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.

Spatio-temporal Associations Between GOES Aerosol Optical Depth Retrievals and Ground-Level PM2.5

We assess the strength of association between aerosol optical depth (AOD) retrievals from the GOES Aerosol/Smoke Product (GASP) and ground-level fine particulate matter (PM2.5) to assess AOD as a proxy for PM2.5 in the United States. GASP AOD is retrieved from a geostationary platform and therefore provides dense temporal coverage with half-hourly observations every day, in contrast to once per day snapshots from polar-orbiting satellites. However, GASP AOD is based on a less-sophisticated instrument and retrieval algorithm. We find that correlations between GASP AOD and PM2.5 over time at fixed locations are reasonably high, except in the winter and in the western U.S. Correlations over space at fixed times are lower. Simple averaging over time actually reduces correlations over space dramatically, but statistical calibration allows averaging over time that produces strong correlations. These results and the data density of GASP AOD highlight its potential to help improve exposure estimates for epidemiological analyses. On average 40% of days in a month have a GASP AOD retrieval compared to 14% for MODIS and 4% for MISR. Furthermore, GASP AOD has been retrieved since November 1994, providing the possibility of a long-term record that pre-dates the availability of most PM2.5 monitoring data and other satellite instruments.

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.

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.

Characterization and source apportionment of organic aerosol using offline aerosol mass spectrometry

Field deployments of the Aerodyne Aerosol Mass Spectrometer (AMS) have significantly advanced real-time measurements and source apportionment of non-refractory particulate matter. However, the cost and complex maintenance requirements of the AMS make its deployment at sufficient sites to determine regional characteristics impractical. Furthermore, the negligible transmission efficiency of the AMS inlet for supermicron particles significantly limits the characterization of their chemical nature and contributing sources. In this study, we utilize the AMS to characterize the water-soluble organic fingerprint of ambient particles collected onto conventional quartz filters, which are routinely sampled at many air quality sites. The method was applied to 256 particulate matter (PM) filter samples (PM1, PM2:5, and PM10, i.e., PM with aerodynamic diameters smaller than 1, 2.5, and 10 μm, respectively), collected at 16 urban and rural sites during summer and winter. We show that the results obtained by the present technique compare well with those from co-located online measurements, e.g., AMS or Aerosol Chemical Speciation Monitor (ACSM). The bulk recoveries of organic aerosol (60–91 %) achieved using this technique, together with low detection limits (0.8 μg of organic aerosol on the analyzed filter fraction) allow its application to environmental samples. We will discuss the recovery variability of individual hydrocarbon ions, ions containing oxygen, and other ions. The performance of such data in source apportionment is assessed in comparison to ACSM data. Recoveries of organic components related to different sources as traffic, wood burning, and secondary organic aerosol are presented. This technique, while subjected to the limitations inherent to filter-based measurements (e.g., filter artifacts and limited time resolution) may be used to enhance the AMS capabilities in measuring size-fractionated, spatially resolved longterm data sets.

Effects of Breastfeeding on Respiratory Symptoms in Infancy.

OBJECTIVE To assess the impact of potential risk factors on the development of respiratory symptoms and their specific modification by breastfeeding in infants in the first year of life. STUDY DESIGN We prospectively studied 436 healthy term infants from the Bern-Basel Infant Lung Development cohort. The breastfeeding status, and incidence and severity of respiratory symptoms (score) were assessed weekly by telephone interview during the first year of life. Risk factors (eg, pre- and postnatal smoking exposure, mode of delivery, gestational age, maternal atopy, and number of older siblings) were obtained using standardized questionnaires. Weekly measurements of particulate matter <10 μg were provided by local monitoring stations. The associations were investigated using generalized additive mixed model with quasi Poisson distribution. RESULTS Breastfeeding reduced the incidence and severity of the respiratory symptom score mainly in the first 27 weeks of life (risk ratio 0.70; 95% CI 0.55-0.88). We found a protective effect of breastfeeding in girls but not in boys. During the first 27 weeks of life, breastfeeding attenuated the effects of maternal smoking during pregnancy, gestational age, and cesarean delivery on respiratory symptoms. There was no evidence for an interaction between breastfeeding and maternal atopy, number of older siblings, child care attendance, or particulate matter <10 μg. CONCLUSIONS This study shows the risk-specific effect of breastfeeding on respiratory symptoms in early life using the comprehensive time-series approach.

Revising the National Ambient Air Quality Standards: The integration of science and policy

Under the Clean Air Act, Congress granted discretionary decision making authority to the Administrator of the Environmental Protection Agency (EPA). This discretionary authority involves setting standards to protect the public's health with an "adequate margin of safety" based on current scientific knowledge. The Administrator of the EPA is usually not a scientist, and for the National Ambient Air Quality Standard (NAAQS) for particulate matter (PM), the Administrator faced the task of revising a standard when several scientific factors were ambiguous. These factors included: (1) no identifiable threshold below which health effects are not manifested, (2) no biological basis to explain the reported associations between particulate matter and adverse health effects, and (3) no consensus among the members of the Clean Air Scientific Advisory Committee (CASAC) as to what an appropriate PM indicator, averaging period, or value would be for the revised standard. ^ This project recommends and demonstrates a tool, integrated assessment (IA), to aid the Administrator in making a public health policy decision in the face of ambiguous scientific factors. IA is an interdisciplinary approach to decision making that has been used to deal with complex issues involving many uncertainties, particularly climate change analyses. Two IA approaches are presented; a rough set analysis by which the expertise of CASAC members can be better utilized, and a flag model for incorporating the views of stakeholders into the standard setting process. ^ The rough set analysis can describe minimal and maximal conditions about the current science pertaining to PM and health effects. Similarly, a flag model can evaluate agreement or lack of agreement by various stakeholder groups to the proposed standard in the PM review process. ^ The use of these IA tools will enable the Administrator to (1) complete the NAAQS review in a manner that is in closer compliance with the Clean Air Act, (2) expand the input from CASAC, (3) take into consideration the views of the stakeholders, and (4) retain discretionary decision making authority. ^