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  • Published: 29 January 2020

A comprehensive review on indoor air quality monitoring systems for enhanced public health

  • Jagriti Saini   ORCID: orcid.org/0000-0001-6903-3722 1 ,
  • Maitreyee Dutta 1 &
  • Gonçalo Marques   ORCID: orcid.org/0000-0001-5834-6571 2  

Sustainable Environment Research volume  30 , Article number:  6 ( 2020 ) Cite this article

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Indoor air pollution (IAP) is a relevant area of concern for most developing countries as it has a direct impact on mortality and morbidity. Around 3 billion people throughout the world use coal and biomass (crop residues, wood, dung, and charcoal) as the primary source of domestic energy. Moreover, humans spend 80–90% of their routine time indoors, so indoor air quality (IAQ) leaves a direct impact on overall health and work efficiency. In this paper, the authors described the relationship between IAP exposure and associated risks. The main idea is to discuss the use of wireless technologies for the development of cyber-physical systems for real-time monitoring. Furthermore, it provides a critical review of microcontrollers used for system designing and challenges in the development of real-time monitoring systems. This paper also presents some new ideas and scopes in the field of IAQ monitoring for the researchers.

Introduction

With the ongoing improvements in quality of life, breathing environment has become an essential area of concern for researchers in the twenty-first century. Many studies confirm that indoor air is more deadly then outdoor air [ 1 ]. Nowadays, 90% of the rural households in the most developing countries and around 50% of the world’s population make use of unprocessed biomass for open fires and poorly functioning cooking stoves indoors. These deficient methods of cooking are responsible for indoor air pollution (IAP) and poor health of women as well as young children who are often exposed to such a polluted environment [ 2 ]. Biomass and coal smoke carry a wide range of harmful pollutants such as Particulate Matter (PM), Nitrogen Dioxide (NO 2 ), Carbon Monoxide (CO), Sulphur Oxides, polycyclic organic matter and formaldehyde [ 3 , 4 ]. Constant exposure to IAP due to the combustion of solid fuels is the common cause of several harmful diseases in developing countries. The list includes chronic obstructive pulmonary disease (COPD), otitis media, acute respiratory infections, tuberculosis, asthma, lung cancer, cancer of larynx and nasopharynx, low birth rate, perinatal conditions and severe eye diseases that can even cause blindness [ 5 , 6 ].

In the developed countries, the impact of modernization has brought a significant shift in indoor fire and heating systems from biomass fuels such as petroleum products and wood to electricity-based appliances. As per World Energy Outlook 2017 [ 7 ], even after several improvements in cooking measures, 1.3 billion people in developing Asia are expected to rely on biomass for cooking by the year 2030. As per current estimates, 2.8 million premature deaths are reported every year due to the use of coal and solid biomass for cooking [ 7 ]. The scenario becomes worse with the use of kerosene, candles and other harmful fuels for lighting [ 7 ]. Generally, the types of fuels being used for household needs can become cleaner and efficient only if people start moving up on the energy ladder. Note that, animal dung is the lowest level of this ladder, and the successive steps are built with crop residues, wood, charcoal, kerosene, gas, and electricity [ 8 ]. People throughout the world tend to move upward on this ladder as their socio-economic conditions allow them to improve their lifestyle, but reports reveal that poverty is the principal obstacle in using advanced and cleaner fuels. The slower development cycle in many parts of the world shows that biomass fuels will be utilized by poor households for decades ahead [ 9 ]. If we look at the stats provided by The Energy Progress Report 2019 [ 10 ], the global access to clean cooking was 58% in the year 2014, and it reached only 59% in the year 2016. The average growth rate was only 0.5% annually; unfortunately, it has been declining since the year 2010. With this annual rate of progress, it is not possible to meet the 2030 target of accessing cleaner fuels on universal level. In order to achieve the set goals, the annual growth rate must accelerate from 0.5 to 3% for the period 2016 to 2030. However, with the present stats, the chances are that almost 2.3 billion people worldwide will not have direct access to clean cooking in 2030. It means the health impacts of IAP will also persist; especially in the areas with inadequate ventilation arrangements [ 10 ].

Ventilation plays an essential role in the measurement of indoor air quality (IAQ). In case if proper ventilation arrangement is missing in building structures, the IAQ decreases and buildings become unhealthy to live. Studies reveal that IAP is observed as one of the major causes of increasing health issues associated with poor ventilation. As per a study conducted in few remote villages of Palpa district located in the western part of Nepal, the percentage deficit in ventilation is 80% as compared to the minimal rate suggested by the American Society of Heating, Refrigeration and Air Conditioning Engineers [ 11 ]. Another study report that poorly ventilation kitchens in Nepal have 100 times higher concentration of total suspended particles in comparison to the standard prescribed limit and it is due to excessive smoke generation in the premises [ 12 ]. Parajuli et al. [ 11 ] also monitored the impact of traditional cooking systems and improved cooking systems in the village houses. The estimated reduction of CO concentration and PM 2.5 concentration was 30 and 39% respectively, with the use of improved cooking systems as compared to traditional cooking systems. Generally, the occupational and educational stats along with housing conditions in urban areas are relatively better when compared to the rural areas. These conditions have a direct relationship with the choice of fuel for household needs and consequently have a significant impact on IAQ.

Reports reveal that poor IAQ is the second major factor for the higher mortality rate in India. It causes around 1.3 million deaths per year in the country. It is observed that out of 70% of the rural population in India [ 13 ], almost 80% of the people rely on biomass fuel to fulfill their household requirements [ 14 ]. The estimated number of people using harmful fuels for cooking in India is highlighted in Fig.  1 [ 15 ]. It means that the largest population of the country lacks access to cleaner and efficient sources of fuel for cooking needs. Kerosene and biomass cooking fuels are also the principal causes of stillbirth in developing countries. Studies reveal that around 12% of stillbirths can be easily prevented by using cleaner cooking fuel for the household needs in India. Similar studies conducted in other developing countries such as Bangladesh, Nepal, Kenya, and Peru show that IAP is causing severe health hazards. Hence it has become necessary to address the challenges, especially for indoor cooking in the rural sectors. Lack of knowledge and understanding of the benefits of cleaner cooking solutions is the principal cause of adverse health consequences. It is essential to design some efficient and affordable household cooking solutions over traditional stoves, and it can be done only after studying behavioral patterns of the low-income population in the country.

figure 1

Stats about people using fuel for cooking in India [ 15 ]

The economic enhancements contribute to reducing IAP caused by various biomass fuels. However, the modern lifestyle is also leading to poor indoor environmental quality. With the improvement in the standard of living, most people are using indoor heating and cooling systems instead of natural ventilation systems [ 4 ]. This scenario has increased the cases of Sick Building Syndrome (SBS) somewhere around 30 to 200% [ 16 ]. Studies reveal that factors affecting indoor environment include the rate of air exchange, humidity, temperature, ventilation, air movement, biological pollutants, particle pollutants, and gaseous pollutants [ 17 ]. Buildings currently constructed are more airtight and make use of advanced insulation materials that help to reduce the loss of energy. However, the air conditioning systems and the latest building envelope also cause a reduction in the circulation of fresh air. Meanwhile, the increasing consumption of chemical products and synthetic materials in indoor environments has increased the presence of several Volatile Organic Compounds (VOC). It is one of the principal causes of hypersensitivity [ 18 ]. So, it is fair to say that we are still not safe from hazards associated with IAP.

To deal with the increased mortality and morbidity rate due to IAP, numerous researchers are developing indoor environmental quality monitoring systems. Most of the people spend 80 to 90% of their time indoors either at home or in the offices. Thus, it is necessary to take immediate steps to improve the quality of indoor air. The idea is to create some healthy solutions that can contribute to a comfortable living environment while reducing the chances of the occurrence of severe diseases. This paper puts some light in the direction of efforts made by early researchers to deal with the challenges associated with IAP.

The remaining parts of this review paper are organized below in three different sections, where section of “Indoor air quality and public health” describes the real-time cases of health impacts of IAP in developing countries along with the effect of various pollutants on public health. Section of “indoor air quality monitoring systems” presents an overview of some IAP monitoring systems developed in the past few years. The following section (Results/Discussion) provides a critical analysis of existing systems, along with the advantage and disadvantages of various technologies and sensor networks. Finally, the brief conclusion with future scopes of this study is given in the last section. This paper highlights the background of IAQ, primarily focusing on developing countries along with the potential ideas proposed for monitoring systems by different researchers. It is expected to guide future researchers to focus on new developments by considering the pros and cons of existing systems.

Indoor air quality and public health

Iaq and rural health.

Several studies have been reported in India regarding the harmful impacts of IAP. In a nationally representative case-control study published in the year 2010 [ 19 ], after adjusting all essential living conditions and demographic factors, excessive exposure to solid fuel increased the number of deaths among children in the age group of 1 to 4. It is because these infants are used to spend more time indoors with their mothers. The prevalence ratio presented in this study for girls was 1.33; 95% Confidence Interval (CI): 1.12–1.58 and for boys: 1.30; 95% CI: 1.08–1.56. Solid fuel was also reported as the most significant reason behind many cases of non-fatal pneumonia with a prevalence ratio of 1.94; 95% CI: 1.13–3.33 for girls and 1.54; 95% CI: 1.01–2.35 for boys [ 19 ].

Another case study [ 20 ] reveals that routine exposure to fuel other than liquid petroleum gas is directly linked to acute infections in the lower respiratory tract. The adjusted Odds Ratio = 4.73; 95% CI: 1.67–13.45, and these stats were obtained even after adjusting the rest of the risk factors. According to this study, out of the total number of children affected with acute lower respiratory tract infection; almost 24.8% were affected by pneumonia, 45.5% suffered from severe pneumonia whereas, the other 29.7% were observed to have a severe disease [ 20 ]. Furthermore, biomass fuel usage in India is also associated with prolonged nasal mucociliary clearance time. It was recorded to be 766 ± 378 s, whereas this time is reported to be 545 ± 216 s in the case of clean fuel users [ 21 ]. If we look at 2018 Environmental Performance Index Results, India ranked 177th among 180 countries; whereas, other developing countries like Nepal and Bangladesh ranked 176th and 179th respectively [ 22 ]. These stats reveal that some serious efforts are required to improve building health in most developing countries.

IAQ and potential pollutants

IAQ is determined by the concentration of several pollutants such as particle matter, primary, and secondary gaseous pollutants. Studies reveal that a higher number of PM in the urban indoor environment is observed to be of ultra-fine size. Typically, smaller than 0.1 μm, whereas the particles with a size larger than 0.1 μm are observed to be present in a short amount, somewhere below the 10% concentration level [ 23 , 24 ].

The list of primary gaseous pollutants includes radon, O 3 , Nitric oxides (NOx), Sulphur dioxide (SO 2 ), CO, Diatomic carbon, and VOCs. Within the past few years, the usage of chemical products in indoor environments has been increased drastically. These chemical materials generate several hazardous chemical pollutants under room temperature including VOCs. These compounds can cause several health issues with symptoms such as nausea, headache, dizziness, tiredness, nose, eye, and throat irritations [ 25 ]. Ground-level ozone is a colorless gas that acts as an integral component of the atmosphere and is the leading cause of several health diseases related to the respiratory system [ 25 ]. Common symptoms of CO poisoning include vomiting, nausea, weakness, dizziness, headache, and loss of consciousness. SO 2 is a highly reactive and colorless gas that plays an essential role in the atmosphere. It is harmful to human health and the patients that are already suffering from lung disease, older people, children, as well as those who face regular exposure to SO, are at higher risks of developing lung diseases and skin related problems. Nitrogen oxide is the leading cause of several infections associated with the respiratory system. Some of the most commonly observed symptoms of NO 2 toxicity include wheezing, coughing, bronchospasm, fever, diaphoresis, chest pain, dyspnea, headache, throat irritations, and pulmonary edema [ 26 ]. CO 2 is a by-product of combustion and is also produced by the metabolic process of living organisms. Several studies reveal that a moderate concentration of CO 2 in indoor air can cause fatigue and headaches, whereas higher levels lead to vomiting, dizziness, and nausea. Loss of concentration can also occur at too high levels of CO 2 [ 27 ].

Higher concentration of VOCs in buildings can irritate skin, throat, nose, and eyes. Medical health experts also report a broader set of illnesses due to VOCs, such as headaches, respiratory symptoms, fatigue and SBS [ 28 ].

The mixture of various pollutants present in the indoor air can cause a chain of chemical reactions, and it further generates secondary pollutants in the environment. Studies reveal that these secondary pollutants are more harmful when compared to the primary ones [ 29 , 30 ]. Indoor secondary pollutants (such as ozone, NO 2 , sulphur trioxide) are observed to cause significant discomfort and a harmful impact on human health. Moreover, they are challenging to measure and predict due to the complexities involved in their composition [ 27 ]. Volatile, non-volatile, and non-biological agents cause a harmful impact on indoor air while degrading the overall quality of the environment. The list of biological organisms includes dust mites, pollen, mildew, fungi, molds, bacteria, and many insects, animal dander, anthropoid, infectious agents, pollen, mycotoxins, infectious agents, and animal saliva. The dangerous combination of several indoor air allergens with specific outdoor allergens such as molds, grass pollen, animal allergens, cockroaches, and smoking cause risks of allergic sensitization, asthma and many other respiratory diseases [ 31 ]. The list of major indoor air pollutants, sources of emission, and associated medical health consequences is shown in Table  1 .

Indoor air quality monitoring (IAQM) systems

Currently, the increasing health issues due to IAP are an essential matter of discussion for researchers worldwide. Some professionals utilized advanced sensor networks and communication technologies to propose IAQ monitoring systems for the enhanced living environment. As researchers are actively working in this field to improve building health, it is difficult to review all existing and proposed IAQ monitoring systems in this paper. Nonetheless, this section includes studies based on the most prominent IAP parameters. As automatic alert systems are need of the hour in our busy schedules, we have preferably picked monitoring systems that propose online access to recorded environmental factors or generate SMS based alerts. Although several techniques have been invented for real-time monitoring, the preference to be reviewed was given to Wireless Sensor Network (WSN) and Internet of Things (IoT) based models due to their rising scope in the Industry 4.0 revolution.

Alhmiedat and Samara [ 32 ] developed a low-cost ZigBee sensor network architecture to monitor IAQ in real-time. It is possible to install four sensor nodes in the indoor environment and collect data for more than four weeks. The environmental data were further transferred for analysis via a ZigBee communication protocol. Authors of this paper analyzed CO 2 , benzene, NOx, and ammonia for IAQ assessment at the time of cooking in the kitchen, while other sensors collected desired input from the bedroom, living room and office area. It provides real-time monitoring of all factors contributing to indoor air; however, few developments to this system can be still made by reducing power consumption and improving the accuracy of monitored parameters.

Wu et al. [ 33 ] worked on mobile microscopy and machine learning methods to perform accurate quantification and impact analysis of PM. The authors demonstrated a cost-effective and portable PM imaging, quantification and sizing model named C-Air, and the results were displayed on a mobile-based app. A remote server was used for automated processing of essential digital holographic microscope images that ensues accurate PM measurements. This system was capable of providing valuable statistics about density distribution and particle size with the sizing accuracy of approximately 93%. C-Air can be customized to detect specific air particles such as mold and pollens. The performance of C-Air was tested for indoor as well as outdoor air environments.

Zampolli et al. [ 34 ] developed a low-cost model with an electronic nose based solid-state sensor array for monitoring IAQ. By using a combination of advanced pattern recognition techniques and optimized gas sensor array, researchers targeted the quantification of NOx, CO, along with VOCs and relative humidity (RH). The performance of the electronic nose was analyzed in real operating conditions where NO 2 concentrations at 20 ppb and CO at 5 ppm were monitored continuously for at least 45 d. This approach helped to identify the presence of individual pollutants along with the mixture of different contaminants in the test environment. This system was found feasible enough to detect NO 2 and CO levels in indoor air, and these results were further used to manage the appropriate usage of heating, ventilation, and air conditioning (HVAC) systems in the indoor environment without disturbing the air quality.

Kim et al. [ 35 ] focused on seven gases (CO 2 , VOCs, SO 2 , NOx, CO, PM, and ozone) to test IAQ in real-time. The experiments were conducted in three different settings: big church, medium size classroom, and small size living room to test the impact of different factors on IAQ. Researchers concluded that so many factors contribute to altering the quality of indoor air. Some of these are wind, location, airflow, the density of people and room size. However, it was found that gas sensors consume lots of power, so it is important to apply critical thinking for the selection of appropriate sensor nodes. Future researchers are also advised to work on environmental settings and sensor characteristics to ensure reliable calibration of the system to obtain accurate results.

Yu and Lin [ 36 ] constructed an intelligent wireless sensing and control system to deal with health issues caused by IAP. The system is made up of three different parts: 1) Data acquisition that helps in obtaining values about environmental indicators such as CO 2 concentration, RH, and temperature through polling mechanism; 2) Data analysis, responsible for collecting data and interfacing with the AutoRegressive Integrated Moving Average (ARIMA) prediction model to analyze air quality trends in the premises; and 3) Data feedback to trigger necessary actions based on fuzzy results. It may send a warning message or may control the speed of the fan automatically. Each sensor node in this hardware architecture is powered by the IEEE1451.4 standard, and the communication channel is established by ZigBee technology. The software architecture is precisely separated into three different sections where 1) Data monitoring agent creates a bridge between software and hardware, 2) Air quality analyzing agent takes care of air quality trends and triggers relevant actions for higher pollution levels; and 3) Application agent provides services for data display automatic control and alerts. The final ARIMA prediction model based IAQ monitoring system was deployed in the real-time environment at nine different areas of Taiwan. It included Environmental Protection Administration, university, and elementary schools. The performance of the system was further tested using two tests: Validation of the accuracy of the prediction model and validation of energy-saving performance. The system used to make useful decisions about ventilation equipment in the premises depending upon the threshold level of air quality parameters.

Pillai et al. [ 37 ] implemented a sensor network for IAQ monitoring using the Controller Area Network (CAN) interface. In order to run the experiment on a real-time basis, the sensors were distributed in a specific area, and a serial standard bus communication network was used for information exchange between them. CAN is a specially designed high integrity serial bus protocol that works on high speed by supporting information exchange rate between 20 kbit s − 1 to 1 Mbit s − 1 . Using CAN, researchers were able to develop a highly reliable, efficient, and economical communication link between display nodes and sensor nodes. The hardware tests provided highly accurate monitoring for IAQ with short processing time.

Abraham and Li [ 38 ] proposed a cost-effective WSN system for monitoring IAQ. The system was designed using low-cost micro gas sensors (CO, VOC, and CO 2 ) and use the Arduino microcontroller as the processing unit. The mesh network for this monitoring system was developed using the ZigBee module that promised low power, low cost and wireless solution for communication. Data calibration for micro gas sensor networks was further performed using Least-Square Method. It helped researchers to study the current status of IAQ while collecting valuable data for the long-term impacts of bad air quality on human health. The proposed system was also compared with standard GrayWolf System, and it was observed to be independent of humidity and temperature variations.

Cheng et al. [ 39 ] developed AirCloud that is a cloud-based air quality monitoring system designed to serve low cost personal and pervasive needs. The authors worked on two types of Internet-connected PM monitors (focused around PM 2.5 levels) that were named as mini air quality monitoring (AQM) and AQM. The monitoring process was based entirely upon the mechanical structures that were designed for maintaining optimal airflow. On the cloud side, the authors created an air quality analytics engine to learn and develop models of measured air quality with the help of sensors. This cloud-based engine helped in the calibration of mini AQMs and AQMs on a real-time basis while inferring PM 2.5 concentrations. This system provided relevant accuracies at lower cost ensuring dense coverage ability.

Kang and Hwang [ 40 ] introduced an air quality monitoring system to test the relevance of the Comprehensive Air Quality Index for accurate IAQ assessment. The authors also proposed a real-time Comprehensive Indoor Air Quality Indicator (CIAQI) system that can work effectively against all dynamic changes and is quite efficient in processing ability along with memory overhead. In order to develop the experimental setup for realistic indoor air environment monitoring, the authors used VOC, PM 10 , CO, temperature and humidity sensors. The authors also compared the proposed system performance with absolute concentration of all considered pollutants used for ambient air quality index (AQI) with Simple Moving Average scheme and observed that the proposed CIAQI system is more adaptive to real-time changes in the IAQ. Also, this system utilized small memory; therefore, it was considered as an economical solution for the IoT based air quality monitoring.

Bhattacharya et al. [ 41 ] developed a wireless system for monitoring IAQ by working on a few essential parameters such as humidity, temperature, gaseous pollutants, and PM. This system determines indoor environment health in terms of the AQI and at the same time gives real-time inputs to control HVAC systems. In order to serve the smart building applications, authors have also developed a toolkit that measures live air quality data in the form of graphs and numbers.

Ahn et al. [ 42 ] designed a microchip by utilizing six atmospheric sensors: VOCs, light quantity, humidity, temperature, fine dust, and CO 2 . The atmospheric changes were estimated using deep learning models. Performance of the proposed Gated Recurrent Network (GRU) model was also compared with other models such as Long Short-Term Memory (LSTM) networks and linear regression, where the proposed system presented better performance with higher accuracy of 85% over a variety of parameter settings.

Pitarma et al. [ 43 ] developed a low-cost IAQ monitoring unit using a WSN system in combination with microsensors, XBee modules, and Arduino. They worked on five major IAP parameters: luminosity, CO 2 , CO, humidity and air temperature while performing real-time monitoring on a web portal. The wireless communication network between sensors and gateway was established with the XBee module utilizing ZigBee networking protocol and IEEE802.15.4 radio standards. Sensors involved in real-time measurement were sensor SHT10 for RH and temperature; MQ7 for CO, T6615 sensor for CO 2 measurement and LDR5 mm for light detection. The web interface was designed using MySQL database and Personal Home Page (PHP). The prime goal to design this system was to help users get instant updates about exposure risks in the living environment.

Benammar et al. [ 44 ] designed an end to end IAQM system using WSN technology. It was focused around the measurement of RH, ambient temperature, Cl 2 , O 3 , NO 2 , SO 2 , CO, and CO 2 . The sensor nodes were made to communicate to the gateway via XBee PRO radio modules. The sensor nodes in this study include a set of calibrated sensor units, a data storage unit named Waspmote, and sensor interface board known as Gas Pro sensor board. The prime role of the gateway in this study was to process the IAQ data collected from target sites and perform reliable dissemination via a web server. This system was adapted to open source IoT web server platform, named Emoncms to ensure long-term storage as well as live monitoring of IAQM data. Seamless integration of smart mobile standards, WSN, and many other sensing technologies is performed to design the ultimate scalable smart system to monitor IAP. In order to meet the power requirements of the system, authors also designed separate battery units for the sensor network.

Saad et al. [ 45 ] created a system to monitor various environmental parameters that are directly related to air quality. They focused on RH, temperature, PM, and gaseous pollutants that have a direct impact on human health. A WSN was used to measure data from the target location, and it was transferred to the base station via the WSN node. A self-developed server program on the computer system used to access and process this data to analyze IAQ on a real-time basis.

Tiele et al. [ 46 ] focused on the design and development of a portable and low-cost indoor environment monitoring system. This study was performed on a few essential parameters of indoor air such as sound levels, illuminance, CO, CO 2 , VOCs, PM 10 , PM 2.5 , RH, and temperature. The experiments were conducted in both indoor work environments and outdoors. The authors defined an Indoor Environment Quality (IEQ) index to estimate the overall percentage of IEQ.

Moreno-Rangel et al. [ 47 ] presented a study to assess usability, accuracy, and the precision of low-cost IAQ monitor within a residential building. After analyzing the cost and complexity related issues associated with existing scientific solutions for IAQ monitoring, the authors proposed a reliable and low-cost system for households. They focused on a few essential parameters, such as PM 2.5 , CO 2 , VOCs, RH, and temperature. All sensors were calibrated before installation to ensure an adequate measurement. The collected data was analyzed using FOOBOT monitors based on the percentage of time the pollutant levels crossed the threshold levels set by World Health Organization. In order to enhance the accuracy of the measurement, authors in this study used IBM SPSS Statistics to perform statistical analysis.

Idrees et al. [ 48 ] closely observed the challenges associated with IAP and developed an Arduino based platform for real-time IAQ monitoring systems. They initiated steps toward the detailed investigation of factors such as computational complexity, infrastructure, issues, and procedures for efficient designing. The prototype for the proposed real-time IAQ monitoring system was designed using the IBM Watson IoT platform and Arduino board. The authors worked on eight parameters that have a considerable impact on human health in the building environment. The list includes RH, temperature, O 3 , SO 2 , NO 2 , CO, PM 2.5 , and PM 10 . The significant advantage of this system was its ability to reduce the computational burden of the sensing nodes by almost 70%, leading to longer battery life. In order to ensure higher accuracy for measurements, authors used standard calibration procedures on sensor networks, and a data transmission strategy was used to minimize the power consumption along with redundant network traffic. The three most essential layers of the proposed monitoring system were sensing layer, edge computing layer, and application layer. This model reported a reduction of 23% in the overall power consumption, and the performance was validated by setting the system in different environments.

Sivasankari et al. [ 49 ] proposed an IoT based system to monitor IAQ, and the analysis was performed using a Raspberry Pi model. The parameters included in this study were RH, temperature, NO 2 , CO, and concentrations of smoke. The measurements were done using MQ series sensors, Mics 2714 NO 2 sensor, LM-35, and DHT11 sensor. An analog to digital converter was also added to the system so that sensors can be directly interfaced with the Raspberry pi module via eight different channels. This system was used to generate an alarm for indicating a high concentration of emissions, such as a warning for the air pollution rate in the premises.

Arroyo et al. [ 50 ] presented an air quality measurement system made of a distributed sensor network and cloud-based WSN system. Low power ZigBee motes were used for collecting field data, and an optimized cloud computing system was implemented for processing, monitoring, storing, and visualizing received data. This laboratory study was based on the measurement of VOCs, including xylene, ethylbenzene, toluene, and benzene. Multilayer perceptron, principle component analysis, support vector machine, and backpropagation learning algorithm were used at the data processing stage.

This section summarizes the review of IAP monitoring systems that are proposed by early researchers from different countries in the past few years. The main idea is to discuss potential techniques, architectures, and configurations that are already used by researchers. Reliable and efficient monitoring systems can be used in urban as well as rural areas to monitor the IAP and its impact on residents. It is believed that instant alerts can guide people to make proper ventilation arrangements by opening windows or doors in the kitchen; such systems are more useful in homes having traditional cooking systems, and inadequate ventilation arrangements. The results and discussion section further provide a detailed analysis of these studies while covering the strengths, weaknesses of the existing IAQ monitoring systems along with future scopes to guide future researchers.

Results and discussion

Wsn based systems.

The trends in the development of the IAQ monitoring system reveal that most of the researchers in the past few years have worked on WSN based designs with ZigBee as the most reliable communication protocol. The ATmega microcontroller manages the real-time data collection; however, Raspberry Pi is another common choice for setting up a sensor network in the target environment. WSN is an Ad Hoc Network, where sensor networks consume immense energy while transmitting data in multiple hops. The time taken by sensors to send a signal to the monitoring unit was observed to be considerably high. In such situations, researchers needed to work on battery power management to improve overall system performance. However, only a few researchers, such as Yu and Lin [ 36 ] were successful in implementing energy-saving and cost-saving monitoring systems using WSN architecture. Trends reveal that most of the WSN based IAQ monitoring systems use web servers as data access platforms; it demands additional efforts to generate real-time alerts on user smartphones to prevent hazardous conditions. Table  2 highlights the summary of WSN based IAQ monitoring systems.

IoT based systems

Considering the battery life expectancy and reliable single-hop communication abilities, IoT monitoring systems are believed to be the most reliable solutions for IAQ measurement. With lower latencies and lesser power consumption, these systems also demand lesser efforts for maintenance. IoT based real-time monitoring systems are known as smart systems; consequently, most of the researchers and industrial manufacturers are more attracted to this architecture. Experts reveal that the IoT system can monitor a large number of parameters, even without compromising system performance. Studies carried by Idrees et al. [ 48 ] and Sivasankari et al. [ 49 ] gave a new edge to the IAQ monitoring systems with impactful IoT architecture design. However, very few researchers in the past few years have worked on prediction systems in the field of IAQ monitoring. Studies reveal that it is much easier to combine IoT monitoring systems to machine learning and deep learning networks to initiate reliable prediction decisions. It is a significant area of work for new age researchers. Table  3 presents a summary of IoT based IAQ monitoring systems.

Other technologies

Some researchers also worked on architectures other than WSN and IoT, but few parameters reveal the low performance of such systems as compared to the potential of IoT systems for real-time monitoring. The most significant disadvantage of the C-Air platform presented by Wu et al. [ 33 ] was that this study was limited to PM levels only; but in the real world, IAQ is affected by many other pollutants as well. Zampolli et al. [ 34 ] tried working on multiple pollutants, but the study was limited to the simulation environment only; the practical implementation of such systems is the real challenge. Moreover, these researchers worked on low-cost sensors where calibration is a significant challenge, and it leads to a lack of performance for the overall design. Similar constraints were found with the approach followed by Pillai et al. [ 37 ], where the system was studied on breadboards in a controlled lab environment only. Cheng et al. [ 39 ] tried to implement a prediction model with CAN interface, but the study was again limited to PM levels only; the impact of other pollutants was not considered in this study. Moreno-Rangel et al. [ 47 ] presented a valuable study with FOOBOT monitors, and they considered multiple IAQ parameters for the real-time analysis, but the sensor calibration was again a relevant challenge to ensure desired performance. Table  4 presents a summary of IAQ monitoring systems based on architectures other than WSN and IoT.

Discussion and critical analysis

The primary requirement at present is to perform real-time monitoring of IAQ parameters and generate alerts to the building occupants to avoid hazardous conditions. The IoT approach has great potential in this direction to ensure lesser power consumption, negligible time delays, and has a better ability to interact with the physical world.

One of the prime concerns in the development of IAQ systems is the higher cost and massive power consumption of sensor nodes. If we consider the real-time applications of IAQ systems, the sensor units are usually installed in an industrial environment, inside homes, offices, and outdoor areas as well. However, in all these cases, the design of the sensor unit demands more focus on size, design cost, power consumption, communication protocol, and performance dependence on temperature and humidity variations. Sensor calibration is currently the main challenge in front of future researchers to ensure accurate real-time monitoring. Although Metal Oxide Semiconductor sensors are cheaper when compared to the optical and electromechanical sensors (some examples are TGS 2442 and TGS416), they work on the resistive heating; hence, consume loads of energy from limited battery unit of wireless motes. As a result, it reduces the overall lifetime of the network. A considerable solution to solve this problem is placing motes (a specific type of sensor node that can collect, process information and can communicate with other nodes in the network) in sleep mode when they are not working actively in the system. Some studies also reveal that a high-quality micro gas sensor can perform better in variable humidity and temperature conditions. One advanced solution to air quality monitoring is Mobile Sensing System for IAQ – personalized mobile sensing system that is gaining popularity due to the portable, energy-efficient and inexpensive design. Most of the researchers have used ZigBee to establish a communication network between sensor nodes and controller unit, but the prime disadvantages of ZigBee modules are short communication range and low network stability with high maintenance cost. The highly efficient IoT systems bring new scope to this field. By using IoT architecture and the Raspberry Pi microcontroller, which has in-built Wi-Fi communication features ensure fast data transfer. Note that the most used Arduino boards do not offer direct network connectivity. Therefore, users need to use additional modules for internet accessibility. One commonly used Wi-Fi module for Arduino boards is ESP8266 chip, but it needs an external converter for 5–3 logic shifting since most Arduino microcontrollers use 5 V operating voltage. Moreover, it leads to additional cost and energy consumption. Furthermore, Raspberry Pi 3 has more processing power than Arduino Uno as the clock speed for the former is 1.2 GHz, whereas later works on 16 MHz.

Several methods for real-time IAQ monitoring are available in the literature. Furthermore, the presented methods provide practical solutions to improve occupational health and contribute to enhanced living environments considering numerous technical challenges. However, few improvements in the system performance are still required to ensure a reliable solution. By using an IAQ monitoring system, the manager can understand the IAQ behavior of the environment and plan interventions to avoid unhealthy situations. Therefore, the development of enhanced IAQ monitoring systems will address critical health challenges in today’s world.

This section describes the weaknesses and strengths of the existing monitoring systems while describing the potential of available technologies and architectures. This in-depth review can guide new researchers to pick the most relevant topics for research in the future so that the quality of the living environment can be improved by inventing new methods and techniques.

Conclusions

In this review, the authors provide details about how various factors such as VOCs, PM 10 , PM 2.5 , CO, SO 2 , NO, O 3 , temperature, and RH affect IAQ. Furthermore, authors have highlighted the technical aspects of the studies performed by early researchers in this field. Trends reveal that most of the researchers till now have worked upon WSN and IoT architectures to study associated factors with IAQ and provide mobile computing software for data consulting.

Instead of working within a controlled laboratory environment or on simulation systems, researchers need to implement real-time IAQ monitoring systems in real scenarios. The development of prediction systems is another primary concern for future studies because it is easier to control the adverse impact of indoor air pollutants when we are aware of future happenings. Deep learning models such as LSTM and GRU can be utilized to design the prediction systems, and the instant alerts about variation in indoor pollutant levels above the threshold limit must be sent via SMS or email to the smartphones. Note that, LSTM is the enhanced strategy to traditional Recurrent Neural Network, whereas GRU is the further extension to LSTM with forget and update gates. These models work with parameterized functions that have a direct impact on ideal parameters of the data; hence lead to better prediction. Mobile app-based systems analysis is also an essential part of the design. This field has considerable scope for development, and future researchers need to work on in-depth design solutions by combining IoT and deep learning models to come up with cost-effective, accurate, and reliable IAQ management systems. However, the research should not be limited to the industrial environment and cities. Only slightly suitable systems must be designed for the village areas where people suffer more due to their excessive exposure to solid fuels. The development of such systems can lead to an incredible contribution to the medical health department as well.

The main areas of work for future researchers can be summarized as:

Developing an IAQ monitoring system that can work efficiently in real-time conditions, instead of simulated or laboratory-based environments.

Consider specific requirements of rural areas and design a cost-effective IAQ monitoring system to provide a safe solution for enhanced living environments.

Work on IAQ prediction systems so that appropriate preventive measures can be followed on time.

Designing a power-efficient and robust system for severe monitoring conditions in the urban as well as rural areas.

Developing more efficient systems that can generate instant alerts to the users via email and SMS whenever IAP crosses certain threshold levels.

Develop mobile app-based monitoring systems that can be operated by non-tech savvy people as well.

Developing quick alert systems with possible preventive measures like switch on/off air conditioner, open/close windows, and check gas leakage to guide people towards healthy solutions with a variety of specific pollutants in the living environment.

In conclusion, the monitoring solutions/architectures proposed to address the IAQ should incorporate artificial intelligence to predict unhealthy situations for the enhanced living environment and occupational health.

Availability of data and materials

No such sources of data or materials are used for this study.

Cincinelli A, Martellini T. Indoor air quality and health. Int J Environ Res Pu. 2017;14:1286.

Google Scholar  

Arungu-Olende S. Rural energy. Nat Resour Forum. 1984;8:117–26.

de Koning HW, Smith KR, Last JM. Biomass fuel combustion and health. B World Health Organ. 1985;63:11–26.

Smith KR, Samet JM, Romieu I, Bruce N. Indoor air pollution in developing countries and acute lower respiratory infections in children. Thorax. 2000;55:518–32.

Bruce N, Perez-Padilla R, Albalak R. Indoor air pollution in developing countries: a major environmental and public health challenge. B World Health Organ. 2000;78:1078–92.

Ezzati M, Kammen DM. Quantifying the effects of exposure to indoor air pollution from biomass combustion on acute respiratory infections in developing countries. Environ Health Perspect. 2001;109:481–8.

IEA. World Energy Outlook 2017. Paris: International Energy Agency; 2017.

Smith KR, Apte MG, Ma YQ, Wongsekiarttirat W, Kulkarni A. Air pollution and the energy ladder in Asian cities. Energy. 1994;19:587–600.

WHO. Fuel for life: household energy and health. Geneva: World Health Organization; 2006.

IEA, IRENA, UNSD, WB, WHO. Tracking SDG 7: the energy Progress report 2019. Washington: International Bank for Reconstruction and Development/The World Bank; 2019.

Parajuli I, Lee H, Shrestha KR. Indoor air quality and ventilation assessment of rural mountainous households of Nepal. Int J Sustain Built Environ. 2016;5:301–11.

Dhakal S. Climate change and cities: the making of a climate friendly future. In: Droege P, editor. Urban energy transition. Amesterdan: Elsevier; 2008. p. 173–92.

Lawrence A, Taneja A. An investigation of indoor air quality in rural residential houses in India – a case study. Indoor Built Environ. 2005;14:321–9.

Sehgal M, Rizwan SA, Krishnan A. Disease burden due to biomass cooking-fuel-related household air pollution among women in India. Glob Health Action. 2014;7:25326.

Ritchie H, Roser M. Indoor air pollution. 2019. OurWorldInData.org .

Seppanen O, Fisk WJ. Association of ventilation system type with SBS symptoms in office workers. Indoor Air. 2002;12:98–112.

Graudenz GS, Oliveira CH, Tribess A, Mendes C, Latorre MRDO, Kalil J. Association of air-conditioning with respiratory symptoms in office workers in tropical climate. Indoor Air. 2005;15:62–6.

Wang Z, Bai Z, Yu H, Zhang J, Zhu T. Regulatory standards related to building energy conservation and indoor-air-quality during rapid urbanization in China. Energ Buildings. 2004;36:1299–308.

Bassani DG, Jha P, Dhingra N, Kumar R. Child mortality from solid-fuel use in India: a nationally-representative case-control study. BMC Public Health. 2010;10:491.

Ramesh Bhat Y, Manjunath N, Sanjay D, Dhanya Y. Association of indoor air pollution with acute lower respiratory tract infections in children under 5 years of age. Paediatr Int Child H. 2012;32:132–5.

Priscilla J, Padmavathi R, Ghosh S, Paul P, Ramadoss S, Balakrishnan K, et al. Evaluation of mucociliary clearance among women using biomass and clean fuel in a periurban area of Chennai: a preliminary study. Lung India. 2011;28:30–3.

Wendling ZA, Emerson JW, Esty DC, Levy MA, de Sherbinin A, et al. 2018 environmental performance index. New Haven: Yale Center for Environmental Law & Policy; 2018.

Thomas S, Morawska L. Size-selected particles in an urban atmosphere of Brisbane, Australia. Atmos Environ. 2002;36:4277–88.

Gramotnev G, Ristovski Z. Experimental investigation of ultra-fine particle size distribution near a busy road. Atmos Environ. 2004;38:1767–76.

Gorai AK, Tuluri F, Tchounwou PB. A GIS based approach for assessing the association between air pollution and asthma in New York state, USA. Int J Env Res Pub He. 2014;11:4845–69.

Hesterberg TW, Bunn WB, McClellan RO, Hamade AK, Long CM, Valberg PA. Critical review of the human data on short-term nitrogen dioxide (NO 2 ) exposures: evidence for NO 2 NO-effect levels. Crit Rev Toxicol. 2009;39:743–81.

Yu BF, Hu ZB, Liu M, Yang HL, Kong QX, Liu YH. Review of research on air-conditioning systems and indoor air quality control for human health. Int J Refrig. 2009;32:3–20.

Yang X, Chen Q, Zhang JS, An Y, Zeng J, Shaw CY. A mass transfer model for simulating VOC sorption on building materials. Atmos Environ. 2001;35:1291–9.

Wainman T, Zhang JF, Weschler CJ, Lioy PJ. Ozone and limonene in indoor air: a source of submicron particle exposure. Environ Health Perspect. 2000;108:1139–45.

Rohr AC, Weschler CJ, Koutrakis P, Spengler JD. Generation and quantification of ultrafine particles through terpene/ozone reaction in a chamber setting. Aerosol Sci Technol. 2003;37:65–78.

Nolte H, Backer V, Porsbjerg C. Environmental factors as a cause for the increase in allergic disease. Ann Allerg Asthma Im. 2001;87:7–11.

Alhmiedat T, Samara G. A low cost ZigBee sensor network architecture for indoor air quality monitoring. Intl J Comp Sci Inf Secur. 2017;15:140–4.

Wu YC, Shiledar A, Li YC, Wong J, Feng S, Chen X, et al. Air quality monitoring using mobile microscopy and machine learning. Light Sci Appl. 2017;6:e17046.

Zampolli S, Elmi I, Ahmed F, Passini M, Cardinali GC, Nicoletti S, et al. An electronic nose based on solid state sensor arrays for low-cost indoor air quality monitoring applications. Sensor Actuat B-Chem. 2004;101:39–46.

Kim JY, Chu CH, Shin SM. ISSAQ: an integrated sensing systems for real-time indoor air quality monitoring. IEEE Sensors J. 2014;14:4230–44.

Yu TC, Lin CC. An intelligent wireless sensing and control system to improve indoor air quality: monitoring, prediction, and preaction. Int J Distrib Sens N. 2015;2015:140978.

Pillai MA, Veerasingam S, Yashwanth SD. Implementation of sensor network for indoor air quality monitoring using CAN interface. In: 2010 International Conference on Advances in Computer Engineering. Bangalore. 2010:20–1.

Abraham S, Li X. A cost-effective wireless sensor network system for indoor air quality monitoring applications. Procedia Comput Sci. 2014;34:165–71.

Cheng Y, Li X, Li Z, Jiang S, Li Y, Jia J, et al. AirCloud: a cloud-based air-quality monitoring system for everyone. In: 12th ACM Conference on Embedded Network Sensor Systems. Memphis; 2014. p. 3–5.

Kang J, Hwang KI. A comprehensive real-time indoor air-quality level indicator. Sustainability-Basel. 2016;8:881.

Bhattacharya S, Sridevi S, Pitchiah R. Indoor air quality monitoring using wireless sensor network. In: 2012 Sixth International Conference on Sensing Technology. Kolkata; 2012. p. 18–21.

Ahn J, Shin D, Kim K, Yang J. Indoor air quality analysis using deep learning with sensor data. Sensors Basel. 2017;17:2476.

Pitarma R, Marques G, Caetano F. Monitoring indoor air quality to improve occupational health. In: Rocha A, Correia A, Adeli H, Reis L, Mendonca Teixeira M, editors. New advances in information systems and technologies. Advances in intelligent systems and computing. Cham: Springer; 2016. p. 13–21.

Benammar M, Abdaoui A, Ahmad SHM, Touati F, Kadri A. A modular IoT platform for real-time indoor air quality monitoring. Sensors Basel. 2018;18:581.

Saad SM, Mohd Saad AR, Kamarudin AMY, Zakaria A, Shakaff AYM. Indoor air quality monitoring system using wireless sensor network (WSN) with web interface. In: 2013 International Conference on Electrical, Electronics and System Engineering. Kuala Lumpur. 2013:4–5.

Tiele A, Esfahani S, Covington J. Design and development of a low-cost, portable monitoring device for indoor environment quality. J Sensors. 2018;2018:5353816.

Moreno-Rangel A, Sharpe T, Musau F, McGill G. Field evaluation of a low-cost indoor air quality monitor to quantify exposure to pollutants in residential environments. J Sens Sens Syst. 2018;7:373–88.

Idrees Z, Zou Z, Zheng LR. Edge computing based IoT architecture for low cost air pollution monitoring systems: a comprehensive system analysis, design considerations & development. Sensors Basel. 2018;18:3021.

Sivasankari B, Prabha CA, Dharini S, Haripriya R. IoT based indoor air pollution monitoring using raspberry pi. Int J Innov Eng Tech. 2017;9:16–21.

Arroyo P, Herrero JL, Suarez JI, Lozano J. Wireless sensor network combined with cloud computing for air quality monitoring. Sensors Basel. 2019;19:691.

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Acknowledgments

The authors wish to thank the National Institute of Technical Teachers’ Training and Research, Chandigarh, India, and Universidade da Beira Interior, Covilhã, Portugal, to provide the valuable resources to carry out this study.

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Saini, J., Dutta, M. & Marques, G. A comprehensive review on indoor air quality monitoring systems for enhanced public health. Sustain Environ Res 30 , 6 (2020). https://doi.org/10.1186/s42834-020-0047-y

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research paper on indoor air pollution

Impacts of Indoor Air Quality on Cognitive Function

research paper on indoor air pollution

The Global CogFx study, a research project conducted among 302 office workers in six countries (China, India, Mexico, Thailand, the UK and the US) aims to understand the effects of indoor air pollution on cognitive performance.

Our paper published today  shows the significant acute effects of PM2.5 and ventilation on cognitive test performance. These findings add to a growing body of evidence of how air pollution affects brain health, both  short-   and  long-term .

In addition, our paper suggests that the effects of PM25 are not exclusive to  children or older populations, but are also present among young adults (the mean age of study participants was 33 years old).

Some key takeaways:

  • We developed an ecological momentary assessment framework to administer cognitive tests based on real-time indoor PM2.5 and CO2 measurements.
  • We found 0.8-0.9% slower response times for every 10ug/m3 increase in PM2.5. Throughput (correct responses per minute) was 0.8-1.7% lower for the same concentration increase.
  • We also found effects of CO2 (a proxy for ventilation) on cognitive function. For every 500ppm increase, we saw response times 1.4-1.8% slower, and 2.1-2.4% lower throughput.
  • We did not find a lower threshold at which effects from low ventilation are no longer present.

In addition to the well-established health benefits from lower PM2.5 levels (e.g. reductions in cardiovascular disease, asthma attacks, premature mortality), and from higher ventilation rates (e.g. reduced infectious disease transmission, fewer sick-building symptoms, and reduced absenteeism), our findings provide further incentive to improve air quality in indoor spaces.

Higher ventilation rates and enhanced filtration that exceed current minimum targets are important public health strategies, and we must pursue them.

“Associations between acute exposures to PM2.5 and carbon dioxide indoors and cognitive function in office workers: a multicountry longitudinal prospective observational study,” Jose Guillermo Cedeño Laurent, Piers MacNaughton, Emily Jones, Anna S Young, Maya Bliss, Skye Flanigan, Jose Vallarino, Ling Jyh Chen, Xiaodong Cao, and Joseph G Allen, Environmental Research Letters, online September 9, 2021, doi: 10.1088/1748-9326/ac1bd8

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Study on infection risk in a negative pressure ward under different fresh airflow patterns based on a radiation air conditioning system

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  • Yunfei Ding 1 &
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COVID-19 and other respiratory infectious viruses are highly contagious, and patients need to be treated in negative pressure wards. At present, many negative pressure wards use independent air conditioning equipment, but independent air conditioning equipment has problems such as indoor air circulation flow, condensate water accumulation, and improper filter maintenance, which increase the risk of infection for healthcare workers and patients. The radiation air conditioning system relies on the radiation ceiling to control the indoor temperature and uses new air to control the indoor humidity and air quality. The problems caused by the use of independent air conditioning equipment should be avoided. This paper studies the thermal comfort, contaminant distribution characteristics, contaminant removal efficiency, and accessibility of supply air in a negative pressure ward with a radiation air conditioning system under three airflow patterns. In addition, the negative pressure ward was divided into 12 areas, and the infection probability of healthcare workers in different areas was analyzed. The results show that the application of radiation air conditioning systems in negative pressure wards can ensure the thermal comfort of patients. Stratum ventilation and ceiling-attached jets have similar effects in protecting healthcare workers; both can effectively reduce the contaminant concentrations and the risk of infection of healthcare workers. Ceiling-attached jets decreases the contaminant concentrations by 10.73%, increases the contaminant removal efficiency by 12.50%, and decreases the infection probability of healthcare workers staying indoors for 10 min by 23.18%, compared with downward ventilation.

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The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Ahmed JK, Ahmed QA, Dakkama HJ, Wisam AMA-S (2023) Improvement of energy saving and indoor air quality by using a spot mixing ventilation (SMV) system in a classroom. J Eng Res 100147. https://doi.org/10.1016/j.jer.2023.100147

American Society of Heating, Refrigerating and Air-Conditioning Engineers (1999) ASHRAE Handbook—Fundamentals. New York :The Society

American Society of Heating, Refrigerating and Air-Conditioning Engineers (2015) ASHRAE Handbook—HVAC Applications. New York :The Society

Andres-Chicote M, Tejero-Gonzalez A, Velasco-Gomez E, Rey-Martinez FJ (2012) Experimental study on the cooling capacity of a radiant cooled ceiling system. Energy Build 54:207–214. https://doi.org/10.1016/j.enbuild.2012.07.043

Article   Google Scholar  

Ansys® Academic research mechanical, release 18.1, help system, coupled field analysis guide, ANSYS, Inc. https://www.ansys.com/academic/terms-and-conditions

Berlanga FA, Olmedo I, de Adana MR, Villafruela JM, San J, Castro F (2018) Experimental assessment of different mixing air ventilation systems on ventilation performance and exposure to exhaled contaminants in hospital rooms. Energy Build 177:207–219. https://doi.org/10.1016/j.enbuild.2018.07.053

Bhattacharyya S, Dey K, Paul AR, Biswas R (2020) A novel CFD analysis to minimize the spread of COVID-19 virus in hospital isolation room. Chaos Solit Fractals 139:10. https://doi.org/10.1016/j.chaos.2020.110294

Cao GY, Ruponen M, Paavilainen R, Kurnitski J (2011) Modelling and simulation of the near-wall velocity of a turbulent ceiling attached plane jet after its impingement with the corner. Build Environ 46(2):489–500. https://doi.org/10.1016/j.buildenv.2010.08.012

Chinn RY, Sehulster L (2003) Guidelines for environmental infection control in health-care facilities: recommendations of CDC and Healthcare Infection Control Practices Advisory Committee (HICPAC). https://www.cdc.gov/infectioncontrol/pdf/guidelines/environmental-guidelines-P.pdf

Centre for Health Protection, Department of Health, The Government of Hong Kong Special Administrative Region (2019) Recommendations on implementing isolation precautions in hospital settings. Centre for Health Protection, Department of Health, The Government of Hong Kong Special Administrative Region. https://www.chp.gov.hk/tc/resources/346/365.html . Accessed 6 Jan 2023

Cho J (2019) Investigation on the contaminant distribution with improved ventilation system in hospital isolation rooms: effect of supply and exhaust air diffuser configurations. Appl Therm Eng 148:208–218. https://doi.org/10.1016/j.applthermaleng.2018.11.023

Dharmasastha K, Samuel DGL, Nagendra SMS, Maiya MP (2022) Thermal comfort of a radiant cooling system in glass fiber reinforced gypsum roof–an experimental study. Appl Therm Eng 214:118842. https://doi.org/10.1016/j.applthermaleng.2022.118842

Article   CAS   Google Scholar  

Fennelly KP, Nardell EA (1998) The relative efficacy of respirators and room ventilation in preventing occupational tuberculosis. Infect Cont Hosp Ep 19(10):754–759. https://doi.org/10.2307/30141420

Firatoglu ZA (2023) The effect of natural ventilation on airborne transmission of the COVID-19 virus spread by sneezing in the classroom. Sci Total Environ 896:17. https://doi.org/10.1016/j.scitotenv.2023.165113

Gao NP, Niu JL, Morawska L (2008) Distribution of respiratory droplets in enclosed environments under different air distribution methods. Build Simul 1(4):326–335. https://doi.org/10.1007/s12273-008-8328-0

Hesaraki A, Huda N (2022) A comparative review on the application of radiant low-temperature heating and high-temperature cooling for energy, thermal comfort, indoor air quality, design and control. Sustain Energy Technol 49:13. https://doi.org/10.1016/j.seta.2021.101661

Huang WJ, Wang KL, Hung CT, Chow KM, Tsang D, Lai RWM, Xu RH, Yeoh EK, Chen C, Ho KF (2022) Evaluation of SARS-CoV-2 transmission in COVID-19 isolation wards: on-site sampling and numerical analysis. J Hazard Mater 436:13. https://doi.org/10.1016/j.jhazmat.2022.129152

International Organization for Standardization (2005) ISO 7730: ergonomics of the thermal environment – analytical determination and interpretation of thermal comfort using calculation of the PMV and PPD indices and local thermal comfort criteria. Genève. Switzerland. https://www.iso.org/obp/ui/en/#iso:std:iso:7730:ed-3:v1:en

Jensen PA, Lambert LA, Iademarco MF, Ridzon R (2005) Guidelines for preventing the transmission of Mycobacterium tuberculosis in health-care settings, 2005. https://stacks.cdc.gov/view/cdc/6659 . Accessed 6 Jan. 2023

Kang ZQ, Peng XY, Cheng XC, Feng GH (2017) Analysis of condensation and thermal comfort of two kinds of compound radiant cooling air conditioning systems based on displacement ventilation. Procedia Eng 205:1529–1534. https://doi.org/10.1016/j.proeng.2017.10.233

Kim MK, Liu JY, Cao SJ (2018) Energy analysis of a hybrid radiant cooling system under hot and humid climates: a case study at Shanghai in China. Build Environ 137:208–214. https://doi.org/10.1016/j.buildenv.2018.04.006

Kong XL, Zi XL, Yun L, Zhang XS (2014) An experimental research on wall radiant cooling and wall-attached-jet air-conditioning system. Appl Mech Mater 501–504:2244–2251. https://doi.org/10.4028/www.scientific.net/AMM.501-504.2244

Le Dréau J, Heiselberg P (2014) Sensitivity analysis of the thermal performance of radiant and convective terminals for cooling buildings. Energy Build 82:482–491. https://doi.org/10.1016/j.enbuild.2014.07.002

Lee JH, Bang JI, Sung M, Jeong JW (2022) Inactivation of airborne microbial contaminants by a heat-pump-driven liquid-desiccant air-conditioning system. J Build Eng 50:14. https://doi.org/10.1016/j.jobe.2022.104157

Li N, Chen Q (2020) Study on dynamic thermal performance and optimization of hybrid systems with capillary mat cooling and displacement ventilation. Int J Refrig 110:196–207. https://doi.org/10.1016/j.ijrefrig.2019.10.016

Li XT, Zhao B (2004) Accessibility: a new concept to evaluate ventilation performance in a finite period of time. Indoor Built Environ 13(4):287–293. https://doi.org/10.1177/1420326x04045440

Lin ZP, Deng SLM (2008a) A study on the thermal comfort in sleeping environments in the subtropics—developing a thermal comfort model for sleeping environments. Build Environ 43(1):70–81. https://doi.org/10.1016/j.buildenv.2006.11.026

Lin ZP, Deng SM (2008b) A study on the thermal comfort in sleeping environments in the subtropics—measuring the total insulation values for the bedding systems commonly used in the subtropics. Build Environ 43(5):905–916. https://doi.org/10.1016/j.buildenv.2007.01.027

Liu SM, Deng ZP (2023) Transmission and infection risk of COVID-19 when people coughing in an elevator. Build Environ 238:18. https://doi.org/10.1016/j.buildenv.2023.110343

Liu F, Zhang CY, Qian H, Zheng XH, Nielsen PV (2019) Direct or indirect exposure of exhaled contaminants in stratified environments using an integral model of an expiratory jet. Indoor Air 29(4):591–603. https://doi.org/10.1111/ina.12563

Liu ZJ, Wang LQ, Rong R, Fu SF, Cao GQ, Hao CC (2020) Full-scale experimental and numerical study of bioaerosol characteristics against cross-infection in a two-bed hospital ward. Build Environ 186:14. https://doi.org/10.1016/j.buildenv.2020.107373

Lu YL, Lin Z (2022) Coughed droplet dispersion pattern in hospital ward under stratum ventilation. Build Environ 208:10. https://doi.org/10.1016/j.buildenv.2021.108602

Lu YL, Oladokun M, Lin Z (2020) Reducing the exposure risk in hospital wards by applying stratum ventilation system. Build Environ 183:13. https://doi.org/10.1016/j.buildenv.2020.107204

Luo HB, Liu JJ, Li CQ, Chen K, Zhang M (2020) Ultra-rapid delivery of specialty field hospitals to combat COVID-19: lessons learned from the Leishenshan Hospital project in Wuhan. Autom Constr 119:10. https://doi.org/10.1016/j.autcon.2020.103345

Luo QQ, Ou CY, Hang J, Luo ZW, Yang HY, Yang X et al (2022) Role of pathogen-laden expiratory droplet dispersion and natural ventilation explaining a COVID-19 outbreak in a coach bus. Build Environ 220:17. https://doi.org/10.1016/j.buildenv.2022.109160

Ministry of Housing and Urban-Rural Development of the People’s Republic of China (2012) Design code for heating ventilation and air conditioning of civil buildings. Beijing, China. https://www.mohurd.gov.cn/gongkai/zhengce/zhengcefilelib/201203/20120327_209265.html

Ministry of Housing and Urban-Rural Development of the People’s Republic of China (2015) Code for design of general hospital. Beijing, China. https://www.mohurd.gov.cn/gongkai/zhengce/zhengcefilelib/201412/20141209_224354.html

Ministry of Housing and Urban-Rural Development of the People’s Republic of China (2015) Code for design of infectious diseases hospital. Beijing, China. https://www.mohurd.gov.cn/gongkai/zhengce/zhengcefilelib/201408/20140828_224341.html

Ministry of Housing and Urban-Rural Development of the People’s Republic of China (2015) Design standard for energy efficiency of public buildings. Beijing, China. https://www.mohurd.gov.cn/gongkai/zhengce/zhengcefilelib/201502/20150203_224011.html

Ministry of Housing and Urban-Rural Development of the People’s Republic of China (2020) Technical guidelines for construction of negative pressure area for COVID-19 emergency Treatment Facilities. https://www.mohurd.gov.cn/gongkai/fdzdgknr/tzgg/202003/20200302_244223.html . Accessed 6 Jan 2023

Olmedo I, Nielsen PV, de Adana MR, Jensen RL, Grzelecki P (2012) Distribution of exhaled contaminants and personal exposure in a room using three different air distribution strategies. Indoor Air 22(1):64–76. https://doi.org/10.1111/j.1600-0668.2011.00736.x

Pan J, Hawks SA, Prussin AJ, Duggal NK, Marr LC (2022) SARS-CoV-2 on surfaces and HVAC filters in dormitory rooms. Environ Sci Technol Lett 9(1):71–76. https://doi.org/10.1021/acs.estlett.1c00892

Public Health Agency of Canada (2014) Canadian Tuberculosis Standards 7th Edition: 2014. Public Health Agency of Canada. https://www.canada.ca/en/public-health/services/infectious-diseases/canadian-tuberculosis-standards-7th-edition/edition-11.html#tab2-e . Accessed 6 Jan 2023

Qian Y, Willeke K, Grinshpun SA, Donnelly J, Coffey CC (1998) Performance of N95 respirators: filtration efficiency for airborne microbial and inert particles. Am Ind Hyg Assoc J 59(2):128–132. https://doi.org/10.1080/15428119891010389

Qian H, Li Y, Nielsen PV, Hyldgaard CE, Wong TW, Chwang ATY (2006) Dispersion of exhaled droplet nuclei in a two-bed hospital ward with three different ventilation systems. Indoor Air 16(2):111–128. https://doi.org/10.1111/j.1600-0668.2005.00407.x

Qian H, Li Y, Nielsen PV, Hyldgaard CE (2008) Dispersion of exhalation pollutants in a two-bed hospital ward with a downward ventilation system. Build Environ 43(3):344–354. https://doi.org/10.1016/j.buildenv.2006.03.025

Ren J, Wang Y, Liu QB, Liu Y (2021) Numerical study of three ventilation strategies in a prefabricated COVID-19 inpatient ward. Build Environ 188:17. https://doi.org/10.1016/j.buildenv.2020.107467

Ren J, Liu JY, Zhou SY, Kim MK, Song SJ (2022a) Experimental study on control strategies of radiant floor cooling system with direct-ground cooling source and displacement ventilation system: a case study in an office building. Energy 239:16. https://doi.org/10.1016/j.energy.2021.122410

Ren JL, Duan SS, Guo LH, Li HW, Kong XF (2022b) Effects of return air inlets’ location on the control of fine particle transportation in a simulated hospital ward. Int J Env Res Pub He 19(18):21. https://doi.org/10.3390/ijerph191811185

Ren C, Wang JQ, Feng ZB, Kim MK, Haghighat F, Cao SJ (2023) Refined design of ventilation systems to mitigate infection risk in hospital wards: perspective from ventilation openings setting. Environ Pollut 333:15. https://doi.org/10.1016/j.envpol.2023.122025

Richardson ET, Morrow CD, Kalil DB, Bekker LG, Wood R (2014) Shared air: a renewed focus on ventilation for the prevention of tuberculosis transmission. Plos One 9(5):e96334. https://doi.org/10.1371/journal.pone.0096334

Riley EC, Murphy G, Riley RL (1978) Airborne spread of measles in a suburban elementary school. Am J Epidemiol 107(5):421–432. https://doi.org/10.1093/oxfordjournals.aje.a112560

Rudnick SN, Milton DK (2003) Risk of indoor airborne infection transmission estimated from carbon dioxide concentration. Indoor Air 13(3):237–245. https://doi.org/10.1034/j.1600-0668.2003.00189.x

Satheesan MK, Mui KW, Wong LT (2020) A numerical study of ventilation strategies for infection risk mitigation in general inpatient wards. Build Simul 13(4):887–896. https://doi.org/10.1007/s12273-020-0623-4

Sheng SY, Yamanaka T, Kobayashi T, Choi N, Chou N (2022) Experimental study and CFD modelling of four-bed hospital ward with all-air wall induction unit for air-conditioning. Build Environ 222:18. https://doi.org/10.1016/j.buildenv.2022.109388

Song YF, Yang CQ, Li H, Chen HB, Shen SN, Hou YQ, Wang JY (2023) Aerodynamic performance of a ventilation system for droplet control by coughing in a hospital isolation ward. Environ Sci Pollut Res 30(29):73812–73824. https://doi.org/10.1007/s11356-023-27614-w

Su W, Yang B, Melikov A, Liang CJY, Lu YL, Wang FM, Li AG, Lin Z, Li XT, Cao GY, Kosonen R (2022) Infection probability under different air distribution patterns. Build Environ 207(16):108555. https://doi.org/10.1016/j.buildenv.2021.108555

Tan HY, Wong KY, Othman MHD, Kek HY, Nyakuma BB, Ho WS, Hashim H, Wahab RA, Sheng D, Wahab NHA, Yatim AS (2023) Why do ventilation strategies matter in controlling infectious airborne particles? A comprehensive numerical analysis in isolation ward. Build Environ 231:14. https://doi.org/10.1016/j.buildenv.2023.110048

Tian Z, Love JA (2008) A field study of occupant thermal comfort and thermal environments with radiant slab cooling. Build Environ 43(10):1658–1670. https://doi.org/10.1016/j.buildenv.2007.10.012

Tomasi R, Krajcik M, Simone A, Olesen BW (2013) Experimental evaluation of air distribution in mechanically ventilated residential rooms: thermal comfort and ventilation effectiveness. Energy Build 60:28–37. https://doi.org/10.1016/j.enbuild.2013.01.003

Villafruela JM, Castro F, San Jose JF, Saint-Martin J (2013) Comparison of air change efficiency, contaminant removal effectiveness and infection risk as IAQ indices in isolation rooms. Energy Build 57:210–219. https://doi.org/10.1016/j.enbuild.2012.10.053

World Health Organization (2022) Coronavirus disease (COVID-19). World Health Organization. https://www.who.int/health-topics/coronavirus#tab=tab_1 . Accessed 17 Dec 2022

Xu RZ, Wu F, Li XL, Yu C, Li HK, Wu RC, Wu YL (2022) Numerical comparison of ventilation modes on the transmission of coughing droplets in a train compartment. J Wind Eng Ind Aerodyn 231:12. https://doi.org/10.1016/j.jweia.2022.105240

Yang CQ, Yang XD, Zhao B (2015) The ventilation needed to control thermal plume and particle dispersion from manikins in a unidirectional ventilated protective isolation room. Build Simul 8(5):551–565. https://doi.org/10.1007/s12273-014-0227-6

Yang B, Melikov AK, Kabanshi A, Zhang C, Bauman FS, Cao G, Awbi H, Wigö H, Niu J, Cheong KWD, Tham KW, Sandberg M, Nielsen PV, Kosonen R, Yao R, Kato S, Sekhar SC, Schiavon S, Karimipanah T, Li X, Lin Z (2019) A review of advanced air distribution methods - theory, practice, limitations and solutions. Energy Build 202(27):109359. https://doi.org/10.1016/j.enbuild.2019.109359

Zhang S, Lin Z (2021) Dilution-based evaluation of airborne infection risk-thorough expansion of Wells-Riley model. Build Environ 194:7. https://doi.org/10.1016/j.buildenv.2021.107674

Zhang S, Niu D, Lu YL, Lin Z (2022) Contaminant removal and contaminant dispersion of air distribution for overall and local airborne infection risk controls. Sci Total Environ 833:11. https://doi.org/10.1016/j.scitotenv.2022.155173

Zhou Q, Qian H, Ren HG, Li YG, Nielsen PV (2017) The lock-up phenomenon of exhaled flow in a stable thermally-stratified indoor environment. Build Environ 116:246–256. https://doi.org/10.1016/j.buildenv.2017.02.010

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This work was financially supported by the National natural Science Foundation of China (No. 51878187) and Guangzhou Science and technology Program key project (No. 202206010132).

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Zhou, C., Ding, Y. & Ye, L. Study on infection risk in a negative pressure ward under different fresh airflow patterns based on a radiation air conditioning system. Environ Sci Pollut Res (2024). https://doi.org/10.1007/s11356-024-32037-2

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  • v.39(4); Oct-Dec 2014

Indoor Air Pollution in India: Implications on Health and its Control

Ankita kankaria.

Centre for Community Medicine, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, India

Baridalyne Nongkynrih

Sanjeev kumar gupta, introduction.

Indoor air pollution is the degradation of indoor air quality by harmful chemicals and other materials; it can be up to 10 times worse than outdoor air pollution. This is because contained areas enable potential pollutants to build up more than open spaces. Statistics suggest that in developing countries, health impacts of indoor air pollution far outweigh those of outdoor air pollution. Indoor air pollution from solid fuels accounted for 3.5 million deaths and 4.5% global daily-adjusted life year (DALY) in 2010; it also accounted for 16% particulate matter pollution. Though there is a decrease in household air pollution from solid fuels in southeast Asia, still it ranked third among risk factors in the report of the Global Burden of Disease.( 1 ) This paper provides an evidence-based insight into indoor air pollution, its effect on health, and suggested control measures.

Status of Indoor Air Pollution in India

The principal sources of indoor air pollution are: Combustion, building material, and bioaerosols.( 2 ) While radon, asbestos, pesticides, heavy metals, volatile organic matter, and environmental tobacco smoke are considered major indoor pollutants in developed countries, the combustion products of biomass fuels contribute most to indoor air pollution in developing nations. In India, out of 0.2 billion people using fuel for cooking; 49% use firewood; 8.9% cow dung cake; 1.5% coal, lignite, or charcoal; 2.9% kerosene; 28.6% liquefied petroleum gas (LPG); 0.1% electricity; 0.4% biogas; and 0.5% any other means.( 3 )

The incomplete combustion products of biomass fuels include suspended particulate matter, carbon monoxide, polyaromatic hydrocarbons, polyorganic matter, formaldehyde, etc., which have adverse effects on health. The combustion of coal results in production of oxides of sulfur, arsenic, and fluorine. Pollutants such as aldehydes, volatile, and semivolatile organic compounds are produced from resins, waxes, polishing materials, cosmetics, and binders. Lastly; biological pollutants like dust mites, molds, pollen, and infectious agents produced in stagnant water, mattresses, carpets, and humidifiers too pollute indoor air.( 4 )

A study on quantifying exposures to respiratory particulate matter found concentrations of particulate matter ranging from 500 to 2,000 mg/m 3 during cooking in biomass-using households. Average 24-h exposures ranged from 82 ± 39 mg/m 3 for those using clean fuels, to 231 ± 109 mg/m 3 for those who used biomass fuel for cooking.( 5 ) In indoor air, carbon monoxide levels during cooking by dung, wood, coal, kerosene, and LPG were found to be 144, 156, 94, 108, and 14 mg/m 3 , respectively. The indoor levels of total polyaromatic hydrocarbons during use of dung, wood, coal, kerosene, and LPG were 3.56, 2.01, 0.55, 0.23, and 0.13 mg/m 3 of air, respectively.( 6 ) The formaldehyde mean levels were 670, 652, 109, 112, and 68 mg/m 3 , respectively, for dung, wood, coal, kerosene, and LPG.( 7 )

Effects of Indoor Air Pollution on Health

The ill-effects of indoor air pollution result in about 2 million premature deaths per year, wherein 44% are due to pneumonia, 54% from chronic obstructive pulmonary disease (COPD), and 2% from lung cancer.( 8 ) The most affected groups are women and younger children, as they spend maximum time at home.( 8 ) The morbidities associated with indoor air pollution are respiratory illnesses, viz., acute respiratory tract infection( 9 ) and COPD,( 10 ) poor perinatal outcomes like low birth weight( 11 ) and still birth, cancer of nasopharynx, larynx, lung,( 12 ) and leukemia. The harmful health effects of formaldehyde range from being an acute irritant, reducing vital capacity, causing bronchitis, to being a carcinogen causing leukemia and lung cancer.( 13 , 14 ) There are few studies done so far to show the effect of wood smoke on cardiovascular health. A study from Guatemala reported that reduction in wood smoke exposure by use of improved chimney stove resulted in lowering of systolic blood pressure by 3.7 mmHg (95% confidence interval (CI): -8.1, 0.6) and diastolic blood pressure by 3.0 mmHg (95% CI: -5.7, -0.4).( 15 ) Another study reported reduction in ST-segment depression (odds ratio (OR) 0.26, 95% CI: 0.08, 0.90) on electrocardiogram after stove intervention.( 16 )

The indoor air pollutants have potential health effects.( 17 ) The particulates cause respiratory infections, chronic bronchitis, COPD, and also lead to exacerbation of COPD. Sulfur dioxide and nitrogen dioxide cause wheezing and exacerbation of asthma. In addition to this, nitrogen dioxide causes respiratory infections and deteriorates lung functions. Sulfur dioxide has an additional etiological role in exacerbation of COPD and cardiovascular disease. The risk of poor perinatal outcomes, viz., low birth weight and perinatal death increases from exposure to carbon monoxide. Biomass smoke, especially metal ions and polycyclic aromatics, leads to development of cataract. Polycyclic aromatic hydrocarbons lead to development of cancers of lungs, mouth, nasopharynx, and larynx. As a consequence of poverty, factors such as living conditions, sanitation, and access to water are associated with solid fuel use, and should be considered while measuring impact of solid fuel on child survival.( 17 )

Various studies in India have reported harmful effects of indoor air pollution. In a large case-control study, after adjustment for demographic factors and living conditions, solid-fuel use significantly increased child deaths at ages 1-4 years (prevalence ratio boys: 1.30, 95% CI: 1.08-1.56; girls: 1.33, 95% CI: 1.12-1.58). More girls than boys died from exposure to solid fuels. Solid fuel use was also associated with nonfatal pneumonia (boys: Prevalence ratio 1.54; 95% CI: 1.01-2.35; girls: Prevalence ratio 1.94; 95% CI: 1.13-3.33).( 18 )

The use of fuel other than LPG was significantly associated with acute lower respiratory tract infection even after adjusting for other risk factors (adjusted OR = 4·73, 95% CI: 1.67-13.45). In children with acute lower respiratory infection, 24.8% had pneumonia, 45.5% had severe pneumonia, and 29.7% had very severe disease.( 19 ) In Ladakh, due to severe cold, and ventilation kept to a minimum, the inmates are exposed to high concentration of soot, resulting in morbidities which resemble pneumoconiosis.( 20 , 21 ) The use of biomass fuel was associated with significantly prolonged nasal mucociliary clearance time (765.8 ± 378.16 s) in comparison to clean fuel users (545.4 ± 215.55 s), and reduced peak expiratory flow rate (319.3 l/min) as compared to clean fuel users (371.7 l/min).( 22 )

The use of biomass as a cooking fuel was found to be significantly associated with a high prevalence of active tuberculosis (OR = 3.56, 95% CI: 2.82-4.50). The prevalence remained large and significant even after analyzing separately for men (OR = 2.46) and women (OR = 2.74) and for urban (OR = 2.29) and rural areas (OR = 2.65). Fifty-one percent of prevalence of active tuberculosis is attributable to cooking smoke in the age group 20 years and above.( 23 )

Results from a study among elderly men and women (age ≥ 60 years) showed higher prevalence of asthma in households using biomass fuels than those using cleaner fuels (OR = 1.59; 95% CI: 1.30-1.94). As compared to men (OR = 1.83; 95% CI: 1.32-2.53), the effect of cooking smoke on asthma was greater among women after adjustment.( 24 ) The results from a study conducted in southern India reported a higher prevalence of COPD among biomass fuel user than clean fuel users (OR: 1.24; 95% CI: 0.36-6.64). It also found that the prevalence was two times higher in women spending more than 2 h a day in cooking.( 25 ) Biomass fuels contain carcinogens like polyaromatic hydrocarbons, formaldehyde, etc. A case-control study among women diagnosed with lung cancer reported that in addition to tobacco, exposure to biomass fuels also leads to development of lung cancer. In nonsmoker women, exposure to biomass fuel was associated with higher risk of developing lung cancer (OR 3.04, 95% CI: 1.1-8.38). The exposure to biomass fuel remained significantly associated with lung cancer despite adjusting for other factors like smoking and passive smoking.( 26 )

As compared to the use of cow dung and wood smoke, LPG use was found to be associated with cortical, nuclear, and mixed cataract with an odds ratio of 0.69 (95% CI: 0.4-0.9),( 27 ) whereas biomass fuel use resulted in partial or complete blindness with odds of 1.32 (95% CI: 1.2-1.5), as compared to other fuels.( 28 ) Similar studies in western India reported use of wood to be an important cause of age-dependent cataract (OR = 2.12, 95% CI: 1.03-4.34). Coal and cattle dung use resulted in eye irritation (OR = 2.04, 95% CI: 1.13-3.68) and (OR = 1.83, 95% CI: 1.35-2.47), respectively.( 29 )

The higher levels of carbon monoxide due to biomass fuels in houses, resulted in higher carboxyhemoglobin levels, which were comparable to smokers.( 30 ) A study among users of biomass fuels during pregnancy found a 50% excess risk of stillbirths.( 31 ) The exposure to biomass fuel was associated with 49% increased risk of low birth weight babies.( 32 ) Mothers from households using high pollution fuels were 1.4 (OR 1.41, 95% CI: 1.27, 1.55) times more likely to give birth to a low birth weight baby as compared to those using cleaner fuels. The use of biomass fuel during pregnancy was found to be associated with size at birth. As compared to newborns born in households using low pollution fuels (electricity, LPG, biogas, and natural gas), those born in households using high pollution fuels (wood, straw, animal dung, crop residue, coal, and charcoal) were 73 g lighter (mean birth weight 2,883.8 g versus 2,810.7 g, P < 0.001).( 33 )

The effects of indoor air pollution in India on health are depicted in Table 1 .

Effects of indoor air pollution in India on health

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Control Measures

Studies done so far in India provide us enough evidence that indoor air pollution is a cause of increasing morbidities and mortalities, and there is a need for an urgent intervention. There are social, cultural, and financial factors that influence the decision of people about energy and cooking.( 34 ) Other factors include the availability and flexibility of traditional fuels, the type of dishes prepared, the taste of food, the problems with smoke, the aesthetic appeal of stoves, and users' perception about other alternatives. Following is a list of suggested measures which should be adopted to curb the menace of indoor air pollution:

  • Public awareness: One of the most important steps in prevention of indoor air pollution is education, viz., spreading awareness among people about the issue and the serious threat it poses to their health and wellbeing. The education should help people in finding different ways of reducing exposures with better kitchen management and protection of children at home. People should also be educated about the use of alternative cleaner sources of energy to replace direct combustion of biomass fuel. The stakeholders must include not only public, but also politicians and administrators to ensure their commitment and increase their awareness about health effects of indoor air pollution.
  • Change in pattern of fuel use: Fuel use depends on ones' habit, its availability, and most importantly, its affordability. At present, majority of low income families rely solely on direct combustion of biomass fuels for their cooking needs as this is the cheapest and easiest option available to them; however, this could be rectified by promoting the use of cleaner energy sources such as gobar gas which utilizes cow dung to produce gas for cooking.
  • Modification of design of cooking stove: The stoves should be modified from traditional smoky and leaky cooking stoves to the ones which are fuel efficient, smokeless and have an exit (e.g., chimney) for indoor pollutants. A good example is the one designed by the National Biomass Cookstoves Initiative, of the Ministry of New and Renewable Energy under a Special Project on Cookstove during 2009-2010, with the primary aim of enhancing the availability of clean and efficient energy for the energy deficient and poorer sections of the country.( 35 )
  • Improvement in ventilation: During construction of a house, importance should be given to adequate ventilation; for poorly ventilated houses, measures such as a window above the cooking stove and cross ventilation though doors should be instituted.
  • Intersectoral coordination and global initiative: Indoor air pollution can only be controlled with coordinated and committed efforts between different sectors concerned with health, energy, environment, housing, and rural development.

Tackling indoor air pollution and providing universal access to clean household energy is a great opportunity to improve health, reduce poverty, and protect our environment; thus, contributing significantly to achieving the Millennium Development Goals (MDGs) which are listed below:

  • Improved household energy practices will provide opportunities for income generation-MDG 1 (eradicate extreme poverty and hunger).
  • With less time spent on fuel collection and lost due to ill health, children will have more time for school attendance and homework-MDG 2 (achieve universal primary education).
  • Freeing women's time for income generation will help in eradicating poverty and hunger (MDG 1) and achieving gender equality (MDG 3).
  • Better respiratory health: MDG 4 ( reduce child mortality), MDG 5 (improve maternal health), and MDG 6 (combat HIV/AIDS, malaria and other diseases like tuberculosis).
  • Use of clean household energy will ensure environmental sustainability; the World Health Organization is the agency responsible for reporting the “proportion of the population using solid fuels” as an indicator for reporting progress towards MDG 7 to ensure environmental sustainability (MDG 7).
  • An intersectoral approach for use of clean household energy practices will lead to economic and social development-MDG 8 (develop a global partnership for development).

Though evidence exists for increase in indoor air pollution in India, and its association with both increased morbidity and mortality, there is still a need of further studies to assess the exposure levels of indoor pollutants and to further strengthen the evidence for their association with outcomes like tuberculosis, cataract, asthma, cardiovascular health, and cancers. At the same time, effective interventions, starting from education, change in fuel patterns, proper designing of stoves and houses, to a committed and determined intersectoral coordination towards promotion of public health is the need of the hour.

Source of Support: Nil

Conflict of Interest: None declared.

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    It is predicted that the development of novel materials for sensors, IAQ-monitoring systems, and smart homes is a promising strategy for control and enhancement of IAQ in the future. Indoor air pollution (IAP) is a serious threat to human health, causing millions of deaths each year. A plethora of pollutants can result in IAP; therefore, it is very important to identify their main sources and ...

  19. Investigation of Indoor Air Quality in Residential Buildings by ...

    Indoor air quality (IAQ) in houses is often deteriorated by chemical substances emitted from heating, building materials, or other household goods. Since it is difficult for occupants to recognize air pollution, they rarely understand the actual conditions of the IAQ. An investigation into the actual condition of IAQ in houses was therefore conducted in this study.

  20. Environmental and Health Impacts of Air Pollution: A Review

    Abstract One of our era's greatest scourges is air pollution, on account not only of its impact on climate change but also its impact on public and individual health due to increasing morbidity and mortality. There are many pollutants that are major factors in disease in humans.

  21. (PDF) INDOOR AIR POLLUTION-A Threat

    Indoor air pollution refers to the deterioration of indoor air quality by harmful chemicals and other products, which can be up to 10 times worse than the outdoor air pollution. Almost 90% of the ...

  22. Exposure to indoor air pollution and angina among aging adults in India

    This study tried to understand the association between exposure to indoor air pollution and angina among the aging population in India. We utilized the data from the Longitudinal Ageing Study in India (LASI) Wave-1 (2017-2018), with a sample of 62,846 aging adults. We applied Chi-square and multivariate logistic regression models.

  23. Study on infection risk in a negative pressure ward under ...

    COVID-19 and other respiratory infectious viruses are highly contagious, and patients need to be treated in negative pressure wards. At present, many negative pressure wards use independent air conditioning equipment, but independent air conditioning equipment has problems such as indoor air circulation flow, condensate water accumulation, and improper filter maintenance, which increase the ...

  24. PDF Contents

    Grant Funding to Address Indoor Air Pollution at Schools (EPA-R- OAR-24-02) on January 11, 2024. This funding opportunity from the Inflation Reduction Act provides funding for ... Is research to enhance indoor air quality an eligible activity? Answer 5: The EPA will not consider applications that are exclusively designed to conduct scientific ...

  25. Indoor Air Pollution in India: Implications on Health and its Control

    ( 1) This paper provides an evidence-based insight into indoor air pollution, its effect on health, and suggested control measures. Go to: Status of Indoor Air Pollution in India The principal sources of indoor air pollution are: Combustion, building material, and bioaerosols.