Physical and Chemical Characteristics and Volatility of PM in the Proximity of a Light-Duty Vehicle Freeway

Kühn, Thomas; Biswas, Subhasis; Fine, Philip M.; Geller, Michael D.; Sioutas, Constantinos

doi:10.1080/027868290930024

Cited by 64 publications

(43 citation statements)

References 46 publications

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“…The EF from S is smaller in the JQ tunnel than measured by Kuhn et al (2005) and Landis et al (2007), however roughly in the same proportion as many other elements. The elements apportioned to crustal source in the JQ tunnel are Na, Mg, Al, Si, K and Ca.…”

Section: Oc Ec and Trace Elementsmentioning

confidence: 79%

“…In this study, Al was used as the reference element. Figure 5 shows the EF analysis results for JQ and RA tunnels, along with results from previous US works near a light-duty vehicle freeway (Kuhn et al, 2005) and in US tunnel measurements (Landis et al, 2007).…”

Section: Oc Ec and Trace Elementsmentioning

confidence: 99%

“…From 10 to 60, the elements are assigned to a mixed contribution between vehicular and crustal origins. The reference element (Kuhn et al, 2005) and in tunnel (Landis et al, 2007). Bottom: EF results from the RA tunnel and results for diesel-fuelled HDVs in tunnels (Landis et al, 2007).…”

Section: Oc Ec and Trace Elementsmentioning

confidence: 99%

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Physical–chemical characterisation of the particulate matter inside two road tunnels in the São Paulo Metropolitan Area

Brito¹,

Rizzo²,

Herckès

et al. 2013

Atmos. Chem. Phys.

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Abstract. The notable increase in biofuel usage by the road transportation sector in Brazil during recent years has significantly altered the vehicular fuel composition. Consequently, many uncertainties are currently found in particulate matter vehicular emission profiles. In an effort to better characterise the emitted particulate matter, measurements of aerosol physical and chemical properties were undertaken inside two tunnels located in the São Paulo Metropolitan Area (SPMA). The tunnels show very distinct fleet profiles: in the Jânio Quadros (JQ) tunnel, the vast majority of the circulating fleet are light duty vehicles (LDVs), fuelled on average with the same amount of ethanol as gasoline. In the Rodoanel (RA) tunnel, the particulate emission is dominated by heavy duty vehicles (HDVs) fuelled with diesel (5 % biodiesel). In the JQ tunnel, PM 2.5 concentration was on average 52 µg m −3 , with the largest contribution of organic mass (OM, 42 %), followed by elemental carbon (EC, 17 %) and crustal elements (13 %). Sulphate accounted for 7 % of PM 2.5 and the sum of other trace elements was 10 %. In the RA tunnel, PM 2.5 was on average 233 µg m −3 , mostly composed of EC (52 %) and OM (39 %). Sulphate, crustal and the trace elements showed a minor contribution with 5 %, 1 %, and 1 %, respectively. The average OC : EC ratio in the JQ tunnel was 1.59 ± 0.09, indicating an important contribution of EC despite the high ethanol fraction in the fuel composition. In the RA tunnel, the OC : EC ratio was 0.49 ± 0.12, consistent with previous measurements of diesel-fuelled HDVs. Besides bulk carbonaceous aerosol measurement, polycyclic aromatic hydrocarbons (PAHs) were quantified. The sum of the PAHs concentration was 56 ± 5 ng m −3 and 45 ± 9 ng m −3 in the RA and JQ tunnel, respectively. In the JQ tunnel, benzo(a)pyrene (BaP) ranged from 0.9 to 6.7 ng m −3 (0.02-0. 1 ‰ of PM 2.5 ) whereas in the RA tunnel BaP ranged from 0.9 to 4.9 ng m −3 (0.004-0. 02 ‰ of PM 2.5 ), indicating an important relative contribution of LDVs emission to atmospheric BaP.Real-time measurements performed in both tunnels provided aerosol size distributions and optical properties. The average particle count yielded 73 000 cm −3 in the JQ tunnel and 366 000 cm −3 in the RA tunnel, with an average diameter of 48 nm in the former and 39 nm in the latter. Aerosol single scattering albedo, calculated from scattering and absorption observations in the JQ tunnel, indicates a value of 0.5 associated with LDVs. Such single scattering albedo is 20-50 % higher than observed in previous tunnel studies, possibly as a result of the large biofuel usage. Given the exceedingly high equivalent black carbon loadings in the RA tunnel, real time light absorption measurements were possible only in the JQ tunnel. Nevertheless, using EC measured from the filters, a single scattering albedo of 0.31 for the RA tunnel has been estimated. The results presented here characterise particulate matter emitted from nearly 1 million vehicles fuelled with a considerable amount of...

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Section: Oc Ec and Trace Elementsmentioning

confidence: 79%

Section: Oc Ec and Trace Elementsmentioning

confidence: 99%

See 1 more Smart Citation

Physical–chemical characterisation of the particulate matter inside two road tunnels in the São Paulo Metropolitan Area

Brito¹,

Rizzo²,

Herckès

et al. 2013

Atmos. Chem. Phys.

View full text Add to dashboard Cite

show abstract

“…Several studies have shown that fine 35 and ultrafine 36 particle concentrations drop off rapidly near roadways. Kuhn et al 35 found that concentrations of PM 2.5 nitrate and PM 2.5 EC were greater near a highway in Southern California, but concentrations of crustal elements (Na, Mg, Al, Si, S, Cl, K, Ca, Ni, Zn, and Ba) and coarse PM were similar both near and far from the highway. Zhu et al 36 found that number and surface area of ultrafine PM dropped off rapidly in the first few hundred meters from the roadway.…”

Section: Emission Estimation Methods and Magnitude Of Emissionsmentioning

confidence: 99%

“…Mobile sources generally emit particles in the ultrafine (Ͻ0.1 m diameter) range [43][44][45] ; number concentrations are typically greatest for particles with diameters between 10 and 20 nm. 35,36 These initial size distributions change rapidly, as a function of distance from roadways, because of coagulation, evaporation, or condensation of semivolatile organics; deposition; and other processes. These processes and source characteristics vary with temperature and other atmospheric conditions, creating seasonal variations in the particle size distributions near roadways.…”

Section: Emission Estimation Methods and Magnitude Of Emissionsmentioning

confidence: 99%

Fine Particulate Matter Emissions Inventories: Comparisons of Emissions Estimates with Observations from Recent Field Programs

Simon¹,

Allen²,

Wittig

2008

Journal of the Air & Waste Management Association

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Emissions inventories of fine particulate matter (PM 2.5 ) were compared with estimates of emissions based on data emerging from U.S. Environment Protection Agency Particulate Matter Supersites and other field programs. Six source categories for PM 2.5 emissions were reviewed: onroad mobile sources, nonroad mobile sources, cooking, biomass combustion, fugitive dust, and stationary sources. Ammonia emissions from all of the source categories were also examined. Regional emissions inventories of PM in the exhaust from on-road and nonroad sources were generally consistent with ambient observations, though uncertainties in some emission factors were twice as large as the emission factors. In contrast, emissions inventories of road dust were up to an order of magnitude larger than ambient observations, and estimated brake wear and tire dust emissions were half as large as ambient observations in urban areas. Although comprehensive nationwide emissions inventories of PM 2.5 from cooking sources and biomass burning are not yet available, observational data in urban areas suggest that cooking sources account for approximately 5-20% of total primary emissions (excluding dust), and biomass burning sources are highly dependent on region. Finally, relatively few observational data were available to assess the accuracy of emission estimates for stationary sources. Overall, the uncertainties in primary emissions for PM 2.5 are substantial. Similar uncertainties exist for ammonia emissions. Because of these uncertainties, the design of PM 2.5 control strategies should be based on inventories that have been refined by a combination of bottom-up and top-down methods. INTRODUCTIONEmissions inventories can be used to establish statewide and nationwide trends in air quality or to prioritize emission sources in specific geographical areas. They can also be used as inputs to models used to predict ambient air quality on specific days. The temporal resolution of the emissions inventory depends on the purpose of the inventory. Emissions inventories that are used to establish air quality trends at regional or national scales need only have information about average emission rates. However, emissions inventories that will be used in models that predict air quality on specific days or that are used to predict the likelihood of extremes in air pollutant concentrations must consider both average emission rates and daily variability in emissions.The goal of this review is to assess the accuracy of emissions inventories of fine particulate matter (PM; PM Ͻ2.5 m in aerodynamic diameter [PM 2.5 ]) and one of its precursors, ammonia. Precursors of secondary PM 2.5 include ammonia, nitrogen oxides, sulfur dioxide, and hydrocarbons (HCs). Of these PM 2.5 precursors, this review addresses only ammonia, because the emissions inventories for nitrogen oxides and sulfur dioxide are reasonably accurate, and the uncertainties in the HC emissions inventory merit a separate review. Ambient observations of PM 2.5 mass and composition are compared wi...

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Comparison of polycyclic aromatic hydrocarbon emissions on gasoline- and diesel-dominated routes

Kuo

Chien

Kuo

et al. 2012

Environ Monit Assess

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Physical and Chemical Characteristics and Volatility of PM in the Proximity of a Light-Duty Vehicle Freeway

Cited by 64 publications

References 46 publications

Physical–chemical characterisation of the particulate matter inside two road tunnels in the São Paulo Metropolitan Area

Physical–chemical characterisation of the particulate matter inside two road tunnels in the São Paulo Metropolitan Area

Fine Particulate Matter Emissions Inventories: Comparisons of Emissions Estimates with Observations from Recent Field Programs

Comparison of polycyclic aromatic hydrocarbon emissions on gasoline- and diesel-dominated routes

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