Validity of residential traffic intensity as an estimate of long-term personal exposure to traffic-related air pollution among adults

The validity of traffic intensity near the home as an estimate for the personal long-term exposure to traffic-related air pollution in an adult population was tested. Personal and near-home outdoor exposure to PM2.5, soot, NO, NO2, and NOx was monitored four to five times during 48 h periods in older adults. A group of 23 participants lived in high traffic intensity streets (>10000 vehicles/(24 h)), and 22 lived in low traffic intensity streets. The relation between average personal exposure and traffic intensity at the residential address was explored by taking indoor sources into account. Large differences in the measured outdoor concentrations between locations in high traffic and low traffic intensity streets were found for soot (68%), NO (127%), and NOx (35%). Differences were smaller for PM2.5 (14%) and NO2 (22%). Slightly elevated ratios were found for personal exposure to soot (1.15; 95% confidence interval (CI), 1.01-1.30)when comparing adults living in high traffic intensity streets with adults living in low traffic intensity streets. For NO, increased personal exposure (1.16) was seen for the same comparison, but this difference failed to reach statistical significance (CI, 0.80-1.66). Traffic intensity on the street of residence predicted personal exposure to soot but not to PM2.5 or nitrogen oxides. Traffic intensity may not correlate well to personal exposure and accordingly substantial misclassification of exposure may occur when traffic intensity is used as an exposure indicator in epidemiological studies. Time spent in traffic and spending time outdoors were associated with increased personal exposure of soot and PM2.5, but not NOx.     

Estimation of outdoor NO(x), NO(2), and BTEX exposure in a cohort of pregnant women using land use regression modeling

Land use regression (LUR) has been successfully used to assess the intraurban variability of air pollution. In the INMA (Environment and Childhood) Study, ambient nitrogen oxides (NO(x) and NO(2)) and aromatic hydrocarbons (BTEX) were measured at 57 sampling sites in Sabadell (northeast Spain). Multiple regression models were developed to predict residential outdoor concentrations in a cohortof pregnantwomen (n = 657), using geographic data as predictor variables. The models accounted for 68 and 69% of the variance in NO(x) and NO(2) levels, respectively, with four predictor variables (altitude, land coverage, and two road length indicators). These percentages of explained variability could be further improved by replacing the two road length indicators with an ordinal indicator (road type). To our knowledge, this is the first study using LUR to assess the intraurban variability of BTEX in Europe, with a model including altitude and source-proximity variables that explained 74% of the variance in BTEX levels. These models will be used to study the association between prenatal exposure to air pollution and adverse pregnancy outcomes and early childhhod effects in the cohort.     

Determination of the sources of indoor PM2.5 in Amsterdam and Helsinki

Daily PM2.5 samples were repeatedly collected (1-8 times) in the homes of elderly nonsmoking individuals with coronary heart disease in Amsterdam, The Netherlands (33 individuals) and Helsinki, Finland (44 individuals). Sources of indoor PM2.5 were evaluated using a two-way multilinear engine model. Because the indoor elemental data lacked a traffic marker, separation of traffic related PM was attempted by combining the indoor data with fixed site outdoor data that also contained NO. Six outdoor sources, including long-range transport (LRT), urban mixture, oil combustion, traffic, sea-salt, and soil were identified, and three indoor sources were resolved: resuspension, potassium-rich and copper-rich sources. The average contribution of the indoor factors was 6% (1.1 microg m(-3)) and 22% (2.4 microg m(-3)) in Amsterdam and Helsinki, respectively. The highest longitudinal correlations between source-specific outdoor and indoor PM2.5 concentrations were found for LRT and urban mixture; the median R was above 0.6 for most sources. The longitudinal correlations were lower in Helsinki than in Amsterdam. Indoor-generated PM2.5 was not related to ambient concentrations. We conclude that using outdoor and indoor data together improved the source apportionment of indoor PM2.5. The results support the use of fixed site outdoor measurements in epidemiological time-series studies on outdoor air pollution.     

Redistribution of traffic related air pollution associated with a new road tunnel

The aim of this study was to assess the effect of a new road tunnel on the concentration and distribution of traffic-related air pollution (TRAP), specifically nitrogen dioxide (NO(2)) and particulate matter (PM), and to determine its relationship to change in traffic flow. We used continuously recorded data from four monitoring stations at nonroadside locations within the study area and three regional monitors outside the area. The four monitors in the study area were in background locations where smaller pollutant changes were expected compared with changes near the bypassed main road. We also deployed passive samplers to assess finer spatial variability in NO(2) including application of a land use regression model (LUR). The study was conducted from 2006 to 2008. Analysis of the continuously recorded data showed that the tunnel intervention did not lead to consistent reductions in NO(2) or PM over the wider study area. However, there were significant decreases in NO(2), NO(x), and PM(10) in the eastern section of the study area. Analysis of passive sampler data indicated that the greatest reductions in NO(2) concentrations occurred within 100 m of the bypassed main road. The LUR model also demonstrated that changes in NO(2) were most marked adjacent to the bypassed main road. These findings support the use of methods that highlight fine spatial variability in TRAP and demonstrate the utility of traffic interventions in reducing air pollution exposures for populations living close to main roads.     

Application of land use regression to estimate long-term concentrations of traffic-related nitrogen oxides and fine particulate matter

Land use regression (LUR) is a promising technique for predicting ambient air pollutant concentrations at high spatial resolution. We expand on previous work by modeling oxides of nitrogen and fine particulate matter in Vancouver, Canada, using two measures of traffic. Systematic review of historical data identified optimal sampling periods for NO and N02. Integrated 14-day mean concentrations were measured with passive samplers at 116 sites in the spring and fall of 2003. Study estimates for annual mean NO and NO2 ranged from 5.4-98.7 and 4.8-28.0 ppb, respectively. Regulatory measurements ranged from 4.8-29.7 and 9.0-24.1 ppb and exhibited less spatial variability. Measurements of particle mass concentration (PM2.5) and light absorbance (ABS) were made at a subset of 25 sites during another campaign. Fifty-five variables describing each sampling site were generated in a Geographic Information System (GIS) and linear regression models for NO, NO2, PM2.5, and ABS were built with the most predictive covariates. Adjusted R(2) values ranged from 0.39 to 0.62 and were similar across traffic metrics. Resulting maps show the distribution of NO to be more heterogeneous than that of NO2, supporting the usefulness of this approach for assessing spatial patterns of traffic-related pollution.     

Seasonal and diurnal variation of PM2.5 apparent particle density in urban air in Augsburg, Germany

The apparent particle density of particulate matter with aerodynamic diameter < 2.5 microm (rho2.5) was determined at an urban site in Augsburg, Germany and its correlation with chemical composition and meteorological conditions was investigated. rho2.5 showed strong day-to-day variation from 1.05 to 2.36 g cm(-3) (5 to 95% percentile), and nearly 64% of the daily variability could be explained by a multiple variable regression model. A minimum in the morning and afternoon (about 1.5 g cm(-3)), and a maximum (near 1.8 g cm(-3)) during midday was observed. The minima represent fresh primary aerosol emissions, which were related to traffic soot particles with low density due to their agglomerate structure, especially observed in the early morning hours of weekdays. The maximum is likely due to increased secondary particle production and the presence of more aged particles with the built-up of the convectively mixed boundary layer. rho2.5 has the potential to serve as a crude tracer for chemical composition and atmospheric processing and might play an important role when considering the associations between health effects and ambient particles.     

Comparison of black smoke and PM2.5 levels in indoor and outdoor environments of four European cities

Recent studies on separated particle-size fractions highlight the health significance of particulate matter smaller than 2.5 microm (PM2.5), but gravimetric methods do not identify specific particle sources. Diesel exhaust particles (DEP) contain elemental carbon (EC), the dominant light-absorbing substance in the atmosphere. Black smoke (BS) is a measure for light absorption of PM and, thus, an alternative way to estimating EC concentrations, which may serve as a proxy for diesel exhaust emissions. We analyzed PM2.5 and BS data collected within the EXPOLIS study (Air Pollution Exposure Distribution within Adult Urban Populations in Europe) in Athens, Basel, Helsinki, and Prague. 186 indoor/outdoor filter pairs were sampled and analyzed. PM2.5 and BS levels were lowest in Helsinki, moderate in Basel, and remarkably higher in Athens and Prague. In each city, Spearman correlation coefficients of indoor versus outdoor were higher for BS (range rspearman: 0.57-0.86) than for PM2.5 (0.05-0.69). In a BS linear regression model (all data), outdoor levels explained clearly more of indoor variation (86%) than in the corresponding PM2.5 model (59%). In conclusion, ambient BS seizes a health-relevant fraction of fine particles to which people are exposed indoors and outdoors and exposure to which can be assessed by monitoring outdoor concentrations. BS measured on PM2.5 filters can be recommended as a valid and cheap additional indicator in studies on combustion-related air pollution and health.     

Integrating address geocoding, land use regression, and spatiotemporal geostatistical estimation for groundwater tetrachloroethylene

Geographic information systems (GIS) based techniques are cost-effective and efficient methods used by state agencies and epidemiology researchers for estimating concentration and exposure. However, budget limitations have made statewide assessments of contamination difficult, especially in groundwater media. Many studies have implemented address geocoding, land use regression, and geostatistics independently, but this is the first to examine the benefits of integrating these GIS techniques to address the need of statewide exposure assessments. A novel framework for concentration exposure is introduced that integrates address geocoding, land use regression (LUR), below detect data modeling, and Bayesian Maximum Entropy (BME). A LUR model was developed for tetrachloroethylene that accounts for point sources and flow direction. We then integrate the LUR model into the BME method as a mean trend while also modeling below detects data as a truncated Gaussian probability distribution function. We increase available PCE data 4.7 times from previously available databases through multistage geocoding. The LUR model shows significant influence of dry cleaners at short ranges. The integration of the LUR model as mean trend in BME results in a 7.5% decrease in cross validation mean square error compared to BME with a constant mean trend.     

Using time- and size-resolved particulate data to quantify indoor penetration and deposition behavior

Because people spend approximately 85-90% of their time indoors, it is widely recognized that a significant portion of total personal exposures to ambient particles occurs in indoor environments. Although penetration efficiencies and deposition rates regulate indoor exposures to ambient particles, few data exist on the levels or variability of these infiltration parameters, in particular for time- and size-resolved data. To investigate ambient particle infiltration, a comprehensive particle characterization study was conducted in nine nonsmoking homes in the metropolitan Boston area. Continuous indoor and outdoor PM2.5 and size distribution measurements were made in each of the study homes over weeklong periods. Data for nighttime, nonsource periods were used to quantify infiltration factors for PM2.5 as well as for 17 discrete particle size intervals between 0.02 and 10 microns. Infiltration factors for PM2.5 exhibited large intra- and interhome variability, which was attributed to seasonal effects and home dynamics. As expected, minimum infiltration factors were observed for ultrafine and coarse particles. A physical-statistical model was used to estimate size-specific penetration efficiencies and deposition rates for these study homes. Our data show that the penetration efficiency depends on particle size as well as home characteristics. These results provide new insight on the protective role of the building shell in reducing indoor exposures to ambient particles, especially for tighter (e.g., winterized) homes and for particles with diameters greater than 1 micron.     

Validation of a spatiotemporal land use regression model incorporating fixed site monitors

Land use regression (LUR) has been widely adopted as a method of describing spatial variation in air pollutants; however, traditional LUR methods are not suitable for characterizing short-term or time-variable exposures. Our aim was to develop and validate a spatiotemporal LUR model for use in epidemiological studies examining health effects attributable to time-variable air pollution exposures. A network of 42 NO(2) passive samplers was deployed for 12 two week periods over three years. A mixed effects model was tested using a combination of spatial predictors, and readings from fixed site continuous monitors, in order to predict NO(2) values for any two week period over three years in the defined study area. The final model, including terms based on traffic density at 50 and 150 m, population density within 500 m, commercial land use area within 750 m, and NO(2) concentrations at a central fixed site monitor, explained over 80% of the overall variation in NO(2) concentrations. We suggest that such a model can be used to study the association between variable air pollutant exposures and health effects in epidemiological studies.     

Characteristics of nucleation and growth events of ultrafine particles measured in Rochester, NY

Number concentrations and size distributions of particles in the size range of 0.010-0.500 microm were measured in Rochester, NY, from December 2001 to December 2002. The relationships between the number concentrations, gaseous pollutants, and meteorological parameters were examined during particle nucleation events. More than 70% of measured total number concentration was associated with ultrafine particles (UFP, 0.011-0.050 microm). Morning nucleation events typically peaking UFP number concentrations at around 08:00 were apparent in winter months with CO increases. These particles appear to be formed following direct emissions from motorvehicles during morning rush hour. There were also often observed increases in this smaller-sized range particles in the late afternoon during the afternoon rush hour, particularly in winter when the mixing heights remain lowerthan in summer. Strong afternoon nucleation events (> 30,000 cm(-3)) peaking at around 13: 00 were more likely to occur in spiring and summer months. During the prominent nucleation events, peaks of SO2 were strongly associated with the number concentrations of UFP, whereas there were no significant correlations between these events and PM2.5 and CO. Increased SO2 concentrations were observed when the wind direction was northwesterly where three SO2 sources were located. It is hypothesized that UFP formed during the events are sulfuric acid and water from the oxidation of SO2. There were also a more limited number of nucleation events followed by particle growth up to approximately 0.1 microm over periods of up to 18 h. The nucleation and growth events tended to be common in spring months especially in April.     

Estimating ground-level PM2.5 in the eastern United States using satellite remote sensing

An empirical model based on the regression between daily PM2.5 (particles with aerodynamic diameters of less than 2.5 microm) concentrations and aerosol optical thickness (AOT) measurements from the multiangle imaging spectroradiometer (MISR) was developed and tested using data from the eastern United States during the period of 2001. Overall, the empirical model explained 48% of the variability in PM2.5 concentrations. The root-mean-square error of the model was 6.2 microg/m3 with a corresponding average PM2.5 concentration of 13.8 microg/m3. When PM2.5 concentrations greater than 40 microg/m3 were removed, model results were shown to be unbiased estimators of observations. Several factors, such as planetary boundary layer height, relative humidity, season, and other geographical attributes of monitoring sites, were found to influence the association between PM2.5 and AOT. The findings of this study illustrate the strong potential of satellite remote sensing in regional ambient air quality monitoring as an extension to ground networks. With the continual advancement of remote sensing technology and global data assimilation systems, AOT measurements derived from satellite remote sensors may provide a cost-effective approach as a supplemental source of information for determining ground-level particle concentrations.     

Chemical characterization and source apportionment of fine and coarse particulate matter inside the refectory of Santa Maria Delle Grazie Church, home of Leonardo Da Vinci's "Last Supper"

The association between exposure to indoor particulate matter (PM) and damage to cultural assets has been of primary relevance to museum conservators. PM-induced damage to the "Last Supper" painting, one of Leonardo da Vinci's most famous artworks, has been a major concern, given the location of this masterpiece inside a refectory in the city center of Milan, one of Europe's most polluted cities. To assess this risk, a one-year sampling campaign was conducted at indoor and outdoor sites of the painting's location, where time-integrated fine and coarse PM (PM(2.5) and PM(2.5-10)) samples were simultaneously collected. Findings showed that PM(2.5) and PM(2.5-10) concentrations were reduced indoors by 88 and 94% on a yearly average basis, respectively. This large reduction is mainly attributed to the efficacy of the deployed ventilation system in removing particles. Furthermore, PM(2.5) dominated indoor particle levels, with organic matter as the most abundant species. Next, the chemical mass balance model was applied to apportion primary and secondary sources to monthly indoor fine organic carbon (OC) and PM mass. Results revealed that gasoline vehicles, urban soil, and wood-smoke only contributed to an annual average of 11.2 ± 3.7% of OC mass. Tracers for these major sources had minimal infiltration factors. On the other hand, fatty acids and squalane had high indoor-to-outdoor concentration ratios with fatty acids showing a good correlation with indoor OC, implying a common indoor source.     

Physicochemical characteristics and biological activities of seasonal atmospheric particulate matter sampling in two locations of Paris

Fine particulate matter present in urban areas seems to be incriminated in respiratory disorders. The aim of this study was to relate physicochemical characteristics of PM2.5 (particulate matter collected with a 50% efficiency for particles with an aerodynamic diameter of 2.5 microm) to their biological activities toward a bronchial epithelial cell line 16-HBE. Two seasonal sampling campaigns of particles were realized, respectively, in a kerbside and an urban background station in Paris. Sampled-PM2.5 mainly consist of particles with a size below 1 microm and are mainly composed of soot as assessed by analytical scanning electron microscopy. The different PM2.5 samples contrasted in their PAH content, which was the highest in the kerbside station in winter, as well as in their metal content. Kerbside station samples were characterized by the highest Fe and Cu content, which appears correlated to their hydroxyl radical generating properties measured by electron paramagnetic resonance. Particles were compared by their capacity to induce cytotoxicity, intracellular ROS production, and proinflammatory cytokine release (GM-CSF and TNF-alpha). At a concentration of 10 microg/cm2, all samples induced peroxide production and cytokine release to the similar extent in the absence of cytotoxicity. In conclusion, whereas the PM2.5 samples differ by their PAH and metal composition, they induce the same biological responses likely either due to components bioavailability and/ or interactions between PM components.     

Factors influencing mobile source particulate matter emissions-to-exposure relationships in the Boston urban area

Benefit-cost and regulatory impact analyses often use atmospheric dispersion models with coarse resolution to estimate the benefits of proposed mobile source emission control regulations. This approach may bias health estimates or miss important intra-urban variability for primary air pollutants. In this study, we estimate primary fine particulate matter (PM2.5) intake fractions (iF; the fraction of a pollutant emitted from a source that is inhaled by the population) for each of 23 398 road segments in the Boston Metro Core area to evaluate the potential for intra-urban variability in the emissions-to-exposure relationship. We estimate iFs using the CAL3QHCR line source model combined with residential populations within 5000 m of each road segment. The annual average values for the road segments range from 0.8 to 53 per million, with a mean of 12 per million. On average, 46% of the total exposure is realized within 200 m of the road segment, though this varies from 0 to 93% largely due to variable population patterns. Our findings indicate the likelihood of substantial intra-urban variability in mobile source primary PM2.5 iF that accounting for population movement with time, localized meteorological conditions, and street-canyon configurations would likely increase.     

Real-time prediction of size-resolved ultrafine particulate matter on freeways

Ultrafine particulate matter (UFP; diameter <0.1 μm) concentrations are relatively high on the freeway, and time spent on freeways can contribute a significant fraction of total daily UFP exposure. We model real-time size-resolved UFP concentrations in summer time on-freeway air. Particle concentrations (32 bins, 5.5 to 600 nm) were measured on Minnesota freeways during summer 2006 and 2007 ( Johnson, J. P.; Kittelson, D. B.; Watts, W. F. Environ. Sci. Technol. 2009 , 43 , 5358 - 5364 ). Here, we develop and apply two-way stratified multilinear regressions, using an approach analogous to mobile-monitoring land-use regression but using real-time meteorological and traffic data. Our models offer the strongest predictions in the 10-100 nm size range (adj-R(2): 0.79-0.89, average adj-R(2): 0.85) and acceptable but weaker predictions in the 130-200 nm range (adj-R(2): 0.41-0.62, average adj-R(2): 0.52). The aggregate model for total particle counts performs well (adj-R(2) = 0.77). Bootstrap resampling (n = 1000) indicates that the proposed models are robust to minor perturbations in input data. The proposed models are based on readily available real-time information (traffic and meteorological parameters) and can thus be exploited to offer spatiotemporally resolved prediction of UFPs on freeways within similar geographic and meteorological environments. The approach developed here provides an important step toward modeling population exposure to UFP.     

Fine (PM2.5) and coarse (PM2.5-10) particulate matter on a heavily trafficked London highway: sources and processes

A large dataset for PM2.5 and PMcoarse (PM2.5-10) concentrations monitored near a busy London highway (Marylebone Road) has been analyzed to define the factors that lead to high concentrations. The following have been highlighted as major influencing parameters: wind speed, prevailing wind direction (because of its role on the microscale dispersion within the street), the daily cycle of the atmospheric boundary layer (stable during the night/ convective and mixed during the day), and traffic density. The mainly diesel heavy-duty vehicles are the main source of fine particulate matter at Marylebone Road. In particular, lorries (trucks) dominate PM10 exhaust emissions which are mainly in the fine (<2.5 microm) size range. A strong correlation with PMcoarse suggests that the heavy-duty traffic is largely responsible for this component also. Substantial local increments in PM2.5 and PMcoarse due to traffic have been estimated and a large part of the increment in PMcoarse concentrations is inferred to arise from resuspended road dust emissions since the contribution of abrasion processes estimated from emission factors is modest. Despite the strong influence of traffic on PM concentrations measured at Marylebone Road the analysis of factors leading to the highest 5% of hourly concentrations of PM10 at Marylebone Road reveals that almost half of these events were due to building works. The other events occurred when all or most of the key factors occurred simultaneously (heavy traffic, poor dispersion, etc.). Some episodes of high PM2.5 concentrations were associated with long-range transport in which the regional PM2.5 constituted most of the local concentrations.     

Characteristics of metals in nano/ultrafine/fine/coarse particles collected beside a heavily trafficked road

Fine particles emitted from vehicles have adverse health effects because of their sizes and chemical compositions. Therefore, this study attempted to characterize the metals in nano (0.010 < Dp < 0.056 microm), ultrafine (Dp < 0.1 microm), fine (Dp < 2.5 microm), and coarse (2.5 < Dp < 10 microm) particles collected near a busy road using a microorifice uniform deposition impactor (MOUDI) and a Nano-MOUDI. The nano particles were found to contain more of traffic-related metals (Pb, Cd, Cu, Zn, Ba, and Ni) than particles of other sizes, although crustal metals accounted for over 90% of all the particulate metals. Most crustal metals, Ba, Ni, Pb, and Zn in ultrafine particles displayed Aitken modes due to their local origins. The Ag, Cd, Cr, Ni, Pb, Sb, V, and Zn were 37, 50, 28, 30, 24, 64, 38, and 22% by mass, respectively, in < 0.1-microm particles, with submicron mass median diameters (MMDs) in PM(0.01-18) (except Zn) (particularly the < 0.1-microm MMDs for Cd and Sb). These levels raise potential health issues. Particle-bound Zn was more abundant in the accumulation mode than in the nucleation/condensation mode, but the opposite was true for Ag, Cd, and Sb. The Ag, Ba, Cd, Pb, Sb, V, and Zn contents in nano particles were strongly associated with diesel fuel, while the Cu, Mn, and Sr in particles < 0.1 microm were more strongly associated with gasoline. The high content of Si in nano particles, more associated with diesel soot than with gasoline exhaust, is another health concern.     

In-cabin commuter exposure to ultrafine particles on Los Angeles freeways

Worldwide people are exposed to toxic ultrafine particles (UFP, with diameters (dp) less than 100 nm) and nanoparticles (NP, dp < 50 nm) under a variety of circumstances. To date, very limited information is available on human exposure to freshly emitted UFP and NP while traveling on major roads and freeways. We report in-cabin and outdoor measurements of particle number concentration and size distributions while driving three vehicles on Los Angeles freeways. Particle number concentrations and size distributions were measured under different vehicle ventilation settings. When the circulation fan was set to on, with substantial external air intake, outside changes in particle counts caused corresponding in-cabin changes approximately 30-60 s later, indicating an maximal air exchange rate of about 120-60 h(-1). Maximum in-cabin protection (approximately 85%) was obtained when both fan and recirculation were on. In-cabin and outdoor particle size distributions in the 7.9-217 nm range were observed to be mostly bimodal, with the primary peak occurring at 10-30 nm and the secondary at 50-70 nm. The vehicle's manufacture-installed particle filter offered an in-cabin protection of about 50% for particles in the 7-40 nm size range and 20-30% for particles in the 40 to approximately 200 nm size range. For an hour daily commute exposure, the in-vehicle microenvironment contributes approximately 10-50% of people's daily exposure to UFP from traffic.     

Platinum and palladium emissions from on-road vehicles in the Kaisermühlen Tunnel (Vienna, Austria)

Total and size-segregated Pt and Pd emission factors from on-road vehicles were measured in the Kaisermühlen Tunnel in Vienna, Austria. Aerosol sampling was performed simultaneously inside and outside the tunnel during April and May 2005. Analysis of the acid-digested aerosol samples was performed using a preconcentration procedure with subsequent on-line detection by electro-thermal atomic absorption spectrometry (ETAAS). Inside the tunnel distinctly increased Pt and Pd concentrations were found with highest levels in total suspended particulate matter samples and reduced concentrations in the size-segregated PM10 and PM2.5 samples. Emission factors were calculated from concentration differences between tunnel inside and tunnel outside samples, the distance between tunnel entrance and sampling location, the ventilation rate, and the number of vehicles passing through the tunnel. Emission rates observed for Pt ranged from 38 +/- 5.9 to 146 +/- 13 ng veh(-1) km(-1), whereas the emission factors of Pd varied between 13 +/- 2.1 and 42 +/- 4.1 ng veh(-1) km(-1). Variations in the emission rates were assumed to originate from alterations in traffic conditions. Size-segregated investigations revealed that the major part of Pt and Pd emissions were released in the coarse aerosol mode (size fraction > PM10), nevertheless a considerable fraction (approximately 12% and approximately 22% respectively) was emitted in the inhalable PM2.5 fraction.