Analysis and monitoring of PM2.5 particle pollution in Hong Kong

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Analysis and monitoring of PM2.5 particle pollution in Hong Kong


Author: Wang, Jingzhi
Title: Analysis and monitoring of PM2.5 particle pollution in Hong Kong
Degree: M.Sc.
Year: 2011
Subject: Hong Kong Polytechnic University -- Dissertations
Air -- Pollution -- Analysis -- China -- Hong Kong
Meteorology -- China -- Hong Kong
Department: Dept. of Land Surveying and Geo-Informatics
Pages: vi, 72 leaves : ill. (some col.), maps (some col.) ; 30 cm.
InnoPac Record:
Abstract: Ambient fine particulates (PM2.5; diameters<2.5μm) are receiving increasing attention for their potential toxicity and roles in visibility and health. The primary objective of this study is to interpret the PM2.5 behavior in terms of relevant meteorological variables and quantify the effect of meteorology on the magnitude of PM2.5 in urban Hong Kong during 2007-2008. Significant diurnal variations of PM2.5 concentrations are pronounced. Two morning and afternoon rush time peaks value were found higher during winter and on weekdays. The trend study exhibited a seasonal PM2.5 concentration pattern with higher concentrations in summer and lower in winter, which suggested anthropogenic factors and meteorological influences. Typical seasonal variation of PM2.5 concentrations was found with highest concentration in winter and lowest in summer, which is attributed to seasonal variability in wind direction, precipitation and temperature. Northerly winds bring pollutants from mainland are frequently observed with highest winter PM2.5 concentration, whereas in summer, southwest monsoons are highly related to the worst PM2.5 pollutions. Fortunately, the dominating eastern winds blowing from the sea are conducive to the lowest PM2.5 concentrations. Successive multiple regression analysis was performed to identity significant variables affecting the PM2.5 concentrations in all four seasons of 2007. Results revealed that temperature and pressure to be the most significant meteorological variable in spring and winter. The identified seasonal meteorological contributors, however, still cannot comprehensively interpret PM2.5 concentrations, with the highest adjusted determination coefficients (R²) being only 0.34 in autumn. This implies the significance of traffic-related local PM2.5 emissions.
To further understand the spatial pattern of PM2.5 concentrations in the context of the built up environment of urban Hong Kong, a geographic information systems (GIS) platform was developed to monitor the detailed spatial variations of PM2.5 based on high resolution remote sensing imagery. This study utilized MODIS AOT 500m image data to better monitor spatial distribution of PM2.5 particle pollution over urban areas. The aerosol vertical profile was firstly estimated and then the satellite-based aerosol optical thickness (AOT) information was divided and represented in 3D over urban Hong Kong. By converting AOT to PM2.5 particle pollution information, the PM2.5 concentration can be directly queried at different elevations for any particular floor on a Geographic Information platform based on ArcEngine. Results showed that the detailed information of PM 2.5 particle pollution in Hong Kong could be obtained from the high-resolution retrieval results and indicated that satellite remote sensing of aerosol could serve as an efficient tool for monitoring the spatial distribution of PM2.5 particle pollution over land, especially urban areas. In essence, this study has systematically analyzed the fine particulate air pollution problem, which incorporates both basic and advanced analysis to fully capture the PM2.5 problem in its entirety and can be applied to major urban areas in the world for a detailed understanding and quantification of the problem. Such a detailed study and analysis of fine particulate matter will provide crucial information to air quality regulators and decision makers to determine the efficacy of the imposed air quality standards and lead to the development of more specific preventive and control strategies.

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