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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Effects of long-term exposure to traffic-related air pollution on mortality and lung cancer

We assessed the association between long-term exposure to air pollution and cause-specific mortality and lung cancer incidence using data from an ongoing cohort study: the Netherlands Cohort Study on Diet and Cancer (NLCS). The NLCS study was initiated in September 1986 with the enrollment of 120,852 subjects aged 55-69 years living in 204 municipalities located throughout the Netherlands. Long-term exposure to nitrogen dioxide (NO2), black smoke (BS), fine particles less than 2.5 ?m (PM2.5) and sulfur dioxide (SO2) was estimated. Exposure at each home address was considered as a function of a regional, an urban and a local component. The regional component was estimated using inverse distance weighed interpolation of measurement data from regional background sites in the national monitoring network. The urban component was estimated using regression models with urban concentrations as dependent variables, and number of inhabitants in different buffers and land use variables, derived with a Geographic Information System (GIS), as predictor variables. The local component was assessed using a GIS and a digital road network with linked traffic intensities. Traffic intensity on the nearest road and the total traffic intensity in a 100 m buffer around each home address were assessed. The methods that were developed explained a relatively large percentage of the spatial variance of the air pollution components. Air pollution and several traffic exposure variables were associated with mortality, but the relative risks were generally small. Statistically significant associations between NO2 and black smoke exposure and natural cause and respiratory mortality were found. The highest relative risks were found for respiratory mortality. We found suggestive evidence for larger effects of black smoke exposure in those with low education and in those with low fruit consumption. We found no association between air pollution concentrations, traffic variables and lung cancer incidence in the full study population. In never smokers, associations between black smoke concentrations and traffic variables with lung cancer incidence were (borderline) significant, however. This is the first time that the effects of air pollution, traffic intensity and traffic noise on cardiovascular mortality have been studied together. We observed an association between traffic intensity on the nearest road and overall cardiovascular mortality, which was driven by an association with ischemic heart disease mortality. Relative risks for background black smoke concentrations were elevated for cerebrovascular and heart failure mortality. These associations were not affected by adjustment for traffic noise. There was an indication of an effect of traffic noise in the highest noise exposure category (> 65 dB(A)), which was largely restricted to heart failure mortality. The relative risk for the association between ischemic heart disease mortality and high traffic noise was reduced to unity after adjustment for background black smoke concentrations and traffic intensity. The associations between traffic intensity on the nearest road with overall cardiovascular mortality and ischemic heart disease mortality were not explained by traffic noise. Overall, the results provide evidence that exposure to background and to traffic-related air pollution increases the risk of cardiovascular, respiratory and lung cancer mortality

Comparison of the performances of land use regression modelling and dispersion modelling in estimating small-scale variations in long-term air pollution concentrations in a Dutch urban area.

The performance of a Land Use Regression (LUR) model and a dispersion model (URBIS - URBis Information System) was compared in a Dutch urban area. For the Rijnmond area, i.e. Rotterdam and surroundings, nitrogen dioxide (NO2) concentrations for 2001 were estimated for nearly 70 000 centroids of a regular grid of 100 × 100 m. A LUR model based upon measurements carried out on 44 sites from the Dutch national monitoring network and upon Geographic Information System (GIS) predictor variables including traffic intensity, industry, population and residential land use was developed. Interpolation of regional background concentration measurements was used to obtain the regional background. The URBIS system was used to estimate NO2 concentrations using dispersion modelling. URBIS includes the CAR model (Calculation of Air pollution from Road traffic) to calculate concentrations of air pollutants near urban roads and Gaussian plume models to calculate air pollution levels near motorways and industrial sources. Background concentrations were accounted for using 1 × 1 km maps derived from monitoring and model calculations. Moderate agreement was found between the URBIS and LUR in calculating NO2 concentrations (R = 0.55). The predictions agreed well for the central part of the concentration distribution but differed substantially for the highest and lowest concentrations. The URBIS dispersion model performed better than the LUR model (R = 0.77 versus R = 0.47 respectively) in the comparison between measured and calculated concentrations on 18 validation sites. Differences can be understood because of the use of different regional background concentrations, inclusion of rather coarse land use category industry as a predictor variable in the LUR model and different treatment of conversion of NO to NO2. Moderate agreement was found between a dispersion model and a land use regression model in calculating annual average NO2 concentrations in an area with multiple sources. The dispersion model explained concentrations at validation sites better

Systematic evaluation of land use regression models for NO₂

Land use regression (LUR) models have become popular to explain the spatial variation of air pollution concentrations. Independent evaluation is important. We developed LUR models for nitrogen dioxide (NO(2)) using measurements conducted at 144 sampling sites in The Netherlands. Sites were randomly divided into training data sets with a size of 24, 36, 48, 72, 96, 108, and 120 sites. LUR models were evaluated using (1) internal "leave-one-out-cross-validation (LOOCV)" within the training data sets and (2) external "hold-out" validation (HV) against independent test data sets. In addition, we calculated Mean Square Error based validation R(2)s. The mean adjusted model and LOOCV R(2) slightly decreased from 0.87 to 0.82 and 0.83 to 0.79, respectively, with an increasing number of training sites. In contrast, the mean HV R(2) was lowest (0.60) with the smallest training sets and increased to 0.74 with the largest training sets. Predicted concentrations were more accurate in sites with out of range values for prediction variables after changing these values to the minimum or maximum of the range observed in the corresponding training data set. LUR models for NO(2) perform less well, when evaluated against independent measurements, when they are based on relatively small training sets. In our specific application, models based on as few as 24 training sites, however, achieved acceptable hold out validation R(2)s of, on average, 0.60

Mapping of background air pollution at a fine spatial scale across the European Union.

BACKGROUND: There is a need to understand much more about the geographic variation of air pollutants. This requires the ability to extrapolate from monitoring stations to unsampled locations. The aim was to assess methods to develop accurate and high resolution maps of background air pollution across the EU. METHODS: We compared the validity of ordinary kriging, universal kriging and regression mapping in developing EU-wide maps of air pollution on a 1x1 km resolution. Predictions were made for the year 2001 for nitrogen dioxide (NO(2)), fine particle

Comparison of land-use regression models between Great Britain and the Netherlands.

Land-use regression models have increasingly been applied for air pollution mapping at typically the city level. Though models generally predict spatial variability well, the structure of models differs widely between studies. The observed differences in the models may be due to artefacts of data and methodology or underlying differences in source or dispersion characteristics. If the former, more standardised methods using common data sets could be beneficial. We compared land-use regression models for NO2 and PM10, developed with a consistent protocol in Great Britain (GB) and the Netherlands (NL). Models were constructed on the basis of 2001 annual mean concentrations from the national air quality networks. Predictor variables used for modelling related to traffic, population, land use and topography. Four sets of models were developed for each country. First, predictor variables derived from data sets common to both countries were used in a pooled analysis, including an indicator for country and interaction terms between country and the identified predictor variables. Second, the common data sets were used to develop individual baseline models for each country. Third, the country-specific baseline models were applied after calibration in the other country to explore transferability. The fourth model was developed using the best possible predictor variables for each country. A common model for GB and NL explained NO2 concentrations well (adjusted R2 0.64), with no significant differences in intercept and slopes between the two countries. The country-specific model developed on common variables for NL but not GB improved the prediction. The performance of models based upon common data was only slightly worse than models optimised with local data. Models transferred to the other country performed substantially worse than the country-specific models. In conclusion, care is needed both in transferring models across different study areas, and in developing large inter-regional LUR models

Long-term exposure to air pollution and vascular damage in young adults

BACKGROUND: Long-term exposure to ambient air pollution has recently been linked to atherosclerosis and cardiovascular events. There are, however, very limited data in healthy young people. We examined the association between air pollutants and indicators of vascular damage in a cohort of young adults. METHODS: We used data from the Atherosclerosis Risk in Young Adults study. We estimated exposure to nitrogen dioxide (NO2), particulate matter less than 2.5 microm in aerodynamic diameter (PM2.5), black smoke, sulfur dioxide (SO2), and various traffic indicators for participants' 2000 home addresses. Exposure for the year 2000 was estimated by land-use regression models incorporating regional background annual air pollution levels, land-use variables, population densities, and traffic intensities on nearby roads. Outcomes were common carotid artery intima-media thickness (n = 745), aortic pulse wave velocity (n = 524), and augmentation index (n = 729). RESULTS: Exposure contrasts were substantial for NO2, SO2, and black smoke (5th-95th percentiles = 19.7 to 44.9, 2.5 to 5.2, and 8.6 to 19.4 microg/m3, respectively) and smaller for PM2.5 (16.5 to 19.9 microg/m3). The variability of carotid artery intima-media thickness was less than for pulse wave velocity and especially augmentation index (5-95th percentiles = 0.42 to 0.58 mm, 4.9 to 7.4 m/s and -12.3% to 27.3%, respectively). No associations were found between any of the pollutants or traffic indicators and carotid artery intima-media thickness, although PM2.5 effect estimates were in line with previous studies. We observed a 4.1% (95% confidence interval = 0.1% to 8.0%) increase in pulse wave velocity and a 37.6% (2.2% to 72.9%) increase in augmentation index associated with a 25 microg/m3 increase in NO2, and a 5.3% (0.1% to 10.4%) increase in pulse wave velocity with a 5 microg/m3 increase in SO2. PM2.5 and black smoke were not associated with either of these 2 outcomes. CONCLUSIONS: Air pollution may accelerate arterial-wall stiffening in young adults. Small outcome variability and lack of residential mobility data may have limited the power to detect an effect on intima-media thickness

Effects of long-term exposure to traffic-related air pollution on respiratory and cardiovascular mortality in the Netherlands: the NLCS-AIR study.

Evidence is increasing that long-term exposure to ambient air pollution is associated with deaths from cardiopulmonary diseases. In a 2002 pilot study, we reported clear indications that traffic-related air pollution, especially at the local scale, was related to cardiopulmonary mortality in a randomly selected subcohort of 5000 older adults participating in the ongoing Netherlands Cohort Study (NLCS) on diet and cancer. In the current study, referred to as NLCS-AIR, our objective was to obtain more precise estimates of the effects of traffic-related air pollution by analyzing associations with cause-specific mortality, as well as lung cancer incidence, in the full cohort of approximately 120,000 subjects. Cohort members were 55 to 69 years of age at enrollment in 1986. Follow-up was from 1987 through 1996 for mortality (17,674 deaths) and from late 1986 through 1997 for lung cancer incidence (2234 cases). Information about potential confounding variables and effect modifiers was available from the questionnaire that subjects completed at enrollment and from publicly available data (including neighborhood-scale information such as income distributions). The NLCS was designed for a case-cohort approach, which makes use of all the cases in the full cohort, while data for the random subcohort are used to estimate person-time experience in the study. Full information on confounders was available for the subjects in the random subcohort and for the emerging cases of mortality and lung cancer incidence during the follow-up period, and in NLCS-AIR we used the case-cohort approach to examine the relation between exposure to air pollution and cause-specific mortality and lung cancer. We also specified a standard Cox proportional hazards model within the full cohort, for which information on potential confounding variables was much more limited. Exposure to air pollution was estimated for the subjects' home addresses at baseline in 1986. Concentrations were estimated for black smoke (a simple marker for soot) and nitrogen dioxide (NO2) as indicators of traffic-related air pollution, as well as nitric oxide (NO), sulfur dioxide (SO2), and particulate matter with aerodynamic diameter 65 A-weighted decibels (dB(A); decibels with the sound pressure scale adjusted to conform with the frequency response of the human ear). Examination of sex, smoking status, educational level, and vegetable and fruit intake as possible effect modifiers showed that for overall black smoke concentrations, associations with mortality tended to be stronger in case-cohort subjects with lower levels of education and those with low fruit intake, but differences between strata were not statistically significant. For lung cancer incidence, we found essentially no relation to exposure to NO2, black smoke, PM2.5, SO2, or several traffic indicators. Associations of overall air pollution concentrations and traffic indicator variables with lung cancer incidence were, however, found in subjects who had never smoked, with an RR of 1.47 (95% CI, 1.01-2.16) for a 10-microg/m3 increase in overall black smoke concentration. In the current study, the mortality risks associated with both background air pollution and traffic exposure variables were much smaller than the estimate previously reported in the pilot study for risk of cardiopulmonary mortality associated with living near a major road (RR, 1.95; 95% CI, 1.09-3.51). The differences are most likely due to the extension of the follow-up period in the current study and to random error in the pilot study related to sampling from the full cohort. Though relative risks were generally small in the current study, long-term average concentrations of black smoke, NO2, and PM2.5 were related to mortality, and associations of black smoke and NO2 exposure with natural-cause and respiratory mortality were statistically significant. Traffic intensity near the home was also related to natural-cause mortality. The highest relative risks associated with background air pollution and traffic variables were for respiratory mortality, though the number of deaths was smaller than for the other mortality categories

Ambient air pollution and low birthweight: a European cohort study (ESCAPE)

Ambient air pollution has been associated with restricted fetal growth, which is linked with adverse respiratory health in childhood. We assessed the effect of maternal exposure to low concentrations of ambient air pollution on birthweight. We pooled data from 14 population-based mother-child cohort studies in 12 European countries. Overall, the study population included 74-178 women who had singleton deliveries between Feb 11, 1994, and June 2, 2011, and for whom information about infant birthweight, gestational age, and sex was available. The primary outcome of interest was low birthweight at term (weight <2500 g at birth after 37 weeks of gestation). Mean concentrations of particulate matter with an aerodynamic diameter of less than 2·5 μm (PM2·5), less than 10 μm (PM10), and between 2·5 μm and 10 μm during pregnancy were estimated at maternal home addresses with temporally adjusted land-use regression models, as was PM2·5 absorbance and concentrations of nitrogen dioxide (NO2) and nitrogen oxides. We also investigated traffic density on the nearest road and total traffic load. We calculated pooled effect estimates with random-effects models. A 5 μg/m3 increase in concentration of PM2·5 during pregnancy was associated with an increased risk of low birthweight at term (adjusted odds ratio [OR] 1·18, 95% CI 1·06-1·33). An increased risk was also recorded for pregnancy concentrations lower than the present European Union annual PM2·5 limit of 25 μg/m3 (OR for 5 μg/m3 increase in participants exposed to concentrations of less than 20 μg/m3 1·41, 95% CI 1·20-1·65). PM10 (OR for 10 μg/m3 increase 1·16, 95% CI 1·00-1·35), NO2 (OR for 10 μg/m3 increase 1·09, 1·00-1·19), and traffic density on nearest street (OR for increase of 5000 vehicles per day 1·06, 1·01-1·11) were also associated with increased risk of low birthweight at term. The population attributable risk estimated for a reduction in PM2·5 concentration to 10 μg/m3 during pregnancy corresponded to a decrease of 22% (95% CI 8-33%) in cases of low birthweight at term. Exposure to ambient air pollutants and traffic during pregnancy is associated with restricted fetal growth. A substantial proportion of cases of low birthweight at term could be prevented in Europe if urban air pollution was reduced.The European Unio

The influence of meteorological factors and atmospheric pollutants on the risk of preterm birth

Atmospheric pollutants and meteorological conditions are suspected to be causes of preterm birth. We aimed to characterize their possible association with the risk of preterm birth (defined as birth occurring before 37 completed gestational weeks). We pooled individual data from 13 birth cohorts in 11 European countries (71,493 births from the period 1994-2011, European Study of Cohorts for Air Pollution Effects (ESCAPE)). City-specific meteorological data from routine monitors were averaged over time windows spanning from 1 week to the whole pregnancy. Atmospheric pollution measurements (nitrogen oxides and particulate matter) were combined with data from permanent monitors and land-use data into seasonally adjusted land-use regression models. Preterm birth risks assoc