| Summary: | 碩士 === 國立臺灣大學 === 環境衛生研究所 === 100 === In many previous studies, the technique of inversing air dispersion model technology was presented to locate unknown emission sources locations. In this study, wWe collected the downwind concentration data using optical remote sensing (ORS)open-path fFourier transform infrared spectroscopy (OP-FTIR) instrument thatwhich can obtainprovide representative data faster than using many point samplers among ain large spatial areas. In our field experiments of releasing tracer gases, we set up three discrete OP-FTIR monitoring lines (lengths of lines were 123, 127, and 127m) at the downwind sites of the survey area near an industrial complex to locate two three artificially released emission sources. ForTo verifying the inversion algorithmtheory, we also conducted computer simulation studies. combine path integrated concentration data and meteological data as input data, and the uncertainty areas of unknown emission source are estimated. For Source A, the distance between the source and the monitoring lines was 355, 565, and 780m, respectively. On the other hand, that distance for Source B was 105, 315, and 530m. The experiment study was conducted with three discrete monitoring lines as the field experimental setup in the reconstruction process. The distance between the Ssource A (duration: 295minutes) and the monitoring lines was 105, 315, and 530m, respectively. The distance between the Ssource B (duration: 180minutes) and the monitoring lines was 355, 565, and 780m, respectively. The distance between the Ssource C (duration: 438minutes) and the monitoring lines was 400, 615, and 825m, respectively. An oOptimization algorithm was used to inverse the U.S. EPA ISCST3 and AERMOD models for to traceing back the source locations considering different scenarios including different wind directions, emission rates and source locations. Previous studies showed that the screening criteria with efficient downwind PICdata and wind direction could improve the reconstruction result. For verifying the theory, we demonstrated the results of uncertainy area with different screening criteria, but we found that screening criteria of CCF and wind direction were not very robustious . The results showed that the true source locations could not be identified exactly but they could be covered by the uncertainty areas.We could estimated the uncertainy area of possible source location with reconstruction procedure of ISCST3 and AERMOD model. The average distance between Source B and the predicted source location was 49.44m (AERMOD model) and 60.40m (ISCST3 model), and Source B was provided the best result after screening for CCF larger smaller than 0.75. The estimated emission rates were underestimated from real emission rate forby 22.6% (ISCST3 model) and 51.9% (AERMOD model). The other emission sources were gave obtained poorworse results because of limitations of the experimental setup. The average distance of errors for Source A ranged from 128.22-340.42m, and Source C was 156.93-295.38m. The poor results were because we could notdue to not offer thehaving suitable proper model parameters and meteorological data for model process. Future studies should obtain local data to improve the performance of the modeling and inversion techniques.
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