Articles | Volume 15, issue 7
https://doi.org/10.5194/gmd-15-2773-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-2773-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
06 Apr 2022
Development and technical paper |
| 06 Apr 2022
| 06 Apr 2022
Implementation of an ensemble Kalman filter in the Community Multiscale Air Quality model (CMAQ model v5.1) for data assimilation of ground-level PM2.5
Soon-Young Park
School of Earth Sciences and Environmental Engineering, Gwangju
Institute of Science and Technology (GIST), Gwangju, 61005, Republic of
Korea
Institute of Environmental Studies, Pusan National University, Busan,
46241, Republic of Korea
Uzzal Kumar Dash
School of Earth Sciences and Environmental Engineering, Gwangju
Institute of Science and Technology (GIST), Gwangju, 61005, Republic of
Korea
Jinhyeok Yu
School of Earth Sciences and Environmental Engineering, Gwangju
Institute of Science and Technology (GIST), Gwangju, 61005, Republic of
Korea
Keiya Yumimoto
Research Institute for Applied Mechanics, Kyushu University, Fukuoka,
816-8580, Japan
Itsushi Uno
Research Institute for Applied Mechanics, Kyushu University, Fukuoka,
816-8580, Japan
Chul Han Song
CORRESPONDING AUTHOR
School of Earth Sciences and Environmental Engineering, Gwangju
Institute of Science and Technology (GIST), Gwangju, 61005, Republic of
Korea
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Despite the crucial role of halogen radicals in the atmosphere, current chemical transport models (CTMs) do not account for multi-phase halogen processes. To address this issue, we incorporated 177 halogen reactions, together with anthropogenic and natural halogen emissions into the CTMs. Our findings reveal that incorporation of these halogen processes significantly improves model performances compared to observations. In addition, we emphasize the influence of halogen radicals on air quality.
Kiyeon Kim, Kyung Man Han, Chul Han Song, Hyojun Lee, Ross Beardsley, Jinhyeok Yu, Greg Yarwood, Bonyoung Koo, Jasper Madalipay, Jung-Hun Woo, and Seogju Cho
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We incorporated each HONO process into the current CMAQ modeling framework to enhance the accuracy of HONO mixing ratio predictions. These results expand our understanding of HONO photochemistry and identify crucial sources of HONO that impact the total HONO budget in Seoul, South Korea. Through this investigation, we contribute to resolving discrepancies in understanding chemical transport models, with implications for better air quality management and environmental protection in the region.
Peng Xian, Jeffrey S. Reid, Melanie Ades, Angela Benedetti, Peter R. Colarco, Arlindo da Silva, Tom F. Eck, Johannes Flemming, Edward J. Hyer, Zak Kipling, Samuel Rémy, Tsuyoshi Thomas Sekiyama, Taichu Tanaka, Keiya Yumimoto, and Jianglong Zhang
Atmos. Chem. Phys., 24, 6385–6411, https://doi.org/10.5194/acp-24-6385-2024, https://doi.org/10.5194/acp-24-6385-2024, 2024
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The study compares and evaluates monthly AOD of four reanalyses (RA) and their consensus (i.e., ensemble mean). The basic verification characteristics of these RA versus both AERONET and MODIS retrievals are presented. The study discusses the strength of each RA and identifies regions where divergence and challenges are prominent. The RA consensus usually performs very well on a global scale in terms of how well it matches the observational data, making it a good choice for various applications.
Bok H. Baek, Rizzieri Pedruzzi, Minwoo Park, Chi-Tsan Wang, Younha Kim, Chul-Han Song, and Jung-Hun Woo
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The Comprehensive Automobile Research System (CARS) is an open-source Python-based automobile emissions inventory model designed to efficiently estimate high-quality emissions. The CARS is designed to utilize the local vehicle activity database, such as vehicle travel distance, road-link-level network information, and vehicle-specific average speed by road type, to generate a temporally and spatially enhanced inventory for policymakers, stakeholders, and the air quality modeling community.
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Geosci. Model Dev., 14, 2235–2264, https://doi.org/10.5194/gmd-14-2235-2021, https://doi.org/10.5194/gmd-14-2235-2021, 2021
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This study compares performance of aerosol representation methods of the Japan Meteorological Agency's regional-scale nonhydrostatic meteorology–chemistry model (NHM-Chem). It indicates separate treatment of sea salt and dust in coarse mode and that of light-absorptive and non-absorptive particles in fine mode could provide accurate assessments on aerosol feedback processes.
Mayumi Yoshida, Keiya Yumimoto, Takashi M. Nagao, Taichu Y. Tanaka, Maki Kikuchi, and Hiroshi Murakami
Atmos. Chem. Phys., 21, 1797–1813, https://doi.org/10.5194/acp-21-1797-2021, https://doi.org/10.5194/acp-21-1797-2021, 2021
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We developed a new aerosol satellite retrieval algorithm combining a numerical aerosol forecast. This is the first study that utilizes the assimilated model forecast of aerosol as an a priori estimate of the retrieval. Aerosol retrievals were improved by effectively incorporating both model and satellite information. By using the assimilated forecast as an a priori estimate, information from previous observations can be propagated to future retrievals, thus leading to better retrieval accuracy.
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Short summary
An EnKF was applied to CMAQ for assimilating ground PM2.5 observations from China and South Korea. The EnKF performed better than that without assimilation and even superior to 3D-Var. The reduced MBs in 24 h predictions were 48 % and 27 % by improving ICs and BCs, respectively.
An EnKF was applied to CMAQ for assimilating ground PM2.5 observations from China and South...
