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Examining The Spatial Spillover Effect And Analyzing The Social Economic Impact Factors Of PM2.5 In China Cities

Posted on:2019-01-08Degree:MasterType:Thesis
Country:ChinaCandidate:J Y CaoFull Text:PDF
GTID:2371330545472585Subject:Human Geography
Abstract/Summary:PDF Full Text Request
In recent years,our country frequently suffers from large-scale haze weather,and many regions in China have been attacked by haze to varying degrees.The continuous haze weather has brought great influence and threat to people’s life,which has also caused a series of social problems.PM2.5.5 is a kind of fine particles with small particle size,which can be inhaled into human body and can easily carry harmful substances,which is harmful to human living environment.As the core substance of haze pollution,PM2.5has become the focus of attention in recent years.For PM2.5.5 pollution,the academic circles have carried on the discussion from temporal and spatial distribution characteristics,source analysis,natural and social factors,etc.But there are two problems that need to be improved:(1)The spatial spillover effect of PM2.5.5 on the national scale of long time series needs to be tested.Since the national PM2.5.5 site monitoring in China only started in 2013,most of the data of domestic related research come from the monitoring of experimental sites.These studies are short time,small scope,research scale.At the same time,the spatial spillover effect of provincial scale masked the spatial difference of prefectural scale.(2)The spatial difference of social and economic factors affecting the formation of PM2.5.5 and its changing law need to be further explored.The method of spatial panel model ignores the spatial difference of social and economic influence factors.Although some scholars have used the method of geographical weighted regression(GWR)to explore the spatial differences of influencing factors in recent two years,the spatial variation of influencing factors with time has not been discussed.Therefore,it can not effectively explain the social and economic drivers of the change in spatial differences.This paper is based on the raster data of the global average annual concentration of PM2.5.5 for1998-2012 based on remote sensing satellite monitoring,data from the Columbia University social economic data and Application Center.On the basis of the vector data of the cities of our country,using Arcgis10.2 to process data,we obtained the average annual concentration of PM2.5.5 in 1999-2011 years.The research contents mainly include three aspects:(1)The global autocorrelation and local autocorrelation methods are used to analyze the spatial spillover effects of PM2.5.5 pollution in China from 1999 to 2011;(2)Combined with the statistical yearbooks,divide our country into three parts.Based on the spatial lag fixed effect model,analyzed the social and economic factors that affecting PM2.5.5 pollution in China.And under the condition of two and three times of economic level,tested the shape of classical environmental Kuznets curve;(3)Build GWR model,select four time nodes(1999,2003,2007,2011),analysis of the influence direction and influence degree of the influence factors of PM2.5.5 pollution in different regions of China.The main conclusions are as follows:(1)From 1999 to 2011,the PM2.5.5 pollution between regions in China showed obvious spatial spillover phenomenon,and continues to be at a high level.The PM2.5.5 pollution showed a significant high-high agglomeration situation,the high frequency areas of pollution are mainly concentrated in the Beijing-Tianjin-Hebei,Yangtze River Delta and central regions,as well as the Sichuan Basin;Low-low type clusters are mainly distributed in the northeast,Qinghai,Yunnan and so on;In other areas,the results of local autocorrelation tests are not significant,such as Guizhou,Guangxi,Guangdong,Fujian and so on,the distribution of PM2.5.5 concentration in these areas is random and irregular.In addition,there is no trend of high-low concentration of haze in our country,and there are few regions with low-high concentration.(2)The analysis of social and economic influence factors of PM2.5.5 shows that:(1)At the national level:The development of population urbanization and ground average GDP are beneficial to the improvement of atmospheric environment quality.The proportion of added value of the second industry and the technical level will promote the production of PM2.5.5 pollution;(2)In the eastern region,coal combustion,the level of R&D,and foreign investment have a negative impact on the local atmospheric environment quality;(3)In the central region,the development of urbanization,the improvement of energy efficiency and the introduction of foreign capital will alleviate the PM2.5.5 pollution,and coal burning is the main driving force for the deterioration of the atmospheric environment in this region;(4)In the western region,population urbanization can promote the reduction of PM2.5.5 pollution in this area,and the increase of secondary production intensifies the formation of haze weather.Coal burning is not the main cause of PM2.5 pollution in this region;(5)China’s economic development and PM2.5 pollution show a significant"reverse N"curve trend,and China has not crossed the second inflection point of inverted N-type curve.For a long period of time in the future,PM2.5.5 pollution will be aggravated with the improvement of economic level.(3)GWR model results show that:(1)The population agglomeration effect brought by urbanization effectively buffers the atmospheric environmental pressure in the process of urban construction(such as the three Northeast provinces,Gansu,Shaanxi,Henan,Yunnan and so on);(2)The development of industrialization has a positive increase in PM2.5.5 pollution(such as northeast,Inner Mongolia,Beijing-Tianjin-Hebei,Northwest,Southwest,Central and so on);(3)The impact of technology development on PM2.5.5 pollution in China is not very significant,and the improvement of R&D level in some areas has not brought about the expected haze reduction effect(for example,Beijing,Tianjin and Hebei,Bohai Rim);(4)In terms of energy efficiency,some regions(such as Gansu,Sichuan,Guangxi and so on)face the dilemma of"energy rebound effect";(5)As a whole,the contribution of coal consumption to PM2.5.5 pollution is positive,and the promoting effect is more and more obvious;(6)For most parts of China(such as Heijiliao,Beijing-Tianjin-Hebei,Shanxi,Henan,Fujian,Guangdong and so on),automobile exhaust is one of the main reasons for the occurrence of haze weather.For some areas(Gansu,Shaanxi,Sichuan,Yunnan,Hunan,etc.),transportation is not the main cause of PM2.5.5 pollution;○7 For the introduction of foreign investment,the"halo"hypothesis is more suitable for the reality of China,that is,foreign direct investment contributes to the improvement of atmospheric environment quality in China.Based on the above conclusions,this paper puts forward the following countermeasures:(1)Adopting the scientific top-level design,controlling PM2.5.5 pollution from the source,adopting the means of combining government regulation with market mechanism,promoting the transformation and upgrading of the mode of economic development of our country;(2)According to the research results,the pollution control of PM2.5.5 is divided into three regions:core area,sub-core area and warning area.According to the actual situation of each region,work out the haze control plan suitable for regional development;(3)considering the spatial spillover effect of pollution,we should take the measures of joint prevention and control,strengthen the cooperation among regions,and establish a long-term and effective cooperation mechanism.Due to the extensive and complex sources of PM2.5,as well as the limited access to statistical data and the existence of regional differences,the related interpretation of PM2.5.5 in this paper is not perfect enough.The study of PM2.5.5 needs to be further explored through long-term stable data accumulation and continuous method innovation.
Keywords/Search Tags:PM2.5, cities spatial spillover effect, spatial lag model, geo-weighted regression, China
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