Articles | Volume 17, issue 21
https://doi.org/10.5194/gmd-17-7679-2024
© Author(s) 2024. 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-17-7679-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
04 Nov 2024
Development and technical paper |
| 04 Nov 2024
| 04 Nov 2024
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
Samiha Binte Shahid
Department of Chemical & Environmental Engineering, Center for Environmental Research & Technology, University of California, Riverside, Riverside, CA 92521, United States
Forrest G. Lacey
Research Applications Laboratory, U.S. National Science Foundation National Center for Atmospheric Research, Boulder, CO 80301, United States
Atmospheric Chemistry Observations and Modeling Laboratory, U.S. National Science Foundation National Center for Atmospheric Research, Boulder, CO 80301, United States
Christine Wiedinmyer
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO 80309, United States
Robert J. Yokelson
Department of Chemistry, University of Montana, Missoula, MT 59812, United States
Department of Chemical & Environmental Engineering, Center for Environmental Research & Technology, University of California, Riverside, Riverside, CA 92521, United States
Atmospheric Chemistry Observations and Modeling Laboratory, U.S. National Science Foundation National Center for Atmospheric Research, Boulder, CO 80301, United States
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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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This paper describes the scientific basis for gas-phase atmospheric chemical mechanisms derived using the SAPRC mechanism generation system, MechGen. It can derive mechanisms for most organic compounds with C, H, O, or N atoms, including initial reactions of organics with OH, O3, NO3, and O3P or by photolysis, as well as the reactions of the various types of intermediates that are formed. The paper includes a description of areas of uncertainty where additional research and updates are needed.
Cynthia H. Whaley, Tim Butler, Jose A. Adame, Rupal Ambulkar, Stephen R. Arnold, Rebecca R. Buchholz, Benjamin Gaubert, Douglas S. Hamilton, Min Huang, Hayley Hung, Johannes W. Kaiser, Jacek W. Kaminski, Christophe 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 Tan, Wenfu Tang, Veerachai Tanpipat, Kostas Tsigaridis, Christine Wiedinmyer, Oliver Wild, Yuanyu Xie, and Paquita Zuidema
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-126, https://doi.org/10.5194/gmd-2024-126, 2024
Revised manuscript under review for GMD
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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 set up are discussed, and the official recommendations for the project are presented.
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.
Natalie M. Mahowald, Longlei Li, Julius Vira, Marje Prank, Douglas S. Hamilton, Hitoshi Matsui, Ron L. Miller, Louis Lu, Ezgi Akyuz, Daphne Meidan, Peter G. Hess, Heikki Lihavainen, Christine Wiedinmyer, Jenny Hand, Maria Grazia Alaimo, Célia Alves, Andres Alastuey, Paulo Artaxo, Africa Barreto, Francisco Barraza, Silvia Becagli, Giulia Calzolai, Shankararaman Chellam, Ying Chen, Patrick Chuang, David D. Cohen, Cristina Colombi, Evangelia Diapouli, Gaetano Dongarra, Konstantinos Eleftheriadis, Johann Engelbrecht, Corinne Galy-Lacaux, Cassandra Gaston, Dario Gomez, Yenny González Ramos, Roy M. Harrison, Chris Heyes, Barak Herut, Philip Hopke, Christoph Hüglin, Maria Kanakidou, Zsofia Kertesz, Zbigniew 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
EGUsphere, https://doi.org/10.5194/egusphere-2024-1617, https://doi.org/10.5194/egusphere-2024-1617, 2024
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Aerosol particles are an important part of the Earth system, but their concentrations are spatially and temporally heterogeneous, as well as variable in size and composition. Here we present a new compilation of PM2.5 and PM10 aerosol observations, focusing on the spatial variability across different observational stations, including composition, and demonstrate a method for comparing the datasets to model output.
Rajesh Kumar, Piyush Bhardwaj, Cenlin He, Jennifer Boehnert, Forrest Lacey, Stefano Alessandrini, Kevin Sampson, Matthew Casali, Scott Swerdlin, Olga Wilhelmi, Gabriele G. Pfister, Benjamin Gaubert, and Helen Worden
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-180, https://doi.org/10.5194/essd-2024-180, 2024
Revised manuscript accepted for ESSD
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We have created a 14-year hourly air quality dataset at 12 km resolution by combining satellite observations of atmospheric composition with air quality models over the contiguous United States (CONUS) . The dataset has been found to reproduce key observed features of air quality over the CONUS. To enable easy visualization and interpretation of county level air quality measures and trends by stakeholders, an ArcGIS air quality dashboard has also been developed.
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
Preprint withdrawn
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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.
Christine Wiedinmyer, Yosuke Kimura, Elena C. McDonald-Buller, Louisa K. Emmons, Rebecca R. Buchholz, Wenfu Tang, Keenan Seto, Maxwell B. Joseph, Kelley C. Barsanti, Annmarie G. Carlton, and Robert Yokelson
Geosci. Model Dev., 16, 3873–3891, https://doi.org/10.5194/gmd-16-3873-2023, https://doi.org/10.5194/gmd-16-3873-2023, 2023
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The Fire INventory from NCAR (FINN) provides daily global estimates of emissions from open fires based on satellite detections of hot spots. This version has been updated to apply MODIS and VIIRS satellite fire detection and better represents both large and small fires. FINNv2.5 generates more emissions than FINNv1 and is in general agreement with other fire emissions inventories. The new estimates are consistent with satellite observations, but uncertainties remain regionally and by pollutant.
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.
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.
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.
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.
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.
Thierno Doumbia, Claire Granier, Nellie Elguindi, Idir Bouarar, Sabine Darras, Guy Brasseur, Benjamin Gaubert, Yiming Liu, Xiaoqin Shi, Trissevgeni Stavrakou, Simone Tilmes, Forrest Lacey, Adrien Deroubaix, and Tao Wang
Earth Syst. Sci. Data, 13, 4191–4206, https://doi.org/10.5194/essd-13-4191-2021, https://doi.org/10.5194/essd-13-4191-2021, 2021
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Most countries around the world have implemented control measures to combat the spread of the COVID-19 pandemic, resulting in significant changes in economic and personal activities. We developed the CONFORM (COvid-19 adjustmeNt Factors fOR eMissions) dataset to account for changes in emissions during lockdowns. This dataset was created with the intention of being directly applicable to existing global and regional inventories used in chemical transport models.
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.
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.
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.
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.
Helen M. Worden, A. Anthony Bloom, John R. Worden, Zhe Jiang, Eloise A. Marais, Trissevgeni Stavrakou, Benjamin Gaubert, and Forrest Lacey
Atmos. Chem. Phys., 19, 13569–13579, https://doi.org/10.5194/acp-19-13569-2019, https://doi.org/10.5194/acp-19-13569-2019, 2019
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Biogenic non-methane volatile organic compounds (NMVOCs) emitted from vegetation play a significant role in air quality and climate. However, there are large uncertainties in their role for climate. We present a Bayesian approach to estimate carbon monoxide fluxes that are chemically produced from biogenic sources. This provides independent constraints on models that predict biogenic emissions in order improve their capability for predicting air quality and future climate scenarios.
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.
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.
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.
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.
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 %.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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
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.
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.
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.
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
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
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
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
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
Related subject area
Atmospheric sciences
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
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
Assessment of object-based indices to identify convective organization
The Global Forest Fire Emissions Prediction System version 1.0
Sensitivity Studies of Four‐Dimensional Local Ensemble Transform Kalman Filter Coupled With WRF-Chem Version 3.9.1 for Improving Particulate Matter Simulation Accuracy
Development of A Fast Radiative Transfer Model for Ground-based Microwave Radiometers (ARMS-gb v1.0): Validation and Comparison to RTTOV-gb
FLEXPART version 11: improved accuracy, efficiency, and flexibility
Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a Neural Network
Air quality modeling intercomparison and multiscale ensemble chain for Latin America
Recommended coupling to global meteorological fields for long-term tracer simulations with WRF-GHG
Estimation of aerosol and cloud radiative heating rate in tropical stratosphere using radiative kernel method
Selecting CMIP6 global climate models (GCMs) for Coordinated Regional Climate Downscaling Experiment (CORDEX) dynamical downscaling over Southeast Asia using a standardised benchmarking framework
Improved definition of prior uncertainties in CO2 and CO fossil fuel fluxes and its impact on multi-species inversion with GEOS-Chem (v12.5)
RASCAL v1.0: an open-source tool for climatological time series reconstruction and extension
Introducing graupel density prediction in Weather Research and Forecasting (WRF) double-moment 6-class (WDM6) microphysics and evaluation of the modified scheme during the ICE-POP field campaign
Enabling high-performance cloud computing for the Community Multiscale Air Quality Model (CMAQ) version 5.3.3: performance evaluation and benefits for the user community
Atmospheric-river-induced precipitation in California as simulated by the regionally refined Simple Convective Resolving E3SM Atmosphere Model (SCREAM) Version 0
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Recent improvements and maximum covariance analysis of aerosol and cloud properties in the EC-Earth3-AerChem model
GPU-HADVPPM4HIP V1.0: using the heterogeneous-compute interface for portability (HIP) to speed up the piecewise parabolic method in the CAMx (v6.10) air quality model on China's domestic GPU-like accelerator
Preliminary evaluation of the effect of electro-coalescence with conducting sphere approximation on the formation of warm cumulus clouds using SCALE-SDM version 0.2.5–2.3.0
Similarity-Based Analysis of Atmospheric Organic Compounds for Machine Learning Applications
Cell tracking -based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
Exploring the footprint representation of microwave radiance observations in an Arctic limited-area data assimilation system
Analysis of model error in forecast errors of extended atmospheric Lorenz 05 systems and the ECMWF system
Description and validation of Vehicular Emissions from Road Traffic (VERT) 1.0, an R-based framework for estimating road transport emissions from traffic flows
Improving the EnSRF in the Community Inversion Framework: a case study with ICON-ART 2024.01
AeroMix v1.0.1: a Python package for modeling aerosol optical properties and mixing states
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.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
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Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
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This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
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Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
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Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
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Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
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The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
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Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
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Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
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This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
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Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
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Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
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This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
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In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
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The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
EGUsphere, https://doi.org/10.5194/egusphere-2024-3321, https://doi.org/10.5194/egusphere-2024-3321, 2024
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The effectiveness of assimilation system and its sensitivity to ensemble member size and length of assimilation window have been investigated. This study advances our understanding about the selection of basic parameters in the four-dimension local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate matter polluted environment.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
EGUsphere, https://doi.org/10.5194/egusphere-2024-2884, https://doi.org/10.5194/egusphere-2024-2884, 2024
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Assimilating Ground-based microwave radiometers' observations into numerical weather prediction models holds significant promise for enhancing forecast accuracy. Radiative transfer models (RTM) are crucial for direct data assimilation. We propose a new RTM capable of simulating brightness temperatures observed by GMRs and their Jacobians. Several improvements are introduced to achieve higher accuracy.The RTM align with RTTOV-gb well and can achieve smaller STD in water vapor absorption channels.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
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Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
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Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
EGUsphere, https://doi.org/10.5194/egusphere-2024-2676, https://doi.org/10.5194/egusphere-2024-2676, 2024
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This work focuses on the prediction of aerosol concentration values at 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 of networks architectures and information fusion methods allows the extraction of knowledge on the most efficient methods in the context of this study.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
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Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
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Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
EGUsphere, https://doi.org/10.5194/egusphere-2024-2815, https://doi.org/10.5194/egusphere-2024-2815, 2024
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate that 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 and consists well with radiative model calculations and can be applied to atmospheric models with speed requirements.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev., 17, 7285–7315, https://doi.org/10.5194/gmd-17-7285-2024, https://doi.org/10.5194/gmd-17-7285-2024, 2024
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We use a comprehensive approach to select a subset of CMIP6 models for dynamical downscaling over Southeast Asia, taking into account model performance, model independence, data availability and the range of future climate projections. The standardised benchmarking framework is applied to assess model performance through both statistical and process-based metrics. Ultimately, we identify two independent model groups that are suitable for dynamical downscaling in the Southeast Asian region.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
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Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Álvaro González-Cervera and Luis Durán
Geosci. Model Dev., 17, 7245–7261, https://doi.org/10.5194/gmd-17-7245-2024, https://doi.org/10.5194/gmd-17-7245-2024, 2024
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RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the analog method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities for broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt
Geosci. Model Dev., 17, 7199–7218, https://doi.org/10.5194/gmd-17-7199-2024, https://doi.org/10.5194/gmd-17-7199-2024, 2024
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We enhance the WDM6 scheme by incorporating predicted graupel density. The modification affects graupel characteristics, including fall velocity–diameter and mass–diameter relationships. Simulations highlight changes in graupel distribution and precipitation patterns, potentially influencing surface snow amounts. The study underscores the significance of integrating predicted graupel density for a more realistic portrayal of microphysical properties in weather models.
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024, https://doi.org/10.5194/gmd-17-7001-2024, 2024
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We present a summary of enabling high-performance computing of the Community Multiscale Air Quality Model (CMAQ) – a state-of-the-science community multiscale air quality model – on two cloud computing platforms through documenting the technologies, model performance, scaling and relative merits. This may be a new paradigm for computationally intense future model applications. We initiated this work due to a need to leverage cloud computing advances and to ease the learning curve for new users.
Peter A. Bogenschutz, Jishi Zhang, Qi Tang, and Philip Cameron-Smith
Geosci. Model Dev., 17, 7029–7050, https://doi.org/10.5194/gmd-17-7029-2024, https://doi.org/10.5194/gmd-17-7029-2024, 2024
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Using high-resolution and state-of-the-art modeling techniques we simulate five atmospheric river events for California to test the capability to represent precipitation for these events. We find that our model is able to capture the distribution of precipitation very well but suffers from overestimating the precipitation amounts over high elevation. Increasing the resolution further has no impact on reducing this bias, while increasing the domain size does have modest impacts.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-145, https://doi.org/10.5194/gmd-2024-145, 2024
Revised manuscript accepted for GMD
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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 in 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Manu Anna Thomas, Klaus Wyser, Shiyu Wang, Marios Chatziparaschos, Paraskevi Georgakaki, Montserrat Costa-Surós, Maria Gonçalves Ageitos, Maria Kanakidou, Carlos Pérez García-Pando, Athanasios Nenes, Twan van Noije, Philippe Le Sager, and Abhay Devasthale
Geosci. Model Dev., 17, 6903–6927, https://doi.org/10.5194/gmd-17-6903-2024, https://doi.org/10.5194/gmd-17-6903-2024, 2024
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Aerosol–cloud interactions occur at a range of spatio-temporal scales. While evaluating recent developments in EC-Earth3-AerChem, this study aims to understand the extent to which the Twomey effect manifests itself at larger scales. We find a reduction in the warm bias over the Southern Ocean due to model improvements. While we see footprints of the Twomey effect at larger scales, the negative relationship between cloud droplet number and liquid water drives the shortwave radiative effect.
Kai Cao, Qizhong Wu, Lingling Wang, Hengliang Guo, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongxing Li, Lina Liu, Dongqing Li, Hao Wu, and Lanning Wang
Geosci. Model Dev., 17, 6887–6901, https://doi.org/10.5194/gmd-17-6887-2024, https://doi.org/10.5194/gmd-17-6887-2024, 2024
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AMD’s heterogeneous-compute interface for portability was implemented to port the piecewise parabolic method solver from NVIDIA GPUs to China's GPU-like accelerators. The results show that the larger the model scale, the more acceleration effect on the GPU-like accelerator, up to 28.9 times. The multi-level parallelism achieves a speedup of 32.7 times on the heterogeneous cluster. By comparing the results, the GPU-like accelerators have more accuracy for the geoscience numerical models.
Ruyi Zhang, Limin Zhou, Shin-ichiro Shima, and Huawei Yang
Geosci. Model Dev., 17, 6761–6774, https://doi.org/10.5194/gmd-17-6761-2024, https://doi.org/10.5194/gmd-17-6761-2024, 2024
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Solar activity weakly ionises Earth's atmosphere, charging cloud droplets. Electro-coalescence is when oppositely charged droplets stick together. We introduce an analytical expression of electro-coalescence probability and use it in a warm-cumulus-cloud simulation. Results show that charge cases increase rain and droplet size, with the new method outperforming older ones. The new method requires longer computation time, but its impact on rain justifies inclusion in meteorology models.
Hilda Sandström and Patrick Rinke
EGUsphere, https://doi.org/10.48550/arXiv.2406.18171, https://doi.org/10.48550/arXiv.2406.18171, 2024
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Machine learning has the potential to aid the identification 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 model in atmospheric sciences.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-99, https://doi.org/10.5194/gmd-2024-99, 2024
Revised manuscript accepted for GMD
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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 rainfall. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and then the model skill is evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with 4 open-source models.
Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev., 17, 6571–6587, https://doi.org/10.5194/gmd-17-6571-2024, https://doi.org/10.5194/gmd-17-6571-2024, 2024
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Satellite observations provide crucial information about atmospheric constituents in a global distribution that helps to better predict the weather over sparsely observed regions like the Arctic. However, the use of satellite data is usually conservative and imperfect. In this study, a better spatial representation of satellite observations is discussed and explored by a so-called footprint function or operator, highlighting its added value through a case study and diagnostics.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 17, 6489–6511, https://doi.org/10.5194/gmd-17-6489-2024, https://doi.org/10.5194/gmd-17-6489-2024, 2024
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The forecast error growth of atmospheric phenomena is caused by initial and model errors. When studying the initial error growth, it may turn out that small-scale phenomena, which contribute little to the forecast product, significantly affect the ability to predict this product. With a negative result, we investigate in the extended Lorenz (2005) system whether omitting these phenomena will improve predictability. A theory explaining and describing this behavior is developed.
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, https://doi.org/10.5194/gmd-17-6465-2024, 2024
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In this study, we present VERT (Vehicular Emissions from Road Traffic), an R package designed to estimate transport emissions using traffic estimates and vehicle fleet composition data. Compared to other tools available in the literature, VERT stands out for its user-friendly configuration and flexibility of user input. Case studies demonstrate its accuracy in both urban and regional contexts, making it a valuable tool for air quality management and transport scenario planning.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
EGUsphere, https://doi.org/10.5194/egusphere-2024-2197, https://doi.org/10.5194/egusphere-2024-2197, 2024
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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 more efficient implementation of the serial and batch versions of the Ensemble Square Root Filter (EnSRF) algorithm in CIF.
Sam P. Raj, Puna Ram Sinha, Rohit Srivastava, Srinivas Bikkina, and Damu Bala Subrahamanyam
Geosci. Model Dev., 17, 6379–6399, https://doi.org/10.5194/gmd-17-6379-2024, https://doi.org/10.5194/gmd-17-6379-2024, 2024
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A Python successor to the aerosol module of the OPAC model, named AeroMix, has been developed, with enhanced capabilities to better represent real atmospheric aerosol mixing scenarios. AeroMix’s performance in modeling aerosol mixing states has been evaluated against field measurements, substantiating its potential as a versatile aerosol optical model framework for next-generation algorithms to infer aerosol mixing states and chemical composition.
Cited articles
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Akagi, S. K., Yokelson, R. J., Wiedinmyer, C., Alvarado, M. J., Reid, J. S., Karl, T., Crounse, J. D., and Wennberg, P. O.: Emission factors for open and domestic biomass burning for use in atmospheric models, Atmos. Chem. Phys., 11, 4039–4072, https://doi.org/10.5194/acp-11-4039-2011, 2011.
Alvarado, M. J. and Prinn, R. G.: Formation of ozone and growth of aerosols in young smoke plumes from biomass burning: 1. Lagrangian parcel studies, J. Geophys. Res., 114, D09306, https://doi.org/10.1029/2008JD011144, 2009.
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Andreae, M. O.: Emission of trace gases and aerosols from biomass burning – an updated assessment, Atmos. Chem. Phys., 19, 8523–8546, https://doi.org/10.5194/acp-19-8523-2019, 2019.
Andreae, M. O. and Merlet, P.: Emission of trace gases and aerosols from biomass burning, Glob. Biogeochem. Cycles, 15, 955–966, https://doi.org/10.1029/2000GB001382, 2001.
Bey, I., Jacob, D. J., Yantosca, R. M., Logan, J. A., Field, B. D., Fiore, A. M., Li, Q., Liu, H. Y., Mickley, L. J., and Schultz, M. G.: Global modeling of tropospheric chemistry with assimilated meteorology: Model description and evaluation, J. Geophys. Res.-Atmos., 106, 23073–23095, https://doi.org/10.1029/2001JD000807, 2001.
Bian, Q., Jathar, S. H., Kodros, J. K., Barsanti, K. C., Hatch, L. E., May, A. A., Kreidenweis, S. M., and Pierce, J. R.: Secondary organic aerosol formation in biomass-burning plumes: theoretical analysis of lab studies and ambient plumes, Atmos. Chem. Phys., 17, 5459–5475, https://doi.org/10.5194/acp-17-5459-2017, 2017.
Binte Shahid, S., Barsanti, K., and Forrest, G. L.: Next Gen Emissions Inventory expansion of Akagi (NEIVA), Zenodo [code and data set], https://doi.org/10.5281/zenodo.10721105, 2024.
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Buysse, C., Kaulfus, A., Nair, U., and Jaffe, D.: Relationships between particulate matter, ozone, and nitrogen oxides during urban smoke events in the Western US, Environ. Sci. Technol., 53, 12519–12528, https://doi.org/10.1021/acs.est.9b05241, 2019.
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Carter, W. P. L.: Documentation of the SAPRC-18 Mechanism, Report to California Air Resources Board Contract No. 11-761, 29 May, https://intra.cert.ucr.edu/~carter/SAPRC/18/S18doc.pdf (last access: February 2024), 2020.
Carter, W. P. L.: Documentation of the SAPRC-22 Mechanisms, Report to the California Air Resources Board contract no. 21AQP011, 15 May, https://intra.cert.ucr.edu/~carter/SAPRC/22/S22doc.pdf (last access: February 2024), 2023a.
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Short summary
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.
The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive...
