2003~2018年四川盆地气溶胶光学厚度空间分异及驱动因子

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (3980 KB) HTML (0 KB)
Export: BibTeX | EndNote (RIS)

Abstract In order to reveal the spatial distribution of aerosol optical depth (AOD) in Sichuan Basin and quantitatively evaluate the driving factors that affect its temporal and spatial differentiation, the geostatistical methods such as Mann-Kendall mutation test, spatial auto-correlation, spatial hot spot detection and geographical detector were used to analyze the data of MODIS aerosol products from 2003 to 2018. There was an overall decreased trend of AOD in Sichuan Basin from 2003 to 2018, and the mutation year was 2015. According to the variation trend, the 16years could be divided into six periods. The characteristics of aerosol regional pollution in Sichuan Basin were obvious. AOD high value areas were mainly concentrated in the middle of the basin, while AOD low value areas were mainly concentrated in the edge of the basin. A significant annual clustering pattern (spatial positive auto-correlation, Moran's I was greater than 0) of the distribution of AOD was showed in Sichuan Basin. The area of the high-high clustering areas had been decreased since 2012, and the variation of the annual clustering areas was consistent with the variation trend of AOD value in different periods. Eight factors were optimized by principal component analysis for geographic detector analysis. And the results showed that the spatial and temporal differentiation of AOD in the basin in the past 16years was mainly caused by the unbalanced development level of urbanization and industrialization. From 2014 to 2015, the driving force of all driving factors decreased 11.2%~59.2% compared with the previous period, which was consistent well with the conclusion that 2015 was a mutation year.

Key words： aerosol optical depth Sichuan Basin space auto-correlation spatial hot spot detection geographical detector

Received: 28 June 2021

PACS:

X511

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	WANG An-yi
	KANG Ping
	ZHANG Yang
	ZENG Sheng-lan
	ZHANG Xiao-ling
	SHI Juan
	LIU Zhi-hong
	XIANG Wei-guo
	WANG Ke-ke
	ZHANG Song-yu
	LU Jun-cen

Cite this article:

WANG An-yi,KANG Ping,ZHANG Yang等. Spatial differentiation and driving factors of aerosol optical depth in Sichuan Basin from 2003 to 2018[J]. CHINA ENVIRONMENTAL SCIENCECE, 2022, 42(2): 528-538.

URL:

http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2022/V42/I2/528

[1]	范娇,郭宝峰,何宏昌.基于MODIS数据的杭州地区气溶胶光学厚度反演[J]. 光学学报, 2015,35(1):1-9. Fan J, Guo B F, He H C. Retrieval of aerosol optical thickness with MODIS data over Hangzhou[J]. Acta Optica Sinica, 2015,35(1):1-9.
[2]	Paciorek C J, Liu Y, Moreno-Macias H, et al. Spatiotemporal associations between GOES aerosol optical depth retrievals and ground-level PM2.5.[J]. Environmental Science & Technology, 2008, 42(15):5800-5806.
[3]	Xue Y, He X, Leeuw G D, et al. Long-time series aerosol optical depth retrieval from AVHRR data over land in North China and Central Europe[J]. Remote Sensing of Environment, 2017,198:471-489.
[4]	Kaufman Y J, D Tanré, Boucher O. A satellite view of aerosols in the climate system[J]. Nature, 2002,419(6903):215-223.
[5]	吕鑫.城市大气气溶胶时空变化特征的地基观测实验与遥感分析[D]. 徐州:中国矿业大学, 2015. LYu X. Analysis of spatio-temporal features of city aerosol based on ground observation experiments and satellite data[D]. Xuzhou:China University of Mining and Technology, 2015.
[6]	Fang L, Yu T, Gu X, et al. Aerosol retrieval and atmospheric correction of HJ-1CCD data over Beijing[J]. Journal of Remote Sensing, 2013, 17(1):151-164.
[7]	Chen J, Xin J, An J, et al. Observation of aerosol optical properties and particulate pollution at background station in the Pearl River Delta region[J]. Atmospheric Research, 2014,143:216-227.
[8]	陈慧忠.基于高时间分辨率MARGA数据分析珠三角地区气溶胶的特征[D]. 北京:中国气象科学研究院, 2013. Chen H Z. Analyses of the characteristics of aerosols in pearl River Delta based on the MARG data[D]. Beijing:Chinese Academy of Meteorological Sciences, 2013.
[9]	刘状,孙曦亮,刘丹,等.2001~2017年中国北方省份气溶胶光学厚度的时空特征[J]. 环境科学学报, 2018,38(8):3177-3184. Liu Z, Sun X L, Liu D, et al. Spatio-temporal characteristics of aerosol optical depth over Beijing-Tianjin-Hebei-Shandong-Henan-Shanxi-Shaanxi region during 2001~2017[J]. Acta Scientiae Circ-umstantiae, 2018,38(8):3177-3184.
[10]	王晨莹,何沐全,陈军辉,等.2006~2017年四川盆地MODIS气溶胶光学厚度时空变化特征[J]. 环境科学研究, 2020,33(1):54-62. Wang X Y, He M Q, Chen J H, et al. Temporal and spatial variation characteristics of MODIS aerosol optical depth in Sichuan Basin from 2006 to 2017[J]. Research of Environmental Sciences, 2020,33(1):54-62.
[11]	艾泽,陈权亮.四川地区气溶胶光学厚度时空分布及其与气象因子的相关性分析[J]. 四川环境, 2019,38(4):79-86. Ai Z, Chen Q L. Temporal and spatial distribution of aerosol optical depth in Sichuan and its correlation with meteorological factors[J]. Sichuan Environment, 2019,38(4):79-86.
[12]	张静怡,卢晓宁,洪佳,等.2000~2014年四川省气溶胶时空格局及其驱动因子定量研究[J]. 自然资源学报, 2016,31(9):1514-1525. Zhang J Y, Lu X N, Hong J, et al. Quantitative study on temporal and spatial patterns of aerosol optical depth and its driving forces in Sichuan Province during 2000~2014[J]. Journal of Natural Resources, 2016,31(9):1514-1525.
[13]	Zhang X Y, Wang Y Q, Niu T, et al. Atmospheric aerosol compositions in China:spatial/temporal variability, chemical signature, regional haze distribution and comparisons with global aerosols[J]. Atmospheric Chemistry & Physics, 2012,12:779-799.
[14]	李晓静,高玲,张兴赢,等.卫星遥感监测全球大气气溶胶光学厚度变化[J]. 科技导报, 2015,33(17):30-40. Li X J, Gao L, Zhang X Y, et al. Global change of aerosol optical depth based on satellite remote sensing data[J]. Science & Technology Review, 2015,33(17):30-40.
[15]	Yi S, Jin L, Wang H. Vegetation changes along the Qinghai-Tibet Plateau engineering corridor since 2000 induced by climate change and human activities[J]. Remote Sensing, 2018,10(1):95-115.
[16]	王华,郭阳洁,洪松,等.区域气溶胶光学厚度空间格局特征研究[J]. 武汉大学学报(信息科学版), 2013,38(7):869-874. Wang H, Guo Y J, Hong S, et al. Spatial pattern characteristics of aerosol optical depth in a region based on spatial autocorrelation[J]. Geomatics and Information Science of Wuhan University, 2013,38(7):869-874.
[17]	汪可可,康平,周明卫,等.四川盆地臭氧浓度空间分异及驱动因子研究[J]. 中国环境科学, 2020,40(6):2361-2370. Wang K K, Kang P, Zhou M W, et al. Spatial differentiation and driving factors of ozone concentration in Sichuan Basin[J]. China Environmental Science, 2020,40(6):2361-2370.
[18]	Anselin L. Local indicators of spatial association-LISA[J]. Geographical Analysis, 2010,27(2):93-115.
[19]	林巧莺,陈永山.我国城市冬季PM2.5空间特征及其人为影响因子[J]. 生态与农村环境学报, 2015,31(4):460-465. Lin Q Y, Chen Y S. Spatial variation of PM2.5 in cities in winter and anthropogenic influencing factors in China[J]. Journal of Ecology and Rural Environment, 2015,31(4):460-465.
[20]	周磊,武建军,贾瑞静,等.京津冀PM2.5时空分布特征及其污染风险因素[J]. 环境科学研究, 2016,29(4):483-493. Zhou L, Wu J J, Jia R J, et al. Investigation of temporal-spatial characteristics and underlying risk factors of PM2.5 pollution in Beijing-Tianjin-Hebei Area[J]. Research of Environmental Sciences, 2016,29(4):483-493.
[21]	王劲峰,徐成东.地理探测器:原理与展望[J]. 地理学报, 2017,72(1):116-134. Wang J F, Xu C D. Geodetector:Principle and prospective[J]. Acta Geographica Sinica, 2017,72(1):116-134.
[22]	黄小刚,邵天杰,赵景波,等.长江经济带空气质量的时空分布特征及影响因素[J]. 中国环境科学, 2020,40(2):874-884. Huang X G, Shao T J, Zhao J B, et al. Spatial-temporal distribution of air quality and its influencing factors in the Yangtze River economic belt[J]. China Environmental Science, 2020,40(2):874-884.
[23]	张洋,刘志红,于明洋,等.四川省气溶胶光学厚度时空分布特征[J]. 四川环境, 2014,33(3):48-53. Zhang Y, Liu Z H, Yu M Y, et al. Temporal and spatial distribution characteristics of aerosol optical depth in Sichuan Province[J]. Sichuan Environment, 2014,33(3):48-53.
[24]	林俊,刘卫,李燕,等.大气气溶胶粒径分布特征与气象条件的相关性分析[J]. 气象与环境学报, 2009,25(1):1-5. Lin J, Liu W, Li Y, et al. Correlation analysis of atmospheric aerosol particle size distribution characteristics and meteorological conditions[J]. Journal of Meteorology and Environment, 2009,25(1):1-5.
[25]	Thurston G D, Spengler J D. A quantitative assessment of source contributions to inhalable particulate matter pollution in metropolitan Boston[J]. Atmospheric Environment, 1987,19(1):9-25.
[26]	郭婉臻,张飞,夏楠,等.近十年中国陆地AOD时空分布及与城市化的关系研究[J]. 环境科学学报, 2019,39(7):2339-2352. Guo W Z, Zhang F, Xia N, et al. Spatio-temporal characteristics of aerosol optical depth and their relationship with urbanization over China's land in nearly a decade[J]. Acta Scientiae Circumstantiae, 2019,39(7):2339-2352.
[27]	陈春江.成渝城市群PM2.5污染的时空分布与治理研究[D]. 重庆:重庆大学, 2019. Chen C J, Research on spatio-temporal differentiation and goverance of PM2.5 pollution in Chengdu-Chongqing urban agglomeration[D]. Chongqing:Chongqing University, 2019.
[28]	Hartman R, Kwon O S. Sustainable growth and the environmental Kuznets curve[J]. Journal of Economic Dynamics & Control, 2002, 29(10):1701-1736.
[29]	曹佳阳,樊晋,罗彬,等.川南四座城市PM2.5化学组分污染特征及其源解析[J]. 环境化学, 2021,40(2):559-570. Cao J Y, Fan J, Luo B, et al. Pollution characteristics and source apportionment of PM2.5 in four urban environment of Southern Sichuan[J]. Environment Chemistry, 2021,40(2):559-570.
[30]	Grossman G M, Krueger A B. Environmental impacts of a north American free trade agreement[J]. CEPR Discussion Papers, 1992, 8(2):223-250.
[31]	宋连春,高荣,李莹,等.1961~2012年中国冬半年霾日数的变化特征及气候成因分析[J]. 气候变化研究进展, 2013,9(5):313-318. Song L, Gao R, Li Y, et al. Analysis of China's haze days in winter half year and climatic background during 1961~2012[J]. Advances in Climate Change Research, 2013,9(5):313-318.