Real-time air monitoring of occupational exposures to particulate matter among hairdressers in Maryland: A pilot study

Hairdressers are exposed to particulate matter (PM), a known air pollutant linked to adverse health effects. Still, studies on occupational PM exposures in hair salons are sparse. We characterized indoor air PM concentrations in three salons primarily serving an African/African American (AA) clientele, and three Dominican salons primarily serving a Latino clientele. We also assessed the performance of low-cost sensors (uRAD, Flow, AirVisual) by comparing them to high-end sensors (DustTrak) to conduct air monitoring in each salon over 3 days to quantify work shift concentrations of PM_2.5, respirable PM (RPM), and PM₁₀. We observed high spatial and temporal variability in 30-min time-weighted average (TWA) RPM concentrations (0.18–5518 μg/m³). Readings for the uRAD and AirVisual sensors were highly correlated with the DustTrak (R² = 0.90–0.99). RPM 8-hour TWAs ranged from 18 to 383 µg/m³ for AA salons, and 9–2115 µg/m³ for Dominican salons. Upper 95th percentiles of daily RPM exposures ranged from 439 to 2669 µg/m³. The overall range of 30-min TWA PM_2.5 and PM₁₀ concentrations was 0.13–5497 and 0.36-,541 μg/m³, respectively. Findings suggest that hairdressers could be overexposed to RPM during an 8-hour shift. Additional comprehensive monitoring studies are warranted to further characterize temporal and spatial variability of PM exposures in this understudied occupational population.     

Monitoring and modeling of household air quality related to use of different Cookfuels in Paraguay

In Paraguay, 49% of the population depends on biomass (wood and charcoal) for cooking. Residential biomass burning is a major source of fine particulate matter (PM_2.5) and carbon monoxide (CO) in and around the household environment. In July 2016, cross‐sectional household air pollution sampling was conducted in 80 households in rural Paraguay. Time‐integrated samples (24 hours) of PM_2.5 and continuous CO concentrations were measured in kitchens that used wood, charcoal, liquefied petroleum gas (LPG), or electricity to cook. Qualitative and quantitative household‐level variables were captured using questionnaires. The average PM_2.5 concentration (μg/m³) was higher in kitchens that burned wood (741.7 ± 546.4) and charcoal (107.0 ± 68.6) than in kitchens where LPG (52.3 ± 18.9) or electricity (52.0 ± 14.8) was used. Likewise, the average CO concentration (ppm) was higher in kitchens that used wood (19.4 ± 12.6) and charcoal (7.6 ± 6.5) than in those that used LPG (0.5 ± 0.6) or electricity (0.4 ± 0.6). Multivariable linear regression was conducted to generate predictive models for indoor PM_2.5 and CO concentrations (predicted R² = 0.837 and 0.822, respectively). This study provides baseline indoor air quality data for Paraguay and presents a multivariate statistical approach that could be used in future research and intervention programs.     

Particulate matter emitted from ultrasonic humidifiers—Chemical composition and implication to indoor air

Household humidification is widely practiced to combat dry indoor air. While the benefits of household humidification are widely perceived, its implications to the indoor air have not been critically appraised. In particular, ultrasonic humidifiers are known to generate fine particulate matter (PM). In this study, we first conducted laboratory experiments to investigate the size, quantity, and chemical composition of PM generated by an ultrasonic humidifier. The mass of PM generated showed a correlation with the total alkalinity of charge water, suggesting that CaCO₃ is likely making a major contribution to PM. Ion chromatography analysis revealed a large amount of SO₄²⁻ in PM, representing a previously unrecognized indoor source. Preliminary results of organic compounds being present in humidifier PM are also presented. A whole-house experiment was further conducted at an actual residential house, with five low-cost sensors (AirBeam) monitoring PM in real time. Operation of a single ultrasonic humidifier resulted in PM_2.5 concentrations up to hundreds of μg m⁻³, and its influence extended across the entire household. The transport and loss of PM_2.5 depended on the rate of air circulation and ventilation. This study emphasizes the need to further investigate the impact of humidifier operation, both on human health and on the indoor atmospheric chemistry, for example, partitioning of acidic and basic compounds.     

Real-time measurements of PM2.5 and ozone to assess the effectiveness of residential indoor air filtration in Shanghai homes

Portable air cleaners are increasingly used in polluted areas in an attempt to reduce human exposure; however, there has been limited work characterizing their effectiveness at reducing exposure. With this in mind, we recruited forty-three children with asthma from suburban Shanghai and deployed air cleaners (with HEPA and activated carbon filters) in their bedrooms. During both 2-week filtration and non-filtration periods, low-cost PM_2.5 and O₃ air monitors were used to measure pollutants indoors, outdoors, and for personal exposure. Indoor PM_2.5 concentrations were reduced substantially with the use of air cleaners, from 34 ± 17 to 10 ± 8 µg/m³, with roughly 80% of indoor PM_2.5 estimated to come from outdoor sources. Personal exposure to PM_2.5 was reduced from 40 ± 17 to 25 ± 14 µg/m³. The more modest reductions in personal exposure and high contribution of outdoor PM_2.5 to indoor concentrations highlight the need to reduce outdoor PM_2.5 and/or to clean indoor air in multiple locations. Indoor O₃ concentrations were generally low (mean = 8±4 ppb), and no significant difference was seen by filtration status. The concentrations of pollutants and the air cleaner effectiveness were highly variable over time and across homes, highlighting the usefulness of real-time air monitors for understanding individual exposure reduction strategies.     

Maternal exposure to carbon monoxide and fine particulate matter during pregnancy in an urban Tanzanian cohort

Low birthweight contributes to as many as 60% of all neonatal deaths; exposure during pregnancy to household air pollution has been implicated as a risk factor. Between 2011 and 2013, we measured personal exposures to carbon monoxide (CO) and fine particulate matter (PM_2.5) in 239 pregnant women in Dar es Salaam, Tanzania. CO and PM_2.5 exposures during pregnancy were moderately high (geometric means 2.0 ppm and 40.5 μg/m³); 87% of PM_2.5 measurements exceeded WHO air quality guidelines. Median and high (75th centile) CO exposures were increased for those cooking with charcoal and kerosene versus kerosene alone in quantile regression. High PM_2.5 exposures were increased with charcoal use. Outdoor cooking reduced median PM_2.5 exposures. For PM_2.5, we observed a 0.15 kg reduction in birthweight per interquartile increase in exposure (23.0 μg/m³) in multivariable linear regression; this finding was of borderline statistical significance (95% confidence interval 0.30, 0.00 kg; P = 0.05). PM_2.5 was not significantly associated with birth length or head circumference nor were CO exposures associated with newborn anthropometrics. Our findings contribute to the evidence that exposure to household air pollution, and specifically fine particulate matter, may adversely affect birthweight.     

Infiltration of fine particles in urban daycares

Singapore is a tropical country with a high density of day-care facilities whose indoor environments may be adversely affected by outdoor fine particle (PM_2.5) air pollution. To reduce this problem requires effective, evidence-based exposure-reduction strategies. Little information is available on the penetration of outdoor PM_2.5 into day-care environments. Our study attempted to address the following objectives: to measure indoor infiltration factor (F_inf) of PM_2.5 from outdoor PM_2.5 and to determine the building parameters that modify the indoor PM_2.5. We collected indoor/outdoor 1-min PM_2.5 from 50 day-care classrooms. We noted mean F_inf ± SD of 0.65 ± 0.22 in day-care rooms which are naturally ventilated and lower F_inf ± SD values of 0.47 ± 0.18 for those that are air-conditioned: values which are lower than those reported in Singapore residences. The air exchange rates were higher in naturally ventilated rooms (1.47 vs 0.86 h⁻¹). However, fine particle deposition rates were lower for naturally ventilated rooms (0.67 ± 0.43 h⁻¹) compared with air-conditioned ones (1.03 ± 0.55 h⁻¹) presumably due to composite rates linked to the filters within the split unit air-conditioners, higher recirculation rates, and interior surfaces in the latter. Our findings indicate that children remaining indoor in daycares where air-conditioning is used can reduce their PM_2.5 exposures during outdoor pollution episodes.     

Interpretation of the variability of levels of regional background aerosols in the Western Mediterranean

Results on interpretation of the variability of regional background PM levels in the Western Mediterranean basin (WMB) are presented. Mean PM levels recorded at Montseny, MSY (North-Eastern Spain) in the 2002-2007 period reached 17, 13 and 11 µg/m³ of PM₁₀, PM_2.5 and PM₁, respectively.The daily evolution of PM levels is regulated by the breeze circulation (mountain and sea breezes). PM levels are lower at the rural sites at night owing to the nocturnal drainage flows and to the lowering of the mixing layer height below the MSY high. These nocturnal low levels allowed us to estimate the continental background PM levels. At midday, the atmospheric pollutants accumulated in the pre-coastal depression are transported upwards by the breeze, increasing PM levels.Maximum PM₁₀ levels were recorded in summer, and February-March and November, and minimum values in the rest of the year coinciding with the highest frequency of Atlantic advection. PM peak episodes attributed to Saharan dust outbreaks were recorded in summer and February-March. In addition, anticyclonic situations (February-March and November) may impact in elevated rural areas by increasing hourly levels of PM₁ up to 75 µg/m³. This scenario induces the stagnation of pollutants in the pre-coastal depression. Solar radiation activates mountain winds, transporting polluted air masses from the valleys to elevated areas resulting in an increase of fine PM levels in areas outside the boundary layer.A significant decrease in PM annual means (40% and 34% for the entire monitoring period, 7 µgPM₁₀/m³ and 5 µgPM_2.5/m³) was recorded at MSY between 2002 and 2007. There appears to be no single cause behind these trends. This could partially be ascribed to the varying frequency and intensity of Saharan dust episodes, but also to large-scale meteorological processes or cycles, and/or to local or meso-scale processes such as nearby anthropogenic emission sources.     

Impacts of stove/fuel use and outdoor air pollution on chemical composition of household particulate matter

Biomass combustion for cooking and heating releases particulate matter (PM_2.5) that contributes to household air pollution. Fuel and stove types affect the chemical composition of household PM, as does infiltration of outdoor PM. Characterization of these impacts can inform future exposure assessments and epidemiologic studies, but is currently limited. In this study, we measured chemical components of PM_2.5 (water-soluble organic matter [WSOM], ions, black carbon, elements, organic tracers) in rural Chinese households using traditional biomass stoves, semi-gasifier stoves with pelletized biomass, and/or non-biomass stoves. We distinguished households using one stove type (traditional, semi-gasifier, or LPG/electric) from those using multiple stoves/fuels. WSOM concentrations were higher in households using only semi-gasifier or traditional stoves (31%-33%) than in those with exclusive LPG/electric stove (13%) or mixed stove use (12%-22%). Inorganic ions comprised 14% of PM in exclusive LPG/electric households, compared to 1%-5% of PM in households using biomass. Total PAH content was much higher in households that used traditional stoves (0.8-2.8 mg/g PM) compared to those that did not (0.1-0.3 mg/g PM). Source apportionment revealed that biomass burning comprised 27%-84% of PM_2.5 in households using biomass. In all samples, identified outdoor sources (vehicles, dust, coal combustion, secondary aerosol) contributed 10%-20% of household PM_2.5.     

A review on reducing indoor particulate matter concentrations from personal-level air filtration intervention under real-world exposure situations

Improving air quality in indoor environments where people live is of importance to protect human health. In this systematic review, we assessed the effectiveness of personal-level use of air filtration units in reducing indoor particulate matters (PM) concentrations under real-world situations following systematic review guidelines. A total of 54 articles were included in the review, in which 20 randomized controlled/crossover trials that reported the changes in indoor fine PM (PM_2.5) concentrations were quantitatively assessed in meta-analysis. Standardized mean differences (SMDs) were calculated for changes in indoor PM concentrations following air filtration interventions. Moderate-to-large reductions of 11%–82% in indoor PM_2.5 concentrations were observed with SMD of −1.19 (95% CI: −1.50, −0.88). The reductions in indoor PM concentrations varied by geographical locations, filtration technology employed, indoor environmental characteristics, and air pollution sources. Most studies were graded with low-to-moderate risk of bias; however, the overall certainty of evidence for indoor PM concentration reductions was graded at very low level. Considering the effectiveness of indoor air filtration under practical uses, socio-economic disparities across study populations, and costs of air filter replacement over time, our results highlight the importance of reducing air pollution exposure at the sources.     

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.     

Modeling approaches and performance for estimating personal exposure to household air pollution: A case study in Kenya

This study assessed the performance of modeling approaches to estimate personal exposure in Kenyan homes where cooking fuel combustion contributes substantially to household air pollution (HAP). We measured emissions (PM_2.5, black carbon, CO); household air pollution (PM_2.5, CO); personal exposure (PM_2.5, CO); stove use; and behavioral, socioeconomic, and household environmental characteristics (eg, ventilation and kitchen volume). We then applied various modeling approaches: a single-zone model; indirect exposure models, which combine person-location and area-level measurements; and predictive statistical models, including standard linear regression and ensemble machine learning approaches based on a set of predictors such as fuel type, room volume, and others. The single-zone model was reasonably well-correlated with measured kitchen concentrations of PM_2.5 (R² = 0.45) and CO (R² = 0.45), but lacked precision. The best performing regression model used a combination of survey-based data and physical measurements (R² = 0.76) and a root mean-squared error of 85 µg/m³, and the survey-only-based regression model was able to predict PM2.5 exposures with an R² of 0.51. Of the machine learning algorithms evaluated, extreme gradient boosting performed best, with an R² of 0.57 and RMSE of 98 µg/m³.     

Size distribution and lung-deposited doses of particulate matter from household exposure to biomass smoke

Exposure to high concentrations of particulate matter (PM) is associated with a number of adverse health effects. However, it is unclear which aspects of PM are most hazardous, and a better understanding of particle sizes and personal exposure is needed. We characterized particle size distribution (PSD) from biomass-related pollution and assessed total and regional lung-deposited doses using multiple-path deposition modeling. Gravimetric measurements of kitchen and personal PM_2.5 (<2.5 µm in size) exposures were collected in 180 households in rural Puno, Peru. Direct-reading measurements of number concentrations were collected in a subset of 20 kitchens for particles 0.3-25 µm, and the continuous PSD was derived using a nonlinear least-squares method. Mean daily PM_2.5 kitchen concentration and personal exposure was 1205 ± 942 µg/m³ and 115 ± 167 µg/m³, respectively, and the mean mass concentration consisted of a primary accumulation mode at 0.21 µm and a secondary coarse mode at 3.17 µm. Mean daily lung-deposited surface area (LDSA) and LDSA during cooking were 1009.6 ± 1469.8 µm²/cm³ and 10,552.5 ± 8261.6 µm²/cm³, respectively. This study presents unique data regarding lung deposition of biomass smoke that could serve as a reference for future studies and provides a novel, more biologically relevant metric for exposure-response analysis compared to traditional size-based metrics.     

Chimney stoves modestly improved Indoor Air Quality measurements compared with traditional open fire stoves: results from a small‐scale intervention study in rural Peru

Nearly half of the world's population depends on biomass fuels to meet domestic energy needs, producing high levels of pollutants responsible for substantial morbidity and mortality. We compare carbon monoxide (CO) and particulate matter (PM_2.5) exposures and kitchen concentrations in households with study‐promoted intervention (OPTIMA‐improved stoves and control stoves) in San Marcos Province, Cajamarca Region, Peru. We determined 48‐h indoor air concentration levels of CO and PM_2.5 in 93 kitchen environments and personal exposure, after OPTIMA‐improved stoves had been installed for an average of 7 months. PM_2.5 and CO measurements did not differ significantly between OPTIMA‐improved stoves and control stoves. Although not statistically significant, a post hoc stratification of OPTIMA‐improved stoves by level of performance revealed mean PM_2.5 and CO levels of fully functional OPTIMA‐improved stoves were 28% lower (n = 20, PM_2.5, 136 μg/m³ 95% CI 54–217) and 45% lower (n = 25, CO, 3.2 ppm, 95% CI 1.5–4.9) in the kitchen environment compared with the control stoves (n = 34, PM_2.5, 189 μg/m³, 95% CI 116–261; n = 44, CO, 5.8 ppm, 95% CI 3.3–8.2). Likewise, although not statistically significant, personal exposures for OPTIMA‐improved stoves were 43% and 17% lower for PM_2.5 (n = 23) and CO (n = 25), respectively. Stove maintenance and functionality level are factors worthy of consideration for future evaluations of stove interventions.     

Acute health effects from exposure to indoor ultrafine particles—A randomized controlled crossover study among young mild asthmatics

Particulate matter is linked to adverse health effects, however, little is known about health effects of particles emitted from typical indoor sources. We examined acute health effects of short-term exposure to emissions from cooking and candles among asthmatics. In a randomized controlled double-blinded crossover study, 36 young non-smoking asthmatics attended three exposure sessions lasting 5 h: (a) air mixed with emissions from cooking (fine particle mass concentration): (PM_2.5: 96.1 μg/m³), (b) air mixed with emissions from candles (PM_2.5: 89.8 μg/m³), and c) clean filtered air (PM_2.5: 5.8 μg/m³). Health effects (spirometry, fractional exhaled Nitric Oxide [FeNO], nasal volume and self-reported symptoms) were evaluated before exposure start, then 5 and 24 h after. During exposures volatile organic compounds (VOCs), particle size distributions, number concentrations and optical properties were measured. Generally, no statistically significant changes were observed in spirometry, FeNO, or nasal volume comparing cooking and candle exposures to clean air. In males, nasal volume and FeNO decreased after exposure to cooking and candles, respectively. Participants reported additional and more pronounced symptoms during exposure to cooking and candles compared to clean air. The results indicate that emissions from cooking and candles exert mild inflammation in asthmatic males and decrease comfort among asthmatic males and females.     

Indoor fine particulate matter and demographic,household, and wood stove characteristics among rural US homes heated with wood fuel

Household heating using wood stoves is common practice in many rural areas of the United States (US) and can lead to elevated concentrations of indoor fine particulate matter (PM_2.5). We collected 6-day measures of indoor PM_2.5 during the winter and evaluated household and stove-use characteristics in homes at three rural and diverse study sites. The median indoor PM_2.5 concentration across all homes was 19 µg/m³, with higher concentrations in Alaska (median = 30, minimum = 4, maximum = 200, n = 10) and Navajo Nation homes (median = 29, minimum = 3, maximum = 105, n = 23) compared with Montana homes (median = 16, minimum = 2, maximum = 139, n = 59). Households that had not cleaned the chimney within the past year had 65% higher geometric mean PM_2.5 compared to those with chimney cleaned within 6 months (95% confidence interval [CI]: −1, 170). Based on a novel wood stove grading method, homes with low-quality and medium-quality stoves had substantially higher PM_2.5 compared to homes with higher-quality stoves (186% higher [95% CI: 32, 519] and 161% higher; [95% CI:27, 434], respectively). Our findings highlight the need for, and complex nature of, regionally appropriate interventions to reduce indoor air pollution in rural wood-burning regions. Higher-quality stoves and behavioral practices such as regular chimney cleaning may help improve indoor air quality in such homes.     

Negative ions offset cardiorespiratory benefits of PM2.5 reduction from residential use of negative ion air purifiers

Negative ion air purifiers (NIAPs), as a less costly alternative to the HEPA filtration, have been increasingly deployed in China and potentially elsewhere. While reducing indoor concentrations of fine particulate matter (PM_2.5), NIAPs generate massive amounts of negative ions that may be of health concern. We performed week-long interventions with NIAPs in the dormitories of 56 healthy college students living in Beijing. In a randomized order, each student underwent a true and a sham NIAP session. Cardiorespiratory outcomes were measured before and after each session. The use of true NIAPs reduced indoor PM_2.5 concentrations significantly, while notably increased negative ion levels. Increases in PM_2.5 and negative ion (NI) exposure were independently associated with increased urinary concentration of malondialdehyde, a biomarker of systemic oxidative stress, resulting in a null net effect of NIAP on malondialdehyde. Likewise, no significant net effects of NIAPs were observed for other outcomes indicative of lung function, vascular tone, arterial stiffness, and inflammation. Our findings suggest that negative ions, possibly along with their reaction products with the room air constituents, adversely affect health. The downsides do not support the use of NIAPs as a health-based mitigation strategy to reduce PM_2.5 exposure, especially in residences with PM_2.5 concentrations that are not extremely high.     

Concurrent assessment of personal,indoor, and outdoor PM2.5 and PM1 levels and source contributions using novel low-cost sensing devices

The intensity, frequency, duration, and contribution of distinct PM_2.5 sources in Asian households have seldom been assessed; these are evaluated in this work with concurrent personal, indoor, and outdoor PM_2.5 and PM₁ monitoring using novel low-cost sensing (LCS) devices, AS-LUNG. GRIMM-comparable observations were acquired by the corrected AS-LUNG readings, with R² up to 0.998. Twenty-six non-smoking healthy adults were recruited in Taiwan in 2018 for 7-day personal, home indoor, and home outdoor PM monitoring. The results showed 5-min PM_2.5 and PM₁ exposures of 11.2 ± 10.9 and 10.5 ± 9.8 µg/m³, respectively. Cooking occurred most frequently; cooking with and without solid fuel contributed to high PM_2.5 increments of 76.5 and 183.8 µg/m³ (1 min), respectively. Incense burning had the highest mean PM_2.5 indoor/outdoor (1.44 ± 1.44) ratios at home and on average the highest 5-min PM_2.5 increments (15.0 µg/m³) to indoor levels, among all single sources. Certain events accounted for 14.0%-39.6% of subjects’ daily exposures. With the high resolution of AS-LUNG data and detailed time-activity diaries, the impacts of sources and ventilations were assessed in detail.     

Kerosene lighting contributes to household air pollution in rural Uganda

The literature on the contribution of kerosene lighting to indoor air particulate concentrations is sparse. In rural Uganda, kitchens are almost universally located outside the main home, and kerosene is often used for lighting. In this study, we obtained longitudinal measures of particulate matter 2.5 microns or smaller in size (PM_2.5) from living rooms and kitchens of 88 households in rural Uganda. Linear mixed‐effects models with a random intercept for household were used to test the hypotheses that primary reported lighting source and kitchen location (indoor vs outdoor) are associated with PM_2.5 levels. During initial testing, households reported using the following sources of lighting: open‐wick kerosene (19.3%), hurricane kerosene (45.5%), battery‐powered (33.0%), and solar (1.1%) lamps. During follow‐up testing, these proportions changed to 29.5%, 35.2%, 18.2%, and 9.1%, respectively. Average ambient, living room, and kitchen PM_2.5 levels were 20.2, 35.2, and 270.0 μg/m³. Living rooms using open‐wick kerosene lamps had the highest PM_2.5 levels (55.3 μg/m³) compared to those using solar lighting (19.4 μg/m³; open wick vs solar, P=.01); 27.6% of homes using open‐wick kerosene lamps met World Health Organization indoor air quality standards compared to 75.0% in homes using solar lighting.     

The impact of biogas and fuelwood use on institutional kitchen air quality in Kampala,Uganda

Experts have suggested that microscale biogas systems offer a source of renewable energy that improves indoor air quality, but such impacts have not been directly measured. This study documented cooking behaviors and measured 2.5‐μm particulate matter (PM_2.5), carbon monoxide (CO), and sulfur dioxide (SO₂) concentrations within 14 institutional kitchens in Kampala, Uganda, that prepare meals using biogas (n=5), a mixture of biogas and fuelwood (n=3), and fuelwood (n=6). Small institutions (10‐30 people) with biogas kitchens had 99% lower concentrations of PM_2.5 (21 μg/m³) than fuelwood kitchens (3100 μg/m³). Larger institutions (>100 people) had biogas systems that produced insufficient gas and relied on fuelwood to meet over 90% of their energy needs. PM_2.5 concentrations in these biogas‐firewood kitchens were equivalent to concentrations in fuelwood kitchens. Although concentrations of hydrogen sulfide (H₂S) in biogas were as high as 2000 ppm, 75% of systems had undetectable H₂S levels (<100 ppm) in the biogas. Kitchens using biogas with high H₂S had correspondingly higher SO₂ concentrations in the kitchen air. However, even the highest SO₂ concentration in biogas kitchens (150 μg/m³) was lower than SO₂ concentration in fuelwood kitchens (390 μg/m³). The results suggest that biogas systems can offer air quality improvements if sized properly for energy demands.     

Indoor exposure to particulate matter and the incidence of acute lower respiratory infections among children: A birth cohort study in urban Bangladesh

Approximately half of all children under two years of age in Bangladesh suffer from an acute lower respiratory infection (ALRI) each year. Exposure to indoor biomass smoke has been consistently associated with an increased risk of ALRI in young children. Our aim was to estimate the effect of indoor exposure to particulate matter (PM_2.5) on the incidence of ALRI among children in a low‐income, urban community in Bangladesh. We followed 257 children through two years of age to determine their frequency of ALRI and measured the PM_2.5 concentrations in their sleeping space. Poisson regression was used to estimate the association between ALRI and the number of hours per day that PM_2.5 concentrations exceeded 100 μg/m³, adjusting for known confounders. Each hour that PM_2.5 concentrations exceeded 100 μg/m³ was associated with a 7% increase in incidence of ALRI among children aged 0–11 months (adjusted incidence rate ratio (IRR) 1.07, 95% CI 1.01–1.14), but not in children 12–23 months old (adjusted IRR 1.00, 95% CI 0.92–1.09). Results from this study suggest that reducing indoor PM_2.5 exposure could decrease the frequency of ALRI among infants, the children at highest risk of death from these infections.