The quality of the indoor environment has become a vital component for buildings due to the time spent indoors. To this extent, the performance of the indoor environment is considered as part of the greenery criteria by green rating schemes such as the Green Building Index in Malaysia. This study aims to investigate and assess the quality of the indoor environment of Platinum-certified office buildings in a tropical climate. This research applied a case study approach over two Platinum-certified office buildings. Post-occupancy evaluation is employed integrating full-scale measurement with an occupants’ survey. The measurement was carried out from May to August, and 112 questionnaires were retrieved to evaluate occupants’ satisfaction with aspects of the indoor environment. Thermal comfort, indoor air quality, acoustic, lighting, furniture, and cleanliness are considered as the main study variables. The findings of full-scale measurement indicated high relative humidity, and low air velocity and illuminance. While occupants reported overall indoor environment quality (IEQ) comfort, a significant correlation of variables was observed. The main sources of dissatisfaction were identified as overcooling around 24 °C, high relative humidity (RH), around 70% RH, glare, and background noise around 51.9 dB. Statistically, a significant difference between occupants’ responses to IEQ of two cases was identified, although both buildings are labelled with a Platinum certificate.

Global warming has become an increasing challenge due to the impact of human activities on the environment. In this regard, university campuses with various activities and departments have a great impact on the environment. Ecological Footprint Analysis (EFA) is a natural resource depletion assessment tool, with a high level of accuracy, that measures the impact of human activities on the environment. Considering the Ecological Footprint (EF) capabilities, this study developed a method to assess the environmental impacts of a university campus using component-based parameters. The goals of the study are to explore the effective components of EF and to propose some policy guidelines to diminish the human impacts on the environment on university campuses. Five components, including natural gas and electricity consumption, water and food usage, and waste production, were measured in a survey from 2013 to 2016 at the building scale. The mean EF of the campus was 16,484 global hectares (gha). Fossil fuel energy had the highest level of environmental impact with 70.73%, followed by waste production and food and water usage with 26.87%, 1.28%, and 1.12%, respectively. The results demonstrate that the EF Index (EFI) of the case study campus was −0.82, which reveals an unsustainable performance. The EF results were illustrated on an Ecological Footprint Map (EFM), which shows the east and west parts of the camps were more unsustainable.

Natural ventilation has been used widely in buildings to deliver a healthy and comfortable indoor environment for occupants. It also reduces the consumption of energy in the built environment and dilutes the concentration of carbon dioxide. Various methods and techniques have been used to evaluate and predict indoor airspeed and patterns in buildings. However, few studies have been implemented to investigate the relevant methods and tools for the evaluation of ventilation performance in indoor and outdoor spaces. The current study aims to review available methods, identifying reliable ones to apply in future research. This study investigates scientific databases and compares the advantages and drawbacks of methods including analytical models, empirical models, zonal models, and CFD models. The findings indicated the computational fluid dynamics (CFD) model is the most relevant method because of cost-effectiveness, informative technique, and proficiency to predict air velocity patterns and ratios in buildings. Finally, widely used CFD codes and tools are compared considering previous studies. It is concluded the application of codes for research is subject to the complexity and characteristics of a studied model, the area and field of study, the desired turbulence model, and the user interface.

Energy consumption to cool an indoor environment is a substantial part of total energy end-use, particularly in a tropical climate with high energy demand for cooling. To improve energy efficiency, cooling systems can be optimized using a variety of neutral indoor temperatures to maintain a balance between an occupant’s thermal comfort and cooling energy demand. This explanatory study investigated the thermal quality and cooling energy demand of a Platinum-certified office building in the tropical climate of Malaysia. The investigation aimed to suggest a balance between occupant thermal comfort and cooling energy demand. The thermal investigation includes an objective field measurement that implements environmental equipment to monitor thermal quality and a subjective occupant’s thermal feedback using a questionnaire survey. To calculate cooling energy demand, the total equivalent temperature difference method (TETD) is applied. The results suggested an occupant’s cooling sensation of around 24 °C, with no significant difference concerning age and gender. Cooling load calculation indicated a 36% energy reduction by increasing air temperature to 26 °C, for occupants to feel thermally comfortable in a tropical climate. These findings contribute to improving sustainable energy policies, sustainable construction, and thermal comfort improvement for a tropical climate.

In 2008, the Chartered Institution of Building Services Engineers (CIBSE TM46 UC) presented an annual-fixed thermal energy benchmark of 240 kWh/m²/yr for university campus (UC) buildings as an attempt to reduce energy consumption in public buildings. However, the CIBSE TM46 UC benchmark fails to consider the difference between energy demand in warm and cold months, as the thermal performance of buildings largely depends on the ambient temperature. This paper presents a new generation of monthly thermal energy benchmarks (MTEBs) using two computational methods including mixed-use model and converter model, which consider the variations of thermal demand throughout a year. MTEBs were generated using five basic variables, including mixed activities in the typical college buildings, university campus revised benchmark (UCrb), typical operation of heating systems, activities impact, and heating degree days. The results showed that MTEBs vary from 24 kWh/m²/yr in January to one and nearly zero kWh/m²/yr in June and July, respectively. Based on the detailed assessments, a typical college building was defined in terms of the percentage of its component activities. Compared with the 100% estimation error of the TM46 UC benchmark, the maximum 21% error of the developed methodologies is a significant achievement. The R-squared value of 99% confirms the reliability of the new generation of benchmarks.