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Exploring the association between the built environment and remotely sensed PM2.5 concentrations in urban areas

市中心 环境科学 空气污染 城市规划 薄雾 土地覆盖 土地利用 污染 建筑环境 中国 环境工程 市区 地理 气象学 土木工程 工程类 有机化学 化学 考古 经济 经济 生物 生态学
作者
Man Yuan,Yan Song,Yaping Huang,Michael K. Ng,Tongwen Li
出处
期刊:Journal of Cleaner Production [Elsevier BV]
卷期号:220: 1014-1023 被引量:80
标识
DOI:10.1016/j.jclepro.2019.02.236
摘要

Haze, especially PM2.5, poses a serious threat to public health in China. PM2.5 primarily originates from urban activities, and built environment may affect its formation and dispersion. Previous studies were based on limited data from ground-monitoring stations, and high resolution pollution maps are unavailable for statistical analyses. In this study, a 1 km*1 km wall-to-wall map of PM2.5 concentration is developed with remote sensing data in Wuhan, China, and spatial statistics are used to figure out the influence of the built environment on PM2.5 concentrations. In terms of land cover, high-rise high-density building areas have the largest impact on PM2.5 concentrations, and the effect of forestland on the concentrations is not obvious in winter. In terms of land use, industrial lands are unrelated to air pollution in the downtown, while transportation has become a main source of PM2.5 pollution. In terms of urban form, floor area ratio and building density are positively associated with PM2.5 concentrations, and different types of road densities have different effects on air pollution. Finally, the implications of the study for urban planning and development are given. It is necessary to develop a polycentric urban structure to balance high population density and reduce traffic emissions in downtown areas. Road and bus networks should be optimized simultaneously to reduce traffic emissions and "small blocks and narrow roads" may be considered as an alternative for urban development. The spatial morphology of streets and buildings should be considered during urban design and urban renewal. In general, the study contributes to the application of remote sensing in urban planning and development, and remotely sensed PM2.5 concentration data could provide further findings than the air pollution data obtained from ground monitoring and "bottom-up" models in past studies.
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