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

doi:10.1007/s11783-011-0369-4

Front Envir Sci Eng Chin

2011, Vol. 5

Issue (4) : 543-551 https://doi.org/10.1007/s11783-011-0369-4

RESEARCH ARTICLE

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

Ni SHENG¹, U Wa TANG^2,3(

)

1. Faculty of Management and Administration, Macau University of Science and Technology, Macau, China; 2. Department of Civil and Environmental Engineering, University of Macau, Macau, China; 3. Dirccao dos Servicos de Proteccao Ambiental, 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.

Keywords traffic air pollution spatial distribution high resolution geographic information system

Corresponding Author(s): TANG U Wa,Email:nsheng.1@gmail.com, uwtang@gmail.com

Issue Date: 05 December 2011

Cite this article:

Ni SHENG,U Wa TANG. A building-based data capture and data mining technique for air quality assessment[J]. Front Envir Sci Eng Chin, 2011, 5(4): 543-551.

URL:

https://academic.hep.com.cn/fese/EN/10.1007/s11783-011-0369-4
https://academic.hep.com.cn/fese/EN/Y2011/V5/I4/543

Fig.1 Structure of air quality model system

Fig.2 Wind sectors generated from the urban landscape model

Fig.3 (a) 3D view of street configuration around a receptor point in Rua da Ribeira do Patane; (b) building heights around the receptor point; (c) extracted building heights (m) and building locations (wind sectors in degrees) stored in an ASCII input file

Fig.4 (a) Distribution of NO emission by 300 m × 300 m grids []; (b) modeled NO concentrations based on 300 m × 300 m grids []; (c) modeled NO concentrations by the building-based approach; (d) 3D view of modeled NO concentrations by the building-based approach (columns represent NO concentrations: blue < 31 ppb, red 31-62 ppb, and black > 62 ppb)

Fig.5 Spatial relationships of urban form, traffic flow, and air pollution in the historic area: (a) historic area in the Macau Peninsula; (b) road network in the historic area; (c) traffic flow in the historic area; (d) air pollution (NO) in the historic area

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