Emission characteristics and probabilistic health risk of volatile organic compounds from leather sofa.

Furniture is identified as a vital volatile organic compound (VOC) emission source in the indoor environment. Leather has become the most common raw and auxiliary fabric material for upholstered furniture, particularly with extensive consumption in sofas, due to its abundant resources and efficient functions. Despite being widely traded across the world, little research has been conducted on the VOCs released by leather materials and their health risk assessment in the indoor environment. Accordingly, this study investigated the VOC emissions of leather with different grades and the health risk of the inhalation exposure. Based on the ultra-fast gas phase electronic nose (EN) and GC-FID/Qtof, the substantial emissions of aliphatic aldehyde ketones (Aks), particularly hexanal, appear to be the cause of off-flavor in medium and low grade (MG and LG) sofa leathers. The health risk assessment indicated that leather materials barely pose non-carcinogenic and carcinogenic effects to residents. Given the abundance of VOC sources and the accumulation of health risks in the indoor environment, more stringent specifications concerning qualitative and quantitative content should be extended to provide VOC treatment basic for the manufacturing industry and obtain better indoor air quality.

Long-term emission characteristics of VOCs from building materials.

Long-term emission behaviors of volatile organic compounds (VOCs) from indoor buildings materials heavily depend on the value of three key parameters (initial concentration C0, diffusion coefficient Dm, partition coefficient K) that govern emissions over time. We made the first attempt to quantitatively explore the variation of parameters through a long-lasting aging test that simulates natural indoor exposure. Over a span of 431 days, we obtained a substantial dataset consisting of ten thousand data points. The parameters of six VOCs (formaldehyde, benzene, toluene, ethylbenzene, o-xylene, p-m-xylene) from three kinds of wood-based boards with different aging intervals were determined. Our findings demonstrate that C0 decreases exponentially with aging time, while Dm and K merely fluctuate with it. With the obtained correlations, ventilation time for renovated house is proposed to meet the WHO standard. These results lay the groundwork for predicting long-term indoor VOC concentrations, which is crucial for indoor air quality pre-evaluation.

Exposure to indoor air pollution using biomass among rural households in Southern Ethiopia.

Most rural households in Ethiopia depend on traditional cooking fuels. The inefficient combustion of those fuels significantly raises health concerns by exposing them to indoor air pollution. This study aimed to assess the factors contributing to indoor air pollution exposure in rural households. The study was based on data from 573 households selected randomly using a multi-stage sampling approach. Descriptive statistics and a Generalized Ordered Logit model, which explores the relationship between various independent variables and levels of exposure to indoor air pollution, were used. The study employed indicators such as traditional solid fuel use, inadequate ventilation during cooking, and lack of improved cookstoves as proxies to assess households' exposure to indoor air pollution. More than 79% of households were found to be severely polluted. Women were the most exposed to indoor air pollution. The number of rooms, having a bank or microfinance savings account, education, income, access to electricity, floor building material, number of dependent family members, and cooking time were the main contributing factors. The use of clean fuels, improved cookstoves, and adequate ventilation must be strongly advocated.

Development, Validation, and Reliability Analysis of the Household-Related Air Pollution on the Childhood Bronchial Asthma Onset Checklist (HAPBAC-Checklist).

Introduction Most studies on indoor air pollution for childhood bronchial asthma (BA) were focused on institutions such as schools. However, many asthma triggers are household sources such as consumer products, smoking, and pets. In Malaysia, there is no specific checklist to evaluate the risk of childhood BA onset from household factors. Thus, the study aims to develop and validate an observation checklist for assessing household-related air pollution on childhood BA onset. Methodology The study was conducted in Kota Bharu Kelantan from March to November 2023. The development of the checklist was conducted in five stages: 1) the construction of domains and items from the existing literature, 2) interviews with the parents, 3) content validation by ten experts (item-level content validity index (I-CVI) and scale-level content validity index (S-CVI), 4) face validation by 12 experts (item-level face validity index (I-FVI) and scale-level face validity index (S-FVI)), and (5) reliability analysis (kappa agreement analysis) involving 20 houses assessed by two assessors. Results The initial draft of the checklist contained five domains with 57 items: sociodemographic (19 items), family history (three items), child's medical history (six items), household attributes (19 items), and outdoor attributes (10 items). The I-CVI scores ranged from 0.90 to 1.00, indicating good relevancy. The S-CVI value was 0.97, showing a satisfactory level. The I-FVI was at least 0.96, and the S-FVI of 0.98 indicating the participants easily understood the checklist. The kappa analysis for five domains combined was 0.92 (95%CI: 0.89-0.95). The final validated checklist consists of five domains with 59 items. Discussion and conclusion The Household-Related Air Pollution on the Childhood Bronchial Asthma Onset Checklist (HAPBAC-Checklist) was designed to address household air pollution originating from indoor sources. However, recognizing the impact of outdoor factors through various pathways, along with considering family history of atopy and medical conditions, is important. The checklist, developed in Malay, aims to enhance utilization and adoption, particularly among local healthcare professionals and authorities. The checklist is a valid and reliable tool for assessing household-related air pollution on childhood BA onset. This novel checklist significantly benefits screening indoor air quality, crucial for preventing childhood BA.

Performance of Triple-Cation Perovskite Solar Cells under Different Indoor Operating Conditions.

We systematically analyze triple-cation perovskite solar cells for indoor applications. A large number of devices with different bandgaps from 1.6 to 1.77 eV were fabricated, and their performance under 1-sun AM1.5 and indoor white light emitting diode (LED) light was compared. We find that the trends agree well with the detailed balance limit; however, the devices near the optimal bandgap (1.77 eV) perform worse due to the lower perovskite quality. Instead, we achieve the highest power conversion efficiency (PCE) of 34.0% under 870 lx with 1.67 eV and Al2O3 passivation. The perovskite with a bandgap of 1.71 eV is not far behind, with a high VOC of 1.02 V. Measurements under different white LED color temperatures confirm that the highest PCE is achieved under the warmest colors. All measurements were carried out in a dedicated indoor setup that ensures the diffuse light typical of indoor environments and allows both short- and long-term measurements. In the best case, we observe no degradation during the 33-day test under simulated office conditions with regular switching on and off of the light and a T80 of 30 days under continuous illumination. The results were obtained from multiple batches, which corroborates our findings and gives them statistical relevance.

Effective detection of indoor fungal contamination through the identification of volatile organic compounds using mass spectrometry and machine learning.

Indoor fungal contamination poses significant challenges to human health and indoor air quality. This study addresses an effective approach using mass spectrometry and machine learning to identify microbial volatile organic compounds (MVOCs) originated from indoor fungi. Three common indoor fungi, including Penicillium Chrysogenum, Cladosporium cladosporioides, and Aspergillus niger, were cultivated on various substrates, namely potato dextrose agar, wallpaper, and silicone. Solid-phase microextraction-gas chromatography-mass spectrometry (SPME-GC-MS) was used to analyze MVOCs together, along with the VOCs (namely, non-MVOCs) emitted by various indoor materials (wallpaper adhesives, diffusers, particle board, oriented strand board, medium-density fiberboard, bleach, print cartridges, and cosmetic creams). This study demonstrates the significant effectiveness of machine learning, particularly the random forest model, in accurately distinguishing MVOCs from non-MVOCs. Furthermore, specific VOCs such as benzocyclobutane, styrene, ethanol, benzene, and 2-butanone emerged as consistent indicators of fungal presence across different fungal species and substrates. A simplified random forest model incorporating these key VOCs achieved a high accuracy of 96.2%, highlighting their practical significance in fungal contamination detection. This integrated approach combining analytical chemistry and machine learning offers a promising strategy for the comprehensive and reliable assessment of indoor fungal contamination.

Heart rate variability, electrodermal activity and cognition in adults: Association with short-term indoor PM2.5 exposure in a real-world intervention study.

BACKGROUND: Long-term effects of ambient fine particulate matter (PM2.5) exposure on mortality and morbidity are well established. The study aims to evaluate how short-term indoor PM2.5 exposure affects physiological responses and understand potential mechanisms mediating the cognitive outcomes in working-age adults. METHODS: This real-world randomized single-blind crossover intervention study was conducted in an urban office setting, with desk-based air purifiers used as the intervention. Participants (N=40) were exposed to average PM2.5 levels of 18.0 µg/m3 in control and 3.7 µg/m3 in intervention conditions. Cognitive tests, heart rate variability (HRV), and electrodermal activity (EDA) measures were conducted after 5 hours of exposure. Self-reported mental effort, exhaustion, and task difficulty were collected after the cognitive tests. RESULTS: Participants in the intervention condition had significantly higher HRV during cognitive testing, particularly in the standard deviation of normal-to-normal intervals (SDNN), root mean square of successive differences (RMSSD), and high-frequency power (HF) indices. Mediation analysis revealed that elevated PM2.5 exposure reduced HRV indices, which mediated the effect on two executive function-related cognitive skills out of 16 assessed skills. No significant differences were found in EDA, self-reported task difficulty, or exhaustion, but self-reported mental effort was higher in the control condition. CONCLUSIONS: Lower indoor PM2.5 level was associated with reduced mental effort and higher HRV during cognitive testing. Furthermore, the association between indoor PM2.5 exposure and executive function might be mediated through cardiovagal responses. These findings provide insights on the mechanisms through which fine particle exposure adversely affects the autonomic nervous system and how this in turn affects cognition. The potential cardiovascular and cognitive health benefits of PM2.5 reduction warrants further research.

Fuel fumes and foliage: the fate of speciated gasoline VOCs during phytoremediation and their impact on the bacterial phenotype.

The capacity of indoor plants including green walls to capture, deposit and remediate individual volatile organic compounds (VOCs) has been well documented. However, in realistic settings, plant systems are exposed to a complex mixture of VOCs from highly varied various emission sources. Gasoline vapour is one of the major sources of these emissions, containing high concentrations of the carcinogens benzene, toluene, ethylbenzene and xylene (BTEX). Using both solid phase micro extraction (SPME) and quick, easy, cheap, effective, rugged and safe (QuEChERS) sampling techniques, we assessed the dynamics of individual speciated gasoline VOC phytoremediation from the air and uptake within green wall plant species and growth substrates within a small passive green wall system, along with quantifying the phenotypic changes within the plant-associated bacterial communities resulting from gasoline exposure. Over 8 hours the green wall system achieved 100% removal of atmospheric benzene, 1,2,3-trimethyl, eicosane and hexadecane, benzene 1,3-diethyl-; 1,3,5 cycloheptatriene,7- ethyl and carbonic acid eicosyl vinyl ester. All plant species tested demonstrated the accumulation 45 petrochemical VOCs (pVOCs) with Spathiphyllum wallisii successfully accumulating the majority of pVOC functional groups after 24 h of gasoline exposure. Within the plants phyllospheric bacterial communities, changes in both cellular complexity and granularity appeared to increase as a result of gasoline exposure, while cell size diminished. This work provides novel findings on the VOC removal processes of botanical systems for realistic and highly toxic VOC profiles.

Facile synthesis of activated carbon/titanium dioxide composite and its application for adsorptive/photocatalytic removal of gaseous toluene.

This study explores the practical utility of activated carbon/titanium dioxide (AC/TiO2) composite for the abatement of a common aromatic volatile organic compound (VOC), toluene. The performance of the prepared AC/TiO2 composite (ACT-x: x as the theoretical mass ratio (in percent) of AC over TiO2 ranging from 0% to 10%) is evaluated individually as an adsorbent and photo-catalyst against gaseous toluene in a packed flow tube reactor under varying operational conditions (e.g., relative humidity and gaseous pollutant composition). The incorporation of AC into TiO2 significantly increases its adsorption capacity (Q), e.g., 1.71 mg g-1 for ACT-10 (relative to 0.01 mg g-1 for ACT-0). The ACT-5, with 3.6% C, exhibits the maximum photocatalytic removal efficiency (XT = 93.77%), quantum efficiency (QE; 1.63 × 10-4 molecules photon-1), space time yield (STY; 1.99 × 10-5 molecules photon-1 mg-1), and specific clear air delivery rate (SCADR; 686.2 L h-1 g-1) of the compositions tested. ACT composite exhibits enhanced adsorption and in-situ degradation-desorption process to facilitate the capture of VOCs while diminishing the generation of by-products. The in-situ diffuse reflectance infrared Fourier transform spectroscopy and gas chromatography-mass spectrometry analyses indicate the formation of several intermediate by-products during the photocatalytic degradation process, including benzyl alcohol, benzaldehyde, benzoic acid, phenol, and alkane species, through ring-opening reactions. In addition, the photocatalytic performance of ACT is demonstrated to be superior to those of other TiO2-based photocatalysts. Accordingly, the ACT composite is recommended as a promising medium for the abatement of aromatic VOCs in indoor air.

Evidence-driven indoor air quality improvement: An innovative and interdisciplinary approach to improving indoor air quality.

Indoor air pollution is a recognized emerging threat, claiming millions of lives annually. People are constantly exposed to ambient and indoor air pollution. The latest research shows that people in developed countries spend up to 90% of their time indoors and almost 70% at home. Although impaired IAQ represents a significant health risk, it affects people differently, and specific populations are more vulnerable: children, the elderly, and people with respiratory illnesses are more sensitive to these environmental risks. Despite rather extensive research on IAQ, most of the current understanding about the subject, which includes pollution sources, indoor-outdoor relationships, and ventilation/filtration, is still quite limited, mainly because air quality monitoring in the EU is primarily focused on ambient air quality and regulatory requirements are lacking for indoor environments. Therefore, the EDIAQI project aims to improve guidelines and awareness for advancing the IAQ in Europe and beyond by allowing user-friendly access to information about indoor air pollution exposures, sources, and related risk factors. The solution proposed with EDIAQI consists of conducting a characterization of sources and routes of exposure and dispersion of chemical, biological, and emerging indoor air pollution in multiple cities in the EU. The project will deploy cost-effective/user-friendly monitoring solutions to create new knowledge on sources, exposure routes, and indoor multipollutant body burdens. The EDIAQI project brings together 18 organizations from 11 different European countries that provide interdisciplinary skills and expertise in various fields, including environmental science and technology, medicine, and toxicology, as well as policy design and public engagement.

Biodeterioration Risk Assessment in Libraries by Airborne Fungal Spores.

Fungal growth on cellulose-based materials in libraries can have detrimental effects on books and documents. This biodeterioration affects their physical, chemical, and esthetical characteristics. Thus, this work aimed to assess fungal aerosols' concentrations and biodeterioration risk in two public libraries with artificial ventilation: the Banco de la República and CAJAMAG libraries. Air sampling was performed using a two-stage viable Andersen cascade impactor with Sabouraud dextrose agar at 4% on Petri dishes. Also, the temperature and relative humidity were measured with a digital thermo-hygrometer HOBO U12 Data Logger. The concentrations were low, with values of around 35 CFU/m3. Aspergillus, Cladosporium, and Penicillium were the predominant genera in the two libraries, with A. niger being the most abundant species. The thermo-hygrometric conditions inside the libraries were stable, with a mean temperature of 25.2 °C and a mean relative humidity of 52.1%. The calculated potential risk associated with fungal aerosols was seen to be medium in both libraries, where Aspergillus genera reported the highest cellulosic activity and hence had a higher risk of biodeterioration.

"The air within: reviewing the sources and health effects of indoor air pollution in households".

Air pollution in the interior of our homes is caused by diverse chemical, physical, and biological entities. This review comprehensively explores the current understanding of sources and health impacts of gaseous and particulate pollutants. Trend analysis of indoor air research worldwide revealed a quantum jump of 2.8 times in the number of publications during the last ten years. Indoor air pollutants are innumerable, but only a few are widely prevalent in most households. The qualitative complexity of pollutants translates to different health problems, including respiratory diseases, cardiovascular conditions, cancer, and deaths. There exist wide-scale disparities in the negative impacts among different economic strata, genders, and age groups; children and elderly populations are more vulnerable. In developing countries, pollutants primarily arise from traditional sources, whereas in developed countries, pollutants from non-conventional sources are comparatively significant. Only a few countries have indoor air regulations, policies, monitoring plans and effective enforcement.

Airborne trichloramine in indoor swimming pools in Sweden.

Trichloramine is a disinfection by-product in chlorinated swimming pools. It can evaporate into the air and irritate eyes and airways among swimmers and pool workers. This study aimed to evaluate airborne concentrations of trichloramine in different types of indoor swimming pools. Altogether, 72 swimming pools across Sweden were included; 36 exercise pools, 16 instruction pools, seven adventure pools, and 13 rehabilitation pools. In total, 167 sampling sessions were performed with the majority (N = 91) conducted in public exercise pools. Repeated sampling sessions on different days were performed within all pool categories. Airborne trichloramine was measured stationary by the poolside using active sampling on quartz filters. In total, 434 air samples were collected. The geometric mean (GM) concentration of trichloramine for the exercise pools was 0.12 mg/m3 (range GMpool: 0.02-0.29 mg/m3) and for about 30% the GMpool exceeded the Swedish public health guideline value (0.2 mg/m3). The geometric mean for instruction pools was 0.18 mg/m3 and for adventure pools 0.20 mg/m3. Trichloramine concentrations were statistically significantly lower in rehabilitation pools (GM: 0.03 mg/m3) compared with the other pool categories. A statistically significant effect of time of the day for sampling was found for the exercise and instruction pools, with higher trichloramine levels during evenings compared with mornings and afternoons. For the rehabilitation pools, trichloramine was significantly higher during the cold season compared with the warm season. Variability in trichloramine concentrations was attributed to between-pool as well as within-pool variances. The within-pool variability encourages a repeated sampling strategy to capture the variation between different days. These findings have implications for exposure assessment in epidemiological studies as well as for indoor air quality monitoring. Trichloramine can cause acute irritative effects at elevated levels, and since trichloramine concentrations may differ depending on the time of the day it is recommended that full-day stationary measurements are supplemented with short-term samplings to capture these variations.

Measurement reproducibility and Storage impact on VOC/SVOC Emission Rate from Decorative Materials.

Building materials are the major sources of Volatile and Semi-Volatile Organic Compounds (VOCs and SVOCs) in indoor air. Measurements of emission rates of these compounds are likely to be influenced by variation in certain environmental factors resulting in intra-specimen variability. This study aims to (i) evaluate the reproducibility of measurements between specimens and (ii) evaluate the impact of storage on VOC and SVOC emissions from antifungal acrylic paint (applied on polyester-cellulose). For this purpose, 15 discs of tested materials (1.63 ± 0.04 g) were prepared. From these, the emissions rates (ER) of 5 samples were analyzed simultaneously during three measurement campaigns (October 2021, January 2022 and March 2022). Between each campaign, specimens were stored in the dark at ambient temperature (25 ± 4 °C) and relative humidity (50 ± 20 %). Measurements were performed using the field and laboratory emission cell (FLEC) and characterized by gas chromatography (TD-GC-MS/FID) and liquid chromatography (HPLC). Intra-specimen reproducibility was assessed by comparing 5 ER of different specimens collected simultaneously. The impact of storage was evaluated by comparing the average VOC/SVOC ER between each campaign. The results show, concerning the reproducibility of the measurements, that the first measurement campaign provides ER with high variability (10 - 36 %) compared to the second and third measurement campaigns, which show lower intra-specimen variability (5 - 24 % and 8 - 20 % respectively). However, weakly emitted compounds (ER < 10 µg m-2 h-1) such as aromatics and aldehydes show large variabilities (6 - 100 % of variation) in all measurement campaigns. Regarding the effect of the 5-months storage a significant decrease in the ER of individual VOC/SVOCs (37 - 85 %) and of TVOCs (74 %) was noted, except for aldehydes, aromatic hydrocarbons, isopropylacetone and vinyl crotonate, which showed a stability or eventual increase (up to 100 %) in the ER over time, depending on the type of emitted compound.

Modeling impacts of indoor environmental variables on secondary organic aerosol formation.

There are numerous air pollutants indoors including chemicals emitted from building environments as well as outdoor-origin species due to human activities. Despite the significance of indoor air quality, the atmospheric process indoors is not well studied. In this study, the secondary organic aerosol (SOA) formation from the oxidation of α-pinene blended with toluene was simulated under varying indoor environments (lamps, NO2, ozone, and inorganic seed) using the UNIfied Partitioning Aerosol Reaction (UNIPAR) model. Explicitly predicted lumping species produced during the atmospheric oxidation of precursors are used in the model and they process multiphase partitioning and aerosol phase reactions. The performance of the model was demonstrated using indoor chamber experiments in both dark conditions (ozonolysis) and light conditions with commercialized fluorescent or LED lamps. α-Pinene SOA was dominated by ozonolysis even in the presence of indoor light. Toluene, which is known to be photochemically processed, was oxidized in the dark condition with OH radicals that were derived from ozonolysis products of α-pinene. At given dark simulation conditions (10 ppb α-pinene, 30 ppb ozone, and 50 ppb of toluene), toluene contributed 15 % of SOA mass. α-Pinene SOA was insensitive to hygroscopicity of inorganic seed, but toluene blended with α-pinene increased the sensitivity to seed conditions due to the formation of oligomeric matter via aqueous reactions of reactive toluene products. In the presence of NO2. α-pinene SOA formation significantly increased with increasing NO2 owing to the reaction of α-pinene with nitrate radicals to form low volatile products. This study concludes that ozone and NO2, intruded from outdoors to indoors, effectively oxidize terpenes and furthermore aromatic hydrocarbons with OH radicals originating from ozonolysis of terpenes. The reaction paths with ozone and nitrate radicals are more effective at forming SOA than that with OH radical under the indoor light condition with commercialized lamps.

Hospital-borne hazardous air pollutants and air cleaning strategies amid the surge of SARS-CoV-2 new variants.

Indoor air pollutants and airborne contamination removal have been challenging in healthcare facilities. The airborne transmission control and HVAC system may collapse in hospitals due to the highly infectious respiratory disease-associated patient surge, like COVID-19. Common air filtration systems and HVAC systems enhance the patients' comfort and support indoor hygiene, hitherto insufficient to control highly infectious airborne pathogens and hospital-borne pollutants such as radon, PM2.5, patient droplets, VOC, high CO2, and anesthetic gases. This review summarized important air cleaning interventions to enhance HVAC efficiency and indoor safety. We discussed efficient air cleaning and ventilation strategies including air filtration, air ionization, passive removal materials (PRM), and UVGI to minimize cross-contamination in hospital wards.

Integrating Real-Time Air Quality Monitoring, Ecological Momentary Assessment, and Spirometry to Evaluate Asthma Symptoms: Usability Study.

BACKGROUND: Individuals are exposed to a variety of indoor residential toxins including volatile organic compounds and particulates. In adults with asthma, such exposures are associated with asthma symptoms, asthma exacerbations, and decreased lung function. However, data on these exposures and asthma-related outcomes are generally collected at different times and not in real time. The integration of multiple platforms to collect real-time data on environmental exposure, asthma symptoms, and lung function has rarely been explored. OBJECTIVE: This paper describes how adults with asthma perceive the acceptability and usability of three integrated devices: (1) residential indoor air quality monitor, (2) ecological momentary assessment (EMA) surveys delivered via a smartphone app, and (3) home spirometry, over 14 days. METHODS: Participants (N=40) with uncontrolled asthma were mailed the Awair Omni indoor air quality monitor, ZEPHYRx home spirometer, and detailed instructions required for the in-home monitoring. The air quality monitor, spirometer, and EMA app were set up and tested during a videoconference or phone orientation with a research team member. Midway through the 14-day data collection period, participants completed an interview about the acceptability of the study devices or apps, instructional materials provided, and the setup process. At the end of the 14-day data collection period, participants completed a modified System Usability Scale. A random sample of 20 participants also completed a phone interview regarding the acceptability of the study and the impact of the study on their asthma. RESULTS: Participants ranged in age from 26 to 77 (mean 45, SD 13.5) years and were primarily female (n=36, 90%), White (n=26, 67%), college graduates (n=25, 66%), and residing in a single-family home (n=30, 75%). Most indicated that the air quality monitor (n=23, 58%), the EMA (n=20, 50%), and the spirometer (n=17, 43%) were easy to set up and use. Challenges with the EMA included repetitive surveys, surveys arriving during the night, and technical issues. While the home spirometer was identified as a plausible means to evaluate lung function in real time, the interpretation of the readings was unclear, and several participants reported side effects from home spirometer use. Overall, the acceptability of the study and the System Usability Scale scores were high. CONCLUSIONS: The study devices were highly acceptable and usable. Participant feedback was instrumental in identifying technical challenges that should be addressed in future studies.

Enhancing indoor PM2.5 predictions based on land use and indoor environmental factors by applying machine learning and spatial modeling approaches.

The presence of fine particulate matter (PM2.5) indoors constitutes a significant component of overall PM2.5 exposure, as individuals spend 90% of their time indoors; however, personal monitoring for large cohorts is often impractical. In light of this, this study seeks to employ a novel geospatial artificial intelligence (Geo-AI) coupled with machine learning (ML) approaches to develop indoor PM2.5 models. Multiple predictor variables were collected from 102 residential households, including meteorological data; elevation; land use; indoor environmental factors including human activities, building characteristics, infiltration factors, and real-time measurements; and various other factors. Geo-AI, which integrates land use regression, inverse distance weighting, and ML algorithms, was utilized to construct outdoor PM2.5 and PM10 estimates for residential households. The most influential variables were identified via correlation analysis and stepwise regression. Three ML methods, namely support vector machine, multiple linear regression, and multilayer perceptron (MLP) were used to estimate indoor PM2.5 concentration. Then, MLP was employed to blend three ML algorithms. The resulting model demonstrated commendable performance, achieving a 10-fold cross-validation R2 of 0.92 and a root mean square error of 2.3 µg/m3 for indoor PM2.5 estimations. Notably, the combination of Geo-AI and ensembled ML models in this study outperformed all other individual models. In addition, the present study pointed out the most influential factors for indoor PM2.5 model were outdoor PM2.5, PM2.5/PM10 ratio, sampling month, infiltration factor, located near factory, cleaning frequency, number of door entrance linked with outdoor, and wall material. Further exploration of diverse ensemble model formats to integrate estimates from different models could enhance overall performance. Consequently, the potential applications of this model extend to estimating real individual exposure to PM2.5 for further epidemiological research. Moreover, the model offers valuable insights for efficient indoor air quality management and control strategies.

Features, reasons, and significance of radon and thoron attributable radiological dose in the indoor environment.

Humans receive around 50% of natural radiation dose due to 222Rn (radon), 220Rn (thoron) and their decay products. Several field campaigns measuring these gases and the decay products in different regions of India have been conducted in the recent past. Some of these studies measured indoor activity concentration and/or dose due to these gases and the associated decay products. This work compares the fraction of 222Rn and decay products and 220Rn and decay products in inhalation dose for 10 studies conducted in Uttarakhand state. It is seen that AEDT (annual effective dose due to 220Rn and decay products) for these regions varies between 21 and 48% and it is significantly higher than the averaged worldwide reference value of 6%. Based on elaborative measurements performed in the Bageshwar district (present work), Almora and Nainital districts (our previous campaigns); the reasons for this high value have been explored. It was observed that a higher source term for mud houses could be the main reason for the high AEDT range. Interestingly, preliminary analysis revealed that the fraction is higher for the dwellings situated at higher altitudes thus indicating the role of the unavailability of modern building construction materials at remote locations. The study highlights the significant contribution of thoron in the Indian Himalayas.

UWB-Assisted Bluetooth Localization Using Regression Models and Multi-Scan Processing.

Bluetooth devices have been widely used for pedestrian positioning and navigation in complex indoor scenes. Bluetooth beacons are scattered throughout the entire indoor walkable area containing stairwells, and pedestrian positioning can be obtained by the received Bluetooth packets. However, the positioning performance is sharply deteriorated by the multipath effects originating from indoor clutter and walls. In this work, an ultra-wideband (UWB)-assisted Bluetooth acquisition of signal strength value method is proposed for the construction of a Bluetooth fingerprint library, and a multi-frame fusion particle filtering approach is proposed for indoor pedestrian localization for online matching. First, a polynomial regression model is developed to fit the relationship between signal strength and location. Then, particle filtering is utilized to continuously update the hypothetical location and combine the data from multiple frames before and after to attenuate the interference generated by the multipath. Finally, the position corresponding to the maximum likelihood probability of the multi-frame signal is used to obtain a more accurate position estimation with an average error as low as 70 cm.