• Energy Research

Yard waste is one of the key components of municipal solid waste and can play a vital role in implementing zero-waste strategy to achieve sustainable municipal solid waste management. Therefore, the objective of this study is to predict yard waste generation using the grey theory from the predicted municipal solid waste generation. The proposed model is implemented using municipal solid waste generation data from the City of Winnipeg, Canada. To identify the generation factors that influence municipal solid waste generation and yard waste generation, a correlation analysis is performed among eight socio-economic factors and six climatic factors. The GM (1, 1) model is utilized to predict individual factors with overall MAPE values of 0.06%-10.39% for the in-sample data, while the multivariable GM (1, N) grey model is employed to forecast the quarterly level of municipal solid waste generation with overall MAPE values of 5.64%-7.54%. In this study, grey models predict quarterly yard waste generation from the predicted municipal solid waste generation values using only twelve historical data points. The results indicate that the grey model (based on the error matrices) performs better than the linear and nonlinear regression-based models. The outcome of this study will support the City of Winnipeg's sustainable planning for yard waste management in terms of budgeting, resource allocation, and estimating energy generation.

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 this study, landfills and transfer stations are 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 2020. The replacement of landfills with transfer stations are more noticeable in divisions 8, 9, and 16. Regression analysis is conducted, and landfill closure operation show no obvious correlation to division land area, annual budget, or population density. Rural division 18, representing Northern Saskatchewan, has approximately 45% of the land area in the province and has the lowest population density. The findings suggest different waste management strategies are required for urban and rural areas. The results of this study will help policy makers to better implement solid waste management strategies in urban and rural areas.

The size of the global textile market was estimated at nearly one trillion USD in 2021 and the circularity of fashion items are of utmost practical and economic interests. Many postconsumer textile wastes are not recycled, and are sent to landfills for permanent disposal. This study examines the profitability of the selected fashion companies and compares the financial performance through weighted average net profit margin and business characteristics. The 10 companies are divided into 2 groups (conventional and sustainability) for analysis. The conventional fashion companies have a total sales revenue approximately 23 times higher than that of the sustainability fashion companies. The weighted average net profit ratio of the conventional fashion industry averaging +4.7 during the 5-year study period, much higher than the sustainability fashion group. Sustainability fashion industry is emerging and appears more sensitive to fluctuations in business expenses and COVID lockdowns. Net profit was negative for the sustainability group in 2022, and more aids such as government initiatives and incentive programs may be critical to the growth of the sustainability fashion sector. Both sustainability and conventional groups have positive relations between net profit and number of employees and net profit and market shares, respectively. The results suggest that fashion industry has opportunities to be more profitable by adopting socially responsible goals.

To prevent the transmission of the Coronavirus (SARS-CoV-2) in the public, the demand and consumption of personal protective equipment (PPE) increased drastically. Such wide use of PPE has brough a new challenge to waste management and disposal. It is difficult to sort PPE waste before further treatment, and such waste will often end up being processed by some traditional disposal methods. During the pandemic, incineration and landfill facilities are currently under significant pressure. In addition, a certain amount of PPE waste is discarded into the environment rather than going to landfills and incinerators. It not only directly affects the ecosystem, but also indirectly threatens human health through various routes of exposure. PPE waste is also the source and carrier of pathogens and chemical contaminants, causing a secondary pollution. Therefore, it is necessary to establish appropriate strategies to deal with the PPE problems related to energy, environment and health, requiring the collaborative efforts of researchers, practitioners, policymakers, and governments.

Effective waste management is critical to environmental sustainability and public health. Various dynamics, such as seasonal changes and waste education programs, influence solid waste generation, increasing the complexity of prediction. This is important, as the proper prediction of waste quantity is necessary to develop a sustainable waste management system. In this study, municipal solid waste (MSW) management is examined in Regina, the capital city of Saskatchewan, Canada. A system dynamics (SD) model is developed to evaluate garbage and recyclable waste generation behaviours in Regina across four seasons. Three years of Regina landfill waste generation records (2016–2018) are considered to analyze and predict seasonal waste-generation trends. The effect of various factors, such as gross domestic product (GDP), population, and education attainment on the amount of waste generation is considered in the SD model. The SD model is designed as a stock-flow diagram to illustrate the relationships between variables and predict the next three years of waste trends. This finding highlights the importance of waste education and awareness program and seasonal effects on the accuracy of SD waste modeling.

Solar energy is abundant, and technological advances have made solar energy systems more affordable than ever before. Using photovoltaic (PV) systems could significantly reduce our reliance on fossil fuels, and facilitate sustainable energy uses. Solar power utilities, such as self-compacting disposal bins could be used to enhance waste management processes. This is particularly important in Canada, where $3.3 billion was spent on waste management systems in 2016. In this study, solar irradiance and climatic conditions at eight locations on a University campus in Regina, Saskatchewan, are studied. Results suggest that solar utilities with automatically adjusting PV receivers could increase energy capture between 18.7 – 27.5%. Temporally, solar irradiance was similar in June and July, but lower in August. Statistical analysis found that some locations tended to be more susceptible to shadow effects. The results highlight the importance of spatial allocations of these small smart disposal bin systems. Regression analysis found that temperature was the most significant factor when relating climate to solar irradiance. The use of smart disposal bins fits well with the University’s 2020–2025 Strategic Plan of reduction in ecological footprint.

Abstract A mathematical model for the catalytic autothermal reforming (ATR) reaction of synthetic crude glycerol to hydrogen in a fixed bed tubular reactor (FBTR) and over an in-house developed metal oxide catalyst is presented in this work. The heterogeneous model equations account for a two-phase system of solid catalyst and bulk feed gas. Also, the ATR of crude glycerol reaction scheme and intrinsic kinetic rate model over an active, selective, and stable nickel-based catalyst were integrated in the developed model. Also, the model was validated using experimental data generated in our labs for the ATR of synthetic crude glycerol. The modelling results adequately described the detailed gas product composition and distribution, temperature profiles, and conversion propagation in the axial direction of the fixed bed reactor over a wide range of reaction temperature (773−923 K) and weight-time (12.71−158.23 g cat·min·molC−1). The crude glycerol conversion predicted with the model showing a close resemblance to those obtained experimentally with an average absolute deviation (AAD) of less than 8%. The maximum crude glycerol conversion and hydrogen yield were found to be 92% and 3 mol hydrogen/mol crude glycerol, respectively. Also, the gas product concentration profile in the reactor was adequately described (90%) accuracy with a hydrogen concentration of 39 vol%.