Ye Luping, Fang Linchuan, Tan Wenfeng, Wang Yunqiang, Huang Yu
State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resources, Yangling 712100, China.
State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling 712100, China.
Environ Sci Process Impacts. 2016 Feb;18(2):265-76. doi: 10.1039/c5em00538h.
A GIS approach and HJ-1B images were employed to determine the effect of landscape structure on aerosol optical depth (AOD) patterns. Landscape metrics, fractal analysis and contribution analysis were proposed to quantitatively illustrate the impact of land use on AOD patterns. The high correlation between the mean AOD and landscape metrics indicates that both the landscape composition and spatial structure affect the AOD pattern. Additionally, the fractal analysis demonstrated that the densities of built-up areas and bare land decreased from the high AOD centers to the outer boundary, but those of water and forest increased. These results reveal that the built-up area is the main positive contributor to air pollution, followed by bare land. Although bare land had a high AOD, it made a limited contribution to regional air pollution due to its small spatial extent. The contribution analysis further elucidated that built-up areas and bare land can increase air pollution more strongly in spring than in autumn, whereas forest and water have a completely opposite effect. Based on fractal and contribution analyses, the different effects of cropland are ascribed to the greater vegetation coverage from farming activity in spring than in autumn. The opposite effect of cropland on air pollution reveals that green coverage and human activity also influence AOD patterns. Given that serious concerns have been raised regarding the effects of built-up areas, bare land and agricultural air pollutant emissions, this study will add fundamental knowledge of the understanding of the key factors influencing urban air quality.
采用地理信息系统（GIS）方法和环境减灾卫星一号B星（HJ - 1B）影像来确定景观结构对气溶胶光学厚度（AOD）模式的影响。提出了景观指标、分形分析和贡献分析，以定量说明土地利用对AOD模式的影响。平均AOD与景观指标之间的高度相关性表明，景观组成和空间结构均会影响AOD模式。此外，分形分析表明，建成区和裸地的密度从高AOD中心向外边界递减，而水体和森林的密度则增加。这些结果表明，建成区是空气污染的主要正向贡献源，其次是裸地。尽管裸地的AOD较高，但由于其空间范围较小，对区域空气污染的贡献有限。贡献分析进一步阐明，建成区和裸地在春季比秋季对空气污染的加剧作用更强，而森林和水体则具有完全相反的作用。基于分形和贡献分析，农田的不同影响归因于春季农业活动带来的植被覆盖度高于秋季。农田对空气污染的相反影响表明，绿色覆盖和人类活动也会影响AOD模式。鉴于人们对建成区、裸地和农业空气污染物排放的影响已提出严重关切，本研究将为理解影响城市空气质量的关键因素增添基础知识。
