Research On Urban Residents’ PM_2.5Exposure Pattern,Process And Mechanism

The distribution and causing of PM2.5 pollution and its impact to human settlement is one of the research hotspots.In this thesis,Baotou city of Inner Mongolia was selected as an example,some data such as of multi-scenes remote sensing imageries of Landsat 5 TM and Landsat 8 OLI(2004～2016),PM2.5 daily monitor data(2014～2015)and 5th and 6th National Population Census data,land use of Baotou city,points of interest(POI)data and micro-blog sigh in data were collected,software such as ArcGIS 10.3,Fragstats 4.2,SPSS 22 and Excel were employed,methods such as mixed linear model,dark target(DT)and dark blue(DB)combined algorithm,image statistics and trends analysis,questionnaire survey,kernel density,correlation analysis and zonal statistical analysis were used.In order to analysis the temporal and spatial distribution characteristics of PM2.5 mass concentration in Baotou city,pattern,process and mechanism of city residents exposure to PM2.5 and understand influences and suggestions to the urban human settlements,multi period PM2.5 mass concentration and city morphology index,landscape index,PM2.5 relative risk of exposure index were computed.The conclusions are as follows:(1)PM2.5 mass concentration remote sensing inversion and its spatiotemporal distribution characteristics:In the remote sensing inversion of PM2.5 model,the mixed linear model had better regression accuracy than linear or multivariate linear models.It was suitable for remote sensing data(/AOD)fitting with less monitoring sites and longer repeated cycles.At temporal scale,the mean PM2.5 concentration of Baotou city showed an increasing trend from 2004 to 2016,and which reaches its peak in 2011.The PM2.5 concentration seasonal variation was summer<autumn<spring<winter.Air quality of daily PM2.5 mean exceeded Nation standard level 1 and level 2 were>200d and>60d in 2014～2015.At spatial scale,the largest area ratio of PM2.5 concentration distribution is 50-75 g/m3(approximately 50%of Baotou city),while the lowest one is range>75 g/m3(area ration less than 10%),show growth trend of both from 2004 to 2016.High PM2.5 pollution zone distributed in Kundulun District from northwest to the north,northern and eastern part of Qingshan District,western part of Jiuyuan District and eastern part of Donghe District,low PM2.5 pollution zone distributed in southern part of Kundulun District,and southern part of Jiuyuan District including unused land or farmland.(2)The PM2.5 exposure risk pattern and process:PM2.5 exposure of city dweller formed an exposure gradually reduce risk pattern from the center to the periphery,in which exposed to PM2.5 relatively risk high level zone are mainly distributed in center of densely populated areas of Kundulun,Qingshan and Donghe in 2005,2010 and 2015,and the relatively risk low and moderate zone located in western,northwestern and southwestern part of Kundulun,from northern to northeastern part of Qingshan,most part of Donghe and Jiuyuan District.Seasonal PM2.5 exposure pattern is "winter>spring>autumn>summer" of 3 time periods in 2005,2010 and 2015.Spring and summer show an increased trends of PM2.5 exposure risk and expansion in area,autumn and winter displayed contrary trends of reduced in PM2.5 exposure risk and area.Different age groups exhibited different exposure risk,age group of exceed 65 suffered the highest exposure risk,15-64 year old residents endured the middle to high risk areas,and young people under age of 14 undergone a lower risk of exposure.(3)The PM2.5 exposure mechanism:The land use type of the highest PM2.5 population exposure risk were residential,commercial and business facilities in 2015 of Baotou city,followed by administration and public services with higher PM2.5 population exposure risk,the third,land use for industrial warehousing and transportation have a relative higher risk of exposure,the last,farmland,woodland,water body and water facilities and other land use exposure risk relatively low.PM2.5 exposure risk showed an negative correlation with those urban morphology factors,such as the area and volume of buildings,the proportion of green space in street blocks,showed an positive correlation with building density and degree of congestion,and there was no significant correlation between the height of the building and the mean floor number of buildings.It was shown a linear relationship between PM2.5 exposure risk and number of population although,the relationship is not statistical significance.(4)The influence and implication of PM2.5 exposure risk for city human settlements:By the survey,residents have a certain degree of awareness to understand the causes of PM2.5 pollution,its health risks and the way to diminish its impact,and their travel and selection of the residence behaviors change due to PM2.5 pollution;for PM2 5 pollution hazards,low age group residents take the initiative to pay attention to "protection",The high age group chose’avoid’ behavior to exposure risk.The spatial distribution of PM2.5 exposure risk in the residential environment of Baotou City is difference.The PM2.5 population exposure risk of residential,commercial and business facilities,administration and public services surrounding A Er Ding Plant Garden and Bayi park in Kundulun District,Baotou teacher’s college in Qingshan and the People’s Park in Donghe Distrcit are higher,and which surrounding environment with low to moderate exposure risk.The PM2.5 exposure risk of industrial and other land use in north of Qingshan and Jiuyuan District is relatively low.And the high PM2.5 exposure risk area is small,and the low PM2 5 exposure risk area is large.At the same time,people’s behavior is also affected by the high exposure risk of PM2.5 in the center of the city.The results supported by points of interest(POI)/micro-blog sign-in data.On this basis,adhere to the "people-oriented" and the principles of coordinated development between human and environment,the suggestions about Baotou city human settlements’ development are conducted from the aspects of improving city air quality and living environment,strengthen the city greening and infrastructure construction.