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University of Regina Institutional Repository

The mission of the oURspace digital repository is to share and preserve the scholarly, creative, and cultural work produced at the University of Regina.

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Now showing 1 - 6 of 6

Recent Submissions

Access status: Open Access ,
Optimization of waste management regions using recursive Thiessen polygons
(Elsevier BV, 2019-10) Richter, Amy; Ng, Kelvin T.W.; Karimi, Nima; Wu, Peng; Kashani, Armin Hajighasem
Geographic Information Systems (GIS) are commonly employed to solve problems related to landfill siting and optimization of waste collection. This research aims to develop an easily implementable tool to optimize the topology of waste management regions in various Canadian jurisdictions using ArcGIS ModelBuilder. Landfill count, populated places, and road length are minimized using standard deviation to determine optimized tessellations. In Nova Scotia, reductions in standard deviation of 9.6 – 30.4% are observed between original and optimized tessellations. The results suggest that an optimized tessellation of Nova Scotia’s Federal subdivisions may perform better than that of their waste management regions. In Saskatchewan, reductions in standard deviation of 4.9 – 46.1% were observed between original and optimized tessellations. Considering all Saskatchewan Federal Subdivisions, no optimization occurred. However, partitions of Saskatchewan Federal Subdivisions yielded better results, with vertical partitions yielding a 30% decrease in standard deviation of roads, while landfills and population were reduced in the horizontal subdivision by 20.0% and 38.0%, respectively. This suggests that a different approach may be required for waste management regions in Northern Saskatchewan. Saskatchewan transportation planning committees regions had the highest standard deviation across all parameters, and optimized at the fourth iteration (landfills and populated places), and first iterations (roads), despite the fact that this tessellation was developed in direct relation to roads in the province. The proposed tool, however, showed a limited application in the City of Regina given that land use planning within City limits. This work will improve the data driven aspect of regional waste management system design.
Access status: Open Access ,
Interactions of residential waste composition and collection truck compartment design on GIS route optimization
(Elsevier BV, 2020-02) Vu, Hoang Lan; Ng, Kelvin Tsun Wai; Fallah, Bahareh; Richter, Amy; Kabir, Golam
Waste collection is an important functional element in a modern waste management system; and may account for up to half of the total expenditure on waste management in industrialized nations. Most optimization of waste collection studies include truck route distance and fuel consumption considerations without explicitly considering the inter-relationships of the model parameters. This study however delineates the complex inter-relationships of waste composition, collection frequency, collection type, and truck compartment configurations in a small waste collection zone in Austin, Texas. A total of 48 different scenarios are modelled and investigated. Truck travel distances are found sensitive to collection frequency, truck capacity, volume ratio of truck compartment, and waste density. The results showed that the increase in waste density and waste collection frequency helped to save up to 18.2% in travel distances and 41.9% in travel time. Waste composition is significant in travel distance, regardless of truck design. Increasing truck capacity by 25% helped to save 4.1% to 24.4% of truck travel distances. Optimal volume ratio of truck compartments was 50:50 (50% volume for garbage and 50% volume for recyclables); a finding that is different than what is currently reported in the literature; pointing to the site-specific nature of studies of this type. The use of dual compartment trucks helps to reduce travel distances by up to 23.0% and travel time by up to 14.3%. It appears that the minimization of operation time within the collection area is key to an efficient system.
Access status: Open Access ,
Siting and ranking municipal landfill sites in regional scale using nighttime satellite imagery
(Elsevier BV, 2020-02) Karimi, Nima; Richter, Amy; Ng, Kelvin Tsun Wai
In 2016, about 24.9 million tonnes of solid waste were disposed of in Canadian landfills, where landfill technology is a common choice. This study aims to develop a data-driven GIS-based method that considers spatial, environmental, and economic constraints using study regions derived from night time light data for a 40 km buffer around Regina, Saskatchewan, Canada. Unlike other similar studies, this site suitability study assumes no political or administrative boundaries as inputs. Road network stands as the most decisive factor that accounts for 0.239 of entire weight, followed by protective areas with a total weight of 0.220. The regions that ranked the best for siting new landfills were generally located far from predominant water resources and protected areas, but are in the vicinity of major road networks, but are also far from urbanized regions. The sensitivity analysis showed that, overall, road network and protected areas are the most essential layers in this analysis. For the environmental group, protected areas and water resources are major layers. For the economic group, road network and surface temperature are the most important. The method presented in this study can easily accommodate other data sets based on importance in any given area.
Access status: Open Access ,
Spatial analysis of designated outdoor smoking areas: accessibility and land use
(Informa UK Limited, 2020-07-07) Chen, Yitong; Ng, Kelvin Tsun Wai; Richter, Amy; Vu, Hoang Lan; Karimi, Nima; Xue, Jinkai
Smoking is the leading cause of premature death in Canada. Smoking also pollutes air and generates litters such as cigarette butts. The use of designated smoking areas (DSAs) is increasingly popular on university campuses and has the potential to influence smoking prevalence. It is however found that the related regulations and policies are largely unknown. This study systematically examines the spatial distribution of DSAs at 12 Canadian campuses using ArcGIS Pro, and predicts the required number of DSAs using regression analysis based on a number of climatic, and socio-economic factors identified by cluster analysis. The density of DSAs ranged from 0.119 to 0.739 DSA/104 m2, with an average of 0.354 DSA/104 m2. Results from the regression models suggested that climatic factors are important to the number of DSAs. The proposed spatial analytical approach is also applicable to the design and planning of other major health institutions or residential complexes.
Access status: Open Access ,
Developing a novel proximity analysis approach for assessment of waste management cost efficiency in low population density regions
(Elsevier BV, 2021-02) Richter, Amy; Ng, Kelvin Tsun Wai; Karimi, Nima; Chang, Wonjae
Waste management system efficiency can be challenging to assess in regions with low population density or where data is only available at certain spatial resolutions. A novel spatial analysis approach is developed and applied in Nova Scotia, Canada to assess costs related to waste collection. Standard Deviational Ellipses are used to narrow areas of interest based on 14 administrative regions. Using these defined areas of interest, land (remote sensing) and infrastructure (vector) datasets are gathered. Pearson correlation is used to explore the relationships between the features and collection cost indicators. Two original indices are developed and analyzed: dwelling ratio (area of dwellings/total building area) and diversion-collection expenditure ratio. Results suggest that normalized difference vegetation index was positively related to collection cost while normalized difference built-up index was positively related to diversion indicators. Waste management facility distribution and road network significantly impact collection costs, and they are important in effective and efficient waste management system. Industrial indicators were also analyzed, and the number of utility towers was found to be related to collection costs. These findings suggest that geospatially dependent policies could be used to develop sustainable and economically efficient waste management systems in Nova Scotia and other low population density areas.