A building-based data capture and data mining technique for air quality assessment |
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Authors: | Ni Sheng and U Wa Tang |
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Institution: | (1) Joint Key Laboratory of Coastal Study, Xiamen University, Xiamen, 361005, China;(2) Environmental Science Research Center, Xiamen University, Xiamen, 361005, China;(3) Department of Environmental Science and Engineering, Tsinghua University, Beijing, 100084, China;(4) The Official Provisional Municipal Council of Macau, Macau, China |
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Abstract: | Recently, a building-based air quality model system which can predict air quality in front of individual buildings along both
sides of a road has been developed. Using the Macau Peninsula as a case study, this paper shows the advantages of building-based
model system in data capture and data mining. Compared with the traditional grid-based model systems with input/output spatial
resolutions of 1–2 km, the building-based approach can extract the street configuration and traffic data building by building
and therefore, can capture the complex spatial variation of traffic emission, urban geometry, and air pollution. The non-homogeneous
distribution of air pollution in the Macau Peninsula was modeled in a high-spatial resolution of 319 receptors·km−2. The spatial relationship among air quality, traffic flow, and urban geometry in the historic urban area is investigated.
The study shows that the building-based approach may open an innovative methodology in data mining of urban spatial data for
environmental assessment. The results are particularly useful to urban planners when they need to consider the influences
of urban form on street environment. |
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