Title
Land use regression modelling of air pollution in high density high rise cities : a case study in Hong Kong
Document Type
Journal article
Source Publication
Science of The Total Environment
Publication Date
8-15-2017
Volume
592
First Page
306
Last Page
315
Publisher
Elsevier B.V.
Keywords
Land use regression, Air pollution, GIS, Exposure assessment
Abstract
Land use regression (LUR) is a common method of predicting spatial variability of air pollution to estimate exposure. Nitrogen dioxide (NO2), nitric oxide (NO), fine particulate matter (PM2.5), and black carbon (BC) concentrations were measured during two sampling campaigns (April–May and November–January) in Hong Kong (a prototypical high-density high-rise city). Along with 365 potential geospatial predictor variables, these concentrations were used to build two-dimensional land use regression (LUR) models for the territory. Summary statistics for combined measurements over both campaigns were: a) NO2(Mean = 106 μg/m3, SD = 38.5, N = 95), b) NO (M = 147 μg/m3, SD = 88.9, N = 40), c) PM2.5 (M = 35 μg/m3, SD = 6.3, N = 64), and BC (M = 10.6 μg/m3, SD = 5.3, N = 76). Final LUR models had the following statistics: a) NO2 (R2 = 0.46, RMSE = 28 μg/m3) b) NO (R2 = 0.50, RMSE = 62 μg/m3), c) PM2.5 (R2 = 0.59; RMSE = 4 μg/m3), and d) BC (R2 = 0.50, RMSE = 4 μg/m3). Traditional LUR predictors such as road length, car park density, and land use types were included in most models. The NO2 prediction surface values were highest in Kowloon and the northern region of Hong Kong Island (downtown Hong Kong). NO showed a similar pattern in the built-up region. Both PM2.5 and BC predictions exhibited a northwest-southeast gradient, with higher concentrations in the north (close to mainland China). For BC, the port was also an area of elevated predicted concentrations. The results matched with existing literature on spatial variation in concentrations of air pollutants and in relation to important emission sources in Hong Kong. The success of these models suggests LUR is appropriate in high-density, high-rise cities.
DOI
10.1016/j.scitotenv.2017.03.094
Print ISSN
00489697
E-ISSN
18791026
Funding Information
This study was supported by the Health Effects Institute, Boston, USA under Research Agreement 4941-RFA13-1. M. Lee was supported in part by funding from a Natural Sciences and Engineering Research Council of Canada CREATE-Atmospheric Aerosol Program fellowship at The University of British Columbia. {4941-RFA13-1}
Publisher Statement
Copyright © 2017 Elsevier B.V. Access to external full text or publisher's version may require subscription.
Additional Information
Corrigendum to this article was published in December 2017, Science of The Total Environment, 603/604, 832-833. doi: 10.1016/j.scitotenv.2017.04.225
Full-text Version
Publisher’s Version
Language
English
Recommended Citation
Lee, M., Brauer, M., Wong, P., Tang, R., Tsui, T. H., Choi, C., ... Barratt, B. (2017). Land use regression modelling of air pollution in high density high rise cities: A case study in Hong Kong. Science of The Total Environment, 592, 306-315. doi: 10.1016/j.scitotenv.2017.03.094
