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- In relation to this article, we declare that there is no conflict of interest.
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Received September 20, 2008
Accepted May 12, 2009
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This is an Open-Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0) which permits
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Speed-up of the disaggregation of emission inventories and increased resolution of disaggregated maps using landuse data
Jong Ho Kim
Byoung Kyu Kwak
Chee Burm Shin1
Hyeon-Soo Park2
Kyunghee Choi3
Sang Mok Lee3
Jongheop Yi†
School of Chemical and Biological Engineering, Seoul National University, San 56-1, Sillim-9-dong, Gwanak-gu, Seoul 151-742, Korea 1Department of Chemical Engineering, Ajou University, Wonchen-dong, Yeongtong-gu,Suwon, Gyeonggi-do 433-749, Korea 2TO21, Lotte Tower 402-Ho, Sindaebang 2-dong, Dongjak-gu, Seoul 156-711, Korea 3National Institute of Environmental Research, Environment Research Complex, Gyeongseo-dong, Seo-gu, Incheon 404-170, Korea
Korean Journal of Chemical Engineering, November 2009, 26(6), 1620-1629(10), 10.1007/s11814-009-0280-x
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Abstract
This study describes the full disaggregation process of emission inventory maps in support of environmental modeling studies in a geographical information system. Using a heuristic approach, appropriate algorithms were found to accelerate the computational disaggregation speed. The algorithms were based on scan-conversion algorithms employed in the field of computer graphics. Various algorithms were analyzed in terms of supporting emission inventories with different shapes, such as points, polylines and polygons. The algorithms were implemented by using Visual Basic, thereby enabling the efficiencies of the algorithms to be analyzed and compared with each other. For the disaggregation of polygon types, with the aim of increasing the resolution of an inventory map, we suggest the advanced polygon-disaggregation method with land use data. An air dispersion simulation was performed in order to compare_x000D_
the accuracy of the emission input data generated by existing disaggregation methods and the advanced method proposed in the present study.
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