Articles | Volume 14, issue 6
https://doi.org/10.5194/gmd-14-3969-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-3969-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Evaluation of the offline-coupled GFSv15–FV3–CMAQv5.0.2 in support of the next-generation National Air Quality Forecast Capability over the contiguous United States
Xiaoyang Chen
Department of Civil and Environmental Engineering, Northeastern
University, Boston, MA 02115, USA
Yang Zhang
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering, Northeastern
University, Boston, MA 02115, USA
Kai Wang
Department of Civil and Environmental Engineering, Northeastern
University, Boston, MA 02115, USA
Daniel Tong
Department of Atmospheric, Oceanic and Earth Sciences, George Mason
University, Fairfax, VA 22030, USA
IM Systems Group, Rockville, MD 20852, USA
Pius Lee
Air Resources Laboratory, National Oceanic and Atmospheric
Administration, College Park, MD 20740, USA
Center for Spatial Information Science and System, George Mason
University, Fairfax, VA 22030, USA
Youhua Tang
Center for Spatial Information Science and System, George Mason
University, Fairfax, VA 22030, USA
Air Resources Laboratory, National Oceanic and Atmospheric
Administration, College Park, MD 20740, USA
Jianping Huang
National Oceanic and Atmospheric Administration/National Centers for
Environmental Prediction/Environmental Modeling Center, College Park, MD
20740, USA
IM Systems Group, Rockville, MD 20852, USA
Patrick C. Campbell
Center for Spatial Information Science and System, George Mason
University, Fairfax, VA 22030, USA
Air Resources Laboratory, National Oceanic and Atmospheric
Administration, College Park, MD 20740, USA
Jeff Mcqueen
National Oceanic and Atmospheric Administration/National Centers for
Environmental Prediction/Environmental Modeling Center, College Park, MD
20740, USA
Havala O. T. Pye
Office of Research and Development, U.S. Environmental Protection
Agency, Research Triangle Park, NC 27711, USA
Benjamin N. Murphy
Office of Research and Development, U.S. Environmental Protection
Agency, Research Triangle Park, NC 27711, USA
Daiwen Kang
Office of Research and Development, U.S. Environmental Protection
Agency, Research Triangle Park, NC 27711, USA
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Benjamin N. Murphy, Darrell Sonntag, Karl M. Seltzer, Havala O. T. Pye, Christine Allen, Evan Murray, Claudia Toro, Drew R. Gentner, Cheng Huang, Shantanu Jathar, Li Li, Andrew A. May, and Allen L. Robinson
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Bryan K. Place, William T. Hutzell, K. Wyat Appel, Sara Farrell, Lukas Valin, Benjamin N. Murphy, Karl M. Seltzer, Golam Sarwar, Christine Allen, Ivan R. Piletic, Emma L. D'Ambro, Emily Saunders, Heather Simon, Ana Torres-Vasquez, Jonathan Pleim, Rebecca H. Schwantes, Matthew M. Coggon, Lu Xu, William R. Stockwell, and Havala O. T. Pye
Atmos. Chem. Phys., 23, 9173–9190, https://doi.org/10.5194/acp-23-9173-2023, https://doi.org/10.5194/acp-23-9173-2023, 2023
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Ground-level ozone is a pollutant with adverse human health and ecosystem effects. Air quality models allow scientists to understand the chemical production of ozone and demonstrate impacts of air quality management plans. In this work, the role of multiple systems in ozone production was investigated for the northeastern US in summer. Model updates to chemical reaction rates and monoterpene chemistry were most influential in decreasing predicted ozone and improving agreement with observations.
Bok H. Baek, Carlie Coats, Siqi Ma, Chi-Tsan Wang, Yunyao Li, Jia Xing, Daniel Tong, Soontae Kim, and Jung-Hun Woo
Geosci. Model Dev., 16, 4659–4676, https://doi.org/10.5194/gmd-16-4659-2023, https://doi.org/10.5194/gmd-16-4659-2023, 2023
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To enable the direct feedback effects of aerosols and local meteorology in an air quality modeling system without any computational bottleneck, we have developed an inline meteorology-induced emissions coupler module within the U.S. Environmental Protection Agency’s Community Multiscale Air Quality modeling system to dynamically model the complex MOtor Vehicle Emission Simulator (MOVES) on-road mobile emissions inline without a separate dedicated emissions processing model like SMOKE.
Havala O. T. Pye, Bryan K. Place, Benjamin N. Murphy, Karl M. Seltzer, Emma L. D'Ambro, Christine Allen, Ivan R. Piletic, Sara Farrell, Rebecca H. Schwantes, Matthew M. Coggon, Emily Saunders, Lu Xu, Golam Sarwar, William T. Hutzell, Kristen M. Foley, George Pouliot, Jesse Bash, and William R. Stockwell
Atmos. Chem. Phys., 23, 5043–5099, https://doi.org/10.5194/acp-23-5043-2023, https://doi.org/10.5194/acp-23-5043-2023, 2023
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Chemical mechanisms describe how emissions from vehicles, vegetation, and other sources are chemically transformed in the atmosphere to secondary products including criteria and hazardous air pollutants. The Community Regional Atmospheric Chemistry Multiphase Mechanism integrates gas-phase radical chemistry with pathways to fine-particle mass. New species were implemented, resulting in a bottom-up representation of organic aerosol, which is required for accurate source attribution of pollutants.
Qian Shu, Sergey L. Napelenok, William T. Hutzell, Kirk R. Baker, Barron H. Henderson, Benjamin N. Murphy, and Christian Hogrefe
Geosci. Model Dev., 16, 2303–2322, https://doi.org/10.5194/gmd-16-2303-2023, https://doi.org/10.5194/gmd-16-2303-2023, 2023
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Source attribution methods are generally used to determine culpability of precursor emission sources to ambient pollutant concentrations. However, source attribution of secondarily formed pollutants such as ozone and its precursors cannot be explicitly measured, making evaluation of source apportionment methods challenging. In this study, multiple apportionment approach comparisons show common features but still reveal wide variations in predicted sector contribution and species dependency.
Forwood Wiser, Bryan K. Place, Siddhartha Sen, Havala O. T. Pye, Benjamin Yang, Daniel M. Westervelt, Daven K. Henze, Arlene M. Fiore, and V. Faye McNeill
Geosci. Model Dev., 16, 1801–1821, https://doi.org/10.5194/gmd-16-1801-2023, https://doi.org/10.5194/gmd-16-1801-2023, 2023
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We developed a reduced model of atmospheric isoprene oxidation, AMORE-Isoprene 1.0. It was created using a new Automated Model Reduction (AMORE) method designed to simplify complex chemical mechanisms with minimal manual adjustments to the output. AMORE-Isoprene 1.0 has improved accuracy and similar size to other reduced isoprene mechanisms. When included in the CRACMM mechanism, it improved the accuracy of EPA’s CMAQ model predictions for the northeastern USA compared to observations.
Yunyao Li, Daniel Tong, Siqi Ma, Saulo R. Freitas, Ravan Ahmadov, Mikhail Sofiev, Xiaoyang Zhang, Shobha Kondragunta, Ralph Kahn, Youhua Tang, Barry Baker, Patrick Campbell, Rick Saylor, Georg Grell, and Fangjun Li
Atmos. Chem. Phys., 23, 3083–3101, https://doi.org/10.5194/acp-23-3083-2023, https://doi.org/10.5194/acp-23-3083-2023, 2023
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Plume height is important in wildfire smoke dispersion and affects air quality and human health. We assess the impact of plume height on wildfire smoke dispersion and the exceedances of the National Ambient Air Quality Standards. A higher plume height predicts lower pollution near the source region, but higher pollution in downwind regions, due to the faster spread of the smoke once ejected, affects pollution exceedance forecasts and the early warning of extreme air pollution events.
Chandan Sarangi, Yun Qian, L. Ruby Leung, Yang Zhang, Yufei Zou, and Yuhang Wang
Atmos. Chem. Phys., 23, 1769–1783, https://doi.org/10.5194/acp-23-1769-2023, https://doi.org/10.5194/acp-23-1769-2023, 2023
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We show that for air quality, the densely populated eastern US may see even larger impacts of wildfires due to long-distance smoke transport and associated positive climatic impacts, partially compensating the improvements from regulations on anthropogenic emissions. This study highlights the tension between natural and anthropogenic contributions and the non-local nature of air pollution that complicate regulatory strategies for improving future regional air quality for human health.
James D. East, Barron H. Henderson, Sergey L. Napelenok, Shannon N. Koplitz, Golam Sarwar, Robert Gilliam, Allen Lenzen, Daniel Q. Tong, R. Bradley Pierce, and Fernando Garcia-Menendez
Atmos. Chem. Phys., 22, 15981–16001, https://doi.org/10.5194/acp-22-15981-2022, https://doi.org/10.5194/acp-22-15981-2022, 2022
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We present a framework that uses a computer model of air quality, along with air pollution data from satellite instruments, to estimate emissions of nitrogen oxides (NOx) across the Northern Hemisphere. The framework, which advances current methods to infer emissions from satellite observations, provides observationally constrained NOx estimates, including in regions of the world where emissions are highly uncertain, and can improve simulations of air pollutants relevant for health and policy.
Daiwen Kang, Nicholas K. Heath, Robert C. Gilliam, Tanya L. Spero, and Jonathan E. Pleim
Geosci. Model Dev., 15, 8561–8579, https://doi.org/10.5194/gmd-15-8561-2022, https://doi.org/10.5194/gmd-15-8561-2022, 2022
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A lightning assimilation (LTA) technique implemented in the WRF model's Kain–Fritsch (KF) convective scheme is updated and applied to simulations from regional to hemispheric scales using observed lightning flashes from ground-based lightning detection networks. Different user-toggled options associated with the KF scheme on simulations with and without LTA are assessed. The model's performance is improved significantly by LTA, but it is sensitive to various factors.
Peeyush Khare, Jordan E. Krechmer, Jo E. Machesky, Tori Hass-Mitchell, Cong Cao, Junqi Wang, Francesca Majluf, Felipe Lopez-Hilfiker, Sonja Malek, Will Wang, Karl Seltzer, Havala O. T. Pye, Roisin Commane, Brian C. McDonald, Ricardo Toledo-Crow, John E. Mak, and Drew R. Gentner
Atmos. Chem. Phys., 22, 14377–14399, https://doi.org/10.5194/acp-22-14377-2022, https://doi.org/10.5194/acp-22-14377-2022, 2022
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Ammonium adduct chemical ionization is used to examine the atmospheric abundances of oxygenated volatile organic compounds associated with emissions from volatile chemical products, which are now key contributors of reactive precursors to ozone and secondary organic aerosols in urban areas. The application of this valuable measurement approach in densely populated New York City enables the evaluation of emissions inventories and thus the role these oxygenated compounds play in urban air quality.
Youhua Tang, Patrick C. Campbell, Pius Lee, Rick Saylor, Fanglin Yang, Barry Baker, Daniel Tong, Ariel Stein, Jianping Huang, Ho-Chun Huang, Li Pan, Jeff McQueen, Ivanka Stajner, Jose Tirado-Delgado, Youngsun Jung, Melissa Yang, Ilann Bourgeois, Jeff Peischl, Tom Ryerson, Donald Blake, Joshua Schwarz, Jose-Luis Jimenez, James Crawford, Glenn Diskin, Richard Moore, Johnathan Hair, Greg Huey, Andrew Rollins, Jack Dibb, and Xiaoyang Zhang
Geosci. Model Dev., 15, 7977–7999, https://doi.org/10.5194/gmd-15-7977-2022, https://doi.org/10.5194/gmd-15-7977-2022, 2022
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This paper compares two meteorological datasets for driving a regional air quality model: a regional meteorological model using WRF (WRF-CMAQ) and direct interpolation from an operational global model (GFS-CMAQ). In the comparison with surface measurements and aircraft data in summer 2019, these two methods show mixed performance depending on the corresponding meteorological settings. Direct interpolation is found to be a viable method to drive air quality models.
Youngseob Kim, Lya Lugon, Alice Maison, Thibaud Sarica, Yelva Roustan, Myrto Valari, Yang Zhang, Michel André, and Karine Sartelet
Geosci. Model Dev., 15, 7371–7396, https://doi.org/10.5194/gmd-15-7371-2022, https://doi.org/10.5194/gmd-15-7371-2022, 2022
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This paper presents the latest version of the street-network model MUNICH, v2.0. The description of MUNICH v1.0, which models gas-phase pollutants in a street network, was published in GMD in 2018. Since then, major modifications have been made to MUNICH. The comprehensive aerosol model SSH-aerosol is now coupled to MUNICH to simulate primary and secondary aerosol concentrations. New parameterisations have also been introduced. Test cases are defined to illustrate the new model functionalities.
Mengying Li, Shaocai Yu, Xue Chen, Zhen Li, Yibo Zhang, Zhe Song, Weiping Liu, Pengfei Li, Xiaoye Zhang, Meigen Zhang, Yele Sun, Zirui Liu, Caiping Sun, Jingkun Jiang, Shuxiao Wang, Benjamin N. Murphy, Kiran Alapaty, Rohit Mathur, Daniel Rosenfeld, and John H. Seinfeld
Atmos. Chem. Phys., 22, 11845–11866, https://doi.org/10.5194/acp-22-11845-2022, https://doi.org/10.5194/acp-22-11845-2022, 2022
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This study constructed an emission inventory of condensable particulate matter (CPM) in China with a focus on organic aerosols (OAs), based on collected CPM emission information. The results show that OA emissions are enhanced twofold for the years 2014 and 2017 after the inclusion of CPM in the new inventory. Sensitivity cases demonstrated the significant contributions of CPM emissions from stationary combustion and mobile sources to primary, secondary, and total OA concentrations.
Li Zhang, Raffaele Montuoro, Stuart A. McKeen, Barry Baker, Partha S. Bhattacharjee, Georg A. Grell, Judy Henderson, Li Pan, Gregory J. Frost, Jeff McQueen, Rick Saylor, Haiqin Li, Ravan Ahmadov, Jun Wang, Ivanka Stajner, Shobha Kondragunta, Xiaoyang Zhang, and Fangjun Li
Geosci. Model Dev., 15, 5337–5369, https://doi.org/10.5194/gmd-15-5337-2022, https://doi.org/10.5194/gmd-15-5337-2022, 2022
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The NOAA’s air quality predictions contribute to protecting lives and health in the US, which requires sustainable development and improvement of forecast systems. GEFS-Aerosols v1 has been developed in a collaboration between the NOAA research laboratories for operational forecast since September 2020 in the NCEP. The predictions demonstrate substantial improvements for both composition and variability of aerosol distributions over those from the former operational system.
Patrick C. Campbell, Youhua Tang, Pius Lee, Barry Baker, Daniel Tong, Rick Saylor, Ariel Stein, Jianping Huang, Ho-Chun Huang, Edward Strobach, Jeff McQueen, Li Pan, Ivanka Stajner, Jamese Sims, Jose Tirado-Delgado, Youngsun Jung, Fanglin Yang, Tanya L. Spero, and Robert C. Gilliam
Geosci. Model Dev., 15, 3281–3313, https://doi.org/10.5194/gmd-15-3281-2022, https://doi.org/10.5194/gmd-15-3281-2022, 2022
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NOAA's National Air Quality Forecast Capability (NAQFC) continues to protect Americans from the harmful effects of air pollution, while saving billions of dollars per year. Here we describe and evaluate the development of the most advanced version of the NAQFC to date, which became operational at NOAA on 20 July 2021. The new NAQFC is based on a coupling of NOAA's operational Global Forecast System (GFS) version 16 with the Community Multiscale Air Quality (CMAQ) model version 5.3.1.
Sally S.-C. Wang, Yun Qian, L. Ruby Leung, and Yang Zhang
Atmos. Chem. Phys., 22, 3445–3468, https://doi.org/10.5194/acp-22-3445-2022, https://doi.org/10.5194/acp-22-3445-2022, 2022
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This study develops an interpretable machine learning (ML) model predicting monthly PM2.5 fire emission over the contiguous US at 0.25° resolution and compares the prediction skills of the ML and process-based models. The comparison facilitates attributions of model biases and better understanding of the strengths and uncertainties in the two types of models at regional scales, for informing future model development and their applications in fire emission projection.
Ruili Wu, Christopher W. Tessum, Yang Zhang, Chaopeng Hong, Yixuan Zheng, Xinyin Qin, Shigan Liu, and Qiang Zhang
Geosci. Model Dev., 14, 7621–7638, https://doi.org/10.5194/gmd-14-7621-2021, https://doi.org/10.5194/gmd-14-7621-2021, 2021
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Reduced-complexity air quality models are less computationally intensive and easier to use. We developed a reduced-complexity air quality Intervention Model for Air Pollution over China (InMAP-China) to rapidly predict the air quality and estimate the health impacts of emission sources in China. We believe that this work will be of great interest to a broad audience, including environmentalists in China and scientists in relevant fields at both national and local institutes.
Elyse A. Pennington, Karl M. Seltzer, Benjamin N. Murphy, Momei Qin, John H. Seinfeld, and Havala O. T. Pye
Atmos. Chem. Phys., 21, 18247–18261, https://doi.org/10.5194/acp-21-18247-2021, https://doi.org/10.5194/acp-21-18247-2021, 2021
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Volatile chemical products (VCPs) are commonly used consumer and industrial items that contribute to the formation of atmospheric aerosol. We implemented the emissions and chemistry of VCPs in a regional-scale model and compared predictions with measurements made in Los Angeles. Our results reduced model bias and suggest that VCPs may contribute up to half of anthropogenic secondary organic aerosol in Los Angeles and are an important source of human-influenced particular matter in urban areas.
Kai Wang, Yang Zhang, Shaocai Yu, David C. Wong, Jonathan Pleim, Rohit Mathur, James T. Kelly, and Michelle Bell
Geosci. Model Dev., 14, 7189–7221, https://doi.org/10.5194/gmd-14-7189-2021, https://doi.org/10.5194/gmd-14-7189-2021, 2021
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The two-way coupled WRF-CMAQ model accounting for complex chemistry–meteorology feedbacks has been applied to the long-term predictions of regional meteorology and air quality over the US. The model results show superior performance and importance of chemistry–meteorology feedbacks when compared to the offline coupled WRF and CMAQ simulations, which suggests that feedbacks should be considered along with other factors in developing future model applications to inform policy making.
Siqi Ma, Daniel Tong, Lok Lamsal, Julian Wang, Xuelei Zhang, Youhua Tang, Rick Saylor, Tianfeng Chai, Pius Lee, Patrick Campbell, Barry Baker, Shobha Kondragunta, Laura Judd, Timothy A. Berkoff, Scott J. Janz, and Ivanka Stajner
Atmos. Chem. Phys., 21, 16531–16553, https://doi.org/10.5194/acp-21-16531-2021, https://doi.org/10.5194/acp-21-16531-2021, 2021
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Predicting high ozone gets more challenging as urban emissions decrease. How can different techniques be used to foretell the quality of air to better protect human health? We tested four techniques with the CMAQ model against observations during a field campaign over New York City. The new system proves to better predict the magnitude and timing of high ozone. These approaches can be extended to other regions to improve the predictability of high-O3 episodes in contemporary urban environments.
Adrian Chappell, Nicholas Webb, Mark Hennen, Charles Zender, Philippe Ciais, Kerstin Schepanski, Brandon Edwards, Nancy Ziegler, Sandra Jones, Yves Balkanski, Daniel Tong, John Leys, Stephan Heidenreich, Robert Hynes, David Fuchs, Zhenzhong Zeng, Marie Ekström, Matthew Baddock, Jeffrey Lee, and Tarek Kandakji
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-337, https://doi.org/10.5194/gmd-2021-337, 2021
Revised manuscript not accepted
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Dust emissions influence global climate while simultaneously reducing the productive potential and resilience of landscapes to climate stressors, together impacting food security and human health. Our results indicate that tuning dust emission models to dust in the atmosphere has hidden dust emission modelling weaknesses and its poor performance. Our new approach will reduce uncertainty and driven by prognostic albedo improve Earth System Models of aerosol effects on future environmental change.
Xinxin Ye, Pargoal Arab, Ravan Ahmadov, Eric James, Georg A. Grell, Bradley Pierce, Aditya Kumar, Paul Makar, Jack Chen, Didier Davignon, Greg R. Carmichael, Gonzalo Ferrada, Jeff McQueen, Jianping Huang, Rajesh Kumar, Louisa Emmons, Farren L. Herron-Thorpe, Mark Parrington, Richard Engelen, Vincent-Henri Peuch, Arlindo da Silva, Amber Soja, Emily Gargulinski, Elizabeth Wiggins, Johnathan W. Hair, Marta Fenn, Taylor Shingler, Shobha Kondragunta, Alexei Lyapustin, Yujie Wang, Brent Holben, David M. Giles, and Pablo E. Saide
Atmos. Chem. Phys., 21, 14427–14469, https://doi.org/10.5194/acp-21-14427-2021, https://doi.org/10.5194/acp-21-14427-2021, 2021
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Wildfire smoke has crucial impacts on air quality, while uncertainties in the numerical forecasts remain significant. We present an evaluation of 12 real-time forecasting systems. Comparison of predicted smoke emissions suggests a large spread in magnitudes, with temporal patterns deviating from satellite detections. The performance for AOD and surface PM2.5 and their discrepancies highlighted the role of accurately represented spatiotemporal emission profiles in improving smoke forecasts.
Syuichi Itahashi, Rohit Mathur, Christian Hogrefe, Sergey L. Napelenok, and Yang Zhang
Geosci. Model Dev., 14, 5751–5768, https://doi.org/10.5194/gmd-14-5751-2021, https://doi.org/10.5194/gmd-14-5751-2021, 2021
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The Community Multiscale Air Quality (CMAQ) modeling system extended for hemispheric-scale applications (H-CMAQ) incorporated the satellite-constrained degassing SO2 emissions from 50 volcanos across the Northern Hemisphere. The impact on tropospheric sulfate aerosol (SO42−) is assessed for 2010. Although the considered volcanic emissions occurred at or below the middle of free troposphere (500 hPa), SO42− enhancements of more than 10 % were detected up to the top of free troposphere (250 hPa).
Andreas Tilgner, Thomas Schaefer, Becky Alexander, Mary Barth, Jeffrey L. Collett Jr., Kathleen M. Fahey, Athanasios Nenes, Havala O. T. Pye, Hartmut Herrmann, and V. Faye McNeill
Atmos. Chem. Phys., 21, 13483–13536, https://doi.org/10.5194/acp-21-13483-2021, https://doi.org/10.5194/acp-21-13483-2021, 2021
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Feedbacks of acidity and atmospheric multiphase chemistry in deliquesced particles and clouds are crucial for the tropospheric composition, depositions, climate, and human health. This review synthesizes the current scientific knowledge on these feedbacks using both inorganic and organic aqueous-phase chemistry. Finally, this review outlines atmospheric implications and highlights the need for future investigations with respect to reducing emissions of key acid precursors in a changing world.
Haipeng Lin, Daniel J. Jacob, Elizabeth W. Lundgren, Melissa P. Sulprizio, Christoph A. Keller, Thibaud M. Fritz, Sebastian D. Eastham, Louisa K. Emmons, Patrick C. Campbell, Barry Baker, Rick D. Saylor, and Raffaele Montuoro
Geosci. Model Dev., 14, 5487–5506, https://doi.org/10.5194/gmd-14-5487-2021, https://doi.org/10.5194/gmd-14-5487-2021, 2021
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Emissions are a central component of atmospheric chemistry models. The Harmonized Emissions Component (HEMCO) is a software component for computing emissions from a user-selected ensemble of emission inventories and algorithms. It allows users to select, add, and scale emissions from different sources through a configuration file with no change to the model source code. We demonstrate the implementation of HEMCO in several models, all sharing the same HEMCO core code and database library.
Benjamin N. Murphy, Christopher G. Nolte, Fahim Sidi, Jesse O. Bash, K. Wyat Appel, Carey Jang, Daiwen Kang, James Kelly, Rohit Mathur, Sergey Napelenok, George Pouliot, and Havala O. T. Pye
Geosci. Model Dev., 14, 3407–3420, https://doi.org/10.5194/gmd-14-3407-2021, https://doi.org/10.5194/gmd-14-3407-2021, 2021
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The algorithms for applying air pollution emission rates in the Community Multiscale Air Quality (CMAQ) model have been improved to better support users and developers. The new features accommodate emissions perturbation studies that are typical in atmospheric research and output a wealth of metadata for each model run so assumptions can be verified and documented. The new approach dramatically enhances the transparency and functionality of this critical aspect of atmospheric modeling.
Mario Eduardo Gavidia-Calderón, Sergio Ibarra-Espinosa, Youngseob Kim, Yang Zhang, and Maria de Fatima Andrade
Geosci. Model Dev., 14, 3251–3268, https://doi.org/10.5194/gmd-14-3251-2021, https://doi.org/10.5194/gmd-14-3251-2021, 2021
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The MUNICH model was used to calculate pollutant concentrations inside the streets of São Paulo. The VEIN emission model provided the vehicular emissions and the coordinates of the streets. We used information from an air quality station to account for pollutant concentrations over the street rooftops. Results showed that when emissions are calibrated, MUNICH satisfied the performance criteria. MUNICH can be used to evaluate the impact of traffic-related air pollution on public health.
K. Wyat Appel, Jesse O. Bash, Kathleen M. Fahey, Kristen M. Foley, Robert C. Gilliam, Christian Hogrefe, William T. Hutzell, Daiwen Kang, Rohit Mathur, Benjamin N. Murphy, Sergey L. Napelenok, Christopher G. Nolte, Jonathan E. Pleim, George A. Pouliot, Havala O. T. Pye, Limei Ran, Shawn J. Roselle, Golam Sarwar, Donna B. Schwede, Fahim I. Sidi, Tanya L. Spero, and David C. Wong
Geosci. Model Dev., 14, 2867–2897, https://doi.org/10.5194/gmd-14-2867-2021, https://doi.org/10.5194/gmd-14-2867-2021, 2021
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This paper details the scientific updates in the recently released CMAQ version 5.3 (and v5.3.1) and also includes operational and diagnostic evaluations of CMAQv5.3.1 against observations and the previous version of the CMAQ (v5.2.1). This work was done to improve the underlying science in CMAQ. This article is used to inform the CMAQ modeling community of the updates to the modeling system and the expected change in model performance from these updates (versus the previous model version).
Qian Shu, Benjamin Murphy, Jonathan E. Pleim, Donna Schwede, Barron H. Henderson, Havala O.T. Pye, Keith Wyat Appel, Tanvir R. Khan, and Judith A. Perlinger
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-129, https://doi.org/10.5194/gmd-2021-129, 2021
Preprint withdrawn
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We have bridged the gap between dry deposition measurement and modeling by rigorous use of box and regional transport models and field measurements, but more efforts are needed. This study highlights that deviation among deposition schemes is most pronounced for small and large particles. This study better links model predictions to available real-world observations and incrementally reduces uncertainties in the magnitude of loss processes important for the lifecycle of air pollutants.
Karl M. Seltzer, Elyse Pennington, Venkatesh Rao, Benjamin N. Murphy, Madeleine Strum, Kristin K. Isaacs, and Havala O. T. Pye
Atmos. Chem. Phys., 21, 5079–5100, https://doi.org/10.5194/acp-21-5079-2021, https://doi.org/10.5194/acp-21-5079-2021, 2021
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Volatile chemical products (VCPs) are an increasingly important source of anthropogenic reactive organic carbon emissions. Here, we develop VCPy, a new framework to model organic emissions from VCPs throughout the United States. At the national-level, VCPy emissions are broadly consistent with the US EPA’s 2017 National Emission Inventory, however county-level and categorical estimates can differ substantially. An observational evaluation indicates high fidelity in the methods employed here.
Youhua Tang, Huisheng Bian, Zhining Tao, Luke D. Oman, Daniel Tong, Pius Lee, Patrick C. Campbell, Barry Baker, Cheng-Hsuan Lu, Li Pan, Jun Wang, Jeffery McQueen, and Ivanka Stajner
Atmos. Chem. Phys., 21, 2527–2550, https://doi.org/10.5194/acp-21-2527-2021, https://doi.org/10.5194/acp-21-2527-2021, 2021
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Chemical lateral boundary condition (CLBC) impact is essential for regional air quality prediction during intrusion events. We present a model mapping Goddard Earth Observing System (GEOS) to Community Multi-scale Air Quality (CMAQ) CB05–AERO6 (Carbon Bond 5; version 6 of the aerosol module) species. Influence depends on distance from the inflow boundary and species and their regional characteristics. We use aerosol optical thickness to derive CLBCs, achieving reasonable prediction.
Xiaodan Ma, Jianping Huang, Tianliang Zhao, Cheng Liu, Kaihui Zhao, Jia Xing, and Wei Xiao
Atmos. Chem. Phys., 21, 1–16, https://doi.org/10.5194/acp-21-1-2021, https://doi.org/10.5194/acp-21-1-2021, 2021
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The present work aims at identifying and quantifying the relative contributions of the key factors in driving a rapid increase in summertime surface O3 over the North China Plain during 2013–2019. In addition to anthropogenic emission reduction and meteorological variabilities, our study highlights the importance of inclusion of aerosol absorption and scattering properties rather than aerosol abundance only in accurate assessment of aerosol radiative effect on surface O3 formation and change.
Yohei Shinozuka, Pablo E. Saide, Gonzalo A. Ferrada, Sharon P. Burton, Richard Ferrare, Sarah J. Doherty, Hamish Gordon, Karla Longo, Marc Mallet, Yan Feng, Qiaoqiao Wang, Yafang Cheng, Amie Dobracki, Steffen Freitag, Steven G. Howell, Samuel LeBlanc, Connor Flynn, Michal Segal-Rosenhaimer, Kristina Pistone, James R. Podolske, Eric J. Stith, Joseph Ryan Bennett, Gregory R. Carmichael, Arlindo da Silva, Ravi Govindaraju, Ruby Leung, Yang Zhang, Leonhard Pfister, Ju-Mee Ryoo, Jens Redemann, Robert Wood, and Paquita Zuidema
Atmos. Chem. Phys., 20, 11491–11526, https://doi.org/10.5194/acp-20-11491-2020, https://doi.org/10.5194/acp-20-11491-2020, 2020
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In the southeast Atlantic, well-defined smoke plumes from Africa advect over marine boundary layer cloud decks; both are most extensive around September, when most of the smoke resides in the free troposphere. A framework is put forth for evaluating the performance of a range of global and regional atmospheric composition models against observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) airborne mission in September 2016.
Cited articles
Adams, J. W. and Cox, R. A.: Halogen chemistry of the marine boundary layer, J. Phys. IV, 12, 105–124, https://doi.org/10.1051/jp4:20020455, 2002.
Appel, K. W., Pouliot, G. A., Simon, H., Sarwar, G., Pye, H. O. T., Napelenok, S. L., Akhtar, F., and Roselle, S. J.: Evaluation of dust and trace metal estimates from the Community Multiscale Air Quality (CMAQ) model version 5.0, Geosci. Model Dev., 6, 883–899, https://doi.org/10.5194/gmd-6-883-2013, 2013.
Appel, K. W., Bash, J. O., Fahey, K. M., Foley, K. M., Gilliam, R. C.,
Hogrefe, C., Hutzell, W. T., Kang, D., Mathur, R., Murphy, B. N., Napelenok,
S. L., Nolte, C. G., Pleim, J. E., Pouliot, G. A., Pye, H. O. T., Ran, L.,
Roselle, S. J., Sarwar, G., Schwede, D. B., Sidi, F. I., Spero, T. L., and
Wong, D. C.: The Community Multiscale Air Quality (CMAQ) Model Versions 5.3
and 5.3.1: System Updates and Evaluation, Geosci. Model
Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2020-345, accepted,
2021.
Arakawa, A. and Lamb, V. R.: Computational design of the basic dynamical processes of the UCLA General Circulation Model, Methods Comput. Phys., 17, 173–265, available at: http://ci.nii.ac.jp/naid/10012003123/en/ (last access: 22 May 2020), 1977.
Arakawa, A. and Schubert, W. H.: Interaction of a Cumulus Cloud Ensemble with
the Large-Scale Environment, Part I, J. Atmos. Sci., 31, 674–701,
https://doi.org/10.1175/1520-0469(1974)031<0674:IOACCE>2.0.CO;2,
1974.
Barnes, L. R., Schultz, D. M., Gruntfest, E. C., Hayden, M. H., and Benight, C. C.: Corrigendum: False alarm rate or false alarm ratio?, Weather Forecast., 24, 1452–1454, https://doi.org/10.1175/2009WAF2222300.1, 2009.
Binkowski, F. S., Arunachalam, S., Adelman, Z., and Pinto, J. P.: Examining photolysis rates with a prototype online photolysis module in CMAQ, J. Appl. Meteorol. Clim., 46, 1252–1256, https://doi.org/10.1175/JAM2531.1, 2007.
Black, T. L.: The New NMC Mesoscale Eta Model: Description and Forecast Examples, Weather Forecast., 9, 265–278, https://doi.org/10.1175/1520-0434(1994)009<0265:TNNMEM>2.0.CO;2, 1994.
Bloomer, B. J., Stehr, J. W., Piety, C. A., Salawitch, R. J., and Dickerson, R. R.: Observed relationships of ozone air pollution with temperature and emissions, Geophys. Res. Lett., 36, L09803, https://doi.org/10.1029/2009GL037308, 2009.
Byun, D. and Schere, K. L.: Review of the governing equations, computational algorithms, and other components of the models-3 community multiscale air quality (CMAQ) modeling system, Appl. Mech. Rev., 59, 51–77, https://doi.org/10.1115/1.2128636, 2006.
Campbell, P., Tang, Y., Lee, P., Baker, B., Tong, D., Saylor, R., Stein, A., Huang, J., Huang, H., Strobach, E., McQueen, J., Stajner, I., Koch, D., Tirado-Delgado, J., and Jung, Y.: An Improved National Air Quality Forecasting Capability Using the NOAA Global Forecast System. Part I: Model Development and Community Application, in: the 19th CMAS Conference, Virtual, 26–30 October 2020, 2020.
Carlton, A. G., Bhave, P. V., Napelenok, S. L., Edney, E. O., Sarwar, G., Pinder, R. W., Pouliot, G. A., and Houyoux, M.: Model representation of secondary organic aerosol in CMAQv4.7, Environ. Sci. Technol., 44, 8553–8560, https://doi.org/10.1021/es100636q, 2010.
Carlton, A. G., Pye, H. O. T., Baker, K. R., and Hennigan, C. J.: Additional Benefits of Federal Air-Quality Rules: Model Estimates of Controllable Biogenic Secondary Organic Aerosol, Environ. Sci. Technol., 52, 9254–9265, https://doi.org/10.1021/acs.est.8b01869, 2018.
Chen, F., Janjić, Z., and Mitchell, K.: Impact of atmospheric surface-layer parameterizations in the new land-surface scheme of the NCEP mesoscale Eta model, Bound.-Lay. Meteorol., 85, 391–421, https://doi.org/10.1023/A:1000531001463, 1997.
Chuang, M. T., Zhang, Y., and Kang, D.: Application of WRF/Chem-MADRID for real-time air quality forecasting over the Southeastern United States, Atmos. Environ., 45, 6241–6250, https://doi.org/10.1016/j.atmosenv.2011.06.071, 2011.
Clough, S. A., Shephard, M. W., Mlawer, E. J., Delamere, J. S., Iacono, M. J., Cady-Pereira, K., Boukabara, S., and Brown, P. D.: Atmospheric radiative transfer modeling: A summary of the AER codes, J. Quant. Spectrosc. Ra., 91, 233–244, https://doi.org/10.1016/j.jqsrt.2004.05.058, 2005.
Cuchiara, G. C., Li, X., Carvalho, J., and Rappenglück, B.: Intercomparison of planetary boundary layer parameterization and its impacts on surface ozone concentration in the WRF/Chem model for a case study in houston/texas, Atmos. Environ., 96, 175–185, https://doi.org/10.1016/j.atmosenv.2014.07.013, 2014.
D'Allura, A., Costa, M. P., and Silibello, C.: Qualearia: European and national scale air quality forecast system performance evaluation, Int. J. Environ. Pollut., 64, 110–124, https://doi.org/10.1504/IJEP.2018.099152, 2018.
Eder, B., Kang, D., Mathur, R., Yu, S., and Schere, K.: An operational evaluation of the Eta-CMAQ air quality forecast model, Atmos. Environ., 40, 4894–4905, https://doi.org/10.1016/j.atmosenv.2005.12.062, 2006.
Eder, B., Kang, D., Mathur, R., Pleim, J., Yu, S., Otte, T., and Pouliot, G.: A performance evaluation of the National Air Quality Forecast Capability for the summer of 2007, Atmos. Environ., 43, 2312–2320, https://doi.org/10.1016/j.atmosenv.2009.01.033, 2009.
Emery, C., Jung, J., Koo, B., and Yarwood, G.: Improvements to CAMx Snow Cover Treatments and Carbon Bond Chemical Mechanism for Winter Ozone, Final report for Utah DAQ, project UDAQ PO 480 52000000001, 2015.
Emery, C., Liu, Z., Russell, A. G., Odman, M. T., Yarwood, G., and Kumar, N.: Recommendations on statistics and benchmarks to assess photochemical model performance, J. Air Waste Manage., 67, 582–598, https://doi.org/10.1080/10962247.2016.1265027, 2017.
Foster, K. L., Plastridge, R. A., Bottenheim, J. W., Shepson, P. B., Finlayson-Pitts, B. J., and Spicer, C. W.: The role of Br2 and BrCl in surface ozone destruction at polar sunrise, Science, 291, 471–474, https://doi.org/10.1126/science.291.5503.471, 2001.
Gantt, B., Sarwar, G., Xing, J., Simon, H., Schwede, D., Hutzell, W. T., Mathur, R., and Saiz-Lopez, A.: The Impact of Iodide-Mediated Ozone Deposition and Halogen Chemistry on Surface Ozone Concentrations Across the Continental United States, Environ. Sci. Technol., 51, 1458–1466, https://doi.org/10.1021/acs.est.6b03556, 2017.
Grell, G. A.: Prognostic Evaluation of Assumptions Used by Cumulus Parameterizations, Mon. Weather Rev., 121, 764–787, https://doi.org/10.1175/1520-0493(1993)121<0764:PEOAUB>2.0.CO;2, 1993.
Ha, S., Liu, Z., Sun, W., Lee, Y., and Chang, L.: Improving air quality forecasting with the assimilation of GOCI aerosol optical depth (AOD) retrievals during the KORUS-AQ period, Atmos. Chem. Phys., 20, 6015–6036, https://doi.org/10.5194/acp-20-6015-2020, 2020.
He, J., He, R., and Zhang, Y.: Impacts of Air-sea Interactions on
Regional Air Quality Predictions Using a Coupled Atmosphere-ocean Model in
Southeastern U.S., Aerosol Air Qual. Res., 18, 1044–1067, https://doi.org/10.4209/aaqr.2016.12.0570, 2018.
He, P., Bian, L., Zheng, X., Yu, J., Sun, C., Ye, P., and Xie, Z.: Observation of surface ozone in the marine boundary layer along a cruise through the Arctic Ocean: From offshore to remote, Atmos. Res., 169, 191–198, https://doi.org/10.1016/j.atmosres.2015.10.009, 2016.
Hou, D., Charles, M., Luo, Y., Toth, Z., Zhu, Y., Krzysztofowicz, R., Lin, Y., Xie, P., Seo, D. J., Pena, M., and Cui, B.: Climatology-calibrated precipitation analysis at fine scales: Statistical adjustment of stage IV toward CPC gauge-based analysis, J. Hydrometeorol., 15, 2542–2557, https://doi.org/10.1175/JHM-D-11-0140.1, 2014.
Hu, X. M., Klein, P. M., and Xue, M.: Evaluation of the updated YSU planetary boundary layer scheme within WRF for wind resource and air quality assessments, J. Geophys. Res.-Atmos., 118, 10490–10505, https://doi.org/10.1002/jgrd.50823, 2013.
Huang, J., McQueen, J., Wilczak, J., Djalalova, I., Stajner, I., Shafran, P., Allured, D., Lee, P., Pan, L., Tong, D., Huang, H.-C., DiMego, G., Upadhayay, S., and Delle Monache, L.: Improving NOAA NAQFC PM2.5 Predictions with a Bias Correction Approach, Weather Forecast., 32, 407–421, https://doi.org/10.1175/WAF-D-16-0118.1, 2017.
Huang, J., McQueen, J., Shafran, P., Huang, H., Kain, J., Tang, Y., Lee, P.,
Stajner, I., and Tirado-Delgado, J.: Development and evaluation of offline
coupling of FV3-based GFS with CMAQ at NOAA, in: the 17th CMAS Conference, UNC-Chapel Hill, NC, 22–24 October 2018, 2018.
Huang, J., McQueen, J., Yang, B., Shafran, P., Pan, L., Huang, H.,
Bhattacharjee, P., Tang, Y., Campbell, P., Tong, D., Lee, P., Stajner, I.,
Kain, J., Tirado-Delgado, J., and Koch, D.: Impact of global scale FV3 versus
regional scale NAM meteorological driver model predictions on regional air
quality forecasting, in: The 100th AGU Fall Meeting, San Francisco, CA, 9–13 December 2019, 2019.
Iacono, M. J., Mlawer, E. J., Clough, S. A., and Morcrette, J.-J.: Impact of an improved longwave radiation model, RRTM, on the energy budget and thermodynamic properties of the NCAR community climate model, CCM3, J. Geophys. Res.-Atmos., 105, 14873–14890, https://doi.org/10.1029/2000JD900091, 2000.
Kang, D., Eder, B. K., Stein, A. F., Grell, G. A., Peckham, S. E., and Mc Henry, J.: The New England Air Quality Forecasting Pilot Program: Development of an Evaluation Protocol and Performance Benchmark, J. Air Waste Manage., 55, 1782–1796, https://doi.org/10.1080/10473289.2005.10464775, 2005.
Kang, D., Mathur, R., Rao, S. T., and Yu, S.: Bias adjustment techniques for improving ozone air quality forecasts, J. Geophys. Res., 113, D23308, https://doi.org/10.1029/2008JD010151, 2008.
Kang, D., Mathur, R., and Trivikrama Rao, S.: Assessment of bias-adjusted PM2.5 air quality forecasts over the continental United States during 2007, Geosci. Model Dev., 3, 309–320, https://doi.org/10.5194/gmd-3-309-2010, 2010a.
Kang, D., Mathur, R., and Trivikrama Rao, S.: Real-time bias-adjusted O3 and PM2.5 air quality index forecasts and their performance evaluations over the continental United States, Atmos. Environ., 44, 2203–2212, https://doi.org/10.1016/j.atmosenv.2010.03.017, 2010b.
Kang, D., Foley, K. M., Mathur, R., Roselle, S. J., Pickering, K. E., and Allen, D. J.: Simulating lightning NO production in CMAQv5.2: performance evaluations, Geosci. Model Dev., 12, 4409–4424, https://doi.org/10.5194/gmd-12-4409-2019, 2019a.
Kang, D., Pickering, K. E., Allen, D. J., Foley, K. M., Wong, D. C., Mathur, R., and Roselle, S. J.: Simulating lightning NO production in CMAQv5.2: evolution of scientific updates, Geosci. Model Dev., 12, 3071–3083, https://doi.org/10.5194/gmd-12-3071-2019, 2019b.
Lee, P., Ngan, F., Kim, H., Tong, D., Tang, Y., Chai, T., Saylor, R., Stein, A., Byun, D., Tsidulko, M., McQueen, J., and Stajner, I.: Incremental Development of Air Quality Forecasting System with Off-Line/On-Line Capability: Coupling CMAQ to NCEP National Mesoscale Model, in: Air Pollution Modeling and its Application XXI, Springer, Dordrecht, 187–192, 2011.
Lee, P., McQueen, J., Stajner, I., Huang, J., Pan, L., Tong, D., Kim, H., Tang, Y., Kondragunta, S., Ruminski, M., Lu, S., Rogers, E., Saylor, R., Shafran, P., Huang, H.-C., Gorline, J., Upadhayay, S., and Artz, R.: NAQFC Developmental Forecast Guidance for Fine Particulate Matter (PM2.5), Weather Forecast., 32, 343–360, https://doi.org/10.1175/waf-d-15-0163.1, 2017.
Levy, R. and Hsu, C.: MODIS Atmosphere L2 Aerosol Product, NASA MODIS Adaptive
Processing System, Goddard Space Flight Center, USA,
https://doi.org/10.5067/MODIS/MOD04_L2.006, 2015.
Liu, Y., Fan, Q., Chen, X., Zhao, J., Ling, Z., Hong, Y., Li, W., Chen, X., Wang, M., and Wei, X.: Modeling the impact of chlorine emissions from coal combustion and prescribed waste incineration on tropospheric ozone formation in China, Atmos. Chem. Phys., 18, 2709–2724, https://doi.org/10.5194/acp-18-2709-2018, 2018.
Lu, C.-H., da Silva, A., Wang, J., Moorthi, S., Chin, M., Colarco, P., Tang, Y., Bhattacharjee, P. S., Chen, S.-P., Chuang, H.-Y., Juang, H.-M. H., McQueen, J., and Iredell, M.: The implementation of NEMS GFS Aerosol Component (NGAC) Version 1.0 for global dust forecasting at NOAA/NCEP, Geosci. Model Dev., 9, 1905–1919, https://doi.org/10.5194/gmd-9-1905-2016, 2016.
Luecken, D. J., Yarwood, G., and Hutzell, W. T.: Multipollutant modeling of ozone, reactive nitrogen and HAPs across the continental US with CMAQ-CB6, Atmos. Environ., 201, 62–72, https://doi.org/10.1016/j.atmosenv.2018.11.060, 2019.
Lyu, B., Zhang, Y., and Hu, Y.: Improving PM2.5 Air Quality Model Forecasts in China Using a Bias-Correction Framework, Atmosphere-Basel, 8, 147, https://doi.org/10.3390/atmos8080147, 2017.
Mathur, R., Yu, S., Kang, D., and Schere, K. L.: Assessment of the wintertime performance of developmental particulate matter forecasts with the Eta-Community Multiscale Air Quality modeling system, J. Geophys. Res., 113, D02303, https://doi.org/10.1029/2007JD008580, 2008.
McHenry, J. N., Ryan, W. F., Seamn, N. L., Coats, C. J., Pudykiewicz, J., Arunachalam, S., and Vukovich, J. M.: A real-time eulerian photochemical model forecast system, B. Am. Meteorol. Soc., 85, 525–548, https://doi.org/10.1175/BAMS-85-4-525, 2004.
McKeen, S., Wilczak, J., Grell, G., Djalalova, I., Peckham, S., Hsie, E.-Y., Gong, W., Bouchet, V., Menard, S., Moffet, R., McHenry, J., McQueen, J., Tang, Y., Carmichael, G. R., Pagowski, M., Chan, A., Dye, T., Frost, G., Lee, P., and Mathur, R.: Assessment of an ensemble of seven real-time ozone forecasts over eastern North America during the summer of 2004, J. Geophys. Res., 110, D21307, https://doi.org/10.1029/2005JD005858, 2005.
McKeen, S., Chung, S. H., Wilczak, J., Grell, G., Djalalova, I., Peckham, S., Gong, W., Bouchet, V., Moffet, R., Tang, Y., Carmichael, G. R., Mathur, R., and Yu, S.: Evaluation of several PM2.5 forecast models using data collected during the ICARTT/NEAQS 2004 field study, J. Geophys. Res.-Atmos., 112, D10S20, https://doi.org/10.1029/2006JD007608, 2007.
McKeen, S., Grell, G., Peckham, S., Wilczak, J., Djalalova, I., Hsie, E.-Y., Frost, G., Peischl, J., Schwarz, J., Spackman, R., Holloway, J., de Gouw, J., Warneke, C., Gong, W., Bouchet, V., Gaudreault, S., Racine, J., McHenry, J., McQueen, J., Lee, P., Tang, Y., Carmichael, G. R., and Mathur, R.: An evaluation of real-time air quality forecasts and their urban emissions over eastern Texas during the summer of 2006 Second Texas Air Quality Study field study, J. Geophys. Res., 114, D00F11, https://doi.org/10.1029/2008JD011697, 2009.
Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., and Clough, S. A.: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave, J. Geophys. Res.-Atmos., 102, 16663–16682, https://doi.org/10.1029/97jd00237, 1997.
Moran, M. D., Lupu, A., Zhang, J., Savic-Jovcic, V., and Gravel, S.: A comprehensive performance evaluation of the next generation of the Canadian operational regional air quality deterministic prediction system, in: Air Pollution Modeling and its Application XXV, edited by: Mensink, C. and Kallos, G., Springer Proceedings in Complexity, Springer, Cham, https://doi.org/10.1007/978-3-319-57645-9_12, pp. 75–81, 2018.
Murphy, B. N., Woody, M. C., Jimenez, J. L., Carlton, A. M. G., Hayes, P. L., Liu, S., Ng, N. L., Russell, L. M., Setyan, A., Xu, L., Young, J., Zaveri, R. A., Zhang, Q., and Pye, H. O. T.: Semivolatile POA and parameterized total combustion SOA in CMAQv5.2: impacts on source strength and partitioning, Atmos. Chem. Phys., 17, 11107–11133, https://doi.org/10.5194/acp-17-11107-2017, 2017.
National Centers for Environmental Prediction: The Global Forecast System
(GFS) – Global Spectral Model (GSM), available at:
https://www.emc.ncep.noaa.gov/emc/pages/numerical_forecast_systems/gfs/documentation.php
(last access: 22 May 2020), 2019a.
National Centers for Environmental Prediction: FV3: The GFDL Finite-Volume
Cubed-Sphere Dynamical Core, available at: https://vlab.ncep.noaa.gov/web/fv3gfs (last access: 22 May 2020), 2019b.
National Oceanic and Atmospheric Administration: Meteorological Assimilation Data Ingest System (MADIS), available at: https://madis.ncep.noaa.gov, last access: 28 May 2020a.
National Oceanic and Atmospheric Administration: Global Precipitation Climatology Project (GPCP) monthly product, available at: https://www.ncei.noaa.gov/data/global-precipitation-climatology-project-gpcp-monthly, last accessed: 21 January 2020b.
Oliveri Conti, G., Heibati, B., Kloog, I., Fiore, M., and Ferrante, M.: A review of AirQ Models and their applications for forecasting the air pollution health outcomes, Environ. Sci. Pollut. R., 24, 6426–6445, https://doi.org/10.1007/s11356-016-8180-1, 2017.
Otte, T. L., Pouliot, G., Pleim, J. E., Young, J. O., Schere, K. L., Wong, D. C., Lee, P. C. S., Tsidulko, M., McQueen, J. T., Davidson, P., Mathur, R., Chuang, H.-Y., DiMego, G., and Seaman, N. L.: Linking the Eta Model with the Community Multiscale Air Quality (CMAQ) Modeling System to Build a National Air Quality Forecasting System, Weather Forecast., 20, 367–384, https://doi.org/10.1175/WAF855.1, 2005.
Park, R. J., Hong, S. K., Kwon, H.-A., Kim, S., Guenther, A., Woo, J.-H., and Loughner, C. P.: An evaluation of ozone dry deposition simulations in East Asia, Atmos. Chem. Phys., 14, 7929–7940, https://doi.org/10.5194/acp-14-7929-2014, 2014.
Peng, Z., Lei, L., Liu, Z., Sun, J., Ding, A., Ban, J., Chen, D., Kou, X., and Chu, K.: The impact of multi-species surface chemical observation assimilation on air quality forecasts in China, Atmos. Chem. Phys., 18, 17387–17404, https://doi.org/10.5194/acp-18-17387-2018, 2018.
Pleim, J., Gilliam, R., Appel, W., and Ran, L.: Recent Advances in Modeling of
the Atmospheric Boundary Layer and Land Surface in the Coupled WRF-CMAQ Model
BT – Air Pollution Modeling and its Application XXIV, in: Air Pollution
Modeling and its Application XXIV, edited by: Steyn, D. G. and Chaumerliac, N., Springer International Publishing, Cham, 391–396, 2016.
Pleim, J. E., Bash, J. O., Walker, J. T., and Cooter, E. J.: Development and evaluation of an ammonia bidirectional flux parameterization for air quality models, J. Geophys. Res.-Atmos., 118, 3794–3806, https://doi.org/10.1002/jgrd.50262, 2013.
Pleim, J. E., Ran, L., Appel, W., Shephard, M. W., and Cady-Pereira, K.: New Bidirectional Ammonia Flux Model in an Air Quality Model Coupled With an Agricultural Model, J. Adv. Model. Earth Sy., 11, 2934–2957, https://doi.org/10.1029/2019MS001728, 2019.
Podrascanin, Z.: Setting-up a Real-Time Air Quality Forecasting system for Serbia: a WRF-Chem feasibility study with different horizontal resolutions and emission inventories, Environ. Sci. Pollut. R., 26, 17066–17079, https://doi.org/10.1007/s11356-019-05140-y, 2019.
Putman, W. M. and Lin, S. J.: Finite-volume transport on various cubed-sphere grids, J. Comput. Phys., 227, 55–78, https://doi.org/10.1016/j.jcp.2007.07.022, 2007.
Pye, H. O. T., Pinder, R. W., Piletic, I. R., Xie, Y., Capps, S. L., Lin, Y. H., Surratt, J. D., Zhang, Z. F., Gold, A., Luecken, D. J., Hutzell, W. T., Jaoui, M., Offenberg, J. H., Kleindienst, T. E., Lewandowski, M., and Edney, E. O.: Epoxide Pathways Improve Model Predictions of Isoprene Markers and Reveal Key Role of Acidity in Aerosol Formation, Environ. Sci. Technol., 47, 11056–11064, https://doi.org/10.1021/es402106h, 2013.
Pye, H. O. T., Luecken, D. J., Xu, L., Boyd, C. M., Ng, N. L., Baker, K. R., Ayres, B. R., Bash, J. O., Baumann, K., Carter, W. P., Edgerton, E., Fry, J. L., Hutzell, W. T., Schwede, D. B., and Shepson, P. B.: Modeling the Current and Future Roles of Particulate Organic Nitrates in the Southeastern United States, Environ. Sci. Technol., 49, 14195–14203, https://doi.org/10.1021/acs.est.5b03738, 2015.
Pye, H. O. T., Murphy, B. N., Xu, L., Ng, N. L., Carlton, A. G., Guo, H., Weber, R., Vasilakos, P., Appel, K. W., Budisulistiorini, S. H., Surratt, J. D., Nenes, A., Hu, W., Jimenez, J. L., Isaacman-VanWertz, G., Misztal, P. K., and Goldstein, A. H.: On the implications of aerosol liquid water and phase separation for organic aerosol mass, Atmos. Chem. Phys., 17, 343–369, https://doi.org/10.5194/acp-17-343-2017, 2017.
Pye, H. O. T., Zuend, A., Fry, J. L., Isaacman-VanWertz, G., Capps, S. L., Appel, K. W., Foroutan, H., Xu, L., Ng, N. L., and Goldstein, A. H.: Coupling of organic and inorganic aerosol systems and the effect on gas–particle partitioning in the southeastern US, Atmos. Chem. Phys., 18, 357–370, https://doi.org/10.5194/acp-18-357-2018, 2018.
Pye, H. O. T., D'Ambro, E. L., Lee, B. H., Schobesberger, S., Takeuchi, M.,
Zhao, Y., Lopez-Hilfiker, F., Liu, J., Shilling, J. E., Xing, J., Mathur, R.,
Middlebrook, A. M., Liao, J., Welti, A., Graus, M., Warneke, C., de
Gouw, J. A., Holloway, J. S., Ryerson, T. B., Pollack, I. B., and
Thornton, J. A.: Anthropogenic enhancements to production of highly oxygenated
molecules from autoxidation, P. Natl. Acad. Sci. USA, 116, 6641–6646, https://doi.org/10.1073/pnas.1810774116, 2019.
Rasmussen, D. J., Fiore, A. M., Naik, V., Horowitz, L. W., McGinnis, S. J., and Schultz, M. G.: Surface ozone-temperature relationships in the eastern US: A monthly climatology for evaluating chemistry-climate models, Atmos. Environ., 47, 142–153, https://doi.org/10.1016/j.atmosenv.2011.11.021, 2012.
Russell, M., Hakami, A., Makar, P. A., Akingunola, A., Zhang, J., Moran, M. D., and Zheng, Q.: An evaluation of the efficacy of very high resolution air-quality modelling over the Athabasca oil sands region, Alberta, Canada, Atmos. Chem. Phys., 19, 4393–4417, https://doi.org/10.5194/acp-19-4393-2019, 2019.
Ryan, W. F.: The air quality forecast rote: Recent changes and future challenges, J. Air Waste Manage., 66, 576–596, https://doi.org/10.1080/10962247.2016.1151469, 2016.
Sarwar, G., Fahey, K., Napelenok, S., Roselle, S., and Mathur, R.: Examining
the impact of CMAQ model updates on aerosol sulfate predictions, in: the 10th Annual CMAS Models-3 User's Conference, Chapel Hill, NC, October 2011, 2011.
Sarwar, G., Simon, H., Bhave, P., and Yarwood, G.: Examining the impact of heterogeneous nitryl chloride production on air quality across the United States, Atmos. Chem. Phys., 12, 6455–6473, https://doi.org/10.5194/acp-12-6455-2012, 2012.
Sarwar, G., Gantt, B., Schwede, D., Foley, K., Mathur, R., and Saiz-Lopez, A.: Impact of Enhanced Ozone Deposition and Halogen Chemistry on Tropospheric Ozone over the Northern Hemisphere, Environ. Sci. Technol., 49, 9203–9211, https://doi.org/10.1021/acs.est.5b01657, 2015.
Schwede, D., Pouliot, G., and Pierce, T.: Changes to the Biogenic Emissions
Inventory System Version 3 (BEIS3), available at:
https://www.cmascenter.org/conference/2005/abstracts/2_7.pdf (last access: 28 June 2020), 2005.
Shen, L., Mickley, L. J., and Gilleland, E.: Impact of increasing
heat waves on U.S. ozone episodes in the 2050s: Results from a multimodel analysis using extreme value theory, Geophys. Res. Lett., 43, 4017–4025, https://doi.org/10.1002/2016GL068432, 2016.
Sillman, S.: The relation between ozone, NOx and hydrocarbons in urban and polluted rural environments, Atmos. Environ., 33, 1821–1845, https://doi.org/10.1016/S1352-2310(98)00345-8, 1999.
Sillman, S. and Samson, P. J.: Impact of temperature on oxidant photochemistry in urban polluted rural and remote environments, J. Geophys. Res., 100, 11497–11508, https://doi.org/10.1029/94jd02146, 1995.
Simon, H. and Bhave, P. V.: Simulating the degree of oxidation in atmospheric
organic particles, Environ. Sci. Technol., 46, 331–339.
https://doi.org/10.1021/es202361w, 2012.
Spiridonov, V., Jakimovski, B., Spiridonova, I., and Pereira, G.: Development
of air quality forecasting system in Macedonia, based on WRF-Chem model, Air
Qual. Atmos. Hlth., 12, 825–836, https://doi.org/10.1007/s11869-019-00698-5,
2019.
Stajner, I., Davidson, P., Byun, D., McQueen, J., Draxler, R., Dickerson, P., and Meagher, J.: US National Air Quality Forecast Capability: Expanding Coverage to Include Particulate Matter, in: Air Pollution Modeling and its Application XXI, Springer, Dordrecht, 379–384, 2011.
Stein, A. F., Lamb, D., and Draxler, R. R.: Incorporation of detailed chemistry into a three-dimensional Lagrangian-Eulerian hybrid model: Application to regional tropospheric ozone, Atmos. Environ., 34, 4361–4372, https://doi.org/10.1016/S1352-2310(00)00204-1, 2000.
Stortini, M., Arvani, B., and Deserti, M.: Operational forecast and daily assessment of the air quality in Italy: A copernicus-CAMS downstream service, Atmosphere-Basel, 11, 447, https://doi.org/10.3390/ATMOS11050447, 2020.
Struzewska, J., Kaminski, J. W., and Jefimow, M.: Application of model output statistics to the GEM-AQ high resolution air quality forecast, Atmos. Res., 181, 186–199, https://doi.org/10.1016/j.atmosres.2016.06.012, 2016.
Tang, Y., Chai, T., Pan, L., Lee, P., Tong, D., Kim, H.-C., and Chen, W.: Using optimal interpolation to assimilate surface measurements and satellite AOD for ozone and PM2.5: A case study for July 2011, J. Air Waste Manage., 65, 1206–1216, https://doi.org/10.1080/10962247.2015.1062439, 2015.
Tang, Y., Pagowski, M., Chai, T., Pan, L., Lee, P., Baker, B., Kumar, R., Delle Monache, L., Tong, D., and Kim, H.-C.: A case study of aerosol data assimilation with the Community Multi-scale Air Quality Model over the contiguous United States using 3D-Var and optimal interpolation methods, Geosci. Model Dev., 10, 4743–4758, https://doi.org/10.5194/gmd-10-4743-2017, 2017.
Taylor, K. E.: Summarizing multiple aspects of model performance in a single diagram, J. Geophys. Res.-Atmos., 106, 7183–7192, https://doi.org/10.1029/2000JD900719, 2001.
Tegtmeier, S., Ziska, F., Pisso, I., Quack, B., Velders, G. J. M., Yang, X., and Krüger, K.: Oceanic bromoform emissions weighted by their ozone depletion potential, Atmos. Chem. Phys., 15, 13647–13663, https://doi.org/10.5194/acp-15-13647-2015, 2015.
United States Environmental Protection Agency: CMAQv5.0.2 (Version 5.0.2), Zenodo, https://doi.org/10.5281/zenodo.1079898, 2014.
United States Environmental Protection Agency: Air Quality System Data Mart [internet database], available at: https://www.epa.gov/airdata, last access: 2 June 2020a.
United States Environmental Protection Agency: Clean Air Markets Division Clean Air Status and Trends Network (CASTNET), available at: https://www.epa.gov/castnet, last access: 10 March 2020b.
Wang, K., Yahya, K., Zhang, Y., Hogrefe, C., Pouliot, G., Knote, C., Hodzic, A., San Jose, R., Perez, J. L., Jiménez-Guerrero, P., Baro, R., Makar, P., and Bennartz, R.: A multi-model assessment for the 2006 and 2010 simulations under the Air Quality Model Evaluation International Initiative (AQMEII) Phase 2 over North America: Part II. Evaluation of column variable predictions using satellite data, Atmos. Environ., 115, 587–603, https://doi.org/10.1016/j.atmosenv.2014.07.044, 2015.
Watanabe, K.: Measurements of ozone concentrations on a commercial vessel in the marine boundary layer over the northern North Pacific Ocean, J. Geophys. Res., 110, D11310, https://doi.org/10.1029/2004JD005514, 2005.
Wu, Z., Schwede, D. B., Vet, R., Walker, J. T., Shaw, M., Staebler, R., and Zhang, L.: Evaluation and Intercomparison of Five North American Dry Deposition Algorithms at a Mixed Forest Site, J. Adv. Model. Earth Sy., 10, 1571–1586, https://doi.org/10.1029/2017MS001231, 2018.
Xu, L., Pye, H. O. T., He, J., Chen, Y., Murphy, B. N., and Ng, N. L.: Experimental and model estimates of the contributions from biogenic monoterpenes and sesquiterpenes to secondary organic aerosol in the southeastern United States, Atmos. Chem. Phys., 18, 12613–12637, https://doi.org/10.5194/acp-18-12613-2018, 2018.
Yang, F.: GDAS/GFS V15.0.0 Upgrades for Q2FY2019, available at: https://www.emc.ncep.noaa.gov/users/Alicia.Bentley/fv3gfs/updates/EMC_CCB_FV3GFS_9-24-18.pdf (last access: 22 May 2020), 2019.
Yang, X., Blechschmidt, A.-M., Bognar, K., McClure-Begley, A., Morris, S., Petropavlovskikh, I., Richter, A., Skov, H., Strong, K., Tarasick, D. W., Uttal, T., Vestenius, M., and Zhao, X.: Pan-Arctic surface ozone: modelling vs. measurements, Atmos. Chem. Phys., 20, 15937–15967, https://doi.org/10.5194/acp-20-15937-2020, 2020.
Yarwood, G., Rao, S., Yocke, M., and Whitten, G.: Updates to the Carbon Bond Chemical Mechanism: CB05. Final Report to the US EPA, RT-0400675. Yocke and Company, Novato, CA, 2005.
Yarwood, G., Whitten, G. Z., Jung, J., Heo, G., and Allen, D. T.: Development, evaluation and testing of version 6 of the Carbon Bond chemical mechanism (CB6), Final report to the Texas Commission on Environmental Quality, Work Order No. 582-7-84005-FY10-26, 2010.
Žabkar, R., Honzak, L., Skok, G., Forkel, R., Rakovec, J., Ceglar, A., and Žagar, N.: Evaluation of the high resolution WRF-Chem (v3.4.1) air quality forecast and its comparison with statistical ozone predictions, Geosci. Model Dev., 8, 2119–2137, https://doi.org/10.5194/gmd-8-2119-2015, 2015.
Zhang, C., Xue, M., Supinie, T. A., Kong, F., Snook, N., Thomas, K. W., Brewster, K., Jung, Y., Harris, L. M., and Lin, S.: How Well Does an FV3-Based Model Predict Precipitation at a Convection-Allowing Resolution? Results From CAPS Forecasts for the 2018 NOAA Hazardous Weather Test Bed With Different Physics Combinations, Geophys. Res. Lett., 46, 3523–3531, https://doi.org/10.1029/2018GL081702, 2019.
Zhang, X., Kondragunta, S., Da Silva, A., Lu, S., Ding, H., Li, F., and
Zhu, Y.: The Blended Global Biomass Burning Emissions Product from MODIS and
VIIRS Observations (GBBEPx), available at:
https://www.ospo.noaa.gov/Products/land/gbbepx/docs/GBBEPx_ATBD.pdf
(last access: 28 June 2020), 2019.
Zhang, Y., Liu, P., Pun, B., and Seigneur, C.: A comprehensive performance evaluation of MM5-CMAQ for the Summer 1999 Southern Oxidants Study episode – Part I: Evaluation protocols, databases, and meteorological predictions, Atmos. Environ., 40, 4825–4838, https://doi.org/10.1016/j.atmosenv.2005.12.043, 2006.
Zhang, Y., Vijayaraghavan, K., Wen, X.-Y., Snell, H. E., and Jacobson, M. Z.: Probing into regional ozone and particulate matter pollution in the United States: 1. A 1 year CMAQ simulation and evaluation using surface and satellite data, J. Geophys. Res., 114, D22304, https://doi.org/10.1029/2009JD011898, 2009.
Zhang, Y., Bocquet, M., Mallet, V., Seigneur, C., and Baklanov, A.: Real-time air quality forecasting, part I: History, techniques, and current status, Atmos. Environ., 60, 632–655, https://doi.org/10.1016/j.atmosenv.2012.06.031, 2012a.
Zhang, Y., Bocquet, M., Mallet, V., Seigneur, C., and Baklanov, A.: Real-time air quality forecasting, Part II: State of the science, current research needs, and future prospects, Atmos. Environ., 60, 656–676, https://doi.org/10.1016/j.atmosenv.2012.02.041, 2012b.
Zhang, Y., Hong, C., Yahya, K., Li, Q., Zhang, Q., and He, K.: Comprehensive evaluation of multi-year real-time air quality forecasting using an online-coupled meteorology-chemistry model over southeastern United States, Atmos. Environ., 138, 162–182, https://doi.org/10.1016/j.atmosenv.2016.05.006, 2016.
Zhang, Y., Jena, C., Wang, K., Paton-Walsh, C., Guérette, É.-A., Utembe, S., Silver, J. D., and Keywood, and M.: Multiscale Applications of Two Online-Coupled Meteorology-Chemistry Models during Recent Field Campaigns in Australia, Part I: Model Description and WRF/Chem-ROMS Evaluation Using Surface and Satellite Data and Sensitivity to Spatial Grid Resolutions, Atmosphere-Basel, 10, 189, https://doi.org/10.3390/atmos10040189, 2019a.
Zhang, Y., Wang, K., Jena, C., Paton-Walsh, C., Guérette, É. A., Utembe, S., Silver, J. D., and Keywood, M.: Multiscale applications of two online-coupled meteorology-chemistry models during recent field campaigns in Australia, Part II: Comparison of WRF/Chem and WRF/Chem-ROMS and impacts of air-sea interactions and boundary conditions, Atmosphere-Basel, 10, 210, https://doi.org/10.3390/ATMOS10040210, 2019b.
Zhou, G., Xu, J., Xie, Y., Chang, L., Gao, W., Gu, Y., and Zhou, J.: Numerical air quality forecasting over eastern China: An operational application of WRF-Chem, Atmos. Environ., 153, 94–108, https://doi.org/10.1016/j.atmosenv.2017.01.020, 2017.
Zhu, Y. and Luo, Y.: Precipitation Calibration Based on the Frequency-Matching Method, Weather Forecast., 30, 1109–1124, https://doi.org/10.1175/WAF-D-13-00049.1, 2015.
Short summary
The continuously updated National Air Quality Forecast Capability (NAQFC) provides air quality forecasts. To support the development of the next-generation NAQFC, we evaluate a prototype of GFSv15-CMAQv5.0.2. The performance and the potential improvements for the system are discussed. This study can provide a scientific basis for further development of NAQFC and help it to provide more accurate air quality forecasts to the public over the contiguous United States.
The continuously updated National Air Quality Forecast Capability (NAQFC) provides air quality...