Optimization Of Urban Expansion For Air Pollution Health Risk Prevention And Control

The process of urban expansion is often accompanied by a series of ecological and environmental problems caused by changes in land use and violent human activities,especially the air pollution problem that causes serious harm to human health.The pattern of urban expansion has an important impact on the health effects of air pollution.This paper took30 provincial capital cities and municipalities directly under the Central Government as the research area,and used nighttime light and land use data to analyze the spatial-temporal characteristics of urban expansion from three perspectives:urban morphology,land use and expansion pattern.Through the comparison and verification results of six typical PM_2.5concentration remote sensing datasets,an optimal combination strategy of PM_2.5 datasets for accurate assessment of air pollution health risk was proposed,and the spatial-temporal evolution characteristics of health risks are explored.Moreover,the correlation analysis method was used to screen urban expansion factors affecting health risks,and a multiple linear regression model（MLR）of influencing factors and PM_2.5 concentration was constructed.By optimizing urban expansion indicators,the goal of health risk regulation was achieved.The main contents and conclusions are as follows:（1）Nighttime light and land use data from 2000 to 2019 was used to analysis the spatial-temporal evolution characteristics of the urban expansion.The results showed that core cities continued to expand from2000 to 2019,and the external morphology and internal structure of cities changed significantly.The expansion speed and expansion intensity have spatial-temporal heterogeneity.Generally,the eastern coastal cities were significantly higher than the western regions.The compactness decreased,the fractal dimension increased,and the urban expansion showed a sprawling characteristic.The area of agricultural land had decreased significantly,while built-up had continued to increase.The changes in land use types from 2005 to 2010 and 2015 to 2019 were faster than other periods.“Agricultural land（?）forest”,“agricultural land→built-up”and“agricultural land→grassland”were the main conversion types.The urban land density has an"inverse S-shape rule",and the urban core,inner urban,suburban and urban fringe areas had steadily increased over time.While there are differences in the intensity of land density growth.（2）There were significant spatial-temporal differences in the PM_2.5attributable premature deaths based on different datasets.On the time scale,the difference was most obvious in 2000;On the spatial scale,the difference was most significant in Chongqing,Hohhot,Beijing and etc.After the optimization and combination of PM_2.5 datasets,the uncertainty of the annual premature deaths at the global and local scales can be reduced by 21.70%and 51.86%,respectively.From 2000 to 2019,the number of premature deaths in the study area showed a trend of increasing first and then slowly decreasing,with an annual death toll of 313,500.Premature deaths are highest in the urban center and lower in the surrounding region.（3）Urban expansion has a significant impact on the PM_2.5 attributable premature deaths,while there are differences in the impact of different expansion factors on the health risk.Among the land use types,the premature death rate of PM_2.5 in built-up was the highest,followed by water,agricultural land and grassland,and the lowest in forest.The risk density and land density were consistent in time and space,showing an"inverse S-shape rule".However,there were certain differences between the risk density and land density.From 2000 to 2019,the land density of each city continued to increase,while the risk density remained basically unchanged,and the land density in the same circle was greater than the risk density.The results of correlation analysis showed that improving urban compactness,increasing grassland area,reducing urban fractal dimension,reducing the proportion of construction land,and reducing the radius of urban circles are conducive to reducing the health risk of air pollution.The highest R² was 0.98 for the model combining urban expansion indicators and premature deaths constructed using the MLR.Based on the optimal regulation model,it is concluded that there are differences in the regulation methods in different regions.The cities in North China,South China and Southwest China need to reduce the extensional expansion.The cities Northwest and Northeast regions need to increase the area of urban.The inner urban area of cities in East China should be more compact,and the inner urban area of Central China should be appropriately increased.This paper reveals the temporal-spatial characteristics of cities expansion process,accurately assesses the temporal-spatial evolution characteristics of PM_2.5attributable health risks,and optimizes and adjusts urban expansion indicators to avoid health risks.The research results provide an auxiliary basis for the precise prevention and control of air pollution health risks and the optimization of urban land space for health improvement.