Indoor Environmental Quality Performance Research Articles

The Stability Performance of Indoor Environmental Quality (IEQ) Parameters: Emphasize the Strategies of Sustainable Comforts in the Learning Environment in a Tropical Climate

Implementing sustainable construction practices in higher educational facilities in Malaysia would enhance the quality of learning activities. Students in higher education predominantly utilize learning areas. The objective of this study is to evaluate indices of indoor environmental quality (IEQ) that prioritise sustainability in educational environments. The major indicators comprised four significant key terms: Indoor Air Quality (IAQ), Thermal Comfort (TC), Visual Comfort (VC), and Acoustic Comfort (AC). The study utilized data from previous studies published between 2021 and 2023 to determine the present issue that emerged inside Malaysian higher educational facilities. This was achieved by a critical assessment of the parameters' findings via fieldwork measurement. This leads to a spectrum that falls within a satisfactory threshold to attain the desired degree of user comfort. The findings demonstrate that students' comfort level is enhanced by their preference for a stable level of IEQ parameters. According to this study, on average standards of IEQ parameters for a sustainable learning environment; temperature (27°C), humidity (40%), air flow (0.30 m/s), illuminate (400lux) and acoustic (40dB). The strategic framework has been recommended to enhance learning environments and act as a reference guideline for future evaluations of indoor environmental quality.

The Stability Performance of Indoor Environmental Quality (IEQ) Parameters: Emphasize the Strategies of Sustainable Comforts in the Learning Environment in a Tropical Climate

Implementing sustainable construction practices in higher educational facilities in Malaysia would enhance the quality of learning activities. Students in higher education predominantly utilize learning areas. The objective of this study is to evaluate indices of indoor environmental quality (IEQ) that prioritise sustainability in educational environments. The major indicators comprised four significant key terms: Indoor Air Quality (IAQ), Thermal Comfort (TC), Visual Comfort (VC), and Acoustic Comfort (AC). The study utilized data from previous studies published between 2021 and 2023 to determine the present issue that emerged inside Malaysian higher educational facilities. This was achieved by a critical assessment of the parameters' findings via fieldwork measurement. This leads to a spectrum that falls within a satisfactory threshold to attain the desired degree of user comfort. The findings demonstrate that students' comfort level is enhanced by their preference for a stable level of IEQ parameters. According to this study, on average standards of IEQ parameters for a sustainable learning environment; temperature (27°C), humidity (40%), air flow (0.30 m/s), illuminate (400lux) and acoustic (40dB). The strategic framework has been recommended to enhance learning environments and act as a reference guideline for future evaluations of indoor environmental quality.

Indoor Environmental Quality Effect Analysis in Green and Non-green Office Building to Staff’s Performance and Satisfaction in Surabaya

The energy efficiency in an office building can decrease the company’s operational cost. Even so, the operational cost for staff is still larger than the cost for energy. It is important to reassure that the impact given by the building’s indoor environmental quality (IEQ) is positive to staff. This research focusses on two office building in Surabaya, one of them is designed using the green principles and calculations, and the other is not. The building’s IEQ aspects being inspected includes indoor air quality, thermal, lighting, acoustics and layout. A questionnaire survey was held to obtain the reaction from the full time staff regarding the building’s IEQ performance, their satisfaction to it and their self-assessed performance. There are IEQ aspects that affects staff’s performance and satisfaction significantly. The IEQ mean score differs significantly in green and non-green building, but the mean difference in satisfaction and performance were found not significant.

Indoor Environmental Quality & Occupant Satisfaction in Green Building (Case Study: Company X at East Jakarta, DKI Jakarta)

The global movement in green building development has been going on since the early 1960s. Although initially driven by environmental agendas such as carbon and energy, there is a growing acknowledgment that green buildings can affect Indoor Environmental Quality (IEQ). Many researchers also state that improved indoor environmental quality is associated with better occupant satisfaction. However, some localized green buildings, especially in developing countries, often don’t recognize IEQs and occupant satisfaction as important issues, so they remain unstudied. Therefore, this study aimed to evaluate the performance of IEQ and occupant satisfaction. The analytical methods used were descriptive statistics and regression analysis. The outcome demonstrated that green building standards do not automatically improve indoor environment quality, particularly when the lighting parameter is below the limit values. The analysis findings showed that most respondents expressed their satisfaction with IEQ and significantly influenced occupant satisfaction. In addition, this research contributes to the development of green building evaluation practices that prioritize environmental health and occupant satisfaction

The Performance of Reinforcement Learning for Indoor Climate Control Devices according to the Level of Outdoor Air Particulate Matters

As people spend more than 90% of their time indoors, indoor environmental quality (IEQ) has become an important factor in maintaining a healthy space for the occupants. There are many indoor climate control devices for improving IEQ. However, it is difficult to maintain an appropriate IEQ with changing outdoor air conditions and occupant behavior in a building. This study proposes a reinforcement learning (RL) algorithm to maintain indoor air quality (IAQ) with low energy consumption in a residential environment by optimally operating indoor climate control devices such as ventilation systems, air purifiers, and kitchen hoods. The proposed artificial intelligence algorithm (AI2C2) employs DDQN (double deep Q-network) to determine the optimal operation of various indoor climate control devices, reflecting IAQ and energy consumption via different outdoor levels of particulate matter. This approach considers the outdoor air condition and occupant activities in training the developed algorithm, which are the most significant factors affecting IEQ and building energy performance. A co-simulation platform using Python and EnergyPlus is applied to train and evaluate the model. As a result, the proposed approach reduced energy consumption and maintained good IAQ. The developed RL algorithm for energy and IAQ showed different performances based on the outdoor PM 2.5 level. The results showed the RL-based control can be more effective when the outdoor PM 2.5 level is higher (or unhealthy) compared to moderate (or healthy) conditions.

Adaptive thermal comfort in the offices of three climates of North-East India

Buildings not only provide shelter to the occupants but also security, safety and comfort, as well as signifying economic and socio-cultural status. The high energy intensity of buildings has become a matter of concern worldwide in the context of climate change and global warming. Adaptive comfort principles and guidelines afford greater design opportunities for reduced energy intensity without compromising occupant thermal comfort and indoor environmental quality performance. However, thermal adaptation opportunities of office occupants in the North-Eastern part of India are rarely addressed by previous thermal comfort studies conducted in the Indian subcontinent. A yearlong questionnaire-based adaptive thermal comfort study with concurrent indoor environmental measurements was conducted in naturally ventilated office buildings located in three locations, i.e., Tezpur, Imphal and Shillong, representing the climatic zones of North-East India. A total of 2326 valid questionnaire responses were collected. ASHRAE Class-II field study protocols, seven-point thermal sensation and five-point preference scales were used to collect objective and subjective comfort assessments. It was found that the clothing insulation (clo) levels worn by occupants varied non-linearly with indoor temperatures. The estimated preferred temperatures for building occupants in Tezpur, Imphal and Shillong were 24 °C, 23.5 °C and 22 °C, respectively. Probit analysis of thermal sensation data indicated that the indoor temperature stimulus associated with a shift of one thermal sensation unit differed between the warm and cool side of the 7-point thermal sensation scale. Increasing indoor air velocity up to 0.8m/s shifted the upper threshold of discomfort to 32 °C. It was also found that 80% of office occupants were comfortable within the temperature range of 25 °C–30 °C. The adaptive comfort model derived from the current database shows lower sensitivity of subjects to outdoor temperature changes compared to existing International standards like ASHRAE Standard 55 or EN16798. The present study demonstrates the potential for low-energy, naturally ventilated office design strategies in similar climatic conditions in North-East India and other parts of the world. Above all, it enriches the worldwide thermal comfort database.

Examining the indirect effects of indoor environmental quality on task performance: The mediating roles of physiological response and emotion

Most studies have been conducted on the impact of indoor environmental quality (IEQ) on occupants' task performance. However, most studies are based on the assumption that IEQ directly affects task performance. Different hypotheses have been proposed that contradict this conventional belief. The objective of this study is to examine the indirect effects of IEQ on task performance. To identify unknown mediating variables between IEQ and task performance, two research hypotheses were set up: (i) Emotion is the result of a physiological response change in the body and would be influenced by the IEQ in the built environment; and (ii) Task performance would be influenced by IEQ-evoked emotion of occupants. The partial least squares structural equation modeling (PLS-SEM) was employed to verify two interrelated research hypotheses and conduct mediating effect analysis using SmartPLS 3.3.1. The results of this study demonstrated the following: (i) IEQ has no direct effect on task performance but has an indirect effect mediated by dominance resulting from skin conductance; (ii) hot and humid thermal environment and unpleasant indoor air quality increase human skin conductance, which in turn leads to passive emotions. The passive emotions that are not under direct human control result in the degradation of task performance. Using the findings of this study, future smart offices need to collect human bio-signals and emotions and manage IEQ based on these data unlike past smart offices that considered only environmental factors.

The indoor environmental quality and energy savings potential of room ventilation units compared to exhaust-only ventilation systems in France

Humidity-controlled mechanical exhaust ventilation (RH-MEV) has been widely used in France for over 35 years, demonstrating high durability and robustness. This exhaust-only ventilation strategy is widely used as an energy-saving measure, replacing constant mechanical exhaust ventilation (Constant-MEV) systems in residential buildings. It demonstrates energy savings due to the restricted airflows, but as a downside, the building’s indoor air quality (IAQ) often deteriorates. Moreover, it is impossible to recover heat with exhaust-only ventilation systems, which means that energy consumption for space heating is still quite significant and cold supply air temperatures are frequently introduced to the heated spaces. Room ventilation units (RVUs) with heat recovery represent an alternative ventilation solution allowing simple installation through the façade and providing fresh outdoor air and exhaust ventilation to each room. This study investigates these units’ energy saving potential and indoor environmental quality performance as an alternative solution to centralized exhaust-only ventilation systems. The dynamic simulations were performed for a reference residential building under various French climatic conditions for a heating season. The three ventilation strategies investigated were Constant-MEV, RH-MEV and room-based ventilation with RVUs. The results demonstrated 61–85% savings in space heating demand with the RVUs, compared to Constant-MEV under all climatic conditions. Compared to RH-MEV, the RVUs saved 44–75% energy for space heating while the CO2 concentration and relative humidity levels were decreased due to RVUs’ constant air exchange rate. In all cases, RVUs provided considerably higher supply air temperatures due to the implemented heat recovery, which can potentially improve indoor thermal comfort.

Ten Questions Concerning Indoor Environmental Quality (IEQ) Models: The Development and Applications

In the past two decades, with advances in data collection and in analytical techniques and tools, there has been a significant increase in research on indoor environmental quality (IEQ) assessment. To better understand the relationships between the overall IEQ performance and individual IEQ aspects, namely, indoor air quality, thermal comfort, acoustic quality, and visual quality, IEQ models have been developed by many previous studies. In this paper, the IEQ models proposed in the literature in the period from 2001 to 2022 are examined and summarized into ten questions, including but not limited to indicator selection, data collection, analysis methods, interpretation, and implication. The proposed answers aim to provide insight into current studies on IEQ models and identify gaps for future research. It has been found that the existing IEQ models differed for different building types or occupants. To compare the IEQ performance of various buildings in other countries, standardized data collection protocols are necessary, including the selection of IEQ aspects/indicators and their corresponding objective measurement strategies and standardized subjective survey methods. In addition, the data analysis approaches used to develop the IEQ models must be unified. Moreover, criteria for overall IEQ performance and the individual IEQ aspects should be provided. This study is the first comprehensive investigation of all the steps involved in IEQ model development. The answers to these ten questions can be seen as practical instructions for establishing an improved, standardized, and repeatable IEQ assessment model.

Appraisal of indoor environment quality (IEQ) in nearly Zero energy Building (nZEB): A literature review

Nearly zero energy buildings (nZEB) are considered a key measure to reduce energy consumption in buildings. However, there is growing evidence that nZEB design strategies may impact indoor environmental quality (IEQ). Most of the current research on nZEB has focused on the energy efficiency and cost-effectiveness of nZEB, with less research on the IEQ of nZEB. This literature reviewed 25 case studies on IEQ assessment to determine the actual IEQ performance in nZEB and the impact of design strategies on IEQ. The results showed that all four parameters of IEQ performance assessment have yet to be included in the scope of IEQ assessment. In addition to physical parameter measurements and criteria, subjective measurements should be the primary determinant of IEQ. Moreover, the analysis shows that overheating, poor air quality, thermal discomfort, and Sick Building Syndrome (SBS) are common IEQ risk factors reported. At the same time, the building envelope, HVAC system, and control system are the main factors contributing to the increase in IEQ risk factors. This review will provide practical reference values and recommendations for building professionals in future studies.

Assessing measurement model of green cleaning components for green buildings

PurposeThis paper aims to assess a measurement model of green cleaning for green buildings in Malaysia. Being one of the contributors to the indoor environmental quality performance, green cleaning has become one of the significant aspects that need to be considered for the well-being and performance of a building, particularly in a green building's operations and maintenance performance. Green buildings without green cleaning practices would hinder the benefits that should be rendered economically, socially and environmentally. However, the absence of clear green cleaning components and requirements in Malaysia has become a motivation to undertake this research.Design/methodology/approachA questionnaire survey involving cleaning service providers and green building index (GBI) facilitators was carried out, and the data was then analyzed using partial least squares structural equation modeling. However, this paper will only be focusing on the measurement model assessment.FindingsMost of the green cleaning components and requirements are acceptable in the model except integrated pest management (in the cleaning procedure component) and hand soaps (in the product and materials component) due to lower factor loadings. Therefore, these two requirements were removed from the measurement model.Research limitations/implicationsDue to a paucity of professionals in the field of green cleaning, the researchers have selected GBI facilitators and cleaning service providers as respondents for this research. The researchers assumed that GBI facilitators are aware of acceptable products and materials for green buildings; meanwhile, cleaning service providers know what is the best cleaning technique and process that helps in achieving cost and resource efficiency. This research also assumed that the green cleaning components identified can be applied to any type of green building, regardless of the differences in needs in each type of building.Practical implicationsThis discovery will give the industry, particularly cleaning service providers and green building management teams, a first look at the green cleaning components and requirements.Originality/valueThis paper fulfills the need to study how green cleaning helps in achieving the benefits rendered by green buildings.

Dynamic modelling of indoor environmental conditions for future energy retrofit scenarios across the UK school building stock

UK schoolchildren spend on average 30% of their waking lives inside schools. While indoor environmental quality (IEQ) is critical for their health and attainment, school buildings are also a key part of the UK's carbon emissions reduction strategy. To address conflicts between energy efficiency and IEQ, predictive models of UK classroom stock should incorporate energy and IEQ performance criteria across dynamic scenarios comprising energy retrofit and IEQ improvement measures. On this basis, we have developed a novel approach for auto-generation, simulation, post-processing and analysis of EnergyPlus UK classroom archetype models. Such modelling facilitates the multi-parameter evaluation of school building performance, whilst incorporating stock-wide heterogeneity and longitudinal dynamic changes.As extent of retrofit increases, decreasing incremental energy demand reduction was quantified and increasing effectiveness of passive ventilation at mitigating overheating was identified. Negative impact of South facing orientation on overheating was reduced after applying a range of IEQ improvement methods. However, low ceiling heights in 1945–1967 era classrooms impact the efficacy of these IEQ mitigations on calculated attainment, requiring design rather than mitigation strategies as a remedial solution. Strategies preventing NO2 pollution ingress could be more-effective than PM2.5, with night-time ventilation avoiding ingress during daily peaks and greater sensitivity to location. Future work shall incorporate multiple criteria into a single tool based on stakeholder preferences to improve quality of retrofit decision making.

A systematic approach to quantify the influence of indoor environmental parameters on students' perceptions, responses, and short-term academic performance.

Several studies found that classrooms' indoor environmental quality (IEQ) can positively influence in-class activities. Understanding and quantifying the combined effect of four indoor environmental parameters, namely indoor air quality and thermal, acoustic, and lighting conditions on people is essential to create an optimal IEQ. Accordingly, a systematic approach was developed to study the effect of multiple IEQ parameters simultaneously. Methods for measuring the IEQ and students' perceived IEQ, internal responses, and academic performance were derived from literature. Next, this systematic approach was tested in a pilot study during a regular academic course. The perceptions, internal responses, and short-term academic performance of participating students (n= 163) were measured. During the pilot study, the IEQ of the classrooms varied slightly. Significant associations (p< 0.05) were observed between these natural variations and students' perceptions of the thermal environment and indoor air quality. These perceptions were significantly associated with their physiological and cognitive responses (p< 0.05). Furthermore, students' perceived cognitive responses were associated with their short-term academic performance (p< 0.01). The observed associations confirm the construct validity of the systematic approach. However, its validity for investigating the influence of lighting remains to be determined.

Factors Influencing the Performance of Indoor Environmental Quality of Pharmaceutical Factory Buildings in Southwest Nigeria

Pharmaceutical factory workers spend 37.5% of their daily time in the production hall manufacturing drugs used for human health needs. There is usually little or no time given to spend in the natural environment. This affects their sanity and well-being. The Pharmaceutical factory building (PFB) is classified as a specialized, controlled, or restrictive building; it provides little or no access to natural environmental conditions like ventilation and lighting, thereby increasing the financial implication of energy for the operation of production of drugs. Hence, the survey was conducted to identify the factors that influence the indoor environmental performance (IEP) of PFBs. The factors responsible for influencing the indoor air quality were measured through a survey conducted in Lagos and Ogun States, Nigeria on 14 PFBs to determine the value of these factors identified, using principal component analysis (PCA), Bartlett Test, and Kaiser-Mayer Olkin (KMO): the conditions for PCA were also observed. PCA is a factors or data reduction technique to select a subset of highly predictive factors from the larger group of factors identified from the study. Indoor environmental quality variables satisfied the condition for PCA while thermal performance variables did not meet the condition. PCA was conducted for Indoor environmental quality and the result showed 2 major factors explaining the variation in the original set of variables. Whereby CO2, P.M1.0, P.M2.5, P.M10, HCHO, airflow, AQICN, and AQIUS as component 1 and TVOC as component 2, the data set was also compared with the standards recommended for indoor environmental quality and thermal performance variables. It was found that at an average air velocity of 29°C and RH of 60%, the average CO, TVOC, PM2.5, and PM10 were 0.25ppm, 0.31ppm, 33.92ppm, and 43.48ppm respectively for the PFBs. Because thermal performance includes several dependent variables, greater research on the indoor environment of PFBs in Nigeria is recommended to determine the impact of indoor environmental characteristics on thermal parameters.

Overlaps in space utilisation patterns and IEQ conditions observed in Activity-Based Working supportive office

One of the potential positive aspects of spaces designed to support Activity-Based Working (ABW) concept is to allow people to choose to work from zones that suit their Indoor Environmental Quality (IEQ) preferences. The vast majority of studies reporting findings relevant to IEQ performance of ABW spaces rely on spot measurements and/or subjective surveys and as such it is difficult to map longitudinal actual utilisation patterns and IEQ performance. This study contributes to this topic by analyzing a longitudinal dataset of space utilisation of an ABW over a twelve-month period. Analysis aims to identify overlaps between space utilisation patterns and expected IEQ performance in order to understand which types of zones occupants seem to prefer to work from. Occupants’ demographics (age and gender) were also analyzed with respect to the use of space. Further, specific physical markers were investigated, namely proximity to window, air-conditioning outlets, and high-low noise locations. The impact of physical markers on workplace choice was classified and predicted during a day using a decision-tree diagram developed on the basis of the CHAID algorithm. Overall, workers tended to choose to work within the inner zones (after 11 a.m.) during winter. Findings show that female workers moved away from air-conditioning outlets. Additionally, female workers worked from workstations situated in high and medium noise zones. Results illustrated the potential to use utilisation datasets to understand how workers move away or towards zones in response to expected IEQ performance - thermal comfort (cold/warm), acoustics (noisy/quiet), and access to the outdoor environment/view (window) proximity.

Commercial building indoor environmental quality models: A critical review

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.

Assessing the perception of overall indoor environmental quality: Model validation and interpretation

The indoor environmental quality (IEQ) was determined by assessment of its various domains, among which the four principal ones are thermal, acoustic, visual and indoor air quality (IAQ). While many IEQ models have been established to develop scheme for assessing the overall IEQ, the lack of model validation significantly limited their applicability. This study aimed to provide new insights into how occupants evaluate the overall IEQ performance by establishing regression models and machine learning models that predict occupants’ overall satisfaction using their satisfactions with the four principal domains of IEQ. Accuracy and applicability of proposed models were examined on two different datasets. Prediction error increased 21% when models were generalized to new dataset collected from different buildings and populations, and error of machine learning models increased more significantly than regression models. The model performance varied across building types. Models trained on samples collected from office settings had better generalization to the similar environment, while increased error was identified for schools and residences. The acoustic environment had a greater impact on females than males, while the IAQ had a greater impact on males. The Shapley Additive Explanations was applied to interpret model predictions and measure contribution of the variables. The results revealed that the unsatisfying IEQ factor often yielded a dominant negative impact on the overall IEQ satisfaction, which can hardly be compensated by a higher satisfaction with another factor. Efficient strategy can be developed to improve overall satisfaction with IEQ based on findings of the present study.

Strengthening Taiwan’s Green Building Certification System from Aspects of Productivity and Energy Costs to Provide a Healthier Workplace

This study estimates the relationship between poor indoor environmental quality (IEQ) and the increasing labor costs in green buildings in Taiwan. Specifically, poor performance of IEQ including HVAC, lighting, and indoor air quality, influences the health and well-being of occupants and leads to worse productivity, ultimately causing increased personnel cost. In Taiwan’s green building certification (GBC) system, the energy-savings category is mandatory while the IEQ category is only optional. It means that certified building cases may not reach the expected level in IEQ. Thus, this study reviews the thermal environment, indoor air quality (IAQ), and illumination performances of IEQ-certified and non-IEQ-certified buildings in 20 green buildings. Building energy and IEQ simulations were conducted to analyze the relationships between indoor comfort, energy cost, and personnel cost in green buildings. The results show that IEQ-certified green buildings averagely perform better than non-IEQ-certified ones in the aspects of IEQ and building costs. Besides, 3 of 13 non-IEQ-certified green buildings undertake extremely high additional expenditure for the poor IEQ. The results correspond to some previous findings that green-certified buildings do not necessarily guarantee good building performance. This study further inspects the pros and cons of Taiwan’s GBC system and proposes recommendations against its insufficient IEQ evaluation category. As the trade-off of energy-saving benefits with health and well-being in green buildings has always been a concern, this study aims to stimulate more quantitative research and promote a more comprehensive green building certification system in Taiwan.

An IoT measurement solution for continuous indoor environmental quality monitoring for buildings renovation

The measurement of Indoor Environmental Quality (IEQ) requires the acquisition of multiple quantities regarding thermal comfort and indoor air quality. The IEQ monitoring is essential to investigate the building’s performance, especially when renovation is needed to improve energy efficiency and occupants’ well-being. Thus, IEQ data should be acquired for long periods inside occupied buildings, but traditional measurement solutions could not be adequate. This paper presents the development and application of a non-intrusive and scalable IoT sensing solution for continuous IEQ measurement in occupied buildings during the renovation process. The solution is composed of an IR scanner for mean radiant temperature measurement and a desk node with environmental sensors (air temperature, relative humidity, CO2, PMs). The integration with a BIM-based renovation approach was developed to automatically retrieve building’s data required for sensor configuration and KPIs calculation. The system was installed in a nursery located in Poland to support the renovation process. IEQ performance measured before the intervention revealed issues related to radiant temperature and air quality. Using measured data, interventions were realized to improve the envelope insulation and the occupant’s behaviour. Results from post-renovation measurements showed the IEQ improvement achieved, demonstrating the impact of the sensing solution.

Modelling platform for schools (MPS): The development of an automated One-By-One framework for the generation of dynamic thermal simulation models of schools

The UK Government has recently committed to achieve net zero carbon status by year 2050. Schools are responsible for around 2% of the UK’s total energy consumption, and around 15% of the UK public sector’s carbon emissions. A detailed analysis of the English school building stock’s performance can help policymakers improve its energy efficiency and indoor environmental quality.Building stock modelling is a technique commonly used to quantify current and future energy demand or indoor environmental quality performance of large numbers of buildings at the neighbourhood, city, regional or national level. ‘Building-by-building’ stock modelling is a modelling technique whereby individual buildings within the stock are modelled and simulated, and performance results are aggregated and analysed at stock level.This paper presents the development of the Modelling Platform for Schools (MPS) – an automated generation of one-by-one thermal models of schools in England through the analysis and integration of a range of data (geometry, size, number of buildings within a school premises etc.) from multiple databases and tools (Edubase/Get Information About Schools, Property Data Survey Programme, Ordanance Survey and others). The study then presents an initial assessment and evaluation of the modelling procedure of the proposed platform.The model evaluation has shown that out of 15,245 schools for which sufficient data were available, nearly 50% can be modelled in an automated manner having a high level of confidence of similarity with the actual buildings. Visual comparison between automatically-generated models and actual buildings has shown that around 70% of the models were, indeed, geometrically accurate.