The ESCAPE study (European Study of Cohorts for Air Pollution Effects) investigates long-term effects of exposure to air pollution on human health in Europe. This paper documents the spatial ...variation of measured NO2 and NOx concentrations between and within 36 ESCAPE study areas across Europe.
In all study areas NO2 and NOx were measured using standardized methods between October 2008 and April 2011. On average, 41 sites were selected per study area, including regional and urban background as well as street sites. The measurements were conducted in three different seasons, using Ogawa badges. Average concentrations for each site were calculated after adjustment for temporal variation using data obtained from a routine monitor background site.
Substantial spatial variability was found in NO2 and NOx concentrations between and within study areas; 40% of the overall NO2 variance was attributable to the variability between study areas and 60% to variability within study areas. The corresponding values for NOx were 30% and 70%. The within-area spatial variability was mostly determined by differences between street and urban background concentrations. The street/urban background concentration ratio for NO2 varied between 1.09 and 3.16 across areas. The highest median concentrations were observed in Southern Europe, the lowest in Northern Europe.
In conclusion, we found significant contrasts in annual average NO2 and NOx concentrations between and especially within 36 study areas across Europe. Epidemiological long-term studies should therefore consider different approaches for better characterization of the intra-urban contrasts, either by increasing of the number of monitors or by modelling.
► We measured NO2 and NOx in 36 European study areas using standardized method. ► Significant contrast in NO2 and NOx levels between and within areas were found. ► Concentrations were generally lower in Northern than in Southern Europe. ► Street/urban background contrast was higher than for the particle metrics. ► Epidemiological studies should characterize intra-urban contrasts.
Land use regression (LUR) models have been developed mostly to explain intraurban variations in air pollution based on often small local monitoring campaigns. Transferability of LUR models from city ...to city has been investigated, but little is known about the performance of models based on large numbers of monitoring sites covering a large area.
We aimed to develop European and regional LUR models and to examine their transferability to areas not used for model development.
We evaluated LUR models for nitrogen dioxide (NO2) and particulate matter (PM; PM2.5, PM2.5 absorbance) by combining standardized measurement data from 17 (PM) and 23 (NO2) ESCAPE (European Study of Cohorts for Air Pollution Effects) study areas across 14 European countries for PM and NO2. Models were evaluated with cross-validation (CV) and hold-out validation (HV). We investigated the transferability of the models by successively excluding each study area from model building.
The European model explained 56% of the concentration variability across all sites for NO2, 86% for PM2.5, and 70% for PM2.5 absorbance. The HV R2s were only slightly lower than the model R2 (NO2, 54%; PM2.5, 80%; PM2.5 absorbance, 70%). The European NO2, PM2.5, and PM2.5 absorbance models explained a median of 59%, 48%, and 70% of within-area variability in individual areas. The transferred models predicted a modest-to-large fraction of variability in areas that were excluded from model building (median R2: NO2, 59%; PM2.5, 42%; PM2.5 absorbance, 67%).
Using a large data set from 23 European study areas, we were able to develop LUR models for NO2 and PM metrics that predicted measurements made at independent sites and areas reasonably well. This finding is useful for assessing exposure in health studies conducted in areas where no measurements were conducted.
Indoor air quality is a growing concern as we spend the majority of time indoors and as new buildings are increasingly airtight for energy saving purposes. For a better understanding of residential ...indoor air pollution in Switzerland we conducted repeated 1-2-week-long indoor and outdoor measurements of particle number concentrations (PNC), particulate matter (PM), light absorbance of PM2.5 (PMabsorbance) and nitrogen dioxide (NO2). Residents of all homes were enrolled in the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA). Indoor levels were comparable in urban areas and generally low in rural homes. Average indoor levels were 7800 particles/cm(3) (interquartile range=7200); 8.7 μg/m(3) (6.5) PM2.5 and 10.2 μg/m(3) (11.2) NO2. All pollutants showed large variability of indoor/outdoor ratios between sites. We observed similar diurnal patterns for indoor and outdoor PNC. Nevertheless, the correlation of average indoor and outdoor PNC between sites as well as longitudinal indoor/outdoor correlations within sites were low. Our results show that a careful evaluation of home characteristics is needed when estimating indoor exposure to pollutants with outdoor origin.
Exposure during transport and at non-residential locations is ignored in most epidemiological studies of traffic-related air pollution. We investigated the impact of separately estimating NO2 ...long-term outdoor exposures at home, work/school, and while commuting on the association between this marker of exposure and potential health outcomes. We used spatially and temporally resolved commuter route data and model-based NO2 estimates of a population sample in Basel, Switzerland, to assign individual NO2-exposure estimates of increasing complexity, namely (1) home outdoor concentration; (2) time-weighted home and work/school concentrations; and (3) time-weighted concentration incorporating home, work/school and commute. On the basis of their covariance structure, we estimated the expectable relative differences in the regression slopes between a quantitative health outcome and our measures of individual NO2 exposure using a standard measurement error model. The traditional use of home outdoor NO2 alone indicated a 12% (95% CI: 11-14%) underestimation of related health effects as compared with integrating both home and work/school outdoor concentrations. Mean contribution of commuting to total weekly exposure was small (3.2%; range 0.1-13.5%). Thus, ignoring commute in the total population may not significantly underestimate health effects as compared with the model combining home and work/school. For individuals commuting between Basel-City and Basel-Country, ignoring commute may produce, however, a significant attenuation bias of 4% (95% CI: 4-5%). Our results illustrate the importance of including work/school locations in assessments of long-term exposures to traffic-related air pollutants such as NO2. Information on individuals' commuting behavior may further improve exposure estimates, especially for subjects having lengthy commutes along major transportation routes.
Summary Background Few studies on long-term exposure to air pollution and mortality have been reported from Europe. Within the multicentre European Study of Cohorts for Air Pollution Effects ...(ESCAPE), we aimed to investigate the association between natural-cause mortality and long-term exposure to several air pollutants. Methods We used data from 22 European cohort studies, which created a total study population of 367 251 participants. All cohorts were general population samples, although some were restricted to one sex only. With a strictly standardised protocol, we assessed residential exposure to air pollutants as annual average concentrations of particulate matter (PM) with diameters of less than 2·5 μm (PM2·5 ), less than 10 μm (PM10 ), and between 10 μm and 2·5 μm (PMcoarse ), PM2.5 absorbance, and annual average concentrations of nitrogen oxides (NO2 and NOx ), with land use regression models. We also investigated two traffic intensity variables—traffic intensity on the nearest road (vehicles per day) and total traffic load on all major roads within a 100 m buffer. We did cohort-specific statistical analyses using confounder models with increasing adjustment for confounder variables, and Cox proportional hazards models with a common protocol. We obtained pooled effect estimates through a random-effects meta-analysis. Findings The total study population consisted of 367 251 participants who contributed 5 118 039 person-years at risk (average follow-up 13·9 years), of whom 29 076 died from a natural cause during follow-up. A significantly increased hazard ratio (HR) for PM2·5 of 1·07 (95% CI 1·02–1·13) per 5 μg/m3 was recorded. No heterogeneity was noted between individual cohort effect estimates (I2 p value=0·95). HRs for PM2·5 remained significantly raised even when we included only participants exposed to pollutant concentrations lower than the European annual mean limit value of 25 μg/m3 (HR 1·06, 95% CI 1·00–1·12) or below 20 μg/m3 (1·07, 1·01–1·13). Interpretation Long-term exposure to fine particulate air pollution was associated with natural-cause mortality, even within concentration ranges well below the present European annual mean limit value. Funding European Community's Seventh Framework Program (FP7/2007–2011).
Land use regression models environmental predictors to estimate ground-floor air pollution concentration surfaces of a study area. While many cities are expanding vertically, such models typically ...ignore the vertical dimension.
We took integrated measurements of NO2 at up to three different floors on the facades of 25 buildings in the mid-sized European city of Basel, Switzerland. We quantified the decrease in NO2 concentration with increasing height at each facade over two 14-day periods in different seasons. Using predictors of traffic load, population density and street configuration, we built conventional land use regression (LUR) models which predicted ground floor concentrations. We further evaluated which predictors best explained the vertical decay rate. Ultimately, we combined ground floor and decay models to explain the measured concentrations at all heights.
We found a clear decrease in mean nitrogen dioxide concentrations between measurements at ground level and those at higher floors for both seasons. The median concentration decrease was 8.1% at 10 m above street level in winter and 10.4% in summer. The decrease with height was sharper at buildings where high concentrations were measured on the ground and in canyon-like street configurations. While the conventional ground floor model was able to explain ground floor concentrations with a model R2 of 0.84 (RMSE 4.1 μg/m3), it predicted measured concentrations at all heights with an R2 of 0.79 (RMSE 4.5 μg/m3), systematically overpredicting concentrations at higher floors. The LUR model considering vertical decay was able to predict ground floor and higher floor concentrations with a model R2 of 0.84 (RMSE 3.8 μg/m3) and without systematic bias.
Height above the ground is a relevant determinant of outdoor residential exposure, even in medium-sized European cities without much high-rise. It is likely that conventional LUR models overestimate exposure for residences at higher floors near major roads. This overestimation can be minimized by considering decay with height.
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•NO2 concentrations are typically 8 to 10% lower 10 m above the street than at street level.•The higher the NO2 concentration at ground level, the sharper the vertical decay.•Canyon-like street configurations trap NO2 at ground level, causing sharper vertical decay.•Land use regression (LUR) models can consider decay by including height as a predictor.•When predicting NO2 at higher floors, 3D LUR models outperformed conventional models.
Recent studies have linked acute respiratory and cardiovascular outcomes to measurements or estimates of traffic-related air pollutants at homes or schools. However, few studies have evaluated these ...outdoor measurements and estimates against personal exposure measurements. We compared measured and modeled home outdoor concentrations with personal measurements of traffic-related air pollutants in the Los Angeles air basin (Whittier and Riverside). Personal exposure of 63 children with asthma and 15 homes were assessed for particulate matter with an aerodynamic diameter less than 2.5 μm (PM
2.5
), elemental carbon (EC), and organic carbon (OC) during sixteen 10-day monitoring runs. Regression models to predict daily home outdoor PM
2.5
, EC, and OC were constructed using home outdoor measurements, geographical and meteorological parameters, as well as CALINE4 estimates at outdoor home sites, which represent the concentrations from local traffic sources. These home outdoor models showed the variance explained (
R
2
) was 0.97 and 0.94 for PM
2.5
, 0.91 and 0.83 for OC, and 0.76 and 0.87 for EC in Riverside and Whittier, respectively. The PM
2.5
outdoor estimates correlated well with the personal measurements (Riverside
R
2
= 0.65 and Whittier
R
2
= 0.69). However, excluding potentially inaccurate samples from Riverside, the correlation between personal exposure to carbonaceous species and home outdoor estimates in Whittier was moderate for EC (
R
2
= 0.37) and poor for OC (
R
2
= 0.08). The CALINE4 estimates alone were not correlated with personal measurements of EC or other pollutants. While home outdoor estimates provide good approximations for daily personal PM
2.5
exposure, they may not be adequate for estimating daily personal exposure to EC and OC.
Long-term ultrafine particle (UFP) exposure estimates at a fine spatial scale are needed for epidemiological studies. Land use regression (LUR) models were developed and evaluated for six European ...areas based on repeated 30 min monitoring following standardized protocols. In each area; Basel (Switzerland), Heraklion (Greece), Amsterdam, Maastricht, and Utrecht (“The Netherlands”), Norwich (United Kingdom), Sabadell (Spain), and Turin (Italy), 160–240 sites were monitored to develop LUR models by supervised stepwise selection of GIS predictors. For each area and all areas combined, 10 models were developed in stratified random selections of 90% of sites. UFP prediction robustness was evaluated with the intraclass correlation coefficient (ICC) at 31–50 external sites per area. Models from Basel and The Netherlands were validated against repeated 24 h outdoor measurements. Structure and model R 2 of local models were similar within, but varied between areas (e.g., 38–43% Turin; 25–31% Sabadell). Robustness of predictions within areas was high (ICC 0.73–0.98). External validation R 2 was 53% in Basel and 50% in The Netherlands. Combined area models were robust (ICC 0.93–1.00) and explained UFP variation almost equally well as local models. In conclusion, robust UFP LUR models could be developed on short-term monitoring, explaining around 50% of spatial variance in longer-term measurements.
Background: Air pollution has been associated with cardiovascular mortality, but it remains unclear as to whether specific pollutants are related to specific cardiovascular causes of death. Within ...the multicenter European Study of Cohorts for Air Pollution Effects (ESCAPE), we investigated the associations of long-term exposure to several air pollutants with all cardiovascular disease (CVD) mortality, as well as with specific cardiovascular causes of death. Methods: Data from 22 European cohort studies were used. Using a standardized protocol, study area–specific air pollution exposure at the residential address was characterized as annual average concentrations of the following: nitrogen oxides (NO2 and NOx); particles with diameters of less than 2.5 μm (PM2.5), less than 10 μm (PM10), and 10 μm to 2.5 μm (PMcoarse); PM2.5 absorbance estimated by land-use regression models; and traffic indicators. We applied cohort-specific Cox proportional hazards models using a standardized protocol. Random-effects meta-analysis was used to obtain pooled effect estimates. Results: The total study population consisted of 367,383 participants, with 9994 deaths from CVD (including 4,992 from ischemic heart disease, 2264 from myocardial infarction, and 2484 from cerebrovascular disease). All hazard ratios were approximately 1.0, except for particle mass and cerebrovascular disease mortality; for PM2.5, the hazard ratio was 1.21 (95% confidence interval = 0.87–1.69) per 5 μg/m3 and for PM10, 1.22 (0.91–1.63) per 10 μg/m3. Conclusion: In a joint analysis of data from 22 European cohorts, most hazard ratios for the association of air pollutants with mortality from overall CVD and with specific CVDs were approximately 1.0, with the exception of particulate mass and cerebrovascular disease mortality for which there was suggestive evidence for an association.
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