EGU2020-12648
https://doi.org/10.5194/egusphere-egu2020-12648
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Land use regression modelling of ambient air pollutants in Hong Kong

Zhiyuan Li1, Steve Hung Lam Yim1,2,3, and Kin-Fai Ho1,3,4
Zhiyuan Li et al.
  • 1Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China
  • 2Department of Geography and Resource Management, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China
  • 3Stanley Ho Big Data Decision Analytics Research Centre, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China
  • 4The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong, China

Land use regression (LUR) models estimate air pollutant concentrations for areas without air quality measurements, which provides valuable information for exposure assessment and epidemiological studies. In the present study, we developed LUR models for ambient air pollutants in Hong Kong, China, a typical high-density and high-rise city. Air quality measurements at sixteen air quality monitoring stations, operated by the Hong Kong Environmental Protection Department, were collected. Moreover, five categories of predictor variables, including population distribution, traffic emissions, land use variables, urban/building morphology, and meteorological parameters, were employed to establish the LUR models of various air pollutants. Then the spatial distribution of air pollutant concentrations at 1 km × 1 km grid cells were plotted. Taking fine particle (PM2.5) as an example, the developed LUR model explained 89% of variability of PM2.5 concentrations, with a leave-one-out-cross-validation R2 of 0.64. LUR modelling results for other air pollutants will be presented. In addition, further improvements on the development of LUR models will be discussed. This study can help to assess long-term exposures to air pollutants for high-density and high-rise urban areas like Hong Kong.

How to cite: Li, Z., Yim, S. H. L., and Ho, K.-F.: Land use regression modelling of ambient air pollutants in Hong Kong , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12648, https://doi.org/10.5194/egusphere-egu2020-12648, 2020

Displays

Display file