Literature DB >> 27376917

Chemical profiles of urban fugitive dust PM2.5 samples in Northern Chinese cities.

Zhenxing Shen1, Jian Sun2, Junji Cao3, Leiming Zhang4, Qian Zhang2, Yali Lei2, Jinjin Gao2, Ru-Jin Huang5, Suixin Liu3, Yu Huang3, Chongshu Zhu3, Hongmei Xu2, Chunli Zheng2, Pingping Liu2, Zhiguo Xue6.   

Abstract

Urban fugitive dust PM2.5 samples were collected in 11 selected cities in North China, and 9 ions (SO4(2-), NO3(-), Cl(-), F(-), Na(+), NH4(+), K(+), Mg(2+), and Ca(2+)) and 22 elements (Si, Al, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Br, Rb, Sr, Sn, Sb, Ba, and Pb) were determined to investigate chemical profiles of PM2.5. The coefficient of divergence (CD) was used to compare the similarities of the chemical profiles for fugitive dust among three regions in North China, and the results showed that their composition are quite similar. Total water soluble ions occupied 9.3% and 10.0% on average of road dust and construction dust, respectively, indicating that most of the materials in urban fugitive dust samples were insoluble. Ca(2+) was the most abundant cation and SO4(2-) dominated in anions. Soil dust loading was calculated to occupy 70.8% and 83.6% in road dust and construction dust, respectively. Ca, Si, Fe, and Al were the most abundant elements in all the samples, and Ca was absolutely the most abundant specie among the 22 detected elements in construction dust samples. Chemical species ratios were used to highlight the characteristics of urban fugitive dust by comparing with other types of aerosols. High Ca/Al ratio was a good marker to distinguish urban fugitive dust from Asian dust and Chinese loess. In addition, low K(+)/K and NO3(-)/SO4(2-), and high Zn/Al and Pb/Al ratios were good indicators to separate urban fugitive dust from desert dust, Chinese loess, or urban PM2.5 samples.
Copyright © 2016 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Ca/Al ratio; Chemical profiles; Urban fugitive dust

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Year:  2016        PMID: 27376917     DOI: 10.1016/j.scitotenv.2016.06.156

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


  6 in total

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2.  Chemical characterization and sources of PM2.5 at 12-hr resolution in Guiyang, China.

Authors:  Longchao Liang; Na Liu; Matthew S Landis; Xiaohang Xu; Xinbin Feng; Zhuo Chen; Lihai Shang; Guangle Qiu
Journal:  Acta Geochimica       Date:  2018

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Journal:  Environ Pollut       Date:  2020-05-13       Impact factor: 9.988

4.  Impacts of particulate matter (PM2.5) on the behavior of freshwater snail Parafossarulus striatulus.

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Journal:  Sci Rep       Date:  2017-04-05       Impact factor: 4.379

5.  Spatio⁻Temporal Relationship and Evolvement of Socioeconomic Factors and PM2.5 in China During 1998⁻2016.

Authors:  Yi Yang; Jie Li; Guobin Zhu; Qiangqiang Yuan
Journal:  Int J Environ Res Public Health       Date:  2019-03-30       Impact factor: 3.390

6.  Impacts of COVID-19 on Black Carbon in Two Representative Regions in China: Insights Based on Online Measurement in Beijing and Tibet.

Authors:  Yue Liu; Yinan Wang; Yang Cao; Xi Yang; Tianle Zhang; Mengxiao Luan; Daren Lyu; Anthony D A Hansen; Baoxian Liu; Mei Zheng
Journal:  Geophys Res Lett       Date:  2021-06-03       Impact factor: 4.720

  6 in total

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