Forecasting PM2.5 induced male lung cancer morbidity in China using   satellite retrieved PM2.5 and spatial analysis

doi:10.1016/j.scitotenv.2017.07.061

CORC > 北京大学 > 城市与环境学院

	Forecasting PM2.5 induced male lung cancer morbidity in China using satellite retrieved PM2.5 and spatial analysis
	Han, Xiao ; Liu, Yuqin ; Gao, Hong ; Ma, Jianmin ; Mao, Xiaoxuan ; Wang, Yuting ; Ma, Xudong
刊名	SCIENCE OF THE TOTAL ENVIRONMENT
	2017
关键词	PM2.5 Lung cancer Morbidity Male China Spatial analysis PARTICULATE AIR-POLLUTION LEAST-SQUARES REGRESSION LONG-TERM EXPOSURE EXTENDED FOLLOW-UP HARVARD 6 CITIES FINE PARTICLES UNITED-STATES MORTALITY COMBINATION NONSMOKERS
DOI	10.1016/j.scitotenv.2017.07.061
英文摘要	The present study predicts a spatial distribution of lung cancer morbidity in Chinese males due to exposure to PM2.5 concentration from 2010 to 2015. A spatial autocorrelation method was used to evaluate the spatial relationship between the lung cancer morbidities from 2006 to 2009 and satellite-derived PM2.5 atmospheric levels. A comprehensive grey correlation degree analysis was carried out to assess the simultaneous and lag associations between the lung cancer morbidity and PM2.5 concentration. These relationships were subsequently applied to predict male lung cancer morbidity in a specific year. Annual mean PM2.5 levels in this specific year and previous 8 years were used as 9 independent variables to establish four statistical models. These models include ridge regression (RR), partial least squares regression (PLSR), support vector regression (SVR), and the combined forecasting model (CFM) to predict the male lung cancer morbidity in China from 2010 to 2015. The model error evaluations suggested that the partial least squares regression model performed the best in the male lung cancer morbidity forecast. We calculated the male lung cancer morbidity by the optimal method among the established statistical forecasting models at 1948 sites in China. The gridded morbidity distribution from 2010 to 2015 across the country was obtained by Kriging interpolation method. Results showed that the male lung cancer morbidity increased significantly from western to eastern China, except for the far north region. This spatial pattern is in line with the spatial distribution of PM2.5 concentration, manifesting a significant relationship between PM2.5 concentration level and lung cancer morbidity in Chinese males. (C) 2017 Published by Elsevier B.V.; National Science Foundation of China [41671460, 41371453]; Key Project of Gansu Province People's Livelihood Science and Technology [1503FCMA003]; SCI(E); ARTICLE; 1009-1017; 607
语种	英语
内容类型	期刊论文
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/470346]
专题	城市与环境学院
推荐引用方式 GB/T 7714	Han, Xiao,Liu, Yuqin,Gao, Hong,et al. Forecasting PM2.5 induced male lung cancer morbidity in China using satellite retrieved PM2.5 and spatial analysis[J]. SCIENCE OF THE TOTAL ENVIRONMENT,2017.
APA	Han, Xiao.,Liu, Yuqin.,Gao, Hong.,Ma, Jianmin.,Mao, Xiaoxuan.,...&Ma, Xudong.(2017).Forecasting PM2.5 induced male lung cancer morbidity in China using satellite retrieved PM2.5 and spatial analysis.SCIENCE OF THE TOTAL ENVIRONMENT.
MLA	Han, Xiao,et al."Forecasting PM2.5 induced male lung cancer morbidity in China using satellite retrieved PM2.5 and spatial analysis".SCIENCE OF THE TOTAL ENVIRONMENT (2017).