Practical Large-Scale Spatio-Temporal Modeling of Particulate Matter Concentrations

The last two decades have seen intense scientific and regulatory interest in the health effects of particulate matter (PM). Influential epidemiological studies that characterize chronic exposure of individuals rely on monitoring data that are sparse in space and time, so they often assign the same exposure to participants in large geographic areas and across time. We estimate monthly PM during 1988-2002 in a large spatial domain for use in studying health effects in the Nurses' Health Study. We develop a conceptually simple spatio-temporal model that uses a rich set of covariates. The model is used to estimate concentrations of PM10 for the full time period and PM2.5 for a subset of the period. For the earlier part of the period, 1988-1998, few PM2.5 monitors were operating, so we develop a simple extension to the model that represents PM2.5 conditionally on PM10 model predictions. In the epidemiological analysis, model predictions of PM10 are more strongly associated with health effects than when using simpler approaches to estimate exposure. Our modeling approach supports the application in estimating both fine-scale and large-scale spatial heterogeneity and capturing space-time interaction through the use of monthly-varying spatial surfaces. At the same time, the model is computationally feasible, implementable with standard software, and readily understandable to the scientific audience. Despite simplifying assumptions, the model has good predictive performance and uncertainty characterization.

Respiratory health effects of diesel particulate matter

Particulate matter (PM) emissions involve a complex mixture of solid and liquid particles suspended in a gas, where it is noted that PM emissions from diesel engines are a major contributor to the ambient air pollution problem. Whilst epidemiological studies have shown a link between increased ambient PM emissions and respiratory morbidity and mortality, studies of this design are not able to identify the PM constituents responsible for driving adverse respiratory health effects. This review explores in detail the physico-chemical properties of diesel particulate matter (DPM), and identifies the constituents of this pollution source that are responsible for the development of respiratory disease. In particular, this review shows that the DPM surface area and adsorbed organic compounds play a significant role in manifesting chemical and cellular processes that if sustained can lead to the development of adverse respiratory health effects. The mechanisms of injury involved included: inflammation, innate and acquired immunity, and oxidative stress. Understanding the mechanisms of lung injury from DPM will enhance efforts to protect at-risk individuals from the harmful respiratory effects of air pollutants.

The application of a profluorescent nitroxide probe to detect reactive oxygen species derived from combustion-generated particulate matter

Particulate pollution has been widely recognised as an important risk factor to human health. In addition to increases in respiratory and cardiovascular morbidity associated with exposure to particulate matter (PM), WHO estimates that urban PM causes 0.8 million premature deaths globally and that 1.5 million people die prematurely from exposure to indoor smoke generated from the combustion of solid fuels. Despite the availability of a huge body of research, the underlying toxicological mechanisms by which particles induce adverse health effects are not yet entirely understood. Oxidative stress caused by generation of free radicals and related reactive oxygen species (ROS) at the sites of deposition has been proposed as a mechanism for many of the adverse health outcomes associated with exposure to PM. In addition to particle-induced generation of ROS in lung tissue cells, several recent studies have shown that particles may also contain ROS. As such, they present a direct cause of oxidative stress and related adverse health effects. Cellular responses to oxidative stress have been widely investigated using various cell exposure assays. However, for a rapid screening of the oxidative potential of PM, less time-consuming and less expensive, cell-free assays are needed. The main aim of this research project was to investigate the application of a novel profluorescent nitroxide probe, synthesised at QUT, as a rapid screening assay in assessing the oxidative potential of PM. Considering that this was the first time that a profluorescent nitroxide probe was applied in investigating the oxidative stress potential of PM, the proof of concept regarding the detection of PM–derived ROS by using such probes needed to be demonstrated and a sampling methodology needed to be developed. Sampling through an impinger containing profluorescent nitroxide solution was chosen as a means of particle collection as it allowed particles to react with the profluorescent nitroxide probe during sampling, avoiding in that way any possible chemical changes resulting from delays between the sampling and the analysis of the PM. Among several profluorescent nitroxide probes available at QUT, bis(phenylethynyl)anthracene-nitroxide (BPEAnit) was found to be the most suitable probe, mainly due to relatively long excitation and emission wavelengths (λex= 430 nm; λem= 485 and 513 nm). These wavelengths are long enough to avoid overlap with the background fluorescence coming from light absorbing compounds which may be present in PM (e.g. polycyclic aromatic hydrocarbons and their derivatives). Given that combustion, in general, is one of the major sources of ambient PM, this project aimed at getting an insight into the oxidative stress potential of combustion-generated PM, namely cigarette smoke, diesel exhaust and wood smoke PM. During the course of this research project, it was demonstrated that the BPEAnit probe based assay is sufficiently sensitive and robust enough to be applied as a rapid screening test for PM-derived ROS detection. Considering that for all three aerosol sources (i.e. cigarette smoke, diesel exhaust and wood smoke) the same assay was applied, the results presented in this thesis allow direct comparison of the oxidative potential measured for all three sources of PM. In summary, it was found that there was a substantial difference between the amounts of ROS per unit of PM mass (ROS concentration) for particles emitted by different combustion sources. For example, particles from cigarette smoke were found to have up to 80 times less ROS per unit of mass than particles produced during logwood combustion. For both diesel and wood combustion it has been demonstrated that the type of fuel significantly affects the oxidative potential of the particles emitted. Similarly, the operating conditions of the combustion source were also found to affect the oxidative potential of particulate emissions. Moreover, this project has demonstrated a strong link between semivolatile (i.e. organic) species and ROS and therefore, clearly highlights the importance of semivolatile species in particle-induced toxicity.

Investigation of the chemical and physical basis of oxidative stress generated by particulate matter using the profluorescent probe technique

Following the growing need for adoption of alternative fuels, this project aimed at getting more information on the oxidative potential of biodiesel particulate matter. Within this scope, the physical and chemical characteristics of biodiesel PM were analysed which lead to identification of reactive organic fractions. An in-house developed proflurescent nitroxide probe was used. This project further developed in-depth understanding of the chemical mechanisms following the detection of the oxidative potential of PM. This knowledge made a significant contribution to our understanding of processes behind negative health effects of pollution and enabled us to further develop new techniques to monitor it.

Real-time Sampling of Particulate Matter Smaller than 2.5 µm from Amazon Forest Biomass Combustion

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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.

In vitro models of the human epithelial airway barrier to study the toxic potential of particulate matter

BACKGROUND: Several epidemiological studies show that inhalation of particulate matter may cause increased pulmonary morbidity and mortality. Of particular interest are the ultrafine particles that are particularly toxic. In addition more and more nanoparticles are released into the environment; however, the potential health effects of these nanoparticles are yet unknown. OBJECTIVES: To avoid particle toxicity studies with animals many cell culture models have been developed during the past years. METHODS: This review focuses on the most commonly used in vitro epithelial airway and alveolar models to study particle-cell interactions and particle toxicity and highlights advantages and disadvantages of the different models. RESULTS/CONCLUSION: There are many lung cell culture models but none of these models seems to be perfect. However, they might be a great tool to perform basic research or toxicity tests. The focus here is on 3D and co-culture models, which seem to be more realistic than monocultures.

Air quality and its impact on health: focus on particulate matter

Inadequate air quality and the inhalation of airborne pollutants pose many risks to human health and wellbeing, and are listed among the top environmental risks worldwide. The importance of outdoor air quality was recognised in the 1950s and indoor air quality emerged as an issue some time later and was soon recognised as having an equal, if not greater importance than outdoor air quality. Identification of ambient air pollution as a health hazard was followed by steps, undertaken by a broad range of national and international professional and government organisations, aimed at reduction or elimination of the hazard. However, the process of achieving better air quality is still in progress. The last 10 years or so have seen an unprecedented increase in the interest in, and attention to, airborne particles, with a special focus on their finer size fractions, including ultrafine (< 0.1 m) and their subset, nano particles (< 0.05 m). This paper discusses the current status of scientific knowledge on the links between air quality and health, with a particular focus on airborne particulate matter, and the directions taken by national and international bodies to improve air quality.

Study of particulate matter removal mechanism by using non-thermal plasma technology

Numbers of diesel engines in both stationary and mobile applications are increasing nowadays. Diesel engines emit lower Hydrocarbon (HC) and Carbon monoxide (CO) than gasoline engines. However, they can produce more nitrogen oxides (NOx) and have higher particulate matter (PM). On the other hand, emissions standards are getting stringent day by day due to considerable concerns about unregulated pollutants and particularly ultrafine particles deleterious effect on human health. Non-thermal plasma (NTP) treatment of exhaust gas is known as a promising technology for both NOx and PM reduction by introducing plasma inside the exhaust gas. Vehicle exhaust gases undergo chemical changes when exposed to plasma. In this study, the PM removal mechanism using NTP by applying high voltage pulses of up to 20 kVpp with a repetition rate of 10 kHz are investigated. It is found that, voltage increase not necessarily has a positive effect on PM removal in diesel engine emissions.

Investigation of the dilution process for measurement of particulate matter from spark-ignition engines

Measurements of particulate matter (PM) from spark ignition (SI) engine exhaust using dilution tunnels will become more prevalent as emission standards are tightened. Hence, a study of the dilution process was undertaken in order to understand how various dilution related parameters affect the accuracy with which PM sizes and concentrations can be determined. A SI and a compression ignition (CI) engine were separately used to examine parameters of the dilution process; the present work discusses the results in the context of SI exhaust dilution. A Scanning Mobility Particle Sizer (SMPS) was used to measure the size distribution, number density, and volume fraction of PM. Temperature measurements in the exhaust pipe and dilution tunnel reveal the degree of mixing between exhaust and dilution air, the effect of flowrate on heat transfer from undiluted and diluted exhaust to the environment, and the minimum permissible dilution ratio for a maximum sample temperature of 52°C. Measurements of PM concentrations as a function of dilution ratio show the competing effects of temperature and particle/vapor concentrations on particle growth dynamics, which result in a range of dilution ratios-from 13 to 18-where the effect of dilution ratio, independent of flowrate, is kept to a minimum. This range of dilution ratios is therefore optimal in order to achieve repeatable PM concentration measurements. Particle dynamics during transit through the tunnel operating at the optimal dilution ratio was found statistically insignificant compared to data scatter. Such small differences in number concentration may be qualitatively representative of particle losses for SI exhaust, but small increases in PM volume fraction during transit through the tunnel may significantly underestimate accretion of mass due to unburned hydrocarbons (HCs) emitted by SI engines. The fraction of SI-derived PM mass due to adsorbed/absorbed vapor, estimated from these data, is consistent with previous chemical analyses of PM. © 1998 Society of Automotive Engineers, Inc.

Characterization of Metal and Trace Element Contents of Particulate Matter (PM10) Emitted by Vehicles Running on Brazilian FuelsHydrated Ethanol and Gasoline with 22% of Anhydrous Ethanol

Emission of fine particles by mobile sources has been a matter of great concern due to its potential risk both to human health and the environment. Although there is no evidence that one sole component may be responsible for the adverse health outcomes, it is postulated that the metal particle content is one of the most important factors, mainly in relation to oxidative stress. Data concerning the amount and type of metal particles emitted by automotive vehicles using Brazilian fuels are limited. The aim of this study was to identify inhalable particles (PM10) and their trace metal content in two light-duty vehicles where one was fueled with ethanol while the other was fueled with gasoline mixed with 22% of anhydrous ethanol (gasohol); these engines were tested on a chassis dynamometer. The elementary composition of the samples was evaluated by the particle-induced x-ray emission technique. The experiment showed that total emission factors ranged from 2.5 to 11.8 mg/km in the gasohol vehicle, and from 1.2 to 3 mg/km in the ethanol vehicle. The majority of particles emitted were in the fine fraction (PM2.5), in which Al, Si, Ca, and Fe corresponded to 80% of the total weight. PM10 emissions from the ethanol vehicle were about threefold lower than those of gasohol. The elevated amount of fine particulate matter is an aggravating factor, considering that these particles, and consequently associated metals, readily penetrate deeply into the respiratory tract, producing damage to lungs and other tissues.

The effects of particulate ambient air pollution on the murine umbilical cord and its vessels: A quantitative morphological and immunohistochemical study

Previous studies have shown that particulate matter (PM) compromise birth weight and placental morphology. We hypothesized that exposing mice to ambient PM would affect umbilical cord (UC) morphology. To test this, mice were kept in paired open-top exposure chambers at the same location and ambient conditions but, in one chamber, the air was filtered (F) and, in the other, it was not (NF). UCs were analysed stereologically and by immunohistochemistry to localize isoprostane and endothelin receptors. The cords of mice from NF chambers were smaller in volume due to loss of mucoid connective tissue and decrease in volume of collagen. These structural changes and in umbilical vessels were associated with greater volumes of regions immunostained for isoprostane, ETAR and ETBR. Findings indicate that the adverse effects of PM on birth weight may be mediated in part by alterations in UC structure or imbalances in the endogenous regulators of vascular tone and oxidative stress. (C) 2012 Elsevier Inc. All rights reserved.

Implementation of road dust resuspension in air quality simulations of particulate matter in Madrid (Spain)

An evaluation of the concentration levels of Particulate Matter (PM) was carried out in Madrid (Spain) by introducing the emissions from road dust resuspension. Road dust resuspension emission factors (EF) for different types of vehicles were calculated from EPA-AP42, a global resuspension factor of 0.097 g veh−1km−1 as described in Amato et al. (2010) and a rain-dependent correction factor. With these resuspension EFs, a simulation at street canyon level was performed with the OSPM model without rainfall. Subsequently, a simulation using the CMAQ model was implemented adding resuspension emissions affected by the rain. These data were compared with monitored data obtained from air quality stations. OSPM model simulations with resuspension EFs but without the effect of rainfall improve the PM estimates in about 20gm−3μ compared to the simulation with default EFs. Total emissions were calculated by adding the emissions estimated with resuspension EFs to the default PM emissions to be used by CMAQ. For the study in the Madrid Area, resuspension emissions are approximately of the same order of magnitude as inventoried emissions. On a monthly scale, rain effects are negligible for resuspension emissions due to the dry weather conditions of Spain. With the exception of April and May, the decrease in resuspension emissions is not >3%. The predicted PM10 concentration increases up to 9μ gm−3 on annual average for each station compared to the same scenario without resuspension. However, in both cases, PM 10 estimates with resuspension are still underestimating observations. It should be noted that although that accounting for resuspension improves the quality of model predictions, other PM sources (e.g., Saharan dust) were not considered in this study.