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There are acknowledged difficulties in epidemiological studies to accurately assign exposure to air pollution for large populations, and large, long-term cohort studies have typically relied upon data from central monitoring stations. This approach has generally been adequate when populations span large areas or diverse cities. However, when the effects of intra-urban differences in exposure are being studied, the use of these existing central sites are likely to be inadequate for representing spatial variability that exists within an urban area. As part of the Border Air Quality Strategy (BAQS), an international agreement between the governments of Canada and the United States, a number of air health effects studies are being undertaken by Health Canada and the US EPA. Health Canada''s research largely focuses on the chronic exposure of elementary school children to air pollution. The exposure characterization for this population to a variety of air pollutants has been assessed using land-use regression (LUR) models. This approach has been applied in several cities to nitrogen dioxide (NO2), as an assumed traffic exposure marker. However, the models have largely been developed from limited periods of saturation monitoring data and often only represent one or two seasons. Two key questions from these previous efforts, which are examined in this paper, are: If NO2 is a traffic marker, what other pollutants, potentially traffic related, might it actually represent? How well is the within city spatial variability of NO2, and other traffic-related pollutants, characterized by a single saturation monitoring campaign. Input data for the models developed in this paper were obtained across a network of 54 monitoring sites situated across Windsor, Ontario. The pollutants studied were NO2, sulfur dioxide (SO2) and volatile organic compounds, which were measured in all four seasons by deploying passive samplers for 2-week periods. Correlations among these pollutants were calculated to assess what other pollutants NO2 might represent, and correlations across seasons for a given pollutant were determined to assess how much the within-city spatial pattern varies with time. LUR models were then developed for NO2, SO2, benzene, and toluene. A multiple regression model including proximity to the Ambassador Bridge (the main Canada—US border crossing point), and proximity to highways and major roads, predicted NO2 concentrations with an R 2=0.77. The SO2 model predictors included distance to the Ambassador Bridge, dwelling density within 1500m, and Detroit-based SO2 emitters within 3000m resulting in a model with an R 2=0.69. Benzene and toluene LUR models included traffic predictors as well as point source emitters resulting in R 2=0.73 and 0.46, respectively. Between season pollutant correlations were all significant although actual concentrations for each site varied by season. This suggests that if one season were to be selected to represent the annual concentrations for a specific site this may lead to a potential under or overestimation in exposure, which could be significant for health research. All pollutants had strong inter-pollutant correlations suggesting that NO2 could represent SO2, benzene, and toluene. [Copyright &y& Elsevier]

Canada's abundant and high-quality water resources support a growing human population, as well as thriving industrial and agricultural economies. However, recent intense drought conditions have raised concerns for current water resource availability. Patterns of long-term ground and surface water (GSW) changes, and their response to environmental conditions, land-use dynamics, and socioeconomic changes are not well-understood across this large and diverse country. To address this crucial gap, we identified regions of ground and surface water (GSW) changes in all the Provinces of Canada between 2002 and 2016 from the Gravity Recovery and Climate Experiment (GRACE) and Global Land Data Assimilation System (GLDAS) datasets. We explored the relationships between GSW changes and environmental, socioeconomic, and land-use dynamics over time. We found that all the Provinces of Canada gained a net 4.46 mm Liquid Water Equivalent (LWE) per year, equivalent to a total increase of 66.9 mm LWE. GSW increases were significantly associated with the normalized difference vegetation index and evapotranspiration rates. In contrast, GSW declines were significantly related to deforestation rate, urban expansion, and economic development (median household income). Despite apparent widespread post-drought recovery detected from 2002 to 2016, the rapid GSW declines were also observed in almost all of Western Canada and part of Ontario, amounting to a net loss of 66.13 mm. This indicates that a pronounced drought had emerged. It is anticipated that Canada will be experiencing more frequent and severe droughts under ongoing climate change and increasing demand for water resources. • This paper presents patterns of long-term ground and surface water (GSW) changes. • GSW increases are significantly associated with improvements in environmental conditions. • The rapid GSW declines are observed in parts of Canada since 2013 indicating the presence of a pronounced drought. • Drought in Canada may become more frequent and severe in the future. • Policy makers should adopt sustainable water management strategies to response future challenges. [ABSTRACT FROM AUTHOR]

Both climate and land use changes can influence water quality and quantity in different ways. Thus, for predicting future water quality and quantity trends, simulations should ideally account for both projected climate and land use changes. In this paper, land use projections and climate change scenarios were integrated with a hydrological model to estimate the relative impact of climate and land use projections on a suite of water quality and quantity endpoints for a Canadian watershed. Climatic time series representing SRES change scenario A2 were generated by downscaling the outputs of the Canadian Regional Climate Model (version 4.1.1) using a combination of quantile–quantile transformation and nearest neighbor search. The SWAT (Soil and Water Assessment Tool) model was used to simulate streamflow, nitrogen and phosphorus loading under different climate and land use scenarios. Results showed that a) climate change will drive up maximum monthly streamflow, nitrate loads, and organic phosphorus loads, while decreasing organic nitrogen and nitrite loads; and b) land use changes were found to drive the same water quality/quantity variables in the same direction as climate change, except for organic nitrogen loads, for which the effects of the two stressors had a reverse impact on loading. [ABSTRACT FROM AUTHOR]

Abstract: Decision making in land management can be greatly enhanced if the perspectives of concerned stakeholders are taken into consideration. This often implies negotiation in order to reach an agreement based on the examination of multiple alternatives. This paper describes a spatial web/agent-based modeling system that was developed to support the negotiation process of stakeholders regarding land development in southern Alberta, Canada. This system integrates a fuzzy analytic hierarchy procedure within an agent-based model in an interactive visualization environment provided through a web interface to facilitate the learning and negotiation of the stakeholders. In the pre-negotiation phase, the stakeholders compare their evaluation criteria using linguistic expressions. Due to the uncertainty and fuzzy nature of such comparisons, a fuzzy Analytic Hierarchy Process is then used to prioritize the criteria. The negotiation starts by a development plan being submitted by a user (stakeholder) through the web interface. An agent called the proposer, which represents the proposer of the plan, receives this plan and starts negotiating with all other agents. The negotiation is conducted in a step-wise manner where the agents change their attitudes by assigning a new set of weights to their criteria. If an agreement is not achieved, a new location for development is proposed by the proposer agent. This process is repeated until a location is found that satisfies all agents to a certain predefined degree. To evaluate the performance of the model, the negotiation was simulated with four agents, one of which being the proposer agent, using two hypothetical development plans. The first plan was selected randomly; the other one was chosen in an area that is of high importance to one of the agents. While the agents managed to achieve an agreement about the location of the land development after three rounds of negotiation in the first scenario, seven rounds were required in the second scenario. The proposed web/agent-based model facilitates the interaction and learning among stakeholders when facing multiple alternatives. [Copyright &y& Elsevier]