Articles | Volume 22, issue 14
https://doi.org/10.5194/acp-22-9583-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-22-9583-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Simulating the radiative forcing of oceanic dimethylsulfide (DMS) in Asia based on machine learning estimates
Junri Zhao
Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
Shanghai Institute of Eco-Chongming (SIEC), Shanghai 200062, China
Weichun Ma
Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
Institute of Digitalized Sustainable Transformation, Big Data Institute, Fudan University, Shanghai 200433, China
Kelsey R. Bilsback
Department of Atmospheric Science, Colorado State University, Fort Collins, CO, United States of America
PSE Healthy Energy, Oakland, CA, United States of America
Jeffrey R. Pierce
Department of Atmospheric Science, Colorado State University, Fort Collins, CO, United States of America
Shengqian Zhou
Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
Shanghai Institute of Eco-Chongming (SIEC), Shanghai 200062, China
Ying Chen
Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
Shanghai Institute of Eco-Chongming (SIEC), Shanghai 200062, China
Guipeng Yang
Key Laboratory of Marine Chemistry Theory and Technology, Ministry of Education, College of Chemistry and Chemical Engineering, Ocean University of China, Qingdao 266100, China
Yan Zhang
CORRESPONDING AUTHOR
Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
Shanghai Institute of Eco-Chongming (SIEC), Shanghai 200062, China
Institute of Digitalized Sustainable Transformation, Big Data Institute, Fudan University, Shanghai 200433, China
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Haihui Zhu, Randall V. Martin, Betty Croft, Shixian Zhai, Chi Li, Liam Bindle, Jeffrey R. Pierce, Rachel Y.-W. Chang, Bruce E. Anderson, Luke D. Ziemba, Johnathan W. Hair, Richard A. Ferrare, Chris A. Hostetler, Inderjeet Singh, Deepangsu Chatterjee, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Jack E. Dibb, Joshua S. Schwarz, and Andrew Weinheimer
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Xiaofei Qin, Shengqian Zhou, Hao Li, Guochen Wang, Cheng Chen, Chengfeng Liu, Xiaohao Wang, Juntao Huo, Yanfen Lin, Jia Chen, Qingyan Fu, Yusen Duan, Kan Huang, and Congrui Deng
Atmos. Chem. Phys., 22, 15851–15865, https://doi.org/10.5194/acp-22-15851-2022, https://doi.org/10.5194/acp-22-15851-2022, 2022
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Using artificial neural network modeling and an explainable analysis approach, natural surface emissions (NSEs) were identified as a main driver of gaseous elemental mercury (GEM) variations during the COVID-19 lockdown. A sharp drop in GEM concentrations due to a significant reduction in anthropogenic emissions may disrupt the surface–air exchange balance of Hg, leading to increases in NSEs. This implies that NSEs may pose challenges to the future control of Hg pollution.
Lin Yang, Jing Zhang, Anja Engel, and Gui-Peng Yang
Biogeosciences, 19, 5251–5268, https://doi.org/10.5194/bg-19-5251-2022, https://doi.org/10.5194/bg-19-5251-2022, 2022
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Enrichment factors of dissolved organic matter (DOM) in the eastern marginal seas of China exhibited a significant spatio-temporal variation. Photochemical and enrichment processes co-regulated DOM enrichment in the sea-surface microlayer (SML). Autochthonous DOM was more frequently enriched in the SML than terrestrial DOM. DOM in the sub-surface water exhibited higher aromaticity than that in the SML.
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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Mathew Sebastian, Sobhan Kumar Kompalli, Vasudevan Anil Kumar, Sandhya Jose, S. Suresh Babu, Govindan Pandithurai, Sachchidanand Singh, Rakesh K. Hooda, Vijay K. Soni, Jeffrey R. Pierce, Ville Vakkari, Eija Asmi, Daniel M. Westervelt, Antti-Pekka Hyvärinen, and Vijay P. Kanawade
Atmos. Chem. Phys., 22, 4491–4508, https://doi.org/10.5194/acp-22-4491-2022, https://doi.org/10.5194/acp-22-4491-2022, 2022
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Characteristics of particle number size distributions and new particle formation in six locations in India were analyzed. New particle formation occurred frequently during the pre-monsoon (spring) season and it significantly modulates the shape of the particle number size distributions. The contribution of newly formed particles to cloud condensation nuclei concentrations was ~3 times higher in urban locations than in mountain background locations.
Michael Cheeseman, Bonne Ford, Zoey Rosen, Eric Wendt, Alex DesRosiers, Aaron J. Hill, Christian L'Orange, Casey Quinn, Marilee Long, Shantanu H. Jathar, John Volckens, and Jeffrey R. Pierce
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2021-751, https://doi.org/10.5194/acp-2021-751, 2021
Revised manuscript not accepted
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This article predicts concentrations of airborne particulate matter over wintertime Denver, CO, USA, using meteorological and geographic information, as well as low-cost aerosol optical depth (AOD) measurements captured by citizen scientists. Machine learning methods revealed that low boundary layer heights and stagnant air were the best predictors of poor air quality, while AOD provided little skill in predicting particulate matter for this location and time period.
Eric A. Wendt, Casey Quinn, Christian L'Orange, Daniel D. Miller-Lionberg, Bonne Ford, Jeffrey R. Pierce, John Mehaffy, Michael Cheeseman, Shantanu H. Jathar, David H. Hagan, Zoey Rosen, Marilee Long, and John Volckens
Atmos. Meas. Tech., 14, 6023–6038, https://doi.org/10.5194/amt-14-6023-2021, https://doi.org/10.5194/amt-14-6023-2021, 2021
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Anna L. Hodshire, Emily Ramnarine, Ali Akherati, Matthew L. Alvarado, Delphine K. Farmer, Shantanu H. Jathar, Sonia M. Kreidenweis, Chantelle R. Lonsdale, Timothy B. Onasch, Stephen R. Springston, Jian Wang, Yang Wang, Lawrence I. Kleinman, Arthur J. Sedlacek III, and Jeffrey R. Pierce
Atmos. Chem. Phys., 21, 6839–6855, https://doi.org/10.5194/acp-21-6839-2021, https://doi.org/10.5194/acp-21-6839-2021, 2021
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Biomass burning emits particles and vapors that can impact both health and climate. Here, we investigate the role of dilution in the evolution of aerosol size and composition in observed US wildfire smoke plumes. Centers of plumes dilute more slowly than edges. We see differences in concentrations and composition between the centers and edges both in the first measurement and in subsequent measurements. Our findings support the hypothesis that plume dilution influences smoke aging.
Jingyu An, Yiwei Huang, Cheng Huang, Xin Wang, Rusha Yan, Qian Wang, Hongli Wang, Sheng'ao Jing, Yan Zhang, Yiming Liu, Yuan Chen, Chang Xu, Liping Qiao, Min Zhou, Shuhui Zhu, Qingyao Hu, Jun Lu, and Changhong Chen
Atmos. Chem. Phys., 21, 2003–2025, https://doi.org/10.5194/acp-21-2003-2021, https://doi.org/10.5194/acp-21-2003-2021, 2021
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This study established a 4 km × 4 km anthropogenic emission inventory in the Yangtze River Delta region, China, for 2017 based on locally measured emission factors and source profiles. There are high-intensity NOx and NMVOC species emissions in the eastern areas of the region. Toluene, 1,2,4-trimethylbenzene, m,p-xylene, propylene, ethylene, o-xylene, and OVOCs from industry and mobile sources have the highest comprehensive potentials for ozone and secondary organic aerosol formation.
Betty Croft, Randall V. Martin, Richard H. Moore, Luke D. Ziemba, Ewan C. Crosbie, Hongyu Liu, Lynn M. Russell, Georges Saliba, Armin Wisthaler, Markus Müller, Arne Schiller, Martí Galí, Rachel Y.-W. Chang, Erin E. McDuffie, Kelsey R. Bilsback, and Jeffrey R. Pierce
Atmos. Chem. Phys., 21, 1889–1916, https://doi.org/10.5194/acp-21-1889-2021, https://doi.org/10.5194/acp-21-1889-2021, 2021
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North Atlantic Aerosols and Marine Ecosystems Study measurements combined with GEOS-Chem-TOMAS modeling suggest that several not-well-understood key factors control northwest Atlantic aerosol number and size. These synergetic and climate-relevant factors include particle formation near and above the marine boundary layer top, particle growth by marine secondary organic aerosol on descent, particle formation/growth related to dimethyl sulfide, sea spray aerosol, and ship emissions.
Agnieszka Kupc, Christina J. Williamson, Anna L. Hodshire, Jan Kazil, Eric Ray, T. Paul Bui, Maximilian Dollner, Karl D. Froyd, Kathryn McKain, Andrew Rollins, Gregory P. Schill, Alexander Thames, Bernadett B. Weinzierl, Jeffrey R. Pierce, and Charles A. Brock
Atmos. Chem. Phys., 20, 15037–15060, https://doi.org/10.5194/acp-20-15037-2020, https://doi.org/10.5194/acp-20-15037-2020, 2020
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Tropical upper troposphere over the Atlantic and Pacific oceans is a major source region of new particles. These particles are associated with the outflow from deep convection. We investigate the processes that govern the formation of these particles and their initial growth and show that none of the formation schemes commonly used in global models are consistent with observations. Using newer schemes indicates that organic compounds are likely important as nucleating and initial growth agents.
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.
Chantelle R. Lonsdale, Matthew J. Alvarado, Anna L. Hodshire, Emily Ramnarine, and Jeffrey R. Pierce
Geosci. Model Dev., 13, 4579–4593, https://doi.org/10.5194/gmd-13-4579-2020, https://doi.org/10.5194/gmd-13-4579-2020, 2020
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The System for Atmospheric Modelling (SAM) has been coupled with the detailed gas/aerosol chemistry model, the Aerosol Simulation Program (ASP), to capture cross-plume concentration gradients as fire plumes evolve downwind. SAM-ASP v1.0 will lead to the development of parameterizations of near-source biomass burning chemistry that can be used to more accurately simulate biomass burning chemical and physical transformations of trace gases and aerosols within coarser chemical transport models.
W. Richard Leaitch, John K. Kodros, Megan D. Willis, Sarah Hanna, Hannes Schulz, Elisabeth Andrews, Heiko Bozem, Julia Burkart, Peter Hoor, Felicia Kolonjari, John A. Ogren, Sangeeta Sharma, Meng Si, Knut von Salzen, Allan K. Bertram, Andreas Herber, Jonathan P. D. Abbatt, and Jeffrey R. Pierce
Atmos. Chem. Phys., 20, 10545–10563, https://doi.org/10.5194/acp-20-10545-2020, https://doi.org/10.5194/acp-20-10545-2020, 2020
Short summary
Short summary
Black carbon is a factor in the warming of the Arctic atmosphere due to its ability to absorb light, but the uncertainty is high and few observations have been made in the high Arctic above 80° N. We combine airborne and ground-based observations in the springtime Arctic, at and above 80° N, with simulations from a global model to show that light absorption by black carbon may be much larger than modelled. However, the uncertainty remains high.
Cited articles
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Short summary
Marine dimethylsulfide (DMS) emissions play important roles in atmospheric sulfur cycle and climate effects. In this study, DMS emissions were estimated by using the machine learning method and drove the global 3D chemical transport model to simulate their climate effects. To our knowledge, this is the first study in the Asian region that quantifies the combined impacts of DMS on sulfate, particle number concentration, and radiative forcings.
Marine dimethylsulfide (DMS) emissions play important roles in atmospheric sulfur cycle and...
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