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
Related authors
No articles found.
Baoshuang Liu, Yao Gu, Yutong Wu, Qili Dai, Shaojie Song, Yinchang Feng, and Philip K. Hopke
Atmos. Chem. Phys., 24, 12861–12879, https://doi.org/10.5194/acp-24-12861-2024, https://doi.org/10.5194/acp-24-12861-2024, 2024
Short summary
Short summary
Reactive loss of volatile organic compounds (VOCs) is a long-term issue yet to be resolved in VOC source analyses. We assess common methods of, and existing issues in, reducing losses, impacts of losses, and sources in current source analyses. We offer a potential supporting role for solving issues of VOC conversion. Source analyses of consumed VOCs that reacted to produce ozone and secondary organic aerosols can play an important role in the effective control of secondary pollution in air.
Yuhang Hao, Peizhao Li, Yafeng Gou, Zhenshuai Wang, Mi Tian, Yang Chen, Ye Kuang, Hanbing Xu, Fenglian Wan, Yuqian Luo, Wei Huang, and Jing Chen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3242, https://doi.org/10.5194/egusphere-2024-3242, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Intensified heatwaves with the global warming have influenced new particle formation (NPF) and related aerosol physicochemical properties. We show that aerosol optical hygroscopicity (f(RH)) was generally higher on NPF event days than non-event cases, likely due to enhanced secondary formation and subsequent growth of both pre-existing and newly formed particles with stronger photooxidation specifically under persistent heatwaves. This would further impact the aerosol direct radiative forcing.
Yiliang Liu, Arttu Yli-Kujala, Fabian Schmidt-Ott, Sebastian Holm, Lauri Ahonen, Tommy Chan, Joonas Enroth, Joonas Vanhanen, Runlong Cai, Tuukka Petäjä, Markku Kulmala, Yang Chen, and Juha Kangasluoma
EGUsphere, https://doi.org/10.5194/egusphere-2024-2603, https://doi.org/10.5194/egusphere-2024-2603, 2024
Short summary
Short summary
Accurate measurement of nanoparticles is crucial for understanding their impact on new particle formation and climate change. In our study, we calibrated the Particle Size Magnifier version 2.0, a novel instrument designed for nanoparticle analysis, using both lab-generated and atmospheric particles. Significant differences were observed in the calibration results, with direct calibration using atmospheric particles enhancing measurement accuracy.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
Assessment of object-based indices to identify convective organization
The Global Forest Fire Emissions Prediction System version 1.0
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
FLEXPART version 11: improved accuracy, efficiency, and flexibility
Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions
Air quality modeling intercomparison and multiscale ensemble chain for Latin America
Recommended coupling to global meteorological fields for long-term tracer simulations with WRF-GHG
Selecting CMIP6 global climate models (GCMs) for Coordinated Regional Climate Downscaling Experiment (CORDEX) dynamical downscaling over Southeast Asia using a standardised benchmarking framework
Improved definition of prior uncertainties in CO2 and CO fossil fuel fluxes and its impact on multi-species inversion with GEOS-Chem (v12.5)
RASCAL v1.0: an open-source tool for climatological time series reconstruction and extension
Introducing graupel density prediction in Weather Research and Forecasting (WRF) double-moment 6-class (WDM6) microphysics and evaluation of the modified scheme during the ICE-POP field campaign
Enabling high-performance cloud computing for the Community Multiscale Air Quality Model (CMAQ) version 5.3.3: performance evaluation and benefits for the user community
Atmospheric-river-induced precipitation in California as simulated by the regionally refined Simple Convective Resolving E3SM Atmosphere Model (SCREAM) Version 0
Recent improvements and maximum covariance analysis of aerosol and cloud properties in the EC-Earth3-AerChem model
GPU-HADVPPM4HIP V1.0: using the heterogeneous-compute interface for portability (HIP) to speed up the piecewise parabolic method in the CAMx (v6.10) air quality model on China's domestic GPU-like accelerator
Preliminary evaluation of the effect of electro-coalescence with conducting sphere approximation on the formation of warm cumulus clouds using SCALE-SDM version 0.2.5–2.3.0
Exploring the footprint representation of microwave radiance observations in an Arctic limited-area data assimilation system
Orbital-Radar v1.0.0: A tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
Analysis of model error in forecast errors of extended atmospheric Lorenz 05 systems and the ECMWF system
Description and validation of Vehicular Emissions from Road Traffic (VERT) 1.0, an R-based framework for estimating road transport emissions from traffic flows
AeroMix v1.0.1: a Python package for modeling aerosol optical properties and mixing states
Impact of ITCZ width on global climate: ITCZ-MIP
Deep-learning-driven simulations of boundary layer clouds over the Southern Great Plains
Mixed-precision computing in the GRIST dynamical core for weather and climate modelling
A conservative immersed boundary method for the multi-physics urban large-eddy simulation model uDALES v2.0
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
RCEMIP-II: mock-Walker simulations as phase II of the radiative–convective equilibrium model intercomparison project
The MESSy DWARF (based on MESSy v2.55.2)
Objective identification of meteorological fronts and climatologies from ERA-Interim and ERA5
TAMS: a tracking, classifying, and variable-assigning algorithm for mesoscale convective systems in simulated and satellite-derived datasets
Development of the adjoint of the unified tropospheric–stratospheric chemistry extension (UCX) in GEOS-Chem adjoint v36
New explicit formulae for the settling speed of prolate spheroids in the atmosphere: theoretical background and implementation in AerSett v2.0.2
ZJU-AERO V0.5: an Accurate and Efficient Radar Operator designed for CMA-GFS/MESO with the capability to simulate non-spherical hydrometeors
The Year of Polar Prediction site Model Intercomparison Project (YOPPsiteMIP) phase 1: project overview and Arctic winter forecast evaluation
Evaluating CHASER V4.0 global formaldehyde (HCHO) simulations using satellite, aircraft, and ground-based remote-sensing observations
Global variable-resolution simulations of extreme precipitation over Henan, China, in 2021 with MPAS-Atmosphere v7.3
The CHIMERE chemistry-transport model v2023r1
tobac v1.5: introducing fast 3D tracking, splits and mergers, and other enhancements for identifying and analysing meteorological phenomena
Merged Observatory Data Files (MODFs): an integrated observational data product supporting process-oriented investigations and diagnostics
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
Short summary
Short summary
A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
Short summary
Short summary
To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
Short summary
Short summary
Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
Short summary
Short summary
Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
Short summary
Short summary
The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
Short summary
Short summary
Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
Short summary
Short summary
Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
Short summary
Short summary
This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
Short summary
Short summary
Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
Short summary
Short summary
Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
Short summary
Short summary
This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
Short summary
Short summary
In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
Short summary
Short summary
The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
Short summary
Short summary
The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
Short summary
Short summary
Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
Short summary
Short summary
Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
Short summary
Short summary
Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
Short summary
Short summary
Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev., 17, 7285–7315, https://doi.org/10.5194/gmd-17-7285-2024, https://doi.org/10.5194/gmd-17-7285-2024, 2024
Short summary
Short summary
We use a comprehensive approach to select a subset of CMIP6 models for dynamical downscaling over Southeast Asia, taking into account model performance, model independence, data availability and the range of future climate projections. The standardised benchmarking framework is applied to assess model performance through both statistical and process-based metrics. Ultimately, we identify two independent model groups that are suitable for dynamical downscaling in the Southeast Asian region.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
Short summary
Short summary
Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Álvaro González-Cervera and Luis Durán
Geosci. Model Dev., 17, 7245–7261, https://doi.org/10.5194/gmd-17-7245-2024, https://doi.org/10.5194/gmd-17-7245-2024, 2024
Short summary
Short summary
RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the analog method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities for broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt
Geosci. Model Dev., 17, 7199–7218, https://doi.org/10.5194/gmd-17-7199-2024, https://doi.org/10.5194/gmd-17-7199-2024, 2024
Short summary
Short summary
We enhance the WDM6 scheme by incorporating predicted graupel density. The modification affects graupel characteristics, including fall velocity–diameter and mass–diameter relationships. Simulations highlight changes in graupel distribution and precipitation patterns, potentially influencing surface snow amounts. The study underscores the significance of integrating predicted graupel density for a more realistic portrayal of microphysical properties in weather models.
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024, https://doi.org/10.5194/gmd-17-7001-2024, 2024
Short summary
Short summary
We present a summary of enabling high-performance computing of the Community Multiscale Air Quality Model (CMAQ) – a state-of-the-science community multiscale air quality model – on two cloud computing platforms through documenting the technologies, model performance, scaling and relative merits. This may be a new paradigm for computationally intense future model applications. We initiated this work due to a need to leverage cloud computing advances and to ease the learning curve for new users.
Peter A. Bogenschutz, Jishi Zhang, Qi Tang, and Philip Cameron-Smith
Geosci. Model Dev., 17, 7029–7050, https://doi.org/10.5194/gmd-17-7029-2024, https://doi.org/10.5194/gmd-17-7029-2024, 2024
Short summary
Short summary
Using high-resolution and state-of-the-art modeling techniques we simulate five atmospheric river events for California to test the capability to represent precipitation for these events. We find that our model is able to capture the distribution of precipitation very well but suffers from overestimating the precipitation amounts over high elevation. Increasing the resolution further has no impact on reducing this bias, while increasing the domain size does have modest impacts.
Manu Anna Thomas, Klaus Wyser, Shiyu Wang, Marios Chatziparaschos, Paraskevi Georgakaki, Montserrat Costa-Surós, Maria Gonçalves Ageitos, Maria Kanakidou, Carlos Pérez García-Pando, Athanasios Nenes, Twan van Noije, Philippe Le Sager, and Abhay Devasthale
Geosci. Model Dev., 17, 6903–6927, https://doi.org/10.5194/gmd-17-6903-2024, https://doi.org/10.5194/gmd-17-6903-2024, 2024
Short summary
Short summary
Aerosol–cloud interactions occur at a range of spatio-temporal scales. While evaluating recent developments in EC-Earth3-AerChem, this study aims to understand the extent to which the Twomey effect manifests itself at larger scales. We find a reduction in the warm bias over the Southern Ocean due to model improvements. While we see footprints of the Twomey effect at larger scales, the negative relationship between cloud droplet number and liquid water drives the shortwave radiative effect.
Kai Cao, Qizhong Wu, Lingling Wang, Hengliang Guo, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongxing Li, Lina Liu, Dongqing Li, Hao Wu, and Lanning Wang
Geosci. Model Dev., 17, 6887–6901, https://doi.org/10.5194/gmd-17-6887-2024, https://doi.org/10.5194/gmd-17-6887-2024, 2024
Short summary
Short summary
AMD’s heterogeneous-compute interface for portability was implemented to port the piecewise parabolic method solver from NVIDIA GPUs to China's GPU-like accelerators. The results show that the larger the model scale, the more acceleration effect on the GPU-like accelerator, up to 28.9 times. The multi-level parallelism achieves a speedup of 32.7 times on the heterogeneous cluster. By comparing the results, the GPU-like accelerators have more accuracy for the geoscience numerical models.
Ruyi Zhang, Limin Zhou, Shin-ichiro Shima, and Huawei Yang
Geosci. Model Dev., 17, 6761–6774, https://doi.org/10.5194/gmd-17-6761-2024, https://doi.org/10.5194/gmd-17-6761-2024, 2024
Short summary
Short summary
Solar activity weakly ionises Earth's atmosphere, charging cloud droplets. Electro-coalescence is when oppositely charged droplets stick together. We introduce an analytical expression of electro-coalescence probability and use it in a warm-cumulus-cloud simulation. Results show that charge cases increase rain and droplet size, with the new method outperforming older ones. The new method requires longer computation time, but its impact on rain justifies inclusion in meteorology models.
Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev., 17, 6571–6587, https://doi.org/10.5194/gmd-17-6571-2024, https://doi.org/10.5194/gmd-17-6571-2024, 2024
Short summary
Short summary
Satellite observations provide crucial information about atmospheric constituents in a global distribution that helps to better predict the weather over sparsely observed regions like the Arctic. However, the use of satellite data is usually conservative and imperfect. In this study, a better spatial representation of satellite observations is discussed and explored by a so-called footprint function or operator, highlighting its added value through a case study and diagnostics.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-129, https://doi.org/10.5194/gmd-2024-129, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Orbital-radar is a Python tool transferring sub-orbital radar data (ground-based, airborne, and forward-simulated NWP) into synthetical space-borne cloud profiling radar data mimicking the platform characteristics, e.g. EarthCARE or CloudSat CPR. The novelty of orbital-radar is the simulation platform characteristic noise floors and errors. By this long time data sets can be transformed into synthetic observations for Cal/Valor sensitivity studies for new or future satellite missions.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 17, 6489–6511, https://doi.org/10.5194/gmd-17-6489-2024, https://doi.org/10.5194/gmd-17-6489-2024, 2024
Short summary
Short summary
The forecast error growth of atmospheric phenomena is caused by initial and model errors. When studying the initial error growth, it may turn out that small-scale phenomena, which contribute little to the forecast product, significantly affect the ability to predict this product. With a negative result, we investigate in the extended Lorenz (2005) system whether omitting these phenomena will improve predictability. A theory explaining and describing this behavior is developed.
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, https://doi.org/10.5194/gmd-17-6465-2024, 2024
Short summary
Short summary
In this study, we present VERT (Vehicular Emissions from Road Traffic), an R package designed to estimate transport emissions using traffic estimates and vehicle fleet composition data. Compared to other tools available in the literature, VERT stands out for its user-friendly configuration and flexibility of user input. Case studies demonstrate its accuracy in both urban and regional contexts, making it a valuable tool for air quality management and transport scenario planning.
Sam P. Raj, Puna Ram Sinha, Rohit Srivastava, Srinivas Bikkina, and Damu Bala Subrahamanyam
Geosci. Model Dev., 17, 6379–6399, https://doi.org/10.5194/gmd-17-6379-2024, https://doi.org/10.5194/gmd-17-6379-2024, 2024
Short summary
Short summary
A Python successor to the aerosol module of the OPAC model, named AeroMix, has been developed, with enhanced capabilities to better represent real atmospheric aerosol mixing scenarios. AeroMix’s performance in modeling aerosol mixing states has been evaluated against field measurements, substantiating its potential as a versatile aerosol optical model framework for next-generation algorithms to infer aerosol mixing states and chemical composition.
Angeline G. Pendergrass, Michael P. Byrne, Oliver Watt-Meyer, Penelope Maher, and Mark J. Webb
Geosci. Model Dev., 17, 6365–6378, https://doi.org/10.5194/gmd-17-6365-2024, https://doi.org/10.5194/gmd-17-6365-2024, 2024
Short summary
Short summary
The width of the tropical rain belt affects many aspects of our climate, yet we do not understand what controls it. To better understand it, we present a method to change it in numerical model experiments. We show that the method works well in four different models. The behavior of the width is unexpectedly simple in some ways, such as how strong the winds are as it changes, but in other ways, it is more complicated, especially how temperature increases with carbon dioxide.
Tianning Su and Yunyan Zhang
Geosci. Model Dev., 17, 6319–6336, https://doi.org/10.5194/gmd-17-6319-2024, https://doi.org/10.5194/gmd-17-6319-2024, 2024
Short summary
Short summary
Using 2 decades of field observations over the Southern Great Plains, this study developed a deep-learning model to simulate the complex dynamics of boundary layer clouds. The deep-learning model can serve as the cloud parameterization within reanalysis frameworks, offering insights into improving the simulation of low clouds. By quantifying biases due to various meteorological factors and parameterizations, this deep-learning-driven approach helps bridge the observation–modeling divide.
Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev., 17, 6301–6318, https://doi.org/10.5194/gmd-17-6301-2024, https://doi.org/10.5194/gmd-17-6301-2024, 2024
Short summary
Short summary
This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The coded equation terms in the governing equations that are sensitive (or insensitive) to the precision level have been identified. The performance of mixed-precision computing in weather and climate simulations was analyzed.
Sam O. Owens, Dipanjan Majumdar, Chris E. Wilson, Paul Bartholomew, and Maarten van Reeuwijk
Geosci. Model Dev., 17, 6277–6300, https://doi.org/10.5194/gmd-17-6277-2024, https://doi.org/10.5194/gmd-17-6277-2024, 2024
Short summary
Short summary
Designing cities that are resilient, sustainable, and beneficial to health requires an understanding of urban climate and air quality. This article presents an upgrade to the multi-physics numerical model uDALES, which can simulate microscale airflow, heat transfer, and pollutant dispersion in urban environments. This upgrade enables it to resolve realistic urban geometries more accurately and to take advantage of the resources available on current and future high-performance computing systems.
Felipe Cifuentes, Henk Eskes, Folkert Boersma, Enrico Dammers, and Charlotte Bryan
EGUsphere, https://doi.org/10.5194/egusphere-2024-2225, https://doi.org/10.5194/egusphere-2024-2225, 2024
Short summary
Short summary
We tested the capability of the flux divergence approach (FDA) to reproduce known NOX emissions using synthetic NO2 satellite column retrievals derived from high-resolution model simulations. The FDA accurately reproduced NOX emissions when column observations were limited to the boundary layer and when the variability of NO2 lifetime, NOX:NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces a strong model dependency, reducing the simplicity of the original FDA formulation.
Allison A. Wing, Levi G. Silvers, and Kevin A. Reed
Geosci. Model Dev., 17, 6195–6225, https://doi.org/10.5194/gmd-17-6195-2024, https://doi.org/10.5194/gmd-17-6195-2024, 2024
Short summary
Short summary
This paper presents the experimental design for a model intercomparison project to study tropical clouds and climate. It is a follow-up from a prior project that used a simplified framework for tropical climate. The new project adds one new component – a specified pattern of sea surface temperatures as the lower boundary condition. We provide example results from one cloud-resolving model and one global climate model and test the sensitivity to the experimental parameters.
Astrid Kerkweg, Timo Kirfel, Doung H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-117, https://doi.org/10.5194/gmd-2024-117, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
This article introduces the MESSy DWARF. Usually, the Modular Earth Submodel System (MESSy) is linked to full dynamical models to build chemistry climate models. However, due to the modular concept of MESSy, and the newly developed DWARF component, it is now possible to create simplified models containing just one or some process descriptions. This renders very useful for technical optimisation (e.g., GPU porting) and can be used to create less complex models, e.g., a chemical box model.
Philip G. Sansom and Jennifer L. Catto
Geosci. Model Dev., 17, 6137–6151, https://doi.org/10.5194/gmd-17-6137-2024, https://doi.org/10.5194/gmd-17-6137-2024, 2024
Short summary
Short summary
Weather fronts bring a lot of rain and strong winds to many regions of the mid-latitudes. We have developed an updated method of identifying these fronts in gridded data that can be used on new datasets with small grid spacing. The method can be easily applied to different datasets due to the use of open-source software for its development and shows improvements over similar previous methods. We present an updated estimate of the average frequency of fronts over the past 40 years.
Kelly M. Núñez Ocasio and Zachary L. Moon
Geosci. Model Dev., 17, 6035–6049, https://doi.org/10.5194/gmd-17-6035-2024, https://doi.org/10.5194/gmd-17-6035-2024, 2024
Short summary
Short summary
TAMS is an open-source Python-based package for tracking and classifying mesoscale convective systems that can be used to study observed and simulated systems. Each step of the algorithm is described in this paper with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this tracker is its support for unstructured grids in the identification stage and grid-independent tracking.
Irene C. Dedoussi, Daven K. Henze, Sebastian D. Eastham, Raymond L. Speth, and Steven R. H. Barrett
Geosci. Model Dev., 17, 5689–5703, https://doi.org/10.5194/gmd-17-5689-2024, https://doi.org/10.5194/gmd-17-5689-2024, 2024
Short summary
Short summary
Atmospheric model gradients provide a meaningful tool for better understanding the underlying atmospheric processes. Adjoint modeling enables computationally efficient gradient calculations. We present the adjoint of the GEOS-Chem unified chemistry extension (UCX). With this development, the GEOS-Chem adjoint model can capture stratospheric ozone and other processes jointly with tropospheric processes. We apply it to characterize the Antarctic ozone depletion potential of active halogen species.
Sylvain Mailler, Sotirios Mallios, Arineh Cholakian, Vassilis Amiridis, Laurent Menut, and Romain Pennel
Geosci. Model Dev., 17, 5641–5655, https://doi.org/10.5194/gmd-17-5641-2024, https://doi.org/10.5194/gmd-17-5641-2024, 2024
Short summary
Short summary
We propose two explicit expressions to calculate the settling speed of solid atmospheric particles with prolate spheroidal shapes. The first formulation is based on theoretical arguments only, while the second one is based on computational fluid dynamics calculations. We show that the first method is suitable for virtually all atmospheric aerosols, provided their shape can be adequately described as a prolate spheroid, and we provide an implementation of the first method in AerSett v2.0.2.
Hejun Xie, Lei Bi, and Wei Han
Geosci. Model Dev., 17, 5657–5688, https://doi.org/10.5194/gmd-17-5657-2024, https://doi.org/10.5194/gmd-17-5657-2024, 2024
Short summary
Short summary
A radar operator plays a crucial role in utilizing radar observations to enhance numerical weather forecasts. However, developing an advanced radar operator is challenging due to various complexities associated with the wave scattering by non-spherical hydrometeors, radar beam propagation, and multiple platforms. In this study, we introduce a novel radar operator named the Accurate and Efficient Radar Operator developed by ZheJiang University (ZJU-AERO) which boasts several unique features.
Jonathan J. Day, Gunilla Svensson, Barbara Casati, Taneil Uttal, Siri-Jodha Khalsa, Eric Bazile, Elena Akish, Niramson Azouz, Lara Ferrighi, Helmut Frank, Michael Gallagher, Øystein Godøy, Leslie M. Hartten, Laura X. Huang, Jareth Holt, Massimo Di Stefano, Irene Suomi, Zen Mariani, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Teresa Remes, Rostislav Fadeev, Amy Solomon, Johanna Tjernström, and Mikhail Tolstykh
Geosci. Model Dev., 17, 5511–5543, https://doi.org/10.5194/gmd-17-5511-2024, https://doi.org/10.5194/gmd-17-5511-2024, 2024
Short summary
Short summary
The YOPP site Model Intercomparison Project (YOPPsiteMIP), which was designed to facilitate enhanced weather forecast evaluation in polar regions, is discussed here, focussing on describing the archive of forecast data and presenting a multi-model evaluation at Arctic supersites during February and March 2018. The study highlights an underestimation in boundary layer temperature variance that is common across models and a related inability to forecast cold extremes at several of the sites.
Hossain Mohammed Syedul Hoque, Kengo Sudo, Hitoshi Irie, Yanfeng He, and Md Firoz Khan
Geosci. Model Dev., 17, 5545–5571, https://doi.org/10.5194/gmd-17-5545-2024, https://doi.org/10.5194/gmd-17-5545-2024, 2024
Short summary
Short summary
Using multi-platform observations, we validated global formaldehyde (HCHO) simulations from a chemistry transport model. HCHO is a crucial intermediate in the chemical catalytic cycle that governs the ozone formation in the troposphere. The model was capable of replicating the observed spatiotemporal variability in HCHO. In a few cases, the model's capability was limited. This is attributed to the uncertainties in the observations and the model parameters.
Zijun Liu, Li Dong, Zongxu Qiu, Xingrong Li, Huiling Yuan, Dongmei Meng, Xiaobin Qiu, Dingyuan Liang, and Yafei Wang
Geosci. Model Dev., 17, 5477–5496, https://doi.org/10.5194/gmd-17-5477-2024, https://doi.org/10.5194/gmd-17-5477-2024, 2024
Short summary
Short summary
In this study, we completed a series of simulations with MPAS-Atmosphere (version 7.3) to study the extreme precipitation event of Henan, China, during 20–22 July 2021. We found the different performance of two built-in parameterization scheme suites (mesoscale and convection-permitting suites) with global quasi-uniform and variable-resolution meshes. This study holds significant implications for advancing the understanding of the scale-aware capability of MPAS-Atmosphere.
Laurent Menut, Arineh Cholakian, Romain Pennel, Guillaume Siour, Sylvain Mailler, Myrto Valari, Lya Lugon, and Yann Meurdesoif
Geosci. Model Dev., 17, 5431–5457, https://doi.org/10.5194/gmd-17-5431-2024, https://doi.org/10.5194/gmd-17-5431-2024, 2024
Short summary
Short summary
A new version of the CHIMERE model is presented. This version contains both computational and physico-chemical changes. The computational changes make it easy to choose the variables to be extracted as a result, including values of maximum sub-hourly concentrations. Performance tests show that the model is 1.5 to 2 times faster than the previous version for the same setup. Processes such as turbulence, transport schemes and dry deposition have been modified and updated.
G. Alexander Sokolowsky, Sean W. Freeman, William K. Jones, Julia Kukulies, Fabian Senf, Peter J. Marinescu, Max Heikenfeld, Kelcy N. Brunner, Eric C. Bruning, Scott M. Collis, Robert C. Jackson, Gabrielle R. Leung, Nils Pfeifer, Bhupendra A. Raut, Stephen M. Saleeby, Philip Stier, and Susan C. van den Heever
Geosci. Model Dev., 17, 5309–5330, https://doi.org/10.5194/gmd-17-5309-2024, https://doi.org/10.5194/gmd-17-5309-2024, 2024
Short summary
Short summary
Building on previous analysis tools developed for atmospheric science, the original release of the Tracking and Object-Based Analysis (tobac) Python package, v1.2, was open-source, modular, and insensitive to the type of gridded input data. Here, we present the latest version of tobac, v1.5, which substantially improves scientific capabilities and computational efficiency from the previous version. These enhancements permit new uses for tobac in atmospheric science and potentially other fields.
Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
Geosci. Model Dev., 17, 5225–5247, https://doi.org/10.5194/gmd-17-5225-2024, https://doi.org/10.5194/gmd-17-5225-2024, 2024
Short summary
Short summary
A Merged Observatory Data File (MODF) format to systematically collate complex atmosphere, ocean, and terrestrial data sets collected by multiple instruments during field campaigns is presented. The MODF format is also designed to be applied to model output data, yielding format-matching Merged Model Data Files (MMDFs). MODFs plus MMDFs will augment and accelerate the synergistic use of model results with observational data to increase understanding and predictive skill.
Cited articles
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.
Bi, X., Dai, Q., Wu, J., Zhang, Q., Zhang, W., Luo, R., Cheng, Y., Zhang, J., Wang, L., Yu, Z., Zhang, Y., Tian, Y., and Feng, Y.: Characteristics of the main primary source profiles of particulate matter across China from 1987 to 2017, Atmos. Chem. Phys., 19, 3223–3243, https://doi.org/10.5194/acp-19-3223-2019, 2019a.
Bi, X., Dai, Q., Wu, J., Zhang, Q., Zhang, W., Luo, R., Cheng, Y., Zhang, J., Wang, L., Yu, Z., Zhang, Y., Tian, Y., and Feng, Y.: Data for: chemical compositions of the main source profiles of ambient particulate matter across China, Mendeley Data [data set], https://doi.org/10.17632/x8dfshjt9j.2, 2019b.
Cao, J., Qiu, X., Gao, J., Wang, F., Wang, J., Wu, J., and Peng, L.: Significant decrease in SO2 emission and enhanced atmospheric oxidation trigger changes in sulfate formation pathways in China during 2008–2016, J. Clean. Prod., 326, 129396, https://doi.org/10.1016/j.jclepro.2021.129396, 2021.
Chapel Hill, N.: Operational Guidance for the Community Multiscale Air Quality (CMAQ) Modeling System Version 5.0, https://www.airqualitymodeling.org/index.php/CMAQ_version_5.0_(February_2010_release)_OGD#Aerosol_Module, last access: February 2012.
Chen, Z., Chen, D., Zhao, C., Kwan, M., Cai, J., Zhuang, Y., Zhao, B., Wang, X., Chen, B., Yang, J., Li, R., He, B., Gao, B., Wang, K., and Xu, B.: Influence of meteorological conditions on PM2.5 concentrations across China: A review of methodology and mechanism, Environ. Int., 139, 105558, https://doi.org/10.1016/j.envint.2020.105558, 2020.
Cheng, N. L., Meng, F., Wang, J. K., Chen, Y. B., Wei, X., and Han, H.: Numerical simulation of the spatial distribution and deposition of PM2.5 in East China coastal area in 2010, J. Safety Environ., 15, 305–310, https://doi.org/10.13637/j.issn.1009-6094.2015.06.063, 2015 (in Chinese).
Eder, B. K. and Yu, S. C.: A performance evaluation of the 2004 release of Models-3 CMAQ, Atmos. Environ., 40, 4811–4824, https://doi.org/10.1007/978-0-387-68854-1_57, 2006.
Feng, Y., Bi, X., Wu, J., and Zhang, Y.: The state environment protection key laboratory of urban particulate air pollution prevention, Database of Source Profiles of Air pollution (SPAP) [data set], http://www.nkspap.com:9091/ (last access: 14 November 2023), 2020.
Foley, K. M., Roselle, S. J., Appel, K. W., Bhave, P. V., Pleim, J. E., Otte, T. L., Mathur, R., Sarwar, G., Young, J. O., Gilliam, R. C., Nolte, C. G., Kelly, J. T., Gilliland, A. B., and Bash, J. O.: Incremental testing of the Community Multiscale Air Quality (CMAQ) modeling system version 4.7, Geosci. Model Dev., 3, 205–226, https://doi.org/10.5194/gmd-3-205-2010, 2010.
Fountoukis, C. and Nenes, A.: ISORROPIA II: a computationally efficient thermodynamic equilibrium model for K+–Ca2+–Mg2+–
Fu, X., Wang, S., Zhao, B., Xing, J., Cheng, Z., Liu, H., and Hao, J.: Emission inventory of primary pollutants and chemical speciation in 2010 for the Yangtze River Delta region, China, Atmos. Environ., 70, 39–50, https://doi.org/10.1016/j.atmosenv.2012.12.034, 2013.
Fu, X., Wang, S. X., Chang, X., Cai, S., Xing, J., and Hao, J. M.: Modeling analysis of secondary inorganic aerosols over China: pollution characteristics, and meteorological and dust impacts, Sci. Rep., 6, 35992, https://doi.org/10.1038/srep35992, 2016.
Gao, S., Zhang, S., Che, X., Ma, Y., Chen, X., Duan, Y., Fu, Q., Wang, S., Zhou, B., Wei, C., and Jiao, Z.: New understanding of source profiles: Example of the coating industry, J. Clean. Prod., 357, 132025, https://doi.org/10.1016/j.jclepro.2022.132025, 2022.
Guo, R., Yang, J., and Liu, Z.: Influence of heat treatment conditions on release of chlorine from Datong coal, J. Anal. Appl. Pyrol., 71, 179–186, https://doi.org/10.1016/S0165-2370(03)00086-X, 2004.
Guo, Y. Y., Gao, X., Zhu, T. Y., Luo, L., and Zheng, Y.: Chemical profiles of PM emitted from the iron and steel industry in northern China, Atmos. Environ., 150, 187–197, https://doi.org/10.1016/j.atmosenv.2016.11.055, 2017.
Guo, Z., Hao, Y., Tian, H., Bai, X., Wu, B., Liu, S., Luo, L., Liu, W., Zhao, S., Lin, S., Lv, Y., Yang, J., and Xiao, Y.: Field measurements on emission characteristics, chemical profiles, and emission factors of size-segregated PM from cement plants in China, Sci. Total Environ., 818, 151822, https://doi.org/10.1016/j.scitotenv.2021.151822, 2021.
Han, Y., Xu, H., Bi, X. H., Lin, F. M., Li, J., Zhang, Y. F., and Feng, Y. C.: The effect of atmospheric particulates on the rainwater chemistry in the Yangtze River Delta, China, J. Air Waste Manage., 69, 1452–1466, https://doi.org/10.1080/10962247.2019.1674750, 2019.
Hopke, P. K., Dai, Q., Li, L., Feng, Y.: Global review of recent source apportionments for airborne particulate matter, Sci. Total Environ., 740, 140091, https://doi.org/10.1016/j.scitotenv.2020.140091, 2020.
Hopke, P. K., Feng, Y. C., and Dai, Q.: Source apportionment of particle number concentrations: A global review, Sci. Total Environ., 819, 153104, https://doi.org/10.1016/j.scitotenv.2022.153104, 2022.
Hsu, Y., Divita, F., and Dorn, J.: SPECIATE 5.0 – Speciation Database Development Documentation, Final Report, Abt Associates Inc./Office of Research and Development/U.S. Environmental Protection Agency Research Triangle Park, NC27711, [data set], https://www.epa.gov/sites/default/files/2019-07/speciate_5.0_0.zip (last access: 14 November 2023), 2019.
Huang, C. H., Hu, J. L., Xue, T., Xu, H., and Wang, M.: High-Resolution Spatiotemporal Modeling for Ambient PM2.5 Exposure Assessment in China from 2013 to 2019, Environ. Sci. Technol., 55, 2152–2162, https://doi.org/10.1021/acs.est.0c05815, 2021.
Huang, Z. J., Zheng, J. Y., Qu, J. M., Zhong, Z. M., Wu, Y. Q., and Shao, M.: A Feasible Methodological Framework for Uncertainty Analysis and Diagnosis of Atmospheric Chemical Transport Models, Environ. Sci. Technol., 53, 3110–3118, https://doi.org/10.1021/acs.est.8b06326, 2019.
Ji, Z., Gan, M., Fan, X., Chen, X., Li, Q., Lv, W., Tian, Y., Zhou, Y., and Jiang, T.: Characteristics of PM2.5 from iron ore sintering process: Influences of raw materials and controlling methods, J. Clean. Prod., 148, 12–22, https://doi.org/10.1016/j.jclepro.2017.01.103, 2017.
Li, J., Wu, Y., Ren, L., Wang, W., Tao, J., Gao, Y., Li, G., Yang, X., Han, Z., and Zhang, R.: Variation in PM2.5 sources in central North China Plain during 2017–2019: Response to mitigation strategies, J. Environ. Manage., 28, 112370, https://doi.org/10.1016/j.jenvman.2021.112370, 2021.
Li, M., Hu, M., Du, B., Guo, Q., Tan, T., Zheng, J., Huang, X., He, L., Wu, Z., and Guo, S.: Temporal and spatial distribution of PM2.5 chemical composition in a coastal city of Southeast China, Sci. Total Environ., 605–606, 337–346, https://doi.org/10.1016/j.scitotenv.2017.03.260, 2017a.
Li, M., Liu, H., Geng, G., Hong, C., Liu, F., Song, Y., Tong, D., Zheng, B., Cui, H., Man, H., Zhang, Q., and He, K.: Anthropogenic emission inventories in China: a review, Natl. Sci. Rev., 4, 834–866, https://doi.org/10.1093/nsr/nwy044, 2017b.
Li, X., He, K., Li, C., Yang, F., Zhao, Q., Ma, Y., Chen, Y., Ouyang, W., and Chen, G.: PM2.5 mass, chemical composition, and light extinction before and during the 2008 Beijing Olympics, J. Geophys. Res., 118, 12158–12167, https://doi.org/10.1002/2013JD020106, 2013.
Liang, F., Xiao, Q., Yang, X., Liu, F., Li, J., Lu, X., Liu, Y., and Gu, D.: The 17-y spatiotemporal trend of PM2.5 and its mortality burden in China, P. Natl. Acad. Sci. USA, 117, 25601–25608, https://doi.org/10.1073/pnas.1919641117, 2020.
Luo, Z.: The effect of emission source chemical profiles on simulated PM2.5 components: sensitivity analysis with CMAQ 5.0.2, Zenodo [data set], https://doi.org/10.5281/zenodo.10122628, 2022.
Lv, L., Wei, P., Li, J., and Hu, J.: Application of machine learning algorithms to improve numerical simulation prediction of PM2.5 and chemical components, Atmos. Pollut. Res., 12, 101211, https://doi.org/10.1016/j.apr.2021.101211, 2021.
National Centers for Environmental Prediction/National Weather Service/NOAA/U.S. Department of Commerce: NCEP FNL Operational Model Global Tropospheric Analyses, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory [data set], https://doi.org/10.5065/D6M043C6, 2000.
National Centers for Environmental Prediction/National Weather Service/NOAA/U.S. Department of Commerce: NCEP ADP Global Surface Observational Weather Data, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory [data set], https://doi.org/10.5065/4F4P-E398, 2004.
NBS (National Bureau of Stastistics of China): China Statistical Yearbook 2021, http://www.stats.gov.cn/sj/ndsj/2021/indexch.htm (last access: 14 November 2023), 2021.
Peterson, G., Hogrefe, C., Corrigan, A., Neas, L., Mathur, R., Rappold, A.: Impact of Reductions in Emissions from Major Source Sectors on Fine Particulate Matter–Related Cardiovascular Mortality, Environ. Health Persp., 128, 017005, https://doi.org/10.1289/EHP5692, 2020.
Qi, H., Cui, C., Zhao, T., Bai, Y., and Liu, L.: Numerical simulation on the characteristics of PM2.5 heavy pollution and the influence of weather system in Hubei Province in winter 2015, Meteorological Monthly, 45, 1113–1122, ISBN 1000-0526, 2019 (in Chinese).
Satellite Services Division/Office of Satellite Data Processing and Distribution/NESDIS/NOAA/U.S. Department of Commerce, and National Centers for Environmental Prediction/National Weather Service/NOAA/U.S. Department of Commerce: NCEP ADP Global Upper Air Observational Weather Data, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, [data set], https://doi.org/10.5065/39C5-Z211, 2004.
Seinfeld, J. H. and Pandis, S. N.: Atmospheric Chemistry and Physics, from air pollution to climate change, John Wiley & Sons, Inc., Hoboken, New Jersey, 47–61, ISBN9781119221166, 2006.
Sha, T., Ma, X., Jia, H., Tian, R., Chang, Y., Cao, F., and Zhang, Y.: Aerosol chemical component: Simulations with WRF-Chem and comparison with observations in Nanjing, Atmos. Environ., 218, 1–14, https://doi.org/10.1016/j.atmosenv.2019.116982, 2019.
Shi, W., Liu, C., Norback, D., Deng, Q., Huang, C., Qian, H., Zhang, X., Sundell, J., Zhang, Y., Li, B., Kan, H., and Zhao, Z.: Effects of fine particulate matter and its constituents on childhood pneumonia: a cross-sectional study in six Chinese cities, Lancet, 392, s79, https://doi.org/10.1016/S0140-6736(18)32708-9, 2018.
Shi, Z., Li, J., Huang, L., Wang, P., Wu, L., Ying, Q., Zhang, H., Lu, L., Liu, X., Liao, H., and Hu, J.: Source apportionment of fine particulate matter in China in 2013 using a source-oriented chemical transport model, Sci. Total Environ., 601–602, 1476–1487, https://doi.org/10.1016/j.scitotenv.2017.06.019, 2017.
Skamarock, W., Klemp, J., Dudhia, J., Gill, D., Barker, D., Duda, D., Huang, X., Wang, W., and Powers, J.: A Description of the Advanced Research WRF Version 3, NCAR Tech. [code], https://doi.org/10.5065/D68S4MVH, 2008.
Song, S. Y., Wang, Y. S., Wang, Y. L., Wang, T., and Tan, H. Z.: The characteristics of particulate matter and optical properties of Brown carbon in air lean condition related to residential coal combustion, Powder Technol., 379, 505–514, https://doi.org/10.1016/j.powtec.2020.10.082, 2021.
Tang, X. Y., Zhang, Y. H., and Shao, M.: Atmosphere Environment Chemistry, 2nd Edn., Higher Education Press, Beijing, China, 268–329, ISBN 978-7-04-019361-9, 2006 (in Chinese).
US EPA Office of Research and Development: CMAQv5.0.2 (5.0.2), Zenodo [code], https://doi.org/10.5281/zenodo.1079898, 2014.
Wang, C., Zheng, J., Du, J., Wang, G., Klemes, J., Wang, B., Liao, Q., and Liang, Y.: Weather condition-based hybrid models for multiple air pollutants forecasting and minimisation, J. Clean. Prod., 352, 131610, https://doi.org/10.1016/j.jclepro.2022.131610, 2022.
Wang, D., Hu, J., Xu, Y., Lv, D., Xie, X., Kleeman, M., Xing, J., Zhang, H., and Ying, Q.: Source contributions to primary and secondary inorganic particulate matter during a severe wintertime PM2.5 pollution episode in Xi'an, China, Atmos. Environ., 97, 182–194, https://doi.org/10.1016/j.atmosenv.2014.08.020, 2014.
Weagle, C., Sinder, G., Li, C. C., Donkelaar, A., S, P., Bissonnette, P., Burke, I., Jackson, J., Latimer, R., Stone, E., Abboud, I., Akoshile, C., Anh, N., Brook, J., Cohen, A., Dong, J., Gibson, M., Griffith, D., He, K., Holben, B., Kahn, R., Keller, C., Kim, J., Lagrosas, N., Lestari, P., Khian, Y., Liu, Y., Marais, E., Martins, J., Misra, A., Muliane, U., Pratiwi, R., Quel, E., Salam, A., Segey, L., Tripathi, S., Wang, C., Zhang, Q., Brauer, M., Rudich, Y., and Martin, R.: Global Sources of Fine Particulate Matter: Interpretation of PM2.5 Chemical Composition Observed by SPARTAN using a Global Chemical Transport Model, Environ. Sci. Technol., 52, 11670–11681, https://doi.org/10.1021/acs.est.8b01658, 2018.
Wongphatarakul, V., Friedlander, S. K., and Pinto, J. P.: A Comparative Study of PM2.5 Ambient Aerosol Chemical Databases, Environ. Sci. Technol., 32, 3926–3934, https://doi.org/10.1021/es9800582, 1998.
Wu, B., Bai, X., Liu, W., Zhu, C., Hao, Y., Lin, S., Liu, S., Luo, L., Liu, X., Zhao, S., Hao, J., and Tian, H.: Variation characteristics of final size-segregated PM emissions from ultralow emission coal-fired power plants in China, Environ. Pollut., 259, 113886, https://doi.org/10.1016/j.envpol.2019.113886, 2020.
Wu, D., Zheng, H., Li, Q., Jin, L., Lyu, R., Ding, X., Huo, Y., Zhao, B., Jiang, J., Chen, J., Li, X., and Wang, S.: Toxic potency-adjusted control of air pollution for solid fuel combustion, Nat. Energ., 7, 194–202, https://doi.org/10.1038/s41560-021-00951-1, 2022.
Wu, Z. X., Hu, T. F., Hu, W., Shao, L. Y., Sun, Y. Z., Xue, F. L., and Niu, H. Y.: Evolution in physicochemical properties of fine particles emitted from residential coal combustion based on chamber experiment, Gondwana Res., 110, 252–263, https://doi.org/10.1016/j.gr.2021.10.017, 2021.
Xia, Z. Q., Fan, X. L., Huang, Z. J., Liu, Y. C., Yin, X. H., Ye, X., and Zheng, J. Y.: Comparison of Domestic and Foreign PM2.5 Source Profiles and Influence on Air Quality Simulation, Res. Environ. Sci., 30, 359–367, https://doi.org/10.13198/j.issn.1001-6929.2017.01.55, 2017 (in Chinese).
Yang, F., Tan, J., Zhao, Q., Du, Z., He, K., Ma, Y., Duan, F., Chen, G., and Zhao, Q.: Characteristics of PM2.5 speciation in representative megacities and across China, Atmos. Chem. Phys., 11, 5207–5219, https://doi.org/10.5194/acp-11-5207-2011, 2011.
Ying, Q., Feng, M., Song, D. L., Wu, L., Hu, J., Zhang, H., Kleeman, M., and Li, X.: Improve regional distribution and source apportionment of PM2.5 trace elements in China using inventory-observation constrained emission factors, Sci. Total Environ., 624, 355–365, https://doi.org/10.1016/j.scitotenv.2017.12.138, 2018.
Yu, S., Mathur, R., Pleim, J., Wong, D., Gilliam, R., Alapaty, K., Zhao, C., and Liu, X.: Aerosol indirect effect on the grid-scale clouds in the two-way coupled WRF–CMAQ: model description, development, evaluation and regional analysis, Atmos. Chem. Phys., 14, 11247–11285, https://doi.org/10.5194/acp-14-11247-2014, 2014.
Yu, Z. C., Jang, M., Kim, S., Bae, C., Koo, B., Beardsley, R., Park, J., Chang, L., Lee, H., Lim, Y., Cho, J.: Simulating the Impact of Long-Range-Transported Asian Mineral Dust on the Formation of Sulfate and Nitrate during the KORUS-AQ Campaign, Earth Space Chem., 4, 1039–1049, https://doi.org/10.1021/acsearthspacechem.0c00074, 2020.
Zhang, J., Wu, J., Lv, R., Song, D., Huang, F., Zhang, Y., and Feng, Y.: Influence of Typical Desulfurization Process on Flue Gas Particulate Matter of Coal-fired Boilers, Environ. Sci., 41, 4455–4461, https://doi.org/10.13227/j.hjkx.202003193, 2020 (in Chinese).
Zhang, Q., Xue, D., Wang, S., Wang, L., Wang, J., Ma, Y., and Liu, X.: Analysis on the evolution of PM2.5 heavy air pollution process in Qingdao (In Chinese), China Environ. Sci., 37, 3623–3635, https://doi.org/10.3969/j.issn.1000-6923.2017.10.003, 2017.
Zhang, S. P., Xing, J., Sarwar, G., Ge, Y. L., He, H., Duan, F., Zhao, Y., He, K., Zhu, L., and Chu, B.: Parameterization of heterogeneous reaction of SO2 to sulfate on dust with coexistence of NH3 and NO2 under different humidity conditions, Atmos. Environ., 208, 133–140, https://doi.org/10.1016/j.atmosenv.2019.04.004, 2019.
Zheng, B., Tong, D., Li, M., Liu, F., Hong, C., Geng, G., Li, H., Li, X., Peng, L., Qi, J., Yan, L., Zhang, Y., Zhao, H., Zheng, Y., He, K., and Zhang, Q.: Trends in China's anthropogenic emissions since 2010 as the consequence of clean air actions, Atmos. Chem. Phys., 18, 14095–14111, https://doi.org/10.5194/acp-18-14095-2018, 2018.
Zheng, B., Zhang, Q., Zhang, Y., He, K. B., Wang, K., Zheng, G. J., Duan, F. K., Ma, Y. L., and Kimoto, T.: Heterogeneous chemistry: a mechanism missing in current models to explain secondary inorganic aerosol formation during the January 2013 haze episode in North China, Atmos. Chem. Phys., 15, 2031–2049, https://doi.org/10.5194/acp-15-2031-2015, 2015.
Zheng, H., Song, S., Sarwar, G., Gen, M., Wang, S., Ding, D., Chang, X., Zhang, S., Xing, J., Sun, Y. L., Ji, D., Chan, C. K., Gao, J., and Mcelory, M.: Contribution of Particulate Nitrate Photolysis to Heterogeneous Sulfate Formation for Winter Haze in China, Environ. Sci. Technol. Lett., 7, 632–638, https://doi.org/10.1021/acs.estlett.0c00368, 2020.
Zhou, L., Chen, X., and Tian, X.: The impact of fine particulate matter (PM2.5) on China's agricultural production from 2001 to 2010, J. Clean. Prod., 178, 133–141, https://doi.org/10.1016/j.jclepro.2017.12.204, 2018.
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...
