The Study On The Spatial-temporal Pattern Of Population Exposure Risk To PM_2.5 In Global

Solid particle named PM_2.5.5 which means PM with an average aerodynamic diameter less than 2.5μm is the primary pollutants in haze weather.And it has been the one of the greatest threats to the health of mankind currently.Scientific and accurate population exposure assessment is the premise of responding risks differently.Based on long time series of remote sensing,PM_2.5.5 with macroscale and refinement study of risk exposure,it’s helpful to deeply analyze the population exposure risk of PM_2.5,which is also significant to the research on the improvement of human settlements,human health effects and environmental risk assessment.Based on PM_2.5 remote sensing data and population raster data,this passage analyzed the spatial and temporal distribution characteristics of global PM_2.5 population exposure risk from 2000 to 2016 and accurately identified the distribution layout of high risk areas by using pollutant population exposure risk model,Theil Sen media and Mann Kendall methods.On this basis,this passage took China as the research area and analyzed the spatial correlation between respiratory diseases and high exposure risk.Meanwhile,it preliminarily explored their spatial variation.So it provides reference for mastering the dynamic change of PM_2.5 population exposure risk and scientific monitoring and management.In order to intuitively present the exposure risk of PM_2.5population,this passage takes the raster as the smallest unit for risk analysis and presents the exposure results with different subregions.The main conclusions of this passage are as follows:（1）The PM_2.5 remote sensing data and population raster data possess good precision,which can objectively evaluate the degree of exposure risk.Three areas involved China,European Union and Canada were selected to verify the precision of PM_2.5 remote sensing data.According to the essential principle of uniform spatial distribution to select verification point,there were 442 groups of effective verification data which were obtained by matching the PM_2.5 remote sensing data with ground monitoring data.It was found that the data had good accuracy at the level of p<0.01which shows the average R² is 0.7551,MPE is 3.512%,RMSE is 4.739μg·m^-3.In research,by electing the population of each country in 2016 which published by the World Bank to verify population data and selecting the total population as the verification value,after matching the sum of population grid data in each country with the World Bank population data,there were 97 groups of effective data obtained to verify the precision.And it was found that the accuracy is accurate.When p less than（<）0.001 and R² is 0.99,the average deviation is only 2.43%.Therefore,the PM_2.5 and population raster data possess the higher precision which can satisfy the need of research.（2）The global average concentration of PM_2.5 was significantly different in different continents.The high value areas of PM_2.5 pollution were mainly distributed in East Asia,South Asia and Southeast Asia.From high to low,the average value of PM_2.5respectively were 14.7μg·m^-33 in Asia,8.1μg·m^-33 in Africa,8.03μg·m^-33 in Europe5.69μg·m^-33 in South America,4.41μg·m^-3 in North America and 1.27μg·m^-3 in Oceania.（3）The global average annual PM_2.5 population exposure risk was gradually decreasing on the macro scale,but it showed the differences in the area on the micro scale.In space,the global PM_2.5 population exposure risk ranked from high to low was Asia（5.94）,Africa（0.62）,Europe（0.45）,South America（0.32）,North America（0.27）and Oceania（0.01）.The high value areas of PM_2.5 population exposure risk were distributed in the eastern of China,India,Southeast Asia,Western Europe and other regions with developed industry and concentrated population.On the contrary,the extremely low values areas of PM_2.5 population exposure risk were mainly distributed in alpine,plateau,alpine,desert,tropical rainforest and other untraversed areas.From the perspective of time,the global PM2.5 population exposure risk has significant differences in time series from 2000 to 2016,which shows an increasing trendency in Asia and Africa,a decreasing trendency in Europe and North America,and a small change in Oceania and South America.（4）There was no significant correlation between exposure risk and standardized mortality from 11 respiratory and cardiovascular diseases.Through the correlation analysis between the province’s domains that the rank of Chinese PM_2.5.5 population exposure risk is desperately dangerous or dangerous（The following content will collectively refers to high exposure risk.）and standardized mortality caused by 11respiratory and cardiovascular diseases in these province’s domains,and by analyzing its Pearson correlation coefficient,at the level of p<0.05,there was no significant correlation between 11 disease-related standardized mortality and high risk of exposure.