Articles | Volume 16, issue 13
https://doi.org/10.5194/gmd-16-3873-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-3873-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
12 Jul 2023
Model description paper |
| 12 Jul 2023
| 12 Jul 2023
The Fire Inventory from NCAR version 2.5: an updated global fire emissions model for climate and chemistry applications
Christine Wiedinmyer
CORRESPONDING AUTHOR
Cooperative Institute for Research in Environmental Sciences,
University of Colorado, Boulder, Boulder, CO, USA
Yosuke Kimura
Center for Energy and Environmental Resources, The University of Texas at Austin, Austin, TX, USA
Elena C. McDonald-Buller
Center for Energy and Environmental Resources, The University of Texas at Austin, Austin, TX, USA
Louisa K. Emmons
Atmospheric Chemistry Observations and Modeling Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
Rebecca R. Buchholz
Atmospheric Chemistry Observations and Modeling Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
Wenfu Tang
Atmospheric Chemistry Observations and Modeling Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
Keenan Seto
Cooperative Institute for Research in Environmental Sciences,
University of Colorado, Boulder, Boulder, CO, USA
Maxwell B. Joseph
Cooperative Institute for Research in Environmental Sciences,
University of Colorado, Boulder, Boulder, CO, USA
Earth Lab, University of Colorado Boulder, Boulder, CO, USA
Kelley C. Barsanti
Department of Chemical and Environmental Engineering, Center for
Environmental Research and Technology, University of California, Riverside, Riverside, CA, USA
Atmospheric Chemistry Observations and Modeling Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
Annmarie G. Carlton
Department of Chemistry, University of California Irvine, Irvine, CA, USA
Robert Yokelson
Department of Chemistry, University of Montana, Missoula, MT, USA
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X. Jiang, M. C. Barth, C. Wiedinmyer, and S. T. Massie
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-21383-2013, https://doi.org/10.5194/acpd-13-21383-2013, 2013
Revised manuscript not accepted
M. Val Martin, C. L. Heald, B. Ford, A. J. Prenni, and C. Wiedinmyer
Atmos. Chem. Phys., 13, 7429–7439, https://doi.org/10.5194/acp-13-7429-2013, https://doi.org/10.5194/acp-13-7429-2013, 2013
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-307, https://doi.org/10.5194/essd-2025-307, 2025
Preprint under review for ESSD
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James D. A. Butler, Afsara Tasnia, Deep Sengupta, Nathan Kreisberg, Kelley C. Barsanti, Allen H. Goldstein, Chelsea V. Preble, Rebecca A. Sugrue, and Thomas W. Kirchstetter
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William P. L. Carter, Jia Jiang, Zhizhao Wang, and Kelley C. Barsanti
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Daniel L. Goldberg, M. Omar Nawaz, Congmeng Lyu, Jian He, Annmarie G. Carlton, Shobha Kondragunta, and Susan C. Anenberg
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Ngoc Thi Nhu Do, Kengo Sudo, Akihiko Ito, Louisa K. Emmons, Vaishali Naik, Kostas Tsigaridis, Øyvind Seland, Gerd A. Folberth, and Douglas I. Kelley
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Understanding historical isoprene emission changes is important for predicting future climate, but trends and their controlling factors remain uncertain. This study shows that long-term isoprene trends vary among Earth system models mainly due to partially incorporating CO2 effects and land cover changes rather than to climate. Future models that refine these factors’ effects on isoprene emissions, along with long-term observations, are essential for better understanding plant–climate interactions.
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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Natalie Brett, Kathy S. Law, Steve R. Arnold, Javier G. Fochesatto, Jean-Christophe Raut, Tatsuo Onishi, Robert Gilliam, Kathleen Fahey, Deanna Huff, George Pouliot, Brice Barret, Elsa Dieudonné, Roman Pohorsky, Julia Schmale, Andrea Baccarini, Slimane Bekki, Gianluca Pappaccogli, Federico Scoto, Stefano Decesari, Antonio Donateo, Meeta Cesler-Maloney, William Simpson, Patrice Medina, Barbara D'Anna, Brice Temime-Roussel, Joel Savarino, Sarah Albertin, Jingqiu Mao, Becky Alexander, Allison Moon, Peter F. DeCarlo, Vanessa Selimovic, Robert Yokelson, and Ellis S. Robinson
Atmos. Chem. Phys., 25, 1063–1104, https://doi.org/10.5194/acp-25-1063-2025, https://doi.org/10.5194/acp-25-1063-2025, 2025
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Processes influencing dispersion of local anthropogenic pollution in Arctic wintertime are investigated with Lagrangian dispersion modelling. Simulated power plant plume rise that considers temperature inversion layers improves results compared to observations (interior Alaska). Modelled surface concentrations are improved by representation of vertical mixing and emission estimates. Large increases in diesel vehicle emissions at temperatures reaching −35°C are required to reproduce observed NOx.
William P. L. Carter, Jia Jiang, John J. Orlando, and Kelley C. Barsanti
Atmos. Chem. Phys., 25, 199–242, https://doi.org/10.5194/acp-25-199-2025, https://doi.org/10.5194/acp-25-199-2025, 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
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Aerosol property measurements recently collected on the ground and by a research aircraft in central Argentina during the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) campaign exhibit large spatial and temporal variability. These measurements coupled with coincident meteorological information provide a valuable data set needed to evaluate and improve model predictions of aerosols in a traditionally data-sparse region of South America.
Yasin Elshorbany, Jerald R. Ziemke, Sarah Strode, Hervé Petetin, Kazuyuki Miyazaki, Isabelle De Smedt, Kenneth Pickering, Rodrigo J. Seguel, Helen Worden, Tamara Emmerichs, Domenico Taraborrelli, Maria Cazorla, Suvarna Fadnavis, Rebecca R. Buchholz, Benjamin Gaubert, Néstor Y. Rojas, Thiago Nogueira, Thérèse Salameh, and Min Huang
Atmos. Chem. Phys., 24, 12225–12257, https://doi.org/10.5194/acp-24-12225-2024, https://doi.org/10.5194/acp-24-12225-2024, 2024
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We investigated tropospheric ozone spatial variability and trends from 2005 to 2019 and related those to ozone precursors on global and regional scales. We also investigate the spatiotemporal characteristics of the ozone formation regime in relation to ozone chemical sources and sinks. Our analysis is based on remote sensing products of the tropospheric column of ozone and its precursors, nitrogen dioxide, formaldehyde, and total column CO, as well as ozonesonde data and model simulations.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
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The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Kavitha Mottungan, Chayan Roychoudhury, Vanessa Brocchi, Benjamin Gaubert, Wenfu Tang, Mohammad Amin Mirrezaei, John McKinnon, Yafang Guo, David W. T. Griffith, Dietrich G. Feist, Isamu Morino, Mahesh K. Sha, Manvendra K. Dubey, Martine De Mazière, Nicholas M. Deutscher, Paul O. Wennberg, Ralf Sussmann, Rigel Kivi, Tae-Young Goo, Voltaire A. Velazco, Wei Wang, and Avelino F. Arellano Jr.
Atmos. Meas. Tech., 17, 5861–5885, https://doi.org/10.5194/amt-17-5861-2024, https://doi.org/10.5194/amt-17-5861-2024, 2024
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A combination of data analysis techniques is introduced to separate local and regional influences on observed levels of carbon dioxide, carbon monoxide, and methane from an established ground-based remote sensing network. We take advantage of the covariations in these trace gases to identify the dominant type of sources driving these levels. Applying these methods in conjunction with existing approaches to other datasets can better address uncertainties in identifying sources and sinks.
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.
Vignesh Vasudevan-Geetha, Lee Tiszenkel, Zhizhao Wang, Robin Russo, Daniel Bryant, Julia Lee-Taylor, Kelley Barsanti, and Shan-Hu Lee
EGUsphere, https://doi.org/10.5194/egusphere-2024-2454, https://doi.org/10.5194/egusphere-2024-2454, 2024
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Our laboratory experiments using two high-resolution mass spectrometers show that these OOMs can also form within the particle phase, in addition to gas-to-particle conversion processes. Our results demonstrate that particle-phase formation processes can contribute to the formation and growth of new particles in biogenic environments.
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.
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.
Natalie M. Mahowald, Longlei Li, Julius Vira, Marje Prank, Douglas S. Hamilton, Hitoshi Matsui, Ron L. Miller, Louis Lu, Ezgi Akyuz, Daphne Meidan, Peter Hess, Heikki Lihavainen, Christine Wiedinmyer, Jenny Hand, Maria Grazia Alaimo, Célia Alves, Andres Alastuey, Paulo Artaxo, Africa Barreto, Francisco Barraza, Silvia Becagli, Giulia Calzolai, Shankarararman Chellam, Ying Chen, Patrick Chuang, David D. Cohen, Cristina Colombi, Evangelia Diapouli, Gaetano Dongarra, Konstantinos Eleftheriadis, Corinne Galy-Lacaux, Cassandra Gaston, Dario Gomez, Yenny González Ramos, Hannele Hakola, Roy M. Harrison, Chris Heyes, Barak Herut, Philip Hopke, Christoph Hüglin, Maria Kanakidou, Zsofia Kertesz, Zbiginiw Klimont, Katriina Kyllönen, Fabrice Lambert, Xiaohong Liu, Remi Losno, Franco Lucarelli, Willy Maenhaut, Beatrice Marticorena, Randall V. Martin, Nikolaos Mihalopoulos, Yasser Morera-Gomez, Adina Paytan, Joseph Prospero, Sergio Rodríguez, Patricia Smichowski, Daniela Varrica, Brenna Walsh, Crystal Weagle, and Xi Zhao
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-1, https://doi.org/10.5194/essd-2024-1, 2024
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Aerosol particles can interact with incoming solar radiation and outgoing long wave radiation, change cloud properties, affect photochemistry, impact surface air quality, and when deposited impact surface albedo of snow and ice, and modulate carbon dioxide uptake by the land and ocean. Here we present a new compilation of aerosol observations including composition, a methodology for comparing the datasets to model output, and show the implications of these results using one model.
Georgios I. Gkatzelis, Matthew M. Coggon, Chelsea E. Stockwell, Rebecca S. Hornbrook, Hannah Allen, Eric C. Apel, Megan M. Bela, Donald R. Blake, Ilann Bourgeois, Steven S. Brown, Pedro Campuzano-Jost, Jason M. St. Clair, James H. Crawford, John D. Crounse, Douglas A. Day, Joshua P. DiGangi, Glenn S. Diskin, Alan Fried, Jessica B. Gilman, Hongyu Guo, Johnathan W. Hair, Hannah S. Halliday, Thomas F. Hanisco, Reem Hannun, Alan Hills, L. Gregory Huey, Jose L. Jimenez, Joseph M. Katich, Aaron Lamplugh, Young Ro Lee, Jin Liao, Jakob Lindaas, Stuart A. McKeen, Tomas Mikoviny, Benjamin A. Nault, J. Andrew Neuman, John B. Nowak, Demetrios Pagonis, Jeff Peischl, Anne E. Perring, Felix Piel, Pamela S. Rickly, Michael A. Robinson, Andrew W. Rollins, Thomas B. Ryerson, Melinda K. Schueneman, Rebecca H. Schwantes, Joshua P. Schwarz, Kanako Sekimoto, Vanessa Selimovic, Taylor Shingler, David J. Tanner, Laura Tomsche, Krystal T. Vasquez, Patrick R. Veres, Rebecca Washenfelder, Petter Weibring, Paul O. Wennberg, Armin Wisthaler, Glenn M. Wolfe, Caroline C. Womack, Lu Xu, Katherine Ball, Robert J. Yokelson, and Carsten Warneke
Atmos. Chem. Phys., 24, 929–956, https://doi.org/10.5194/acp-24-929-2024, https://doi.org/10.5194/acp-24-929-2024, 2024
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This study reports emissions of gases and particles from wildfires. These emissions are related to chemical proxies that can be measured by satellite and incorporated into models to improve predictions of wildfire impacts on air quality and climate.
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.
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.
Lixu Jin, Wade Permar, Vanessa Selimovic, Damien Ketcherside, Robert J. Yokelson, Rebecca S. Hornbrook, Eric C. Apel, I-Ting Ku, Jeffrey L. Collett Jr., Amy P. Sullivan, Daniel A. Jaffe, Jeffrey R. Pierce, Alan Fried, Matthew M. Coggon, Georgios I. Gkatzelis, Carsten Warneke, Emily V. Fischer, and Lu Hu
Atmos. Chem. Phys., 23, 5969–5991, https://doi.org/10.5194/acp-23-5969-2023, https://doi.org/10.5194/acp-23-5969-2023, 2023
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Air quality in the USA has been improving since 1970 due to anthropogenic emission reduction. Those gains have been partly offset by increased wildfire pollution in the western USA in the past 20 years. Still, we do not understand wildfire emissions well due to limited measurements. Here, we used a global transport model to evaluate and constrain current knowledge of wildfire emissions with recent observational constraints, showing the underestimation of wildfire emissions in the western USA.
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.
Hao Guo, Clare M. Flynn, Michael J. Prather, Sarah A. Strode, Stephen D. Steenrod, Louisa Emmons, Forrest Lacey, Jean-Francois Lamarque, Arlene M. Fiore, Gus Correa, Lee T. Murray, Glenn M. Wolfe, Jason M. St. Clair, Michelle Kim, John Crounse, Glenn Diskin, Joshua DiGangi, Bruce C. Daube, Roisin Commane, Kathryn McKain, Jeff Peischl, Thomas B. Ryerson, Chelsea Thompson, Thomas F. Hanisco, Donald Blake, Nicola J. Blake, Eric C. Apel, Rebecca S. Hornbrook, James W. Elkins, Eric J. Hintsa, Fred L. Moore, and Steven C. Wofsy
Atmos. Chem. Phys., 23, 99–117, https://doi.org/10.5194/acp-23-99-2023, https://doi.org/10.5194/acp-23-99-2023, 2023
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We have prepared a unique and unusual result from the recent ATom aircraft mission: a measurement-based derivation of the production and loss rates of ozone and methane over the ocean basins. These are the key products of chemistry models used in assessments but have thus far lacked observational metrics. It also shows the scales of variability of atmospheric chemical rates and provides a major challenge to the atmospheric models.
Thibaud M. Fritz, Sebastian D. Eastham, Louisa K. Emmons, Haipeng Lin, Elizabeth W. Lundgren, Steve Goldhaber, Steven R. H. Barrett, and Daniel J. Jacob
Geosci. Model Dev., 15, 8669–8704, https://doi.org/10.5194/gmd-15-8669-2022, https://doi.org/10.5194/gmd-15-8669-2022, 2022
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We bring the state-of-the-science chemistry module GEOS-Chem into the Community Earth System Model (CESM). We show that some known differences between results from GEOS-Chem and CESM's CAM-chem chemistry module may be due to the configuration of model meteorology rather than inherent differences in the model chemistry. This is a significant step towards a truly modular Earth system model and allows two strong but currently separate research communities to benefit from each other's advances.
Ali Jalali, Kaley A. Walker, Kimberly Strong, Rebecca R. Buchholz, Merritt N. Deeter, Debra Wunch, Sébastien Roche, Tyler Wizenberg, Erik Lutsch, Erin McGee, Helen M. Worden, Pierre Fogal, and James R. Drummond
Atmos. Meas. Tech., 15, 6837–6863, https://doi.org/10.5194/amt-15-6837-2022, https://doi.org/10.5194/amt-15-6837-2022, 2022
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This study validates MOPITT version 8 carbon monoxide measurements over the Canadian high Arctic for the period 2006 to 2019. The MOPITT products from different detector pixels and channels are compared with ground-based measurements from the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada. These results show good consistency between the satellite and ground-based measurements and provide guidance on the usage of these MOPITT data at high latitudes.
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.
Nicole A. June, Anna L. Hodshire, Elizabeth B. Wiggins, Edward L. Winstead, Claire E. Robinson, K. Lee Thornhill, Kevin J. Sanchez, Richard H. Moore, Demetrios Pagonis, Hongyu Guo, Pedro Campuzano-Jost, Jose L. Jimenez, Matthew M. Coggon, Jonathan M. Dean-Day, T. Paul Bui, Jeff Peischl, Robert J. Yokelson, Matthew J. Alvarado, Sonia M. Kreidenweis, Shantanu H. Jathar, and Jeffrey R. Pierce
Atmos. Chem. Phys., 22, 12803–12825, https://doi.org/10.5194/acp-22-12803-2022, https://doi.org/10.5194/acp-22-12803-2022, 2022
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The evolution of organic aerosol composition and size is uncertain due to variability within and between smoke plumes. We examine the impact of plume concentration on smoke evolution from smoke plumes sampled by the NASA DC-8 during FIREX-AQ. We find that observed organic aerosol and size distribution changes are correlated to plume aerosol mass concentrations. Additionally, coagulation explains the majority of the observed growth.
Robert J. Yokelson, Bambang H. Saharjo, Chelsea E. Stockwell, Erianto I. Putra, Thilina Jayarathne, Acep Akbar, Israr Albar, Donald R. Blake, Laura L. B. Graham, Agus Kurniawan, Simone Meinardi, Diah Ningrum, Ati D. Nurhayati, Asmadi Saad, Niken Sakuntaladewi, Eko Setianto, Isobel J. Simpson, Elizabeth A. Stone, Sigit Sutikno, Andri Thomas, Kevin C. Ryan, and Mark A. Cochrane
Atmos. Chem. Phys., 22, 10173–10194, https://doi.org/10.5194/acp-22-10173-2022, https://doi.org/10.5194/acp-22-10173-2022, 2022
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Fire plus non-fire GHG emissions associated with draining peatlands are the largest per area of any land use change considered by the IPCC. To characterize average and variability for tropical peat fire emissions, highly mobile smoke sampling teams were deployed across four Indonesian provinces to explore an extended interannual, climatic, and spatial range. Large adjustments to IPCC-recommended emissions are suggested. Lab data bolster an extensive emissions database for tropical peat fires.
Yutong Liang, Christos Stamatis, Edward C. Fortner, Rebecca A. Wernis, Paul Van Rooy, Francesca Majluf, Tara I. Yacovitch, Conner Daube, Scott C. Herndon, Nathan M. Kreisberg, Kelley C. Barsanti, and Allen H. Goldstein
Atmos. Chem. Phys., 22, 9877–9893, https://doi.org/10.5194/acp-22-9877-2022, https://doi.org/10.5194/acp-22-9877-2022, 2022
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This article reports the measurements of organic compounds emitted from western US wildfires. We identified and quantified 240 particle-phase compounds and 72 gas-phase compounds emitted in wildfire and related the emissions to the modified combustion efficiency. Higher emissions of diterpenoids and monoterpenes were observed, likely due to distillation from unburned heated vegetation. Our results can benefit future source apportionment and modeling studies as well as exposure assessments.
Christos Stamatis and Kelley Claire Barsanti
Atmos. Meas. Tech., 15, 2591–2606, https://doi.org/10.5194/amt-15-2591-2022, https://doi.org/10.5194/amt-15-2591-2022, 2022
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Building on the identification of hundreds of gas-phase chemicals in smoke samples from laboratory and field studies, an algorithm was developed that successfully identified chemical patterns that were consistent among types of trees and unique between types of trees that are common fuels in western coniferous forests. The algorithm is a promising approach for selecting chemical speciation profiles for air quality modeling using a highly reduced suite of measured compounds.
Qi Li, Jia Jiang, Isaac K. Afreh, Kelley C. Barsanti, and David R. Cocker III
Atmos. Chem. Phys., 22, 3131–3147, https://doi.org/10.5194/acp-22-3131-2022, https://doi.org/10.5194/acp-22-3131-2022, 2022
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Chamber-derived secondary organic aerosol (SOA) yields from camphene are reported for the first time. The role of peroxy radicals (RO2) was investigated using chemically detailed box models. We observed higher SOA yields (up to 64 %) in the experiments with added NOx than without due to the formation of highly oxygenated organic molecules (HOMs) when
NOx is present. This work can improve the representation of camphene in air quality models and provide insights into other monoterpene studies.
Michael A. Battaglia Jr., Nicholas Balasus, Katherine Ball, Vanessa Caicedo, Ruben Delgado, Annmarie G. Carlton, and Christopher J. Hennigan
Atmos. Chem. Phys., 21, 18271–18281, https://doi.org/10.5194/acp-21-18271-2021, https://doi.org/10.5194/acp-21-18271-2021, 2021
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This study characterizes aerosol liquid water content and aerosol pH at a land–water transition site near Baltimore, Maryland. We characterize the effects of unique meteorology associated with the close proximity to the Chesapeake Bay and episodic NH3 events derived from industrial and agricultural sources on aerosol chemistry during the summer. We also examine two events where primary Bay emissions underwent aging in the polluted urban atmosphere.
Zachary C. J. Decker, Michael A. Robinson, Kelley C. Barsanti, Ilann Bourgeois, Matthew M. Coggon, Joshua P. DiGangi, Glenn S. Diskin, Frank M. Flocke, Alessandro Franchin, Carley D. Fredrickson, Georgios I. Gkatzelis, Samuel R. Hall, Hannah Halliday, Christopher D. Holmes, L. Gregory Huey, Young Ro Lee, Jakob Lindaas, Ann M. Middlebrook, Denise D. Montzka, Richard Moore, J. Andrew Neuman, John B. Nowak, Brett B. Palm, Jeff Peischl, Felix Piel, Pamela S. Rickly, Andrew W. Rollins, Thomas B. Ryerson, Rebecca H. Schwantes, Kanako Sekimoto, Lee Thornhill, Joel A. Thornton, Geoffrey S. Tyndall, Kirk Ullmann, Paul Van Rooy, Patrick R. Veres, Carsten Warneke, Rebecca A. Washenfelder, Andrew J. Weinheimer, Elizabeth Wiggins, Edward Winstead, Armin Wisthaler, Caroline Womack, and Steven S. Brown
Atmos. Chem. Phys., 21, 16293–16317, https://doi.org/10.5194/acp-21-16293-2021, https://doi.org/10.5194/acp-21-16293-2021, 2021
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To understand air quality impacts from wildfires, we need an accurate picture of how wildfire smoke changes chemically both day and night as sunlight changes the chemistry of smoke. We present a chemical analysis of wildfire smoke as it changes from midday through the night. We use aircraft observations from the FIREX-AQ field campaign with a chemical box model. We find that even under sunlight typical
nighttimechemistry thrives and controls the fate of key smoke plume chemical processes.
Hélène Angot, Connor Davel, Christine Wiedinmyer, Gabrielle Pétron, Jashan Chopra, Jacques Hueber, Brendan Blanchard, Ilann Bourgeois, Isaac Vimont, Stephen A. Montzka, Ben R. Miller, James W. Elkins, and Detlev Helmig
Atmos. Chem. Phys., 21, 15153–15170, https://doi.org/10.5194/acp-21-15153-2021, https://doi.org/10.5194/acp-21-15153-2021, 2021
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After a multidecadal global decline in atmospheric abundance of ethane and propane (precursors of tropospheric ozone and aerosols), previous work showed a reversal of this trend in 2009–2015 in the Northern Hemisphere due to the growth in oil and natural gas production in North America. Here we show a temporary pause in the growth of atmospheric ethane and propane in 2015–2018 and highlight the critical need for additional top-down studies to further constrain ethane and propane emissions.
Xinxin Ye, Pargoal Arab, Ravan Ahmadov, Eric James, Georg A. Grell, Bradley Pierce, Aditya Kumar, Paul Makar, Jack Chen, Didier Davignon, Greg R. Carmichael, Gonzalo Ferrada, Jeff McQueen, Jianping Huang, Rajesh Kumar, Louisa Emmons, Farren L. Herron-Thorpe, Mark Parrington, Richard Engelen, Vincent-Henri Peuch, Arlindo da Silva, Amber Soja, Emily Gargulinski, Elizabeth Wiggins, Johnathan W. Hair, Marta Fenn, Taylor Shingler, Shobha Kondragunta, Alexei Lyapustin, Yujie Wang, Brent Holben, David M. Giles, and Pablo E. Saide
Atmos. Chem. Phys., 21, 14427–14469, https://doi.org/10.5194/acp-21-14427-2021, https://doi.org/10.5194/acp-21-14427-2021, 2021
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Wildfire smoke has crucial impacts on air quality, while uncertainties in the numerical forecasts remain significant. We present an evaluation of 12 real-time forecasting systems. Comparison of predicted smoke emissions suggests a large spread in magnitudes, with temporal patterns deviating from satellite detections. The performance for AOD and surface PM2.5 and their discrepancies highlighted the role of accurately represented spatiotemporal emission profiles in improving smoke forecasts.
Hao Guo, Clare M. Flynn, Michael J. Prather, Sarah A. Strode, Stephen D. Steenrod, Louisa Emmons, Forrest Lacey, Jean-Francois Lamarque, Arlene M. Fiore, Gus Correa, Lee T. Murray, Glenn M. Wolfe, Jason M. St. Clair, Michelle Kim, John Crounse, Glenn Diskin, Joshua DiGangi, Bruce C. Daube, Roisin Commane, Kathryn McKain, Jeff Peischl, Thomas B. Ryerson, Chelsea Thompson, Thomas F. Hanisco, Donald Blake, Nicola J. Blake, Eric C. Apel, Rebecca S. Hornbrook, James W. Elkins, Eric J. Hintsa, Fred L. Moore, and Steven Wofsy
Atmos. Chem. Phys., 21, 13729–13746, https://doi.org/10.5194/acp-21-13729-2021, https://doi.org/10.5194/acp-21-13729-2021, 2021
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The NASA Atmospheric Tomography (ATom) mission built a climatology of the chemical composition of tropospheric air parcels throughout the middle of the Pacific and Atlantic oceans. The level of detail allows us to reconstruct the photochemical budgets of O3 and CH4 over these vast, remote regions. We find that most of the chemical heterogeneity is captured at the resolution used in current global chemistry models and that the majority of reactivity occurs in the
hottest20 % of parcels.
Haipeng Lin, Daniel J. Jacob, Elizabeth W. Lundgren, Melissa P. Sulprizio, Christoph A. Keller, Thibaud M. Fritz, Sebastian D. Eastham, Louisa K. Emmons, Patrick C. Campbell, Barry Baker, Rick D. Saylor, and Raffaele Montuoro
Geosci. Model Dev., 14, 5487–5506, https://doi.org/10.5194/gmd-14-5487-2021, https://doi.org/10.5194/gmd-14-5487-2021, 2021
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Emissions are a central component of atmospheric chemistry models. The Harmonized Emissions Component (HEMCO) is a software component for computing emissions from a user-selected ensemble of emission inventories and algorithms. It allows users to select, add, and scale emissions from different sources through a configuration file with no change to the model source code. We demonstrate the implementation of HEMCO in several models, all sharing the same HEMCO core code and database library.
Nicholas Balasus, Michael A. Battaglia Jr., Katherine Ball, Vanessa Caicedo, Ruben Delgado, Annmarie G. Carlton, and Christopher J. Hennigan
Atmos. Chem. Phys., 21, 13051–13065, https://doi.org/10.5194/acp-21-13051-2021, https://doi.org/10.5194/acp-21-13051-2021, 2021
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Measurements of aerosol and gas composition were carried out at a land–water transition site near Baltimore, MD. Gas-phase ammonia concentrations were highly elevated compared to measurements at a nearby inland site. Our analysis reveals that NH2 was from both industrial and agricultural sources. This had a pronounced effect on aerosol chemical composition at the site, most notably contributing to episodic spikes of aerosol nitrate.
Sabrina Chee, Kelley Barsanti, James N. Smith, and Nanna Myllys
Atmos. Chem. Phys., 21, 11637–11654, https://doi.org/10.5194/acp-21-11637-2021, https://doi.org/10.5194/acp-21-11637-2021, 2021
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We explored molecular properties affecting atmospheric particle formation efficiency and derived a parameterization between particle formation rate and heterodimer concentration, which showed good agreement to previously reported experimental data. Considering the simplicity of calculating heterodimer concentration, this approach has potential to improve estimates of global cloud condensation nuclei in models that are limited by the computational expense of calculating particle formation rate.
Isaac Kwadjo Afreh, Bernard Aumont, Marie Camredon, and Kelley Claire Barsanti
Atmos. Chem. Phys., 21, 11467–11487, https://doi.org/10.5194/acp-21-11467-2021, https://doi.org/10.5194/acp-21-11467-2021, 2021
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This is the first mechanistic modeling study of secondary organic aerosol (SOA) from the understudied monoterpene, camphene. The semi-explicit chemical model GECKO-A predicted camphene SOA yields that were ~2 times α-pinene. Using 50/50 α-pinene + limonene as a surrogate for camphene increased predicted SOA mass from biomass burning fuels by up to ~100 %. The accurate representation of camphene in air quality models can improve predictions of SOA when camphene is a dominant monoterpene.
Wenfu Tang, David P. Edwards, Louisa K. Emmons, Helen M. Worden, Laura M. Judd, Lok N. Lamsal, Jassim A. Al-Saadi, Scott J. Janz, James H. Crawford, Merritt N. Deeter, Gabriele Pfister, Rebecca R. Buchholz, Benjamin Gaubert, and Caroline R. Nowlan
Atmos. Meas. Tech., 14, 4639–4655, https://doi.org/10.5194/amt-14-4639-2021, https://doi.org/10.5194/amt-14-4639-2021, 2021
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We use high-resolution airborne mapping spectrometer measurements to assess sub-grid variability within satellite pixels over urban regions. The sub-grid variability within satellite pixels increases with increasing satellite pixel sizes. Temporal variability within satellite pixels decreases with increasing satellite pixel sizes. This work is particularly relevant and useful for future satellite design, satellite data interpretation, and point-grid data comparisons.
Yaman Liu, Xinyi Dong, Minghuai Wang, Louisa K. Emmons, Yawen Liu, Yuan Liang, Xiao Li, and Manish Shrivastava
Atmos. Chem. Phys., 21, 8003–8021, https://doi.org/10.5194/acp-21-8003-2021, https://doi.org/10.5194/acp-21-8003-2021, 2021
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Secondary organic aerosol (SOA) is considered one of the most important uncertainties in climate modeling. We evaluate SOA performance in the Community Earth System Model version 2.1 (CESM2.1) configured with the Community Atmosphere Model version 6 with chemistry (CAM6-Chem) through a long-term simulation (1988–2019) with observations in the United States, which indicates monoterpene-formed SOA contributes most to the overestimation of SOA at the surface and underestimation in the upper air.
Fernando Chouza, Thierry Leblanc, Mark Brewer, Patrick Wang, Sabino Piazzolla, Gabriele Pfister, Rajesh Kumar, Carl Drews, Simone Tilmes, Louisa Emmons, and Matthew Johnson
Atmos. Chem. Phys., 21, 6129–6153, https://doi.org/10.5194/acp-21-6129-2021, https://doi.org/10.5194/acp-21-6129-2021, 2021
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The tropospheric ozone lidar at the JPL Table Mountain Facility (TMF) was used to investigate the impact of Los Angeles (LA) Basin pollution transport and stratospheric intrusions in the planetary boundary layer on the San Gabriel Mountains. The results of this study indicate a dominant role of the LA Basin pollution on days when high ozone levels were observed at TMF (March–October period).
Paul T. Griffiths, Lee T. Murray, Guang Zeng, Youngsub Matthew Shin, N. Luke Abraham, Alexander T. Archibald, Makoto Deushi, Louisa K. Emmons, Ian E. Galbally, Birgit Hassler, Larry W. Horowitz, James Keeble, Jane Liu, Omid Moeini, Vaishali Naik, Fiona M. O'Connor, Naga Oshima, David Tarasick, Simone Tilmes, Steven T. Turnock, Oliver Wild, Paul J. Young, and Prodromos Zanis
Atmos. Chem. Phys., 21, 4187–4218, https://doi.org/10.5194/acp-21-4187-2021, https://doi.org/10.5194/acp-21-4187-2021, 2021
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We analyse the CMIP6 Historical and future simulations for tropospheric ozone, a species which is important for many aspects of atmospheric chemistry. We show that the current generation of models agrees well with observations, being particularly successful in capturing trends in surface ozone and its vertical distribution in the troposphere. We analyse the factors that control ozone and show that they evolve over the period of the CMIP6 experiments.
Duseong S. Jo, Alma Hodzic, Louisa K. Emmons, Simone Tilmes, Rebecca H. Schwantes, Michael J. Mills, Pedro Campuzano-Jost, Weiwei Hu, Rahul A. Zaveri, Richard C. Easter, Balwinder Singh, Zheng Lu, Christiane Schulz, Johannes Schneider, John E. Shilling, Armin Wisthaler, and Jose L. Jimenez
Atmos. Chem. Phys., 21, 3395–3425, https://doi.org/10.5194/acp-21-3395-2021, https://doi.org/10.5194/acp-21-3395-2021, 2021
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Secondary organic aerosol (SOA) is a major component of submicron particulate matter, but there are a lot of uncertainties in the future prediction of SOA. We used CESM 2.1 to investigate future IEPOX SOA concentration changes. The explicit chemistry predicted substantial changes in IEPOX SOA depending on the future scenario, but the parameterization predicted weak changes due to simplified chemistry, which shows the importance of correct physicochemical dependencies in future SOA prediction.
Gillian D. Thornhill, William J. Collins, Ryan J. Kramer, Dirk Olivié, Ragnhild B. Skeie, Fiona M. O'Connor, Nathan Luke Abraham, Ramiro Checa-Garcia, Susanne E. Bauer, Makoto Deushi, Louisa K. Emmons, Piers M. Forster, Larry W. Horowitz, Ben Johnson, James Keeble, Jean-Francois Lamarque, Martine Michou, Michael J. Mills, Jane P. Mulcahy, Gunnar Myhre, Pierre Nabat, Vaishali Naik, Naga Oshima, Michael Schulz, Christopher J. Smith, Toshihiko Takemura, Simone Tilmes, Tongwen Wu, Guang Zeng, and Jie Zhang
Atmos. Chem. Phys., 21, 853–874, https://doi.org/10.5194/acp-21-853-2021, https://doi.org/10.5194/acp-21-853-2021, 2021
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This paper is a study of how different constituents in the atmosphere, such as aerosols and gases like methane and ozone, affect the energy balance in the atmosphere. Different climate models were run using the same inputs to allow an easy comparison of the results and to understand where the models differ. We found the effect of aerosols is to reduce warming in the atmosphere, but this effect varies between models. Reactions between gases are also important in affecting climate.
Benjamin Gaubert, Louisa K. Emmons, Kevin Raeder, Simone Tilmes, Kazuyuki Miyazaki, Avelino F. Arellano Jr., Nellie Elguindi, Claire Granier, Wenfu Tang, Jérôme Barré, Helen M. Worden, Rebecca R. Buchholz, David P. Edwards, Philipp Franke, Jeffrey L. Anderson, Marielle Saunois, Jason Schroeder, Jung-Hun Woo, Isobel J. Simpson, Donald R. Blake, Simone Meinardi, Paul O. Wennberg, John Crounse, Alex Teng, Michelle Kim, Russell R. Dickerson, Hao He, Xinrong Ren, Sally E. Pusede, and Glenn S. Diskin
Atmos. Chem. Phys., 20, 14617–14647, https://doi.org/10.5194/acp-20-14617-2020, https://doi.org/10.5194/acp-20-14617-2020, 2020
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This study investigates carbon monoxide pollution in East Asia during spring using a numerical model, satellite remote sensing, and aircraft measurements. We found an underestimation of emission sources. Correcting the emission bias can improve air quality forecasting of carbon monoxide and other species including ozone. Results also suggest that controlling VOC and CO emissions, in addition to widespread NOx controls, can improve ozone pollution over East Asia.
Steven T. Turnock, Robert J. Allen, Martin Andrews, Susanne E. Bauer, Makoto Deushi, Louisa Emmons, Peter Good, Larry Horowitz, Jasmin G. John, Martine Michou, Pierre Nabat, Vaishali Naik, David Neubauer, Fiona M. O'Connor, Dirk Olivié, Naga Oshima, Michael Schulz, Alistair Sellar, Sungbo Shim, Toshihiko Takemura, Simone Tilmes, Kostas Tsigaridis, Tongwen Wu, and Jie Zhang
Atmos. Chem. Phys., 20, 14547–14579, https://doi.org/10.5194/acp-20-14547-2020, https://doi.org/10.5194/acp-20-14547-2020, 2020
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A first assessment is made of the historical and future changes in air pollutants from models participating in the 6th Coupled Model Intercomparison Project (CMIP6). Substantial benefits to future air quality can be achieved in future scenarios that implement measures to mitigate climate and involve reductions in air pollutant emissions, particularly methane. However, important differences are shown between models in the future regional projection of air pollutants under the same scenario.
Lawrence I. Kleinman, Arthur J. Sedlacek III, Kouji Adachi, Peter R. Buseck, Sonya Collier, Manvendra K. Dubey, Anna L. Hodshire, Ernie Lewis, Timothy B. Onasch, Jeffery R. Pierce, John Shilling, Stephen R. Springston, Jian Wang, Qi Zhang, Shan Zhou, and Robert J. Yokelson
Atmos. Chem. Phys., 20, 13319–13341, https://doi.org/10.5194/acp-20-13319-2020, https://doi.org/10.5194/acp-20-13319-2020, 2020
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Aerosols from wildfires affect the Earth's temperature by absorbing light or reflecting it back into space. This study investigates time-dependent chemical, microphysical, and optical properties of aerosols generated by wildfires in the Pacific Northwest, USA. Wildfire smoke plumes were traversed by an instrumented aircraft at locations near the fire and up to 3.5 h travel time downwind. Although there was no net aerosol production, aerosol particles grew and became more efficient scatters.
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.
Amy E. Christiansen, Annmarie G. Carlton, and Barron H. Henderson
Atmos. Chem. Phys., 20, 11607–11624, https://doi.org/10.5194/acp-20-11607-2020, https://doi.org/10.5194/acp-20-11607-2020, 2020
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We quantify differences in surface-level fine particle mass (PM2.5) chemical composition in relation to satellite-derived cloud flags and find significant differences between clear-sky and cloud days. The work suggests that future analysis in this area is warranted.
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
James M. Roberts, Chelsea E. Stockwell, Robert J. Yokelson, Joost de Gouw, Yong Liu, Vanessa Selimovic, Abigail R. Koss, Kanako Sekimoto, Matthew M. Coggon, Bin Yuan, Kyle J. Zarzana, Steven S. Brown, Cristina Santin, Stefan H. Doerr, and Carsten Warneke
Atmos. Chem. Phys., 20, 8807–8826, https://doi.org/10.5194/acp-20-8807-2020, https://doi.org/10.5194/acp-20-8807-2020, 2020
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We measured total reactive nitrogen, Nr, in lab fires from western North American fuels, along with measurements of individual nitrogen compounds. We measured the amount of N that gets converted to inactive compounds (avg. 70 %), and the amount that is accounted for by individual species (85 % of remaining N). We provide guidelines for how the reactive nitrogen is distributed among individual compounds such as NOx and ammonia. This will help estimates and predictions of wildfire emissions.
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.
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
Md. Robiul Islam, Thilina Jayarathne, Isobel J. Simpson, Benjamin Werden, John Maben, Ashley Gilbert, Puppala S. Praveen, Sagar Adhikari, Arnico K. Panday, Maheswar Rupakheti, Donald R. Blake, Robert J. Yokelson, Peter F. DeCarlo, William C. Keene, and Elizabeth A. Stone
Atmos. Chem. Phys., 20, 2927–2951, https://doi.org/10.5194/acp-20-2927-2020, https://doi.org/10.5194/acp-20-2927-2020, 2020
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The Kathmandu Valley experiences high levels of air pollution. In this study, atmospheric gases and particulate matter were characterized by online and off-line measurements, with an emphasis on understanding their sources. The major sources of particulate matter and trace gases were identified as garbage burning, biomass burning, and vehicles. The majority of secondary organic aerosol was attributed to anthropogenic precursors, while a minority was attributed to biogenic gases.
Therese S. Carter, Colette L. Heald, Jose L. Jimenez, Pedro Campuzano-Jost, Yutaka Kondo, Nobuhiro Moteki, Joshua P. Schwarz, Christine Wiedinmyer, Anton S. Darmenov, Arlindo M. da Silva, and Johannes W. Kaiser
Atmos. Chem. Phys., 20, 2073–2097, https://doi.org/10.5194/acp-20-2073-2020, https://doi.org/10.5194/acp-20-2073-2020, 2020
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Fires and the smoke they emit impact air quality, health, and climate, but the abundance and properties of smoke remain uncertain and poorly constrained. To explore this, we compare model simulations driven by four commonly-used fire emission inventories with surface, aloft, and satellite observations. We show that across inventories smoke emissions differ by factors of 4 to 7 over North America, challenging our ability to accurately characterize the impact of smoke on air quality and climate.
Lauren T. Fleming, Peng Lin, James M. Roberts, Vanessa Selimovic, Robert Yokelson, Julia Laskin, Alexander Laskin, and Sergey A. Nizkorodov
Atmos. Chem. Phys., 20, 1105–1129, https://doi.org/10.5194/acp-20-1105-2020, https://doi.org/10.5194/acp-20-1105-2020, 2020
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We have explored the nature and stability of molecules that give biomass burning smoke its faint brown color. Different types of biomass fuels were burned and the resulting smoke was collected for a detailed chemical analysis. We found that brown molecules in smoke become less colored when they are irradiated by sunlight, but this photobleaching process is very slow. This means that biomass burning smoke will remain brown-colored for a long time and efficiently warm up the atmosphere.
Matthew M. Coggon, Christopher Y. Lim, Abigail R. Koss, Kanako Sekimoto, Bin Yuan, Jessica B. Gilman, David H. Hagan, Vanessa Selimovic, Kyle J. Zarzana, Steven S. Brown, James M. Roberts, Markus Müller, Robert Yokelson, Armin Wisthaler, Jordan E. Krechmer, Jose L. Jimenez, Christopher Cappa, Jesse H. Kroll, Joost de Gouw, and Carsten Warneke
Atmos. Chem. Phys., 19, 14875–14899, https://doi.org/10.5194/acp-19-14875-2019, https://doi.org/10.5194/acp-19-14875-2019, 2019
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Wildfire emissions significantly contribute to adverse air quality; however, the chemical processes that lead to hazardous pollutants, such as ozone, are not fully understood. In this study, we describe laboratory experiments where we simulate the atmospheric chemistry of smoke emitted from a range of biomass fuels. We show that certain understudied compounds, such as furans and phenolic compounds, are significant contributors to pollutants formed as a result of typical atmospheric oxidation.
Jiajue Chai, David J. Miller, Eric Scheuer, Jack Dibb, Vanessa Selimovic, Robert Yokelson, Kyle J. Zarzana, Steven S. Brown, Abigail R. Koss, Carsten Warneke, and Meredith Hastings
Atmos. Meas. Tech., 12, 6303–6317, https://doi.org/10.5194/amt-12-6303-2019, https://doi.org/10.5194/amt-12-6303-2019, 2019
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Isotopic analysis offers a potential tool to distinguish between sources and interpret transformation pathways of atmospheric species. We applied recently developed techniques in our lab to characterize the isotopic composition of reactive nitrogen species (NOx, HONO, HNO3, pNO3-) in fresh biomass burning emissions. Intercomparison with other techniques confirms the suitability of our methods, allowing for future applications of our techniques in a variety of environments.
Chi-Tsan Wang, Christine Wiedinmyer, Kirsti Ashworth, Peter C. Harley, John Ortega, Quazi Z. Rasool, and William Vizuete
Atmos. Chem. Phys., 19, 13973–13987, https://doi.org/10.5194/acp-19-13973-2019, https://doi.org/10.5194/acp-19-13973-2019, 2019
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The legal commercialization of cannabis has created a new and almost unregulated industry. Here we present the first inventory of volatile organic compound emissions from cannabis cultivation facilities (CCFs) for Colorado. When applied within a regulatory air quality model to predict regional ozone impacts, our inventory results in net ozone formation near CCFs with the largest increases in Denver County. However, our inventory is highly uncertain and we identify future critical data needs.
Hayley S. Glicker, Michael J. Lawler, John Ortega, Suzane S. de Sá, Scot T. Martin, Paulo Artaxo, Oscar Vega Bustillos, Rodrigo de Souza, Julio Tota, Annmarie Carlton, and James N. Smith
Atmos. Chem. Phys., 19, 13053–13066, https://doi.org/10.5194/acp-19-13053-2019, https://doi.org/10.5194/acp-19-13053-2019, 2019
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An understanding of the chemical composition of the smallest particles in the air over the Amazon Basin provides insights into the natural and human-caused influences on particle production in this sensitive region. We present measurements of the composition of sub-100 nm diameter particles performed during the wet season and identify unique constituents that point to both natural and human-caused sources and processes.
Jacob K. Hedelius, Tai-Long He, Dylan B. A. Jones, Bianca C. Baier, Rebecca R. Buchholz, Martine De Mazière, Nicholas M. Deutscher, Manvendra K. Dubey, Dietrich G. Feist, David W. T. Griffith, Frank Hase, Laura T. Iraci, Pascal Jeseck, Matthäus Kiel, Rigel Kivi, Cheng Liu, Isamu Morino, Justus Notholt, Young-Suk Oh, Hirofumi Ohyama, David F. Pollard, Markus Rettinger, Sébastien Roche, Coleen M. Roehl, Matthias Schneider, Kei Shiomi, Kimberly Strong, Ralf Sussmann, Colm Sweeney, Yao Té, Osamu Uchino, Voltaire A. Velazco, Wei Wang, Thorsten Warneke, Paul O. Wennberg, Helen M. Worden, and Debra Wunch
Atmos. Meas. Tech., 12, 5547–5572, https://doi.org/10.5194/amt-12-5547-2019, https://doi.org/10.5194/amt-12-5547-2019, 2019
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We seek ways to improve the accuracy of column measurements of carbon monoxide (CO) – an important tracer of pollution – made from the MOPITT satellite instrument. We devise a filtering scheme which reduces the scatter and also eliminates bias among the MOPITT detectors. Compared to ground-based observations, MOPITT measurements are about 6 %–8 % higher. When MOPITT data are implemented in a global assimilation model, they tend to reduce the model mismatch with aircraft measurements.
Fang Li, Maria Val Martin, Meinrat O. Andreae, Almut Arneth, Stijn Hantson, Johannes W. Kaiser, Gitta Lasslop, Chao Yue, Dominique Bachelet, Matthew Forrest, Erik Kluzek, Xiaohong Liu, Stephane Mangeon, Joe R. Melton, Daniel S. Ward, Anton Darmenov, Thomas Hickler, Charles Ichoku, Brian I. Magi, Stephen Sitch, Guido R. van der Werf, Christine Wiedinmyer, and Sam S. Rabin
Atmos. Chem. Phys., 19, 12545–12567, https://doi.org/10.5194/acp-19-12545-2019, https://doi.org/10.5194/acp-19-12545-2019, 2019
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Fire emissions are critical for atmospheric composition, climate, carbon cycle, and air quality. We provide the first global multi-model fire emission reconstructions for 1700–2012, including carbon and 33 species of trace gases and aerosols, based on the nine state-of-the-art global fire models that participated in FireMIP. We also provide information on the recent status and limitations of the model-based reconstructions and identify the main uncertainty sources in their long-term changes.
Laura Kiely, Dominick V. Spracklen, Christine Wiedinmyer, Luke Conibear, Carly L. Reddington, Scott Archer-Nicholls, Douglas Lowe, Stephen R. Arnold, Christoph Knote, Md Firoz Khan, Mohd Talib Latif, Mikinori Kuwata, Sri Hapsari Budisulistiorini, and Lailan Syaufina
Atmos. Chem. Phys., 19, 11105–11121, https://doi.org/10.5194/acp-19-11105-2019, https://doi.org/10.5194/acp-19-11105-2019, 2019
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In 2015, a large fire episode occurred in Indonesia, reducing air quality. Fires occurred predominantly on peatland, where large uncertainties are associated with emissions. Current fire emissions datasets underestimate peat fire emissions. We created new fire emissions data, with data specific to Indonesian peat fires. Using these emissions in simulations of particulate matter and aerosol optical depth shows an improvement over simulations using current data, when compared with observations.
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.
Min Zhong, Eri Saikawa, Alexander Avramov, Chen Chen, Boya Sun, Wenlu Ye, William C. Keene, Robert J. Yokelson, Thilina Jayarathne, Elizabeth A. Stone, Maheswar Rupakheti, and Arnico K. Panday
Atmos. Chem. Phys., 19, 8209–8228, https://doi.org/10.5194/acp-19-8209-2019, https://doi.org/10.5194/acp-19-8209-2019, 2019
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Air pollution is one of the most pressing environmental issues in the Kathmandu Valley, the capital city of Nepal. We estimated emissions from two of the major source types in the valley (vehicles and brick kilns) and found that they have significant impacts on air quality surrounding the valley. Our results highlight the importance of improving local emissions estimates for air quality modeling.
Wenfu Tang, Avelino F. Arellano, Benjamin Gaubert, Kazuyuki Miyazaki, and Helen M. Worden
Atmos. Chem. Phys., 19, 4269–4288, https://doi.org/10.5194/acp-19-4269-2019, https://doi.org/10.5194/acp-19-4269-2019, 2019
Vanessa Selimovic, Robert J. Yokelson, Gavin R. McMeeking, and Sarah Coefield
Atmos. Chem. Phys., 19, 3905–3926, https://doi.org/10.5194/acp-19-3905-2019, https://doi.org/10.5194/acp-19-3905-2019, 2019
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A massive wildfire smoke episode impacted the western US and Canada in summer 2017. We measured CO, other trace gases, PM, BC, and aerosol optical properties at a heavily impacted, ground-based site affected by this event. Brown carbon diminished as smoke aged but was a persistent component of the regional smoke, accounting for about half of aerosol absorption at 401 nm on average. The PM / CO ratios suggested aerosol evaporation was dominant at the surface at smoke ages of up to ~ 1–2 days.
Ivan Ortega, Rebecca R. Buchholz, Emrys G. Hall, Dale F. Hurst, Allen F. Jordan, and James W. Hannigan
Atmos. Meas. Tech., 12, 873–890, https://doi.org/10.5194/amt-12-873-2019, https://doi.org/10.5194/amt-12-873-2019, 2019
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In this work we evaluate the accuracy of water vapor ground-based FTIR retrievals in the lower and upper troposphere using coincident high-quality vertically resolved balloon-borne NOAA FPH measurements. Our results suggest that highly structured water vapor vertical gradients are captured with the FTIR and found a negligible bias in the immediate layer above the instrument altitude accounting for a water vapor time variability of less than 2 %.
Dagny A. Ullmann, Mallory L. Hinks, Adrian M. Maclean, Christopher L. Butenhoff, James W. Grayson, Kelley Barsanti, Jose L. Jimenez, Sergey A. Nizkorodov, Saeid Kamal, and Allan K. Bertram
Atmos. Chem. Phys., 19, 1491–1503, https://doi.org/10.5194/acp-19-1491-2019, https://doi.org/10.5194/acp-19-1491-2019, 2019
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We measured the viscosity and diffusion of organic molecules in secondary organic aerosol (SOA) generated from the ozonolysis of limonene. The results suggest that the mixing times of large organics in the SOA studied are short (< 1 h) for conditions found in the planetary boundary layer. The results also show that the Stokes–Einstein equation gives accurate predictions of diffusion coefficients of large organics within the studied SOA up to a viscosity of 102 to 104 Pa s.
Coty N. Jen, Lindsay E. Hatch, Vanessa Selimovic, Robert J. Yokelson, Robert Weber, Arantza E. Fernandez, Nathan M. Kreisberg, Kelley C. Barsanti, and Allen H. Goldstein
Atmos. Chem. Phys., 19, 1013–1026, https://doi.org/10.5194/acp-19-1013-2019, https://doi.org/10.5194/acp-19-1013-2019, 2019
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Wildfires in the western US are occurring more frequently and burning larger land areas. Smoke from these fires will play a greater role in regional air quality and atmospheric chemistry than in the past. To help fire and climate modelers and atmospheric experimentalists better understand how smoke impacts the environment, we have separated, identified, classified, and quantified the thousands of organic compounds found in smoke and related their amounts emitted to fire conditions.
Lindsay E. Hatch, Albert Rivas-Ubach, Coty N. Jen, Mary Lipton, Allen H. Goldstein, and Kelley C. Barsanti
Atmos. Chem. Phys., 18, 17801–17817, https://doi.org/10.5194/acp-18-17801-2018, https://doi.org/10.5194/acp-18-17801-2018, 2018
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We demonstrate the use of solid-phase extraction (SPE) disks for the untargeted analysis of gas-phase intermediate volatility and semi-volatile organic compounds emitted from biomass burning. SPE and Teflon filter samples collected from laboratory fires were analyzed by two-dimensional gas chromatography, with distinct differences in the observed chromatographic profiles as a function of
fuel type. Fuel-dependent emissions and volatility differences among benzenediol isomers were captured.
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.
Kyle J. Zarzana, Vanessa Selimovic, Abigail R. Koss, Kanako Sekimoto, Matthew M. Coggon, Bin Yuan, William P. Dubé, Robert J. Yokelson, Carsten Warneke, Joost A. de Gouw, James M. Roberts, and Steven S. Brown
Atmos. Chem. Phys., 18, 15451–15470, https://doi.org/10.5194/acp-18-15451-2018, https://doi.org/10.5194/acp-18-15451-2018, 2018
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Emissions of glyoxal and methylglyoxal from fuels common to the western United States were measured using cavity-enhanced spectroscopy, which provides a more selective measurement of those compounds than was previously available. Primary emissions of glyoxal were lower than previously reported and showed variability between the different fuel groups. However, emissions of glyoxal relative to formaldehyde were constant across almost all the fuel groups at 6 %–7 %.
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.
J. Douglas Goetz, Michael R. Giordano, Chelsea E. Stockwell, Ted J. Christian, Rashmi Maharjan, Sagar Adhikari, Prakash V. Bhave, Puppala S. Praveen, Arnico K. Panday, Thilina Jayarathne, Elizabeth A. Stone, Robert J. Yokelson, and Peter F. DeCarlo
Atmos. Chem. Phys., 18, 14653–14679, https://doi.org/10.5194/acp-18-14653-2018, https://doi.org/10.5194/acp-18-14653-2018, 2018
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Size distributions and emission factors of submicron aerosol were quantified using online techniques for a variety of common but under-sampled combustion sources in South Asia: wood and dung cooking fires, groundwater pumps, brick kilns, trash burning, and open burning of crop residues. Optical properties (brown carbon light absorption and the absorption Ångström exponent, AAE) of the emissions were also investigated. Contextual comparisons to the literature and other NAMaSTE results were made.
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.
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.
Wenfu Tang, Avelino F. Arellano, Joshua P. DiGangi, Yonghoon Choi, Glenn S. Diskin, Anna Agustí-Panareda, Mark Parrington, Sebastien Massart, Benjamin Gaubert, Youngjae Lee, Danbi Kim, Jinsang Jung, Jinkyu Hong, Je-Woo Hong, Yugo Kanaya, Mindo Lee, Ryan M. Stauffer, Anne M. Thompson, James H. Flynn, and Jung-Hun Woo
Atmos. Chem. Phys., 18, 11007–11030, https://doi.org/10.5194/acp-18-11007-2018, https://doi.org/10.5194/acp-18-11007-2018, 2018
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.
Kanako Sekimoto, Abigail R. Koss, Jessica B. Gilman, Vanessa Selimovic, Matthew M. Coggon, Kyle J. Zarzana, Bin Yuan, Brian M. Lerner, Steven S. Brown, Carsten Warneke, Robert J. Yokelson, James M. Roberts, and Joost de Gouw
Atmos. Chem. Phys., 18, 9263–9281, https://doi.org/10.5194/acp-18-9263-2018, https://doi.org/10.5194/acp-18-9263-2018, 2018
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We found that on average 85 % of the VOC emissions from biomass burning across various fuels representative of the western US (including various coniferous and chaparral fuels) can be explained using only two emission profiles: (i) a high-temperature pyrolysis profile and (ii) a low-temperature pyrolysis profile. The high-temperature profile is quantitatively similar between different fuel types (r2 > 0.84), and likewise for the low-temperature profile.
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.
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.
Chelsea E. Stockwell, Agnieszka Kupc, Bartłomiej Witkowski, Ranajit K. Talukdar, Yong Liu, Vanessa Selimovic, Kyle J. Zarzana, Kanako Sekimoto, Carsten Warneke, Rebecca A. Washenfelder, Robert J. Yokelson, Ann M. Middlebrook, and James M. Roberts
Atmos. Meas. Tech., 11, 2749–2768, https://doi.org/10.5194/amt-11-2749-2018, https://doi.org/10.5194/amt-11-2749-2018, 2018
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This work investigates the total conversion of particle-bound nitrogen and organic carbon across platinum and molybdenum catalysts followed by NO–O3 chemiluminescence and nondispersive infrared CO2 detection. We show the instrument is an accurate particle mass measurement method and demonstrate its ability to calibrate particle mass measurement instrumentation through comparisons with a calibrated particle-into-liquid sampler coupled to an electrospray ionization source of a mass spectrometer.
Abigail R. Koss, Kanako Sekimoto, Jessica B. Gilman, Vanessa Selimovic, Matthew M. Coggon, Kyle J. Zarzana, Bin Yuan, Brian M. Lerner, Steven S. Brown, Jose L. Jimenez, Jordan Krechmer, James M. Roberts, Carsten Warneke, Robert J. Yokelson, and Joost de Gouw
Atmos. Chem. Phys., 18, 3299–3319, https://doi.org/10.5194/acp-18-3299-2018, https://doi.org/10.5194/acp-18-3299-2018, 2018
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Non-methane organic gases (NMOGs) were detected by proton-transfer-reaction mass spectrometry (PTR-ToF) during an extensive laboratory characterization of wildfire emissions. Identifications for PTR-ToF ion masses are proposed and supported by a combination of techniques. Overall excellent agreement with other instrumentation is shown. Scalable emission factors and ratios are reported for many newly reported reactive species. An analysis of chemical characteristics is presented.
Vanessa Selimovic, Robert J. Yokelson, Carsten Warneke, James M. Roberts, Joost de Gouw, James Reardon, and David W. T. Griffith
Atmos. Chem. Phys., 18, 2929–2948, https://doi.org/10.5194/acp-18-2929-2018, https://doi.org/10.5194/acp-18-2929-2018, 2018
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We burned fuels representing western US wildfires in large-scale laboratory simulations to generate relevant emissions as confirmed by lab–field comparison. We report emission factors (EFs) for light scattering and absorption and BC along with SSA at 870 and 401 nm and AAE. We report EF for 22 trace gases that are major inorganic and organic emissions from flaming and smoldering. We report trace gas EF for species rarely (NH3) or not yet measured (e.g., HONO, acetic acid) for real US wildfires.
Jingqiu Mao, Annmarie Carlton, Ronald C. Cohen, William H. Brune, Steven S. Brown, Glenn M. Wolfe, Jose L. Jimenez, Havala O. T. Pye, Nga Lee Ng, Lu Xu, V. Faye McNeill, Kostas Tsigaridis, Brian C. McDonald, Carsten Warneke, Alex Guenther, Matthew J. Alvarado, Joost de Gouw, Loretta J. Mickley, Eric M. Leibensperger, Rohit Mathur, Christopher G. Nolte, Robert W. Portmann, Nadine Unger, Mika Tosca, and Larry W. Horowitz
Atmos. Chem. Phys., 18, 2615–2651, https://doi.org/10.5194/acp-18-2615-2018, https://doi.org/10.5194/acp-18-2615-2018, 2018
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This paper is aimed at discussing progress in evaluating, diagnosing, and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models.
Thilina Jayarathne, Chelsea E. Stockwell, Ashley A. Gilbert, Kaitlyn Daugherty, Mark A. Cochrane, Kevin C. Ryan, Erianto I. Putra, Bambang H. Saharjo, Ati D. Nurhayati, Israr Albar, Robert J. Yokelson, and Elizabeth A. Stone
Atmos. Chem. Phys., 18, 2585–2600, https://doi.org/10.5194/acp-18-2585-2018, https://doi.org/10.5194/acp-18-2585-2018, 2018
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Fine particulate matter (PM2.5) emissions from Indonesian peat burning were measured in situ. Fuel-based emission factors from 6.0–29.6 gPM kg-1. Detailed chemical analysis revealed high levels of organic carbon that was primarily water insoluble, little to no detectable elemental carbon, and alkane contributions to organic carbon in the range of 6 %. These data were used to estimate that 3.2–11 Tg of PM2.5 were emitted by the 2015 peat burning episodes in Indonesia.
Thilina Jayarathne, Chelsea E. Stockwell, Prakash V. Bhave, Puppala S. Praveen, Chathurika M. Rathnayake, Md. Robiul Islam, Arnico K. Panday, Sagar Adhikari, Rashmi Maharjan, J. Douglas Goetz, Peter F. DeCarlo, Eri Saikawa, Robert J. Yokelson, and Elizabeth A. Stone
Atmos. Chem. Phys., 18, 2259–2286, https://doi.org/10.5194/acp-18-2259-2018, https://doi.org/10.5194/acp-18-2259-2018, 2018
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Emissions of fine particulate matter and its constituents were quantified for a variety of under-sampled combustion sources in South Asia: wood and dung cooking fires, generators, groundwater pumps, brick kilns, trash burning, and open burning of biomasses. Garbage burning and three-stone cooking fires were among the highest emitters, while servicing of motor vehicles significantly reduced PM. These data may be used in source apportionment and to update regional and global emission inventories.
Katherine M. Manfred, Rebecca A. Washenfelder, Nicholas L. Wagner, Gabriela Adler, Frank Erdesz, Caroline C. Womack, Kara D. Lamb, Joshua P. Schwarz, Alessandro Franchin, Vanessa Selimovic, Robert J. Yokelson, and Daniel M. Murphy
Atmos. Chem. Phys., 18, 1879–1894, https://doi.org/10.5194/acp-18-1879-2018, https://doi.org/10.5194/acp-18-1879-2018, 2018
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In this study, we use a new laser imaging nephelometer to measure the bulk aerosol scattering phase function for biomass burning aerosol from controlled fires. By comparing measurements to models for spherical and fractal particles, we demonstrate that the dominant morphology varies by fuel type. This instrument has unique capabilities to directly measure how morphology affects optical properties, and can be used in the future for important validations of remote sensing retrievals.
Haihan Chen, Anna L. Hodshire, John Ortega, James Greenberg, Peter H. McMurry, Annmarie G. Carlton, Jeffrey R. Pierce, Dave R. Hanson, and James N. Smith
Atmos. Chem. Phys., 18, 311–326, https://doi.org/10.5194/acp-18-311-2018, https://doi.org/10.5194/acp-18-311-2018, 2018
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Much of what we know about atmospheric new particle formation (NPF) is based on ground-level measurements. We used tethered balloon measurements and remote sensing to study the location in the boundary layer in which NPF events are initiated, the degree to which the boundary layer is well-mixed during NPF, and the potential role that water may play in aerosol particle chemical evolution. This information will improve the representativeness of process level models and laboratory experiments.
Adrian M. Maclean, Christopher L. Butenhoff, James W. Grayson, Kelley Barsanti, Jose L. Jimenez, and Allan K. Bertram
Atmos. Chem. Phys., 17, 13037–13048, https://doi.org/10.5194/acp-17-13037-2017, https://doi.org/10.5194/acp-17-13037-2017, 2017
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Using laboratory data, meteorological fields and a chemical transport model, we investigated how often mixing times are < 1 h within SOA in the planetary boundary layer (PBL). Based on viscosity data for alpha-pinene SOA generated using mass concentrations of ~1000 µg m −3, mixing times in biogenic SOA are < 1h most of the time.
Benjamin N. Murphy, Matthew C. Woody, Jose L. Jimenez, Ann Marie G. Carlton, Patrick L. Hayes, Shang Liu, Nga L. Ng, Lynn M. Russell, Ari Setyan, Lu Xu, Jeff Young, Rahul A. Zaveri, Qi Zhang, and Havala O. T. Pye
Atmos. Chem. Phys., 17, 11107–11133, https://doi.org/10.5194/acp-17-11107-2017, https://doi.org/10.5194/acp-17-11107-2017, 2017
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We incorporate recent findings about the behavior of organic pollutants in urban airsheds into the Community Multiscale Air Quality (CMAQ) model to refine predictions of organic particulate pollution in the United States. The new techniques, which account for the volatility and ongoing chemistry of airborne organic compounds, substantially reduce biases, particularly in the winter time and near emission sources.
Guido R. van der Werf, James T. Randerson, Louis Giglio, Thijs T. van Leeuwen, Yang Chen, Brendan M. Rogers, Mingquan Mu, Margreet J. E. van Marle, Douglas C. Morton, G. James Collatz, Robert J. Yokelson, and Prasad S. Kasibhatla
Earth Syst. Sci. Data, 9, 697–720, https://doi.org/10.5194/essd-9-697-2017, https://doi.org/10.5194/essd-9-697-2017, 2017
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Fires occur in many vegetation types and are sometimes natural but often ignited by humans for various purposes. We have estimated how much area they burn globally and what their emissions are. Total burned area is roughly equivalent to the size of the EU with most fires burning in tropical savannas. Their emissions vary substantially from year to year and contribute to the atmospheric burdens of many trace gases and aerosols. The 20-year dataset is mostly suited for large-scale assessments.
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.
Clare Paton-Walsh, Élise-Andrée Guérette, Dagmar Kubistin, Ruhi Humphries, Stephen R. Wilson, Doreena Dominick, Ian Galbally, Rebecca Buchholz, Mahendra Bhujel, Scott Chambers, Min Cheng, Martin Cope, Perry Davy, Kathryn Emmerson, David W. T. Griffith, Alan Griffiths, Melita Keywood, Sarah Lawson, Suzie Molloy, Géraldine Rea, Paul Selleck, Xue Shi, Jack Simmons, and Voltaire Velazco
Earth Syst. Sci. Data, 9, 349–362, https://doi.org/10.5194/essd-9-349-2017, https://doi.org/10.5194/essd-9-349-2017, 2017
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The MUMBA campaign provides a detailed snapshot of the atmospheric composition in an urban coastal environment with strong biogenic sources nearby. This campaign involved collaboration between several institutes and was undertaken to provide a case study for atmospheric models in a poorly sampled region of the globe.
Rebecca R. Buchholz, Merritt N. Deeter, Helen M. Worden, John Gille, David P. Edwards, James W. Hannigan, Nicholas B. Jones, Clare Paton-Walsh, David W. T. Griffith, Dan Smale, John Robinson, Kimberly Strong, Stephanie Conway, Ralf Sussmann, Frank Hase, Thomas Blumenstock, Emmanuel Mahieu, and Bavo Langerock
Atmos. Meas. Tech., 10, 1927–1956, https://doi.org/10.5194/amt-10-1927-2017, https://doi.org/10.5194/amt-10-1927-2017, 2017
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The study presents the first systematic use of ground-based remote-sensing data from the Network for the Detection of Atmospheric Composition Change (NDACC) to validate satellite-based Measurements of Pollution in the Troposphere (MOPITT) total column carbon monoxide (CO). MOPITT generally shows low bias with respect to the ground-based instruments. The geographic and temporal dependence of validation results are determined. Our findings inform some recommendations for using MOPITT measurements.
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.
Qijing Bian, Shantanu H. Jathar, John K. Kodros, Kelley C. Barsanti, Lindsay E. Hatch, Andrew A. May, Sonia M. Kreidenweis, and Jeffrey R. Pierce
Atmos. Chem. Phys., 17, 5459–5475, https://doi.org/10.5194/acp-17-5459-2017, https://doi.org/10.5194/acp-17-5459-2017, 2017
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In this paper, we perform simulations of the evolution of biomass-burning organic aerosol in laboratory smog-chamber experiments and ambient plumes. We find that in smog-chamber experiments, vapor wall losses lead to a large reduction in the apparent secondary organic aerosol formation. In ambient plumes, fire size and meteorology regulate the plume dilution rate, primary organic aerosol evaporation rate, and secondary organic aerosol formation rate.
Rudra P. Pokhrel, Eric R. Beamesderfer, Nick L. Wagner, Justin M. Langridge, Daniel A. Lack, Thilina Jayarathne, Elizabeth A. Stone, Chelsea E. Stockwell, Robert J. Yokelson, and Shane M. Murphy
Atmos. Chem. Phys., 17, 5063–5078, https://doi.org/10.5194/acp-17-5063-2017, https://doi.org/10.5194/acp-17-5063-2017, 2017
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This study investigates enhancement of black carbon (BC) absorption in biomass burning emissions due to absorbing and non-absorbing coatings. The fraction of absorption due to BC, brown carbon (BrC), and lensing is estimated using different approaches. The similarities and differences between the results from these approaches are discussed. Absorption by BrC is shown to have good correlation with the elemental to organic carbon ratio (EC / OC) and AAE.
Kathleen M. Fahey, Annmarie G. Carlton, Havala O. T. Pye, Jaemeen Baek, William T. Hutzell, Charles O. Stanier, Kirk R. Baker, K. Wyat Appel, Mohammed Jaoui, and John H. Offenberg
Geosci. Model Dev., 10, 1587–1605, https://doi.org/10.5194/gmd-10-1587-2017, https://doi.org/10.5194/gmd-10-1587-2017, 2017
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Chemical transport models (CTMs) are a crucial tool in understanding links between emissions, air quality, and climate. Only a simple description of cloud chemistry has been implemented in many of these; however, clouds play a major role in the physicochemical processing of atmospheric species. In CMAQ, EPA’s widely used CTM, the cloud code is limited to the treatment of simple chemistry. We update CMAQ clouds to consider additional chemistry and then examine regional impacts of these updates.
Lindsay E. Hatch, Robert J. Yokelson, Chelsea E. Stockwell, Patrick R. Veres, Isobel J. Simpson, Donald R. Blake, John J. Orlando, and Kelley C. Barsanti
Atmos. Chem. Phys., 17, 1471–1489, https://doi.org/10.5194/acp-17-1471-2017, https://doi.org/10.5194/acp-17-1471-2017, 2017
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The most comprehensive database of gaseous biomass burning emissions to date was compiled. Four complementary instruments were deployed together during laboratory fires. The results generally compared within experimental uncertainty and highlighted that a range of measurement approaches are required for adequate characterization of smoke composition. Observed compounds were binned based on volatility, and priority recommendations were made to improve secondary organic aerosol predictions.
Havala O. T. Pye, Benjamin N. Murphy, Lu Xu, Nga L. Ng, Annmarie G. Carlton, Hongyu Guo, Rodney Weber, Petros Vasilakos, K. Wyat Appel, Sri Hapsari Budisulistiorini, Jason D. Surratt, Athanasios Nenes, Weiwei Hu, Jose L. Jimenez, Gabriel Isaacman-VanWertz, Pawel K. Misztal, and Allen H. Goldstein
Atmos. Chem. Phys., 17, 343–369, https://doi.org/10.5194/acp-17-343-2017, https://doi.org/10.5194/acp-17-343-2017, 2017
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We use a chemical transport model to examine how organic compounds in the atmosphere interact with water present in particles. Organic compounds themselves lead to water uptake, and organic compounds interact with water associated with inorganic compounds in the rural southeast atmosphere. Including interactions of organic compounds with water requires a treatment of nonideality to more accurately represent aerosol observations during the Southern Oxidant and Aerosol Study (SOAS) 2013.
Marielle Saunois, Philippe Bousquet, Ben Poulter, Anna Peregon, Philippe Ciais, Josep G. Canadell, Edward J. Dlugokencky, Giuseppe Etiope, David Bastviken, Sander Houweling, Greet Janssens-Maenhout, Francesco N. Tubiello, Simona Castaldi, Robert B. Jackson, Mihai Alexe, Vivek K. Arora, David J. Beerling, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Victor Brovkin, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, Charles Curry, Christian Frankenberg, Nicola Gedney, Lena Höglund-Isaksson, Misa Ishizawa, Akihiko Ito, Fortunat Joos, Heon-Sook Kim, Thomas Kleinen, Paul Krummel, Jean-François Lamarque, Ray Langenfelds, Robin Locatelli, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Julia Marshall, Joe R. Melton, Isamu Morino, Vaishali Naik, Simon O'Doherty, Frans-Jan W. Parmentier, Prabir K. Patra, Changhui Peng, Shushi Peng, Glen P. Peters, Isabelle Pison, Catherine Prigent, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Paul Steele, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Michiel van Weele, Guido R. van der Werf, Ray Weiss, Christine Wiedinmyer, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Earth Syst. Sci. Data, 8, 697–751, https://doi.org/10.5194/essd-8-697-2016, https://doi.org/10.5194/essd-8-697-2016, 2016
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An accurate assessment of the methane budget is important to understand the atmospheric methane concentrations and trends and to provide realistic pathways for climate change mitigation. The various and diffuse sources of methane as well and its oxidation by a very short lifetime radical challenge this assessment. We quantify the methane sources and sinks as well as their uncertainties based on both bottom-up and top-down approaches provided by a broad international scientific community.
Neha Sareen, Annmarie G. Carlton, Jason D. Surratt, Avram Gold, Ben Lee, Felipe D. Lopez-Hilfiker, Claudia Mohr, Joel A. Thornton, Zhenfa Zhang, Yong B. Lim, and Barbara J. Turpin
Atmos. Chem. Phys., 16, 14409–14420, https://doi.org/10.5194/acp-16-14409-2016, https://doi.org/10.5194/acp-16-14409-2016, 2016
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.
Chelsea E. Stockwell, Thilina Jayarathne, Mark A. Cochrane, Kevin C. Ryan, Erianto I. Putra, Bambang H. Saharjo, Ati D. Nurhayati, Israr Albar, Donald R. Blake, Isobel J. Simpson, Elizabeth A. Stone, and Robert J. Yokelson
Atmos. Chem. Phys., 16, 11711–11732, https://doi.org/10.5194/acp-16-11711-2016, https://doi.org/10.5194/acp-16-11711-2016, 2016
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We present the first or rare field measurements of emission factors for Indonesian peat fires made in Borneo during the 2015 El Niño. The data include up to 90 gases, aerosol mass, and aerosol optical properties at two wavelengths (405 and 870 nm). Brown carbon dominates aerosol absorption, revisions to previous values for greenhouse gas emissions are supported and air toxics are assessed.
Chelsea E. Stockwell, Ted J. Christian, J. Douglas Goetz, Thilina Jayarathne, Prakash V. Bhave, Puppala S. Praveen, Sagar Adhikari, Rashmi Maharjan, Peter F. DeCarlo, Elizabeth A. Stone, Eri Saikawa, Donald R. Blake, Isobel J. Simpson, Robert J. Yokelson, and Arnico K. Panday
Atmos. Chem. Phys., 16, 11043–11081, https://doi.org/10.5194/acp-16-11043-2016, https://doi.org/10.5194/acp-16-11043-2016, 2016
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We present the first, or rare, field measurements in South Asia of emission factors for up to 80 gases (pollutants, greenhouse gases, and precursors) and black carbon and aerosol optical properties at 405 and 870 nm for many previously under-sampled sources that are important in developing countries such as cooking with dung and wood, garbage and crop residue burning, brick kilns, motorcycles, generators and pumps, etc. Brown carbon contributes significantly to total aerosol absorption.
Yao Té, Pascal Jeseck, Bruno Franco, Emmanuel Mahieu, Nicholas Jones, Clare Paton-Walsh, David W. T. Griffith, Rebecca R. Buchholz, Juliette Hadji-Lazaro, Daniel Hurtmans, and Christof Janssen
Atmos. Chem. Phys., 16, 10911–10925, https://doi.org/10.5194/acp-16-10911-2016, https://doi.org/10.5194/acp-16-10911-2016, 2016
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This paper studies the seasonal variation of surface and column CO at three different sites (Paris, Jungfraujoch and Wollongong), with an emphasis on establishing a link between the CO vertical distribution and the nature of CO emission sources. We find the first evidence of a time lag between surface and free tropospheric CO seasonal variations in the Northern Hemisphere.
Maite Bauwens, Trissevgeni Stavrakou, Jean-François Müller, Isabelle De Smedt, Michel Van Roozendael, Guido R. van der Werf, Christine Wiedinmyer, Johannes W. Kaiser, Katerina Sindelarova, and Alex Guenther
Atmos. Chem. Phys., 16, 10133–10158, https://doi.org/10.5194/acp-16-10133-2016, https://doi.org/10.5194/acp-16-10133-2016, 2016
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Relying on a 9-year record of satellite observations of formaldehyde, we use inverse techniques to derive global top–down hydrocarbon fluxes over 2005–2013, infer seasonal and interannual variability, and detect emission trends. Our results suggest changes in fire seasonal patterns, a stronger contribution of agricultural burning, overestimated isoprene flux rates in the tropics, overly decreased isoprene emissions due to soil moisture stress in arid areas, and enhanced isoprene trends.
Rudra P. Pokhrel, Nick L. Wagner, Justin M. Langridge, Daniel A. Lack, Thilina Jayarathne, Elizabeth A. Stone, Chelsea E. Stockwell, Robert J. Yokelson, and Shane M. Murphy
Atmos. Chem. Phys., 16, 9549–9561, https://doi.org/10.5194/acp-16-9549-2016, https://doi.org/10.5194/acp-16-9549-2016, 2016
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This paper gives first multi-wavelength estimates of SSA and AAE of emissions from combustion of Indonesian peat. In addition, it demonstrates that SSA of biomass burning emissions can be parameterized with EC / (EC+OC) and that this parameterization is quantitatively superior to previously published parameterizations based on MCE. It also shows that EC / (EC+OC) parameterization accurately predicts SSA during the first few hours of aging of a biomass burning plume.
Anna L. Hodshire, Michael J. Lawler, Jun Zhao, John Ortega, Coty Jen, Taina Yli-Juuti, Jared F. Brewer, Jack K. Kodros, Kelley C. Barsanti, Dave R. Hanson, Peter H. McMurry, James N. Smith, and Jeffery R. Pierce
Atmos. Chem. Phys., 16, 9321–9348, https://doi.org/10.5194/acp-16-9321-2016, https://doi.org/10.5194/acp-16-9321-2016, 2016
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Processes that control the growth of newly formed particles are not well understood and limit predictions of aerosol climate impacts. We combine state-of-the-art measurements at a central-US site with a particle-growth model to investigate the species and processes contributing to growth. Observed growth was dominated by organics, sulfate salts, or a mixture of these two. The model qualitatively captures the variability between different days.
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.
John K. Kodros, Rachel Cucinotta, David A. Ridley, Christine Wiedinmyer, and Jeffrey R. Pierce
Atmos. Chem. Phys., 16, 6771–6784, https://doi.org/10.5194/acp-16-6771-2016, https://doi.org/10.5194/acp-16-6771-2016, 2016
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We provide a first estimate of the aerosol radiative effects from open, uncontrolled combustion of domestic waste. We find the direct and cloud-albedo indirect radiative effects are predominantly negative (cooling tendency) with regional forcings exceeding −0.4 W m−2; however, the magnitude of these effects depends on the assumed emitted aerosol size, mass, and optical properties.
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.
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.
Markus Müller, Bruce E. Anderson, Andreas J. Beyersdorf, James H. Crawford, Glenn S. Diskin, Philipp Eichler, Alan Fried, Frank N. Keutsch, Tomas Mikoviny, Kenneth L. Thornhill, James G. Walega, Andrew J. Weinheimer, Melissa Yang, Robert J. Yokelson, and Armin Wisthaler
Atmos. Chem. Phys., 16, 3813–3824, https://doi.org/10.5194/acp-16-3813-2016, https://doi.org/10.5194/acp-16-3813-2016, 2016
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Atmospheric emissions from small forest fires and their impact on regional air quality are still poorly characterized. We used an instrumented NASA P-3B aircraft to study emissions from a small forest understory fire in Georgia (USA) and to investigate chemical transformations in the fire plume in the 1 h downwind region. A state-of-the-art chemical model was able to accurately simulate key chemical processes in the aging plume.
J. B. Gilman, B. M. Lerner, W. C. Kuster, P. D. Goldan, C. Warneke, P. R. Veres, J. M. Roberts, J. A. de Gouw, I. R. Burling, and R. J. Yokelson
Atmos. Chem. Phys., 15, 13915–13938, https://doi.org/10.5194/acp-15-13915-2015, https://doi.org/10.5194/acp-15-13915-2015, 2015
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A comprehensive suite of instruments was used to quantify the emissions of over 200 organic and inorganic gases from 56 laboratory burns of 18 different biomass fuel types common in the southeastern, southwestern, or northern United States. Emission ratios relative to carbon monoxide (CO) are used to characterize the composition of gases emitted by mass; OH reactivity; and potential secondary organic aerosol (SOA) precursors for the three different U.S. fuel regions presented here.
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.
R. Gonzalez-Abraham, S. H. Chung, J. Avise, B. Lamb, E. P. Salathé Jr., C. G. Nolte, D. Loughlin, A. Guenther, C. Wiedinmyer, T. Duhl, Y. Zhang, and D. G. Streets
Atmos. Chem. Phys., 15, 12645–12665, https://doi.org/10.5194/acp-15-12645-2015, https://doi.org/10.5194/acp-15-12645-2015, 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.
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.
M. J. Alvarado, C. R. Lonsdale, R. J. Yokelson, S. K. Akagi, H. Coe, J. S. Craven, E. V. Fischer, G. R. McMeeking, J. H. Seinfeld, T. Soni, J. W. Taylor, D. R. Weise, and C. E. Wold
Atmos. Chem. Phys., 15, 6667–6688, https://doi.org/10.5194/acp-15-6667-2015, https://doi.org/10.5194/acp-15-6667-2015, 2015
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Being able to understand and simulate the chemical evolution of biomass burning smoke plumes under a wide variety of conditions is a critical part of forecasting the impact of these fires on air quality, atmospheric composition, and climate. Here we use an improved model of this chemistry to simulate the evolution of ozone and secondary organic aerosol within a young biomass burning smoke plume from the Williams prescribed burn in chaparral, which was sampled over California in November 2009.
A. A. May, T. Lee, G. R. McMeeking, S. Akagi, A. P. Sullivan, S. Urbanski, R. J. Yokelson, and S. M. Kreidenweis
Atmos. Chem. Phys., 15, 6323–6335, https://doi.org/10.5194/acp-15-6323-2015, https://doi.org/10.5194/acp-15-6323-2015, 2015
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Smoke plumes from some prescribed fires in the southeastern United States were sampled via aircraft to observe changes in organic aerosol (OA) with atmospheric transport. These plumes underwent rapid mixing, and, hence, substantial dilution with background air occurred. Dilution-driven evaporation appears to be the primary driver of OA transformations within the sampled plumes rather than photochemistry.
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.
P. L. Hayes, A. G. Carlton, K. R. Baker, R. Ahmadov, R. A. Washenfelder, S. Alvarez, B. Rappenglück, J. B. Gilman, W. C. Kuster, J. A. de Gouw, P. Zotter, A. S. H. Prévôt, S. Szidat, T. E. Kleindienst, J. H. Offenberg, P. K. Ma, and J. L. Jimenez
Atmos. Chem. Phys., 15, 5773–5801, https://doi.org/10.5194/acp-15-5773-2015, https://doi.org/10.5194/acp-15-5773-2015, 2015
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(1) Four different parameterizations for the formation and chemical evolution of secondary organic aerosol (SOA) are evaluated using a box model representing the Los Angeles region during the CalNex campaign.
(2) The SOA formed only from the oxidation of VOCs is insufficient to explain the observed SOA concentrations.
(3) The amount of SOA mass formed from diesel vehicle emissions is estimated to be 16-27%.
(4) Modeled SOA depends strongly on the P-S/IVOC volatility distribution.
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. 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.
B. de Foy, Y. Y. Cui, J. J. Schauer, M. Janssen, J. R. Turner, and C. Wiedinmyer
Atmos. Chem. Phys., 15, 2405–2427, https://doi.org/10.5194/acp-15-2405-2015, https://doi.org/10.5194/acp-15-2405-2015, 2015
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Elemental carbon and organic carbon are components of fine particulate matter that are harmful to health. We use computer simulations of wind patterns and pollution dispersion to analyze a year-long time series of hourly measurements made at the St. Louis-Midwest supersite. The inverse method produced improved estimates of emissions of these pollutants by different types of sources such as on-road and off-road emissions and open burning.
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.
L. E. Hatch, W. Luo, J. F. Pankow, R. J. Yokelson, C. E. Stockwell, and K. C. Barsanti
Atmos. Chem. Phys., 15, 1865–1899, https://doi.org/10.5194/acp-15-1865-2015, https://doi.org/10.5194/acp-15-1865-2015, 2015
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This work represents the first application of two-dimensional gas chromatography to broadly characterize the gas-phase emissions of biomass burning, including comparisons among the emissions from burns of selected conifer, grass, crop residue, and peat fuel types. In these smoke samples, over 700 compounds were detected, which are discussed in the context of potential secondary organic aerosol formation.
S. Kulkarni, N. Sobhani, J. P. Miller-Schulze, M. M. Shafer, J. J. Schauer, P. A. Solomon, P. E. Saide, S. N. Spak, Y. F. Cheng, H. A. C. Denier van der Gon, Z. Lu, D. G. Streets, G. Janssens-Maenhout, C. Wiedinmyer, J. Lantz, M. Artamonova, B. Chen, S. Imashev, L. Sverdlik, J. T. Deminter, B. Adhikary, A. D'Allura, C. Wei, and G. R. Carmichael
Atmos. Chem. Phys., 15, 1683–1705, https://doi.org/10.5194/acp-15-1683-2015, https://doi.org/10.5194/acp-15-1683-2015, 2015
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This study presents a regional-scale modeling analysis of aerosols in the Central Asia region including detailed characterization of seasonal source region and sector contributions along with the predicted changes in distribution of aerosols using 2030 future emission scenarios. The influence of long transport and impact of varied emission sources including dust, biomass burning, and anthropogenic sources on the regional aerosol distributions and the associated transport pathways are discussed.
C. E. Stockwell, P. R. Veres, J. Williams, and R. J. Yokelson
Atmos. Chem. Phys., 15, 845–865, https://doi.org/10.5194/acp-15-845-2015, https://doi.org/10.5194/acp-15-845-2015, 2015
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We used a high-resolution proton-transfer-reaction time-of-flight mass spectrometer to measure emissions from peat, crop residue, cooking fires, etc. We assigned > 80% of the mass of gas-phase organic compounds and much of it was secondary organic aerosol precursors. The open cooking emissions were much larger than from advanced cookstoves. Little-studied N-containing organic compounds accounted for 0.1-8.7% of the fuel N and may influence new particle formation.
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.
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.
A. P. Sullivan, A. A. May, T. Lee, G. R. McMeeking, S. M. Kreidenweis, S. K. Akagi, R. J. Yokelson, S. P. Urbanski, and J. L. Collett Jr.
Atmos. Chem. Phys., 14, 10535–10545, https://doi.org/10.5194/acp-14-10535-2014, https://doi.org/10.5194/acp-14-10535-2014, 2014
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
C. E. Stockwell, R. J. Yokelson, S. M. Kreidenweis, A. L. Robinson, P. J. DeMott, R. C. Sullivan, J. Reardon, K. C. Ryan, D. W. T. Griffith, and L. Stevens
Atmos. Chem. Phys., 14, 9727–9754, https://doi.org/10.5194/acp-14-9727-2014, https://doi.org/10.5194/acp-14-9727-2014, 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
S. K. Akagi, I. R. Burling, A. Mendoza, T. J. Johnson, M. Cameron, D. W. T. Griffith, C. Paton-Walsh, D. R. Weise, J. Reardon, and R. J. Yokelson
Atmos. Chem. Phys., 14, 199–215, https://doi.org/10.5194/acp-14-199-2014, https://doi.org/10.5194/acp-14-199-2014, 2014
T. Yli-Juuti, K. Barsanti, L. Hildebrandt Ruiz, A.-J. Kieloaho, U. Makkonen, T. Petäjä, T. Ruuskanen, M. Kulmala, and I. Riipinen
Atmos. Chem. Phys., 13, 12507–12524, https://doi.org/10.5194/acp-13-12507-2013, https://doi.org/10.5194/acp-13-12507-2013, 2013
K. C. Barsanti, A. G. Carlton, and S. H. Chung
Atmos. Chem. Phys., 13, 12073–12088, https://doi.org/10.5194/acp-13-12073-2013, https://doi.org/10.5194/acp-13-12073-2013, 2013
A. G. Carlton and B. J. Turpin
Atmos. Chem. Phys., 13, 10203–10214, https://doi.org/10.5194/acp-13-10203-2013, https://doi.org/10.5194/acp-13-10203-2013, 2013
R. J. Yokelson, M. O. Andreae, and S. K. Akagi
Atmos. Meas. Tech., 6, 2155–2158, https://doi.org/10.5194/amt-6-2155-2013, https://doi.org/10.5194/amt-6-2155-2013, 2013
X. Jiang, M. C. Barth, C. Wiedinmyer, and S. T. Massie
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-21383-2013, https://doi.org/10.5194/acpd-13-21383-2013, 2013
Revised manuscript not accepted
M. Val Martin, C. L. Heald, B. Ford, A. J. Prenni, and C. Wiedinmyer
Atmos. Chem. Phys., 13, 7429–7439, https://doi.org/10.5194/acp-13-7429-2013, https://doi.org/10.5194/acp-13-7429-2013, 2013
M. Xie, K. C. Barsanti, M. P. Hannigan, S. J. Dutton, and S. Vedal
Atmos. Chem. Phys., 13, 7381–7393, https://doi.org/10.5194/acp-13-7381-2013, https://doi.org/10.5194/acp-13-7381-2013, 2013
A. Mahmud and K. Barsanti
Geosci. Model Dev., 6, 961–980, https://doi.org/10.5194/gmd-6-961-2013, https://doi.org/10.5194/gmd-6-961-2013, 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
C. He, J. Liu, A. G. Carlton, S. Fan, L. W. Horowitz, H. Levy II, and S. Tao
Atmos. Chem. Phys., 13, 1913–1926, https://doi.org/10.5194/acp-13-1913-2013, https://doi.org/10.5194/acp-13-1913-2013, 2013
S. K. Akagi, R. J. Yokelson, I. R. Burling, S. Meinardi, I. Simpson, D. R. Blake, G. R. McMeeking, A. Sullivan, T. Lee, S. Kreidenweis, S. Urbanski, J. Reardon, D. W. T. Griffith, T. J. Johnson, and D. R. Weise
Atmos. Chem. Phys., 13, 1141–1165, https://doi.org/10.5194/acp-13-1141-2013, https://doi.org/10.5194/acp-13-1141-2013, 2013
R. J. Yokelson, I. R. Burling, J. B. Gilman, C. Warneke, C. E. Stockwell, J. de Gouw, S. K. Akagi, S. P. Urbanski, P. Veres, J. M. Roberts, W. C. Kuster, J. Reardon, D. W. T. Griffith, T. J. Johnson, S. Hosseini, J. W. Miller, D. R. Cocker III, H. Jung, and D. R. Weise
Atmos. Chem. Phys., 13, 89–116, https://doi.org/10.5194/acp-13-89-2013, https://doi.org/10.5194/acp-13-89-2013, 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
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.
The Fire INventory from NCAR (FINN) provides daily global estimates of emissions from open fires...
