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Study On The Law Of Air Pollution Changes And Its Influencing Factors In Beijing-Tianjin-Hebei Region

Posted on:2019-04-18Degree:MasterType:Thesis
Country:ChinaCandidate:X Z PengFull Text:PDF
GTID:2321330542465035Subject:Geological Engineering
Abstract/Summary:PDF Full Text Request
Air is the material basis for the survival of life,and it is also an important resource for production activities.Maintaining air quality and safety is crucial to maintaining people's health and social stability.In recent years,with the deepening of domestic economic development and human activities,air pollution has become a hot issue in the society,especially in the Beijing-Tianjin-Hebei region.Therefore,this paper studies the temporal and spatial distribution of PM10,SO2,and NO2 concentrations in eight cities in Beijing,Tianjin and Hebei from 2001 to 2015,and draws the change rule.Then,by combining demographic and economic data,meteorological data,energy data,and land use data,the correlations between pollutant concentrations and the above factors were analyzed.The panel data analysis method was used to investigate the influencing factors of air pollution,with a view to providing reference for the causes of air pollution and academic research and government decision-making in prevention and control of air pollution.The main research contents and achievements of this article are:?1?Through the study of the spatial distribution and temporal variation characteristics of the three pollutants in the Beijing-Tianjin-Hebei region,it was found that the levels of pollution in Shijiazhuang,Fujian,and Tangshan were heavier,Baoding,Beijing and Tianjin were second,Hengshui,and Langfang were less polluting;in terms of time,Concentration of pollutants showed a trend of falling first and then rising and then falling again.?2?The correlation between air pollutant concentration and various factors in Beijing-Tianjin-Hebei region was studied.The influencing factors of the three pollutants in the study area are different,and the correlations of the factors in each city are also not the same,but the factors that have a high correlation with each pollutant are generally fixed.PM10 is mainly related to the average relative humidity in the meteorological elements,wind speed,and cultivated land area in land use.SO2 has significant correlation with population,GDP,land use factor,and energy consumption factors.NO2 has a large correlation with meteorological factors,motor vehicle ownership and is not highly correlated with land use factors.?3?Analyze the panel data of atmospheric pollution in the Jing-Jin-Ji region to find out the influencing factors of atmospheric pollution.The empirical analysis shows that in the Beijing-Tianjin-Hebei region,the pressure on the environment caused by population growth has basically disappeared,and it even has an effect on the environment;the increase in GDP will generally increase major air pollution,but the development of primary and tertiary industries will increase.It will cause the reduction of SO2 and PM10 concentrations respectively,indicating that the impact of GDP is not a single one;the impact of meteorological factors on pollutant concentration is bidirectional on the annual scale,and the increase of temperature will cause the increase of PM10 and NO2 concentrations and the decrease of SO2 concentration.The increase of relative humidity will increase the concentration of three pollutants.When the wind speed increases,the concentration of PM10 will increase and the concentration of SO2will decrease.In terms of energy consumption,coal and gasoline have the greatest impact,and natural gas and electricity have no significant effect,indicating that China still has It is necessary to control the consumption of coal and gasoline and adjust the energy structure.In terms of land use,the reduction of cultivated land will cause an increase in the concentration of PM10;an increase in the number of motor vehicles will cause an increase in the concentration of PM10 and NO2.
Keywords/Search Tags:Air Pollution, Jing-Jin-Ji Area, Correlation, Influencing Factors, Panel Data
PDF Full Text Request
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