donald R. Blake, Armin Wisthaler, and Thao Paul V. Bui
Atmos. Chem. Phys., 20, 3739–3776, https://doi.org/10.5194/acp-20-3739-2020, https://doi.org/10.5194/acp-20-3739-2020, 2020
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Ozone is a greenhouse gas and air pollutant that is harmful to human health and plants. During the summer in the southeastern US, many regional and global models are biased high for surface ozone compared to observations. Here adding more complex and updated chemistry for isoprene and terpenes, which are biogenic hydrocarbons emitted from trees and vegetation, into an earth system model greatly reduces the simulated surface ozone bias compared to aircraft and monitoring station data.
Wenfu Tang, Helen M. Worden, Merritt N. Deeter, David P. Edwards, Louisa K. Emmons, Sara Martínez-Alonso, Benjamin Gaubert, Rebecca R. Buchholz, Glenn S. Diskin, Russell R. Dickerson, Xinrong Ren, Hao He, and Yutaka Kondo
Atmos. Meas. Tech., 13, 1337–1356, https://doi.org/10.5194/amt-13-1337-2020, https://doi.org/10.5194/amt-13-1337-2020, 2020
Tia R. Scarpelli, Daniel J. Jacob, Joannes D. Maasakkers, Melissa P. Sulprizio, Jian-Xiong Sheng, Kelly Rose, Lucy Romeo, John R. Worden, and Greet Janssens-Maenhout
Earth Syst. Sci. Data, 12, 563–575, https://doi.org/10.5194/essd-12-563-2020, https://doi.org/10.5194/essd-12-563-2020, 2020
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Methane, a potent greenhouse gas, is emitted through the exploitation of oil, gas, and coal resources, and many efforts to reduce emissions have targeted these sources. We have created a global inventory of oil, gas, and coal methane emissions based on country reporting to the United Nations. The inventory can be used along with satellite observations of methane to better understand the contribution of these sources to global emissions and to identify potential biases in emissions reporting.
Viral Shah, Daniel J. Jacob, Ke Li, Rachel F. Silvern, Shixian Zhai, Mengyao Liu, Jintai Lin, and Qiang Zhang
Atmos. Chem. Phys., 20, 1483–1495, https://doi.org/10.5194/acp-20-1483-2020, https://doi.org/10.5194/acp-20-1483-2020, 2020
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We analyze 15 years of satellite observations of nitrogen dioxide (NO2) and use an atmospheric chemistry model to understand the seasonal changes and trends in nitrogen oxides (NOx) over China. We show that the seasonal changes in NO2 occur due to changes in the NOx oxidation lifetime. We find that Chinese NOx emissions peaked in 2011 and had decreased by about 25 % by 2018. But the decrease in NO2 in winter was larger, likely because of a simultaneous decrease in the NOx oxidation lifetime.
Daniel H. Cusworth, Daniel J. Jacob, Daniel J. Varon, Christopher Chan Miller, Xiong Liu, Kelly Chance, Andrew K. Thorpe, Riley M. Duren, Charles E. Miller, David R. Thompson, Christian Frankenberg, Luis Guanter, and Cynthia A. Randles
Atmos. Meas. Tech., 12, 5655–5668, https://doi.org/10.5194/amt-12-5655-2019, https://doi.org/10.5194/amt-12-5655-2019, 2019
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We examine the potential for global detection of methane plumes from individual point sources with the new generation of spaceborne imaging spectrometers scheduled for launch in 2019–2025. We perform methane retrievals on simulated scenes with varying surfaces and atmospheric methane concentrations. Our results suggest that imaging spectrometers in space could play a transformative role in the future for quantifying methane emissions from point sources on a global scale.
Shixian Zhai, Daniel J. Jacob, Xuan Wang, Lu Shen, Ke Li, Yuzhong Zhang, Ke Gui, Tianliang Zhao, and Hong Liao
Atmos. Chem. Phys., 19, 11031–11041, https://doi.org/10.5194/acp-19-11031-2019, https://doi.org/10.5194/acp-19-11031-2019, 2019
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Observed annual mean PM2.5 decreased by 30–50 % in China from 2013–2018. However, meteorologically PM2.5 variability complicates trend attribution. We used a stepwise multiple linear regression model to quantitatively separate contributions from anthropogenic emissions and meteorology. Results show that 88 % of the PM2.5 decrease across China is attributable to anthropogenic emission changes, and 12 % is attributable to meteorology.
Katherine R. Travis and Daniel J. Jacob
Geosci. Model Dev., 12, 3641–3648, https://doi.org/10.5194/gmd-12-3641-2019, https://doi.org/10.5194/gmd-12-3641-2019, 2019
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Models of ozone air pollution are often evaluated with the policy metric set by the EPA of the maximum daily 8 h average ozone concentration. These models may be used in policy settings to evaluate air quality regulations. However, most models have difficulty simulating how ozone varies over the course of the day, and thus the use of this metric in model evaluation is problematic. Improved representation of mixed layer dynamics and ozone loss to the surface is needed to resolve this issue.
Kelvin H. Bates and Daniel J. Jacob
Atmos. Chem. Phys., 19, 9613–9640, https://doi.org/10.5194/acp-19-9613-2019, https://doi.org/10.5194/acp-19-9613-2019, 2019
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Isoprene is a highly reactive chemical released to the atmosphere by plants. Its gas-phase reactions and interactions with chemicals released by human activity have far-reaching atmospheric consequences, contributing to ozone and particulate pollution and prolonging the lifetime of methane, a potent greenhouse gas. We use global simulations with a new isoprene reaction scheme to quantify those effects and to show how recently discovered aspects of isoprene chemistry play out on a global scale.
Duseong S. Jo, Alma Hodzic, Louisa K. Emmons, Eloise A. Marais, Zhe Peng, Benjamin A. Nault, Weiwei Hu, Pedro Campuzano-Jost, and Jose L. Jimenez
Geosci. Model Dev., 12, 2983–3000, https://doi.org/10.5194/gmd-12-2983-2019, https://doi.org/10.5194/gmd-12-2983-2019, 2019
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We developed a parameterization method for IEPOX-SOA based on the detailed chemical mechanism. Our parameterizations were tested using a box model and 3-D chemical transport model, which accurately captured the spatiotemporal distribution and response to changes in emissions compared to the explicit full chemistry, while being more computationally efficient. The method developed in this study can be applied to global climate models for long-term studies with a lower computational cost.
Rachel F. Silvern, Daniel J. Jacob, Loretta J. Mickley, Melissa P. Sulprizio, Katherine R. Travis, Eloise A. Marais, Ronald C. Cohen, Joshua L. Laughner, Sungyeon Choi, Joanna Joiner, and Lok N. Lamsal
Atmos. Chem. Phys., 19, 8863–8878, https://doi.org/10.5194/acp-19-8863-2019, https://doi.org/10.5194/acp-19-8863-2019, 2019
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The US EPA reports a steady decrease in nitrogen oxide (NOx) emissions from fuel combustion over the 2005–2017 period, while satellite observations show a leveling off after 2009, suggesting emission reductions and related air quality gains have halted. We show the sustained decrease in NOx emissions is in fact consistent with observed trends in surface NO2 and ozone concentrations and that the flattening of the satellite trend reflects a growing influence from the non-anthropogenic background.
Joannes D. Maasakkers, Daniel J. Jacob, Melissa P. Sulprizio, Tia R. Scarpelli, Hannah Nesser, Jian-Xiong Sheng, Yuzhong Zhang, Monica Hersher, A. Anthony Bloom, Kevin W. Bowman, John R. Worden, Greet Janssens-Maenhout, and Robert J. Parker
Atmos. Chem. Phys., 19, 7859–7881, https://doi.org/10.5194/acp-19-7859-2019, https://doi.org/10.5194/acp-19-7859-2019, 2019
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We use 2010–2015 satellite observations of atmospheric methane to improve estimates of methane emissions and their trends, as well as the concentration and trend of tropospheric OH (hydroxyl radical, methane's main sink). We find overestimates of Chinese coal and Middle East oil/gas emissions in the prior estimate. The 2010–2015 growth in methane is attributed to an increase in emissions from India, China, and areas with large tropical wetlands. The contribution from OH is small in comparison.
Lu Shen, Daniel J. Jacob, Xiong Liu, Guanyu Huang, Ke Li, Hong Liao, and Tao Wang
Atmos. Chem. Phys., 19, 6551–6560, https://doi.org/10.5194/acp-19-6551-2019, https://doi.org/10.5194/acp-19-6551-2019, 2019
Lei Zhu, Daniel J. Jacob, Sebastian D. Eastham, Melissa P. Sulprizio, Xuan Wang, Tomás Sherwen, Mat J. Evans, Qianjie Chen, Becky Alexander, Theodore K. Koenig, Rainer Volkamer, L. Gregory Huey, Michael Le Breton, Thomas J. Bannan, and Carl J. Percival
Atmos. Chem. Phys., 19, 6497–6507, https://doi.org/10.5194/acp-19-6497-2019, https://doi.org/10.5194/acp-19-6497-2019, 2019
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We quantify the effect of sea salt aerosol on tropospheric bromine chemistry with a new mechanistic description of the halogen chemistry in a global atmospheric chemistry model. For the first time, we are able to reproduce the observed levels of bromide activation from the sea salt aerosol in a manner consistent with bromine oxide radical measured from various platforms. Sea salt aerosol plays a far more complex role in global tropospheric chemistry than previously recognized.
Meghana Velegar, N. Benjamin Erichson, Christoph A. Keller, and J. Nathan Kutz
Geosci. Model Dev., 12, 1525–1539, https://doi.org/10.5194/gmd-12-1525-2019, https://doi.org/10.5194/gmd-12-1525-2019, 2019
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We introduce a new set of algorithmic tools capable of producing scalable, low-rank decompositions of global spatiotemporal atmospheric chemistry data. By exploiting emerging randomized linear algebra algorithms, a suite of decompositions are proposed that efficiently extract the dominant features from global atmospheric chemistry at longitude, latitude, and elevation with improved interpretability. The algorithms provide a strategy for the global monitoring of atmospheric chemistry.
Christoph A. Keller and Mat J. Evans
Geosci. Model Dev., 12, 1209–1225, https://doi.org/10.5194/gmd-12-1209-2019, https://doi.org/10.5194/gmd-12-1209-2019, 2019
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Computer simulations of atmospheric chemistry are a central tool to study the impact of air pollutants on the environment. These models are highly complex and require a lot of computing resources. In this study we show that machine learning can be used to predict air pollution with an accuracy that is comparable to the traditional, computationally expensive method. Such a machine-learning-based model has the potential to be orders of magnitude faster.
Xuan Wang, Daniel J. Jacob, Sebastian D. Eastham, Melissa P. Sulprizio, Lei Zhu, Qianjie Chen, Becky Alexander, Tomás Sherwen, Mathew J. Evans, Ben H. Lee, Jessica D. Haskins, Felipe D. Lopez-Hilfiker, Joel A. Thornton, Gregory L. Huey, and Hong Liao
Atmos. Chem. Phys., 19, 3981–4003, https://doi.org/10.5194/acp-19-3981-2019, https://doi.org/10.5194/acp-19-3981-2019, 2019
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Chlorine radicals have a broad range of implications for tropospheric chemistry, air quality, and climate. We present a comprehensive simulation of tropospheric chlorine in a global 3-D model, which includes explicit accounting of chloride mobilization from sea salt aerosol. We find the chlorine chemistry contributes 1.0 % of the global oxidation of methane and decreases global burdens of tropospheric ozone by 7 % and OH by 3 % through the associated bromine radical chemistry.
Kai-Lan Chang, Owen R. Cooper, J. Jason West, Marc L. Serre, Martin G. Schultz, Meiyun Lin, Virginie Marécal, Béatrice Josse, Makoto Deushi, Kengo Sudo, Junhua Liu, and Christoph A. Keller
Geosci. Model Dev., 12, 955–978, https://doi.org/10.5194/gmd-12-955-2019, https://doi.org/10.5194/gmd-12-955-2019, 2019
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We developed a new method for combining surface ozone observations from thousands of monitoring sites worldwide with the output from multiple atmospheric chemistry models. The result is a global surface ozone distribution with greater accuracy than any single model can achieve. We focused on an ozone metric relevant to human mortality caused by long-term ozone exposure. Our method can be applied to studies that quantify the impacts of ozone on human health and mortality.
Shaojie Song, Meng Gao, Weiqi Xu, Yele Sun, Douglas R. Worsnop, John T. Jayne, Yuzhong Zhang, Lei Zhu, Mei Li, Zhen Zhou, Chunlei Cheng, Yibing Lv, Ying Wang, Wei Peng, Xiaobin Xu, Nan Lin, Yuxuan Wang, Shuxiao Wang, J. William Munger, Daniel J. Jacob, and Michael B. McElroy
Atmos. Chem. Phys., 19, 1357–1371, https://doi.org/10.5194/acp-19-1357-2019, https://doi.org/10.5194/acp-19-1357-2019, 2019
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Chemistry responsible for sulfate production in northern China winter haze remains mysterious. We propose a potentially key pathway through the reaction of formaldehyde and sulfur dioxide that has not been accounted for in previous studies. The special atmospheric conditions favor the formation and existence of their complex, hydroxymethanesulfonate (HMS).
Lu Shen, Daniel J. Jacob, Loretta J. Mickley, Yuxuan Wang, and Qiang Zhang
Atmos. Chem. Phys., 18, 17489–17496, https://doi.org/10.5194/acp-18-17489-2018, https://doi.org/10.5194/acp-18-17489-2018, 2018
Eloise A. Marais, Daniel J. Jacob, Sungyeon Choi, Joanna Joiner, Maria Belmonte-Rivas, Ronald C. Cohen, Steffen Beirle, Lee T. Murray, Luke D. Schiferl, Viral Shah, and Lyatt Jaeglé
Atmos. Chem. Phys., 18, 17017–17027, https://doi.org/10.5194/acp-18-17017-2018, https://doi.org/10.5194/acp-18-17017-2018, 2018
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We intercompare two new products of global upper tropospheric nitrogen dioxide (NO2) retrieved from the Ozone Monitoring Instrument (OMI). We evaluate these products with aircraft observations from NASA DC8 aircraft campaigns and interpret the useful information these products can provide about nitrogen oxides (NOx) in the global upper troposphere using the GEOS-Chem chemical transport model.
Jian-Xiong Sheng, Daniel J. Jacob, Joannes D. Maasakkers, Yuzhong Zhang, and Melissa P. Sulprizio
Atmos. Meas. Tech., 11, 6379–6388, https://doi.org/10.5194/amt-11-6379-2018, https://doi.org/10.5194/amt-11-6379-2018, 2018
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We conduct Observing System Simulation Experiments to compare the ability of future satellite measurements of atmospheric methane columns for constraining methane emissions at the 25 km scale. We find that the geostationary instruments can do much better than TROPOMI and are less sensitive to cloud cover. GeoCARB observing twice a day would provide 70 % of the information from the nominal GEO-CAPE mission considered by NASA in response to the Decadal Survey of the US National Research Council.
Daniel H. Cusworth, Daniel J. Jacob, Jian-Xiong Sheng, Joshua Benmergui, Alexander J. Turner, Jeremy Brandman, Laurent White, and Cynthia A. Randles
Atmos. Chem. Phys., 18, 16885–16896, https://doi.org/10.5194/acp-18-16885-2018, https://doi.org/10.5194/acp-18-16885-2018, 2018
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Methane emissions from oil/gas fields originate from a large number of small and densely clustered point sources. We examine the potential of recently launched or planned satellites to locate these high-mode emitters through measurements of atmospheric methane. We find that the recently launched TROPOMI and the planned GeoCARB instruments are successful at locating high-emitting sources for fields of 20-50 emitters within the 50 × 50 km2 geographic domain but are unsuccessful for denser fields.
Lu Hu, Christoph A. Keller, Michael S. Long, Tomás Sherwen, Benjamin Auer, Arlindo Da Silva, Jon E. Nielsen, Steven Pawson, Matthew A. Thompson, Atanas L. Trayanov, Katherine R. Travis, Stuart K. Grange, Mat J. Evans, and Daniel J. Jacob
Geosci. Model Dev., 11, 4603–4620, https://doi.org/10.5194/gmd-11-4603-2018, https://doi.org/10.5194/gmd-11-4603-2018, 2018
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We present a full-year online global simulation of tropospheric chemistry at 12.5 km resolution. To the best of our knowledge, such a resolution in a state-of-the-science global simulation of tropospheric chemistry is unprecedented. This simulation will serve as the Nature Run for observing system simulation experiments to support the future geostationary satellite constellation for tropospheric chemistry, and can also be used for various air quality applications.
Yuzhong Zhang, Daniel J. Jacob, Joannes D. Maasakkers, Melissa P. Sulprizio, Jian-Xiong Sheng, Ritesh Gautam, and John Worden
Atmos. Chem. Phys., 18, 15959–15973, https://doi.org/10.5194/acp-18-15959-2018, https://doi.org/10.5194/acp-18-15959-2018, 2018
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We assess the potential of using satellite observations of atmospheric methane to monitor global mean tropospheric OH concentration, a key parameter for the oxidizing power of the atmosphere.
Xinyi Dong, Joshua S. Fu, Qingzhao Zhu, Jian Sun, Jiani Tan, Terry Keating, Takashi Sekiya, Kengo Sudo, Louisa Emmons, Simone Tilmes, Jan Eiof Jonson, Michael Schulz, Huisheng Bian, Mian Chin, Yanko Davila, Daven Henze, Toshihiko Takemura, Anna Maria Katarina Benedictow, and Kan Huang
Atmos. Chem. Phys., 18, 15581–15600, https://doi.org/10.5194/acp-18-15581-2018, https://doi.org/10.5194/acp-18-15581-2018, 2018
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We have applied the HTAP phase II multi-model data to investigate the long-range transport impacts on surface concentration and column density of PM from Europe and Russia, Belarus, and Ukraine to eastern Asia, with a special focus on the long-range transport contribution during haze episodes in China. We found that long-range transport plays a more important role in elevating the background concentration of surface PM during the haze days.
Daniel J. Varon, Daniel J. Jacob, Jason McKeever, Dylan Jervis, Berke O. A. Durak, Yan Xia, and Yi Huang
Atmos. Meas. Tech., 11, 5673–5686, https://doi.org/10.5194/amt-11-5673-2018, https://doi.org/10.5194/amt-11-5673-2018, 2018
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Methane is a powerful greenhouse gas emitted from numerous human activities. Space-based observation of point sources would be a cost-effective monitoring solution, but the resolution of most current and planned methane-observing satellites is too coarse to resolve individual emitters. We simulate fine-resolution (50 m) satellite observations of methane plumes as would be measured by GHGSat (to be launched in 2019) and show that such data can usefully quantify large methane point sources.
Benjamin Brown-Steiner, Noelle E. Selin, Ronald Prinn, Simone Tilmes, Louisa Emmons, Jean-François Lamarque, and Philip Cameron-Smith
Geosci. Model Dev., 11, 4155–4174, https://doi.org/10.5194/gmd-11-4155-2018, https://doi.org/10.5194/gmd-11-4155-2018, 2018
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We conduct three simulations of atmospheric chemistry using chemical mechanisms of different levels of complexity and compare their results to observations. We explore situations in which the simplified mechanisms match the output of the most complex mechanism, as well as when they diverge. We investigate how concurrent utilization of chemical mechanisms of different complexities can further our atmospheric-chemistry understanding at various scales and give some strategies for future research.
Jan Eiof Jonson, Michael Schulz, Louisa Emmons, Johannes Flemming, Daven Henze, Kengo Sudo, Marianne Tronstad Lund, Meiyun Lin, Anna Benedictow, Brigitte Koffi, Frank Dentener, Terry Keating, Rigel Kivi, and Yanko Davila
Atmos. Chem. Phys., 18, 13655–13672, https://doi.org/10.5194/acp-18-13655-2018, https://doi.org/10.5194/acp-18-13655-2018, 2018
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Focusing on Europe, this HTAP 2 study computes ozone in several global models when reducing anthropogenic emissions by 20 % in different world regions. The differences in model results are explored
by use of a novel stepwise approach combining a tracer, CO and ozone. For ozone the contributions from the rest of the world are larger than from Europe, with the largest contributions from North America and eastern Asia. Contributions do, however, depend on the choice of ozone metric.
Jian-Xiong Sheng, Daniel J. Jacob, Alexander J. Turner, Joannes D. Maasakkers, Joshua Benmergui, A. Anthony Bloom, Claudia Arndt, Ritesh Gautam, Daniel Zavala-Araiza, Hartmut Boesch, and Robert J. Parker
Atmos. Chem. Phys., 18, 12257–12267, https://doi.org/10.5194/acp-18-12257-2018, https://doi.org/10.5194/acp-18-12257-2018, 2018
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Analysis of 7 years (2010–2016) of GOSAT methane trends over Canada, the contiguous US, and Mexico suggests that US methane emissions increased by 2.5 ± 1.4 % a−1 over the 7-year period, with contributions from both oil–gas systems and livestock in the Midwest. Mexican emissions show a decrease that can be attributed to a decreasing cattle population. Canadian emissions show year-to-year variability driven by wetland emissions and correlated with wetland areal extent.
Jiani Tan, Joshua S. Fu, Frank Dentener, Jian Sun, Louisa Emmons, Simone Tilmes, Johannes Flemming, Toshihiko Takemura, Huisheng Bian, Qingzhao Zhu, Cheng-En Yang, and Terry Keating
Atmos. Chem. Phys., 18, 12223–12240, https://doi.org/10.5194/acp-18-12223-2018, https://doi.org/10.5194/acp-18-12223-2018, 2018
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Have contributions of hemispheric air pollution to deposition at global scale been overlooked in the past years? How do we assess the critical load for the acid deposition when we look for the demand of forest and crop? This study highlights the significant impact of hemispheric transport on deposition in coastal regions, open ocean and low-emission regions. Further research is proposed for improving ecosystem and human health in these regions, with regards to the enhanced hemispheric transport.
Prasad Kasibhatla, Tomás Sherwen, Mathew J. Evans, Lucy J. Carpenter, Chris Reed, Becky Alexander, Qianjie Chen, Melissa P. Sulprizio, James D. Lee, Katie A. Read, William Bloss, Leigh R. Crilley, William C. Keene, Alexander A. P. Pszenny, and Alma Hodzic
Atmos. Chem. Phys., 18, 11185–11203, https://doi.org/10.5194/acp-18-11185-2018, https://doi.org/10.5194/acp-18-11185-2018, 2018
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Recent measurements of NOx and HONO suggest that photolysis of particulate nitrate in sea-salt aerosols is important in terms of marine boundary layer oxidant chemistry. We present the first global-scale assessment of the significance of this new chemical pathway for NOx, O3, and OH in the marine boundary layer. We also present a preliminary assessment of the potential impact of photolysis of particulate nitrate associated with other aerosol types on continental boundary layer chemistry.
Sebastian D. Eastham, Michael S. Long, Christoph A. Keller, Elizabeth Lundgren, Robert M. Yantosca, Jiawei Zhuang, Chi Li, Colin J. Lee, Matthew Yannetti, Benjamin M. Auer, Thomas L. Clune, Jules Kouatchou, William M. Putman, Matthew A. Thompson, Atanas L. Trayanov, Andrea M. Molod, Randall V. Martin, and Daniel J. Jacob
Geosci. Model Dev., 11, 2941–2953, https://doi.org/10.5194/gmd-11-2941-2018, https://doi.org/10.5194/gmd-11-2941-2018, 2018
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Global atmospheric chemical transport models are crucial tools in atmospheric science, used to address problems ranging from climate change to acid rain. GEOS-Chem High Performance (GCHP) is a new implementation of the widely used GEOS-Chem model, designed for massively parallel architectures. GCHP v11-02c is shown to be highly scalable from 6 to over 500 cores, enabling the routine simulation of global atmospheric chemistry from the surface to the stratopause at resolutions of ~50 km or finer.
Ciao-Kai Liang, J. Jason West, Raquel A. Silva, Huisheng Bian, Mian Chin, Yanko Davila, Frank J. Dentener, Louisa Emmons, Johannes Flemming, Gerd Folberth, Daven Henze, Ulas Im, Jan Eiof Jonson, Terry J. Keating, Tom Kucsera, Allen Lenzen, Meiyun Lin, Marianne Tronstad Lund, Xiaohua Pan, Rokjin J. Park, R. Bradley Pierce, Takashi Sekiya, Kengo Sudo, and Toshihiko Takemura
Atmos. Chem. Phys., 18, 10497–10520, https://doi.org/10.5194/acp-18-10497-2018, https://doi.org/10.5194/acp-18-10497-2018, 2018
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Emissions from one continent affect air quality and health elsewhere. Here we quantify the effects of intercontinental PM2.5 and ozone transport on human health using a new multi-model ensemble, evaluating the health effects of emissions from six world regions and three emission source sectors. Emissions from one region have significant health impacts outside of that source region; similarly, foreign emissions contribute significantly to air-pollution-related deaths in several world regions.
Steven T. Turnock, Oliver Wild, Frank J. Dentener, Yanko Davila, Louisa K. Emmons, Johannes Flemming, Gerd A. Folberth, Daven K. Henze, Jan E. Jonson, Terry J. Keating, Sudo Kengo, Meiyun Lin, Marianne Lund, Simone Tilmes, and Fiona M. O'Connor
Atmos. Chem. Phys., 18, 8953–8978, https://doi.org/10.5194/acp-18-8953-2018, https://doi.org/10.5194/acp-18-8953-2018, 2018
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A simple parameterisation was developed in this study to provide a rapid assessment of the impacts and uncertainties associated with future emission control strategies by predicting changes to surface ozone air quality and near-term climate forcing of ozone. Future emissions scenarios based on currently implemented legislation are shown to worsen surface ozone air quality and enhance near-term climate warming, with changes in methane becoming increasingly important in the future.
Benjamin Brown-Steiner, Noelle E. Selin, Ronald G. Prinn, Erwan Monier, Simone Tilmes, Louisa Emmons, and Fernando Garcia-Menendez
Atmos. Chem. Phys., 18, 8373–8388, https://doi.org/10.5194/acp-18-8373-2018, https://doi.org/10.5194/acp-18-8373-2018, 2018
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Detecting signals in observations and simulations of atmospheric chemistry is difficult due to the underlying variability in the chemistry, meteorology, and climatology. Here we examine the scale dependence of ozone variability and explore strategies for reducing or averaging this variability and thereby enhancing ozone signal detection capabilities. We find that 10–15 years of temporal averaging, and some level of spatial averaging, reduces the risk of overconfidence in ozone signals.
Alexander J. Turner, Daniel J. Jacob, Joshua Benmergui, Jeremy Brandman, Laurent White, and Cynthia A. Randles
Atmos. Chem. Phys., 18, 8265–8278, https://doi.org/10.5194/acp-18-8265-2018, https://doi.org/10.5194/acp-18-8265-2018, 2018
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We conduct a 1-week WRF-STILT simulation to generate methane column footprints at 1.3 km spatial resolution and hourly temporal resolution over the Barnett Shale. We find that a week of TROPOMI observations should provide regional (~30 km) information on temporally invariant sources and GeoCARB should provide information on temporally invariant sources at 2–7 km spatial resolution. An instrument precision better than 6 ppb is an important threshold for achieving fine resolution of emissions.
Jiani Tan, Joshua S. Fu, Frank Dentener, Jian Sun, Louisa Emmons, Simone Tilmes, Kengo Sudo, Johannes Flemming, Jan Eiof Jonson, Sylvie Gravel, Huisheng Bian, Yanko Davila, Daven K. Henze, Marianne T. Lund, Tom Kucsera, Toshihiko Takemura, and Terry Keating
Atmos. Chem. Phys., 18, 6847–6866, https://doi.org/10.5194/acp-18-6847-2018, https://doi.org/10.5194/acp-18-6847-2018, 2018
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We study the distributions of sulfur and nitrogen deposition, which are associated with current environmental issues such as formation of acid rain and ecosystem eutrophication and result in widespread problems such as loss of environmental diversity, harming the crop yield and even food insecurity. According to our study, both the amount and distribution of sulfate and nitrogen deposition have changed significantly in the last decade, particularly in East Asia, South Asia and Southeast Asia.
Jian-Xiong Sheng, Daniel J. Jacob, Alexander J. Turner, Joannes D. Maasakkers, Melissa P. Sulprizio, A. Anthony Bloom, Arlyn E. Andrews, and Debra Wunch
Atmos. Chem. Phys., 18, 6483–6491, https://doi.org/10.5194/acp-18-6483-2018, https://doi.org/10.5194/acp-18-6483-2018, 2018
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We use observations of boundary layer methane from the SEAC4RS aircraft campaign over the Southeast US to estimate methane emissions in that region. Our results suggest that the EPA inventory is regionally unbiased but there are large local biases, suggesting variable emission factors. Our results also suggest that the choice of landcover map is the dominant source of error for wetland emission estimates.
Jiawei Zhuang, Daniel J. Jacob, and Sebastian D. Eastham
Atmos. Chem. Phys., 18, 6039–6055, https://doi.org/10.5194/acp-18-6039-2018, https://doi.org/10.5194/acp-18-6039-2018, 2018
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Our work explains why current model simulations are unable to capture the intercontinental influences of pollution plumes that are often observed over some regions like California. Due to inadequate vertical grid resolution in these models, the plumes get diffused too rapidly during intercontinental transport. Increasing the vertical grid resolution greatly improves the simulation of plumes and considerably increases the estimate of local surface pollution influence.
Jennifer Kaiser, Daniel J. Jacob, Lei Zhu, Katherine R. Travis, Jenny A. Fisher, Gonzalo González Abad, Lin Zhang, Xuesong Zhang, Alan Fried, John D. Crounse, Jason M. St. Clair, and Armin Wisthaler
Atmos. Chem. Phys., 18, 5483–5497, https://doi.org/10.5194/acp-18-5483-2018, https://doi.org/10.5194/acp-18-5483-2018, 2018
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Isoprene emissions from vegetation have a large effect on atmospheric chemistry and air quality. Here we use the adjoint of GEOS-Chem in an inversion of OMI formaldehyde observations to produce top-down estimates of isoprene emissions in the southeast US during the summer of 2013. We find that MEGAN v2.1 is biased high on average by 40 %. Our downward correction of isoprene emissions leads to a small reduction in modeled surface O3 and decreases the contribution of isoprene to organic aerosol.
Karen Yu, Christoph A. Keller, Daniel J. Jacob, Andrea M. Molod, Sebastian D. Eastham, and Michael S. Long
Geosci. Model Dev., 11, 305–319, https://doi.org/10.5194/gmd-11-305-2018, https://doi.org/10.5194/gmd-11-305-2018, 2018
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Global simulations of atmospheric chemistry are generally conducted with off-line chemical transport models (CTMs) driven by archived meteorological data from general circulation models (GCMs). The off-line approach has the advantages of simplicity and expediency, but it is unable to reproduce the GCM transport exactly. We investigate the cascade of errors associated with the off-line approach using the GEOS-5 GCM and GEOS-Chem CTM and discuss improvements in the use of archived meteorology.
Theodore K. Koenig, Rainer Volkamer, Sunil Baidar, Barbara Dix, Siyuan Wang, Daniel C. Anderson, Ross J. Salawitch, Pamela A. Wales, Carlos A. Cuevas, Rafael P. Fernandez, Alfonso Saiz-Lopez, Mathew J. Evans, Tomás Sherwen, Daniel J. Jacob, Johan Schmidt, Douglas Kinnison, Jean-François Lamarque, Eric C. Apel, James C. Bresch, Teresa Campos, Frank M. Flocke, Samuel R. Hall, Shawn B. Honomichl, Rebecca Hornbrook, Jørgen B. Jensen, Richard Lueb, Denise D. Montzka, Laura L. Pan, J. Michael Reeves, Sue M. Schauffler, Kirk Ullmann, Andrew J. Weinheimer, Elliot L. Atlas, Valeria Donets, Maria A. Navarro, Daniel Riemer, Nicola J. Blake, Dexian Chen, L. Gregory Huey, David J. Tanner, Thomas F. Hanisco, and Glenn M. Wolfe
Atmos. Chem. Phys., 17, 15245–15270, https://doi.org/10.5194/acp-17-15245-2017, https://doi.org/10.5194/acp-17-15245-2017, 2017
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Tropospheric inorganic bromine (BrO and Bry) shows a C-shaped profile over the tropical western Pacific Ocean, and supports previous speculation that marine convection is a source for inorganic bromine from sea salt to the upper troposphere. The Bry profile in the tropical tropopause layer (TTL) is complex, suggesting that the total Bry budget in the TTL is not closed without considering aerosol bromide. The implications for atmospheric composition and bromine sources are discussed.
Youhua Tang, Mariusz Pagowski, Tianfeng Chai, Li Pan, Pius Lee, Barry Baker, Rajesh Kumar, Luca Delle Monache, Daniel Tong, and Hyun-Cheol Kim
Geosci. Model Dev., 10, 4743–4758, https://doi.org/10.5194/gmd-10-4743-2017, https://doi.org/10.5194/gmd-10-4743-2017, 2017
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In order to evaluate the data assimilation tools for regional real-time PM2.5 forecasts, we applied a 3D-Var assimilation tool to adjust the aerosol initial condition by assimilating satellite-retrieved aerosol optical depth and surface PM2.5 observations for a regional air quality model, which is compared to another assimilation method, optimal interpolation. We discuss the pros and cons of these two assimilation methods based on the comparison of their 1-month four-cycles-per-day runs.
Li Pan, Hyun Cheol Kim, Pius Lee, Rick Saylor, YouHua Tang, Daniel Tong, Barry Baker, Shobha Kondragunta, Chuanyu Xu, Mark G. Ruminski, Weiwei Chen, Jeff Mcqueen, and Ivanka Stajner
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-207, https://doi.org/10.5194/gmd-2017-207, 2017
Revised manuscript not accepted
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In this study, a system accounting for fire emissions in a chemical transport model is described. The focus of this work is to qualitatively evaluate the system's capability to capture fire signals identified by multiple observation data sets. We discuss how to use observational data correctly to filter out fire signals and synergistic use of multiple data sets together. We also address the limitations of each of the observation data sets and of the evaluation methods.
Jihyun Han, Meehye Lee, Xiaona Shang, Gangwoong Lee, and Louisa K. Emmons
Atmos. Chem. Phys., 17, 10619–10631, https://doi.org/10.5194/acp-17-10619-2017, https://doi.org/10.5194/acp-17-10619-2017, 2017
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Peroxyacetyl nitrate (PAN) was first measured at Gosan Climate Observatory during the fall of 2010, when PAN was better correlated with PM10 than with O3. In particular, PAN and O3 concentrations were greatly elevated in haze and the Beijing plume and much higher than those from model simulation. This study highlights the decoupling of PAN from O3 in Chinese outflows and suggests PAN as a potential indicator of overall aerosol formation in aged air masses impacted by biomass burning.
Katherine R. Travis, Daniel J. Jacob, Christoph A. Keller, Shi Kuang, Jintai Lin, Michael J. Newchurch, and Anne M. Thompson
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-596, https://doi.org/10.5194/acp-2017-596, 2017
Preprint retracted
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Models severely overestimate surface ozone in the Southeast US during summertime which has implications for the design of air quality regulations. We use a model (GEOS-Chem) to interpret ozone observations from a suite of observations taken during August–September 2013. The model is unbiased relative to observations below 1 km but is biased high at the surface. We attribute this bias to model representation error, an underestimate in low-cloud, and insufficient treatment of vertical mixing.
Christopher Chan Miller, Daniel J. Jacob, Eloise A. Marais, Karen Yu, Katherine R. Travis, Patrick S. Kim, Jenny A. Fisher, Lei Zhu, Glenn M. Wolfe, Thomas F. Hanisco, Frank N. Keutsch, Jennifer Kaiser, Kyung-Eun Min, Steven S. Brown, Rebecca A. Washenfelder, Gonzalo González Abad, and Kelly Chance
Atmos. Chem. Phys., 17, 8725–8738, https://doi.org/10.5194/acp-17-8725-2017, https://doi.org/10.5194/acp-17-8725-2017, 2017
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The use of satellite glyoxal observations for estimating isoprene emissions has been limited by knowledge of the glyoxal yield from isoprene. We use SENEX aircraft observations over the southeast US to evaluate glyoxal yields from isoprene in a 3-D atmospheric model. The SENEX observations support a pathway for glyoxal formation in pristine regions that we propose here, which may have implications for improving isoprene emissions estimates from upcoming high-resolution geostationary satellites.
A. Anthony Bloom, Kevin W. Bowman, Meemong Lee, Alexander J. Turner, Ronny Schroeder, John R. Worden, Richard Weidner, Kyle C. McDonald, and Daniel J. Jacob
Geosci. Model Dev., 10, 2141–2156, https://doi.org/10.5194/gmd-10-2141-2017, https://doi.org/10.5194/gmd-10-2141-2017, 2017
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Wetland emissions are a principal source of uncertainty in the global atmospheric methane budget due to poor knowledge of wetland processes. We construct a wetland methane emission and uncertainty dataset for use in global atmospheric methane models. Our wetland model ensemble is based on static wetland maps, satellite-derived inundation and carbon cycle models. The ensemble performs favourably against regional flux estimates and atmospheric methane measurements relative to previous studies.
Hannah M. Horowitz, Daniel J. Jacob, Yanxu Zhang, Theodore S. Dibble, Franz Slemr, Helen M. Amos, Johan A. Schmidt, Elizabeth S. Corbitt, Eloïse A. Marais, and Elsie M. Sunderland
Atmos. Chem. Phys., 17, 6353–6371, https://doi.org/10.5194/acp-17-6353-2017, https://doi.org/10.5194/acp-17-6353-2017, 2017
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Mercury is a toxic, global pollutant released to the air from human activities like coal burning. Chemical reactions in air determine how far mercury is transported before it is deposited to the environment, where it may be converted to a form that accumulates in fish. We use a 3-D atmospheric model to evaluate a new set of chemical reactions and its effects on mercury deposition. We find it is consistent with observations and leads to increased deposition to oceans, especially in the tropics.
Min Huang, Gregory R. Carmichael, R. Bradley Pierce, Duseong S. Jo, Rokjin J. Park, Johannes Flemming, Louisa K. Emmons, Kevin W. Bowman, Daven K. Henze, Yanko Davila, Kengo Sudo, Jan Eiof Jonson, Marianne Tronstad Lund, Greet Janssens-Maenhout, Frank J. Dentener, Terry J. Keating, Hilke Oetjen, and Vivienne H. Payne
Atmos. Chem. Phys., 17, 5721–5750, https://doi.org/10.5194/acp-17-5721-2017, https://doi.org/10.5194/acp-17-5721-2017, 2017
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In support of the HTAP phase 2 experiment, we conducted a number of regional-scale Sulfur Transport and dEposition Model base and sensitivity simulations over North America during May–June 2010. The STEM chemical boundary conditions were downscaled from three (GEOS-Chem, RAQMS, and ECMWF C-IFS) global chemical transport models' simulations. Analyses were performed on large spatial–temporal scales relative to HTAP1 and also on subcontinental and event scales including the use of satellite data.
Rachel F. Silvern, Daniel J. Jacob, Patrick S. Kim, Eloise A. Marais, Jay R. Turner, Pedro Campuzano-Jost, and Jose L. Jimenez
Atmos. Chem. Phys., 17, 5107–5118, https://doi.org/10.5194/acp-17-5107-2017, https://doi.org/10.5194/acp-17-5107-2017, 2017
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We identify a fundamental discrepancy between thermodynamic equilibrium theory and observations of inorganic aerosol composition in the eastern US in summer that shows low ammonium sulfate aerosol ratios. In addition, from 2003 to 2013, while SO2 emissions have declined due to US emission controls, aerosols have become more acidic in the southeastern US. To explain these observations, we suggest that the large and increasing source of organic aerosol may be affecting thermodynamic equilibrium.
Sebastian D. Eastham and Daniel J. Jacob
Atmos. Chem. Phys., 17, 2543–2553, https://doi.org/10.5194/acp-17-2543-2017, https://doi.org/10.5194/acp-17-2543-2017, 2017
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Intercontinental atmospheric transport can disrupt local chemistry and cause air quality issues thousands of kilometers from the source, complicating correct attribution of air quality exceedances. This transport occurs in long, thin plumes which current-generation models consistently fail to reproduce. Our study investigates the cause of this failure, finding that greater vertical resolution than is currently available is required to reliably resolve the plumes and their effects.
Daniel J. Jacob, Alexander J. Turner, Joannes D. Maasakkers, Jianxiong Sheng, Kang Sun, Xiong Liu, Kelly Chance, Ilse Aben, Jason McKeever, and Christian Frankenberg
Atmos. Chem. Phys., 16, 14371–14396, https://doi.org/10.5194/acp-16-14371-2016, https://doi.org/10.5194/acp-16-14371-2016, 2016
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Methane is a greenhouse gas emitted by a range of natural and anthropogenic sources. Atmospheric methane has been measured continuously from space since 2003, and new instruments are planned to launch in the near future that will greatly expand the capabilities of space-based observations. We review the value of current, future, and proposed satellite observations to better quantify methane emissions from the global scale down to the scale of point sources.
Katherine R. Travis, Daniel J. Jacob, Jenny A. Fisher, Patrick S. Kim, Eloise A. Marais, Lei Zhu, Karen Yu, Christopher C. Miller, Robert M. Yantosca, Melissa P. Sulprizio, Anne M. Thompson, Paul O. Wennberg, John D. Crounse, Jason M. St. Clair, Ronald C. Cohen, Joshua L. Laughner, Jack E. Dibb, Samuel R. Hall, Kirk Ullmann, Glenn M. Wolfe, Illana B. Pollack, Jeff Peischl, Jonathan A. Neuman, and Xianliang Zhou
Atmos. Chem. Phys., 16, 13561–13577, https://doi.org/10.5194/acp-16-13561-2016, https://doi.org/10.5194/acp-16-13561-2016, 2016
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Ground-level ozone pollution in the Southeast US involves complex chemistry driven by anthropogenic emissions of nitrogen oxides (NOx) and biogenic emissions of isoprene. We find that US NOx emissions are overestimated nationally by as much as 50 % and that reducing model emissions by this amount results in good agreement with SEAC4RS aircraft measurements in August and September 2013. Observations of nitrate wet deposition fluxes and satellite NO2 columns further support this result.
Lei Zhu, Daniel J. Jacob, Patrick S. Kim, Jenny A. Fisher, Karen Yu, Katherine R. Travis, Loretta J. Mickley, Robert M. Yantosca, Melissa P. Sulprizio, Isabelle De Smedt, Gonzalo González Abad, Kelly Chance, Can Li, Richard Ferrare, Alan Fried, Johnathan W. Hair, Thomas F. Hanisco, Dirk Richter, Amy Jo Scarino, James Walega, Petter Weibring, and Glenn M. Wolfe
Atmos. Chem. Phys., 16, 13477–13490, https://doi.org/10.5194/acp-16-13477-2016, https://doi.org/10.5194/acp-16-13477-2016, 2016
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HCHO column data are widely used as a proxy for VOCs emissions, but validation of the data has been extremely limited. We use accurate aircraft observations to validate and intercompare 6 HCHO retrievals with GEOS-Chem as the intercomparison platform. Retrievals are interconsistent in spatial variability over the SE US and in daily variability, but are biased low by 20–51 %. Our work supports the use of HCHO column as a quantitative proxy for isoprene emission after correction of the low bias.
Camilla Weum Stjern, Bjørn Hallvard Samset, Gunnar Myhre, Huisheng Bian, Mian Chin, Yanko Davila, Frank Dentener, Louisa Emmons, Johannes Flemming, Amund Søvde Haslerud, Daven Henze, Jan Eiof Jonson, Tom Kucsera, Marianne Tronstad Lund, Michael Schulz, Kengo Sudo, Toshihiko Takemura, and Simone Tilmes
Atmos. Chem. Phys., 16, 13579–13599, https://doi.org/10.5194/acp-16-13579-2016, https://doi.org/10.5194/acp-16-13579-2016, 2016
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Air pollution can reach distant regions through intercontinental transport. Here we first present results from the Hemispheric Transport of Air Pollution Phase 2 exercise, where many models performed the same set of coordinated emission-reduction experiments. We find that mitigations have considerable extra-regional effects, and show that this is particularly true for black carbon emissions, as long-range transport elevates aerosols to higher levels where their radiative influence is stronger.
Tomás Sherwen, Johan A. Schmidt, Mat J. Evans, Lucy J. Carpenter, Katja Großmann, Sebastian D. Eastham, Daniel J. Jacob, Barbara Dix, Theodore K. Koenig, Roman Sinreich, Ivan Ortega, Rainer Volkamer, Alfonso Saiz-Lopez, Cristina Prados-Roman, Anoop S. Mahajan, and Carlos Ordóñez
Atmos. Chem. Phys., 16, 12239–12271, https://doi.org/10.5194/acp-16-12239-2016, https://doi.org/10.5194/acp-16-12239-2016, 2016
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We present a simulation of tropospheric Cl, Br, I chemistry within the GEOS-Chem CTM. We find a decrease in tropospheric ozone burden of 18.6 % and a 8.2 % decrease in global mean OH concentrations. Cl oxidation of some VOCs range from 15 to 27 % of the total loss. Bromine plays a small role in oxidising oVOCs. Surface ozone, ozone sondes, and methane lifetime are in general improved by the inclusion of halogens. We argue that simulated bromine and chlorine represent a lower limit.
Sarah A. Strode, Helen M. Worden, Megan Damon, Anne R. Douglass, Bryan N. Duncan, Louisa K. Emmons, Jean-Francois Lamarque, Michael Manyin, Luke D. Oman, Jose M. Rodriguez, Susan E. Strahan, and Simone Tilmes
Atmos. Chem. Phys., 16, 7285–7294, https://doi.org/10.5194/acp-16-7285-2016, https://doi.org/10.5194/acp-16-7285-2016, 2016
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We use global models to interpret trends in MOPITT observations of CO. Simulations with time-dependent emissions reproduce the observed trends over the eastern USA and Europe, suggesting that the emissions are reasonable for these regions. The simulations produce a positive trend over eastern China, contrary to the observed negative trend. This may indicate that the assumed emission trend over China is too positive. However, large variability in the overhead ozone column also contributes.
Simone Tilmes, Jean-Francois Lamarque, Louisa K. Emmons, Doug E. Kinnison, Dan Marsh, Rolando R. Garcia, Anne K. Smith, Ryan R. Neely, Andrew Conley, Francis Vitt, Maria Val Martin, Hiroshi Tanimoto, Isobel Simpson, Don R. Blake, and Nicola Blake
Geosci. Model Dev., 9, 1853–1890, https://doi.org/10.5194/gmd-9-1853-2016, https://doi.org/10.5194/gmd-9-1853-2016, 2016
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The state of the art Community Earth System Model, CESM1 CAM4-chem has been used to perform reference and sensitivity simulations as part of the Chemistry Climate Model Initiative (CCMI). Specifics of the model and details regarding the setup of the simulations are described. In additions, the main behavior of the model, including selected chemical species have been evaluated with climatological datasets. This paper is therefore a references for studies that use the provided model results.
Jenny A. Fisher, Daniel J. Jacob, Katherine R. Travis, Patrick S. Kim, Eloise A. Marais, Christopher Chan Miller, Karen Yu, Lei Zhu, Robert M. Yantosca, Melissa P. Sulprizio, Jingqiu Mao, Paul O. Wennberg, John D. Crounse, Alex P. Teng, Tran B. Nguyen, Jason M. St. Clair, Ronald C. Cohen, Paul Romer, Benjamin A. Nault, Paul J. Wooldridge, Jose L. Jimenez, Pedro Campuzano-Jost, Douglas A. Day, Weiwei Hu, Paul B. Shepson, Fulizi Xiong, Donald R. Blake, Allen H. Goldstein, Pawel K. Misztal, Thomas F. Hanisco, Glenn M. Wolfe, Thomas B. Ryerson, Armin Wisthaler, and Tomas Mikoviny
Atmos. Chem. Phys., 16, 5969–5991, https://doi.org/10.5194/acp-16-5969-2016, https://doi.org/10.5194/acp-16-5969-2016, 2016
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We use new airborne and ground-based observations from two summer 2013 campaigns in the southeastern US, interpreted with a chemical transport model, to understand the impact of isoprene and monoterpene chemistry on the atmospheric NOx budget via production of organic nitrates (RONO2). We find that a diversity of species contribute to observed RONO2. Our work implies that the NOx sink to RONO2 production is only sensitive to NOx emissions in regions where they are already low.
Catherine Wespes, Daniel Hurtmans, Louisa K. Emmons, Sarah Safieddine, Cathy Clerbaux, David P. Edwards, and Pierre-François Coheur
Atmos. Chem. Phys., 16, 5721–5743, https://doi.org/10.5194/acp-16-5721-2016, https://doi.org/10.5194/acp-16-5721-2016, 2016
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In this paper, we assess how daily ozone measurements from the Infrared Atmospheric Sounding Interferometer (IASI/MetOp) can contribute to the analyses of the processes driving O3 variability in the troposphere and the stratosphere with a set of parameterized geophysical variables, and we demonstrate the added value of IASI exceptional frequency sampling for monitoring medium- to long-term changes in global ozone concentrations in the future.
Christopher Chan Miller, Daniel J. Jacob, Gonzalo González Abad, and Kelly Chance
Atmos. Chem. Phys., 16, 4631–4639, https://doi.org/10.5194/acp-16-4631-2016, https://doi.org/10.5194/acp-16-4631-2016, 2016
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Volatile organic compounds (VOCs) are important precursors for photochemical smog.
Glyoxal is an organic compound produced in the atmosphere from reactions of larger VOCs. OMI satellite observations of glyoxal show a large hotspot over the Pearl River delta. The hotspot can be explained by industrial paint and solvent emissions of aromatic VOCs. Our work shows OMI observations are consistent with current VOC emissions estimates, whereas previous work has suggested large underestimates.
Karen Yu, Daniel J. Jacob, Jenny A. Fisher, Patrick S. Kim, Eloise A. Marais, Christopher C. Miller, Katherine R. Travis, Lei Zhu, Robert M. Yantosca, Melissa P. Sulprizio, Ron C. Cohen, Jack E. Dibb, Alan Fried, Tomas Mikoviny, Thomas B. Ryerson, Paul O. Wennberg, and Armin Wisthaler
Atmos. Chem. Phys., 16, 4369–4378, https://doi.org/10.5194/acp-16-4369-2016, https://doi.org/10.5194/acp-16-4369-2016, 2016
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Increasing the spatial resolution of a chemical transport model may improve simulations but can be computationally expensive. Using observations from the SEAC4RS aircraft campaign, we find that at higher spatial resolutions, models are better able to simulate the chemical pathways of ozone precursors, but the overall effect on regional mean concentrations is small. This implies that for continental boundary layer applications, coarse resolution models are adequate.
E. A. Marais, D. J. Jacob, J. L. Jimenez, P. Campuzano-Jost, D. A. Day, W. Hu, J. Krechmer, L. Zhu, P. S. Kim, C. C. Miller, J. A. Fisher, K. Travis, K. Yu, T. F. Hanisco, G. M. Wolfe, H. L. Arkinson, H. O. T. Pye, K. D. Froyd, J. Liao, and V. F. McNeill
Atmos. Chem. Phys., 16, 1603–1618, https://doi.org/10.5194/acp-16-1603-2016, https://doi.org/10.5194/acp-16-1603-2016, 2016
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Isoprene secondary organic aerosol (SOA) is a dominant aerosol component in the southeast US, but models routinely underestimate isoprene SOA with traditional schemes based on chamber studies operated under conditions not representative of isoprene-emitting forests. We develop a new irreversible uptake mechanism to reproduce isoprene SOA yields (3.3 %) and composition, and find a factor of 2 co-benefit of SO2 emission controls on reducing sulfate and organic aerosol in the southeast US.
H.-M. Lee, F. Paulot, D. K. Henze, K. Travis, D. J. Jacob, L. H. Pardo, and B. A. Schichtel
Atmos. Chem. Phys., 16, 525–540, https://doi.org/10.5194/acp-16-525-2016, https://doi.org/10.5194/acp-16-525-2016, 2016
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Sources of nitrogen deposition (Ndep) in Federal Class I areas in the US are investigated, identifying unique features in contributions from different species, sectors and locations. Ndep in many parks is impacted by emissions several hundred km away; the role of oxidized vs reduced sources varies regionally. Emissions reductions in the western US most effectively reduce the extent of areas in critical load exceedance, while reductions in the east most effectively reduce exceedance magnitudes.
J. He, Y. Zhang, S. Tilmes, L. Emmons, J.-F. Lamarque, T. Glotfelty, A. Hodzic, and F. Vitt
Geosci. Model Dev., 8, 3999–4025, https://doi.org/10.5194/gmd-8-3999-2015, https://doi.org/10.5194/gmd-8-3999-2015, 2015
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The global simulations with CB05_GE and MOZART-4x predict similar chemical profiles for major gases compared to aircraft measurements, with better agreement for the NOy profile by CB05_GE. The SOA concentrations of SOA at four sites in CONUS and organic carbon over the IMPROVE sites are better predicted by MOZART-4x. The two simulations result in a global average difference of 0.5W m-2 in simulated shortwave cloud radiative forcing, with up to 13.6W m-2 over subtropical regions.
Y. Zheng, N. Unger, A. Hodzic, L. Emmons, C. Knote, S. Tilmes, J.-F. Lamarque, and P. Yu
Atmos. Chem. Phys., 15, 13487–13506, https://doi.org/10.5194/acp-15-13487-2015, https://doi.org/10.5194/acp-15-13487-2015, 2015
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Nitrogen oxides (NOx) play an important but complex role in secondary organic aerosol (SOA) formation. In this study we update the SOA scheme in a global 3-D chemistry-climate model by implementing a 4-product volatility basis set (VBS) framework with NOx-dependent yields and simplified aging parameterizations. We find that the SOA decrease in response to a 50% reduction in anthropogenic NOx emissions is limited due to the buffering in different chemical pathways.
P. S. Kim, D. J. Jacob, J. A. Fisher, K. Travis, K. Yu, L. Zhu, R. M. Yantosca, M. P. Sulprizio, J. L. Jimenez, P. Campuzano-Jost, K. D. Froyd, J. Liao, J. W. Hair, M. A. Fenn, C. F. Butler, N. L. Wagner, T. D. Gordon, A. Welti, P. O. Wennberg, J. D. Crounse, J. M. St. Clair, A. P. Teng, D. B. Millet, J. P. Schwarz, M. Z. Markovic, and A. E. Perring
Atmos. Chem. Phys., 15, 10411–10433, https://doi.org/10.5194/acp-15-10411-2015, https://doi.org/10.5194/acp-15-10411-2015, 2015
J. Kaiser, G. M. Wolfe, K. E. Min, S. S. Brown, C. C. Miller, D. J. Jacob, J. A. deGouw, M. Graus, T. F. Hanisco, J. Holloway, J. Peischl, I. B. Pollack, T. B. Ryerson, C. Warneke, R. A. Washenfelder, and F. N. Keutsch
Atmos. Chem. Phys., 15, 7571–7583, https://doi.org/10.5194/acp-15-7571-2015, https://doi.org/10.5194/acp-15-7571-2015, 2015
G. Zeng, J. E. Williams, J. A. Fisher, L. K. Emmons, N. B. Jones, O. Morgenstern, J. Robinson, D. Smale, C. Paton-Walsh, and D. W. T. Griffith
Atmos. Chem. Phys., 15, 7217–7245, https://doi.org/10.5194/acp-15-7217-2015, https://doi.org/10.5194/acp-15-7217-2015, 2015
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We assess the impact of biogenic emissions on CO and HCHO in the Southern Hemisphere (SH), with simulations using different emission inventories. Differences in biogenic emissions result in large differences on modelled CO in the source and the remote regions. Substantial inter-model differences exist. Models significantly underestimate observed HCHO columns in the SH, suggesting missing sources in the models. Differences in the CO/OH/CH4 chemistry lead to differences in HCHO in remote regions.
A. J. Turner and D. J. Jacob
Atmos. Chem. Phys., 15, 7039–7048, https://doi.org/10.5194/acp-15-7039-2015, https://doi.org/10.5194/acp-15-7039-2015, 2015
A. J. Turner, D. J. Jacob, K. J. Wecht, J. D. Maasakkers, E. Lundgren, A. E. Andrews, S. C. Biraud, H. Boesch, K. W. Bowman, N. M. Deutscher, M. K. Dubey, D. W. T. Griffith, F. Hase, A. Kuze, J. Notholt, H. Ohyama, R. Parker, V. H. Payne, R. Sussmann, C. Sweeney, V. A. Velazco, T. Warneke, P. O. Wennberg, and D. Wunch
Atmos. Chem. Phys., 15, 7049–7069, https://doi.org/10.5194/acp-15-7049-2015, https://doi.org/10.5194/acp-15-7049-2015, 2015
L. K. Emmons, S. R. Arnold, S. A. Monks, V. Huijnen, S. Tilmes, K. S. Law, J. L. Thomas, J.-C. Raut, I. Bouarar, S. Turquety, Y. Long, B. Duncan, S. Steenrod, S. Strode, J. Flemming, J. Mao, J. Langner, A. M. Thompson, D. Tarasick, E. C. Apel, D. R. Blake, R. C. Cohen, J. Dibb, G. S. Diskin, A. Fried, S. R. Hall, L. G. Huey, A. J. Weinheimer, A. Wisthaler, T. Mikoviny, J. Nowak, J. Peischl, J. M. Roberts, T. Ryerson, C. Warneke, and D. Helmig
Atmos. Chem. Phys., 15, 6721–6744, https://doi.org/10.5194/acp-15-6721-2015, https://doi.org/10.5194/acp-15-6721-2015, 2015
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Eleven 3-D tropospheric chemistry models have been compared and evaluated with observations in the Arctic during the International Polar Year (IPY 2008). Large differences are seen among the models, particularly related to the model chemistry of volatile organic compounds (VOCs) and reactive nitrogen (NOx, PAN, HNO3) partitioning. Consistency among the models in the underestimation of CO, ethane and propane indicates the emission inventory is too low for these compounds.
S. R. Arnold, L. K. Emmons, S. A. Monks, K. S. Law, D. A. Ridley, S. Turquety, S. Tilmes, J. L. Thomas, I. Bouarar, J. Flemming, V. Huijnen, J. Mao, B. N. Duncan, S. Steenrod, Y. Yoshida, J. Langner, and Y. Long
Atmos. Chem. Phys., 15, 6047–6068, https://doi.org/10.5194/acp-15-6047-2015, https://doi.org/10.5194/acp-15-6047-2015, 2015
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The extent to which forest fires produce the air pollutant and greenhouse gas ozone (O3) in the atmosphere at high latitudes in not well understood. We have compared how fire emissions produce O3 and its precursors in several models of atmospheric chemistry. We find enhancements in O3 in air dominated by fires in all models, which increase on average as fire emissions age. We also find that in situ O3 production in the Arctic is sensitive to details of organic chemistry and vertical lifting.
S. Tilmes, J.-F. Lamarque, L. K. Emmons, D. E. Kinnison, P.-L. Ma, X. Liu, S. Ghan, C. Bardeen, S. Arnold, M. Deeter, F. Vitt, T. Ryerson, J. W. Elkins, F. Moore, J. R. Spackman, and M. Val Martin
Geosci. Model Dev., 8, 1395–1426, https://doi.org/10.5194/gmd-8-1395-2015, https://doi.org/10.5194/gmd-8-1395-2015, 2015
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The Community Atmosphere Model (CAM), version 5, is now coupled to extensive tropospheric and stratospheric chemistry, called CAM5-chem, and is available in addition to CAM4-chem in the Community Earth System Model (CESM) version 1.2. Both configurations are well suited as tools for atmospheric chemistry modeling studies in the troposphere and lower stratosphere.
S. A. Monks, S. R. Arnold, L. K. Emmons, K. S. Law, S. Turquety, B. N. Duncan, J. Flemming, V. Huijnen, S. Tilmes, J. Langner, J. Mao, Y. Long, J. L. Thomas, S. D. Steenrod, J. C. Raut, C. Wilson, M. P. Chipperfield, G. S. Diskin, A. Weinheimer, H. Schlager, and G. Ancellet
Atmos. Chem. Phys., 15, 3575–3603, https://doi.org/10.5194/acp-15-3575-2015, https://doi.org/10.5194/acp-15-3575-2015, 2015
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Multi-model simulations of Arctic CO, O3 and OH are evaluated using observations. Models show highly variable concentrations but the relative importance of emission regions and types is robust across the models, demonstrating the importance of biomass burning as a source. Idealised tracer experiments suggest that some of the model spread is due to variations in simulated transport from Europe in winter and from Asia throughout the year.
J. A. Fisher, S. R. Wilson, G. Zeng, J. E. Williams, L. K. Emmons, R. L. Langenfelds, P. B. Krummel, and L. P. Steele
Atmos. Chem. Phys., 15, 3217–3239, https://doi.org/10.5194/acp-15-3217-2015, https://doi.org/10.5194/acp-15-3217-2015, 2015
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The Southern Hemisphere (SH) serves as an important test bed for evaluating our understanding of the processes that drive the composition of the clean background atmosphere. Using data from two aircraft campaigns, combined with four atmospheric chemistry models, we find a large sensitivity in the remote SH to biogenic emissions and their subsequent chemistry and transport. Future model evaluation and measurement campaigns should prioritize reducing uncertainties in these processes.
M. S. Long, R. Yantosca, J. E. Nielsen, C. A. Keller, A. da Silva, M. P. Sulprizio, S. Pawson, and D. J. Jacob
Geosci. Model Dev., 8, 595–602, https://doi.org/10.5194/gmd-8-595-2015, https://doi.org/10.5194/gmd-8-595-2015, 2015
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This paper presents results from the modularization of the GEOS-Chem chemical transport model, and its coupling as the chemical operator within the NASA-GMAO GEOS-5 Earth system model (ESM). The key findings are that chemistry within the modular GEOS-Chem system shows consistent, high strong-scaling properties across the range of distributed processors, transport is the limiting component prohibiting efficient scalability, and GEOS-Chem is able to generate suitable chemical results in an ESM.
M. Val Martin, C. L. Heald, J.-F. Lamarque, S. Tilmes, L. K. Emmons, and B. A. Schichtel
Atmos. Chem. Phys., 15, 2805–2823, https://doi.org/10.5194/acp-15-2805-2015, https://doi.org/10.5194/acp-15-2805-2015, 2015
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We present for the first time the relative effect of climate, emissions, and land use change on ozone and PM25 over the United States, focusing on the national parks. Air quality in 2050 will likely be dominated by emission patterns, but climate and land use changes alone can lead to a substantial increase in air pollution over most of the US, with important implications for O3 air quality, visibility and ecosystem health degradation in the national parks.
C. Viatte, K. Strong, J. Hannigan, E. Nussbaumer, L. K. Emmons, S. Conway, C. Paton-Walsh, J. Hartley, J. Benmergui, and J. Lin
Atmos. Chem. Phys., 15, 2227–2246, https://doi.org/10.5194/acp-15-2227-2015, https://doi.org/10.5194/acp-15-2227-2015, 2015
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Seven tropospheric species (CO, HCN, C2H6, C2H2, CH3OH, HCOOH, and H2CO) released by biomass burning events transported to the high Arctic were monitored with two sets of FTIR measurements, located at Eureka (Nunavut, Canada) and Thule (Greenland), from 2008 to 2012. We compared these data sets with the MOZART-4 chemical transport model to help improve its simulations in the Arctic. Emission factors of these biomass burning products were derived and compared to the literature.
T. Amnuaylojaroen, M. C. Barth, L. K. Emmons, G. R. Carmichael, J. Kreasuwun, S. Prasitwattanaseree, and S. Chantara
Atmos. Chem. Phys., 14, 12983–13012, https://doi.org/10.5194/acp-14-12983-2014, https://doi.org/10.5194/acp-14-12983-2014, 2014
F. L. Herron-Thorpe, G. H. Mount, L. K. Emmons, B. K. Lamb, D. A. Jaffe, N. L. Wigder, S. H. Chung, R. Zhang, M. D. Woelfle, and J. K. Vaughan
Atmos. Chem. Phys., 14, 12533–12551, https://doi.org/10.5194/acp-14-12533-2014, https://doi.org/10.5194/acp-14-12533-2014, 2014
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Wildfire season simulations from an air quality forecast system for the Pacific Northwest were compared to surface monitor observations across the region and NASA Earth Observing System satellite retrievals of plume top, nitrogen dioxide, aerosol optical depth, and carbon monoxide. This study discusses why the Community Multi-scale Air Quality model predictions under-predicted secondary organic aerosol (SOA) production for events when fire emissions were transported large distances.
C. Chan Miller, G. Gonzalez Abad, H. Wang, X. Liu, T. Kurosu, D. J. Jacob, and K. Chance
Atmos. Meas. Tech., 7, 3891–3907, https://doi.org/10.5194/amt-7-3891-2014, https://doi.org/10.5194/amt-7-3891-2014, 2014
M. N. Deeter, S. Martínez-Alonso, D. P. Edwards, L. K. Emmons, J. C. Gille, H. M. Worden, C. Sweeney, J. V. Pittman, B. C. Daube, and S. C. Wofsy
Atmos. Meas. Tech., 7, 3623–3632, https://doi.org/10.5194/amt-7-3623-2014, https://doi.org/10.5194/amt-7-3623-2014, 2014
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The MOPITT Version 6 product for carbon monoxide (CO) incorporates several enhancements. First, a geolocation bias has been eliminated. Second, the new variable a priori for CO concentrations is based on simulations performed with the CAM-Chem chemical transport model for the years 2000-2009. Third, required meteorological fields are extracted from the MERRA reanalysis. Finally, a retrieval bias in the upper troposphere was substantially reduced. Validation results are presented.
J. D. Fast, J. Allan, R. Bahreini, J. Craven, L. Emmons, R. Ferrare, P. L. Hayes, A. Hodzic, J. Holloway, C. Hostetler, J. L. Jimenez, H. Jonsson, S. Liu, Y. Liu, A. Metcalf, A. Middlebrook, J. Nowak, M. Pekour, A. Perring, L. Russell, A. Sedlacek, J. Seinfeld, A. Setyan, J. Shilling, M. Shrivastava, S. Springston, C. Song, R. Subramanian, J. W. Taylor, V. Vinoj, Q. Yang, R. A. Zaveri, and Q. Zhang
Atmos. Chem. Phys., 14, 10013–10060, https://doi.org/10.5194/acp-14-10013-2014, https://doi.org/10.5194/acp-14-10013-2014, 2014
K. J. Wecht, D. J. Jacob, M. P. Sulprizio, G. W. Santoni, S. C. Wofsy, R. Parker, H. Bösch, and J. Worden
Atmos. Chem. Phys., 14, 8173–8184, https://doi.org/10.5194/acp-14-8173-2014, https://doi.org/10.5194/acp-14-8173-2014, 2014
C. A. Keller, M. S. Long, R. M. Yantosca, A. M. Da Silva, S. Pawson, and D. J. Jacob
Geosci. Model Dev., 7, 1409–1417, https://doi.org/10.5194/gmd-7-1409-2014, https://doi.org/10.5194/gmd-7-1409-2014, 2014
P. Zoogman, D. J. Jacob, K. Chance, X. Liu, M. Lin, A. Fiore, and K. Travis
Atmos. Chem. Phys., 14, 6261–6271, https://doi.org/10.5194/acp-14-6261-2014, https://doi.org/10.5194/acp-14-6261-2014, 2014
M. Li, Q. Zhang, D. G. Streets, K. B. He, Y. F. Cheng, L. K. Emmons, H. Huo, S. C. Kang, Z. Lu, M. Shao, H. Su, X. Yu, and Y. Zhang
Atmos. Chem. Phys., 14, 5617–5638, https://doi.org/10.5194/acp-14-5617-2014, https://doi.org/10.5194/acp-14-5617-2014, 2014
L. Zhang, D. J. Jacob, X. Yue, N. V. Downey, D. A. Wood, and D. Blewitt
Atmos. Chem. Phys., 14, 5295–5309, https://doi.org/10.5194/acp-14-5295-2014, https://doi.org/10.5194/acp-14-5295-2014, 2014
E. V. Fischer, D. J. Jacob, R. M. Yantosca, M. P. Sulprizio, D. B. Millet, J. Mao, F. Paulot, H. B. Singh, A. Roiger, L. Ries, R.W. Talbot, K. Dzepina, and S. Pandey Deolal
Atmos. Chem. Phys., 14, 2679–2698, https://doi.org/10.5194/acp-14-2679-2014, https://doi.org/10.5194/acp-14-2679-2014, 2014
P. S. Kim, D. J. Jacob, X. Liu, J. X. Warner, K. Yang, K. Chance, V. Thouret, and P. Nedelec
Atmos. Chem. Phys., 13, 9321–9335, https://doi.org/10.5194/acp-13-9321-2013, https://doi.org/10.5194/acp-13-9321-2013, 2013
J. L. Thomas, J.-C. Raut, K. S. Law, L. Marelle, G. Ancellet, F. Ravetta, J. D. Fast, G. Pfister, L. K. Emmons, G. S. Diskin, A. Weinheimer, A. Roiger, and H. Schlager
Atmos. Chem. Phys., 13, 3825–3848, https://doi.org/10.5194/acp-13-3825-2013, https://doi.org/10.5194/acp-13-3825-2013, 2013
R. D. Saylor
Atmos. Chem. Phys., 13, 693–715, https://doi.org/10.5194/acp-13-693-2013, https://doi.org/10.5194/acp-13-693-2013, 2013
J. Mao, S. Fan, D. J. Jacob, and K. R. Travis
Atmos. Chem. Phys., 13, 509–519, https://doi.org/10.5194/acp-13-509-2013, https://doi.org/10.5194/acp-13-509-2013, 2013
L. K. Emmons, P. G. Hess, J.-F. Lamarque, and G. G. Pfister
Geosci. Model Dev., 5, 1531–1542, https://doi.org/10.5194/gmd-5-1531-2012, https://doi.org/10.5194/gmd-5-1531-2012, 2012
Related subject area
Atmospheric sciences
New submodel for emissions from Explosive Volcanic ERuptions (EVER v1.1) within the Modular Earth Submodel System (MESSy, version 2.55.1)
Quantifying the oscillatory evolution of simulated boundary-layer cloud fields using Gaussian process regression
Numerical investigations on the modelling of ultrafine particles in SSH-aerosol-v1.3a: size resolution and redistribution
The third Met Office Unified Model–JULES Regional Atmosphere and Land Configuration, RAL3
The sensitivity of aerosol data assimilation to vertical profiles: case study of dust storm assimilation with LOTOS-EUROS v2.2
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a neural network
Tuning the ICON-A 2.6.4 climate model with machine-learning-based emulators and history matching
A novel method for quantifying the contribution of regional transport to PM2.5 in Beijing (2013–2020): combining machine learning with concentration-weighted trajectory analysis
Quantification of CO2 hotspot emissions from OCO-3 SAM CO2 satellite images using deep learning methods
Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data
Improving winter condition simulations in SURFEX-TEB v9.0 with a multi-layer snow model and ice
UA-ICON with the NWP physics package (version ua-icon-2.1): mean state and variability of the middle atmosphere
Integrated Methane Inversion (IMI) 2.0: an improved research and stakeholder tool for monitoring total methane emissions with high resolution worldwide using TROPOMI satellite observations
HTAP3 Fires: towards a multi-model, multi-pollutant study of fire impacts
Using a data-driven statistical model to better evaluate surface turbulent heat fluxes in weather and climate numerical models: a demonstration study
Pochva: a new hydro-thermal process model in soil, snow, and vegetation for application in atmosphere numerical models
ClimKern v1.2: a new Python package and kernel repository for calculating radiative feedbacks
Accounting for effects of coagulation and model uncertainties in particle number concentration estimates based on measurements from sampling lines – a Bayesian inversion approach with SLIC v1.0
Top-down CO emission estimates using TROPOMI CO data in the TM5-4DVAR (r1258) inverse modeling suit
The Multi-Compartment Hg Modeling and Analysis Project (MCHgMAP): mercury modeling to support international environmental policy
Similarity-based analysis of atmospheric organic compounds for machine learning applications
Porting the Meso-NH atmospheric model on different GPU architectures for the next generation of supercomputers (version MESONH-v55-OpenACC)
Estimation of aerosol and cloud radiative heating rate in the tropical stratosphere using a radiative kernel method
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
A REtrieval Method for optical and physical Aerosol Properties in the stratosphere (REMAPv1)
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
Generalized local fractions – a method for the calculation of sensitivities to emissions from multiple sources for chemically active species, illustrated using the EMEP MSC-W model (rv5.5)
SanDyPALM v1.0: Static and Dynamic Drivers for the PALM-4U Model to Facilitate Realistic Urban Microclimate Simulations
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Implementation of a dry deposition module (DEPAC v3.11) in a large eddy simulation code (DALES v4.4)
Accurate and fast prediction of radioactive pollution by Kriging coupled with Auto-Associative Models
Mitigating Hail Overforecasting in the 2-Moment Milbrandt-Yau Microphysics Scheme (v2.25.2_beta_04) in WRF (v4.5.1) by Incorporating the Graupel Spongy Wet Growth Process (MY2_GSWG v1.0)
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Matthias Kohl, Christoph Brühl, Jennifer Schallock, Holger Tost, Patrick Jöckel, Adrian Jost, Steffen Beirle, Michael Höpfner, and Andrea Pozzer
Geosci. Model Dev., 18, 3985–4007, https://doi.org/10.5194/gmd-18-3985-2025, https://doi.org/10.5194/gmd-18-3985-2025, 2025
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SO2 from explosive volcanic eruptions reaching the stratosphere can oxidize and form sulfur aerosols, potentially persisting for several years. We developed a new submodel, Explosive Volcanic ERuptions (EVER), that seamlessly includes stratospheric volcanic SO2 emissions in global numerical simulations based on a novel standard historical model setup, successfully evaluated with satellite observations. Sensitivity studies on the Nabro eruption in 2011 evaluate different emission methods.
Gunho Loren Oh and Philip H. Austin
Geosci. Model Dev., 18, 3921–3940, https://doi.org/10.5194/gmd-18-3921-2025, https://doi.org/10.5194/gmd-18-3921-2025, 2025
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It is difficult to study the behaviour of a cloud field due to internal fluctuations and observational noise. We perform a high-resolution simulation of the boundary-layer cloud field and introduce statistical and numerical techniques, including machine-learning models, to study the evolution of the cloud field, which shows a periodic behaviour. We aim to use the numerical techniques to identify the underlying behaviour within noisy observations.
Oscar Jacquot and Karine Sartelet
Geosci. Model Dev., 18, 3965–3984, https://doi.org/10.5194/gmd-18-3965-2025, https://doi.org/10.5194/gmd-18-3965-2025, 2025
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Modelling the size distribution and the number concentration is important to represent ultrafine particles. A new analytic formulation is presented to compute coagulation partition coefficients, allowing us to lower the numerical diffusion associated with the resolution of aerosol dynamics. The significance of this effect is assessed in a 0D box model and over greater Paris with a chemistry transport model, using different size resolutions of the particle distribution.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev., 18, 3819–3855, https://doi.org/10.5194/gmd-18-3819-2025, https://doi.org/10.5194/gmd-18-3819-2025, 2025
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RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre- and sub-kilometre-scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and an improved representation of clouds and visibility.
Mijie Pang, Jianbing Jin, Ting Yang, Xi Chen, Arjo Segers, Batjargal Buyantogtokh, Yixuan Gu, Jiandong Li, Hai Xiang Lin, Hong Liao, and Wei Han
Geosci. Model Dev., 18, 3781–3798, https://doi.org/10.5194/gmd-18-3781-2025, https://doi.org/10.5194/gmd-18-3781-2025, 2025
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Aerosol data assimilation has gained popularity as it combines the advantages of modelling and observation. However, few studies have addressed the challenges in the prior vertical structure. Different observations are assimilated to examine the sensitivity of assimilation to vertical structure. Results show that assimilation can optimize the dust field in general. However, if the prior introduces an incorrect structure, the assimilation can significantly deteriorate the integrity of the aerosol profile.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
Geosci. Model Dev., 18, 3707–3733, https://doi.org/10.5194/gmd-18-3707-2025, https://doi.org/10.5194/gmd-18-3707-2025, 2025
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This work focuses on the prediction of aerosol concentration values at the ground level, which are a strong indicator of air quality, using artificial neural networks. A study of different variables and their efficiency as inputs for these models is also proposed and reveals that the best results are obtained when using all of them. Comparison between network architectures and information fusion methods allows for the extraction of knowledge on the most efficient methods in the context of this study.
Pauline Bonnet, Lorenzo Pastori, Mierk Schwabe, Marco Giorgetta, Fernando Iglesias-Suarez, and Veronika Eyring
Geosci. Model Dev., 18, 3681–3706, https://doi.org/10.5194/gmd-18-3681-2025, https://doi.org/10.5194/gmd-18-3681-2025, 2025
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Tuning a climate model means adjusting uncertain parameters in the model to best match observations like the global radiation balance and cloud cover. This is usually done by running many simulations of the model with different settings, which can be time-consuming and relies heavily on expert knowledge. To make this process faster and more objective, we developed a machine learning emulator to create a large ensemble and apply a method called history matching to find the best settings.
Kang Hu, Hong Liao, Dantong Liu, Jianbing Jin, Lei Chen, Siyuan Li, Yangzhou Wu, Changhao Wu, Shitong Zhao, Xiaotong Jiang, Ping Tian, Kai Bi, Ye Wang, and Delong Zhao
Geosci. Model Dev., 18, 3623–3634, https://doi.org/10.5194/gmd-18-3623-2025, https://doi.org/10.5194/gmd-18-3623-2025, 2025
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This study combines machine learning with concentration-weighted trajectory analysis to quantify regional transport PM2.5. From 2013–2020, local emissions dominated Beijing's pollution events. The Air Pollution Prevention and Control Action Plan reduced regional transport pollution, but the eastern region showed the smallest decrease. Beijing should prioritize local emission reduction while considering the east region's contributions in future strategies.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 18, 3607–3622, https://doi.org/10.5194/gmd-18-3607-2025, https://doi.org/10.5194/gmd-18-3607-2025, 2025
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We developed a deep learning method to estimate CO2 emissions from power plants using satellite images. Trained and validated on simulated data, our model accurately predicts emissions despite challenges like cloud cover. When applied to real OCO3 satellite images, the results closely match reported emissions. This study shows that neural networks trained on simulations can effectively analyse real satellite data, offering a new way to monitor CO2 emissions from space.
Wonbae Bang, Jacob T. Carlin, Kwonil Kim, Alexander V. Ryzhkov, Guosheng Liu, and GyuWon Lee
Geosci. Model Dev., 18, 3559–3581, https://doi.org/10.5194/gmd-18-3559-2025, https://doi.org/10.5194/gmd-18-3559-2025, 2025
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Microphysics model-based diagnosis, such as the spectral bin model (SBM), has recently been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM has a relatively higher accuracy for dry-snow and wet-snow events, whereas it has lower accuracy for rain events. When the microphysics scheme in the SBM was optimized for the corresponding region, the accuracy for rain events improved.
Gabriel Colas, Valéry Masson, François Bouttier, Ludovic Bouilloud, Laura Pavan, and Virve Karsisto
Geosci. Model Dev., 18, 3453–3472, https://doi.org/10.5194/gmd-18-3453-2025, https://doi.org/10.5194/gmd-18-3453-2025, 2025
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In winter, snow- and ice-covered artificial surfaces are important aspects of the urban climate. They may influence the magnitude of the urban heat island effect, but this is still unclear. In this study, we improved the representation of the snow and ice cover in the Town Energy Balance (TEB) urban climate model. Evaluations have shown that the results are promising for using TEB to study the climate of cold cities.
Markus Kunze, Christoph Zülicke, Tarique A. Siddiqui, Claudia C. Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev., 18, 3359–3385, https://doi.org/10.5194/gmd-18-3359-2025, https://doi.org/10.5194/gmd-18-3359-2025, 2025
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with an upper-atmospheric extension with the physics package for numerical weather prediction (UA-ICON(NWP)). We optimized the parameters for the gravity wave parameterizations and achieved realistic modeling of the thermal and dynamic states of the mesopause regions. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
Geosci. Model Dev., 18, 3311–3330, https://doi.org/10.5194/gmd-18-3311-2025, https://doi.org/10.5194/gmd-18-3311-2025, 2025
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Reducing emissions of methane, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from individual basin to global scales with continuous emissions monitoring.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Steve R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christoph Knote, Gerbrand Koren, Jean-Luc Kouassi, Meiyun Lin, Tianjia Liu, Jianmin Ma, Kasemsan Manomaiphiboon, Elisa Bergas Masso, Jessica L. McCarty, Mariano Mertens, Mark Parrington, Helene Peiro, Pallavi Saxena, Saurabh Sonwani, Vanisa Surapipith, Damaris Y. T. Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev., 18, 3265–3309, https://doi.org/10.5194/gmd-18-3265-2025, https://doi.org/10.5194/gmd-18-3265-2025, 2025
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The multi-model experiment design of the HTAP3 Fires project takes a multi-pollutant approach to improving our understanding of transboundary transport of wildland fire and agricultural burning emissions and their impacts. The experiments are designed with the goal of answering science policy questions related to fires. The options for the multi-model approach, including inputs, outputs, and model setup, are discussed, and the official recommendations for the project are presented.
Maurin Zouzoua, Sophie Bastin, Fabienne Lohou, Marie Lothon, Marjolaine Chiriaco, Mathilde Jome, Cécile Mallet, Laurent Barthes, and Guylaine Canut
Geosci. Model Dev., 18, 3211–3239, https://doi.org/10.5194/gmd-18-3211-2025, https://doi.org/10.5194/gmd-18-3211-2025, 2025
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This study proposes using a statistical model to freeze errors due to differences in environmental forcing when evaluating the surface turbulent heat fluxes from numerical simulations with observations. The statistical model is first built with observations and then applied to the simulated environment to generate possibly observed fluxes. This novel method provides insight into differently evaluating the numerical formulation of turbulent heat fluxes with a long period of observational data.
Oxana Drofa
Geosci. Model Dev., 18, 3175–3209, https://doi.org/10.5194/gmd-18-3175-2025, https://doi.org/10.5194/gmd-18-3175-2025, 2025
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This paper presents the result of many years of effort of the author, who developed an original mathematical numerical model of heat and moisture exchange processes in soil, vegetation, and snow. The author relied on her 30 years of research experience in atmospheric numerical modelling. The presented model is the fruit of the author's research on physical processes at the surface–atmosphere interface and their numerical approximation and aims at improving numerical weather forecasting and climate simulations.
Tyler P. Janoski, Ivan Mitevski, Ryan J. Kramer, Michael Previdi, and Lorenzo M. Polvani
Geosci. Model Dev., 18, 3065–3079, https://doi.org/10.5194/gmd-18-3065-2025, https://doi.org/10.5194/gmd-18-3065-2025, 2025
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We developed ClimKern, a Python package and radiative kernel repository, to simplify calculating radiative feedbacks and make climate sensitivity studies more reproducible. Testing of ClimKern with sample climate model data reveals that radiative kernel choice may be more important than previously thought, especially in polar regions. Our work highlights the need for kernel sensitivity analyses to be included in future studies.
Matti Niskanen, Aku Seppänen, Henri Oikarinen, Miska Olin, Panu Karjalainen, Santtu Mikkonen, and Kari Lehtinen
Geosci. Model Dev., 18, 2983–3001, https://doi.org/10.5194/gmd-18-2983-2025, https://doi.org/10.5194/gmd-18-2983-2025, 2025
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Particle size is a key factor determining the properties of aerosol particles which have a major influence on the climate and on human health. When measuring the particle sizes, however, sometimes the sampling lines that transfer the aerosol to the measurement device distort the size distribution, making the measurement unreliable. We propose a method to correct for the distortions and estimate the true particle sizes, improving measurement accuracy.
Johann Rasmus Nüß, Nikos Daskalakis, Fabian Günther Piwowarczyk, Angelos Gkouvousis, Oliver Schneising, Michael Buchwitz, Maria Kanakidou, Maarten C. Krol, and Mihalis Vrekoussis
Geosci. Model Dev., 18, 2861–2890, https://doi.org/10.5194/gmd-18-2861-2025, https://doi.org/10.5194/gmd-18-2861-2025, 2025
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We estimate carbon monoxide emissions through inverse modeling, an approach where measurements of tracers in the atmosphere are fed to a model to calculate backwards in time (inverse) where the tracers came from. We introduce measurements from a new satellite instrument and show that, in most places globally, these on their own sufficiently constrain the emissions. This alleviates the need for additional datasets, which could shorten the delay for future carbon monoxide source estimates.
Ashu Dastoor, Hélène Angot, Johannes Bieser, Flora Brocza, Brock Edwards, Aryeh Feinberg, Xinbin Feng, Benjamin Geyman, Charikleia Gournia, Yipeng He, Ian M. Hedgecock, Ilia Ilyin, Jane Kirk, Che-Jen Lin, Igor Lehnherr, Robert Mason, David McLagan, Marilena Muntean, Peter Rafaj, Eric M. Roy, Andrei Ryjkov, Noelle E. Selin, Francesco De Simone, Anne L. Soerensen, Frits Steenhuisen, Oleg Travnikov, Shuxiao Wang, Xun Wang, Simon Wilson, Rosa Wu, Qingru Wu, Yanxu Zhang, Jun Zhou, Wei Zhu, and Scott Zolkos
Geosci. Model Dev., 18, 2747–2860, https://doi.org/10.5194/gmd-18-2747-2025, https://doi.org/10.5194/gmd-18-2747-2025, 2025
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This paper introduces the Multi-Compartment Mercury (Hg) Modeling and Analysis Project (MCHgMAP) aimed at informing the effectiveness evaluations of two multilateral environmental agreements: the Minamata Convention on Mercury and the Convention on Long-Range Transboundary Air Pollution. The experimental design exploits a variety of models (atmospheric, land, oceanic ,and multimedia mass balance models) to assess the short- and long-term influences of anthropogenic Hg releases into the environment.
Hilda Sandström and Patrick Rinke
Geosci. Model Dev., 18, 2701–2724, https://doi.org/10.5194/gmd-18-2701-2025, https://doi.org/10.5194/gmd-18-2701-2025, 2025
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Machine learning has the potential to aid the identification of organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning models in atmospheric sciences.
Juan Escobar, Philippe Wautelet, Joris Pianezze, Florian Pantillon, Thibaut Dauhut, Christelle Barthe, and Jean-Pierre Chaboureau
Geosci. Model Dev., 18, 2679–2700, https://doi.org/10.5194/gmd-18-2679-2025, https://doi.org/10.5194/gmd-18-2679-2025, 2025
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The Meso-NH weather research code is adapted for GPUs using OpenACC, leading to significant performance and energy efficiency improvements. Called MESONH-v55-OpenACC, it includes enhanced memory management, communication optimizations and a new solver. On the AMD MI250X Adastra platform, it achieved up to 6× speedup and 2.3× energy efficiency gain compared to CPUs. Storm simulations at 100 m resolution show positive results, positioning the code for future use on exascale supercomputers.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
Geosci. Model Dev., 18, 2569–2586, https://doi.org/10.5194/gmd-18-2569-2025, https://doi.org/10.5194/gmd-18-2569-2025, 2025
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate this effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense, is consistent with radiative model calculations, and can be applied to atmospheric models with speed requirements.
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Andrin Jörimann, Timofei Sukhodolov, Beiping Luo, Gabriel Chiodo, Graham Mann, and Thomas Peter
EGUsphere, https://doi.org/10.5194/egusphere-2025-145, https://doi.org/10.5194/egusphere-2025-145, 2025
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Aerosol particles in the stratosphere affect our climate. Climate models therefore need an accurate description of their properties and evolution. Satellites measure how strongly aerosol particles extinguish light passing through the stratosphere. We describe a method to use such aerosol extinction data to retrieve the number and sizes of the aerosol particles and calculate their optical effects. The resulting data sets for models are validated against ground-based and balloon observations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Peter Wind and Willem van Caspel
EGUsphere, https://doi.org/10.5194/egusphere-2024-3571, https://doi.org/10.5194/egusphere-2024-3571, 2025
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This paper presents a numerical method to assess the origin of air pollution. Combined with a numerical air pollution transport and chemistry model, it can follow the contributions from a large number of emission sources. The result is a series of maps that give the relative contributions from for example all European countries at each point.
Julian Vogel, Sebastian Stadler, Ganesh Chockalingam, Afshin Afshari, Johanna Henning, and Matthias Winkler
EGUsphere, https://doi.org/10.5194/egusphere-2025-144, https://doi.org/10.5194/egusphere-2025-144, 2025
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This study presents a toolkit to simplify input data creation for the urban microclimate model PALM-4U. It introduces novel methods to automate the use of open data sources. Our analysis of four test cases created from different geographic data sources shows variations in temperature, humidity, and wind speed, influenced by data quality. Validation indicates that the automated methods yield results comparable to expert-driven approaches, facilitating user-friendly urban climate modeling.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
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An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
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As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
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In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Leon Geers, Ruud Janssen, Gudrun Thorkelsdottir, Jordi Vilà-Guerau de Arellano, and Martijn Schaap
EGUsphere, https://doi.org/10.5194/egusphere-2025-426, https://doi.org/10.5194/egusphere-2025-426, 2025
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High-resolution data on reactive nitrogen deposition are needed to inform cost-effective policies. Here, we describe the implementation of a dry deposition module into a large eddy simulation code. With this model, we are able to represent the turbulent exchange of tracers at the hectometer resolution. The model calculates the dispersion and deposition of NOx and NH3 in great spatial detail, clearly showing the influence of local land use patterns.
Raphaël Périllat, Sylvain Girard, and Irène Korsakissok
EGUsphere, https://doi.org/10.5194/egusphere-2024-3838, https://doi.org/10.5194/egusphere-2024-3838, 2025
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We developed a method to improve decision-making during nuclear crises by predicting the spread of radiation more efficiently. Existing approaches are often too slow, especially when analyzing complex data like radiation maps. Our method combines techniques to simplify these maps and predict them quickly using statistical tools. This approach could help authorities respond faster and more accurately in emergencies, reducing risks to the population and the environment.
Shaofeng Hua, Gang Chen, Baojun Chen, Mingshan Li, and Xin Xu
EGUsphere, https://doi.org/10.5194/egusphere-2024-3834, https://doi.org/10.5194/egusphere-2024-3834, 2025
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Hail forecasting using numerical models remains a challenge. In this study, we found that the commonly used graupel-to-hail conversion parameterization method led to hail overforecasting in heavy rainfall cases where no hail was observed. By incorporating the spongy wet growth process, we successfully mitigated hail overforecasting. The modified scheme also produced hail in real hail events. This research contributes to a better understanding of hail formation.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
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We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
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Short summary
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.
Emissions are a central component of atmospheric chemistry models. The Harmonized Emissions...
