Estimation of the Contributions of Brake Dust, Tire Wear, and Resuspension to Nonexhaust Traffic Particles Derived from Atmospheric Measurements

Harrison, Roy M.; Jones, Alan M.; Gietl, Johanna K.; Yin, Jianxin; Green, David C.

doi:10.1021/es300894r

Cited by 510 publications

(334 citation statements)

References 31 publications

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“…The mode centered at around 2.6 µm (Street) essentially comprised coarse particles, and was mainly attributed to traffic sources following interpretation from previous research linking the coarse fraction to tyre wear, road abrasion, and re-suspended dust (Harrison et al, 2012;Lenschow et al, 2010;Ondráček et al, 2011;Pant and Harrison, 2013;Thorpe and Harrison, 2008). The relative abundance of such particles in the lower part of tree crown depicts the availability of their source at the ground level, which could be either through direct emission or particle resuspension.…”

Section: Discussionmentioning

confidence: 71%

Characterization of leaf-level particulate matter for an industrial city using electron microscopy and X-ray microanalysis

Sgrigna

Baldacchini

Esposito

et al. 2016

Science of The Total Environment

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This study reports application of monitoring and characterization protocol for particulate matter (PM) deposited on tree leaves, using Quercus ilex as a case study species. The study area is located in the industrial city of Terni in central Italy, with high PM concentrations. Four trees were selected as representative of distinct pollution environments based on their proximity to a steel factory and a street. Wash off from leaves onto cellulose filters were characterized using scanning electron microscopy and energy dispersive X-ray spectroscopy, inferring the associations between particle sizes, chemical composition, and sampling location.Modeling of particle size distributions showed a tri-modal fingerprint, with the three modes centered at 0.6 (factory related), 1.2 (urban background), and 2.6 μm (traffic related). Chemical detection identified 23 elements abundant in the PM samples. Principal component analysis recognized iron and copper as sourcespecific PM markers, attributed mainly to industrial and heavy traffic pollution respectively. Upscaling these results on leaf area basis provided a useful indicator for strategic evaluation of harmful PM pollutants using tree leaves.

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Section: Discussionmentioning

confidence: 71%

Characterization of leaf-level particulate matter for an industrial city using electron microscopy and X-ray microanalysis

Sgrigna

Baldacchini

Esposito

et al. 2016

Science of The Total Environment

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“…Non-exhaust particulate emission factors were adjusted based on work by Harrison et al (2012), who analysed measurements of speciated and size-segregated particulates at the Marylebone Road monitoring site and nearby urban background sites, made during four month-long campaigns between 2007 and 2011. Non-exhaust emissions were found to contribute 77 % of the total traffic-related particulate emissions, with 55 % of the non-exhaust attributable to brake wear and smaller proportions from resuspension of road dust and tyre wear.…”

Section: Road Traffic Emissions Factor Adjustmentsmentioning

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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“…Lin et al, 2005;Ntziachristos et al, 2007), and non-tailpipe emissions caused by abrasion of brakes (e.g. Councell et al, 2004;Lough et al, 2005;Schauer et al, 2006;Johansson et al, 2009;Pérez et al, 2010;Apeagyei et al, 2011;Song and Gao, 2011;Harrison et al, 2012). Dall'Osto et al (2013), for example, found a comparable brake dust factor characterized by Cu and Fe with a strong 30 diurnal pattern.…”

Section: Primary Vehicle Emissionsmentioning

confidence: 99%

Source Apportionment of Urban Particulate Matter using Hourly Resolved Trace Metals, Organics, and Inorganic Aerosol Components

Jeong

Wang

Evans

2016

Preprint

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Abstract. Source apportionment analysis of hourly resolved particulate matter (PM) speciation data was performed using positive matrix factorization (PMF). The data were measured at an urban site in downtown Toronto, Canada during two campaign periods (April-July, 2013;November, 2013-February, 2014, and included trace metals, black carbon, and mass 10 spectra for organic and inorganic species (PMFFull). The chemical composition was measured by collocated high time resolution instrumentation, including an Aerosol Chemical Speciation Monitor, an Xact metals monitor, and a seven-wavelength Aethalometer. Separate PMF analyses were conducted using the trace metal only data (PMFmetal) and organic mass spectra only (PMForg), and compared with the PMFFull results. Comparison of these three PMF analyses demonstrated that the full analysis offered many advantages in the apportionment of local and regional sources compared to using the organic or metals data 15 individually. In combining the high time resolution data, this analysis enabled i) the quantification of metal-rich sources of PM2.5 (PM < 2.5 μm), ii) the resolution of more robust factor profiles and contributions, and iii) the identification of additional organic aerosol sources.Nine factors were identified through the PMFFull analysis: five local factors (i.e. Road Dust, Primary Vehicle Emissions, Tire Wear, Cooking, and Industrial Sector) and four regional factors (i.e. Biomass Burning, Oxidised Organics, Sulphate and 20Oxidised Organics, and Nitrate and Oxidised Organics). The majority of the metal emissions (83%) and almost half of the black carbon (49%) were associated with the three traffic-related factors which, on average, contributed a minority (17%) of the overall PM2.5 mass. Strong seasonal patterns were observed for the traffic-related emissions: higher contributions of resuspended road dust in spring vs. a winter high for tire wear related emissions. Biomass Burning contributed the majority of the PM2.5 mass (52%) in June and July due to a major forest fire event. Much of this mass was due to photochemical aging of the biomass 25 burning aerosol. On average, industrially related factors contributed almost half (49%) of the PM2.5; most of this mass was secondary aerosol species. Nitrate coupled with highly oxidised organics was the largest contributor, accounting for 30% of PM2.5 on average, with higher levels in winter and at night. Including the temporal variabilities of inorganic ions and trace metals in the PMFFull analysis provided additional structure to subdivide the low volatility oxidised organic aerosol into three sources.Resuspended road dust was identified as a potential source of aged organic aerosol. 30The novelty of this study is the application of PMF receptor modeling to hourly resolved trace metals in conjunction with organic mass spectra, inorganic species, and black carbon for different seasons, and the comparison of separate PMF analyses applied to metals or organics alone. The inclusion of these different types of hourly data all...

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Estimation of the Contributions of Brake Dust, Tire Wear, and Resuspension to Nonexhaust Traffic Particles Derived from Atmospheric Measurements

Cited by 510 publications

References 31 publications

Characterization of leaf-level particulate matter for an industrial city using electron microscopy and X-ray microanalysis

Characterization of leaf-level particulate matter for an industrial city using electron microscopy and X-ray microanalysis

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

Source Apportionment of Urban Particulate Matter using Hourly Resolved Trace Metals, Organics, and Inorganic Aerosol Components

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