Heterogeneous hydrochlorination of lipids mediated by fatty acids in an indoor environment.

Fatty acids from cooking fumes and hypochlorous acid (HOCl) released from indoor cleaning adversely affect respiratory health, but the molecular-level mechanism remains unclear. Here, the effect of cooking oil fumes [palmitic acid (PA), oleic acid (OA), and linoleic acid (LA)] on lung model phospholipid (POPG) hydrochlorination mediated by HOCl at the air-water interface of the hanged droplets was investigated. Interfacial hydrochlorination of POPG was impeded by OA and LA, while that of POPG was facilitated by PA. The effect on POPG hydrochlorination increased with the decrease in oil fume concentration. A potential mechanism with respect to the chain length of these oil fumes, regardless of their saturation, was proposed. PA with a short carbon chain looses the POPG packing and leads to the exposure of the C=C double bonds of POPG, whereas OA and LA with a long carbon chain hinder HOCl from reaching the C=C bonds of POPG. These results for short chain and low concentration dependence suggest that the decay of oil fumes or the conversion of short-chain species by indoor interfacial chemistry might be adverse to lung health. These results provide insights into the relationship between indoor multicomponent pollutants and the respiratory system.

Reducing Transmission of Airborne Respiratory Pathogens: A New Beginning as the COVID-19 Emergency Ends.

BACKGROUND: In response to the COVID-19 pandemic, new evidence-based strategies have emerged for reducing transmission of respiratory infections through management of indoor air. OBJECTIVES: This paper reviews critical advances that could reduce the burden of disease from inhaled pathogens and describes challenges in their implementation. DISCUSSION: Proven strategies include assuring sufficient ventilation, air cleaning by filtration, and air disinfection by germicidal ultraviolet (UV) light. Layered intervention strategies are needed to maximize risk reduction. Case studies demonstrate how to implement these tools while also revealing barriers to implementation. Future needs include standards designed with infection resilience and equity in mind, buildings optimized for infection resilience among other drivers, new approaches and technologies to improve ventilation, scientific consensus on the amount of ventilation needed to achieve a desired level of risk, methods for evaluating new air-cleaning technologies, studies of their long-term health effects, workforce training on ventilation systems, easier access to federal funds, demonstration projects in schools, and communication with the public about the importance of indoor air quality and actions people can take to improve it. https://doi.org/10.1289/EHP13878.

Nitrogen dioxide exposure, health outcomes, and associated demographic disparities due to gas and propane combustion by U.S. stoves.

Gas and propane stoves emit nitrogen dioxide (NO2) pollution indoors, but the exposures of different U.S. demographic groups are unknown. We estimate NO2 exposure and health consequences using emissions and concentration measurements from >100 homes, a room-specific indoor air quality model, epidemiological risk parameters, and statistical sampling of housing characteristics and occupant behavior. Gas and propane stoves increase long-term NO2 exposure 4.0 parts per billion volume on average across the United States, 75% of the World Health Organization's exposure guideline. This increased exposure likely causes ~50,000 cases of current pediatric asthma from long-term NO2 exposure alone. Short-term NO2 exposure from typical gas stove use frequently exceeds both World Health Organization and U.S. Environmental Protection Agency benchmarks. People living in residences <800 ft2 in size incur four times more long-term NO2 exposure than people in residences >3000 ft2 in size; American Indian/Alaska Native and Black and Hispanic/Latino households incur 60 and 20% more NO2 exposure, respectively, than the national average.

Microbial dynamics and climatic interactions in pig sheds: Insights into airborne microbes and particulate matter concentrations.

Emissions of airborne pollutants from livestock buildings affect indoor air quality, the health and well-being of farmers, animals and the environment. This study aimed to evaluate the microbial count within pig sheds and its relationship with meteorological variables (temperature, relative humidity and air velocity) and particulate matter (PM10 and PM2.5) and microbial diversity. Sampling was conducted both inside and outside of two pig sheds over three seasons (summer, rainy and winter), with regular monitoring at fortnightly intervals. Results showed that the bacterial and fungal counts ranged from 0.07 to 3.98 x 103 cfu/m3 inside the sheds and 0.01 to 1.82 x 103 cfu/m3 outside. Seasonal variations were observed, with higher concentrations of particulate matter detected during the winter season, followed by summer. Climatic variables such as temperature, air velocity and relative humidity demonstrated significant impacts on the abundance of Enterobacteriaceae and fungi, while air velocity specifically influenced the presence of mesophilic bacteria and staphylococci. Importantly, no significant disparities were found between microbial counts and particulate matter levels. Staphylococcaceae emerged as the predominant bacterial family, while Aspergillus and Cladosporium spp. were the dominant fungal species within the pig sheds. The average levels of airborne bacteria and fungi in pig sheds were found to be within the recommended range, which can be attributed to the loose housing design and lower animal population on the farms.

Monitoring the ventilation of living spaces to assess the risk of airborne transmission of infection using a novel Pocket CO2 Logger to track carbon dioxide concentrations in Tokyo.

We employed carbon dioxide (CO2) concentration monitoring using mobile devices to identify location-specific risks for airborne infection transmission. We lent a newly developed, portable Pocket CO2 Logger to 10 participants, to be carried at all times, for an average of 8 days. The participants recorded their location at any given time as cinema, gym, hall, home, hospital, other indoors, other outgoings, pub, restaurant, university, store, transportation, or workplace. Generalized linear mixed model was used for statistical analysis, with the objective variable set to the logarithm of CO2 concentration. Analysis was performed by assigning participant identification as the random effect and location as the fixed effect. The data were collected per participant (seven males, four females), resulting in a total of 12,253 records. Statistical analysis identified three relatively poorly ventilated locations (median values > 1,000 ppm) that contributed significantly (p < 0.0001) to CO2 concentrations: homes (1,316 ppm), halls (1,173 ppm), and gyms (1005ppm). In contrast, two locations were identified to contribute significantly (p < 0.0001) to CO2 concentrations but had relatively low average values (<1,000 ppm): workplaces (705 ppm) and stores (620 ppm). The Pocket CO2 Logger can be used to visualize airborne infectious transmission risk by location to help guide recommendation regarding infectious disease policies, such as restrictions on human flow and ventilation measures and guidelines. In the future, large-scale surveys are expected to utilize the global positioning system, Wi-Fi, or Bluetooth of an individual's smartphone to improve ease and accuracy.

Exploring toilet plume bioaerosol exposure dynamics in public toilets using a Design of Experiments approach.

Bioaerosols generated during toilet flushing can contribute to the spread of airborne pathogens and cross-contamination in indoor environments. This presents an increased risk of fomite-mediated or aerosol disease transmission. This study systematically investigated the factors contributing to increased bioaerosol exposure following toilet flushing and developed an empirical model for predicting the exposure-relevant bioaerosol concentration. Air in a toilet cubicle was sampled by impaction after seeding with Clostridium difficile spores. Design of Experiments (DoE) main effects screening and full factorial design approaches were then employed to investigate the significant factors that heighten the risk of exposure to bioaerosols post-flush. Our findings reveal that the inoculated bacterial concentration (C), time elapsed after flushing (t), lateral distance (d), and mechanical ventilation (v) are significant predictors of bioaerosol concentration, with p-values < 0.05. The interaction term, C × d showed a marked increase in bioaerosol concentration up to 232 CFU/m3 at the closest proximity and highest pathogen load. The interplay of C and t (C × t) demonstrated a time-dependent attenuation of bioaerosol viability, with concentrations peaking at 241 CFU/m3 immediately post-flush and notably diminishing over time. The lateral distance and time post-flush (d × t) interaction also revealed a gradual decrease in bioaerosol concentration, highlighting the effectiveness of spatial and temporal dilution in mitigating bioaerosol exposure risks. Furthermore, there is an immediate rise in relative humidity levels post-flush, impacting the air quality in the toilet environment. This study not only advances our understanding of exposure pathways in determining bioaerosol exposure, but also offers pivotal insights for designing targeted interventions to reduce bioaerosol exposure. Recommendations include designing public toilets with antimicrobial surfaces, optimizing ventilation, and initiating timely disinfection protocols to prioritise surfaces closest to the toilet bowl during peak exposure periods, thereby promoting healthier indoor environments and safeguarding public health in high-traffic toilet settings.

Machine-Learning-Assisted Descriptors Identification for Indoor Formaldehyde Oxidation Catalysts.

The development of highly efficient catalysts for formaldehyde (HCHO) oxidation is of significant interest for the improvement of indoor air quality. Up to 400 works relating to the catalytic oxidation of HCHO have been published to date; however, their analysis for collective inference through conventional literature search is still a challenging task. A machine learning (ML) framework was presented to predict catalyst performance from experimental descriptors based on an HCHO oxidation catalysts database. MnOx, CeO2, Co3O4, TiO2, FeOx, ZrO2, Al2O3, SiO2, and carbon-based catalysts with different promoters were compiled from the literature. Notably, 20 descriptors including reaction catalyst composition, reaction conditions, and catalyst physical properties were collected for data mining (2263 data points). Furthermore, the eXtreme Gradient Boosting algorithm was employed, which successfully predicted the conversion efficiency of HCHO with an R-square value of 0.81. Shapley additive analysis suggested Pt/MnO2 and Ag/Ce-Co3O4 exhibited excellent catalytic performance of HCHO oxidation based on the analysis of the entire database. Validated by experimental tests and theoretical simulations, the key descriptor identified by ML, i.e., the first promoter, was further described as metal-support interactions. This study highlights ML as a useful tool for database establishment and the catalyst rational design strategy based on the importance of analysis between experimental descriptors and the performance of complex catalytic systems.

Ozone Chemistry on Greasy Glass Surfaces Affects the Levels of Volatile Organic Compounds in Indoor Environments.

The chemistry of ozone (O3) on indoor surfaces leads to secondary pollution, aggravating the air quality in indoor environments. Here, we assess the heterogeneous chemistry of gaseous O3 with glass plates after being 1 month in two different kitchens where Chinese and Western styles of cooking were applied, respectively. The uptake coefficients of O3 on the authentic glass plates were measured in the dark and under UV light irradiation typical for indoor environments (320 nm < λ < 400 nm) at different relative humidities. The gas-phase product compounds formed upon reactions of O3 with the glass plates were evaluated in real time by a proton-transfer-reaction quadrupole-interface time-of-flight mass spectrometer. We observed typical aldehydes formed by the O3 reactions with the unsaturated fatty acid constituents of cooking oils. The formation of decanal, 6-methyl-5-hepten-2-one (6-MHO), and 4-oxopentanal (4-OPA) was also observed. The employed dynamic mass balance model shows that the estimated mixing ratios of hexanal, octanal, nonanal, decanal, undecanal, 6-MHO, and 4-OPA due to O3 chemistry with authentic grime-coated kitchen glass surfaces are higher in the kitchen where Chinese food was cooked compared to that where Western food was cooked. These results show that O3 chemistry on greasy glass surfaces leads to enhanced VOC levels in indoor environments.

The Long Hazy Tail: Analysis of the Impacts and Trends of Severe Outdoor and Indoor Air Pollution in North China.

China, especially the densely populated North China region, experienced severe haze events in the past decade that concerned the public. Although the most extreme cases have been largely eliminated through recent mitigation measures, severe outdoor air pollution persists and its environmental impact needs to be understood. Severe indoor pollution draws less public attention due to the short visible distance indoors, but its public health impacts cannot be ignored. Herein, we assess the trends and impacts of severe outdoor and indoor air pollution in North China from 2014 to 2021. Our results demonstrate the uneven contribution of severe hazy days to ambient and exposure concentrations of particulate matter with an aerodynamic diameter <2.5 (PM2.5). Although severe indoor pollution contributes to indoor PM2.5 concentrations (23%) to a similar extent as severe haze contributes to ambient PM2.5 concentrations (21%), the former's contribution to premature deaths was significantly higher. Furthermore, residential emissions contributed more in the higher PM2.5 concentration range both indoors and outdoors. Notably, severe haze had greater health impacts on urban residents, while severe indoor pollution was more impactful in rural areas. Our findings suggest that, besides reducing severe haze, mitigating severe indoor pollution is an important aspect of combating air pollution, especially toward improving public health.

Association between indoor air pollution and depression: a systematic review and meta-analysis of cohort studies.

OBJECTIVES: Incomplete combustion of solid fuel and exposure to secondhand smoke (SHS) are the primary causes of indoor air pollution (IAP), potentially leading to detrimental effects on individual mental health. However, current evidence regarding the association between IAP and depression remains inconclusive. This study aims to systematically investigate the evidence regarding the association between IAP and the risk of depression. DESIGN: Systematic review and meta-analysis of cohort studies. DATA SOURCES: Two independent reviewers searched PubMed, the Cochrane Library, Web of Science and EMBASE for available studies published up to 13 January 2024. ELIGIBILITY CRITERIA: We included all cohort studies published in English that aimed to explore the relationship between IAP from solid fuel use and SHS exposure and the risk of depression. DATA EXTRACTION AND SYNTHESIS: Two independent reviewers extracted data and assessed the risk of bias. The association between IAP and depression was calculated using pooled relative risk (RR) with 95% CIs. Heterogeneity was assessed using the I2 value, and the effect estimates were pooled using fixed-effects or random-effects models depending on the results of homogeneity analysis. RESULTS: We included 12 articles with data from 61 217 participants. The overall findings demonstrated a significant association between IAP exposure and depression (RR=1.22, 95% CI: 1.13 to 1.31), although with substantial heterogeneity (I2=75%). Subgroup analyses based on pollutant type revealed that IAP from solid fuel use was associated with a higher risk of depression (RR=1.20, 95% CI: 1.13 to 1.26; I2=62%; 5 studies, 36 768 participants) than that from SHS exposure (RR=1.11, 95% CI: 0.87 to 1.41; I2=80%; 7 studies, 24 449 participants). In terms of fuel use, the use of solid fuel for cooking (RR: 1.23, 95% CI: 1.16 to 1.31; I2=58%; 4 studies, 34 044 participants) and heating (RR 1.15, 95% CI: 1.04 to 1.27; I2=65%; 3 studies, 24 874 participants) was associated with increased depression risk. CONCLUSIONS: The findings from this systematic review and meta-analysis of cohort studies indicated an association between exposure to IAP and depression. PROSPERO REGISTRATION NUMBER: CRD42022383285.

Evaluation of particle and volatile organic compound emissions during the use of 3D pens.

This study investigated particle and volatile organic compound (VOC) emission rates (ER) from 3D pens, which are increasingly popular in children's toys. Nine filaments and two 3D pens were evaluated using a flow tunnel, a scanning mobility particle sizer, a proton-transfer-reaction time-of-flight mass spectrometer for particles, and a thermal desorption-gas chromatography-mass spectrometer for VOCs. Results showed that the ERs varied with the pen type, filament, and brand. The particle ER was highest for acrylonitrile butadiene styrene (ABS), followed by polylactic acid (PLA) and polycaprolactone (PCL). Notably, ERs of 83 % and 33 % of ABS and PLA filaments exceeded the maximum allowable particle ER (MAER; 5 × 109 particles/min) for 3D printers but were lower than the VOC MAER (173 µg/min in the office). Different filaments emitted diverse VOCs; ABS emitted styrene and benzene, PLA emitted lactide, and PCL emitted phenol. While particle ERs from 3D pens were comparable to those from printers, the total VOC ERs from 3D pens were slightly lower. Caution is warranted when using 3D pens because of potential health risks, especially their prolonged use, proximity to the breathing zone, and usage by children. This study highlights the need for considering particles and VOCs when assessing the safety of 3D pens, emphasizing awareness of potential hazards, particularly in child-oriented settings.

Influence of type of cooking fuel on risk of hypertension among reproductive-age women in sub-Saharan Africa: insights from nationally representative cross-sectional surveys.

BACKGROUND: Nearly one-third of the world's population (2.4 billion people) rely on unclean cooking fuel sources. The study assessed the association of the type of cooking fuel and hypertension risk in sub-Saharan Africa (SSA). METHODS: The study analysed pooled data from 97 942 individuals in the Demographic and Health Survey (DHS) between 2014 and 2021 in 10 SSA countries. Univariate, bivariate and multivariate analyses were performed, including basic descriptive statistics and binary logistic regression. The independent variable of interest was the type of cooking fuel, while hypertension served as the outcome variable. RESULTS: Women using unclean cooking fuel were 1.21 times more likely to be hypertensive compared with those using clean cooking fuel (adjusted odds ratio [aOR] 1.21 [95% confidence interval {CI} 1.11 to 1.31]). Older age (aOR 5.78 [95% CI 5.04 to 6.62]), higher education (aOR 1.14 [95% CI 1.05 to 1.23]), being married (aOR 1.64 [95% CI 1.49 to 1.80]), working in sales and services occupations (aOR 1.34 [95% CI 1.24 to 1.44]), frequent health facility visits (aOR 1.59 [95% CI 1.51 to 1.68]), higher wealth index and exposure to media were significantly associated with hypertension risk. CONCLUSIONS: Efforts to reduce reliance on unclean cooking fuel at both the household and population levels need to be intensified in SSA countries. Promoting the use of clean cooking technologies and fuels and implementing supportive policies for transitioning from unclean cooking fuels are crucial. Targeted interventions to reduce hypertension risk in SSA should focus on women using unclean cooking fuel, older women, individuals from wealthier households and those with higher education levels.

Evaluation of consumer digital radon measurement devices: a comparative analysis.

Kansas State University (KSU) Engineering Extension conducted an abridged evaluation of eight consumer grade digital radon monitors. Using the KSU secondary radon chamber, these devices were exposed to three different radon concentrations for 7 d in average household temperature and relative humidity conditions. The three different radon concentration ranges used were: 12.8 pCi L-1to 15.5 pCi L-1(473.6 Bq m-3-573.5 Bq m-3), 27.7 pCi L-1to 29.4 pCi L-1(1024.9-10 857.8 Bq m-3), and ambient room level average radon concentration of 0.6 pCi L-1(22.2 Bq m-3). The American National Standards Institute/American Academy of Radon Scientists and Technologists Performance Specifications for Instrumentation Systems Designed to Measure Radon Gas in Air (ANSI/AARST MS-PC) (ANSI/AARST MS-PC 2022Performance Specifications for Instrumentation Systems Designed to Measure Radon Gas in Air(AARST Radon Standards)) minimum performance metrics were used to evaluate the accuracy and precision of each model type for each radon concentration tested. The eight different device models performed within the 0 ± 25% requirement for the individual percent error (IPE) for radon concentrations between 27.7 pCi L-1and 29.4 pCi L-1(1024.9-10 857.8 Bq m-3). For radon concentrations between 12.8 pCi L-1and 15.5 pCi L-1(444-592 Bq m-3) seven of the eight monitors fell within the IPE requirement and for ambient room radon concentrations six of the eight monitors fell within the IPE requirement for the ANSI/AARST MS-PC minimum performance requirement (ANSI/AARST MS-PC 2022Performance Specifications for Instrumentation Systems Designed to Measure Radon Gas in Air(AARST Radon Standards)) ranges. All eight device models fell within the ± 15% ANSI/AARST MS-PC minimum performance requirement (ANSI/AARST MS-PC 2022Performance Specifications for Instrumentation Systems Designed to Measure Radon Gas in Air(AARST Radon Standards)) coefficient of variation (CV) range for radon concentrations between 12.8 pCi L-1and 15.5 pCi L-1(444-592 Bq m-3) and for radon concentrations between 27.7 pCi L-1and 29.4 pCi L-1(1024.9-10 857.8 Bq m-3). In the future, evaluating the performance of these models over time to observe their long term accuracy and precision is anticipated.

Early life ambient air pollution, household fuel use, and under-5 mortality in Ghana.

INTRODUCTION: Environmental exposures, such as ambient air pollution and household fuel use affect health and under-5 mortality (U5M) but there is a paucity of data in the Global South. This study examined early-life exposure to ambient particulate matter with a diameter of 2.5 µm or less (PM2.5), alongside household characteristics (including self-reported household fuel use), and their relationship with U5M in the Navrongo Health and Demographic Surveillance Site (HDSS) in northern Ghana. METHODS: We employed Satellite-based spatiotemporal models to estimate the annual average PM2.5 concentrations with the Navrongo HDSS area (1998 to 2016). Early-life exposure levels were determined by pollution estimates at birth year. Socio-demographic and household data, including cooking fuel, were gathered during routine surveillance. Cox proportional hazards models were applied to assess the link between early-life PM2.5 exposure and U5M, accounting for child, maternal, and household factors. FINDINGS: We retrospectively studied 48,352 children born between 2007 and 2017, with 1872 recorded deaths, primarily due to malaria, sepsis, and acute respiratory infection. Mean early-life PM2.5 was 39.3 µg/m3, and no significant association with U5M was observed. However, Children from households using "unclean" cooking fuels (wood, charcoal, dung, and agricultural waste) faced a 73 % higher risk of death compared to those using clean fuels (adjusted HR = 1.73; 95 % CI: 1.29, 2.33). Being born female or to mothers aged 20-34 years were linked to increased survival probabilities. INTERPRETATION: The use of "unclean" cooking fuel in the Navrongo HDSS was associated with under-5 mortality, highlighting the need to improve indoor air quality by introducing cleaner fuels.

Quantitative evaluation of the impact of indoor relative humidity on deposition of aerosols generated during tooth grinding in a real-world clinical setting.

OBJECTIVES: Exposure to aerosol particles generated from tooth grinding has a negative impact on the health of dental personnel. The aim of this study was to quantitatively analyze the impact of indoor relative humidity (IRH) on the deposition of these suspended particles in a well-controlled dental environment. MATERIALS AND METHODS: In this study, a humidity control system was employed to effectively regulate and maintain indoor relative humidity (IRH). A novel computer-assisted numerical control system was developed to pre-treat the molar specimens, and accurately simulate clinical tooth grinding procedures. Each procedure was performed in triplicate, with an online real-time particle counter (ORPC; TR-8301, TongrenCo.) measuring aerosol production. All testing devices were controlled remotely. The data obtained were statistically analyzed using descriptive statistics and non-parametric tests (Kruskal-Wallis/ Dunn's post hoc test with Bonferroni correction, p < 0.05). RESULTS: The findings showed that with increasing IRH, the maximum peak concentration of aerosol particles decreased by 397% from 6.51 × 107 particles/m3 at 30% to 1.64 × 107 particles/m3 at 80%. The Kruskal-Wallis test results indicated a statistically significant effect of IRH on the aerosol increment (p < 0.05). CONCLUSIONS: Increasing the IRH level can effectively promote the deposition of aerosol particles, with a return to baseline within 15 min after reaching 60% or above. CLINICAL RELEVANCE: Our study suggested that maintaining IRH above 70% during the cleaning process, allowing natural recovery to ambient humidity levels within 15 min after cleaning, and taking basic precautions, may lead to an adequate reduction in the possible health risks of aerosol contamination.

Determining the toxicological effects of indoor air pollution on both a healthy and an inflammatory-comprised model of the alveolar epithelial barrier in vitro.

Exposure to indoor air pollutants (IAP) has increased recently, with people spending more time indoors (i.e. homes, offices, schools and transportation). Increased exposures of IAP on a healthy population are poorly understood, and those with allergic respiratory conditions even less so. The objective of this study, therefore, was to implement a well-characterised in vitro model of the human alveolar epithelial barrier (A549 + PMA differentiated THP-1 incubated with and without IL-13, IL-5 and IL-4) to determine the effects of a standardised indoor particulate (NIST 2583) on both a healthy lung model and one modelling a type-II (stimulated with IL-13, IL-5 and IL-4) inflammatory response (such as asthma).Using concentrations from the literature, and an environmentally appropriate exposure we investigated 232, 464 and 608ng/cm2 of NIST 2583 respectively. Membrane integrity (blue dextran), viability (trypan blue), genotoxicity (micronucleus (Mn) assay) and (pro-)/(anti-)inflammatory effects (IL-6, IL-8, IL-33, IL-10) were then assessed 24 h post exposure to both models. Models were exposed using a physiologically relevant aerosolisation method (VitroCell Cloud 12 exposure system).No changes in Mn frequency or membrane integrity in either model were noted when exposed to any of the tested concentrations of NIST 2583. A significant decrease (p < 0.05) in cell viability at the highest concentration was observed in the healthy model. Whilst cell viability in the "inflamed" model was decreased at the lower concentrations (significantly (p < 0.05) after 464ng/cm2). A significant reduction (p < 0.05) in IL-10 and a significant increase in IL-33 was seen after 24 h exposure to NIST 2583 (464, 608ng/cm2) in the "inflamed" model.Collectively, the results indicate the potential for IAP to cause the onset of a type II response as well as exacerbating pre-existing allergic conditions. Furthermore, the data imposes the importance of considering unhealthy individuals when investigating the potential health effects of IAP. It also highlights that even in a healthy population these particles have the potential to induce this type II response and initiate an immune response following exposure to IAP.

Bedroom Concentrations and Emissions of Volatile Organic Compounds during Sleep.

Because humans spend about one-third of their time asleep in their bedrooms and are themselves emission sources of volatile organic compounds (VOCs), it is important to specifically characterize the composition of the bedroom air that they experience during sleep. This work uses real-time indoor and outdoor measurements of volatile organic compounds (VOCs) to examine concentration enhancements in bedroom air during sleep and to calculate VOC emission rates associated with sleeping occupants. Gaseous VOCs were measured with proton-transfer reaction time-of-flight mass spectrometry during a multiweek residential monitoring campaign under normal occupancy conditions. Results indicate high emissions of nearly 100 VOCs and other species in the bedroom during sleeping periods as compared to the levels in other rooms of the same residence. Air change rates for the bedroom and, correspondingly, emission rates of sleeping-associated VOCs were determined for two bounding conditions: (1) air exchange between the bedroom and outdoors only and (2) air exchange between the bedroom and other indoor spaces only (as represented by measurements in the kitchen). VOCs from skin oil oxidation and personal care products were present, revealing that many emission pathways can be important occupant-associated emission factors affecting bedroom air composition in addition to direct emissions from building materials and furnishings.

AhR agonists screening and identification in indoor dust based on non-target chemical analysis by GC-Q-TOFMS and biological effect evaluation referring to ToxCast/Tox21 database.

Numerous studies reported the concentration of agonists of aryl hydrocarbon receptor (AhR) in indoor dust by target chemical analysis or the biological effects of activating the AhR by indoor extracts, but the major AhR agonists identification in indoor dust were rarely researched. In the present study, the indoor dust samples were collected for 7-ethoxyresorufin O-deethylase (EROD) assay and both non-targeted and targeted chemical analysis for AhR agonists by gas chromatography quadrupole time-of-flight mass spectrometry and gas chromatography-mass spectrometry analysis. Coupled with non-targeted analysis and toxicity Forecaster (ToxCast)/Tox21 database, 104 ToxCast chemicals were screened to be able to induce EROD response. The combination of targeted chemical analyses and biological effects evaluation indicated that PAHs, dibutyl phthalate (DBP) and Cypermethrin might be the important AhR-agonists in different indoor dust and mainly contributed in 1.84%-97.56 % (median: 26.62%) of total observed biological effects through comparing toxic equivalency quotient derived from chemical analysis with biological equivalences derived from bioassay. DBP and cypermethrin seldom reported in the analysis of AhR agonists should raise great concern. In addition, the present results in experiment of synthetic solution of 4 selected AhR-agonists pointed out that some unidentified AhR agonists existed in indoor dust.

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

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