This project aims to use temporal and spatial data analysis to express the measured air pollutant concentrations as well as their relation with the aerosol traces, indicated by the intensity ratio (IR). The surveying were performed during a field campaign of several days of mobile optical remote sensing measurements in Tianjing city, China. The spectroscopic data were recorded by different spectrometers from which the most two mature techniques are the Differential Optical Absorption Spectroscopy (DOAS) and the Solar Occultation Flux (SOF). Besides, a third measuring approach of using a ‘Flame’ spectrometer was explored to discover the sulphur dioxide (SO2) traces. Except for the different spectrometers, other auxiliary data were taken from the wind meter and the GPS tracker. To construct an integral geographic information, data inspecting, cleaning, merging were heavily applied based on physical modeling.

本文旨在利用时间-空间域数据分析来探索所测量的大气污染物浓度以及它们与其诱发的气溶胶之间的关联情况。气溶胶痕迹以特定波长的光强度之比（IR）来表征。本文所用到的数据采自于针对天津市工业园区及天津港进行的车载移动光学遥感测量。所关注的大气污染物浓度通过国际上最成熟的差分吸收光谱（DOAS）技术和掩光通量（SOF）测量法计算得出，而光谱数据则通过第三种技术手段，即利用迷你型‘火焰’光谱仪，记录测量。研究表明该小型光谱仪可以发现并记录二氧化硫气体的踪迹。本文在物理建模的基础上大量应用到信号检测、滤波，数据清洗、合并。综合浓度数据，光谱数据以及辅助数据诸如取自测风仪的风速风向信息和取自GPS跟踪器的位置信息，成功构建出完整的区域地理信息。