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Higher education institutions (HEIs) consume significant energy and water and contribute to greenhouse gas (GHG) emissions. HEIs are under pressure internally and externally to improve their overall performance on reducing GHG emissions within their boundaries. It is necessary to identify critical areas of high GHG emissions within a campus to help find solutions to improve the overall sustainability performance of the campus. An integrated probabilistic-fuzzy framework is developed to help universities address the uncertainty associated with the reporting of water, energy, and carbon (WEC) flows within a campus. The probabilistic assessment using Monte Carlo Simulations effectively addressed the aleatory uncertainties, due to the randomness in the variations of the recorded WEC usages, while the fuzzy synthetic evaluation addressed the epistemic uncertainties, due to vagueness in the linguistic variables associated with WEC benchmarks. The developed framework is applied to operational, academic, and residential buildings at the University of British Columbia (Okanagan Campus). Three scenarios are analyzed, allocating the partial preference to water, or energy, or carbon. Furthermore, nine temporal seasons are generated to assess the variability, due to occupancy and climate changes. Finally, the aggregation is completed for the assessed buildings. The study reveals that climatic and type of buildings significantly affect the overall performance of a university. This study will help the sustainability centers and divisions in HEIs assess the spatiotemporal variability of WEC flows and effectively address the uncertainties to cover a wide range of human judgment.
Abdulaziz Alghamdi; Guangji Hu; Gyan Chhipi-Shrestha; Husnain Haider; Kasun Hewage; Rehan Sadiq. Investigating Spatiotemporal Variability of Water, Energy, and Carbon Flows: A Probabilistic Fuzzy Synthetic Evaluation Framework for Higher Education Institutions. Environments 2021, 8, 72 .
AMA StyleAbdulaziz Alghamdi, Guangji Hu, Gyan Chhipi-Shrestha, Husnain Haider, Kasun Hewage, Rehan Sadiq. Investigating Spatiotemporal Variability of Water, Energy, and Carbon Flows: A Probabilistic Fuzzy Synthetic Evaluation Framework for Higher Education Institutions. Environments. 2021; 8 (8):72.
Chicago/Turabian StyleAbdulaziz Alghamdi; Guangji Hu; Gyan Chhipi-Shrestha; Husnain Haider; Kasun Hewage; Rehan Sadiq. 2021. "Investigating Spatiotemporal Variability of Water, Energy, and Carbon Flows: A Probabilistic Fuzzy Synthetic Evaluation Framework for Higher Education Institutions." Environments 8, no. 8: 72.
In Canada, higher educational institutions (HEIs) are responsible for a significant portion of energy consumption and anthropogenic greenhouse gas (GHG) emissions. Improving the environmental performance of HEIs is an important step to achieve nationwide impact reduction. Academic buildings are among the largest infrastructure units in HEIs. Therefore, it is crucial to improve the environmental performance of academic buildings during their operations. Identifying critical academic buildings posing high impacts calls for methodologies that can holistically assess the environmental performance of buildings with respect to water and energy consumption, and GHG emission. This study proposes a fuzzy clustering approach to classify academic buildings in an HEI and benchmark their environmental performance in terms of water, energy, and carbon flows. To account for the fuzzy uncertainties in partitioning, the fuzzy c-means algorithm is employed to classify the buildings based on water, energy, and carbon flow indicators. The application of the developed methodology is demonstrated by a case study of 71 academic buildings in the University of British Columbia, Canada. The assessed buildings are grouped into three clusters representing different levels of performances with different degrees of membership. The environmental performance of each cluster is then benchmarked. Based on the results, the environmental performances of academic buildings are holistically determined, and the building clusters associated with low environmental performances are identified for potential improvements. The subsequent benchmark will allow HEIs to compare the impacts of academic building operations and set realistic targets for impact reduction.
Abdulaziz Alghamdi; Guangji Hu; Husnain Haider; Kasun Hewage; Rehan Sadiq. Benchmarking of Water, Energy, and Carbon Flows in Academic Buildings: A Fuzzy Clustering Approach. Sustainability 2020, 12, 4422 .
AMA StyleAbdulaziz Alghamdi, Guangji Hu, Husnain Haider, Kasun Hewage, Rehan Sadiq. Benchmarking of Water, Energy, and Carbon Flows in Academic Buildings: A Fuzzy Clustering Approach. Sustainability. 2020; 12 (11):4422.
Chicago/Turabian StyleAbdulaziz Alghamdi; Guangji Hu; Husnain Haider; Kasun Hewage; Rehan Sadiq. 2020. "Benchmarking of Water, Energy, and Carbon Flows in Academic Buildings: A Fuzzy Clustering Approach." Sustainability 12, no. 11: 4422.
The education sector is one of the major contributors to the total greenhouse gas (GHG) emissions in Canada, i.e., 16% of total emissions among 11 sectors. Canadian higher education institutions (HEIs) consume around 60% of the total energy fed to the educational sector. Existing tools holistically cover a wide array of functions to assess the sustainability of HEIs. The infrastructure (engineered) systems are the pivotal units responsible for the majority of energy and water consumption and may have been built, retrofitted, or replaced at different times using different materials and technologies. Consequently, infrastructures have varying efficiency, designs, building envelopes, and environmental impacts. For technical-level decision making for improving the engineered systems, HEIs need to be benchmarked on the basis of their water, energy, and carbon flows. A methodology is developed for sustainability assessment of 34 Canadian HEIs that are classified into small, medium, and large sizes based on their number of full-time equivalent students (FTE). Energy, water consumption, number of students, and floor area is measured in different units and are, thus, normalized. The study revealed that the energy source was the primary factor affecting the sustainability performance of an institution. The analysis also revealed that small-sized institutions outperformed medium-to-large-sized institutions.
Abdulaziz Alghamdi; Husnain Haider; Kasun Hewage; Rehan Sadiq. Inter-University Sustainability Benchmarking for Canadian Higher Education Institutions: Water, Energy, and Carbon Flows for Technical-Level Decision-Making. Sustainability 2019, 11, 2599 .
AMA StyleAbdulaziz Alghamdi, Husnain Haider, Kasun Hewage, Rehan Sadiq. Inter-University Sustainability Benchmarking for Canadian Higher Education Institutions: Water, Energy, and Carbon Flows for Technical-Level Decision-Making. Sustainability. 2019; 11 (9):2599.
Chicago/Turabian StyleAbdulaziz Alghamdi; Husnain Haider; Kasun Hewage; Rehan Sadiq. 2019. "Inter-University Sustainability Benchmarking for Canadian Higher Education Institutions: Water, Energy, and Carbon Flows for Technical-Level Decision-Making." Sustainability 11, no. 9: 2599.