Exposure efficiency: concept and application to perchloroethylene exposure from dry cleaners

Standard approaches for computing population exposures due to specific sources of air pollutants are relatively complex. In many cases, more simple and approximate methods would be useful. This paper develops an approach, based on the concept of exposure efficiency, that may be used for estimating the impact of a source (or source class) on the integrated population exposure. The approach is illustrated by an example, which uses the concept of exposure efficiency to examine the impact of perchloroethylene emissions from dry cleaners in the United States. The paper explores the geographic variability of exposure efficiency by evaluating it for each of 100 randomly selected dry cleaners. For perchloroethylene, which has a long atmospheric residence time, the site-to-site variability in exposure efficiency is found to be relatively small. This suggests that simple exposure assessments, based on generic distributional characterizations of exposure efficiency, may be used in risk assessments without introducing appreciable uncertainty. For many compounds, like perchloroethylene, the uncertainty inherent in the estimation of cancer potency or source emissions would dominate these small errors.     

An Analysis of Visual Range in the Eastern United States Under Different Meteorological Regimes

ABSTRACT

The issue of fine particle (PM₂₅) exposures and their potential health effects is a focus of scientific research because of the recently promulgated National Ambient Air Quality Standard for PM_{2 5}. Before final implementation, the health and exposure basis for the standard will be reviewed by the U.S. Environmental Protection Agency within the next five years. As part of this process, it is necessary to understand total particle exposure issues and to determine the relative importance of the origin of PM_{2 5} exposure in various micro-environments. The results presented in this study examine emissions of fine particles from a previously uncharacterized indoor source: the residential vacuum cleaner. Eleven standard vacuum cleaners were tested for the emission rate of fine particles by their individual motors and for their efficiency in collecting laboratory-generated fine particles. An aerosol generator was used to introduce fine potassium chloride (KC1) particles into the vacuum cleaner inlet for the collection efficiency tests. Measurements of the motor emissions, which include carbon, and the KCl aerosol were made using a continuous HIAC/Royco 5130A light-scattering particle detector. All tests were conducted in a metal chamber specifically designed to completely contain the vacuum cleaner and operate it in a stationary position. For the tested vacuum cleaners, fine particle motor emissions ranged from 9.6 x 10⁴ to 3.34 x 10⁸ particles/min, which were estimated to be 0.028 to 176 mg/min for mass emissions, respectively. The vast majority of particles released were in the range of 0.3-0.5 mm in diameter. The lowest particle emission rate was obtained for a vacuum cleaner that had a high efficiency (HEPA) filter placed after the vacuum cleaner bag and the motor within a sealed exhaust system. This vacuum cleaner removed the KC1particles that escaped the vacuum cleaner bag and the particles emitted by the motor. Results obtained for the KC1 collection efficiency tests show >99% of the fine particles were captured by the two vacuum cleaners that used a HEPA filter. A series of tests conducted on two vacuum cleaners found that the motors also emitted ultra-fine particles above 0.01 mm in diameter at rates of greater than 10⁸ ultra-fine particles/CF of air. The model that had the best collection efficiency for fine particles also reduced the ultra-fine particle emissions by a factor of 1 x 10³.     

Air Quality Modeling of Interpollutant Trading for Ozone Precursors in an Urban Area

Abstract

Emission trading is a market‐based approach designed to improve the efficiency and economic viability of emission control programs; emission trading has typically been confined to trades among single pollutants. Interpollutant trading (IPT), as described in this work, allows for trades among emissions of different compounds that affect the same air quality end point, in this work, ambient ozone (O₃) concentrations. Because emissions of different compounds impact air quality end points differently, weighting factors or trading ratios (tons of emissions of nitrogen oxides (NO_x) equivalent to a ton of emissions of volatile organic compounds [VOCs]) must be developed to allow for IPT. In this work, IPT indices based on reductions in O₃ concentrations and based on reductions in population exposures to O₃ were developed and evaluated using a three‐dimensional gridded photochemical model for Austin, TX, a city currently on the cusp of nonattainment with the National Ambient Air Quality Standards for O₃ concentrations averaged over 8 hr. Emissions of VOC and NO_x from area and mobile sources in Austin are larger than emissions from point sources. The analysis indicated that mobile and area sources exhibited similar impacts. Trading ratios based on maximum O₃ concentration or population exposure were similar. In contrast, the trading ratios did exhibit significant (more than a factor of two) day‐to‐day variability. Analysis of the air quality modeling indicated that the daily variability in trading ratios could be attributed to daily variations in both emissions and meteorology.     

Typical household vacuum cleaners: the collection efficiency and emissions characteristics for fine particles

The issue of fine particle (PM2.5) exposures and their potential health effects is a focus of scientific research because of the recently promulgated National Ambient Air Quality Standard for PM2.5. Before final implementation, the health and exposure basis for the standard will be reviewed by the U.S. Environmental Protection Agency within the next five years. As part of this process, it is necessary to understand total particle exposure issues and to determine the relative importance of the origin of PM2.5 exposure in various micro-environments. The results presented in this study examine emissions of fine particles from a previously uncharacterized indoor source: the residential vacuum cleaner. Eleven standard vacuum cleaners were tested for the emission rate of fine particles by their individual motors and for their efficiency in collecting laboratory-generated fine particles. An aerosol generator was used to introduce fine potassium chloride (KCl) particles into the vacuum cleaner inlet for the collection efficiency tests. Measurements of the motor emissions, which include carbon, and the KCl aerosol were made using a continuous HIAC/Royco 5130 A light-scattering particle detector. All tests were conducted in a metal chamber specifically designed to completely contain the vacuum cleaner and operate it in a stationary position. For the tested vacuum cleaners, fine particle motor emissions ranged from 9.6 x 10(4) to 3.34 x 10(8) particles/min, which were estimated to be 0.028 to 176 micrograms/min for mass emissions, respectively. The vast majority of particles released were in the range of 0.3-0.5 micron in diameter. The lowest particle emission rate was obtained for a vacuum cleaner that had a high efficiency (HEPA) filter placed after the vacuum cleaner bag and the motor within a sealed exhaust system. This vacuum cleaner removed the KCl particles that escaped the vacuum cleaner bag and the particles emitted by the motor. Results obtained for the KCl collection efficiency tests show > 99% of the fine particles were captured by the two vacuum cleaners that used a HEPA filter. A series of tests conducted on two vacuum cleaners found that the motors also emitted ultra-fine particles above 0.01 micron in diameter at rates of greater than 10(8) ultra-fine particles/CF of air. The model that had the best collection efficiency for fine particles also reduced the ultra-fine particle emissions by a factor of 1 x 10(3).     

Sustainable Development by Design: Review of Life Cycle Design and Related Approaches

Abstract

The quality of stationary source emission factors is typically described using data quality ratings, which provide no quantification of the precision of the emission factor for an average source, nor of the variability from one source to another within a category. Variability refers to actual differences caused by differences in feedstock composition, design, maintenance, and operation. Uncertainty refers to lack of knowledge regarding the true emissions. A general methodology for the quantification of variability and uncertainty in emission factors, activity factors, and emission inventories (EIs) is described, featuring the use of bootstrap simulation and related techniques. The methodology is demonstrated via a case study for a selected example of NO_x emissions from coal-fired power plants. A prototype software tool was developed to implement the methodology. The range of interunit variability in selected activity and emission factors was shown to be as much as a factor of 4, and the range of uncertainty in mean emissions is shown to depend on the interunit variability and sample size. The uncertainty in the total inventory of ?16 to +19% was attributed primarily to one technology group, suggesting priorities for collecting data and improving the inventory. The implications for decision-making are discussed.     

Analysis of coupled model uncertainties in source-to-dose modeling of human exposures to ambient air pollution: A PM2.5 case study

Quantitative assessment of human exposures and health effects due to air pollution involve detailed characterization of impacts of air quality on exposure and dose. A key challenge is to integrate these three components on a consistent spatial and temporal basis taking into account linkages and feedbacks. The current state-of-practice for such assessments is to exercise emission, meteorology, air quality, exposure, and dose models separately, and to link them together by using the output of one model as input to the subsequent downstream model. Quantification of variability and uncertainty has been an important topic in the exposure assessment community for a number of years. Variability refers to differences in the value of a quantity (e.g., exposure) over time, space, or among individuals. Uncertainty refers to lack of knowledge regarding the true value of a quantity. An emerging challenge is how to quantify variability and uncertainty in integrated assessments over the source-to-dose continuum by considering contributions from individual as well as linked components. For a case study of fine particulate matter (PM_2.5) in North Carolina during July 2002, we characterize variability and uncertainty associated with each of the individual concentration, exposure and dose models that are linked, and use a conceptual framework to quantify and evaluate the implications of coupled model uncertainties. We find that the resulting overall uncertainties due to combined effects of both variability and uncertainty are smaller (usually by a factor of 3–4) than the crudely multiplied model-specific overall uncertainty ratios. Future research will need to examine the impact of potential dependencies among the model components by conducting a truly coupled modeling analysis.     

Model and input uncertainty in multi-media fate modeling: benzo[a]pyrene concentrations in Europe

This paper evaluates the contribution of (i) uncertainty in substance properties, (ii) lack of spatial variability, (iii) intermodel differences and (iv) neglecting sorption to black carbon (BC) to the uncertainty of Benzo[a]pyrene (BaP) concentrations in European air, soil and fresh water predicted by the multi-media fate model Simplebox. Uncertainty in substance properties was quantified using probabilistic modeling. The influence of spatial variability was quantified by estimating variation in predicted concentrations with three spatially explicit fate models (Impact 2002, EVn BETR and BETR Global). Intermodel differences were quantified by comparing concentration estimates of Simplebox, Impact 2002, EVn BETR and the European part of BETR Global. Finally, predictions of a BC-inclusive version of Simplebox were compared with predictions of a BC-exclusive version. For air concentrations of BaP, the lack of spatial variability in emissions was most influential. For freshwater concentrations of BaP, intermodel differences and lack of spatial variability in dimensions of fresh water bodies were the dominant sources of uncertainty. For soil, all sources of uncertainty were of comparable magnitude. Our results indicate that uncertainty in Simplebox can be as large as three orders of magnitude for BaP concentrations in the environment and would be substantially underestimated by focusing on one source of uncertainty only.     

Residual Perchloroethylene in Dry-Cleaned Acetate: The Effect of Pressing and Extent of Inter-Dry-Cleaner Variability

ABSTRACT

Measurements of residual perchloroethylene (PCE), a dry-cleaning solvent associated with human health effects, were made in dry-cleaned acetate cloth to enable improved characterizations of both occupational and environmental exposure. A limited sample size (25 acetate cloths) was used to explore the extent of inter-dry-cleaner variability in residual PCE and to characterize the effect of the pressing operation on residual PCE. A new method, which uses carbon-disulfide as the direct extracting agent, proved effective in the analysis of residual PCE, with a recovery-efficiency ≈ 75%. Inter-dry-cleaner variability of residual PCE, although marginally statistically significant, was relatively low, showing only a fourfold range compared to a 5-order-of-magnitude range obtained from Kawauchi and Nishiyama¹. Pairwise comparison of residual PCE in nonpressed versus pressed acetate samples revealed a statistically significant reduction (p < 0.008), which amounted to a consistent (among dry-cleaners) pressing-related removal efficiency of 75 ± 4%. A preliminary assessment of the source term associated with the pressing operation (mass PCE liberated per kg cloth dry-cleaned, S_PCE ≈ 30 mg/kg) indicates a minor contribution to the average ambient air concentrations within dry-cleaning establishments.     

The viability of professional wet cleaning as a pollution prevention alternative to perchloroethylene dry cleaning

The vast majority of dry cleaners worldwide use the toxic chemical perchloroethylene (PCE), which is associated with a number of adverse health and environmental impacts. Professional wet cleaning was developed as a nontoxic alternative to PCE dry cleaning but has not been widely adopted as substitute technology. In the greater Los Angeles, CA, region, a demonstration project was set up to showcase this technology and evaluate its commercial viability by converting seven cleaners from PCE dry cleaning to professional wet cleaning. The demonstration site cleaners who switched to professional wet cleaning were able to maintain their level of service and customer base while lowering operating costs. The cleaners were able to transition to professional wet cleaning without a great degree of difficulty and expressed a high level of satisfaction with professional wet cleaning. Crucial to this success was the existence of the demonstration project, which helped to develop a supporting infrastructure for professional wet cleaning that had otherwise been lacking in the garment care industry.     

The Sensitivity of Probabilistic Risk Assessment Results to Alternative Model Structures: A Case Study of Municipal Waste Incineration

Abstract

In this analysis, human health risk due to exposure to municipal waste incinerator emissions is assessed as an example of the application of probabilistic techniques (e.g., Monte Carlo or Latin Hypercube simulations). Incinerator risk assessments are characterized by the dominance of indirect exposure, thus this analysis focuses on exposure via the ingestion of locally grown foods. In addition, since exposure to 2, 3, 7, 8-TCDD drives most incinerator risk assessments, this compound is the subject of the illustrative calculations. An important part of probabilistic risk assessment is determining the relative influence of the input parameters on the magnitude of the variance in the output distribution. This constitutes an important step toward prioritizing data needs for additional research. However, under various possible model forms reflecting incompletely understood aspects of contaminant transport, differences may be observed in estimates of risk, variance in risk, and the relative contributions of individual uncertain and variable inputs to the variance. In this analysis, a sequential structural decomposition of the relationships between the input variables is used to partition the variance in the output (i.e., risk) to identify the most influential contributors to overall variance among them. For comparison, the partitioning of variance is repeated, using techniques of multivariate regression. In summary, this study considers the degree to which results of a probabilistic assessment are contingent on critical model assumptions about the representation of deposition velocity. Specifically, this analysis assesses the impact on the results of uncertainty about the best model of the vapor/particle partitioning behavior of semi-volatile airborne pollutants.     

Developing intake fraction estimates with limited data: Comparison of methods in Mexico City

In order to estimate the health benefits of reducing mobile source emissions, analysts typically use detailed atmospheric models to estimate the change in population exposure that results from a given change in emissions. However, this may not be feasible in settings where data are limited or policy decisions are needed in the short term. Intake fraction (iF), defined as the fraction of emissions of a pollutant or its precursor that is inhaled by the population, is a metric that can be used to compare exposure assessment methods in a health benefits analysis context. To clarify the utility of rapid-assessment methods, we calculate particulate matter iFs for the Mexico City Metropolitan Area using five methods, some more resource intensive than others. First, we create two simple box models to describe dispersion of primary fine particulate matter (PM_2.5) in the Mexico City basin. Second, we extrapolate iFs for primary PM_2.5, ammonium sulfate, and ammonium nitrate from US values using a regression model. Third, we calculate iFs by assuming a linear relationship between emissions and population-weighted concentrations of primary PM_2.5, ammonium nitrate, and ammonium sulfate (a particle composition method). Finally, we estimate PM iFs from detailed atmospheric dispersion and chemistry models run for only a short period of time. Intake fractions vary by up to a factor of five, from 23 to 120 per million for primary PM_2.5. Estimates of 60, 7, and 0.7 per million for primary PM, secondary ammonium sulfate, and secondary ammonium nitrate, respectively, represent credible central estimates, with an approximate factor of two uncertainty surrounding each estimate. Our results emphasize that multiple rapid-assessment methods can provide meaningful estimates of iFs in resource-limited environments, and that formal uncertainty analysis, with special attention to model biases and uncertainty, would be important for health benefits analyses.     

Air Levels and Mutagenicity of PM-10 in an Indoor Ice Arena

Abstract

Hazardous waste sites and industrial facilities contain area sources of fugitive emissions. Emission rate measurements or estimates are necessary for air pathway assessments for these sources. Emission rate data can be useful for the design of emission control and remediation strategies as well as for predictive modeling for population exposure assessments. This paper describes the use of a direct emission measurement approach – the enclosure approach using an emission isolation flux chamber – to measure emission rates of various volatile organic compounds (VOCs) from contaminated soil and water. A variety of flux chamber equipment designs and operating procedures have been employed by various researchers. This paper contains a review of the design and operational variables that affect the accuracy and precision of the method. Guidance is given as to the optimum flux chamber design and operating conditions for various types of emission sources. Also presented is a generic quality control program that gives the minimum number of duplicate, blank, background, and repeat samples that should be performed.     

Air quality modeling of interpollutant trading for ozone precursors in an urban area

Emission trading is a market-based approach designed to improve the efficiency and economic viability of emission control programs; emission trading has typically been confined to trades among single pollutants. Interpollutant trading (IPT), as described in this work, allows for trades among emissions of different compounds that affect the same air quality end point, in this work, ambient ozone (O3) concentrations. Because emissions of different compounds impact air quality end points differently, weighting factors or trading ratios (tons of emissions of nitrogen oxides (NO(x)) equivalent to a ton of emissions of volatile organic compounds [VOCs]) must be developed to allow for IPT. In this work, IPT indices based on reductions in O3 concentrations and based on reductions in population exposures to O3 were developed and evaluated using a three-dimensional gridded photochemical model for Austin, TX, a city currently on the cusp of nonattainment with the National Ambient Air Quality Standards for O3 concentrations averaged over 8 hr. Emissions of VOC and NO(x) from area and mobile sources in Austin are larger than emissions from point sources. The analysis indicated that mobile and area sources exhibited similar impacts. Trading ratios based on maximum O3 concentration or population exposure were similar. In contrast, the trading ratios did exhibit significant (more than a factor of two) day-to-day variability. Analysis of the air quality modeling indicated that the daily variability in trading ratios could be attributed to daily variations in both emissions and meteorology.     

Methods for Quantifying Variability and Uncertainty in AP-42 Emission Factors: Case Studies for Natural Gas-Fueled Engines

Abstract

Quantitative methods for characterizing variability and uncertainty were applied to case studies of oxides of nitrogen and total organic carbon emission factors for lean-burn natural gas-fueled internal combustion engines. Parametric probability distributions were fit to represent inter-engine variability in specific emission factors. Bootstrap simulation was used to quantify uncertainty in the fitted cumulative distribution function and in the mean emission factor. Some methodological challenges were encountered in analyzing the data. For example, in one instance, five data points were available, with each data point representing a different market share. Therefore, an approach was developed in which parametric distributions were fitted to population-weighted data. The uncertainty in mean emission factors ranges from as little as ~±10% to as much as -90 to 21+180%. The wide range of uncertainty in some emission factors emphasizes the importance of recognizing and accounting for uncertainty in emissions estimates. The skewness in some uncertainty estimates illustrates the importance of using numerical simulation approaches that do not impose restrictive symmetry assumptions on the confidence interval for the mean. In this paper, the quantitative method, the analysis results, and key findings are presented.     

Sensitivity of Source Apportionment of Urban Particulate Matter to Uncertainty in Motor Vehicle Emissions Profiles

Abstract

A sensitivity analysis was conducted to characterize sources of uncertainty in results of a molecular marker source apportionment model of ambient particulate matter using mobile source emissions profiles obtained as part of the Gasoline/Diesel PM Split Study. A chemical mass balance (CMB) model was used to determine source contributions to samples of fine particulate matter (PM_2.5) collected over 3 weeks at two sites in the Los Angeles area in July 2001. The ambient samples were composited for organic compound analysis by the day of the week to investigate weekly trends in source contributions. The sensitivity analysis specifically examined the impact of the uncertainty in mobile source emissions profiles on the CMB model results. The key parameter impacting model sensitivity was the source profile for gasoline smoker vehicles. High-emitting gasoline smoker vehicles with visible plumes were seen to be a significant source of PM in the area, but use of different measured profiles for smoker vehicles in the model gave very different results for apportionment of gasoline, diesel, and smoker vehicle tailpipe emissions. In addition, the contributions of gasoline and diesel emissions to total ambient PM varied as a function of the site and the day of the week.     

Inhalation Transfer Factors for Air Pollution Health Risk Assessment

ABSTRACT

To facilitate routine health risk assessments, we develop the concept of an inhalation transfer factor (ITF). The ITF is defined as the pollutant mass inhaled by an exposed individual per unit pollutant mass emitted from an air pollution source. A cumulative population inhalation transfer factor (PITF) is also defined to describe the total fraction of an emitted pollutant inhaled by all members of the exposed population. In this paper, ITFs and PITFs are calculated for outdoor releases from area, point, and line sources, indoor releases in single zone and multizone indoor environments, and releases within motor vehicles. Typical PITFs for an urban area from emissions outdoors are ~10^-6–10^-3. PITFs associated with emissions in buildings or in moving vehicles are typically much higher, ~10^-3–10^-1.     

A History of Dry Cleaners and Sources of Solvent Releases from Dry Cleaning Equipment

Approximately 25, 000–35, 000 dry cleaning facilities currently operate in the U.S. The release of perchloroethylene and other solvents from these establishments represents a major source of soil and groundwater contamination. The manner in which dry cleaning solvents escape from dry cleaning plants is, for all practical purposes, identical for chlorinated and petroleum hydrocarbon solvents and is related to one of the following events: the catastrophic failure of a component of the dry cleaning system, the improper installation, operation or maintenance of the dry cleaning equipment or a combination of all of these causes. Acceptable customs, codes and regulations can also dictate what is authorized for operation of a dry cleaning facility in a particular community, geographic area during a particular time frame. Environmental litigation dealing with the origin of a solvent release from dry cleaners tends to focus on the design and manufacture of dry cleaning industry machines such as washers, washer extractors, tumblers, solvent filters, water separators, stills and spotting boards. A thorough analysis of the daily operations of dry cleaners often reveals that poor maintenance, failure to follow the manufacturer's instructions and the actions of the operator are the most likely causes of soil and groundwater pollution. In order to forensically evaluate the most probable origins of a solvent release and to examine issues regarding liability, a thorough understanding of the history of dry cleaning and a detailed analysis of the operation and maintenance of the dry cleaning equipment are necessary. The discovery of solvent plumes in the vicinity of dry cleaning plants may suggest that the solvent source is the dry cleaning plant; however, the presence of these plumes does not necessarily indicate that the dry cleaning equipment was defectively designed or manufactured. A thorough review of the type of equipment used over the life of the dry cleaning plant and verifiable solvent mileage records frequently indicates that operators of the plant have disposed of solvent and contaminated solids into the municipal sewer or on ground surfaces.     

A History of Dry Cleaners and Sources of Solvent Releases from Dry Cleaning Equipment

Approximately 25, 000-35, 000 dry cleaning facilities currently operate in the U.S. The release of perchloroethylene and other solvents from these establishments represents a major source of soil and groundwater contamination. The manner in which dry cleaning solvents escape from dry cleaning plants is, for all practical purposes, identical for chlorinated and petroleum hydrocarbon solvents and is related to one of the following events: the catastrophic failure of a component of the dry cleaning system, the improper installation, operation or maintenance of the dry cleaning equipment or a combination of all of these causes. Acceptable customs, codes and regulations can also dictate what is authorized for operation of a dry cleaning facility in a particular community, geographic area during a particular time frame. Environmental litigation dealing with the origin of a solvent release from dry cleaners tends to focus on the design and manufacture of dry cleaning industry machines such as washers, washer extractors, tumblers, solvent filters, water separators, stills and spotting boards. A thorough analysis of the daily operations of dry cleaners often reveals that poor maintenance, failure to follow the manufacturer's instructions and the actions of the operator are the most likely causes of soil and groundwater pollution. In order to forensically evaluate the most probable origins of a solvent release and to examine issues regarding liability, a thorough understanding of the history of dry cleaning and a detailed analysis of the operation and maintenance of the dry cleaning equipment are necessary. The discovery of solvent plumes in the vicinity of dry cleaning plants may suggest that the solvent source is the dry cleaning plant; however, the presence of these plumes does not necessarily indicate that the dry cleaning equipment was defectively designed or manufactured. A thorough review of the type of equipment used over the life of the dry cleaning plant and verifiable solvent mileage records frequently indicates that operators of the plant have disposed of solvent and contaminated solids into the municipal sewer or on ground surfaces.     

Spatial Modeling for Air Pollution Monitoring Network Design: Example of Residential Woodsmoke

Abstract

The purpose of this paper is to demonstrate how to develop an air pollution monitoring network to characterize small-area spatial contrasts in ambient air pollution concentrations. Using residential woodburning emissions as our case study, this paper reports on the first three stages of a four-stage protocol to measure, estimate, and validate ambient residential woodsmoke emissions in Vancouver, British Columbia. The first step is to develop an initial winter nighttime woodsmoke emissions surface using inverse-distance weighting of emissions information from consumer woodburning surveys and property assessment data. Second, fireplace density and a compound topo-graphic index based on hydrological flow regimes are used to enhance the emissions surface. Third, the spatial variation of the surface is used in a location-allocation algorithm to design a network of samplers for the woodsmoke tracer compound levoglucosan and fine particulate matter. Measurements at these network sites are then used in the fourth stage of the protocol (not presented here): a mobile sampling campaign aimed at developing a high-resolution surface of woodsmoke concentrations for exposure assignment in health effects studies. Overall the results show that relatively simple data inputs and spatial analysis can be effective in capturing the spatial variability of ambient air pollution emissions and concentrations.