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Statistical Measurement Of The Impact Of Nitrogen Dioxide On Haze In Beijing-Tianjin-Hebei City

Posted on:2021-05-25Degree:MasterType:Thesis
Country:ChinaCandidate:Y LiFull Text:PDF
GTID:2381330623976680Subject:Applied Statistics
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China's sustained high-speed and high-quality economic development is accompanied by air pollution problems.The growth of the urban population and the surge in the number of motor vehicles has led to the problem of urban haze pollution.Especially in the Beijing-Tianjin-Hebei region,which is a severely polluted area,the haze PM2.5 continues to exceed the standard in autumn and winter.In addition,the formation mechanism of PM2.5 is very complicated.In addition to pollution sources such as coal combustion and motor vehicles,which will directly emit fine particulate matter PM2.5 to the atmosphere,it also emits gaseous pollutants such as nitrogen dioxide and sulfur dioxide,which will be converted into nitrate and sulfate.These secondary particles have promoted the rapid growth of PM2.5.According to relevant data,in2017,the contribution of motor vehicle emissions to PM2.5 in Beijing reached 45%.Under such complex pollution conditions of PM2.5 fine particles and gaseous pollutants such as nitrogen dioxide,it is an urgent problem to quantify the impact of the main precursor nitrogen dioxide on the PM2.5 fine particles in the haze.Issues worth studying.Based on the above background and problems,this article mainly uses 13 cities in Beijing,Tianjin,and Hebei as the research object to carry out statistical research on the impact of nitrogen dioxide on haze,so as to provide data support and decision support for the coordinated treatment of haze pollution in Beijing,Tianjin and Hebei.This paper mainly uses the visual analysis technology to excavate the distribution characteristics of haze pollution and nitrogen dioxide in cities and Beijing-Tianjin-Hebei air monitoring stations from the two aspects of time and space,and uses the relevant analysis methods to analyze the relationship between PM2.5 and NO2.Combined with the spatial autocorrelation analysis and the establishment of a spatial panel model to quantify The influence of gaseous pollutant nitrogen dioxide on fine particulate matter PM2.5 was analyzed in consideration of meteorological conditions,heating days,and holidays.In the end,the following conclusions were reached:First,the nitrogen dioxide and haze PM2.5 in Beijing-Tianjin-Hebei cities have obvious characteristics of high pollution levels in winter and holidays.At the same time,the overall pollution situation in 2018-2020 is improved compared to 2017.During the outbreak of new coronavirus in early 2020,PM2.5 and NO2 concentrations were also higher than in the same period of previous years.These have a lot to do with socio-economic activities such as coal-fired heating,motor vehicle exhaust,and industrial production.From a spatial perspective,it is found that the haze pollution in urban areas,transportation areas,industrial areas,and commercial areas is more serious.Overall,the two substance concentrations in Beijing-Tianjin-Hebei cities are geographically lower than those in the central and southern cities.Second,the correlation between NO2 as PM2.5 precursor oxide and PM2.5.5 is indeed strong,and the panel space lag model?PSLM?with individual fixed effects is found to find that there is a spatial agglomeration effect of haze PM2.5,Xingtai,Handan,Shijiazhuang,Baoding,etc.located in the south of Beijing,Tianjin and Hebei belong to the haze PM2.5diffusion zone.At the same time,it has been verified that NO2 has a significant haze-enhancing effect,and for every 1%increase in NO2 concentration,the haze PM2.5 will increase by 0.312%.In addition to the increase in motor vehicle pollutant emissions during holidays and coal-fired heating in winter,the man-made factors will increase the haze,and the weather conditions such as wind speed and temperature will also affect the haze.
Keywords/Search Tags:Space panel model, Beijing-Tianjin-Hebei city, Spatiotemporal distribution, Haze, PM2.5, Nitrogen dioxide
PDF Full Text Request
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