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Abstract: The insulation of residential buildings affects human exposure to fine particles. According to current EU guidelines, insulation is regulated for energy saving reasons. As buildings become tighter, the air exchange rate is reduced and, thus, the indoor concentration of pollutants is increased if there are significant indoor sources. While usually the effects of heat insulation and increase of the air-tightness of buildings on greenhouse gas emissions are highlighted, the negative impacts on human health due to higher indoor concentrations are not addressed. Thus, we investigated these impacts using scenarios in three European countries, i. e. Czech Republic, Switzerland and Greece. The assessment was based on modelling the human exposure to fine particles originating from sources of particles within outdoor and indoor air, including environmental tobacco smoke. Exposure response relationships were derived to link (adverse) health effects to the exposure. Furthermore, probable values for the parameters influencing the infiltration of fine particles into residential buildings were modelled. Results show that the insulation and increase of the air-tightness of residential buildings leads to an overall increase of the mean population exposure – and consequently adverse health effects – in all considered countries (ranging for health effects from 0.4% in Czech Republic to 11.8% in Greece for 100% insulated buildings) due to an accumulation of particles indoors, especially from environmental tobacco smoke. Considering only the emission reductions in outdoor air (omitting changes in infiltration parameters) leads to a decrease of adverse health effects. This study highlights the importance of ensuring a sufficient air exchange rate when insulating buildings, e. g. by prescribing heat ventilation and air conditioning systems in new buildings and information campaigns on good airing practice in renovated buildings. It also shows that assessing policy measures based on the exposure may provide different recommendations compared to an assessment based on only the outdoor air concentration. [Copyright &y& Elsevier]

Background: Few studies have investigated the independent health effects of different size fractions of particulate matter (PM) in multiple locations, especially in Europe. Objectives: We estimated the short-term effects of PM with aerodynamic diameter ≤ 10 µm (PM10), ≤ 2.5 µm (PM2.5), and between 2.5 and 10 µm (PM2.5−10) on all-cause, cardiovascular, and respiratory mortality in 10 European Mediterranean metropolitan areas within the MEDPARTICLES project. Methods: We analyzed data from each city using Poisson regression models, and combined city-specific estimates to derive overall effect estimates. We evaluated the sensitivity of our estimates to co-pollutant exposures and city-specific model choice, and investigated effect modification by age, sex, and season. We applied distributed lag and threshold models to investigate temporal patterns of associations. Results: A 10-µg/m3 increase in PM2.5 was associated with a 0.55% (95% CI: 0.27, 0.84%) increase in all-cause mortality (0−1 day cumulative lag), and a 1.91% increase (95% CI: 0.71, 3.12%) in respiratory mortality (0−5 day lag). In general, associations were stronger for cardiovascular and respiratory mortality than all-cause mortality, during warm versus cold months, and among those ≥ 75 versus < 75 years of age. Associations with PM2.5−10 were positive but not statistically significant in most analyses, whereas associations with PM10 seemed to be driven by PM2.5. Conclusions: We found evidence of adverse effects of PM2.5 on mortality outcomes in the European Mediterranean region. Associations with PM2.5−10 were positive but smaller in magnitude. Associations were stronger for respiratory mortality when cumulative exposures were lagged over 0−5 days, and were modified by season and age. [ABSTRACT FROM AUTHOR]

Abstract: The adverse consequences of particulate matter (PM) on human health have been well documented. Recently, special attention has been given to mineral dust particles, which may be a serious health threat. The main global source of atmospheric mineral dust is the Sahara desert, which produces about half of the annual mineral dust. Sahara dust transport can lead to PM levels that substantially exceed the established limit values. A review was undertaken using the ISI web of knowledge database with the objective to identify all studies presenting results on the potential health impact from Sahara dust particles. The review of the literature shows that the association of fine particles, PM2.5, with total or cause‐specific daily mortality is not significant during Saharan dust intrusions. However, regarding coarser fractions PM10 and PM2.5–10 an explicit answer cannot be given. Some of the published studies state that they increase mortality during Sahara dust days while other studies find no association between mortality and PM10 or PM2.5–10. The main conclusion of this review is that health impact of Saharan dust outbreaks needs to be further explored. Considering the diverse outcomes for PM10 and PM2.5–10, future studies should focus on the chemical characterization and potential toxicity of coarse particles transported from Sahara desert mixed or not with anthropogenic pollutants. The results of this review may be considered to establish the objectives and strategies of a new European directive on ambient air quality. An implication for public policy in Europe is that to protect public health, anthropogenic sources of particulate pollution need to be more rigorously controlled in areas highly impacted by the Sahara dust. [Copyright &y& Elsevier]

Polycyclic aromatic hydrocarbons (PAHs) were investigated in size-segregated particulate samples collected in a series of 7-week sampling campaigns in Europe 2002–2003. The principal objective of the study was to provide new insight into the distribution of PAHs between ultrafine, fine and coarse particle size ranges during different particulate pollution situations in Europe. The samplings were conducted in urban background sites of six cities: Duisburg, Germany (autumn), Prague, Czech Republic (winter), Amsterdam, The Netherlands (winter), Helsinki, Finland (spring), Barcelona, Spain (spring) and Athens, Greece (summer). Particulate samples were collected in 3- and 4-day periods per week using a high volume cascade impactor (HVCI). 32 PAHs were analysed from pooled samples in ultrafine (PM0.2), fine (PM0.2–2.5) and coarse (PM2.5–10) size ranges. The campaigns showed different PAH profiles, not only by concentration but also by detailed PAH composition. The PAH concentrations were high (PM10-PAH 9.9–55 ng m−3) in the autumn and winter campaigns compared to spring and summer samples (PM10-PAH 2.9–5.2 ng m−3). In Prague, the PAH contribution was the highest in PM0.2, whereas in the five other cities the PAH contribution was the highest in PM0.2–2.5. PAHs with four rings had a large contribution (41–47% of total PAH concentration in PM10) to the total PAHs in each of the campaigns. In cold-season campaigns, the contributions of the 5- and 6-ring PAHs, many of which are suspected carcinogens or genotoxic agents, became prominent in the fine (28–45%) and ultrafine (41–65%) size ranges. The representativeness of benzo[a]pyrene as a marker of total and known carcinogenic PAHs was poorer than that of benzo[k]fluoranthene. [Copyright &y& Elsevier]

The fine particle and gas emissions from the residential wood combustion (RWC) appear to be a major contributor to winter-time pollution in Europe. In this study, we characterized the effect of two different combustion conditions on particulate and gaseous emissions from a conventional masonry heater. Normal combustion (NC) is the best available operational practice for the heater, whereas smoldering combustion (SC) mimicked slow heating combustion. It was found that the operational practice in RWC can significantly influence the quantity and quality of particle and gaseous emissions into the atmosphere. In SC, the emissions of carbon monoxide were 3.5-fold, total volatile organics 14-fold and PM1 6-fold to those of NC, whereas the mass of the inorganic compounds (“fine ash”) and particle number emissions were lower from SC than from NC. According to electron microscopy analyses, the observed fine ash particles seemed to occur mainly as separate spherical or irregularly shaped particles but not as agglomerates. Ultrafine (<100nm) fine ash particles were composed mainly of K, S and Zn, but also in a lesser extent of C, Ca, Fe, Mg, Cl, P and Na. Large agglomerates were found to contain mainly carbon and are considered to be primarily soot particles. The larger spherical and irregularly shaped particles were composed of same alkali metal compounds as ultrafine particles, but they were probably covered with heavy organic compounds. From SC, particles were composed mainly of carbon compounds and they had a more closed structure than the particles from NC, due to organic matter on the particles. In the present experiments, the ultrafine mode in the particle number distributions seemed to be determined mainly by the amount of released ash forming material in combustion, and the shifting of particle size during different combustion conditions seemed to be determined by the amount of condensed organic vapor in the flue gas. [Copyright &y& Elsevier]

The performance of a modified Harvard high-volume cascade impactor (HVCI) was evaluated in six field campaigns with size-segregated particulate samplings for chemical and toxicological characterization. The 7-week sampling campaigns in 2002–2003 in Duisburg (autumn), Prague (winter), Amsterdam (winter), Helsinki (spring), Barcelona (spring), and Athens (summer) were selected to represent contrasting urban environments and seasons of public health interest due to high particulate concentrations or previous findings in epidemiological studies. Particulate samples were collected in parallel with the HVCI (PM10–2. 5, PM2. 5–1, PM1–0. 2, PM0. 2), a virtual impactor (VI; PM10–2. 5, PM2. 5), and a Berner low-pressure impactor (BLPI; 10 stages between 0. 035 and 10 μm in particle diameter) using a 3-or 4-day sampling duration. The campaigns exhibited different profiles with regard to particulate mass concentration, size distribution, chemical composition and meteorological conditions, thus providing a demanding setup for an overall field comparison of the HVCI with the VI and BLPI reference samplers. Size-segregated particulate mass concentration could be reasonably well measured with the present HVCI configuration. The coarse (PM10–2. 5) and fine (PM2. 5) particulate mass agreed within 10% with the low-volume reference samplers, and the four-stage size distribution of the HVCI followed the modal pattern of urban aerosol. The concentrations of chemical constituents measured and integrated especially for the HVCI-PM2. 5 differed to some extent from those measured from the corresponding VI-PM2. 5 samples. This implies that when investigating the association of toxicological responses with the chemical constituents of particulate matter, it is necessary to use the chemical composition data of the same samples as used in toxicological experiments. [Copyright &y& Elsevier]

The emission of fine particles (FP) generated by biomass combustion poses a substantial health risk. The immediate emissions from biomass boilers are mainly influenced by the operating parameters. The authors of this article present the results of an experimental identification of the real FP emissions from small biomass boilers and residential stoves in Central Europe. A single method was used in the study to measure the FP emissions from an automatic boiler burning spruce pellets and from a manual stove burning beech logs. The measurement is extended by a thermo-gravimetric analysis of samples of the fuels used, supplemented with an analysis of the emitted particles. The boilers were tested in an operating cycle that included the phases of fuel ignition, steady combustion, and afterburning. The paper presents the concentrations and size distributions observed of the emitted FP ranging from 17 to 544 nm in size. Operating cycles including a "cold start" and "warm start" are compared. The results achieved are summarized by the expression of the nominal FP emission presenting the number and mass emission corresponding to burning 1 kg of fuel. The tested automatic boiler fed by spruce pellets produced a nominal FP emission of 173 mg kg−1 in the size range of 17–544 nm during the testing operation cycle. The tested manual stove, fed by beech logs, produced a nominal emission of 1043 mg kg−1 in the same size range of particles during the similar testing cycle. Image 1 [ABSTRACT FROM AUTHOR]

Numerous epidemiological studies have confirmed the negative influences of air pollutants on human health, where fine particles (PM2.5) and nitrogen dioxide (NO 2 ) cause the highest health risks. However, the traditional studies have only involved the ambient concentration for a short to medium time period, which ignores the influence of indoor sources, the individual time-activity pattern, and the fact that the health status is impacted by the long-term accumulated exposure. The aim of this paper is to develop a methodology to simulate the lifelong exposure (rather than outdoor concentration) to PM2.5 and NO 2 for individuals in Europe. This method is realized by developing a probabilistic model that integrates an outdoor air quality model, a model estimating indoor air pollution, an exposure model, and a life course trajectory model for predicting retrospectively the employment status. This approach has been applied to samples of two population studies in the frame of the European Commission FP7-ENVIRONMENT research project HEALS (Health and Environment-wide Associations based on Large Population Surveys), where socioeconomic data of the participants have been collected. Results show that the simulated exposures to both pollutants for the samples are influenced by socio-demographic characteristics, including age, gender, residential location, employment status and smoking habits. Both outdoor concentrations and indoor sources play an important role in the total exposure. Moreover, large variances have been observed among countries and cities. The application of this methodology provides valuable insights for the exposure modelling, as well as important input data for exploring the correlation between exposure and health impacts., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Empirical spatial air pollution models have been applied extensively to assess exposure in epidemiological studies with increasingly sophisticated and complex statistical algorithms beyond ordinary linear regression. However, different algorithms have rarely been compared in terms of their predictive ability. This study compared 16 algorithms to predict annual average fine particle (PM 2.5) and nitrogen dioxide (NO 2) concentrations across Europe. The evaluated algorithms included linear stepwise regression, regularization techniques and machine learning methods. Air pollution models were developed based on the 2010 routine monitoring data from the AIRBASE dataset maintained by the European Environmental Agency (543 sites for PM 2.5 and 2399 sites for NO 2), using satellite observations, dispersion model estimates and land use variables as predictors. We compared the models by performing five-fold cross-validation (CV) and by external validation (EV) using annual average concentrations measured at 416 (PM 2.5) and 1396 sites (NO 2) from the ESCAPE study. We further assessed the correlations between predictions by each pair of algorithms at the ESCAPE sites. For PM 2.5 , the models performed similarly across algorithms with a mean CV R2 of 0.59 and a mean EV R2 of 0.53. Generalized boosted machine, random forest and bagging performed best (CV R2~0.63; EV R2 0.58–0.61), while backward stepwise linear regression, support vector regression and artificial neural network performed less well (CV R2 0.48–0.57; EV R2 0.39–0.46). Most of the PM 2.5 model predictions at ESCAPE sites were highly correlated (R2 > 0.85, with the exception of predictions from the artificial neural network). For NO 2 , the models performed even more similarly across different algorithms, with CV R2s ranging from 0.57 to 0.62, and EV R2s ranging from 0.49 to 0.51. The predicted concentrations from all algorithms at ESCAPE sites were highly correlated (R2 > 0.9). For both pollutants, biases were low for all models except the artificial neural network. Dispersion model estimates and satellite observations were two of the most important predictors for PM 2.5 models whilst dispersion model estimates and traffic variables were most important for NO 2 models in all algorithms that allow assessment of the importance of variables. Different statistical algorithms performed similarly when modelling spatial variation in annual average air pollution concentrations using a large number of training sites. • Multiple statistical algorithms with very different assumptions were compared. • Despite the difference in modeling frameworks, predictions among the models exhibit generally good agreement. • The use of an external evaluation dataset strengthens evaluation by cross-validation. [ABSTRACT FROM AUTHOR]

Background: One of the potential mechanisms linking air pollution to health effects is through changes in DNA-methylation, which so far has mainly been analyzed globally or at candidate sites., Objective: We investigated the association of personal and ambient air pollution exposure measures with genome-wide DNA-methylation changes., Methods: We collected repeated 24-hour personal and ambient exposure measurements of particulate matter (PM 2.5 ), PM 2.5 absorbance, and ultrafine particles (UFP) and peripheral blood samples from a panel of 157 healthy non-smoking adults living in four European countries. We applied univariate mixed-effects models to investigate the association between air pollution and genome-wide DNA-methylation perturbations at single CpG (cytosine-guanine dinucleotide) sites and in Differentially Methylated Regions (DMRs). Subsequently, we explored the association of air pollution-induced methylation alterations with gene expression and serum immune marker levels measured in the same subjects., Results: Personal exposure to PM 2.5 was associated with methylation changes at 13 CpG sites and 69 DMRs. Two of the 13 identified CpG sites (mapped to genes KNDC1 and FAM50B) were located within these DMRs. In addition, 42 DMRs were associated with personal PM 2.5 absorbance exposure, 16 DMRs with personal exposure to UFP, 4 DMRs with ambient exposure to PM 2.5 , 16 DMRs with ambient PM 2.5 absorbance exposure, and 15 DMRs with ambient UFP exposure. Correlation between methylation levels at identified CpG sites and gene expression and immune markers was generally moderate., Conclusion: This study provides evidence for an association between 24-hour exposure to air pollution and DNA-methylation at single sites and regional clusters of CpGs. Analysis of differentially methylated regions provides a promising avenue to further explore the subtle impact of environmental exposures on DNA-methylation., (Copyright © 2018 Elsevier Ltd. All rights reserved.)