Articles | Volume 13, issue 6
https://doi.org/10.5194/gmd-13-2569-2020
© Author(s) 2020. 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-13-2569-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development of a reduced-complexity plant canopy physics surrogate model for use in chemical transport models: a case study with GEOS-Chem v12.3.0
Department of Civil and Environmental Engineering, Massachusetts
Institute of Technology, Cambridge, MA, USA
now at: Pacific Northwest National Laboratory, Richland, WA, USA
Department of Civil and Environmental Engineering, Massachusetts
Institute of Technology, Cambridge, MA, USA
Alex B. Guenther
Department of Earth System Science, University of California Irvine,
Irvine, CA, USA
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This technical note presents the research protocols for phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4). This initiative has three goals: (i) to define the state of wet and dry deposition in regional models, (ii) to evaluate how dry deposition influences air concentration and flux predictions, and (iii) to identify the causes for prediction differences. The evaluation compares LULC-specific dry deposition and effective conductances and fluxes.
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The activation of aerosol into cloud droplets is an important but uncertain process in the Earth system. The physical and chemical interactions that govern this process are too computationally expensive to explicitly resolve in modern Earth system models. Here, we demonstrate how hybrid machine learning approaches can provide a potential path forward, enabling the representation of the more detailed physics and chemistry at a reduced computational cost while still retaining physical information.
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Dry deposition is an important, but highly uncertain, sink for surface ozone. Several popular parameterizations exist to model this process, which vary with respect to how they depend on land cover and environmental variables. Here, we predict ozone dry deposition globally over 30 years, comparing four different approaches. We find that the choice of dry deposition parameterization affects the distribution, seasonal means, long-term trends, and interannual variability of surface ozone.
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Atmos. Chem. Phys., 16, 10621–10635, https://doi.org/10.5194/acp-16-10621-2016, https://doi.org/10.5194/acp-16-10621-2016, 2016
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We investigate the impacts of current (2010) and future (2020) oil palm plantations across Southeast Asia on surface–atmosphere exchange and air quality using satellite data, land maps, and a chemical transport model. These changes lead to increases in surface ozone and particulate matter. Oil palm plantations are likely to continue to degrade regional air quality in the coming decade and hinder efforts to achieve air quality regulations in major urban areas such as Kuala Lumpur and Singapore.
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EGUsphere, https://doi.org/10.5194/egusphere-2024-530, https://doi.org/10.5194/egusphere-2024-530, 2024
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Atmos. Chem. Phys., 24, 2207–2237, https://doi.org/10.5194/acp-24-2207-2024, https://doi.org/10.5194/acp-24-2207-2024, 2024
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Formaldehyde observations from satellites can be used to constrain the emissions of volatile organic compounds, but those observations have biases. Using an atmospheric model, aircraft and ground-based remote sensing data, we quantify these biases, propose a correction to the data, and assess the consequence of this correction for the evaluation of emissions.
Min Huang, Gregory R. Carmichael, James H. Crawford, Kevin W. Bowman, Isabelle De Smedt, Andreas Colliander, Michael H. Cosh, Sujay V. Kumar, Alex B. Guenther, Scott J. Janz, Ryan M. Stauffer, Anne M. Thompson, Niko M. Fedkin, Robert J. Swap, John D. Bolten, and Alicia T. Joseph
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This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Atmos. Chem. Phys., 23, 13301–13327, https://doi.org/10.5194/acp-23-13301-2023, https://doi.org/10.5194/acp-23-13301-2023, 2023
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Water deficit modifies emissions of isoprene, an aromatic compound released by plants that influences the production of an air pollutant such as ozone. Numerical modelling shows that, during the warmest and driest summers, isoprene decreases between −20 and −60 % over the Euro-Mediterranean region, while near-surface ozone only diminishes by a few percent. Decreases in isoprene emissions not only happen under dry conditions, but also could occur after prolonged or repeated water deficits.
Eliane Gomes Alves, Raoni Aquino Santana, Cléo Quaresma Dias-Júnior, Santiago Botía, Tyeen Taylor, Ana Maria Yáñez-Serrano, Jürgen Kesselmeier, Efstratios Bourtsoukidis, Jonathan Williams, Pedro Ivo Lembo Silveira de Assis, Giordane Martins, Rodrigo de Souza, Sérgio Duvoisin Júnior, Alex Guenther, Dasa Gu, Anywhere Tsokankunku, Matthias Sörgel, Bruce Nelson, Davieliton Pinto, Shujiro Komiya, Diogo Martins Rosa, Bettina Weber, Cybelli Barbosa, Michelle Robin, Kenneth J. Feeley, Alvaro Duque, Viviana Londoño Lemos, Maria Paula Contreras, Alvaro Idarraga, Norberto López, Chad Husby, Brett Jestrow, and Iván Mauricio Cely Toro
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Detlev Helmig, Alex Guenther, Jacques Hueber, Ryan Daly, Wei Wang, Jeong-Hoo Park, Anssi Liikanen, and Arnaud P. Praplan
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This research demonstrates a new method for determination of the chemical reactivity of volatile organic compounds that are emitted from the leaves and needles of trees. These measurements allow elucidating if and how much of these emissions and their associated reactivity are captured and quantified by currently applicable chemical analysis methods.
Therese S. Carter, Colette L. Heald, Jesse H. Kroll, Eric C. Apel, Donald Blake, Matthew Coggon, Achim Edtbauer, Georgios Gkatzelis, Rebecca S. Hornbrook, Jeff Peischl, Eva Y. Pfannerstill, Felix Piel, Nina G. Reijrink, Akima Ringsdorf, Carsten Warneke, Jonathan Williams, Armin Wisthaler, and Lu Xu
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Deanna C. Myers, Saewung Kim, Steven Sjostedt, Alex B. Guenther, Roger Seco, Oscar Vega Bustillos, Julio Tota, Rodrigo A. F. Souza, and James N. Smith
Atmos. Chem. Phys., 22, 10061–10076, https://doi.org/10.5194/acp-22-10061-2022, https://doi.org/10.5194/acp-22-10061-2022, 2022
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We present the first measurements of gas-phase sulfuric acid from the Amazon basin and evaluate the efficacy of existing sulfuric acid parameterizations in this understudied region. Sulfuric acid is produced during the daytime and nighttime, though current proxies underestimate nighttime production. These results illustrate the need for better parameterizations of sulfuric acid and its precursors that are informed by measurements across a broad range of locations.
Ka Ming Fung, Colette L. Heald, Jesse H. Kroll, Siyuan Wang, Duseong S. Jo, Andrew Gettelman, Zheng Lu, Xiaohong Liu, Rahul A. Zaveri, Eric C. Apel, Donald R. Blake, Jose-Luis Jimenez, Pedro Campuzano-Jost, Patrick R. Veres, Timothy S. Bates, John E. Shilling, and Maria Zawadowicz
Atmos. Chem. Phys., 22, 1549–1573, https://doi.org/10.5194/acp-22-1549-2022, https://doi.org/10.5194/acp-22-1549-2022, 2022
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Understanding the natural aerosol burden in the preindustrial era is crucial for us to assess how atmospheric aerosols affect the Earth's radiative budgets. Our study explores how a detailed description of dimethyl sulfide (DMS) oxidation (implemented in the Community Atmospheric Model version 6 with chemistry, CAM6-chem) could help us better estimate the present-day and preindustrial concentrations of sulfate and other relevant chemicals, as well as the resulting aerosol radiative impacts.
Stefano Galmarini, Paul Makar, Olivia E. Clifton, Christian Hogrefe, Jesse O. Bash, Roberto Bellasio, Roberto Bianconi, Johannes Bieser, Tim Butler, Jason Ducker, Johannes Flemming, Alma Hodzic, Christopher D. Holmes, Ioannis Kioutsioukis, Richard Kranenburg, Aurelia Lupascu, Juan Luis Perez-Camanyo, Jonathan Pleim, Young-Hee Ryu, Roberto San Jose, Donna Schwede, Sam Silva, and Ralf Wolke
Atmos. Chem. Phys., 21, 15663–15697, https://doi.org/10.5194/acp-21-15663-2021, https://doi.org/10.5194/acp-21-15663-2021, 2021
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This technical note presents the research protocols for phase 4 of the Air Quality Model Evaluation International Initiative (AQMEII4). This initiative has three goals: (i) to define the state of wet and dry deposition in regional models, (ii) to evaluate how dry deposition influences air concentration and flux predictions, and (iii) to identify the causes for prediction differences. The evaluation compares LULC-specific dry deposition and effective conductances and fluxes.
Chinmoy Sarkar, Gracie Wong, Anne Mielnik, Sanjeevi Nagalingam, Nicole Jenna Gross, Alex B. Guenther, Taehyoung Lee, Taehyun Park, Jihee Ban, Seokwon Kang, Jin-Soo Park, Joonyoung Ahn, Danbi Kim, Hyunjae Kim, Jinsoo Choi, Beom-Keun Seo, Jong-Ho Kim, Jeong-Ho Kim, Soo Bog Park, and Saewung Kim
Atmos. Chem. Phys., 21, 11505–11518, https://doi.org/10.5194/acp-21-11505-2021, https://doi.org/10.5194/acp-21-11505-2021, 2021
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We present experimental proofs illustrating the emission of an unexplored volatile organic compound, tentatively assigned as ketene, in an industrial facility in South Korea. The emission of such a compound has rarely been reported, but our experimental data show that the emission rate is substantial. It potentially has tremendous implications for regional air quality and public health, as it is highly reactive and toxic at the same time.
Beata Opacka, Jean-François Müller, Trissevgeni Stavrakou, Maite Bauwens, Katerina Sindelarova, Jana Markova, and Alex B. Guenther
Atmos. Chem. Phys., 21, 8413–8436, https://doi.org/10.5194/acp-21-8413-2021, https://doi.org/10.5194/acp-21-8413-2021, 2021
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Isoprene is mainly emitted from plants, and about 80 % of its global emissions occur in the tropics. Current isoprene inventories are usually based on modelled vegetation maps, but high pressure on land use over the last decades has led to severe losses, especially in tropical forests, that are not considered by models. We provide a study on the present-day impact of spaceborne land cover changes on isoprene emissions and the first inventory based on high-resolution Landsat tree cover dataset.
Sam J. Silva, Po-Lun Ma, Joseph C. Hardin, and Daniel Rothenberg
Geosci. Model Dev., 14, 3067–3077, https://doi.org/10.5194/gmd-14-3067-2021, https://doi.org/10.5194/gmd-14-3067-2021, 2021
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The activation of aerosol into cloud droplets is an important but uncertain process in the Earth system. The physical and chemical interactions that govern this process are too computationally expensive to explicitly resolve in modern Earth system models. Here, we demonstrate how hybrid machine learning approaches can provide a potential path forward, enabling the representation of the more detailed physics and chemistry at a reduced computational cost while still retaining physical information.
Dianne Sanchez, Roger Seco, Dasa Gu, Alex Guenther, John Mak, Youngjae Lee, Danbi Kim, Joonyoung Ahn, Don Blake, Scott Herndon, Daun Jeong, John T. Sullivan, Thomas Mcgee, Rokjin Park, and Saewung Kim
Atmos. Chem. Phys., 21, 6331–6345, https://doi.org/10.5194/acp-21-6331-2021, https://doi.org/10.5194/acp-21-6331-2021, 2021
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We present observations of total reactive gases in a suburban forest observatory in the Seoul metropolitan area. The quantitative comparison with speciated trace gas observations illustrated significant underestimation in atmospheric reactivity from the speciated trace gas observational dataset. We present scientific discussion about potential causes.
Hui Wang, Qizhong Wu, Alex B. Guenther, Xiaochun Yang, Lanning Wang, Tang Xiao, Jie Li, Jinming Feng, Qi Xu, and Huaqiong Cheng
Atmos. Chem. Phys., 21, 4825–4848, https://doi.org/10.5194/acp-21-4825-2021, https://doi.org/10.5194/acp-21-4825-2021, 2021
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We assessed the influence of the greening trend on BVOC emission in China. The comparison among different scenarios showed that vegetation changes resulting from land cover management are the main driver of BVOC emission change in China. Climate variability contributed significantly to interannual variations but not much to the long-term trend during the study period.
Ruud H. H. Janssen, Colette L. Heald, Allison L. Steiner, Anne E. Perring, J. Alex Huffman, Ellis S. Robinson, Cynthia H. Twohy, and Luke D. Ziemba
Atmos. Chem. Phys., 21, 4381–4401, https://doi.org/10.5194/acp-21-4381-2021, https://doi.org/10.5194/acp-21-4381-2021, 2021
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Bioaerosols are ubiquitous in the atmosphere and have the potential to affect cloud formation, as well as human and ecosystem health. However, their emissions are not well quantified, which hinders the assessment of their role in atmospheric processes. Here, we develop two new emission schemes for fungal spores based on multi-annual datasets of spore counts. We find that our modeled global emissions and burden are an order of magnitude lower than previous estimates.
Chen Dayan, Erick Fredj, Pawel K. Misztal, Maor Gabay, Alex B. Guenther, and Eran Tas
Atmos. Chem. Phys., 20, 12741–12759, https://doi.org/10.5194/acp-20-12741-2020, https://doi.org/10.5194/acp-20-12741-2020, 2020
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We studied the emission of biogenic volatile organic compounds from both marine and terrestrial ecosystems in the Eastern Mediterranean Basin, a global warming hot spot. We focused on isoprene and dimethyl sulfide (DMS), which are well recognized for their effect on climate and strong impact on photochemical pollution by the former. We found high emissions of isoprene and a strong decadal decrease in the emission of DMS which can both be attributed to the strong increase in seawater temperature.
Archit Mehra, Jordan E. Krechmer, Andrew Lambe, Chinmoy Sarkar, Leah Williams, Farzaneh Khalaj, Alex Guenther, John Jayne, Hugh Coe, Douglas Worsnop, Celia Faiola, and Manjula Canagaratna
Atmos. Chem. Phys., 20, 10953–10965, https://doi.org/10.5194/acp-20-10953-2020, https://doi.org/10.5194/acp-20-10953-2020, 2020
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Emissions of volatile organic compounds (VOCs) from plants are important for tropospheric ozone and secondary organic aerosol (SOA) formation. Real plant emissions are much more diverse than the few proxies widely used for studies of plant SOA. Here we present the first study of SOA from Californian sage plants and the oxygenated monoterpenes representing their major emissions. We identify SOA products and show the importance of the formation of highly oxygenated organic molecules and oligomers.
Katherine R. Travis, Colette L. Heald, Hannah M. Allen, Eric C. Apel, Stephen R. Arnold, Donald R. Blake, William H. Brune, Xin Chen, Róisín Commane, John D. Crounse, Bruce C. Daube, Glenn S. Diskin, James W. Elkins, Mathew J. Evans, Samuel R. Hall, Eric J. Hintsa, Rebecca S. Hornbrook, Prasad S. Kasibhatla, Michelle J. Kim, Gan Luo, Kathryn McKain, Dylan B. Millet, Fred L. Moore, Jeffrey Peischl, Thomas B. Ryerson, Tomás Sherwen, Alexander B. Thames, Kirk Ullmann, Xuan Wang, Paul O. Wennberg, Glenn M. Wolfe, and Fangqun Yu
Atmos. Chem. Phys., 20, 7753–7781, https://doi.org/10.5194/acp-20-7753-2020, https://doi.org/10.5194/acp-20-7753-2020, 2020
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Atmospheric models overestimate the rate of removal of trace gases by the hydroxyl radical (OH). This is a concern for studies of the climate and air quality impacts of human activities. Here, we evaluate the performance of a commonly used model of atmospheric chemistry against data from the NASA Atmospheric Tomography Mission (ATom) over the remote oceans where models have received little validation. The model is generally successful, suggesting that biases in OH may be a concern over land.
Chinmoy Sarkar, Alex B. Guenther, Jeong-Hoo Park, Roger Seco, Eliane Alves, Sarah Batalha, Raoni Santana, Saewung Kim, James Smith, Julio Tóta, and Oscar Vega
Atmos. Chem. Phys., 20, 7179–7191, https://doi.org/10.5194/acp-20-7179-2020, https://doi.org/10.5194/acp-20-7179-2020, 2020
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Biogenic volatile organic compounds (BVOCs) are important components of the atmosphere due to their contribution to atmospheric chemistry and biogeochemical cycles. In this study, we report major BVOCs, e.g. isoprene and total monoterpene flux measurements with a proton transfer reaction time-of-flight mass spectrometer (PTR-TOF-MS) using the eddy covariance (EC) method at a primary rainforest in eastern Amazonia. We used the measured data to evaluate the MEGAN2.1 model for the emission site.
Sidhant J. Pai, Colette L. Heald, Jeffrey R. Pierce, Salvatore C. Farina, Eloise A. Marais, Jose L. Jimenez, Pedro Campuzano-Jost, Benjamin A. Nault, Ann M. Middlebrook, Hugh Coe, John E. Shilling, Roya Bahreini, Justin H. Dingle, and Kennedy Vu
Atmos. Chem. Phys., 20, 2637–2665, https://doi.org/10.5194/acp-20-2637-2020, https://doi.org/10.5194/acp-20-2637-2020, 2020
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Aerosols in the atmosphere have significant health and climate impacts. Organic aerosol (OA) accounts for a large fraction of the total aerosol burden, but models have historically struggled to accurately simulate it. This study compares two very different OA model schemes and evaluates them against a suite of globally distributed airborne measurements with the goal of providing insight into the strengths and weaknesses of each approach across different environments.
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.
Anthony Y. H. Wong, Jeffrey A. Geddes, Amos P. K. Tai, and Sam J. Silva
Atmos. Chem. Phys., 19, 14365–14385, https://doi.org/10.5194/acp-19-14365-2019, https://doi.org/10.5194/acp-19-14365-2019, 2019
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Dry deposition is an important, but highly uncertain, sink for surface ozone. Several popular parameterizations exist to model this process, which vary with respect to how they depend on land cover and environmental variables. Here, we predict ozone dry deposition globally over 30 years, comparing four different approaches. We find that the choice of dry deposition parameterization affects the distribution, seasonal means, long-term trends, and interannual variability of surface ozone.
Maria A. Zawadowicz, Karl D. Froyd, Anne E. Perring, Daniel M. Murphy, Dominick V. Spracklen, Colette L. Heald, Peter R. Buseck, and Daniel J. Cziczo
Atmos. Chem. Phys., 19, 13859–13870, https://doi.org/10.5194/acp-19-13859-2019, https://doi.org/10.5194/acp-19-13859-2019, 2019
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We report measurements of small particles of biological origin (for example, fragments of bacteria, pollen, or fungal spores) in the atmosphere over the continental United States. We use a recently developed identification technique based on airborne mass spectrometry in conjunction with an extensive aircraft dataset. We show that biological particles are present at altitudes up to 10 km and we quantify typical concentrations.
William C. Porter and Colette L. Heald
Atmos. Chem. Phys., 19, 13367–13381, https://doi.org/10.5194/acp-19-13367-2019, https://doi.org/10.5194/acp-19-13367-2019, 2019
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In this paper we explore the connection between changes in surface temperature and changes in ozone pollution. While explanations for this connection have been proposed in the past, we attempt to better quantify them using models and statistics. We find that some of the most commonly cited mechanisms, including biogenic emissions and temperature-dependent chemical processes, can explain less than half of the O3–T correlation. Meteorology is identified as the most likely driver for the remainder.
Daun Jeong, Roger Seco, Dasa Gu, Youngro Lee, Benjamin A. Nault, Christoph J. Knote, Tom Mcgee, John T. Sullivan, Jose L. Jimenez, Pedro Campuzano-Jost, Donald R. Blake, Dianne Sanchez, Alex B. Guenther, David Tanner, L. Gregory Huey, Russell Long, Bruce E. Anderson, Samuel R. Hall, Kirk Ullmann, Hye-jung Shin, Scott C. Herndon, Youngjae Lee, Danbi Kim, Joonyoung Ahn, and Saewung Kim
Atmos. Chem. Phys., 19, 12779–12795, https://doi.org/10.5194/acp-19-12779-2019, https://doi.org/10.5194/acp-19-12779-2019, 2019
Emma L. D'Ambro, Siegfried Schobesberger, Cassandra J. Gaston, Felipe D. Lopez-Hilfiker, Ben H. Lee, Jiumeng Liu, Alla Zelenyuk, David Bell, Christopher D. Cappa, Taylor Helgestad, Ziyue Li, Alex Guenther, Jian Wang, Matthew Wise, Ryan Caylor, Jason D. Surratt, Theran Riedel, Noora Hyttinen, Vili-Taneli Salo, Galib Hasan, Theo Kurtén, John E. Shilling, and Joel A. Thornton
Atmos. Chem. Phys., 19, 11253–11265, https://doi.org/10.5194/acp-19-11253-2019, https://doi.org/10.5194/acp-19-11253-2019, 2019
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Isoprene is the most abundantly emitted reactive organic gas globally, and thus it is important to understand its fate and role in aerosol formation and growth. A major product of its oxidation is an epoxydiol, IEPOX, which can be efficiently taken up by acidic aerosol to generate substantial amounts of secondary organic aerosol (SOA). We present chamber experiments exploring the properties of IEPOX SOA and reconcile discrepancies between field, laboratory, and model studies of this process.
Karena A. McKinney, Daniel Wang, Jianhuai Ye, Jean-Baptiste de Fouchier, Patricia C. Guimarães, Carla E. Batista, Rodrigo A. F. Souza, Eliane G. Alves, Dasa Gu, Alex B. Guenther, and Scot T. Martin
Atmos. Meas. Tech., 12, 3123–3135, https://doi.org/10.5194/amt-12-3123-2019, https://doi.org/10.5194/amt-12-3123-2019, 2019
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Volatile organic compound (VOC) emissions influence air quality and particulate distributions, particularly in major source regions such as the Amazon. A sampler for collecting VOCs from an unmanned aerial vehicle (UAV) is described. Field tests of its performance and an initial example data set collected in the Amazon are also presented. The low cost, ease of use, and maneuverability of UAVs give this method the potential to significantly advance knowledge of the spatial distribution of VOCs.
Moshe Shechner, Alex Guenther, Robert Rhew, Asher Wishkerman, Qian Li, Donald Blake, Gil Lerner, and Eran Tas
Atmos. Chem. Phys., 19, 7667–7690, https://doi.org/10.5194/acp-19-7667-2019, https://doi.org/10.5194/acp-19-7667-2019, 2019
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Along with other recent studies, our findings point to strong emission of a suite of volatile halogenated organic compounds (VHOCs) from saline soils and salt lakes. Some emitted VHOCs were not known to be emitted from terrestrial sources, and our observations point to apparent new common controls for the emission of several VHOCs. These findings are an important milestone toward a more complete understanding of the effect of VHOCs on atmospheric ozone concentrations and oxidation capacity.
Shan S. Zhou, Amos P. K. Tai, Shihan Sun, Mehliyar Sadiq, Colette L. Heald, and Jeffrey A. Geddes
Atmos. Chem. Phys., 18, 14133–14148, https://doi.org/10.5194/acp-18-14133-2018, https://doi.org/10.5194/acp-18-14133-2018, 2018
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Surface ozone pollution harms vegetation. As plants play key roles shaping air quality, the plant damage may further worsen air pollution. We use various computer models to examine such feedback effects, and find that ozone-induced decline in leaf density can lead to much higher ozone levels in forested regions, mostly due to the reduced ability of leaves to absorb pollutants. This study highlights the importance of considering the two-way interactions between plants and air pollution.
Harri Kokkola, Thomas Kühn, Anton Laakso, Tommi Bergman, Kari E. J. Lehtinen, Tero Mielonen, Antti Arola, Scarlet Stadtler, Hannele Korhonen, Sylvaine Ferrachat, Ulrike Lohmann, David Neubauer, Ina Tegen, Colombe Siegenthaler-Le Drian, Martin G. Schultz, Isabelle Bey, Philip Stier, Nikos Daskalakis, Colette L. Heald, and Sami Romakkaniemi
Geosci. Model Dev., 11, 3833–3863, https://doi.org/10.5194/gmd-11-3833-2018, https://doi.org/10.5194/gmd-11-3833-2018, 2018
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In this paper we present a global aerosol–chemistry–climate model with the focus on its representation for atmospheric aerosol particles. In the model, aerosols are simulated using the aerosol module SALSA2.0, which in this paper is compared to satellite, ground, and aircraft-based observations of the properties of atmospheric aerosol. Based on this study, the model simulated aerosol properties compare well with the observations.
Fernando Santos, Karla Longo, Alex Guenther, Saewung Kim, Dasa Gu, Dave Oram, Grant Forster, James Lee, James Hopkins, Joel Brito, and Saulo Freitas
Atmos. Chem. Phys., 18, 12715–12734, https://doi.org/10.5194/acp-18-12715-2018, https://doi.org/10.5194/acp-18-12715-2018, 2018
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We investigated the impact of biomass burning on the chemical composition of trace gases in the Amazon. The findings corroborate the influence of biomass burning activity not only on direct emissions of particulate matter but also on the oxidative capacity to produce secondary organic aerosol. The scientists plan to use this information to improve the numerical model simulation with a better representativeness of the chemical processes, which can impact on global climate prediction.
Anna L. Hodshire, Brett B. Palm, M. Lizabeth Alexander, Qijing Bian, Pedro Campuzano-Jost, Eben S. Cross, Douglas A. Day, Suzane S. de Sá, Alex B. Guenther, Armin Hansel, James F. Hunter, Werner Jud, Thomas Karl, Saewung Kim, Jesse H. Kroll, Jeong-Hoo Park, Zhe Peng, Roger Seco, James N. Smith, Jose L. Jimenez, and Jeffrey R. Pierce
Atmos. Chem. Phys., 18, 12433–12460, https://doi.org/10.5194/acp-18-12433-2018, https://doi.org/10.5194/acp-18-12433-2018, 2018
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We investigate the nucleation and growth processes that shape the aerosol size distribution inside oxidation flow reactors (OFRs) that sampled ambient air from Colorado and the Amazon rainforest. Results indicate that organics are important for both nucleation and growth, vapor uptake was limited to accumulation-mode particles, fragmentation reactions were important to limit particle growth at higher OH exposures, and an H2SO4-organics nucleation mechanism captured new particle formation well.
Luke D. Schiferl, Colette L. Heald, and David Kelly
Biogeosciences, 15, 4301–4315, https://doi.org/10.5194/bg-15-4301-2018, https://doi.org/10.5194/bg-15-4301-2018, 2018
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To understand future food security, it is critical to develop realistic crop models with reliable sensitivity to environmental factors. We find that particulate matter (PM) causes a significant, but smaller, enhancement for global wheat and rice production than estimated without nutrient and physiological limitations imposed by a crop model. In contrast, maize grows near its physiological maximum, with little enhancement from PM. Nitrogen deposition leads to a small increase in crop production.
Eliane G. Alves, Julio Tóta, Andrew Turnipseed, Alex B. Guenther, José Oscar W. Vega Bustillos, Raoni A. Santana, Glauber G. Cirino, Julia V. Tavares, Aline P. Lopes, Bruce W. Nelson, Rodrigo A. de Souza, Dasa Gu, Trissevgeni Stavrakou, David K. Adams, Jin Wu, Scott Saleska, and Antonio O. Manzi
Biogeosciences, 15, 4019–4032, https://doi.org/10.5194/bg-15-4019-2018, https://doi.org/10.5194/bg-15-4019-2018, 2018
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This study shows that leaf quantity and leaf age have an important effect on seasonal changes in isoprene emissions and that these could play an even more important role in regulating ecosystem isoprene fluxes than light and temperature at seasonal timescales in tropical forests. These results bring novelty and new insight for future research because in the past leaf phenology was not considered as an important factor that controls biological processes in the tropics.
Chunxiang Ye, Xianliang Zhou, Dennis Pu, Jochen Stutz, James Festa, Max Spolaor, Catalina Tsai, Christopher Cantrell, Roy L. Mauldin III, Andrew Weinheimer, Rebecca S. Hornbrook, Eric C. Apel, Alex Guenther, Lisa Kaser, Bin Yuan, Thomas Karl, Julie Haggerty, Samuel Hall, Kirk Ullmann, James Smith, and John Ortega
Atmos. Chem. Phys., 18, 9107–9120, https://doi.org/10.5194/acp-18-9107-2018, https://doi.org/10.5194/acp-18-9107-2018, 2018
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Substantial levels of HONO existed during the day throughout the troposphere over the southeastern US during NOMADSS 2013. Particulate nitrate photolysis appeared to be the major volume HONO source, while NOx was an important HONO precursor only in industrial and urban plumes. HONO was not a significant OH radical precursor in the rural troposphere away from the ground surface; however, its production from particulate nitrate photolysis was an important renoxification pathway.
Maite Bauwens, Trissevgeni Stavrakou, Jean-François Müller, Bert Van Schaeybroeck, Lesley De Cruz, Rozemien De Troch, Olivier Giot, Rafiq Hamdi, Piet Termonia, Quentin Laffineur, Crist Amelynck, Niels Schoon, Bernard Heinesch, Thomas Holst, Almut Arneth, Reinhart Ceulemans, Arturo Sanchez-Lorenzo, and Alex Guenther
Biogeosciences, 15, 3673–3690, https://doi.org/10.5194/bg-15-3673-2018, https://doi.org/10.5194/bg-15-3673-2018, 2018
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Biogenic isoprene fluxes are simulated over Europe with the MEGAN–MOHYCAN model for the recent past and end-of-century climate at high spatiotemporal resolution (0.1°, 3 min). Due to climate change, fluxes increased by 40 % over 1979–2014. Climate scenarios for 2070–2099 suggest an increase by 83 % due to climate, and an even stronger increase when the potential impact of CO2 fertilization is considered (up to 141 %). Accounting for CO2 inhibition cancels out a large part of these increases.
Nan Li, Qingyang He, Jim Greenberg, Alex Guenther, Jingyi Li, Junji Cao, Jun Wang, Hong Liao, Qiyuan Wang, and Qiang Zhang
Atmos. Chem. Phys., 18, 7489–7507, https://doi.org/10.5194/acp-18-7489-2018, https://doi.org/10.5194/acp-18-7489-2018, 2018
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O3 pollution has been increasing in most Chinese cities in recent years. Our study reveals that the synergistic impact of individual source contributions to O3 formation should be considered in the formation of air pollution control strategies, especially for big cities in the vicinity of forests.
Luke D. Schiferl and Colette L. Heald
Atmos. Chem. Phys., 18, 5953–5966, https://doi.org/10.5194/acp-18-5953-2018, https://doi.org/10.5194/acp-18-5953-2018, 2018
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Global population growth and industrialization have contributed to poor air quality worldwide, and increasing population will put pressure on global food production. We therefore assess how air pollution may impact crop growth. Ozone has previously been shown to damage crops. We demonstrate that the impact of particles associated with enhanced light scattering promotes growth, offsetting much, if not all, ozone damage. This has implications for air quality management and global food security.
Jingqiu Mao, Annmarie Carlton, Ronald C. Cohen, William H. Brune, Steven S. Brown, Glenn M. Wolfe, Jose L. Jimenez, Havala O. T. Pye, Nga Lee Ng, Lu Xu, V. Faye McNeill, Kostas Tsigaridis, Brian C. McDonald, Carsten Warneke, Alex Guenther, Matthew J. Alvarado, Joost de Gouw, Loretta J. Mickley, Eric M. Leibensperger, Rohit Mathur, Christopher G. Nolte, Robert W. Portmann, Nadine Unger, Mika Tosca, and Larry W. Horowitz
Atmos. Chem. Phys., 18, 2615–2651, https://doi.org/10.5194/acp-18-2615-2018, https://doi.org/10.5194/acp-18-2615-2018, 2018
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This paper is aimed at discussing progress in evaluating, diagnosing, and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models.
Xuan Wang, Colette L. Heald, Jiumeng Liu, Rodney J. Weber, Pedro Campuzano-Jost, Jose L. Jimenez, Joshua P. Schwarz, and Anne E. Perring
Atmos. Chem. Phys., 18, 635–653, https://doi.org/10.5194/acp-18-635-2018, https://doi.org/10.5194/acp-18-635-2018, 2018
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Brown carbon (BrC) contributes significantly to uncertainty in estimating the global direct radiative effect (DRE) of aerosols. We develop a global model simulation of BrC and test it against BrC absorption measurements from two aircraft campaigns in the continental United States. We suggest that BrC DRE has been overestimated previously due to the lack of observational constraints from direct measurements and omission of the effects of photochemical whitening.
Brett B. Palm, Suzane S. de Sá, Douglas A. Day, Pedro Campuzano-Jost, Weiwei Hu, Roger Seco, Steven J. Sjostedt, Jeong-Hoo Park, Alex B. Guenther, Saewung Kim, Joel Brito, Florian Wurm, Paulo Artaxo, Ryan Thalman, Jian Wang, Lindsay D. Yee, Rebecca Wernis, Gabriel Isaacman-VanWertz, Allen H. Goldstein, Yingjun Liu, Stephen R. Springston, Rodrigo Souza, Matt K. Newburn, M. Lizabeth Alexander, Scot T. Martin, and Jose L. Jimenez
Atmos. Chem. Phys., 18, 467–493, https://doi.org/10.5194/acp-18-467-2018, https://doi.org/10.5194/acp-18-467-2018, 2018
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Ambient air was oxidized by OH or O3 in an oxidation flow reactor during both wet and dry seasons in the GoAmazon2014/5 campaign to study secondary organic aerosol (SOA) formation. We investigated how much biogenic, urban, and biomass burning sources contributed to the ambient concentrations of SOA precursor gases and how their contributions changed diurnally and seasonally. SOA yields and hygroscopicity of organic aerosol in the oxidation flow reactor were also studied.
David H. Hagan, Gabriel Isaacman-VanWertz, Jonathan P. Franklin, Lisa M. M. Wallace, Benjamin D. Kocar, Colette L. Heald, and Jesse H. Kroll
Atmos. Meas. Tech., 11, 315–328, https://doi.org/10.5194/amt-11-315-2018, https://doi.org/10.5194/amt-11-315-2018, 2018
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The use of low-cost sensors for air pollution research has outpaced our understanding of their capabilities and limitations under real-world conditions. Here we describe the deployment, calibration and evaluation of electrochemical sensors on the Island of Hawai‘i. We obtain excellent performance (RMSE < 7 ppb, r2 = 0.997) across a wide dynamic range (1 ppb–2 ppm). We introduce a hybrid regression algorithm which works across a large dynamic range and shows little decay in sensitivity over time.
Robert C. Rhew, Malte Julian Deventer, Andrew A. Turnipseed, Carsten Warneke, John Ortega, Steve Shen, Luis Martinez, Abigail Koss, Brian M. Lerner, Jessica B. Gilman, James N. Smith, Alex B. Guenther, and Joost A. de Gouw
Atmos. Chem. Phys., 17, 13417–13438, https://doi.org/10.5194/acp-17-13417-2017, https://doi.org/10.5194/acp-17-13417-2017, 2017
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Alkenes emanate from both natural and anthropogenic sources and can contribute to atmospheric ozone production. This study measured
lightalkene (ethene, propene and butene) fluxes from a ponderosa pine forest using a novel relaxed eddy accumulation method, revealing much larger emissions than previously estimated and accounting for a significant fraction of OH reactivity. Emissions have a diurnal cycle related to sunlight and temperature, and the forest canopy appears to be the source.
Min Huang, Gregory R. Carmichael, James H. Crawford, Armin Wisthaler, Xiwu Zhan, Christopher R. Hain, Pius Lee, and Alex B. Guenther
Geosci. Model Dev., 10, 3085–3104, https://doi.org/10.5194/gmd-10-3085-2017, https://doi.org/10.5194/gmd-10-3085-2017, 2017
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Various sensitivity simulations during two airborne campaigns were performed to assess the impact of different initialization methods and model resolutions on NUWRF-modeled weather states, heat fluxes, and the follow-on MEGAN isoprene emission calculations. Proper land initialization is shown to be important to the coupled weather modeling and the follow-on emission modeling, which is also critical to accurately representing other processes in air quality modeling and data assimilation.
Molly B. Smith, Natalie M. Mahowald, Samuel Albani, Aaron Perry, Remi Losno, Zihan Qu, Beatrice Marticorena, David A. Ridley, and Colette L. Heald
Atmos. Chem. Phys., 17, 3253–3278, https://doi.org/10.5194/acp-17-3253-2017, https://doi.org/10.5194/acp-17-3253-2017, 2017
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Using different meteorology reanalyses to drive dust in climate modeling can produce dissimilar global dust distributions, especially in the Southern Hemisphere (SH). It may therefore not be advisable for SH dust studies to base results on simulations driven by one reanalysis. Northern Hemisphere dust varies mostly on seasonal timescales, while SH dust varies on interannual timescales. Dust is an important part of climate modeling, and we hope this contributes to understanding these simulations.
Kerneels Jaars, Pieter G. van Zyl, Johan P. Beukes, Heidi Hellén, Ville Vakkari, Micky Josipovic, Andrew D. Venter, Matti Räsänen, Leandra Knoetze, Dirk P. Cilliers, Stefan J. Siebert, Markku Kulmala, Janne Rinne, Alex Guenther, Lauri Laakso, and Hannele Hakola
Atmos. Chem. Phys., 16, 15665–15688, https://doi.org/10.5194/acp-16-15665-2016, https://doi.org/10.5194/acp-16-15665-2016, 2016
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Biogenic volatile organic compounds (BVOCs) – important in tropospheric ozone and secondary organic aerosol formation – were measured at a savannah grassland in South Africa. Results presented are the most extensive for this type of landscape. Compared to other parts of the world, monoterpene levels were similar, while very low isoprene levels led to significantly lower total BVOC levels. BVOC levels were an order of magnitude lower compared to anthropogenic VOC levels measured at Welgegund.
David A. Ridley, Colette L. Heald, Jasper F. Kok, and Chun Zhao
Atmos. Chem. Phys., 16, 15097–15117, https://doi.org/10.5194/acp-16-15097-2016, https://doi.org/10.5194/acp-16-15097-2016, 2016
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Mineral dust aerosol affects climate through interaction with radiation and clouds, human health through contribution to particulate matter, and ecosystem health through nutrient transport and deposition. In this study, we use satellite and in situ retrievals to derive an observational estimate of the global dust AOD with which evaluate modeled dust AOD. Differences in the seasonality and regional distribution of dust AOD between observations and models are highlighted.
Colette L. Heald and Jeffrey A. Geddes
Atmos. Chem. Phys., 16, 14997–15010, https://doi.org/10.5194/acp-16-14997-2016, https://doi.org/10.5194/acp-16-14997-2016, 2016
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Humans have altered the surface of the Earth since preindustrial times. These changes (largely expansion of croplands and pasturelands) have modified biosphere–atmosphere fluxes. In this study we use a global model to assess the impact of these changes on the formation of secondary particulate matter and troposphere ozone. We find that there are significant air quality and climate impacts associated with these changes.
Xuan Wang, Colette L. Heald, Arthur J. Sedlacek, Suzane S. de Sá, Scot T. Martin, M. Lizabeth Alexander, Thomas B. Watson, Allison C. Aiken, Stephen R. Springston, and Paulo Artaxo
Atmos. Chem. Phys., 16, 12733–12752, https://doi.org/10.5194/acp-16-12733-2016, https://doi.org/10.5194/acp-16-12733-2016, 2016
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We describe a new approach to estimate the absorption of brown carbon (BrC) from multiple-wavelength absorption measurements. By applying this method to column and surface observations globally, we find that BrC contributes up to 40 % of the absorption measured at 440 nm. The analysis of two surface sites also suggests that BrC absorptivity decreases with photochemical aging in biomass burning plumes, but not in typical urban conditions.
Luke D. Schiferl, Colette L. Heald, Martin Van Damme, Lieven Clarisse, Cathy Clerbaux, Pierre-François Coheur, John B. Nowak, J. Andrew Neuman, Scott C. Herndon, Joseph R. Roscioli, and Scott J. Eilerman
Atmos. Chem. Phys., 16, 12305–12328, https://doi.org/10.5194/acp-16-12305-2016, https://doi.org/10.5194/acp-16-12305-2016, 2016
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This study combines new observations and a simulation to assess the interannual variability of atmospheric ammonia concentrations over the United States. The model generally underrepresents the observed variability. Nearly two-thirds of the simulated variability is caused by meteorology, twice that caused by regulations on fossil fuel combustion emissions. Adding ammonia emissions variability does not substantially improve the simulation and has little impact on summer particle concentrations.
Ivan Kourtchev, Ricardo H. M. Godoi, Sarah Connors, James G. Levine, Alex T. Archibald, Ana F. L. Godoi, Sarah L. Paralovo, Cybelli G. G. Barbosa, Rodrigo A. F. Souza, Antonio O. Manzi, Roger Seco, Steve Sjostedt, Jeong-Hoo Park, Alex Guenther, Saewung Kim, James Smith, Scot T. Martin, and Markus Kalberer
Atmos. Chem. Phys., 16, 11899–11913, https://doi.org/10.5194/acp-16-11899-2016, https://doi.org/10.5194/acp-16-11899-2016, 2016
Weiwei Hu, Brett B. Palm, Douglas A. Day, Pedro Campuzano-Jost, Jordan E. Krechmer, Zhe Peng, Suzane S. de Sá, Scot T. Martin, M. Lizabeth Alexander, Karsten Baumann, Lina Hacker, Astrid Kiendler-Scharr, Abigail R. Koss, Joost A. de Gouw, Allen H. Goldstein, Roger Seco, Steven J. Sjostedt, Jeong-Hoo Park, Alex B. Guenther, Saewung Kim, Francesco Canonaco, André S. H. Prévôt, William H. Brune, and Jose L. Jimenez
Atmos. Chem. Phys., 16, 11563–11580, https://doi.org/10.5194/acp-16-11563-2016, https://doi.org/10.5194/acp-16-11563-2016, 2016
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IEPOX-SOA is biogenically derived secondary organic aerosol under anthropogenic influence, which has been shown to comprise a substantial fraction of OA globally. We investigated the lifetime of ambient IEPOX-SOA in the SE US and Amazonia, with an oxidation flow reactor and thermodenuder coupled with MS-based instrumentation. The low volatility and long lifetime of IEPOX-SOA against OH radicals' oxidation (> 2 weeks) was observed, which can help to constrain OA impact on air quality and climate.
Sam J. Silva, Colette L. Heald, Jeffrey A. Geddes, Kemen G. Austin, Prasad S. Kasibhatla, and Miriam E. Marlier
Atmos. Chem. Phys., 16, 10621–10635, https://doi.org/10.5194/acp-16-10621-2016, https://doi.org/10.5194/acp-16-10621-2016, 2016
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We investigate the impacts of current (2010) and future (2020) oil palm plantations across Southeast Asia on surface–atmosphere exchange and air quality using satellite data, land maps, and a chemical transport model. These changes lead to increases in surface ozone and particulate matter. Oil palm plantations are likely to continue to degrade regional air quality in the coming decade and hinder efforts to achieve air quality regulations in major urban areas such as Kuala Lumpur and Singapore.
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.
Pawel K. Misztal, Jeremy C. Avise, Thomas Karl, Klaus Scott, Haflidi H. Jonsson, Alex B. Guenther, and Allen H. Goldstein
Atmos. Chem. Phys., 16, 9611–9628, https://doi.org/10.5194/acp-16-9611-2016, https://doi.org/10.5194/acp-16-9611-2016, 2016
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In this study, for the first time regional BVOC models are compared with direct regional measurements of fluxes from aircraft, allowing assessment of model accuracy at scales relevant to air quality modeling. We directly assess modeled isoprene emission inventories which are important for regional air quality simulations of ozone and secondary particle concentrations.
Matthew J. Alvarado, Chantelle R. Lonsdale, Helen L. Macintyre, Huisheng Bian, Mian Chin, David A. Ridley, Colette L. Heald, Kenneth L. Thornhill, Bruce E. Anderson, Michael J. Cubison, Jose L. Jimenez, Yutaka Kondo, Lokesh K. Sahu, Jack E. Dibb, and Chien Wang
Atmos. Chem. Phys., 16, 9435–9455, https://doi.org/10.5194/acp-16-9435-2016, https://doi.org/10.5194/acp-16-9435-2016, 2016
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Understanding the scattering and absorption of light by aerosols is necessary for understanding air quality and climate change. We used data from the 2008 ARCTAS campaign to evaluate aerosol optical property models using a closure methodology that separates errors in these models from other errors in aerosol emissions, chemistry, or transport. We find that the models on average perform reasonably well, and make suggestions for how remaining biases could be reduced.
Albert Rivas-Ubach, Yina Liu, Jordi Sardans, Malak M. Tfaily, Young-Mo Kim, Eric Bourrianne, Ljiljana Paša-Tolić, Josep Peñuelas, and Alex Guenther
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2016-209, https://doi.org/10.5194/amt-2016-209, 2016
Revised manuscript not accepted
Kathryn M. Emmerson, Ian E. Galbally, Alex B. Guenther, Clare Paton-Walsh, Elise-Andree Guerette, Martin E. Cope, Melita D. Keywood, Sarah J. Lawson, Suzie B. Molloy, Erin Dunne, Marcus Thatcher, Thomas Karl, and Simin D. Maleknia
Atmos. Chem. Phys., 16, 6997–7011, https://doi.org/10.5194/acp-16-6997-2016, https://doi.org/10.5194/acp-16-6997-2016, 2016
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We have tested how a model using a global inventory of plant-based emissions compares with four sets of measurements made in southeast Australia. This region is known for its eucalypt species, which dominate the summertime global inventory. The Australian part of the inventory has been produced using measurements made on eucalypt saplings. The model could not match the measurements, and the inventory needs to be improved by taking measurements of a wider range of Australian plant types and ages.
Chun Zhao, Maoyi Huang, Jerome D. Fast, Larry K. Berg, Yun Qian, Alex Guenther, Dasa Gu, Manish Shrivastava, Ying Liu, Stacy Walters, Gabriele Pfister, Jiming Jin, John E. Shilling, and Carsten Warneke
Geosci. Model Dev., 9, 1959–1976, https://doi.org/10.5194/gmd-9-1959-2016, https://doi.org/10.5194/gmd-9-1959-2016, 2016
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In this study, the latest version of MEGAN is coupled within CLM4 in WRF-Chem. In this implementation, MEGAN shares a consistent vegetation map with CLM4. This improved modeling framework is used to investigate the impact of two land surface schemes on BVOCs and examine the sensitivity of BVOCs to vegetation distributions in California. This study indicates that more effort is needed to obtain the most appropriate and accurate land cover data sets for climate and air quality models.
Eliane G. Alves, Kolby Jardine, Julio Tota, Angela Jardine, Ana Maria Yãnez-Serrano, Thomas Karl, Julia Tavares, Bruce Nelson, Dasa Gu, Trissevgeni Stavrakou, Scot Martin, Paulo Artaxo, Antonio Manzi, and Alex Guenther
Atmos. Chem. Phys., 16, 3903–3925, https://doi.org/10.5194/acp-16-3903-2016, https://doi.org/10.5194/acp-16-3903-2016, 2016
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For a long time, it was thought that tropical rainforests are evergreen forests and the processes involved in these ecosystems do not change all year long. However, some satellite retrievals have suggested that ecophysiological processes may present seasonal variations mainly due to variation in light and leaf phenology in Amazonia. These in situ measurements are the first showing of a seasonal trend of volatile organic compound emissions, correlating with light and leaf phenology in Amazonia.
Bonne Ford and Colette L. Heald
Atmos. Chem. Phys., 16, 3499–3523, https://doi.org/10.5194/acp-16-3499-2016, https://doi.org/10.5194/acp-16-3499-2016, 2016
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As motivation for air quality research, many studies cite the fact that exposure to particulate matter is associated with premature mortality. Recently, more studies have also tried to quantify this burden; however, there are many data sets that can be used and many different methodological choices to be made. In this paper, we seek to explain the different sources of uncertainty in health impact assessments through the example of using model and satellite-based PM2.5 concentrations.
Jeffrey A. Geddes, Colette L. Heald, Sam J. Silva, and Randall V. Martin
Atmos. Chem. Phys., 16, 2323–2340, https://doi.org/10.5194/acp-16-2323-2016, https://doi.org/10.5194/acp-16-2323-2016, 2016
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Land use and land cover changes driven by anthropogenic activities or natural causes (e.g., forestry management, agriculture, wildfires) can impact climate and air quality in many complex ways. Using a state-of-the-art chemistry model, we investigate how tree mortality in the US due to insect infestation and disease outbreak may impact atmospheric composition. We find that the surface concentrations of ozone and aerosol can be altered due to changing background emissions and loss processes.
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
T. Stavrakou, J.-F. Müller, M. Bauwens, I. De Smedt, M. Van Roozendael, M. De Mazière, C. Vigouroux, F. Hendrick, M. George, C. Clerbaux, P.-F. Coheur, and A. Guenther
Atmos. Chem. Phys., 15, 11861–11884, https://doi.org/10.5194/acp-15-11861-2015, https://doi.org/10.5194/acp-15-11861-2015, 2015
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Formaldehyde columns from two space sensors, GOME-2 and OMI, constrain by inverse modeling the global emissions of HCHO precursors in 2010. The resulting biogenic and pyrogenic fluxes from both optimizations show a very good degree of consistency. The isoprene fluxes are reduced globally by ca. 10%, and emissions from fires decrease by ca. 35%, compared to the prior. Anthropogenic emissions are weakly constrained except over China. Sensitivity inversions show robustness of the inferred fluxes.
F. Xiong, K. M. McAvey, K. A. Pratt, C. J. Groff, M. A. Hostetler, M. A. Lipton, T. K. Starn, J. V. Seeley, S. B. Bertman, A. P. Teng, J. D. Crounse, T. B. Nguyen, P. O. Wennberg, P. K. Misztal, A. H. Goldstein, A. B. Guenther, A. R. Koss, K. F. Olson, J. A. de Gouw, K. Baumann, E. S. Edgerton, P. A. Feiner, L. Zhang, D. O. Miller, W. H. Brune, and P. B. Shepson
Atmos. Chem. Phys., 15, 11257–11272, https://doi.org/10.5194/acp-15-11257-2015, https://doi.org/10.5194/acp-15-11257-2015, 2015
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Hydroxynitrates from isoprene oxidation were quantified both in the laboratory and through field studies. The yield of hydroxynitrates 9(+4/-3)% derived from chamber experiments was applied in a zero-dimensional model to simulate the production and loss of isoprene hydroxynitrates in an ambient environment during the 2013 Southern Oxidant and Aerosol Study (SOAS). NOx was determined to be the limiting factor for the formation of isoprene hydroxynitrates during SOAS.
W. C. Porter, C. L. Heald, D. Cooley, and B. Russell
Atmos. Chem. Phys., 15, 10349–10366, https://doi.org/10.5194/acp-15-10349-2015, https://doi.org/10.5194/acp-15-10349-2015, 2015
L. Zhou, R. Gierens, A. Sogachev, D. Mogensen, J. Ortega, J. N. Smith, P. C. Harley, A. J. Prenni, E. J. T. Levin, A. Turnipseed, A. Rusanen, S. Smolander, A. B. Guenther, M. Kulmala, T. Karl, and M. Boy
Atmos. Chem. Phys., 15, 8643–8656, https://doi.org/10.5194/acp-15-8643-2015, https://doi.org/10.5194/acp-15-8643-2015, 2015
G. Wohlfahrt, C. Amelynck, C. Ammann, A. Arneth, I. Bamberger, A. H. Goldstein, L. Gu, A. Guenther, A. Hansel, B. Heinesch, T. Holst, L. Hörtnagl, T. Karl, Q. Laffineur, A. Neftel, K. McKinney, J. W. Munger, S. G. Pallardy, G. W. Schade, R. Seco, and N. Schoon
Atmos. Chem. Phys., 15, 7413–7427, https://doi.org/10.5194/acp-15-7413-2015, https://doi.org/10.5194/acp-15-7413-2015, 2015
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Methanol is the second most abundant volatile organic compound in the troposphere and plays a significant role in atmospheric chemistry. While there is consensus about the dominant role of plants as the major source and the reaction with OH as the major sink, global methanol budgets diverge considerably in terms of source/sink estimates. Here we present micrometeorological methanol flux data from eight sites in order to provide a first cross-site synthesis of the terrestrial methanol exchange.
S. Kim, S.-Y. Kim, M. Lee, H. Shim, G. M. Wolfe, A. B. Guenther, A. He, Y. Hong, and J. Han
Atmos. Chem. Phys., 15, 4357–4371, https://doi.org/10.5194/acp-15-4357-2015, https://doi.org/10.5194/acp-15-4357-2015, 2015
M. Val Martin, C. L. Heald, J.-F. Lamarque, S. Tilmes, L. K. Emmons, and B. A. Schichtel
Atmos. Chem. Phys., 15, 2805–2823, https://doi.org/10.5194/acp-15-2805-2015, https://doi.org/10.5194/acp-15-2805-2015, 2015
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We present for the first time the relative effect of climate, emissions, and land use change on ozone and PM25 over the United States, focusing on the national parks. Air quality in 2050 will likely be dominated by emission patterns, but climate and land use changes alone can lead to a substantial increase in air pollution over most of the US, with important implications for O3 air quality, visibility and ecosystem health degradation in the national parks.
C. S. Brauer, T. A. Blake, A. B. Guenther, S. W. Sharpe, R. L. Sams, and T. J. Johnson
Atmos. Meas. Tech., 7, 3839–3847, https://doi.org/10.5194/amt-7-3839-2014, https://doi.org/10.5194/amt-7-3839-2014, 2014
Y. You, V. P. Kanawade, J. A. de Gouw, A. B. Guenther, S. Madronich, M. R. Sierra-Hernández, M. Lawler, J. N. Smith, S. Takahama, G. Ruggeri, A. Koss, K. Olson, K. Baumann, R. J. Weber, A. Nenes, H. Guo, E. S. Edgerton, L. Porcelli, W. H. Brune, A. H. Goldstein, and S.-H. Lee
Atmos. Chem. Phys., 14, 12181–12194, https://doi.org/10.5194/acp-14-12181-2014, https://doi.org/10.5194/acp-14-12181-2014, 2014
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Amiens play important roles in atmospheric secondary aerosol formation and human health, but the fast response measurements of amines are lacking. Here we show measurements in a southeastern US forest and a moderately polluted midwestern site. Our results show that gas to particle conversion is an important process that controls ambient amine concentrations and that biomass burning is an important source of amines.
X. Wang, C. L. Heald, D. A. Ridley, J. P. Schwarz, J. R. Spackman, A. E. Perring, H. Coe, D. Liu, and A. D. Clarke
Atmos. Chem. Phys., 14, 10989–11010, https://doi.org/10.5194/acp-14-10989-2014, https://doi.org/10.5194/acp-14-10989-2014, 2014
P. K. Misztal, T. Karl, R. Weber, H. H. Jonsson, A. B. Guenther, and A. H. Goldstein
Atmos. Chem. Phys., 14, 10631–10647, https://doi.org/10.5194/acp-14-10631-2014, https://doi.org/10.5194/acp-14-10631-2014, 2014
S. Smolander, Q. He, D. Mogensen, L. Zhou, J. Bäck, T. Ruuskanen, S. Noe, A. Guenther, H. Aaltonen, M. Kulmala, and M. Boy
Biogeosciences, 11, 5425–5443, https://doi.org/10.5194/bg-11-5425-2014, https://doi.org/10.5194/bg-11-5425-2014, 2014
K. Sindelarova, C. Granier, I. Bouarar, A. Guenther, S. Tilmes, T. Stavrakou, J.-F. Müller, U. Kuhn, P. Stefani, and W. Knorr
Atmos. Chem. Phys., 14, 9317–9341, https://doi.org/10.5194/acp-14-9317-2014, https://doi.org/10.5194/acp-14-9317-2014, 2014
D. V. Spracklen and C. L. Heald
Atmos. Chem. Phys., 14, 9051–9059, https://doi.org/10.5194/acp-14-9051-2014, https://doi.org/10.5194/acp-14-9051-2014, 2014
R. J. Park, S. K. Hong, H.-A. Kwon, S. Kim, A. Guenther, J.-H. Woo, and C. P. Loughner
Atmos. Chem. Phys., 14, 7929–7940, https://doi.org/10.5194/acp-14-7929-2014, https://doi.org/10.5194/acp-14-7929-2014, 2014
E. A. Marais, D. J. Jacob, A. Guenther, K. Chance, T. P. Kurosu, J. G. Murphy, C. E. Reeves, and H. O. T. Pye
Atmos. Chem. Phys., 14, 7693–7703, https://doi.org/10.5194/acp-14-7693-2014, https://doi.org/10.5194/acp-14-7693-2014, 2014
J. P. Greenberg, J. Peñuelas, A. Guenther, R. Seco, A. Turnipseed, X. Jiang, I. Filella, M. Estiarte, J. Sardans, R. Ogaya, J. Llusia, and F. Rapparini
Atmos. Meas. Tech., 7, 2263–2271, https://doi.org/10.5194/amt-7-2263-2014, https://doi.org/10.5194/amt-7-2263-2014, 2014
K. Jaars, J. P. Beukes, P. G. van Zyl, A. D. Venter, M. Josipovic, J. J. Pienaar, V. Vakkari, H. Aaltonen, H. Laakso, M. Kulmala, P. Tiitta, A. Guenther, H. Hellén, L. Laakso, and H. Hakola
Atmos. Chem. Phys., 14, 7075–7089, https://doi.org/10.5194/acp-14-7075-2014, https://doi.org/10.5194/acp-14-7075-2014, 2014
J. Ortega, A. Turnipseed, A. B. Guenther, T. G. Karl, D. A. Day, D. Gochis, J. A. Huffman, A. J. Prenni, E. J. T. Levin, S. M. Kreidenweis, P. J. DeMott, Y. Tobo, E. G. Patton, A. Hodzic, Y. Y. Cui, P. C. Harley, R. S. Hornbrook, E. C. Apel, R. K. Monson, A. S. D. Eller, J. P. Greenberg, M. C. Barth, P. Campuzano-Jost, B. B. Palm, J. L. Jimenez, A. C. Aiken, M. K. Dubey, C. Geron, J. Offenberg, M. G. Ryan, P. J. Fornwalt, S. C. Pryor, F. N. Keutsch, J. P. DiGangi, A. W. H. Chan, A. H. Goldstein, G. M. Wolfe, S. Kim, L. Kaser, R. Schnitzhofer, A. Hansel, C. A. Cantrell, R. L. Mauldin, and J. N. Smith
Atmos. Chem. Phys., 14, 6345–6367, https://doi.org/10.5194/acp-14-6345-2014, https://doi.org/10.5194/acp-14-6345-2014, 2014
D. A. Ridley, C. L. Heald, and J. M. Prospero
Atmos. Chem. Phys., 14, 5735–5747, https://doi.org/10.5194/acp-14-5735-2014, https://doi.org/10.5194/acp-14-5735-2014, 2014
C. L. Heald, D. A. Ridley, J. H. Kroll, S. R. H. Barrett, K. E. Cady-Pereira, M. J. Alvarado, and C. D. Holmes
Atmos. Chem. Phys., 14, 5513–5527, https://doi.org/10.5194/acp-14-5513-2014, https://doi.org/10.5194/acp-14-5513-2014, 2014
M. Liu, K. Rajagopalan, S. H. Chung, X. Jiang, J. Harrison, T. Nergui, A. Guenther, C. Miller, J. Reyes, C. Tague, J. Choate, E. P. Salathé, C. O. Stöckle, and J. C. Adam
Biogeosciences, 11, 2601–2622, https://doi.org/10.5194/bg-11-2601-2014, https://doi.org/10.5194/bg-11-2601-2014, 2014
M. Van Damme, L. Clarisse, C. L. Heald, D. Hurtmans, Y. Ngadi, C. Clerbaux, A. J. Dolman, J. W. Erisman, and P. F. Coheur
Atmos. Chem. Phys., 14, 2905–2922, https://doi.org/10.5194/acp-14-2905-2014, https://doi.org/10.5194/acp-14-2905-2014, 2014
R. Zhang, T. Duhl, M. T. Salam, J. M. House, R. C. Flagan, E. L. Avol, F. D. Gilliland, A. Guenther, S. H. Chung, B. K. Lamb, and T. M. VanReken
Biogeosciences, 11, 1461–1478, https://doi.org/10.5194/bg-11-1461-2014, https://doi.org/10.5194/bg-11-1461-2014, 2014
L. Kaser, T. Karl, A. Guenther, M. Graus, R. Schnitzhofer, A. Turnipseed, L. Fischer, P. Harley, M. Madronich, D. Gochis, F. N. Keutsch, and A. Hansel
Atmos. Chem. Phys., 13, 11935–11947, https://doi.org/10.5194/acp-13-11935-2013, https://doi.org/10.5194/acp-13-11935-2013, 2013
S. Situ, A. Guenther, X. Wang, X. Jiang, A. Turnipseed, Z. Wu, J. Bai, and X. Wang
Atmos. Chem. Phys., 13, 11803–11817, https://doi.org/10.5194/acp-13-11803-2013, https://doi.org/10.5194/acp-13-11803-2013, 2013
N. Unger, K. Harper, Y. Zheng, N. Y. Kiang, I. Aleinov, A. Arneth, G. Schurgers, C. Amelynck, A. Goldstein, A. Guenther, B. Heinesch, C. N. Hewitt, T. Karl, Q. Laffineur, B. Langford, K. A. McKinney, P. Misztal, M. Potosnak, J. Rinne, S. Pressley, N. Schoon, and D. Serça
Atmos. Chem. Phys., 13, 10243–10269, https://doi.org/10.5194/acp-13-10243-2013, https://doi.org/10.5194/acp-13-10243-2013, 2013
J. E. Mak, L. Su, A. Guenther, and T. Karl
Atmos. Meas. Tech., 6, 2703–2712, https://doi.org/10.5194/amt-6-2703-2013, https://doi.org/10.5194/amt-6-2703-2013, 2013
B. Ford and C. L. Heald
Atmos. Chem. Phys., 13, 9269–9283, https://doi.org/10.5194/acp-13-9269-2013, https://doi.org/10.5194/acp-13-9269-2013, 2013
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
X. Tie, F. Geng, A. Guenther, J. Cao, J. Greenberg, R. Zhang, E. Apel, G. Li, A. Weinheimer, J. Chen, and C. Cai
Atmos. Chem. Phys., 13, 5655–5669, https://doi.org/10.5194/acp-13-5655-2013, https://doi.org/10.5194/acp-13-5655-2013, 2013
T. R. Duhl, R. Zhang, A. Guenther, S. H. Chung, M. T. Salam, J. M. House, R. C. Flagan, E. L. Avol, F. D. Gilliland, B. K. Lamb, T. M. VanReken, Y. Zhang, and E. Salathé
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-6-2325-2013, https://doi.org/10.5194/gmdd-6-2325-2013, 2013
Revised manuscript not accepted
A. R. Berg, C. L. Heald, K. E. Huff Hartz, A. G. Hallar, A. J. H. Meddens, J. A. Hicke, J.-F. Lamarque, and S. Tilmes
Atmos. Chem. Phys., 13, 3149–3161, https://doi.org/10.5194/acp-13-3149-2013, https://doi.org/10.5194/acp-13-3149-2013, 2013
L. Kaser, T. Karl, R. Schnitzhofer, M. Graus, I. S. Herdlinger-Blatt, J. P. DiGangi, B. Sive, A. Turnipseed, R. S. Hornbrook, W. Zheng, F. M. Flocke, A. Guenther, F. N. Keutsch, E. Apel, and A. Hansel
Atmos. Chem. Phys., 13, 2893–2906, https://doi.org/10.5194/acp-13-2893-2013, https://doi.org/10.5194/acp-13-2893-2013, 2013
T. R. Duhl, D. Gochis, A. Guenther, S. Ferrenberg, and E. Pendall
Biogeosciences, 10, 483–499, https://doi.org/10.5194/bg-10-483-2013, https://doi.org/10.5194/bg-10-483-2013, 2013
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cloudbandPy 1.0: an automated algorithm for the detection of tropical–extratropical cloud bands
PyRTlib: an educational Python-based library for non-scattering atmospheric microwave radiative transfer computations
Deep learning applied to CO2 power plant emissions quantification using simulated satellite images
Sensitivity of the WRF-Chem v4.4 simulations of ozone and formaldehyde and their precursors to multiple bottom-up emission inventories over East Asia during the KORUS-AQ 2016 field campaign
Optimising urban measurement networks for CO2 flux estimation: a high-resolution observing system simulation experiment using GRAMM/GRAL
Assessment of climate biases in OpenIFS version 43r3 across model horizontal resolutions and time steps
High-resolution multi-scaling of outdoor human thermal comfort and its intra-urban variability based on machine learning
Effects of vertical grid spacing on the climate simulated in the ICON-Sapphire global storm-resolving model
Development of the tangent linear and adjoint models of the global online chemical transport model MPAS-CO2 v7.3
Impacts of updated reaction kinetics on the global GEOS-Chem simulation of atmospheric chemistry
Spatial spin-up of precipitation in limited-area convection-permitting simulations over North America using the CRCM6/GEM5.0 model
Sensitivity of atmospheric rivers to aerosol treatment in regional climate simulations: insights from the AIRA identification algorithm
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Implementation of the ISORROPIA-lite aerosol thermodynamics model into the EMAC chemistry climate model (based on MESSy v2.55): implications for aerosol composition and acidity
Evaluation of surface shortwave downward radiation forecasts by the numerical weather prediction model AROME
GEO4PALM v1.1: an open-source geospatial data processing toolkit for the PALM model system
Modeling collision–coalescence in particle microphysics: numerical convergence of mean and variance of precipitation in cloud simulations using the University of Warsaw Lagrangian Cloud Model (UWLCM) 2.1
Modeling below-cloud scavenging of size-resolved particles in GEM-MACHv3.1
Impacts of a double-moment bulk cloud microphysics scheme (NDW6-G23) on aerosol fields in NICAM.19 with a global 14 km grid resolution
Sensitivity of air quality model responses to emission changes: comparison of results based on four EU inventories through FAIRMODE benchmarking methodology
A simple and realistic aerosol emission approach for use in the Thompson–Eidhammer microphysics scheme in the NOAA UFS Weather Model (version GSL global-24Feb2022)
On the formation of biogenic secondary organic aerosol in chemical transport models: an evaluation of the WRF-CHIMERE (v2020r2) model with a focus over the Finnish boreal forest
The first application of a numerically exact, higher-order sensitivity analysis approach for atmospheric modelling: implementation of the hyperdual-step method in the Community Multiscale Air Quality Model (CMAQ) version 5.3.2
GAN-argcPredNet v2.0: a radar echo extrapolation model based on spatiotemporal process enhancement
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A model for rapid PM2.5 exposure estimates in wildfire conditions using routinely available data: rapidfire v0.1.3
BoundaryLayerDynamics.jl v1.0: a modern codebase for atmospheric boundary-layer simulations
The wave-age-dependent stress parameterisation (WASP) for momentum and heat turbulent fluxes at sea in SURFEX v8.1
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An improved version of the piecewise parabolic method advection scheme: description and performance assessment in a bidimensional test case with stiff chemistry in toyCTM v1.0.1
INCHEM-Py v1.2: a community box model for indoor air chemistry
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Comprehensive evaluation of typical planetary boundary layer (PBL) parameterization schemes in China – Part 2: Influence of uncertainty factors
A mountain-induced moist baroclinic wave test case for the dynamical cores of atmospheric general circulation models
The effect of emission source chemical profiles on simulated PM2.5 components: sensitivity analysis with the Community Multiscale Air Quality (CMAQ) modeling system version 5.0.2
Challenges of constructing and selecting the "perfect" initial and boundary conditions for the LES model PALM
Comprehensive evaluation of typical planetary boundary layer (PBL) parameterization schemes in China – Part 1: Understanding expressiveness of schemes for different regions from the mechanism perspective
Evaluating 3 decades of precipitation in the Upper Colorado River basin from a high-resolution regional climate model
Efficient and Stable Coupling of the SuperdropNet Deep Learning-based Cloud Microphysics (v0.1.0) to the ICON Climate and Weather Model (v2.6.5)
How non-equilibrium aerosol chemistry impacts particle acidity: the GMXe AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel of MESSy
Implementation of a satellite-based tool for the quantification of CH4 emissions over Europe (AUMIA v1.0) – Part 1: forward modelling evaluation against near-surface and satellite data
Validation and Analysis of the Polair3D v1.11 Chemical Transport Model Over Quebec
The capabilities of the adjoint of GEOS-Chem model to support HEMCO emission inventories and MERRA-2 meteorological data
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 2347–2358, https://doi.org/10.5194/gmd-17-2347-2024, https://doi.org/10.5194/gmd-17-2347-2024, 2024
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In the last decades, weather forecasting up to 15 d into the future has been dominated by physics-based numerical models. Recently, deep learning models have challenged this paradigm. However, the latter models may struggle when forecasting weather extremes. In this article, we argue for deep learning models specifically designed to handle extreme events, and we propose a foundational framework to develop such models.
Stefan Rahimi, Lei Huang, Jesse Norris, Alex Hall, Naomi Goldenson, Will Krantz, Benjamin Bass, Chad Thackeray, Henry Lin, Di Chen, Eli Dennis, Ethan Collins, Zachary J. Lebo, Emily Slinskey, Sara Graves, Surabhi Biyani, Bowen Wang, Stephen Cropper, and the UCLA Center for Climate Science Team
Geosci. Model Dev., 17, 2265–2286, https://doi.org/10.5194/gmd-17-2265-2024, https://doi.org/10.5194/gmd-17-2265-2024, 2024
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Here, we project future climate across the western United States through the end of the 21st century using a regional climate model, embedded within 16 latest-generation global climate models, to provide the community with a high-resolution physically based ensemble of climate data for use at local scales. Strengths and weaknesses of the data are frankly discussed as we overview the downscaled dataset.
Romain Pilon and Daniela I. V. Domeisen
Geosci. Model Dev., 17, 2247–2264, https://doi.org/10.5194/gmd-17-2247-2024, https://doi.org/10.5194/gmd-17-2247-2024, 2024
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This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano
Geosci. Model Dev., 17, 2053–2076, https://doi.org/10.5194/gmd-17-2053-2024, https://doi.org/10.5194/gmd-17-2053-2024, 2024
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PyRTlib is an attractive educational tool because it provides a flexible and user-friendly way to broadly simulate how electromagnetic radiation travels through the atmosphere as it interacts with atmospheric constituents (such as gases, aerosols, and hydrometeors). PyRTlib is a so-called radiative transfer model; these are commonly used to simulate and understand remote sensing observations from ground-based, airborne, or satellite instruments.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Grégoire Broquet, Gerrit Kuhlmann, and Marc Bocquet
Geosci. Model Dev., 17, 1995–2014, https://doi.org/10.5194/gmd-17-1995-2024, https://doi.org/10.5194/gmd-17-1995-2024, 2024
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Our research presents an innovative approach to estimating power plant CO2 emissions from satellite images of the corresponding plumes such as those from the forthcoming CO2M satellite constellation. The exploitation of these images is challenging due to noise and meteorological uncertainties. To overcome these obstacles, we use a deep learning neural network trained on simulated CO2 images. Our method outperforms alternatives, providing a positive perspective for the analysis of CO2M images.
Kyoung-Min Kim, Si-Wan Kim, Seunghwan Seo, Donald R. Blake, Seogju Cho, James H. Crawford, Louisa K. Emmons, Alan Fried, Jay R. Herman, Jinkyu Hong, Jinsang Jung, Gabriele G. Pfister, Andrew J. Weinheimer, Jung-Hun Woo, and Qiang Zhang
Geosci. Model Dev., 17, 1931–1955, https://doi.org/10.5194/gmd-17-1931-2024, https://doi.org/10.5194/gmd-17-1931-2024, 2024
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Three emission inventories were evaluated for East Asia using data acquired during a field campaign in 2016. The inventories successfully reproduced the daily variations of ozone and nitrogen dioxide. However, the spatial distributions of model ozone did not fully agree with the observations. Additionally, all simulations underestimated carbon monoxide and volatile organic compound (VOC) levels. Increasing VOC emissions over South Korea resulted in improved ozone simulations.
Sanam Noreen Vardag and Robert Maiwald
Geosci. Model Dev., 17, 1885–1902, https://doi.org/10.5194/gmd-17-1885-2024, https://doi.org/10.5194/gmd-17-1885-2024, 2024
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We use the atmospheric transport model GRAMM/GRAL in a Bayesian inversion to estimate urban CO2 emissions on a neighbourhood scale. We analyse the effect of varying number, precision and location of CO2 sensors for CO2 flux estimation. We further test the inclusion of co-emitted species and correlation in the inversion. The study showcases the general usefulness of GRAMM/GRAL in measurement network design.
Abhishek Savita, Joakim Kjellsson, Robin Pilch Kedzierski, Mojib Latif, Tabea Rahm, Sebastian Wahl, and Wonsun Park
Geosci. Model Dev., 17, 1813–1829, https://doi.org/10.5194/gmd-17-1813-2024, https://doi.org/10.5194/gmd-17-1813-2024, 2024
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The OpenIFS model is used to examine the impact of horizontal resolutions (HR) and model time steps. We find that the surface wind biases over the oceans, in particular the Southern Ocean, are sensitive to the model time step and HR, with the HR having the smallest biases. When using a coarse-resolution model with a shorter time step, a similar improvement is also found. Climate biases can be reduced in the OpenIFS model at a cheaper cost by reducing the time step rather than increasing the HR.
Ferdinand Briegel, Jonas Wehrle, Dirk Schindler, and Andreas Christen
Geosci. Model Dev., 17, 1667–1688, https://doi.org/10.5194/gmd-17-1667-2024, https://doi.org/10.5194/gmd-17-1667-2024, 2024
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We present a new approach to model heat stress in cities using artificial intelligence (AI). We show that the AI model is fast in terms of prediction but accurate when evaluated with measurements. The fast-predictive AI model enables several new potential applications, including heat stress prediction and warning; downscaling of potential future climates; evaluation of adaptation effectiveness; and, more fundamentally, development of guidelines to support urban planning and policymaking.
Hauke Schmidt, Sebastian Rast, Jiawei Bao, Amrit Cassim, Shih-Wei Fang, Diego Jimenez-de la Cuesta, Paul Keil, Lukas Kluft, Clarissa Kroll, Theresa Lang, Ulrike Niemeier, Andrea Schneidereit, Andrew I. L. Williams, and Bjorn Stevens
Geosci. Model Dev., 17, 1563–1584, https://doi.org/10.5194/gmd-17-1563-2024, https://doi.org/10.5194/gmd-17-1563-2024, 2024
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A recent development in numerical simulations of the global atmosphere is the increase in horizontal resolution to grid spacings of a few kilometers. However, the vertical grid spacing of these models has not been reduced at the same rate as the horizontal grid spacing. Here, we assess the effects of much finer vertical grid spacings, in particular the impacts on cloud quantities and the atmospheric energy balance.
Tao Zheng, Sha Feng, Jeffrey Steward, Xiaoxu Tian, David Baker, and Martin Baxter
Geosci. Model Dev., 17, 1543–1562, https://doi.org/10.5194/gmd-17-1543-2024, https://doi.org/10.5194/gmd-17-1543-2024, 2024
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The tangent linear and adjoint models have been successfully implemented in the MPAS-CO2 system, which has undergone rigorous accuracy testing. This development lays the groundwork for a global carbon flux data assimilation system, which offers the flexibility of high-resolution focus on specific areas, while maintaining a coarser resolution elsewhere. This approach significantly reduces computational costs and is thus perfectly suited for future CO2 geostationery and imager satellites.
Kelvin H. Bates, Mathew J. Evans, Barron H. Henderson, and Daniel J. Jacob
Geosci. Model Dev., 17, 1511–1524, https://doi.org/10.5194/gmd-17-1511-2024, https://doi.org/10.5194/gmd-17-1511-2024, 2024
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Accurate representation of rates and products of chemical reactions in atmospheric models is crucial for simulating concentrations of pollutants and climate forcers. We update the widely used GEOS-Chem atmospheric chemistry model with reaction parameters from recent compilations of experimental data and demonstrate the implications for key atmospheric chemical species. The updates decrease tropospheric CO mixing ratios and increase stratospheric nitrogen oxide mixing ratios, among other changes.
François Roberge, Alejandro Di Luca, René Laprise, Philippe Lucas-Picher, and Julie Thériault
Geosci. Model Dev., 17, 1497–1510, https://doi.org/10.5194/gmd-17-1497-2024, https://doi.org/10.5194/gmd-17-1497-2024, 2024
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Our study addresses a challenge in dynamical downscaling using regional climate models, focusing on the lack of small-scale features near the boundaries. We introduce a method to identify this “spatial spin-up” in precipitation simulations. Results show spin-up distances up to 300 km, varying by season and driving variable. Double nesting with comprehensive variables (e.g. microphysical variables) offers advantages. Findings will help optimize simulations for better climate projections.
Eloisa Raluy-López, Juan Pedro Montávez, and Pedro Jiménez-Guerrero
Geosci. Model Dev., 17, 1469–1495, https://doi.org/10.5194/gmd-17-1469-2024, https://doi.org/10.5194/gmd-17-1469-2024, 2024
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Atmospheric rivers (ARs) represent a significant source of water but are also related to extreme precipitation events. Here, we present a new regional-scale AR identification algorithm and apply it to three simulations that include aerosol interactions at different levels. The results show that aerosols modify the intensity and trajectory of ARs and redistribute the AR-related precipitation. Thus, the correct inclusion of aerosol effects is important in the simulation of AR behavior.
Sofía Gómez Maqueo Anaya, Dietrich Althausen, Matthias Faust, Holger Baars, Bernd Heinold, Julian Hofer, Ina Tegen, Albert Ansmann, Ronny Engelmann, Annett Skupin, Birgit Heese, and Kerstin Schepanski
Geosci. Model Dev., 17, 1271–1295, https://doi.org/10.5194/gmd-17-1271-2024, https://doi.org/10.5194/gmd-17-1271-2024, 2024
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Mineral dust aerosol particles vary greatly in their composition depending on source region, which leads to different physicochemical properties. Most atmosphere–aerosol models consider mineral dust aerosols to be compositionally homogeneous, which ultimately increases model uncertainty. Here, we present an approach to explicitly consider the heterogeneity of the mineralogical composition for simulations of the Saharan atmospheric dust cycle with regard to dust transport towards the Atlantic.
Alexandros Milousis, Alexandra P. Tsimpidi, Holger Tost, Spyros N. Pandis, Athanasios Nenes, Astrid Kiendler-Scharr, and Vlassis A. Karydis
Geosci. Model Dev., 17, 1111–1131, https://doi.org/10.5194/gmd-17-1111-2024, https://doi.org/10.5194/gmd-17-1111-2024, 2024
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This study aims to evaluate the newly developed ISORROPIA-lite aerosol thermodynamic module within the EMAC model and explore discrepancies in global atmospheric simulations of aerosol composition and acidity by utilizing different aerosol phase states. Even though local differences were found in regions where the RH ranged from 20 % to 60 %, on a global scale the results are similar. Therefore, ISORROPIA-lite can be a reliable and computationally effective alternative to ISORROPIA II in EMAC.
Marie-Adèle Magnaldo, Quentin Libois, Sébastien Riette, and Christine Lac
Geosci. Model Dev., 17, 1091–1109, https://doi.org/10.5194/gmd-17-1091-2024, https://doi.org/10.5194/gmd-17-1091-2024, 2024
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With the worldwide development of the solar energy sector, the need for reliable solar radiation forecasts has significantly increased. However, meteorological models that predict, among others things, solar radiation have errors. Therefore, we wanted to know in which situtaions these errors are most significant. We found that errors mostly occur in cloudy situations, and different errors were highlighted depending on the cloud altitude. Several potential sources of errors were identified.
Dongqi Lin, Jiawei Zhang, Basit Khan, Marwan Katurji, and Laura E. Revell
Geosci. Model Dev., 17, 815–845, https://doi.org/10.5194/gmd-17-815-2024, https://doi.org/10.5194/gmd-17-815-2024, 2024
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GEO4PALM is an open-source tool to generate static input for the Parallelized Large-Eddy Simulation (PALM) model system. Geospatial static input is essential for realistic PALM simulations. However, existing tools fail to generate PALM's geospatial static input for most regions. GEO4PALM is compatible with diverse geospatial data sources and provides access to free data sets. In addition, this paper presents two application examples, which show successful PALM simulations using GEO4PALM.
Piotr Zmijewski, Piotr Dziekan, and Hanna Pawlowska
Geosci. Model Dev., 17, 759–780, https://doi.org/10.5194/gmd-17-759-2024, https://doi.org/10.5194/gmd-17-759-2024, 2024
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In computer simulations of clouds it is necessary to model the myriad of droplets that constitute a cloud. A popular method for this is to use so-called super-droplets (SDs), each representing many real droplets. It has remained a challenge to model collisions of SDs. We study how precipitation in a cumulus cloud depends on the number of SDs. Surprisingly, we do not find convergence in mean precipitation even for numbers of SDs much larger than typically used in simulations.
Roya Ghahreman, Wanmin Gong, Paul A. Makar, Alexandru Lupu, Amanda Cole, Kulbir Banwait, Colin Lee, and Ayodeji Akingunola
Geosci. Model Dev., 17, 685–707, https://doi.org/10.5194/gmd-17-685-2024, https://doi.org/10.5194/gmd-17-685-2024, 2024
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The article explores the impact of different representations of below-cloud scavenging on model biases. A new scavenging scheme and precipitation-phase partitioning improve the model's performance, with better SO42- scavenging and wet deposition of NO3- and NH4+.
Daisuke Goto, Tatsuya Seiki, Kentaroh Suzuki, Hisashi Yashiro, and Toshihiko Takemura
Geosci. Model Dev., 17, 651–684, https://doi.org/10.5194/gmd-17-651-2024, https://doi.org/10.5194/gmd-17-651-2024, 2024
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Global climate models with coarse grid sizes include uncertainties about the processes in aerosol–cloud–precipitation interactions. To reduce these uncertainties, here we performed numerical simulations using a new version of our global aerosol transport model with a finer grid size over a longer period than in our previous study. As a result, we found that the cloud microphysics module influences the aerosol distributions through both aerosol wet deposition and aerosol–cloud interactions.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, Enrico Pisoni, and Bertrand Bessagnet
Geosci. Model Dev., 17, 587–606, https://doi.org/10.5194/gmd-17-587-2024, https://doi.org/10.5194/gmd-17-587-2024, 2024
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In our study the robustness of the model responses to emission reductions in the EU is assessed when the emission data are changed. Our findings are particularly important to better understand the uncertainties associated to the emission inventories and how these uncertainties impact the level of accuracy of the resulting air quality modelling, which is a key for designing air quality plans. Also crucial is the choice of indicator to avoid misleading interpretations of the results.
Haiqin Li, Georg A. Grell, Ravan Ahmadov, Li Zhang, Shan Sun, Jordan Schnell, and Ning Wang
Geosci. Model Dev., 17, 607–619, https://doi.org/10.5194/gmd-17-607-2024, https://doi.org/10.5194/gmd-17-607-2024, 2024
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We developed a simple and realistic method to provide aerosol emissions for aerosol-aware microphysics in a numerical weather forecast model. The cloud-radiation differences between the experimental (EXP) and control (CTL) experiments responded to the aerosol differences. The strong positive precipitation biases over North America and Europe from the CTL run were significantly reduced in the EXP run. This study shows that a realistic representation of aerosol emissions should be considered.
Giancarlo Ciarelli, Sara Tahvonen, Arineh Cholakian, Manuel Bettineschi, Bruno Vitali, Tuukka Petäjä, and Federico Bianchi
Geosci. Model Dev., 17, 545–565, https://doi.org/10.5194/gmd-17-545-2024, https://doi.org/10.5194/gmd-17-545-2024, 2024
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The terrestrial ecosystem releases large quantities of biogenic gases in the Earth's Atmosphere. These gases can effectively be converted into so-called biogenic aerosol particles and, eventually, affect the Earth's climate. Climate prediction varies greatly depending on how these processes are represented in model simulations. In this study, we present a detailed model evaluation analysis aimed at understanding the main source of uncertainty in predicting the formation of biogenic aerosols.
Jiachen Liu, Eric Chen, and Shannon L. Capps
Geosci. Model Dev., 17, 567–585, https://doi.org/10.5194/gmd-17-567-2024, https://doi.org/10.5194/gmd-17-567-2024, 2024
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Air pollution harms human life and ecosystems, but its sources are complex. Scientists and policy makers use air pollution models to advance knowledge and inform control strategies. We implemented a recently developed numeral system to relate any set of model inputs, like pollutant emissions from a given activity, to all model outputs, like concentrations of pollutants harming human health. This approach will be straightforward to update when scientists discover new processes in the atmosphere.
Kun Zheng, Qiya Tan, Huihua Ruan, Jinbiao Zhang, Cong Luo, Siyu Tang, Yunlei Yi, Yugang Tian, and Jianmei Cheng
Geosci. Model Dev., 17, 399–413, https://doi.org/10.5194/gmd-17-399-2024, https://doi.org/10.5194/gmd-17-399-2024, 2024
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Radar echo extrapolation is the common method in precipitation nowcasting. Deep learning has potential in extrapolation. However, the existing models have low prediction accuracy for heavy rainfall. In this study, the prediction accuracy is improved by suppressing the blurring effect of rain distribution and reducing the negative bias. The results show that our model has better performance, which is useful for urban operation and flood prevention.
Li Pan, Partha S. Bhattacharjee, Li Zhang, Raffaele Montuoro, Barry Baker, Jeff McQueen, Georg A. Grell, Stuart A. McKeen, Shobha Kondragunta, Xiaoyang Zhang, Gregory J. Frost, Fanglin Yang, and Ivanka Stajner
Geosci. Model Dev., 17, 431–447, https://doi.org/10.5194/gmd-17-431-2024, https://doi.org/10.5194/gmd-17-431-2024, 2024
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A GEFS-Aerosols simulation was conducted from 1 September 2019 to 30 September 2020 to evaluate the model performance of GEFS-Aerosols. The purpose of this study was to understand how aerosol chemical and physical processes affect ambient aerosol concentrations by placing aerosol wet deposition, dry deposition, reactions, gravitational deposition, and emissions into the aerosol mass balance equation.
Sean Raffuse, Susan O'Neill, and Rebecca Schmidt
Geosci. Model Dev., 17, 381–397, https://doi.org/10.5194/gmd-17-381-2024, https://doi.org/10.5194/gmd-17-381-2024, 2024
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Large wildfires are increasing throughout the western United States, and wildfire smoke is hazardous to public health. We developed a suite of tools called rapidfire for estimating particle pollution during wildfires using routinely available data sets. rapidfire uses official air monitoring, satellite data, meteorology, smoke modeling, and low-cost sensors. Estimates from rapidfire compare well with ground monitors and are being used in public health studies across California.
Manuel F. Schmid, Marco G. Giometto, Gregory A. Lawrence, and Marc B. Parlange
Geosci. Model Dev., 17, 321–333, https://doi.org/10.5194/gmd-17-321-2024, https://doi.org/10.5194/gmd-17-321-2024, 2024
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Turbulence-resolving flow models have strict performance requirements, as simulations often run for weeks using hundreds of processes. Many flow scenarios also require the flexibility to modify physical and numerical models for problem-specific requirements. With a new code written in Julia we hope to make such adaptations easier without compromising on performance. In this paper we discuss the modeling approach and present validation and performance results.
Marie-Noëlle Bouin, Cindy Lebeaupin Brossier, Sylvie Malardel, Aurore Voldoire, and César Sauvage
Geosci. Model Dev., 17, 117–141, https://doi.org/10.5194/gmd-17-117-2024, https://doi.org/10.5194/gmd-17-117-2024, 2024
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In numerical models, the turbulent exchanges of heat and momentum at the air–sea interface are not represented explicitly but with parameterisations depending on the surface parameters. A new parameterisation of turbulent fluxes (WASP) has been implemented in the surface model SURFEX v8.1 and validated on four case studies. It combines a close fit to observations including cyclonic winds, a dependency on the wave growth rate, and the possibility of being used in atmosphere–wave coupled models.
Lukas Fehr, Chris McLinden, Debora Griffin, Daniel Zawada, Doug Degenstein, and Adam Bourassa
Geosci. Model Dev., 16, 7491–7507, https://doi.org/10.5194/gmd-16-7491-2023, https://doi.org/10.5194/gmd-16-7491-2023, 2023
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This work highlights upgrades to SASKTRAN, a model that simulates sunlight interacting with the atmosphere to help measure trace gases. The upgrades were verified by detailed comparisons between different numerical methods. A case study was performed using SASKTRAN’s multidimensional capabilities, which found that ignoring horizontal variation in the atmosphere (a common practice in the field) can introduce non-negligible errors where there is snow or high pollution.
Sylvain Mailler, Romain Pennel, Laurent Menut, and Arineh Cholakian
Geosci. Model Dev., 16, 7509–7526, https://doi.org/10.5194/gmd-16-7509-2023, https://doi.org/10.5194/gmd-16-7509-2023, 2023
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We show that a new advection scheme named PPM + W (piecewise parabolic method + Walcek) offers geoscientific modellers an alternative, high-performance scheme designed for Cartesian-grid advection, with improved performance over the classical PPM scheme. The computational cost of PPM + W is not higher than that of PPM. With improved accuracy and controlled computational cost, this new scheme may find applications in chemistry-transport models, ocean models or atmospheric circulation models.
David R. Shaw, Toby J. Carter, Helen L. Davies, Ellen Harding-Smith, Elliott C. Crocker, Georgia Beel, Zixu Wang, and Nicola Carslaw
Geosci. Model Dev., 16, 7411–7431, https://doi.org/10.5194/gmd-16-7411-2023, https://doi.org/10.5194/gmd-16-7411-2023, 2023
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Exposure to air pollution is one of the greatest risks to human health, and it is indoors, where we spend upwards of 90 % of our time, that our exposure is greatest. The INdoor CHEMical model in Python (INCHEM-Py) is a new, community-led box model that tracks the evolution and fate of atmospheric chemical pollutants indoors. We have shown the processes simulated by INCHEM-Py, its ability to model experimental data and how it may be used to develop further understanding of indoor air chemistry.
Willem E. van Caspel, David Simpson, Jan Eiof Jonson, Anna M. K. Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah L. Walker, and Mathew R. Heal
Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, https://doi.org/10.5194/gmd-16-7433-2023, 2023
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Radiation coming from the sun is essential to atmospheric chemistry, driving the breakup, or photodissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of photodissociation effects is therefore essential in atmospheric chemistry modeling. One such model is the EMEP MSC-W model, for which a new way of calculating the photodissociation rates is tested and evaluated in this paper.
Jungmin Lee, Walter M. Hannah, and David C. Bader
Geosci. Model Dev., 16, 7275–7287, https://doi.org/10.5194/gmd-16-7275-2023, https://doi.org/10.5194/gmd-16-7275-2023, 2023
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Representing accurate land–atmosphere interaction processes is overlooked in weather and climate models. In this study, we propose three methods to represent land–atmosphere coupling in the Energy Exascale Earth System Model (E3SM) with the Multi-scale Modeling Framework (MMF) approach. In this study, we introduce spatially homogeneous and heterogeneous land–atmosphere interaction processes within the cloud-resolving model domain. Our 5-year simulations reveal only small differences.
Liangke Huang, Shengwei Lan, Ge Zhu, Fade Chen, Junyu Li, and Lilong Liu
Geosci. Model Dev., 16, 7223–7235, https://doi.org/10.5194/gmd-16-7223-2023, https://doi.org/10.5194/gmd-16-7223-2023, 2023
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The existing zenith tropospheric delay (ZTD) models have limitations such as using a single fitting function, neglecting daily cycle variations, and relying on only one resolution grid data point for modeling. This model considers the daily cycle variation and latitude factor of ZTD, using the sliding window algorithm based on ERA5 atmospheric reanalysis data. The ZTD data from 545 radiosonde stations and MERRA-2 atmospheric reanalysis data are used to validate the accuracy of the GGZTD-P model.
Jonathan J. Guerrette, Zhiquan Liu, Chris Snyder, Byoung-Joo Jung, Craig S. Schwartz, Junmei Ban, Steven Vahl, Yali Wu, Ivette Hernández Baños, Yonggang G. Yu, Soyoung Ha, Yannick Trémolet, Thomas Auligné, Clementine Gas, Benjamin Ménétrier, Anna Shlyaeva, Mark Miesch, Stephen Herbener, Emily Liu, Daniel Holdaway, and Benjamin T. Johnson
Geosci. Model Dev., 16, 7123–7142, https://doi.org/10.5194/gmd-16-7123-2023, https://doi.org/10.5194/gmd-16-7123-2023, 2023
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We demonstrate an ensemble of variational data assimilations (EDA) with the Model for Prediction Across Scales and the Joint Effort for Data assimilation Integration (JEDI) software framework. When compared to 20-member ensemble forecasts from operational initial conditions, those from 80-member EDA-generated initial conditions improve flow-dependent error covariances and subsequent 10 d forecasts. These experiments are repeatable for any atmospheric model with a JEDI interface.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Hang, and Feijuan Li
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-201, https://doi.org/10.5194/gmd-2023-201, 2023
Revised manuscript accepted for GMD
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In this study, we have developed a model (RF-PWV) to characterize PWV variation with altitude in the study area. The RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.
Minjie Zheng, Hongyu Liu, Florian Adolphi, Raimund Muscheler, Zhengyao Lu, Mousong Wu, and Nønne L. Prisle
Geosci. Model Dev., 16, 7037–7057, https://doi.org/10.5194/gmd-16-7037-2023, https://doi.org/10.5194/gmd-16-7037-2023, 2023
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The radionuclides 7Be and 10Be are useful tracers for atmospheric transport studies. Here we use the GEOS-Chem to simulate 7Be and 10Be with different production rates: the default production rate in GEOS-Chem and two from the state-of-the-art beryllium production model. We demonstrate that reduced uncertainties in the production rates can enhance the utility of 7Be and 10Be as tracers for evaluating transport and scavenging processes in global models.
Wenxing Jia, Xiaoye Zhang, Hong Wang, Yaqiang Wang, Deying Wang, Junting Zhong, Wenjie Zhang, Lei Zhang, Lifeng Guo, Yadong Lei, Jizhi Wang, Yuanqin Yang, and Yi Lin
Geosci. Model Dev., 16, 6833–6856, https://doi.org/10.5194/gmd-16-6833-2023, https://doi.org/10.5194/gmd-16-6833-2023, 2023
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In addition to the dominant role of the PBL scheme on the results of the meteorological field, many factors in the model are influenced by large uncertainties. This study focuses on the uncertainties that influence numerical simulation results (including horizontal resolution, vertical resolution, near-surface scheme, initial and boundary conditions, underlying surface update, and update of model version), hoping to provide a reference for scholars conducting research on the model.
Owen K. Hughes and Christiane Jablonowski
Geosci. Model Dev., 16, 6805–6831, https://doi.org/10.5194/gmd-16-6805-2023, https://doi.org/10.5194/gmd-16-6805-2023, 2023
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Atmospheric models benefit from idealized tests that assess their accuracy in a simpler simulation. A new test with artificial mountains is developed for models on a spherical earth. The mountains trigger the development of both planetary-scale and small-scale waves. These can be analyzed in dry or moist environments, with a simple rainfall mechanism. Four atmospheric models are intercompared. This sheds light on the pros and cons of the model design and the impact of mountains on the flow.
Zhongwei Luo, Yan Han, Kun Hua, Yufen Zhang, Jianhui Wu, Xiaohui Bi, Qili Dai, Baoshuang Liu, Yang Chen, Xin Long, and Yinchang Feng
Geosci. Model Dev., 16, 6757–6771, https://doi.org/10.5194/gmd-16-6757-2023, https://doi.org/10.5194/gmd-16-6757-2023, 2023
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This study explores how the variation in the source profiles adopted in chemical transport models (CTMs) impacts the simulated results of chemical components in PM2.5 based on sensitivity analysis. The impact on PM2.5 components cannot be ignored, and its influence can be transmitted and linked between components. The representativeness and timeliness of the source profile should be paid adequate attention in air quality simulation.
Jelena Radovic, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-197, https://doi.org/10.5194/gmd-2023-197, 2023
Revised manuscript accepted for GMD
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The initial and boundary conditions are of crucial importance for numerical model (e.g., PALM model) validation studies and have a large influence on the model results especially in the case of studying the atmosphere of a real, complex, and densely built urban environments. Our experiments with different driving conditions for the LES model PALM show its strong dependency on them which is important for the proper separation of errors coming from the boundary conditions and the model itself.
Wenxing Jia, Xiaoye Zhang, Hong Wang, Yaqiang Wang, Deying Wang, Junting Zhong, Wenjie Zhang, Lei Zhang, Lifeng Guo, Yadong Lei, Jizhi Wang, Yuanqin Yang, and Yi Lin
Geosci. Model Dev., 16, 6635–6670, https://doi.org/10.5194/gmd-16-6635-2023, https://doi.org/10.5194/gmd-16-6635-2023, 2023
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Most current studies on planetary boundary layer (PBL) parameterization schemes are relatively fragmented and lack systematic in-depth analysis and discussion. In this study, we comprehensively evaluate the performance capability of the PBL scheme in five typical regions of China in different seasons from the mechanism of the scheme and the effects of PBL schemes on the near-surface meteorological parameters, vertical structures of the PBL, PBL height, and turbulent diffusion.
William Rudisill, Alejandro Flores, and Rosemary Carroll
Geosci. Model Dev., 16, 6531–6552, https://doi.org/10.5194/gmd-16-6531-2023, https://doi.org/10.5194/gmd-16-6531-2023, 2023
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It is important to know how well atmospheric models do in mountains, but there are not very many weather stations. We evaluate rain and snow from a model from 1987–2020 in the Upper Colorado River basin against the available data. The model works rather well, but there are still some uncertainties in remote locations. We then use snow maps collected by aircraft, streamflow measurements, and some advanced statistics to help identify how well the model works in ways we could not do before.
Caroline Arnold, Shivani Sharma, Tobias Weigel, and David Greenberg
EGUsphere, https://doi.org/10.5194/egusphere-2023-2047, https://doi.org/10.5194/egusphere-2023-2047, 2023
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In weather and climate models, rain formation is simplified by parameterizations to be computationally efficient. We trained a machine learning algorithm, SuperdropNet, to emulate rain formation in warm clouds based on physically more accurate super-droplet simulations. Here, we validate SuperdropNet coupled to ICON in a warm bubble experiment. We find the coupled simulation runs stable and produces reasonable results, and present a computational benchmark for the coupling software.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
EGUsphere, https://doi.org/10.5194/egusphere-2023-2587, https://doi.org/10.5194/egusphere-2023-2587, 2023
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The capabilities of the Modular Earth Submodel System (MESSy) are extended to account for non-equilibrium aqueous-phase chemistry in the representation of deliquescent aerosols. When applying the new development in a global simulation we find that MESSy’s bias in modelling routinely observed inorganic aerosol mass concentrations is reduced. Furthermore, the representation of fine aerosol pH is particularly improved in the marine boundary layer.
Angel Liduvino Vara-Vela, Christoffer Karoff, Noelia Rojas Benavente, and Janaina P. Nascimento
Geosci. Model Dev., 16, 6413–6431, https://doi.org/10.5194/gmd-16-6413-2023, https://doi.org/10.5194/gmd-16-6413-2023, 2023
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A 1-year simulation of atmospheric CH4 over Europe is performed and evaluated against observations based on the TROPOspheric Monitoring Instrument (TROPOMI). A good general model–observation agreement is found, with discrepancies reaching their minimum and maximum values during the summer peak season and winter months, respectively. A huge and under-explored potential for CH4 inverse modeling using improved TROPOMI XCH4 data sets in large-scale applications is identified.
Shoma Yamanouchi, Shayamilla Mahagammulla Gamage, Sara Torbatian, Jad Zalzal, Laura Minet, Audrey Smargiassi, Ying Liu, Ling Liu, Youngseob Kim, Daniel Yazgi, Andrée-Anne Brown, and Marianne Hatzopoulou
EGUsphere, https://doi.org/10.5194/egusphere-2023-2038, https://doi.org/10.5194/egusphere-2023-2038, 2023
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Air pollution is a major health hazard, and chemical transport models are valuable tools that aid in our understanding of the risks of air pollution both at local and regional scales. In this study, the Polair3D CTM of the Polyphemus air quality modeling platform was set up over Quebec, Canada to assess the model’s capability in predicting key air pollutant species over the region, at seasonal temporal scales and at regional spatial scales.
Zhaojun Tang, Zhe Jiang, Jiaqi Chen, Panpan Yang, and Yanan Shen
Geosci. Model Dev., 16, 6377–6392, https://doi.org/10.5194/gmd-16-6377-2023, https://doi.org/10.5194/gmd-16-6377-2023, 2023
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We designed a new framework to facilitate emission inventory updates in the adjoint of GEOS-Chem model. It allows us to support Harmonized Emissions Component (HEMCO) emission inventories conveniently and to easily add more emission inventories following future updates in GEOS-Chem forward simulations. Furthermore, we developed new modules to support MERRA-2 meteorological data; this allows us to perform long-term analysis with consistent meteorological data.
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Short summary
Simulating the influence of the biosphere on atmospheric chemistry has traditionally been computationally intensive. We describe a surrogate canopy physics model parameterized using a statistical learning technique and specifically designed for use in large-scale chemical transport models. Our surrogate model reproduces a more detailed model to within 10 % without a large computational demand, improving the process representation of biosphere–atmosphere exchange.
Simulating the influence of the biosphere on atmospheric chemistry has traditionally been...