Characterization of PM10 and PM2.5 source profiles for resuspended road dust collected using mobile sampling methodology

Han, Se-Hyun; Youn, Jong-Chan; Jung, Yongwon

doi:10.1016/j.atmosenv.2011.04.015

Cited by 53 publications

(19 citation statements)

References 20 publications

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“…These profiles are derived from scientific papers including fugitive dust from Chinese Loess Plateau (Cao et al, 2008), Asian dust source areas (Zhang et al, 2014b), north plain , southwest basin (Liu et al, 2016b) and other Chinese regions (Ho et al, 2003;Zhao et al, 2006;Han et al, 2009;Kong et al, 2011;Han et al, 2011;Chen et al, 2012;Han et al, 2014;Kong et al, 2014;Cheng et al, 2015), coal-fired boilers (Zhang et al, 2008;Wang et al, 2009;Pei et al, 2016), industrial sources (Zheng et al, 2013); biomass burning (Zhang et al, 2007;Zhang et al, 2012;Tao et al, 2015) and vehicle exhaust . Source profiles are also collected from source apportionment studies in Chinese cities such as Beijing, Tianjin, Chongqing and so on.…”

Section: Structure Of the Databasementioning

confidence: 99%

China Source Profile Shared Service (CSPSS): The Chinese PM2.5 Database for Source Profiles

Liu

Zhang

et al. 2017

Aerosol Air Qual. Res.

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China Source Profile Shared Service (CSPSS, www.speciate.org.cn), a new database of emission source profiles for particulate matter (PM), has been developed by researchers from Chinese Research Academy of Environmental Sciences (CRAES). The first release of CSPSS 1.0 consists of comprehensive data from China that reveals the emission profiles of different sources in selected regions. Related source categories include coal-fired boiler, industrial process, fugitive dust, vehicle exhaust emissions, biomass burning and cooking. Compositing methodology and data quality control were applied to create high quality composite profiles of each source category. Statistical measures of correlation coefficient, t-test and and distribution of weighted differences can be used to compare the similarities and differences among individual and composite profiles. In addition, differences between data of SPECIATE and CSPSS were compared. The chemical composition shows special characteristics in different source categories. For example, SO 4 2-and OC mark coal-fired bolier; Ca and Ca 2+ are the most abundant elements in cement production and construction dust emissions; Cl -, K + and K mark biomass burning; several metals such as V, Zn Sn and Pb could be used as tracers for paved road dust while Sr, Ba and Pb marked industrial emissions. The highest abundances of organic matter are observed in cooking emissions. Toxic species such as Cr and As are enriched in PM 2.5 from coal combustion. Distinguished features of source profiles between SPECIATE and CSPSS indicate that the knowledge of local source profiles are needed for further research. This database should better reflect the emission profiles observed in Chinese environment. Sensitivity tests have been conducted to examine the impact of sub-composite source profiles usually used to establish the composite ones. The result shows that the use of sub-composite source profiles of coal combustion dose not impact the apportionment results for biomass burning, but other sources are varying influenced.

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Section: Structure Of the Databasementioning

confidence: 99%

China Source Profile Shared Service (CSPSS): The Chinese PM2.5 Database for Source Profiles

Liu

Zhang

et al. 2017

Aerosol Air Qual. Res.

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“…For example, many studies have pointed to a significant correlation between the blood lead levels (BLLs) of children and Pb concentration in urban soil/dust [3][4][5]. Furthermore, re-suspended soil or road dust is likely to contribute significantly to fine particulate matter (<10 μm, PM 10 ) in air, a topic that has been widely studied in relation with the respiratory health of humans [6][7][8]. Therefore, the trace metals present in soil/dust might have a considerable influence on the composition of PM 10 in the surrounding air environment [9].…”

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confidence: 99%

Trace metals in soil, dust, and tree leaves of the urban environment, Guangzhou, China

Liang

2012

Chin. Sci. Bull.

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Metals have been constantly introduced to urban environments via various point and non-point sources of pollution, and have contaminated different urban compartments (sample types). However, most research projects have focused on a single environmental compartment to characterize urban metal contamination. In the present study, an integrated sampling program that includes surface soils, different size fractions of soil and road dust (<50 μm, 50-100 μm, 100-250 μm, and 250-1000 μm), tree leaves, and grasses, was conducted in a typical urban area of Guangzhou, China. The aim of the study was to investigate the interrelationships among the metal pollutants in these samples. The concentrations of trace metals varied greatly among different sample types, and their distribution was generally in the following order: road dust > soil dust ≥ surface soils ≈ top soils > grasses ≥ tree leaves. As for the relationships among the trace metals, different combinations were seen among the sample types, indicating different loadings of trace metals in the sampling medium. Significant correlations of metal concentrations were found between tree leaves and the smallest (<50 μm) fraction of road dust, and between soil dust (50-100 μm) and surface soils, suggesting that trace metals in these samples may influence each other. urban environment, trace metals, soil, dust, tree leaf, grass Citation:Bi X Y, Liang S Y, Li X D. Trace metals in soil, dust, and tree leaves of the urban environment,

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“…Heo et al, 2013;Hwang and Hopke, 2007;Polissar et al, 2001), 계산방법은 식 2와 같다. 추정된다 (Han et al, 2011;Vega et al, 2004;Watson et al, 1988a, b, c).…”

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Characteristics of PM<sub>2.5</sub> in Gyeongsan Using Statistical Analysis

Li¹,

Hwang²

2015

Journal of Korean Society for Atmospheric Environment

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서 론대기질 AbstractThe ambient PM 2.5 samples were collected by PM 2.5 sampler from September 2010 to December 2012 at Daegu University, Gyeongsan. A total of 260 samples were collected and 27 species were analyzed by inductively coupled plasma, ion chromatography, and thermal optical reflectance methods. Factor analysis identified four sources such as biomass burning source/secondary aerosol source, soil source, industry source, and incinerator source/mobile source. Also, backward trajectories were calculated using HYSPLIT 4 (Hybrid single-particle lagrangian integrated trajectory) model and PSCF (Potential source contribution function) model was applied to identify the possible source locations of carbonaceous species and water soluble ions species. PSCF results showed that the possible source locations of most chemical constituents measured in Gyeongsan were the industrial areas in the eastern coast of China, northeast regions of China, the Gobi Desert, and east sea of Korea.

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Characterization of PM10 and PM2.5 source profiles for resuspended road dust collected using mobile sampling methodology

Cited by 53 publications

References 20 publications

China Source Profile Shared Service (CSPSS): The Chinese PM2.5 Database for Source Profiles

China Source Profile Shared Service (CSPSS): The Chinese PM2.5 Database for Source Profiles

Trace metals in soil, dust, and tree leaves of the urban environment, Guangzhou, China

Characteristics of PM<sub>2.5</sub> in Gyeongsan Using Statistical Analysis

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