Investigating spatiotemporal variability of water, energy, and carbon flows: A probabilistic fuzzy synthetic evaluation framework for higher education institutions

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 a...

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Bibliographic Details
Main Authors: Alghamdi, A. (Author), Chhipi-Shrestha, G. (Author), Haider, H. (Author), Hewage, K. (Author), Hu, G. (Author), Sadiq, R. (Author)
Format: Article
Language:English
Published: MDPI AG 2021
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Online Access:View Fulltext in Publisher
LEADER 02734nam a2200277Ia 4500
001 10.3390-environments8080072
008 220427s2021 CNT 000 0 und d
020 |a 20763298 (ISSN) 
245 1 0 |a Investigating spatiotemporal variability of water, energy, and carbon flows: A probabilistic fuzzy synthetic evaluation framework for higher education institutions 
260 0 |b MDPI AG  |c 2021 
856 |z View Fulltext in Publisher  |u https://doi.org/10.3390/environments8080072 
520 3 |a 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. © 2021 by the authors. Licensee MDPI, Basel, Switzerland. 
650 0 4 |a Analytical hierarchical process 
650 0 4 |a Benchmarking 
650 0 4 |a Fuzzy synthetic evaluation 
650 0 4 |a GHG emissions 
650 0 4 |a Higher educational institutions 
650 0 4 |a Probabilistic techniques 
650 0 4 |a Uncertainty 
700 1 |a Alghamdi, A.  |e author 
700 1 |a Chhipi-Shrestha, G.  |e author 
700 1 |a Haider, H.  |e author 
700 1 |a Hewage, K.  |e author 
700 1 |a Hu, G.  |e author 
700 1 |a Sadiq, R.  |e author 
773 |t Environments - MDPI