• Energy Research

Although COVID-19 has significantly changed the higher educational sector, there are few studies revealing how this pandemic has changed the energy use of higher education buildings. This study was conducted not only to disclose the energy use change under COVID-19 but also to identify the corresponding facilities management strategies for future learning and teaching delivery modes under virtual campuses. This study collected the energy use data of 122 buildings across five campuses in Griffith University, located in Southeast Queensland, Australia, during the COVID-19 academic year (February 17, 2020, to February 21, 2021) and during a typical normal academic year (February 18, 2019, to February 16, 2020) by PI Vision Platform, and compared the data using the t-test and multiple linear regression. The results indicated that learning and administration activities became off campus during the pandemic, while research activities remained on campus. During the COVID-19 academic year, an amount of 9,646,933 kWh energy or around 24.88 kWh/m2 of energy use intensity was saved, which accounted for 16% of the total energy use per academic year. Specifically, the shutting down of air conditioning in academic buildings, administration buildings, retail buildings and teaching buildings during COVID-19 saved 4,566 kWh (1.13 kWh/m2), 966 kWh (0.8 kWh/m2), 1,472 kWh (1.4 kWh/m2) and 860 kWh (1.3 kWh/m2) of electricity use per week, respectively, which accounted for 51.5%, 44.3%, 48.3% and 57.1% of total energy use per week during this period, respectively. Based on this analysis and the changing educational environment, this study also speculated on the energy implications of future teaching and learning practices, which provided guidance to the facilities management under virtual campuses.

Although COVID-19 has significantly changed the higher educational sector, there are few studies revealing how this pandemic has changed the energy use of higher education buildings. This study was conducted not only to disclose the energy use change under COVID-19 but also to identify the corresponding facilities management strategies for future learning and teaching delivery modes under virtual campuses. This study collected the energy use data of 122 buildings across five campuses in Griffith University, located in Southeast Queensland, Australia, during the COVID-19 academic year (February 17, 2020, to February 21, 2021) and during a typical normal academic year (February 18, 2019, to February 16, 2020) by PI Vision Platform, and compared the data using the t-test and multiple linear regression. The results indicated that learning and administration activities became off campus during the pandemic, while research activities remained on campus. During the COVID-19 academic year, an amount of 9,646,933 kWh energy or around 24.88 kWh/m2 of energy use intensity was saved, which accounted for 16% of the total energy use per academic year. Specifically, the shutting down of air conditioning in academic buildings, administration buildings, retail buildings and teaching buildings during COVID-19 saved 4,566 kWh (1.13 kWh/m2), 966 kWh (0.8 kWh/m2), 1,472 kWh (1.4 kWh/m2) and 860 kWh (1.3 kWh/m2) of electricity use per week, respectively, which accounted for 51.5%, 44.3%, 48.3% and 57.1% of total energy use per week during this period, respectively. Based on this analysis and the changing educational environment, this study also speculated on the energy implications of future teaching and learning practices, which provided guidance to the facilities management under virtual campuses.

Indoor environmental quality (IEQ) models merge various influencing IEQ factors into a single overall indicator. The outcome of the IEQ model is usually a numerical rating or score that provides an evaluative summary of the IEQ performance. Many publications have developed IEQ models from their field measurement and/or satisfaction survey results, however with distinct measurement protocols, IEQ weighting schemes and analytical methods. This paper presents a comprehensive review of 25 studies focusing on developing IEQ evaluation models in commercial buildings. Two IEQ measurement approaches (objective and subjective measurement), and three types of IEQ models—subjective-objective models, objective models and subjective models—are first differentiated. Five commonly used analytical methods (linear regression, non-linear regression, analytical hierarchy process, ensemble averaging method, and updated IEQ acceptance model) are discussed. The interaction effects between IEQ factors and relative contribution of them to the overall IEQ satisfaction are also assessed. Twenty-five studies are then mapped by data collection method, analytical method and number of survey responses. Five key criteria for developing quality IEQ models—number of IEQ factors included, spatial and temporal variability in physical measurement, analytical methods for model development, and the number of responses if subjective surveys are carried out—are proposed and discussed. A simple ranking and scoring system is propounded for evaluating the quality of the IEQ models developed in the reviewed studies. Results show that two studies achieved a total score equal to or higher than 80% of the total score, and 16 studies achieved a minimum of 60% of the total score. This tool can help researchers quickly assess the accuracy and reliability of IEQ models developed from diverse methods and make an informed decision. ; Full Text

Indoor environmental quality (IEQ) models merge various influencing IEQ factors into a single overall indicator. The outcome of the IEQ model is usually a numerical rating or score that provides an evaluative summary of the IEQ performance. Many publications have developed IEQ models from their field measurement and/or satisfaction survey results, however with distinct measurement protocols, IEQ weighting schemes and analytical methods. This paper presents a comprehensive review of 25 studies focusing on developing IEQ evaluation models in commercial buildings. Two IEQ measurement approaches (objective and subjective measurement), and three types of IEQ models—subjective-objective models, objective models and subjective models—are first differentiated. Five commonly used analytical methods (linear regression, non-linear regression, analytical hierarchy process, ensemble averaging method, and updated IEQ acceptance model) are discussed. The interaction effects between IEQ factors and relative contribution of them to the overall IEQ satisfaction are also assessed. Twenty-five studies are then mapped by data collection method, analytical method and number of survey responses. Five key criteria for developing quality IEQ models—number of IEQ factors included, spatial and temporal variability in physical measurement, analytical methods for model development, and the number of responses if subjective surveys are carried out—are proposed and discussed. A simple ranking and scoring system is propounded for evaluating the quality of the IEQ models developed in the reviewed studies. Results show that two studies achieved a total score equal to or higher than 80% of the total score, and 16 studies achieved a minimum of 60% of the total score. This tool can help researchers quickly assess the accuracy and reliability of IEQ models developed from diverse methods and make an informed decision. ; Full Text

Living wall systems have been widely recognized as one of the promising approaches for building applications due to their aesthetic value and ecological benefits. Compared with outdoor living wall systems, indoor living wall systems (ILWS) play a more vital role in indoor air quality. The aim of this study is to investigate the effects of ILWS on indoor air quality. In an office building, two parallel corridors were selected as comparative groups. A 10.6 m2 ILWS was installed on the sidewall of the west corridor while the east corridor was empty. Some important parameters, including indoor air temperature, relative humidity, concentrations of carbon dioxide (CO2), and particulate matter (PM) were obtained based on the actual environment monitoring. According to the statistical analysis of the data, there were significant differences in the concentrations of CO2 and PMs in the corridors with and without ILWS, which indicated that CO2 and PM2.5 removal rate ranged from 12% to 17% and 8% to 14%, respectively. The temperature difference is quite small (0.13 °C on average), while relative humidity slightly increased by 3.1–6.4% with the presence of the ILWS.

Living wall systems have been widely recognized as one of the promising approaches for building applications due to their aesthetic value and ecological benefits. Compared with outdoor living wall systems, indoor living wall systems (ILWS) play a more vital role in indoor air quality. The aim of this study is to investigate the effects of ILWS on indoor air quality. In an office building, two parallel corridors were selected as comparative groups. A 10.6 m2 ILWS was installed on the sidewall of the west corridor while the east corridor was empty. Some important parameters, including indoor air temperature, relative humidity, concentrations of carbon dioxide (CO2), and particulate matter (PM) were obtained based on the actual environment monitoring. According to the statistical analysis of the data, there were significant differences in the concentrations of CO2 and PMs in the corridors with and without ILWS, which indicated that CO2 and PM2.5 removal rate ranged from 12% to 17% and 8% to 14%, respectively. The temperature difference is quite small (0.13 °C on average), while relative humidity slightly increased by 3.1–6.4% with the presence of the ILWS.

Sustainable retrofit can increase a building's performance and extend its lifetime. Common sustainable retrofit guides usually ignore the building's indoor environmental quality (IEQ) and occupant satisfaction while only focus on the energy efficiency. During the retrofit, prioritizing improvements to IEQ parameters that are critical for increasing occupant satisfaction but do not considerably increase energy consumption is crucial given the budgetary constraints. This project aims to identify different building experts' perspectives on the impact of IEQ factors and underlying parameters that contribute to occupant satisfaction and energy efficiency in office buildings, and develop an index that ranks the IEQ parameters' overall cost-effectiveness in a sustainable retrofit. The study surveys the views of 30 carefully selected building experts (ten architects, ten building engineers, and ten building assessors) in Australia using multiple criteria decision-making method. Results show that the building engineers and assessors regard thermal comfort as the most critical factor influencing occupant satisfaction, 54.2% and 57.6%, respectively. Alternatively, the architects regard visual comfort as the most important (38.8%). All expert groups have a similar opinion on the relative importance of IEQ factors in office energy consumption. An IEQ Effectiveness index is developed to evaluate the cost-effectiveness of improving a specific IEQ parameter in achieving high occupant satisfaction while not demanding extra energy input. Visual and acoustic IEQ parameters turn out to be ideal IEQ parameters that can be prioritized in a retrofit. Results from this study can provide guidance for the decision-making process of the office building sustainable retrofit. ; Full Text