Temporal and Spatial Analysis of Landfills and Transfer Stations in Saskatchewan

Abstract

Saskatchewan has the highest number of landfills per capita in Canada. Given the lower population density and the skewed spatial population distribution, comprehensive analysis of municipal solid waste management systems in Saskatchewan is inherently difficult. Most of the published waste studies however focus on city-level waste management, and there is a lack of literature with respect to the rural areas. In first part of the study, landfills and transfer stations were examined temporally and spatially using Geographic Information System. Landfills and transfer stations from 2017 and 2020 were plotted against census division land area, annual budget, and population density to study temporal changes. Saskatchewan witnessed a 54% reduction in the number of landfills and a 55% increase in number of transfer stations between 2017 and

The replacement of landfills with transfer stations were more noticeable in

divisions 8, 9, and 16. Further, regression analysis was conducted, and landfill closure operation showed no obvious correlation to division land area, annual budget, or population density. Rural division 18, representing Northern Saskatchewan, was identified as one of the challenging areas. Inclusion of division 18 in data analysis skewed the data set and need to take a different analytical approach has been recommended. The findings suggest different waste management strategies are required for urban and rural areas. The second part of the study concentrates further into the design and operation of waste management systems in rural areas with scarce populations which are often neglected in literature and are less well understood. The study proposed a simplified GIS-based technique to examine the temporal and spatial evolution of waste facilities at a regional level. The key objective was to examine the geospatial distribution of landfills and transfer stations in Saskatchewan, Canada, from 2018 to 2020 based on changes in Euclidean distance computed by both the Central feature (CF) and median center (MdC) spatial statistical tools. Both the CF and MdC results suggest that transfer stations in 2020 were located significantly closer to communities, and an improved level of landfill regionalization is observed. Smoother LF and TS radial curves are generally observed using the MdC tool. About 47.1% of the divisions are classified as challenging areas using the CF method, whereas only 41.1% of the divisions are classified as challenging areas using the MdC method. It appears that the combination of the CF and MdC tools provides a more comprehensive assessment on the temporal-spatial evolution of waste facilities. Six divisions (35.3%) are considered as appropriately managed by both CF and MdC methods. On the contrary, 23.5% of all divisions are suggested by both methods as challenging areas. Most divisions with an improving placement of waste facilities were located near the Canada-US border. The presences of major cities and total division population appear not key factors affecting the evolution of waste facility siting. The results of both the studies will help policy makers to better implement solid waste management strategies in urban and rural areas.