Temporal variations and potential sources of organophosphate esters in PM2.5 in Xinxiang, North China. (January 2019)

• Record Type: Journal Article
• Authors: Yang, Kong; Li, Qilu; Yuan, Meng; Guo, Mengran; Wang, Yanqiang; Li, Shuyang; Tian, Chongguo; Tang, Jianhui; Sun, Jianhui; Li, Jun; Zhang, Gan
• Is Part Of: Chemosphere. Volume 215(2019)
• Page Start: 500
• Page End: 506
• Publication Date: 2019-01
• Subjects: Organophosphate esters -- PM2.5 -- Temporal variations -- Potential source area -- PSCF; Pollution -- Periodicals; Pollution -- Physiological effect -- Periodicals; Environmental sciences -- Periodicals; Atmospheric chemistry -- Periodicals; 551.511
• DOI: 10.1016/j.chemosphere.2018.10.063
• Languages: English
• ISSNs: 0045-6535

Abstract

Abstract: We monitored the concentrations of 10 organophosphate esters (OPEs) in 52 fine particulate matter (PM2.5 ) samples in Xinxiang, Henan Province, North China, in 2015. During the sampling period, the OPE concentrations in most samples (n = 47) differed minimally and were relatively stable (mean: 2.02 ± 0.93 ng m −3 ), although several samples (n = 5) had high total OPE (Ʃ10 OPE) concentrations (mean: 9.99 ± 5.69 ng m −3 ), which may have been influenced by high PM2.5 levels. Meanwhile, some samples had high PM2.5 concentrations but low Ʃ10 OPE concentrations (i.e. low OPE/PM2.5 ratios) or low PM2.5 concentrations but high Ʃ10 OPE concentrations, which might have been influenced by air mass sources. Therefore, we assessed air mass sources using the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and wind direction frequency data, and subsequently analysed PM2.5 and OPE sources using a potential source contribution function (PSCF) model. The results revealed that air mass sources couldn't represent the source of specific pollutants, including PM2.5 and OPEs. Generally, both PM2.5 and OPEs were from Henan and Shandong Provinces; however, the major source areas differed, which may have resulted from diverse pollution characteristics in various source areas. The principal component analysis and PSCF results revealed that the 10 OPEs could be segmented into three groups, which were associated with different source areas. These results suggested that pollution characteristics of contaminants in source areas should be considered in source apportionment. Graphical abstract: Highlights: OPE concentrations in most samples showed slight differences at a stable level. Large differences of OPEs/PM2.5 ratios in few samples may result from air mass source. The major source areas of OPEs and PM2.5 were discrepant according to PSCF results. The major source areas of ten OPEs were diverse following PCA and PSCF results.