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Development of a spatiotemporal composite measure of climate change-related human health effects in urban environments: a Metro Vancouver study
Meeting Abstracts
Development of a spatiotemporal composite measure of climate change-related human health effects in urban environments: a Metro Vancouver study Amin Owrangi, Robert Lannigan, Slobodan Simonovic
Abstract Published Online April 28, 2017 Department of Pathology, Schulich School of Medicine and Dentistry (Prof R Lannigan) and Department of Civil and Environmental Engineering, University of Western Ontario, London, ON, Canada (A Owrangi, Prof S Simonovic) Correspondence to: Dr Amin Owrangi, Department of Civil and Environmental Engineering, University of Western Ontario, London, ON N6A 5B9, Canada [email protected]
Background Rapid population growth along with an increase in the frequency and intensity of climate change-related effects in coastal urban environments emphasise the need for the development of new instruments to help disaster planners and policy makers to select and prioritise mitigation and adaptation measures. The concept of the resilience of a community, which is a measure of how rapidly the community can recover to its previous level of functionality following a disruptive event is still a relatively new concept for many engineers, planners, and policy makers, but is becoming recognised as an increasingly important, and, some would argue, essential component for the development and subsequent assessment of adaptation plans being considered for communities at risk of climate change-related events. The holistic approach, which is the cornerstone of resilience, is designed to integrate physical, economic, health, social, and organisational effects of climate change in urban environments. Methods This research presents a method for the development of a quantitative spatial and temporal composite measure to assess climate change-related health effects in urban environments. This approach uses inputs such as total population density and densities of various demographics, burden of diseases conditions, flood inundation mapping, and land use change for both historical and current conditions. The research has shown that the methodology presented generates sufficiently accurate information to be useful for planning adaptive strategies. To assemble all inputs into a single measure of health impacts, a weighting system was assigned to apply various priorities to the spatiotemporal data sources. Weights could be varied to assess how they impact the final results. Finally, using spatiotemporal extrapolation methods the future behaviour of the same key spatial variables can be projected. Although this method was developed for application to any coastal mega-city, this thesis demonstrates the results obtained for Metro Vancouver, British Columbia, Canada. Findings The data was collected for the years 1981, 1986, 1991, 1996, 2001, 2006, and 2011, because information was readily available for these years. Fine resolution spatial data for these years was used to give a dynamic simulation of possible health impacts for future projections. Linear and auto-regressive spatiotemporal extrapolations were used for projecting a 2050’s Metro Vancouver health impact map (HIM). Interpretation The approach would be useful in the development of more targeted adaptation and risk reduction strategies at a local level. In addition, this methodology can be used to generate inputs for further resilience simulations. The overall value of this approach is that it allows for a more integrated assessment of the city vulnerability and could lead to more effective adaptive strategies. Funding International Development Research Center (IDRC), Canadian Institutes of Health Research (CIHR), Natural Sciences and Engineering Research Council of Canada (NSERC), and Social Sciences and Humanities Research Council of Canada (SSHRC). Contributors AO, RL, and SS designed the study. AO extracted and collected the data. AO did the statistical analysis. AO wrote the Abstract. All authors (AO, RL, and SS) reviewed the final Abstract. Declaration of interests We declare no competing interests. Acknowledgments We would like to acknowledge the financial support made available by the International Development Research Center (IDRC) together with the Canadian Institutes of Health Research (CIHR), the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Social Sciences and Humanities Research Council of Canada (SSHRC).
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Development of a spatiotemporal composite measure of climate change-related human health effects in urban environments: a Metro Vancouver study Amin Owrangi, Robert Lannigan, Slobodan Simonovic
Abstract Published Online April 28, 2017 Department of Pathology, Schulich School of Medicine and Dentistry (Prof R Lannigan) and Department of Civil and Environmental Engineering, University of Western Ontario, London, ON, Canada (A Owrangi, Prof S Simonovic) Correspondence to: Dr Amin Owrangi, Department of Civil and Environmental Engineering, University of Western Ontario, London, ON N6A 5B9, Canada [email protected]
Background Rapid population growth along with an increase in the frequency and intensity of climate change-related effects in coastal urban environments emphasise the need for the development of new instruments to help disaster planners and policy makers to select and prioritise mitigation and adaptation measures. The concept of the resilience of a community, which is a measure of how rapidly the community can recover to its previous level of functionality following a disruptive event is still a relatively new concept for many engineers, planners, and policy makers, but is becoming recognised as an increasingly important, and, some would argue, essential component for the development and subsequent assessment of adaptation plans being considered for communities at risk of climate change-related events. The holistic approach, which is the cornerstone of resilience, is designed to integrate physical, economic, health, social, and organisational effects of climate change in urban environments. Methods This research presents a method for the development of a quantitative spatial and temporal composite measure to assess climate change-related health effects in urban environments. This approach uses inputs such as total population density and densities of various demographics, burden of diseases conditions, flood inundation mapping, and land use change for both historical and current conditions. The research has shown that the methodology presented generates sufficiently accurate information to be useful for planning adaptive strategies. To assemble all inputs into a single measure of health impacts, a weighting system was assigned to apply various priorities to the spatiotemporal data sources. Weights could be varied to assess how they impact the final results. Finally, using spatiotemporal extrapolation methods the future behaviour of the same key spatial variables can be projected. Although this method was developed for application to any coastal mega-city, this thesis demonstrates the results obtained for Metro Vancouver, British Columbia, Canada. Findings The data was collected for the years 1981, 1986, 1991, 1996, 2001, 2006, and 2011, because information was readily available for these years. Fine resolution spatial data for these years was used to give a dynamic simulation of possible health impacts for future projections. Linear and auto-regressive spatiotemporal extrapolations were used for projecting a 2050’s Metro Vancouver health impact map (HIM). Interpretation The approach would be useful in the development of more targeted adaptation and risk reduction strategies at a local level. In addition, this methodology can be used to generate inputs for further resilience simulations. The overall value of this approach is that it allows for a more integrated assessment of the city vulnerability and could lead to more effective adaptive strategies. Funding International Development Research Center (IDRC), Canadian Institutes of Health Research (CIHR), Natural Sciences and Engineering Research Council of Canada (NSERC), and Social Sciences and Humanities Research Council of Canada (SSHRC). Contributors AO, RL, and SS designed the study. AO extracted and collected the data. AO did the statistical analysis. AO wrote the Abstract. All authors (AO, RL, and SS) reviewed the final Abstract. Declaration of interests We declare no competing interests. Acknowledgments We would like to acknowledge the financial support made available by the International Development Research Center (IDRC) together with the Canadian Institutes of Health Research (CIHR), the Natural Sciences and Engineering Research Council of Canada (NSERC) and the Social Sciences and Humanities Research Council of Canada (SSHRC).
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