Zhou Manguo, Huang Yanguo, Li Guilan
Jiangxi University of Science and Technology School of Electrical Engineering and Automation, Ganzhou, China.
Environ Sci Pollut Res Int. 2021 May;28(18):23405-23419. doi: 10.1007/s11356-020-12164-2. Epub 2021 Jan 14.
In order to control the spread of COVID-19, China had implemented strict lockdown measures. The closure of cities had had a huge impact on human production and consumption activities, which had greatly reduced population mobility. This article used air pollutant data from 341 cities in mainland China and divided these cities into seven major regions based on geographic conditions and climatic environment. The impact of urban blockade on air quality during COVID-19 was studied from the perspectives of time, space, and season. In addition, this article used Normalized Difference Vegetation Index (NDVI) to systematically analyze the characteristics of air pollution in the country and used the Pearson correlation coefficient to explore the relationship between NDVI and the air pollutant concentrations during the COVID-19 period. Then, linear regression was used to find the quantitative relationship between NDVI and AQI, and the fitting effect of the model was found to be significant through t test. Finally, some countermeasures were proposed based on the analysis results, and suggestions were provided for improving air quality. This paper has drawn the following conclusions: (1) the concentration of pollutants varied greatly in different regions, and the causes of their pollution sources were also different. The region with the largest decline in AQI was the Northeast China (60.01%), while the AQI in the southwest China had the smallest change range, and its value had increased by 1.72%. In addition, after the implementation of the city blockade, the concentration of NO in different regions dropped the most, but the increase in O was more obvious. (2) Higher vegetation coverage would have a beneficial impact on the atmospheric environment. Areas with higher NDVI values have relatively low AQI. There is a negative correlation between NDVI and AQI, and an average increase of 0.1 in NDVI will reduce AQI by 3.75 (95% confidence interval). In the case of less human intervention, the higher the vegetation coverage, the lower the local pollutant concentration will be. Therefore, the degree of vegetation coverage would have a direct or indirect impact on air pollution.
为控制新冠疫情传播,中国实施了严格的封锁措施。城市封控对人类生产和消费活动产生了巨大影响,极大地减少了人口流动。本文利用中国大陆341个城市的空气污染物数据,并根据地理条件和气候环境将这些城市划分为七个主要区域。从时间、空间和季节的角度研究了新冠疫情期间城市封锁对空气质量的影响。此外,本文利用归一化植被指数(NDVI)系统分析了全国空气污染特征,并利用皮尔逊相关系数探讨了新冠疫情期间NDVI与空气污染物浓度之间的关系。然后,采用线性回归方法找出NDVI与空气质量指数(AQI)之间的定量关系,并通过t检验发现模型的拟合效果显著。最后,根据分析结果提出了一些对策,并为改善空气质量提供了建议。本文得出以下结论:(1)不同地区污染物浓度差异很大,其污染源成因也不同。空气质量指数下降幅度最大的地区是中国东北地区(60.01%),而中国西南地区空气质量指数变化范围最小,其值上升了1.72%。此外,城市封锁实施后,不同地区的一氧化氮(NO)浓度下降最多,但臭氧(O)的增加更为明显。(2)较高的植被覆盖率对大气环境有有益影响。归一化植被指数值较高的地区空气质量指数相对较低。NDVI与AQI之间存在负相关关系,NDVI平均每增加0.1,AQI将降低3.75(95%置信区间)。在人类干预较少的情况下,植被覆盖率越高,当地污染物浓度越低。因此,植被覆盖程度会对空气污染产生直接或间接影响。