Effect of Land Use and Cover Change on Air Quality in Urban Sprawl

被引:65
作者
Zou, Bin [1 ,2 ]
Xu, Shan [2 ]
Sternberg, Troy [3 ]
Fang, Xin [2 ]
机构
[1] Minist Educ, Key Lab Metallogen Predict Nonferrous Met & Geol, Changsha 410083, Peoples R China
[2] Cent S Univ, Sch Geosci & Infophys, Changsha 410083, Peoples R China
[3] Univ Oxford, Sch Geog & Environm, Oxford OX1 2JD, England
基金
中国国家自然科学基金;
关键词
urban sprawl; air quality; LUCC; landscape; urban agglomeration; AEROSOL OPTICAL DEPTH; USE REGRESSION-MODEL; POPULATION EXPOSURE; LANDSCAPE METRICS; METROPOLITAN-AREA; PM2.5; EXPOSURES; SATELLITE; POLLUTION; IMPACT; CITIES;
D O I
10.3390/su8070677
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Due to the frequent urban air pollution episodes worldwide recently, decision-makers and government agencies are struggling for sustainable strategies to optimize urban land use/cover change (LUCC) and improve the air quality. This study, thus, aims to identify the underlying relationships between PM10 concentration variations and LUCC based on the simulated PM10 surfaces in 2006 and 2013 in the Changsha-Zhuzhou-Xiangtan agglomeration (CZT), using a regression modeling approach. LUCC variables and associated landscape indexes are developed and correlated with PM10 concentration variations at grid level. Results reveal that the overall mean PM10 concentrations in the CZT declined from 106.74 mu g/m(3) to 94.37 mu g/m(3) between 2006 and 2013. Generally, variations of PM10 concentrations are positively correlated with the increasing built-up area, and negatively correlated with the increase in forests. In newly-developed built-up areas, PM10 concentrations declined with the increment of the landscape shape index and the Shannon diversity index and increased with the growing Aggregation index and Contagion index. In other areas, however, the reverse happens. These results suggest that LUCC caused by urban sprawl might be an important factor for the PM10 concentration variation in the CZT. The influence of the landscape pattern on PM10 concentration may vary in different stages of urban development.
引用
收藏
页数:14
相关论文
共 36 条
[31]   Characterization and spatial modeling of urban sprawl in the Wuhan Metropolitan Area, China [J].
Zeng, Chen ;
Liu, Yaolin ;
Stein, Alfred ;
Jiao, Limin .
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2015, 34 :10-24
[32]   High-Resolution Satellite Mapping of Fine Particulates Based on Geographically Weighted Regression [J].
Zou, Bin ;
Pu, Qiang ;
Bilal, Muhammad ;
Weng, Qihao ;
Zhai, Liang ;
Nichol, Janet E. .
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2016, 13 (04) :495-499
[33]   Spatial modeling of PM2.5 concentrations with a multifactoral radial basis function neural network [J].
Zou, Bin ;
Wang, Min ;
Wan, Neng ;
Wilson, J. Gaines ;
Fang, Xin ;
Tang, Yuqi .
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2015, 22 (14) :10395-10404
[34]   Performance comparison of LUR and OK in PM2.5 concentration mapping: a multidimensional perspective [J].
Zou, Bin ;
Luo, Yanqing ;
Wan, Neng ;
Zheng, Zhong ;
Sternberg, Troy ;
Liao, Yilan .
SCIENTIFIC REPORTS, 2015, 5
[35]   Spatial Cluster Detection of Air Pollution Exposure Inequities across the United States [J].
Zou, Bin ;
Peng, Fen ;
Wan, Neng ;
Mamady, Keita ;
Wilson, Gaines J. .
PLOS ONE, 2014, 9 (03)
[36]   Air pollution exposure assessment methods utilized in epidemiological studies [J].
Zou, Bin ;
Wilson, J. Gaines ;
Zhan, F. Benjamin ;
Zeng, Yongnian .
JOURNAL OF ENVIRONMENTAL MONITORING, 2009, 11 (03) :475-490