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Review

Methodologies Used to Determine the Main Markers of Indoor Air Quality

by
Ivan Notardonato
1,*,
Cristina Di Fiore
1 and
Pasquale Avino
1,2
1
Department of Agriculture, Environmental and Food Science, University of Molise, Via Francesco De Sanctis, 86100 Campobasso, Italy
2
SIIAQ—Society Italian Indoor Air Quality, Via Francesco De Sanctis, 86100 Campobasso, Italy
*
Author to whom correspondence should be addressed.
Purification 2025, 1(1), 3; https://doi.org/10.3390/purification1010003
Submission received: 17 March 2025 / Revised: 14 May 2025 / Accepted: 15 May 2025 / Published: 22 May 2025

Abstract

:
Indoor air quality (IAQ) has emerged as a critical area of research, reflecting growing concerns regarding occupant health, well-being, and comfort in enclosed environments. The increasing complexity of modern indoor spaces, coupled with rapid advancements in sensing technologies and data analysis methodologies, has intensified scientific interest in effective IAQ assessment and management. This review aims to examine current technologies and methodologies for monitoring key indoor air quality indicators. Furthermore, it offers practical recommendations for enhancing IAQ in diverse built environments and explores the integration of artificial intelligence (AI) into monitoring systems. The findings underscore the potential of AI-enhanced approaches to optimize indoor environmental conditions and support proactive air quality management strategies.

1. Introduction

The chemical composition and quality of air have become a central focus of scientific research. This is evidenced by the increasing number of publications on this topic each year [1]. In particular, indoor air quality (IAQ) is a subject of great scientific interest, as individuals spend approximately 90% of their time in enclosed environments [2]. Scientific evidence suggests that indoor air quality is 2 to 5 times worse than outdoor air conditions [3]. Studies conducted in schools indicate that the primary causes of poor IAQ are reduced air recirculation within indoor environments and the presence of occupants in classrooms [4]. Airborne particles and molecules capable of altering the perception of air quality have been the subject of investigation by international organizations such as the World Health Organization (WHO) [2] and national bodies such as the Italian National Institute of Health (ISS) [5] for several years. The quality of indoor air in confined spaces (e.g., homes, public and private offices, gyms, restaurants) can have a significant impact on human health, affecting both comfort and well-being. The presence of pollutants such as particulate matter (PM, including both respirable and inhalable fractions), volatile organic compounds (VOCs), carbon monoxide (CO), and radon can lead to various health issues, particularly in indoor environments. Among all the identified pollutants, WHO has selected nine markers to characterize indoor air quality: formaldehyde (HCHO), polycyclic aromatic hydrocarbons (PAHs), radon (Rn), nitrogen dioxide (NO2), carbon monoxide (CO), trichloroethylene (C2HCl3), tetrachloroethylene (C2Cl4), benzene (C6H6), and toluene (C6H5OH) [2]. In addition to these markers, fine particulate matter and physicochemical parameters are monitored in accordance with Directive 2008/50/EC to certify indoor air quality. Studies and reviews have highlighted the complexity of IAQ [6], demonstrating that it is influenced by multiple factors, including outdoor air pollution [7], indoor activities [8], and ventilation systems [9]. Additionally, IAQ is affected by the presence of odors [10], yet no clear and unified legislation currently exists on this matter [11]. The scientific literature suggests preventive measures such as proper ventilation, material selection, cleaning practices, and maintenance of heating and air conditioning systems to ensure good IAQ. The ongoing experimental Horizon project, Evidence-Driven Indoor Air Quality Improvement (EDIAQI), investigates and recommends the effectiveness of modern technologies for IAQ management [12]. Moreover, it is crucial for policymakers and healthcare organizations to continue their efforts to improve indoor air quality standards and provide clear and accessible guidelines to the public. The aim of this study is to conduct a literature review comparing current methodologies used to assess the WHO-identified markers for IAQ monitoring. These methods contribute to understanding pollutant levels in indoor environments and their potential sources, thereby facilitating improved air quality management.

2. Main IAQ Markers and Analysis Methodologies

2.1. Formaldehyde (HCHO)

Formaldehyde is a colorless gas at room temperature. It possesses a sharp, irritating odor that can be detected even at very low concentrations. It exhibits high water solubility and readily disperses into the air, even at ambient temperatures. HCOH is a highly reactive compound capable of participating in numerous chemical reactions, including the formation of tropospheric ozone in the presence of other compounds. It has been classified by the International Agency for Research on Cancer (IARC) as a Group 1 human carcinogen. The World Health Organization (WHO) has established a guideline value of 0.1 mg m−3 for a 30 min exposure. However, there is no universally harmonized regulation, and reference values may vary depending on national legislation. The determination of formaldehyde in indoor air is crucial for ensuring air quality and protecting occupants’ health. Most formaldehyde emissions originate from building materials or furniture [13]. In addition, formaldehyde release is also associated with paints [14], household products, cosmetics [15], tobacco smoke [16], combustion processes, and high-temperature activities such as cooking or ironing. The emission process is governed by mass transfer and is controlled by three independent parameters related to the type of building materials: initial emission concentration CO (μg m−3), diffusion coefficient D (m2 s−1), and material/air partition coefficient K (dimensionless) [17]. Domestic exposure to formaldehyde significantly increases the risk of asthma in young children, eye and upper respiratory tract irritation, and carcinogenic potential [18]. WHO guidelines and ISO standards, such as ISO 16000-23 [19], provide reference criteria for measuring and evaluating formaldehyde concentrations in indoor environments. The most widely used method for formaldehyde determination involves active sampling with pumps that draw air through a chemical absorbent, 2,4-dinitrophenylhydrazine (DNPH), which reacts with formaldehyde to form a stable derivative. This derivative is then analyzed by high-performance liquid chromatography (HPLC) with UV detection [20]. Alternative methods allow for formaldehyde determination using different analytical techniques. These include thermal desorption coupled with gas chromatography [21] and microwave-assisted derivatization [22]. Formaldehyde can also be measured using passive sampling, employing devices that adsorb formaldehyde from the air without the use of pumps. These devices are exposed for a specific duration and subsequently analyzed in the laboratory [23]. However, these methods require extended sampling times and trained personnel. To date, liquid chromatography remains the most commonly used analytical technique for formaldehyde determination, often coupled with mass spectrometry [24] or a diode array detector [25]. Table 1 compares the key analytical parameters of the proposed methodologies.
Table 1 presents a comparison of alternative methodologies employed for the determination of formaldehyde. Where available, key performance parameters are evaluated: limit of detection (LOD), linear dynamic range (LDR), correlation coefficient, and recovery. The latter parameter is available for only one of the articles analyzed. The lowest LOD is achieved through assisted derivatization (0.12 ng·mL−1), indicating the high sensitivity of the technique. Thermal desorption also shows a relatively low LOD (0.26 ppbv), although expressed in different units. Conversely, LC-DAD exhibits the highest LOD (5 ng·mL−1), suggesting lower sensitivity compared to the other methods. The LDR varies significantly across techniques. Passive sampling demonstrates the widest range (15–3200 ppbv), implying greater flexibility but also increased variability in quantification. Assisted derivatization and LC-MS provide narrower and more manageable ranges, with a lower bound of 0.5 ng·mL−1, consistent with their higher sensitivity. All methods exhibit excellent linearity, with correlation coefficients (R2) ≥ 0.9900. Recovery data are reported only for assisted derivatization (84.9–95.1%), which is satisfactory and compatible with reliable quantitative analyses. The absence of recovery data for the other techniques limits direct comparison for this parameter. Based on the reported data, assisted derivatization appears to offer a good compromise between sensitivity, precision, and recovery, making it a promising technique for quantitative applications. However, chromatographic techniques (LC-MS and LC-DAD) also demonstrate good performance, particularly in terms of linearity. Passive sampling and thermal desorption offer the advantage of being applicable for environmental or field analyses, albeit with slightly lower sensitivity and greater variability in quantification.

2.2. Polycyclic Aromatic Hydrocarbons (PAHs)

PAHs are a class of organic compounds composed of two or more fused aromatic rings. Some are colorless, while others exhibit a yellowish hue and may have an aromatic odor. With the exception of naphthalene, which is highly volatile, most PAHs display low volatility. They are poorly soluble in water and tend to accumulate in dust and on surfaces. PAHs have a strong tendency to adsorb onto fine particulate matter (PM 2.5) and exhibit long environmental persistence. Benzo[a]pyrene (BaP), classified as a Group 1 human carcinogen by the International Agency for Research on Cancer (IARC), is considered the most hazardous compound among them. Although there are currently no universally applied indoor air quality standards for PAHs, their presence is routinely monitored in sensitive environments (e.g., schools, hospitals). The World Health Organization (WHO) has established guideline values for only a few PAHs; for example, the recommended ambient air concentration for BaP is 1 ng m−3. Determining the presence of PAHs in indoor air is essential for assessing air quality and potential health risks. The primary emission source of PAHs is the incomplete combustion of organic material. Anthropogenic contributions mainly originate from vehicular traffic, industrial processes, fossil fuel combustion, waste incineration, domestic heating, cigarette smoke, and building materials. Natural sources are primarily associated with wildfires, natural fires, and volcanic eruptions. PAHs can be emitted from building materials, and their indoor air concentrations can be estimated using mixing equations that account for production rates and air exchange rates [26]. Several methodologies are employed for PAHs determination. Sampling using filters or adsorbent tubes followed by analysis via gas chromatography-mass spectrometry (GC-MS) [27] or high-performance liquid chromatography (HPLC) [28] are among the most widely used techniques. For long-term monitoring, PAHs can also be determined using passive samplers with subsequent laboratory analysis [29]. Additionally, polyurethane foam (PUF) disks have been employed for passive sampling [30]. Another technique reported in the literature is thermal desorption analysis. In this method, PAHs are collected on an adsorbent material, which is then heated to release the analytes for analysis via GC-MS [31]. Table 2 reports the methodologies considered and references for the determination of PAHs.
Table 2 summarizes the analytical methodologies considered for the determination of PAHs, distinguishing by document type, analytical technique, and sampling matrix. The application context varies among urban, rural, and general environments. Of the four documents reviewed, only one is a review article, which provides an overview of the state of the art regarding the use of sorbent tubes coupled with GC-MS in broader environmental contexts. Three out of the four methodologies employ sorbent tubes, combined with different detection techniques such as GC-MS or LC-MS. Polyurethane foam is presented as an alternative solution, although it is more commonly associated with long-term sampling and lipophilic compounds. Thermal desorption is a well-established technique for the controlled release of adsorbed analytes and is particularly useful for direct environmental monitoring. The contexts of analysis include urban, rural, and general environmental settings.

2.3. Radon (Rn)

Radon is a noble gas that is colorless, odorless, and tasteless, and it is highly radioactive. It originates from the natural decay of radium-226, which in turn is a decay product of uranium-238. The most common isotope is radon-222, which has a half-life of approximately 3.8 days. Due to its higher density compared to air, radon tends to accumulate in low-lying areas (e.g., basements, ground floors). According to the World Health Organization (WHO) and the International Agency for Research on Cancer (IARC), radon is the second leading cause of lung cancer after tobacco smoking [32]. The risk is particularly elevated in enclosed, poorly ventilated environments. The WHO recommends a reference level below 100 Bq m−3, while the European Union (EU), through Directive 2013/59/Euratom, sets a maximum reference level of 300 Bq m−3. The main source of radon emissions into the environment is soil. However, other sources such as rocks, groundwater, mining activities, nuclear power plants, and waste disposal sites also contribute to radon emissions into the environment. Radon accumulation in buildings typically occurs in basements and ground floors. Structures with foundations in direct contact with the soil serve as accumulation points, as radon infiltrates through cracks, fissures, and structural joints. The buildup is particularly significant in areas with poor air exchange. Inadequate or insufficient ventilation can further promote radon accumulation in enclosed spaces. One of the most commonly used methods for radon detection is the ionization chamber (AlfaGUARD), which utilizes an ionization chamber to detect alpha particles emitted by radon and its decay products [33]. Cartridge-based sampling involves drawing air through a cartridge containing activated carbon, which adsorbs radon. The captured radon is then measured using solid scintillation techniques [34]. Among the primary passive methods, the literature highlights alpha track detection using radiation-sensitive films or polymers, which record the traces left by alpha particles emitted by radon [35]. Another passive radon sampling technique involves electrets, a dielectric material with an almost permanent electric charge. An electret generates both internal and external electric fields, functioning as the electrostatic equivalent of a permanent magnet. This technique measures radon concentration by assessing variations in electrical potential [36]. Table 3 reports the methodologies considered and references for the determination of radon.
Table 3 provides a comparative overview of the four studies considered for radon detection. The application matrices differ, including environmental samples and building materials, which are particularly relevant for assessing radon emissions from construction surfaces, an important factor in indoor safety. Ionization chambers are commonly used for the quantitative measurement of radioactivity in building materials due to their high sensitivity and capability to provide direct, real-time measurements. Solid-state scintillation is also an effective technique for detecting radioactive gases in air, offering good sensitivity and portability. Alpha track detection is a passive, integrative method that is simple and reliable. Electret-based sampling represents another passive approach, relying on electrostatic charge to detect alpha particles. It is particularly well-suited for widespread environmental applications due to its low cost and ease of use. Active techniques, such as ionization and scintillation, offer higher temporal resolution and accuracy but are typically employed in more specific settings and require more sophisticated instrumentation. Conversely, passive techniques, such as alpha track detectors and electret-based methods, are better suited for long-term environmental monitoring.

2.4. Nitrogen Dioxide (NO2)

NO2 is a gas at room temperature with a sharp, acrid odor. It exhibits moderate solubility in water, leading to the formation of acids. NO2 is a highly reactive species and plays a key role in the formation of tropospheric ozone and secondary particulate matter. The primary emission sources of NO2 originate from both anthropogenic activities and natural processes. Major sources include vehicular traffic, industrial combustion processes, domestic heating, lightning, vegetation emissions, and natural fires. It can cause irritation of the respiratory tract, eyes, and throat. NO2 may also enhance the effects of other pollutants (e.g., fine particulate matter) and can react with VOCs to form more toxic compounds. The World Health Organization (WHO) has established a guideline value of 40 µg m−3 as an annual mean and 200 µg m−3 as an hourly mean, which should not be exceeded more than 18 times per year. Various methods are employed for NO2 determination. Chemiluminescence-based detection is a highly effective method for measuring NO2. This technique relies on the reaction of nitric oxide (NO) with ozone (O3) to produce light, which is then measured. This method offers a very low detection limit and minimal interferences [37]. Another widely used approach is ultraviolet-visible (UV-Vis) spectrophotometry, which takes advantage of NO2’s ability to absorb ultraviolet and visible light. The NO2 concentration is determined by measuring light absorption at specific wavelengths [38]. Electrochemical methods are also employed, using electrochemical sensors with thin films of tungsten oxide (WO3) to detect NO2 [39]. These sensors are commonly used in portable air quality monitoring devices [40]. Additionally, passive sampling methods followed by laboratory analysis are frequently applied. In these methods, air is sampled onto adsorbent substrates and later analyzed in the laboratory using ion chromatography or other analytical techniques [41]. Table 4 reports the methodologies considered and references for the determination of NO2.
Table 4 provides a summary of the methodologies considered for the determination of NO2. The analyzed matrices include urban environments, atmospheric air, and emissions from water samples. Chemiluminescence is highly sensitive and selective, making it ideal for real-time measurements, but it requires expensive instrumentation and meticulous maintenance. UV-Vis spectrophotometry is cost-effective and relatively simple, although it is less sensitive and prone to interferences. Electrochemical sensors are practical and portable, well-suited for field monitoring, but they have limited lifespans and lower selectivity. Finally, adsorbent substrates enable extended passive monitoring, though they offer reduced temporal resolution and require chemical extraction prior to analysis.

2.5. Carbon Monoxide (CO)

CO is a colorless, tasteless, and odorless gas that diffuses easily throughout the environment. It has moderate solubility in water and is relatively stable, but highly toxic to humans. Major sources include combustion engines, cigarette smoke, stoves and fireplaces, candles, incense, and charcoal grills or barbecues, particularly when used indoors. Its toxicity is primarily due to its high affinity for hemoglobin, forming carboxyhemoglobin (COHb) in the blood, which interferes with oxygen transport. Even low concentrations can cause severe symptoms. The WHO has set guideline values of 10 mg m−3 as an 8 h mean and 100 mg m−3 as a 15 min mean. Several methods are available for determining carbon monoxide (CO) in air, with the most commonly used technique involving automatic analyzers operating on the principle of non-dispersive infrared absorption (NDIR) [42]. This method is standardized in the technical norm UNI EN 14626:20121 [43]. CO analyzers utilize the absorption of infrared radiation at a specific wavelength (4.67 µm), where CO exhibits a characteristic absorption peak. To eliminate interferences from other compounds such as water vapor and carbon dioxide, a “correlation wheel” is used, alternating the passage of radiation through a reference cell containing nitrogen and another containing a known concentration of CO in nitrogen. A pump draws air into a measurement cell, where infrared radiation passes through and is absorbed by the CO present. The difference in signals detected through the two halves of the correlation wheel allows for the precise determination of CO concentration, minimizing interferences and ensuring high sensitivity. Alternative methods for CO determination are also available in the literature. The chemical method with colorimetric reagents employs a reaction in which CO reacts with a specific reagent (palladium chloride, PdCl2) to form a colored compound [44]. The color intensity, measured via spectrophotometry, is proportional to the CO concentration. This method is simple and relatively inexpensive but can be affected by interferences from other gases or compounds in the sample. The electrochemical method, one of the most widely used techniques today, utilizes an electrochemical sensor that measures the variation in electrical current generated by the reaction of CO with an electrode [45]. This method is commonly employed in portable gas detectors due to its ability to provide rapid measurements, even at low concentrations. Chromatographic techniques, though less frequently used, are also applied. In these techniques, the gas sample is separated using chromatography and detected with a flame ionization detector (FID) or a thermal conductivity detector (TCD). Chromatographic methods offer high precision and accuracy but are associated with higher analytical and operational costs [46]. Table 5 reports the methodologies considered and references for the determination of CO.
Table 5 provides a summary of the analytical methodologies evaluated for the determination of CO. The NDIR offers high sensitivity and selectivity, making it particularly suitable for environmental monitoring applications. Nonetheless, the presence of other infrared-absorbing gases can introduce spectral interferences that affect accuracy. Colorimetric methods utilize chemical reagents that react with CO to produce a measurable color change, the intensity of which is proportional to the gas concentration. These methods are cost-effective and user-friendly but generally exhibit lower sensitivity compared to spectroscopic techniques and are more prone to chemical interferences. Electrochemical sensors detect CO via redox reactions occurring at a dedicated electrode. These sensors are typically compact, portable, and capable of real-time monitoring. However, their measurements may be affected by signal drift or instability over time. Despite their high analytical sensitivity and precision, chromatographic techniques are less frequently employed for CO determination, primarily due to their requirement for sophisticated instrumentation and extensive sample preparation procedures.

2.6. Volatile Organic Compounds (VOCs)

VOCs are organic substances characterized by high volatility. They can release vapors into the air, evaporating easily at room temperature. The main VOCs include a variety of chemicals that can have significant effects on indoor air quality and human health. VOC determination is essential for monitoring air pollution, indoor air quality, and for complying with environmental and health regulations. Some VOCs exhibit low reactivity, are often present in small amounts, and do not pose a significant risk to the environment or human health. However, a substantial number of VOCs, particularly when present at higher concentrations, can contribute to air pollution, the formation of photochemical smog, and tropospheric ozone. They can cause respiratory issues, particularly in children [47]. Their monitoring is particularly important in office environments [48]. The effects that VOCs can have on an individual may be short-term or long-term. Short-term effects primarily include irritation of the eyes and respiratory tract [49], especially the nose and throat; headaches, nausea, and dizziness [50]; allergic reactions such as skin rashes [51]. Long-term effects may include damage to organs such as the liver, kidneys, and central nervous system [52], or respiratory problems such as asthma [47]. Some VOCs, such as benzene, are recognized as carcinogenic and can increase the risk of cancer [53]. The main emissive sources of VOCs in indoor environments are cleaning products [54], building materials (e.g., paints and adhesives) [55], wood, and lacquers used in furniture. New furniture or carpets may emit VOCs, especially in the first few weeks after installation [56]. Recent studies show that even stationery [57], laser cutters and engravers [58], laser printers [59], and 3D printers [60] can emit VOCs in indoor environments. To date, there are no universally established limit values for total VOCs (T-VOCs). However, guideline classifications suggest that air quality is considered excellent when T-VOC concentrations are below 300 µg m−3, acceptable when values range between 300 and 1000 µg m−3, and poor when concentrations exceed 1000 µg m−3. VOCs are primarily divided into different categories.
Aliphatic: This category includes chemical compounds containing carbon and hydrogen that do not feature aromatic rings. Aliphatic VOCs are found in many industrial and consumer products such as solvents, fuels, and plasticizers. Methane is one of the primary VOCs in this category. Fortunately, their presence is not particularly harmful to human health or the environment.
Aromatic: These are volatile organic compounds containing one or more benzene rings, which are cyclic structures consisting of six carbon atoms linked by alternating single and double bonds. They are commonly used as solvents in paints, fuels, and various industrial processes. Their presence in the atmosphere is usually related to combustion processes and is often associated with vehicular traffic. Benzene, Toluene, and Xylenes (BTX) are among the most studied aromatic VOCs.
Chlorinated: Unlike the first two, chlorinated VOCs contain chlorine atoms bonded to carbon structures. These compounds are mainly used as industrial solvents, cleaners, disinfectants, etc. Although useful in various sectors, many chlorinated VOCs can be among the most carcinogenic. Chloroform is among the main molecules of the category. Their presence in the atmosphere should be limited and periodically controlled.
Aldehydes: These are characterized by the presence of an aldehyde group (-CHO). They are highly reactive and can be found in both natural sources (e.g., organic decomposition, plant emissions) and anthropogenic sources (e.g., combustion of fuels, building materials). Formaldehyde and acetaldehyde are among the most common.
Alcohols: These compounds contain one or more alcohol functional groups (-OH). They exhibit varying volatility depending on the molecular structure and are found in both natural (e.g., biological fermentation, plants) and anthropogenic (paints, solvents, cleaners) sources. Ethanol, methanol, and isopropanol are among the most common.
Ketones: These are characterized by the presence of a carbonyl group (C=O) bonded to two alkyl or aryl groups. They are highly volatile and originate from both natural (e.g., biological processes) and anthropogenic (e.g., solvents, paints, adhesives) sources. Acetone and methyl ethyl ketone are common examples.
Ethers: These compounds are characterized by an oxygen atom bonded to two alkyl or aryl groups (R-O-R’). They are highly volatile and are primarily used as solvents in paints, adhesives, and industrial processes. Common examples include diethyl ether and methyl-tertiary-butyl-ether (MTBE), which is typical in fuels.
Terpenes: These naturally occurring compounds are composed of isoprene units (C5H8). They are primarily emitted by plants and trees (e.g., pine, citrus) and provide characteristic fragrances. Common examples include limonene, which is studied with ever greater attention, pinene, and myrcene. Terpenes contribute to the formation of secondary organic aerosols and tropospheric ozone. At high concentrations, they can cause respiratory irritation or allergies. Table 6 summarizes the most common VOCs and their primary emissive sources.
Gas chromatography combined with mass spectrometry (GC-MS) is one of the most widely used techniques. This method allows for the identification and quantification of VOCs based on their mass and structural characteristics [61]. However, sensor-based techniques have been developed and are utilized, where specific chemical sensors are employed to detect the presence of VOCs. These sensors operate by detecting changes in electrical, optical, or thermal properties in the presence of specific volatile compounds [62]. Fourier-transform infrared (FTIR) spectroscopy can be used to identify and quantify VOCs through the absorption of specific wavelengths by the compounds [63]. In the tube adsorption technique, VOCs are adsorbed onto a specific material, such as Tenax, and subsequently desorbed for chromatographic analysis [64]. Additionally, passive sampling methods are employed, where a device absorbs the VOCs present in the environment, concentrates them over time, and preserves them for later analysis in the laboratory [65].

3. Systems Adopted to Improve IAQ

Numerous systems are available to improve air quality in enclosed environments. This review considers the main methodologies currently discussed in the literature. In particular, ventilation, the use of HEPA filters, humidity, and the use of eco-sustainable materials can contribute to improving IAQ.

3.1. Ventilation

Ensuring adequate air exchange is essential. This process is carried out through both natural ventilation and controlled mechanical ventilation (CMV) systems [66]. The choice between mechanical and natural ventilation depends on several factors, including building characteristics, local climate, occupant comfort, health requirements [67], and the building’s energy efficiency [68]. Both solutions have advantages and disadvantages (Table 7), and the decision on which to adopt depends on specific circumstances.
Natural ventilation relies on spontaneous air exchange driven by temperature and pressure differences between the interior and exterior of a building [69]. This process occurs through openings such as windows, doors, ventilation grilles, or passive ventilation systems. It is particularly used to reduce the airborne transmission of infections in hospitals [70]. Natural ventilation does not require mechanical systems or electricity, reducing operational costs and avoiding the use of motors or complex systems, making it a more environmentally friendly option. When the outdoor environment is clean and minimally polluted, the incoming air can be of high quality [71]. However, precise control of airflow is not always possible. In extremely cold or hot climates, natural ventilation may be insufficient. Moreover, ventilation effectiveness depends on weather conditions and outdoor air pollution levels [72]. In urban or polluted areas, outdoor air quality may be compromised. Natural ventilation is ideal for settings where external atmospheric conditions are favorable (e.g., low-urbanization areas with good air quality) and where a low-cost, simple system is preferred.
Conversely, mechanical ventilation uses motors, fans, and duct systems to force air exchange. Modern systems are equipped with heat recovery units that enhance energy efficiency by transferring heat between incoming and outgoing air. The main advantages of mechanical ventilation include precise control over ventilation levels, ensuring a constant and uniform airflow regardless of external conditions. These systems typically provide continuous air filtration, reducing fine particulate matter, allergens, and pollutants. Unlike natural ventilation, mechanical ventilation is independent of external weather conditions and ensures adequate air exchange even in enclosed spaces without windows. However, mechanical systems require a higher initial investment and maintenance costs. Installation can be complex and expensive, especially in existing buildings. Filters must be replaced periodically, and motors require regular inspection to maintain optimal operation.
Mechanical ventilation is preferable in environments where air quality control and consistent air exchange are essential, such as high-occupancy buildings, polluted areas, or during seasons when natural ventilation is insufficient or ineffective. Many modern facilities adopt hybrid ventilation systems, combining both methods to optimize energy efficiency and indoor air quality, utilizing natural ventilation whenever possible and supplementing it with mechanical ventilation when necessary.

3.2. Air Purifiers with High-Efficiency Particulate Air (HEPA) Filters

These devices are highly effective in improving indoor air quality, as they can capture extremely small particles, down to 0.3 µm, which constitute the majority of allergens, fine dust, and other airborne contaminants. HEPA purifiers are particularly recommended for individuals with allergies [73], asthma, or other respiratory conditions, but they are also beneficial for anyone seeking to maintain a healthier indoor environment. A HEPA-filter air purifier operates by drawing in room air and passing it through a series of filters. Some purifiers also include additional filtration systems, such as activated carbon filters or UV filters, to remove other impurities like gases and bacteria [74]. The main advantages of HEPA-filter air purifiers are the removal of fine dust and allergens, improvement of air quality, removal of fumes and odors, improvement of respiratory health, silence, and ease of use. The main disadvantages of HEPA-filter air purifiers are room surface area, HEPA filter type, noise, and filter maintenance and replacement. HEPA filters capture dust particles, pollen, pet dander, mold, and dust mites, which are common allergens [75]. They are also used to reduce pollution generated by vehicular traffic [76]. The literature describes nanofilter systems made of nanofibers, which offer higher efficiency than HEPA filters, reaching up to 99% [77]. Their effectiveness has been extensively studied to improve indoor air quality during the SARS-CoV-2 emergency [78]. A HEPA-filter air purifier reduces the concentration of harmful airborne particles [79], making the air cleaner and easier to breathe, particularly beneficial for individuals living in urban areas with high pollution levels. Many HEPA purifiers are also equipped with activated carbon filters [74], which help remove smoke, unpleasant odors, and VOCs that can originate from building materials, paints, cleaning products, or cigarettes. Using a HEPA purifier can help alleviate symptoms associated with respiratory conditions, such as coughing, shortness of breath, and airway irritation, thereby improving daily quality of life [80]. Most HEPA purifiers are designed to operate quietly, minimizing disruption in home or work environments. Additionally, they are generally easy to use and maintain [79].

3.3. Humidity Control

Humidity control in indoor environments is essential for ensuring a healthy and comfortable atmosphere. Excess humidity can lead to several issues, including the proliferation of bacteria and dust mites [81], and an unpleasant, damp sensation that affects air quality and overall well-being [82]. Humidity levels above 60% [83] can create ideal conditions for mold and fungi growth, which not only damage structures and furnishings but also pose health risks, exacerbating respiratory problems and allergies. Additionally, excessive humidity can cause condensation on cold surfaces, leading to the deterioration of materials such as wood, paper, and fabrics. A highly humid environment can also feel uncomfortable, creating an oppressive and sticky sensation of heat. Excess humidity can irritate the respiratory tract, contributing to nasal congestion, coughing, and other respiratory issues [84]. Conversely, humidity levels below 30% [83] can cause discomfort such as dry skin, eye irritation, and respiratory tract irritation, and negative effects on plants and delicate materials. The use of dehumidifiers or maintaining an appropriate humidity level helps prevent these problems [85]. Dehumidifiers are particularly useful in naturally humid environments or in spaces with limited ventilation, such as basements, cellars, or windowless bathrooms [86]. The quality of a dehumidifier often depends on component handling methods, systems, and materials [87]. Dehumidifiers help maintain fresh and comfortable air, reducing perspiration and improving sleep quality. The use of dehumidifiers is an effective solution for keeping humidity levels under control.

3.4. Eco-Sustainable Furniture and Materials

Eco-sustainable furniture materials have become an increasingly popular choice for individuals seeking to furnish their homes or offices responsibly, reducing environmental impact while promoting well-being [88]. The adoption of these materials not only helps minimize the consumption of natural resources and pollution but also contributes to the creation of healthier and safer indoor environments by reducing emissions of VOCs and other harmful substances [89]. Eco-sustainable furniture refers to the use of furniture, materials, and decorations designed to minimize environmental impact throughout their production, use, and disposal [90]. This approach involves adopting sustainable production and consumption practices. Eco-friendly materials are typically renewable resources that can be rapidly regenerated, such as wood sourced from responsibly managed forests [91]. The use of recycled and recyclable materials derived from repurposing processes reduces the demand for new raw materials. Additionally, easily recyclable materials contribute to closing the product life cycle, minimizing waste. Eco-sustainable furniture is often free from harmful chemicals, such as formaldehyde, solvent-based paints, and VOCs [92]. Many eco-friendly products are designed for energy efficiency, reducing energy consumption both during manufacturing and usage. Furthermore, eco-sustainable materials tend to be more durable and resilient, meaning furniture and accessories require less frequent replacement, which lowers resource consumption and waste production [93]. Wood is one of the most common materials used in furniture; however, its production can have a significant environmental impact. Opting for wood certified by the Forest Stewardship Council (FSC) ensures that the material originates from responsible forest management practices that protect ecosystems and local communities [94]. Bamboo is an exceptional resource for furniture due to its rapid growth rate (up to one meter per day) and its ability to thrive without pesticides or chemical fertilizers. It is strong, durable, and versatile, making it suitable for furniture, flooring, textiles, and decorations [95]. Hemp is a resilient and biodegradable plant fiber that can be used in textiles and upholstery. It is also one of the most environmentally friendly crops, as it grows rapidly without the need for pesticides while enhancing soil quality [96]. Organic cotton is cultivated without pesticides or chemical fertilizers, thereby reducing its environmental footprint. It is used for carpets, curtains, cushions, and furniture coverings, and since it is biodegradable, it represents an ecological choice for furnishing [97]. Coconut fiber, commonly used in carpets, mattresses, and cushions, is a natural material derived from the outer husk of the coconut. It is durable, biodegradable, and provides excellent properties for reducing noise pollution [98]. The use of eco-sustainable furniture materials helps lower environmental impact, improves occupant health, and reduces the risk of allergies and respiratory diseases. The adoption of natural materials contributes to healthier indoor environments, ultimately enhancing indoor air quality.

4. Integration of Low-Cost Sensors and Artificial Intelligence in Indoor Air Quality Monitoring

Low-cost sensors (LCSs) for the assessment of indoor air quality represent an increasingly utilized technological solution to enhance environmental awareness and promote health-conscious behaviors. These devices offer a cost-effective and scalable alternative to reference-grade instrumentation for real-time monitoring of indoor environmental parameters [99,100]. Despite their affordability and ease of integration into Internet of Things (IoT) infrastructures [101], LCSs exhibit limitations in terms of accuracy and long-term stability. Their performance is susceptible to drift over time and can be significantly affected by environmental variables such as temperature and relative humidity. As a result, periodic calibration and maintenance are essential to ensure data reliability [102]. Nonetheless, low-cost sensors provide significant benefits, particularly in applications where widespread deployment and user accessibility are prioritized. They are commonly employed for the indirect estimation of indoor air ventilation efficiency through the measurement of CO2 concentrations. This functionality is especially relevant in shared environments such as schools and offices, where appropriate ventilation can reduce the risk of airborne disease transmission [103]. In educational settings, LCSs serve as effective tools for hands-on learning, enabling students to explore concepts in electronics, programming, and environmental science through the construction and deployment of custom air monitoring systems [104]. Furthermore, their integration into home automation platforms allows for responsive control of air purification systems, HVAC units, and user alert systems [105]. Low-cost sensors do not match the precision of laboratory-grade equipment, but their affordability, versatility, and ease of use make them suitable for a wide range of practical applications, particularly in contexts that prioritize awareness, accessibility, and user engagement. In recent years, the integration of artificial intelligence (AI) in indoor air quality monitoring has led to the development of advanced technologies that enhance health and well-being in indoor environments [106]. Numerous projects are currently underway aimed at improving indoor air quality using AI. A significant example is the Optimizing Air Safety for Indoor Spaces (OASIS), project n° F/350321/01-03/X60, funded by the Ministry of Business and Made in Italy within the program “Agreements for Innovation (DM 31 December 2021, D.D. 14 November 2022)”[107]. The project utilizes advanced sensors to detect pollution levels and monitor ventilation systems. This system employs 3D cellular models to simulate the impact of pollutants on the environment, enabling more efficient air quality management. Rome’s Fiumicino Airport will be one of the first buildings to experiment with this technology. Another innovative approach is represented by the use of physics-based machine learning models to approximate indoor air quality. These models combine state-space concepts with recurrent units and decomposition techniques to accurately predict pollutant concentrations, offering efficient and precise solutions [108]. Furthermore, systems such as AirSPEC integrate the Internet of Things (IoT) with machine learning frameworks to detect and predict specific air quality parameters. This combination allows real-time data analysis and accurate predictions, improving the response capability to changes in air quality [109]. AI is revolutionizing the monitoring and improvement of IAQ through various innovative applications. AI enables the continuous collection and analysis of data from environmental sensors. These intelligent systems can detect fluctuations in pollutant levels and provide real-time information about IAQ. AI algorithms can predict trends and potential issues related to air quality, allowing for proactive interventions before conditions worsen. These technologies represent a significant advancement in IAQ monitoring, providing more precise and efficient tools to ensure healthier indoor environments. AI will help create healthier and more efficient indoor environments by providing timely alerts and suggesting corrective actions to protect people’s health. By continuously monitoring air quality and predicting potential hazards, AI can play a crucial role in ensuring that indoor spaces remain safe and conducive to well-being.

5. Conclusions

IAQ is a current issue that continues to capture the attention of researchers and scholars. In this field, research and new technologies converge to improve the quality of life. This review aimed to consider the methodologies used to determine the main markers identified by the WHO related to air quality in confined environments. Analytical methods and systems for improving IAQ were considered. Additionally, a brief overview was provided on the use and applications of low-cost sensors and artificial intelligence to enhance indoor air quality and the health and well-being of individuals. In this context, policymakers and specialized research or quality management bodies must continue to collaborate to ensure a healthy environment for occupants.

Funding

This paper was supported by the EDIAQI project. The EDIAQI project is funded by the European Union under G.A. No. 101057497. The views and opinions expressed are, however, those of the author(s) alone and do not necessarily reflect those of the European Union. Neither the European Union nor the granting authority can be held responsible for them.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Settimo, G.; Manigrasso, M.; Avino, P. Indoor Air Quality: A Focus on the European Legislation and State-of-the-Art Research in Italy. Atmosphere 2020, 11, 370. [Google Scholar] [CrossRef]
  2. WHO Global Air Quality Guidelines: Particulate Matter (PM2.5 and PM10), Ozone, Nitrogen Dioxide, Sulfur Dioxide and Carbon Monoxide. Available online: https://www.who.int/publications/i/item/9789240034228 (accessed on 28 January 2025).
  3. Jones, N.C.; Thornton, C.A.; Mark, D.; Harrison, R.M. Indoor/Outdoor Relationships of Particulate Matter in Domestic Homes with Roadside, Urban and Rural Locations. Atmos. Environ. 2000, 34, 2603–2612. [Google Scholar] [CrossRef]
  4. Settimo, G.; Indinnimeo, L.; Inglessis, M.; De Felice, M.; Morlino, R.; di Coste, A.; Fratianni, A.; Avino, P. Indoor Air Quality Levels in Schools: Role of Student Activities and No Activities. Int. J. Environ. Res. Public Health 2020, 17, 6695. [Google Scholar] [CrossRef] [PubMed]
  5. Settimo, G.; Yu, Y.; Gola, M.; Buffoli, M.; Capolongo, S. Challenges in IAQ for Indoor Spaces: A Comparison of the Reference Guideline Values of Indoor Air Pollutants from the Governments and International Institutions. Atmosphere 2023, 14, 633. [Google Scholar] [CrossRef]
  6. Wei, G.; Yu, X.; Fang, L.; Wang, Q.; Tanaka, T.; Amano, K.; Yang, X. A Review and Comparison of the Indoor Air Quality Requirements in Selected Building Standards and Certifications. Build. Environ. 2022, 226, 109709. [Google Scholar] [CrossRef]
  7. Chen, C.; Zhao, B. Review of Relationship between Indoor and Outdoor Particles: I/O Ratio, Infiltration Factor and Penetration Factor. Atmos. Environ. 2011, 45, 275–288. [Google Scholar] [CrossRef]
  8. Mannan, M.; Al-Ghamdi, S.G. Indoor Air Quality in Buildings: A Comprehensive Review on the Factors Influencing Air Pollution in Residential and Commercial Structure. Int. J. Environ. Res. Public Health 2021, 18, 3276. [Google Scholar] [CrossRef]
  9. Chenari, B.; Dias Carrilho, J.; Gameiro Da Silva, M. Towards Sustainable, Energy-Efficient and Healthy Ventilation Strategies in Buildings: A Review. Renew. Sustain. Energy Rev. 2016, 59, 1426–1447. [Google Scholar] [CrossRef]
  10. Kabir, E.; Kim, K.-H. An Investigation on Hazardous and Odorous Pollutant Emission during Cooking Activities. J. Hazard. Mater. 2011, 188, 443–454. [Google Scholar] [CrossRef]
  11. Settimo, G.; Avino, P. State-of-Art of the Legislation on Odour Emissions with a Focus on the Italian Studies. Environ. Pollut. 2024, 348, 123525. [Google Scholar] [CrossRef]
  12. Lovrić, M.; Gajski, G.; Fernández-Agüera, J.; Pöhlker, M.; Gursch, H.; Lovrić, M.; Switters, J.; Borg, A.; Mureddu, F.; Auguštin, D.H.; et al. Evidence Driven Indoor Air Quality Improvement: An Innovative and Interdisciplinary Approach to Improving Indoor Air Quality. BioFactors 2025, 51, e2126. [Google Scholar] [CrossRef]
  13. Mendell, M.J. Indoor Residential Chemical Emissions as Risk Factors for Respiratory and Allergic Effects in Children: A Review. Indoor Air 2007, 17, 259–277. [Google Scholar] [CrossRef]
  14. Silva, I.G.D.; Reis, I.D.S.; Franco, R.W.D.A.; Sanchez, B.; Canela, M.C. Effect of Volatile Organic Compounds on the Stability of Inorganic Pigments in Oil-Based Paintings. J. Cult. Herit. 2025, 73, 277–285. [Google Scholar] [CrossRef]
  15. Søgaard, R.; Poulsen, P.B.; Gelardi, R.M.; Geschke, S.; Schwensen, J.F.B.; Johansen, J.D. Hidden Formaldehyde in Cosmetic Products. Contact Dermat. 2024, 91, 497–502. [Google Scholar] [CrossRef]
  16. Zeng, T.; Liu, Y.; Jiang, Y.; Zhang, L.; Zhang, Y.; Zhao, L.; Jiang, X.; Zhang, Q. Advanced Materials Design for Adsorption of Toxic Substances in Cigarette Smoke. Adv. Sci. 2023, 10, e2301834. [Google Scholar] [CrossRef] [PubMed]
  17. Chen, H.; Liu, N.; Guo, J.; Wang, L.; Zhang, Y.; Wei, J.; Xu, Y.; Cao, Y.; Zhang, Y. Two-Parameter C-History Method: A Fast and Accurate Method for Determining the Characteristic Parameters of Formaldehyde/VOC Early-Stage Emissions from Building Materials. Sci. Total Environ. 2024, 946, 174218. [Google Scholar] [CrossRef] [PubMed]
  18. Rumchev, K.B.; Spickett, J.T.; Bulsara, M.K.; Phillips, M.R.; Stick, S.M. Domestic Exposure to Formaldehyde Significantly Increases the Risk of Asthma in Young Children. Eur. Respir. J. 2002, 20, 403–408. [Google Scholar] [CrossRef]
  19. ISO 16000-23:2018—UNI Ente Italiano Di Normazione. Available online: https://webstore.uni.com/iso-16000-23-2018 (accessed on 14 May 2025).
  20. Tejada, S.B. Evaluation of Silica Gel Cartridges Coated In Situ With Acidified 2,4-Dinitrophenylhydrazine for Sampling Aldehydes and Ketones in Air. Int. J. Environ. Anal. Chem. 1986, 26, 167–185. [Google Scholar] [CrossRef]
  21. Ho, S.S.H.; Yu, J.Z. Determination of Airborne Carbonyls: Comparison of a Thermal Desorption/GC Method with the Standard DNPH/HPLC Method. Environ. Sci. Technol. 2004, 38, 862–870. [Google Scholar] [CrossRef]
  22. Xu, X.; Su, R.; Zhao, X.; Liu, Z.; Li, D.; Li, X.; Zhang, H.; Wang, Z. Determination of Formaldehyde in Beverages Using Microwave-Assisted Derivatization and Ionic Liquid-Based Dispersive Liquid-Liquid Microextraction Followed by High-Performance Liquid Chromatography. Talanta 2011, 85, 2632–2638. [Google Scholar] [CrossRef]
  23. Martos, P.A.; Pawliszyn, J. Sampling and Determination of Formaldehyde Using Solid-Phase Microextraction with on-Fiber Derivatization. Anal. Chem. 1998, 70, 2311–2320. [Google Scholar] [CrossRef]
  24. Zhang, X.; Kong, Y.; Cao, J.; Li, H.; Gao, R.; Zhang, Y.; Wang, K.; Li, Y.; Ren, Y.; Wang, W. A Sensitive Simultaneous Detection Approach for the Determination of 30 Atmospheric Carbonyls by 2,4-Dinitrophenylhydrazine Derivatization with HPLC-MS Technique and Its Preliminary Application. Chemosphere 2022, 303, 134985. [Google Scholar] [CrossRef]
  25. de Lima, L.F.; Brandão, P.F.; Donegatti, T.A.; Ramos, R.M.; Gonçalves, L.M.; Cardoso, A.A.; Pereira, E.A.; Rodrigues, J.A. 4-Hydrazinobenzoic Acid as a Derivatizing Agent for Aldehyde Analysis by HPLC-UV and CE-DAD. Talanta 2018, 187, 113–119. [Google Scholar] [CrossRef] [PubMed]
  26. Impact of PAH Compounds in Building Materials on Indoor Air Quality-PAHSIS|Finnish Institute of Occupational Health. Available online: https://www.ttl.fi/en/research/projects/impact-pah-compounds-building-materials-indoor-air-quality-pahsis (accessed on 2 October 2024).
  27. Poster, D.L.; Schantz, M.M.; Sander, L.C.; Wise, S.A. Analysis of Polycyclic Aromatic Hydrocarbons (PAHs) in Environmental Samples: A Critical Review of Gas Chromatographic (GC) Methods. Anal. Bioanal. Chem. 2006, 386, 859–881. [Google Scholar] [CrossRef] [PubMed]
  28. Motelay-Massei, A.; Harner, T.; Shoeib, M.; Diamond, M.; Stern, G.; Rosenberg, B. Using Passive Air Samplers to Assess Urban-Rural Trends for Persistent Organic Pollutants and Polycyclic Aromatic Hydrocarbons. 2. Seasonal Trends for PAHs, PCBs, and Organochlorine Pesticides. Environ. Sci. Technol. 2005, 39, 5763–5773. [Google Scholar] [CrossRef]
  29. Jaward, F.M.; Farrar, N.J.; Harner, T.; Sweetman, A.J.; Jones, K.C. Passive Air Sampling of Polycyclic Aromatic Hydrocarbons and Polychlorinated Naphthalenes across Europe. Environ. Toxicol. Chem. 2004, 23, 1355–1364. [Google Scholar] [CrossRef]
  30. Harner, T.; Su, K.; Genualdi, S.; Karpowicz, J.; Ahrens, L.; Mihele, C.; Schuster, J.; Charland, J.-P.; Narayan, J. Calibration and Application of PUF Disk Passive Air Samplers for Tracking Polycyclic Aromatic Compounds (PACs). Atmos. Environ. 2013, 75, 123–128. [Google Scholar] [CrossRef]
  31. Zacharia, R.; Ulbricht, H.; Hertel, T. Interlayer Cohesive Energy of Graphite from Thermal Desorption of Polyaromatic Hydrocarbons. Phys. Rev. B-Condens. Matter Mater. Phys. 2004, 69, 155406. [Google Scholar] [CrossRef]
  32. Liu, Y.; Xu, Y.; Xu, W.; He, Z.; Fu, C.; Du, F. Radon and Lung Cancer: Current Status and Future Prospects. Crit. Rev. Oncol. Hematol. 2024, 198, 104363. [Google Scholar] [CrossRef]
  33. Righi, S.; Bruzzi, L. Natural Radioactivity and Radon Exhalation in Building Materials Used in Italian Dwellings. J. Environ. Radioact. 2006, 88, 158–170. [Google Scholar] [CrossRef]
  34. Prichard, H.M.; Mariën, K. A Passive Diffusion 222Rn Sampler Based on Activated Carbon Adsorption. Health Phys. 1985, 48, 797–803. [Google Scholar] [CrossRef]
  35. Urban, M.; Piesch, E. Low Level Environmental Radon Dosimetry with a Passive Track Etch Detector Device. Radiat. Prot. Dosim. 1981, 1, 97–109. [Google Scholar]
  36. Kotrappa, P.; Dempsey, J.C.; Hickey, J.R.; Stieff, L.R. An Electret Passive Environmental 222rn Monitor Based on Ionization Measurement. Health Phys. 1988, 54, 47–56. [Google Scholar] [CrossRef] [PubMed]
  37. Dunlea, E.J.; Herndon, S.C.; Nelson, D.D.; Volkamer, R.M.; San Martini, F.; Sheehy, P.M.; Zahniser, M.S.; Shorter, J.H.; Wormhoudt, J.C.; Lamb, B.K.; et al. Evaluation of Nitrogen Dioxide Chemiluminescence Monitors in a Polluted Urban Environment. Atmos. Chem. Phys. 2007, 7, 2691–2704. [Google Scholar] [CrossRef]
  38. García-Robledo, E.; Corzo, A.; Papaspyrou, S. A Fast and Direct Spectrophotometric Method for the Sequential Determination of Nitrate and Nitrite at Low Concentrations in Small Volumes. Mar. Chem. 2014, 162, 30–36. [Google Scholar] [CrossRef]
  39. Shendage, S.S.; Patil, V.L.; Vanalakar, S.A.; Patil, S.P.; Harale, N.S.; Bhosale, J.L.; Kim, J.H.; Patil, P.S. Sensitive and Selective NO2 Gas Sensor Based on WO3 Nanoplates. Sens. Actuators B Chem. 2017, 240, 426–433. [Google Scholar] [CrossRef]
  40. Khan, M.A.H.; Rao, M.V.; Li, Q. Recent Advances in Electrochemical Sensors for Detecting Toxic Gases: NO2, SO2 and H2S. Sensors 2019, 19, 905. [Google Scholar] [CrossRef]
  41. Tang, Y.S.; Cape, J.N.; Sutton, M.A. Development and Types of Passive Samplers for Monitoring Atmospheric NO2 and NH3 Concentrations. Sci. World J. 2001, 1, 513–529. [Google Scholar] [CrossRef]
  42. Tan, X.; Zhang, H.; Li, J.; Wan, H.; Guo, Q.; Zhu, H.; Liu, H.; Yi, F. Non-Dispersive Infrared Multi-Gas Sensing via Nanoantenna Integrated Narrowband Detectors. Nat. Commun. 2020, 11, 5245. [Google Scholar] [CrossRef]
  43. UNI EN 14626:2012—UNI Ente Italiano Di Normazione. Available online: https://store.uni.com/uni-en-14626-2012 (accessed on 14 May 2025).
  44. Allen, T.H.; Root, W.S. Colorimetric Determination of Carbon Monoxide in Air by an Improved Palladium Chloride Method. J. Biol. Chem. 1955, 216, 309–317. [Google Scholar] [CrossRef]
  45. Łukaszewski, M.; Soszko, M.; Czerwiński, A. Electrochemical Methods of Real Surface Area Determination of Noble Metal Electrodes—An Overview. Int. J. Electrochem. Sci. 2016, 11, 4442–4469. [Google Scholar] [CrossRef]
  46. Atta, K.R.; Gavril, D.; Karaiskakis, G. A New Gas Chromatographic Methodology for the Estimation of the Composition of Binary Gas Mixtures. J. Chromatogr. Sci. 2003, 41, 123–132. [Google Scholar] [CrossRef]
  47. Rumchev, K.; Spickett, J.; Bulsara, M.; Phillips, M.; Stick, S. Association of Domestic Exposure to Volatile Organic Compounds with Asthma in Young Children. Thorax 2004, 59, 746–751. [Google Scholar] [CrossRef] [PubMed]
  48. Wolkoff, P.; Wilkins, C.K.; Clausen, P.A.; Nielsen, G.D. Organic Compounds in Office Environments-Sensory Irritation, Odor, Measurements and the Role of Reactive Chemistry. Indoor Air 2006, 16, 7–19. [Google Scholar] [CrossRef]
  49. Wolkoff, P.; Nielsen, G.D. Organic Compounds in Indoor Air-Their Relevance for Perceived Indoor Air Quality? Atmos. Environ. 2001, 35, 4407–4417. [Google Scholar] [CrossRef]
  50. Chen, D.; Xu, Y.; Xu, J.; Lian, M.; Zhang, W.; Wu, W.; Wu, M.; Zhao, J. The Vertical Distribution of VOCs and Their Impact on the Environment: A Review. Atmosphere 2022, 13, 1940. [Google Scholar] [CrossRef]
  51. Pacheco-Torgal, F.; Falkinham, J.O.; Gałaj, J.A. Advances in the Toxicity of Construction and Building Materials; Woodhead Publishing: Cambridge, UK, 2022; p. 334. [Google Scholar]
  52. Anand, S.S.; Philip, B.K.; Mehendale, H.M. Volatile Organic Compounds. In Encyclopedia of Toxicology, 3rd ed.; Academic Press: Cambridge, MA, USA, 2014; pp. 967–970. [Google Scholar]
  53. Vardoulakis, S.; Giagloglou, E.; Steinle, S.; Davis, A.; Sleeuwenhoek, A.; Galea, K.S.; Dixon, K.; Crawford, J.O. Indoor Exposure to Selected Air Pollutants in the Home Environment: A Systematic Review. Int. J. Environ. Res. Public Health 2020, 17, 8972. [Google Scholar] [CrossRef]
  54. Bello, A.; Quinn, M.M.; Perry, M.J.; Milton, D.K. Characterization of Occupational Exposures to Cleaning Products Used for Common Cleaning Tasks-a Pilot Study of Hospital Cleaners. Environ. Health A Glob. Access Sci. Source 2009, 8, 11. [Google Scholar] [CrossRef] [PubMed]
  55. Yu, C.; Crump, D. A Review of the Emission of VOCs from Polymeric Materials Used in Buildings. Build. Environ. 1998, 33, 357–374. [Google Scholar] [CrossRef]
  56. Jiang, C.; Li, D.; Zhang, P.; Li, J.; Wang, J.; Yu, J. Formaldehyde and Volatile Organic Compound (VOC) Emissions from Particleboard: Identification of Odorous Compounds and Effects of Heat Treatment. Build. Environ. 2017, 117, 118–126. [Google Scholar] [CrossRef]
  57. Lee, S.C.; Lam, S.; Kin Fai, H. Characterization of VOCs, Ozone, and PM10 Emissions from Office Equipment in an Environmental Chamber. Build. Environ. 2001, 36, 837–842. [Google Scholar] [CrossRef]
  58. O’neill, K.; Niu, X.; Wang, J.; Fang, R. Respirable Particles and Gas Contaminants Emissions from a Desktop Laser Cutter and Engraver. Aerosol Air Qual. Res. 2024, 24, 240032. [Google Scholar] [CrossRef]
  59. Kagi, N.; Fujii, S.; Horiba, Y.; Namiki, N.; Ohtani, Y.; Emi, H.; Tamura, H.; Kim, Y.S. Indoor Air Quality for Chemical and Ultrafine Particle Contaminants from Printers. Build. Environ. 2007, 42, 1949–1954. [Google Scholar] [CrossRef]
  60. Steinle, P. Characterization of Emissions from a Desktop 3D Printer and Indoor Air Measurements in Office Settings. J. Occup. Environ. Hyg. 2016, 13, 121–132. [Google Scholar] [CrossRef] [PubMed]
  61. Hoshi, J.; Higuchi, M.; Sasaki, Y.; Korenaga, T. Determination of Oxygenated Volatile Organic Compounds in Ambient Air Using Canister Collection–Gas Chromatography/Mass Spectrometry. Anal. Sci. 2007, 23, 987–992. [Google Scholar] [CrossRef] [PubMed]
  62. Hu, L.-P.; Li, Y.; Zhang, L.; Zhang, L.-M.; Wang, J.-D. Advanced Development of Remote Sensing FTIR in Air Environment Monitoring. Guang Pu Xue Yu Guang Pu Fen Xi/Spectrosc. Spectr. Anal. 2006, 26, 1863–1867. [Google Scholar]
  63. Fathy, A.; Sabry, Y.M.; Amr, M.; Gnambodoe-Capo-chichi, M.; Anwar, M.; Ghoname, A.O.; Amr, A.; Saeed, A.; Gad, M.; Haron, M.A.; et al. MEMS FTIR Optical Spectrometer Enables Detection of Volatile Organic Compounds (VOCs) in Part-per-Billion (Ppb) Range for Air Quality Monitoring. In Proceedings of the MOEMS and Miniaturized Systems XVIII, San Francisco, CA, USA, 4 March 2019; SPIE: Bellingham, WA, USA; Volume 10931, pp. 69–75. [Google Scholar]
  64. Czaplicka, M.; Klejnowski, K. Determination of Volatile Organic Compounds in Ambient Air: Comparison of Methods. J. Chromatogr. A 2002, 976, 369–376. [Google Scholar] [CrossRef]
  65. Matysik, S.; Herbarth, O.; Mueller, A. Determination of Microbial Volatile Organic Compounds (MVOCs) by Passive Sampling onto Charcoal Sorbents. Chemosphere 2009, 76, 114–119. [Google Scholar] [CrossRef]
  66. Lim, A.-Y.; Yoon, M.; Kim, E.-H.; Kim, H.-A.; Lee, M.J.; Cheong, H.-K. Effects of Mechanical Ventilation on Indoor Air Quality and Occupant Health Status in Energy-Efficient Homes: A Longitudinal Field Study. Sci. Total Environ. 2021, 785, 147324. [Google Scholar] [CrossRef]
  67. Frontczak, M.; Wargocki, P. Literature Survey on How Different Factors Influence Human Comfort in Indoor Environments. Build. Environ. 2011, 46, 922–937. [Google Scholar] [CrossRef]
  68. Vakiloroaya, V.; Samali, B.; Fakhar, A.; Pishghadam, K. A Review of Different Strategies for HVAC Energy Saving. Energy Convers. Manag. 2014, 77, 738–754. [Google Scholar] [CrossRef]
  69. Ghiaus, C.; Allard, F. The Physics of Natural Ventilation. In Natural Ventilation in the Urban Environment; Routledge: New York, NY, USA, 2005; ISBN 978-1-84977-206-8. [Google Scholar]
  70. Qian, H.; Li, Y.; Seto, W.H.; Ching, P.; Ching, W.H.; Sun, H.Q. Natural Ventilation for Reducing Airborne Infection in Hospitals. Build. Environ. 2010, 45, 559–565. [Google Scholar] [CrossRef] [PubMed]
  71. Remion, G.; Moujalled, B.; El Mankibi, M. Review of Tracer Gas-Based Methods for the Characterization of Natural Ventilation Performance: Comparative Analysis of Their Accuracy. Build. Environ. 2019, 160, 106180. [Google Scholar] [CrossRef]
  72. Shrestha, P.M.; Humphrey, J.L.; Carlton, E.J.; Adgate, J.L.; Barton, K.E.; Root, E.D.; Miller, S.L. Impact of Outdoor Air Pollution on Indoor Air Quality in Low-Income Homes during Wildfire Seasons. Int. J. Environ. Res. Public Health 2019, 16, 3535. [Google Scholar] [CrossRef]
  73. Wood, R.A.; Johnson, E.F.; Van Natta, M.L.; Pei, H.C.; Eggleston, P.A. A Placebo-Controlled Trial of a HEPA Air Cleaner in the Treatment of Cat Allergy. Am. J. Respir. Crit. Care Med. 1998, 158, 115–120. [Google Scholar] [CrossRef]
  74. Li, P.; Wang, C.; Zhang, Y.; Wei, F. Air Filtration in the Free Molecular Flow Regime: A Review of High-Efficiency Particulate Air Filters Based on Carbon Nanotubes. Small 2014, 10, 4543–4561. [Google Scholar] [CrossRef]
  75. Lowther, S.D.; Deng, W.; Fang, Z.; Booker, D.; Whyatt, D.J.; Wild, O.; Wang, X.; Jones, K.C. How Efficiently Can HEPA Purifiers Remove Priority Fine and Ultrafine Particles from Indoor Air? Environ. Int. 2020, 144, 106001. [Google Scholar] [CrossRef]
  76. Peck, R.L.; Grinshpun, S.A.; Yermakov, M.; Rao, M.B.; Kim, J.; Reponen, T. Efficiency of Portable HEPA Air Purifiers against Traffic Related Combustion Particles. Build. Environ. 2016, 98, 21–29. [Google Scholar] [CrossRef]
  77. Ahn, Y.C.; Park, S.K.; Kim, G.T.; Hwang, Y.J.; Lee, C.G.; Shin, H.S.; Lee, J.K. Development of High Efficiency Nanofilters Made of Nanofibers. Curr. Appl. Phys. 2006, 6, 1030–1035. [Google Scholar] [CrossRef]
  78. Myers, N.T.; Laumbach, R.J.; Black, K.G.; Ohman-Strickland, P.; Alimokhtari, S.; Legard, A.; De Resende, A.; Calderón, L.; Lu, F.T.; Mainelis, G.; et al. Portable Air Cleaners and Residential Exposure to SARS-CoV-2 Aerosols: A Real-World Study. Indoor Air 2022, 32, e13029. [Google Scholar] [CrossRef]
  79. Cheek, E.; Guercio, V.; Shrubsole, C.; Dimitroulopoulou, S. Portable Air Purification: Review of Impacts on Indoor Air Quality and Health. Sci. Total Environ. 2021, 766, 142585. [Google Scholar] [CrossRef] [PubMed]
  80. Sublett, J.L. Effectiveness of Air Filters and Air Cleaners in Allergic Respiratory Diseases: A Review of the Recent Literature. Curr. Allergy Asthma Rep. 2011, 11, 395–402. [Google Scholar] [CrossRef] [PubMed]
  81. Cabrera, P.; Julià-Serdà, G.; de Castro, F.R.; Caminero, J.; Barber, D.; Carrillo, T. Reduction of House Dust Mite Allergens after Dehumidifier Use. J. Allergy Clin. Immunol. 1995, 95, 635–636. [Google Scholar] [CrossRef] [PubMed]
  82. Mendell, M.J.; Mirer, A.G.; Cheung, K.; Tong, M.; Douwes, J. Respiratory and Allergic Health Effects of Dampness, Mold, and Dampness-Related Agents: A Review of the Epidemiologic Evidence. Environ. Health Perspect. 2011, 119, 748–756. [Google Scholar] [CrossRef]
  83. Arundel, A.V.; Sterling, E.M.; Biggin, J.H.; Sterling, T.D. Indirect Health Effects of Relative Humidity in Indoor Environments. Environ. Health Perspect. 1986, 65, 351–361. [Google Scholar] [CrossRef]
  84. Guo, M.; Zhou, M.; Li, B.; Du, C.; Yao, R.; Wang, L.; Yang, X.; Yu, W. Reducing Indoor Relative Humidity Can Improve the Circulation and Cardiorespiratory Health of Older People in a Cold Environment: A Field Trial Conducted in Chongqing, China. Sci. Total Environ. 2022, 817, 152695. [Google Scholar] [CrossRef]
  85. Jain, S.; Bansal, P.K. Performance Analysis of Liquid Desiccant Dehumidification Systems. Int. J. Refrig. 2007, 30, 861–872. [Google Scholar] [CrossRef]
  86. Bamba, I.; Azuma, M.; Hamada, N.; Kubo, H.; Isoda, N. Case Study of Airborne Fungi According to Air Temperature and Relative Humidity in Houses with Semi-Basements Adjacent to a Forested Hillside. Biocontrol Sci. 2014, 19, 1–9. [Google Scholar] [CrossRef]
  87. Qi, R.; Dong, C.; Zhang, L.-Z. A Review of Liquid Desiccant Air Dehumidification: From System to Material Manipulations. Energy Build. 2020, 215, 109897. [Google Scholar] [CrossRef]
  88. Zhu, H.; Luo, W.; Ciesielski, P.N.; Fang, Z.; Zhu, J.Y.; Henriksson, G.; Himmel, M.E.; Hu, L. Wood-Derived Materials for Green Electronics, Biological Devices, and Energy Applications. Chem. Rev. 2016, 116, 9305–9374. [Google Scholar] [CrossRef]
  89. Cinelli, P.; Anguillesi, I.; Lazzeri, A. Green Synthesis of Flexible Polyurethane Foams from Liquefied Lignin. Eur. Polym. J. 2013, 49, 1174–1184. [Google Scholar] [CrossRef]
  90. Kumar, R.; Ul Haq, M.I.; Raina, A.; Anand, A. Industrial Applications of Natural Fibre-Reinforced Polymer Composites–Challenges and Opportunities. Int. J. Sustain. Eng. 2019, 12, 212–220. [Google Scholar] [CrossRef]
  91. Wintle, B.A.; Lindenmayer, D.B. Adaptive Risk Management for Certifiably Sustainable Forestry. For. Ecol. Manag. 2008, 256, 1311–1319. [Google Scholar] [CrossRef]
  92. Ge, S.; Ma, N.L.; Jiang, S.; Ok, Y.S.; Lam, S.S.; Li, C.; Shi, S.Q.; Nie, X.; Qiu, Y.; Li, D.; et al. Processed Bamboo as a Novel Formaldehyde-Free High-Performance Furniture Biocomposite. ACS Appl. Mater. Interfaces 2020, 12, 30824–30832. [Google Scholar] [CrossRef] [PubMed]
  93. Asdrubali, F.; Ferracuti, B.; Lombardi, L.; Guattari, C.; Evangelisti, L.; Grazieschi, G. A Review of Structural, Thermo-Physical, Acoustical, and Environmental Properties of Wooden Materials for Building Applications. Build. Environ. 2017, 114, 307–332. [Google Scholar] [CrossRef]
  94. Anderson, R.C.; Hansen, E.N. The Impact of Environmental Certification on Preferences for Wood Furniture: A Conjoint Analysis Approach. For. Prod. J. 2004, 54, 42–50. [Google Scholar]
  95. Yu, Y.; Zhu, R.; Wu, B.; Hu, Y.; Yu, W. Fabrication, Material Properties, and Application of Bamboo Scrimber. Wood Sci. Technol. 2015, 49, 83–98. [Google Scholar] [CrossRef]
  96. Crini, G.; Lichtfouse, E.; Chanet, G.; Morin-Crini, N. Applications of Hemp in Textiles, Paper Industry, Insulation and Building Materials, Horticulture, Animal Nutrition, Food and Beverages, Nutraceuticals, Cosmetics and Hygiene, Medicine, Agrochemistry, Energy Production and Environment: A Review. Environ. Chem. Lett. 2020, 18, 1451–1476. [Google Scholar] [CrossRef]
  97. Kushwaha, A.; Chaudhary, K.; Prakash, C. A Study on the Mechanical Properties of Pineapple, Bamboo, and Cotton Woven Fabrics. Biomass Convers. Biorefinery 2024, 14, 16307–16318. [Google Scholar] [CrossRef]
  98. Hassan, T.; Jamshaid, H.; Mishra, R.; Khan, M.Q.; Petru, M.; Novak, J.; Choteborsky, R.; Hromasova, M. Acoustic, Mechanical and Thermal Properties of Green Composites Reinforced with Natural Fiberswaste. Polymers 2020, 12, 654. [Google Scholar] [CrossRef]
  99. Spinelle, L.; Gerboles, M.; Kok, G.; Persijn, S.; Sauerwald, T. Review of Portable and Low-Cost Sensors for the Ambient Air Monitoring of Benzene and Other Volatile Organic Compounds. Sensors 2017, 17, 1520. [Google Scholar] [CrossRef] [PubMed]
  100. Castell, N.; Dauge, F.R.; Schneider, P.; Vogt, M.; Lerner, U.; Fishbain, B.; Broday, D.; Bartonova, A. Can Commercial Low-Cost Sensor Platforms Contribute to Air Quality Monitoring and Exposure Estimates? Environ. Int. 2017, 99, 293–302. [Google Scholar] [CrossRef]
  101. Zampolli, S.; Elmi, I.; Ahmed, F.; Passini, M.; Cardinali, G.C.; Nicoletti, S.; Dori, L. An Electronic Nose Based on Solid State Sensor Arrays for Low-Cost Indoor Air Quality Monitoring Applications. Sens. Actuators B Chem. 2004, 101, 39–46. [Google Scholar] [CrossRef]
  102. Mead, M.I.; Popoola, O.A.M.; Stewart, G.B.; Landshoff, P.; Calleja, M.; Hayes, M.; Baldovi, J.J.; McLeod, M.W.; Hodgson, T.F.; Dicks, J.; et al. The Use of Electrochemical Sensors for Monitoring Urban Air Quality in Low-Cost, High-Density Networks. Atmos. Environ. 2013, 70, 186–203. [Google Scholar] [CrossRef]
  103. Peng, Z.; Jimenez, J.L. Exhaled CO2 as a COVID-19 Infection Risk Proxy for Different Indoor Environments and Activities. Environ. Sci. Technol. Lett. 2021, 8, 392–397. [Google Scholar] [CrossRef] [PubMed]
  104. Thepnurat, M.; Saphet, P.; Tong-On, A. Low-Cost DIY Vane Anemometer Based on LabVIEW Interface for Arduino. J. Phys. Conf. Ser. 2018, 1144, 012028. [Google Scholar] [CrossRef]
  105. Tapashetti, A.; Vegiraju, D.; Ogunfunmi, T. IoT-Enabled Air Quality Monitoring Device: A Low Cost Smart Health Solution; IEEE: Seattle, WA, USA, 2016; pp. 682–685. [Google Scholar]
  106. Halhoul Merabet, G.; Essaaidi, M.; Ben Haddou, M.; Qolomany, B.; Qadir, J.; Anan, M.; Al-Fuqaha, A.; Abid, M.R.; Benhaddou, D. Intelligent Building Control Systems for Thermal Comfort and Energy-Efficiency: A Systematic Review of Artificial Intelligence-Assisted Techniques. Renew. Sustain. Energy Rev. 2021, 144, 110969. [Google Scholar] [CrossRef]
  107. Oasis, l’AI per Qualità dell’aria e Salute Delle Persone » inno3; Roma (Italy). 2024. Available online: https://inno3.it/2024/06/21/oasis-santer-reply-enea-cefriel-ai-per-qualita-dellaria-e-salute-delle-persone/ (accessed on 14 May 2025).
  108. Wei, W.; Ramalho, O.; Malingre, L.; Sivanantham, S.; Little, J.C.; Mandin, C. Machine Learning and Statistical Models for Predicting Indoor Air Quality. Indoor Air 2019, 29, 704–726. [Google Scholar] [CrossRef]
  109. Reggente, M.; Höhn, R.; Takahama, S. An Open Platform for Aerosol InfraRed Spectroscopy Analysis-AIRSpec. Atmos. Meas. Tech. 2019, 12, 2313–2329. [Google Scholar] [CrossRef]
Table 1. Comparison of alternative analytical methodologies considered for the determination of HCHO.
Table 1. Comparison of alternative analytical methodologies considered for the determination of HCHO.
LODLDRCorrelation
Coefficient
RecoveryReference
Thermal desorption0.26 ppbv a0.5–2.5 ppbv0.9910-[21]
Assisted derivatization0.12 ng·mL−1 b0.5–50 ng mL−10.996584.9–95.1%[22]
Passive sampling4.6 ppbv15–3200 ppbv0.9990-[23]
LC-MS0.395 ng mL−11–600 ng mL−10.9902-[24]
LC-DAD5 ng·mL−110 µg mL−1 c–n.d.0.9990-[25]
a Assume a sampled air volume of 24 L, i.e., 4-h sampling at 0.1 L min−1; b nanograms/milliliters; c micrograms/milliliters.
Table 2. The methodologies considered for the determination of PAHs.
Table 2. The methodologies considered for the determination of PAHs.
Methodology UsedMatrixReference
Adsorbent tubes and GC-MSEnvironmental[27]
Adsorbent tubes and LC-MSAir urban-rural[28]
Polyurethane foamAir[30]
Thermal desorptionAir[31]
Table 3. The methodologies considered for the determination of radon.
Table 3. The methodologies considered for the determination of radon.
Methodology UsedMatrixReference
Ionization chamberBuilding Materials[33]
Solid scintillationAir[34]
Alpha track detectionEnvironmental[35]
ElectretEnvironmental[36]
Table 4. The methodologies considered for the determination of NO2.
Table 4. The methodologies considered for the determination of NO2.
Methodology UsedMatrixReference
ChemiluminescenceUrban Environment[37]
UV-Vis SpectrophotometryMarine and freshwater samples[38]
Electrochemical sensorsAtmospheric Air[38]
Adsorbent substratesAtmospheric Air[41]
Table 5. The methodologies considered for the determination of CO.
Table 5. The methodologies considered for the determination of CO.
Methodology UsedMatrixReference
NDIRGases[42]
Colorimetric reagentsAir[44]
Electrochemical sensor-[45]
Chromatographic techniquesPure gases[46]
Table 6. Most common VOCs and main emission sources.
Table 6. Most common VOCs and main emission sources.
TypologyCompoundMain Emission Sources
Aliphatic HydrocarbonsMethaneNatural emissions and combustion phenomena
Aromatic HydrocarbonsBenzeneIndustrial processes and vehicular traffic
ToluenePaints, glues, and solvents
Halogenated HydrocarbonsChloroformIndustrial processes
AldehydesFormaldehydeBuilding materials, furniture, and cleaning products
AlcoholsEthanolDisinfectants and cleaning products
PropanolSolvents and cleaning products
KetonesAcetoneSolvents and nail polish removers
EstersEthyl acetatePaints and adhesives
TerpenesLimoneneCleaning products and air fresheners
Table 7. The main advantages and disadvantages of natural and mechanical ventilation.
Table 7. The main advantages and disadvantages of natural and mechanical ventilation.
Ventilation
NaturalMechanics
AdvantagesDisadvantagesAdvantagesDisadvantages
AffordabilityLimited controlOptimal air controlHigh costs
SustainabilityDependence on external conditionsGreater energy efficiencyEnergy consumption
Difficulty in the intermediate seasonsImproved air qualityRegular maintenance
Independence from weather conditions
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Notardonato, I.; Di Fiore, C.; Avino, P. Methodologies Used to Determine the Main Markers of Indoor Air Quality. Purification 2025, 1, 3. https://doi.org/10.3390/purification1010003

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Notardonato I, Di Fiore C, Avino P. Methodologies Used to Determine the Main Markers of Indoor Air Quality. Purification. 2025; 1(1):3. https://doi.org/10.3390/purification1010003

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Notardonato, Ivan, Cristina Di Fiore, and Pasquale Avino. 2025. "Methodologies Used to Determine the Main Markers of Indoor Air Quality" Purification 1, no. 1: 3. https://doi.org/10.3390/purification1010003

APA Style

Notardonato, I., Di Fiore, C., & Avino, P. (2025). Methodologies Used to Determine the Main Markers of Indoor Air Quality. Purification, 1(1), 3. https://doi.org/10.3390/purification1010003

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