Articles | Volume 16, issue 22
https://doi.org/10.5194/gmd-16-6757-2023
© Author(s) 2023. 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-16-6757-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model experiment description paper
| 
22 Nov 2023
Model experiment description paper |
| 22 Nov 2023
| 22 Nov 2023
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
Zhongwei Luo
State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
Yan Han
State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
Research Center for Atmospheric Environment, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China
Kun Hua
State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
Yufen Zhang
CORRESPONDING AUTHOR
State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
Jianhui Wu
State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
Xiaohui Bi
State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
Baoshuang Liu
State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
Yang Chen
Research Center for Atmospheric Environment, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China
Xin Long
Research Center for Atmospheric Environment, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China
State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
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Haoqi Wang, Xiao Tian, Wanting Zhao, Jiacheng Li, Haoyu Yu, Yinchang Feng, and Shaojie Song
Atmos. Chem. Phys., 24, 6583–6592, https://doi.org/10.5194/acp-24-6583-2024, https://doi.org/10.5194/acp-24-6583-2024, 2024
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pH is a key property of ambient aerosols, which affect many atmospheric processes. As aerosol pH is a non-conservative parameter, diverse averaging metrics and temporal resolutions may influence the pH values calculated by thermodynamic models. This technical note seeks to quantitatively evaluate the average pH using varied metrics and resolutions. The ultimate goal is to establish standardized reporting practices in future research endeavors.
Baoshuang Liu, Yao Gu, Yutong Wu, Qili Dai, Shaojie Song, Yinchang Feng, and Philip K. Hopke
EGUsphere, https://doi.org/10.5194/egusphere-2024-916, https://doi.org/10.5194/egusphere-2024-916, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Reactive loss of VOCs is a long-term issue yet to be resolved in VOC source analyses. This review assesses the common methods and existing issues of reducing losses, impacts of losses, and sources in current source analyses. We provided a potential supporting role in solving the issues of VOC conversion. Source analyses of consumed VOCs produced by reactions for O3 and secondary organic aerosols can play an important role in effective prevention and control of atmospheric secondary pollution.
Chen He, Hanxiong Che, Zier Bao, Yiliang Liu, Qing Li, Miao Hu, Jiawei Zhou, Shumin Zhang, Xiaojiang Yao, Quan Shi, Chunmao Chen, Yan Han, Lingshuo Meng, Xin Long, Fumo Yang, and Yang Chen
Atmos. Chem. Phys., 24, 1627–1639, https://doi.org/10.5194/acp-24-1627-2024, https://doi.org/10.5194/acp-24-1627-2024, 2024
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We examined the daily evolution of high molecular-weight organic compounds with a molecular weight of up to 1000 Da in order to comprehend their behaviors in the atmosphere under actual conditions. These compounds were proven to undergo multi-generation oxidation, carboxylation, and nitrification via both day- and nighttime chemistry.
Taomou Zong, Zhijun Wu, Junrui Wang, Kai Bi, Wenxu Fang, Yanrong Yang, Xuena Yu, Zhier Bao, Xiangxinyue Meng, Yuheng Zhang, Song Guo, Yang Chen, Chunshan Liu, Yue Zhang, Shao-Meng Li, and Min Hu
Atmos. Meas. Tech., 16, 3679–3692, https://doi.org/10.5194/amt-16-3679-2023, https://doi.org/10.5194/amt-16-3679-2023, 2023
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This study developed and characterized an indoor chamber system (AIR) to simulate atmospheric multiphase chemistry processes. The AIR chamber can accurately control temperature and relative humidity (RH) over a broad range and simulate diurnal variation of ambient atmospheric RH. The aerosol generation unit can generate organic-coating seed particles with different phase states. The AIR chamber demonstrates high-quality performance in simulating secondary aerosol formation.
Zhier Bao, Xinyi Zhang, Qing Li, Jiawei Zhou, Guangming Shi, Li Zhou, Fumo Yang, Shaodong Xie, Dan Zhang, Chongzhi Zhai, Zhenliang Li, Chao Peng, and Yang Chen
Atmos. Chem. Phys., 23, 1147–1167, https://doi.org/10.5194/acp-23-1147-2023, https://doi.org/10.5194/acp-23-1147-2023, 2023
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We characterised non-refractory fine particulate matter (PM2.5) during winter in the Sichuan Basin (SCB), Southwest China. The factors driving severe aerosol pollution were revealed, highlighting the importance of rapid nitrate formation and intensive biomass burning. Nitrate was primarily formed through gas-phase oxidation during daytime and aqueous-phase oxidation during nighttime. Controlling nitrate and biomass burning will benefit the mitigation of haze formation in the SCB.
Baoshuang Liu, Yanyang Wang, He Meng, Qili Dai, Liuli Diao, Jianhui Wu, Laiyuan Shi, Jing Wang, Yufen Zhang, and Yinchang Feng
Atmos. Chem. Phys., 22, 8597–8615, https://doi.org/10.5194/acp-22-8597-2022, https://doi.org/10.5194/acp-22-8597-2022, 2022
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Understanding effectiveness of air pollution regulatory measures is critical for control policy. Machine learning and dispersion-normalized approaches were applied to decouple meteorologically deduced variations in Qingdao, China. Most pollutant concentrations decreased substantially after the Clean Air Action Plan. The largest emission reduction was from coal combustion and steel-related smelting. Qingdao is at risk of increased emissions from increased vehicular population and ozone pollution.
Xinyao Feng, Yingze Tian, Qianqian Xue, Danlin Song, Fengxia Huang, and Yinchang Feng
Atmos. Chem. Phys., 21, 16219–16235, https://doi.org/10.5194/acp-21-16219-2021, https://doi.org/10.5194/acp-21-16219-2021, 2021
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This study focused on PM2.5 compositions and sources and explored their spatiotemporal and policy-related variations based on observation at 19 sites during wintertime of 2015–2019 in a fast-developing megacity. We found that PM2.5 compositions for the outermost zone in 2019 were similar to those for the core zone 2 or 3 years ago. Percentage contributions of coal and biomass combustion dramatically declined in the core zone, while the traffic source showed an increasing trend.
Wei Yuan, Ru-Jin Huang, Lu Yang, Ting Wang, Jing Duan, Jie Guo, Haiyan Ni, Yang Chen, Qi Chen, Yongjie Li, Ulrike Dusek, Colin O'Dowd, and Thorsten Hoffmann
Atmos. Chem. Phys., 21, 3685–3697, https://doi.org/10.5194/acp-21-3685-2021, https://doi.org/10.5194/acp-21-3685-2021, 2021
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We characterized the seasonal variations in nitrated aromatic compounds (NACs) in composition, sources, and their light absorption contribution to brown carbon (BrC) aerosol in Xi'an, Northwest China. Our results show that secondary formation and vehicular emission were dominant sources in summer (~80 %), and biomass burning and coal combustion were major sources in winter (~75 %), and they indicate that the composition and sources of NACs have a profound impact on the light absorption of BrC
Qiyuan Wang, Li Li, Jiamao Zhou, Jianhuai Ye, Wenting Dai, Huikun Liu, Yong Zhang, Renjian Zhang, Jie Tian, Yang Chen, Yunfei Wu, Weikang Ran, and Junji Cao
Atmos. Chem. Phys., 20, 15427–15442, https://doi.org/10.5194/acp-20-15427-2020, https://doi.org/10.5194/acp-20-15427-2020, 2020
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Recently, China has promulgated a series of regulations to reduce air pollutants. The decreased black carbon (BC) and co-emitted pollutants could affect the interactions between BC and other aerosols, which in turn results in changes in BC. Herein, we re-assessed the characteristics of BC of a representative pollution site in northern China in the final year of the Chinese
Action Plan for the Prevention and Control of Air Pollution.
Jingsha Xu, Shaojie Song, Roy M. Harrison, Congbo Song, Lianfang Wei, Qiang Zhang, Yele Sun, Lu Lei, Chao Zhang, Xiaohong Yao, Dihui Chen, Weijun Li, Miaomiao Wu, Hezhong Tian, Lining Luo, Shengrui Tong, Weiran Li, Junling Wang, Guoliang Shi, Yanqi Huangfu, Yingze Tian, Baozhu Ge, Shaoli Su, Chao Peng, Yang Chen, Fumo Yang, Aleksandra Mihajlidi-Zelić, Dragana Đorđević, Stefan J. Swift, Imogen Andrews, Jacqueline F. Hamilton, Ye Sun, Agung Kramawijaya, Jinxiu Han, Supattarachai Saksakulkrai, Clarissa Baldo, Siqi Hou, Feixue Zheng, Kaspar R. Daellenbach, Chao Yan, Yongchun Liu, Markku Kulmala, Pingqing Fu, and Zongbo Shi
Atmos. Meas. Tech., 13, 6325–6341, https://doi.org/10.5194/amt-13-6325-2020, https://doi.org/10.5194/amt-13-6325-2020, 2020
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An interlaboratory comparison was conducted for the first time to examine differences in water-soluble inorganic ions (WSIIs) measured by 10 labs using ion chromatography (IC) and by two online aerosol chemical speciation monitor (ACSM) methods. Major ions including SO42−, NO3− and NH4+ agreed well in 10 IC labs and correlated well with ACSM data. WSII interlab variability strongly affected aerosol acidity results based on ion balance, but aerosol pH computed by ISORROPIA II was very similar.
Yingze Tian, Yinchang Feng, Yongli Liang, Yixuan Li, Qianqian Xue, Zongbo Shi, Jingsha Xu, and Roy M. Harrison
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-507, https://doi.org/10.5194/acp-2020-507, 2020
Revised manuscript not accepted
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Size distributions of inorganic and organic components in particulate matter (PM) can provide critical information on sources and pollution processes. Ions, elements, carbon fractions, n-alkanes, PAHs, hopanes and steranes in size-resolved PM were analyzed during one year in a northern Chinese megacity. Results reveal that size distributions of inorganic and organic aerosol components are dependent on seasons and pollution levels as a result of differing sources and physicochemical processes.
Yang Chen, Jing Cai, Zhichao Wang, Chao Peng, Xiaojiang Yao, Mi Tian, Yiqun Han, Guangming Shi, Zongbo Shi, Yue Liu, Xi Yang, Mei Zheng, Tong Zhu, Kebin He, Qiang Zhang, and Fumo Yang
Atmos. Chem. Phys., 20, 9231–9247, https://doi.org/10.5194/acp-20-9231-2020, https://doi.org/10.5194/acp-20-9231-2020, 2020
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Patterns of particle transport, accumulation, and evolution in both urban and rural areas of Beijing are investigated. The two sites shared 17 common particle types in different stages of atmospheric processing.
Yang Chen, Guangming Shi, Jing Cai, Zongbo Shi, Zhichao Wang, Xiaojiang Yao, Mi Tian, Chao Peng, Yiqun Han, Tong Zhu, Yue Liu, Xi Yang, Mei Zheng, Fumo Yang, Qiang Zhang, and Kebin He
Atmos. Chem. Phys., 20, 9249–9263, https://doi.org/10.5194/acp-20-9249-2020, https://doi.org/10.5194/acp-20-9249-2020, 2020
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Individual particles were observed in two field studies during winter 2016 in the urban and rural areas of Beijing. An online single-particle chemical composition analysis was used as a tracing system to investigate the impact of heating activities and the formation of haze events. During the pollution events, a pattern of transport and accumulation was found with evidence of single particles. The transport from Pinggu to Peking University was significant but PKU to PG occurred occasionally.
Ru-Jin Huang, Yao He, Jing Duan, Yongjie Li, Qi Chen, Yan Zheng, Yang Chen, Weiwei Hu, Chunshui Lin, Haiyan Ni, Wenting Dai, Junji Cao, Yunfei Wu, Renjian Zhang, Wei Xu, Jurgita Ovadnevaite, Darius Ceburnis, Thorsten Hoffmann, and Colin D. O'Dowd
Atmos. Chem. Phys., 20, 9101–9114, https://doi.org/10.5194/acp-20-9101-2020, https://doi.org/10.5194/acp-20-9101-2020, 2020
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We systematically compared the submicron particle (PM1) processes in haze days with low and high relative humidity (RH) in wintertime Beijing. Nitrate had similar daytime growth rates in low-RH and high-RH pollution. OOA had a higher growth rate in low-RH pollution than in high-RH pollution. Sulfate had a decreasing trend in low-RH pollution, while it increased significantly in high-RH pollution. This distinction may be explained by the different processes affected by meteorological conditions.
Wei Yuan, Ru-Jin Huang, Lu Yang, Jie Guo, Ziyi Chen, Jing Duan, Ting Wang, Haiyan Ni, Yongming Han, Yongjie Li, Qi Chen, Yang Chen, Thorsten Hoffmann, and Colin O'Dowd
Atmos. Chem. Phys., 20, 5129–5144, https://doi.org/10.5194/acp-20-5129-2020, https://doi.org/10.5194/acp-20-5129-2020, 2020
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We characterized light-absorbing properties, chromophore composition and sources of brown carbon (BrC) in Xi'an; identified three groups of light-absorbing organics; and quantified their contribution to overall BrC absorption. Our results showed that vehicle emissions and secondary formation are major sources of BrC in spring, coal combustion and vehicle emissions are major sources in fall, biomass burning and coal combustion become major sources in winter, and secondary BrC dominates in summer.
Jing Duan, Ru-Jin Huang, Yongjie Li, Qi Chen, Yan Zheng, Yang Chen, Chunshui Lin, Haiyan Ni, Meng Wang, Jurgita Ovadnevaite, Darius Ceburnis, Chunying Chen, Douglas R. Worsnop, Thorsten Hoffmann, Colin O'Dowd, and Junji Cao
Atmos. Chem. Phys., 20, 3793–3807, https://doi.org/10.5194/acp-20-3793-2020, https://doi.org/10.5194/acp-20-3793-2020, 2020
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We characterized secondary aerosol formation in Beijing. Our results showed that relative humidity (RH) and Ox have opposite effects on sulfate and nitrate formation in summer and winter. The wintertime more-oxidized OOA (MO-OOA) showed a good correlation with aerosol liquid water content (ALWC). Meanwhile, the dependence of less-oxidized OOA (LO-OOA) and the mass ratio of LO-OOA to MO-OOA in Ox both degraded when RH > 60 %, suggesting that RH or ALWC may also affect LO-OOA formation.
Meng Wang, Ru-Jin Huang, Junji Cao, Wenting Dai, Jiamao Zhou, Chunshui Lin, Haiyan Ni, Jing Duan, Ting Wang, Yang Chen, Yongjie Li, Qi Chen, Imad El Haddad, and Thorsten Hoffmann
Atmos. Meas. Tech., 12, 4779–4789, https://doi.org/10.5194/amt-12-4779-2019, https://doi.org/10.5194/amt-12-4779-2019, 2019
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The analytical performances of SE-GC-MS and TD-GC-MS for the determination of n-alkanes, PAHs and hopanes were evaluated and compared. The two methods show a good agreement with a high correlation efficient (R2 > 0.98) and a slope close to unity. The concentrations of n-alkanes, PAHs and hopanes are found to be much higher in Beijing than those in Chengdu, Shanghai and Guangzhou, most likely due to emissions from coal combustion for wintertime heating in Beijing.
Ruihe Lyu, Zongbo Shi, Mohammed Salim Alam, Xuefang Wu, Di Liu, Tuan V. Vu, Christopher Stark, Pingqing Fu, Yinchang Feng, and Roy M. Harrison
Atmos. Chem. Phys., 19, 10865–10881, https://doi.org/10.5194/acp-19-10865-2019, https://doi.org/10.5194/acp-19-10865-2019, 2019
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Severe pollution of the Beijing atmosphere is a frequent occurrence. The airborne particles which characterize the episodes of haze contain a wide range of chemical constituents but organic compounds make up a substantial proportion. In this study individual compounds are analysed under both haze and non-haze conditions, and the measurements are compared with samples collected in London, where the air pollution climate and sources are very different.
Jing Duan, Ru-Jin Huang, Chunshui Lin, Wenting Dai, Meng Wang, Yifang Gu, Ying Wang, Haobin Zhong, Yan Zheng, Haiyan Ni, Uli Dusek, Yang Chen, Yongjie Li, Qi Chen, Douglas R. Worsnop, Colin D. O'Dowd, and Junji Cao
Atmos. Chem. Phys., 19, 10319–10334, https://doi.org/10.5194/acp-19-10319-2019, https://doi.org/10.5194/acp-19-10319-2019, 2019
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We present the seasonal distinction of secondary aerosol formation in urban Beijing. Both photochemical oxidation and aqueous-phase processing played important roles in SOA (secondary organic aerosol) formation during all three seasons; while for sulfate formation, gas-phase photochemical oxidation was the major pathway in late summer, aqueous-phase reactions were more responsible during early winter, and both processes had contributions during autumn.
Qili Dai, Benjamin C. Schulze, Xiaohui Bi, Alexander A. T. Bui, Fangzhou Guo, Henry W. Wallace, Nancy P. Sanchez, James H. Flynn, Barry L. Lefer, Yinchang Feng, and Robert J. Griffin
Atmos. Chem. Phys., 19, 9641–9661, https://doi.org/10.5194/acp-19-9641-2019, https://doi.org/10.5194/acp-19-9641-2019, 2019
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The formation processes of secondary organic aerosol remain to be fully understood. We reported the measurement data from two field campaigns within Houston, TX, to investigate the effects of aqueous-phase chemistry and photochemistry in processing oxygenated organic aerosol (OOA) in winter and summer. Both photochemistry and aqueous-phase processing appear to facilitate more-oxidized OOA formation. The processing mechanism of less-oxidized OOA apparently depended on relative humidity.
Jing Ding, Pusheng Zhao, Jie Su, Qun Dong, Xiang Du, and Yufen Zhang
Atmos. Chem. Phys., 19, 7939–7954, https://doi.org/10.5194/acp-19-7939-2019, https://doi.org/10.5194/acp-19-7939-2019, 2019
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Aerosol acidity plays a key role in secondary aerosol formation. To provide a more comprehensive reference for aerosol pH and a basis for controlling secondary aerosol generation, this study used the latest data covering four seasons and different particle sizes to obtain the characteristics of aerosol pH and explore the main factors affecting aerosol pH and gas–particle partitioning in the Beijing area.
Zongbo Shi, Tuan Vu, Simone Kotthaus, Roy M. Harrison, Sue Grimmond, Siyao Yue, Tong Zhu, James Lee, Yiqun Han, Matthias Demuzere, Rachel E. Dunmore, Lujie Ren, Di Liu, Yuanlin Wang, Oliver Wild, James Allan, W. Joe Acton, Janet Barlow, Benjamin Barratt, David Beddows, William J. Bloss, Giulia Calzolai, David Carruthers, David C. Carslaw, Queenie Chan, Lia Chatzidiakou, Yang Chen, Leigh Crilley, Hugh Coe, Tie Dai, Ruth Doherty, Fengkui Duan, Pingqing Fu, Baozhu Ge, Maofa Ge, Daobo Guan, Jacqueline F. Hamilton, Kebin He, Mathew Heal, Dwayne Heard, C. Nicholas Hewitt, Michael Hollaway, Min Hu, Dongsheng Ji, Xujiang Jiang, Rod Jones, Markus Kalberer, Frank J. Kelly, Louisa Kramer, Ben Langford, Chun Lin, Alastair C. Lewis, Jie Li, Weijun Li, Huan Liu, Junfeng Liu, Miranda Loh, Keding Lu, Franco Lucarelli, Graham Mann, Gordon McFiggans, Mark R. Miller, Graham Mills, Paul Monk, Eiko Nemitz, Fionna O'Connor, Bin Ouyang, Paul I. Palmer, Carl Percival, Olalekan Popoola, Claire Reeves, Andrew R. Rickard, Longyi Shao, Guangyu Shi, Dominick Spracklen, David Stevenson, Yele Sun, Zhiwei Sun, Shu Tao, Shengrui Tong, Qingqing Wang, Wenhua Wang, Xinming Wang, Xuejun Wang, Zifang Wang, Lianfang Wei, Lisa Whalley, Xuefang Wu, Zhijun Wu, Pinhua Xie, Fumo Yang, Qiang Zhang, Yanli Zhang, Yuanhang Zhang, and Mei Zheng
Atmos. Chem. Phys., 19, 7519–7546, https://doi.org/10.5194/acp-19-7519-2019, https://doi.org/10.5194/acp-19-7519-2019, 2019
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APHH-Beijing is a collaborative international research programme to study the sources, processes and health effects of air pollution in Beijing. This introduction to the special issue provides an overview of (i) the APHH-Beijing programme, (ii) the measurement and modelling activities performed as part of it and (iii) the air quality and meteorological conditions during joint intensive field campaigns as a core activity within APHH-Beijing.
Yang Chen, Mi Tian, Ru-Jin Huang, Guangming Shi, Huanbo Wang, Chao Peng, Junji Cao, Qiyuan Wang, Shumin Zhang, Dongmei Guo, Leiming Zhang, and Fumo Yang
Atmos. Chem. Phys., 19, 3245–3255, https://doi.org/10.5194/acp-19-3245-2019, https://doi.org/10.5194/acp-19-3245-2019, 2019
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Amine-containing particles were characterized in an urban area of Chongqing during both summer and winter using a single-particle aerosol mass spectrometer (SPAMS). Amines were observed to internally mix with elemental carbon (EC), organic carbon (OC), sulfate, and nitrate. Diethylamine (DEA) was the most abundant in both number and peak area among amine-containing particles. Vegetation and traffic were the primary sources of particulate amines.
Xiaohui Bi, Qili Dai, Jianhui Wu, Qing Zhang, Wenhui Zhang, Ruixue Luo, Yuan Cheng, Jiaying Zhang, Lu Wang, Zhuojun Yu, Yufen Zhang, Yingze Tian, and Yinchang Feng
Atmos. Chem. Phys., 19, 3223–3243, https://doi.org/10.5194/acp-19-3223-2019, https://doi.org/10.5194/acp-19-3223-2019, 2019
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Source profiles are of great importance for the application of receptor models in source apportionment studies, as they characterize specific sources from a chemical point of view, revealing the signatures of source emissions. Here, a total of 3326 chemical profiles of the main primary sources across China from 1987 to 2017 are reviewed. The results highlight the urgent need for increased investigation of more specific markers beyond routinely measured components to better discriminate sources.
Ruihe Lyu, Mohammed S. Alam, Christopher Stark, Ruixin Xu, Zongbo Shi, Yinchang Feng, and Roy M. Harrison
Atmos. Chem. Phys., 19, 2233–2246, https://doi.org/10.5194/acp-19-2233-2019, https://doi.org/10.5194/acp-19-2233-2019, 2019
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Organic matter comprises a substantial proportion of the mass of toxic airborne particles which cause poor health and premature death. In this paper, new measurements of three important groups of organic compounds are reported and are analysed to infer their sources and their contributions to airborne particle concentrations.
Qiyuan Wang, Suixin Liu, Nan Li, Wenting Dai, Yunfei Wu, Jie Tian, Yaqing Zhou, Meng Wang, Steven Sai Hang Ho, Yang Chen, Renjian Zhang, Shuyu Zhao, Chongshu Zhu, Yongming Han, Xuexi Tie, and Junji Cao
Atmos. Chem. Phys., 19, 1881–1899, https://doi.org/10.5194/acp-19-1881-2019, https://doi.org/10.5194/acp-19-1881-2019, 2019
Benjamin C. Schulze, Henry W. Wallace, Alexander T. Bui, James H. Flynn, Matt H. Erickson, Sergio Alvarez, Qili Dai, Sascha Usenko, Rebecca J. Sheesley, and Robert J. Griffin
Atmos. Chem. Phys., 18, 14217–14241, https://doi.org/10.5194/acp-18-14217-2018, https://doi.org/10.5194/acp-18-14217-2018, 2018
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Atmospheric field measurements at a coastal site near Houston, TX, were used to investigate the influence of shipping vessel emissions on aerosol mass and composition over the Gulf of Mexico. Results suggest that, despite recent regulations, these vessels still produce a considerable fraction of inorganic and organic aerosol mass in the region. Secondary effects of shipping emissions on organic aerosol composition, such as influences on aerosol aging, were also identified.
Ru-Jin Huang, Junji Cao, Yang Chen, Lu Yang, Jincan Shen, Qihua You, Kai Wang, Chunshui Lin, Wei Xu, Bo Gao, Yongjie Li, Qi Chen, Thorsten Hoffmann, Colin D. O'Dowd, Merete Bilde, and Marianne Glasius
Atmos. Meas. Tech., 11, 3447–3456, https://doi.org/10.5194/amt-11-3447-2018, https://doi.org/10.5194/amt-11-3447-2018, 2018
Congbo Song, Yan Liu, Shida Sun, Luna Sun, Yanjie Zhang, Chao Ma, Jianfei Peng, Qian Li, Jinsheng Zhang, Qili Dai, Baoshuang Liu, Peng Wang, Yi Zhang, Ting Wang, Lin Wu, Min Hu, and Hongjun Mao
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-387, https://doi.org/10.5194/acp-2018-387, 2018
Revised manuscript not accepted
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Vehicular emission is a key contributor to ambient volatile organic compounds (VOCs) and NOx in Chinese megacities. Information on real-world emission factors (EFs) for a typical urban fleet is still limited. We found that improvement of fuel quality can significantly reduce feet-average EFs of VOCs (especially for BTEX). Our study provided implications for O3 control in China from the view of primary emission, and highlighted the importance of further control of evaporative emissions.
Baoshuang Liu, Yuan Cheng, Ming Zhou, Danni Liang, Qili Dai, Lu Wang, Wei Jin, Lingzhi Zhang, Yibin Ren, Jingbo Zhou, Chunling Dai, Jiao Xu, Jiao Wang, Yinchang Feng, and Yufen Zhang
Atmos. Chem. Phys., 18, 7019–7039, https://doi.org/10.5194/acp-18-7019-2018, https://doi.org/10.5194/acp-18-7019-2018, 2018
Xing Peng, Jian Gao, Guoliang Shi, Xurong Shi, Yanqi Huangfu, Jiayuan Liu, Yuechong Zhang, Yinchang Feng, Wei Wang, Ruoyu Ma, Cesunica E. Ivey, and Yi Deng
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-997, https://doi.org/10.5194/acp-2017-997, 2018
Preprint withdrawn
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A finding here is that source emission dominates the level of pollutants and short-term meteorological condition determines the variation of pollutants. Primary source impact levels are mainly influenced by source emissions, and secondary source impact levels are mainly influenced by synoptic scale fluctuations and source emissions. The implications of results are for source apportionment analyses conducted with data from different geographical locations and under various weather conditions.
Huanbo Wang, Mi Tian, Yang Chen, Guangming Shi, Yuan Liu, Fumo Yang, Leiming Zhang, Liqun Deng, Jiayan Yu, Chao Peng, and Xuyao Cao
Atmos. Chem. Phys., 18, 865–881, https://doi.org/10.5194/acp-18-865-2018, https://doi.org/10.5194/acp-18-865-2018, 2018
Mi Tian, Huanbo Wang, Yang Chen, Fumo Yang, Xiaohua Zhang, Qiang Zou, Renquan Zhang, Yongliang Ma, and Kebin He
Atmos. Chem. Phys., 16, 7357–7371, https://doi.org/10.5194/acp-16-7357-2016, https://doi.org/10.5194/acp-16-7357-2016, 2016
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The discussion was based on high time resolution data which could provide detailed insight into short haze periods. The dominant species in PM2.5 and which were responsible for the visibility reduction were identified in Suzhou.
The formation mechanisms of sulfate and nitrate were explored as high secondary aerosol contributions to particulate pollution during haze events. The impact of local and transport sources on the origin of aerosol pollution in Suzhou was discussed.
S. Han, Y. Zhang, J. Wu, X. Zhang, Y. Tian, Y. Wang, J. Ding, W. Yan, X. Bi, G. Shi, Z. Cai, Q. Yao, H. Huang, and Y. Feng
Atmos. Chem. Phys., 15, 11165–11177, https://doi.org/10.5194/acp-15-11165-2015, https://doi.org/10.5194/acp-15-11165-2015, 2015
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It is crucial for studying regional-scale PM pollution and for the development of efficient joint control policy to improve understanding of the regional background PM concentration. Based on the vertical variation periodic characteristics of particle mass concentration, the atmospheric boundary layer structure, as well as the vertical distribution of chemical composition and pollution source apportionment, a method to estimate regional background PM concentration is proposed.
Y. Z. Tian, J. Wang, X. Peng, G. L. Shi, and Y. C. Feng
Atmos. Chem. Phys., 14, 9469–9479, https://doi.org/10.5194/acp-14-9469-2014, https://doi.org/10.5194/acp-14-9469-2014, 2014
Related subject area
Atmospheric sciences
Implementation of a Simple Actuator Disk for Large-Eddy Simulation in the Weather Research and Forecasting Model (WRF-SADLES v1.2) for wind turbine wake simulation
WRF-PDAF v1.0: implementation and application of an online localized ensemble data assimilation framework
Implementation and evaluation of diabatic advection in the Lagrangian transport model MPTRAC 2.6
An improved and extended parameterization of the CO2 15 µm cooling in the middle and upper atmosphere (CO2_cool_fort-1.0)
Development of a multiphase chemical mechanism to improve secondary organic aerosol formation in CAABA/MECCA (version 4.7.0)
Application of regional meteorology and air quality models based on the microprocessor without interlocked piped stages (MIPS) and LoongArch CPU platforms
Investigating ground-level ozone pollution in semi-arid and arid regions of Arizona using WRF-Chem v4.4 modeling
An objective identification technique for potential vorticity structures associated with African easterly waves
Importance of microphysical settings for climate forcing by stratospheric SO2 injections as modeled by SOCOL-AERv2
Assessment of surface ozone products from downscaled CAMS reanalysis and CAMS daily forecast using urban air quality monitoring stations in Iran
Open boundary conditions for atmospheric large-eddy simulations and their implementation in DALES4.4
Efficient and stable coupling of the SuperdropNet deep-learning-based cloud microphysics (v0.1.0) with the ICON climate and weather model (v2.6.5)
Three-dimensional variational assimilation with a multivariate background error covariance for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta)
FUME 2.0 – Flexible Universal processor for Modeling Emissions
DEUCE v1.0: a neural network for probabilistic precipitation nowcasting with aleatoric and epistemic uncertainties
Evaluation of multi-season convection-permitting atmosphere – mixed-layer ocean simulations of the Maritime Continent
Investigating the impact of coupling HARMONIE-WINS50 (cy43) meteorology to LOTOS-EUROS (v2.2.002) on a simulation of NO2 concentrations over the Netherlands
Balloon drift estimation and improved position estimates for radiosondes
Emission ensemble approach to improve the development of multi-scale emission inventories
What is the relative impact of nudging and online coupling on meteorological variables, pollutant concentrations and aerosol optical properties?
Diagnosing drivers of PM2.5 simulation biases in China from meteorology, chemical composition, and emission sources using an efficient machine learning method
Validation and analysis of the Polair3D v1.11 chemical transport model over Quebec
Assimilation of GNSS tropospheric gradients into the Weather Research and Forecasting (WRF) model version 4.4.1
Identifying atmospheric rivers and their poleward latent heat transport with generalizable neural networks: ARCNNv1
Assessing acetone for the GISS ModelE2.1 Earth system model
Bergen metrics: composite error metrics for assessing performance of climate models using EURO-CORDEX simulations
A dynamic approach to three-dimensional radiative transfer in subkilometer-scale numerical weather prediction models: the dynamic TenStream solver v1.0
Evaluation and development of surface layer scheme representation of temperature inversions over boreal forests in Arctic wintertime conditions
Modelling wind farm effects in HARMONIE–AROME (cycle 43.2.2) – Part 1: Implementation and evaluation
Analytical and adaptable initial conditions for dry and moist baroclinic waves in the global hydrostatic model OpenIFS (CY43R3)
Challenges of constructing and selecting the “perfect” boundary conditions for the large-eddy simulation model PALM
A machine learning approach for evaluating Southern Ocean cloud radiative biases in a global atmosphere model
Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India
How non-equilibrium aerosol chemistry impacts particle acidity: the GMXe AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel of MESSy
A grid model for vertical correction of precipitable water vapor over the Chinese mainland and surrounding areas using random forest
MEXPLORER 1.0.0 – a mechanism explorer for analysis and visualization of chemical reaction pathways based on graph theory
Advances and prospects of deep learning for medium-range extreme weather forecasting
An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)
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
Hai Bui, Mostafa Bakhoday-Paskyabi, and Mohammadreza Mohammadpour-Penchah
Geosci. Model Dev., 17, 4447–4465, https://doi.org/10.5194/gmd-17-4447-2024, https://doi.org/10.5194/gmd-17-4447-2024, 2024
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We developed a new wind turbine wake model, the Simple Actuator Disc for Large Eddy Simulation (SADLES), integrated with the widely used Weather Research and Forecasting (WRF) model. WRF-SADLES accurately simulates wind turbine wakes at resolutions of a few dozen meters, aligning well with idealized simulations and observational measurements. This makes WRF-SADLES a promising tool for wind energy research, offering a balance between accuracy, computational efficiency, and ease of implementation.
Changliang Shao and Lars Nerger
Geosci. Model Dev., 17, 4433–4445, https://doi.org/10.5194/gmd-17-4433-2024, https://doi.org/10.5194/gmd-17-4433-2024, 2024
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This paper introduces and evaluates WRF-PDAF, a fully online-coupled ensemble data assimilation (DA) system. A key advantage of the WRF-PDAF configuration is its ability to concurrently integrate all ensemble states, eliminating the need for time-consuming distribution and collection of ensembles during the coupling communication. The extra time required for DA amounts to only 20.6 % per cycle. Twin experiment results underscore the effectiveness of the WRF-PDAF system.
Jan Clemens, Lars Hoffmann, Bärbel Vogel, Sabine Grießbach, and Nicole Thomas
Geosci. Model Dev., 17, 4467–4493, https://doi.org/10.5194/gmd-17-4467-2024, https://doi.org/10.5194/gmd-17-4467-2024, 2024
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Lagrangian transport models simulate the transport of air masses in the atmosphere. For example, one model (CLaMS) is well suited to calculating transport as it uses a special coordinate system and special vertical wind. However, it only runs inefficiently on modern supercomputers. Hence, we have implemented the benefits of CLaMS into a new model (MPTRAC), which is already highly efficient on modern supercomputers. Finally, in extensive tests, we showed that CLaMS and MPTRAC agree very well.
Manuel López-Puertas, Federico Fabiano, Victor Fomichev, Bernd Funke, and Daniel R. Marsh
Geosci. Model Dev., 17, 4401–4432, https://doi.org/10.5194/gmd-17-4401-2024, https://doi.org/10.5194/gmd-17-4401-2024, 2024
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The radiative infrared cooling of CO2 in the middle atmosphere is crucial for computing its thermal structure. It requires one however to include non-local thermodynamic equilibrium processes which are computationally very expensive, which cannot be afforded by climate models. In this work, we present an updated, efficient, accurate and very fast (~50 µs) parameterization of that cooling able to cope with CO2 abundances from half the pre-industrial values to 10 times the current abundance.
Felix Wieser, Rolf Sander, Changmin Cho, Hendrik Fuchs, Thorsten Hohaus, Anna Novelli, Ralf Tillmann, and Domenico Taraborrelli
Geosci. Model Dev., 17, 4311–4330, https://doi.org/10.5194/gmd-17-4311-2024, https://doi.org/10.5194/gmd-17-4311-2024, 2024
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The chemistry scheme of the atmospheric box model CAABA/MECCA is expanded to achieve an improved aerosol formation from emitted organic compounds. In addition to newly added reactions, temperature-dependent partitioning of all new species between the gas and aqueous phases is estimated and included in the pre-existing scheme. Sensitivity runs show an overestimation of key compounds from isoprene, which can be explained by a lack of aqueous-phase degradation reactions and box model limitations.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
Geosci. Model Dev., 17, 4383–4399, https://doi.org/10.5194/gmd-17-4383-2024, https://doi.org/10.5194/gmd-17-4383-2024, 2024
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There is relatively limited research on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPUs, have distinct advantages in energy efficiency and scalability. The air quality modeling system can run stably on the MIPS and LoongArch platforms, and the experiment results verify the stability of scientific computing on the platforms. The work provides a technical foundation for the scientific application based on MIPS and LoongArch.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev., 17, 4331–4353, https://doi.org/10.5194/gmd-17-4331-2024, https://doi.org/10.5194/gmd-17-4331-2024, 2024
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This research focuses on surface ozone (O3) pollution in Arizona, a historically air-quality-challenged arid and semi-arid region in the US. The unique characteristics of this kind of region, e.g., intense heat, minimal moisture, and persistent desert shrubs, play a vital role in comprehending O3 exceedances. Using the WRF-Chem model, we analyzed O3 levels in the pre-monsoon month, revealing the model's skill in capturing diurnal and MDA8 O3 levels.
Christoph Fischer, Andreas H. Fink, Elmar Schömer, Marc Rautenhaus, and Michael Riemer
Geosci. Model Dev., 17, 4213–4228, https://doi.org/10.5194/gmd-17-4213-2024, https://doi.org/10.5194/gmd-17-4213-2024, 2024
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This study presents a method for identifying and tracking 3-D potential vorticity structures within African easterly waves (AEWs). Each identified structure is characterized by descriptors, including its 3-D position and orientation, which have been validated through composite comparisons. A trough-centric perspective on the descriptors reveals the evolution and distinct characteristics of AEWs. These descriptors serve as valuable statistical inputs for the study of AEW-related phenomena.
Sandro Vattioni, Andrea Stenke, Beiping Luo, Gabriel Chiodo, Timofei Sukhodolov, Elia Wunderlin, and Thomas Peter
Geosci. Model Dev., 17, 4181–4197, https://doi.org/10.5194/gmd-17-4181-2024, https://doi.org/10.5194/gmd-17-4181-2024, 2024
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We investigate the sensitivity of aerosol size distributions in the presence of strong SO2 injections for climate interventions or after volcanic eruptions to the call sequence and frequency of the routines for nucleation and condensation in sectional aerosol models with operator splitting. Using the aerosol–chemistry–climate model SOCOL-AERv2, we show that the radiative and chemical outputs are sensitive to these settings at high H2SO4 supersaturations and how to obtain reliable results.
Najmeh Kaffashzadeh and Abbas-Ali Aliakbari Bidokhti
Geosci. Model Dev., 17, 4155–4179, https://doi.org/10.5194/gmd-17-4155-2024, https://doi.org/10.5194/gmd-17-4155-2024, 2024
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This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology. It is found that the global model data need to be downscaled for regulatory purposes or policy applications at local scales. The method can be useful not only for the evaluation but also for the prediction of other chemical species, such as aerosols.
Franciscus Liqui Lung, Christian Jakob, A. Pier Siebesma, and Fredrik Jansson
Geosci. Model Dev., 17, 4053–4076, https://doi.org/10.5194/gmd-17-4053-2024, https://doi.org/10.5194/gmd-17-4053-2024, 2024
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Traditionally, high-resolution atmospheric models employ periodic boundary conditions, which limit simulations to domains without horizontal variations. In this research open boundary conditions are developed to replace the periodic boundary conditions. The implementation is tested in a controlled setup, and the results show minimal disturbances. Using these boundary conditions, high-resolution models can be forced by a coarser model to study atmospheric phenomena in realistic background states.
Caroline Arnold, Shivani Sharma, Tobias Weigel, and David S. Greenberg
Geosci. Model Dev., 17, 4017–4029, https://doi.org/10.5194/gmd-17-4017-2024, https://doi.org/10.5194/gmd-17-4017-2024, 2024
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In atmospheric models, rain formation is simplified to be computationally efficient. We trained a machine learning model, SuperdropNet, to emulate warm-rain formation based on super-droplet simulations. Here, we couple SuperdropNet with an atmospheric model in a warm-bubble experiment and find that the coupled simulation runs stable and produces reasonable results, making SuperdropNet a viable ML proxy for droplet simulations. We also present a comprehensive benchmark for coupling architectures.
Byoung-Joo Jung, Benjamin Ménétrier, Chris Snyder, Zhiquan Liu, Jonathan J. Guerrette, Junmei Ban, Ivette Hernández Baños, Yonggang G. Yu, and William C. Skamarock
Geosci. Model Dev., 17, 3879–3895, https://doi.org/10.5194/gmd-17-3879-2024, https://doi.org/10.5194/gmd-17-3879-2024, 2024
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We describe the multivariate static background error covariance (B) for the JEDI-MPAS 3D-Var data assimilation system. With tuned B parameters, the multivariate B gives physically balanced analysis increment fields in the single-observation test framework. In the month-long cycling experiment with a global 60 km mesh, 3D-Var with static B performs stably. Due to its simple workflow and minimal computational requirements, JEDI-MPAS 3D-Var can be useful for the research community.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
Geosci. Model Dev., 17, 3867–3878, https://doi.org/10.5194/gmd-17-3867-2024, https://doi.org/10.5194/gmd-17-3867-2024, 2024
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For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms, and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure, facilitating further processing to allow for emission processing from the continental to the street scale.
Bent Harnist, Seppo Pulkkinen, and Terhi Mäkinen
Geosci. Model Dev., 17, 3839–3866, https://doi.org/10.5194/gmd-17-3839-2024, https://doi.org/10.5194/gmd-17-3839-2024, 2024
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Probabilistic precipitation nowcasting (local forecasting for 0–6 h) is crucial for reducing damage from events like flash floods. For this goal, we propose the DEUCE neural-network-based model which uses data and model uncertainties to generate an ensemble of potential precipitation development scenarios for the next hour. Trained and evaluated with Finnish precipitation composites, DEUCE was found to produce more skillful and reliable nowcasts than established models.
Emma Howard, Steven Woolnough, Nicholas Klingaman, Daniel Shipley, Claudio Sanchez, Simon C. Peatman, Cathryn E. Birch, and Adrian J. Matthews
Geosci. Model Dev., 17, 3815–3837, https://doi.org/10.5194/gmd-17-3815-2024, https://doi.org/10.5194/gmd-17-3815-2024, 2024
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This paper describes a coupled atmosphere–mixed-layer ocean simulation setup that will be used to study weather processes in Southeast Asia. The set-up has been used to compare high-resolution simulations, which are able to partially resolve storms, to coarser simulations, which cannot. We compare the model performance at representing variability of rainfall and sea surface temperatures across length scales between the coarse and fine models.
Andrés Yarce Botero, Michiel van Weele, Arjo Segers, Pier Siebesma, and Henk Eskes
Geosci. Model Dev., 17, 3765–3781, https://doi.org/10.5194/gmd-17-3765-2024, https://doi.org/10.5194/gmd-17-3765-2024, 2024
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HARMONIE WINS50 reanalysis data with 0.025° × 0.025° resolution from 2019 to 2021 were coupled with the LOTOS-EUROS Chemical Transport Model. HARMONIE and ECMWF meteorology configurations against Cabauw observations (52.0° N, 4.9° W) were evaluated as simulated NO2 concentrations with ground-level sensors. Differences in crucial meteorological input parameters (boundary layer height, vertical diffusion coefficient) between the hydrostatic and non-hydrostatic models were analysed.
Ulrich Voggenberger, Leopold Haimberger, Federico Ambrogi, and Paul Poli
Geosci. Model Dev., 17, 3783–3799, https://doi.org/10.5194/gmd-17-3783-2024, https://doi.org/10.5194/gmd-17-3783-2024, 2024
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This paper presents a method for calculating balloon drift from historical radiosonde ascent data. The drift can reach distances of several hundred kilometres and is often neglected. Verification shows the beneficial impact of the more accurate balloon position on model assimilation. The method is not limited to radiosondes but would also work for dropsondes, ozonesondes, or any other in situ sonde carried by the wind in the pre-GNSS era, provided the necessary information is available.
Philippe Thunis, Jeroen Kuenen, Enrico Pisoni, Bertrand Bessagnet, Manjola Banja, Lech Gawuc, Karol Szymankiewicz, Diego Guizardi, Monica Crippa, Susana Lopez-Aparicio, Marc Guevara, Alexander De Meij, Sabine Schindlbacher, and Alain Clappier
Geosci. Model Dev., 17, 3631–3643, https://doi.org/10.5194/gmd-17-3631-2024, https://doi.org/10.5194/gmd-17-3631-2024, 2024
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An ensemble emission inventory is created with the aim of monitoring the status and progress made with the development of EU-wide inventories. This emission ensemble serves as a common benchmark for the screening and allows for the comparison of more than two inventories at a time. Because the emission “truth” is unknown, the approach does not tell which inventory is the closest to reality, but it identifies inconsistencies that require special attention.
Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev., 17, 3645–3665, https://doi.org/10.5194/gmd-17-3645-2024, https://doi.org/10.5194/gmd-17-3645-2024, 2024
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This study is about the modelling of the atmospheric composition in Europe during the summer of 2022, when massive wildfires were observed. It is a sensitivity study dedicated to the relative impacts of two modelling processes that are able to modify the meteorology used for the calculation of the atmospheric chemistry and transport of pollutants.
Shuai Wang, Mengyuan Zhang, Yueqi Gao, Peng Wang, Qingyan Fu, and Hongliang Zhang
Geosci. Model Dev., 17, 3617–3629, https://doi.org/10.5194/gmd-17-3617-2024, https://doi.org/10.5194/gmd-17-3617-2024, 2024
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Numerical models are widely used in air pollution modeling but suffer from significant biases. The machine learning model designed in this study shows high efficiency in identifying such biases. Meteorology (relative humidity and cloud cover), chemical composition (secondary organic components and dust aerosols), and emission sources (residential activities) are diagnosed as the main drivers of bias in modeling PM2.5, a typical air pollutant. The results will help to improve numerical models.
Shoma Yamanouchi, Shayamilla Mahagammulla Gamage, Sara Torbatian, Jad Zalzal, Laura Minet, Audrey Smargiassi, Ying Liu, Ling Liu, Forood Azargoshasbi, Jinwoong Kim, Youngseob Kim, Daniel Yazgi, and Marianne Hatzopoulou
Geosci. Model Dev., 17, 3579–3597, https://doi.org/10.5194/gmd-17-3579-2024, https://doi.org/10.5194/gmd-17-3579-2024, 2024
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Air pollution is a major health hazard, and chemical transport models (CTMs) are valuable tools that aid in our understanding of the risks of air pollution at both 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.
Rohith Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev., 17, 3599–3616, https://doi.org/10.5194/gmd-17-3599-2024, https://doi.org/10.5194/gmd-17-3599-2024, 2024
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Global Navigation Satellite Systems (GNSS) provides moisture observations through its densely distributed ground station network. In this research, we assimilate a new type of observation called tropospheric gradient observations, which has never been incorporated into a weather model. We develop a forward operator for gradient-based observations and conduct an assimilation impact study. The study shows significant improvements in the model's humidity fields.
Ankur Mahesh, Travis A. O'Brien, Burlen Loring, Abdelrahman Elbashandy, William Boos, and William D. Collins
Geosci. Model Dev., 17, 3533–3557, https://doi.org/10.5194/gmd-17-3533-2024, https://doi.org/10.5194/gmd-17-3533-2024, 2024
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Atmospheric rivers (ARs) are extreme weather events that can alleviate drought or cause billions of US dollars in flood damage. We train convolutional neural networks (CNNs) to detect ARs with an estimate of the uncertainty. We present a framework to generalize these CNNs to a variety of datasets of past, present, and future climate. Using a simplified simulation of the Earth's atmosphere, we validate the CNNs. We explore the role of ARs in maintaining energy balance in the Earth system.
Alexandra Rivera, Kostas Tsigaridis, Gregory Faluvegi, and Drew Shindell
Geosci. Model Dev., 17, 3487–3505, https://doi.org/10.5194/gmd-17-3487-2024, https://doi.org/10.5194/gmd-17-3487-2024, 2024
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This paper describes and evaluates an improvement to the representation of acetone in the GISS ModelE2.1 Earth system model. We simulate acetone's concentration and transport across the atmosphere as well as its dependence on chemistry, the ocean, and various global emissions. Comparisons of our model’s estimates to past modeling studies and field measurements have shown encouraging results. Ultimately, this paper contributes to a broader understanding of acetone's role in the atmosphere.
Alok K. Samantaray, Priscilla A. Mooney, and Carla A. Vivacqua
Geosci. Model Dev., 17, 3321–3339, https://doi.org/10.5194/gmd-17-3321-2024, https://doi.org/10.5194/gmd-17-3321-2024, 2024
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Any interpretation of climate model data requires a comprehensive evaluation of the model performance. Numerous error metrics exist for this purpose, and each focuses on a specific aspect of the relationship between reference and model data. Thus, a comprehensive evaluation demands the use of multiple error metrics. However, this can lead to confusion. We propose a clustering technique to reduce the number of error metrics needed and a composite error metric to simplify the interpretation.
Richard Maier, Fabian Jakub, Claudia Emde, Mihail Manev, Aiko Voigt, and Bernhard Mayer
Geosci. Model Dev., 17, 3357–3383, https://doi.org/10.5194/gmd-17-3357-2024, https://doi.org/10.5194/gmd-17-3357-2024, 2024
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Based on the TenStream solver, we present a new method to accelerate 3D radiative transfer towards the speed of currently used 1D solvers. Using a shallow-cumulus-cloud time series, we evaluate the performance of this new solver in terms of both speed and accuracy. Compared to a 3D benchmark simulation, we show that our new solver is able to determine much more accurate irradiances and heating rates than a 1D δ-Eddington solver, even when operated with a similar computational demand.
Julia Maillard, Jean-Christophe Raut, and François Ravetta
Geosci. Model Dev., 17, 3303–3320, https://doi.org/10.5194/gmd-17-3303-2024, https://doi.org/10.5194/gmd-17-3303-2024, 2024
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Atmospheric models struggle to reproduce the strong temperature inversions in the vicinity of the surface over forested areas in the Arctic winter. In this paper, we develop modified simplified versions of surface layer schemes widely used by the community. Our modifications are used to correct the fact that original schemes place strong limits on the turbulent collapse, leading to a lower surface temperature gradient at low wind speeds. Modified versions show a better performance.
Jana Fischereit, Henrik Vedel, Xiaoli Guo Larsén, Natalie E. Theeuwes, Gregor Giebel, and Eigil Kaas
Geosci. Model Dev., 17, 2855–2875, https://doi.org/10.5194/gmd-17-2855-2024, https://doi.org/10.5194/gmd-17-2855-2024, 2024
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Wind farms impact local wind and turbulence. To incorporate these effects in weather forecasting, the explicit wake parameterization (EWP) is added to the forecasting model HARMONIE–AROME. We evaluate EWP using flight data above and downstream of wind farms, comparing it with an alternative wind farm parameterization and another weather model. Results affirm the correct implementation of EWP, emphasizing the necessity of accounting for wind farm effects in accurate weather forecasting.
Clément Bouvier, Daan van den Broek, Madeleine Ekblom, and Victoria A. Sinclair
Geosci. Model Dev., 17, 2961–2986, https://doi.org/10.5194/gmd-17-2961-2024, https://doi.org/10.5194/gmd-17-2961-2024, 2024
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An analytical initial background state has been developed for moist baroclinic wave simulation on an aquaplanet and implemented into OpenIFS. Seven parameters can be controlled, which are used to generate the background states and the development of baroclinic waves. The meteorological and numerical stability has been assessed. Resulting baroclinic waves have proven to be realistic and sensitive to the jet's width.
Jelena Radović, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev., 17, 2901–2927, https://doi.org/10.5194/gmd-17-2901-2024, https://doi.org/10.5194/gmd-17-2901-2024, 2024
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Boundary conditions are of crucial importance for numerical model (e.g., PALM) validation studies and have a large influence on the model results, especially when studying the atmosphere of real, complex, and densely built urban environments. Our experiments with different driving conditions for the large-eddy simulation model PALM show its strong dependency on boundary conditions, which is important for the proper separation of errors coming from the boundary conditions and the model itself.
Sonya L. Fiddes, Marc D. Mallet, Alain Protat, Matthew T. Woodhouse, Simon P. Alexander, and Kalli Furtado
Geosci. Model Dev., 17, 2641–2662, https://doi.org/10.5194/gmd-17-2641-2024, https://doi.org/10.5194/gmd-17-2641-2024, 2024
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In this study we present an evaluation that considers complex, non-linear systems in a holistic manner. This study uses XGBoost, a machine learning algorithm, to predict the simulated Southern Ocean shortwave radiation bias in the ACCESS model using cloud property biases as predictors. We then used a novel feature importance analysis to quantify the role that each cloud bias plays in predicting the radiative bias, laying the foundation for advanced Earth system model evaluation and development.
Gaurav Govardhan, Sachin D. Ghude, Rajesh Kumar, Sumit Sharma, Preeti Gunwani, Chinmay Jena, Prafull Yadav, Shubhangi Ingle, Sreyashi Debnath, Pooja Pawar, Prodip Acharja, Rajmal Jat, Gayatry Kalita, Rupal Ambulkar, Santosh Kulkarni, Akshara Kaginalkar, Vijay K. Soni, Ravi S. Nanjundiah, and Madhavan Rajeevan
Geosci. Model Dev., 17, 2617–2640, https://doi.org/10.5194/gmd-17-2617-2024, https://doi.org/10.5194/gmd-17-2617-2024, 2024
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A newly developed air quality forecasting framework, Decision Support System (DSS), for air quality management in Delhi, India, provides source attribution with numerous emission reduction scenarios besides forecasts. DSS shows that during post-monsoon and winter seasons, Delhi and its neighboring districts contribute to 30 %–40 % each to pollution in Delhi. On average, a 40 % reduction in the emissions in Delhi and the surrounding districts would result in a 24 % reduction in Delhi's pollution.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
Geosci. Model Dev., 17, 2597–2615, https://doi.org/10.5194/gmd-17-2597-2024, https://doi.org/10.5194/gmd-17-2597-2024, 2024
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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 reduced inorganic aerosol mass concentrations, especially in the United States. Furthermore, the representation of fine-aerosol pH is particularly improved in the marine boundary layer.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Huang, and Feijuan Li
Geosci. Model Dev., 17, 2569–2581, https://doi.org/10.5194/gmd-17-2569-2024, https://doi.org/10.5194/gmd-17-2569-2024, 2024
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In this study, we have developed a model (RF-PWV) to characterize precipitable water vapor (PWV) variation with altitude in the study area. 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.
Rolf Sander
Geosci. Model Dev., 17, 2419–2425, https://doi.org/10.5194/gmd-17-2419-2024, https://doi.org/10.5194/gmd-17-2419-2024, 2024
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The open-source software MEXPLORER 1.0.0 is presented here. The program can be used to analyze, reduce, and visualize complex chemical reaction mechanisms. The mathematics behind the tool is based on graph theory: chemical species are represented as vertices, and reactions as edges. MEXPLORER is a community model published under the GNU General Public License.
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.
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Short summary
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.
This study explores how the variation in the source profiles adopted in chemical transport...
