Health effects caused by primary fine particulate matter (PM2.5) emitted from buses in the Helsinki metropolitan area, Finland

Health risk assessment of PM2.5 and PM2.5-bound trace elements in Pretoria, South Africa

Exposure to outdoor air pollutants poses a risk for both non-carcinogenic and carcinogenic respiratory disease outcomes. A standardized health risk assessment (US EPA) utilizes air quality data, body mass and breathing rates to determine potential risk. This health risk assessment study assesses the hazard quotient (HQ) for total PM_2.5 and trace elemental constituents (Br, Cl, K, Ni, S, Si, Ti and U) exposure in Pretoria, South Africa. The World Health Organization (WHO) air quality guideline (5 µg m^-3) and the yearly South African National Ambient Air Quality Standard (NAAQS) (20 µg m^-3) were the references dosages for total PM_2.5. A total of 350 days was sampled in Pretoria, South Africa. The mean total PM_2.5 concentration during the 34-month study period was 23.2 µg m^-3 (0.7-139 µg m^-3). The HQ for total PM_2.5 was 1.17, 3.47 and 3.78 for adults, children and infants. Non-carcinogenic risks for trace elements K, Cl, S and Si were above 1 for adults. Seasonally, Si was the highest during autumn for adults (1.9) and during spring for S (5.5). The HQ values for K and Cl were highest during winter. The exposure to Ni posed a risk for cancer throughout the year and for As during winters.

Integrated molecular response of exposure to traffic-related pollutants in the US trucking industry

Exposure to traffic-related pollutants, including diesel exhaust, is associated with increased risk of cardiopulmonary disease and mortality; however, the precise biochemical pathways underlying these effects are not known. To investigate biological response mechanisms underlying exposure to traffic related pollutants, we used an integrated molecular response approach that included high-resolution metabolomic profiling and peripheral blood gene expression to identify biological responses to diesel exhaust exposure. Plasma samples were collected from 73 non-smoking males employed in the US trucking industry between February 2009 and October 2010, and analyzed using untargeted high-resolution metabolomics to characterize metabolite associations with shift- and week-averaged levels of elemental carbon (EC), organic carbon (OC) and particulate matter with diameter ≤ 2.5 μm (PM2.5). Metabolic associations with EC, OC and PM2.5 were evaluated for biochemical processes known to be associated with disease risk. Annotated metabolites associated with exposure were then tested for relationships with the peripheral blood transcriptome using multivariate selection and network correlation. Week-averaged EC and OC levels, which were averaged across multiple shifts during the workweek, resulted in the greatest exposure-associated metabolic alterations compared to shift-averaged exposure levels. Metabolic changes associated with EC exposure suggest increased lipid peroxidation products, biomarkers of oxidative stress, thrombotic signaling lipids, and metabolites associated with endothelial dysfunction from altered nitric oxide metabolism, while OC exposures were associated with antioxidants, oxidative stress biomarkers and critical intermediates in nitric oxide production. Correlation with whole blood RNA gene expression provided additional evidence of changes in processes related to endothelial function, immune response, inflammation, and oxidative stress. We did not detect metabolic associations with PM2.5. This study provides an integrated molecular assessment of human exposure to traffic-related air pollutants that includes diesel exhaust. Metabolite and transcriptomic changes associated with exposure to EC and OC are consistent with increased risk of cardiovascular diseases and the adverse health effects of traffic-related air pollution.

Gene expression network analyses in response to air pollution exposures in the trucking industry

BACKGROUND

Exposure to air pollution, including traffic-related pollutants, has been associated with a variety of adverse health outcomes, including increased cardiopulmonary morbidity and mortality, and increased lung cancer risk.

METHODS

To better understand the cellular responses induced by air pollution exposures, we performed genome-wide gene expression microarray analysis using whole blood RNA sampled at three time-points across the work weeks of 63 non-smoking employees at 10 trucking terminals in the northeastern US. We defined genes and gene networks that were differentially activated in response to PM_2.5 (particulate matter ≤ 2.5 microns in diameter) and elemental carbon (EC) and organic carbon (OC).

RESULTS

Multiple transcripts were strongly associated (p_adj < 0.001) with pollutant levels (48, 260, and 49 transcripts for EC, OC, and PM_2.5, respectively), including 63 that were statistically significantly correlated with at least two out of the three exposures. These genes included many that have been implicated in ischemic heart disease, chronic obstructive pulmonary disease (COPD), lung cancer, and other pollution-related illnesses. Through the combination of Gene Set Enrichment Analysis and network analysis (using GeneMANIA), we identified a core set of 25 interrelated genes that were common to all three exposure measures and were differentially expressed in two previous studies assessing gene expression attributable to air pollution. Many of these are members of fundamental cancer-related pathways, including those related to DNA and metal binding, and regulation of apoptosis and also but include genes implicated in chronic heart and lung diseases.

CONCLUSIONS

These data provide a molecular link between the associations of air pollution exposures with health effects.

Occupational vehicle-related particulate exposure and inflammatory markers in trucking industry workers

BACKGROUND

Previous studies have suggested an association between particulate air pollution and cardiovascular disease, but the mechanism is still unclear.

OBJECTIVE

We examined the association between workplace exposure to vehicle-related particles and cardiovascular disease related systemic inflammatory markers, C-reactive protein (hs-CRP), soluble intercellular adhesion molecule-1 (sICAM-1), and interleukin-6 (IL-6) in 137 trucking terminal workers (non-drivers) in the U.S. trucking industry.

METHODS

We visited two large trucking terminals in 2009 and measured vehicle-related elemental carbon (EC), organic carbon (OC), and particulate matter with aerodynamic diameter ≤2.5µm (PM2.5), for 5 days consecutively at the main work areas. Each participant provided a blood sample and completed a health questionnaire during the sampling period. Individual workplace exposure level was calculated by 12-h time weighted moving averages based on work shift. The association between each blood marker and exposure to each pollutant during 0-12, 12-24, 24-36, and 36-48h before the blood draw was examined by multivariable regression analyses.

RESULTS

In general, OC and EC had a positive association with sICAM-1, especially for exposure periods 12-24 (lag12-24) and 24-36 (lag24-36)h prior to blood draw [β=54.9 (95%CI: 12.3-97.5) for lag12-24 and β=46.5 (95%CI: 21.2-71.8) for lag12-24; change in sICAM-1 (in ng/mL) corresponding to an IQR increase in OC]. A similar pattern was found for EC and PM2.5. We did not find an association between measured pollutants up to 48h before blood draw and hs-CRP or IL-6.

CONCLUSION

In this group of healthy workers, short-term exposure to vehicle-related air pollutants may be associated with sICAM-1. Our findings may be dependent on the exposure period studied.

Evaluation of a high efficiency cabin air (HECA) filtration system for reducing particulate pollutants inside school buses

An increasing number of studies have reported deleterious health effects of vehicle-emitted particulate matter (PM), including PM2.5 (aerodynamic diameter≤2.5 μm), black carbon (BC), and ultrafine particles (UFPs, diameter≤100 nm). When commuting inside school buses, children are exposed to high level of these pollutants due to emissions from both school bus itself and other on-road vehicles. This study developed an on-board high efficiency cabin air (HECA) filtration system for reducing children's exposure inside school buses. Six school buses were driven on two typical routes to evaluate to what extent the system reduces particulate pollutant levels inside the buses. The testing routes included freeways and major arterial roadways in Los Angeles, CA. UFP number concentrations and size distributions as well as BC and PM2.5 concentrations were monitored concurrently inside and outside of each bus. With the HECA filtration system on, in-cabin UFP and BC levels were reduced by 88±6% and 84±5% on averages across all driving conditions, respectively. The system was less effective for PM2.5 (55±22%) but successfully kept its levels below 12 μg/m3 inside all the buses. For all three types of particulate pollutants, in-cabin reductions were higher on freeways than on arterial roadways.

Structured expert judgment to characterize uncertainty between PM2.5 exposure and mortality in Chile

To further the understanding and implementation of expert elicitation methods in the evaluation of public policies related to air pollution, the present study's main goal was to explore the potential strengths and weaknesses of structured expert judgment (SEJ) methodology as a way to derive a C-R function for chronic PM(2.5) exposure and premature mortality in Chile. Local experts were classified in two groups according to background and experience: physicians (Group 1) and engineers (Group 2). Experts were required to provide an estimate of the true percent change in nonaccidental mortality resulting from a permanent 1 μg/m(3) reduction in PM2.5 annual average ambient concentration across the entire Chilean territory. Cooke's Classical Model was used to combine the individual experts' assessments. Experts' mortality estimations varied markedly across groups: while experts in Group 1 delivered higher estimations than those reported in major international cohort studies, estimations from Group 2 were, to varying degrees, anchored to previous studies. Accordingly, combined distributions for each group and all experts were significantly different, due to the high sensitivity of the weighted distribution to experts' performance in calibration variables. Results of this study suggest that, while the use of SEJ has great potential for estimating C-R functions for chronic exposure to PM2.5 and premature mortality and its major sources of uncertainty in countries where no studies are available, its successful implementation is conditioned by a number of factors, which are analyzed and discussed.

Short-term traffic related exposures and biomarkers of nitro-PAH exposure and oxidative DNA damage

Exposure to vehicle exhaust has been associated with cardiac and respiratory disease, lung cancer, and greater overall mortality. We investigated whether amino- polycyclic aromatic hydrocarbon (amino-PAH) metabolites of nitro-PAHs could be used as biomarkers of these exposures. Pre- and post-shift urine samples were collected at the beginning and end of a work week from 82 male U.S trucking industry workers. We used repeated-measures analysis to examine associations of total 1- and 2-aminonaphthalene (1 & 2-AN) and 1-aminopyrene (1-AP) urinary concentrations with microenvironment exposures to particulate matter (PM_2.5), elemental and organic carbon, and between 1&2-AN and 1-AP with urinary 8-hydroxy-2'-deoxyguanosine (8-OHdG). There was an association between work week mean PM_2.5 levels and post-shift 1 & 2-AN, [141.8 pg/ml increase (95% CI:53.3, 230.2) for each IQR increase (5.54 µg/m³) in PM_2.5,] but no associations with other exposure measures. There was a statistically significant increase in 8-OHdG concentrations with 1 & 2-AN (2.38 µg/mg creatinine (95%CI: 0.19, 4.58) per 242.85 pg/mg creatinine increase in 1 & 2-AN), and suggestive associations with all other exposure measures. Our findings suggest associations between urinary amino-PAHs with vehicle exhaust related PM_2.5 as well as with a biomarker of oxidative DNA damage.

Traffic-related exposures and biomarkers of systemic inflammation, endothelial activation and oxidative stress: a panel study in the US trucking industry

BACKGROUND

Experimental evidence suggests that inhaled particles from vehicle exhaust have systemic effects on inflammation, endothelial activation and oxidative stress. In the present study we assess the relationships of short-term exposures with inflammatory endothelial activation and oxidative stress biomarker levels in a population of trucking industry workers.

METHODS

Blood and urine samples were collected pre and post-shift, at the beginning and end of a workweek from 67 male non-smoking US trucking industry workers. Concurrent measurements of microenvironment concentrations of elemental and organic carbon (EC & OC), and fine particulate matter (PM2.5) combined with time activity patterns allowed for calculation of individual exposures. Associations between daily and first and last-day average levels of exposures and repeated measures of intercellular and vascular cell adhesion molecule-1 (ICAM-1 & VCAM-1), interleukin 6 (IL-6) and C-reactive protein (CRP) blood levels and urinary 8-Hydroxy-2'-Deoxyguanosine (8-OHdG) were assessed using linear mixed effects models for repeated measures.

RESULTS

There was a statistically significant association between first and last-day average PM2.5 and 8-OHdG (21% increase, 95% CI: 2, 42%) and first and last-day average OC and IL-6 levels (18% increase 95% CI: 1, 37%) per IQR in exposure. There were no significant findings associated with EC or associations suggesting acute cross-shift effects.

CONCLUSION

Our findings suggest associations between weekly average exposures of PM2.5 on markers of oxidative stress and OC on IL-6 levels.

Minimizing the health and climate impacts of emissions from heavy-duty public transportation bus fleets through operational optimization

In contrast to capital control strategies (i.e., investments in new technology), the potential of operational control strategies (e.g., vehicle scheduling optimization) to reduce the health and climate impacts of the emissions from public transportation bus fleets has not been widely considered. This case study demonstrates that heterogeneity in the emission levels of different bus technologies and the exposure potential of bus routes can be exploited though optimization (e.g., how vehicles are assigned to routes) to minimize these impacts as well as operating costs. The magnitude of the benefits of the optimization depend on the specific transit system and region. Health impacts were found to be particularly sensitive to different vehicle assignments and ranged from worst to best case assignment by more than a factor of 2, suggesting there is significant potential to reduce health impacts. Trade-offs between climate, health, and cost objectives were also found. Transit agencies that do not consider these objectives in an integrated framework and, for example, optimize for costs and/or climate impacts alone, risk inadvertently increasing health impacts by as much as 49%. Cost-benefit analysis was used to evaluate trade-offs between objectives, but large uncertainties make identifying an optimal solution challenging.

Plasma fluorescent oxidation products and short-term occupational particulate exposures

BACKGROUND

Evidence suggests that fine particulate air pollution results in oxidative induced tissue damage.

METHODS

A global fluorescent oxidation products (FLOx) assay (fluorescent intensity (FI) units per milliliter of plasma) was measured in blood samples collected from 236 nonsmoking, Caucasian, male trucking industry workers either prior to, during, or after their work shifts. Occupational exposures to particulate matter (PM)(2.5) were based on job-specific area-level sampling. Generalized linear models were used to determine associations between FLOx levels and PM(2.5) , adjusted for age, time since last meal, alcohol consumption, aspirin, and cholesterol medications.

RESULTS

The mean (standard deviation) level of FLOx was 265.9 FI/ml (96.0). Levels of FLOx were higher among older individuals and lower among those who had consumed alcohol in the past 24 hr. However, no associations were observed between FLOx and PM(2.5) .

CONCLUSIONS

Our results indicate no association between occupational PM(2.5) exposure and this marker of global oxidative stress.

Spatial distribution of diesel transit bus emissions and urban populations: implications of coincidence and scale on exposure

Macroscale emissions modeling approaches have been widely applied in impact assessments of mobile source emissions. However, these approaches poorly characterize the spatial distribution of emissions and have been shown to underestimate emissions of some pollutants. To quantify the implications of these limitations on exposure assessments, CO, NO(X), and HC emissions from diesel transit buses were estimated at 50 m intervals along a bus rapid transit route using a microscale emissions modeling approach. The impacted population around the route was estimated using census, pedestrian count and transit ridership data. Emissions exhibited significant spatial variability. In intervals near major intersections and bus stops, emissions were 1.6-3.0 times higher than average. The coincidence of these emission hot spots and peaks in pedestrian populations resulted in a 20-40% increase in exposure compared to estimates that assumed homogeneous spatial distributions of emissions and/or populations along the route. An additional 19-30% increase in exposure resulted from the underestimate of CO and NO(X) emissions by macroscale modeling approaches. The results of this study indicate that macroscale modeling approaches underestimate exposure due to poor characterization of the influence of vehicle activity on the spatial distribution of emissions and total emissions.

Particulate air pollution and health effects for cardiovascular and respiratory causes in Temuco, Chile: a wood-smoke-polluted urban area

Temuco is one of the most highly wood-smoke-polluted cities in the world. Its population in 2004 was 340,000 inhabitants with 1587 annual deaths, of which 24% were due to cardiovascular and 11% to respiratory causes. For hospital admissions, cardiovascular diseases represented 6% and respiratory diseases 13%. Emergency room visits for acute respiratory infections represented 28%. The objective of the study presented here was to determine the relationship between air pollution from particulate matter less than or equal to 10 microm in aerodynamic diameter (PM10; mostly PM2.5, or particulate matter <2.5 microm in aerodynamic diameter) and health effects measured as the daily number of deaths, hospital admissions, and emergency room visits for cardiovascular, respiratory, and acute respiratory infection (ARI) diseases. The Air Pollution Health Effects European Approach (APHEA2) protocol was followed, and a multivariate Poisson regression model was fitted, controlling for trend, seasonality, and confounders for Temuco during 1998-2006. The results show that PM10 had a significant association with daily mortality and morbidity, with the elderly (population >65 yr of age) being the group that presented the greatest risk. The relative risk for respiratory causes, with an increase of 100 microg/m3 of PM10, was 1.163 with a 95% confidence interval (CI) of 1.057-1.279 for mortality, 1.137 (CI 1.096-1.178) for hospital admissions, and 1.162 for ARI (CI 1.144-1.181). There is evidence in Temuco of positive relationships between ambient particulate levels and mortality, hospital admissions, and ARI for cardiovascular and respiratory diseases. These results are consistent with those of comparable studies in other similar cities where wood smoke is the most important air pollution problem.

Symptoms and medication use in children with asthma and traffic-related sources of fine particle pollution

BACKGROUND

Exposure to ambient fine particles [particulate matter < or = 2.5 microm diameter (PM(2.5))] is a potential factor in the exacerbation of asthma. National air quality particle standards consider total mass, not composition or sources, and may not protect against health impacts related to specific components.

OBJECTIVE

We examined associations between daily exposure to fine particle components and sources, and symptoms and medication use in children with asthma.

METHODS

Children with asthma (n = 149) 4-12 years of age were enrolled in a year-long study. We analyzed particle samples for trace elements (X-ray fluorescence) and elemental carbon (light reflectance). Using factor analysis/source apportionment, we identified particle sources (e.g., motor vehicle emissions) and quantified daily contributions. Symptoms and medication use were recorded on study diaries. Repeated measures logistic regression models examined associations between health outcomes and particle exposures as elemental concentrations and source contributions.

RESULTS

More than half of mean PM(2.5) was attributed to traffic-related sources motor vehicles (42%) and road dust (12%). Increased likelihood of symptoms and inhaler use was largest for 3-day averaged exposures to traffic-related sources or their elemental constituents and ranged from a 10% increased likelihood of wheeze for each 5-microg/m(3) increase in particles from motor vehicles to a 28% increased likelihood of shortness of breath for increases in road dust. Neither the other sources identified nor PM(2.5) alone was associated with increased health outcome risks.

CONCLUSIONS

Linking respiratory health effects to specific particle pollution composition or sources is critical to efforts to protect public health. We associated increased risk of symptoms and inhaler use in children with asthma with exposure to traffic-related fine particles.

Health impact assessment of particulate pollution in Tallinn using fine spatial resolution and modeling techniques

BACKGROUND

Health impact assessments (HIA) use information on exposure, baseline mortality/morbidity and exposure-response functions from epidemiological studies in order to quantify the health impacts of existing situations and/or alternative scenarios. The aim of this study was to improve HIA methods for air pollution studies in situations where exposures can be estimated using GIS with high spatial resolution and dispersion modeling approaches.

METHODS

Tallinn was divided into 84 sections according to neighborhoods, with a total population of approx. 390,000 persons. Actual baseline rates for total mortality and hospitalization with cardiovascular and respiratory diagnosis were identified. The exposure to fine particles (PM2.5) from local emissions was defined as the modeled annual levels. The model validation and morbidity assessment were based on 2006 PM10 or PM2.5 levels at 3 monitoring stations. The exposure-response coefficients used were for total mortality 6.2% (95% CI 1.6-11%) per 10 microg/m3 increase of annual mean PM2.5 concentration and for the assessment of respiratory and cardiovascular hospitalizations 1.14% (95% CI 0.62-1.67%) and 0.73% (95% CI 0.47-0.93%) per 10 microg/m3 increase of PM10. The direct costs related to morbidity were calculated according to hospital treatment expenses in 2005 and the cost of premature deaths using the concept of Value of Life Year (VOLY).

RESULTS

The annual population-weighted-modeled exposure to locally emitted PM2.5 in Tallinn was 11.6 microg/m3. Our analysis showed that it corresponds to 296 (95% CI 76528) premature deaths resulting in 3859 (95% CI 10236636) Years of Life Lost (YLL) per year. The average decrease in life-expectancy at birth per resident of Tallinn was estimated to be 0.64 (95% CI 0.17-1.10) years. While in the polluted city centre this may reach 1.17 years, in the least polluted neighborhoods it remains between 0.1 and 0.3 years. When dividing the YLL by the number of premature deaths, the decrease in life expectancy among the actual cases is around 13 years. As for the morbidity, the short-term effects of air pollution were estimated to result in an additional 71 (95% CI 43-104) respiratory and 204 (95% CI 131-260) cardiovascular hospitalizations per year. The biggest external costs are related to the long-term effects on mortality: this is on average euro 150 (95% CI 40-260) million annually. In comparison, the costs of short-term air-pollution driven hospitalizations are small euro 0.3 (95% CI 0.2-0.4) million.

CONCLUSION

Sectioning the city for analysis and using GIS systems can help to improve the accuracy of air pollution health impact estimations, especially in study areas with poor air pollution monitoring data but available dispersion models.

Comparative risk analysis of dioxins in fish and fine particles from heavy-duty vehicles

Dioxins and airborne fine particles are both environmental health problems that have been the subject of active public debate. Knowledge on fine particles has increased substantially during the last 10 years, and even the current, lowered levels in the Europe and in the United States appear to be a major public health problem. On the other hand, dioxins are ubiquitous persistent contaminants, some being carcinogens at high doses, and therefore of great concern. Our aim was to (a) quantitatively analyze the two pollutant health risks and (b) study the changes in risk in view of the current and forthcoming EU legislations on pollutants. We performed a comparative risk assessment for both pollutants in the Helsinki metropolitan area (Finland) and estimated the health effects with several scenarios. For primary fine particles: a comparison between the present emission situation for heavy-duty vehicles and the new fine particle emission standards set by the EU. For dioxins: an EU directive that regulates commercial fishing of Baltic salmon and herring that exceed the dioxin concentration limit set for fish meat, and a derogation (= exemption) from the directive for these two species. Both of these two decisions are very topical issues and this study estimates the expected changes in health effects due to these regulations. It was found that the estimated fine particle risk clearly outweighed the estimated dioxin risk. A substantial improvement to public health could be achieved by initiating reductions in emission standards; about 30 avoided premature deaths annually in the study area. In addition, the benefits of fish consumption due to omega-3 exposure were notably higher than the potential dioxin cancer risk. Both regulations were instigated as ways of promoting public health.

Modeling and source apportionment of diesel particulate matter

The fine and ultra fine sizes of diesel particulate matter (DPM) are of greatest health concern. The composition of these primary and secondary fine and ultra fine particles is principally elemental carbon (EC) with adsorbed organic compounds, sulfate, nitrate, ammonia, metals, and other trace elements. The purpose of this study was to use an advanced air quality modeling technique to predict and analyze the emissions and the primary and secondary aerosols concentrations that come from diesel-fueled sources (DFS). The National Emissions Inventory for 1999 and a severe southeast ozone episode that occurred between August and September 1999 were used as reference. Five urban areas and one rural area in the Southeastern US were selected to compare the main results. For urban emissions, results showed that DFS contributed (77.9%+/-8.0) of EC, (16.8%+/-8.2) of organic aerosols, (14.3%+/-6.2) of nitrate, and (8.3%+/-6.6) of sulfate during the selected episodes. For the rural site, these contributions were lower. The highest DFS contribution on EC emissions was allocated in Memphis, due mainly to diesel non-road sources (60.9%). For ambient concentrations, DFS contributed (69.5%+/-6.5) of EC and (10.8%+/-2.4) of primary anthropogenic organic aerosols, where the highest DFS contributions on EC were allocated in Nashville and Memphis on that episode. The DFS contributed (8.3%+/-1.2) of the total ambient PM(2.5) at the analyzed sites. The maximum primary DPM concentration occurred in Atlanta (1.44 microg/m(3)), which was 3.8 times higher than that from the rural site. Non-linearity issues were encountered and recommendations were made for further research. The results indicated significant geographic variability in the EC contribution from DFS, and the main DPM sources in the Southeastern U.S. were the non-road DFS. The results of this work will be helpful in addressing policy issues targeted at designing control strategies on DFS in the Southeastern U.S.

Parameter and model uncertainty in a life-table model for fine particles (PM2.5): a statistical modeling study

BACKGROUND

The estimation of health impacts involves often uncertain input variables and assumptions which have to be incorporated into the model structure. These uncertainties may have significant effects on the results obtained with model, and, thus, on decision making. Fine particles (PM2.5) are believed to cause major health impacts, and, consequently, uncertainties in their health impact assessment have clear relevance to policy-making. We studied the effects of various uncertain input variables by building a life-table model for fine particles.

METHODS

Life-expectancy of the Helsinki metropolitan area population and the change in life-expectancy due to fine particle exposures were predicted using a life-table model. A number of parameter and model uncertainties were estimated. Sensitivity analysis for input variables was performed by calculating rank-order correlations between input and output variables. The studied model uncertainties were (i) plausibility of mortality outcomes and (ii) lag, and parameter uncertainties (iii) exposure-response coefficients for different mortality outcomes, and (iv) exposure estimates for different age groups. The monetary value of the years-of-life-lost and the relative importance of the uncertainties related to monetary valuation were predicted to compare the relative importance of the monetary valuation on the health effect uncertainties.

RESULTS

The magnitude of the health effects costs depended mostly on discount rate, exposure-response coefficient, and plausibility of the cardiopulmonary mortality. Other mortality outcomes (lung cancer, other non-accidental and infant mortality) and lag had only minor impact on the output. The results highlight the importance of the uncertainties associated with cardiopulmonary mortality in the fine particle impact assessment when compared with other uncertainties.

CONCLUSION

When estimating life-expectancy, the estimates used for cardiopulmonary exposure-response coefficient, discount rate, and plausibility require careful assessment, while complicated lag estimates can be omitted without this having any major effect on the results.

Overview of particulate exposures in the US trucking industry

As part of a large epidemiologic study of lung cancer, 55,000 subjects, we have conducted a nation-wide survey of particulate exposures in the US trucking industry. The goal is to differentiate the risks from various types of particulate exposures, such as traffic emissions and general air pollution. We hypothesize that exposures defined by job and work site characteristics can be linked with subjects using their personal job histories. This report covers exposures at 36 randomly chosen large truck freight terminals in the US. Measurements were made of PM2.5, elemental carbon (EC), and organic carbon (OC) upwind of the terminal (background) and in work areas, and by personal samples. Significant differences in exposure intensity, microg m(-3), were found for work locations and jobs relative to background levels (GM[GSD]) at terminal sites: PM2.5 9.8[2.34], EC 0.5[3.24], and OC 5.0[1.76]. Using EC as a marker for diesel particles, work locations varied significantly: office 0.3[3.7], dock area 0.7[2.89] and shop area 1.5[3.52]), as did job titles (non-smokers): clerk 0.1[9.98], dock worker 0.8[2.13], and mechanic 2.0[3.82]. Cigarette smoking contributed substantially to personal exposures, approximately doubling PM2.5 and OC, but having less of an effect on EC. Large differences were seen across the terminal sites due to differences in local regional air pollution levels from traffic and other sources. We conclude that it will be possible to estimate current exposures of the cohort using an exposure assignment matrix based on job title, work location, and terminal site. This distribution overlaps substantially with the general public's exposure to these sources.

An economic way of reducing health, environmental, and other pressures of urban traffic: a decision analysis on trip aggregation

Background

Traffic congestion is rapidly becoming the most important obstacle to urban development. In addition, traffic creates major health, environmental, and economical problems. Nonetheless, automobiles are crucial for the functions of the modern society. Most proposals for sustainable traffic solutions face major political opposition, economical consequences, or technical problems.

Methods

We performed a decision analysis in a poorly studied area, trip aggregation, and studied decisions from the perspective of two different stakeholders, the passenger and society. We modelled the impact and potential of composite traffic, a hypothetical large-scale demand-responsive public transport system for the Helsinki metropolitan area, where a centralised system would collect the information on all trip demands online, would merge the trips with the same origin and destination into public vehicles with eight or four seats, and then would transmit the trip instructions to the passengers' mobile phones.

Results

We show here that in an urban area with one million inhabitants, trip aggregation could reduce the health, environmental, and other detrimental impacts of car traffic typically by 50–70%, and if implemented could attract about half of the car passengers, and within a broad operational range would require no public subsidies.

Conclusion

Composite traffic provides new degrees of freedom in urban decision-making in identifying novel solutions to the problems of urban traffic.