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基于遥感与地面监测数据的城市气溶胶定量反演研究 【作者】王耀庭 【导师】王桥; 闾…

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【中文摘要】 气溶胶是影响地表能量收支平衡的决定性因素之一,它以直接辐射强迫和间接辐射强迫两种方式影响着气候系统,同时在局地、区域乃至全球大气环境质量中也扮演着一个重要角色。本文在气溶胶卫星遥感国内外研究现状及归纳总结出所要解决的主要问题的基础上,对大气气溶胶的遥感机理进行了系统性的分析;利用地基CE318气溶胶观测数据和地面大气污染监测数据,对气溶胶在大气环境领域中的适用性进行了研究分析;根据地基激光雷达数据和气象数据确定出大气污染边界层;并基于Landsat/7 TM遥感数据和同步的地面大气环境质量监测数据,以经过完善后的DTA法和统计回归为主要研究方法,探讨了北京示范区的气溶胶和主要大气污染物(PM10、SO2)的空间分布。 本文用地面太阳光度计观测数据和大气环境监测数据相结合的方法,应用统计回归方式计算,肯定了气溶胶光学厚度可以在大气环境领域中应用,能够指示大气污染。利用这些数据统计分析了北京地区的气溶胶光学厚度和大气污染之间的对应关系和季节变化特点,并对季节变化特征予以详细的分析。发现用AOT表征大气污染时,表征方法和精度对于不同的污染物,在不同的季节有所差异。用气溶胶光学厚度来描述大气...更多污染指标时,PM10的描述关系最为简单,受季节影响不大,相关性都保持在0.7附近,属于高度正相关。对NO2的描述,受季节影响明显,冬季具有极高相关性,春季和秋季具有高的相关性,夏季具有一般相关性。对SO2的描述最为复杂,受季节影响最为明显,除了冬季与气溶胶光学厚度有高度相关关系外,其余季节相关性都不高。 本文利用AML-1车载测污激光雷达资料和气象廓线探空数据,建立了二者之间的对应关系,确定了北京冬季大气污染边界层的厚度。这为后面是否可以将卫星遥感反演的AOT和PM10等污染物关联起来,构建二者之间的统计经验模型的思路奠定了基础。因为气溶胶主要集中在近地层的结论有时候是不成立的,论文给出了一个污染个例,来对这种情况作了进一步的论述。 本文以北京为示范区,利用Landsat/7 TM卫星数据,定量反演了气溶胶光学厚度的空间分布。提出了最佳距离指数的确定方式,完善和发展了DTA方法。补充了对“洁净日”影像进行云检测和大气校正的过程,减小了方法适用的局限性限制,增加了参考影像的“洁净”程度,减少了大气对“参考日”影像的影响,使地表反射率更接近“真实”地表反射率,最终增加了反演精度。通过对北京地区的AOT反演结果与NASA的10Km空间分辨率的MOD04 Level2的气溶胶光学厚度产品进行了比较,发现反演结果有很好的精度,二者之间的相关性达到了  还原

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:kY q,h P,Y"u0【英文摘要】 Aerosol is one of the most important factors which affect the balance of the outing and incoming solar energy of ground surface, and affect the climate system through their direct and indirect forcing mechanism on solar and long-wave radiation. They also have a crucial role in local, regional and global air pollution problems. There are five main studies were made based on the research of progress and problems of aerosol satellite remote sensing. The firstly, the theory of aerosol remote sensing was reviewed comprehensively, the secondly, applicability that AOT was used in field of air environment was affirmed based on the relation between AOT retrieved from CE318 and air pollution data ground-based, the thirdly, the height of pollution boundary layer was established based on the lidar data and meteorological sounding data in winter for Beijing, the fouth, the method of DTA was discussed and improved, in the end, a case study in Beijing, the procedure of modeling of the spatial distrib...更多ution of aerosol and main air pollutant was studied with Landsat7/TM remote sensing data and isochronous ground measured air pollution data by using improved DTA and statistical regress methods.Based on calculations from statistical regress, a method combining sun-photometer observations and air pollution data is used to confirm aerosol loading can be used to indicate the degree of air pollution. The seasonal characteristics and variations of AOT and air pollution are analyzed using these data. In particular, the detailed seasonal changes and relation between AOT and air pollution were described. The results show there is discrepancy in mode and precision when AOT used to indicate air pollution for different pollutant in different season. In general, relation between PM10 and AOT is the simplest, and give good correlations, come to 0.7, and the good correlations was not affected by season. For NO2, the correlation was affected obviously by season, the best correlations appeared in winter, and the better correlation appwared in spring and in autumn, there is a common correlation in summer. The relation between AOT and SO2 is complex, with the exception of winter, there is no good correlation between them in any season.A simple relation is created linking data from mobile lidar AML-1 and meteorological sound data. The air pollution boundary layer(PBL) height data are obtained for Beijing in winter based on these data, which is important to link AOT and pollutant by statistical experiential model, for the assumption that aerosol was  还原水利论文9e WX3k`

F9u9q4ZF/f0【中文关键词】 Landsat/7 TM; 气溶胶光学厚度; 污染边界层; 遥感; 空气污染水利论文q!Hf LI[-n.e)w c
【英文关键词】 Landsat/7 TM; Aerosol Optical Thickness; Pollution Boundary Layer; Remote Sensing; Air pollution水利论文B/hTc&hwb _#`D



TAG: 导师 定量 气溶胶 遥感 王耀庭
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