A building-based data capture and data mining technique for air quality assessment

• Published in: Frontiers of environmental science & engineering Vol. 5; no. 4; pp. 543 - 551
• Main Authors: SHENG, Ni, TANG, U Wa
• Format: Journal Article
• Language: English
• Published: Heidelberg Higher Education Press 01-12-2011; Springer Nature B.V
• Subjects: Air pollution; Air quality; Air quality assessments; Data capture; Data mining; Environmental assessment; geographic information system; high resolution; Outdoor air quality; Quality assessment; Quality control; Spatial data; Spatial discrimination; spatial distribution; Spatial resolution; Spatial variations; Streets; traffic air pollution; Traffic flow; Traffic information; Urban areas; Urban planning; Vehicle emissions; Macao
• ISSN: 2095-2201; 2095-221X
• DOI: 10.1007/s11783-011-0369-4

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.