| PM2.5 air pollution has serious harm to human health.With the increasing air pollution in recent years,the control of pollution caused by PM2.5 has been widely concerned and discussed internationally.The spatial and temporal distribution of PM2.5 and its influencing factors Research has also become the focus of research in academia.The research and simulation of PM2.5 spatio-temporal differentiation plays an important role in the status of pollution caused by PM2.5 and the division of pollution range.The research on the influencing factors of PM2.5 has great assistance to the management department to take pollution control measures.effect.Since the 1960 s,GIS has continuously improved its spatial analysis capabilities and expanded its application fields,which has greatly helped the research on environmental protection.Statistical methods such as regression analysis are also commonly used to study the relationship between various factors.This paper takes the spatial and temporal differentiation of PM2.5 population exposure and the influencing factors as the research objectives,and combines the spatial analysis ability of GIS with the regression analysis model in statistics,and draws several conclusions.This paper mainly studies two aspects:(1)Two kinds of PM2.5 population exposure risk assessment system study 1 is the population exposure risk of PM2.5 air quality in the elderly triangle in 2016.This paper combines the Yangtze River Delta urban agglomeration In-range air monitoring site data,spatial autocorrelation analysis,and the use of inverse distance weight interpolation and factor extraction to achieve spatialization of PM2.5 concentration data.The second is to calculate the PM2.5 population exposure risk(PWEL)by POI-weighted population data combined with PM2.5 air mass concentration data.This paper combines these two risk assessment systems to visualize and analyze the spatial and temporal distribution characteristics of PM2.5 population exposure risk in the Yangtze River Delta urban agglomeration in 2016.(2)Study the impact factors of PM2.5 population exposure risk.This paper constructs an indicator system from three aspects: city size,industrial activity and residents' life,and verifies the correlation between the eight statistical indicators related to PM2.5 and the exposure risks people are exposed to.The main conclusions of the study are as follows:(1)Explain the population exposure risk based on PM2.5 concentration and the temporal and spatial variation of PM2.5-based population exposure risk based on POI.In terms of time,the exposure risks calculated by the two evaluation systems are characterized by “high autumn and winter,low in spring and summer”,and winter>autumn>spring>summer,but the highest value of the former appears in February,and the highest value of the latter appears in In January;spatially,both evaluation systems showed a trend of “low coastal and high inland”,and their annual average performance was in Anhui>Jiangsu>Zhejiang>Shanghai,the highest value of the former appeared in Tongling City,Anhui Province.The highest value appears in Zhangzhou City,and the lowest is Zhoushan City.(2)This paper analyzes the influencing factors of PM2.5 pollution from eight aspects of city scale,resident activity and industrial activity,and concludes that industrial activities are the most important cause of PM2.5 pollution,followed by Resident activities have the least impact on the size of the city.The main research significance of this paper is to use geospatial analysis tools to simulate the spatial and temporal differentiation of PM2.5,and to describe the accumulation of PM2.5 pollution from different time and space scales.The exposure degree of the Yangtze River Delta urban agglomeration is presented in two evaluation systems.Different effects,but there are obvious regional differences and seasonal differences,and there are characteristics of high and low aggregation;and the regression analysis model is used to explore the main factors affecting population exposure. |
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