Stories
International Society of Exposure Science (ISES) 2024:
"Exposures that Impact Health in Vulnerable Populations"
Montreal, Canada
October 20-24, 2024
The Positive Zero Transport Futures team attended the International Society of Exposure Science (ISES) 2024 annual meeting, held in Montreal, Canada, from October 20-24. This year’s theme, Exposures that Impact Health in Vulnerable Populations, provided impactful discussions on the intersection of environmental exposures, public health, and social equity. Our team took part in symposiums covering topics such as community engagement in air pollution exposure research and climate-related health impacts.
Postdoctoral fellow, Dr. Jad Zalzal, co-chaired a symposium on “Advancements in Characterizing Exposure to Air Pollutants from Residential Wood Burning” with Prof. Audrey Smargiassi from the Université de Montréal. The symposium featured a range of presentations on topics such as the impacts of wood burning on indoor air quality, the chemical composition of wood smoke, spatial patterns of wood smoke pollution using mobile monitoring, and the use of drones with advanced computer vision to detect wood-burning appliances.
Dr. Zalzal also presented his research titled “Integrating Multiple Data Sources to Generate an Emission Inventory for Residential Wood Burning in Quebec, Canada.” His study introduced a data-driven approach to generating wood-burning emission inventories by combining multiple datasets with machine learning techniques. This work highlighted significant social aspects of wood burning emissions, which are essential for addressing environmental justice and energy security in regulating this pollution source.
PhD candidate Weaam Jaafar presented his work on “Comparing Neighborhood Exposure to Air Pollutants Using Citywide and Neighborhood Land Use Regression Models” as part of the precision environmental health in exposure assessment and health effects research symposium. This study highlighted the importance of spatial aggregation when developing land use regression models to improve exposure assessment accuracy. The findings revealed that machine learning models outperformed traditional methods to develop exposure surfaces. However, they still underscore some hotspots across different neighborhoods. While traditional methods failed to accurately assess exposure at a neighborhood level, they were more transferable compared to machine learning models. However, when machine learning models were tuned using spatial cross validation, they were able to achieve better transferability than traditional models. This research provides key insights into the development of exposure surfaces, emphasizing the role of mobile monitoring campaign design, model development methods, and spatial grouping in achieving accurate and generalizable results.
Miranda Doris, PhD Candidate, presented her talk “Inequity of exposure to unconventional natural gas development in northeastern British Columbia, Canada – an environmental justice analysis” as part of the symposium for “Contending with Cumulative Impacts in Rural Communities”. This study explores whether three oil and gas-related hazards: modelled concentrations of air pollution; oil and gas facility-reported emissions; and active wells are disproportionately distributed in areas with higher concentrations of Indigenous people and community socio-economic vulnerability. The study finds that areas with greater than 90% Indigenous population experience 1.2 to 1.8 times higher air pollution than areas with less than 10% Indigenous population. The study also estimates that areas DAs with high community vulnerability experience higher modelled air pollution and higher odds of exposure to facility emissions, with the most vulnerable areas experiencing 11 to 96 times higher air pollution concentrations. Overall, the study suggests the presence of environmental injustice in an area expected to continue producing a large portion of Canadian natural gas. Living near oil and gas production can lead to deteriorated air quality that negatively impacts human health, and rural populations often receive a disproportioned burden of pollution from resource extraction.
PhD candidate Emily Farrar presented her work on “Exploring the impacts of public transit service levels on GHG and air pollutant emissions” as part of the student poster competition. This research investigates the efficacy of policies that aim to reduce air pollutant (PM2.5 and NOx) and greenhouse gas (GHG) emissions from the transport sector if no investment to expand physical public transit infrastructure is made. The findings revealed that increasing the frequency of existing public transit services leads to only marginal reductions in regional emissions for the Greater Toronto and Hamilton Area (GTHA). Significant reductions in emissions require interventions that drive mode shift from personal vehicles to public transit, supplemented by expanded public transit infrastructure. The research highlights that a shift in mode use offers the greatest benefits to disadvantaged populations; the neighbourhoods with the highest reductions in exposure to NO2 had high levels of residential instability. This research provides key insight into the efficacy of transport policies in meeting regional climate goals, as well as the exposure implications of these policies.
Click here for more details on the posters and presentations!