Long-term exposure to ambient air pollution and incidence of brain tumor: the European Study of Cohorts for Air Pollution Effects (ESCAPE).

Background: Epidemiological evidence on the association between ambient air pollution and brain tumor risk is sparse and inconsistent. Methods: In 12 cohorts from 6 European countries, individual estimates of annual mean air pollution levels at the baseline residence were estimated by standardized land-use regression models developed within the ESCAPE and TRANSPHORM projects: particulate matter (PM) ≤2.5, ≤10, and 2.5-10 µm in diameter (PM2.5, PM10, and PMcoarse), PM2.5 absorbance, nitrogen oxides (NO2 and NOx) and elemental composition of PM. We estimated cohort-specific associations of air pollutant concentrations and traffic intensity with total, malignant, and nonmalignant brain tumor, in separate Cox regression models, adjusting for risk factors, and pooled cohort-specific estimates using random-effects meta-analyses. Results: Of 282194 subjects from 12 cohorts, 466 developed malignant brain tumors during 12 years of follow-up. Six of the cohorts also had data on nonmalignant brain tumor, where among 106786 subjects, 366 developed brain tumor: 176 nonmalignant and 190 malignant. We found a positive, statistically nonsignificant association between malignant brain tumor and PM2.5 absorbance (hazard ratio and 95% CI: 1.67; 0.89-3.14 per 10-5/m3), and weak positive or null associations with the other pollutants. Hazard ratio for PM2.5 absorbance (1.01; 0.38-2.71 per 10-5/m3) and all other pollutants were lower for nonmalignant than for malignant brain tumors. Conclusion: We found suggestive evidence of an association between long-term exposure to PM2.5 absorbance indicating traffic-related air pollution and malignant brain tumors, and no association with overall or nonmalignant brain tumors.

Long-Term Exposure to Ambient Air Pollution and Incidence of Postmenopausal Breast Cancer in 15 European Cohorts within the ESCAPE Project.

BACKGROUND: Epidemiological evidence on the association between ambient air pollution and breast cancer risk is inconsistent. OBJECTIVE: We examined the association between long-term exposure to ambient air pollution and incidence of postmenopausal breast cancer in European women. METHODS: In 15 cohorts from nine European countries, individual estimates of air pollution levels at the residence were estimated by standardized land-use regression models developed within the European Study of Cohorts for Air Pollution Effects (ESCAPE) and Transport related Air Pollution and Health impacts ­ Integrated Methodologies for Assessing Particulate Matter (TRANSPHORM) projects: particulate matter (PM) ≤2.5µm, ≤10µm, and 2.5­10µm in diameter (PM2.5, PM10, and PMcoarse, respectively); PM2.5 absorbance; nitrogen oxides (NO2 and NOx); traffic intensity; and elemental composition of PM. We estimated cohort-specific associations between breast cancer and air pollutants using Cox regression models, adjusting for major lifestyle risk factors, and pooled cohort-specific estimates using random-effects meta-analyses. RESULTS: Of 74,750 postmenopausal women included in the study, 3,612 developed breast cancer during 991,353 person-years of follow-up. We found positive and statistically insignificant associations between breast cancer and PM2.5 {hazard ratio (HR)=1.08 [95% confidence interval (CI): 0.77, 1.51] per 5 µg/m3}, PM10 [1.07 (95% CI: 0.89, 1.30) per 10 µg/m3], PMcoarse[1.20 (95% CI: 0.96, 1.49 per 5 µg/m3], and NO2 [1.02 (95% CI: 0.98, 1.07 per 10 µg/m3], and a statistically significant association with NOx [1.04 (95% CI: 1.00, 1.08) per 20 µg/m3, p=0.04]. CONCLUSIONS: We found suggestive evidence of an association between ambient air pollution and incidence of postmenopausal breast cancer in European women. https://doi.org/10.1289/EHP1742.

Particulates and noise exposure during bicycle, bus and car commuting: A study in three European cities.

BACKGROUND: In order to curb traffic-related air pollution and its impact on the physical environment, contemporary city commuters are encouraged to shift from private car use to active or public transport modes. However, personal exposures to particulate matter (PM), black carbon and noise during commuting may be substantial. Therefore, studies comparing exposures during recommended modes of transport versus car trips are needed. METHODS: We measured personal exposure to various-sized particulates, soot, and noise during commuting by bicycle, bus and car in three European cities: Helsinki in Finland, Rotterdam in the Netherlands and Thessaloniki in Greece using portable monitoring devices. We monitored commonly travelled routes in these cities. RESULTS: The total number of one-way trips yielding data on any of the measured parameters were 84, 72, 94 and 69 for bicycle, bus, closed-window car and open-window car modes, respectively. The highest mean PM2.5 (85µg/m3), PM10 (131µg/m3), black carbon (10.9µg/m3) and noise (75dBA) levels were recorded on the bus, bus (again), open-window car and bicycle modes, respectively, all in Thessaloniki, PM and soot concentrations were generally higher during biking and taking a bus than during a drive in a a car with closed windows. Ratios of bike:car PM10 ranged from 1.1 in Thessaloniki to 2.6 in Helsinki, while bus:car ratios ranged from in 1.0 in Rotterdam to 5.6 in Thessaloniki. Higher noise levels were mostly recorded during bicycle rides. CONCLUSION: Based on our study, active- and public-transport commuters are often at risk of higher air pollution and noise exposure than private car users. This should be taken into account in urban transportation planning.

Public health impacts of city policies to reduce climate change: findings from the URGENCHE EU-China project.

BACKGROUND: Climate change is a global threat to health and wellbeing. Here we provide findings of an international research project investigating the health and wellbeing impacts of policies to reduce greenhouse gas emissions in urban environments. METHODS: Five European and two Chinese city authorities and partner academic organisations formed the project consortium. The methodology involved modelling the impact of adopted urban climate-change mitigation transport, buildings and energy policy scenarios, usually for the year 2020 and comparing them with business as usual (BAU) scenarios (where policies had not been adopted). Carbon dioxide emissions, health impacting exposures (air pollution, noise and physical activity), health (cardiovascular, respiratory, cancer and leukaemia) and wellbeing (including noise related wellbeing, overall wellbeing, economic wellbeing and inequalities) were modelled. The scenarios were developed from corresponding known levels in 2010 and pre-existing exposure response functions. Additionally there were literature reviews, three longitudinal observational studies and two cross sectional surveys. RESULTS: There are four key findings. Firstly introduction of electric cars may confer some small health benefits but it would be unwise for a city to invest in electric vehicles unless their power generation fuel mix generates fewer emissions than petrol and diesel. Second, adopting policies to reduce private car use may have benefits for carbon dioxide reduction and positive health impacts through reduced noise and increased physical activity. Third, the benefits of carbon dioxide reduction from increasing housing efficiency are likely to be minor and co-benefits for health and wellbeing are dependent on good air exchange. Fourthly, although heating dwellings by in-home biomass burning may reduce carbon dioxide emissions, consequences for health and wellbeing were negative with the technology in use in the cities studied. CONCLUSIONS: The climate-change reduction policies reduced CO2 emissions (the most common greenhouse gas) from cities but impact on global emissions of CO2 would be more limited due to some displacement of emissions. The health and wellbeing impacts varied and were often limited reflecting existing relatively high quality of life and environmental standards in most of the participating cities; the greatest potential for future health benefit occurs in less developed or developing countries.

High resolution exposure modelling of heat and air pollution and the impact on mortality.

BACKGROUND: Elevated temperature and air pollution have been associated with increased mortality. Exposure to heat and air pollution, as well as the density of vulnerable groups varies within cities. The objective was to investigate the extent of neighbourhood differences in mortality risk due to heat and air pollution in a city with a temperate maritime climate. METHODS: A case-crossover design was used to study associations between heat, air pollution and mortality. Different thermal indicators and air pollutants (PM10, NO2, O3) were reconstructed at high spatial resolution to improve exposure classification. Daily exposures were linked to individual mortality cases over a 15year period. RESULTS: Significant interaction between maximum air temperature (Tamax) and PM10 was observed. During "summer smog" days (Tamax>25°C and PM10>50µg/m(3)), the mortality risk at lag 2 was 7% higher compared to the reference (Tamax 15°C and PM10 15µg/m(3)). Persons above age 85 living alone were at highest risk. CONCLUSION: We found significant synergistic effects of high temperatures and air pollution on mortality. Single living elderly were the most vulnerable group. Due to spatial differences in temperature and air pollution, mortality risks varied substantially between neighbourhoods, with a difference up to 7%.

Health impact assessment of transport policies in Rotterdam: Decrease of total traffic and increase of electric car use.

BACKGROUND: Green house gas (GHG) mitigation policies can be evaluated by showing their co-benefits to health. METHOD: Health Impact Assessment (HIA) was used to quantify co-benefits of GHG mitigation policies in Rotterdam. The effects of two separate interventions (10% reduction of private vehicle kilometers and a share of 50% electric-powered private vehicle kilometers) on particulate matter (PM2.5), elemental carbon (EC) and noise (engine noise and tyre noise) were assessed using Years of Life Lost (YLL) and Years Lived with Disability (YLD). The baseline was 2010 and the end of the assessment 2020. RESULTS: The intervention aimed at reducing traffic is associated with a decreased exposure to noise resulting in a reduction of 21 (confidence interval (CI): 11-129) YLDs due to annoyance and 35 (CI: 20-51) YLDs due to sleep disturbance for the population per year. The effects of 50% electric-powered car use are slightly higher with a reduction of 26 (CI: 13-116) and 41 (CI: 24-60) YLDs, respectively. The two interventions have marginal effects on air pollution, because already implemented traffic policies will reduce PM2.5 and EC by around 40% and 60% respectively, from 2010 to 2020. DISCUSSION: The evaluation of planned interventions, related to climate change policies, targeting only the transport sector can result in small co-benefits for health, if the analysis is limited to air pollution and noise. This urges to expand the analysis by including other impacts, e.g. physical activity and well-being, as a necessary step to better understanding consequences of interventions and carefully orienting resources useful to build knowledge to improve public health.

Spatial variation of PM elemental composition between and within 20 European study areas--Results of the ESCAPE project.

An increasing number of epidemiological studies suggest that adverse health effects of air pollution may be related to particulate matter (PM) composition, particularly trace metals. However, we lack comprehensive data on the spatial distribution of these elements. We measured PM2.5 and PM10 in twenty study areas across Europe in three seasonal two-week periods over a year using Harvard impactors and standardized protocols. In each area, we selected street (ST), urban (UB) and regional background (RB) sites (totaling 20) to characterize local spatial variability. Elemental composition was determined by energy-dispersive X-ray fluorescence analysis of all PM2.5 and PM10 filters. We selected a priori eight (Cu, Fe, K, Ni, S, Si, V, Zn) well-detected elements of health interest, which also roughly represented different sources including traffic, industry, ports, and wood burning. PM elemental composition varied greatly across Europe, indicating different regional influences. Average street to urban background ratios ranged from 0.90 (V) to 1.60 (Cu) for PM2.5 and from 0.93 (V) to 2.28 (Cu) for PM10. Our selected PM elements were variably correlated with the main pollutants (PM2.5, PM10, PM2.5 absorbance, NO2 and NOx) across Europe: in general, Cu and Fe in all size fractions were highly correlated (Pearson correlations above 0.75); Si and Zn in the coarse fractions were modestly correlated (between 0.5 and 0.75); and the remaining elements in the various size fractions had lower correlations (around 0.5 or below). This variability in correlation demonstrated the distinctly different spatial distributions of most of the elements. Variability of PM10_Cu and Fe was mostly due to within-study area differences (67% and 64% of overall variance, respectively) versus between-study area and exceeded that of most other traffic-related pollutants, including NO2 and soot, signaling the importance of non-tailpipe (e.g., brake wear) emissions in PM.

Development of a quantitative methodology to assess the impacts of urban transport interventions and related noise on well-being.

Well-being impact assessments of urban interventions are a difficult challenge, as there is no agreed methodology and scarce evidence on the relationship between environmental conditions and well-being. The European Union (EU) project "Urban Reduction of Greenhouse Gas Emissions in China and Europe" (URGENCHE) explored a methodological approach to assess traffic noise-related well-being impacts of transport interventions in three European cities (Basel, Rotterdam and Thessaloniki) linking modeled traffic noise reduction effects with survey data indicating noise-well-being associations. Local noise models showed a reduction of high traffic noise levels in all cities as a result of different urban interventions. Survey data indicated that perception of high noise levels was associated with lower probability of well-being. Connecting the local noise exposure profiles with the noise-well-being associations suggests that the urban transport interventions may have a marginal but positive effect on population well-being. This paper also provides insight into the methodological challenges of well-being assessments and highlights the range of limitations arising from the current lack of reliable evidence on environmental conditions and well-being. Due to these limitations, the results should be interpreted with caution.

Long-term Exposure to Particulate Matter Constituents and the Incidence of Coronary Events in 11 European Cohorts.

BACKGROUND: Long-term exposure to particulate matter (PM) has been associated with increased cardiovascular morbidity and mortality but little is known about the role of the chemical composition of PM. This study examined the association of residential long-term exposure to PM components with incident coronary events. METHODS: Eleven cohorts from Finland, Sweden, Denmark, Germany, and Italy participated in this analysis. 5,157 incident coronary events were identified within 100,166 persons followed on average for 11.5 years. Long-term residential concentrations of PM < 10 µm (PM10), PM < 2.5 µm (PM2.5), and a priori selected constituents (copper, iron, nickel, potassium, silicon, sulfur, vanadium, and zinc) were estimated with land-use regression models. We used Cox proportional hazard models adjusted for a common set of confounders to estimate cohort-specific component effects with and without including PM mass, and random effects meta-analyses to pool cohort-specific results. RESULTS: A 100 ng/m³ increase in PM10 K and a 50 ng/m³ increase in PM2.5 K were associated with a 6% (hazard ratio and 95% confidence interval: 1.06 [1.01, 1.12]) and 18% (1.18 [1.06, 1.32]) increase in coronary events. Estimates for PM10 Si and PM2.5 Fe were also elevated. All other PM constituents indicated a positive association with coronary events. When additionally adjusting for PM mass, the estimates decreased except for K. CONCLUSIONS: This multicenter study of 11 European cohorts pointed to an association between long-term exposure to PM constituents and coronary events, especially for indicators of road dust.

Air Pollution and Lung Function in Dutch Children: A Comparison of Exposure Estimates and Associations Based on Land Use Regression and Dispersion Exposure Modeling Approaches.

BACKGROUND: There is limited knowledge about the extent to which estimates of air pollution effects on health are affected by the choice for a specific exposure model. OBJECTIVES: We aimed to evaluate the correlation between long-term air pollution exposure estimates using two commonly used exposure modeling techniques [dispersion and land use regression (LUR) models] and, in addition, to compare the estimates of the association between long-term exposure to air pollution and lung function in children using these exposure modeling techniques. METHODS: We used data of 1,058 participants of a Dutch birth cohort study with measured forced expiratory volume in 1 sec (FEV1), forced vital capacity (FVC), and peak expiratory flow (PEF) measurements at 8 years of age. For each child, annual average outdoor air pollution exposure [nitrogen dioxide (NO2), mass concentration of particulate matter with diameters ≤ 2.5 and ≤ 10 µm (PM2.5, PM10), and PM2.5 soot] was estimated for the current addresses of the participants by a dispersion and a LUR model. Associations between exposures to air pollution and lung function parameters were estimated using linear regression analysis with confounder adjustment. RESULTS: Correlations between LUR- and dispersion-modeled pollution concentrations were high for NO2, PM2.5, and PM2.5 soot (R = 0.86-0.90) but low for PM10 (R = 0.57). Associations with lung function were similar for air pollutant exposures estimated using LUR and dispersion modeling, except for associations of PM2.5 with FEV1 and FVC, which were stronger but less precise for exposures based on LUR compared with dispersion model. CONCLUSIONS: Predictions from LUR and dispersion models correlated very well for PM2.5, NO2, and PM2.5 soot but not for PM10. Health effect estimates did not depend on the type of model used to estimate exposure in a population of Dutch children.

Particulate matter composition and respiratory health: the PIAMA Birth Cohort study.

BACKGROUND: Ambient particulate matter (PM) exposure is associated with children's respiratory health. Little is known about the importance of different PM constituents. We investigated the effects of PM constituents on asthma, allergy, and lung function until the age of 11-12 years. METHODS: For 3,702 participants of a prospective birth cohort study, questionnaire-reported asthma and hay fever and measurements of allergic sensitization and lung function were linked with annual average concentrations of copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc in particles with diameters of less than 2.5 and 10 µm (PM2.5 and PM10) at birth addresses and current addresses from land-use regression models. Exposure-health relations were analyzed by multiple (repeated measures) logistic and linear regressions. RESULTS: Asthma incidence and prevalence of asthma symptoms and rhinitis were positively associated with zinc in PM10 at the birth address (odds ratio [95% confidence interval] per interquartile range increase in exposure 1.13 [1.02, 1.25], 1.08 [1.00, 1.17], and 1.16 [1.04, 1.30], respectively). Moreover, asthma symptoms were positively associated with copper in PM10 at the current address (1.06 [1.00, 1.12]). Allergic sensitization was positively associated with copper and iron in PM10 at the birth address (relative risk [95% confidence interval] 1.07 [1.01, 1.14] and 1.10 [1.03, 1.18]) and current address. Forced expiratory volume in 1 second was negatively associated with copper and iron in PM2.5 (change [95% confidence interval] -2.1% [-1.1, -0.1%] and -1.0% [-2.0, -0.0%]) and FEF75-50 with copper in PM10 at the current address (-2.3% [-4.3, -0.3%]). CONCLUSION: PM constituents, in particular iron, copper, and zinc, reflecting poorly regulated non-tailpipe road traffic emissions, may increase the risk of asthma and allergy in schoolchildren.

Spatial variations of levoglucosan in four European study areas.

Relatively little is known about long term effects of wood smoke on population health. A wood combustion marker - levoglucosan - was measured using a standardized sampling and measurement method in four European study areas (Oslo, The Netherlands, Munich/Augsburg, Catalonia) to assess within and between study area spatial variation. Levoglucosan was analyzed in addition to: PM2.5, PM2.5 absorbance, PM10, polycyclic aromatic hydrocarbons (PAH), nitrogen oxides (NOx), elemental and organic carbon (EC/OC), hopanes, steranes and elemental composition. Measurements were conducted at street, urban and regional background sites. Three two-week samples were taken per site and the annual average concentrations of pollutants were calculated using continuous measurements at one background reference site. Land use regression (LUR) models were developed to explain the spatial variation of levoglucosan. Much larger within than between study area contrast in levoglucosan concentration was found. Spatial variation patterns differed from other measured pollutants: PM2.5, NOx and EC. Levoglucosan had the highest spatial correlation with ΣPAH (r=0.65) and the lowest with traffic markers - NOx, Σhopanes/steranes (r=-0.22). Levoglucosan concentrations in the cold (heating) period were between 3 and 20 times higher compared to the warm period. The contribution of wood-smoke calculated based on levoglucosan measurements and previous European emission data to OC and PM2.5 mass was 13 to 28% and 3 to 9% respectively in the full year. Larger contributions were calculated for the cold period. The median model R(2) of the LUR models was 60%. The LUR models included population and natural land related variables. In conclusion, substantial spatial variability was found in levoglucosan concentrations within study areas. Wood smoke contributed substantially to especially wintertime PM2.5 OC and mass. The low to moderate correlation with PM2.5 mass and traffic markers offers the potential to assess health effects of wood smoke separate from traffic-related air pollution.

Development of land use regression models for elemental, organic carbon, PAH, and hopanes/steranes in 10 ESCAPE/TRANSPHORM European study areas.

Land use regression (LUR) models have been used to model concentrations of mainly traffic-related air pollutants (nitrogen oxides (NOx), particulate matter (PM) mass or absorbance). Few LUR models are published of PM composition, whereas the interest in health effects related to particle composition is increasing. The aim of our study was to evaluate LUR models of polycyclic aromatic hydrocarbons (PAH), hopanes/steranes, and elemental and organic carbon (EC/OC) content of PM2.5. In 10 European study areas, PAH, hopanes/steranes, and EC/OC concentrations were measured at 16-40 sites per study area. LUR models for each study area were developed on the basis of annual average concentrations and predictor variables including traffic, population, industry, natural land obtained from geographic information systems. The highest median model explained variance (R(2)) was found for EC - 84%. The median R(2) was 51% for OC, 67% for benzo[a]pyrene, and 38% for sum of hopanes/steranes, with large variability between study areas. Traffic predictors were included in most models. Population and natural land were included frequently as additional predictors. The moderate to high explained variance of LUR models and the overall moderate correlation with PM2.5 model predictions support the application of especially the OC and PAH models in epidemiological studies.

Comparing land use regression and dispersion modelling to assess residential exposure to ambient air pollution for epidemiological studies.

BACKGROUND: Land-use regression (LUR) and dispersion models (DM) are commonly used for estimating individual air pollution exposure in population studies. Few comparisons have however been made of the performance of these methods. OBJECTIVES: Within the European Study of Cohorts for Air Pollution Effects (ESCAPE) we explored the differences between LUR and DM estimates for NO2, PM10 and PM2.5. METHODS: The ESCAPE study developed LUR models for outdoor air pollution levels based on a harmonised monitoring campaign. In thirteen ESCAPE study areas we further applied dispersion models. We compared LUR and DM estimates at the residential addresses of participants in 13 cohorts for NO2; 7 for PM10 and 4 for PM2.5. Additionally, we compared the DM estimates with measured concentrations at the 20-40 ESCAPE monitoring sites in each area. RESULTS: The median Pearson R (range) correlation coefficients between LUR and DM estimates for the annual average concentrations of NO2, PM10 and PM2.5 were 0.75 (0.19-0.89), 0.39 (0.23-0.66) and 0.29 (0.22-0.81) for 112,971 (13 study areas), 69,591 (7) and 28,519 (4) addresses respectively. The median Pearson R correlation coefficients (range) between DM estimates and ESCAPE measurements were of 0.74 (0.09-0.86) for NO2; 0.58 (0.36-0.88) for PM10 and 0.58 (0.39-0.66) for PM2.5. CONCLUSIONS: LUR and dispersion model estimates correlated on average well for NO2 but only moderately for PM10 and PM2.5, with large variability across areas. DM predicted a moderate to large proportion of the measured variation for NO2 but less for PM10 and PM2.5.

Elemental composition of particulate matter and the association with lung function.

BACKGROUND: Negative effects of long-term exposure to particulate matter (PM) on lung function have been shown repeatedly. Spatial differences in the composition and toxicity of PM may explain differences in observed effect sizes between studies. METHODS: We conducted a multicenter study in 5 European birth cohorts-BAMSE (Sweden), GINIplus and LISAplus (Germany), MAAS (United Kingdom), and PIAMA (The Netherlands)-for which lung function measurements were available for study subjects at the age of 6 or 8 years. Individual annual average residential exposure to copper, iron, potassium, nickel, sulfur, silicon, vanadium, and zinc within PM smaller than 2.5 µm (PM2.5) and smaller than 10 µm (PM10) was estimated using land-use regression models. Associations between air pollution and lung function were analyzed by linear regression within cohorts, adjusting for potential confounders, and then combined by random effects meta-analysis. RESULTS: We observed small reductions in forced expiratory volume in the first second, forced vital capacity, and peak expiratory flow related to exposure to most elemental pollutants, with the most substantial negative associations found for nickel and sulfur. PM10 nickel and PM10 sulfur were associated with decreases in forced expiratory volume in the first second of 1.6% (95% confidence interval = 0.4% to 2.7%) and 2.3% (-0.1% to 4.6%) per increase in exposure of 2 and 200 ng/m, respectively. Associations remained after adjusting for PM mass. However, associations with these elements were not evident in all cohorts, and heterogeneity of associations with exposure to various components was larger than for exposure to PM mass. CONCLUSIONS: Although we detected small adverse effects on lung function associated with annual average levels of some of the evaluated elements (particularly nickel and sulfur), lower lung function was more consistently associated with increased PM mass.

Associations between particulate matter elements and early-life pneumonia in seven birth cohorts: results from the ESCAPE and TRANSPHORM projects.

Evidence for a role of long-term particulate matter exposure on acute respiratory infections is growing. However, which components of particulate matter may be causative remains largely unknown. We assessed associations between eight particulate matter elements and early-life pneumonia in seven birth cohort studies (N total=15,980): BAMSE (Sweden), GASPII (Italy), GINIplus and LISAplus (Germany), INMA (Spain), MAAS (United Kingdom) and PIAMA (The Netherlands). Annual average exposure to copper, iron, potassium, nickel, sulfur, silicon, vanadium and zinc, each respectively derived from particles with aerodynamic diameters ≤ 10 µm (PM10) and 2.5 µm (PM2.5), were estimated using standardized land use regression models and assigned to birth addresses. Cohort-specific associations between these exposures and parental reports of physician-diagnosed pneumonia between birth and two years were assessed using logistic regression models adjusted for host and environmental covariates and total PM10 or PM2.5 mass. Combined estimates were calculated using random-effects meta-analysis. There was substantial within and between-cohort variability in element concentrations. In the adjusted meta-analysis, pneumonia was weakly associated with zinc derived from PM10 (OR: 1.47 (95% CI: 0.99, 2.18) per 20 ng/m(3) increase). No other associations with the other elements were consistently observed. The independent effect of particulate matter mass remained after adjustment for element concentrations. In conclusion, associations between particulate matter mass exposure and pneumonia were not explained by the elements we investigated. Zinc from PM10 was the only element which appeared independently associated with a higher risk of early-life pneumonia. As zinc is primarily attributable to non-tailpipe traffic emissions, these results may suggest a potential adverse effect of non-tailpipe emissions on health.

The policy relevance of wear emissions from road transport, now and in the future--an international workshop report and consensus statement.

UNLABELLED: Road transport emissions are a major contributor to ambient particulate matter concentrations and have been associated with adverse health effects. Therefore, these emissions are targeted through increasingly stringent European emission standards. These policies succeed in reducing exhaust emissions, but do not address "nonexhaust" emissions from brake wear, tire wear, road wear and suspension in air of road dust. Is this a problem? To what extent do nonexhaust emissions contribute to ambient concentrations of PM10 or PM2.5? In the near future, wear emissions may dominate the remaining traffic-related PM10 emissions in Europe, mostly due to the steep decrease in PM exhaust emissions. This underlines the need to determine the relevance of the wear emissions as a contribution to the existing ambient PM concentrations, and the need to assess the health risks related to wear particles, which has not yet received much attention. During a workshop in 2011, available knowledge was reported and evaluated so as to draw conclusions on the relevance of traffic-related wear emissions for air quality policy development. On the basis of available evidence, which is briefly presented in this paper it was concluded that nonexhaust emissions and in particular suspension in air of road dust are major contributors to exceedances at street locations of the PM10 air quality standards in various European cities. Furthermore, wear-related PM emissions that contain high concentrations of metals may (despite their limited contribution to the mass of nonexhaust emissions) cause significant health risks for the population, especially those living near intensely trafficked locations. To quantify the existing health risks, targeted research is required on wear emissions, their dispersion in urban areas, population exposure, and its effects on health. Such information will be crucial for environmental policymakers as an input for discussions on the need to develop control strategies. IMPLICATIONS: Road transport particulate matter (PM) emissions are associated with adverse health effects. Stringent policies succeed in reducing the exhaust PM emissions, but do not address "nonexhaust" emissions from brake wear, tire wear, road wear, and suspension in air of road dust. In the near future the nonexhaust emissions will dominate the road transport PM emissions. Based on the limited available evidence, it is argued that dedicated research is required on nonexhaust emissions and dispersion to urban areas from both an air quality and a public health perspective. The implicated message to regulators and policy makers is that road transport emissions continue to be an issue for health and air quality, despite the encouraging rapid decrease of tailpipe exhaust emissions.

Black carbon as an additional indicator of the adverse health effects of airborne particles compared with PM10 and PM2.5.

BACKGROUND: Current air quality standards for particulate matter (PM) use the PM mass concentration [PM with aerodynamic diameters ≤ 10 µm (PM(10)) or ≤ 2.5 µm (PM(2.5))] as a metric. It has been suggested that particles from combustion sources are more relevant to human health than are particles from other sources, but the impact of policies directed at reducing PM from combustion processes is usually relatively small when effects are estimated for a reduction in the total mass concentration. OBJECTIVES: We evaluated the value of black carbon particles (BCP) as an additional indicator in air quality management. METHODS: We performed a systematic review and meta-analysis of health effects of BCP compared with PM mass based on data from time-series studies and cohort studies that measured both exposures. We compared the potential health benefits of a hypothetical traffic abatement measure, using near-roadway concentration increments of BCP and PM(2.5) based on data from prior studies. RESULTS: Estimated health effects of a 1-µg/m3 increase in exposure were greater for BCP than for PM(10) or PM(2.5), but estimated effects of an interquartile range increase were similar. Two-pollutant models in time-series studies suggested that the effect of BCP was more robust than the effect of PM mass. The estimated increase in life expectancy associated with a hypothetical traffic abatement measure was four to nine times higher when expressed in BCP compared with an equivalent change in PM(2.5) mass. CONCLUSION: BCP is a valuable additional air quality indicator to evaluate the health risks of air quality dominated by primary combustion particles.

Non-exhaust emissions of PM and the efficiency of emission reduction by road sweeping and washing in the Netherlands.

From research on PM(2.5) and PM(10) in 2007/2008 in the Netherlands, it was concluded that the coarse fraction (PM(2.5-10)) attributed 60% and 50% respectively, to the urban-regional and street-urban increments of PM(10). Contrary to Scandinavian and Mediterranean countries which exhibit significant seasonal variation in the coarse fraction of particulate matter (PM), in the Netherlands the coarse fraction in PM at a street location is rather constant during the year. Non-exhaust emissions by road traffic are identified as the main source for coarse PM in urban areas. Non-exhaust emissions mainly originate from re-suspension of accumulated deposited PM and road wear related particles, while primary tire and brake wear hardly contribute to the mass of non-exhaust emissions. However, tire and brake wear can clearly be identified in the total mass through the presence of the heavy metals: zinc, a tracer for tire wear and copper, a tracer for brake wear. The efficiency of road sweeping and washing to reduce non-exhaust emissions in a street-canyon in Amsterdam was investigated. The increments of the coarse fraction at a kerbside location and a housing façade location versus the urban background were measured at days with and without sweeping and washing. It was concluded that this measure did not significantly reduce non-exhaust emissions.