Spatiotemporal Analysis Of PM_2.5 And Its Disease Burden Assessment In Hubei Province

At present,air pollution has become a worldwide environmental problem.As a rapidly developing country,China's air pollution problem is more prominent.After exposure to air pollutants reaches a certain concentration and time,it will pose a huge threat to human health and the living environment.Therefore,it is of great significance to investigate environmental pollution and formulate measures to explore the temporal and spatial variation of pollutant concentration in the region and assess the disease burden caused by pollutants.In this study,Hubei Province,which has a dense population and frequent air pollution,was selected as the research area,and the most polluted PM_2.5 in the study area was used as the target pollutant to explore its temporal and spatial distribution and the resulting COPD and ischemia heart disease,lung cancer and stroke deaths.In order to obtain the spatial grid data of PM_2.5,LUR is used to simulate its spatial distribution and verify the accuracy of the data,which makes up for the deficiencies of the data of air monitoring stations that used points instead of polygons.Combined with the yearbook data,the population grid data of unknown years is calculated and the deviation of the original population grid data is reduced.Through the above research work,the objectivity of the spatial distribution of PM_2.5 and the validity of the disease burden assessment results are guaranteed.The specific research results are as follows:?1?Select the original data according to the research needs,preprocess the data and analyze the data characteristics.Calculate the correlation between the dependent variable PM_2.5 concentration and the respective variable factor,and pre-screen the independent variable factor according to the influence degree of the respective variable factor on the dependent variable.Through two-way selection and stepwise regression,select variables from the updated independent variable factor set to construct a multiple linear regression equation between dependent variable and independent variable factor,that is,the Land Use Regression?LUR?model in the study area.Based on the obtained LUR model,the spatial distribution of PM_2.5.5 concentration in the study area was fitted.?2?Verify the fitting accuracy of the spatial distribution data of PM_2.5concentration based on the LUR model and global PM_2.5 estimated data.The experimental results show that the PM_2.5 spatial distribution data based on the LUR model has high accuracy.The R-square of the 2014-2016 data is above 0.77,and the root-mean-square error is below 18.Based on the global PM_2.5 estimated data,the concentration data of the three-year R-squared are all above 0.7,and the root-mean-square error is all below 25.?3?Taking 2015 as an example,the LUR model was used to simulate and analyze the spatial distribution of PM_2.5.5 concentration in Hubei Province in four quarters.The simulation results show that the PM_2.5 concentration in Hubei Province shows the spatial distribution law of high in the east and low in the west in different seasons,and the high-value areas in the space are mainly concentrated in the Wuhan city circle.The areas with high concentration of PM_2.5 are the most in winter and higher in autumn.In the spring and summer seasons,there are fewer high-concentration areas of PM_2.5,with summer being the least.Based on the global PM_2.5 estimated data to analyze its interannual changes,the experimental results show that the spatial distribution of PM_2.5concentration is consistent with the seasonal analysis results,the eastern high and western low.From 2014 to 2016,the PM_2.5 concentration in Hubei Province increased first and then decreased.?4?Combined with the Hubei Provincial Yearbook,calculate the population data of Hubei Province in unknown years and recalculate the values of the grid population data.Using the IER?Integrated exposure-response?method to calculate the relative risk of pollutants in an overexposed environment and combining it with HIA?Health Impact Assessment?,based on two types of spatial data,the internal causes of Hubei Province were evaluated from 2014 to 2016.Four types of premature deaths caused by excessive PM_2.5.5 exposure.The results of the study show that PM_2.5 has the greatest impact on the health of stroke.The three-year average of the number of premature deaths caused by air pollution is 35,100.The health impact of ischemic heart disease is second,and the three-year average of the number of premature deaths due to such diseases is 19,100.The three-year average of premature deaths due to PM_2.5.5 causing COPD is 8.2 thousand.The number of premature deaths from lung cancer caused by PM_2.5 is the lowest,with an average annual value of 5.5 thousand in 2014-2016.The four types of disease burden caused by PM_2.5.5 showed the law of interannual changes that increased first and then decreased.The spatial distribution of disease burden is high in the east and low in the west,and the high values are concentrated in the Wuhan metropolitan area.?5?Combining the results of the existing research,compare the evaluation results of the concentration distribution data of two different sources.The evaluation results based on PM_2.5 concentration data from different sources are quantitatively deviated,but the spatial distribution law and the health impact law of the four types of diseases are consistent.The mutual reference between the two ensures the reasonableness of the evaluation results.The evaluation results of the concentration data based on the LUR model are more similar to the results of other studies.The average value of premature deaths in three years is 67,000,and the evaluation results based on global PM_2.5estimates are relatively 63,000.