Local Sustainability Assessment for Human Well-being Using Global Ecological Footprint Data

Abstract

This proof-of-concept study examined an approach to downscaling the ecological footprint (EF) at the local level. In this study, an EF disaggregation methodology was applied, using national EF data and adjusting them to the local level (Dissemination Area (DA)) using ratios informed by recent data. The study then employed a citizen science methodology to enhance and calibrate the EF data at the DA level. Data from 429 participants (403 complete) on consumption habits were analyzed using the Greater Golden Horseshoe Area (GGHA) average EF as a baseline. Linear regression, correlation analysis, t-tests and Cohen’s d tests validated findings across two Canadian demographic groups. The methodology focused on the Region of Peel in the Greater Toronto Area (GTA) to compare the EF of consumption and related health and well-being outcomes between two demographic groups: recent immigrants and established Canadians. The study aimed to address a gap by utilizing a citizen science method to gather local insights. The relationship between those two methods and two community groups was explored. The disaggregation method differed significantly from the citizen science method (p < 0.05). For example, despite having a national average of 7.42 gha/cap, established Canadians in the study area exhibit an EF of 11.5 gha/cap, while recent immigrants have an EF of 10.75 gha/cap, exhibiting a statistically significant difference (p ≤ 0.05) using the disaggregation method, with a ratio adjusted to reflect more recent data. The citizen-science-based approach revealed that established Canadians in the study area exhibit an EF of consumption of 8.73 gha/cap, compared to 8.07 gha/cap for recent immigrants, exhibiting a statistically significant difference (p ≤ 0.05). Thus, it was found to enhance the granularity and relevance of EF measurements, revealing important differences between population groups. As a proof-of-concept, the study demonstrates the value of local sustainability assessments, revealing differences between recent immigrants and established Canadians in the Region of Peel. Future attempts to employ this disaggregation approach to calibrate EF estimates should have sufficient citizen science data to adequately represent local phenomena.