Abstract

Knowing water and energy consumption patterns sets the baseline for understanding their drivers and assessing the performance of potential measures to increase efficiency and/or reliability. These patterns can vary substantially depending on the building characteristics, on the building users and use, on the cultural, social, economic, environmental context in which the building is located, among many other factors. This article presents a general methodological framework for characterizing water and energy consumption patterns in buildings based on the evaluation of the characteristics of the equipments and appliances, as well as the type of users and the activities developed in each type of room. This allows estimating water and energy use, by end use per square meter and by roomtype. The methodological framework proposed was applied to the buildings of the Paricarana Campus of Federal University of Roraima (UFRR), Brazil, providing one of the few examples in the literature reporting water and energy consumption in university buildings in tropical climates. Universities, in most cases, represent large water and energy consumers with distinctive consumption drivers and patterns which have received limited attention when compared to other types of buildings (e.g., residential). The findings have shown that teaching rooms and administration rooms are the main consumers, representing 48% and 49% of the institution's energy and water consumption, respectively. Air conditioning is the biggest energy consumption (63%), while personal use represents 72% of the total water consumption in a building. The toilets represent a large water consumption in a university building (46.40%). Comparing different building uses, the central library is the highest consumer, due to the longest operating time and the highest occupational density. The methodological proposal intends to be a useful tool to support managers and decision-makers to understand the dynamics of consumption and then propose effective practices to reduce water and energy uses, as well as providing reference data for comparison with other educational institutions.

Highlights

  • Assessing the performance of existing buildings is crucial to meet the needs and expectations of both users and managers (Sink et al, 1984)

  • This paper presents a methodology to estimate water and energy consumption patterns per end-use in buildings by modeling its drivers, namely the function and features of the building rooms and the characteristics of their main users

  • By enabling the estimate of water and energy consumption patterns, the proposed methodology is useful for managers and decision-makers of buildings because it provides the basis for assessing the performance of potential water and energy efficiency measures

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Summary

Introduction

Assessing the performance of existing buildings is crucial to meet the needs and expectations of both users and managers (Sink et al, 1984). The expansion of higher education in Brazil did not envisage the sustainability of consumption resources such as energy and water (Marinho et al, 2014) In this context, it has become a matter of global concern for university managers and decision makers to implement sustainability measures, as a result of awareness of the impacts that universities have on the environment (Alshuwaikhat and Abubakar, 2008). It has become a matter of global concern for university managers and decision makers to implement sustainability measures, as a result of awareness of the impacts that universities have on the environment (Alshuwaikhat and Abubakar, 2008) These institutions must play a leading role towards sustainable development (Viebahn, 2002), through education and research in the topic, and through practical example by implementing measures to improve the performance of their infrastructures (Bellia et al, 2018; Bertone et al, 2018; Marinho et al, 2014).

Water and energy consumption in buildings
Consumption in university building
Methodological framework
Presentation
Data collection
Consumption estimation
Campus characterization
Indirect consumption
Calibration
End-use consumption
Findings
Discussion
Conclusion
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