Using a dispersion model to estimate emission rates of particulate matter from paved roads

From January 1996 to June 1997, we carried out a series of measurements to estimate emissions of PM₁₀ from paved roads in Riverside County, California. The program involved the measurement of upwind and downwind vertical profiles of PM₁₀, in addition to meteorological variables such as wind speed and vertical turbulent intensity. This information was analyzed using a new dispersion model that incorporates current understanding of micrometeorology and dispersion. The emission rate was inferred by fitting model predictions to measurements. The inferred emission factors ranged from 0.2 g VKT^-1 for freeways to about 3 g VKT^-1 for city roads. The uncertainty in these factors is estimated to be approximately a factor of two since the contributions of paved road PM₁₀ emissions to ambient concentrations were comparable to the uncertainty in the mean value of the measurement. At this stage, our best estimate of emission factor lies between 0.1 and 10 g VKT^-1; there is some indication that it is about 0.1 g VKT^-1 for heavily traveled freeways, and is an order of magnitude higher for older city roads. We found that measured silt loadings were poor predictors of emission factors.The measured emission factors imply that paved road emissions may contribute about 30% to the total PM₁₀ emissions from a high traffic area such as Los Angeles. This suggests that it is necessary to develop methods that are more reliable than the upwind–downwind concentration difference technique.     

Measurements and modelling of PM2.5 concentrations near a major road in Kuopio,Finland

A particle measurement campaign was conducted in a suburban environment near a major road in Kuopio, Central Finland from 3 August to 9 September 1999. The mass concentrations of fine particles (PM_2.5) were measured simultaneously at distances of 12, 25, 52 and 87 m from the centre of a major road at a height of 1.8 m, using identical samplers. The concentration measurements were conducted during 16 daytime hours (from 6.00 a.m. to 10.00 p.m.) for 27 days. Traffic flows and relevant meteorological parameters were measured on-site; meteorological measurements from a nearby synoptic weather station were also utilised. We also suggest a preliminary model for predicting the concentrations of PM_2.5 and apply this model in order to analyse the measured data. The regionally and long-range transported contribution was evaluated on the basis of a semi-empirical mathematical model utilising as input values the daily sulphate, nitrate and ammonium measurements at the EMEP stations (Co-operative programme for monitoring and evaluation of the long-range transmission of air pollutants in Europe). The influence of primary vehicular emissions from the nearest roads was evaluated using a roadside emission and dispersion model, CAR-FMI, in combination with a meteorological pre-processing model, MPP-FMI. The contribution of non-exhaust particulate matter emissions (including resuspension of particulate matter from road surfaces) was estimated simply to be directly proportional to the concentrations originating from primary vehicular emissions. Comparison of the predicted results and measurements yields information on the relative importance of various source categories of the measured concentrations of PM_2.5. The regionally and long-range transported contribution, the primary and non-exhaust vehicular emissions, and other sources were estimated to contribute on average 41±6%, 33±6% and 26±7% of the observed PM_2.5 concentrations, respectively. The model presented could also be applied in other European cities for analysing the source contributions to measured fine particulate matter concentrations.     

Fugitive Dust Emission Source Profiles and Assessment of Selected Control Strategies for Particulate Matter at Gravel Processing Sites in Taiwan

Abstract

Particles emitted from gravel processing sites are one contributor to worsening air quality in Taiwan. Major pollution sources at gravel processing sites include gravel and sand piles, unpaved roads, material crushers, and bare ground. This study analyzed fugitive dust emission characteristics at each pollution source using several types of particle samplers, including total suspended particulates (TSP), suspended particulate (PM₁₀), fine suspended particulate (PM_2.5), particulate sizer, and dust-fall collectors. Furthermore, silt content and moisture in the gravel were measured to develop particulate emission factors. The results showed that TSP (<100 µm) concentrations at the boundary of gravel sites ranged from 280 to 1290 µg/m³, which clearly exceeds the Taiwan hourly air quality standard of 500 µg/m³. Moreover, PM₁₀ concentrations, ranging from 135 to 550 µg/m³, were also above the daily air quality standard of 125 µg/m³ and approximately 1.2 and 1.5 times the PM_2.5 concentrations, ranging from 105 to 470 µg/m³. The size distribution analysis reveals that mass mean diameter and geometric standard deviation ranged from 3.2 to 5.7 µm and from 2.82 to 5.51, respectively. In this study, spraying surfactant was the most effective control strategy to abate windblown dust from unpaved roads, having a control efficiency of approximately 93%, which is significantly higher than using paved road strategies with a control efficiency of approximately 45%. For paved roads, wet suppression provided the best dust control efficiencies ranging from 50 to 83%. Re-vegetation of disturbed ground had dust control efficiencies ranging from 48 to 64%.     

The measurement of roadway PM10 emission rates using atmospheric tracer ratio techniques

In this work, stationary and mobile point source tracer release techniques have been used to determine PM₁₀ emission rates from four-lane commercial/residential paved roads under sanded and unsanded conditions, and from unpaved roads relative to site-specific vehicular and ambient parameters. Measured street (4 + lanes; ? 10,000 vehicles per day) emission factors for unsanded and sanded roads were 40 and 20% lower, respectively, than the EPA approved reference value. The sanded road emission factor was approximately 40% higher than that for the unsanded road. These results indicate a consistent relationship between PM₁₀ and relative humidity under unsanded conditions. There is some evidence to suggest that street sweeping has a measurable effect on PM,, emission reduction during periods of low relative humidity (i.e. ? 30%). Within the constraints imposed by the variable experimental conditions, the emission factors determined for unpaved roads agreed reasonably well with the unpaved road empirical formula. Limited correlations were observed with ambient meteorological parameters. The capability of the “upwind-dowiawind” concentration modeling method to predict accurate emission was tested using a Gaussian dispersion model (SIMFLUX). Predictions agreed well with the experimentally determined emission factors.     

Near-road air pollution impacts of goods movement in communities adjacent to the Ports of Los Angeles and Long Beach

A mobile platform was outfitted with real-time instruments to spatially characterize pollution concentrations in communities adjacent to the Ports of Los Angeles and Long Beach, communities heavily impacted by emissions related to dieselized goods movement, with the highest localized air pollution impacts due to heavy-duty diesel trucks (HDDT). Measurements were conducted in the winter and summer of 2007 on fixed routes driven both morning and afternoon. Diesel-related pollutant concentrations such as black carbon, nitric oxide, ultrafine particles, and particle-bound polycyclic aromatic hydrocarbons were frequently elevated two to five times within 150 m downwind of freeways (compared to more than 150 m) and up to two times within 150 m downwind of arterial roads with significant amounts of diesel traffic. While wind direction was the dominant factor associated with downwind impacts, steady and consistent wind direction was not required to produce; high impacts were observed when a given area was downwind of a major roadway for any significant fraction of time. This suggests elevated pollution impacts downwind of freeways and of busy arterials are continuously occurring on one side of the road or the other, depending on wind direction. The diesel truck traffic in the area studied was high, with more than 2000 trucks per peak hour on the freeway and two- to six-hundred trucks per hour on the arterial roads studied. These results suggest that similarly-frequent impacts occur throughout urban areas in rough proportion to diesel truck traffic fractions. Thus, persons living or working near and downwind of busy roadways can have several-fold higher exposures to diesel vehicle-related pollution than would be predicted by ambient measurements in non-impacted locations.     

Evaluation and application of biomagnetic monitoring of traffic-derived particulate pollution

Inhalation of particulate pollutants below 10 μm in size (PM₁₀) is associated with adverse health effects. Here we use magnetic remanence measurements of roadside tree leaves to examine levels of vehicle-derived PM around Lancaster, UK. Leaf saturation remanence (SIRM) values exhibit strong correlation with both the SIRM and particulate mass of co-located, pumped-air samples, indicating that these leaf magnetic values are an effective proxy for ambient PM₁₀ concentrations. Biomagnetic monitoring using tree leaves can thus provide high spatial resolution data sets for assessment of particulate pollution levels at pedestrian-relevant heights. Leaf SIRM values not only increase with proximity to roads with higher traffic volumes, but are also ～100% higher at 0.3 m than at ～1.5–2 m height. Magnetic and SEM data indicate that the particle populations are dominated by spherical, iron-rich particles ～0.1–1 μm in diameter, with fewer larger, more angular, silica-rich particles. Comparison of the roadside leaf-calculated PM₁₀ concentrations with PM₁₀ concentrations predicted by a widely-used atmospheric dispersion model indicates some agreement between them. However, the model under-predicts PM₁₀ concentrations at ‘urban hotspots’ such as major–minor road junctions and traffic lights. Conversely, the model over-predicts PM₁₀ concentrations with distance from the road wherever one tree is screened by another, indicating the filtering/protective effect of roadside trees in leaf.     

Monitoring of dust emission on gravel roads: Development of a mobile methodology and examination of horizontal diffusion

Traffic-generated fugitive dust on gravel roads impairs visibility and deposits on the adjacent environment. Particulate matter smaller than 10 μm in diameter (PM₁₀) is also associated with human health problems. Dust emission strength depends on the composition of granular material, road moisture, relative humidity, local climate (precipitation, wind velocity, etc.), and vehicle characteristics.The objectives of this study were to develop a reliable and rapid mobile methodology to measure dust concentrations on gravel roads, evaluate the precision and repeatability of the methodology and correspondence with the currently used visual assessment technique. Downwind horizontal diffusion was studied to evaluate the risk of exceeding the maximum allowed particulate matter concentration in ambient air near gravel roads according to European Council Directive [European Council Directive 1999/30/EC of 22 April 1999 relating to limit values for sulphur dioxide, nitrogen dioxide and oxides of nitrogen, particulate matter and lead in ambient air. Official Journal of the European Communities. L163/41.].A TSI DustTrak Aerosol Monitor was mounted on an estate car travelling along test sections treated with various dust suppressants. Measured PM₁₀ concentrations were compared to visual assessments performed at the same time. Airborne particles were collected in filters mounted behind the vehicle to compare the whole dust fraction with the PM₁₀ concentration. For measuring the horizontal diffusion, DustTraks were placed at various distances downwind of a dusty road section.The mobile methodology was vehicle and speed dependent but not driver dependent with pre-specified driving behaviours. A high linear correlation between PM₁₀ of different vehicles makes relative measurements of dust concentrations possible. The methodology gives continuous data series, mobility, and easy handling and provides fast, reliable and inexpensive measurements for estimating road conditions to make road maintenance more efficient.Good correlations between measured PM₁₀-values, visually assessed dust generation and dust collected in filters were obtained. PM₁₀ seems to be correlated to the whole dust fraction that impairs visibility on gravel roads.A decay in PM₁₀ concentration as a function of distance from the road was observed. Measured particles principally did not travel further than 45 m from the road. The risk of exceeding the PM₁₀ concentration stated in the EC-directive seems small.     

PM<Subscript>10</Subscript> source apportionment in the surroundings of the San Vicente del Raspeig cement plant complex in southeastern Spain

Introduction  

The concentrations of trace metals, ionic species, and carbonaceous components in PM₁₀ (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.     

Mesoscale modeling of wintertime particulate matter episodes in eastern Washington, USA

The Spokane, Washington area is classified as a non-attainment area for the 24-h PM₁₀ standard due to a history of high particulate matter concentrations. A Eulerian regional air quality model (CALMET/CALGRID) has been used to characterize the emission, transport and dispersion of PM₁₀ and PM_2.5 in Spokane. Observations from a residential site (Rockwood, RW) and an industrial site (Crown Zellerbach, CZ), spanning July 1994–August 1996 were used to evaluate the current emission inventory. Two major tasks were devised to conduct the objectives of this investigation. First, a simple and efficient urban dispersion model (WYNDValley) was used to simulate important episodes characterized by the highest PM₁₀ and PM_2.5 concentrations. The selected episodes included four days with wet conditions for which no roads would have been emitting and seven days with dry conditions for which roads would emit. In the second step, a single road-emitting event was selected from the previous predicted results for further analysis using the Eulerian regional air quality model to examine the emission inventory. The urban and regional models predicted the observed concentration distributions reasonably well for the source emissions inventoried in Spokane. The mass concentrations of PM₁₀ were well predicted for the roads emitting case examined by both models indicating that the emission inventory based primarily upon area sources including roads is reasonably well characterized, at least at the RW site. The area sources around CZ are less well characterized, so that the PM₁₀ concentrations are underpredicted at CZ. The models appear unable to reach an equilibrium mass balance status at the beginning of the simulation, and the urban model seems unable to properly resolve the nocturnal boundary layer.     

Characteristics of vertical profiles and sources of PM2.5, PM10 and carbonaceous species in Beijing

In August 2003 during the anticipated month of the 2008 Beijing Summer Olympic Games, we simultaneously collected PM₁₀ and PM_2.5 samples at 8, 100, 200 and 325 m heights up a meteorological tower and in an urban and a suburban site in Beijing. The samples were analysed for organic carbon (OC) and elemental carbon (EC) contents. Particulate matter (PM) and carbonaceous species pollution in the Beijing region were serious and widespread with 86% of PM_2.5 samples exceeding the daily National Ambient Air Quality Standard of the USA (65 μg m⁻³) and the overall daily average PM₁₀ concentrations of the three surface sites exceeding the Class II National Air Quality Standard of China (150 μg m⁻³). The maximum daily PM_2.5 and PM₁₀ concentrations reached 178.7 and 368.1 μg m⁻³, respectively, while those of OC and EC reached 22.2 and 9.1 μg m⁻³ in PM_2.5 and 30.0 and 13.0 μg m⁻³ in PM₁₀, respectively. PM, especially PM_2.5, OC and EC showed complex vertical distributions and distinct layered structures up the meteorological tower with elevated levels extending to the 100, 200 and 300 m heights. Meteorological evidence suggested that there exist fine atmospheric layers over urban Beijing. These layers were featured by strong temperature inversions close to the surface (<50 m) and more stable conditions aloft. They enhanced the accumulation of pollutants and probably caused the complex vertical distributions of PM and carbonaceous species over urban Beijing. The built-up of PM was accompanied by transport of industrial emissions from the southwest direction of the city. Emissions from road traffic and construction activities as well as secondary organic carbon (SOC) are important sources of PM. High OC/EC ratios (range of 1.8–5.1 for PM_2.5 and 2.0–4.3 for PM₁₀) were found, especially in the higher levels of the meteorological tower suggesting there were substantial productions of SOC in summer Beijing. SOC is estimated to account for at least 33.8% and 28.1% of OC in PM_2.5 and PM₁₀, respectively, with higher percentages at the higher levels of the tower.     

The impact of transportation control measures on emission reductions during the 2008 Olympic Games in Beijing,China

Traffic congestion and air pollution were two major challenges for the planners of the 2008 Olympic Games in Beijing. The Beijing municipal government implemented a package of temporary transportation control measures during the event. In this paper, we report the results of a recent research project that investigated the effects of these measures on urban motor vehicle emissions in Beijing. Bottom–up methodology has been used to develop grid-based emission inventories with micro-scale vehicle activities and speed-dependent emission factors. The urban traffic emissions of volatile organic compounds (VOC), carbon monoxide (CO), nitrogen oxides (NO_x) and particulate matter with an aerodynamic diameter of 10 μm or less (PM₁₀) during the 2008 Olympics were reduced by 55.5%, 56.8%, 45.7% and 51.6%, respectively, as compared to the grid-based emission inventory before the Olympics. Emission intensity was derived from curbside air quality monitoring at the North 4th Ring Road site, located about 7 km from the National Stadium. Comparison between the emission intensity before and during the 2008 Olympics shows a reduction of 44.5% and 49.0% in daily CO and NO_x emission from motor vehicles. The results suggest that reasonable traffic system improvement strategies along with vehicle technology improvements can contribute to controlling total motor vehicle emissions in Beijing after the Olympic Games.     

Estimating PM10 air concentrations from dust storms in Iraq,Kuwait and Saudi Arabia

A model for the emission of PM₁₀ dust has been constructed using the concept of a threshold friction velocity which is dependent on surface roughness. Surface roughness in turn was correlated with geomorphology or soil properties for Kuwait, Iraq, part of Syria, Saudi Arabia, the United Arab Emirates and Oman. The PM₁₀ emission algorithm was incorporated into a Lagrangian transport and dispersion model. PM₁₀ air concentrations were computed from August 1990 through August 1991. The model predicted about the right number of dust events over Kuwait (events occur 18% of the time). The model results agreed quantitatively with measurements at four locations in Saudi Arabia and one in Kuwait for one major dust event (>1000 μg/m³). However, for smaller scale dust events (200–1000 μg/m³), especially at the coastal sampling locations, the model substantially over-predicted the air concentrations. Part of the over-prediction was attributed to the entrainment of dust-free air by the sea breeze, a flow feature not represented by the large-scale gridded meteorological data fields used in the model computation. Another part of the over-prediction was the model's strong sensitivity to threshold friction velocity and the surface soil texture coefficient (the soil emission factor), and the difficulty in accurately representing these parameters in the model. A comparison of the model predicted PM₁₀ spatial pattern with the TOMS satellite aerosol index (AI) yielded a spatial pattern covering a major portion of Saudi Arabia that was quite similar to the observed AI pattern.     

Responses of future air quality to emission controls over North Carolina,Part II: Analyses of future-year predictions and their policy implications

The MM5/CMAQ system evaluated in Part I paper is applied to study the impact of emission control on future air quality over North Carolina (NC). Simulations are conducted at a 4-km horizontal grid resolution for four one-month periods, i.e., January, June, July, and August 2009 and 2018. Simulated PM_2.5 in 2009 and 2018 show distribution patterns similar to those in 2002. PM_2.5 concentrations over the whole domain in January and July reduced by 5.8% and 23.3% in 2009 and 12.0% and 35.6% in 2018, respectively, indicating that the planned emission control strategy has noticeable effects on PM_2.5 reduction in this region, particularly in summer. More than 10% and 20% of 1-h and 8-h O₃ mixing ratios are reduced in July 2009 and 2018, respectively, demonstrating the effectiveness of emission control for O₃ reduction in summer. However, O₃ mixing ratios in January 2009 and 2018 increase by more than 5% because O₃ chemistry is VOC-limited in winter and the effect of NO_x reduction dominates over that of VOC reduction under such a condition. The projected emission control simulated at 4-km will reduce the number of sites in non-attainment for max 8-h O₃ from 49 to 23 in 2009 and to 1 in 2018 and for 24-h average PM_2.5 from 1 to 0 in 2009 and 2018 based on the latest 2008 O₃ and 2006 PM_2.5 standards. The variability in model predictions at different grid resolutions contributes to 1–3.8 ppb and 1–7.9 μg m^?3 differences in the projected future-year design values for max 8-h O₃ and 24-h average PM_2.5, respectively.     

Sources and characteristics of carbonaceous aerosol in two largest cities in Pearl River Delta Region,China

PM_2.5 samples were collected at five sites in Guangzhou and Hong Kong, Pearl River Delta Region (PRDR), China in both summer and winter during 2004–2005. Elemental carbon (EC) and organic carbon (OC) in these samples were measured. The OC and EC concentrations ranked in the order of urban Guangzhou > urban Hong Kong > background Hong Kong. Total carbonaceous aerosol (TCA) contributed less to PM_2.5 in urban Guangzhou (32–35%) than that in urban Hong Kong (43–57%). The reason may be that, as an major industrial city in South China, Guangzhou would receive large amount of inorganic aerosol from all kinds of industries, however, as a trade center and seaport, urban Hong Kong would mainly receive organic aerosol and EC from container vessels and heavy-duty diesel trucks. At Hong Kong background site Hok Tsui, relatively lower contribution of TCA to PM_2.5 may result from contributions of marine inorganic aerosol and inland China pollutant. Strong correlation (R²=0.76–0.83) between OC and EC indicates minor fluctuation of emission and the secondary organic aerosol (SOA) formation in urban Guangzhou. Weak correlation between OC and EC in Hong Kong can be related to the impact of the long-range transported aerosol from inland China. Averagely, secondary OC (SOC) concentrations were 3.8–5.9 and 10.2–12.8 μg m⁻³, respectively, accounting for 21–32% and 36–42% of OC in summer and winter in Guangzhou. The average values of 4.2–6.8% for SOA/ PM_2.5 indicate that SOA was minor component in PM_2.5 in Guangzhou.     

Road Dust Resuspension in the Vicinity of Limestone Quarries in Jordan

Abstract

Many areas in Jordan suffer from elevated levels of coarse particulate matter (PM₁₀). One potentially significant source of the observed PM is the resuspension of road dust in the vicinity of limestone quarries. To obtain data to assess the impact from this source, PM₁₀ road dust resus-pension factors near Abusiiah, a town to the north east of Amman surrounded by many quarries and brick factories, were measured. Measurements included PM₁₀ mass, particle size distributions, wind speed, and wind direction.The results showed that PM₁₀ concentrations could be as high as 600 µg/m³, and most of the airborne PM is in the coarse fraction. Loading trucks play a major role in resus-pending road dust, with an observed PM₁₀ emission rate of >6000 mg/km.     

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.     

The impact of wood smoke on ambient PM2.5 in northern Rocky Mountain valley communities

During the winters of 2006/2007 and 2007/2008, PM_2.5 source apportionment programs were carried out within five western Montana valley communities. Filter samples were analyzed for mass and chemical composition. Information was utilized in a Chemical Mass Balance (CMB) computer model to apportion the sources of PM_2.5. Results showed that wood smoke (likely residential woodstoves) was the major source of PM_2.5 in each of the communities, contributing from 56% to 77% of the measured wintertime PM_2.5. Results of ¹⁴C analyses showed that between 44% and 76% of the measured PM_2.5 came from a new carbon (wood smoke) source, confirming the results of the CMB modeling. In summary, the CMB model results, coupled with the ¹⁴C results, support that wood smoke is the major contributor to the overall PM_2.5 mass in these rural, northern Rocky Mountain airsheds throughout the winter months.     

Exposure of PM2.5 and EC from diesel and gasoline vehicles in communities near the Ports of Los Angeles and Long Beach,California

The Ports of Los Angeles and Long Beach are the entry point for almost half of all cargo containers entering the United States. The use of diesel trucks to move Port-related goods has raised significant public health concerns associated with black carbon and other air pollutants. It is difficult to reliably estimate people's exposure to vehicle-related pollutants due to the narrow impact zone of traffic, usually within 200–300 m downwind of major roadways. Previous studies suffer from the lack of traffic count data on surface streets and the lack of neighborhood-level population data. We examined seasonal and annual average exposures of particulate matter less than 2.5 μm (PM_2.5) and elemental carbon (EC) at a neighborhood scale for communities heavily impacted by diesel trucks near these ports. We assembled a traffic-activity database that distinguishes gasoline and diesel vehicles on both freeways and surface streets, by consolidating information from several sources, including our own field measurements. The CALINE4 model was used to estimate residential exposure of the study population to PM_2.5 and EC. Parcel property data were used to allocate Census block group (BG) population to increase spatial resolution. The annual average PM_2.5 and EC exposure due to local traffic was 3.8 and 0.4 μg m^?3, respectively. On average, surface streets contributed a little more than freeways (55% vs. 45% for EC and 57% and 43% for PM_2.5). Light-duty vehicles contributed significantly more than heavy-duty trucks for PM_2.5 (61% vs. 39%), but slightly less than heavy-duty trucks for EC (49% vs. 51%). Community mean population exposure was similar using parcel, census block, and BG population data, but extreme values and standard deviations varied significantly at different spatial resolutions. The intake fraction for the study population was in the range of 1.0–2.2 × 10^?5 by vehicle type, roadway type, and season.     

Spatial variability of carbonaceous aerosols and associated source tracers in two cites in the Midwestern United States

Semi-continuous and 24-h averaged measurements of fine carbonaceous aerosols were made concurrently at three sites within each of two U.S. Midwestern Cities; Detroit, Michigan and Cleveland, Ohio; during two, one-month intensive campaigns conducted in July of 2007 and January & February of 2008. A comparison of 24-h measurements revealed substantial intra-urban variability in carbonaceous aerosols consistent with the influence of local sources, and excesses in both PM_2.5 organic carbon (OC) and elemental carbon (EC) were identified at individual sites within each city. High time-resolved black carbon (BC) measurements indicated that elemental carbon concentrations were higher at sites adjacent to freeways and busy surface streets, and temporal patterns suggested that excess EC at sites adjacent to freeways was dominated by mobile source emissions while excesses in EC away from traffic corridors was dominated by point/area source emissions. The site-to-site variability in OC concentrations was approximately 7% within the neighborhood scale (0.5–4 km) and between 4 and 27% at the urban scale (4–100 km). In contrast, measurements of organic source tracers, in conjunction with a Chemical Mass Balance (CMB) source-apportionment model, indicated that the spatial variation in the contribution of both mobile and stationary sources to PM_2.5 OC often exceeded the variation in OC mass concentration by a factor of 3 or more. Markers for mobile sources, biomass smoke, natural gas, and coal combustion differed by as much as 60% within the neighborhood scale and by greater than 200% within the urban scale. The observations made during this study suggest that the urban excess of carbonaceous aerosols is much more complex than has been previously reported and that a more rigorous, source-oriented approach should be taken in order to assess the risk associated with exposure to carbonaceous aerosols within the industrialized environments of the Midwestern United States.     

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.