당신은 주제를 찾고 있습니까 “气 溶胶 光学 厚度 – 【科普】什么是气溶胶传播+怎么预防？“? 다음 카테고리의 웹사이트 you.maxfit.vn 에서 귀하의 모든 질문에 답변해 드립니다: you.maxfit.vn/blog. 바로 아래에서 답을 찾을 수 있습니다. 작성자 iLuv It 이(가) 작성한 기사에는 조회수 1,528회 및 좋아요 36개 개의 좋아요가 있습니다.
气溶胶光学厚度,英文名称为AOD（Aerosol Optical Depth）或AOT（Aerosol Optical Thickness），定义为介质的消光系数在垂直方向上的积分，是描述气溶胶对光的削减作用的。 它是气溶胶最重要的参数之一，表征大气浑浊程度的关键的物理量，也是确定气溶胶气候效应的重要因素。
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d여기에서 【科普】什么是气溶胶传播+怎么预防？ – 气 溶胶 光学 厚度 주제에 대한 세부정보를 참조하세요
8号上海举行的防疫工作发布会上，卫生防疫专家指出，目前可以确定新冠状肺炎的主要传播途径是直接传播、气溶胶传播和接触传播。搞得人心惶惶的气溶胶传播是什么？ 这个是我看到解释得最清楚的视频了。
视频出处：微博@普外科曾医生 https://www.weibo.com/zengdashuaiguo?
气 溶胶 光学 厚度 주제에 대한 자세한 내용은 여기를 참조하세요.
基于MODIS数据的中国气溶胶光学厚度时空分布特征
气溶胶光学厚度(Aerosol Optical Depth, AOD)是大气气溶胶的重要光学特性之一, 其为气溶胶的消光系数在垂直方向上的积分, 是推算气溶胶含量和研究气溶胶气候效应的关键因子 …
Source: www.actasc.cn
Date Published: 12/27/2022
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基于气溶胶光学厚度反演大气气溶胶尺度分布! – 物理学报
从实测气溶胶光学厚度出发，依据严. 格的Mie 散射理论，将气溶胶尺度分布函数离散，采用线性回归法确定气溶胶尺度分布. 还通过对多重共线性的讨. 论，确定了用于反演气溶胶 …
Source: wulixb.iphy.ac.cn
Date Published: 9/6/2021
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亚洲大陆气溶胶光学厚度数据集（2002-2011）
China Collection 1.0”气溶胶光学厚度（AOD）数据集采用可见光波段遥感反演方法制作。原始数据来自Terra和Aqua上搭载的MODIS传感器。数据覆盖时间从2002年到2011年， …
Source: data.tpdc.ac.cn
Date Published: 9/21/2021
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高分辨率气溶胶光学厚度反演及其与地表特征和热环境的相关 …
气溶胶光学厚度(Aerosol Optical Depth,AOD)不仅是影响遥感影像定量反演的重要因素,还是地球大气系统中的一个重要参数,与其他地表参数一起影响了地表能量收支平衡状况 …
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Date Published: 2/6/2021
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卫星遥感监测全球大气气溶胶光学厚度变化
卫星遥感监测全球大气气溶胶光学厚度变化. 李晓静, 高玲, 张兴赢, 张鹏. 中国气象局国家卫星气象中心, 北京100081. Global change of aerosol optical depth based on …
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Date Published: 6/23/2021
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주제와 관련된 이미지 气 溶胶 光学 厚度
주제와 관련된 더 많은 사진을 참조하십시오 【科普】什么是气溶胶传播+怎么预防？. 댓글에서 더 많은 관련 이미지를 보거나 필요한 경우 더 많은 관련 기사를 볼 수 있습니다.
주제에 대한 기사 평가 气 溶胶 光学 厚度
- Author: iLuv It
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- Date Published: 2020. 2. 9.
- Video Url link: https://www.youtube.com/watch?v=saGmCEzJ3uo
基于MODIS数据的中国气溶胶光学厚度时空分布特征
引用本文 张亮林, 潘竟虎, 张大弘. 2018. 基于MODIS数据的中国气溶胶光学厚度时空分布特征[J]. 环境科学学报, 38(11): 4431-4439. Zhang L L, Pan J H, Zhang D H. 2018. Spatio-temporal distribution characteristics of aerosol optical depths in China based on MODIS data[J]. Acta Scientiae Circumstantiae, 38(11): 4431-4439.
张亮林 潘竟虎 张大弘
摘要: 利用Aqua/MODIS C006大气气溶胶光学厚度（AOD）遥感数据，统计了中国2007—2017年的AOD值，对11年间AOD的空间分布特征及年际和四季变化特征进行分析，并采用Theil-Sen Median趋势分析、标准偏差和Hurst指数3种方法，分析了基于像元的中国大陆地区AOD时空变化特征.结果表明：①空间特征：11年间AOD分布具有东部高、西部低，东部减少、西部基本不变的特征；②时间特征：AOD变化在年际间呈余弦曲线式波动下降的特征，最高值出现在2007年，为0.34，最低值出现在2016年，为0.22，11年间AOD平均值下降了35.29%；年内AOD值表现出春夏高（0.33/0.32），秋季次之（0.26），冬季最小（0.15）的季节变化特征；③稳定性与持续性：东部稳定性差但集聚、西部稳定性好但分散，东西差异显著；中国AOD持续性特征以弱反持续性为主，弱持续和弱反持续镶嵌分布，西北干旱区表现为强反持续性的特点.
关键词 : 气溶胶光学厚度(AOD) MODIS 时空分布 中国
Spatio-temporal distribution characteristics of aerosol optical depths in China based on MODIS data
ZHANG Lianglin PAN Jinghu ZHANG Dahong
College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070 Supported by the National Natural Science Foundation of China (No. 41661025), the Project of Educational Commission of Gansu Province of China (No. 2016A-001) and the Research Ability Promotion Project for Young Teachers of Northwest Normal University (No. NWNU-LKQN-16-7) Biography: ZHANG Lianglin (1993—), male, E-mail: [email protected] *Corresponding author: PAN Jinghu, E-mail: Corresponding author: PAN Jinghu, E-mail: [email protected]
Abstract: The Aqua/MODIS C006 aerosol optical depths (AOD) products were used to calculate the AOD values in China from 2007 to 2017. The spatial distribution characteristics of AOD over the 11 years as well as the characteristics of inter-annual and seasons changes were analyzed. In addition, the spatial and temporal changes were analyzed using the Theil-Sen Median trend analysis, standard deviation and Hurst index based on pixels of AOD in mainland China. The results show that:① Spatial characteristics:the distribution of AOD over the 11 years demonstrates the characteristics of high in the east, low in the west, decreasing in the east, and basically unchanged in the west; ② Temporal characteristics:the variation of AOD shows a cosine curve-like fluctuation decline from year to year. The highest value appeared in 2007 was 0.34 and the lowest value appeared in 2016 was 0.22, with a decrease of 35.29% comparatively. In one year, the seasonal variation was characterized by spring-summer (0.33/0.32), autumn (0.26) and winter (0.15); ③ Stability and persistence:the stability in eastern China was poor but concentrated, while the stability in western China was good but scattered, with the significant difference between the East and the West. The persistent feature of AOD in China is mainly weak anti-persistence, weak persistent and weak anti-persistence mosaic distribution, but strong anti-persistence is the main characteristic in arid areas of northwest China.
亚洲大陆气溶胶光学厚度数据集（2002-2011）-国家青藏高原科学数据中心
查看大图 “China Collection 1.0”气溶胶光学厚度（AOD）数据集采用可见光波段遥感反演方法制作。原始数据来自Terra和Aqua上搭载的MODIS传感器。数据覆盖时间从2002年到2011年，时间分辨率为逐日，覆盖范围为亚洲大陆，空间分辨率为0.1°。遥感反演方法采用自主研发的SRAP算法反演了陆地上空的气溶胶光学厚度，算法考虑了地表的BRDF特性，适用于亮地表和暗地表上的气溶胶光学厚度反演。此外，叠加了MOD04/MYD04海洋上空的气溶胶产品。通过实测站点的验证表明亚洲气溶胶光学厚度数据相对偏差在20%以内。数据每一天存放一个hdf文件，每个文件由550nm处的Terra AOD和Aqua AOD组成。
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光洁, 薛勇. (2018). 亚洲大陆气溶胶光学厚度数据集（2002-2011）. 国家青藏高原科学数据中心, DOI: 10.11888/AtmosEnviron.tpe.00000031.file. CSTR: 18406.11.AtmosEnviron.tpe.00000031.file.
[Guang, J., Xue, Y. (2018). SRAP AOD dataset of Asia (2002-2011). National Tibetan Plateau Data Center, DOI: 10.11888/AtmosEnviron.tpe.00000031.file. CSTR: 18406.11.AtmosEnviron.tpe.00000031.file. ] (下载引用： RIS格式 | RIS英文格式 | Bibtex格式 | Bibtex英文格式 )文章的引用
1. Xue, Y., He, X.W., Xu, H., Guang, J., Guo, J.P., &Mei, L.L. (2014). China Collection 2.0: The Aerosol Optical Depth Dataset from the Synergetic Retrieval of Aerosol Properties Algorithm. Atmospheric Environment, 95, 45-58.( 查看 | Bibtex格式)
2. Guang, J., Xue, Y., Li, Y.J., Liang, S.L., Mei, L.L., &Xu, H. (2012). Retrieval of Aerosol Optical Depth over Bright Land Surfaces by Coupling Bidirectional Reflectance Distribution Function Model and Aerosol Retrieval Model. Remote Sensing Letter, 3 (7), 577-584.( 查看 | Bibtex格式)
3. Tang, J.K., Xue, Y., Yu, T., &Guan, Y.N. (2005). Aerosol Optical Thickness Determination by Exploiting the Synergy of TERRA and AQUA MODIS (SYNTAM). Remote Sensing of Environment, 94(3), 327-334.( 查看 | Bibtex格式)
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中文发表的成果致谢中参考以下规范注明： 数据来源于“国家青藏高原科学数据中心”(http://data.tpdc.ac.cn)。
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License： This work is licensed under an Attribution 4.0 International (CC BY 4.0)
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卫星遥感监测全球大气气溶胶光学厚度变化
科技导报 2015, Vol. 33 Issue (17): 30-39 DOI: 10.3981/j.issn.1000-7857.2015.17.003 专题论文 本期目录 | 过刊浏览 | 高级检索 | 卫星遥感监测全球大气气溶胶光学厚度变化 李晓静, 高玲, 张兴赢, 张鹏 中国气象局国家卫星气象中心, 北京100081 Global change of aerosol optical depth based on satellite remote sensing data LI Xiaojing, GAO Ling, ZHANG Xingying, ZHANG Peng National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China 摘要
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输出: BibTeX | EndNote (RIS) 摘要 全球大气气溶胶类型和含量变化与气候变化和大气环境污染密切相关,是气象学、环境学和医学研究关注的热点问题。为认识全球气溶胶分布基本特征,发现和跟踪全球气溶胶显著变化地区,本文利用美国NASA 发布的C6 版MODIS气溶胶光学厚度产品分析全球大气气溶胶光学厚度时空年变化特征及其影响因素;分析气溶胶光学厚度分布与中国霾区的关系,提出霾区治理的气溶胶光学厚度年平均值参考标准。分析2003—2014 年卫星监测的气溶胶光学厚度(AOD)空间分布特征显示,全球气溶胶光学厚度稳定高值区位于亚洲东部及其邻近太平洋海区、印度半岛及其邻近印度洋海区、非洲北部和中部及其邻近大西洋海区;重点变化关注区为俄罗斯西伯利亚东部增量区和南美洲亚马逊平原热带雨林减量区。气溶胶光学厚度高值地区的形成与沙尘暴、火山喷发、生物质燃烧、工业排放等自然源,以及工业污染物排放、交通运输、秸秆焚烧等人类活动造成的人为源气溶胶排放直接相关,并受气象因素和山脉等地形阻挡因素影响,这些因素的稳定性与季节变化最终形成全球气溶胶的时空分布特征。中国东部气溶胶光学厚度年平均值大于0.5 的区域为主要霾天气区,其中华北南部、黄淮、江淮、江汉地区和四川盆地为全球气溶胶光学厚度极端高值区,年平均极端高值达到0.8~1.0,为霾天气常态化发生区;通过全球气溶胶光学厚度量值分析认为,气溶胶光学厚度年平均值0.5 可作为中国大气环境最大承载量,中国东部地区高于此值的区域为主要大气污染控制区,大范围工业生产污染物减排可带来整体环境改善,通过工业结构调整有望降低的气溶胶污染中位比率为33%,平均比率为26.5%。 服务 把本文推荐给朋友 加入我的书架 加入引用管理器 E-mail Alert RSS 作者相关文章 李晓静 高玲 张兴赢 张鹏 关键词 ： 大气气溶胶, 气溶胶光学厚度, 霾, MODIS Abstract：The aerosol type and the concentration variation are the hotspots related to the climate change, the environment and the human-health. The AQUA/MODIS aerosol optical depth (AOD) product issued by NASA is used to analyze the temporal and spatial changes of the multi-yearly and annual mean AODs in the whole world and in China for diagnosing the aerosol events that directly emitted or affected, such as the haze, the dust storm or the volcano eruption. The results show that the eastern Asia, the Indian peninsula, the northern and central Africa and their adjacent ocean areas have relatively high AODs. The significantly changing areas include the east area of Siberia due to the smoke by fire and the Amazon rainforest for bioaerosols by vegetation emissions. These high and sensitive AOD regions are closely related with the aerosol emission by natural and human activities, and they are also influenced by weather and terrain. In China, the regions in the eastern China with the yearly mean AOD higher than 0.5 are the haze weather areas. In particular, the Huanghe-Huaihe River basin, the Yangtze-Huaihe River basin and the central part of China have the highest mean AODs of 0.8-1.0, where serious haze weather often occurs. The highest AOD is caused by the highest emission from the industrial and agricultural productions, constructions, and heavy transportations. So, based on the reference the AOD (background 0.2, natural events impact 0.15, human living impact 0.15) obtained from the aerosol distinctive area, the annual mean AOD of 0.5 is defined as a threshold for delimiting the haze area and the pollution control district. In China, the environmental improvement depends on the cutting back the industrial emissions in the regions with annual mean AOD higher than 0.5, and the middle cutting ratio is 33% and the averaged cutting ratio is 26.5%. Key words： atmospheric aerosol AOD haze MODIS 收稿日期: 2015-06-18 ZTFLH: P407 基金资助:国家重点基础研究发展计划(973计划)项目(2011CB403401);国家科技支撑计划项目(2014BAC16B01) 作者简介: 李晓静,副研究员,研究方向为卫星气溶胶参数反演算法及产品应用,电子信箱:[email protected] 引用本文: 李晓静, 高玲, 张兴赢, 张鹏. 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): 30-39.
LI Xiaojing, GAO Ling, ZHANG Xingying, ZHANG Peng. Global change of aerosol optical depth based on satellite remote sensing data. Science & Technology Review, 2015, 33(17): 30-39. 链接本文: http://www.kjdb.org/CN/10.3981/j.issn.1000-7857.2015.17.003 或 http://www.kjdb.org/CN/Y2015/V33/I17/30 [1] 段婧, 毛节泰. 华北地区气溶胶对区域降水的影响[J]. 科学通报, 2008, 53(23):2947-2955. Duan Jing, Mao Jietai. Influence of aerosol on regional precipitation in North China[J]. Chinese Science Bulletin, 2008, 53(23):2947-2955.
[2] Lau K M, Ramanathan V, Wu G X, et al. The joint aerosol-hydrologic cycle interaction:A new challenge to monsoon climate research[J]. Bulletin of the American Meteorological Society, 2008, 89(3):369-383. [3] Menon S, Hansen J, Nazarenko L, et al. Climate effects of black carbon aerosols in China and India[J]. Science, 2002, 297:2250-2253. [4] 李成才, 毛节泰, 刘启汉, 等. MODIS卫星遥感气溶胶产品在北京市大 气污染研究中的应用[J]. 中国科学:D辑, 2005, 35(增1):177-186. Li Chengcai, Mao Jietai, Liu Qihan, et al. Application of aerosol products retrieved by satellite data on the air pollution in Beijing[J]. Science in China, Series D, 2007, 35(Suppl 1):177-186. [5] 徐祥德, 丁国安, 卞林根. 北京城市大气环境污染机理与调控原理[J]. 应用气象学报, 2006, 17(6):815-828. Xu Xiangde, Ding Guoan, Bian Lingen. Beijing air pollution observation experiment[J]. Journal of Applied Meteorological Science, 2006, 17(6):815-828. [6] 丁国安, 郑向东, 马建中, 等. 近30年大气化学和大气环境研究回顾 ——纪念中国气象科学研究院成立50周年[J]. 应用气象学报, 2006, 17(6):796-814. Ding Guoan, Zheng Xiangdong, Ma Jianzhong, et al. Review of atmospheric chemistry and environment research work in recent 30 years[J]. Journal of Applied Meteorological Science, 2006, 17(6):796-814. [7] van Donkelaar A, Martin R V, Brauer M, et al. Global estimates of ambient fine particulate matter concentrations from satellite-based aerosol optical depth:Development and application[J]. Environmental Health Perspectives, 2010, 118(6):847-855. [8] 邱金桓, 王普才, 夏祥鳌, 等. 近年来大气遥感研究进展[J]. 大气科 学, 2008, 32(4):841-853. Qiu Jinhuan, Wang Pucai, Xia Xiangao, et al. Recent progresses in atmospheric remote sensing researches[J]. Chinese Journal of Atmospheric Sciences, 2008, 32(4):841-853. [9] Li B, Yuan H, Feng N, et al. Spatial and temporal variations of aerosol optical depth in China during the period from 2003 to 2006[J]. International Journal of Remote Sensing, 2010, 31(7):1801-1817. [10] 蔡惠文, 杨军, 李晓静, 等. 近10年全球气溶胶光学厚度变化特征及 其可能原因[J]. 遥感技术与应用, 2012, 27(6):961-966. Cai Huiwen, Yang Jun, Li Xiaojing, et al. Characteristics and possible reasons of global trend in aerosol optical depth over the past decate[J]. Remote Sensing Technology and Application, 2012, 27(6):961-966. [11] 杨军, 董超华, 卢乃锰, 等. 新一代风云极轨气象卫星业务产品及应 用[M]. 北京:科学出版社, 2010. Yang Jun, Dong Chaohua, Lu Naimeng, et al. Products and application of new serial FY polar orbit meteorological satellite[M]. Beijing:Science Press, 2010. [12] de Leeuw G, Holzer-Popp T, Bevan S, et al. Evaluation of seven European aerosol optical depth retrieval algorithms for climate analysis[J]. Remote Sensing of Environment, 2015, 162:295-315. [13] Levy R C, Mattoo S, Munchak L A, et al. The collection 6 MODIS aerosol products over land and ocean[J]. Atmospheric Measurement Techniques, 2013, 6(1):159-259. [14] Kaufman Y J, Tanre D, Remer L A, et al. Operational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer[J]. Journal of Geophysical Research, 1997, 102(D14):17051-17067. [15] Levy R C, Remer L A, Dubovik O. Global aerosol optical properties and application to moderate resolution imaging spectroradiometer aerosol retrieval over land[J]. Journal of Geophysical Research, 2007, 112(D13):doi:10.1029/2006JD007815. [16] Levy R C, Remer L A, Mattoo S, et al. Second-generation operational algorithm:Properties over land from inversion of moderate resolution imaging spectroradiometer spectral reflectance Retrieval of aerosol[J]. Journal of Geophysical Research, 2007, 112(D13):doi:10.1029/2006JD007811:1-21. [17] 李晓静, 张鹏, 张兴赢, 等. 中国区域业务MODIS陆地气溶胶光学厚 度产品质量检验[J]. 应用气象学报, 2009, 20(2):147-156. Li Xiaojing, Zhang Peng, Zhang Xingying, et al. Validation of aerosol optical thickness product over China with MODIS data operated at NSMC[J]. Journal of Applied Meteorological Science, 2009, 20(2):147-156. [18] 毛节泰, 李成才, 张军华, 等. MODIS卫星遥感北京地区气溶胶光学 厚度与地面光度计遥感对比[J]. 应用气象学报, 2002, 13(增1):127-135. Mao Jietai, Li Chengcai, Zhang Junhua, et al. The comparison of remote sensing aerosol optical depth from MODIS data and ground sun-photometer observations[J]. Journal of Applied Meteorological Science, 2002, 13(Suppl 1):127-135. [19] 夏祥鳌. 全球陆地上空MODIS 气溶胶光学厚度显著偏高[J]. 科学通 报, 2006, 51(19):2297-2303. Xia Xiangao. Aerosol optical depth over land from MODIS was significantly over-estimated[J]. Chinese Science Bulletin, 2006, 51 (19):2297-2303. [20] Li Z, Niu F, Lee K H, et al. Validation and understanding of moderate resolution imaging spectroradiometer aerosol products (C5) using ground-based measurements from the handheld sun photometer network in China[J]. Journal of Geophysical Research, 2007, 112 (D22):doi:10.1029/2007JD008479. [21] Li B, Yuan H, Feng N, et al. Comparing MODIS and AERONET aerosol optical depth over China[J]. International Journal of Remote Sensing, 2009, 30(24):6519-6529. [22] 张小曳, 孙俊英, 王亚强, 等. 我国雾-霾成因及其治理的思考[J]. 科 学通报,2013, 58(13):1178-1187. Zhang Xiaoye, Sun Junying, Wang Yaqiang, et al. Factors contributing to haze and fog in China[J]. Chinese Science Bulletin, 2013, 58(13):1178-1187. [23] Ravindra K, Wauters E, Tyagi S K, et al. Assessment of air quality after the implementation of compressed natural gas (CNG) as fuel in public transport in Delhi, India[J]. Environmental Monitoring and Assessment, 2006, 115(1-3):405-417. [24] Guttikunda S K, Goel R. Health impacts of particulate pollution in a megacity—Delhi, India[J]. Environmental Development, 2013, 6:8-20. [25] Prospero J M, Glaccum R A, Nees R T. Atmospheric transport of soil dust from Africa to South America[J]. Nature, 1981, 289:570-572. [26] Barbosa P M, Stroppiana D, Gregoire J M. An assessment of vegetation fire in Africa (1981-1991):Burned areas, burned biomass, and atmospheric emissions[J]. Global Biogeochemical Cycles, 1999, 13(4):933-950. [27] Hebrew University of Jerusalem. New model provides more effective basis for biodiversity conservation[N/OL]. Science Daily, [2010-09-12]. http://www.sciencedaily.com/releases/2010/09/100912084116.htm. [28] Hilker T, Lyapustin A I, Tucker C J, et al. Vegetation dynamics and rainfall sensitivity of the Amazon[J]. Proceedings of the National Academy of Sciences of the United States of America, 2014, 111(45):16041-16046. [29] Voight B, Constantine E K, Siswowidjoyo S, et al. Historical eruptions of Merapi Volcano, Central Java, Indonesia, 1768-1998[J]. Journal of Volcanology and Geothermal Research, 2000, 100(1-4):69-138. [30] Field R D, van der Werf G R, Shen S S P. Human amplification of drought-induced biomass burning in Indonesia since 1960[J]. Nature Geoscience, 2009, 2(3):185-188. [31] Micklin P. The aral sea disaster annual review of earth and planetary sciences[J]. Earth and Planetary Sciences, 2007, 35:47-72. [32] Davies S M, Larsen G, Wastegård S, et al. Widespread dispersal of Icelandic tephra:How does the Eyjafjöll eruption of 2010 compare to past Icelandic events?[J]. Journal of Quaternary Science, 2010, 25(5):605-611. [33] 张人禾, 李强, 张若楠. 2013年1月中国东部持续性强雾霾天气产生 的气象条件分析[J]. 中国科学:地球科学, 2014, 44(1):27-36. Zhang Renhe, Li Qiang, Zhang Ruonan. Meteorological conditions for the persistent severe fog and haze event over eastern China in January 2013[J]. Science China:Earth Sciences, 2014, 44(1):27-36. [34] 穆穆, 张人禾. 应对雾霾天气:气象科学与技术大有可为[J]. 中国科 学:地球科学, 2014, 44(1):1-2. Mu Mu, Zhang Renhe. Addressing the issue of fog and haze:A promising way of meteorological science and technology[J]. Science China Earth Sciences, 2014, 44(1):1-2. [35] Stothers R B. The great tambora eruption in 1815 and its aftermath[J]. Science, 1984, 224(4654):1191-1198. [36] Handler P. The effect of volcanic aerosols on global climate[J]. Journal of Volcanology and Geothermal Research, 1989, 37(3-4):233-249. [37] 王中挺, 厉青, 李莘莘, 等. 基于环境一号卫星的霾监测应用[J]. 光 谱学与光谱分析, 2012, 32(32):775-780. Wang Zhongting, Li Qing, Li Shenshen, et al. The monitoring of haze from HJ-1[J]. Spectroscopy and Spectral Analysis March, 2012, 32 (32):775-780. [38] 吴兑. 霾与雾的识别和资料分析处理[J]. 环境化学, 2008, 27(3):327-330. Wu Dui. Discussion on the distinction between haze and fog and analysis and processing of data[J]. Environmental Chemistry, 2008, 27 (3):327-330. [39] 马国欣, 薛永祺, 李高丰. 珠江三角洲地区的灰霾监控与卫星遥感[J]. 科技导报, 2008, 26(16):72-76. Ma Guoxin, Xue Yongqi, Li Gaofeng. Satellite remote sensing for haze monitoring in Pearl River delta region[J]. Science & Technology Review, 2008, 26(16):72-76. [40] 吴兑, 吴晓京, 李菲,等. 1951—2005年中国大陆霾的时空变化[J]. 气象学报, 2010, 68(5):680-688. Wu Dui, Wu Xiaojing, Li Fei, et al. Temporal and special variation of haze during 1951-2005 in Chinese mainland[J]. Acta Meteorological Sinica, 2010, 68(5):680-688. [1] 孔君, 苏正军. 关于人工影响消减雾霾的思考[J]. 科技导报, 2015, 33(6): 86-90. [2] 马保东;吴立新;刘英;林亚卫. 基于MODIS的神东矿区土壤湿度变化监测[J]. , 2011, 29(35): 45-49. [3] 张红卫;;陈怀亮;申双和. 基于EOS/MODIS数据的土壤水分遥感[J]. , 2009, 27(0912): 85-92. [4] 金晓媚;余秋生;薛忠歧;于艳青. 宁夏回族自治区生态植被变化规律研究[J]. , 2007, 25(0710): 19-22. [5] 杨中华;王卫东;马浩录. “四星三源”模式监测黄河凌汛的研究与实践[J]. , 2006, 24(0604): 64-67.
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