基于AERONET的中国地区典型站点气溶胶类型变化特征

Abstract
Figure/Table
References (47)
Related Citation (15)

Download: PDF (1130 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract

Basing on the aerosol optical depth (AOD) and aerosol relative optical depth (AROD), retrieved from the Aerosol Robotic Network (AERONET) sites in China from 2006 to 2018, we classified the aerosol types and studied its spatiotemporal variations at the sites including Beijing, Taihu, Hong Kong and SACOL, representative of North China, East China, South China and Northwest China, respectively. The continental and urban industry aerosols were the dominant types of aerosols in the North, South and East China. The continental aerosols was the dominant aerosol type in Northwest China. The ratio of different aerosol types to the total aerosol existed distinct interannual variation in each region. Our results showed that the continental aerosols increased while sub-continental aerosols decreased during the past decade in North China, and especially in East China, where the clean continental aerosols' proportion rose at the rate of 2.78% per year, and the proportion of the urban industry aerosols dropped by 1.86% per year. On the other hand, the proportion of continental aerosol grew by 0.78% and urban industrial aerosol fell by 0.66% annually in South China. As the main source area of dust emission, the proportion of dust aerosols changed significantly in Northwest China, with an average annual increase of 0.51%. The seasonal variations of aerosol types were also found to be large in different areas. Dust aerosols occurred frequently during spring in North China, East China and Northwest China, and the percentage of dust in the latter was much higher than the other two regions (19%). The proportions of the urban industrial aerosols and continental aerosols in North China showed the highest values in summer and winter, respectively. The ratio of the urban industry aerosol in East China was substantial in summer and autumn, but the highest ratio of the urban industry aerosol in South China occurred in spring with the value of 57%. As for the Northwest China, the proportion of the continental aerosol was the highest in summer and autumn (83%).

Key words： AERONET aerosol type spatial and temporal variation

Received: 25 July 2019

PACS:

X513

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	HE Xin
	ZHOU Ru
	YAO Yuan
	SHEN Zi-xuan
	ZHU Jun

Cite this article:

HE Xin,ZHOU Ru,YAO Yuan等. The spatiotemporal variations of aerosol types in representative sites of China basing on the Aerosol Robotic Network (AERONET)[J]. CHINA ENVIRONMENTAL SCIENCECE, 2020, 40(2): 485-496.

URL:

http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2020/V40/I2/485

[1]	张小曳,廖宏,王芬娟.对IPCC第五次评估报告气溶胶-云对气候变化影响与响应结论的解读[J]. 气候变化研究进展, 2014,10(1):37-39. Zhang X Y, Liao H, Wang F J. The effects of aerosols and clouds on climate change and their responses[J]. Advances in Climate Change Research, 2014,10(1):37-39.
[2]	夏祥鳌,王明星.气溶胶吸收及气候效应研究的新进展[J]. 地球科学进展, 2004,(4):630-635. Xia X A, Wang M X. Latest advances in aerosol absorption and its climate effects[J]. Advances in Earth Science, 2004,(4):630-635.
[3]	刘毅,王明星,张仁健.中国气溶胶研究进展[J]. 气候与环境研究, 1999,(4):406-414. Li Y, Wang M X, Zhang R J. The present status of aerosol research in China[J]. Climatic and Environmental Research, 1999,(4):406-414.
[4]	Zhang B, Wang Y, Hao J. Simulating aerosol-radiation-cloud feedbacks on meteorology and air quality over eastern China under severe haze conditions in winter[J]. Atmospheric Chemistry and Physics, 2015,15(5):2387-2404.
[5]	Xing C Z, Liu C, Wang S S, et al. Observations of the vertical distributions of summertime atmospheric pollutants and the corresponding ozone production in Shanghai, China[J]. Atmospheric Chemistry & Physics, 2017,17(23):14275-14289.
[6]	Che H Z, Xia X A, Zhao H J, et al. Spatial distribution of aerosol microphysical and optical properties and direct radiative effect from the China Aerosol Remote Sensing Network[J]. Atmospheric Chemistry and Physics, 2019,19(18):11843-11864.
[7]	Sarna K, Russchenberg H. Ground-based remote sensing scheme for monitoring aerosol-cloud interactions[J]. Atmospheric Measurement Techniques Discussions, 2015,8(11):11953-11986.
[8]	Che H Z, Qi B, Zhao H J, et al. Aerosol optical properties and direct radiative forcing based on measurements from the China Aerosol Remote Sensing Network (CARSNET) in eastern China[J]. Atmospheric Chemistry and Physics, 2018,18(1):405-425.
[9]	Zhu J, Xia X A, Wang J, et al. Impact of Southeast Asian smoke on aerosol properties in Southwest China:first comparison of model simulations with satellite and ground observations[J]. Journal of Geophysical Research:Atmospheres, 2017,122(7):3904-3919.
[10]	Li J, Huang J, Stamnes K, et al. A global survey of cloud overlap based on CALIPSO and CloudSat measurements[J]. Atmospheric Chemistry and Physics, 2015,15(1):519-536.
[11]	Li J M, Lv Q Y, Zhang M, et al. Effects of atmospheric dynamics and aerosols on the fraction of supercooled water clouds.[J]. Atmospheric Chemistry & Physics, 2017,17(3).
[12]	Li J M, Jian B D, Huang J P, et al. Long-term variation of cloud droplet number concentrations from space-based Lidar[J]. Remote Sensing of Environment, 2018,213:144-161.
[13]	Korras-Carraca M B, Hatzianastassiou N, Matsoukas C, et al. The regime of aerosol asymmetry parameter over Europe, the Mediterranean and the Middle East based on MODIS satellite data:evaluation against surface AERONET measurements[J]. Atmospheric Chemistry and Physics, 2015,15(22):13113-13132.
[14]	Xia X G, Li Z Q, Holben B, et al. Aerosol optical properties and radiative effects in the Yangtze Delta region of China[J]. Journal of Geophysical Research, 2007,112(D22):449-456.
[15]	Che H Z, Xia X A, Zhu J, et al. Column aerosol optical properties and aerosol radiative forcing during a serious haze-fog month over North China Plain in 2013 based on ground-based sunphotometer measurements[J]. Atmospheric Chemistry and Physics, 2014,14(4):2125-2138.
[16]	Ansmann A, Engelmann R, Althausen D, et al. High aerosol load over the Pearl River Delta, China, observed with Raman lidar and Sun photometer[J]. Geophysical Research Letters, 2005,32(13):L13815.
[17]	Pan L, Che H Z, Geng F H, et al. Aerosol optical properties based on ground measurements over the Chinese Yangtze Delta Region[J]. Atmospheric Environment, 2010,44(21/22):2587-2596.
[18]	Mai B, Deng X, Xia X, et al. Column-integrated aerosol optical properties of coarse- and fine-mode particles over the Pearl River Delta region in China[J]. Science of the Total Environment, 2018, 622-623:481-492.
[19]	Che H Z, Zhang X Y, Xia X A, et al. Ground-based aerosol climatology of China:aerosol optical depths from the China Aerosol Remote Sensing Network (CARSNET) 2002-2013[J]. Atmospheric Chemistry and Physics, 2015,15(13):7619-7652.
[20]	Dubovik O, King M D. A flexible inversion algorithm for retrieval of aerosol optical properties from sun and sky radiance measurements[J]. Journal of Geophysical Research:Atmospheres, 2000,105(D16):20673-20696.
[21]	王宏斌,张志薇,张镭,等.中国3个AERONET站点气溶胶大小的识别及特征分析[J]. 中国环境科学, 2015,35(4):995-1003. Wang H B, Zhang Z W, Zhang L, et al. Identify the size of aerosol particles and analyze its characteristic at three AERONET sites in China[J]. China Environmental Science, 2015,35(4):995-1003.
[22]	张志薇,王宏斌,张镭,等.中国3个AERONET站点气溶胶微物理特性分析及比较[J]. 中国环境科学, 2014,34(8):1927-1937. Zhang Z W, Wang H B, Zhang L, et al. Analysis and comparison of the aerosol microphysical properties at three AERONET sites in China[J]. China Environmental Science, 2014,34(8):1927-1937.
[23]	赵俊芳,徐慧,孔祥娜,等.基于MODIS和AERONET的气溶胶地表直接辐射效应评价[J]. 中国农业气象, 2018,39(11):693-701. Zhao J F, Xu H, Kong X N, et al. Estimating surface direct radiation effect of aerosol based on MODIS and AERONET Data[J]. Chinese Journal of Agrometeorology, 2018,39(11):693-701.
[24]	许文龙,胡方超,王雨轩.基于AERONET数据估算近地面PM2.5[J]. 环境科学学报, 2019,39(6):1902-1912. Xu W L, Hu F C, Wang Y X. Estimating the near-ground PM2.5 concentration based on AERONET data[J]. Acta Scientiae Circumstantiae, 2019,39(6):1902-1912.
[25]	Eck T F, Holben B N, Reid J S, et al. Wavelength dependence of the optical depth of biomass burning, urban, and desert dust aerosols[J]. Journal of Geophysical Research:Atmospheres, 1999,104(D24):31333-31349.
[26]	Holben B N, Eck T F, Slutsker I, et al. AERONET-a federated instrument network and data archive for aerosol characterization[J]. Remote Sensing of Environment, 1998,66(1):1-16.
[27]	Chen Q X, Yuan Y, Shuai Y, et al. Graphical aerosol classification method using aerosol relative optical depth[J]. Atmospheric Environment, 2016,135:84-91.
[28]	李霞,陈勇航,胡秀清,等.乌鲁木齐大气气溶胶的光学特性分析[J]. 中国环境科学, 2005,25(S1):22-25. Li X, Chen Y H, Hu X Q, et al. Analysis of atmospheric aerosol optical properties over Urumqi[J]. China Environmental Science, 2005, 25(S1):22-25.
[29]	Gobbi G P, Kaufman Y J, Koren I, et al. Classification of aerosol properties derived from AERONET direct sun data[J]. Atmospheric Chemistry and Physics, 2007,7(2):453-458.
[30]	Dubovik O, Holben B, Eck T F, et al. Variability of absorption and optical properties of key aerosol types observed in worldwide locations[J]. Journal of the Atmospheric Sciences, 2002,59(3):590-608.
[31]	于杰,车慧正,陈权亮,等.2010~2012年我国西北地区沙尘个例气溶胶特征分析[J]. 气象与环境科学, 2016,39(2):33-40. Yu J, Che H Z, Chen Q L, et al. Characteristics analysis of aerosol on dust weather cases in northwestern China from 2010 to 2012[J]. Meteorological and Environmental Sciences, 2016,39(2):33-40.
[32]	张西雅,扈海波.京津冀地区气溶胶时空分布及与城市化关系的研究[J]. 大气科学, 2017,41(4):797-810. Zhang X Y, Hu H B. Spatio-temporal characteristics of aerosol optical depth and their relationship with urbanization over Beijing-Tianjin-Hebei region[J]. Chinese Journal of Atmospheric Sciences, 2017, 41(4):797-810.
[33]	韩亚芳,吴立新,白杨,等.太湖北岸气溶胶光学特性长期变化特征[J]. 中国环境科学, 2017,37(7):2492-2503. Hang Y F, Wu L X, Bai Y, et al. Long-term variation of aerosol optical properties at Tai Lake's north bank[J]. China Environmental Science, 2017,37(7):2492-2503.
[34]	张谦元,梁海燕.西北地区土壤污染治理与制度完善[J]. 中国资源综合利用, 2010,28(10):52-56. Zhang Q Y, Liang H Y. The soil pollution control and system improvement in Northwest area[J]. China Resources Comprehensive Utilization, 2010,28(10):52-56.
[35]	单楠,杨晓晖,时忠杰,闫峰.基于MODIS的中国陆地气溶胶光学厚度时空分布特征[J]. 中国水土保持科学, 2012,10(5):24-30. Shan N, Yang X H, Shi Z J, et al. Spatio-temporal distribution characteristics of aerosol optical depth over China based on MODIS[J]. Science of Soil and Water Conservation, 2012,10(5):24-30.
[36]	许秀玲.基于MODIS产品的中国陆地气溶胶时空特征分析[D]. 南京:南京师范大学, 2012. Xu X L. Spatio-temporal characteristics of land aerosols in China based on MODIS products[D]. Nanjing:Nanjing Normal University, 2012.
[37]	沈凡卉,王体健,庄炳亮,等.中国沙尘气溶胶的间接辐射强迫与气候效应[J]. 中国环境科学, 2011,31(7):1057-1063. Chen F B, Wang T J, Zhuang B L, et al. The first indirect radiative forcing of dust aerosol and its effect on regional climate in China[J]. China Environmental Science, 2011,31(7):1057-1063.
[38]	尚丽萍,王天河.西北地区大气环境中沙尘气溶胶的时空变化特征[J]. 甘肃科技, 2018,34(16):19-22. Shang L P, Wang T H. Spatial and temporal variations of dust aerosols in the atmospheric environment of Northwest China[J]. Gansu Science and Technology, 2018,34(16):19-22.
[39]	晏利斌,刘晓东.京津冀地区气溶胶季节变化及与云量的关系[J]. 环境科学研究, 2009,22(8):924-931. Yan L B, Liu X D. Seasonal variation of atmospheric aerosol and its relation to cloud faction over Beijing -Tianjing-Hebei region[J]. Research of Environmental Sciences, 2009,22(8):924-931.
[40]	李成才,毛节泰,刘启汉,等.利用MODIS光学厚度遥感产品研究北京及周边地区的大气污染[J]. 大气科学, 2003,(5):869-880+951-953. Li C C, Mao J T, Liu Q H, et al. Using MODIS optical depth remote sensing products to study atmospheric pollution in Beijing and Its surrounding areas[J]. Chinese Journal of Atmospheric Sciences, 2003,(5):869-880+951-953.
[41]	朱爱华,李成才,刘桂青,等.北京地区MODIS卫星遥感气溶胶资料的检验与应用[J]. 环境科学学报, 2004,25(1):86-90. Zhu A H, Li C C, Liu G Q, Mao J T. Validation and application of MODIS remote aerosol information in Beijing[J]. Acta Scientiae Circumstantiae, 2004,25(1):86-90.
[42]	王丽丽,张仁健,李定龙,等.北京秋季气溶胶化学成分的高分辨率观测及来源分析[J]. 气候与环境研究, 2009,14(4):399-404. Wang L L, Zhang R J, Li D L, et al. High-resolution observation of chemical components of atmospheric aerosol in autumn of Beijing and its source identification[J]. Climatic and Environmental Research, 2009,2514(4):399-404.
[43]	刘璇,朱彬,关学锋,等.华东地区气溶胶分布和变化特征研究[J]. 沙漠与绿洲气象, 2017,11(1):11-21. Liu X, Zhu B, Guan X F, et al. Study on aerosol distribution and change characteristics in east China[J]. Desert and Oasis Meteorology, 2017,11(1):11-21.
[44]	Fan S, Wang B, Tesche M, et al. Meteorological conditions and structures of atmospheric boundary layer in October 2004over Pearl River Delta area[J]. Atmospheric Environment, 2008,42(25):6174-6186.
[45]	朱李华,陶俊,张仁健,等.冬夏季广州城区碳气溶胶特征及其与O3和气象条件的关联[J]. 环境科学学报, 2010,30(10):1942-1949. Zhu L H, Tao J, Zhang R J, et al. Characteristics of the carbonaceous aerosol in PM2.5 and its relation to O3 and meteorological conditions in the urban Guangzhou area in winter and summer[J]. Acta Scientiae Circumstantiae, 2010,30(10):1942-1949.
[46]	赵仕伟,高晓清.基于MODIS数据的西北地区气溶胶光学厚度和Angstrom波长指数的研究[J]. 大气与环境光学学报, 2017,12(5):321-331. Zhao S W, Gao X Q. Study of aerosol optical depth and Angstrom exponent in the Northwest of China based on MODIS product[J]. Journal of Atmospheric and Environmental Optics, 2017,12(5):321-331.
[47]	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 and Physics, 2012,12:779-799.