C. Peter Keller

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. 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. 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. 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.

Geographically Weighted Regression (GWR) is used to analyze the spatial variability of the relationship between the surface and the subsurface (b horizon) soil metal concentration. We used publiclyavailable soil samples from provincial government websites in Canada. The correlation between the log of concentration levels of the two layers are 0.51 for As, 0.40 for Cd, 0.33 for Cr, 0.52 for Co, 0.38 for Ni, and 0.23 for Pb. Although the correlation results show that the two layers seem to be related, the GWR analysis suggests that other factors might play important role in predicting the surface soil concentration of these metals. For example, only arsenic (R 2 =0.34) shows no spatial autocorrelation in the residuals. This study proposes that factors (natural and anthropogenic) other than the subsurface concentration itself are controlling the concentration surface levels for all the studied metals in this dataset.

Land Use Regression (LUR) models are increasingly used in environmental and exposure assessments to predict the concentration of contaminants in outdoor air. We explore the use of LUR as an alternative to more complex models to predict the concentration of metals in surface soil. Here, we used 55 soil samples of As and Pb collected in 1996 across British Columbia (BC), Canada by the Ministry of Environment. Predictor variables were derived for each sample site using Geographic Information System (GIS). For As (R 2 = 0.44), the resulting linear regression model includes the total length of roads (m) within 25 km, and bedrock geology. For the Pb model (R 2 =0.78), the predictor variables are the total surface area of industrial land use (m 2) within 5 km , the emissions of Pb (t) within 10 and 25 km, and the presence of closed mines within 50 km. The study proposes that LUR can reasonably predict the concentrations of As and Pb in surface soil over large areas.

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.

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. 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. 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.