Abstract:Using a Machine Learning Model (MLM) to decouple meteorological parameters, this paper quantified true impacts of emission reduction by pollution sources resulting from COVID-19 on air quality in Xianyang. Compared with the non-epidemic scenario, the results showed that concentrations of PM2.5, PM10, SO2, NO2, and CO in Xianyang had significantly decreased by 19.3%, 26.0%, 13.4%, 60.1% and 9.1%, respectively, with NO2 decreasing the most, SO2 and CO decreasing slightly, and O3 increased by 50.9% conversely. Under the condition that both primary emission and precursors of secondary particulate matter decreased, the concentration of PM2.5 dropped lower than expected, and O3 increased though, showing the complexity of PM2.5 and O3 control, in the meanwhile implying that the impact of operating pollution sources during the epidemic on air quality was greater than malfunctioned sources, and official regulations to restrict and suspend production in factories (similar to the impact of the pandemic) had limited improvement on air quality. In the future, emphases should be put on the treatment of operating pollution sources during the pandemic such as scattered coal and biomass combustion, heat production and supply, and crude oil processing and petroleum product manufacturing.
代兴良, 宋国君, 姜晓群, 余景娟, 方丹阳. 新冠肺炎疫情对咸阳市空气质量的影响[J]. 中国环境科学, 2021, 41(7): 3106-3114.
DAI Xing-liang, SONG Guo-jun, JIANG Xiao-qun, YU Jing-juan, FANG Dan-yang. Impacts of the COVID-19 pandemic on air quality in Xianyang. CHINA ENVIRONMENTAL SCIENCECE, 2021, 41(7): 3106-3114.
Vu T V, Shi Z, Cheng J, et al. Assessing the impact of clean air action on air quality trends in Beijing using a machine learning technique[J]. Atmos. Chem. Phys., 2019,19(17):11303-11314.
[2]
Rao S T, Zurbenko I G. Detecting and tracking changes in ozone air quality[J]. Air & Waste, 1994,44(9):1089-1092.
[3]
Libiseller C, Grimvall A. Model selection for local and regional meteorological normalisation of background concentrations of tropospheric ozone[J]. Atmospheric Environment, 2003,37(28):3923-3931.
[4]
Elminir H K. Dependence of urban air pollutants on meteorology[J]. Science of the Total Environment, 2005,350(1):225-237.
[5]
Grange S K, Carslaw D C, Lewis A C, et al. Random forest meteorological normalisation models for Swiss PM10 trend analysis[J]. Atmos. Chem. Phys., 2018,18(9):6223-6239.
[6]
Grange S K, Carslaw D C. Using meteorological normalisation to detect interventions in air quality time series[J]. Science of the Total Environment, 2019,653:578-588.
[7]
Jacob D J, Winner D A. Effect of climate change on air quality[J]. Atmospheric Environment, 2009,43(1):51-63.
[8]
Sharma S, Zhang M, Anshika, et al. Effect of restricted emissions during COVID-19 on air quality in India[J]. Science of the Total Environment, 2020,728:138878.
[9]
Sicard P, De Marco A, Agathokleous E, et al. Amplified ozone pollution in cities during the COVID-19 lockdown[J]. Science of the Total Environment, 2020,735:139542.
[10]
Venter Z S, Aunan K, Chowdhury S, et al. COVID-19 lockdowns cause global air pollution declines[J]. Proceedings of the National Academy of Sciences, 2020,117(32):18984.
[11]
Wang P, Chen K, Zhu S, et al. Severe air pollution events not avoided by reduced anthropogenic activities during COVID-19 outbreak[J]. Resources, Conservation and Recycling, 2020,158:104814.
[12]
Zhao Y, Zhang K, Xu X, et al. Substantial changes in nitrogen dioxide and ozone after excluding meteorological impacts during the COVID-19 outbreak in mainland China[J]. Environmental Science & Technology Letters, 2020,7(6):402-408.
[13]
康俊锋,黄烈星,张春艳,等.多机器学习模型下逐小时PM2.5预测及对比分析[J]. 中国环境科学, 2020,40(5):1895-1905. Kang J F, Huang L X, Zhang C Y, et al. Hourly PM2.5 prediction and its comparative analysis under multi-machine learning model[J]. China Environmental Science, 2020,40(5):1895-1905.
[14]
李建新,刘小生,刘静,等.基于MRMR-HK-SVM模型的PM2.5浓度预测[J]. 中国环境科学, 2019,39(6):2304-2310. Li J X, Liu X S, Liu J, et al. Prediction of PM2.5 concentration based on MRMR-HK-SVM model[J]. China Environmental Science, 2019, 39(6):2304-2310.
[15]
侯俊雄,李琦,朱亚杰,等.基于随机森林的PM2.5实时预报系统[J]. 测绘科学, 2017,42(1):1-6. Hou J X, Li Q, Zhu Y J, et al. Real-time forecasting system of PM2.5 concentration based on spark framework and random forest model[J]. Science of Surveying and Mapping, 2017,42(1):1-6.
[16]
Huang K X Q M X. Predicting monthly high-resolution PM2.5 concentrations with random forest model in the North China Plain[J]. Environmental Pollution, 2018:675-683.
[17]
王敏,邹滨,郭宇,等.基于BP人工神经网络的城市PM2.5浓度空间预测[J]. 环境污染与防治, 2013,35(9):63-66. Wang M, Zou B, Guo Y, et al. BP artificial neural network-based analysis of spatial variability of urban PM2.5 concentration[J]. Environmental Pollution and Control, 2013,35(9):63-66.
[18]
宋国君,国潇丹,杨啸,等.沈阳市PM2.5浓度ARIMA-SVM组合预测研究[J]. 中国环境科学, 2018,38(11):4031-4039. Song G J, Guo X D, Yang X. ARIMA-SVM combination prediction of PM2.5 concentration in Shenyang[J]. China Environmental Science, 2018,38(11):4031-4039.
[19]
Shi Z, Song C, Liu B, et al. Abrupt but smaller than expected changes in surface air quality attributable to COVID-19 lockdowns[J]. Science Advances, 2021,7(3):d6696.
[20]
Lovrić M, Pavlović K, Vuković M, et al. Understanding the true effects of the COVID-19 lockdown on air pollution by means of machine learning[J]. Environmental Pollution, 2020:115900.
[21]
郭立力,赵春江.十折交叉检验的支持向量机参数优化算法[J]. 计算机工程与应用, 2009,45(8):55-57. Guo L L, Zhao C J. Optimizing parameters of support vector machine's model based on genetic algorithm[J]. Computer Engineering and Applications, 2009,45(8):55-57.
[22]
Lin G F J Y J. Spatial variation of the relationship between PM2.5 concentrations and meteorological parameters in China[J]. Biomed Research International, 2015,2015(21):259-65.
[23]
孟宁,贝耐芳,李国辉,等.关中地区冬季人为源减排对PM2.5浓度的影响[J]. 中国环境科学, 2017,37(5):1646-1656. Meng N, Bei N F, Li G H, et al. Response of the wintertime PM2.5 level to anthropogenic emission mitigations in the Guanzhong basin[J]. China Environmental Science, 2017,37(5):1646-1656.
[24]
Lian X, Huang J, Huang R, et al. Impact of city lockdown on the air quality of COVID-19-hit of Wuhan city[J]. Science of the Total Environment, 2020,742:140556.
[25]
Wang S, Zhang Y, Ma J, et al. Responses of decline in air pollution and recovery associated with COVID-19 lockdown in the Pearl River Delta[J]. Science of the Total Environment, 2021,756:143868.
[26]
Wang J, Xu X, Wang S, et al. Heterogeneous effects of COVID-19 lockdown measures on air quality in Northern China[J]. Applied Energy, 2021,282:116179.
[27]
Li M, Wang T, Xie M, et al. Drivers for the poor air quality conditions in North China Plain during the COVID-19 outbreak[J]. Atmospheric Environment, 2021,246:118103.
[28]
Li L, Li Q, Huang L, et al. Air quality changes during the COVID-19 lockdown over the Yangtze River Delta Region:An insight into the impact of human activity pattern changes on air pollution variation[J]. Science of the Total Environment, 2020,732:139282.
[29]
Shi Z, Li J, Huang L, et al. Source apportionment of fine particulate matter in China in 2013 using a source-oriented chemical transport model[J]. Science of the Total Environment, 2017,601-602:1476-1487.
[30]
Huang L, Hu J, Chen M, et al. Impacts of power generation on air quality in China-part I:An overview[J]. Resources, Conservation and Recycling, 2017,121:103-114.
[31]
Wang Y, Yuan Y, Wang Q, et al. Changes in air quality related to the control of coronavirus in China:Implications for traffic and industrial emissions[J]. Science of the Total Environment, 2020,731:139133.
[32]
Aneja V P, Agarwal A, Roelle P A, et al. Measurements and analysis of criteria pollutants in New Delhi, India[J]. Environment International, 2001,27(1):35-42.
[33]
Li K, Jacob D J, Liao H, et al. Anthropogenic drivers of 2013~2017 trends in summer surface ozone in China[J]. Proceedings of the National Academy of Sciences, 2019,116(2):422-427.
[34]
Salah E S, Nezha M, Abderrahim N, et al. Air quality change during the COVID-19 pandemic lockdown over the Auvergne-Rhône-Alpes region, France[J]. Air Quality, Atmosphere & Health, 2021.
[35]
Liu H, Wang X M, Pang J M, et al. Feasibility and difficulties of China's new air quality standard compliance:PRD case of PM2.5 and ozone from 2010 to 2025[J]. Atmos. Chem. Phys., 2013,13(23):12013-12027.
[36]
王爱平,朱彬,秦玮,等.新冠疫情严控期间南京市空气质量分析[J]. 中国环境科学, 2021:1-11. Wang A P, Zhu B, Qin W, et al. Analysis on air quality in Nanjing during COVID-19 lockdown period[J]. China Environmental Science, 2021:1-11.
[37]
杨新兴,冯丽华,尉鹏.大气颗粒物PM2.5及其危害[J]. 前沿科学, 2012,6(1):22-31. Yang X X, Feng L H, Wei P. Air Matter PM2.5 in Beijing and Its Harm[J]. Frontier Science, 2012,6(1):22-31.
[38]
杨洪斌,邹旭东,汪宏宇,等.大气环境中PM2.5的研究进展与展望[J]. 气象与环境学报, 2012,28(3):77-82. Yang H B, Zou X D, Wang H Y, et al. Study progress on PM2.5 in atmospheric environment[J]. Journal of Meteorology and Environment, 2012,28(3):77-82.
[39]
Sørensen M, Daneshvar B, Hansen M, et al. Personal PM2.5 exposure and markers of oxidative stress in blood.[J]. Environmental Health Perspectives, 2003,111(2):161-166.
[40]
郭新彪,魏红英.大气PM2.5对健康影响的研究进展[J]. 科学通报, 2013,58(13):1171-1177. Guo X B, Wei H Y. Progress on the health effects of ambient PM2.5 pollution[J]. Chinese Science Bulletin, 2013,58(13):1171-1177.
[41]
张小曳,孙俊英,王亚强,等.我国雾霾成因及其治理的思考[J]. 科学通报, 2013,58(13):1178-1187. Zhang X Y, Sun J Y, Wang Y Q, et al. Factors contributing to haze and fog in China[J]. Chinese Science Bulletin, 2013,58(13):1178-1187.
[42]
潘本锋,汪巍,李亮,等.我国大中型城市秋冬季节雾霾天气污染特征与成因分析[J]. 环境与可持续发展, 2013,38(1):33-36. Pan B F, Wang W, Li L, et al. Analysis of the Reason of Formation and the Characteristic of Pollution about Fog or Haze at Key Cities in Autumn and Winter in China[J]. Environment and Sustainable Development, 2013,38(1):33-36.
[43]
王跃思,姚利,刘子锐,等.京津冀大气霾污染及控制策略思考[J]. 中国科学院院刊, 2013,28(3):353-363. Wang Y S, Yao L, Liu Z R, et al. Formation of haze pollution in Beijing-Tianjin-Hebei region and their control strategies[J]. Bulletin of Chinese Academy of Sciences, 2013,28(3):353-363.
[44]
GB 3095-2012环境空气质量标准[S]. 2012. GB 3095-2012 Ambient air quality standards[S]. 2012.
[45]
Sun Y, Lei L, Zhou W, et al. A chemical cocktail during the COVID-19 outbreak in Beijing, China:Insights from six-year aerosol particle composition measurements during the Chinese New Year holiday[J]. Science of the Total Environment, 2020,742:140739.
[46]
王申博,范相阁,和兵,等.河南省春节和疫情影响情景下PM2.5组分特征[J]. 中国环境科学, 2020,40(12):5115-5123. Wang S B, Fan X G, He B, et al. Chemical composition characteristics of PM2.5 in Henan Province during the Spring Festival and COVID-19 outbreak[J]. China Environmental Science, 2020,40(12):5115-5123.
[47]
Zhao Y, Saleh R, Saliba G, et al. Reducing secondary organic aerosol formation from gasoline vehicle exhaust[J]. Proceedings of the National Academy of Sciences, 2017,114(27):6984-6989.
[48]
Le T, Wang Y, Liu L, et al. Unexpected air pollution with marked emission reductions during the COVID-19 outbreak in China[J]. Science, 2020,369(6504):702-706.
[49]
Huang X, Ding A, Gao J, et al. Enhanced secondary pollution offset reduction of primary emissions during COVID-19 lockdown in China[J]. National Science Review, 2020,Doi:10.1093/nsr/nwaa137.
[50]
徐媛,刘茂辉,孙猛,等.天津市生活散煤燃烧污染物排放特征分析研究[J]. 环境科学与管理, 2020,45(2):124-128. Xu Y, Liu M H, Sun M, et al. Emission Characteristics of Pollutants from Domestic Bulk Coal Combustion in Tianjin[J]. Environmental Science and Management, 2020,45(2):124-128.