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.@en

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.@en

District heating (DH) has a major potential to increase the efficiency, security, and sustainability of energy management at the community scale. However, there is a huge challenge for decision makers due to the lack of knowledge about thermal energy demand during a year. Thermal energy demand is strongly dependent on the outdoor temperature, building area, and activities. In this context, this paper presents an innovative monthly thermal energy mapping method to calculate and visualize heat demand accurately for various types of buildings. The method includes three consecutive phases: (i) calculating energy loss, (ii) completing a dataset that includes energy and building information, and (iii) generating the monthly heat demand maps for the community. Determining the amount of demand and the best location for energy generators from the perspective of energy efficiency in a DH system in an urban context is one of the important applications of heat maps. Exploring heat demand characteristics and visualizing them on maps is the foundation of smart DHs.@en

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.@en