Anthropogenic Drivers of Hourly Air Pollutant Change in an Urban Environment during 2019–2021—A Case Study in Wuhan
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Wuhan experienced a noticeable enhancement in air quality from January to April 2020 due to the epidemic lockdown. The improvement was a combined result of anthropogenic emission reduction and meteorological variability. Environmental policymakers are often concerned about the impact of industrial production and human activities on improvements in environmental sustainability. This study split and quantified the impact of anthropogenic emissions on the pollution level changes of six major air pollutants (CO, SO2, NO2, O3, PM10, and PM2.5) for the first half year of 2019 to 2021 in Wuhan with an improved meteorological normalization algorithm. The results show sharp decreases in anthropogenic pollutant loads during 2020, except for O3, with the ranking of NO2 > PM10 > SO2 > CO > PM2.5. The decrease in NO2 emissions caused by humans was more than 50% compared to 2019. The low NO2 led to a decrease in O3 consumption, resulting in high O3 concentrations from February to April 2020 during the city lockdown. Moreover, except O3, the impact of anthropogenic and weather influences on air pollution exhibited opposing effects; that is, meteorology tended to aggravate pollution, while human intervention was conducive to improving air quality, and human factors played the dominant role. Of all six pollutants, O3 is the one that is relatively least subject to anthropogenic emissions. Although concentrations of SO2, NO2, PM10, and PM2.5 rebounded in 2021, none of them were able to return to their pre-lockdown levels, suggesting the epidemic’s continuous inhibition of people’s activities. Compared with 2019 and 2021, the atmospheric oxidation capacity and secondary aerosol formation showed an overall decreasing trend during 2020. This study provides a reference for assessing the effectiveness of anthropogenic emission reduction policies.Keywords:
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This study explored the relationship between the actual level of air pollution and residents’ concern about air pollution. The actual air pollution level was measured by the air quality index (AQI) reported by environmental monitoring stations, while residents’ concern about air pollution was reflected by the Baidu index using the Internet search engine keywords “Shanghai air quality”. On the basis of the daily data of 2068 days for the city of Shanghai in China over the period between 2 December 2013 and 31 July 2019, a vector autoregression (VAR) model was built for empirical analysis. Estimation results provided three interesting findings. (1) Local residents perceived the deprivation of air quality and expressed their concern on air pollution quickly, within the day on which the air quality index rose. (2) A decline in air quality in another major city, such as Beijing, also raised the concern of Shanghai residents about local air quality. (3) A rise in Shanghai residents’ concern had a beneficial impact on air quality improvement. This study implied that people really cared much about local air quality, and it was beneficial to inform more residents about the situation of local air quality and the risks associated with air pollution.
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The air quality in Taiwan, at present, is determined by a pollution standard index (PSI) that is applied to areas of possible serious air pollution and Air Quality Total Quantity Control Districts (AQTQCD). Many studies, both in Taiwan and in other countries have examined the characteristics and levels of air pollution with PSI. This study uses air quality data collected from eight automatic air quality monitoring stations in an AQTQCD in central Taiwan and discusses the correlation between air quality variables with statistical analysis in an attempt to accurately reflect the difference of air quality observed by each monitoring station as well as to establish an air quality classification system suitable for the whole Taiwan. After using factor analysis (FA), seven air pollutants are grouped into three factors: organic, photochemical, and fuel. These three factors are the dominant ones in regards to the air quality of central Taiwan. Cluster analysis is used to classify air quality in central Taiwan into five clusters to present different characteristics and pollution degrees of air quality. This research results should serve as a reference for those involved in the review of air quality management effectiveness and/or the enactment of management control strategies.
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