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中国 COVID-19 期间空气质量的变化。

Changes in Air Quality during the Period of COVID-19 in China.

机构信息

School of Economics and Management, China University of Geosciences (Beijing), Beijing 100083, China.

Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Natural Resources, Beijing 100083, China.

出版信息

Int J Environ Res Public Health. 2022 Dec 2;19(23):16119. doi: 10.3390/ijerph192316119.

Abstract

This paper revisits the heterogeneous impacts of COVID-19 on air quality. For different types of Chinese cities, we analyzed the different degrees of improvement in the concentrations of six air pollutants (PM2.5, PM10, SO, NO, CO, and O) during COVID-19 by analyzing the predictivity of air quality. Specifically, we divided the sample into three groups: cities with severe outbreaks, cities with a few confirmed cases, and cities with secondary outbreaks. Ensemble empirical mode decomposition (EEMD), recursive plots (RPs), and recursive quantitative analysis (RQA) were used to analyze these heterogeneous impacts and the predictivity of air quality. The empirical results indicated the following: (1) COVID-19 did not necessarily improve air quality due to factors such as the rebound effect of consumption, and its impacts on air quality were short-lived. After the initial outbreak, NO, CO, and PM2.5 emissions declined for the first 1-3 months. (2) For the cities with severe epidemics, air quality was improved, but for the cities with second outbreaks, air quality was first enhanced and then deteriorated. For the cities with few confirmed cases, air quality first deteriorated and then improved. (3) COVID-19 changed the stability of the air quality sequence. The predictability of the air quality index (AQI) declined in cities with serious epidemic situations and secondary outbreaks, but for the cities with a few confirmed cases, the AQI achieved a stable state sooner. The conclusions may facilitate the analysis of differences in air quality evolution characteristics and fluctuations before and after outbreaks from a quantitative perspective.

摘要

本文重新探讨了 COVID-19 对空气质量的异质影响。对于不同类型的中国城市,我们通过分析空气质量的可预测性,分析了 COVID-19 期间六种空气污染物(PM2.5、PM10、SO、NO、CO 和 O)浓度的不同改善程度。具体来说,我们将样本分为三组:疫情严重的城市、确诊病例较少的城市和二次爆发的城市。我们使用集合经验模态分解(EEMD)、递归图(RPs)和递归定量分析(RQA)来分析这些异质影响和空气质量的可预测性。实证结果表明:(1)由于消费反弹等因素,COVID-19 不一定会改善空气质量,而且其对空气质量的影响是短暂的。在最初爆发后,NO、CO 和 PM2.5 的排放量在最初的 1-3 个月内下降。(2)对于疫情严重的城市,空气质量得到了改善,但对于二次爆发的城市,空气质量先是得到了改善,然后又恶化了。对于确诊病例较少的城市,空气质量先是恶化,然后又得到了改善。(3)COVID-19 改变了空气质量序列的稳定性。严重疫情和二次爆发城市的空气质量指数(AQI)的可预测性下降,但对于确诊病例较少的城市,AQI 更快地达到了稳定状态。这些结论可能有助于从定量角度分析爆发前后空气质量演变特征和波动的差异。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ed7/9737528/9f5c5d45b4a0/ijerph-19-16119-g001.jpg

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