Developing urban planning optimization strategies for improving air quality in compact cities using geo-spatial modelling based on in-situ data  (14610717) (1 Jan 18 - 31 Dec 20)
• Researchers: NG Yan Yung, LAU, Alexis Kai Hon
• Funding Amount: HK$1,066,320
• Funding source: Research Grants Council - General Research Fund

Air pollution is a major problem in high-density cities in Asia (Schwela, Haq et al. 2012). There are two ways to solve the problem: control pollution emission or enhance pollution dispersion. A well-planned urban form helps with the dispersion of pollutants (Robins and Macdonald 1999). Therefore, optimizing urban planning schemes at early stages is an effective way to enhance pollution dispersion. Using PM2.5, a commonly-used proxy to investigate pollution dispersion (Chan and Kwok 2000), this study focuses on optimizing urban planning for better pollution dispersion in compact urban environment. Recent studies have proved that the densely built urban form of Hong Kong is not optimized for pollution dispersion (Yuan, Ng et al. 2014, Shi, Lau et al. 2016). Most current methods on pollution dispersion in urban environments are based on complex numerical simulations (Kakosimos, Hertel et al. 2010, ANSYS 2014, CERC 2016). However, they are too complicated and time-consuming to help planners optimize the planning scheme at early stages efficiently. Planners need straightforward information of reasonable accuracy and quick methods during the initial strategic planning stage of urban renewal and new development areas (NDAs) plan.

To address the gap, this study aims to develop scientifically correct and straightforward optimization strategies for planners in Hong Kong. This will allow considerations of pollution dispersion to be incorporated in early-stage planning practices. The objectives of this study are: (A) to study and select suitable and representative sites based on the morphological understanding of Hong Kong’s urban context; (B) to conduct PM2.5 field measurements in sites selected in Task A under designated weather conditions for sampling in-situ data; (C) to collate in-situ data sets and with the collated data to develop spatial-temporal PM2.5 multistage geostatistical models and mappings; (D) based on the findings of Task C, to draw up urban planning optimization strategies for planners and decision-makers. The study output will directly inform the existing Air Ventilation Assessment (AVA) system and Hong Kong Planning Standards and Guidelines (HKPSG) chapter 11 by providing another consideration of pollution dispersion for planning decision-making. This study will also substantially enrich the government effort of “A Clean Air Plan for Hong Kong” by providing practical action plans for policy-makers. Moreover, the study method will be readily applicable beyond Hong Kong to other heavily polluted high-density cities in Asia.