Land use regression modelling of air pollution in high density high rise cities: A case study in Hong Kong.
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=106μg/m3, SD=38.5, N=95), b) NO (M=147μg/m3, SD=88.9, N=40), c) PM2.5(M=35μg/m3, SD=6.3, N=64), and BC (M=10.6μg/m3, SD=5.3, N=76). Final LUR models had the following statistics: a) NO2(R2=0.46, RMSE=28μg/m3) b) NO (R2=0.50, RMSE=62μg/m3), c) PM2.5(R2=0.59; RMSE=4μg/m3), and d) BC (R2=0.50, RMSE=4μg/m3). Traditional LUR predictors such as road length, car park density, and land use types were included in most models. The NO2prediction 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 PM2.5and 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.
University of British Columbia, School of Population and Public Health, 2206 East Mall, Vancouver, BC V6T 1Z3, Canada. Electronic address: martha.lee@alumni.ubc.ca.
Martha
M
Lee
University of British Columbia, School of Population and Public Health, 2206 East Mall, Vancouver, BC V6T 1Z3, Canada.
Michael
M
Brauer
The University of Hong Kong, Department of Geography, The Jockey Club Tower, Pokfulam Road, Hong Kong Special Administrative Region.
Paulina
P
Wong
The University of Hong Kong, School of Public Health, 7 Sassoon Road, Hong Kong Special Administrative Region.
Robert
R
Tang
The University of Hong Kong, School of Public Health, 7 Sassoon Road, Hong Kong Special Administrative Region.
Tsz Him
TH
Tsui
The University of Hong Kong, School of Public Health, 7 Sassoon Road, Hong Kong Special Administrative Region.
Crystal
C
Choi
The University of Hong Kong, Department of Geography, The Jockey Club Tower, Pokfulam Road, Hong Kong Special Administrative Region.
Wei
W
Cheng
The University of Hong Kong, Department of Geography, The Jockey Club Tower, Pokfulam Road, Hong Kong Special Administrative Region.
Poh-Chin
PC
Lai
The University of Hong Kong, School of Public Health, 7 Sassoon Road, Hong Kong Special Administrative Region.
Linwei
L
Tian
The University of Hong Kong, School of Public Health, 7 Sassoon Road, Hong Kong Special Administrative Region.
Thuan-Quoc
TQ
Thach
Simon Fraser University, Faculty of Health Sciences, 8888 University Drive, Burnaby, BC V5A 1S6, Canada.
Ryan
R
Allen
King's College London, Franklin-Wilkins Building, 150 Stamford Street, London, SE1 9NH, UK.
Benjamin
B
Barratt
D000393:Air Pollutants / Q000032:analysis; D000397:Air Pollution / Q000032:analysis*; D002947:Cities; D004784:Environmental Monitoring; D006723:Hong Kong; D008962:Models, Theoretical; D009569:Nitric Oxide / Q000032:analysis; D009585:Nitrogen Dioxide / Q000032:analysis; D052638:Particulate Matter; D012044:Regression Analysis; D053260:Soot / Q000032:analysis
D000393:Air Pollutants; D052638:Particulate Matter; D053260:Soot; D009569:Nitric Oxide; D009585:Nitrogen Dioxide
Air pollution; Exposure assessment; GIS; Land use regression