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.

中文翻译：

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调查水、能源和碳流的时空变化：高等教育机构的概率模糊综合评估框架

高等教育机构 (HEI) 消耗大量能源和水，并导致温室气体 (GHG) 排放。高等教育机构在内部和外部都面临着提高其在其范围内减少温室气体排放的整体绩效的压力。有必要确定校园内高温室气体排放的关键区域，以帮助找到提高校园整体可持续性绩效的解决方案。开发了一个集成的概率模糊框架，以帮助大学解决与校园内水、能源和碳 (WEC) 流量报告相关的不确定性。由于记录的 WEC 使用变化的随机性，使用蒙特卡罗模拟的概率评估有效地解决了偶然的不确定性，而模糊综合评估解决了认知不确定性，这是由于与 WEC 基准相关的语言变量的模糊性。开发的框架应用于不列颠哥伦比亚大学（奥肯那根校区）的运营、学术和住宅建筑。分析了三种情景，将部分偏好分配给水、能源或碳。此外，生成了九个时间季节来评估由于占用和气候变化而导致的可变性。最后，完成对评估建筑物的聚合。研究表明，气候和建筑类型显着影响大学的整体表现。