Niu Zhi, Hu Tingting, Kong Lin, Zhang Wenqi, Rao Pinhua, Ge Dafeng, Zhou Mengge, Duan Yuseng
Shool of Chemistry and Chemical Engineering, Shanghai University of Engineering Science, Shanghai, 201620 China.
School of Atmospheric Sciences, Nanjing University, Nanjing, 210023 China.
Air Qual Atmos Health. 2021;14(4):523-532. doi: 10.1007/s11869-020-00956-x. Epub 2020 Oct 21.
To curb the spread of the coronavirus, China implemented lockdown policies on January 23, 2020. The resulting extreme changes in human behavior may have influenced the air pollutants concentration. However, despite these changes, hazy weather persisted in Shanghai and became a public issue. This study aims to investigate air pollutant mass concentration changes during the lockdown in Shanghai. Air pollutant mass concentration data and meteorological data during the pre-lockdown period and the level I response lockdown period were analyzed by statistical analysis and a Lagrangian particle diffusion model. The data was classified in three periods: P1 (pre-lockdown: 10 days before the Spring Festival), P2 (the first 10 days after lockdown: during the Spring Festival celebration), and P3 (the second 10 days after lockdown: after the Spring Festival). Data for the same period in 2019 were used as a reference. The results indicate that the Spring Festival holiday in 2019 resulted in a reduction in energy consumption, which led to a decrease in PM (26.4%) and NO (43.41%) mass concentration, but an increase in ozone mass concentration (31.39%) in P2 compared with P1. The integrated effect of the Spring Festival holiday and lockdown in 2020 resulted in a decrease in PM (36.5%) and NO (51.9%) mass concentrations, but an increase in ozone mass concentration (43.8%) in P2 compared with P1. After the Spring Festival, the mass concentrations of PM, SO, and NO increased by 74.41%, 5.52%, and 53.28%, respectively in P3 compared with P2 in 2019. However, PM and SO concentrations in 2020 continued to decrease, by 14.74% and 4.61%, respectively, while NO mass concentration increased by 7.82% in P3 compared with P2. We also found that PM mass concentration is susceptible to regional transmission from the surrounding cities. PM and other gaseous pollutants show different correlations in different periods, while NO and O always show a strong negative correlation. The principal components before the Spring Festival in 2019 were O and NO, and after the Spring Festival, they were PM and CO, while the principal components before the lockdown in 2020 were PM and CO, and during lockdown they were O and NO.
为遏制新冠病毒传播,中国于2020年1月23日实施了封锁政策。人类行为由此产生的极端变化可能影响了空气污染物浓度。然而,尽管有这些变化,上海的雾霾天气仍持续存在并成为一个公共问题。本研究旨在调查上海封锁期间空气污染物质量浓度的变化。通过统计分析和拉格朗日粒子扩散模型,分析了封锁前时期和一级响应封锁时期的空气污染物质量浓度数据及气象数据。数据分为三个时期:P1(封锁前:春节前10天)、P2(封锁后前10天:春节期间)和P3(封锁后第二个10天:春节后)。将2019年同期数据作为参考。结果表明,2019年春节假期导致能源消耗减少,这使得P2期的PM(26.4%)和NO(43.41%)质量浓度降低,但臭氧质量浓度增加(31.39%),与P1期相比。2020年春节假期和封锁的综合影响导致P2期的PM(36.5%)和NO(51.9%)质量浓度降低,但臭氧质量浓度增加(43.8%),与P1期相比。春节后,2019年P3期的PM、SO和NO质量浓度分别比P2期增加了74.41%、5.52%和53.28%。然而,2020年的PM和SO浓度继续下降,分别下降了14.74%和4.61%,而P3期的NO质量浓度比P2期增加了7.82%。我们还发现,PM质量浓度易受周边城市区域传输的影响。PM和其他气态污染物在不同时期表现出不同的相关性,而NO和O始终呈现出强烈的负相关。2019年春节前的主要成分是O和NO,春节后是PM和CO,而2020年封锁前的主要成分是PM和CO,封锁期间是O和NO。