Literature DB >> 18546684

Source apportionment and spatial distributions of coarse particles during the Regional Air Pollution Study.

Injo Hwang1, Philip K Hopke, Joseph P Pinto.   

Abstract

To identify the coarse particle sources and to estimate the variability in their contributions to coarse particle mass (CPM) concentrations across the St. Louis metropolitan area, positive matrix factorization (PMF) was applied to historic ambient coarse particle compositional data from 10 Regional Air Pollution Study/Regional Air Monitoring System (RAPS/RAMS) monitoring sites in St. Louis. Coarse particles in this study had aerodynamic sizes between 2.4 and 20 microm. The sources were qualitatively identified, and the source contributions were quantitatively estimated. Nine sources were identified for 8 of the 10 sampling sites (except rural sites 122 and 124) including soil, cement kiln/quarry, iron and steel, motor vehicle, incinerator, pigment plant primary/secondary lead smelter, zinc smelter, and copper production, respectively. At site 122, five sources were identified as soil, cement kiln/quarry, motor vehicle, incinerator, and zinc smelter. At site 124, six sources were identified as soil, cement kiln/quarry, motor vehicle, incinerator, primary/secondary lead smelter, and zinc smelter. Soil was the largest coarse particle source across the study area (6.15 microg/m3, 29.3%). Cement kiln/quarry, iron and steel, and motorvehicle sources were the other large contributions to the coarse particles mass (5.27 microg/m3, 25.1%; 3.53 microg/m3, 16.8%; 2.72 microg/m3, 12.9%). The results of this study suggest there can be significant potential for exposure misclassification in time-series epidemiologic studies when regressing health outcomes against source contributions if they were to be estimated at a single central monitoring site.

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Year:  2008        PMID: 18546684     DOI: 10.1021/es0716204

Source DB:  PubMed          Journal:  Environ Sci Technol        ISSN: 0013-936X            Impact factor:   9.028


  7 in total

1.  Source Identification of Coarse Particles in the Desert Southwest, USA using Positive Matrix Factorization.

Authors:  Andrea L Clements; Matthew P Fraser; Nabin Upadhyay; Pierre Herckes; Michael Sundblom; Jeffrey Lantz; Paul A Solomon
Journal:  Atmos Pollut Res       Date:  2017-09       Impact factor: 4.352

2.  Trends on PM2.5 research, 1997-2016: a bibliometric study.

Authors:  Sheng Yang; Jing Sui; Tong Liu; Wenjuan Wu; Siyi Xu; Lihong Yin; Yuepu Pu; Xiaomei Zhang; Yan Zhang; Bo Shen; Geyu Liang
Journal:  Environ Sci Pollut Res Int       Date:  2018-04-05       Impact factor: 4.223

3.  Intra-urban spatial variability of PM2.5-bound carbonaceous components.

Authors:  Mingjie Xie; Teresa L Coons; Steven J Dutton; Jana B Milford; Shelly L Miller; Jennifer L Peel; Sverre Vedal; Michael P Hannigan
Journal:  Atmos Environ (1994)       Date:  2012-12       Impact factor: 4.798

4.  Constrained Source Apportionment of Coarse Particulate Matter and Selected Trace Elements in Three Cities from the Multi-Ethnic Study of Atherosclerosis.

Authors:  Timothy M Sturtz; Sara D Adar; Timothy Gould; Timothy V Larson
Journal:  Atmos Environ (1994)       Date:  2014-02       Impact factor: 4.798

5.  Intra-urban spatial variability and uncertainty assessment of PM2.5 sources based on carbonaceous species.

Authors:  Mingjie Xie; Teresa L Coons; Joshua G Hemann; Steven J Dutton; Jana B Milford; Jennifer L Peel; Shelly L Miller; Sun-Young Kim; Sverre Vedal; Lianne Sheppard; Michael P Hannigan
Journal:  Atmos Environ (1994)       Date:  2012-12-01       Impact factor: 4.798

6.  Assessment of regional air quality by a concentration-dependent Pollution Permeation Index.

Authors:  Chun-Sheng Liang; Huan Liu; Ke-Bin He; Yong-Liang Ma
Journal:  Sci Rep       Date:  2016-10-12       Impact factor: 4.379

7.  Dynamic Correlation Analysis Method of Air Pollutants in Spatio-Temporal Analysis.

Authors:  Yu-Ting Bai; Xue-Bo Jin; Xiao-Yi Wang; Xiao-Kai Wang; Ji-Ping Xu
Journal:  Int J Environ Res Public Health       Date:  2020-01-05       Impact factor: 3.390

  7 in total

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