PM10 emission factors for non-exhaust particles generated by road traffic in an urban street canyon and along a freeway in Switzerland

Recent studies have shown clear contributions of non-exhaust emissions to the traffic related PM10 load of the ambient air. These emissions consist of particles produced by abrasion from brakes, road wear, tire wear, as well as vehicle induced resuspension of deposited road dust. The main scope of the presented work was to identify and quantify the non-exhaust fraction of traffic related PM10 for two roadside locations in Switzerland with different traffic regimes. The two investigated locations, an urban street canyon with heavily congested traffic and an interurban freeway, are considered as being typical for Central Europe. Mass-relevant contributions from abrasion particles and resuspended road dust mainly originated from particles in the size range 1–10 μm. The results showed a major influence of vehicle induced resuspension of road dust. In the street canyon, the traffic related PM10 emissions (LDV: 24 ± 8 mg km^?1 vehicle^?1, HDV: 498 ± 86 mg km^?1 vehicle^?1) were assigned to 21% brake wear, 38% resuspended road dust and 41% exhaust emissions. Along the freeway (LDV: 50 ± 13 mg km^?1 vehicle^?1, HDV: 288 ± 72 mg km^?1 vehicle^?1), respective contributions were 3% brake wear, 56% resuspended road dust and 41% exhaust emissions. There was no indication for relevant contributions from tire wear and abrasion from undamaged pavements.     

Assessment of heavy metal releases from the use phase of road transport in Europe

An emission inventory was compiled for heavy metal air emissions from road transport in Europe (EU-40). For the database, country-specific data was taken such as the diesel and gasoline fuel consumption per country, the content of Pb in gasoline and diesel fuel and the share of different vehicle types. For tyre and brake wear emissions, average wear rates and heavy metal contents of different materials were used to develop emission factors for tyre and brake wear. It covers exhaust emissions (Pb from gasoline and diesel) as well as non-exhaust emissions (As, Cd, Cr, Ni and Pb from the wear of brake linings and vehicle tyres). The base year is 2000, and two scenarios were developed for 2010, a business as usual (BAU) scenario and a maximum feasible technical reduction (MFTR) scenario. Both result in a remarkable decrease in Pb exhaust emissions and a rising share of non-exhaust emissions. To assess the results, the inventory is (a) compared to an inventory compiled with a top-down approach that covers the same area and years but only emissions from combustion processes and (b) added to an inventory covering all sectors for heavy metal air emissions.     

Mobile load simulators – A tool to distinguish between the emissions due to abrasion and resuspension of PM10 from road surfaces

Mechanically produced abrasion particles and resuspension processes are responsible for a significant part of the PM10 emissions of road traffic. However, specific differentiation between PM10 emissions due to abrasion and resuspension from road pavement is very difficult due to their similar elemental composition and highly correlated variation in time. In this work Mobile Load Simulators were used to estimate PM10 emission factors for pavement abrasion and resuspension on different pavement types for light and heavy duty vehicles.From the experiments it was derived that particle emissions due to abrasion from pavements in good condition are quite low in the range of only a few mg·km^?1 per vehicle if quantifiable at all. Considerable abrasion emissions, however, can occur from damaged pavements. Resuspension of deposited dust can cause high and extremely variable particle emissions depending strongly on the dirt load of the road surface. Porous pavements seem to retain deposited dust better than dense pavements, thus leading to lower emissions due to resuspension compared to pavements with a dense structure (e.g. asphalt concrete). Tyre wear seemed not to be a quantitatively significant source of PM10 emissions from road traffic.     

Identification of brake wear particles and derivation of a quantitative tracer for brake dust at a major road

Traffic-generated air pollutant emissions can be classified into exhaust and non-exhaust emissions. Increased attention is focussing on non-exhaust emissions as exhaust emissions are progressively limited by regulations. To characterise metal-rich emission from abrasion processes, size-segregated analysis of atmospheric aerosol particles sampled with micro-orifice uniform deposit impactors (MOUDI) in March 2007 in London was performed. The samples were collected at a roadside and a background site and were analysed for Al, Ba, Cu, Fe, Sb, Ti, V, Zn, Ca²⁺, K⁺, Mg²⁺, Na⁺, and NH₄⁺. Most components showed a clear roadside increment, which was evident as a higher mass concentration and a change in the size distribution. In particular, Fe, Cu, Ba, and Sb correlated highly, indicative of a common traffic-related source. Using complementary information on the fleet composition, vehicle number and average speed, the brake wear emission was calculated using the EMEP/CORINAIR emission database. The total PM₁₀ and barium emission of the traffic was determined by ratio to NO_x whose source strength was estimated from published emission factors. Barium was found to comprise 1.1% of brake wear (PM₁₀) particles from the traffic fleet as a whole, allowing its use as a quantitative tracer of brake wear emissions at other traffic-influenced sites.     

Evaluating urban PM10 pollution benefit induced by street cleaning activities

Despite their burden in urban particulate air pollution, road traffic non-exhaust emissions are often uncontrolled and information about the effectiveness of mitigation measures on paved roads is still scarce. The present study is aimed to evaluate the effectiveness of mechanical sweeping/water flushing treatments in mitigating urban road dust resuspension and to quantify the real benefit in terms of ambient PM₁₀ concentrations. To this aim a specific campaign was carried out in a heavily trafficked central road of Barcelona (Spain), a Mediterranean city suffering from a traffic-related pollution, both for a high car density and a frequent lack of precipitation. Several street washings were performed by means of mechanical sweepers and pressure water during night in all traffic lanes and sidewalks. PM₁₀ levels were simultaneously compared with four reference urban background air quality stations to interpret any meteorological variability. At the downwind measurement site, PM₁₀ concentrations registered a mean daily decrease of 8.8 μg m^?3 during the 24 h after street washing treatments. However 3.7–4.9 μg m^?3 of such decrease were due to the meteorological variability detected at the upwind site, as well as at two of the reference sites. This reveals that an effective decrease of 4–5 μg m^?3 (7–10%) can be related to street washing efficiency. Mitigation of road dust resuspension was confirmed by investigating the chemical composition of airborne-PM₁₀ filters. Concentrations of Cu, Sb, Fe and mineral matter decrease significantly with respect to concentrations of elemental carbon, used as tracer for exhaust diesel emissions. High efficiency of street washing in reducing road dust loads was found by performing periodic samplings both on the treated and the untreated areas.     

Development and preliminary evaluation of a particulate matter emission factor model for European motor vehicles

Although modeling of gaseous emissions from motor vehicles is now quite advanced, prediction of particulate emissions is still at an unsophisticated stage. Emission factors for gasoline vehicles are not reliably available, since gasoline vehicles are not included in the European Union (EU) emission test procedure. Regarding diesel vehicles, emission factors are available for different driving cycles but give little information about change of emissions with speed or engine load. We have developed size-specific speed-dependent emission factors for gasoline and diesel vehicles. Other vehicle-generated emission factors are also considered and the empirical equation for re-entrained road dust is modified to include humidity effects. A methodology is proposed to calculate modal (accelerating, cruising, or idling) emission factors. The emission factors cover particle size ranges up to 10 microns, either from published data or from user-defined size distributions. A particulate matter emission factor model (PMFAC), which incorporates virtually all the available information on particulate emissions for European motor vehicles, has been developed. PMFAC calculates the emission factors for five particle size ranges [i.e., total suspended particulates (TSP), PM10, PM5, PM2.5, and PM1] from both vehicle exhaust and nonexhaust emissions, such as tire wear, brake wear, and re-entrained road dust. The model can be used for an unlimited number of roads and lanes, and to calculate emission factors near an intersection in user-defined elements of the lane. PMFAC can be used for a variety of fleet structures. Hot emission factors at the user-defined speed can be calculated for individual vehicles, along with relative cold-to-hot emission factors. The model accounts for the proportions of distance driven with cold engines as a function of ambient temperature and road type (i.e., urban, rural, or motorway). A preliminary evaluation of PMFAC with an available dispersion model to predict the airborne concentration in the urban environment is presented. The trial was on the A6 trunk road where it passes through Loughborough, a medium-size town in the English East Midlands. This evaluation for TSP and PM10 was carried out for a range of traffic fleet compositions, speeds, and meteorological conditions. Given the limited basis of the evaluation, encouraging agreement was shown between predicted and measured concentrations.     

Road traffic emission factors for heavy metals

Quantifying the emissions and concentrations of heavy metals in urban air is a prerequisite for assessing their health effects. In this paper a combination of measurements and modelling is used to assess the contribution from road traffic emissions. Concentrations of particulate heavy metals in air were measured simultaneously during 1 year at a densely trafficked street and at an urban background site in Stockholm, Sweden. Annual mean concentrations of cadmium were 50 times lower than the EU directive and for nickel and arsenic concentrations were 10 and six times lower, respectively. More than a factor of two higher concentrations was in general observed at the street in comparison to roof levels indicating the strong influence from local road traffic emissions. The only compound with a significantly decreasing trend in the urban background was Pb with 9.1 ng m^?3 in 1995/96 compared to 3.4 ng m^?3 2003/04. This is likely due to decreased emissions from wear of brake linings and reduced emissions due to oil and coal combustion in central Europe.Total road traffic emission factors for heavy metals were estimated using parallel measurements of NOx concentrations and knowledge of NOx emission factors. In general, the emission factors for the street were higher than reported in road tunnel measurements. This could partly be due to different driving conditions, since especially for metals which are mainly emitted from brake wear, more stop and go driving in the street compared to in road tunnels is likely to increase emissions. Total emissions were compared with exhaust emissions, obtained from the COPERT model and brake wear emissions based on an earlier study in Stockholm. For Cu, Ni and Zn the sum of brake wear and exhaust emissions agreed very well with estimated total emission factors in this study. More than 90% of the road traffic emissions of Cu were due to brake wear. For Ni more than 80% is estimated to be due to exhaust emissions and for Zn around 40% of road traffic emissions are estimated to be due to exhaust emissions. Pb is also mainly due to exhaust emissions (90%); a fuel Pb content of only 0.5 mg L^?1 would give similar emission factor as that based on the concentration increment at the street. This is the first study using simultaneous measurements of heavy metals at street and roof enabling calculations of emission factors using a tracer technique.     

Separate determination of PM10 emission factors of road traffic for tailpipe emissions and emissions from abrasion and resuspension processes

Little is known about the relevance of mechanically produced particles of road traffic from abrasion and resuspension processes in relation to the exhaust pipe particles. In this paper, emission factors of PM₁₀ and PM₁ for light and heavy-duty vehicles were derived for different representative traffic regimes from concentration differences of particles and nitrogen oxides (NO_x) in ambient air upwind and downwind of busy roads, or alternatively of kerbsides and nearby background sites. Hereby, PM₁ was interpreted as direct exhaust emissions and PM₁₀-PM₁ as mechanically produced emissions from abrasion and resuspension processes. The results show that abrasion and resuspension processes represent a significant part of the total primary PM₁₀ emissions of road traffic. At sites with relatively undisturbed traffic flow they are in the same range as the exhaust pipe emissions. At sites with disturbed traffic flow due to traffic lights, emissions from abrasion/resuspension are even higher than those from the exhaust pipes.     

Quantifying road dust resuspension in urban environment by Multilinear Engine: A comparison with PMF2

Atmospheric PM pollution from traffic comprises not only direct emissions but also non-exhaust emissions because resuspension of road dust that can produce high human exposure to heavy metals, metalloids, and mineral matter. A key task for establishing mitigation or preventive measures is estimating the contribution of road dust resuspension to the atmospheric PM mixture. Several source apportionment studies, applying receptor modeling at urban background sites, have shown the difficulty in identifying a road dust source separately from other mineral sources or vehicular exhausts. The Multilinear Engine (ME-2) is a computer program that can solve the Positive Matrix Factorization (PMF) problem. ME-2 uses a programming language permitting the solution to be guided toward some possible targets that can be derived from a priori knowledge of sources (chemical profile, ratios, etc.). This feature makes it especially suitable for source apportionment studies where partial knowledge of the sources is available.In the present study ME-2 was applied to data from an urban background site of Barcelona (Spain) to quantify the contribution of road dust resuspension to PM₁₀ and PM_2.5 concentrations. Given that recently the emission profile of local resuspended road dust was obtained (Amato, F., Pandolfi, M., Viana, M., Querol, X., Alastuey, A., Moreno, T., 2009. Spatial and chemical patterns of PM₁₀ in road dust deposited in urban environment. Atmospheric Environment 43 (9), 1650–1659), such a priori information was introduced in the model as auxiliary terms of the object function to be minimized by the implementation of the so-called “pulling equations”.ME-2 permitted to enhance the basic PMF solution (obtained by PMF2) identifying, beside the seven sources of PMF2, the road dust source which accounted for 6.9 μg m^?3 (17%) in PM₁₀, 2.2 μg m^?3 (8%) of PM_2.5 and 0.3 μg m^?3 (2%) of PM₁. This reveals that resuspension was responsible of the 37%, 15% and 3% of total traffic emissions respectively in PM₁₀, PM_2.5 and PM₁. Therefore the overall traffic contribution resulted in 18 μg m^?3 (46%) in PM₁₀, 14 μg m^?3 (51%) in PM_2.5 and 8 μg m^?3 (48%) in PM₁. In PMF2 this mass explained by road dust resuspension was redistributed among the rest of sources, increasing mostly the mineral, secondary nitrate and aged sea salt contributions.     

A revised estimate of copper emissions from road transport in UNECE-Europe and its impact on predicted copper concentrations

Comparisons of measured and model-predicted atmospheric copper concentrations show a severe underestimation of the observed concentrations by the models. This underestimation may be (partly) due to underestimated emissions of copper to air. Since the phase out of asbestos brake lining material, the composition of brake lining material has changed and may contain up to ∼15% copper. This makes brake wear from vehicles potentially an important source of atmospheric (particulate) copper concentrations. In this paper, we reassess the copper emissions due to exhaust emissions and brake wear from road transport. Overall, our reassessments result in an estimate of total copper emission to air in UNECE-Europe of 4.0–5.5 ktonnes yr⁻¹, which is substantially higher than the previous estimate of 2.8 ktonnes yr⁻¹. Copper concentrations over Europe are calculated with the LOTOS-EUROS model using the revised emission data as model input. The results show that the revised emission estimates are a major step towards gap closure of predicted versus observed copper concentrations in ambient air. Brake wear emissions may be responsible for 50–75% of the total copper emissions to air for most of Western Europe. The hypothesis that road transport is an important source of copper emissions is tested and confirmed by (1) reviewing available literature data of chemically speciated PM data from road tunnel studies and (2) the gradient observed in copper concentrations from ambient PM monitoring going from rural sites to street stations. The literature review and observational data suggest that the majority of the emitted PM10 brake wear particles is in the PM2.5–10 size range. The results of this study indicate that modification of brake lining composition is an important mitigation option to reduce copper exposure of the population in Western Europe.     

Changes in elemental composition and mass of atmospheric aerosol pollution between 1996 and 2002 in a Central European city

Median atmospheric concentrations of Pb, Br, S, As, Se, and particulate matter (PM) decreased, and median concentrations of Sb, Cu, Zn, Fe, Ca, Cr and Ba increased in urban aerosol in downtown Budapest between 1996 and 2002. The changes in Pb and Br concentrations were unambiguously attributed to the phasing out of leaded gasoline. The increments were mainly related to and explained by non-exhaust vehicular emissions. The mechanical wear of asbestos-free brake linings of road vehicles contributed to the concentration of Cu and Sb on average by 69% and 66%, respectively in the PM10 size fraction. Tire rubber abrasion was a major source for atmospheric Zn; on average, non-crustal sources accounted for 67% of Zn in the PM10 size fraction. Contribution of the tire wear component to the PM10 mass was estimated to be 6% at most, while its contribution to organic aerosol was of the order of 15%.     

PM Emissions Emanating from Limited-Access Highways

ABSTRACT

Motor vehicle contributions to primary particulate matter (PM) emissions include exhaust, tire wear, brake and clutch wear, and resuspended road dust. Relatively few field studies have been conducted to quantify fleetaverage exhaust emissions for actual on-road conditions. Therefore, direct measurements of motor vehicle-related PM emissions are warranted. In this study, PM₁₀ and PM_2.5 mass concentrations were measured near two major highways in the St. Louis area over the period from February–April 1997. Samplers were deployed both upwind and downwind of the roadways to capture the transport and dispersion of PM with distance from the roadway. The observed microscale concentration fields were compared to estimates using the PART5 emission factor model together with the CALINE4 highway dispersion model. Traffic- induced PM mass concentrations observed downwind of the roadway were always less than PART5/CALINE4 predictions; average percent differences for observed traffic-induced mass concentrations compared to predicted values were ?34% for PM_2.5 and -70% for PM₁₀. In most cases, the observed PM concentration decay with increasing distance from the roadway was steeper than predicted by dispersion modeling. Motor vehicle-induced emission factors were reconstructed by fitting CALINE4 to the observed concentration data with the emission factor as the sole adjustable parameter. Reconstructed fleet-average motor vehicle emission factors for the urban interstate highway were 0.03–0.04 g/VMT for both PM_2.5 and PM₁₀, while the fleet-average emission factors for the rural interstate highway were 0.2 and 0.3 g/VMT for PM_2.5 and PM₁₀, respectively.     

Road traffic impact on urban atmospheric aerosol loading at Oporto,Portugal

At urban areas in south Europe atmospheric aerosol levels are frequently above legislation limits as a result of road traffic and favourable climatic conditions for photochemical formation and dust suspension. Strategies for urban particulate pollution control have to take into account specific regional characteristics and need correct information concerning the sources of the aerosol.With these objectives, the ionic and elemental composition of the fine (PM_2.5) and coarse (PM_2.5–10) aerosol was measured at two contrasting sites in the centre of the city of Oporto, roadside (R) and urban background (UB), during two campaigns, in winter and summer.Application of Spatial Variability Factors, in association with Principal Component/Multilinear Regression/Inter-site Mass Balance Analysis, to aerosol data permitted to identify and quantify 5 main groups of sources, namely direct car emissions, industry, photochemical production, dust suspension and sea salt transport. Traffic strongly influenced PM mass and composition. Direct car emissions and road dust resuspension contributed with 44–66% to the fine aerosol and with 12 to 55% to the coarse particles mass at both sites, showing typically highest loads at roadside. In fine particles secondary origin was also quite important in aerosol loading, principally during summer, with 28–48% mass contribution, at R and UB sites respectively. Sea spray has an important contribution of 18–28% to coarse aerosol mass in the studied area, with a highest relative contribution at UB site.Application of Spatial Variability/Mass Balance Analysis permitted the estimation of traffic contribution to soil dust in both size ranges, across sites and seasons, demonstrating that as much as 80% of present dust can result from road traffic resuspension.     

Time-series analysis of above-road particulate matter at the Caldecott Tunnel exit

On November 18, 1997, above-road particulate matter (PM) lidar (light detection and ranging) signals and heavy-duty (HD) and light-duty (LD) vehicle counts were simultaneously collected for 894 10-sec sampling periods at the Caldecott Tunnel in Orinda, CA, for the purpose of measuring the relative contributions of LD and HD vehicles to the PM lidar signal under real-world driving conditions. The relationship between the PM lidar signal and traffic activity (i.e., LD and HD traffic volumes) was examined using a time-series analysis technique, multilagged regression. The time-series model results indicate that the PM lidar signal in the current sampling period (PMt) depended on the level recorded in the previous three sampling periods (i.e., PMt-1, PMt-2, and PMt-3), the number of LD vehicles in the seventh past sampling period (LDt-7), and the number of HD vehicles measured 80 sec previous to the current sampling period (HDt-8). On a 10-sec period basis, the model results indicate that HD vehicles contributed, on average, 3 times more to above-road PM lidar signals than did LD vehicles. The observed lag in the relationship between vehicle types and the lidar signal 20 m above the road suggests that resuspended road dust, rather than tailpipe exhaust emissions, was the main source of the detected PM. Detection of road dust at such heights above the road suggests the need for investigating the processes governing the vertical transport and recycling of PM over the road as a function of vehicle dynamics under a range of meteorological conditions.     

Examining intra-urban variation in fine particle mass constituents using GIS and constrained factor analysis

Recent studies have used land use regression (LUR) techniques to explain spatial variability in exposures to PM_2.5 and traffic-related pollutants. Factor analysis has been used to determine source contributions to measured concentrations. Few studies have combined these methods, however, to construct and explain latent source effects. In this study, we derive latent source factors using confirmatory factor analysis constrained to non-negative loadings, and develop LUR models to predict the influence of outdoor sources on latent source factors using GIS-based measures of traffic and other local sources, central site monitoring data, and meteorology. We collected 3–4 day samples of nitrogen dioxide (NO₂) and PM_2.5 outside of 44 homes in summer and winter, from 2003 to 2005 in and around Boston, Massachusetts. Reflectance analysis, X-ray fluorescence spectroscopy (XRF), and high-resolution inductively-coupled plasma mass spectrometry (ICP-MS) were performed on particle filters to estimate elemental carbon (EC), trace element, and water-soluble metals concentrations. Within our constrained factor analysis, a five-factor model was optimal, balancing statistical robustness and physical interpretability. This model produced loadings indicating long-range transport, brake wear/traffic exhaust, diesel exhaust, fuel oil combustion, and resuspended road dust. LUR models largely corroborated factor interpretations through covariate significance. For example, ‘long-range transport’ was predicted by central site PM_2.5 and season; ‘brake wear/traffic exhaust’ and ‘resuspended road dust’ by traffic and residential density; ‘diesel exhaust’ by percent diesel traffic on nearest major road; and ‘fuel oil combustion’ by population density. Results suggest that outdoor residential PM_2.5 source contributions can be partially predicted using GIS-based terms, and that LUR techniques can support factor interpretation for source apportionment. Together, LUR and factor analysis facilitate source identification, assessment of spatial and temporal variability, and more refined source exposure assignment for evaluation of source contributions to health outcomes in epidemiological studies.     

Estimation and validation of PM2.5/PM10 exhaust and non-exhaust emission factors for practical street pollution modelling

In order to carry out efficient traffic and air quality management, validated models and PM emission estimates are needed. This paper compares current available emission factor estimates for PM₁₀ and PM_2.5 from emission databases and different emission models, and validates these against eight high quality street pollution measurements in Denmark, Sweden, Germany, Finland and Austria.The data sets show large variation of the PM concentration and emission factors with season and with location. Consistently at all roads the PM₁₀ and PM_2.5 emission factors are lower in the summer month than the rest of the year. For example, PM₁₀ emission factors are in average 5–45% lower during the month 6–10 compared to the annual average.The range of observed total emission factors (including non-exhaust emissions) for the different sites during summer conditions are 80–130 mg km⁻¹ for PM₁₀, 30–60 mg km⁻¹ for PM_2.5 and 20–50 mg km⁻¹ for the exhaust emissions.We present two different strategies regarding modelling of PM emissions: (1) For Nordic conditions with strong seasonal variations due to studded tyres and the use of sand/salt as anti-skid treatment a time varying emission model is needed. An empirical model accounting for these Nordic conditions was previously developed in Sweden. (2) For other roads with a less pronounced seasonal variation (e.g. in Denmark, Germany, Austria) methods using a constant emission factor maybe appropriate. Two models are presented here.Further, we apply the different emission models to data sets outside the original countries. For example, we apply the “Swedish” model for two streets without studded tyre usage and the “German” model for Nordic data sets. The “Swedish” empirical model performs best for streets with studded tyre use, but was not able to improve the correlation versus measurements in comparison to using constant emission factors for the Danish side. The “German” method performed well for the streets without clear seasonal variation and reproduces the summer conditions for streets with pronounced seasonal variation. However, the seasonal variation of PM emission factors can be important even for countries not using studded tyres, e.g. in areas with cold weather and snow events using sand and de-icing materials. Here a constant emission factor probably will under-estimate the 90-percentiles and therefore a time varying emission model need to be used or developed for such areas.All emission factor models consistently indicate that a large part (about 50–85% depending on the location) of the total PM₁₀ emissions originates from non-exhaust emissions. This implies that reduction measures for the exhaust part of the vehicle emissions will only have a limited effect on ambient PM₁₀ levels.     

Development and Preliminary Evaluation of a Particulate Matter Emission Factor Model for European Motor Vehicles

ABSTRACT

Although modeling of gaseous emissions from motor vehicles is now quite advanced, prediction of particulate emissions is still at an unsophisticated stage. Emission factors for gasoline vehicles are not reliably available, since gasoline vehicles are not included in the European Union (EU) emission test procedure. Regarding diesel vehicles, emission factors are available for different driving cycles but give little information about change of emissions with speed or engine load. We have developed size-specific speed-dependent emission factors for gasoline and diesel vehicles. Other vehicle-generated emission factors are also considered and the empirical equation for re-entrained road dust is modified to include humidity effects. A methodology is proposed to calculate modal (accelerating, cruising, or idling) emission factors. The emission factors cover particle size ranges up to 10 um, either from published data or from user-defined size distributions.

A particulate matter emission factor model (PMFAC), which incorporates virtually all the available information on particulate emissions for European motor vehicles, has been developed. PMFAC calculates the emission factors for five particle size ranges [i.e., total suspended particulates (TSP), PM₁₀, PM₅, PM₂₅, and PM₁] from both vehicle exhaust and nonexhaust emissions, such as tire wear, brake wear, and re-entrained road dust. The model can be used for an unlimited number of roads and lanes, and to calculate emission factors near an intersection in user-defined elements of the lane. PMFAC can be used for a variety of fleet structures. Hot emission factors at the user-defined speed can be calculated for individual vehicles, along with relative cold-to-hot emission factors. The model accounts for the proportions of distance driven with cold engines as a function of ambient temperature and road type (i.e., urban, rural, or motorway).

A preliminary evaluation of PMFAC with an available dispersion model to predict the airborne concentration in the urban environment is presented. The trial was on the A6 trunk road where it passes through Loughborough, a medium-size town in the English East Midlands. This evaluation for TSP and PM₁₀ was carried out for a range of traffic fleet compositions, speeds, and meteorological conditions. Given the limited basis of the evaluation, encouraging agreement was shown between predicted and measured concentrations.     

Time-Series Analysis of Above-Road Particulate Matter at the Caldecott Tunnel Exit

ABSTRACT

On November 18, 1997, above-road particulate matter (PM) lidar (light detection and ranging) signals and heavy-duty (HD) and light-duty (LD) vehicle counts were simultaneously collected for 894 10-sec sampling periods at the Caldecott Tunnel in Orinda, CA, for the purpose of measuring the relative contributions of LD and HD vehicles to the PM lidar signal under real-world driving conditions. The relationship between the PM lidar signal and traffic activity (i.e., LD and HD traffic volumes) was examined using a time-series analysis technique, multilagged regression. The time-series model results indicate that the PM lidar signal in the current sampling period (PM_t) depended on the level recorded in the previous three sampling periods (i.e., PM_t-1, PM_t-2, and PM_t-3), the number of LD vehicles in the seventh past sampling period (LD_t-7), and the number of HD vehicles measured 80 sec previous to the current sampling period (HD_t-8). On a 10-sec period basis, the model results indicate that HD vehicles contributed, on average, 3 times more to above-road PM li-dar signals than did LD vehicles. The observed lag in the relationship between vehicle types and the lidar signal 20 m above the road suggests that resuspended road dust, rather than tailpipe exhaust emissions, was the main source of the detected PM. Detection of road dust at such heights above the road suggests the need for investigating the processes governing the vertical transport and recycling of PM over the road as a function of vehicle dynamics under a range of meteorological conditions.     

Characterization of the fugitive particulate emissions from construction mud/dirt carryout

Although the fugitive dust associated with construction mud/dirt carryout can represent a substantial portion of the particulate matter (PM) emissions inventory in nonattainment areas, it has not been well characterized by direct sampling methods. In this paper, a research program is described that directly determined both PM10 and PM2.5 (particles < or =10 and 2.5 microm in classical aerodynamic diameter, respectively) emission factors for mud/dirt carryout from a major construction project located in metropolitan Kansas City, MO. The program also assessed the contribution of automotive emissions to the total PM2.5 burden and determined the baseline emissions from the test road. As part of the study, both time-integrated and continuous exposure-profiling methods were used to assess the PM emissions, including particle size and elemental composition. This research resulted in overall PM10 and PM2.5 emission factors of 6 and 0.2 g/vehicle, respectively. Although PM10 is within the range of prior U.S. Environmental Protection Agency (EPA) guidance, the PM2.5 emission factor is far lower than previous estimates published by EPA. In addition, based on both the particle size and chemical data obtained in the study, a major portion of the PM2.5 emissions appears to be attributable to automotive exhaust from light-duty, gasoline-powered vehicles and not to the fugitive dust associated with reentrained mud/dirt carryout.     

PM10 source apportionment in a Swiss Alpine valley impacted by highway traffic

Although trans-Alpine highway traffic exhaust is one of the major sources of air pollution along the highway valleys of the Alpine regions, little is known about its contribution to residential exposure and impact on respiratory health. In this paper, source-specific contributions to particulate matter with an aerodynamic diameter?<?10 μm (PM₁₀) and their spatio-temporal distribution were determined for later use in a pediatric asthma panel study in an Alpine village. PM₁₀ sources were identified by positive matrix factorization using chemical trace elements, elemental, and organic carbon from daily PM₁₀ filters collected between November 2007 and June 2009 at seven locations within the village. Of the nine sources identified, four were directly road traffic-related: traffic exhaust, road dust, tire and brake wear, and road salt contributing 16 %, 8 %, 1 %, and 2 % to annual PM₁₀ concentrations, respectively. They showed a clear dependence with distance to highway. Additional contributions were identified from secondary particles (27 %), biomass burning (18 %), railway (11 %), and mineral dust including a local construction site (13 %). Comparing these source contributions with known source-specific biomarkers (e.g., levoglucosan, nitro-polycyclic aromatic hydrocarbons) showed high agreement with biomass burning, moderate with secondary particles (in winter), and lowest agreement with traffic exhaust.