A review of atmospheric fine particulate matters: chemical composition, source identification and their variations in Beijing
Yinjie Ma, Yuhan Huang, Jianghua Wu, E Jiaqiang, Bin Zhang, Dandan Han, Hwai Chyuan Ong
Abstract
Fine particulate matter (PM2.5) is a major air pollutant worldwide. Characterizing its chemical compositions and source contributions is a critical prerequisite for effective control of PM2.5 pollution. This paper systematically reviews the sampling methods, chemical compositions, and source apportionments of PM2.5. Sampling methods have significant influences on the identification of chemical compositions and source contributions, with Quartz and Teflon filters being the most widely used. Receptor models are commonly adopted for identifying the sources of PM2.5, such as positive matrix factorization, chemical mass balance, principal component analysis, and UNMIX models, which have their respective advantages and limitations that determine their applications. The variations of PM2.5 compositions and sources in the past two decades in Beijing are also reviewed, which is the political, economic, and cultural center of China and is experiencing severe haze pollution events frequently. It was found that organic matters were the largest component (28.2%) in PM2.5, followed by sulfate (15.1%) during 2004–2013, which was overtaken by nitrate (14.9%) after 2013. Each PM2.5 source demonstrated significant seasonal and annual variations due to changes in climatic conditions and anthropogenic activities. Future research on the impacts of these external factors is urgently needed. This review is expected to provide valuable advice and evidence for those fast-growing megacities like Beijing to identify and control their PM2.5-related air pollution problems.