A prospective study of the impact of air pollution on respiratory symptoms and infections in infants

Rationale: There is increasing evidence that short-term exposure to air pollution has a detrimental effect on respiratory health, but data from healthy populations, particularly infants, are scarce. Objectives: To assess the association of air pollution with frequency and severity of respiratory symptoms and infections measured weekly in healthy infants. Methods: In a prospective birth cohort of 366 infants of unselected mothers, respiratory health was assessed weekly by telephone interviews during the first year of life (19,106 total observations). Daily mean levels of particulate matter (PM10), nitrogen dioxide (NO2), and ozone (O3) were obtained from local monitoring stations. We determined the association of the preceding week's pollutant levels with symptom scores and respiratory tract infections using a generalized additive mixed model with an autoregressive component. In addition, we assessed whether neonatal lung function influences this association and whether duration of infectious episodes differed between weeks with normal PM10 and weeks with elevated levels. Measurements and Main Results: We found a significant association between air pollution and respiratory symptoms, particularly in the week after respiratory tract infections (risk ratio, 1.13 [1.02-1.24] per 10 μg/m(3) PM10 levels) and in infants with premorbid lung function. During times of elevated PM10 (>33.3 μg/m(3)), duration of respiratory tract infections increased by 20% (95% confidence interval, 2-42%). Conclusions: Exposure to even moderate levels of air pollution was associated with increased respiratory symptoms in healthy infants. Particularly in infants with premorbid lung function and inflammation, air pollution contributed to longer duration of infectious episodes with a potentially large socioeconomic impact.

Adaptations of intestinal macrophages to an antigen-rich environment

Intestinal macrophages, preferentially located in the subepithelial lamina propria, represent in humans the largest pool of tissue macrophages. To comply with their main task, i.e. the efficient removal of microbes and particulate matter that might have gained access to the mucosa from the intestinal lumen while maintaining local tissue homeostasis, several phenotypic and functional adaptations evolved. Most notably, microbe-associated molecular pattern (MAMP) receptors, including the lipopolysaccharide receptors CD14 and TLR4, but also the Fc receptors for IgA and IgG are absent on most intestinal Mø. Here we review recent findings on the phenotypic and functional adaptations of intestinal Mø and their implications for the pathogenesis of inflammatory bowel diseases.

The Importance of Scale for Spatial-confounding Bias and Precision of Spatial Regression Estimators

Increasingly, regression models are used when residuals are spatially correlated. Prominent examples include studies in environmental epidemiology to understand the chronic health effects of pollutants. I consider the effects of residual spatial structure on the bias and precision of regression coefficients, developing a simple framework in which to understand the key issues and derive informative analytic results. When the spatial residual is induced by an unmeasured confounder, regression models with spatial random effects and closely-related models such as kriging and penalized splines are biased, even when the residual variance components are known. Analytic and simulation results show how the bias depends on the spatial scales of the covariate and the residual; bias is reduced only when there is variation in the covariate at a scale smaller than the scale of the unmeasured confounding. I also discuss how the scales of the residual and the covariate affect efficiency and uncertainty estimation when the residuals can be considered independent of the covariate. In an application on the association between black carbon particulate matter air pollution and birth weight, controlling for large-scale spatial variation appears to reduce bias from unmeasured confounders, while increasing uncertainty in the estimated pollution effect.

Ozone and Mortality: A Meta-Analysis of Time-Series Studies and Comparison to a Multi-City Study (The National Morbidity, Mortality, and Air Pollution Study)

While many time-series studies of ozone and daily mortality identified positive associations,others yielded null or inconclusive results. We performed a meta-analysis of 144 effect estimates from 39 time-series studies, and estimated pooled effects by lags, age groups,cause-specific mortality, and concentration metrics. We compared results to estimates from the National Morbidity, Mortality, and Air Pollution Study (NMMAPS), a time-series study of 95 large U.S. cities from 1987 to 2000. Both meta-analysis and NMMAPS results provided strong evidence of a short-term association between ozone and mortality, with larger effects for cardiovascular and respiratory mortality, the elderly, and current day ozone exposure as compared to other single day lags. In both analyses, results were not sensitive to adjustment for particulate matter and model specifications. In the meta-analysis we found that a 10 ppb increase in daily ozone is associated with a 0.83 (95% confidence interval: 0.53, 1.12%) increase in total mortality, whereas the corresponding NMMAPS estimate is 0.25%(0.12, 0.39%). Meta-analysis results were consistently larger than those from NMMAPS,indicating publication bias. Additional publication bias is evident regarding the choice of lags in time-series studies, and the larger heterogeneity in posterior city-specific estimates in the meta-analysis, as compared with NMAMPS.

A BAYESIAN HIERARCHICAL MODEL FOR CONSTRAINED DISTRIBUTED LAG FUNCTIONS: ESTIMATING THE TIME COURSE OF HOSPITALIZATION ASSOCIATED WITH AIR POLLUTION EXPOSURE

Numerous time series studies have provided strong evidence of an association between increased levels of ambient air pollution and increased levels of hospital admissions, typically at 0, 1, or 2 days after an air pollution episode. An important research aim is to extend existing statistical models so that a more detailed understanding of the time course of hospitalization after exposure to air pollution can be obtained. Information about this time course, combined with prior knowledge about biological mechanisms, could provide the basis for hypotheses concerning the mechanism by which air pollution causes disease. Previous studies have identified two important methodological questions: (1) How can we estimate the shape of the distributed lag between increased air pollution exposure and increased mortality or morbidity? and (2) How should we estimate the cumulative population health risk from short-term exposure to air pollution? Distributed lag models are appropriate tools for estimating air pollution health effects that may be spread over several days. However, estimation for distributed lag models in air pollution and health applications is hampered by the substantial noise in the data and the inherently weak signal that is the target of investigation. We introduce an hierarchical Bayesian distributed lag model that incorporates prior information about the time course of pollution effects and combines information across multiple locations. The model has a connection to penalized spline smoothing using a special type of penalty matrix. We apply the model to estimating the distributed lag between exposure to particulate matter air pollution and hospitalization for cardiovascular and respiratory disease using data from a large United States air pollution and hospitalization database of Medicare enrollees in 94 counties covering the years 1999-2002.

Reduced Bayesian Hierarchical Models: Estimating Health Effects of Simultaneous Exposure to Multiple Pollutants

Quantifying the health effects associated with simultaneous exposure to many air pollutants is now a research priority of the US EPA. Bayesian hierarchical models (BHM) have been extensively used in multisite time series studies of air pollution and health to estimate health effects of a single pollutant adjusted for potential confounding of other pollutants and other time-varying factors. However, when the scientific goal is to estimate the impacts of many pollutants jointly, a straightforward application of BHM is challenged by the need to specify a random-effect distribution on a high-dimensional vector of nuisance parameters, which often do not have an easy interpretation. In this paper we introduce a new BHM formulation, which we call "reduced BHM", aimed at analyzing clustered data sets in the presence of a large number of random effects that are not of primary scientific interest. At the first stage of the reduced BHM, we calculate the integrated likelihood of the parameter of interest (e.g. excess number of deaths attributed to simultaneous exposure to high levels of many pollutants). At the second stage, we specify a flexible random-effect distribution directly on the parameter of interest. The reduced BHM overcomes many of the challenges in the specification and implementation of full BHM in the context of a large number of nuisance parameters. In simulation studies we show that the reduced BHM performs comparably to the full BHM in many scenarios, and even performs better in some cases. Methods are applied to estimate location-specific and overall relative risks of cardiovascular hospital admissions associated with simultaneous exposure to elevated levels of particulate matter and ozone in 51 US counties during the period 1999-2005.

Two dimensional Lattice Boltzmann simulation of fluid flow through an idealized micro-structure of disordered media

This technical report discusses the application of Lattice Boltzmann Method (LBM) in the fluid flow simulation through porous filter-wall of disordered media. The diesel particulate filter (DPF) is an example of disordered media. DPF is developed as a cutting edge technology to reduce harmful particulate matter in the engine exhaust. Porous filter-wall of DPF traps these soot particles in the after-treatment of the exhaust gas. To examine the phenomena inside the DPF, researchers are looking forward to use the Lattice Boltzmann Method as a promising alternative simulation tool. The lattice Boltzmann method is comparatively a newer numerical scheme and can be used to simulate fluid flow for single-component single-phase, single-component multi-phase. It is also an excellent method for modelling flow through disordered media. The current work focuses on a single-phase fluid flow simulation inside the porous micro-structure using LBM. Firstly, the theory concerning the development of LBM is discussed. LBM evolution is always related to Lattice gas Cellular Automata (LGCA), but it is also shown that this method is a special discretized form of the continuous Boltzmann equation. Since all the simulations are conducted in two-dimensions, the equations developed are in reference with D2Q9 (two-dimensional 9-velocity) model. The artificially created porous micro-structure is used in this study. The flow simulations are conducted by considering air and CO2 gas as fluids. The numerical model used in this study is explained with a flowchart and the coding steps. The numerical code is constructed in MATLAB. Different types of boundary conditions and their importance is discussed separately. Also the equations specific to boundary conditions are derived. The pressure and velocity contours over the porous domain are studied and recorded. The results are compared with the published work. The permeability values obtained in this study can be fitted to the relation proposed by Nabovati [8], and the results are in excellent agreement within porosity range of 0.4 to 0.8.

Evaluating the Effectiveness of a Commercial Portable Air Purifier in Homes with Wood Burning Stoves: A Preliminary Study

Wood burning for residential heating is prevalent in the Rocky Mountain regions of the United States. Studies have shown that wood stoves can be a significant source of PM2.5 within homes. In this study, the effectiveness of an electrostatic filter portable air purifier was evaluated (1) in a home where a wood stove was the sole heat source and (2) in a home where a wood stove was used as a supplemental heat source. Particle count concentrations in six particle sizes and particle mass concentrations in two particle sizes weremeasured for ten 12-hour purifier on and ten purifier off trials in each home. Particle count concentrations were reduced by 61–85 percent. Similar reductions were observed in particle mass concentrations. These findings, although limited to one season, suggest that a portable air purifier may effectively reduce indoor particulate matter concentrations associated with wood combustion during home heating.

Pelagic molybdenum concentration anomalies and the impact of sediment resuspension on the molybdenum budget in two tidal systems of the North Sea

The seasonal dynamics of molybdenum (Mo) were studied in the water column of two tidal basins of the German Wadden Sea (Sylt-Rømø and Spiekeroog) between 2007 and 2011. In contrast to its conservative behaviour in the open ocean, both, losses of more than 50% of the usual concentration level of Mo in seawater and enrichments up to 20% were observed repeatedly in the water column of the study areas. During early summer, Mo removal by adsorption on algae-derived organic matter (e.g. after Phaeocystis blooms) is postulated to be a possible mechanism. Mo bound to organic aggregates is likely transferred to the surface sediment where microbial decomposition enriches Mo in the pore water. First δ98/95Mo data of the study area disclose residual Mo in the open water column being isotopically heavier than MOMo (Mean Ocean Molybdenum) during a negative Mo concentration anomaly, whereas suspended particulate matter shows distinctly lighter values. Based on field observations a Mo isotope enrichment factor of ε = −0.3‰ has been determined which was used to argue against sorption on metal oxide surfaces. It is suggested here that isotope fractionation is caused by biological activity and association to organic matter. Pelagic Mo concentration anomalies exceeding the theoretical salinity-based concentration level, on the other hand, cannot be explained by replenishment via North Sea waters alone and require a supply of excess Mo. Laboratory experiments with natural anoxic tidal flat sediments and modelled sediment displacement during storm events suggest fast and effective Mo release during the resuspension of anoxic sediments in oxic seawater as an important process for a recycling of sedimentary sulphide bound Mo into the water column.

Intercomparison of C-14 Analysis of Carbonaceous Aerosols: Exercise 2009

Radiocarbon analysis of the carbonaceous aerosol allows an apportionment of fossil and non-fossil sources of airborne particulate matter (PM). A chemical separation of total carbon (TC) into its subfractions organic carbon (OC) and elemental carbon (EC) refines this powerful technique, as OC and EC originate from different sources and undergo different processes in the atmosphere. Although C-14 analysis of TC, EC, and OC has recently gained increasing attention, interlaboratory quality assurance measures have largely been missing, especially for the isolation of EC and OC. In this work, we present results from an intercomparison of 9 laboratories for C-14 analysis of carbonaceous aerosol samples on quartz fiber filters. Two ambient PM samples and 1 reference material (RM 8785) were provided with representative filter blanks. All laboratories performed C-14 determinations of TC and a subset of isolated EC and OC for isotopic measurement. In general, C-14 measurements of TC and OC agreed acceptably well between the laboratories, i.e. for TC within 0.015-0.025 (FC)-C-14 for the ambient filters and within 0.041 (FC)-C-14 for RM 8785. Due to inhomogeneous filter loading, RM 8785 demonstrated only limited applicability as a reference material for C-14 analysis of carbonaceous aerosols. C-14 analysis of EC revealed a large deviation between the laboratories of 28-79 as a consequence of different separation techniques. This result indicates a need for further discussion on optimal methods of EC isolation for C-14 analysis and a second stage of this intercomparison.

A compact and portable deposition chamber to study nanoparticles in air-exposed tissue

BACKGROUND Epidemiological studies show that elevated levels of particulate matter in ambient air are highly correlated with respiratory and cardiovascular diseases. Atmospheric particles originate from a large number of sources and have a highly complex and variable composition. An assessment of their potential health risks and the identification of the most toxic particle sources would require a large number of investigations. Due to ethical and economic reasons, it is desirable to reduce the number of in vivo studies and to develop suitable in vitro systems for the investigation of cell-particle interactions. METHODS We present the design of a new particle deposition chamber in which aerosol particles are deposited onto cell cultures out of a continuous air flow. The chamber allows for a simultaneous exposure of 12 cell cultures. RESULTS Physiological conditions within the deposition chamber can be sustained constantly at 36-37°C and 90-95% relative humidity. Particle deposition within the chamber and especially on the cell cultures was determined in detail, showing that during a deposition time of 2 hr 8.4% (24% relative standard deviation) of particles with a mean diameter of 50 nm [mass median diameter of 100 nm (geometric standard deviation 1.7)] are deposited on the cell cultures, which is equal to 24-34% of all charged particles. The average well-to-well variability of particles deposited simultaneously in the 12 cell cultures during an experiment is 15.6% (24.7% relative standard deviation). CONCLUSIONS This particle deposition chamber is a new in vitro system to investigate realistic cell-particle interactions at physiological conditions, minimizing stress on the cell cultures other than from deposited particles. A detailed knowledge of particle deposition characteristics on the cell cultures allows evaluating reliable dose-response relationships. The compact and portable design of the deposition chamber allows for measurements at any particle sources of interest.

More efficient aboveground nitrogen use in more diverse Central European forest canopies

We hypothesized that biodiversity improves ecosystem functioning and services such as nutrient cycling because of increased complementarity. We examined N canopy budgets of 27 Central European forests of varying dominant tree species, stand density, and tree and shrub species diversity (Shannon index) in three study regions by quantifying bulk and fine particulate dry deposition and dissolved below canopy N fluxes. Average regional canopy N retention ranged from 16% to 51%, because of differences in the N status of the ecosystems. Canopy N budgets of coniferous forests differed from deciduous forest which we attribute to differences in biogeochemical N cycling, tree functional traits and canopy surface area. The canopy budgets of N were related to the Shannon index which explained 14% of the variance of the canopy budgets of N, suggesting complementary aboveground N use of trees and diverse understorey vegetation. The relationship between plant diversity and canopy N retention varied among regional site conditions and forest types. Our results suggest that the traditional view of belowground complementarity of nutrient uptake by roots in diverse plant communities can be transferred to foliar uptake in forest canopies.

PM2.5-bound oxygenated PAHs, nitro-PAHs and parent-PAHs from the atmosphere of a Chinese megacity: seasonal variation, sources and cancer risk assessment

Polycyclic aromatic compounds (PACs) in air particulate matter contribute considerably to the health risk of air pollution. The objectives of this study were to assess the occurrence and variation in concentrations and sources of PM2.5-bound PACs [Oxygenated PAHs (OPAHs), nitro-PAHs and parent-PAHs] sampled from the atmosphere of a typical Chinese megacity (Xi'an), to study the influence of meteorological conditions on PACs and to estimate the lifetime excess cancer risk to the residents of Xi'an (from inhalation of PM2.5-bound PACs). To achieve these objectives, we sampled 24-h PM2.5 aerosols (once in every 6 days, from 5 July 2008 to 8 August 2009) from the atmosphere of Xi'an and measured the concentrations of PACs in them. The PM2.5-bound concentrations of Σcarbonyl-OPAHs, ∑ hydroxyl + carboxyl-OPAHs, Σnitro-PAHs and Σalkyl + parent-PAHs ranged between 5–22, 0.2–13, 0.3–7, and 7–387 ng m− 3, respectively, being markedly higher than in most western cities. This represented a range of 0.01–0.4% and 0.002–0.06% of the mass of organic C in PM2.5 and the total mass of PM2.5, respectively. The sums of the concentrations of each compound group had winter-to-summer ratios ranging from 3 to 8 and most individual OPAHs and nitro-PAHs had higher concentrations in winter than in summer, suggesting a dominant influence of emissions from household heating and winter meteorological conditions. Ambient temperature, air pressure, and wind speed explained a large part of the temporal variation in PACs concentrations. The lifetime excess cancer risk from inhalation (attributable to selected PAHs and nitro-PAHs) was six fold higher in winter (averaging 1450 persons per million residents of Xi'an) than in summer. Our results call for the development of emission control measures.

Toxicity of aged gasoline exhaust particles to normal and diseased airway epithelia

Particulate matter (PM) pollution is a leading cause of premature death, particularly in those with pre-existing lung disease. A causative link between particle properties and adverse health effects remains unestablished mainly due to complex and variable physico-chemical PM parameters. Controlled laboratory experiments are required. Generating atmospherically realistic Aerosols and performing cell-exposure studies at relevant particle-doses are challenging. Here we examine gasoline-exhaust particle toxicity from a Euro-5 passenger car in a uniquely realistic exposure scenario, combining a smog chamber simulating atmospheric ageing, an aerosol enrichment System varying particle number concentration independent of particle chemistry, and an aerosol Deposition chamber physiologically delivering particles on air-liquid interface (ALI) cultures reproducing normal and susceptible health status. Gasoline-exhaust is an important PM source with largely unknown health effects. We investigated acute responses of fully-differentiated normal, distressed (antibiotics treated) normal, and cystic fibrosis human bronchial epithelia (HBE), and a proliferating, single-cell type bronchial epithelial cell-line (BEAS-2B). We show that a single, short-term exposure to realistic doses of atmospherically-aged gasoline-exhaust particles impairs epithelial key-defence mechanisms, rendering it more vulnerable to subsequent hazards. We establish dose-response curves at realistic particle-concentration levels. Significant differences between cell models suggest the use of fully differentiated HBE is most appropriate in future toxicity studies.