Ulrich Quass

Development of Land Use Regression Models for PM2.5, PM2.5 Absorbance, PM10 and PMcoarse in 20 European Study Areas; Results of the ESCAPE Project

Land Use Regression (LUR) models have been used increasingly for modeling small-scale spatial variation in air pollution concentrations and estimating individual exposure for participants of cohort studies. Within the ESCAPE project, concentrations of PM(2.5), PM(2.5) absorbance, PM(10), and PM(coarse) were measured in 20 European study areas at 20 sites per area. GIS-derived predictor variables (e.g., traffic intensity, population, and land-use) were evaluated to model spatial variation of annual average concentrations for each study area. The median model explained variance (R(2)) was 71% for PM(2.5) (range across study areas 35-94%). Model R(2) was higher for PM(2.5) absorbance (median 89%, range 56-97%) and lower for PM(coarse) (median 68%, range 32- 81%). Models included between two and five predictor variables, with various traffic indicators as the most common predictors. Lower R(2) was related to small concentration variability or limited availability of predictor variables, especially traffic intensity. Cross validation R(2) results were on average 8-11% lower than model R(2). Careful selection of monitoring sites, examination of influential observations and skewed variable distributions were essential for developing stable LUR models. The final LUR models are used to estimate air pollution concentrations at the home addresses of participants in the health studies involved in ESCAPE.

Adult lung function and long-term air pollution exposure. ESCAPE: a multicentre cohort study and meta-analysis

The chronic impact of ambient air pollutants on lung function in adults is not fully understood. The objective of this study was to investigate the association of long-term exposure to ambient air pollution with lung function in adult participants from five cohorts in the European Study of Cohorts for Air Pollution Effects (ESCAPE). Residential exposure to nitrogen oxides (NO2, NOx) and particulate matter (PM) was modelled and traffic indicators were assessed in a standardised manner. The spirometric parameters forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) from 7613 subjects were considered as outcomes. Cohort-specific results were combined using meta-analysis. We did not observe an association of air pollution with longitudinal change in lung function, but we observed that a 10 μg·m−3 increase in NO2 exposure was associated with lower levels of FEV1 (−14.0 mL, 95% CI −25.8 to −2.1) and FVC (−14.9 mL, 95% CI −28.7 to −1.1). An increase of 10 μg·m−3 in PM10, but not other PM metrics (PM2.5, coarse fraction of PM, PM absorbance), was associated with a lower level of FEV1 (−44.6 mL, 95% CI −85.4 to −3.8) and FVC (−59.0 mL, 95% CI −112.3 to −5.6). The associations were particularly strong in obese persons. This study adds to the evidence for an adverse association of ambient air pollution with lung function in adults at very low levels in Europe. The ESCAPE study finds that, even at very low levels, air pollution has adverse effects on lung function in adults http://ow.ly/A1ssB

Development of Land Use Regression Models for Particle Composition in Twenty Study Areas in Europe

Land Use Regression (LUR) models have been used to describe and model spatial variability of annual mean concentrations of traffic related pollutants such as nitrogen dioxide (NO2), nitrogen oxides (NOx) and particulate matter (PM). No models have yet been published of elemental composition. As part of the ESCAPE project, we measured the elemental composition in both the PM10 and PM2.5 fraction sizes at 20 sites in each of 20 study areas across Europe. LUR models for eight a priori selected elements (copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V), and zinc (Zn)) were developed. Good models were developed for Cu, Fe, and Zn in both fractions (PM10 and PM2.5) explaining on average between 67 and 79% of the concentration variance (R(2)) with a large variability between areas. Traffic variables were the dominant predictors, reflecting nontailpipe emissions. Models for V and S in the PM10 and PM2.5 fractions and Si, Ni, and K in the PM10 fraction performed moderately with R(2) ranging from 50 to 61%. Si, NI, and K models for PM2.5 performed poorest with R(2) under 50%. The LUR models are used to estimate exposures to elemental composition in the health studies involved in ESCAPE.

Air Pollution and Respiratory Infections during Early Childhood: An Analysis of 10 European Birth Cohorts within the ESCAPE Project

Background: Few studies have investigated traffic-related air pollution as a risk factor for respiratory infections during early childhood. Objectives: We aimed to investigate the association between air pollution and pneumonia, croup, and otitis media in 10 European birth cohorts—BAMSE (Sweden), GASPII (Italy), GINIplus and LISAplus (Germany), MAAS (United Kingdom), PIAMA (the Netherlands), and four INMA cohorts (Spain)—and to derive combined effect estimates using meta-analysis. Methods: Parent report of physician-diagnosed pneumonia, otitis media, and croup during early childhood were assessed in relation to annual average pollutant levels [nitrogen dioxide (NO2), nitrogen oxide (NOx), particulate matter ≤ 2.5 μm (PM2.5), PM2.5 absorbance, PM10, PM2.5–10 (coarse PM)], which were estimated using land use regression models and assigned to children based on their residential address at birth. Identical protocols were used to develop regression models for each study area as part of the ESCAPE project. Logistic regression was used to calculate adjusted effect estimates for each study, and random-effects meta-analysis was used to calculate combined estimates. Results: For pneumonia, combined adjusted odds ratios (ORs) were elevated and statistically significant for all pollutants except PM2.5 (e.g., OR = 1.30; 95% CI: 1.02, 1.65 per 10-μg/m3 increase in NO2 and OR = 1.76; 95% CI: 1.00, 3.09 per 10-μg/m3 PM10). For otitis media and croup, results were generally null across all analyses except for NO2 and otitis media (OR = 1.09; 95% CI: 1.02, 1.16 per 10-μg/m3). Conclusion: Our meta-analysis of 10 European birth cohorts within the ESCAPE project found consistent evidence for an association between air pollution and pneumonia in early childhood, and some evidence for an association with otitis media. Citation: MacIntyre EA, Gehring U, Mölter A, Fuertes E, Klümper C, Krämer U, Quass U, Hoffmann B, Gascon M, Brunekreef B, Koppelman GH, Beelen R, Hoek G, Birk M, de Jongste JC, Smit HA, Cyrys J, Gruzieva O, Korek M, Bergström A, Agius RM, de Vocht F, Simpson A, Porta D, Forastiere F, Badaloni C, Cesaroni G, Esplugues A, Fernández-Somoano A, Lerxundi A, Sunyer J, Cirach M, Nieuwenhuijsen MJ, Pershagen G, Heinrich J. 2014. Air pollution and respiratory infections during early childhood: an analysis of 10 European birth cohorts within the ESCAPE project. Environ Health Perspect 122:107–113; http://dx.doi.org/10.1289/ehp.1306755

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.

Sources and source contributions to fine particles

Fine dust is currently seen is one of the major issues in air quality as being responsible for causing negative health effects. Hence it is important to derive information on particle sources and their contribution to the ambient concentrations. This paper reviews two recent studies related to fine particle sources in Germany. The first study deals with the attribution of source regions to PM10 mass concentrations in nine agglomeration areas of Germany. The second study focuses on the diffusive sources from traffic differentiating and quantifying the various non-exhaust related emissions at an Autobahn.

Respiratory Effects of Fine and Ultrafine Particles from Indoor Sources—A Randomized Sham-Controlled Exposure Study of Healthy Volunteers

Particulate air pollution is linked to impaired respiratory health. We analyzed particle emissions from common indoor sources (candles burning (CB), toasting bread (TB), frying sausages (FS)) and lung function in 55 healthy volunteers (mean age 33.0 years) in a randomized cross-over controlled exposure study. Lung-deposited particle surface area concentration (PSC), size-specific particle number concentration (PNC) up to 10 µm, and particle mass concentration (PMC) of PM1, PM2.5 and PM10 were determined during exposure (2 h). FEV1, FVC and MEF25%–75% was measured before, 4 h and 24 h after exposure. Wilcoxon-rank sum tests (comparing exposure scenarios) and mixed linear regression using particle concentrations and adjusting for personal characteristics, travel time and transportation means before exposure sessions were performed. While no effect was seen comparing the exposure scenarios and in the unadjusted model, inverse associations were found for PMC from CB and FS in relation to FEV1 and MEF25%–75%. with a change in 10 µg/m3 in PM2.5 from CB being associated with a change in FEV1 of −19 mL (95%-confidence interval:−43; 5) after 4 h. PMC from TB and PNC of UFP were not associated with lung function changes, but PSC from CB was. Elevated indoor fine particles from certain sources may be associated with small decreases in lung function in healthy adults.

Association Between Short-term Exposure to Ultrafine Particles and Mortality in Eight European Urban Areas.

Background: Epidemiologic evidence on the association between short-term exposure to ultrafine particles and mortality is weak, due to the lack of routine measurements of these particles and standardized multicenter studies. We investigated the relationship between ultrafine particles and particulate matter (PM) and daily mortality in eight European urban areas. Methods: We collected daily data on nonaccidental and cardiorespiratory mortality, particle number concentrations (as proxy for ultrafine particle number concentration), fine and coarse PM, gases and meteorologic parameters in eight urban areas of Finland, Sweden, Denmark, Germany, Italy, Spain, and Greece, between 1999 and 2013. We applied city-specific time-series Poisson regression models and pooled them with random-effects meta-analysis. Results: We estimated a weak, delayed association between particle number concentration and nonaccidental mortality, with mortality increasing by approximately 0.35% per 10,000 particles/cm3 increases in particle number concentration occurring 5 to 7 days before death. A similar pattern was found for cause-specific mortality. Estimates decreased after adjustment for fine particles (PM2.5) or nitrogen dioxide (NO2). The stronger association found between particle number concentration and mortality in the warmer season (1.14% increase) became null after adjustment for other pollutants. Conclusions: We found weak evidence of an association between daily ultrafine particles and mortality. Further studies are required with standardized protocols for ultrafine particle data collection in multiple European cities over extended study periods.

Air Pollution Monitoring Strategies and Technologies for Urban Areas

Current ambient air quality monitoring is solely based on fixed monitoring sites, not always reflecting the exposure and effects on humans. This article reviews the current situation in Europe, the USA and Asia and discusses the main differences and similarities. Based on the analysis of the relation between monitoring techniques and strategies as well as the analysis of current trends and developments in monitoring strategies, new concepts and directions of future urban monitoring networks and strategies are presented and discussed.

Arterial blood pressure responses to short-term exposure to fine and ultrafine particles from indoor sources - A randomized sham-controlled exposure study of healthy volunteers.

Objectives Particulate air pollution is linked to adverse cardiovascular effects. The aim of the study was to investigate the effect of short‐term exposure to indoor particles on blood pressure (BP). Methods We analyzed the association of particle emissions from indoor sources (candle burning, toasting bread, frying sausages) with BP changes in 54 healthy volunteers in a randomized cross‐over controlled exposure study. Particle mass concentration (PMC), size‐specific particle number concentration (PNC) and lung‐deposited particle surface area concentration (PSC) were measured during the 2 h exposure. Systolic and diastolic blood pressure were measured before, during, directly, 2, 4 and 24 h after exposure. We performed multiple mixed linear regression analyses of different particle metrics and BP. Results BP significantly increased with increasing PMC, PSC and PNC resulting from toasting bread. For example, an increase per 10 &mgr;g/m3 PM10 and PM2.5, systolic BP increased at all time points with largest changes 1 h after exposure initiation of 1.5 mmHg (95%‐CI: 1.1; 1.9) and of 2.2 mmHg (95%‐CI: 1.3; 3.1), respectively. Conclusions Our study suggests an association of short‐term exposure to fine and ultrafine particles emitted from toasting bread with increases in BP. Particles emitted from frying sausages and candle burning did not consistently affect BP. HighlightsOur study suggests differential effects of indoor exposure on blood pressure depending on source and particle metric.In contrast to particle exposure from toasting bread, frying sausages and burning candles showed no consistent association.Differences in chemical composition of source‐specific particles might account for these differential effects.SBP increased most rapidly in association with the commonly used metrics PM10 and PM2.5.Yet, the highest increase of SBP was observed 4 h after exposure for the metrics PNC and PSC.