Literature DB >> 27017073

Simultaneous monitoring and compositions analysis of PM1 and PM2.5 in Shanghai: Implications for characterization of haze pollution and source apportionment.

Ting Qiao1, Mengfei Zhao2, Guangli Xiu3, Jianzhen Yu4.   

Abstract

A year-long simultaneous observation of PM1 and PM2.5 were conducted at ECUST campus in Shanghai, the compositions were analyzed and compared. Results showed that PM2.5 was dominated by PM1 on clear days while the contribution of PM1-2.5 to PM2.5 increased on haze days, indicating that PM2.5 should be given priority to characterize or predict haze pollution. On haze days, accumulation of organic carbon (OC), elemental carbon (EC) and primary organic carbon (POC) in PM1-2.5 was faster than that in PM1. Humic-like substances carbon (Hulis-C) in both PM2.5 and PM1 formed faster than water soluble organic carbon (WSOC) on haze days, hence Hulis-C/WSOC increased with the intensification of haze pollution. In terms of water soluble ions, NO3(-)/SO4(2-) in PM1 increased with the aggravation of haze pollution, implying that mobile sources dominated on haze days, so is nitrogen oxidation ratio (NOR). Liquid water content (LWC) in both PM1 and PM2.5 had positive correlations with relative humidity (RH) but negative correlations with visibility, implying that hygroscopic growth might be a factor for visibility impairment, especially LWC in PM1. By comparison with multi-linear equations of LWC in PM1 and PM2.5, NO3(-) exerted a higher influence on hygroscopicity of PM1 than PM2.5, while RH, WSOC, SO4(2-) and NH4(+) had higher effects on PM2.5, especially WSOC. Source apportionment of PM2.5 was also investigated to provide reference for policy making. Cluster analysis by HYSPLIT (HYbrid Single Particle Lagrangian Integrated Trajectory) model showed that PM2.5 originated from marine aerosols, middle-scale transportation and large-scale transportation. Furthermore, PM2.5 on haze days was dominated by middle-scale transportation. In line with source apportionment by positive matrix factorization (PMF) model, PM2.5 was attributed to secondary inorganics, aged sea salt, combustion emissions, hygroscopic growth and secondary organics. Secondary formation was the principle source of PM2.5. Furthermore, the contribution of combustion emissions to PM2.5 increased with the intensification of haze pollution, which was just opposite to hygroscopic growth, while that of secondary formation kept quite stable on clear days and haze days.
Copyright © 2016. Published by Elsevier B.V.

Entities:  

Keywords:  Haze pollution; Humic like substances (Hulis); Liquid water content (LWC); PM(1); PM(2.5); Source apportionment

Year:  2016        PMID: 27017073     DOI: 10.1016/j.scitotenv.2016.03.095

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  4 in total

Review 1.  A critical review of assays for hazardous components of air pollution.

Authors:  Henry Jay Forman; Caleb Ellicott Finch
Journal:  Free Radic Biol Med       Date:  2018-01-31       Impact factor: 7.376

2.  Differential transcriptional changes in human alveolar epithelial A549 cells exposed to airborne PM2.5 collected from Shanghai, China.

Authors:  Xiaoning Lei; Joshua E Muscat; Zhongsi Huang; Chao Chen; Guangli Xiu; Jiahui Chen
Journal:  Environ Sci Pollut Res Int       Date:  2018-10-01       Impact factor: 4.223

3.  Day-Ahead PM2.5 Concentration Forecasting Using WT-VMD Based Decomposition Method and Back Propagation Neural Network Improved by Differential Evolution.

Authors:  Deyun Wang; Yanling Liu; Hongyuan Luo; Chenqiang Yue; Sheng Cheng
Journal:  Int J Environ Res Public Health       Date:  2017-07-12       Impact factor: 3.390

4.  Characteristics of Chemical Speciation in PM1 in Six Representative Regions in China.

Authors:  Kaixu Bai; Can Wu; Jianjun Li; Ke Li; Jianping Guo; Gehui Wang
Journal:  Adv Atmos Sci       Date:  2021-04-07       Impact factor: 3.158

  4 in total

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