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Exposure to poor indoor air in refurbished buildings is a matter of health concern due to the growing concentrations of various contaminants as a result of building airtightness without amendment of ventilation, or the use of building materials such as glue, paint, thinner and varnishes. Recent studies have been conducted to measure indoor air pollutants and assess the health risks affecting the quality of life, productivity and well-being of human beings. However, limited review studies have been recently conducted to provide an overview of the state of knowledge. This study aims to conduct a scoping review of indoor air quality (IAQ) in the context of refurbished or energy-retrofitted buildings.

A systematic screening process based on the PRISMA protocol was followed to extract relevant articles. Web of Science, Scopus, Google Scholar and PubMed were searched using customised search formulas. Among 276 potentially relevant records, 38 studies were included in the final review covering a period from 2015 to 2022.

Researchers mapped out the measured compounds in the selected studies and found that carbon dioxide (CO₂) (11%) and total volatile organic compounds (11%) were among the most commonly measured contaminants. Two trends of research were found including (1) the impact of ventilative properties on IAQ and (2) the impact of introducing building materials on IAQ.

The contribution of this study lies in summarising evidence on IAQ measurements in refurbished buildings, discussing recent advancements, revealing significant gaps and limitations, identifying the trends of research and drawing conclusions regarding future research directions on the topic.

Indoor environments are characterized by several pollutant sources. Some of these can be sufficiently characterized through the prediction of the airflow and pollutant distribution patterns. The purpose of this study was to simulate, analyze and compare different locations of known pollutant source inside a ventilated room.

Computational fluid dynamics modelling approach was used to analyze the prediction of the airflow and pollutant distribution patterns for different locations of known pollutant source inside a ventilated room by mixing ventilation.

Distinct areas of poor air quality, perfectly identified by concentration fields, were given. The indoor air quality obtained by the different simulated conditions was analyzed and compared.

Pollutant concentration was not measured in the validation experiments (qualitative validation based on the velocity fields).

Once the contaminant concentration fields are calculated based on the source location, the model is very useful to choose the best place to install any pollutant indoor equipment to preserve breathing zones.

Providing an effective indoor air quality assessment to prevent exposure risk. The results would be useful for making decisions to optimize the design procedure, such as establish the best location to install polluting equipment, occupied areas and their interdependence with ventilation systems. In addition, this tool also helps to choose the best location and correct set point adjustment for the pollutant sensors.

Maintaining good indoor air quality (IAQ) in the built environment is essential to assure health, safety and productivity of occupants. The purpose of this paper is to report on the preliminary IAQ assessment of selected air-conditioned laboratories and naturally ventilated workshops in a tropical education institution.

The concentration levels of five major indoor air pollutants (IAPs) – carbon dioxide, carbon monoxide, respirable particulates, formaldehyde (HCHO) and total volatile organic compounds (TVOC) in each sampling area were measured using calibrated air sampling sensors and the tracer-gas analysis was used to determine the ventilation effectiveness. A questionnaire survey was carried out concurrently to study the prevalence of sick building syndrome (SBS) among users of laboratories and workshops and the data collected were statistically analysed using χ² test.

The air pollutant levels were found to be below the threshold limit values set in the local code of practice on IAQ, except for two of the air-conditioned laboratories. This is possibly due to insufficient ventilation, smaller floor area per occupant ratio, long-term exposure to chemical substances, and improper disposal of the used chemical substances. The total particulate levels were higher in naturally ventilated workshops because such spaces were assigned for mechanical works which involved grinding, welding and fabrication. Besides, it was identified that most of the air contaminant levels were not normally distributed (p<0.05) within the sampling areas and SBS like dry eyes, watery eyes, tiredness and dry throat were reported in both laboratories and workshops. The outcomes of this work suggest that an increase of ventilation rate was necessary to reduce the concentration of the IAPs in air-conditioned laboratories and improved housekeeping would help mitigate the prevalence of SBS symptoms.

This research was carried out in selected laboratories and workshops in a Malaysian educational institution and only five major IAPs stipulated in the Department of Occupational Safety and Health (DOSH) code of practice were measured.

The results of this study will enable facility engineers and managers to understand the IAPs concentration levels and potential SBS problems in academic laboratories and workshops. The recommended strategies can be considered to improve IAQ conditions in such spaces.

Most of the previously conducted IAQ studies focused only on commonly occupied building spaces such as offices, classrooms and houses. Information of the quality of air and SBS conditions in experimental facilities in developing nations that is available is currently very limited. This case study provides detailed information on IAQ in laboratories and workshops in Malaysia with focuses on the concentration levels of particular harmful gases, the prevalence of SBS among users of these facilities and the appropriate mitigation strategies. The results presented are of value to both academic and industry communities.

The purpose of this paper is to evaluate the indoor environmental quality among residential buildings in dense urban living environment, after the outbreak of Severe Acute Respiratory Syndrome (SARS), which called for a review on the relationship between health issues and the authors' built facilities.

Environmental tests include thermal comfort, noise, daylight and air quality inside the residence of typical housing units were carried out. Based on inferences drawn from test results, the paper developed systematic conclusions.

It was observed that most of the occupants (over 70 per cent of 125 households) were tolerating the higher air temperature and dimmer daylight inside their residence, which was proven to fall behind Hong Kong Standard. On the contrary, people reflected that they were also trying to abate noise and dust concentration in their daily life.

Owing to the flat occupants' exclusive property rights in law, there were limited access to the residents' flats and only 32 occupants out of 125 allowed us to conduct the survey. Yet, the data set was justified.

The results provides practical guidance for the design of future housing to enhance health and comfort of occupants.

Originality of the findings is based on on‐site data collected in dense urban housing condition. Rating data were also collected from the occupants concerned about their habituation conditions in Hong Kong after the outbreak of SARS, which was a major crisis that called for fundamental review of the authors' built facilities.

There is growing concern in the more affluent, developed countries about the possible relationship between the environment created in energy‐efficient, high‐tech, air‐conditioned buildings, and the health problems of occupants. Over the past decade there has been a considerable increase in interest shown in the indoor air quality of offices, due in the main to improvements in measuring indoor air contaminants, a greater understanding of the health effects and the fact that 80 to 90 per cent of people now spend their time indoors. There is also a greater public awareness of the need for an adequate working environment. It is significant that the increased involvement of unions in white collar areas of work has generated considerable debate on the subject of hazards in the office environment which coincides with the national and international concern now materialising.

This study aims to provide a comprehensive framework for the study of indoor air quality (IAQ) in hospitality premises. The goal is to identify the drivers of air pollution, both at the exogenous and endogenous level, to generate insights for facility managers.

The complexity of hospitality premises requires an integrated approach to properly investigate IAQ. The authors develop an overarching framework encompassing a monitoring method, based on real-time sensors, a technological standard and a set of statistical analyses for the assessment of both IAQ performance and drivers, based on correlation analyses, analysis of variance and multivariate regressions.

The findings suggest that the main drivers of IAQ differ depending on the area monitored: areas in contact with the outdoors or with high ventilation rates, such as halls, are affected by outdoor air quality more than guestrooms or fitness areas, where human activities are the main sources of contamination.

The results suggest that the integration of IAQ indicators into control dashboards would support management decisions, both in defining protocols to support resilience of the sector in a postpandemic world and in directing investments on the premises. This would also address guests’ pressing demands for a broader approach to cleanliness and safety and support their satisfaction and intention to return.

To the best of the authors’ knowledge, this is the first study developing a comprehensive framework to systematically address IAQ and its drivers, based on a standard and real-time monitoring. The framework has been applied across the longest period of monitoring for a hospitality premise thus far and over an entire hotel facility.

Sensor arrays and pattern recognition-based electronic nose (E-nose) is a typical detection and recognition instrument for indoor air quality (IAQ). The E-nose is able to monitor several pollutants in the air by mimicking the human olfactory system. Formaldehyde concentration prediction is one of the major functionalities of the E-nose, and three typical machine learning (ML) algorithms are most frequently used, including back propagation (BP) neural network, radial basis function (RBF) neural network and support vector regression (SVR).

This paper comparatively evaluates and analyzes those three ML algorithms under controllable environment, which is built on a marketable sensor arrays E-nose platform. Variable temperature (T), relative humidity (RH) and pollutant concentrations (C) conditions were measured during experiments to support the investigation.

Regression models have been built using the above-mentioned three typical algorithms, and in-depth analysis demonstrates that the model of the BP neural network results in a better prediction performance than others.

Finally, the empirical results prove that ML algorithms, combined with low-cost sensors, can make high-precision contaminant concentration detection indoor.

At the beginning of the Corona Virus Disease 2019 (COVID-19) pandemic, a digitalized construction environments surfaced in the heating, ventilation and air conditioning (HVAC) systems in the form of a modern delivery system called demand controlled ventilation (DCV). Demand controlled ventilation has the potential to solve the building ventilation's biggest problem of managing indoor air quality (IAQ) for controlling COVID-19 transmission in indoor environments. However, the improper evaluation and information management of infection prevention on dense crowd activities such as measurement errors and volatile organic compound (VOC) generation failure rates, is fragmented so the aim of this research is to integrate this and explore potentials with machine learning algorithms (MLAs).

The method used is a thorough systematic literature review (SLR) approach. The results of this research consist of a detailed description of the DCV system and digitalized construction process of its IAQ elements.

The discussion revealed that DCV has a potential for being further integrated by perceiving it as a MLAs and hereby enabling the management of IAQ level from the perspective of health risk function mechanism (i.e. VOC and CO₂) for maintaining a comfortable thermal environment and save energy of public and private buildings (PPBs). The appropriate MLA can also be selected in different occupancy patterns for seasonal variations, ventilation behavior, building type and locations, as well as current indoor air pollution control strategies. Furthermore, the conceptual framework showed that MLA application such as algorithm design/Model Predictive Control (MPC) integration can alleviate the high spread limitation of COVID-19 in the indoor environment.

Finally, the research concludes that a large unexploited potential within integration and innovation is recognized in the DCV system and MLAs which can be improved to optimize level of IAQ from the perspective of health throughout the building sector DCV process systems. The requirements of CO₂ based DCV along with VOC concentrations monitoring practice should be taken into consideration through further research and experience with adaption and implementation from the ventilation control initial stage of the DCV process.

The use of indoor living plants for enhancement of indoor relative humidity and the general environment of a large, modern, open plan office building are studied using a mixed-methods paradigm.

The quantitative element involved designated experimental and control zones within the building, selected using orientation, user density and users’ work roles criteria. For a period of six months, relative humidity was monitored using data loggers at 30 min intervals, and volatile organic compounds were measured using air sampling. Qualitative “perception data” of the building’s users were collected via a structured questionnaire survey among both experimental and control zones.

Study findings include that living plants did not achieve the positive effect on relative humidity predicted by (a-priori) theoretical calculations and that building users’ perceived improvements to indoor relative humidity, temperature and background noise levels were minimal. The strongest perceived improvement was for work environment aesthetics. Findings demonstrate the potential of indoor plants to reduce carbon emissions of the [as] built environment through elimination or reduction of energy use and capital-intensive humidification air-conditioning systems.

The study’s practical value lies in its unique application of (mainly laboratory-derived) existing theory in a real-life work environment.