Literature DB >> 26766363

Source regional contributions to PM2.5 in a megacity in China using an advanced source regional apportionment method.

Ying-Ze Tian1, Gang Chen1, Hai-Ting Wang1, Yan-Qi Huang-Fu1, Guo-Liang Shi2, Bo Han3, Yin-Chang Feng1.   

Abstract

To quantify contributions of individual source categories from diverse regions to PM2.5, PM2.5 samples were collected in a megacity in China and analyzed through a newly developed source regional apportionment (SRA) method. Levels, compositions and seasonal variations of speciated PM2.5 dataset were investigated. Sources were determined by Multilinear Engine 2 (ME2) model, and results showed that the PM2.5 in Tianjin was mainly influenced by secondary sulphate & secondary organic carbon SOC (percent contribution of 26.2%), coal combustion (24.6%), crustal dust & cement dust (20.3%), secondary nitrate (14.9%) and traffic emissions (14.0%). The SRA method showed that northwest region R2 was the highest regional contributor to secondary sources, with percent contributions to PM2.5 being 9.7% for secondary sulphate & SOC and 6.0% for secondary nitrates; the highest coal combustion was from local region R1 (6.2%) and northwest R2 (8.0%); the maximum contributing region to crustal & cement dust was southeast region R4 (5.0%); and contributions of traffic emissions were relatively spatial homogeneous. The seasonal variation of regional source contributions was observed: in spring, the crustal and cement dust contributed a higher percentage and the R4 was an important contributor; the secondary process attributed an increase fraction in summer; the mixed coal combustion from southwest R5 enhanced in autumn.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  ME2; Particulate matter; Seasonal variations; Source regional apportionment

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Year:  2016        PMID: 26766363     DOI: 10.1016/j.chemosphere.2015.12.132

Source DB:  PubMed          Journal:  Chemosphere        ISSN: 0045-6535            Impact factor:   7.086


  2 in total

1.  Development and application of three-dimensional potential source contribution function (3D-PSCF).

Authors:  In Sun Kim; Daehyun Wee; Yong Pyo Kim; Ji Yi Lee
Journal:  Environ Sci Pollut Res Int       Date:  2016-05-06       Impact factor: 4.223

2.  Primary Carbonaceous Particle Emission from Four Power Plants with Ultralow Emission in China.

Authors:  Ruihe Lyu; Jinsheng Zhang; Jianhui Wu; Yinchang Feng
Journal:  ACS Omega       Date:  2021-01-07
  2 in total

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