An analysis of factors that influence personal exposure to nitrogen oxides in residents of Richmond, Virginia

Traffic-related air pollution and dementia incidence in the Adult Changes in Thought Study

BACKGROUND

While epidemiologic evidence links higher levels of exposure to fine particulate matter (PM2.5) to decreased cognitive function, fewer studies have investigated links with traffic-related air pollution (TRAP), and none have examined ultrafine particles (UFP, ≤100 nm) and late-life dementia incidence.

OBJECTIVE

To evaluate associations between TRAP exposures (UFP, black carbon [BC], and nitrogen dioxide [NO2]) and late-life dementia incidence.

METHODS

We ascertained dementia incidence in the Seattle-based Adult Changes in Thought (ACT) prospective cohort study (beginning in 1994) and assessed ten-year average TRAP exposures for each participant based on prediction models derived from an extensive mobile monitoring campaign. We applied Cox proportional hazards models to investigate TRAP exposure and dementia incidence using age as the time axis and further adjusting for sex, self-reported race, calendar year, education, socioeconomic status, PM2.5, and APOE genotype. We ran sensitivity analyses where we did not adjust for PM2.5 and other sensitivity and secondary analyses where we adjusted for multiple pollutants, applied alternative exposure models (including total and size-specific UFP), modified the adjustment covariates, used calendar year as the time axis, assessed different exposure periods, dementia subtypes, and others.

RESULTS

We identified 1,041 incident all-cause dementia cases in 4,283 participants over 37,102 person-years of follow-up. We did not find evidence of a greater hazard of late-life dementia incidence with elevated levels of long-term TRAP exposures. The estimated hazard ratio of all-cause dementia was 0.98 (95 % CI: 0.92-1.05) for every 2000 pt/cm3 increment in UFP, 0.95 (0.89-1.01) for every 100 ng/m3 increment in BC, and 0.96 (0.91-1.02) for every 2 ppb increment in NO2. These findings were consistent across sensitivity and secondary analyses.

DISCUSSION

We did not find evidence of a greater hazard of late-life dementia risk with elevated long-term TRAP exposures in this population-based prospective cohort study.

Long-term monitoring of indoor, outdoor, and personal exposure to gaseous chemical compounds

Seasonal variations of chemical compounds in indoor air and outdoor air and personal exposure to these chemicals were continuously monitored for 6 years using four types of passive sampling devices: PSD-BPE/DNPH packed with 2,4-dinitrophenylhydrazine and trans-1,2-bis(2-pyridyl)ethylene coated silica for ozone and carbonyls; PSD-VOC packed with Carboxen 572 or Active Carbon Beads particles for volatile organic compounds; PSD-TEA packed with triethanolamine impregnated silica for acid gases; and PSD-TEA packed with phosphoric acid impregnated silica for basic gases. Many chemical compounds except for nitrogen dioxide, formic acid, and benzene showed seasonal variations with high concentrations in summer and low concentrations in winter. In particular, formaldehyde, nonanal, 2-ethyl-1-hexanol, 2,2,4-trimethyl-1,3-pentanediol monoisobutyrate, and ammonia concentrations showed remarkable seasonal variation. For example, the concentration of formaldehyde in February and August was 5.9 and 40 μg/m3, respectively, a difference of about 7 times. Although there were large differences in the concentrations in each house, the fluctuation pattern was almost the same every year in each house. By contrast, nitrogen dioxide, formic acid, and benzene concentrations were low in summer and high in winter. These compounds were generated by kerosine and gas stoves in winter. Long-term continuous monitoring revealed that annual mean concentrations could be estimated using data from February and August. Personal exposure concentrations could be classified into four patterns: chemicals affected by the indoor environment such as formaldehyde, chemicals affected by the outdoor environment such as ozone, chemicals affected by the occupational environment such as hexane, and background level chemicals such as benzene (without kerosine and gas stoves). Indoor and outdoor measurements are means to investigate the "health" of each environment. Personal exposure measurement using PSD-samplers is suitable for assessing the health risk of chemical compounds to humans.

Indoor Exposure to Selected Air Pollutants in the Home Environment: A Systematic Review

(1) Background: There is increasing awareness that the quality of the indoor environment affects our health and well-being. Indoor air quality (IAQ) in particular has an impact on multiple health outcomes, including respiratory and cardiovascular illness, allergic symptoms, cancers, and premature mortality. (2) Methods: We carried out a global systematic literature review on indoor exposure to selected air pollutants associated with adverse health effects, and related household characteristics, seasonal influences and occupancy patterns. We screened records from six bibliographic databases: ABI/INFORM, Environment Abstracts, Pollution Abstracts, PubMed, ProQuest Biological and Health Professional, and Scopus. (3) Results: Information on indoor exposure levels and determinants, emission sources, and associated health effects was extracted from 141 studies from 29 countries. The most-studied pollutants were particulate matter (PM_2.5 and PM₁₀); nitrogen dioxide (NO₂); volatile organic compounds (VOCs) including benzene, toluene, xylenes and formaldehyde; and polycyclic aromatic hydrocarbons (PAHs) including naphthalene. Identified indoor PM_2.5 sources include smoking, cooking, heating, use of incense, candles, and insecticides, while cleaning, housework, presence of pets and movement of people were the main sources of coarse particles. Outdoor air is a major PM_2.5 source in rooms with natural ventilation in roadside households. Major sources of NO₂ indoors are unvented gas heaters and cookers. Predictors of indoor NO₂ are ventilation, season, and outdoor NO₂ levels. VOCs are emitted from a wide range of indoor and outdoor sources, including smoking, solvent use, renovations, and household products. Formaldehyde levels are higher in newer houses and in the presence of new furniture, while PAH levels are higher in smoking households. High indoor particulate matter, NO₂ and VOC levels were typically associated with respiratory symptoms, particularly asthma symptoms in children. (4) Conclusions: Household characteristics and occupant activities play a large role in indoor exposure, particularly cigarette smoking for PM_2.5, gas appliances for NO₂, and household products for VOCs and PAHs. Home location near high-traffic-density roads, redecoration, and small house size contribute to high indoor air pollution. In most studies, air exchange rates are negatively associated with indoor air pollution. These findings can inform interventions aiming to improve IAQ in residential properties in a variety of settings.

Exposure to indoor air pollution across socio-economic groups in high-income countries: A scoping review of the literature and a modelling methodology

Disparities in outdoor air pollution exposure between individuals of differing socio-economic status is a growing area of research, widely explored in the environmental health literature. However, in developed countries, around 80% of time is spent indoors, meaning indoor air pollution may be a better proxy for personal exposure. Building characteristics - such as build quality, volume and ventilation - and occupant behaviour, mean indoor air pollution may also vary across socio-economic groups, leading to health inequalities. Much of the existing literature has focused on inequalities in exposure to outdoor air pollution, and there is thus a lack of an evidence base reviewing data for indoor environments. In this study, a scoping review of the literature on indoor air pollution exposures across different socio-economic groups is performed, examining evidence from both monitoring and modelling studies in the developed world. The literature was reviewed, identifying different indoor pollutants, definitions for socio-economic status and pre- and post- housing interventions. Based on the review, the study proposes a modelling methodology for evaluating the effects of environmental policies on different socio-economic populations. Using a sample size calculation, obstacles in obtaining sufficiently large samples of monitored data are demonstrated. A modelling framework for the rapid quantification of daily home exposure is then outlined as a proof of concept. While significant additional research is required to examine inequalities in indoor exposures, modelling approaches may provide opportunities to quantify exposure disparities due to housing and behaviours across populations of different socio-economic status.

PM2.5 and NO2 exposure errors using proxy measures, including derived personal exposure from outdoor sources: A systematic review and meta-analysis

BACKGROUND

The use of proxy exposure estimates for PM_2.5 and NO₂ in air pollution studies instead of personal exposures, introduces measurement error, which can produce biased epidemiological effect estimates. Most studies consider total personal exposure as the gold standard. However, when studying the effects of ambient air pollution, personal exposure from outdoor sources is the exposure of interest.

OBJECTIVES

We assessed the magnitude and variability of exposure measurement error by conducting a systematic review of the differences between personal exposures from outdoor sources and the corresponding measurements for ambient concentrations in order to increase understanding of the measurement error structures of the pollutants.

DATA SOURCES AND ELIGIBILITY CRITERIA

We reviewed the literature (ISI Web of Science, Medline, 2000-2016) for English language studies (in any age group in any location (NO₂) or Europe and North America (PM_2.5)) that reported repeated measurements over time both for personal and ambient PM_2.5 or NO₂ concentrations. Only a few studies reported personal exposure from outdoor sources. We also collected data for infiltration factors and time-activity patterns of the individuals in order to estimate personal exposures from outdoor sources in every study.

STUDY APPRAISAL AND SYNTHESIS METHODS

Studies using modelled rather than monitored exposures were excluded. Type of personal exposure monitor was assessed. Random effects meta-analysis was conducted to quantify exposure error as the mean difference between "true" and proxy measures.

RESULTS

Thirty-two papers for PM_2.5 and 24 for NO₂ were identified. Outdoor sources were found to contribute 44% (range: 33-55%) of total personal exposure to PM_2.5 and 74% (range: 57-88%) to NO₂. Overall estimates of personal exposure (24-hour averages) from outdoor sources were 9.3 μg/m³ and 12.0 ppb for PM_2.5 and NO₂ respectively, while the corresponding difference between these exposures and the ambient concentrations (i.e. the measurement error) was 5.72 μg/m³ and 7.17 ppb. Our findings indicated also higher error variability for NO₂ than PM_2.5. Large heterogeneity was observed which was not explained sufficiently by geographical location or age group of the study sample.

LIMITATIONS, CONCLUSIONS AND IMPLICATIONS OF KEY FINDINGS

Relying only on information available in published studies led to some limitations: the contribution of outdoor sources to total personal exposure for NO₂ had to be inferred, individual variation in exposure misclassification was unavailable and instrument error could not be addressed. The larger magnitude and variability of errors for NO₂ compared with PM_2.5 has implications for biases in the health effect estimates of multi-pollutant epidemiological models. Results suggest that further research is needed regarding personal exposure studies and measurement error bias in epidemiological models.

Long-Term Ambient Residential Traffic-Related Exposures and Measurement Error-Adjusted Risk of Incident Lung Cancer in the Netherlands Cohort Study on Diet and Cancer

BACKGROUND

The International Agency for Research on Cancer (IARC) recently declared air pollution carcinogenic to humans. However, no study of air pollution and lung cancer to date has incorporated adjustment for exposure measurement error, and few have examined specific histological subtypes.

OBJECTIVES

Our aim was to assess the association of air pollution and incident lung cancer in the Netherlands Cohort Study on Diet and Cancer and the impact of measurement error on these associations.

METHODS

The cohort was followed from 1986 through 2003, and 3,355 incident cases were identified. Cox proportional hazards models were used to estimate hazard ratios and 95% confidence intervals, for long-term exposures to nitrogen dioxide (NO2), black smoke (BS), PM2.5 (particulate matter with diameter ≤ 2.5 μm), and measures of roadway proximity and traffic volume, adjusted for potential confounders. Information from a previous validation study was used to correct the effect estimates for measurement error.

RESULTS

We observed elevated risks of incident lung cancer with exposure to BS [hazard ratio (HR) = 1.16; 95% CI: 1.02, 1.32, per 10 μg/m3], NO2 (HR = 1.29; 95% CI: 1.08, 1.54, per 30 μg/m3), PM2.5 (HR = 1.17; 95% CI: 0.93, 1.47, per 10 μg/m3), and with measures of traffic at the baseline address. The exposures were positively associated with all lung cancer subtypes. After adjustment for measurement error, the HRs increased and the 95% CIs widened [HR = 1.19 (95% CI: 1.02, 1.39) for BS and HR = 1.37 (95% CI: 0.86, 2.17) for PM2.5].

CONCLUSIONS

These findings add support to a growing body of literature on the effects of air pollution on lung cancer. In addition, they highlight variation in measurement error by pollutant and support the implementation of measurement error corrections when possible.

CITATION

Hart JE, Spiegelman D, Beelen R, Hoek G, Brunekreef B, Schouten LJ, van den Brandt P. 2015. Long-term ambient residential traffic-related exposures and measurement error-adjusted risk of incident lung cancer in the Netherlands Cohort Study on Diet and Cancer. Environ Health Perspect 123:860-866; http://dx.doi.org/10.1289/ehp.1408762.

The microenvironmental modelling approach to assess children's exposure to air pollution - A review

Exposures to a wide spectrum of air pollutants were associated to several effects on children's health. Exposure assessment can be used to establish where and how air pollutants' exposures occur. However, a realistic estimation of children's exposures to air pollution is usually a great ethics challenge, especially for young children, because they cannot intentionally be exposed to contaminants and according to Helsinki declaration, they are not old enough to make a decision on their participation. Additionally, using adult surrogates introduces bias, since time-space-activity patterns are different from those of children. From all the different available approaches for exposure assessment, the microenvironmental (ME) modelling (indirect approach, where personal exposures are estimated or predicted from microenvironment measurements combined with time-activity data) seemed to be the best to assess children's exposure to air pollution as it takes into account the varying levels of pollution to which an individual is exposed during the course of the day, it is faster and less expensive. Thus, this review aimed to explore the use of the ME modelling approach methodology to assess children's exposure to air pollution. To meet this goal, a total of 152 articles, published since 2002, were identified and titles and abstracts were scanned for relevance. After exclusions, 26 articles were fully reviewed and main characteristics were detailed, namely: (i) study design and outcomes, including location, study population, calendar time, pollutants analysed and purpose; and (ii) data collection, including time-activity patterns (methods of collection, record time and key elements) and pollution measurements (microenvironments, methods of collection and duration and time resolution). The reviewed studies were from different parts of the world, confirming the worldwide application, and mostly cross-sectional. Longitudinal studies were also found enhancing the applicability of this approach. The application of this methodology on children is different from that on adults because of data collection, namely the methods used for collecting time-activity patterns must be different and the time-activity patterns are itself different, which leads to select different microenvironments to the data collection of pollutants' concentrations. The most used methods to gather information on time-activity patterns were questionnaires and diaries, and the main microenvironments considered were home and school (indoors and outdoors). Although the ME modelling approach in studies to assess children's exposure to air pollution is highly encouraged, a validation process is needed, due to the uncertainties associated with the application of this approach.

Hazard assessment of chemical air contaminants measured in residences

Identifying air pollutants that pose a potential hazard indoors can facilitate exposure mitigation. In this study, we compiled summary results from 77 published studies reporting measurements of chemical pollutants in residences in the United States and in countries with similar lifestyles. These data were used to calculate representative mid-range and upper-bound concentrations relevant to chronic exposures for 267 pollutants and representative peak concentrations relevant to acute exposures for five activity-associated pollutants. Representative concentrations are compared to available chronic and acute health standards for 97 pollutants. Fifteen pollutants appear to exceed chronic health standards in a large fraction of homes. Nine other pollutants are identified as potential chronic health hazards in a substantial minority of homes, and an additional nine are identified as potential hazards in a very small percentage of homes. Nine pollutants are identified as priority hazards based on the robustness of measured concentration data and the fraction of residences that appear to be impacted: acetaldehyde; acrolein; benzene; 1,3-butadiene; 1,4-dichlorobenzene; formaldehyde; naphthalene; nitrogen dioxide; and PM(2.5). Activity-based emissions are shown to pose potential acute health hazards for PM(2.5), formaldehyde, CO, chloroform, and NO(2).

PRACTICAL IMPLICATIONS

This analysis identifies key chemical contaminants of concern in residential indoor air using a comprehensive and consistent hazard-evaluation protocol. The identification of a succinct group of chemical hazards in indoor air will allow for successful risk ranking and mitigation prioritization for the indoor residential environment. This work also indicates some common household activities that may lead to the acute levels of pollutant exposure and identifies hazardous chemicals for priority removal from consumer products and home furnishings.

Predicting personal nitrogen dioxide exposure in an elderly population: integrating residential indoor and outdoor measurements, fixed-site ambient pollution concentrations, modeled pollutant levels, and time-activity patterns

Predicting chronic exposure to air pollution at the intra-urban scale has been recognized as a priority area of research for environmental epidemiology. Exposure assessment models attempt to predict and proxy for individuals' personal exposure to ambient air pollution, and there are no studies to date that explicitly attempt to compare and cross-validate personal exposure concentrations with pollutants modeled at the intra-urban level using methods such as interpolated surfaces and land-use regression (LUR) models. This study aimed to identify how well personal exposure to NO(2) (nitrogen dioxide) can be predicted from ambient exposure measurements and intra-urban exposure estimates using LUR and what other factors contribute to predicting variations in personal exposure beyond measured pollutant levels within home. Personal, indoor and outdoor NO(2) were measured in a population of older adults (>65 yr old) living in Hamilton, Canada. Our results show that personal NO(2) was most strongly associated with contemporaneously collected indoor and outdoor concentrations of NO(2). Predicted NO(2) exposures from intra-urban LUR models were not associated with personal NO(2), whereas interpolated surfaces of particulates and ozone were modestly associated. Combinations of variables that best predicted personal NO(2) variability were derived from time-activity diaries, interpolated surfaces of ambient particulate pollutants, and a city wide temporally matched average of NO(2). The nonsignificant associations between personal NO(2) and the modeled ambient NO(2) concentrations suggest that observed associations between NO(2) generated by LUR models and health effects are probably not produced by NO(2), but by other pollutants that follow a similar spatial pattern.

Passive dosimeters for nitrogen dioxide in personal/indoor air sampling: a review

Accurate measurement of nitrogen dioxide concentrations in both outdoor and indoor environments, including personal exposures, is a fundamental step for linking atmospheric nitrogen dioxide levels to potential health and ecological effects. The measurement has been conducted generally in two ways: active (pumped) sampling and passive (diffusive) sampling. Diffusion samplers, initially developed and used for workplace air monitoring, have been found to be useful and cost-effective alternatives to conventional pumped samplers for monitoring ambient, indoor and personal exposures at the lower concentrations found in environmental settings. Since the 1970s, passive samplers have been deployed for ambient air monitoring in urban and rural sites, and to determine personal and indoor exposure to NO2. This article reviews the development of NO2 passive samplers, the sampling characteristics of passive samplers currently available, and their application in ambient and indoor air monitoring and personal exposure studies. The limitations and advantages of the various passive sampler geometries (i.e., tube, badge, and radial type) are also discussed. This review provides researchers and risk assessors with practical information about NO2 passive samplers, especially useful when designing field sampling strategies for exposure and indoor/outdoor air sampling.

Predicting personal exposure of pregnant women to traffic-related air pollutants

As epidemiological studies report associations between ambient air pollution and adverse birth outcomes, it is important to understand determinants of exposures among pregnant women. We measured (48-h, personal exposure) and modeled (using outdoor ambient monitors and a traffic-based land-use regression model) NO, NO(2), fine particle mass and absorbance in 62 non-smoking pregnant women in Vancouver, Canada on 1-3 occasions during pregnancy (total N=127). We developed predictive models for personal measurements using modeled ambient concentrations and individual determinants of exposure. Geometric mean exposures of personal samples were relatively low (GM (GSD) NO=37 ppb (2.0); NO(2)=17 ppb (1.6); 'soot', as filter absorbance=0.8 10(-5) m(-1) (1.5); PM(2.2)=10 microg m(-3) (1.6)). Having a gas stove (vs. electric stove) in the home was associated with exposure increases of 89% (NO), 44% (NO(2)), 20% (absorbance) and 35% (fine PM). Interpolated concentrations from outdoor fixed-site monitors were associated with all personal exposures except NO(2). Land-use regression model estimates of outdoor air pollution were associated with personal NO and NO(2) only. The effects of outdoor air pollution on personal samples were consistent, with and without adjustment for other individual determinants (e.g. gas stove). These findings improve our understanding of sources of exposure to air pollutants among pregnant women and support the use of outdoor concentration estimates as proxies for exposure in epidemiologic studies.

Predicting residential indoor concentrations of nitrogen dioxide, fine particulate matter, and elemental carbon using questionnaire and geographic information system based data

Previous studies have identified associations between traffic-related air pollution and adverse health effects. Most have used measurements from a few central ambient monitors and/or some measure of traffic as indicators of exposure, disregarding spatial variability and/or factors influencing personal exposure-ambient concentration relationships. This study seeks to utilize publicly available data (i.e., central site monitors, geographic information system (GIS), and property assessment data) and questionnaire responses to predict residential indoor concentrations of traffic-related air pollutants for lower socioeconomic status (SES) urban households.As part of a prospective birth cohort study in urban Boston, we collected indoor and outdoor 3-4 day samples of nitrogen dioxide (NO(2)) and fine particulate matter (PM(2.5)) in 43 low SES residences across multiple seasons from 2003 - 2005. Elemental carbon concentrations were determined via reflectance analysis. Multiple traffic indicators were derived using Massachusetts Highway Department data and traffic counts collected outside sampling homes. Home characteristics and occupant behaviors were collected via a standardized questionnaire. Additional housing information was collected through property tax records, and ambient concentrations were collected from a centrally-located ambient monitor.The contributions of ambient concentrations, local traffic and indoor sources to indoor concentrations were quantified with regression analyses. PM(2.5) was influenced less by local traffic but had significant indoor sources, while EC was associated with traffic and NO(2) with both traffic and indoor sources. Comparing models based on covariate selection using p-values or a Bayesian approach yielded similar results, with traffic density within a 50m buffer of a home and distance from a truck route as important contributors to indoor levels of NO(2) and EC, respectively. The Bayesian approach also highlighted the uncertanity in the models. We conclude that by utilizing public databases and focused questionnaire data we can identify important predictors of indoor concentrations for multiple air pollutants in a high-risk population.

Bias and confounding in longitudinal measures of exhaled monoxides

The measurement of exhaled nitric oxide and carbon monoxide concentrations is an emerging method of monitoring airway inflammation longitudinally in community-based studies. Inhaled concentrations of these monoxides influence exhaled concentrations. Little is known about the degree to which inhaled concentrations distort temporal trends in, or estimated effects of air pollutants on, exhaled monoxides. We sought to evaluate whether estimated effects of air pollutants on exhaled monoxides are distorted by trends in indoor and outdoor monoxides, and to characterize determinants of exhaled monoxide concentrations among residents of public housing. In a panel study, 42 residents of public housing provided over 1000 exhaled breath samples. Samples from all subjects were analyzed for nitric oxide; samples from 27 of these subjects were also analyzed for carbon monoxide. The effects of indoor and outdoor monoxide concentrations on exhaled concentrations were quantified. Confounding of associations between particulate matter concentrations and exhaled nitric oxide concentrations was explored. Determinants of exhaled monoxide concentrations among public housing residents are similar to those of other populations. Exhaled monoxide concentrations are more strongly associated with indoor than with outdoor monoxide concentrations. Approximately half of the variability in exhaled monoxide concentrations over time can be explained by changes in indoor monoxide concentrations. Indoor monoxide concentrations can markedly distort both temporal trends in exhaled concentrations as well as estimated effects of particulate matter on exhaled monoxides. Prior estimated effects of particulate matter on exhaled nitric oxide concentrations may have been confounded by nitric concentrations indoors at the time of exhaled air collection. To prevent distortions of longitudinal trends in airway inflammation and estimated health effects of air pollutants, inspiratory scrubber use is necessary but not sufficient to remove the confounding effect of indoor monoxides, and analyses should adjust exhaled monoxide concentrations for concentrations indoors.

Predictors of concentrations of nitrogen dioxide, fine particulate matter, and particle constituents inside of lower socioeconomic status urban homes

Air pollution exposure patterns may contribute to known spatial patterning of asthma morbidity within urban areas. While studies have evaluated the relationship between traffic and outdoor concentrations, few have considered indoor exposure patterns within low socioeconomic status (SES) urban communities. In this study, part of a prospective birth cohort study assessing asthma etiology in urban Boston, we collected indoor and outdoor 3-4 day samples of nitrogen dioxide (NO2) and fine particulate matter (PM2.5) in 43 residences across multiple seasons from 2003 to 2005. Homes were chosen to represent low SES households, including both cohort and non-cohort residences in similar neighborhoods, and consisted almost entirely of multiunit residences. Reflectance analysis and X-ray fluorescence spectroscopy were performed on the particle filters to determine elemental carbon (EC) and trace element concentrations, respectively. Additionally, information on home characteristics (e.g. type, age, stove fuel) and occupant behaviors (e.g. smoking, cooking, cleaning) were collected via a standardized questionnaire. The contributions of outdoor and indoor sources to indoor concentrations were quantified with regression analyses using mass balance principles. For NO2 and most particle constituents (except outdoor-dominated constituents like sulfur and vanadium), the addition of selected indoor source terms improved the model's predictive power. Cooking time, gas stove usage, occupant density, and humidifiers were identified as important contributors to indoor levels of various pollutants. A comparison between cohort and non-cohort participants provided another means to determine the influence of occupant activity patterns on indoor-outdoor ratios. Although the groups had similar housing characteristics and were located in similar neighborhoods, cohort members had significantly higher indoor concentrations of PM2.5 and NO2, associated with indoor activities. We conclude that the effect of indoor sources may be more pronounced in high-density multiunit dwellings, and that future epidemiological studies in these populations should explicitly consider these sources in assigning exposures.

A review and evaluation of intraurban air pollution exposure models

The development of models to assess air pollution exposures within cities for assignment to subjects in health studies has been identified as a priority area for future research. This paper reviews models for assessing intraurban exposure under six classes, including: (i) proximity-based assessments, (ii) statistical interpolation, (iii) land use regression models, (iv) line dispersion models, (v) integrated emission-meteorological models, and (vi) hybrid models combining personal or household exposure monitoring with one of the preceding methods. We enrich this review of the modelling procedures and results with applied examples from Hamilton, Canada. In addition, we qualitatively evaluate the models based on key criteria important to health effects assessment research. Hybrid models appear well suited to overcoming the problem of achieving population representative samples while understanding the role of exposure variation at the individual level. Remote sensing and activity-space analysis will complement refinements in pre-existing methods, and with expected advances, the field of exposure assessment may help to reduce scientific uncertainties that now impede policy intervention aimed at protecting public health.