Spatial variation of PM2.5, PM10, PM2.5 absorbance and PMcoarse concentrations between and within 20 European study areas and the relationship with NO2 - Results of the ESCAPE project

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Особливості державного регулювання інвестиційно-інноваційної діяльності, в сфері екології

BACKGROUND: Particulate matter (PM) air pollution is a human lung carcinogen; however, the components responsible have not been identified. We assessed the associations between PM components and lung cancer incidence. METHODS: We used data from 14 cohort studies in eight European countries. We geocoded baseline addresses and assessed air pollution with land-use regression models for eight elements (Cu, Fe, K, Ni, S, Si, V and Zn) in size fractions of PM2.5 and PM10. We used Cox regression models with adjustment for potential confounders for cohort-specific analyses and random effect models for meta-analysis. RESULTS: The 245,782 cohort members contributed 3,229,220 person-years at risk. During follow-up (mean, 13.1 years), 1878 incident cases of lung cancer were diagnosed. In the meta-analyses, elevated hazard ratios (HRs) for lung cancer were associated with all elements except V; none was statistically significant. In analyses restricted to participants who did not change residence during follow-up, statistically significant associations were found for PM2.5 Cu (HR, 1.25; 95% CI, 1.01-1.53 per 5 ng/m(3)), PM10 Zn (1.28; 1.02-1.59 per 20 ng/m(3)), PM10 S (1.58; 1.03-2.44 per 200 ng/m(3)), PM10 Ni (1.59; 1.12-2.26 per 2 ng/m(3)) and PM10 K (1.17; 1.02-1.33 per 100 ng/m(3)). In two-pollutant models, associations between PM10 and PM2.5 and lung cancer were largely explained by PM2.5 S. CONCLUSIONS: This study indicates that the association between PM in air pollution and lung cancer can be attributed to various PM components and sources. PM containing S and Ni might be particularly important

Variation of NO2 and NOx concentrations between and within 36 European study areas: Results from the ESCAPE study

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Comparison of short-term exposure to particle number, PM10 and soot concentrations on three (sub) urban locations.

Recent interest has focused on the health effects of ultrafine particles because of the documented toxicity and the larger concentration contrast near motorways of UFP than for PM10 or PM2.5. There are only few studies that have measured UFP at inner-city streets simultaneously with other PM components. The aim of this study was to compare the contrast of UFP, PM(10) and soot measured simultaneously at 3 inner-city locations, namely a moderately busy street (15,000 vehicles/day), a city and a suburban background location. Simultaneously, measurements of particle number concentrations (PNC), PM(10) and soot have been conducted on three locations in and around Utrecht, a medium-sized city in the Netherlands for 20 weekdays in autumn 2008. Measurements were done for 6-h during afternoon and early evening. The mean PNC at the street location was more than 3 times higher than at the two background locations. The contrast was similar for soot concentrations. In PM(10) concentrations less contrast was found, namely 1.8 times. Mean PNC concentrations were poorly correlated with PM(10) and soot. At the street location, high temporal variation of PNC concentrations occurred within each sampling day, probably related to variations in traffic volumes, high-emission individual vehicles and wind direction. Temporal variation was smaller at the two background locations. Occasional unexplained short-term peaks occurred at the suburban background location. A relatively high correlation between PNC minute values at the two background locations was found, pointing to similar area-wide sources. Typically low correlations were found with the street locations, consistent with the dominant impact of local traffic. A large contrast between two background locations and a moderately busy urban street location was found for PNC and soot, comparable to previous studies of much busier motorways. Temporal variation of PNC was higher at the street location and uncorrelated with background variations

Respiratory health effects of ultrafine and fine particle exposure in cyclists.

OBJECTIVES: Monitoring studies have shown that commuters are exposed to high air pollution concentrations, but there is limited evidence of associated health effects. We carried out a study to investigate the acute respiratory health effects of air pollution related to commuting by bicycle. METHODS: Twelve healthy adults cycled a low- and a high-traffic intensity route during morning rush hour in Utrecht, The Netherlands. Exposure to traffic-related air pollution was characterised by measurements of PM(10), soot and particle number. Before, directly after and 6 h after cycling we measured lung function (FEV(1), FVC, PEF), exhaled NO (FE(NO)) and respiratory symptoms. The association between post- minus pre-exposure difference in health effects and exposure during cycling was evaluated with linear regression models. RESULTS: The average particle number concentration was 59% higher, while the average soot concentration was 39% higher on the high-traffic route than on the low-traffic route. There was no difference for PM(10). Contrary to our hypothesis, associations between air pollution during cycling and lung function changes immediately after cycling were mostly positive. Six hours after cycling, associations between air pollution exposure and health were mostly negative for lung function changes and positive for changes in exhaled NO, although non-significant. CONCLUSIONS: We found substantial differences in ultrafine particle number and soot exposure between two urban cycling routes. Exposure to ultrafine particles and soot during cycling was weakly associated with increased exhaled NO, indicative of airway inflammation, and decrements in lung function 6 h after exposure. A limitation of the study was the relatively small sample size

A hybrid air pollution / land use regression model for predicting air pollution concentrations in Durban, South Africa

The objective of this paper was to incorporate source-meteorological interaction information from two commonly employed atmospheric dispersion models into the land use regression technique for predicting ambient nitrogen dioxide (NO2), sulphur dioxide (SO2), and particulate matter (PM10). The study was undertaken across two regions in Durban, South Africa, one with a high industrial profile and a nearby harbour, and the other with a primarily commercial and residential profile. Multiple hybrid models were developed by integrating air pollution dispersion modelling predictions for source specific NO2, SO2, and PM10 concentrations into LUR models following the European Study of Cohorts for Air Pollution Effects (ESCAPE) methodology to characterise exposure, in Durban. Industrial point sources, ship emissions, domestic fuel burning, and vehicle emissions were key emission sources. Standard linear regression was used to develop annual, summer and winter hybrid models to predict air pollutant concentrations. Higher levels of NO2 and SO2 were predicted in south Durban as compared to north Durban as these are industrial related pollutants. Slightly higher levels of PM10 were predicted in north Durban as compared to south Durban and can be attributed to either traffic, bush burning or domestic fuel burning. The hybrid NO2 models for annual, summer and winter explained 60%, 58% and 63%, respectively, of the variance with traffic, population and harbour being identified as important predictors. The SO2 models were less robust with lower R(2) annual (44%), summer (53%) and winter (46%), in which industrial and traffic variables emerged as important predictors. The R(2) for PM10 models ranged from 80% to 85% with population and urban land use type emerging as predictor variables

Effect of short-term exposure to ambient nitrogen dioxide and particulate matter on repeated lung function measures in infancy: a South African birth cohort

BACKGROUND: The developing lung is highly susceptible to environmental toxicants, with both short- and long-term exposure to ambient air pollutants linked to early childhood effects. This study assessed the short-term exposure effects of nitrogen dioxide (NO2) and particulate matter (PM10) on lung function in infants aged 6 weeks, 6, 12 and 24 months, the early developmental phase of child growth. METHODS: Lung function was determined by multiple breath washout and tidal breathing measurement in non-sedated infants. Individual exposure to NO2 and PM10 was determined by hybrid land use regression and dispersion modelling, with two-week average estimates (preceding the test date). Linear mixed models were used to adjust for the repeated measures design and an age*exposure interaction was introduced to obtain effect estimates for each age group. RESULTS: There were 165 infants that had lung function testing, with 82 of them having more than one test occasion. Exposure to PM10 (mug/m(3)) resulted in a decline in tidal volume at 6 weeks [-0.4 ml (-0.9; 0.0), p = 0.065], 6 months [-0.5 ml (-1.0; 0.0), p = 0.046] and 12 months [-0.3 ml (-0.7; 0.0), p = 0.045]. PM10 was related to an increase in respiratory rate and minute ventilation, while a decline was observed for functional residual capacity for the same age groups, though not statistically significant for these outcomes. Such associations were however less evident for exposure to NO2, with inconsistent changes observed across measurement parameters and age groups. CONCLUSION: Our study suggests that PM10 results in acute lung function impairments among infants from a low-socioeconomic setting, while the association with NO2 is less convincing

Spatial variability of fine particle concentrations in three European areas.

Epidemiological studies of long-term air pollution effects have been hampered by difficulties in characterizing the spatial variation in air pollution. We conducted a study to assess the risk of long-term exposure to traffic-related air pollution for the development of inhalant allergy and asthma in children in Stockholm county, Munich and the Netherlands. Exposure to traffic-related air pollution was assessed through a 1-year monitoring program and regression modeling using exposure indicators. This paper documents the performance of the exposure monitoring strategy and the spatial variation of ambient particle concentrations. We measured the ambient concentration of PM2.5 and the reflectance of PM2.5 filters (‘soot’) at 40–42 sites representative of different exposure conditions of the three study populations. Each site was measured during four 14-day average sampling periods spread over one year (spring 1999 to summer 2000). In each study area, a continuous measurement site was operated to remove potential bias due to temporal variation. The selected approach was an efficient method to characterize spatial differences in annual average concentration between a large number of sites in each study area. Adjustment with data from the continuous measurement site improved the precision of the calculated annual averages, especially for PM2.5. Annual average PM2.5 concentrations ranged from 11 to 20 μg/m3 in Munich, from 8 to 16 μg/m3 in Stockholm and from 14 to 26 μg/m3 in the Netherlands. Larger spatial contrasts were found for the absorption coefficient of PM2.5. PM2.5 concentrations were on average 17–18% higher at traffic sites than at urban background sites, but PM2.5 absorption coefficients at traffic sites were between 31% and 55% increased above background. This suggests that spatial variation of traffic-related air pollution may be underestimated if PM2.5 only is measured