Abstract:The spatial-temporal pattern of aerosol optical thickness (AOD) across Shandong Province was investigated based on MOD04_3K data from 2010 to 2019. The results showed that the annual average AOD fluctuated from 0.545 to 0.851 with a mean value of 0.706. It was a trend of decline during the last 10 years. It had a dramatically high reduction rate of 33% and eventually decreased about 0.269 by the end of 2019. The AOD had an obvious seasonal variation, with the peak value in summer and the lowest value in winter. Overall, the average value of AOD during heating periods presented to be lower than that during non-heating periods. The spatial pattern of AOD was mainly characterized with the high value in the northern Bohai Rim region,, the western Shandong province and Jining City, while with low value in the northeastern coastal areas and central Shandong province. Meanwhile, high AOD values were primarily in low-altitude regions, while low AOD values were mainly in high-altitude regions. Besides, the variation trend rate of AOD time-series was basically consistent with the pattern characteristics of annual average AOD.
王萍, 汤庆新, 梁天全, 于泉洲, 李欣. 基于MODIS数据的山东省近十年AOD时空变化特征[J]. 中国环境科学, 2021, 41(11): 5019-5026.
WANG Ping, TANG Qing-xin, LIANG Tian-quan, YU Quan-zhou, LI Xin. Spatiotemporal variation of AOD in Shandong Province in recent ten years based on MODIS data. CHINA ENVIRONMENTAL SCIENCECE, 2021, 41(11): 5019-5026.
谢志英,刘浩,唐新明.北京市MODIS气溶胶光学厚度与PM10质量浓度的相关性分析[J]. 环境科学学报, 2015,35(10):3292-3299.Xie Z Y, Liu H, Tang X M. Correlation analysis between MODIS aerosol optical depth and PM10 concentration over Beijing[J]. Acta Scientiae Circumstantiae, 2015,35(10):3292-3299.
[2]
郑小波,周成霞,罗宇翔,等.中国各省区近10年遥感气溶胶光学厚度和变化[J]. 生态环境学报, 2011,20(4):595-599.Zheng X B, Zhou C X, Luo Y X, et al. Chinese province-level variations and trends in aerosol optical depth from recent 10years of remote sensing data[J]. Ecology and Environmental Sciences, 2011, 20(4):595-599.
[3]
张宸赫,赵天良,王富,等.2003~2014年东北三省气溶胶光学厚度变化分析[J]. 环境科学, 2017,38(2):476-484.Zhang Z H, Zhao T L, Wang F, et al. Variations in aerosol optical depth over three Northeastern Provinces of China, in 2003~2014[J]. Environmental Science, 2017,38(2):476-484.
[4]
玛依拉·热西丁,丁建丽,张喆等.乌鲁木齐市气溶胶光学厚度时空分布特征及潜在来源分析[J]. 环境科学学报, 2020,40(5):1611-1620.Mayila Rexiding, Ding J L, Zhang Z, et al. Spatiotemporal distribution characteristics and potential sources of aerosol optical depth in Urumqi[J]. Acta Scientiae Circumstantiae, 2020,40(5):1611-1620.
[5]
罗宇翔,陈娟,郑小波.近10年中国大陆MODIS遥感气溶胶光学厚度特征[J]. 生态环境学报, 2012,21(5):876-883.LuoY X, Chen J, Zheng X B. Climatology of aerosol optical depth over China from recent 10years of MODIS remote sensing data[J]. Ecology and Environmental Sciences, 2012,21(5):876-883.
[6]
Grgurić S, Križan J, Gašparac G, et al. Relationship between MODIS based aerosol optical depth and PM10 over Croatia[J]. Open Geosciences, 2014,6(1):2-16.
[7]
齐冰,杜荣光,于之锋,等.杭州市大气气溶胶光学厚度研究[J]. 中国环境科学, 2014,34(3):588-595.Qi B, Du R G, Yu Z F, et al. Aerosol optical depth in urban site of Hangzhou[J]. China Environmental Science, 2014,34(3):588-595.
[8]
李一凡,陈文忠.基于MODIS和CALIOP卫星遥感数据的气溶胶光学厚度与海洋初级生产力相关性[J]. 中国环境科学, 2017,37(1):76-86.Li Y F, Chen W Z. Correlation between aerosol optical depth and ocean primary productivity based on MODIS and CALIOP data[J]. China Environmental Science, 2017,37(1):76-86.
[9]
马奋华,管兆勇.中国东部AOD等级变化及与东亚夏季风的联系[J]. 中国环境科学, 2018,38(9):3201-3210.Ma F H, Guan Z Y. Features of graded AOD in East China in association with East Asian summer monsoon anomalies[J]. China Environmental Science, 2018,38(9):3201-3210.
[10]
王银牌,喻鑫,谢广奇.中国近15年气溶胶光学厚度时空分布特征[J]. 中国环境科学, 2018,38(2):426-434.Wang Y P, Yu X, Xie G Q. Spatial distribution and temporal variation of aerosol optical depth over China in the past 15years[J]. China Environmental Science, 2018,38(2):426-434.
[11]
刘状,石晨烈,张萌,等.基于聚类分析的气溶胶光学厚度时间变化特征研究[J]. 大气与环境光学学报, 2019,14(6):411-418.Liu Z, Shi C L, Zhang M, et al. Temporal characteristics of aerosol optical depth based on cluser analysis method[J]. Journal of Atmospheric and Environmental Optics, 2019,14(6):411-418.
[12]
胡俊,钟珂,亢燕铭,等.新疆典型城市气溶胶光学厚度变化特征[J]. 中国环境科学, 2019,39(10):4074-4081.Hu J, Zhong K, Kang Y M, et al. Variation in aerosol optical depth over the typical cities in the Xinjiang region[J]. China Environmental Science, 2019,39(10):4074-4081.
[13]
丁莹,冯徽徽,邹滨,等.长株潭城市群气溶胶时空分布与传输规律[J]. 中国环境科学, 2020,40(5):1906-1914.Ding Y, Feng H H, Zou B, et al. Spatial-temporal distribution and transport characteristic of aerosol in Changsha-Zhuzhou-Xiangtan urban agglomeration[J]. China Environmental Science, 2020,40(5):1906-1914.
[14]
刘雨华,郑小慎.环渤海地区气溶胶光学厚度数据选取及时空特征分析[J]. 环境科学学报, 2020,40(5):1621-1628.Liu Y H, Zheng X S. Analysis of temporal and spatial characteristics and data selection of aerosol optical depth in the Bohai Rim Region[J]. Acta Scientiae Circumstantiae, 2020,40(5):1621-1628.
[15]
Gunadhar B, Prasenjit A, Arabinda M, et al. A synergy of linear model and wavelet analysis towards space-time characterization of aerosol optical depth (AOD) during pre-monsoon season (2007~2016) over Indian sub-continent[J]. Journal of Atmospheric and Solar-Terrestrial Physics, 2020,211.
[16]
牛林芝,王旭红,韩海青,等.中亚五国气溶胶光学厚度时空分布特征研究[J]. 环境科学学报, 2021,41(2):321-333.Niu L Z, Wang X H, Han H Q, et al. Spatiotemporal distribution of aerosol optical depth in the five Central Asian countries[J]. Acta Scientiae Circumstantiae, 2021,41(2):321-333.
[17]
King M D, Kaufman Y J, Menzel W P, et al. Remote sensing of cloud, aerosol, and water vapor properties from the moderate resolution imaging spectrometer (MODIS)[J]. IEEE Transactions on Geoscience and Remote Sensing, 1992,30(1):2-27.
[18]
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.
[19]
Li Jing, Bo Yu, Xie Shaodong. Estimating emissions from crop residue open burning in China based on statistics and MODIS fire products[J]. Journal of Environmental Sciences, 2016,44:158-170.
[20]
Jerome Vidot, Richard Santer, Didier Ramon. Atmospheric particulate matter (PM) estimation from SeaWiFS imagery[J]. Remote Sensing of Environment, 2007,111(1):1-10.
[21]
中国多尺度排放清单模型MEIC[EB/OL]. http://www.meicmodel.org/. Multi-resolution Emission Inventory for China[EB/OL]. http://www.meicmodel.org/.
[22]
汤玉明,邓孺孺,刘永明,等.大气气溶胶遥感反演研究综述[J]. 遥感技术与应用, 2018,33(1):25-34.Tang Y M, Deng R R, Liu Y M, et al. Research review of remote sensing for at mospheric aerosol retrieval[J]. Remote Sensing Technology and Application, 2018,33(1):25-34.
[23]
芦亚玲,迟建伟,姚兰,等.中国北部背景区域霾天气溶胶的水溶性无机离子组分及混合状态[J]. 中国科学:地球科学, 2015,45(11):1728-1736.Lu Y L, Chi J W, Yao L, et al. Composition and mixing state of water soluble inorganic ions during hazy days in a background region of North China[J]. Science China:Earth Sciences, 2015,45(11):1728-1736.
[24]
许潇锋,刘晨璇,唐志伟,等.基于CALIPSO的华北地区气溶胶垂直分布特征[J]. 大气科学学报, 2018,41(1):126-134.Xu X F, Liu C X, Tang Z W, et al. Characteristics of aerosol vertical distribution based on CALIPSO over North China[J]. Transactions of Atmospheric Sciences, 2018,41(1):126-134.
[25]
吴燕杰,满其霞,艾文育,等.2001~2018年济南气溶胶光学厚度时空分布及影响因素研究[J]. 山东师范大学学报(自然科学版), 2020, 35(4):449-459.Wu Y M, Man Q X, Ai W Y, et al. Temporal and spatial distribution of aerosol optical depth and its influencing factors in jinan from 2001to 2018[J]. Journal of Shandong Normal University(Natural Science), 2020,35(4):449-459.
[26]
山东省大气污染防治条例[EB/OL]. http://www.sdrd.gov.cn/articles/ch00023/201812/9d34892a-b597-4096-a3de-7878e4cc4df1.shtml, 2018-12-05.Regulations of Shandong Province on prevention and control of air pollution[EB/OL]. http://www.sdrd.gov.cn/articles/ch00023/201812/9d34892a-b597-4096-a3de-7878e4cc4df1.shtml, 2018-12-05.
[27]
徐新华,姚荣奎,李金龙.青岛地区大气气溶胶海洋因子贡献研究[J]. 海洋环境科学, 1997,(2):56-60.Xu X H, Yao R K, Li J L. Study on the sea contribution to atmospheric aerosol in Qingdao district[J]. Marine Environmental Science, 1997, (2):56-60.
[28]
关佳欣,李成才.我国中、东部主要地区气溶胶光学厚度的分布和变化[J]. 北京大学学报(自然科学版), 2010,46(2):185-191.Guan J X, Li C C. Spatial distributions and changes of aerosol optical depth over Eastern and Central China[J]. Acta Scientiarum Naturalium Universitatis Pekinensis, 2010,46(2):185-191.
[29]
岳辉,刘英,张元敏.基于MODIS数据的中国地区气溶胶光学厚度时空变化特征[J]. 环境污染与防治, 2020,42(1):89-93.Yue H, Liu Y, Zhang Y M. Study on temporal and spatial variabilitu of aerosol optical depth in China region based on MODIS data[J]. Environmental Pollution & Control, 2020,42(1):89-93.
[30]
常明,刘晓环,刘明旭,等.非采暖期和采暖期青岛市及中国东部臭氧和细颗粒物模拟研究[J]. 中国海洋大学学报(自然科学版), 2016, 46(2):14-25.Chang M, Liu X H, Liu M X, et al. Simulation study of ozone and fine particulate matter in Qingdao and eastern China in non-heating and heating periods[J]. Periodical of Ocean University of China, 2016, 46(2):14-25.
[31]
陈文泰,邵敏,袁斌,等.大气中挥发性有机物(VOCs)对二次有机气溶胶(SOA)生成贡献的参数化估算[J]. 环境科学学报, 2013, 33(1):163-172.Chen W T, Shao M, Yuan B, et al. Parameterization of contribution to secondary organic aerosol (SOA) formation from ambient volatile organic compounds (VOCs)[J]. Acta Scientiae Circumstantiae, 2013, 33(1):163-172.
[32]
张晶,朱兆洲,李绪威,等.煤改气后天津市采暖期大气污染特征的时空分布研究[J]. 生态环境学报, 2019,28(2):324-331.Zhang J, Zhu Z Z, Li X W, et al. Spatial and temporal distribution of atmospheric pollutants in Tianjin during winter heating period after the "coal to gas" project[J]. Ecology and Environmental Sciences, 2019, 28(2):324-331.
[33]
刘利,邓宇宸,吴丹,等.广东省城市环境空气质量时空特征及经济影响因素分析[J]. 中国环境监测, 2021,37(3):40-50.Liu L, Deng Y C, Wu D, et al. Analysis of temporal and spatial characteristics and economic influencing factors of urban ambient air quality in Guangdong Province[J]. Environmental Monitoring in China, 2021,37(3):40-50.
[34]
林美含,张晓平.华北地区空气质量时空变化特征及其影响因素探究[C]//2019年中国地理学会经济地理专业委员会学术年会摘要集, 2019.Lin M H, Zhang X P. Spatiotemporal variation of air quality in North China and its influencing factors[C]//Abstract of the Academic Annual Meeting of Economic Geography Committee of Chinese Geographical Society in 2019, 2019.
[35]
王雁,郭伟,闫世明,等.山西省气溶胶光学厚度时空变化特征及气候效应分析[J]. 生态环境学报, 2018,27(5):900-907.Wang Y, Guo W, Yan S M, et al. Analysis of spatio-temporal variation of aerosol optical depth and climatic effects in Shanxi Province[J]. Ecology and Environmental Sciences, 2018,27(5):900-907.
[36]
Miao Zhang, Jing Liu, Muhammad Bilal, et al. Optical and Physical Characteristics of the Lowest Aerosol Layers over the Yellow River Basin[J]. Atmosphere, 2019,10(10).
[37]
纪晓璐,廉丽姝,周甜甜,等.基于MODIS数据的环渤海地区气溶胶时空变化特征分析[J]. 环境污染与防治, 2017,39(11):1238-1241, 1245.Jj X L, Lian L S, Zhou T T, et al. Temporal and spatial variation characteristics analysis of around Bohai Sea region based on MODIS data[J]. Environmental Pollution & Control, 2017,39(11):1238-1241,1245.
[38]
侯思远,刘雨华,郑小慎,等.基于MODIS数据气溶胶光学厚度特征分析[J]. 海洋信息, 2019,34(2):36-42.Hou S Y, Liu Y H, Zheng X S, et al. Analysis of Aerosol Optical Thickness Characteristics Based on MODIS Data[J]. Marine Information, 2019,34(2):36-42.
[39]
吴振信,闫洪举.产业结构变迁对环渤海经济圈大气污染物排放的影响[J]. 商业研究, 2015,(6):30-35.Wu Z X, Yan H J. The effects of industrial structure change on Bohai Rim Region Economic Circle's air pollution[J]. Commercial Research, 2015,(6):30-35.