Fine particles in homes of predominantly low-income families with children and smokers: Key physical and behavioral determinants to inform indoor-air-quality interventions

Exposure to Secondhand Cannabis Smoke Among Children

Importance

The degree that in-home cannabis smoking can be detected in the urine of resident children is unclear.

Objective

Test association of in-home cannabis smoking with urinary cannabinoids in children living at home.

Design, Setting, and Participants

This cross-sectional study used baseline data from Project Fresh Air, a 2012-2016 randomized clinical trial to reduce fine particulate matter levels. Eligible participants were recruited from households in San Diego County, California, with children under age 14 years and an adult tobacco smoker in residence. Children's urine samples were analyzed in 2022.

Exposures

In-home cannabis smoking, measured by: parent or guardian report of in-home cannabis smoking; number of daily nonspecific smoking events computed via an air particle count algorithm; and number of daily cannabis smoking events ascertained by residualization, adjusting for air nicotine, tobacco smoking, and other air particle generating or ventilating activities.

Main Outcomes and Measures

Levels of the cannabis biomarker Δ9-tetrahydrocannabinol (THC) and its major metabolites, 11-hydroxy-Δ9-tetrahydrocannabinol and 11-nor-9-carboxy-Δ9-tetrahydrocannabinol. Biomarker molar equivalents were summed to represent total THC equivalents (TTE) in urine. Logistic regression assessed whether in-home smoking was associated with cannabis biomarker detection. For children with detectable urinary cannabinoids, linear regression assessed in-home smoking association with quantity of urinary TTE.

Results

A total of 275 children were included in analysis (mean [SD] age, 3.6 [3.6] years; 144 male [52.4%]; 38 Black [13.8%], 132 Hispanic [48.0%], and 52 White [18.9%]). Twenty-nine households (10.6%) reported in-home cannabis smoking in the past 7 days; 75 children [27.3%] had detectable urinary cannabinoids. Odds of detectable TTE in children's urine were significantly higher in households with reported in-home cannabis smoking than households without (odds ratio [OR], 5.0; 95% CI, 2.4-10.4) and with each additional ascertained daily cannabis smoking event (OR, 2.5; 95% CI, 1.6-3.9). Although the point estimate for TTE levels was higher among children with detectable urinary cannabinoids and exposure to more daily cannabis smoking events (increase per event, 35.68%; 95% CI, -7.12% to 98.21%), the difference was not statistically significant.

Conclusions and Relevance

In this cross-sectional study, in-home cannabis smoking was associated with significantly increased odds of child exposure to cannabis smoke, as assessed by urinary cannabinoid biomarkers. As young children spend most of their time at home, reducing in-home cannabis smoking could substantially reduce their exposure to the toxic and carcinogenic chemicals found in cannabis smoke.

Incense Use and the Risk of Chronic Limb-Threatening Ischemia Among Middle-Aged and Older Adults in the Singapore Chinese Health Study

BACKGROUND

Epidemiologic studies have shown that daily exposure to incense smoke is associated with greater risk of cardiovascular mortality, which suggests that chronic exposure to incense could be linked to atherosclerosis. We studied the association between home incense use and the risk of chronic limb-threatening ischemia (CLTI), the most severe outcome of peripheral arterial disease.

METHODS

We used data from the Singapore Chinese Health Study, which recruited 63,257 Chinese participants 45-74 years old from 1993-1998. Data were collected via in-person interviews conducted at the participants' homes by trained interviewers. Linkage to the nationwide hospital discharge database was used to determine incident cases, defined as participants who underwent revascularization or lower extremity amputation for CLTI. Association between use of incense and risk of CLTI was examined using multivariable Cox proportional hazards regression models, adjusted for demographics and cardiovascular risk factors.

RESULTS

In this cohort, 76.9% were current users of incense at recruitment, and 92.6% of those used incense daily at home. During a mean 18.8 years of follow-up, 1,097 participants developed CLTI. Compared to never or former users, current users had a 22% higher risk of CLTI [hazard ratio ( HR ) = 1.22 ; 95% confidence interval (CI): 1.04, 1.43]. The risk was greater with chronicity of use, and the HR was highest and statistically significant in participants who had used incense daily for > 40 years [HR = 1.25 (95% CI: 1.06, 1.46)]. The results did not differ by sex, history of diabetes, or smoking status.

CONCLUSIONS

Daily exposure to incense in the home environment for more than 40 years was associated with a greater risk of developing CLTI. https://doi.org/10.1289/EHP14674.

Determinants of Indoor NO2 and PM2.5 Concentration in Senior Housing with Gas Stoves

Nitrogen dioxide (NO2) and particulate matter of 2.5 microns (PM2.5) are air pollutants that impact health, especially among vulnerable populations with respiratory disease. This study identifies factors influencing indoor NO2 and PM2.5 in low-income households of older adults with asthma who use gas stoves in Lowell, Massachusetts. Environmental sampling was conducted in 73 homes, measuring NO2, PM2.5, fractional stove-use, temperature, and humidity for 5-7 days. Participants were recruited between December 2020 and July 2022. Questionnaires were used to collect data on factors influencing indoor NO2 and PM2.5 concentrations. Daily outdoor NO2 and PM2.5 concentrations were obtained from a United States Environmental Protection Agency (EPA) monitoring station. Paired t-tests were conducted between indoor and outdoor NO2 and PM2.5 concentrations, and linear regression was used to evaluate factors influencing indoor NO2 and PM2.5 concentrations. The average indoor concentration for NO2 and PM2.5 were 21.8 (GSD = 2.1) ppb and 16.2 (GSD = 2.7) µg/m3, respectively. Indoor NO2 and PM2.5 concentrations exceeded outdoor concentrations significantly. In multiple regression models, season and pilot light stove use significantly predicted indoor NO2. Season and air freshener use for 6-7 days/week significantly predicted indoor PM2.5. Season-influenced higher indoor concentrations are likely due to reduced ventilation in colder months in the Northeast U.S.

Assessing bias in personal exposure estimates when indoor air quality is ignored: A comparison between GPS-enabled mobile air sensor data and stationary outdoor sensor data

Neglecting indoor air quality in exposure assessments may lead to biased exposure estimates and erroneous conclusions about the health impacts of exposure and environmental health disparities. This study assessed these biases by comparing two types of personal exposure estimates for 100 individuals: one derived from real-time particulate matter (PM2.5) measurements collected both indoors and outdoors using a low-cost portable air monitor (GeoAir2.0) and the other from PurpleAir sensor network data collected exclusively outdoors. The PurpleAir measurement data were used to create smooth air pollution surfaces using geostatistical methods. To obtain mobility-based exposure estimates, both sets of air pollution data were combined with the individuals' GPS tracking data. Paired-sample t-tests were then performed to examine the differences between these two estimates. This study also investigated whether GeoAir2.0- and PurpleAir-based estimates yielded consistent conclusions about gender and economic disparities in exposure by performing Welch's t-tests and ANOVAs and comparing their t-values and F-values. The study revealed significant discrepancies between GeoAir2.0- and PurpleAir-based estimates, with PurpleAir data consistently overestimating exposure (t = 5.94; p < 0.001). It also found that females displayed a higher average exposure than males (15.65 versus. 8.55 μg/m3) according to GeoAir2.0 data (t = 4.654; p = 0.055), potentially due to greater time spent indoors engaging in pollution-generating activities traditionally associated with females, such as cooking. This contrasted with the PurpleAir data, which indicated higher exposure for males (43.78 versus. 46.26 μg/m3) (t = 3.793; p = 0.821). Additionally, GeoAir2.0 data revealed significant economic disparities (F = 7.512; p < 0.002), with lower-income groups experiencing higher exposure-a disparity not captured by PurpleAir data (F = 0.756; p < 0.474). These findings highlight the importance of considering both indoor and outdoor air quality to reduce bias in exposure estimates and more accurately represent environmental disparities.

A seasonal investigation of indoor air quality in relation to architectural features in government office buildings in Enugu, Nigeria

Indoor air quality (IAQ) is crucial to environmental health significantly impacting on the well-being and productivity of building occupants. Several studies have explored various aspects of IAQ in non-tropical regions but there is limited information on how seasonal variations affect IAQ in hot-humid climates like Enugu, Nigeria. This study investigated seasonal changes in key indoor air parameters including CO, CO2, HCHO, TVOC, temperature, RH, PM2.5, and AQI across rainy and dry seasons in 58 government offices in Enugu, and evaluated how these fluctuations relate to architectural features of the offices. Using a mixed-methods approach, data collection involved qualitative assessments of building design attributes alongside quantitative IAQ measurements taken with the BOSEAN T-Z01Pro detector. Seasonal variations were analyzed using paired T-tests, ANOVA, and regression models. The results revealed a marked increase in pollutant concentrations during the dry season (p < 0.001-0.005), resulting in a poorer air quality index compared to the rainy season. Architectural features accounted for 68.5% of the variability in AQI (R2 = 0.685, p = 0.000), with casement windows being significantly associated with better air quality (Exp B = -4.217, p = 0.013) These shows that the dry season poses a greater risk to IAQ which is worsened in offices where projecting windows were used, potentially impacting health and productivity. The study emphasizes the need to address seasonal IAQ differences when designing office buildings in tropical regions. Design architects can help reduce seasonal air quality challenges and support healthier, more productive indoor environments by incorporating ventilation strategies, such as the use of casement windows. Further research should include long-term monitoring across various settings and additional IAQ parameters for better understanding of IAQ dynamics.

Association between long-term PM2.5 exposure and risk of Kawasaki disease in children: A nationwide longitudinal cohort study

BACKGROUND

Based on previous studies suggesting air pollution as a potential risk factor for Kawasaki Disease (KD), we examined the association of long-term exposure to childhood fine particulate matter (PM2.5) with the risk of KD.

METHODS

We used National Health Insurance Service-National Sample Cohort data from 2002 to 2019, which included beneficiaries aged 0 years at enrollment and followed-up until the onset of KD or age 5 years. The onset of KD was defined as the first hospital visit record with a primary diagnostic code of M30.3, based on the 10th revision of the International Classification of Diseases, and with an intravenous immunoglobulin (IVIG) prescription. We assigned PM2.5 concentrations to 226 districts, based on mean annual predictions from a machine learning-based ensemble prediction model. We performed Cox proportional-hazards modeling with time-varying exposures and confounders.

RESULTS

We identified 134,634 individuals aged five or less at enrollment and, of these, 1220 individuals who had a KD onset and an IVIG prescription during study period. The average annual concentration of PM2.5 exposed to the entire cohort was 28.2 μg/m³ (Standard Deviation 2.9). For each 5 μg/m³ increase in annual PM2.5 concentration, the hazard ratio of KD was 1.21 (95% CI 1.05-1.39).

CONCLUSIONS

In this nationwide, population-based, cohort study, long-term childhood exposure to PM2.5 was associated with an increased incidence of KD in children. The study highlights plausible mechanisms for the association between PM2.5 and KD, but further studies are needed to confirm our findings.

PM2.5 exposure to marijuana smoke on golf courses and other public outdoor locations: A pilot observational study

Secondhand exposure to cannabis smoke occurs in public outdoor locations due to outdoor smoking or leakage of indoor smoking. Very little is known regarding the actual levels of exposure. This study examined PM2.5 exposure to marijuana smoke, focusing on one type of public outdoor location - golf courses where illegal marijuana consumption is increasingly common. Based on 24 visits to 10 courses over a 6-month period, >20 % visits encountered marijuana smoke, with peak PM2.5 exposures up to 149 μg/m3. The levels of exposure depended upon the source type (smoking versus vaping) and the proximity to the smoker/vaper. Ten additional investigations were performed to measure marijuana secondhand exposure in other public outdoor locations (near a smoker in a public park, near a parked car with in-car smoking/vaping, and near a residential garage with indoor smoking/vaping). 23 encounters of marijuana exposure events were documented in total. Average outdoor exposures to PM2.5 close to public outdoor smoking and vaping (on golf courses and a public park) were >3 times as high as those near a car or a building with indoor marijuana emissions. The average outdoor exposure caused by the leakage of in-car secondhand smoke was higher than that caused by in-building emissions.

The impacts of cooking and indoor air quality assessment in the southwestern region of Bangladesh

The main objective of this study is to assess the impacts of cooking and indoor air quality (IAQ) in the southwestern region of Bangladesh. Here we report and compare the IAQ in considering a total of eight kitchens and living rooms of four selected households (HHs) in Jashore city and suburb area, the southwest district of Bangladesh. Air quality parameters, such as particulate matter (PM_2.5) and volatile organic compounds (VOC), were assessed continuously for 24 h. In addition, Carbon dioxide (CO₂) was evaluated in different phases during the study period. PM_2.5, VOC, and CO₂ levels were ranged from 18.52 to 207 μg/m³, 7.95-35.66 ppm, and 1061-2459 mg/m³, respectively, in the indoor cooking HHs. Conversely, while the average concentration was found between 20.63 and 23.72 μg/m³ PM_2.5, 11.18-12.36 ppm VOC, and 1097-1747 mg/m³ CO₂ in the outdoor cooking HHs. A significant increase in CO₂ due to kitchen activities (cooking, frying, boiling) was observed that ranged between 5 and 77% compared to the background level. The calculated range of toxicity potential (TP) values was between 0.8 and 8.3 for PM_2.5 in the HHs. In most of the observations, PM_2.5, VOC, and CO₂ exceed the standard values. The study reports that well ventilation systems and clean fuel use significantly reduce the indoor air contaminants level. Our study offers new insights about the IAQ of the southwest region of Bangladesh, particularly for suburbs and urban setups, and provides a background for further study, and decision-making. It will serve as a reference for the formulation and implementation of policies to improve air quality.

The Role of Ethnicity and Nativity in the Correspondence between Subjective and Objective Measures of In-Home Smoking

Studies are needed to understand the association between self-reported home smoking bans and objective measures of in-home smoking according to smokers' ethnicity/nativity. Data came from a trial that used air particle monitors to reduce children's secondhand smoke exposure in smokers' households (N = 251). Linear regressions modeled (a) full home smoking bans by ethnicity/nativity, and (b) objectively measured in-home smoking events, predicted by main and interaction effects of self-reported home smoking bans and ethnicity/nativity. Among smokers reporting < a full ban, US-born and Foreign-born Latinos had fewer in-home smoking events than US-born Whites (p < 0.001). Participants who reported a full smoking ban had a similar frequency of smoking events regardless of ethnicity/nativity. Results indicate that self-reported home smoking bans can be used as a proxy for in-home smoking. Establishing smoking bans in the households of US-born White smokers has the largest impact on potential exposure compared to other ethnicity/nativity groups.

Characteristics of particle-bound polycyclic aromatic hydrocarbons (PAHs) in indoor PM2.5 of households in the Southwest part of Ulaanbaatar capital, Mongolia

Air pollution, including PM_2.5 concentration in Ulaanbaatar (capital of Mongolia) is a serious matter of concern. As the majority of households use coal in large areas of the city, indoor air quality is also posing a serious risk to human health. This study investigated the concentration of polycyclic aromatic compounds (PAHs) in indoor particulate matter (PM_2.5) in 10 non-smoker households. Sampling was conducted in winter of 2018, between 27 January and 09 February. Concentrations of PM_2.5 in the indoor air of households ranged between 62.8 and 324.8 µg m^-3. Total concentration of PAHs also varied in a relatively wide range, between 46.2 and 175.7 ng m^-3. Five-ring PAHs represented a considerably high fraction of total PAHs between 25 and 53%, benzo[b]fluoranthene (BbF) and benzo[a]pyrene (BaP) were the two predominant compounds within five-ring PAHs. Significant correlation was found between indoor and outdoor particulate matter levels in wintertime. Considering individual characteristic PAHs, heavier PAHs homologues (4- to 5-ring and 6-ring PAHs) were detected in all households, which suggested the influence of coal combustion and traffic exhaust. Health risk of children attributed to PAHs inhalation was assessed by taking into account the lifetime-average daily dose (LADD) and corresponding lifetime cancer risk. Lifetime average daily dose for children in only one household were slightly higher than health-based guideline level (1.0 × 10^-5), defined by WHO, whereas LADD for adults and children of other households were within acceptable limit. The cancer risks from the exposure of children to air pollutants in all households except HH-3 were found high. In the Vibrio fischeri bioluminescence inhibition assay, according to the toxic unit (TU) values of indoor PM_2.5 from ten households, all samples were classified as toxic.

Real-time feedback of air quality in children’s bedrooms reduces exposure to secondhand smoke

INTRODUCTION

Secondhand smoke (SHS) exposure creates health risks for non-smokers and is especially detrimental to children. This study evaluated whether immediate feedback in response to poor indoor air quality in children’s bedrooms can reduce the potential for SHS exposure, as measured by adherence to a World Health Organization (WHO) indoor air standard.

METHODS

Homes that contained children and an adult who regularly smoked inside (n=298) had an air particle monitor installed in the child’s bedroom. These devices measured the concentration of particulate matter (PM2.5) for approximately three months and, for half of the participants, immediately provided aversive feedback in response to elevated PM2.5. Hierarchical linear models were fit to the data to assess whether the intervention increased the probability that: 1) a given day was below the WHO guideline for daily exposure, and 2) a household established and maintained a smoke-free home (SFH), operationalized as achieving 30 consecutive days below the WHO guideline. The intervention’s impact was calculated as group-by-time effects.

RESULTS

The likelihood that a child’s bedroom met the WHO indoor air quality standard on a given day increased such that the baseline versus post-baseline odds ratio (OR) of maintaining indoor PM2.5 levels below the WHO guideline was 2.38 times larger for participants who received the intervention. Similarly, the baseline versus post-baseline OR associated with achieving an SFH was 3.49 times larger for participants in the intervention group.

CONCLUSIONS

The real-time intervention successfully drove clinically meaningful changes in smoking behavior that mitigated indoor PM2.5 levels in children’s bedrooms and thereby reduced SHS exposure. These results demonstrate the effectiveness of targeting sensitive microenvironments by giving caregivers actionable information about children’s SHS risks. Future extensions should examine additional microenvironments and focus on identifying the potential for SHS exposure before it occurs.

Intercomparison of PurpleAir Sensor Performance over Three Years Indoors and Outdoors at a Home: Bias, Precision, and Limit of Detection Using an Improved Algorithm for Calculating PM2.5

Low-cost particle sensors are now used worldwide to monitor outdoor air quality. However, they have only been in wide use for a few years. Are they reliable? Does their performance deteriorate over time? Are the algorithms for calculating PM_2.5 concentrations provided by the sensor manufacturers accurate? We investigate these questions using continuous measurements of four PurpleAir monitors (8 sensors) under normal conditions inside and outside a home for 1.5–3 years. A recently developed algorithm (called ALT-CF3) is compared to the two existing algorithms (CF1 and CF_ATM) provided by the Plantower manufacturer of the PMS 5003 sensors used in PurpleAir PA-II monitors. Results. The Plantower CF1 algorithm lost 25–50% of all indoor data due in part to the practice of assigning zero to all concentrations below a threshold. None of these data were lost using the ALT-CF3 algorithm. Approximately 92% of all data showed precision better than 20% using the ALT-CF3 algorithm, but only approximately 45–75% of data achieved that level using the Plantower CF1 algorithm. The limits of detection (LODs) using the ALT-CF3 algorithm were mostly under 1 µg/m³, compared to approximately 3–10 µg/m³ using the Plantower CF1 algorithm. The percentage of observations exceeding the LOD was 53–92% for the ALT-CF3 algorithm, but only 16–44% for the Plantower CF1 algorithm. At the low indoor PM_2.5 concentrations found in many homes, the Plantower algorithms appear poorly suited.

Changes in Personal Exposure to Fine Particulate Matter (PM2.5) during the Spring 2020 COVID-19 Lockdown in the UK: Results of a Simulation Model

Objectives: Policy responses to the COVID-19 pandemic in 2020 led to behaviour changes in the UK’s population, including a sudden shift towards working from home. These changes may have affected overall exposure to fine particulate matter (PM2.5), an air pollutant and source of health harm. We report the results of a simulation model of a representative sample of the UK’s population, including workers and non-workers, to estimate PM2.5 exposure before and during the pandemic. Methods: PM2.5 exposure was simulated in April and August 2017–2020 for 10,000 individuals across the UK drawn from the 2011 nationwide census. These data were combined with data from the UK’s ambient PM2.5 monitoring network, time use data and data on relevant personal behaviour before and during the first stage of the pandemic (such as changes in smoking and cooking). Results: The simulated exposures were significantly different between each year. Changes in ambient PM2.5 resulted in regional and temporal variation. People living in homes where someone smoked experienced higher exposure than those in smoke-free homes, with an increase of 4 µg/m3 in PM2.5 exposure in 2020. Conclusions: Changes in PM2.5 exposure were minimal for most individuals despite the simulated increases in cooking activity. Those living in smoking homes (estimated to be around 11% of the UK population) experienced increased exposure to PM2.5 during COVID lockdown measures and this is likely to have increased mortality and morbidity among this group. Government policy should address the risk of increased exposure to second-hand smoke in the event of future COVID-19-related restrictions.

Indoor home environments of Danish children and the socioeconomic position and health of their parents: A descriptive study

BACKGROUND

Housing and indoor home environments are associated with the risk of infections and asthma in children. To better understand the determinants and characteristics of these environments, we aimed to describe the associations between parental health and socioeconomic position and housing and indoor home environments of children in Denmark, and the clustering of the factors within these environments.

METHODS

Offspring in the Danish National Birth Cohort (DNBC) whose parents responded to the 11-year follow-up were eligible for inclusion. We included complete cases only. Data on the indoor and housing environments (i.e. variables on housing, sources of gaseous and particle pollution, mould and moisture, and pets) were collected through an online questionnaire responded to by a parent. Data on socioeconomic position were obtained through linkage with registry data on maternal education at offspring birth and household equivalized income at offspring birth. Data on parental health were obtained by linking self-reported data from the 11-year follow-up for mother and father with administrative registry data for the mother. We present descriptive statistics and exploratory factor analyses.

RESULTS

A total of 42 723 offspring were included for analyses. The distributions of nearly all indoor and housing environments differed according to educational and income strata, with patterns similar for both education and income. Generally, higher parental educational and income strata had more favorable indoor and housing environments (less secondhand smoking, gas stove use, mould and condensation and higher house ownership, detached house dwellings and newer building age). However, candle use was approximately similar between strata, fireplace use among lower educational and income strata tended towards the extremes (none or daily), and water damage was more common among higher educational and income strata. Parental health was strongly associated with housing and indoor home environment factors - especially parental affective disorders was strongly associated with mould. Four factors were extracted from the exploratory factor analyses, relating primarily in order of extraction to: housing ownership, mould and moisture, candle use and household density.

CONCLUSION

Parental health and socioeconomic position are strongly related to housing and indoor home environments. Additionally, several factors in these environments correlate strongly and cluster together. Observational studies on associations and causal effects of factors in the indoor and housing environments of children on their morbidity, must consider both of these conclusions to arrive at valid estimates and effects.

Thirdhand smoke from tobacco, e-cigarettes, cannabis, methamphetamine and cocaine: Partitioning, reactive fate, and human exposure in indoor environments

A source of chemical exposure to humans, thirdhand smoke (THS) refers to the contamination that persists indoors following the cessation of a smoking event. The composition of thirdhand smoke depends on the type of substance from which it originates. Although past studies have investigated the effects of tobacco THS on indoor air quality and human health, few have focused on the chemical composition and health impacts of other sources and components of THS. Here we review the state of knowledge of the composition and partitioning behavior of various types of indoor THS, with a focus on THS from tobacco, e-cigarettes, cannabis, and illicit substances (methamphetamine and cocaine). The discussion is supplemented by estimates of human exposure to THS components made with a chemical fate and exposure model. The modeling results show that while very volatile THS compounds (i.e., aromatics) are likely to be taken up by inhalation, highly water-soluble compounds tended to be dermally absorbed. Conversely, minimally volatile THS compounds with low solubility are predicted to be ingested through hand-to-mouth and object-to-mouth contact.

PM2.5 exposure close to marijuana smoking and vaping: A case study in residential indoor and outdoor settings

We conducted 35 experiments for spatial measurement of marijuana aerosols in a current smoker's residential spaces. Fine particulate matter (PM_2.5) concentrations were measured every second at 1, 2, and 3 m horizontal distances from the smoker who performed prescribed 5-min smoking and vaping activities. In each experiment, five SidePak monitors measured PM_2.5 concentrations at five different angles facing the front of the smoker, representing the worst-case exposures. We studied the effect of distance from the smoker for two marijuana sources - smoking a marijuana cigarette, or joint, and vaping a liquid-cartridge vaping pen. Experiments were conducted in the family room indoors and in the backyard outdoors where the smoker normally consumes marijuana. Indoor marijuana vaping had higher average exposures (5-min PM_2.5) at 1 m distance than indoor marijuana smoking, but the levels from indoor vaping decreased more rapidly with distance (e.g., 77% reduction for vaping versus 33% for smoking from 1 to 2 m). Smoking and vaping in the outdoor environment reduce the average exposures down to <5% of the indoor levels at each distance. Cumulative frequency distributions of the 1-s PM_2.5 concentrations revealed the frequencies of exceeding any selected transient peak exposure limit at a given distance. The frequency of exceedance decreased more quickly with distance for vaping than for smoking. Smoking and vaping outdoors made the transient peak exposures close to the source much less frequent than smoking and vaping indoors (e.g., <1% exceeded 1000 μg/m³ outdoors versus >20% indoors at 1 m). Plotting the frequency of exceedance versus distance could offer additional guidance for a recommended minimum distance from a marijuana source.

Residential indoor air quality interventions through a social-ecological systems lens: A systematic review

Indoor air quality (IAQ) is an important consideration for health and well-being as people spend most of their time indoors. Multi-disciplinary interest in IAQ is growing, resulting in more empirical research, especially in affordable housing settings, given disproportionate impacts on vulnerable populations. Conceptually, there is little coherency among these case studies; they traverse diverse spatial scales, indoor and outdoor environments, and populations, making it difficult to implement research findings in any given setting. We employ a social-ecological systems (SES) framework to review and categorize existing interventions and other literature findings to elucidate relationships among spatially and otherwise diverse IAQ factors. This perspective is highly attentive to the role of agency, highlighting individual, household, and organizational behaviors and constraints in managing IAQ. When combined with scientific knowledge about the effectiveness of IAQ interventions, this approach favors actionable strategies for reducing the presence of indoor pollutants and personal exposures.

Secondary indoor air pollution and passive smoking associated with cannabis smoking using electric cigarette device-demonstrative in silico study

With electronic (e)-liquids containing cannabis components easily available, many anecdotal examples of cannabis vaping using electronic cigarette devices have been reported. For electronic cigarette cannabis vaping, there are potential risks of secondary indoor air pollution from vapers. However, quantitative and accurate prediction of the inhalation and dermal exposure of a passive smoker in the same room is difficult to achieve due to the ethical constraints on subject experiments. The numerical method, i.e., in silico method, is a powerful tool to complement these experiments with real humans. In this study, we adopted a computer-simulated person that has been validated from multiple perspectives for prediction accuracy. We then conducted an in silico study to elucidate secondary indoor air pollution and passive smoking associated with cannabis vaping using an electronic cigarette device in an indoor environment. The aerosols exhaled by a cannabis vaper were confirmed to be a secondary emission source in an indoor environment; non-smokers were exposed to these aerosols via respiratory and dermal pathways. Tetrahydrocannabinol was used as a model chemical compound for the exposure study. Its uptake by the non-smoker through inhalation and dermal exposure under a worst-case scenario was estimated to be 5.9% and 2.6% of the exhaled quantity from an e-cigarette cannabis user, respectively.

How can we best mitigate unintended passive smoking in an indoor environment? As marijuana tends to be legalized in more countries, there is an increasing number of cases of vaping cannabis using e-cigarette devices. E-cigarette vaping is presumed to cause relatively low levels of indoor air pollution due to the absence of a direct combustion process. In this study, we developed a numerical simulation model to quantitatively predict the impact of first- and second-hand cannabis vaping in an indoor environment. The study was conducted in response to vulnerable residents who are concerned regarding the deterioration of indoor air quality and informs policymakers of the potential risk of second-hand cannabis vaping exposure.

Smoking behaviours and indoor air quality: a comparative analysis of smoking-permitted versus smoke-free homes in Dhaka, Bangladesh

INTRODUCTION

Exposure to secondhand smoke (SHS) is a health risk to non-smokers. Indoor particulate matter (PM_2.5) is associated with SHS exposure and is used as a proxy measure. However, PM_2.5 is non-specific and influenced by a number of environmental factors, which are subject to geographical variation. The nature of association between SHS exposure and indoor PM_2.5-studied primarily in high-income countries (HICs) context-may not be globally applicable. We set out to explore this association in a low/middle-income country setting, Dhaka, Bangladesh.

METHODS

A cross-sectional study was conducted among households with at least one resident smoker. We inquired whether smoking was permitted inside the home (smoking-permitted homes, SPH) or not (smoke-free homes, SFH), and measured indoor PM_2.5 concentrations using a low-cost instrument (Dylos DC1700) for at least 22 hours. We describe and compare SPH and SFH and use multiple linear regression to evaluate which variables are associated with PM_2.5 level among all households.

RESULTS

We surveyed 1746 households between April and August 2018; 967 (55%) were SPH and 779 (45%) were SFH. The difference between PM_2.5 values for SFH (median 27 µg/m³, IQR 25) and SPH (median 32 µg/m³, IQR 31) was 5 µg/m³ (p<0.001). Lead participant's education level, being a non-smoker, having outdoor space and smoke-free rule at home and not using kerosene oil for cooking were significantly associated with lower PM_2.5.

CONCLUSIONS

We found a small but significant difference between PM_2.5 concentrations in SPH compared with SFH in Dhaka, Bangladesh-a value much lower than observed in HICs.

Indoor Exposure to Selected Air Pollutants in the Home Environment: A Systematic Review

(1) Background: There is increasing awareness that the quality of the indoor environment affects our health and well-being. Indoor air quality (IAQ) in particular has an impact on multiple health outcomes, including respiratory and cardiovascular illness, allergic symptoms, cancers, and premature mortality. (2) Methods: We carried out a global systematic literature review on indoor exposure to selected air pollutants associated with adverse health effects, and related household characteristics, seasonal influences and occupancy patterns. We screened records from six bibliographic databases: ABI/INFORM, Environment Abstracts, Pollution Abstracts, PubMed, ProQuest Biological and Health Professional, and Scopus. (3) Results: Information on indoor exposure levels and determinants, emission sources, and associated health effects was extracted from 141 studies from 29 countries. The most-studied pollutants were particulate matter (PM_2.5 and PM₁₀); nitrogen dioxide (NO₂); volatile organic compounds (VOCs) including benzene, toluene, xylenes and formaldehyde; and polycyclic aromatic hydrocarbons (PAHs) including naphthalene. Identified indoor PM_2.5 sources include smoking, cooking, heating, use of incense, candles, and insecticides, while cleaning, housework, presence of pets and movement of people were the main sources of coarse particles. Outdoor air is a major PM_2.5 source in rooms with natural ventilation in roadside households. Major sources of NO₂ indoors are unvented gas heaters and cookers. Predictors of indoor NO₂ are ventilation, season, and outdoor NO₂ levels. VOCs are emitted from a wide range of indoor and outdoor sources, including smoking, solvent use, renovations, and household products. Formaldehyde levels are higher in newer houses and in the presence of new furniture, while PAH levels are higher in smoking households. High indoor particulate matter, NO₂ and VOC levels were typically associated with respiratory symptoms, particularly asthma symptoms in children. (4) Conclusions: Household characteristics and occupant activities play a large role in indoor exposure, particularly cigarette smoking for PM_2.5, gas appliances for NO₂, and household products for VOCs and PAHs. Home location near high-traffic-density roads, redecoration, and small house size contribute to high indoor air pollution. In most studies, air exchange rates are negatively associated with indoor air pollution. These findings can inform interventions aiming to improve IAQ in residential properties in a variety of settings.

A Case-Crossover Analysis of Indoor Heat Exposure on Mortality and Hospitalizations among the Elderly in Houston, Texas

BACKGROUND

Despite the substantial role indoor exposure has played in heat wave-related mortality, few epidemiological studies have examined the health effects of exposure to indoor heat. As a result, knowledge gaps regarding indoor heat-health thresholds, vulnerability, and adaptive capacity persist.

OBJECTIVE

We evaluated the role of indoor heat exposure on mortality and morbidity among the elderly (≥65 years of age) in Houston, Texas.

METHODS

Mortality and emergency hospital admission data were obtained through the Texas Department of State Health Services. Summer indoor heat exposure was modeled at the U.S. Census block group (CBG) level using building energy models, outdoor weather data, and building characteristic data. Indoor heat-health associations were examined using time-stratified case-crossover models, controlling for temporal trends and meteorology, and matching on CBG of residence, year, month, and weekday of the adverse health event. Separate models were fitted for three indoor exposure metrics, for individual lag days 0-6, and for 3-d moving averages (lag 0-2). Effect measure modification was explored via stratification on individual- and area-level vulnerability factors.

RESULTS

We estimated positive associations between short-term changes in indoor heat exposure and cause-specific mortality and morbidity [e.g., circulatory deaths, odds ratio per 5°C increase=1.16 (95% CI: 1.03, 1.30)]. Associations were generally positive for earlier lag periods and weaker across later lag periods. Stratified analyses suggest stronger associations between indoor heat and emergency hospital admissions among African Americans compared with Whites.

DISCUSSION

Findings suggest excess mortality among certain elderly populations in Houston who are likely exposed to high indoor heat. We developed a novel methodology to estimate indoor heat exposure that can be adapted to other U.S.

LOCATIONS

In locations with high air conditioning prevalence, simplified modeling approaches may adequately account for indoor heat exposure in vulnerable neighborhoods. Accounting for indoor heat exposure may improve the estimation of the total impact of heat on health. https://doi.org/10.1289/EHP6340.

Changes in outdoor air pollution due to COVID-19 lockdowns differ by pollutant: evidence from Scotland

Objectives

To examine the impact of COVID-19 lockdown restrictions in March/April 2020 on concentrations of nitrogen dioxide (NO2) and ambient fine particulate matter (PM2.5) air pollution measured at roadside monitors across Scotland by comparing data with previous years.

Methods

Publicly available data of PM2.5 concentrations from reference monitoring systems at sites across Scotland were extracted for the 31-day period immediately following the imposition of lockdown rules on 23 March 2020. Similar data for 2017, 2018 and 2019 were gathered for comparison. Mean period values were calculated from the hourly data and logged values compared using pairwise t-tests. Weather effects were corrected using meteorological normalisation.

Results

NO2 concentrations were significantly lower in the 2020 lockdown period than in the previous 3 years (p<0.001). Mean outdoor PM2.5 concentrations in 2020 were much lower than during the same period in 2019 (p<0.001). However, despite UK motor vehicle journeys reducing by 65%, concentrations in 2020 were within 1 µg/m3 of those measured in 2017 (p=0.66) and 2018 (p<0.001), suggesting that traffic-related emissions may not explain variability of PM2.5 in outdoor air in Scotland.

Conclusions

The impact of reductions in motor vehicle journeys during COVID-19 lockdown restrictions may not have reduced ambient PM2.5 concentrations in some countries. There is also a need for work to better understand how movement restrictions may have impacted personal exposure to air pollutants generated within indoor environments.

In Situ Measurements of Energy Consumption and Indoor Environmental Quality of a Pre-Retrofitted Student Dormitory in Athens

In the following years all European Union member states should bring into force national laws on the energy performance of buildings. Moreover, university campus dormitories are buildings of great importance, due to their architectural characteristics and their social impact. In this study, the energy performance along with the indoor environmental conditions of a dormitory of a university has been analysed. The in situ measurements included temperature, relative humidity, concentrations of carbon dioxide, total volatile organic compounds, and electrical consumption; lastly, the energy signature of the whole building was investigated. The study focused on the summer months, during which significantly increased thermal needs of the building were identified. The ground floor was found to be the floor with the highest percentage of thermal conditions within the comfort range, and the third floor the lowest. Lastly, a significant correlation between electrical consumption and the outdoor temperature was presented, highlighting the lack of thermal insulation. Overall, it was clear that a redesign of the cooling and heating system, the installation of a ventilation system, and thermal insulation are essential for improving the energy efficiency of this building.

Sociodemographic factors associated with secondhand smoke exposure and smoking rules in homes with children

Background

This study aims to identify sociodemographic characteristics associated with secondhand smoke (SHS) exposure and the adoption of smoking bans in homes with children in Spain

Methods

We performed, in 2016, a cross-sectional study to a representative sample of Spanish households with children under 12 years old. We administered a telephone survey to the parents asking about smoking patterns at home, children’s SHS exposure and sociodemographic characteristics. Poisson regression models with robust variance were built to assess sociodemographic characteristics associated with household SHS exposure and the adoption of smoking rules.

Results

In this study participated 2411 families, 25.8% of which reported exposure at home and 84.4% implemented smoking bans. SHS exposure was associated with having one (aPR = 2.09; 95% CI: 1.43–3.04) or two Spanish parents (aPR = 1.71; 95% CI: 1.24–2.36), lower educational attainment (primary: aPR = 1.74; 95% CI: 1.45–2.10; secondary: aPR = 1.37; 95% CI: 1.17–1.60 compared with university studies), a family structure different from two-parent family (aPR = 1.38; 95% CI: 1.14–1.67) and parents between 31 and 40 years (aPR = 0.75; 95% CI: 0.57–0.99) and 41–50 years (aPR = 0.62; 95% CI: 0.47–0.81) compared with 18- to 30-year-old parents. The adoption of smoking bans was associated with two-parent family (aPR = 1.09; 95% CI: 1.01–1.17), living with non-smokers (aPR = 1.46; 95% CI: 1.31–1.62), parents of foreign origin (aPR = 1.09; 95% CI: 1.04–1.14) and younger children (0–3 years: aPR = 1.05; 95% CI: 1.01–1.09) compared with the oldest children (8–11 years).

Conclusion

The parent’s origin and the family structure were associated with SHS exposure and the adoption of smoking bans at home. Moreover, the number of smokers living at home was relevant for the adoption of smoking bans, and the educational attainment for SHS exposure. These factors should be taken into consideration when designing or implementing smoke-free home programmes.

Urban heat and air pollution: A framework for integrating population vulnerability and indoor exposure in health risk analyses

Urban growth and climate change will exacerbate extreme heat events and air pollution, posing considerable health challenges to urban populations. Although epidemiological studies have shown associations between health outcomes and exposures to ambient air pollution and extreme heat, the degree to which indoor exposures and social and behavioral factors may confound or modify these observed effects remains underexplored. To address this knowledge gap, we explore the linkages between vulnerability science and epidemiological conceptualizations of risk to propose a conceptual and analytical framework for characterizing current and future health risks to air pollution and extreme heat, indoors and outdoors. Our framework offers guidance for research on climatic variability, population vulnerability, the built environment, and health effects by illustrating how health data, spatially resolved ambient data, estimates of indoor conditions, and household-level vulnerability data can be integrated into an epidemiological model. We also describe an approach for characterizing population adaptive capacity and indoor exposure for use in population-based epidemiological models. Our framework and methods represent novel resources for the evaluation of health risks from extreme heat and air pollution, both indoors and outdoors.

The effects of filters for an intelligent air pollutant control system considering natural ventilation and the occupants

Experimental analysis was conducted on the indoor air pollutant concentration using natural ventilation and filters. The study targeted two office rooms each of which was occupied by four people, and with the same outdoor environments. A non-woven fabric filter (room A) and an electrostatic filter (room B) were installed on the window frame, and the indoor air pollutant concentration and indoor climate factors were monitored based on the number of occupants and the occupants' activities. The results are as follows: (i) when the number of occupants in each room increased from 0.03-0.06 to 1.53-1.63, room A showed a 60% average PM₁₀ concentration increase while room B showed an opposite result (10% average PM₁₀ concentration decrease), meaning the electrostatic filter's lower resistance to flow contributed to better ventilation and also decreased the influence of the occupants on the indoor air pollutant concentration. A low correlation (0.323-0.350) between the CO₂ concentration and the occupants in room B also proved these results; (ii) while the average PM₁₀ concentration in room A was 9 μg/m³ higher than that in room B, the average PM_2.5 concentration in room A was higher by only 0.2 μg/m³, which showing that much of the generated or resuspended indoor particulate matter was PM₁₀; and (iii) due to the more frequent heat transfer from outdoors to indoors, room B consumed 23% more heating energy. The results of this study are expected to be used as bases for the establishment of an appropriate management strategy that considers the indoor air pollutant concentration caused by the number of occupants and occupants' activities by combining natural ventilation and filters.

Indoor cannabis smoke and children's health

Cannabis use is increasing and cannabis is typically consumed by smoking. This study explored how indoor secondhand cannabis smoke (SCS) was associated with child health. As part of a larger trial, air particle monitors were placed in 298 homes of families with at least one cigarette smoker and one child under 14 years old in San Diego County, California. Assessment included past 7-day indoor cigarette and cannabis use, the youngest child's exposure to cigarette smoke, and 5 smoke-related past-year child health outcomes: emergency department use for coughing/difficulty breathing; physician diagnosis of ear infection, bronchitis/bronchiolitis, asthma, or eczema/atopic dermatitis. An ordinal measure of adverse health outcomes (0, 1, or ≥2) was regressed on reported indoor cannabis smoking—the main measure of exposure (yes/no). Of 221 parents/guardians asked about cannabis use, 192 (86.9%) provided all required data, and 29 (15.1%) reported indoor cannabis smoking; reports were supported by air particle data. Homes without indoor smoking had lower average 7-day particle concentrations (1968 particles/0.01ft³) than homes with cannabis smoking only (3131 particles/0.01ft³), cigarette smoking only (3095 particles/0.01ft³), or both cigarette and cannabis smoking (6006 particles/0.01ft³). Odds of reporting a greater number of adverse health outcomes were 1.83 (95% CI = 0.89–3.80, p = 0.10) times higher for children of families with indoor cannabis smoking vs families without cannabis smoking, after controlling for exposure to cigarette smoke and other covariates. Our results do not indicate a statistically significant association. However, the magnitude of the (non-significant) association between indoor cannabis smoking and adverse health outcomes warrants more studies.

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Indoor cannabis smoking raises particle levels and risk of child particle exposure.

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Smoking cannabis in-home may adversely impact child health.

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This adverse impact may occur in homes with or without indoor cigarette smoking.

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Health effects of secondhand cannabis smoke exposure need to be further explored.

Randomised controlled trial of real-time feedback and brief coaching to reduce indoor smoking

BACKGROUND

Previous secondhand smoke (SHS) reduction interventions have provided only delayed feedback on reported smoking behaviour, such as coaching, or presenting results from child cotinine assays or air particle counters.

DESIGN

This SHS reduction trial assigned families at random to brief coaching and continuous real-time feedback (intervention) or measurement-only (control) groups.

PARTICIPANTS

We enrolled 298 families with a resident tobacco smoker and a child under age 14.

INTERVENTION

We installed air particle monitors in all homes. For the intervention homes, immediate light and sound feedback was contingent on elevated indoor particle levels, and up to four coaching sessions used prompts and praise contingent on smoking outdoors. Mean intervention duration was 64 days.

MEASURES

The primary outcome was 'particle events' (PEs) which were patterns of air particle concentrations indicative of the occurrence of particle-generating behaviours such as smoking cigarettes or burning candles. Other measures included indoor air nicotine concentrations and participant reports of particle-generating behaviour.

RESULTS

PEs were significantly correlated with air nicotine levels (r=0.60) and reported indoor cigarette smoking (r=0.51). Interrupted time-series analyses showed an immediate intervention effect, with reduced PEs the day following intervention initiation. The trajectory of daily PEs over the intervention period declined significantly faster in intervention homes than in control homes. Pretest to post-test, air nicotine levels, cigarette smoking and e-cigarette use decreased more in intervention homes than in control homes.

CONCLUSIONS

Results suggest that real-time particle feedback and coaching contingencies reduced PEs generated by cigarette smoking and other sources.

TRIAL REGISTRATION NUMBER

NCT01634334; Post-results.

Electronic cigarettes: a task force report from the European Respiratory Society

There is a marked increase in the development and use of electronic nicotine delivery systems or electronic cigarettes (ECIGs). This statement covers electronic cigarettes (ECIGs), defined as "electrical devices that generate an aerosol from a liquid" and thus excludes devices that contain tobacco. Database searches identified published articles that were used to summarise the current knowledge on the epidemiology of ECIG use; their ingredients and accompanied health effects; second-hand exposure; use of ECIGs for smoking cessation; behavioural aspects of ECIGs and social impact; in vitro and animal studies; and user perspectives.ECIG aerosol contains potentially toxic chemicals. As compared to conventional cigarettes, these are fewer and generally in lower concentrations. Second-hand exposures to ECIG chemicals may represent a potential risk, especially to vulnerable populations. There is not enough scientific evidence to support ECIGs as an aid to smoking cessation due to a lack of controlled trials, including those that compare ECIGs with licenced stop-smoking treatments. So far, there are conflicting data that use of ECIGs results in a renormalisation of smoking behaviour or for the gateway hypothesis. Experiments in cell cultures and animal studies show that ECIGs can have multiple negative effects. The long-term effects of ECIG use are unknown, and there is therefore no evidence that ECIGs are safer than tobacco in the long term. Based on current knowledge, negative health effects cannot be ruled out.

Spatial-Temporal Analysis of PM2.5 and NO₂ Concentrations Collected Using Low-Cost Sensors in Peñuelas, Puerto Rico

The U.S. Environmental Protection Agency (EPA) is involved in the discovery, evaluation, and application of low-cost air quality (AQ) sensors to support citizen scientists by directly engaging with them in the pursuit of community-based interests. The emergence of low-cost (<$2500) sensors have allowed a wide range of stakeholders to better understand local AQ conditions. Here we present results from the deployment of the EPA developed Citizen Science Air Monitor (CSAM) used to conduct approximately five months (October 2016⁻February 2017) of intensive AQ monitoring in an area of Puerto Rico (Tallaboa-Encarnación, Peñuelas) with little historical data on pollutant spatial variability. The CSAMs were constructed by combining low-cost particulate matter size fraction 2.5 micron (PM2.5) and nitrogen dioxide (NO₂) sensors and distributed across eight locations with four collocated weather stations to measure local meteorological parameters. During this deployment 1 h average concentrations of PM2.5 and NO₂ ranged between 0.3 to 33.6 µg/m³ and 1.3 to 50.6 ppb, respectively. Peak concentrations were observed for both PM2.5 and NO₂ when conditions were dominated by coastal-originated winds. These results advanced the community's understanding of pollutant concentrations and trends while improving our understanding of the limitations and necessary procedures to properly interpret measurements produced by low-cost sensors.

Developing a predictive model for fine particulate matter concentrations in low socio-economic households in Durban, South Africa

In low-resource settings, there is a need to develop models that can address contributions of household and outdoor sources to population exposures. The aim of the study was to model indoor PM_2.5 using household characteristics, activities, and outdoor sources. Households belonging to participants in the Mother and Child in the Environment (MACE) birth cohort, in Durban, South Africa, were randomly selected. A structured walk-through identified variables likely to generate PM_2.5 . MiniVol samplers were used to monitor PM_2.5 for a period of 24 hours, followed by a post-activity questionnaire. Factor analysis was used as a variable reduction tool. Levels of PM_2.5 in the south were higher than in the north of the city (P < .05); crowding and dwelling type, household emissions (incense, candles, cooking), and household smoking practices were factors associated with an increase in PM_2.5 levels (P < .05), while room magnitude and natural ventilation factors were associated with a decrease in the PM_2.5 levels (P < .05). A reasonably robust PM_2.5 predictive model was obtained with model R² of 50%. Recognizing the challenges in characterizing exposure in environmental epidemiological studies, particularly in resource-constrained settings, modeling provides an opportunity to reasonably estimate indoor pollutant levels in unmeasured homes.