Occupant centric indoor environmental quality assessment within institutional settings

Are Humans Good Sensors? Using Occupants as Sensors for Indoor Environmental Quality Assessment and for Developing Thresholds that Matter

Indoor environment quality is a relative measure of comfort perception by people exposed to the indoor conditions. It is expected that any assessment of energy performance should also include indoor comfort. This study is to review indoor environmental quality models (with respect to thermal and acoustic comfort, indoor air and lighting quality). A simplified indoor environmental quality model is also developed with consideration of EN 15251 draft ‘Guideline for using indoor environmental input parameters for the design and assessment of energy performance of buildings’. This article analyses what components should be modelled and in particular discusses the effect of different weighting schemes on the overall indoor environmental quality index. The analysis includes thermal comfort models, indoor air quality, acoustic comfort and daylight illumination versus lightning. The proposed indoor environmental quality component sub-models will give the most reliable results when the model indoor environment input data are correctly measured and disturbing influences of indoor environmental quality monitoring process are well defined and properly assessed. The final indoor environmental quality result is based on subjoining the uncertainty values achieved in panel analysis of percentage of persons dissatisfied with indoor environmental quality with corrected measurement uncertainty. All simulations for IEQindex sub-components and preliminary metrological analysis of the whole indoor environmental quality model were performed with the NIST program for Monte Carlo tests. The presented indoor environmental quality model proposal is developed to support engineers’ practice as the convenient tool for a practical assessment of building’s occupational satisfaction.

Purpose This paper aims to examine the relationship between the building physical condition (BPC) and indoor environmental quality (IEQ). Various building defects and their effects on occupants’ comfort, satisfaction, health and productivity were identified and analysed. Design/methodology/approach The six-phase thematic analysis was used to examine the content of 27 papers, and three primary themes were identified: BPC–IEQ Performance Assessment: Tools and Techniques, BPC’s Influence on IEQ and Occupants’ Effect: BPC–IEQ Relationship. The first theme emphasised innovative approaches for assessing criticality (defect, space and key performance indicator-based assessments). The second theme highlighted the significant correlation between BPC and IEQ, including the impact of building defects and external factors on indoor air quality. The third theme explored how BPC and IEQ settings influenced occupants’ perceptions (satisfaction, health, comfort and absenteeism). Findings An increasing interest about the correlation between BPC and IEQ was identified in this paper. Various issues, including cracks, insufficient insulation and inadequate ventilation systems, adversely impacted IEQ and occupants’ perceptions. Research areas that require further investigation were also determined. Practical implications The outcomes of this narrative review suggest the importance of BPC assessment in enabling facility managers to implement preventive maintenance, optimise building performance and make informed, data-driven decisions to enhance IEQ and occupant well-being. Originality/value This paper contributes information regarding the correlation between BPC–IEQ, constraint identifications and potential research routes for improving building performance and the well-being of occupants, given that previous studies did not specifically explore these concerns.

Investigation of Indoor Environmental Quality (IEQ) in various types of buildings has currently evolved into a rather intense research activity. IEQ refers to the acceptable levels of thermal, visual and acoustic comfort in addition to Indoor Air Quality (IAQ). In the proposed work, a systematic measurement campaign in university classrooms in the Educational School of the University of Western Macedonia, Florina, Greece, is presented; the campaign was performed by the end of the Spring Semester, in free-running classrooms. Measurements include thermal comfort parameters, as well as IAQ ones, namely volatile organic compounds (VOCs), CO2 and NO2 concentration. Lighting and acoustic measurements are also performed, contributing to an integrated IEQ assessment. As far as thermal comfort is concerned, a questionnaire survey aims at providing insight into the validity of the examined comfort models, i.e., Fanger’s and adaptive one. CFD analysis, according to the DesignBuilder software, allows the investigation of spatial phenomena in terms of thermal comfort, as well as the evaluation of the effect of different scenarios regarding the degree of crowding in the classes and windows opening. All in all, the proposed analysis represents an integrated experimental and simulation approach, for the evaluation of IEQ of a demanding space.

Indoor environmental quality (IEQ) is important to the health, comfort, and well-being of building occupants. Unsatisfactory IEQ is associated with a number of phenomena, most notably, sick building syndrome (SBS), building-related illnesses (BRIs), and multiple chemical sensitivity (MCS), which have major negative effects on productivity. However, green building investors (owners) are not only concerned about reducing the negative impact of their buildings on the environment, but also about the potentially negative impact green buildings can have on their employees' productivity. This research sets out to address, through a questionnaire survey in South Africa, what constitutes the determinants of green building occupants' satisfaction with the IEQ elements of a green building and the health implications of a building's IEQ on the building occupants. Data analysis (involving a one-sample t-test) reveals some interesting findings in regard to what constitutes the determinants of green building occupants' satisfaction with the IEQ elements and the health implications of the IEQ elements of a five-star green rated building in South Africa. Findings from the survey revealed that the occupants of the building were not satisfied with the green building's IEQ, most especially the ineffectiveness of blocking natural and artificial lighting. Also, it was revealed that the IEQ with particular reference to the noise level and ventilation of the space has some serious health implications for the building occupants. The occupants' evaluation revealed that the major health issues from which they suffer include fatigue, headache, common cold, coughing, and influenza, and these affect their productivity and performance. Since building occupants are a rich source of information about IEQ assessment and its effect on productivity, the study can be used to assess the performance of green buildings, identify areas needing improvement, and provide useful feedback to designers and operators about specific aspects of green building design features and operating strategies that need improvement. This study adds to the body of knowledge on green buildings' IEQ performance.

Combined pollutant effects from indoor and outdoor sources on children's health, while being at school have not been holistically tackled. The aim of the School Temperature and Environmental Pollutants Study (STEPS) was to perform a school population representative assessment of indoor air quality (IAQ) in primary schools of densely and intermediate populated areas of Cyprus (n = 42). The study took place during May–July 2021 when a school-specific COVID-19 protocol was in place. Questionnaire-based characteristics of schools/classrooms were collected along with 24/48-h long IAQ monitoring of air temperature, relative humidity (RH), particulate matter (PM), carbon dioxide (CO2) and volatile organic compounds (VOCs), using low-cost sensors. Mixed effect models assessed the IAQ determinants during school hours. Indoor PM, temperature, RH and VOCs increased with progressing school periods in the day, while indoor CO2 decreased. Indoor RH and CO2 were negatively associated with % open windows, while indoor PM2.5 was positively associated. Most of school time (85%), indoor air temperature exceeded the recommended upper limit (27 °C), while a third of indoor PM2.5 (24-h) measurements exceeded 15 μg/m3. The interplay of clean indoor air with adequate ventilation and adaptation to heat stress in schools is important and its comprehensive characterization requires holistic methodological approaches and tools.

Ensuring adequate indoor environmental quality (IEQ) in educational settings is essential for safeguarding students' well-being and optimizing learning.Despite the importance of this issue, limited research has examined the cross-modal effects of acoustics and indoor air quality (IAQ).In this laboratory study, 29 university students were tasked with assessing soundscapes and evaluating IAQ under two CO2 concentrations (800 and 3000 ppm) and four acoustic conditions (quiet, babble noise, mechanical ventilation noise, and birdsongs).Soundscape data were analysed using linear mixed-effects models, while IAQ assessments were analysed with general linear mixed models.All models accounted for the effects of the sounds, CO2 concentrations, and their interactions.The results revealed that soundscape evaluations were influenced solely by the acoustic conditions, with birdsongs being perceived as pleasant, quiet and calm, mechanical ventilation as monotonous, and babble noise as chaotic.In contrast, IAQ evaluations were affected only by the CO2 concentration, with poorer air quality leading to worse perceptions.In conclusion, for the conditions tested in this experiment, each assessment was independently influenced by its respective domain, suggesting an absence of cross-modal effects.

This study aims to analyze the factors of indoor environment on occupants’ health and comfort by post-occupancy evaluation (POE) and to accumulate the fundamental data of occupants’ behaviour in relation to indoor environment, in an effort to ascertain the optimal building energy management system (BEMS). For this purpose, indoor temperature, relative humidity, vertical temperature distribution, air velocity, predicted mean vote (PMV), radiant temperature, outdoor temperature, and humidity were measured for evaluating thermal environment for nearly 2 years. Indoor air contaminants, such as PM10, CO2, formaldehyde, and volatile organic compounds (VOCs) were measured in the building and at outdoor locations. Working plane illuminance, window luminance, and the equivalent continuous a-weighted sound pressure level (Leq) were also monitored. In addition, the occupants in the intelligent office building were surveyed regarding the indoor environmental quality via the intranet. Results showed that all indoor environmental factors satisfied the recommendation, except the indoor relative humidity and PMV. The physical factors of thermal environment had been stable since two months after it was built. However, it should be necessary to improve the sound privacy caused by low background noise, seasonal air-conditioning for appropriate humidity, air freshness, and Video Display Terminal (VDT) glare in order to reduce the level of occupants’ annoyance.

Indoor Environmental Quality is an important issue in educational buildings since it is directly related to students’ well-being and learning activities. Indoor Environmental Quality parameters have been assessed in three representative campus building typologies (old, new, and retrofitted), in Tehran, Iran, by measurements and questionnaire (n = 842) from July 2016 to April 2017. Results have been compared to the students’ overall satisfaction level and recommended standards. According to results, minimum attention to local standards with regard to Indoor Air Quality, acoustic, and lighting, especially in the old and retrofitted buildings, seems the main reason of low environmental quality in the studied cases. Fitting a multiple regression model to the questionnaire data, a mathematical model is developed to predict the overall comfort (Indoor Environmental Quality index). Studied buildings have been ranked based on the Indoor Environmental Quality index from high quality: I (building C) to out of the comfort range: IV (building A). Moreover, results reveal that the acceptable range of each Indoor Environmental Quality parameters, especially with regard to thermal and acoustic comfort, is broader in real condition in comparison with the standards. Finally, the buildings’ annual energy consumption is used to propose a Retrofit Potential Index in order to assess the impact of comfort parameters on energy consumption by integrated analyses.

This exploratory research aims to evaluate indoor environmental quality in the classrooms of three school buildings in Southern Manitoba, Canada, and to evaluate the well-being of these schools' teachers as it pertains to their perception of their classrooms' indoor environment. The schools include a middle-aged, conventional school; a new, non-green school; and a new, green school certified using the Leadership in Energy and Environmental Design rating system. The methodology involved using a mobile instrument cart to conduct snapshot measurements of thermal comfort, indoor air quality, lighting and acoustics in classrooms and an occupant survey to evaluate teachers' long-term satisfaction with their classrooms' indoor environmental quality. The results showed that the new, green and new, non-green schools' classrooms performed better than the conventional, middle-aged school's classrooms with respect to some aspects of thermal comfort and indoor air quality only. Teachers in the new, green school and in the new, non-green school were more satisfied than teachers in the conventional, middle-aged school with their classrooms' overall indoor environmental quality, lighting quality and indoor air quality. Surprisingly, the new, green and new-non green school classrooms' performance were very comparable with the new, green school's classrooms performing statistically significantly better with respect to relative humidity. Similarly, none of the differences in teachers' satisfaction ratings between the new, green and new, non-green school were statistically significant.

PurposeThe purpose of this paper is to review the concept of occupant behavior and its relation with indoor environmental quality (IEQ) and building energy consumption. The behavior is referred to any direct or indirect action, which is selected by an occupant to manage the unpleasant indoor environmental conditions. Thermal comfort, indoor air quality, aural comfort and visual comfort are the key factors of IEQ evaluation. Human behavior significantly interacts with energy consumption in buildings.Design/methodology/approachEach IEQ parameter was reviewed separately and the overall IEQ acceptance was considered. In addition, this paper reviews the methods that were used to measure and simulate the IEQ factors, energy consumption and human behavior. Finally, the lack of knowledge in this field is based on the review demonstrated.FindingsMost studies considered one or two IEQ factors to evaluate IEQ acceptance in buildings. Further, weakness of simulating all IEQ factors at the same time is the deficiency of IEQ simulation, based on reviews. In the case of occupant behavior simulation, the uncertainly of human psychological parameter is a drawback to predict behavior.Originality/valueEnergy consumption, occupant health and productivity are related to IEQ. Human behavior affects building energy consumption directly. Simulation software and methods can predict IEQ factors and human behavior. Therefore, reviewing the existing studies is critical to find new methods for measuring and simulating IEQ, energy consumption and human behavior in buildings.

Assessment of wellbeing in an indoor office environment

Contributors. Preface. Acknowledgements. Part I: Introduction. 1. Defining an Educational Framework for Indoor Air Sciences N. Boschi. Part II: Historical Perspective: Defining the Scientific Field. 2. Indoor Air Sciences: A Defined Area of Study or a Field to be Defined J. Sundell. Part III: Current Trends in Indoor Air Sciences Education. 3. Toward an Internationally Harmonized, Multiprofessional Educational Program in Indoor Air Sciences: Needs and Strategies M. Maroni. 4. Trends in the Post Graduate Educational Curriculum of The Indoor Air Sciences L. Molhave. Part IV: On-Going Educational Programs. 5. Indoor Air Science Training and Education in Finland P.J. Kalliokoski. 6. Graduate Education and Training in Indoor Air Science - A Canadian Approach F. Haghighat. 7. Indoor Air Fundamentals and Graduate Education in the Czech Republic V. Benchko, I. Holcatova. 8. The Teaching of Indoor Air Quality at the Department of Mechanical Engineering at the Technical University of Budapest L. Banhidi. 9. Post Graduate Training on the Health Significance of Indoor Air Quality in Hungary P. Rudnai. 10. Indoor Air Quality Education at the Slovak University of Technology in Bratislava Slovak Republic D. Petras. 11. Environmental Engineering Educational Process in the Field of Indoor Air Sciences I. Senitkova. 12. Indoor Air Education in the Slovak Republic: Education at the Medical Faculties K. Slotova. Part V: Research and Problem Based Education. 13. Training Specialists in Occupational Medicine: The Benefitsof Research Experience in the Field of Indoor Environment G. Muzi. 14. Indoor Environmental Quality Research and Education at Harvard University H.S. Brightman, et al. 15. Problem Based Teaching in Indoor Air Sciences and Practice. Danish and International Experiences S. Kjoergaard. 16. The Assessment Techniques of the Indoor Environment: The Case of the Italian University Libraries G. Guarnerio, R. Pavesi. Part VI: Emerging Issues. 17. A Sustainable Environment Basis for Education in Indoor Air Sciences H. Levin. 18. Engineering Education for Indoor Air Specialists G. Clausen, D.P. Wyon. 19. Occupant Assessment of Indoor Air Quality G.J. Raw, D. Cpsychol. 20. Knowledge and Technology Transfer in Teaching in Indoor Air Sciences L. Morawska. Part VII: Different Educational Players for Different Audiences and Needs. 21. Federal Roles in Education and Training in the Indoor Air Sciences: Case Studies of U.S. Environmental Protection Agency Involvement in Training Development and Delivery E. Feldman. 22. Education and Training in the Field of Indoor Air Sciences in Bulgaria M. Tchoutchkova. 23. Education Needs in Eastern European Countries and New Independent States L. Banhidi, V. Bencko. 24. Education in Indoor Air Sciendes in Poland A. Charkowska. 25. Education in Indoor Air Sciences in Romania I. Mocsy. 26. CIB and Education and Training in Indoor Air Sciences P.M. Bluyssen, W. Bakens. 27. Assessment of Indoor Air Quality and its Impact on Children's Health A. P&aa

An indoor environmental quality (IEQ) monitoring station (5), an IEQ monitoring system (1) and a method (100) for monitoring an IEQ efficiency for an occupied zone (3). Sensors provide signals relating to thermal comfort, lighting, acoustics and indoor air quality at the occupied zone (3) that may be the basis for IEQ parameter data. IEQ efficiency may be determined based on IEQ parameter data and supplementary data. information Poesn threshold IEQ data ... 18..3.5

Post-occupancy evaluation is a well-known research method documenting occupants’ satisfaction with indoor environmental quality (IEQ) factors. Despite potentially significant roles of gender differences in IEQ satisfaction, it has not always been acknowledged by researchers and findings are debated. Through a self-administered questionnaire over nine years, students (n = 3140) in 11 different higher education classroom buildings in Minnesota, USA rated their satisfaction with 23 IEQ factors. They were most satisfied with overall cleaning and maintenance followed by overall indoor air quality and amount of electric lighting. Students were least satisfied with access to electric outlets followed by daylighting IEQ factors. Mann–Whitney U tests showed that female students were statistically less satisfied with overall thermal conditions and temperature, while male students were statistically less satisfied with daylighting, electric lighting, and view conditions. Subsequent logistic regression analyses indicated the most significant impact of amount of electric lighting. The results imply that once students were dissatisfied with amount of electric lighting, they were more likely to be dissatisfied with the classroom. Despite the significant impacts of all IEQ factors, the different degree of the likelihoods indicates that some IEQ factors may impact classroom satisfaction more than other IEQ factors as indicated by this benchmark study.