Indoor Air Quality Parameters Research Articles

Evaluation of Sick Building Syndrome (SBS) Symptoms and Measurement of Indoor Air Quality (IAQ) Parameter in One of Hospital Building in Johor

Evaluation of Sick Building Syndrome (SBS) Symptoms and Measurement of Indoor Air Quality (IAQ) Parameter in One of Hospital Building in Johor

Intelligent Forest Hospital as a New Management System for Hospital-Acquired Infection Control.

Hospital-acquired infection (HAI) is a significant global health concern, elevating the risks of morbidity and imposing a substantial socioeconomic burden. To enhance the management of HAI, particularly in the aftermath of the coronavirus disease 2019 (COVID-19) pandemic, the Guangdong Second Provincial General Hospital (GD2H) has launched a new system called Intelligent Forest Hospital (IFH). Leveraging advancements in artificial intelligence, 5G technology, and cloud networking, the IFH implements customized indoor air quality (IAQ) control strategies tailored to different medical settings. It utilizes various intelligent disinfection devices and air purification systems. The IFH features a dynamic 3D hospital model with real-time monitoring of crucial IAQ parameters and a risk assessment ranking for clinical departments, providing timely risk alerts, communication prompts, and automatic disinfection processes. The IFH aims to effectively mitigate HAI post-COVID-19 and other future pandemics, ensuring a safe and pleasant environment for patients, hospital staff, and visitors.

Investigation of microbiological quality of indoor air in university campus due to students returning after COVID-19 restriction

Abstract COVID-19 has opened the world’s eyes to microbiological indoor air quality, which is essential to know the disease’s behaviour and spread. COVID-19 has caused several campuses to restrict campus activities to minimize the virus’s transmission among students. As students return to campus, microbiological indoor air quality can deteriorate. Therefore, understanding related to this matter needs to be improved. This study aims to give a glimpse to investigate the impact of a student returning to microbiological indoor air quality and determine the main contributing factors influencing it. This study measured two microbial air pollutants, total bacteria, and fungi, in a different indoor environment at the Sumatra Institute of Technology in Lampung, Indonesia. Simultaneously, the main factor, (the number of occupants/students) and several environmental factors that could potentially influence microbial air pollutants such as room temperature, relative humidity, light intensity, ventilation area, and the direction of wind movement were also measured. Compared to measurements taken during the pandemic, the intensified number of averaged total bacteria and total fungi reached 248% and 63%, respectively. The total bacteria measured at the sampling locations were higher than the total fungi of 799.27 CFU/m3 compared to 552.99 CFU/m3. The number of bacteria also exceeds the Indonesian Bacteria Indoor Air Quality parameters standard. Based on the regression linier analysis, different significant variables influence each parameter. In general, the return of students after COVID-19 restrictions has significantly affected indoor microbiological air quality. In addition, the environmental factors that affect the parameters of bacteria and fungi are different, so further attention shall be addressed by the campus.

Assessments and application of low-cost sensors to study indoor air quality in layer facilities

Indoor poultry facilities often experience poor air quality due to intensive farming and restricted ventilation. Monitoring the air quality in these barns is crucial considering the health of both the birds and producers. Advancements in sensor technologies have led to the development of low-cost sensors (LCS) that can continuously monitor air pollutants. Even though most poultry facilities in Canada are indoors due to harsh winter weather conditions, there is a lack of indoor air quality (IAQ) studies. This study aimed to evaluate the field performance of the LCS network in a table egg farm in Canada, where the sensors were designed specifically for operating in dusty poultry facilities continuously. The LCS monitored IQA parameters such as particulate matter (PM), carbon dioxide (CO2), relative humidity, and temperature in real-time. By implementing a correction factor, the sensor data resulted in an agreement range of 80 ± 20% with a reference instrument. The study observed that PM concentration exceeded several thousand μg/m3, with PM10 at 5.5 × 104 ± 2.2 × 104 and PM2.5 at 6.3 × 103 ± 2.3 × 103, which was found to be most affected by the chicken activity and light regime. The IAQ parameters also exhibited a complex intercorrelation with each other, as well as the outdoor temperature and the building ventilation rate. Sensors were able to make observations that were found only with research-grade instruments in previous studies. Overall, the study showcases the potential of the LCS network as an affordable solution for environmental monitoring in poultry facilities.

A comparative study of indoor and outdoor air quality and associated potential health effects in Gurugram, India.

Abstract Deteriorating air quality remains a leading reason for global human illness and death. This study aims to investigate and compare inside and outside ambient air quality in 15 locations of Gurugram, India. Research technique adopted comprised of extracting outdoor air quality parameter values via Air Quality Index reporting stations for the entire year 2022. Parallel to that, indoor air quality parameter values of houses close to those monitoring stations were recorded through low-cost IoT based AirCubic sensors (T1595) as PM2.5, PM10, relative humidity (RH) and carbon monoxide (CO). After statistical evaluation, it was found that there were significant variations in outdoor and indoor air quality with maximum variations seen in colder season. The study revealed that PM levels were generally lower inside homes than outsides, while CO and RH concentrations were higher indoors. However, these levels often exceeded the acceptable thresholds set by both Indian national and global air quality standards, that could potentially result in harmful health effects, as well as increased risk of short and long-term illnesses, and even death. It may be concluded that more research, extensive air quality monitoring, data sharing, citizen awareness, and better technical and policy inputs are required to maintain healthy air quality for a sustainable lifestyle.

Sustainable Building Construction Materials in the United Arab Emirates: A Review

The construction industry, a major player in economic development, is facing increased pressure to address sustainability concerns amidst rapid population growth and urbanization. With global projections indicating a significant rise in building demand by 2050, sustainability has emerged as a crucial focus area and paradigm shift to enhance environmental friendliness, quality, and project outcomes. The UAE, renowned for its vibrant construction industry, offers a unique context for examining the integration of sustainable practices. The use of sustainable construction practices is growing in the UAE, where the built environment plays a key role in economic growth and environmental stewardship. The United Arab Emirates (UAE) aims to foster long-term sustainability while enhancing the standard of living for current and future generations by integrating social, environmental, and economic aspects within construction projects, while also reevaluating conventional sustainable development frameworks and embracing a triple bottom line approach. This research was conducted to explore sustainable construction material usage and evaluation in the United Arab Emirates. The literature was reviewed for sustainable building construction materials across the UAE in the SCOPUS index from 2014 to 2024, as well as the regional regulations concerning the subject. This study evaluated the increasing trend of sustainable construction material research works, as well as the sound regional parameters of sustainable construction materials implemented across the country. Through an exploration of the significance of sustainable construction materials, this research underscores the multifaceted benefits of locally sourced, recyclable, and renewable materials in reducing environmental impacts, fostering economic and social well-being, and improving overall project performance and project management practices. The construction sector’s role in economic development and its substantial environmental impact are discussed in alignment with sustainable construction materials, sustainable construction practices, and the need to enhance environmental sustainability and create healthier built environments. In the realm of sustainable construction materials, project management knowledge areas encompass a range of factors. These include the properties of materials sourced regionally; the incorporation of recycled content; considerations for indoor air quality, energy, and water efficiency parameters; and how these properties relate to project scopes, scheduling constraints, and challenges. Additionally, the availability of resources and competency levels, quality control standards, specifications, communication strategies, and stakeholder involvement play crucial roles. It is important to assess both the positive and negative risks associated with these elements across construction projects.

Toward occupant-centric system: Multicriteria optimization of hybrid displacement–personalized ventilation system using computational fluid dynamics with computer-simulated person

Engineers have integrated general ventilation systems with personalized ventilation (PV) to achieve energy efficiency while providing good indoor air quality (IAQ) and thermal comfort. Previous studies conducted parametric analyses of PV by varying its flow rate and temperature, analyzing energy, IAQ, and thermal comfort while keeping main ventilation settings constant, even though the latter significantly affect the general flow field. Therefore, computational fluid dynamics simulation is performed to simultaneously optimize the above-mentioned three outputs in an office with displacement ventilation (DV) and PV by varying the DV supply flow rate and temperature, the fraction of outlet air being resupplied to inlet or DV recirculation, and PV supply flow rate and temperature. We utilize the Taguchi design to minimize the number of simulations as well as use the “technique for order preference by similarity to ideal solution” (TOPSIS) coupled with Taguchi's signal-to-noise ratio analysis for optimization. Four optimization cases are investigated by varying the thermal comfort and IAQ parameters from volume-averaged to occupant-centric values, such as the skin temperature and inhaled concentration. Results show that occupant-centric optimization presents low energy requirements with acceptable IAQ and thermal comfort compared with volume-averaged optimization, which can be attributed to imperfect mixing conditions. Furthermore, the DV settings and thermal plumes significantly affect the direction of jet released by the PV, which does not improve the IAQ. This underscores the importance of considering the aforementioned effects in maximizing the PV potential. Nevertheless, the PV system functions as intended under a flow rate of 6 L/s.

Impact of ventilation system retrofitting on indoor air quality in a single-family building

Due to prolonged human occupancy within indoor environments, the quality of indoor air holds significant importance. This study evaluates the impact of retrofitting a ventilation system from natural to mechanical on indoor air quality (IAQ) in a bedroom during heating seasons in 2017/18 and 2020/21. Measurements were conducted before and after modernization to assess CO2 concentrations, temperature, humidity, particulate matter (PM) and bacterial and fungal aerosols levels indoors and outdoors. Results show a significant decrease in CO2 concentration (from 1000 ± 240 ppm to 806 ± 165 ppm) and relative humidity (from 53.0 ± 3.6 % to 28.2 ± 4.1 %) post-modernization. Notable reduction in CO2 concentrations averaging 20 % was recorded, thereby elevating air quality category from IDAIII to IDAII. Additionally, the study determined the infiltration coefficient for PM2.5, which increased from 0.48 under natural ventilation to 0.63 after retrofitting. PM2.5 concentrations increased indoors (from 23.49 ± 11.21 μg/m3 to 56.68 ± 13.47 μg/m3) due to higher infiltration rates with mechanical ventilation. Bioaerosol measurements indicate fluctuating concentrations, with bacterial aerosols peaking in the evening. The use of mechanical ventilation led to increased transport and dispersion of bacterial bioaerosols indoors. In contrast, this was not observed for fungal aerosols. Additionally, the study highlights limitations in ventilation filtration efficiency and recommends the installation of PM2.5 sensors to regulate airflow during periods of high outdoor PM2.5 concentrations. Overall, while mechanical ventilation improved some IAQ parameters, it posed challenges in controlling particulate matter infiltration, emphasizing the need for comprehensive ventilation strategies to ensure indoor air quality and occupants' well-being.

Systematic Review of Factors Influencing Students’ Performance in Educational Buildings: Focus on LCA, IoT, and BIM

In the evolving field of civil engineering studies, a significant transition is evident from fundamental to new-generation research approaches. This paper presents a systematic literature review aimed at analyzing these shifts, focusing specifically on the performance of students in educational buildings thought the integration of modern technologies such as the Internet of Things, life cycle assessments, and building information modeling. Covering the literature from the late twentieth century to the early twenty-first century, the review emphasizes advancements in sustainable infrastructure, eco-friendly designs, digitalization, and advanced modeling. A comparative analysis reveals that while the fundamental articles are primarily focused on indoor air quality parameters, the new-generation articles prioritize technological integration to address broader environmental concerns and for improved building performance. Challenges in the education sector, such as insufficient energy use, high maintenance costs, and poor working conditions, are also discussed, showcasing their impact on student learning outcomes. The methodology employed for this review included a comprehensive search in databases such as Scopus and Web of Science, using keywords such as “school buildings”, “IoT”, “BIM”, and “LCA”, ensuring a robust and diverse collection of academic articles. The findings show that new trends supplement existing topics, suggesting an integration rather than a replacement of traditional practices. Consequently, future research efforts will need to include a broader range of information to fully account for the evolving landscape in this field.

Comparative Analysis of Indoor Air Quality and Thermal Comfort Standards in School Buildings across New Zealand with Other OECD Countries

COVID-19 has improved awareness of the importance of appropriate indoor air quality (IAQ) in indoor spaces, particularly in classrooms where children are expected to learn. Research has shown that poor IAQ and temperature levels affect the cognitive performance of children. In this paper, we critically compare IAQ standards for New Zealand’s Designing Quality Learning Spaces (DQLS Document) against international benchmarks from the Organization for Economic Co-operation and Development (OECD) countries, including ASHRAE 62.1, CIBSE TM57, EN-15251, WHO AQGs, and Building Bulletins 99 and 101. The aim was to ascertain the robustness of New Zealand’s DQLS document, identify areas of superiority, and recommend the required improvement for appropriate IAQ and thermal comfort in classrooms. This comparison review focuses on IAQ parameters: CO2 levels, temperature, ventilation rates, room size, occupant density, and occupancy rates. The findings illuminate a slight lag in New Zealand’s DQLS standards compared to her international counterparts. For instance, while New Zealand’s standards align closely with WHO standards for IAQ concerning temperature and ventilation rates, the recommended CO2 range appears slightly inadequate (800 to 2000 ppm) along with occupancy and classroom size for effectively controlling classroom pollutant growth. This paper emphasises the need to align New Zealand’s IAQ and thermal comfort standards with optimal OECD benchmarks. The identified disparities present opportunities for improving learning spaces in terms of CO2 concentration, size of classroom, and occupant density in schools in New Zealand to meet globally recognised standards, ultimately creating a healthier and more conducive learning environment.

Indoor air quality prediction modeling for a naturally ventilated fitness building using RNN-LSTM artificial neural networks

Indoor air quality prediction modeling for a naturally ventilated fitness building using RNN-LSTM artificial neural networks

Indoor sulfur dioxide prediction through air quality modeling and assessment of sulfur dioxide and nitrogen dioxide levels in industrial and non-industrial areas.

In this study, the levels of sulfur dioxide (SO2) and nitrogen dioxide (NO2) were measured indoors and outdoors using passive samplers in Tymar village (20 homes), an industrial area, and Haji Wsu (15 homes), a non-industrial region, in the summer and the winter seasons. In comparison to Haji Wsu village, the results showed that Tymar village had higher and more significant mean SO2 and NO2 concentrations indoors and outdoors throughout both the summer and winter seasons. The mean outdoor concentration of SO2 was the highest in summer, while the mean indoor NO2 concentration was the highest in winter in both areas. The ratio of NO2 indoors to outdoors was larger than one throughout the winter at both sites. Additionally, the performance of machine learning (ML) approaches: multiple linear regression (MLR), artificial neural network (ANN), and random forest (RF) were compared in predicting indoor SO2 concentrations in both the industrial and non-industrial areas. Factor analysis (FA) was conducted on different indoor and outdoor meteorological and air quality parameters, and the resulting factors were employed as inputs to train the models. Cross-validation was applied to ensure reliable and robust model evaluation. RF showed the best predictive ability in the prediction of indoor SO2 for the training set (RMSE = 2.108, MAE = 1.780, and R2 = 0.956) and for the unseen test set (RMSE = 4.469, MAE = 3.728, and R2 = 0.779) values compared to other studied models. As a result, it was observed that the RF model could successfully approach the nonlinear relationship between indoor SO2 and input parameters and provide valuable insights to reduce exposure to this harmful pollutant.

Indoor air quality and sick building syndrome symptoms in administrative office at public university

Sick Building Syndrome (SBS) is an illness among workers linked to time spent in a building. This study aimed to investigate the Indoor Air Quality (IAQ) and symptoms of Sick Building Syndrome (SBS) among administrative office workers. The IAQ parameters consist of ventilation performance indicators, and physical and chemical parameters were measured using specified instruments for three days during weekdays. The SBS symptoms were assessed by a questionnaire adopted from the Industry Code of Practice of Indoor Air Quality (ICOP-IAQ) 2010 among 19 employees from the office in East Coast Malaysia. Relationship between past symptoms and present symptoms which are draught (past symptoms) with feeling heavy headed (present symptoms) (r = 0.559, p < 0.05), room temperature too high (past symptoms) was highly correlated with feeling heavy headed (present symptoms) (r = 0.598, p < 0.01) and cough (present symptoms) (r = 0.596, p < 0.01). Room temperature (past symptoms) has a positive medium relationship with cough (present symptoms) (r = 0.477, p < 0.05) and scaling itching scalp or ears (present symptoms) has a relationship between stuffy bad air (r = 0.475, p < 0.05) and dry air (r = 0.536, p < 0.05). There was a significant association between RH with drowsiness (χ2 = 7.090, p = 0.049) and dizziness (χ2 = 7.090, p = 0.049). The association was found between temperature and SBS symptoms between temperature with headache (χ2 = 7.574, p = 0.051), feeling heavy-headed (χ2 = 8.090, p = 0.046), and skin rash itchiness (χ2 = 7.451, p = 0.044). Air movement also showed a positive association with symptoms of feeling heavy-headed (x2 = 8.726, p = 0.021). PM10 has positive significance with SBSS which are feeling heavy-headed (χ2 = 7.980, p = 0.023), and eyer's irritation (χ2 = 7.419, p = 0.038). The conclusion of this study showed that there were positive significant between temperature and relative humidity toward SBSS.

Spatial mapping of indoor air quality in a light metro system using the geographic information system method

Abstract It is known that one of the greatest problems of developed countries in the twenty-first century is traffic. For this reason, engineers have searched for alternative solutions to the problem of traffic. One such solution is the construction and utilization of rail systems instead of main roads. From an engineering perspective, rail systems can be divided into three groups: metro, light metro, and tram systems. Light metro systems, which are a form of public transportation, are not directly inside the traffic. Their most important advantages include the fact that they do not release combustion products such as CO, and metro and light metro systems may be considered environmentally friendly based solely on their electricity consumption. In this study, measurements of parameters affecting indoor air quality were made inside light metro cars and in and around light metro stations belonging to the light metro system of the Metropolitan Municipality of Antalya, known as the tourism capital of Turkey. In February and March 2021, when the COVID-19 pandemic was first registered in Turkey, particulate matter (PM), temperature, and relative humidity measurements were made for testing indoor and outside air quality. Moreover, as outside air parameters, outside temperature, outside relative humidity, CO, normalized difference vegetation index, and ultraviolet aerosol index data were obtained from the General Directorate of Meteorology of Turkey. The measurement results were analyzed using the inverse distance weighting method in the geographic information system. Based on the results of the analyses, spatial maps were created for indoor and outside air quality parameters in the light metro system. Using these maps, the effects of passenger density and environmental factors both inside the metro cars and at the metro stations on indoor air quality were identified. In addition, the spread of the SARS-CoV-2 virus in the COVID-19 period was analyzed using spatial maps of the PM0.3 and PM0.5 parameters. It is believed that the results of this study will set an example for further indoor air quality studies worldwide, and this study is unique in that it employed a method that is used particularly in survey and geomatics engineering for analyzing indoor air quality in light metro systems.

Indoor Air Quality and Bioaerosols in Spanish University Classrooms.

A comprehensive study assessed indoor air quality parameters, focusing on relevant air pollutants such as particulate matter (PM10 and PM2.5), gaseous compounds (CO, CO2, formaldehyde, NO2) and volatile/semi-volatile organic chemicals, as well as respiratory viruses (including SARS-CoV-2), fungi and bacteria in Spanish university classrooms. Non-target screening strategies evaluated the presence of organic pollutants inside and outside the classrooms. Saliva samples from teachers and students were collected to explore correlations between respiratory viruses in the air and biological samples. Indoor results revealed the punctual exceedance of recommended guidelines for CO2, formaldehyde (HCHO), volatile organic compounds (TVOCs) and PM in the least naturally ventilated classrooms. Significant differences occurred between the classes, with the least ventilated one showing higher average concentrations of CO2, HCHO, NO2, PM10 and PM2.5. A respiratory virus (rhinovirus/enterovirus) was detected in the medium naturally ventilated classroom, although saliva samples tested negative. Suspect screening tentatively identified 65 substances indoors and over 200 outdoors, with approximately half reporting a high toxicological risk based on the Cramer rules. The study provides a comprehensive overview of indoor air quality, respiratory viruses and organic pollutants in university classrooms, highlighting the variations and potential health risks associated with ventilation differences.

Respiratory infection transmission risk and indoor air quality at outpatient departments and emergency treatment units of Sri Lankan teaching hospitals.

Indoor carbon dioxide (CO2) concentration has been used as a proxy of the degree of ventilation and, by extension, as an indicator of the risk of contracting respiratory infections. No publications exist regarding indoor air quality (IAQ) parameters of Sri Lankan hospitals.We measured the levels of CO2 and seven other IAQ parameters during morning rush hours for three days, in outpatient departments (OPDs) and emergency treatment units (ETUs) of all 21 teaching hospitals of Sri Lanka. We measured the same parameters of outdoor air also. We calculated the mean values of those parameters. We looked for correlations between outdoors and OPD and ETU levels of selected air quality parameters.The average CO2 levels of outdoors, OPDs and ETUs respectively were 514ppm (ppm = parts per million), 749ppm and 795ppm. The average levels of PM2.5 (particulate matter with diameters <2.5μm) outdoors, OPDs and ETUs respectively, were 28.7μg/m3,32μg/m3 and 25.6 μg/m3. The average levels of PM10 (particulate matter with diameters <10μm) outdoors, OPDs and ETUs respectively, were 49.4μg/m3, 55.5μg/m3 and 47.9 μg/m3. The median levels of formaldehyde outdoors, OPDs and ETUs respectively, were 0.03mg/m3, 0.04mg/m3 and 0.08mg/m3. The median levels of total volatile organic compounds (VOC) outdoors, OPDs and ETUs respectively were 0.12mg/m3, 0.19mg/m3 and 0.38mg/m3.CO2 levels of air in OPDs and ETUs generally were below the national ceilings but above the ceilings used by some developed countries. Outdoors, OPDs and ETUs air contain PM10, PM2.5 levels higher than WHO ceilings, although below the national ceilings. VOC and formaldehyde levels are generally below the national ceilings. Air in OPDs and ETUs is hotter and humid than national ceilings. Outdoor PM10, PM2.5 levels influence OPDs and ETUs levels. We propose methods to reduce the risk of nosocomial respiratory infections and to improve IAQ of Sri Lankan OPDs and ETUs.

Indoor pollution control based on surrogate model for residential buildings

Individuals typically spend most of their lives indoors, predominantly in spaces like offices and residences. Consequently, prolonged indoor exposure underscores the critical significance of maintaining optimal indoor air quality (IAQ) to safeguard one's health. The primary impediment to attaining efficient regulation of Indoor Air Quality (IAQ) is the challenge of monitoring the IAQ parameters, particularly within the immediate vicinity of an individual's breathing space. Current heating, ventilation, and air conditioning systems lack the ability to rapidly predict and optimize the quality of indoor air. The objective of this study is to acquire the distribution features of indoor pollutants and precise indoor environment data in order to efficiently forecast and enhance the IAQ. To achieve this objective, a proposed surrogate model was developed using computational fluid dynamics (CFD). Notably, the Kriging surrogate model can rapidly predict IAQ while using a limited number of CFD runs. CFD are widely used as numerical simulation methods to obtain the accurate information. Surrogate models can rapidly forecast indoor environmental conditions using CFD simulation data simultaneously. Optimization algorithms can efficiently achieve desirable indoor ambient conditions, offering highly effective and intelligent control techniques for indoor atmospheric ventilation.

Low-cost IoT-enabled indoor air quality monitoring systems: A systematic review

Indoor air quality (IAQ) is a critical challenge much less controlled in comparison with outdoor air quality. Bad IAQ is related to significant health complications such as respiratory problems, heart disease, and cancer. Many people spend most of their days inside buildings and don’t have air quality monitoring systems. Therefore, the occupants don’t know when the space has a higher quantity of pollutants than recommended, saturating the environment, and compromising people’s health. This is a problem that can be addressed by using Internet of Things (IoT) technologies to develop monitoring systems that allow a greater number of possibilities regarding the storage and processing of data and access to information by the end user, assisting the decision-making process regarding the indoor air pollution problem. Real-time data can be compared to default values, alerting the user of that situation, and suggesting an action to decrease the air pollutants concentration. There already are multiple solutions involving IoT-based technologies, many of them using low-cost sensors. Those are analyzed in this systematic review. Furthermore, the COVID-19 pandemic pointed out the importance of IAQ monitoring to evaluate the risk of contamination. The microcontrollers, IAQ parameters, sensors, data storage and visualization methods used in monitoring systems have been analyzed. The results show that most of the studies store data in Cloud systems and use Web platforms for data consulting. However, sensor calibration and efficient energy consumption are challenges that still exist.

Indoor air quality analysis and sustainable practices

A constant supply of fresh air is vital for eliminating harmful bacteria and supporting the body's immune system against viruses and infections. Poor indoor air quality poses significant health risks, affecting human well-being and productivity. To address this issue, indoor air quality analysis is essential for enclosed spaces like homes, offices, and schools. According to the United States Environmental Protection Agency, indoor air can be up to 1000 times more polluted than outdoor air, with modern lifestyles leading to people spending 80-90% of their time indoors. Air pollution, as reported by the World Health Organization, causes 7 million deaths annually, primarily affecting the lungs and increasing the risk of cardiovascular diseases. Monitoring indoor air quality parameters such as CO2 and humidity levels is crucial for a healthy lifestyle. By utilizing sensors like MQ135 and DHT11, we can measure indoor pollutants and evaluate ventilation systems' effectiveness. Automation, such as using servo motors for ventilation, helps maintain safe indoor air quality levels. This approach can be implemented across various sectors, including schools, malls, and offices, to create healthier environments. Ultimately, indoor air quality analysis plays a vital role in enhancing indoor air quality and promoting occupant well-being.

Window Planning for Healthier Workplaces: IAQ Enhancement and Performance Benefits

Abstract: Indoor Air Quality (IAQ) significantly impacts the health and productivity of individuals within built environments. The complex interplay between building design elements, IAQ parameters, and their influence on human well-being has spurred extensive research endeavors. Understanding the effects of architectural configurations, window orientation, and integration of green spaces on IAQ remains crucial for optimizing indoor environments. This research aimed to investigate the impact of building design on IAQ and subsequently on human health and productivity. The study focused on analyzing IAQ parameters concerning various architectural settings, window orientations, and the inclusion of green spaces. The primary objectives were to assess IAQ variations across different spatial configurations, understand the influence of window orientation, and explore the effects of green elements on IAQ and occupant experiences.