Identification of Neighbourhood Hotspots via the Cumulative Hazard Index: Results from a Community-Partnered Low-cost Sensor Network Deployment
Sakshi Jain, Rivkah Gardner-Frolick, Nika Martinussen, Dan Jackson, Amanda Giang, NAOMI ZIMMERMAN,
University of British Columbia Abstract Number: 254
Working Group: Identifying and Addressing Disparate Health and Social Impacts of Exposure to Aerosols and Other Contaminants across Continents, Communities, and Microenvironments
AbstractHistorically marginalized communities often experience environmental injustice due to disproportionately high air pollution concentrations relative to other communities. The Strathcona neighborhood in Vancouver is particularly vulnerable to environmental injustice due to its close proximity to the Port of Vancouver, major roads and railways, and a high proportion of Indigenous and low-income households. Furthermore, local sources of air pollutants (individual roadways, individual industrial facilities) can contribute to small-scale variations within communities.
The aim of this study was to assess hyperlocal air quality patterns (intra-neighborhood variability) and compare them to average Vancouver concentrations (inter-neighborhood variability) to recognize the disparities in risks and burdens faced by the Strathcona community. Between May and August 2022, 11 low-cost sensors (LCS) were deployed in household backyards within the neighborhood to collect PM
2.5, NO
2, and O
3 concentrations. The collected 15-minute concentrations were down-averaged to daily concentrations and compared to greater Vancouver region concentrations to quantify the inequities faced by the community. Concentrations were also estimated at every 25m grid within the neighborhood using ordinary kriging. Using population information from Census data, cumulative hazard indices (CHIs) were computed for every dissemination block.
We found that although PM
2.5 concentrations in the neighbourhood were lower than Vancouver averages, daily NO2 concentrations and summer ozone concentrations consistently exceeded the Vancouver averages; comparing sensor data with average city concentrations can assist the community in their advocacy efforts. Although CHIs varied daily, we found that CHIs were consistently higher in areas with high commercial activity. As such, estimating CHI for dissemination blocks was useful in identifying hotspots and areas of concern within the neighborhood. The kriging model was more easily implemented than traditional land use regression models, and may be useful community-deployable tools for spatial air pollutant modelling.