Mass levels,crustal component and trace elements in PM10 in Palermo,Italy

Results concerning the levels and elemental compositions of daily PM₁₀ samples collected at four air quality monitoring sites in Palermo (Italy) are presented. The highest mean value of PM₁₀ concentrations (46 μg m⁻³, with a peak value of 158 μg m⁻³) was recorded at the Di Blasi urban station, and the lowest at Boccadifalco station (25 μg m⁻³), considered as a sub-urban background station. Seventeen elements (Al, As, Ba, Co, Cr, Cu, Fe, Li, Mn, Mo, Ni, Pb, Sb, Sr, U, V, Zn) were measured by ICP-MS. Al and Fe showed the highest concentrations, indicating the significant contribution of soil and resuspended mineral particles to atmospheric PM₁₀. Ba, Cr, Cu, Mn, Mo, Ni, Pb, Sb, V and Zn had higher concentrations at the three urban sampling sites than at the sub-urban background station. Besides soil-derived particles, an R-mode cluster analysis revealed a group of elements, Mo, Cu, Cr, Sb and Zn, probably related to non-exhaust vehicle emission, and another group, consisting of Ba, As and Ni, which seemed to be associated both with exhaust emissions from road traffic, and other combustion processes such as incinerators or domestic heating plants. The results also suggest that Sb, or the association Sb–Cu–Mo, offers a way of tracing road traffic emissions.     

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.     

Evaluation of particulate matter emissions from non-passenger diesel vehicles in Qatar

ABSTRACT

Road traffic is one of the main sources of particulate matter (PM) in the atmosphere. Despite its importance, there are significant challenges in the quantitative evaluation of its contribution to airborne concentrations. In order to propose effective mitigation scenarios, the proportions of PM traffic emissions, whether they are exhaust or non-exhaust emissions, should be evaluated for any given geographical location. In this work, we report on the first study to evaluate particulate matter emissions from all registered heavy duty diesel vehicles in Qatar. The study was applied to an active traffic zone in urban Doha. Dust samples were collected and characterized for their shape and size distribution. It was found that the particle size ranged from few to 600 μm with the dominance of small size fraction (less than 100 μm). In-situ elemental composition analysis was conducted for side and main roads traffic dust, and compared with non-traffic PM. The results were used for the evaluation of the enrichment factor and preliminary source apportionment. The enrichment factor of anthropogenic elements amounted to 350. The traffic source based on sulfur elemental fingerprint was almost 5 times higher in main roads compared with the samples from non-traffic locations. Moreover, PM exhaust and non-exhaust emissions (tyre wear, brake wear and road dust resuspension) were evaluated. It was found that the majority of the dust was generated from tyre wear with 33% followed by road dust resuspension (31%), brake wear (19%) and then exhaust emissions with 17%. The low contribution of exhaust PM₁₀ emissions was due to the fact that the majority of the registered vehicle models were recently made and equipped with efficient exhaust PM reduction technologies.

Implication: This study reports on the first results related to the evaluation of PM emission from all registered diesel heavy duty vehicles in Qatar. In-situ XRF elemental analysis from main, side roads as well as non-traffic dust samples was conducted. Several characterization techniques were implemented and the results show that the majority of the dust was generated from tyre wear, followed by road dust resuspension and then brake wear; whereas exhaust emissions were tremendously reduced since the majority of the registered vehicle models were recently made and equipped with efficient exhaust PM reduction technologies. This implies that policy makers should place stringent measures on old vehicle license renewals and encourage the use of metro and public transportation.     

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.     

Determination of sources of fine particles in different ambient atmospheres in South Korea using a chemical mass balance model

Abstract

To determine the sources of particulate matter less than 2.5?μm (PM_2.5 in different ambient atmospheres (urban, roadside, industrial, and rural sites), the chemical components of PM_2.5 such as ions (Cl^-, NO₃^-, SO₄^2-, NH₄⁺, Na⁺, K⁺, Ca²⁺, and Mg²⁺), carbonaceous species, and elements (Al, As, Ba, Cd, Cu, Fe, Mn, Ni, Pb, Se, V, and Zn) were measured. The average mass concentrations of PM_2.5 at the urban, roadside, industrial, and rural sites were 31.5?±?14.8, 31.6?±?22.3, 31.4?±?16.0, and 25.8?±?12.4?μg/m³, respectively. Except for secondary ammonium sulfate and ammonium nitrate, the model results showed that the traffic source (i.e., the sum of gasoline and diesel vehicle sources) was the most dominant source of PM_2.5 (17.1%) followed by biomass burning (13.8%) at the urban site. The major primary sources of PM_2.5 were consistent with the site characteristics (diesel vehicle source at the roadside site, coal-fired plants at the industrial site, and biomass burning at the rural site). Seasonal data from the urban site suggested that ammonium sulfate and ammonium nitrate were the most dominant sources of PM_2.5 during all seasons. Further, the contribution of road dust source to PM_2.5 increased during spring and fall seasons. We conclude that the determination of the major PM_2.5 sources is useful for establishing efficient control strategies for PM_2.5 in different regions and seasons.     

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.     

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.     

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.     

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.     

Traffic generated non-exhaust particulate emissions from concrete pavement: A mass and particle size study for two-wheelers and small cars

This study aimed to understand the non-exhaust (NE) emission of particles from wear of summer tire and concrete pavement, especially for two wheelers and small cars. A fully enclosed laboratory-scale model was fabricated to simulate road tire interaction with a facility to collect particles in different sizes. A road was cast using the M-45 concrete mixture and the centrifugal casting method. It was observed that emission of large particle non exhaust emission (LPNE) as well as PM₁₀ and PM_2.5 increased with increasing load. The LPNE was 3.5 mg tire⁻¹ km⁻¹ for a two wheeler and 6.4 mg tire⁻¹ km⁻¹ for a small car. The LPNE can lead to water pollution through water run-off from the roads. The contribution of the PM₁₀ and PM_2.5 was smaller compared to the LPNE particles (less than 0.1%). About 32 percent of particle mass of PM₁₀ was present below 1 μm. The number as well as mass size distribution for PM₁₀ was observed to be bi-modal with peaks at 0.3 μm and 4–5 μm. The NE emissions did not show any significant trend with change in tire pressure.     

PM2.5 concentrations in London for 2008–A modeling analysis of contributions from road traffic

We report on the analysis of contributions from road traffic emissions to fine particulate matter (PM_2.5) concentrations within London for 2008 with the OSCAR Air Quality Assessment System. A spatiotemporal evaluation of the OSCAR system has been conducted with measurements from the London air quality network (LAQN). For the predicted and measured hourly time series of concentrations at 18 sites in London, the medians of correlation, mean absolute error, index of agreement, and factor of two (FAC2) of all stations were 0.80, 4.1 μg/m³, 0.86, and 74%, respectively. Spatial evaluation of modeled and observed annual mean concentrations also showed a fairly good agreement, with all the values falling within the FAC2 range. According to model predictions, the urban increment (including the contributions from urban traffic and other urban sources) was evaluated to be on the average 18%, 33%, 39%, and 43% of the total PM_2.5 in suburban environments, in the urban background, near roads, and near busy roads, respectively. However, the highest values of the urban traffic increment can be around 50% of the total PM_2.5 concentrations near motorways and major roads. The total concentrations (including regional background, and the contributions from urban traffic and other urban sources) can therefore be almost three times the regional background. The total urban increment close to busy roads was around 7–8 μg/m³, in which the estimated traffic contribution is more than 2 μg/m³. On the average, urban traffic contributes approximately 1 μg/m³ of PM_2.5 to the urban background across London. According to modeling, approximately two-thirds of the traffic increment originated from exhaust emissions and most of the rest was due to brake and tire wear.

Implications: The urban increment and traffic contribution to the total PM_2.5 are significant and spatially heterogeneous across London. The highly heterogeneous distribution of PM_2.5 hence requires detailed modeling studies to be carried out at high spatial resolution, which can be particularly important for exposure and health impact assessment. This type of information can be used to quantify health impacts resulting from specific sources of PM_2.5 such as traffic emissions, to aid city and national decision makers when formulating pollution control strategies.     

Particle size and composition distribution analysis of automotive brake abrasion dusts for the evaluation of antimony sources of airborne particulate matter

Abrasion dusts from three types of commercially available non-steel brake pads were generated by a brake dynamometer at disk temperatures of 200, 300 and 400 °C. The number concentration of the abrasion dusts and their aerodynamic diameters (D_p) were measured by using an aerodynamic particle sizer (APS) spectrometer with high temporal and size resolution. Simultaneously, the abrasion dusts were also collected based on their size by using an Andersen low-volume sampler, and the concentrations of metallic elements (K, Ti, Fe, Cu, Zn, Sb and Ba) in the size-classified dusts were measured by ICP-AES and ICP-MS. The number distributions of the brake abrasion dusts had a peak at D_p values of 1 and 2 μm; this peak shifted to the coarse side with an increase in the disk temperature. The mass distributions calculated from the number distributions have peaks between D_p values of 3 and 6 μm. The shapes of the elemental mass distributions (Ti, Fe, Cu, Zn, Sb and Ba) in size-classified dusts were very similar to the total mass distributions of the brake abrasion dusts. These experimental results indicated that the properties of brake abrasion dusts were consistent with the characteristics of Sb-enriched fine airborne particulate matter. Based on these findings and statistical data, the estimation of Sb emission as airborne particulate matter from friction brakes was also discussed.     

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.     

Fine particulate speciation profile and emission factor of municipal solid waste incinerator established by dilution sampling method

In this study, fine particulate matter (PM_2.5) emitted from a municipal solid waste incinerator (MSWI) was collected using dilution sampling method. Chemical compositions of the collected PM_2.5 samples, including carbon content, metal elements, and water-soluble ions, were analyzed. Traditional in-stack hot sampling was simultaneously conducted to compare the influences of dilution on PM_2.5 emissions and the characteristics of the bonded chemical species. The results, established by a dilution sampling method, show that PM_2.5 and total particulate matter (TPM) emission factors were 61.6 ± 4.52 and 66.1 ± 5.27 g ton-waste^?1, respectively. The average ratio of PM_2.5/TPM is 0.93, indicating that more than 90% of PM emission from the MSWI was fine particulate. The major chemical species in PM_2.5 included organic carbon (OC), Cl^?, NH₄⁺, elemental carbon (EC) and Si, which account for 69.7% of PM_2.5 mass. OC was from the unburned carbon in the exhaust, which adsorbed onto the particulate during the cooling process. High Cl^? emission is primarily attributable to wastes containing plastic bags made of polyvinyl chloride, salt in kitchen refuse and waste biomass, and so on. Minor species that account for 0.01–1% of PM_2.5 mass included SO₄^2-, K⁺, Na, K, NO₃^?, Al, Ca²⁺, Zn, Ca, Cu, Fe, Pb, and Mg. The mean ratio of dilution method/in-stack hot method was 0.454. The contents of water-soluble ions (Cl^?, SO₄^2-, NO₃^?) were significantly enriched in PM_2.5 via gas-to-particle conversion in the dilution process. Results indicate that in-stack hot sampling would underestimate levels of these species in PM_2.5.

Implications: PM_2.5 samples from a municipal solid waste incinerator (MSWI) were collected simultaneously by a dilution sampling technique and a traditional in-stack method. PM_2.5 emission factors and chemical speciation profiles were established. Dilution sampling provides more reliable data than in-stack hot sampling. The results can be applied to estimate the PM_2.5 emission inventories of MSWI, and the source profile can be used for contribution estimate of chemical mass balance modeling.     

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.     

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

Abstract

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: on-road 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.     

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.     

Interpretation of air quality in relation to monitoring station's surroundings

This study explores the appropriateness of the locality of air monitoring stations which are meant to indicate air quality in the area. Daily variations in NO₂ and PM₁₀ concentrations at 14 monitoring stations in Hong Kong are examined. The daily variations in NO₂ at a number of background monitoring stations exhibit patterns similar to variations in traffic volume while variations in PM₁₀ concentration exhibit less discernible pattern. Principal component analysis (PCA) and cluster analysis (CA) are applied to analyse NO₂ and PM₁₀ measurements between January 2001 and December 2005. The results show that NO₂ concentrations at background stations within the urban area are highly influenced by vehicle emissions. The effect vehicle emission has on NO₂ at stations within new towns is smaller. CA results also show that variations in PM₁₀ concentrations are distinguished by the area the station is located in. PCA results show that there are two principal components (PC's) associated with variations in roadside concentration of PM₁₀. The strong influence of roadside emissions towards concentrations of NO₂ and PM₁₀ at a number of urban background stations may be due to their close proximity to busy roadways and the high density of surrounding tall buildings, which creates an enclosure that hinders dispersion of roadside emissions and results in air pollution behaviour that reflects variation in traffic.     

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.