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Liu Z, Wang H, Zhang L, Zhou Y, Zhang W, Peng Y, Zhang Y, Che H, Zhao M, Hu J, Liu H, Wang Y, Li S, Han C, Zhang X. Incorporation and improvement of a heterogeneous chemistry mechanism in the atmospheric chemistry model GRAPES_Meso5.1/CUACE and its impacts on secondary inorganic aerosol and PM 2.5 simulations in Middle-Eastern China. Sci Total Environ 2022; 847:157530. [PMID: 35878848 DOI: 10.1016/j.scitotenv.2022.157530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 07/13/2022] [Accepted: 07/16/2022] [Indexed: 06/15/2023]
Abstract
Heterogeneous chemistry is considered one of the critical pathways of secondary inorganic aerosol (SIA) productions. In this study, a heterogeneous chemistry mechanism is incorporated into the atmospheric chemistry model GRAPES_Meso5.1/CUACE. Varying uptake coefficient schemes of SO2 and NO2 are compared and the equivalent ratio of inorganic aerosol (ER)-dependent scheme for SO2 and relative humidity (RH)/ER-dependent scheme for NO2 are used to form the improved heterogeneous chemistry. Focusing on a severe haze episode in Middle-Eastern China, the impacts of heterogeneous mechanism on SIA and PM2.5 composition are investigated based on the updated model. Study results show that the differences in RH or ER uptake coefficients result in obvious differences in sulfate and nitrate concentrations, especially during the severe pollution period, because the ER schemes restrict the excessive production of sulfate and nitrate under high RH effectively by including the self-limitation of heterogeneous reactions, which shows better performance in capturing the magnitude and temporal variations of surface SIA and PM2.5. Normalized mean bias of sulfate, nitrate, ammonium, and PM2.5 in megacity Beijing decreases from -27.0, -28.3, -58.2, and -26.3 to 1.0, -2.2, -47.2, and -16.5 %, respectively. And the fractions of sulfate, nitrate, ammonium, and organics during the polluted period change from 13.7, 19.3, 6.9, and 60.1 to 16.5, 23.0, 7.6, and 52.9 %, respectively, which is more consistent with the observation (16.0, 23.2, 14.1, and 46.7 %). SIA and PM2.5 simulations in another megacity Shanghai have the similar improvements. The modeled SIA by heterogeneous processes contributes 11.7 % of total PM2.5 in Beijing and 22.5 % in Shanghai. That is 13.5 % in the Chinese megalopolis Beijing-Tianjin-Hebei and 19.8 % in Yangtze-River-Delta, indicating a considerable contribution of heterogeneous pathways to haze pollution. This work indicates the importance of detailed and reasonable heterogeneous schemes for better SIA and haze/fog prediction in the atmospheric chemistry model.
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Affiliation(s)
- Zhaodong Liu
- State Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, China; Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Hong Wang
- State Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, China.
| | - Lei Zhang
- State Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, China
| | - Yike Zhou
- National Meteorological Information Center, China Meteorological Administration, Beijing 100081, China
| | - Wenjie Zhang
- State Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, China
| | - Yue Peng
- State Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, China
| | - Yangmei Zhang
- State Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, China
| | - Huizheng Che
- State Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, China
| | - Mengchu Zhao
- School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
| | - Jianlin Hu
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Jiangsu Engineering Technology Research Center of Environmental Cleaning Materials, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Hongli Liu
- State Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, China
| | - Yaqiang Wang
- State Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, China
| | - Siting Li
- State Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, China
| | - Chen Han
- State Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, China
| | - Xiaoye Zhang
- State Key Laboratory of Severe Weather (LASW), Chinese Academy of Meteorological Sciences (CAMS), CMA, Beijing 100081, China
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Zhou Y, Gong S, Zhou C, Zhang L, He J, Wang Y, Ji D, Feng J, Mo J, Ke H. A new parameterization of uptake coefficients for heterogeneous reactions on multi-component atmospheric aerosols. Sci Total Environ 2021; 781:146372. [PMID: 33784528 DOI: 10.1016/j.scitotenv.2021.146372] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 03/03/2021] [Accepted: 03/05/2021] [Indexed: 06/12/2023]
Abstract
Based on laboratory studies and field observations, a new parameterization of uptake coefficients for heterogeneous reactions on multi-component aerosols is developed in this work. The equivalent ratio (ER) of inorganic aerosol is used to establish the quantitative relationship between the heterogeneous uptake coefficients and the composition of aerosols. Incorporating the new ER-dependent scheme, the WRF-CUACE model has been applied to simulate sulfate mass concentrations during December 2017 in the Beijing-Tianjin-Hebei region and evaluate the role of aerosol chemical components played in the sulfate formation. Simulated temporal variations and magnitudes of sulfate show good agreement with the observations by using this new scheme. From clean to polluted cases, although both dominant cations and anions increase significantly, the equivalent ratio decreases gradually and is closer to unity, representing the variation of aerosol compositions, which inhibits the heterogeneous uptake of SO2, with the uptake coefficient decreasing from 1 × 10-4 to 5.3 × 10-5. Based on this phenomenon, a self-limitation process for heterogeneous reactions with the increasing secondary inorganic aerosol from clean to polluted cases is proposed.
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Affiliation(s)
- Yike Zhou
- Climate and Weather Disasters Collaborative Innovation Center, Nanjing University of Information Science & Technology, Nanjing 210044, China; State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Sunling Gong
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China.
| | - Chunhong Zhou
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Lei Zhang
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China.
| | - Jianjun He
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Yuesi Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Dongsheng Ji
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Jianing Feng
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Jingyue Mo
- Climate and Weather Disasters Collaborative Innovation Center, Nanjing University of Information Science & Technology, Nanjing 210044, China; State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Huabing Ke
- Climate and Weather Disasters Collaborative Innovation Center, Nanjing University of Information Science & Technology, Nanjing 210044, China; State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
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