Determination of road dust loadings and chemical characteristics using resuspension

Chen, Jianhua; Wang, Wei; Liu, Hongjie; Ren, Liehui

doi:10.1007/s10661-011-2071-1

Cited by 64 publications

(46 citation statements)

References 29 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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“…On the other hand, taking into account that one of the main primary contributors to indoor particles is probably resuspended dust, some of which associated with soil, high OC/EC ratios are not surprising. In fact, it has been reported that particles from dust resuspension present high OC/EC ratios (e.g., Amato et al, 2009;Chen et al, 2012). The poor indoor-outdoor correlations of OC (r 2 between 0.22 and 0.30) indicate the presence of multiple carbon sources, and different contributions to indoor and outdoor carbonaceous particles.…”

Section: Particulate Matter Levels and Chemical Compositionmentioning

confidence: 99%

Comfort Parameters and Particulate Matter (PM10 and PM2.5) in School Classrooms and Outdoor Air

Alves

Nunes

Silva

et al. 2013

Aerosol Air Qual. Res.

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In January 2012, one kindergarten and eight elementary school classrooms were monitored. The campaign included simultaneous measurements, indoors and outdoors, of comfort parameters, CO, CO 2 and particles. Automatic monitors using a light scattering technique were employed to measure PM 10 continuously. During occupied periods, low volume samplers were used to daily collect PM 2.5 samples, which were subsequently analysed for carbonates, organic carbon (OC), elemental carbon (EC) and water soluble inorganic ions. With regard to comfort, the schools did not meet the recommended levels in many rooms. Indoor-outdoor CO 2 ratios between 3 and 12, and indoor levels much higher than 1000 ppm during the occupied periods, indicate the highly inadequate ventilation in these locations. The results clearly demonstrate that there is a high level of exposure to particulate matter in these schools. The continuous measurements of PM 10 suggest that the physical activity of pupils, which is assumed to be more marked in younger children, contributes to a constant process of resuspension of sedimented particles. In addition, peak PM 10 concentrations coincident with cleaning activities suggest the need to change certain practices to improve cleanliness. Around 40% of the PM 2.5 mass is composed of carbonaceous matter, with 4-5 times higher OC mass fractions than EC. It was observed that both OC and EC were significantly influenced by indoor sources. Water-soluble inorganic ions represented around 10-20% of the PM 2.5 mass measured in classrooms. Excluding calcium, in general the ionic species were present at indoor-outdoor ratios of less than 1, suggesting the major origin in the outdoor air.

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“…The contribution of road dust particles to atmospheric particulate pollution through resuspension has been studied in many cities around the world (Table 4), and such particles have been found to contribute 16-56% and 8-19% to PM 10 and PM 2.5 , respectively (Amato et al, 2009a;Avino et al, 2014;Bukowiecki et al, 2010;Chen et al, 2012;Fan et al, 2007;Karanasiou et al, 2011;Kuhns et al, 2001;Song et al, 2006). However, the amounts of various pollutants in resuspended road dust have been assessed in very few studies, and this severely hampers the ability to reliably assess the acute impacts of atmospheric particulate pollution.…”

Section: Contribution Of Road Dust Particles To Atmospheric Particulamentioning

confidence: 99%

“…At present, air quality degradation due to ambient particulate matter has become an environmental issue of public health concern in most metropolitan areas in China (Chen et al, 2012;Huang et al, 2014). It is well known that the resuspension of road dust particles from urban street surfaces is an important source of atmospheric particulate pollution (Amato et al, 2009b;Martuzevicius et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

An index for estimating the potential metal pollution contribution to atmospheric particulate matter from road dust in Beijing

Zhao

Shao

Yin

et al. 2016

Science of The Total Environment

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• An innovative road dust index was developed.• Road dust characteristics were ranked and weighted in the index model.• Source and transport factors were both considered in the index model. The resuspension of road dust from street surfaces could be a big contributor to atmospheric particulate pollution in the rapid urbanization context in the world. However, to date what its potential contribution to the spatial pattern is little known. Here we developed an innovative index model called the road dust index (RI b105 μm ) and it combines source and transport factors for road dust particles b 105 μm in diameter. It could quantify and differentiate the impact of the spatial distribution of the potential risks posed by metals associated with road dust on atmospheric suspended particles. The factors were ranked and weighted based on road dust characteristics (the amounts, grain sizes, and mobilities of the road dust, and the concentrations and toxicities of metals in the road dust). We then applied the RI b105 μm in the Beijing region to assess the spatial distribution of the potential risks posed by metals associated with road dust on atmospheric suspended particles. The results demonstrated that the road dust in urban areas has higher potential risk of metal to atmospheric particles than that in rural areas. The RI b105 μm method offers a new and useful tool for assessing the potential risks posed by metals associated with road dust on atmospheric suspended particles and for controlling atmospheric particulate pollution caused by road dust emissions.

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Determination of road dust loadings and chemical characteristics using resuspension

Cited by 64 publications

References 29 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

Comfort Parameters and Particulate Matter (PM10 and PM2.5) in School Classrooms and Outdoor Air

An index for estimating the potential metal pollution contribution to atmospheric particulate matter from road dust in Beijing

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