Sources and properties of non-exhaust particulate matter from road traffic: A review

Thorpe, A.; Harrison, Roy M.

doi:10.1016/j.scitotenv.2008.06.007

Cited by 1,285 publications

(756 citation statements)

References 54 publications

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“…Pakkanen et al (2001) identified Ba as one of the species markers of "road dust." Brake pads are commonly filled with BaSO 4 , and antimony trisulfide (Sb 2 S 3 ) is often added as a lubricant (Thorpe and Harrison 2008). Important quantities of crustal elements (like Ca and Fe) also appear in the source profile, whose explanation could be resuspended dust that had been previously deposited upon the pavement (Kim and Henry 2000).…”

Section: Resultsmentioning

confidence: 99%

PM10 source apportionment in the surroundings of the San Vicente del Raspeig cement plant complex in southeastern Spain

Yubero

Carratalá

Crespo

et al. 2010

Environ Sci Pollut Res

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Introduction The concentrations of trace metals, ionic species, and carbonaceous components in PM 10 (particulate matter with aerodynamic diameters smaller than 10 µm) were measured from samples collected near an industrial complex, primarily composed of cement plants, in southeastern Spain, from September 2005 to August 2006. Materials and methods Positive matrix factorization and conditional probability function were applied to this data set to identify different types of sources. Results Six significant sources were identified: crustal matter, traffic, aged sea salt, industrial emissions, secondary aerosol, and sea salt. The difficulty of separating anthropogenic sources from those of natural origin is highlighted in this study; in particular, the crustal source can be connected with both natural (African outbreaks, wind resuspension) and man-made emissions, like fugitive emissions in an industrial environment.

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Section: Resultsmentioning

confidence: 99%

PM10 source apportionment in the surroundings of the San Vicente del Raspeig cement plant complex in southeastern Spain

Yubero

Carratalá

Crespo

et al. 2010

Environ Sci Pollut Res

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“…13,16,17 The Cu/Sb ratios of PM 2.5-80 (Cu/Sb = 19±7) are 348 significantly higher than those typically found in brakes (Cu/Sb = 4.6±2.3) 47,54 and those of 349 With respect to Zn, we constrain the isotope signature of natural sources (wind-blown 365 mineral dust and soil) using values determined for igneous rocks. 11 The anthropogenic 366 signatures include (i) ore concentrates and sphalerite [12][13][14] representing non-exhaust traffic 367 sources (i.e., tire wear, galvanised steel), and (ii) PM collected around smelters and from 368 coal-fired power plants representing PM from high temperature processes.…”

Section: Conceptual Models For the Controls Of Zn And Cu Isotope Fingmentioning

confidence: 99%

New Insights from Zinc and Copper Isotopic Compositions into the Sources of Atmospheric Particulate Matter from Two Major European Cities

Gonzalez

Strekopytov

Amato

et al. 2016

Environ. Sci. Technol.

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This study reports spatial and temporal variability of Zn and Cu isotopes in atmospheric particulate matter (PM) collected in two major European cities with contrasting atmospheric pollution, Barcelona and London. We demonstrate that nontraditional stable isotopes identify source contributions of Zn and Cu and can play a major role in future air quality studies. In Barcelona, samples of fine PM were collected at street level at sites with variable traffic density. The isotopic signatures ranged between −0.13 ± 0.09 and −0.51 ± 0.05‰ for δ 66 Zn IRMM and between +0.04 ± 0.20 and +0.33 ± 0.15‰ for δ 65 Cu AE633 .Copper isotope signatures similar to those of Cu sulfides and Cu/ Sb ratios within the range typically found in brake wear suggest that nonexhaust emissions from vehicles are dominant. Negative Zn isotopic signatures characteristic for gaseous emissions from smelting and combustion and large enrichments of Zn and Cd suggest contribution from metallurgical industries. In London, samples of coarse PM collected on the top of a building over 18 months display isotope signatures ranging between +0.03 ± 0.04 and +0.49 ± 0.02‰ for δ 66 Zn IRMM and between +0.37 ± 0.17 and +0.97 ± 0.21‰ for δ 65 Cu AE633 . Heavy Cu isotope signatures (up to +0.97 ± 0.21‰) and higher enrichments and Cu/Sb ratios during winter time indicate important contribution from fossil fuel combustion. The positive δ 66 Zn IRMM signatures are in good agreement with signatures characteristic for ore concentrates used for the production of tires and galvanized materials, suggesting nonexhaust emissions from vehicles as the main source of Zn pollution.

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“…There is further uncertainty in the rates of particulate emissions from road vehicles due to wear of tyre, brake, and road surfaces and resuspension of pre-existing particulates (Thorpe and Harrison, 2008). Particulate exhaust emissions have decreased considerably in recent years, primarily due to the introduction of diesel particulate filters, so the relative contribution of non-exhaust PM 10 and PM 2.5 to total traffic emissions is now considerable, of the order of half of the total exhaust (Grigoratos and Martini, 2014).…”

Section: Introductionmentioning

confidence: 99%

Air quality simulations for London using a coupled regional-to-local modelling system

et al. 2018

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Abstract. A coupled regional-to-local modelling system comprising a regional chemistry-climate model with 5 km horizontal resolution (EMEP4UK) and an urban dispersion and chemistry model with explicit road source emissions (ADMS-Urban) has been used to simulate air quality in 2012 across London. The study makes use of emission factors for NO x and NO 2 and non-exhaust emission rates of PM 10 and PM 2.5 which have been adjusted compared to standard factors to reflect real-world emissions, with increases in total emissions of around 30 % for these species. The performance of the coupled model and each of the two component models is assessed against measurements from background and near-road sites in London using a range of metrics concerning annual averages, high hourly average concentrations and diurnal cycles. The regional model shows good performance compared to measurements for background sites for these metrics, but under-predicts concentrations of all pollutants except O 3 at near-road sites due to the low resolution of input emissions and calculations. The coupled model shows good performance at both background and near-road sites, which is broadly comparable with that of the urban model that uses measured concentrations as regional background, except for PM 2.5 where the under-prediction of the regional model causes the coupled model to also under-predict concentrations. Using the coupled model, it is estimated that 13 % of the area of London exceeded the EU limit value of 40 µg m −3 for annual average NO 2 in 2012, whilst areas of exceedances of the annual average limit values of 40 and 25 µg m −3 for PM 10 and PM 2.5 respectively were negligible.

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Sources and properties of non-exhaust particulate matter from road traffic: A review

Cited by 1,285 publications

References 54 publications

PM10 source apportionment in the surroundings of the San Vicente del Raspeig cement plant complex in southeastern Spain

PM10 source apportionment in the surroundings of the San Vicente del Raspeig cement plant complex in southeastern Spain

New Insights from Zinc and Copper Isotopic Compositions into the Sources of Atmospheric Particulate Matter from Two Major European Cities

Air quality simulations for London using a coupled regional-to-local modelling system

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