HealthyPlan.City: A Web Tool to Support Urban Environmental Equity and Public Health in Canadian Communities.

Urban environmental factors such as air quality, heat islands, and access to greenspaces and community amenities impact public health. Some vulnerable populations such as low-income groups, children, older adults, new immigrants, and visible minorities live in areas with fewer beneficial conditions, and therefore, face greater health risks. Planning and advocating for equitable healthy urban environments requires systematic analysis of reliable spatial data to identify where vulnerable populations intersect with positive or negative urban/environmental characteristics. To facilitate this effort in Canada, we developed HealthyPlan.City ( https://healthyplan.city/ ), a freely available web mapping platform for users to visualize the spatial patterns of built environment indicators, vulnerable populations, and environmental inequity within over 125 Canadian cities. This tool helps users identify areas within Canadian cities where relatively higher proportions of vulnerable populations experience lower than average levels of beneficial environmental conditions, which we refer to as Equity priority areas. Using nationally standardized environmental data from satellite imagery and other large geospatial databases and demographic data from the Canadian Census, HealthyPlan.City provides a block-by-block snapshot of environmental inequities in Canadian cities. The tool aims to support urban planners, public health professionals, policy makers, and community organizers to identify neighborhoods where targeted investments and improvements to the local environment would simultaneously help communities address environmental inequities, promote public health, and adapt to climate change. In this paper, we report on the key considerations that informed our approach to developing this tool and describe the current web-based application.

Predicting walking-to-work using street-level imagery and deep learning in seven Canadian cities.

New 'big data' streams such as street-level imagery are offering unprecedented possibilities for developing health-relevant data on the urban environment. Urban environmental features derived from street-level imagery have been used to assess pedestrian-friendly neighbourhood design and to predict active commuting, but few such studies have been conducted in Canada. Using 1.15 million Google Street View (GSV) images in seven Canadian cities, we applied image segmentation and object detection computer vision methods to extract data on persons, bicycles, buildings, sidewalks, open sky (without trees or buildings), and vegetation at postal codes. The associations between urban features and walk-to-work rates obtained from the Canadian Census were assessed. We also assessed how GSV-derived urban features perform in predicting walk-to-work rates relative to more widely used walkability measures. Results showed that features derived from street-level images are better able to predict the percent of people walking to work as their primary mode of transportation compared to data derived from traditional walkability metrics. Given the increasing coverage of street-level imagery around the world, there is considerable potential for machine learning and computer vision to help researchers study patterns of active transportation and other health-related behaviours and exposures.

Cancer and the Environment projects with four First Nations organizations: working together to address concerns about carcinogens in the environment.

SETTING: For First Nations people, human health and well-being are interconnected with a healthy environment. First Nations organizations commonly raise concerns regarding carcinogens in the environment; however, few case studies are available as guidance for working in a participatory and respectful way to help assess and address these concerns. INTERVENTION: Through four community-led pilot projects executed over two years, we collaborated with 15 participants from four First Nations organizations across four provinces to identify concerns related to environmental carcinogens and to address those concerns through an integrated knowledge translation (KT) approach. We co-developed and implemented strategic KT plans for each pilot project, and conducted evaluation surveys and interviews with participants at multiple time points to assess process, progress, barriers and facilitators, and impact. OUTCOMES: The activities and outputs of the pilot projects are available at www.carexcanada.ca . Participants identified 18 concerns, and we co-developed 24 knowledge products. Tailored fact sheets for communities and briefing notes for leadership were deemed most useful; interactive maps were deemed less useful. Evaluation indicated that the collaborative projects were effective in addressing the concerns raised regarding exposures to carcinogens. IMPLICATIONS: The participant-led approach and multi-year funding to support capacity enhancement and face-to-face engagement were facilitators to project success. However, participants did face important barriers to collaborate which should be considered in future projects of this kind: the most important being a lack of resources (people and time), given competing and often more urgent priorities.

RéSUMé: LIEU: Pour les Premiers Peuples, la santé et le bien-être humains sont indissociables de la santé de l'environnement. Les organismes des Premières Nations se disent souvent préoccupés par les cancérogènes présents dans l'environnement, mais peu d'études de cas sont disponibles pour apprendre à travailler de façon participative et respectueuse à évaluer ces préoccupations et à y répondre. INTERVENTION: Dans le cadre de quatre projets pilotes de proximité menés sur une période de deux ans, nous avons collaboré avec 15 participants, issus de quatre organismes des Premières Nations dans quatre provinces, à cerner leurs préoccupations liées aux cancérogènes dans l'environnement et à y répondre selon une démarche intégrée d'application des connaissances. Nous avons conjointement élaboré et mis en œuvre des plans stratégiques d'application des connaissances pour chaque projet pilote et mené des sondages d'évaluation et des entretiens avec les participants à plusieurs reprises pour évaluer le processus, les progrès accomplis, les éléments favorables et défavorables et les impacts des projets. RéSULTATS: Les activités et les extrants des projets pilotes sont présentés sur le site www.carexcanada.ca . Les participants ont exprimé 18 motifs de préoccupation, et nous avons élaboré avec eux 24 produits du savoir. Les fiches d'information adaptées à chaque communauté et les notes d'information pour les dirigeants ont été jugées très utiles, mais les cartes interactives un peu moins. Selon l'évaluation, les projets collaboratifs ont réussi à répondre aux préoccupations soulevées quant à l'exposition aux cancérogènes. CONSéQUENCES: La démarche axée sur les participants et le financement pluriannuel consacré au renforcement des capacités et aux contacts directs ont été des éléments favorables à la réussite des projets. Par contre, les participants ont fait face à d'importants obstacles à la collaboration dont il faudrait tenir compte dans les futurs projets de la sorte, le principal obstacle étant le manque de ressources (personnes et temps), étant donné l'existence de priorités concurrentes et souvent plus urgentes.

Centralizing environmental datasets to support (inter)national chronic disease research: Values, challenges, and recommendations.

Whereas environmental data are increasingly available, it is often not clear how or if datasets are available for health research. Exposure metrics are typically developed for specific research initiatives using disparate exposure assessment methods and no mechanisms are put in place for centralizing, archiving, or distributing environmental datasets. In parallel, potentially vast amounts of environmental data are emerging due to new technologies such as high resolution imagery and machine learning. OBJECTIVES: The Canadian Urban Environmental Health Research Consortium (CANUE) and the Geoscience and Health Cohort Consortium (GECCO) provide a proof of concept that centralizing and disseminating environmental data for health research is valuable and can accelerate discovery. In this essay, we argue that more efficient use of exposure data for environmental epidemiological research over the next decade requires progress in four key areas: metadata and data access portals, linkage with health databases, harmonization of exposure measures and models over large areas, and leveraging "big data" streams for exposure characterization and evaluation of temporal changes. DISCUSSION: Optimizing the use of existing environmental data and exploiting emerging data streams can provide unprecedented research opportunities in environmental epidemiology through a better characterization of individuals' exposures and the ability to study the intersecting impacts of multiple environmental features or urban attributes across different populations around the world. Proper documentation, linkage, and dissemination of new and emerging exposure data leads to a better awareness of data availability, a reduction of duplication of effort and increases research output.

Healthy built environment: Spatial patterns and relationships of multiple exposures and deprivation in Toronto, Montreal and Vancouver.

BACKGROUND: Various aspects of the urban environment and neighbourhood socio-economic status interact with each other to affect health. Few studies to date have quantitatively assessed intersections of multiple urban environmental factors and their distribution across levels of deprivation. OBJECTIVES: To explore the spatial patterns of urban environmental exposures within three large Canadian cities, assess how exposures are distributed across socio-economic deprivation gradients, and identify clusters of favourable or unfavourable environmental characteristics. METHODS: We indexed nationally standardized estimates of active living friendliness (i.e. "walkability"), NO2 air pollution, and greenness to 6-digit postal codes within the cities of Toronto, Montreal and Vancouver. We compared the distribution of within-city exposure tertiles across quintiles of material deprivation. Tertiles of each exposure were then overlaid with each other in order to identify potentially favorable (high walkability, low NO2, high greenness) and unfavorable (low walkability, high NO2, and low greenness) environments. RESULTS: In all three cities, high walkability was more common in least deprived areas and less prevalent in highly deprived areas. We also generally saw a greater prevalence of postal codes with high vegetation indices and low NO2 in areas with low deprivation, and a lower greenness prevalence and higher NO2 concentrations in highly deprived areas, suggesting environmental inequity is occurring. Our study showed that relatively few postal codes were simultaneously characterized by desirable or undesirable walkability, NO2and greenness tertiles. DISCUSSION: Spatial analyses of multiple standardized urban environmental factors such as the ones presented in this manuscript can help refine municipal investments and policy priorities. This study illustrates a methodology to prioritize areas for interventions that increase active living and exposure to urban vegetation, as well as lower air pollution. Our results also highlight the importance of considering the intersections between the built environment and socio-economic status in city planning and urban public health decision-making.

The Canadian Urban Environmental Health Research Consortium - a protocol for building a national environmental exposure data platform for integrated analyses of urban form and health.

BACKGROUND: Multiple external environmental exposures related to residential location and urban form including, air pollutants, noise, greenness, and walkability have been linked to health impacts or benefits. The Canadian Urban Environmental Health Research Consortium (CANUE) was established to facilitate the linkage of extensive geospatial exposure data to existing Canadian cohorts and administrative health data holdings. We hypothesize that this linkage will enable investigators to test a variety of their own hypotheses related to the interdependent associations of built environment features with diverse health outcomes encompassed by the cohorts and administrative data. METHODS: We developed a protocol for compiling measures of built environment features that quantify exposure; vary spatially on the urban and suburban scale; and can be modified through changes in policy or individual behaviour to benefit health. These measures fall into six domains: air quality, noise, greenness, weather/climate, and transportation and neighbourhood factors; and will be indexed to six-digit postal codes to facilitate merging with health databases. Initial efforts focus on existing data and include estimates of air pollutants, greenness, temperature extremes, and neighbourhood walkability and socioeconomic characteristics. Key gaps will be addressed for noise exposure, with a new national model being developed, and for transportation-related exposures, with detailed estimates of truck volumes and diesel emissions now underway in selected cities. Improvements to existing exposure estimates are planned, primarily by increasing temporal and/or spatial resolution given new satellite-based sensors and more detailed national air quality modelling. Novel metrics are also planned for walkability and food environments, green space access and function and life-long climate-related exposures based on local climate zones. Critical challenges exist, for example, the quantity and quality of input data to many of the models and metrics has changed over time, making it difficult to develop and validate historical exposures. DISCUSSION: CANUE represents a unique effort to coordinate and leverage substantial research investments and will enable a more focused effort on filling gaps in exposure information, improving the range of exposures quantified, their precision and mechanistic relevance to health. Epidemiological studies may be better able to explore the common theme of urban form and health in an integrated manner, ultimately contributing new knowledge informing policies that enhance healthy urban living.

Lifetime excess cancer risk due to carcinogens in food and beverages: Urban versus rural differences in Canada.

OBJECTIVES: To explore differences in urban versus rural lifetime excess risk of cancer from five specific contaminants found in food and beverages. METHODS: Probable contaminant intake is estimated using Monte Carlo simulations of contaminant concentrations in combination with dietary patterns. Contaminant concentrations for arsenic, benzene, lead, polychlorinated biphenyls (PCBs) and tetrachloroethylene (PERC) were derived from government dietary studies. The dietary patterns of 34 944 Canadians from 10 provinces were available from Health Canada's Canadian Community Health Survey, Cycle 2.2, Nutrition (2004). Associated lifetime excess cancer risk (LECR) was subsequently calculated from the results of the simulations. RESULTS: In the calculation of LECR from food and beverages for the five selected substances, two (lead and PERC) were shown to have excess risk below 10 per million; whereas for the remaining three (arsenic, benzene and PCBs), it was shown that at least 50% of the population were above 10 per million excess cancers. Arsenic residues, ingested via rice and rice cereal, registered the greatest disparity between urban and rural intake, with LECR per million levels well above 1000 per million at the upper bound. The majority of PCBs ingestion comes from meat, with values slightly higher for urban populations and LECR per million estimates between 50 and 400. Drinking water is the primary contributor of benzene intake in both urban and rural populations, with LECR per million estimates of 35 extra cancers in the top 1% of sampled population. CONCLUSION: Overall, there are few disparities between urban and rural lifetime excess cancer risk from contaminants found in food and beverages. Estimates could be improved with more complete Canadian dietary intake and concentration data in support of detailed exposure assessments in estimating LECR.

Identifying potential exposure reduction priorities using regional rankings based on emissions of known and suspected carcinogens to outdoor air in Canada.

BACKGROUND: Emissions inventories aid in understanding the sources of hazardous air pollutants and how these vary regionally, supporting targeted reduction actions. Integrating information on the relative toxicity of emitted pollutants with respect to cancer in humans helps to further refine reduction actions or recommendations, but few national programs exist in North America that use emissions estimates in this way. The CAREX Canada Emissions Mapping Project provides key regional indicators of emissions (total annual and total annual toxic equivalent, circa 2011) of 21 selected known and suspected carcinogens. METHODS: The indicators were calculated from industrial emissions reported to the National Pollutant Release Inventory (NPRI) and estimates of emissions from transportation (airports, trains, and car and truck traffic) and residential heating (oil, gas and wood), in conjunction with human toxicity potential factors. We also include substance-specific annual emissions in toxic equivalent kilograms and annual emissions in kilograms, to allow for ranking substances within any region. RESULTS: For provinces and territories in Canada, the indicators suggest the top five substances contributing to the total toxic equivalent emissions in any region could be prioritized for further investigation. Residents of Quebec and New Brunswick may be more at risk of exposure to industrial emissions than those in other regions, suggesting that a more detailed study of exposure to industrial emissions in these provinces is warranted. Residential wood smoke may be an important emission to control, particularly in the north and eastern regions of Canada. Residential oil and gas heating, along with rail emissions contribute little to regional emissions and therefore may not be an immediate regional priority. CONCLUSIONS: The developed indicators support the identification of pollutants and sources for additional investigation when planning exposure reduction actions among Canadian provinces and territories, but have important limitations similar to other emissions inventory-based tools. Additional research is required to evaluate how the Emissions Mapping Project is used by different groups and organizations with respect to informing actions aimed at reducing Canadians' potential exposure to harmful air pollutants.

Geographic variation in radon and associated lung cancer risk in Canada.

OBJECTIVE: Radon is an important risk factor for lung cancer. Here we use maps of the geographic variation in radon to estimate the lung cancer risk associated with living in high radon areas of Canada. METHODS: Geographic variation in radon was estimated using two mapping methods. The first used a Health Canada survey of 14,000 residential radon measurements aggregated to health regions, and the second, radon risk areas previously estimated from geology, sediment geochemistry and aerial gamma-ray spectrometry. Lung cancer risk associated with living in these radon areas was examined using a population-based case-control study of 2,390 lung cancer cases and 3,507 controls collected from 1994-1997 in eight Canadian provinces. Residential histories over a 20-year period were used in combination with the two mapping methods to estimate ecological radon exposures. Hierarchical logistic regression analyses were used to estimate odds ratios for lung cancer incidence, after adjusting for a comprehensive set of individual and geographic covariates. RESULTS: Across health regions in Canada, significant variation in average residential radon concentrations (range: 16-386 Bq/m3) and in high geological-based radon areas (range: 0-100%) is present. In multivariate models, a 50 Bq/m3 increase in average health region radon was associated with a 7% (95% CI: -6-21%) increase in the odds of lung cancer. For every 10 years that individuals lived in high radon geological areas, the odds of lung cancer increased by 11% (95% CI: 1-23%). CONCLUSIONS: These findings provide further evidence that radon is an important risk factor for lung cancer and that risks are unevenly distributed across Canada.

Risk-based indicators of Canadians' exposures to environmental carcinogens.

BACKGROUND: Tools for estimating population exposures to environmental carcinogens are required to support evidence-based policies to reduce chronic exposures and associated cancers. Our objective was to develop indicators of population exposure to selected environmental carcinogens that can be easily updated over time, and allow comparisons and prioritization between different carcinogens and exposure pathways. METHODS: We employed a risk assessment-based approach to produce screening-level estimates of lifetime excess cancer risk for selected substances listed as known carcinogens by the International Agency for Research on Cancer. Estimates of lifetime average daily intake were calculated using population characteristics combined with concentrations (circa 2006) in outdoor air, indoor air, dust, drinking water, and food and beverages from existing monitoring databases or comprehensive literature reviews. Intake estimates were then multiplied by cancer potency factors from Health Canada, the United States Environmental Protection Agency, and the California Office of Environmental Health Hazard Assessment to estimate lifetime excess cancer risks associated with each substance and exposure pathway. Lifetime excess cancer risks in excess of 1 per million people are identified as potential priorities for further attention. RESULTS: Based on data representing average conditions circa 2006, a total of 18 carcinogen-exposure pathways had potential lifetime excess cancer risks greater than 1 per million, based on varying data quality. Carcinogens with moderate to high data quality and lifetime excess cancer risk greater than 1 per million included benzene, 1,3-butadiene and radon in outdoor air; benzene and radon in indoor air; and arsenic and hexavalent chromium in drinking water. Important data gaps were identified for asbestos, hexavalent chromium and diesel exhaust in outdoor and indoor air, while little data were available to assess risk for substances in dust, food and beverages. CONCLUSIONS: The ability to track changes in potential population exposures to environmental carcinogens over time, as well as to compare between different substances and exposure pathways, is necessary to support comprehensive, evidence-based prevention policy. We used estimates of lifetime excess cancer risk as indicators that, although based on a number of simplifying assumptions, help to identify important data gaps and prioritize more detailed data collection and exposure assessment needs.

Creating national air pollution models for population exposure assessment in Canada.

BACKGROUND: Population exposure assessment methods that capture local-scale pollutant variability are needed for large-scale epidemiological studies and surveillance, policy, and regulatory purposes. Currently, such exposure methods are limited. METHODS: We created 2006 national pollutant models for fine particulate matter [PM with aerodynamic diameter ≤ 2.5 µm (PM2.5)], nitrogen dioxide (NO2), benzene, ethylbenzene, and 1,3-butadiene from routinely collected fixed-site monitoring data in Canada. In multiple regression models, we incorporated satellite estimates and geographic predictor variables to capture background and regional pollutant variation and used deterministic gradients to capture local-scale variation. The national NO2 and benzene models are evaluated with independent measurements from previous land use regression models that were conducted in seven Canadian cities. National models are applied to census block-face points, each of which represents the location of approximately 89 individuals, to produce estimates of population exposure. RESULTS: The national NO2 model explained 73% of the variability in fixed-site monitor concentrations, PM2.5 46%, benzene 62%, ethylbenzene 67%, and 1,3-butadiene 68%. The NO2 model predicted, on average, 43% of the within-city variability in the independent NO2 data compared with 18% when using inverse distance weighting of fixed-site monitoring data. Benzene models performed poorly in predicting within-city benzene variability. Based on our national models, we estimated Canadian ambient annual average population-weighted exposures (in micrograms per cubic meter) of 8.39 for PM2.5, 23.37 for NO2, 1.04 for benzene, 0.63 for ethylbenzene, and 0.09 for 1,3-butadiene. CONCLUSIONS: The national pollutant models created here improve exposure assessment compared with traditional monitor-based approaches by capturing both regional and local-scale pollution variation. Applying national models to routinely collected population location data can extend land use modeling techniques to population exposure assessment and to informing surveillance, policy, and regulation.

The impact of daily mobility on exposure to traffic-related air pollution and health effect estimates.

Epidemiological studies of traffic-related air pollution typically estimate exposures at residential locations only; however, if study subjects spend time away from home, exposure measurement error, and therefore bias, may be introduced into epidemiological analyses. For two study areas (Vancouver, British Columbia, and Southern California), we use paired residence- and mobility-based estimates of individual exposure to ambient nitrogen dioxide, and apply error theory to calculate bias for scenarios when mobility is not considered. In Vancouver, the mean bias was 0.84 (range: 0.79-0.89; SD: 0.01), indicating potential bias of an effect estimate toward the null by ~16% when using residence-based exposure estimates. Bias was more strongly negative (mean: 0.70, range: 0.63-0.77, SD: 0.02) when the underlying pollution estimates had higher spatial variation (land-use regression versus monitor interpolation). In Southern California, bias was seen to become more strongly negative with increasing time and distance spent away from home (e.g., 0.99 for 0-2 h spent at least 10 km away, 0.66 for ≥ 10 h spent at least 40 km away). Our results suggest that ignoring daily mobility patterns can contribute to bias toward the null hypothesis in epidemiological studies using individual-level exposure estimates.

Built environment influences on healthy transportation choices: bicycling versus driving.

A growing body of evidence links the built environment to physical activity levels, health outcomes, and transportation behaviors. However, little of this research has focused on cycling, a sustainable transportation option with great potential for growth in North America. This study examines associations between decisions to bicycle (versus drive) and the built environment, with explicit consideration of three different spatial zones that may be relevant in travel behavior: trip origins, trip destinations, and along the route between. We analyzed 3,280 utilitarian bicycle and car trips in Metro Vancouver, Canada made by 1,902 adults, including both current and potential cyclists. Objective measures were developed for built environment characteristics related to the physical environment, land use patterns, the road network, and bicycle-specific facilities. Multilevel logistic regression was used to model the likelihood that a trip was made by bicycle, adjusting for trip distance and personal demographics. Separate models were constructed for each spatial zone, and a global model examined the relative influence of the three zones. In total, 31% (1,023 out of 3,280) of trips were made by bicycle. Increased odds of bicycling were associated with less hilliness; higher intersection density; less highways and arterials; presence of bicycle signage, traffic calming, and cyclist-activated traffic lights; more neighborhood commercial, educational, and industrial land uses; greater land use mix; and higher population density. Different factors were important within each spatial zone. Overall, the characteristics of routes were more influential than origin or destination characteristics. These findings indicate that the built environment has a significant influence on healthy travel decisions, and spatial context is important. Future research should explicitly consider relevant spatial zones when investigating the relationship between physical activity and urban form.

Intercity transferability of land use regression models for estimating ambient concentrations of nitrogen dioxide.

Land use regression (LUR) is a method for predicting the spatial distribution of traffic-related air pollution. To facilitate risk and exposure assessment, and the design of future monitoring networks and sampling campaigns, we sought to determine the extent to which LUR can be used to predict spatial patterns in air pollution in the absence of dedicated measurements. We evaluate the transferability of one LUR model to two other geographically comparable areas with similar climates and pollution types. The source model, developed in 2003 to estimate ambient nitrogen dioxide (NO(2)) concentrations in Vancouver (BC, Canada) was applied to Victoria (BC, Canada) and Seattle (WA, USA). Model estimates were compared with measurements made with Ogawa passive samplers in both cities. As part of this study, 42 locations were sampled in Victoria for a 2-week period in June 2006. Data obtained for Seattle were collected for a different project at 26 locations in March 2005. We used simple linear regression to evaluate the fit of the source model under three scenarios: (1) using the same variables and coefficients as the source model; (2) using the same variables as the source model, but calculating new coefficients for local calibration; and (3) developing site-specific equations with new variables and coefficients. In Scenario 1, we found that the source model had a better fit in Victoria (R(2)=0.51) than in Seattle (R(2)=0.33). Scenario 2 produced improved R(2)-values in both cities (Victoria=0.58, Seattle=0.65), with further improvement achieved under Scenario 3 (Victoria=0.61, Seattle=0.72). Although it is possible to transfer LUR models between geographically similar cities, success may depend on the between-city consistency of the input data. Modest field sampling campaigns for location-specific model calibration can help to produce transfer models that are equally as predictive as their sources.

Modeling residential fine particulate matter infiltration for exposure assessment.

Individuals spend the majority of their time indoors; therefore, estimating infiltration of outdoor-generated fine particulate matter (PM(2.5)) can help reduce exposure misclassification in epidemiological studies. As indoor measurements in individual homes are not feasible in large epidemiological studies, we evaluated the potential of using readily available data to predict infiltration of ambient PM(2.5) into residences. Indoor and outdoor light scattering measurements were collected for 84 homes in Seattle, Washington, USA, and Victoria, British Columbia, Canada, to estimate residential infiltration efficiencies. Meteorological variables and spatial property assessment data (SPAD), containing detailed housing characteristics for individual residences, were compiled for both study areas using a geographic information system. Multiple linear regression was used to construct models of infiltration based on these data. Heating (October to February) and non-heating (March to September) season accounted for 36% of the yearly variation in detached residential infiltration. Two SPAD housing characteristic variables, low building value, and heating with forced air, predicted 37% of the variation found between detached residential infiltration during the heating season. The final model, incorporating temperature and the two SPAD housing characteristic variables, with a seasonal interaction term, explained 54% of detached residential infiltration. Residences with low building values had higher infiltration efficiencies than other residences, which could lead to greater exposure gradients between low and high socioeconomic status individuals than previously identified using only ambient PM(2.5) concentrations. This modeling approach holds promise for incorporating infiltration efficiencies into large epidemiology studies, thereby reducing exposure misclassification.

Spatial variations in estimated chronic exposure to traffic-related air pollution in working populations: a simulation.

BACKGROUND: Chronic exposure to traffic-related air pollution is associated with a variety of health impacts in adults and recent studies show that exposure varies spatially, with some residents in a community more exposed than others. A spatial exposure simulation model (SESM) which incorporates six microenvironments (home indoor, work indoor, other indoor, outdoor, in-vehicle to work and in-vehicle other) is described and used to explore spatial variability in estimates of exposure to traffic-related nitrogen dioxide (not including indoor sources) for working people. The study models spatial variability in estimated exposure aggregated at the census tracts level for 382 census tracts in the Greater Vancouver Regional District of British Columbia, Canada. Summary statistics relating to the distributions of the estimated exposures are compared visually through mapping. Observed variations are explored through analyses of model inputs. RESULTS: Two sources of spatial variability in exposure to traffic-related nitrogen dioxide were identified. Median estimates of total exposure ranged from 8 microg/m3 to 35 microg/m3 of annual average hourly NO2 for workers in different census tracts in the study area. Exposure estimates are highest where ambient pollution levels are highest. This reflects the regional gradient of pollution in the study area and the relatively high percentage of time spent at home locations. However, for workers within the same census tract, variations were observed in the partial exposure estimates associated with time spent outside the residential census tract. Simulation modeling shows that some workers may have exposures 1.3 times higher than other workers residing in the same census tract because of time spent away from the residential census tract, and that time spent in work census tracts contributes most to the differences in exposure. Exposure estimates associated with the activity of commuting by vehicle to work were negligible, based on the relatively short amount of time spent in this microenvironment compared to other locations. We recognize that this may not be the case for pollutants other than NO2. These results represent the first time spatially disaggregated variations in exposure to traffic-related air pollution within a community have been estimated and reported. CONCLUSION: The results suggest that while time spent in the home indoor microenvironment contributes most to between-census tract variation in estimates of annual average exposures to traffic-related NO2, time spent in the work indoor microenvironment contributes most to within-census tract variation, and time spent in transit by vehicle makes a negligible contribution. The SESM has potential as a policy evaluation tool, given input data that reflect changes in pollution levels or work flow patterns due to traffic demand management and land use development policy.

A spatial model of urban winter woodsmoke concentrations.

In many urban areas, residential wood burning is a significant wintertime source of PM2.5. In this study, we used a combination of fixed and mobile monitoring along with a novel spatial buffering procedure to estimate the spatial patterns of woodsmoke. Two-week average PM2.5 and levoglucosan (a marker for wood smoke) concentrations were concurrently measured at upto seven sites in the study region. In addition, pre-selected routes spanning the major population areas in and around Vancouver, B.C. were traversed during 19 cold, clear winter evenings from November, 2004 to March, 2005 by a vehicle equipped with GPS receiver and a nephelometer. Fifteen-second-average values of light scattering coefficient (bsp) were adjusted for variations between evenings and then combined into a single, highly resolved map of nighttime winter bsp levels. A relatively simple but robust (R(2) = 0.64) land use regression model was developed using selected spatial covariates to predict these temporally adjusted bsp values. The bsp values predicted by this model were also correlated with the measured average levoglucosan concentrations at our fixed site locations (R(2) = 0.66). This model, the first application of land use regression for woodsmoke, enabled the identification and prediction of previously unrecognized high woodsmoke regions within an urban airshed.

Opportunities for using spatial property assessment data in air pollution exposure assessments.

BACKGROUND: Many epidemiological studies examining the relationships between adverse health outcomes and exposure to air pollutants use ambient air pollution measurements as a proxy for personal exposure levels. When pollution levels vary at neighbourhood levels, using ambient pollution data from sparsely located fixed monitors may inadequately capture the spatial variation in ambient pollution. A major constraint to moving toward exposure assessments and epidemiological studies of air pollution at a neighbourhood level is the lack of readily available data at appropriate spatial resolutions. Spatial property assessment data are widely available in North America and may provide an opportunity for developing neighbourhood level air pollution exposure assessments. RESULTS: This paper provides a detailed description of spatial property assessment data available in the Pacific Northwest of Canada and the United States, and provides examples of potential applications of spatial property assessment data for improving air pollution exposure assessment at the neighbourhood scale, including: (1) creating variables for use in land use regression modelling of neighbourhood levels of ambient air pollution; (2) enhancing wood smoke exposure estimates by mapping fireplace locations; and (3) using data available on individual building characteristics to produce a regional air pollution infiltration model. CONCLUSION: Spatial property assessment data are an extremely detailed data source at a fine spatial resolution, and therefore a source of information that could improve the quality and spatial resolution of current air pollution exposure assessments.