Using a new WALSPMF model to quantify the source contributions to PM2.5 at a harbour site in China. (February 2016)

• Record Type: Journal Article
• Authors: Shi, Guo-Liang; Xu, Jiao; Peng, Xing; Tian, Ying-Ze; Wang, Wei; Han, Bo; Zhang, Yu-Fen; Feng, Yin-Chang; Russell, Armistead G.
• Is Part Of: Atmospheric environment. Volume 126(2016)
• Page Start: 66
• Page End: 75
• Publication Date: 2016-02
• Subjects: Source apportionment -- WALSPMF -- Particulate matter -- Receptor model; Air -- Pollution -- Periodicals; Air -- Pollution -- Meteorological aspects -- Periodicals; 551.51
• DOI: 10.1016/j.atmosenv.2015.11.046
• Languages: English
• ISSNs: 1352-2310

Abstract

Abstract: PM2.5 variances have adverse impacts on human beings and the environment; therefore, source apportionment is very important and is a hot global topic. In this work, a new model called WALSPMF is proposed and evaluated for its accuracy. First, a synthetic test was carried out to compare the estimated source profile and contributions with the synthetic ones. Average absolute error (AAE) values were also calculated between the estimated and synthetic source contributions; most of the values were low (<15%), which indicated that the results of the WALSPMF model might be acceptable. Next, samples of PM2.5 were collected from a large harbour sampling site in China (Tanggu). The PM2.5 mean level was 110.63 μg m −3, with a range of 28.67 μg m −3 –302.17 μg m −3 . The ambient PM2.5 dataset was separately introduced into both the WALSPMF and EPAPMF 5.0 models to identify the possible sources and their contributions. Five source categories were extracted by the two models and can be identified in the following consistent order: coal combustion (33% for WALSPMF, 30% for EPAPMF 5.0), secondary nitrate (19% for WALSPMF, 21% for EPAPMF 5.0), crustal dust (18% for WALSPMF, 22% for EPAPMF 5.0), secondary sulphate (16% for WALSPMF, 15% for EPAPMF 5.0), and vehicle exhaust (14% for WALSPMF, 12% for EPAPMF 5.0). The positive results of multiple verifications suggested good performance of the WALSPMF model; thus, it is essential to put this new model forward as a way to potentially enrich the modern source apportionment technique. Highlights: WALSPMF model was proposed in this work. Synthetic receptor dataset was apportioned by the new model. PM2.5 samples were collected in a large harbour in China. WALSPMF and EPAPMF model were used to apportion PM2.5 sources.