Incorporating wind availability into land use regression modelling of air quality in mountainous high-density urban environment

Shi, Yuan ORCID: 0000-0003-4011-8735, Lau, Kevin Ka-Lun and Ng, Edward (2017) Incorporating wind availability into land use regression modelling of air quality in mountainous high-density urban environment. ENVIRONMENTAL RESEARCH, 157. pp. 17-29.

Text ER-2017-Incorporating Wind Availability into Land Use Regression Modelling.pdf - Author Accepted Manuscript Download (2MB) | Preview

Abstract

Urban air quality serves as an important function of the quality of urban life. Land use regression (LUR) modelling of air quality is essential for conducting health impacts assessment but more challenging in mountainous high-density urban scenario due to the complexities of the urban environment. In this study, a total of 21 LUR models are developed for seven kinds of air pollutants (gaseous air pollutants CO, NO₂, NO_x, O₃, SO₂ and particulate air pollutants PM_2.5, PM₁₀) with reference to three different time periods (summertime, wintertime and annual average of 5-year long-term hourly monitoring data from local air quality monitoring network) in Hong Kong. Under the mountainous high-density urban scenario, we improved the traditional LUR modelling method by incorporating wind availability information into LUR modelling based on surface geomorphometrical analysis. As a result, 269 independent variables were examined to develop the LUR models by using the "ADDRESS" independent variable selection method and stepwise multiple linear regression (MLR). Cross validation has been performed for each resultant model. The results show that wind-related variables are included in most of the resultant models as statistically significant independent variables. Compared with the traditional method, a maximum increase of 20% was achieved in the prediction performance of annual averaged NO₂ concentration level by incorporating wind-related variables into LUR model development.

Item Type:	Article
Uncontrolled Keywords:	Air pollution modelling, Land use regression, Mountainous high-density city, Wind availability, Urban surface geomorphometry
Divisions:	Faculty of Science and Engineering > School of Environmental Sciences
Depositing User:	Symplectic Admin
Date Deposited:	25 Jul 2022 14:57
Last Modified:	18 Jan 2023 20:55
DOI:	10.1016/j.envres.2017.05.007
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3159306