Browsing by Author "Richter, Amy Johanna"

Now showing 1 - 2 of 2
  • Thumbnail Image
    ItemOpen Access
    Improving Data Driven Canadian Waste Management Policy Using GIS, Remote Sensing, and Other Advanced Techniques
    (Faculty of Graduate Studies and Research, University of Regina, 2021-05) Richter, Amy Johanna; Ng, Kelvin Tsun Wai Ng; Piwowar, Joseph; Sharma, Satish; Veawab, Amornvadee; Jin, Yee-Chung; Rowe, Kerry
    Data-driven techniques are vital to improve the efficiency of waste management systems in Canada and around the world. Canadians generated 935.6 kg/cap of waste in 2016 and spent $3.3 billion to manage this waste. This research aims to solve problems related to waste region optimization and landfill siting. Specifically, this research develops topologies for regional waste management systems and analyzes specific features of preexisting regionalized and non-regionalized systems to increase system efficiencies. Methods including Geographic Information Systems (GIS), remote sensing (RS), spatial statistics, and data science are incorporated to inform data driven policies in waste management. First, a novel recursive algorithm is proposed to optimize the shape of waste management regions using ArcGIS. The outcome was a set of regions where the spread of populated places, roads, and landfills were more equally spread throughout each region. The recursive algorithm was then altered, applying the Central Feature spatial statistics instead of the geometric centroid as the ‘seed’ input in the algorithm. In some cases, this alteration was able to further improve the ability of the algorithm to equally spread infrastructure within regions. Along with provinces, this method was also tested on cities, and the results were positive for larger metropolitan cities, however, limited improvements were observed in smaller urban centers. After proposing a new recursion algorithm and an alteration, the shape characteristics of the regions were examined. Two new metrics were proposed, accounting for the percent spread of landfills, populated places, and roads, as well as the area of each proposed region in a tessellation. The isoperimetric quotient and its measures of central tendency are used to further evaluate proposed tessellations. The number of sub-regions in a tessellation and the area of the resulting polygons are important factors in spatial optimization of waste management regions. Finally, other spatial statistics are investigated in smaller regions of Saskatchewan. Centroidal Voronoi Tessellation is generally the most efficient method. However, when the ratio of populated places to road length was low, the median center spatial statistic was better able to optimize populated places. A trade off exists between the number of sub-regions, computational efficiency, and optimized percent standard deviation. Size of sub-regions remains important. Three novel analysis methods are also presented. First, a method for determining optimal landfill expansion locations is proposed. The method was able to determine the best areas for landfill expansion. Independent of expert opinion, the method relies solely on vector and remote sensing data; but is flexible enough to apply weighting methods if so desired. Remote sensing and vector data can capture distinctly different aspects of the study area, and vector data can be used as a proxy when cloud cover is present. Next, Standard Deviational Ellipses were used to assess costs related to waste collection in Nova Scotia. The distribution of waste facilities and road network significantly impact collection costs and a framework for geospatially dependent policies in Nova Scotia is presented. Finally, landfill design criteria are assessed and compared using data science techniques. Word distributions and other characteristics are related to climatic and other features in each province. Tables and figures are important in Canadian landfill design standards and guidelines
  • Thumbnail Image
    ItemOpen Access
    Investigating the Nova Scotia Waste Management Model: Business and Financial Aspects
    (Faculty of Graduate Studies and Research, University of Regina, 2017-09) Richter, Amy Johanna; Ng, Kelvin; Sharma, Satish; Peng, Wei; Al-Anbagi, Irfan; Lozecznik, Stan
    Canadians disposed 965 kg of solid waste per capita (kg/cap) in 2010, while in Nova Scotia, a Canadian province, the average disposal was only 390 kg/cap. Using aggregate data from national surveys, the first part of this study used regression analysis to analyze disposal and diversion trends, and their relationships with expenditure, GDP, business size, and diversion rates in Nova Scotia, Québec, Ontario, and nationally. Waste diversion increased by 35% in Nova Scotia, compared to a 1.5% increase nationally over the study period (1996-2010). In Nova Scotia, Ontario, and Canada there were somewhat strong relationships between GDP and residential diversion (0.5 ≤ R2 ≤ 0.8); however, Nova Scotia had a strong and positive relationship (R2 = 0.886, p = 0.0016) between nonresidential diversion and GDP. An analysis of capital and operating expenditure found that, using a simple linear model, Nova Scotia would only have to spend $455/tonne of waste managed to achieve a diversion rate of 60%, while Ontario would have to spend $2,200/tonne of waste managed to achieve the same result. Nova Scotia has more waste management businesses per capita, and the average number of employees increased more than in other provinces, implying that diversion requires more employees than disposal, a finding consistent with the literature. In the second part of this study, multiple regression analysis was conducted to examine diversion trends with respect to percentage of expenditure on various parameters related to the management of solid waste in Canada. Budget allocation varies significantly in Nova Scotia, with only 33% of the budget being spent on Collection and Transportation, compared to the national average expenditure of 46%. In Nova Scotia, tipping fees were strongly positively related (m = 2.044, p = 0.001) to diversion rate. Interestingly, tipping fees were found to be related to diversion rates in Nova Scotia and Canada, but not in Ontario or Québec. A lagged relationship between increases in budget allocation for operation of organics processing facilities and diversion rates was found in Québec, with a lag period of about 6 years. When considering Nova Scotia’s regional curbside collection diversion rates and operations costs for disposal, recycling, organics processing, and transfer facilities, only garbage and recycling operations costs were found to be related to diversion rates. It appears that regions with only transfer facilities have poor diversion rates compared to regions with landfill disposal facilities.