高分五号大气痕量气体差分吸收光谱仪对流层NO2柱浓度遥感反演研究

搭载于“高分五号”（GF-5）卫星上的痕量气体差分吸收光谱仪（EMI）是一台星下观测的高光谱载荷,测量紫外和可见光光谱范围的地球后向散射辐射,设计用于大气痕量气体的探测。本研究基于EMI在VIS1通道的实测光谱,利用差分光学吸收光谱（DOAS）方法进行了对流层NO₂柱浓度反演,展示了基于EMI载荷的对流层NO₂柱浓度反演结果,与同类载荷产品进行交叉验证,并利用地基观测结果进行了地基验证。研究表明,EMI反演结果与OMI、TROPOMI具有较好的空间分布一致性和较低的相对偏差,与TROPOMI具有较好的时间变化一致性。地面验证结果表明EMI NO₂反演结果具有较高的精度。本研究证明了EMI在全球NO₂监测方面的能力,可以为中国后续污染气体探测载荷的设计和反演算法的开发提供参考。     

O2-O2云反演算法及其在TROPOMI上的应用

利用遥感技术对大气环境污染进行监测时，云是影响痕量气体反演精度的重要因素，因此在痕量气体反演中需要对云的影响进行校正，通常使用的云参数主要是有效云量和云压。本文基于O₂-O₂ 477 nm吸收波段构建了O₂-O₂云反演算法：首先，根据有效云量和云高与连续反射率和O₂-O₂斜柱浓度之间的对应关系，结合假定的云模型利用VLIDORT辐射传输模型建立关于有效云量和云压的查找表；然后，通过差分吸收光谱技术拟合卫星载荷观测的大气层顶辐射，获得O₂-O₂斜柱浓度并计算连续反射率；最后，结合辅助数据，根据查找表进行插值反演获得有效云量和云压。通过将算法应用到OMI观测数据，将反演结果与OMCLDO2产品进行对比验证，有效云量和云压空间分布一致，相关系数R均超过0.97；并还将该算法应用于下一代大气成分监测仪器TROPOMI，与FRESCO+产品对比，有效云量和云压空间分布基本一致，当地表类型为海洋时，有效云量相关系数R大于0.97，云压相关系数R大于0.94，云压反演结果存在一定的区别；通过将O₂-O₂云反演算法和FRESCO+云压反演结果与CALIOP Cloud Layer产品进行对比，结果表明，在低云情况下，O₂-O₂云反演算法线性回归方程斜率为0.782，截距为198.0 hPa，相关系数R为0.850，算法表现优于FRESCO+。而在高云情况下，FRESCO+反演结果更接近CALIOP云压结果。在OMI和TROPOMI上的应用表明O₂-O₂云反演算法在大气云反演中具有较高的准确性和可行性，可以为大气痕量气体反演的校正提供云参数，并为中国同类型卫星载荷的云反演算法提供算法参考。     

GF-5 AIUS切高校正算法研究与反演验证

利用红外掩星获取温压及其大气成分廓线,需要获得精确的指向信息,针对高分五号大气环境甚高分辨率探测仪（GF-5 AIUS）一级光谱信息,本文首先分析了不同切高的光谱变化情况,在此基础上,利用查找表方法进行切高校正。在低切高段（10—20 km）,选取N₂吸收波段,模拟6—40 km高度上的透过率光谱,通过查找表校正方法对一级数据中的低层切高进行校正。在高切高段（20—100 km）,模拟6—90 km切高上的透过率光谱,利用O₃吸收波段（20—90 km）进行校正。校正算法采取全局最小均方根误差的方法进行统计实验,确定最小校正半径为15 km。最后选取O₃、HCl、N₂O共3种大气成分的反演波段,进行校正后的透过率数据对比验证与反演产品精度的验证。结果表明：在O₃、HCl、N₂O共3种成分的反演通道上,校正后的观测透过率与模拟的透过率数据一致性较好,两者最大偏差小于0.1,切高校正算法得到的结果与模拟透过率吻合度较好;同时基于Aura MLS（Microwave Limb Sounder）、ACE-FTS（Atmospheric Chemistry Experiment Fourier-Transform Spectrometer）Level 2产品进行了O₃、HCl、N₂O单廓线交叉验证。结果表明：GF-5 AIUS反演的单廓线O₃与MLS、ACE-FTS相对偏差在30 km以下小于50%,在30—60 km小于20%;单廓线HCl与MLS、ACE-FTS相对偏差整体小于20%;单廓线N₂O与MLS、ACE-FTS相对偏差30 km以下小于20%,30—60 km相对偏差较大。     

高分五号大气痕量气体差分吸收光谱仪甲醛反演可行性分析及初步结果

大气痕量气体差分吸收光谱仪EMI（ Environmental trace gases Monitoring Instrument）是搭载在“高分五号”（GF-5）卫星上的覆盖紫外—可见光波段的光谱仪,用于测量240—710 nm波长范围内的地球后向散射和太阳辐射,旨在量化全球对流层和平流层痕量气体的分布,如臭氧、二氧化氮等。本文关注EMI载荷对大气弱痕量气体甲醛（HCHO）的探测能力,并基于实测数据初步评估EMI HCHO产品的探测能力与精度。研究结果表明EMI的辐照度波长校准精度高,但在不同行之间存在较大的不均匀性,其波长校正的精度与仪器的狭缝函数高度依赖行位置的变化。基于EMI的HCHO反演的结果表明,EMI UV2频段的标称信噪比较低,使得利用差分吸收光谱技术（DOAS）得到的HCHO斜柱浓度SCD（Slant Column Density）存在较大的随机误差和拟合残差。现阶段,评估得到的EMI HCHO斜柱浓度的不确定性为1.2×10¹⁶ molec./cm²。与国际同类载荷TROPOMI（TROPospheric Ozone Monitoring Instrument）、OMI（Ozone Monitoring Instrument）的交叉对比验证结果表明,EMI可以捕捉到中国地区夏季HCHO的空间分布特征。EMI & TROPOMI与EMI & OMI的相关系数均大于0.8。但是在华东地区EMI HCHO普遍高于OMI和TROPOMI,其原因需要进一步研究。本文的研究证明了EMI对夏季HCHO的探测潜力及不足,可为后续类似载荷的指标设计和算法研发提供参考。     

北京城市下垫面大气CO2反演算法

大气温室气体监测仪GMI（Greenhouse gases Monitor Instrument）是高分五号（GF-5）卫星载荷之一，主要用于全球温室气体含量监测和碳循环研究。高精度反演是卫星大气CO₂遥感的基本需求。地表反射率影响卫星遥感辐射量及辐射传输过程中的地气耦合过程，严重制约着CO₂的反演精度，针对GMI开发高精度的大气CO₂反演算法，地表反射是一个需要重点考虑的因素。城市是CO₂重要的发射源，且城市下垫面存在明显的二向反射特性，加上城市大气条件不良，复杂的地气耦合效应存在这都考验反演算法的准确性和鲁棒性。本文针对北京城市地区，利用2011年—2016年共5年的MODIS（MODerate-resolution Imaging Spectroradiometer）地表二向反射分布函数BRDF（Bidirectional Reflectance Distribution Function）数据，构建了适合利用单次观测数据反演的BRDF模型，并提出一种同时反演地表BRDF参数和大气CO₂含量的算法。结果表明在550 nm波长处气溶胶光学厚度AOD（Aerosol Optical Depth）小于0.4时，大部分GMI模拟数据的反演误差控制在0.5%（~2 ppm）内。利用GOSAT （Greenhouse gases Observing SATellite）实测数据的反演结果与修正后的日本国立环境研究所NIES（National Institute for Environmental Studies）反演结果进行对比，其平均误差为1.25 ppm，相关性达到0.85。本算法满足GMI数据在北京城市区域高精度CO₂反演的需求，并使得反演高值气溶胶区域数据成为可能，增加了GMI观测数据的利用率。     

海水背景下不同浓度的甲烷含量高光谱定量反演

在油气资源遥感探测中，通过烃渗漏引起的海表面甲烷气浓度异常来探测海底气藏是最直接的方法之一。为了更好地识别海表甲烷异常，提高遥感反演精度，对海表甲烷气含量进行定量光谱分析研究。设计室内甲烷波谱测试平台，获取海水背景下不同含量甲烷高光谱数据为数据，对光谱数据预处理及进行比值导数光谱法，并提取光谱吸收特征参数，对甲烷含量与光谱参数之间进行相关性分析，构建甲烷含量的反演模型。比值导数光谱法确实抑制了海水背景信息，突出了甲烷特征。1650—1664 nm和2180—2210 nm波段范围的光谱参数与甲烷含量相关性显著；其中，波谷、波深、面积、斜率与甲烷含量显著相关。基于2180—2210 nm波段范围建立的波谷、波深、面积、斜率四元回归方程y=-14.356 - 5931.796x₁ - 4325.081x₂+241.481x₃+7531.973x₄拟合效果最好，R²为0.9817；且在此波段范围内基于波深建立的单变量甲烷反演模型y = 2047.571x - 9.758，R²为0.9741，比基于其他变量所建立的反演模型效果要好。成功获取了和海水背景下甲烷含量线性相关显著的对应波段和吸收特征，可为利用多/高光谱遥感预测勘探海表面甲烷气浓度提供一定的理论和技术依据。     

珠江三角洲地区SO2浓度卫星遥感长时间序列监测

利用卫星OMI(Ozone Monitoring Instrument)数据获得的长时间序列SO₂浓度,分析广州亚运会从申办到成功举办期间珠江三角洲地区近地面SO₂浓度的变化过程,以及亚运会举办期间珠江三角洲SO₂浓度分布状况。结果表明OMI能够反映近地表的SO₂浓度变化趋势,广州亚运会从申办到成功举办期间珠江三角洲地区近地面SO₂浓度表现出明显的季节变化,且亚运会期间该地区近地面SO₂浓度比以往年同期要低,说明珠江三角洲地区联动的空气质量保障措施明显降低了该地区近地面的SO₂浓度。     

利用遥感数据评价燃煤电厂空气质量

卫星观测数据可以评价燃煤电厂的空气质量等级。NO₂、SO₂ 和烟尘是燃煤电厂排放的主要污染物,本文利用卫星遥感观测的NO₂、SO₂和气溶胶光学厚度AOD(Aerosol Optical Depth)开展燃煤电厂空气质量评价。以中国华北地区为实验区,分析对比了3种污染物不同时间分辨率和空间分辨率的污染状况,确定了单因子的5级分级标准,根据燃煤电厂排放污染物的权重不同,提出了评价近地表空气质量状况的模型。本文综合考虑3种污染因子来反映电厂空气质量,有利于提高评价的准确性以及反应信息的全面性。结果表明,该模型能正确反映不同地区电厂的空气质量特点。     

利用卫星红外高光谱资料反演大气甲烷浓度垂直廓线

基于欧洲中尺度天气预报中心(ECMWF)大气廓线库和RTTOV9.3辐射传输正向模式,探讨了大气CH₄混合比浓度垂直廓线和柱总量的经验正交函数(EOF)反演方法,并利用地基傅里叶热红外光谱仪(FTS)观测数据和红外EOSAQUA卫星的大气红外传感器(AIRS)实际观测资料进行反演实验和验证。并且与地基傅里叶热红外光谱仪(FTS)观测结果相比,300hPa以下EOF模型反演的CH₄混合比均方根相对误差小于AIRS的CH₄产品,CH₄柱总量的相对误差也小于AIRS产品。与AIRS的CH₄产品相比,EOF模型反演的CH₄混合比廓线相关系数为0.97,均方根相对误差小于2.5%。验证结果表明EOF模型可以为物理反演提供很好的初始值,由于其稳定且运算更快捷,在业务化运行方面具有很大应用前景。     

利用走航式数据对南大洋大气CO2廓线遥感反演

利用中国第24次南极考察期间获取的南大洋上空走航式大气CO₂数据和大气红外探测器(AIRS)探测的辐射率, 进行基于纬度分类下的统计回归, 其结果作为物理反演的初始猜测场。通过逐线积分辐射传输模式, 利用AMSU大气温度廓线和AIRS中13个通道的辐射测值反演南大洋上空的大气CO₂浓度廓线, 与WDCGG提供的固定站点下的大气CO₂浓度进行比较, 反演精度随纬度的变化而变化, 从低纬到高纬相对误差分别为0.31%、1.17%、2.63%。与同期国外卫星产品CO₂/AIRS比较, 相对误差为1.11%、1.07%。     

Application of geographical information system for mapping/monitoring seismological hazards in Pakistan

This study attempts to use the geographic information system (GIS) technique to map and understand the tectonics and crustal structures of Pakistan. Maps of surficial tectonic features and seismological parameters including Moho depth, P_n velocity and P_g velocity are complied. Based on the seismological data-set of the country the earthquake hazard map of Pakistan is also presented by applying regression technique on seismological, geological and topographical parameters. A case study of 8 October 2005 earthquake is used to validate the hazard map. It is envisaged that the developed GIS database would help policy-makers and scientists in natural hazard evaluation, seismic risk assessment and understanding of earthquake occurrences in Pakistan.     

Evaluating Hyperspectral Imager for the Coastal Ocean (HICO) data for seagrass mapping in Indian River Lagoon,FL

Differentiation between benthic habitats, particularly seagrass and macroalgae, using satellite data is complicated because of water column effects plus the presence of chlorophyll-a in both seagrass and algae that result in similar spectral patterns. Hyperspectral imager for the coastal ocean data over the Indian River Lagoon, Florida, USA, was used to develop two benthic classification models, Slope_RED and Slope_NIR. Their performance was compared with iterative self-organizing data analysis technique and spectral angle mapping classification methods. The slope models provided greater overall accuracies (63–64%) and were able to distinguish between seagrass and macroalgae substrates more accurately compared to the results obtained using the other classifications methods.     

CO2 concentration and its spatiotemporal variation in the troposphere using multi-sensor satellite data,carbon tracker,and aircraft observations

Satellite-based atmospheric CO₂ observations have provided a great opportunity to improve our understanding of the global carbon cycle. However, thermal infrared (TIR)-based satellite observations, which are useful for the investigation of vertical distribution and the transport of CO₂, have not yet been studied as much as the column amount products derived from shortwave infrared data. In this study, TIR-based satellite CO₂ products – from Atmospheric Infrared Sounder, Tropospheric Emission Spectrometer (TES), and Thermal And Near infrared Sensor for carbon Observation – and carbon tracker mole fraction data were compared with in situ Comprehensive Observation Network for Trace gases by AIrLiner (CONTRAIL) data for different locations. The TES CO₂ product showed the best agreement with CONTRAIL CO₂ data resulting in R² ~ 0.87 and root-mean-square error ~0.9. The vertical distribution of CO₂ derived by TES strongly depends on the geophysical characteristics of an area. Two different climate regions (i.e., southeastern Japan and southeastern Australia) were examined in terms of the vertical distribution and transport of CO₂. Results show that while vertical distribution of CO₂ around southeastern Japan was mainly controlled by horizontal and vertical winds, horizontal wind might be a major factor to control the CO₂ transport around southeastern Australia. In addition, the vertical transport of CO₂ also varies by region, which is mainly controlled by anthropogenic CO₂, and horizontal and omega winds. This study improves our understanding of vertical distribution and the transport of CO₂, both of which vary by region, using TIR-based satellite CO₂ observations and meteorological variables.     

短波红外CO2反演过程约束研究及初步反演结果

短波红外通道卫星CO2遥感是近年国际研究热点。首先,开展了卫星观测对气溶胶及大气温度的敏感性研究;其次,针对基于最优化理论的非线性迭代反演方法反演过程中的不收敛问题,提出了修正的阻尼牛顿方法(MDNM),并利用模拟数据评估了MDNM方法的有效性;最后,利用GOSAT卫星数据反演CO2的垂直混合比浓度,并与地基TCCON站点数进行比对。研究结果表明:短波近红外CO2卫星遥感受气溶胶散射及温度影响明显;通过地基比对初步验证了MDNM具有良好的精度,两者的相关性R2达到了0.729。     

Increased accuracy of geostatistical prediction of nitrogen dioxide in the United Kingdom with secondary data

Five techniques were used to map nitrogen dioxide (NO₂) concentrations in the United Kingdom. The methods used to predict from point data, collected as part of the UK NO₂ diffusion tube network, were local linear regression (LR), inverse distance weighting (IDW), ordinary kriging (OK), simple kriging with a locally varying mean (SKlm) and kriging with an external drift (KED). These techniques may be divided into two groups: (i) those that use only a single variable in the prediction process (IDW, OK) and (ii) those that make use of additional variables as a part of prediction (LR, SKlm and KED). Nitrous oxides emission data were used as secondary data with LR, SKlm and KED. It was concluded that SKlm provided the most accurate predictions based on the summary statistics of prediction errors from cross-validation.     

GOSAT卫星数据监测中国大陆上空CO2浓度时空变化特征

中国地区大气CO2浓度对全球气候变化有重要的影响。本文基于日本GOSAT卫星短波红外CO2的长期观测数据,对2010年-2016年中国大陆上空CO2浓度的分布特征和变化趋势进行分析研究。利用高精度的地基TCCON站点CO2观测对GOSAT CO2数据进行精度验证,结果表明,GOSAT CO2具有较高的精度,相对TCCON CO2的偏差为-1.04±2.10 ppm,两者的相关系数高达0.90;利用中国地区7年的GOSAT CO2观测数据分析研究显示,CO2浓度高值主要分布在中国的浙江-江苏-安徽地区、京津冀地区和湖南-湖北-河南-陕西地区;截至2016年,中国大部地区CO2浓度超过400 ppm;中国大陆CO2平均浓度呈现明显的逐年增长趋势,从2010年的387.76 ppm增长到2016年的402.18 ppm,年增长率约为2.31 ppm/a,略高于同期全球平均水平。     

Detecting anomalous CO2 flux using space borne spectroscopy

Over the time-scale, earth's atmospheric CO₂ concentration has varied and that is mostly determined by balance among the geochemical processes including burial of organic carbon in sediments, silicate rock weathering and volcanic activity. The best recorded atmospheric CO₂ variability is derived from Vostok ice core that records last four glacial/interglacial cycles. The present CO₂ concentration of earth's atmosphere has exceeded far that it was predicted from the ice core data. Other than rapid industrialization and urbanization since last century, geo-natural hazards such as volcanic activity, leakage from hydrocarbon reservoirs and spontaneous combustion of coal contribute a considerable amount of CO₂ to the atmosphere. Spontaneous combustion of coal is common occurrence in most coal producing countries and sometimes it could be in an enormous scale. Remote sensing has already proved to be a significant tool in coalfire identification and monitoring studies. However, coalfire related CO₂ quantification from remote sensing data has not endeavoured yet by scientific communities because of low spectral resolution of commercially available remote sensing data and relatively sparse CO₂ plume than other geological hazards like volcanic activity. The present research has attempted two methods to identify the CO₂ flux emitted from coalfires in a coalmining region in north China. Firstly, a band rationing method was used for column atmospheric retrieval of CO₂ and secondly atmospheric models were simulated in fast atmospheric signature code (FASCOD) to understand the local radiation transport and then the model was implemented with the inputs from hyperspectral remote sensing data. It was observed that retrieval of columnar abundance of CO₂ with the band rationing method is faster as less simulation required in FASCOD. Alternatively, the inversion model could retrieve CO₂ concentration from a (certain) source because it excludes the uncertainties in the higher altitude.