Liu, Wenhao and Ling, Xiaolu and Xue, Yong and Wu, Shuhui and Gao, Jian and Zhao, Liang and He, Botao (2024) Study on the Concentration of Top Air Pollutants in Xuzhou City in Winter 2020 Based on the WRF-Chem and ADMS-Urban Models. Atmosphere, 15 (1). p. 129. ISSN 2073-4433
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Abstract
In recent years, the issue of air pollution has garnered significant public attention globally, with a particular emphasis on the challenge of atmospheric fine particulate matter (PM2.5) pollution. The efficient and precise simulation of changes in pollutant concentrations, as well as their spatial and temporal distribution, is essential for effectively addressing the air pollution issue. In this paper, the WRF-Chem model is used to simulate the meteorological elements including temperature (T), relative humidity (RH), wind speed (WS), and pressure (P), and the concentrations of PM2.5 and PM10 atmospheric pollutants in December 2020 in Xuzhou City. Simultaneously, the ADMS-Urban model was employed to conduct a higher spatial resolution study of PM2.5 concentrations during the heavy pollution days of 11–12 December 2020 in Xuzhou City. The study shows that the WRF-Chem model can simulate the meteorological conditions of the study time period better, and the correlation coefficients (R) of pressure, temperature, wind speed, and relative humidity are 0.99, 0.87, 0.75, and 0.70, respectively. The WRF-Chem model can accurately simulate the PM2.5 concentration on clean days (R of 0.66), but the simulation of polluted days is not satisfactory. Therefore, the ADMS-Urban model was chosen to simulate the PM2.5 concentration on polluted days in the center of Xuzhou City. The ADMS-Urban model can simulate the distribution characteristics and concentration changes of PM2.5 around roads and buildings in the center of Xuzhou City. Comparing the simulation results of the two models, it was found that the two models have their own advantages in PM2.5 concentration simulation, and how to better couple the two models is the next research direction
Item Type: | Article |
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Subjects: | Apsci Archives > Multidisciplinary |
Depositing User: | Unnamed user with email support@apsciarchives.com |
Date Deposited: | 23 Jan 2024 05:21 |
Last Modified: | 23 Jan 2024 05:21 |
URI: | http://eprints.go2submission.com/id/eprint/2549 |