Literature DB >> 33447974

Changes in the concentration of air pollutants before and after the COVID-19 blockade period and their correlation with vegetation coverage.

Manguo Zhou1, Yanguo Huang2, Guilan Li1.   

Abstract

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 NO2 in different regions dropped the most, but the increase in O3 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.

Entities:  

Keywords:  Air pollution; Air quality; COVID-19; Correlation coefficient; Lockdown; Vegetation cover

Mesh:

Substances:

Year:  2021        PMID: 33447974      PMCID: PMC7808704          DOI: 10.1007/s11356-020-12164-2

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  5 in total

Review 1.  Impact of COVID-19 Pandemic on Air Quality: A Systematic Review.

Authors:  Ana Catarina T Silva; Pedro T B S Branco; Sofia I V Sousa
Journal:  Int J Environ Res Public Health       Date:  2022-02-10       Impact factor: 3.390

2.  Diverse spillover effects of COVID-19 control measures on air quality improvement: evidence from typical Chinese cities.

Authors:  Laijun Zhao; Yu Wang; Honghao Zhang; Ying Qian; Pingle Yang; Lixin Zhou
Journal:  Environ Dev Sustain       Date:  2022-04-25       Impact factor: 4.080

3.  Urban air quality changes resulting from the lockdown period due to the COVID-19 pandemic.

Authors:  D Galán-Madruga
Journal:  Int J Environ Sci Technol (Tehran)       Date:  2022-08-20       Impact factor: 3.519

4.  Evaluation of urban green space per capita with new remote sensing and geographic information system techniques and the importance of urban green space during the COVID-19 pandemic.

Authors:  Sima Pouya; Majid Aghlmand
Journal:  Environ Monit Assess       Date:  2022-08-03       Impact factor: 3.307

5.  Estimating ground-level PM2.5 over Bangkok Metropolitan Region in Thailand using aerosol optical depth retrieved by MODIS.

Authors:  Bussayaporn Peng-In; Peeyaporn Sanitluea; Pimnapat Monjatturat; Pattaraporn Boonkerd; Arthit Phosri
Journal:  Air Qual Atmos Health       Date:  2022-08-26       Impact factor: 5.804

  5 in total

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