Impact of Meteorological Conditions and Human Activities on Air Quality During the COVID-19 Lockdown in Northeast China
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During the lockdown implemented to curb the spread of COVID-19, human activities have drastically reduced, providing a valuable opportunity to study and compare the impact of meteorological conditions and human activities on air quality. In this study, large-scale weather circulation, local meteorological conditions, and the impact of human activities are comprehensively considered, and changes in the concentration of major air pollutants in the northeast during this period are systematically studied. The large-scale weather circulation patterns that mainly affect the northeast region are divided into nine types by using the T-mode Principal components analysis objective circulation classification method. It is found that the northeast region is located at the edge of weak high pressure (Types 1, 2, and 7) and at the rear of high pressure (Type 4) and has higher concentrations of PM2.5, NO 2 , SO 2 , and CO; in cyclonic weather systems, low vortices (Types 3 and 5) and under the influence of the updraft (Type 6) in front of the trough, the ozone concentration is higher. The changes in the concentrations of PM2.5, NO 2 , CO, SO 2 , and O 3 in the three cities, namely Shenyang, Changchun, and Harbin, during the lockdown period are compared, and it is found that the concentrations of PM2.5, NO 2 , CO, and SO 2 have a tendency to first decrease and then increase, while the changes of O 3 concentration are cyclical and increased significantly during this period. This demonstrates that pollutants such as PM2.5, NO 2 , CO, and SO 2 are more susceptible to human activities and local meteorological conditions, and changes in O 3 concentration are more closely related to changes in weather circulation types. Finally, the FLEXPART-WRF model is used to simulate the pollution process of nine circulation types, which confirms that particulate pollution in the northeast is mainly affected by local emissions and local westward sinking airflow.Keywords:
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Shenzhen is China’s top ten clean air city and the cleanest air megacity. Even so, epidemiologic studies have shown ambient air pollution had significant adverse impacts on human health in this less polluted city. In this study, the concentrations of six criteria air pollutants (PM2.5, PM10, O3, NO2, SO2, and CO) from 2014 to 2017 were analyzed and compared to thresholds of both national and international air quality standards. The results showed concentrations of all air pollutants were below target values of current national air quality standard, but levels of particulate matter (PM) and O3 were still much higher than the recommended levels by the World Health Organization. Within national air quality standards, the number of over-limit days was rare with few variations between highly polluted and low pollution areas. The air quality improvement was slowing down recently. Our results suggest annual and daily thresholds for PM are too loose for air quality improvement in Shenzhen. Hence, we call for evaluation and establishment of tougher air quality standard.
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In order to understand the temporal-spatial patterns of air pollutants in Shanghai, the concentrations of six air pollutants (SO2, NO2, PM10, PM2.5, CO, O3) and air quality index (AQI) were analyzed. The results showed that, the percentage of excellent/good-AQI days was 70.7% during the whole year of 2015, and PM2.5, O3 and NO2 were the main air pollutants in Shanghai. Besides, the air quality in winter was most serious, followed by that in spring and autumn, and the air quality in summer was the best. From the perspective of spatial distribution, monitoring stations in YangpuSipiao and Putuo which were located in the urban area were affected by traditional industries and the air quality were poor, while those in Chuansha and Zhangjiang of Pudong which were located on the edge of the city showed relatively good air quality.
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This study investigated the AQI (air quality index) and atmospheric pollutants including PM2.5, PM10, CO, SO2, NO2 and O3 in Chongqing, Luzhou and Chengdu from 2017 to 2019. In addition, the impacts of the COVID-19 event on the air quality in the three cities in 2020 were compared and discussed. For the combined AQIs for the three cities, in spring, the daily AQIs ranged between 25 and 182 and averaged 72.1. In summer, the daily AQIs ranged between 24 and 206 and averaged 77.5. In autumn, the daily AQIs ranged between 22 and 170 and averaged 61.1, and in winter, the daily AQIs ranged between 28 and 375 and averaged 99.6. The distributions of the six AQI classes in spring were 3%, 94%, 3%, 0%, 0%, and 0%; in summer, they were 11%, 74%, 15%, 0%, 0% and 0%; in autumn, they were 29%, 70%, 1%, 0%, 0%, and 0%, and in winter, they were 1%, 52%, 44%, 3%, 0%, and 0%, respectively. The average AQIs, in order, were Chengdu (85.4) > Chongqing (73.8) > Luzhou (73.2). Both the highest AQIs and PM2.5 (as the major indicatory air pollutant) occurred mainly in the low temperature season (January, December, and February), while O3 was the main air pollutant in June and August when the weather was hot. In February 2020, during the epidemic prevention and control actions taken in response to COVID-19 for the three cities, the combined AQIs for the top five days with the highest AQIs in February 2020 was 79.4, which was 23.6% lower than that from 2017–2019 (AQI = 100.7), and the average concentrations of PM2.5, PM10, SO2, CO, and NO2 were 89.4 µg m–3, 106 µg m–3, 2.31 ppb, 0.72 ppm, and 12.3 ppb, respectively, and were 17.9%, 30.8%, 83.8%, 19.8%, and 62.1%, lower than those in February 2017–2019. However, the average O3 concentration (31.8 ppb) in February 2020 rather than decreasing, increased by 6.2%. This is because a lower NO2 concentration hindered the NO + O3 reaction and led to increase O3 concentration in the ambient air.
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Air quality index (AQI) or air pollution index (API) is commonly used to report the level of severity of air pollution to public. A number of methods were developed in the past by various researchers/environmental agencies for determination of AQI or API but there is no universally accepted method exists, which is appropriate for all situations. Different method uses different aggregation function in calculating AQI or API and also considers different types and numbers of pollutants. The intended uses of AQI or API are to identify the poor air quality zones and public reporting for severity of exposure of poor air quality. Most of the AQI or API indices can be broadly classify as single pollutant index or multi-pollutant index with different aggregation method. Every indexing method has its own characteristic strengths and weaknesses that affect its suitability for particular applications. This paper attempt to present a review of all the major air quality indices developed worldwide.
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Both the air quality index (AQI) and indicatory air pollutants of Anqing, Hefei, and Suzhou near central China from 2017 to 2019, and the impact of COVID-19 epidemic prevention and control actions on air quality were investigated. The combined data for the three cities from 2017 to 2019 indicated that the lowest AQI (averaged 78.1) occurred in the summer season, for which the AQI proportions for classes I, II, III, IV, V, and VI were 25.6%, 49.9%, 21.9%, 2.7%, 0%, and 0%, respectively. The highest (AQI average of 112.6) was in winter, for which the proportions were 7.4%, 39.5%, 33.3%, 12.5%, 7.2%, and 0.1%, respectively. PM2.5, PM10, and NO2 in order were the most important indicatory air pollutants for AQI classes IV, V, and VI, which all prevailed in winter and spring, while O3 was the indicatory air pollutant that occurred most in summer. The COVID-19 event, which triggered global attention, broke out at the end of 2019. This study also investigated and compared the air quality levels in the three cities from January to March 2017–2019 with those in 2020. The results showed that during February 2020, in the three cities, the average ambient air concentrations of PM2.5, PM10, SO2, CO, and NO2 were 41.9 µg m–3, 50.1 µg m–3, 2.18 ppb, 0.48 ppm, and 8.97 ppb, and were 46.5%, 48.9%, 52.5%, 36.2%, and 52.8%, respectively, lower than those in the same month in 2017–2019, respectively. However, the O3 average concentration (80.6 ppb) did not show significant fluctuations and even slightly increased by 3.6%. This is because a lower concentration of NO2 resulted in constraints on the reaction of NO + O3, so the O3 level could not be effectively further reduced. In addition, this study also analyzed and compared the five highest daily AQIs from February 2017–2019 with those of 2020 for the three cities. The mean AQI for the 5 days with the highest daily AQI (averaged 122.6) in February 2020 was 45.1% lower than that for February 2017–2019 (averaging 223.2), and the indicatory air pollutant was always PM2.5, which decreased by 46.7% (from 173.6 to 92.6 µg m–3). It is clear that during the COVID-19 epidemic prevention and control action periods, the air quality near central China improved significantly.
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