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.

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.