Development and evaluation of an ultrasonic personal aerosol sampler

Application of an Ultra-Low-Cost Passive Sampler for Light-Absorbing Carbon in Mongolia

Low-cost, long-term measures of air pollution concentrations are often needed for epidemiological studies and policy analyses of household air pollution. The Washington passive sampler (WPS), an ultra-low-cost method for measuring the long-term average levels of light-absorbing carbon (LAC) air pollution, uses digital images to measure the changes in the reflectance of a passively exposed paper filter. A prior publication on WPS reported high precision and reproducibility. Here, we deployed three methods to each of 10 households in Ulaanbaatar, Mongolia: one PurpleAir for PM2.5; two ultrasonic personal aerosol samplers (UPAS) with quartz filters for the thermal-optical analysis of elemental carbon (EC); and two WPS for LAC. We compared multiple rounds of 4-week-average measurements. The analyses calibrating the LAC to the elemental carbon measurement suggest that 1 µg of EC/m3 corresponds to 62 PI/month (R2 = 0.83). The EC-LAC calibration curve indicates an accuracy (root-mean-square error) of 3.1 µg of EC/m3, or ~21% of the average elemental carbon concentration. The RMSE values observed here for the WPS are comparable to the reported accuracy levels for other methods, including reference methods. Based on the precision and accuracy results shown here, as well as the increased simplicity of deployment, the WPS may merit further consideration for studying air quality in homes that use solid fuels.

Identifying the Relationship between PM2.5 and Hyperlipidemia Using Mendelian Randomization, RNA-seq Data and Model Mice Subjected to Air Pollution

Air pollution is an important public health problem that endangers human health. However, the casual association and pathogenesis between particles < 2.5 μm (PM2.5) and hyperlipidemia remains incompletely unknown. Mendelian randomization (MR) and transcriptomic data analysis were performed, and an air pollution model using mice was constructed to investigate the association between PM2.5 and hyperlipidemia. MR analysis demonstrated that PM2.5 is associated with hyperlipidemia and the triglyceride (TG) level in the European population (IVW method of hyperlipidemia: OR: 1.0063, 95%CI: 1.0010-1.0118, p = 0.0210; IVW method of TG level: OR: 1.1004, 95%CI: 1.0067-1.2028, p = 0.0350). Mest, Adipoq, Ccl2, and Pcsk9 emerged in the differentially expressed genes of the liver and plasma of PM2.5 model mice, which might mediate atherosclerosis accelerated by PM2.5. The studied animal model shows that the Paigen Diet (PD)-fed male LDLR-/- mice had higher total cholesterol (TC), TG, and CM/VLDL cholesterol levels than the control group did after 10 times 5 mg/kg PM2.5 intranasal instillation once every three days. Our study revealed that PM2.5 had causality with hyperlipidemia, and PM2.5 might affect liver secretion, which could further regulate atherosclerosis. The lipid profile of PD-fed Familial Hypercholesterolemia (FH) model mice is more likely to be jeopardized by PM2.5 exposure.

AirPen: A Wearable Monitor for Characterizing Exposures to Particulate Matter and Volatile Organic Compounds

Exposure to air pollution is a leading risk factor for disease and premature death, but technologies for assessing personal exposure to particulate and gaseous air pollutants, including the timing and location of such exposures, are limited. We developed a small, quiet, wearable monitor, called the AirPen, to quantify personal exposures to fine particulate matter (PM_2.5) and volatile organic compounds (VOCs). The AirPen combines physical sample collection (PM onto a filter and VOCs onto a sorbent tube) with a suite of low-cost sensors (for PM, VOCs, temperature, pressure, humidity, light intensity, location, and motion). We validated the AirPen against conventional personal sampling equipment in the laboratory and then conducted a field study to measure at-work and away-from-work exposures to PM_2.5 and VOCs among employees at an agricultural facility in Colorado, USA. The resultant sampling and sensor data indicated that personal exposures to benzene, toluene, ethylbenzene, and xylenes were dominated by a specific workplace location. These results illustrate how the AirPen can be used to advance our understanding of personal exposure to air pollution as a function of time, location, source, and activity, even in the absence of detailed activity diary data.

Higher mold levels found in in the deteriorated housing in the Sun Valley neighborhood of Denver, Colorado compared to other Denver housing and higher rates of health insurance claims for some diseases documented for the Sun Valley residents compared to other Denver residents

The Sun Valley Homes public housing in Denver, Colorado (CO) will be replaced because of its deteriorated condition. Our goal was to document the mold contamination and particulate matter (PM2.5) concentrations in Sun Valley homes and the circulatory and respiratory health of Sun Valley compared to all Denver residents (total 2761 and 1,049,046, respectively) based on insurance claims data for 2015 to 2019. Mold contamination in Sun Valley homes (n = 49) was quantified using the Environmental Relative Moldiness Index (ERMI) scale. Indoor PM2.5 concentrations were measured in Sun Valley homes (n = 11) using time-integrated, filter-based samples and quantified using gravimetric analysis. Outdoor PM2.5 concentrations data were obtained from a near-by United States Environmental Protection Agency monitoring station. In Sun Valley homes, the average ERMI value was 5.25 compared to -1.25 for other Denver homes. The PM2.5 median concentration inside Sun Valley homes was 7.6 μg/m3 (interquartile range - 6.4 μg/m3). The ratio of indoor to outdoor concentrations of PM2.5 was 2.3 (interquartile range - 1.5). In the last five years, ischemic heart disease was significantly more likely for Denver compared to Sun Valley residents. However, acute upper respiratory infections, chronic lower respiratory diseases and asthma were all significantly more likely for Sun Valley than Denver residents. Since the process of replacing and occupying the new housing will take several years, the next phase of the study will not occur until that process is complete.

Personal and household PM2.5 and black carbon exposure measures and respiratory symptoms in 8 low- and middle-income countries

BACKGROUND

Household air pollution (HAP) from cooking with solid fuels has been associated with adverse respiratory effects, but most studies use surveys of fuel use to define HAP exposure, rather than on actual air pollution exposure measurements.

OBJECTIVE

To examine associations between household and personal fine particulate matter (PM_2.5) and black carbon (BC) measures and respiratory symptoms.

METHODS

As part of the Prospective Urban and Rural Epidemiology Air Pollution study, we analyzed 48-h household and personal PM_2.5 and BC measurements for 870 individuals using different cooking fuels from 62 communities in 8 countries (Bangladesh, Chile, China, Colombia, India, Pakistan, Tanzania, and Zimbabwe). Self-reported respiratory symptoms were collected after monitoring. Associations between PM_2.5 and BC exposures and respiratory symptoms were examined using logistic regression models, controlling for individual, household, and community covariates.

RESULTS

The median (interquartile range) of household and personal PM_2.5 was 73.5 (119.1) and 65.3 (91.5) μg/m³, and for household and personal BC was 3.4 (8.3) and 2.5 (4.9) x10^-5 m^-1, respectively. We observed associations between household PM_2.5 and wheeze (OR: 1.25; 95%CI: 1.07, 1.46), cough (OR: 1.22; 95%CI: 1.06, 1.39), and sputum (OR: 1.26; 95%CI: 1.10, 1.44), as well as exposure to household BC and wheeze (OR: 1.20; 95%CI: 1.03, 1.39) and sputum (OR: 1.20; 95%CI: 1.05, 1.36), per IQR increase. We observed associations between personal PM_2.5 and wheeze (OR: 1.23; 95%CI: 1.00, 1.50) and sputum (OR: 1.19; 95%CI: 1.00, 1.41). For household PM_2.5 and BC, associations were generally stronger for females compared to males. Models using an indicator variable of solid versus clean fuels resulted in larger OR estimates with less precision.

CONCLUSIONS

We used measurements of household and personal air pollution for individuals using different cooking fuels and documented strong associations with respiratory symptoms.

Field measurements of indoor and community air quality in rural Beijing before, during, and after the COVID-19 lockdown

The coronavirus (COVID-19) lockdown in China is thought to have reduced air pollution emissions due to reduced human mobility and economic activities. Few studies have assessed the impacts of COVID-19 on community and indoor air quality in environments with diverse socioeconomic and household energy use patterns. The main goal of this study was to evaluate whether indoor and community air pollution differed before, during, and after the COVID-19 lockdown in homes with different energy use patterns. Using calibrated real-time PM_2.5 sensors, we measured indoor and community air quality in 147 homes from 30 villages in Beijing over 4 months including periods before, during, and after the COVID-19 lockdown. Community pollution was higher during the lockdown (61 ± 47 μg/m³ ) compared with before (45 ± 35 μg/m³ , p < 0.001) and after (47 ± 37 μg/m³ , p < 0.001) the lockdown. However, we did not observe significantly increased indoor PM_2.5 during the COVID-19 lockdown. Indoor-generated PM_2.5 in homes using clean energy for heating without smokers was the lowest compared with those using solid fuel with/without smokers, implying air pollutant emissions are reduced in homes using clean energy. Indoor air quality may not have been impacted by the COVID-19 lockdown in rural settings in China and appeared to be more impacted by the household energy choice and indoor smoking than the COVID-19 lockdown. As clean energy transitions occurred in rural households in northern China, our work highlights the importance of understanding multiple possible indoor sources to interpret the impacts of interventions, intended or otherwise.

Socioeconomic and Demographic Associations with Wintertime Air Pollution Exposures at Household, Community, and District Scales in Rural Beijing, China

The Chinese government implemented a national household energy transition program that replaced residential coal heating stoves with electricity-powered heat pumps for space heating in northern China. As part of a baseline assessment of the program, this study investigated variability in personal air pollution exposures within villages and between villages and evaluated exposure patterns by sociodemographic factors. We randomly recruited 446 participants in 50 villages in four districts in rural Beijing and measured 24 h personal exposures to fine particulate matter (PM_2.5) and black carbon (BC). The geometric mean personal exposure to PM_2.5 and BC was 72 and 2.5 μg/m³, respectively. The variability in PM_2.5 and BC exposures was greater within villages than between villages. Study participants who used traditional stoves as their dominant source of space heating were exposed to the highest levels of PM_2.5 and BC. Wealthier households tended to burn more coal for space heating, whereas less wealthy households used more biomass. PM_2.5 and BC exposures were almost uniformly distributed by socioeconomic status. Future work that combines these results with PM_2.5 chemical composition analysis will shed light on whether air pollution source contributors (e.g., industrial, traffic, and household solid fuel burning) follow similar distributions.

Reduced Black Carbon Concentrations following a Three-Year Stepped-Wedge Randomized Trial of the Wood-Burning Justa Cookstove in Rural Honduras

Introduction

Household air pollution from cooking-related biomass combustion remains a leading risk factor for global health. Black carbon (BC) is an important component of particulate matter (PM) in household air pollution. We evaluated the impact of the engineered, wood-burning Justa stove intervention on BC concentrations.

Methods

We conducted a 3-year stepped-wedge randomized controlled trial with 6 repeated visits among 230 female primary cooks in rural Honduras. Participants used traditional stoves at baseline and were randomized to receive the Justa after visit 2 or after visit 4. At each visit, we measured 24-hour gravimetric personal and kitchen fine PM (PM2.5) concentrations and estimated BC mass concentrations (Sootscan Transmissometer). We conducted intent-to-treat analyses using linear mixed models with natural log-transformed 24-hour personal and kitchen BC.

Results

BC concentrations were reduced for households assigned to the Justa vs. traditional stoves: e.g., personal BC geometric mean (GSD), 3.6 μg/m3 (6.4) vs. 11.5 μg/m3 (4.6), respectively. Following the intervention, we observed 53% (95% CI: 35-65%) lower geometric mean personal BC concentrations and 76% (95% CI: 66-83%) lower geometric mean kitchen BC concentrations.

Conclusions

The Justa stove intervention substantially reduced BC concentrations, mitigating household air pollution and potentially benefitting human and climate health.

Measuring and predicting personal and household Black Carbon levels from 88 communities in eight countries

Black Carbon (BC) is an important component of household air pollution (HAP) in low- and middle- income countries (LMICs), but levels and drivers of exposure are poorly understood. As part of the Prospective Urban and Rural Epidemiological (PURE) study, we analyzed 48-hour BC measurements for 1187 individual and 2242 household samples from 88 communities in 8 LMICs (Bangladesh, Chile, China, Colombia, India, Pakistan, Tanzania, and Zimbabwe). Light absorbance (10^-5 m^-1) of collected PM_2.5 filters, a proxy for BC concentrations, was calculated via an image-based reflectance method. Surveys of household/personal characteristics and behaviors were collected after monitoring. The geometric mean (GM) of personal and household BC measures was 2.4 (3.3) and 3.5 (3.9)·10^-5 m^-1, respectively. The correlation between BC and PM_2.5 was r = 0.76 for personal and r = 0.82 for household measures. A gradient of increasing BC concentrations was observed for cooking fuels: BC increased 53% (95%CI: 30, 79) for coal, 142% (95%CI: 117, 169) for wood, and 190% (95%CI: 149, 238) for other biomass, compared to gas. Each hour of cooking was associated with an increase in household (5%, 95%CI: 3, 7) and personal (5%, 95%CI: 2, 8) BC; having a window in the kitchen was associated with a decrease in household (-38%, 95%CI: -45, -30) and personal (-31%, 95%CI: -44, -15) BC; and cooking on a mud stove, compared to a clean stove, was associated with an increase in household (125%, 95%CI: 96, 160) and personal (117%, 95%CI: 71, 117) BC. Male participants only had slightly lower personal BC (-0.6%, 95%CI: -1, 0.0) compared to females. In multivariate models, we were able to explain 46-60% of household BC variation and 33-54% of personal BC variation. These data and models provide new information on exposure to BC in LMICs, which can be incorporated into future exposure assessments, health research, and policy surrounding HAP and BC.

Assessing the External Exposome Using Wearable Passive Samplers and High-Resolution Mass Spectrometry among South African Children Participating in the VHEMBE Study

Children in low- and middle-income countries are often exposed to higher levels of chemicals and are more vulnerable to the health effects of air pollution. Little is known about the diversity, toxicity, and dynamics of airborne chemical exposures at the molecular level. We developed a workflow employing state-of-the-art wearable passive sampling technology coupled with high-resolution mass spectrometry to comprehensively measure 147 children's personal exposures to airborne chemicals in Limpopo, South Africa, as part of the Venda Health Examination of Mothers, Babies, and Their Environment (VHEMBE). 637 environmental exposures were detected, many of which have never been measured in this population; of these 50 airborne chemical exposures of concern were detected, including pesticides, plasticizers, organophosphates, dyes, combustion products, and perfumes. Biocides detected in wristbands included p,p'-dichlorodiphenyltrichloroethane (p,p'-DDT), p,p'-dichlorodiphenyldichloroethane (p,p'-DDD), p,p'-dichlorodiphenyldichloroethylene (p,p'-DDE), propoxur, piperonyl butoxide, and triclosan. Exposures differed across the assessment period with 27% of detected chemicals observed to be either higher or lower in the wet or dry seasons.

Digital Healthcare for Airway Diseases from Personal Environmental Exposure

Digital technologies have emerged in various dimensions of human life, ranging from education to professional services to well-being. In particular, health products and services have expanded by the use and development of artificial intelligence, mobile health applications, and wearable electronic devices. Such advancements have enabled accurate and updated tracking and modeling of health conditions. For instance, digital health technologies are capable of measuring environmental pollution and predicting its adverse health effects. Several health conditions, including chronic airway diseases such as asthma and chronic obstructive pulmonary disease, can be exacerbated by pollution. These diseases impose substantial health burdens with high morbidity and mortality. Recently, efforts have been made to develop digital technologies to alleviate such conditions. Moreover, the COVID-19 pandemic has facilitated the application of telemedicine and telemonitoring for patients with chronic airway diseases. This article reviews current trends and studies in digital technology utilization for investigating and managing environmental exposure and chronic airway diseases. First, we discussed the recent progression of digital technologies in general environmental healthcare. Then, we summarized the capacity of digital technologies in predicting exacerbation and self-management of airway diseases. Concluding these reviews, we provided suggestions to improve digital health technologies' abilities to reduce the adverse effects of environmental exposure in chronic airway diseases, based on personal exposure-response modeling.

LPG stove and fuel intervention among pregnant women reduce fine particle air pollution exposures in three countries: Pilot results from the HAPIN trial

The Household Air Pollution Intervention Network trial is a multi-country study on the effects of a liquefied petroleum gas (LPG) stove and fuel distribution intervention on women's and children's health. There is limited data on exposure reductions achieved by switching from solid to clean cooking fuels in rural settings across multiple countries. As formative research in 2017, we recruited pregnant women and characterized the impact of the intervention on personal exposures and kitchen levels of fine particulate matter (PM2.5) in Guatemala, India, and Rwanda. Forty pregnant women were enrolled in each site. We measured cooking area concentrations of and personal exposures to PM2.5 for 24 or 48 h using gravimetric-based PM2.5 samplers at baseline and two follow-ups over two months after delivery of an LPG cookstove and free fuel supply. Mixed models were used to estimate PM2.5 reductions. Median kitchen PM2.5 concentrations were 296 μg/m3 at baseline (interquartile range, IQR: 158-507), 24 μg/m3 at first follow-up (IQR: 18-37), and 23 μg/m3 at second follow-up (IQR: 14-37). Median personal exposures to PM2.5 were 134 μg/m3 at baseline (IQR: 71-224), 35 μg/m3 at first follow-up (IQR: 23-51), and 32 μg/m3 at second follow-up (IQR: 23-47). Overall, the LPG intervention was associated with a 92% (95% confidence interval (CI): 90-94%) reduction in kitchen PM2.5 concentrations and a 74% (95% CI: 70-79%) reduction in personal PM2.5 exposures. Results were similar for each site. CONCLUSIONS: The intervention was associated with substantial reductions in kitchen and personal PM2.5 overall and in all sites. Results suggest LPG interventions in these rural settings may lower exposures to the WHO annual interim target-1 of 35 μg/m3. The range of exposure contrasts falls on steep sections of estimated exposure-response curves for birthweight, blood pressure, and acute lower respiratory infections, implying potentially important health benefits when transitioning from solid fuels to LPG.

Design and Testing of a Low-Cost Sensor and Sampling Platform for Indoor Air Quality

Americans spend most of their time indoors at home, but comprehensive characterization of in-home air pollution is limited by the cost and size of reference-quality monitors. We assembled small "Home Health Boxes" (HHBs) to measure indoor PM2.5, PM10, CO2, CO, NO2, and O3 concentrations using filter samplers and low-cost sensors. Nine HHBs were collocated with reference monitors in the kitchen of an occupied home in Fort Collins, Colorado, USA for 168 h while wildfire smoke impacted local air quality. When HHB data were interpreted using gas sensor manufacturers' calibrations, HHBs and reference monitors (a) categorized the level of each gaseous pollutant similarly (as either low, elevated, or high relative to air quality standards) and (b) both indicated that gas cooking burners were the dominant source of CO and NO2 pollution; however, HHB and reference O3 data were not correlated. When HHB gas sensor data were interpreted using linear mixed calibration models derived via collocation with reference monitors, root-mean-square error decreased for CO2 (from 408 to 58 ppm), CO (645 to 572 ppb), NO2 (22 to 14 ppb), and O3 (21 to 7 ppb); additionally, correlation between HHB and reference O3 data improved (Pearson's r increased from 0.02 to 0.75). Mean 168-h PM2.5 and PM10 concentrations derived from nine filter samples were 19.4 μg m-3 (6.1% relative standard deviation [RSD]) and 40.1 μg m-3 (7.6% RSD). The 168-h PM2.5 concentration was overestimated by PMS5003 sensors (median sensor/filter ratio = 1.7) and underestimated slightly by SPS30 sensors (median sensor/filter ratio = 0.91).

Miniaturizing Wet Scrubbers for Aerosolized Droplet Capture

Aerosols dispersed and transmitted through the air (e.g., particulate matter pollution and bioaerosols) are ubiquitous and one of the leading causes of adverse health effects and disease transmission. A variety of sampling methods (e.g., filters, cyclones, and impactors) have been developed to assess personal exposures. However, a gap still remains in the accessibility and ease-of-use of these technologies for people without experience or training in collecting airborne samples. Additionally, wet scrubbers (large non-portable industrial systems) utilize liquid sprays to remove aerosols from the air; the goal is to "scrub" (i.e., clean) the exhaust of industrial smokestacks, not collect the aerosols for analysis. Inspired by wet scrubbers, we developed a device fundamentally different from existing portable air samplers by using aerosolized microdroplets to capture aerosols in personal spaces (e.g., homes, offices, and schools). Our aerosol-sampling device is the size of a small teapot, can be operated without specialized training, and features a winding flow path in a supersaturated relative humidity environment, enabling droplet growth. The integrated open mesofluidic channels shuttle coalesced droplets to a collection chamber for subsequent sample analysis. Here, we present the experimental demonstration of aerosol capture in water droplets. An iterative study optimized the non-linear flow manipulating baffles and enabled an 83% retention of the aerosolized microdroplets in the confined volume of our device. As a proof-of-concept for aerosol capture into a liquid medium, 0.5-3 μm model particles were used to evaluate aerosol capture efficiency. Finally, we demonstrate that the device can capture and keep a bioaerosol (bacteriophage MS2) viable for downstream analysis.

Indoor Air Pollution and Susceptibility to Tuberculosis Infection in Urban Vietnamese Children

RATIONALE

The Southeast Asian tuberculosis burden is high, and it remains unclear if urban indoor air pollution in this setting is exacerbating the epidemic.

OBJECTIVES

To determine the associations of latent tuberculosis with common urban indoor air pollution sources (secondhand smoke, indoor motorcycle emissions, and cooking) in Southeast Asia.

METHODS

We enrolled child household contacts of patients with microbiologically confirmed active tuberculosis in Vietnam, July 2017-December 2019. We tested children for latent tuberculosis and evaluated air pollution exposures with questionnaires and personal aerosol sampling. We tested hypotheses using generalized estimating equations.

MEASUREMENTS AND MAIN RESULTS

We enrolled 72 tuberculosis patients (27% with cavitary disease) and 109 of their child household contacts. Of household contacts, 58 (53%) were diagnosed with latent tuberculosis at baseline visit. Children experienced a 2.56-fold increased odds of latent tuberculosis for each additional household member who smoked (95%CI 1.27-5.16). Odds were highest among children exposed to indoor smokers and children under five years old exposed to household smokers. Each residential floor above street-level pollution decreased the odds of latent tuberculosis by 36% (aOR 0.64, 95%CI 0.42-0.96). Motorcycles parked inside children's homes and cooking with liquid petroleum gas compared to electricity increased the odds of latent tuberculosis while kitchen ventilation decreased the effect, but these findings were not statistically significant.

CONCLUSION

Common urban indoor air pollution sources were associated with increased odds of latent tuberculosis infection in child household contacts of active tuberculosis patients.

The Exposome in the Era of the Quantified Self

Human health is regulated by complex interactions among the genome, the microbiome, and the environment. While extensive research has been conducted on the human genome and microbiome, little is known about the human exposome. The exposome comprises the totality of chemical, biological, and physical exposures that individuals encounter over their lifetimes. Traditional environmental and biological monitoring only targets specific substances, whereas exposomic approaches identify and quantify thousands of substances simultaneously using nontargeted high-throughput and high-resolution analyses. The quantified self (QS) aims at enhancing our understanding of human health and disease through self-tracking. QS measurements are critical in exposome research, as external exposures impact an individual's health, behavior, and biology. This review discusses both the achievements and the shortcomings of current research and methodologies on the QS and the exposome and proposes future research directions.

Environmental Particulate Matter (PM) Exposure Assessment of Construction Activities Using Low-Cost PM Sensor and Latin Hypercubic Technique

Dust generation is generally considered a natural process in construction sites; ergo, workers are exposed to health issues due to fine dust exposure during construction work. The primary activities in the execution of construction work, such as indoor concrete and mortar mixing, are investigated to interrogate and understand the critical high particulate matter concentrations and thus health threats. Two low-cost dust sensors (Sharp GP2Y1014AU0F and Alphasense OPC N2) without implementing control measures to explicitly evaluate, compare and gauge them for these construction activities were utilized. The mean exposures to PM10, PM2.5 and PM1 during both activities were 3522.62, 236.46 and 47.62 µg/m3 and 6762.72, 471.30 and 59.09 µg/m3, respectively. The results show that PM10 and PM2.5 caused during the concrete mixing activity was approximately double compared to the mortar. The Latin Hypercube Sampling method is used to analyze the measurement results and to predict the exposure concentrations. The high dust emission and exposure from mixing activities fail to meet the World Health Organization and Health and Safety Commission standards for environmental exposure. These findings will leverage the integration of low-cost dust sensors with Building Information Modelling (BIM) to formulate a digital twin for automated dust control techniques in the construction site.

Wearable Devices for Environmental Monitoring in the Built Environment: A Systematic Review

The so-called Internet of Things (IoT), which is rapidly increasing the number of network-connected and interconnected objects, could have a far-reaching impact in identifying the link between human health, well-being, and environmental concerns. In line with the IoT concept, many commercial wearables have been introduced in recent years, which differ from the usual devices in that they use the term "smart" alongside the terms "watches", "glasses", and "jewellery". Commercially available wearables aim to enhance smartphone functionality by enabling payment for commercial items or monitoring physical activity. However, what is the trend of scientific production about the concept of wearables regarding environmental monitoring issues? What are the main areas of interest covered by scientific production? What are the main findings and limitations of the developed solution in this field? The methodology used to answer the above questions is based on a systematic review. The data were acquired following a reproducible methodology. The main result is that, among the thermal, visual, acoustic, and air quality environmental factors, the last one is the most considered when using wearables even though in combination with some others. Another relevant finding is that of the acquired studies; in only one, the authors shared their wearables as an open-source device, and it will probably be necessary to encourage researchers to consider open-source as a means to promote scalability and proliferation of new wearables customized to cover different domains.

Spatial-temporal patterns of ambient fine particulate matter (PM2.5) and black carbon (BC) pollution in Accra

Sub-Saharan Africa (SSA) is rapidly urbanizing, and ambient air pollution has emerged as a major environmental health concern in growing cities. Yet, effective air quality management is hindered by limited data. We deployed robust, low-cost and low-power devices in a large-scale measurement campaign and characterized within-city variations in fine particulate matter (PM2.5) and black carbon (BC) pollution in Accra, Ghana. Between April 2019 and June 2020, we measured weekly gravimetric (filter-based) and minute-by-minute PM2.5 concentrations at 146 unique locations, comprising of 10 fixed (∼1 year) and 136 rotating (7 day) sites covering a range of land-use and source influences. Filters were weighed for mass, and light absorbance (10-5m-1) of the filters was used as proxy for BC concentration. Year-long data at four fixed sites that were monitored in a previous study (2006-2007) were compared to assess changes in PM2.5 concentrations. The mean annual PM2.5 across the fixed sites ranged from 26 μg m-3 at a peri-urban site to 43 μg m-3 at a commercial, business, and industrial (CBI) site. CBI areas had the highest PM2.5 levels (mean: 37 μg m-3), followed by high-density residential neighborhoods (mean: 36 μg m-3), while peri-urban areas recorded the lowest (mean: 26 μg m-3). Both PM2.5 and BC levels were highest during the dry dusty Harmattan period (mean PM2.5: 89 μg m-3) compared to non-Harmattan season (mean PM2.5: 23 μg m-3). PM2.5 at all sites peaked at dawn and dusk, coinciding with morning and evening heavy traffic. We found about a 50% reduction (71 vs 37 μg m-3) in mean annual PM2.5 concentrations when compared to measurements in 2006-2007 in Accra. Ambient PM2.5 concentrations in Accra may have plateaued at levels lower than those seen in large Asian megacities. However, levels are still 2- to 4-fold higher than the WHO guideline. Effective and equitable policies are needed to reduce pollution levels and protect public health.

Assessing the Impact of Wildfires on the Use of Black Carbon as an Indicator of Traffic Exposures in Environmental Epidemiology Studies

Epidemiological studies frequently use black carbon (BC) as a proxy for traffic-related air pollution (TRAP). However, wildfire smoke (WFS) represents an important source of BC not often considered when using BC as a proxy for TRAP. Here, we examined the potential for WFS to bias TRAP exposure assessments based on BC measurements. Weekly integrated BC samples were collected across the Denver, CO region from May to November 2018. We collected 609 filters during our sampling campaigns, 35% of which were WFS-impacted. For each filter we calculated an average BC concentration. We assessed three GIS-based indicators of TRAP for each sampling location: annual average daily traffic within a 300 m buffer, the minimum distance to a highway, and the sum of the lengths of roadways within 300 m. Median BC concentrations were 9% higher for WFS-impacted filters (median = 1.14 μg/m3, IQR = 0.23 μg/m3) than nonimpacted filters (median = 1.04 μg/m3, IQR = 0.48 μg/m3). During WFS events, BC concentrations were elevated and expected spatial gradients in BC were reduced. We conducted a simulation study to estimate TRAP exposure misclassification as the result of regional WFS. Our results suggest that linear health effect estimates were biased away from the null when WFS was present. Thus, exposure assessments relying on BC as a proxy for TRAP may be biased by wildfire events. Alternative metrics that account for the influence of "brown" carbon associated with biomass burning may better isolate the effects of traffic emissions from those of other black carbon sources.

Impact of the wood-burning Justa cookstove on fine particulate matter exposure: A stepped-wedge randomized trial in rural Honduras

TRIAL DESIGN

We evaluated the impact of a biomass stove intervention on fine particulate matter (PM2.5) concentrations using an individual-level, stepped-wedge randomized trial.

METHODS

We enrolled 230 women in rural Honduran households using traditional biomass stoves and randomly allocated them to one of two study arms. The Justa stove, the study intervention, was locally-sourced, wood-burning, and included an engineered combustion chamber and chimney. At each of 6 visits over 3 years, we measured 24-hour gravimetric personal and kitchen PM2.5 concentrations. Half of the households received the intervention after Visit 2 and half after Visit 4. We conducted intent-to-treat analyses to evaluate the intervention effect using linear mixed models with log-transformed kitchen or personal PM2.5 (separately) as the dependent variable, adjusting for time. We also compared PM2.5 concentrations to World Health Organization (WHO) guidelines.

RESULTS

Arms 1 and 2 each had 115 participants with 664 and 632 completed visits, respectively. Median 24-hour average personal PM2.5 exposures were 81 μg/m3 (25th-75th percentile: 50-141 μg/m3) for the traditional stove condition (n=622) and 43 μg/m3 (25th-75th percentile: 27-73 μg/m3) for the Justa stove condition (n=585). Median 24-hour average kitchen concentrations were 178 μg/m3 (25th-75th percentile: 69-440 μg/m3; n=629) and 53 μg/m3 (25th-75th percentile: 29-103 μg/m3; n=578) for the traditional and Justa stove conditions, respectively. The Justa intervention resulted in a 32% reduction in geometric mean personal PM2.5 (95% confidence interval [CI]: 20-43%) and a 56% reduction (95% CI: 46-65%) in geometric mean kitchen PM2.5. During rainy and dry seasons, 53% and 41% of participants with the Justa intervention had 24-hour average personal PM2.5 exposures below the WHO interim target-3 guideline (37.5 μg/m3), respectively.

CONCLUSION

The Justa stove intervention substantially lowered personal and kitchen PM2.5 and may be a provisional solution that is feasible for Latin American communities where cleaner fuels may not be available, affordable, or acceptable for some time. Clinicaltrials.gov: NCT02658383.

A Narrative Review of Occupational Air Pollution and Respiratory Health in Farmworkers

The agricultural crop sector in the United States depends on migrant, seasonal, and immigrant farmworkers. As an ethnic minority group in the U.S. with little access to health care and a high level of poverty, farmworkers face a combination of adverse living and workplace conditions, such as exposure to high levels of air pollution, that can place them at a higher risk for adverse health outcomes including respiratory infections. This narrative review summarizes peer-reviewed original epidemiology research articles (2000-2020) focused on respirable dust exposures in the workplace and respiratory illnesses among farmworkers. We found studies (n = 12) that assessed both air pollution and respiratory illnesses in farmworkers. Results showed that various air pollutants and respiratory illnesses have been assessed using appropriate methods (e.g., personal filter samplers and spirometry) and a consistent pattern of increased respiratory illness in relation to agricultural dust exposure. There were several gaps in the literature; most notably, no study coupled occupational air exposure and respiratory infection among migrant, seasonal and immigrant farmworkers in the United States. This review provides an important update to the literature regarding recent epidemiological findings on the links between occupational air pollution exposures and respiratory health among vulnerable farmworker populations.

Wearable Devices in Health Monitoring from the Environmental towards Multiple Domains: A Survey

The World Health Organization (WHO) recognizes the environmental, behavioral, physiological, and psychological domains that impact adversely human health, well-being, and quality of life (QoL) in general. The environmental domain has significant interaction with the others. With respect to proactive and personalized medicine and the Internet of medical things (IoMT), wearables are most important for continuous health monitoring. In this work, we analyze wearables in healthcare from a perspective of innovation by categorizing them according to the four domains. Furthermore, we consider the mode of wearability, costs, and prolonged monitoring. We identify features and investigate the wearable devices in the terms of sampling rate, resolution, data usage (propagation), and data transmission. We also investigate applications of wearable devices. Web of Science, Scopus, PubMed, IEEE Xplore, and ACM Library delivered wearables that we require to monitor at least one environmental parameter, e.g., a pollutant. According to the number of domains, from which the wearables record data, we identify groups: G1, environmental parameters only; G2, environmental and behavioral parameters; G3, environmental, behavioral, and physiological parameters; and G4 parameters from all domains. In total, we included 53 devices of which 35, 9, 9, and 0 belong to G1, G2, G3, and G4, respectively. Furthermore, 32, 11, 7, and 5 wearables are applied in general health and well-being monitoring, specific diagnostics, disease management, and non-medical. We further propose customized and quantified output for future wearables from both, the perspectives of users, as well as physicians. Our study shows a shift of wearable devices towards disease management and particular applications. It also indicates the significant role of wearables in proactive healthcare, having capability of creating big data and linking to external healthcare systems for real-time monitoring and care delivery at the point of perception.

Field Evaluation of the Ultrasonic Personal Aerosol Sampler (UPAS) for Respirable Dust Exposure in a Taconite Mine

Exposure to respirable dust (RD; the mass fraction of inhaled particles that penetrate to the unciliated airways) is a major health concern in a variety of workplaces. While the estimation of personal exposure is an essential step in protecting worker health from aerosol hazards, the traditional method for assessing personal exposure to RD, suggested by the National Institute for Occupational Safety and Health (NIOSH method 0600), requires equipment that is heavy, bulky, noisy, and has the need of frequent calibration. The ultrasonic personal aerosol sampler (UPAS) is a new personal sampling technology designed to address some of these drawbacks associated with traditional sampling methods. In this study, we field tested and evaluated the performance of the UPAS for assessing worker exposure to RD in a taconite mine. Mineworkers (n = 39) from various job categories were recruited to wear both UPAS and NIOSH 0600 samplers on a work vest to estimate time-weighted exposure to RD. A strong linear relationship was observed (NIOSH method 0600 = 1.06 (UPAS) -9.22 µg m-3, r2 of 0.72, and Pearson correlation coefficient of 0.854). None of the workers were exposed to a RD concentration above the Occupational Safety and Health Administration permissible exposure limit (5 mg m-3). A Bland-Altman analysis revealed that 72% of the valid UPAS samples agreed within ±25% of the traditional method mean. The impact of job category on the correlation of the methods was not statistically significant. This work suggests that the UPAS may present a viable alternative for assessing personal exposure to RD in the workplace.

A Spatiotemporal Prediction Model for Black Carbon in the Denver Metropolitan Area, 2009-2020

Studies on health effects of air pollution from local sources require exposure assessments that capture spatial and temporal trends. To facilitate intraurban studies in Denver, Colorado, we developed a spatiotemporal prediction model for black carbon (BC). To inform our model, we collected more than 700 weekly BC samples using personal air samplers from 2018 to 2020. The model incorporated spatial and spatiotemporal predictors and smoothed time trends to generate point-level weekly predictions of BC concentrations for the years 2009-2020. Our results indicate that our model reliably predicted weekly BC concentrations across the region during the year in which we collected data. We achieved a 10-fold cross-validation R² of 0.83 and a root-mean-square error of 0.15 μg/m³ for weekly BC concentrations predicted at our sampling locations. Predicted concentrations displayed expected temporal trends, with the highest concentrations predicted during winter months. Thus, our prediction model improves on typical land use regression models that generally only capture spatial gradients. However, our model is limited by a lack of long-term BC monitoring data for full validation of historical predictions. BC predictions from the weekly spatiotemporal model will be used in traffic-related air pollution exposure-disease associations more precisely than previous models for the region have allowed.

Quantitative Protection Factors for Common Masks and Face Coverings

The performance of masks, whether intended to protect the community from exhaled infectious aerosol or to protect the wearer from inhaled infectious aerosol, depends on factors such as filtration efficiency, particle size distribution, leakage, and ventilation rate. These factors depend on the activities and facial features of the mask wearer so that the mask performance for real-world applications is difficult to predict. The present work shows how protection factor, a quantity often used to describe mask performance, can be estimated without involving human volunteers. By constraining these factors to known values, mask protection factors can be compared fairly and efficiently following a series of filtration efficiency measurements performed in the laboratory. Protection factors and mask emissions for exhalation and inhalation were evaluated for masks of seven types currently in use around the world and for a hypothetical mask with 99% efficiency on all particles. The performance of reusable masks made from cotton fabric was limited by the size of the native cotton fibers. Masks that utilized finer fibers, particularly electret fibers with relatively small diameters, showed excellent performance with moderate flow resistance. Results from this work, in addition to simple guidance for mask fit and usage, can facilitate risk communication and decision-making efforts during the COVID-19 pandemic.

Decoding personal biotic and abiotic airborne exposome

The complexity and dynamics of human diseases are driven by the interactions between internal molecular activities and external environmental exposures. Although advances in omics technology have dramatically broadened the understanding of internal molecular and cellular mechanisms, understanding of the external environmental exposures, especially at the personal level, is still rudimentary in comparison. This is largely owing to our limited ability to efficiently collect the personal environmental exposome (PEE) and extract the nucleic acids and chemicals from PEE. Here we describe a protocol that integrates hardware and experimental pipelines to collect and decode biotic and abiotic external exposome at the individual level. The described protocol has several advantages over conventional approaches, such as exposome monitoring at the personal level, decontamination steps to increase sensitivity and simultaneous capture and high-throughput profiling of biotic and abiotic exposures. The protocol takes ~18 h of bench time over 2-3 d to prepare samples for high-throughput profiling and up to a couple of weeks of instrumental time to analyze, depending on the number of samples. Hundreds to thousands of species and organic compounds could be detected in the airborne particulate samples using this protocol. The composition and complexity of the biotic and abiotic substances are heavily influenced by the sampling spatiotemporal factors. Basic skillsets in molecular biology and analytical chemistry are required to carry out this protocol. This protocol could be modified to decode biotic and abiotic substances in other types of low or ultra-low input samples.

Exposure contrasts associated with a liquefied petroleum gas (LPG) intervention at potential field sites for the multi-country household air pollution intervention network (HAPIN) trial in India: results from pilot phase activities in rural Tamil Nadu

BACKGROUND

The Household Air Pollution Intervention Network (HAPIN) trial aims to assess health benefits of a liquefied petroleum gas (LPG) cookfuel and stove intervention among women and children across four low- and middle-income countries (LMICs). We measured exposure contrasts for women, achievable under alternative conditions of biomass or LPG cookfuel use, at potential HAPIN field sites in India, to aid in site selection for the main trial.

METHODS

We recruited participants from potential field sites within Villupuram and Nagapattinam districts in Tamil Nadu, India, that were identified during a feasibility assessment. We performed. (i) cross-sectional measurements on women (N = 79) using either biomass or LPG as their primary cookfuel and (ii) before-and-after measurements on pregnant women (N = 41), once at baseline while using biomass fuel and twice - at 1 and 2 months - after installation of an LPG stove and free fuel intervention. We involved participants to co-design clothing and instrument stands for personal and area sampling. We measured 24 or 48-h personal exposures and kitchen and ambient concentrations of fine particulate matter (PM2.5) using gravimetric samplers.

RESULTS

In the cross-sectional analysis, median (interquartile range, IQR) kitchen PM2.5 concentrations in biomass and LPG using homes were 134 μg/m3 [IQR:71-258] and 27 μg/m3 [IQR:20-47], while corresponding personal exposures were 75 μg/m3 [IQR:55-104] and 36 μg/m3 [IQR:26-46], respectively. In before-and-after analysis, median 48-h personal exposures for pregnant women were 72 μg/m3 [IQR:49-127] at baseline and 25 μg/m3 [IQR:18-35] after the LPG intervention, with a sustained reduction of 93% in mean kitchen PM2.5 concentrations and 78% in mean personal PM2.5 exposures over the 2 month intervention period. Median ambient concentrations were 23 μg/m3 [IQR:19-27). Participant feedback was critical in designing clothing and instrument stands that ensured high compliance.

CONCLUSIONS

An LPG stove and fuel intervention in the candidate HAPIN trial field sites in India was deemed suitable for achieving health-relevant exposure reductions. Ambient concentrations indicated limited contributions from other sources. Study results provide critical inputs for the HAPIN trial site selection in India, while also contributing new information on HAP exposures in relation to LPG interventions and among pregnant women in LMICs.

TRIAL REGISTRATION

ClinicalTrials.Gov. NCT02944682 ; Prospectively registered on October 17, 2016.

Dynamic classification of personal microenvironments using a suite of wearable, low-cost sensors

Human exposure to air pollution is associated with increased risk of morbidity and mortality. However, personal air pollution exposures can vary substantially depending on an individual's daily activity patterns and air quality within their residence and workplace. This work developed and validated an adaptive buffer size (ABS) algorithm capable of dynamically classifying an individual's time spent in predefined microenvironments using data from global positioning systems (GPS), motion sensors, temperature sensors, and light sensors. Twenty-two participants in Fort Collins, CO were recruited to carry a personal air sampler for a 48-h period. The personal sampler was retrofitted with a GPS and a pushbutton to complement the existing sensor measurements (temperature, motion, light). The pushbutton was used in conjunction with a traditional time-activity diary to note when the participant was located at "home", "work", or within an "other" microenvironment. The ABS algorithm predicted the amount of time spent in each microenvironment with a median accuracy of 99.1%, 98.9%, and 97.5% for the "home", "work", and "other" microenvironments. The ability to classify microenvironments dynamically in real time can enable the development of new sampling and measurement technologies that classify personal exposure by microenvironment.

Measuring Environmental Exposure to Enteric Pathogens in Low-Income Settings: Review and Recommendations of an Interdisciplinary Working Group

Infections with enteric pathogens impose a heavy disease burden, especially among young children in low-income countries. Recent findings from randomized controlled trials of water, sanitation, and hygiene interventions have raised questions about current methods for assessing environmental exposure to enteric pathogens. Approaches for estimating sources and doses of exposure suffer from a number of shortcomings, including reliance on imperfect indicators of fecal contamination instead of actual pathogens and estimating exposure indirectly from imprecise measurements of pathogens in the environment and human interaction therewith. These shortcomings limit the potential for effective surveillance of exposures, identification of important sources and modes of transmission, and evaluation of the effectiveness of interventions. In this review, we summarize current and emerging approaches used to characterize enteric pathogen hazards in different environmental media as well as human interaction with those media (external measures of exposure), and review methods that measure human infection with enteric pathogens as a proxy for past exposure (internal measures of exposure). We draw from lessons learned in other areas of environmental health to highlight how external and internal measures of exposure can be used to more comprehensively assess exposure. We conclude by recommending strategies for advancing enteric pathogen exposure assessments.

Household and personal air pollution exposure measurements from 120 communities in eight countries: results from the PURE-AIR study

BACKGROUND

Approximately 2·8 billion people are exposed to household air pollution from cooking with polluting fuels. Few monitoring studies have systematically measured health-damaging air pollutant (ie, fine particulate matter [PM2·5] and black carbon) concentrations from a wide range of cooking fuels across diverse populations. This multinational study aimed to assess the magnitude of kitchen concentrations and personal exposures to PM2·5 and black carbon in rural communities with a wide range of cooking environments.

METHODS

As part of the Prospective Urban and Rural Epidemiological (PURE) cohort, the PURE-AIR study was done in 120 rural communities in eight countries (Bangladesh, Chile, China, Colombia, India, Pakistan, Tanzania, and Zimbabwe). Data were collected from 2541 households and from 998 individuals (442 men and 556 women). Gravimetric (or filter-based) 48 h kitchen and personal PM2·5 measurements were collected. Light absorbance (10-5m-1) of the PM2·5 filters, a proxy for black carbon concentrations, was calculated via an image-based reflectance method. Surveys of household characteristics and cooking patterns were collected before and after the 48 h monitoring period.

FINDINGS

Monitoring of household air pollution for the PURE-AIR study was done from June, 2017, to September, 2019. A mean PM2·5 kitchen concentration gradient emerged across primary cooking fuels: gas (45 μg/m3 [95% CI 43-48]), electricity (53 μg/m3 [47-60]), coal (68 μg/m3 [61-77]), charcoal (92 μg/m3 [58-146]), agricultural or crop waste (106 μg/m3 [91-125]), wood (109 μg/m3 [102-118]), animal dung (224 μg/m3 [197-254]), and shrubs or grass (276 μg/m3 [223-342]). Among households cooking primarily with wood, average PM2·5 concentrations varied ten-fold (range: 40-380 μg/m3). Fuel stacking was prevalent (981 [39%] of 2541 households); using wood as a primary cooking fuel with clean secondary cooking fuels (eg, gas) was associated with 50% lower PM2·5 and black carbon concentrations than using only wood as a primary cooking fuel. Similar average PM2·5 personal exposures between women (67 μg/m3 [95% CI 62-72]) and men (62 [58-67]) were observed. Nearly equivalent average personal exposure to kitchen exposure ratios were observed for PM2·5 (0·79 [95% 0·71-0·88] for men and 0·82 [0·74-0·91] for women) and black carbon (0·64 [0·45-0·92] for men and 0·68 [0·46-1·02] for women).

INTERPRETATION

Using clean primary fuels substantially lowers kitchen PM2·5 concentrations. Importantly, average kitchen and personal PM2·5 measurements for all primary fuel types exceeded WHO's Interim Target-1 (35 μg/m3 annual average), highlighting the need for comprehensive pollution mitigation strategies.

FUNDING

Canadian Institutes for Health Research, National Institutes of Health.

Recent Advances in Occupational Exposure Assessment of Aerosols

Exposure science is underpinned by characterization (measurement) of exposures. In this article, six recent advances in exposure characterization by sampling and analysis are reviewed as tools in the occupational exposure assessment of aerosols. Three advances discussed in detail are (1) recognition and inclusion of sampler wall deposits; (2) development of a new sampling and analytical procedure for respirable crystalline silica that allows non-destructive field analysis at the end of the sampling period; and (3) development of a new sampler to collect the portion of sub-300 nm aerodynamic diameter particles that would deposit in human airways. Three additional developments are described briefly: (4) a size-selective aerosol sampler that allows the collection of multiple physiologically-relevant size fractions; (5) a miniaturized pump and versatile sampling head to meet multiple size-selective sampling criteria; and (6) a novel method of sampling bioaerosols including viruses while maintaining viability. These recent developments are placed in the context of the historical evolution in sampling and analytical developments from 1900 to the present day. While these are not the only advances in exposure characterization, or exposure assessment techniques, they provide an illustration of how technological advances are adding more tools to our toolkit. The review concludes with a number of recommended areas for future research, including expansion of real-time and end-of-shift on-site measurement, development of samplers that operate at higher flow-rates to ensure measurement at lowered limit values, and development of procedures that accurately distinguish aerosol and vapor phases of semi-volatile substances.

High-resolution spatiotemporal measurement of air and environmental noise pollution in Sub-Saharan African cities: Pathways to Equitable Health Cities Study protocol for Accra, Ghana

INTRODUCTION

Air and noise pollution are emerging environmental health hazards in African cities, with potentially complex spatial and temporal patterns. Limited local data are a barrier to the formulation and evaluation of policies to reduce air and noise pollution.

METHODS AND ANALYSIS

We designed a year-long measurement campaign to characterise air and noise pollution and their sources at high-resolution within the Greater Accra Metropolitan Area (GAMA), Ghana. Our design uses a combination of fixed (year-long, n=10) and rotating (week-long, n =~130) sites, selected to represent a range of land uses and source influences (eg, background, road traffic, commercial, industrial and residential areas, and various neighbourhood socioeconomic classes). We will collect data on fine particulate matter (PM_2.5), nitrogen oxides (NO_x), weather variables, sound (noise level and audio) along with street-level time-lapse images. We deploy low-cost, low-power, lightweight monitoring devices that are robust, socially unobtrusive, and able to function in Sub-Saharan African (SSA) climate. We will use state-of-the-art methods, including spatial statistics, deep/machine learning, and processed-based emissions modelling, to capture highly resolved temporal and spatial variations in pollution levels across the GAMA and to identify their potential sources. This protocol can serve as a prototype for other SSA cities.

ETHICS AND DISSEMINATION

This environmental study was deemed exempt from full ethics review at Imperial College London and the University of Massachusetts Amherst; it was approved by the University of Ghana Ethics Committee (ECH 149/18-19). This protocol is designed to be implementable in SSA cities to map environmental pollution to inform urban planning decisions to reduce health harming exposures to air and noise pollution. It will be disseminated through local stakeholder engagement (public and private sectors), peer-reviewed publications, contribution to policy documents, media, and conference presentations.

Long-standing LPG subsidies, cooking fuel stacking, and personal exposure to air pollution in rural and peri-urban Ecuador

Ecuador presents a unique case study for evaluating personal air pollution exposure in a middle-income country where a clean cooking fuel has been available at low cost for several decades. We measured personal PM_2.5 exposure, stove use, and participant location during a 48-h monitoring period for 157 rural and peri-urban households in coastal and Andean Ecuador. While nearly all households owned a liquefied petroleum gas (LPG) stove and used it as their primary cooking fuel, one-quarter of households utilized firewood as a secondary fuel and 10% used induction stoves secondary to LPG. Stove use monitoring demonstrated clear within- and across-meal fuel stacking patterns. Firewood-owning participants had higher distributions of 48-h and 10-min PM_2.5 exposure as compared with primary LPG and induction stove users, and this effect became more pronounced with firewood use during monitoring.Accounting for within-subject clustering, contemporaneous firewood stove use was associated with 101 μg/m³ higher 10-min PM_2.5 exposure (95% CI: 94-108 μg/m³). LPG and induction cooking events were largely not associated with contemporaneous PM_2.5 exposure. Our results suggest that firewood use is associated with average and short-term personal air pollution exposure above the WHO interim-I guideline, even when LPG is the primary cooking fuel.

Developing a Low-Cost Passive Method for Long-Term Average Levels of Light-Absorbing Carbon Air Pollution in Polluted Indoor Environments

We propose a low-cost passive method for monitoring long-term average levels of light-absorbing carbon air pollution in polluted indoor environments. Building on prior work, the method here estimates the change in reflectance of a passively exposed surface through analysis of digital images. To determine reproducibility and limits of detection, we tested low-cost passive samplers with exposure to kerosene smoke in the laboratory and to environmental pollution in 20 indoor locations. Preliminary results suggest robust reproducibility (r = 0.99) and limits of detection appropriate for longer-term (~1-3 months) monitoring in households that use solid fuels. The results here suggest high precision; further testing involving "gold standard" measurements is needed to investigate accuracy.

Using Low-Cost Measurement Systems to Investigate Air Quality: A Case Study in Palapye, Botswana

Exposure to particulate air pollution is a major cause of mortality and morbidity worldwide. In developing countries, the combustion of solid fuels is widely used as a source of energy, and this process can produce exposure to harmful levels of particulate matter with diameters smaller than 2.5 microns (PM2.5). However, as countries develop, solid fuel may be replaced by centralized coal combustion, and vehicles burning diesel and gasoline may become common, changing the concentration and composition of PM2.5, which ultimately changes the population health effects. Therefore, there is a continuous need for in-situ monitoring of air pollution in developing nations, both to estimate human exposure and to monitor changes in air quality. In this study, we present measurements from a 5-week field experiment in Palapye, Botswana. We used a low-cost, highly portable instrument package to measure surface-based aerosol optical depth (AOD), real-time surface PM2.5 concentrations using a third-party optical sensor, and time-integrated PM2.5 concentration and composition by collecting PM2.5 onto Teflon filters. Furthermore, we employed other low-cost measurements of real-time black carbon and time-integrated ammonia to help interpret the observed PM2.5 composition and concentration information during the field experiment. We found that the average PM2.5 concentration (9.5 µg∙m−3) was below the World Health Organization (WHO) annual limit, and this concentration closely agrees with estimates from the Global Burden of Disease (GBD) report estimates for this region. Sulfate aerosol and carbonaceous aerosol, likely from coal combustion and biomass burning, respectively, were the main contributors to PM2.5 by mass (33% and 27% of total PM2.5 mass, respectively). While these observed concentrations were on average below WHO guidelines, we found that the measurement site experienced higher concentrations of aerosol during first half our measurement period (14.5 µg∙m−3), which is classified as “moderately unhealthy” according to the WHO standard.

Bayesian Nonparametric Monotone Regression

In many applications there is interest in estimating the relation between a predictor and an outcome when the relation is known to be monotone or otherwise constrained due to the physical processes involved. We consider one such application-inferring time-resolved aerosol concentration from a low-cost differential pressure sensor. The objective is to estimate a monotone function and make inference on the scaled first derivative of the function. We proposed Bayesian nonparametric monotone regression which uses a Bernstein polynomial basis to construct the regression function and puts a Dirichlet process prior on the regression coefficients. The base measure of the Dirichlet process is a finite mixture of a mass point at zero and a truncated normal. This construction imposes monotonicity while clustering the basis functions. Clustering the basis functions reduces the parameter space and allows the estimated regression function to be linear. With the proposed approach we can make closed-formed inference on the derivative of the estimated function including full quantification of uncertainty. In a simulation study the proposed method performs similar to other monotone regression approaches when the true function is wavy but performs better when the true function is linear. We apply the method to estimate time-resolved aerosol concentration with a newly-developed portable aerosol monitor. The R package bnmr is made available to implement the method.

Design and performance of UPAS inlets for respirable and thoracic mass sampling

The Ultrasonic Personal Aerosol Sampler (UPAS) is a small, lightweight, and quiet sampler that collects airborne particulate matter on a filter for gravimetric or compositional analysis. The objective of this work was to develop UPAS inlets with collection efficiencies that match criteria for respirable or thoracic mass sampling. The two-stage inlet for respirable mass described here utilizes an impaction stage and a cyclone, whereas the one-stage inlet for thoracic mass sampling utilizes a circular slot impactor. Inlet designs are based on particle collection theory used in conjunction with an optimization algorithm to predict initial inlet dimensions; these predictions were the starting points for experiments that finalized dimensions and operating conditions. Both the respirable mass inlet and the thoracic mass inlet described here are interchangeable with the UPAS, and both have efficiencies that match well with their respective standards. With either inlet, the collected sample should be within ±5% of what the standard specifies for aerosols with reasonably broad size distributions.

Comparison of next-generation portable pollution monitors to measure exposure to PM2.5 from household air pollution in Puno, Peru

Assessment of personal exposure to PM_2.5 is critical for understanding intervention effectiveness and exposure-response relationships in household air pollution studies. In this pilot study, we compared PM_2.5 concentrations obtained from two next-generation personal exposure monitors (the Enhanced Children MicroPEM or ECM; and the Ultrasonic Personal Air Sampler or UPAS) to those obtained with a traditional Triplex Cyclone and SKC Air Pump (a gravimetric cyclone/pump sampler). We co-located cyclone/pumps with an ECM and UPAS to obtain 24-hour kitchen concentrations and personal exposure measurements. We measured Spearmen correlations and evaluated agreement using the Bland-Altman method. We obtained 215 filters from 72 ECM and 71 UPAS co-locations. Overall, the ECM and the UPAS had similar correlation (ECM ρ = 0.91 vs UPAS ρ = 0.88) and agreement (ECM mean difference of 121.7 µg/m³ vs UPAS mean difference of 93.9 µg/m³ ) with overlapping confidence intervals when compared against the cyclone/pump. When adjusted for the limit of detection, agreement between the devices and the cyclone/pump was also similar for all samples (ECM mean difference of 68.8 µg/m³ vs UPAS mean difference of 65.4 µg/m³ ) and personal exposure samples (ECM mean difference of -3.8 µg/m³ vs UPAS mean difference of -12.9 µg/m³ ). Both the ECM and UPAS produced comparable measurements when compared against a cyclone/pump setup.

Can the South African Milestones for Reducing Exposure to Respirable Crystalline Silica and Silicosis be Achieved and Reliably Monitored?

Silicosis and other respirable crystalline silica-associated diseases, most notably tuberculosis, have long been substantial causes of morbidity and mortality in South Africa. For the mining and non-mining industries, silicosis elimination programmes have been developed with milestones regarding reduction of levels of exposure to respirable crystalline silica (RCS) and targets regarding the date of eradication. The present paper explores the feasibility of achieving these targets by investigating the evidence that levels of exposure and silicosis incidence rates have declined by an appraisal of the methods for data collection and reporting. In the mining industry the silicosis elimination programme is supported by the development and advocacy of leading practices to reduce the exposure. RCS exposure data are routinely collected according to a Code of Practice (CoP) and the results are reported to the Mine Health and Safety Inspectorate. As the CoP and the actual workplace practices have been demonstrated to have some flaws, there is some concern about the accuracy of the actual exposure data and the data interpretation. The annually reported levels of exposure suggest a decline, however, the actual levels of RCS as well as the number of exposed workers, were not reported over the last few years. With regard to the silicosis incidence rates, a steady decline of new cases is reported. However, there is a risk of under-diagnosis and- reporting especially in former miners. In the non-mining industries, a systematic baseline of RCS exposure levels and silicosis incidence is lacking. The reporting by industries on assigning of the workforce to exposure categories seems to be fragmented and incomplete. Consequently, any evidence of progress toward achieving the silicosis elimination target cannot be documented. Both the silicosis elimination target and the exposure milestone are aspirational but are unlikely to be achieved. Nevertheless, the formal mining industry may get close. Exposure control interventions, especially in the non-mining industries, should be developed and implemented and pragmatic methods need to be put in place to identify sources of new silicosis cases for targeted intervention.

Analysis of black carbon on filters by image-based reflectance

Black carbon (BC) is an important contributor to global particulate matter emissions. BC is associated with adverse health effects, and an important short-lived climate pollutant. Here, we describe a low cost method of analysis that utilizes images of PTFE filters taken with a digital camera to estimate BC content on filters. This method is compared with two existing optical methods for analyzing BC (Smokestain Reflectance and Hybrid Integrating Plate and Sphere System) as well as the standard chemical analysis method for determining elemental carbon (Thermal-Optical Reflectance). In comparisons of aerosol generated under controlled conditions (using an inverted diffusion flame burner to cover a range of mass loading and reflectance levels) (N=12) and in field samples collected from residential solid fuel combustion in China and India (N=50), the image-based method was found to correlate well (normalized RMSE <10% for all comparisons) with existing methods. A correlational analysis of field samples between the optical methods and Fourier-transform infrared spectroscopy indicated that the same functional groups were predominantly responsible for light attenuation in each optical method. This method offers reduced equipment cost, rapid analysis time, and is available at no cost, which may facilitate more measurement of BC where PM2.5 mass concentrations are already measured, especially in low income countries or other sampling efforts with limited resources.

Women exposure to household air pollution after an improved cookstove program in rural San Luis Potosi, Mexico

The state government of San Luis Potosí (SLP), Mexico implemented an improved cookstove (ICS) program in rural areas. As part of the comprehensive program evaluation, we compared fine particulate material (PM_2.5) concentrations in kitchens and patios in treated (TH), and non-treated households (NTH), and analyzed pollutant levels according to patterns of fuels and devices use reported by the women. A panel study was conducted in 728 households (357 TH and 371 NTH) in three regions of SLP including two sampling rounds in 2015-16. Data on exposure determinants, ICS conditions and cooking practices were collected. Daily PM_2.5 in kitchen and patio was measured in a subsample. The average treatment effect was estimated using the double difference method. We constructed a mixed linear model to estimate PM_2.5 levels for the entire study sample and obtained personal exposure according to time-activity logs. NTH had lower socioeconomic status compared to TH. The average daily PM_2.5 concentrations in NTH compared to TH were 155.2 and 92.6 μg/m³ for kitchen and 35.4 and 39.8 μg/m³ for patio, respectively. PM_2.5 levels showed significant regional differences but no significant treatment effect. In many cases, the ICS was added to previous open fire and LPG use (stacking). The household size, kitchen ventilation, relative humidity, temperature and the ratio of indoor/outdoor PM_2.5 concentration were significant predictors of kitchen PM_2.5 levels. The daily PM_2.5 personal exposure was significantly reduced using ICS in good conditions or LPG (57 μg/m³) compared to the traditional open fire (86 μg/m³). This study strengthens the evidence on the potential daily PM_2.5 exposure reduction for women using an ICS in good conditions or LPG, displacing the polluting open fire. Comprehensive strategies tailored to the sociocultural context of the communities are needed to implement clean energy programs that achieve adoption and sustained use of ICS or LPG.

Extensive evaluation and classification of low-cost dust sensors in laboratory using a newly developed test method

An extensive evaluation of low-cost dust sensors was performed using an exponentially decaying particle concentration. A total of 264 sensors including 27 sensors with light-emitting diodes (LEDs) and 237 sensors with laser lighting sources were tested. Those tested sensors were classified into 4 groups based on the deviation from the reference data obtained by a reference instrument. The response linearities of all the tested samples for PM1 , PM2.5 , and PM10 were in excellent agreement with the reference instrument, except a few samples. For the measurements of PM1 and PM2.5 , the lighting source, that is, LED or laser, did not show any significant difference in overall sensor performance. However, LED-based sensors did not perform well for PM10 measurements. The 32, 24, and 16% of all the tested sensors for PM1 , PM2.5 , and PM10 measurement, respectively, are in the category of Class 1 (reference instrument reading ± 20%) requirement. The performance of the low-cost dust sensors for PM10 measurement was relatively less satisfactory.

Design and evaluation of a portable PM2.5 monitor featuring a low-cost sensor in line with an active filter sampler

Fine particulate air pollution (PM2.5) is a health hazard with numerous indoor and outdoor sources. Versatile monitors are needed to characterize PM2.5 sources, concentrations, and exposures in a range of locations and applications. Whereas low-cost light-scattering PM sensors provide real-time measurements with limited accuracy, gravimetric samples provide more accurate, albeit time-integrated, measurements. When used together, low-cost sensor data can be corrected to gravimetric samples. Here we describe the development of a portable PM2.5 monitor that features a low-cost sensor in line with an active filter sampler. Laboratory tests were conducted to determine (1) the accuracy and precision of PM2.5 concentrations derived from the filter sample and (2) correction factors for the low-cost sensor response to ammonium sulfate, Arizona road dust, urban particulate matter, and match smoke. Filter samples collected at 0.25 and 1.0 L min-1 had mean biases of -10% and -4%, relative to a tapered element oscillating microbalance, and a relative standard deviation (RSD) that ranged from 1% to 17%. The low-cost sensor correction factor varied with the test aerosol, sample flow rate, and between individual monitors. Gravimetric correction reduced the bias and RSD of ∼1 hour average concentrations measured by low-cost sensors in three collocated monitors. A week-long field experiment was also conducted to investigate how the monitor could be used to learn about sources of residential air pollution. Field data were used to identify: (1) pollution events resulting from cooking and use of a wood furnace and (2) variations in the number of air changes per hour inside the residence.

Study protocol for a stepped-wedge randomized cookstove intervention in rural Honduras: household air pollution and cardiometabolic health

BACKGROUND

Growing evidence links household air pollution exposure from biomass-burning cookstoves to cardiometabolic disease risk. Few randomized controlled interventions of cookstoves (biomass or otherwise) have quantitatively characterized changes in exposure and indicators of cardiometabolic health, a growing and understudied burden in low- and middle-income countries (LMICs). Ideally, the solution is to transition households to clean cooking, such as with electric or liquefied petroleum gas stoves; however, those unable to afford or to access these options will continue to burn biomass for the foreseeable future. Wood-burning cookstove designs such as the Justa (incorporating an engineered combustion zone and chimney) have the potential to substantially reduce air pollution exposures. Previous cookstove intervention studies have been limited by stove types that did not substantially reduce exposures and/or by low cookstove adoption and sustained use, and few studies have incorporated community-engaged approaches to enhance the intervention.

METHODS/DESIGN

We conducted an individual-level, stepped-wedge randomized controlled trial with the Justa cookstove intervention in rural Honduras. We enrolled 230 female primary cooks who were not pregnant, non-smoking, aged 24-59 years old, and used traditional wood-burning cookstoves at baseline. A community advisory board guided survey development and communication with participants, including recruitment and retention strategies. Over a 3-year study period, participants completed 6 study visits approximately 6 months apart. Half of the women received the Justa after visit 2 and half after visit 4. At each visit, we measured 24-h gravimetric personal and kitchen fine particulate matter (PM2.5) concentrations, qualitative and quantitative cookstove use and adoption metrics, and indicators of cardiometabolic health. The primary health endpoints were blood pressure, C-reactive protein, and glycated hemoglobin. Overall study goals are to explore barriers and enablers of new cookstove adoption and sustained use, compare health endpoints by assigned cookstove type, and explore the exposure-response associations between PM2.5 and indicators of cardiometabolic health.

DISCUSSION

This trial, utilizing an economically feasible, community-vetted cookstove and evaluating endpoints relevant for the major causes of morbidity and mortality in LMICs, will provide critical information for household air pollution stakeholders globally.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier NCT02658383 , posted January 18, 2016, field work completed May 2018. Official title, "Community-Based Participatory Research: A Tool to Advance Cookstove Interventions." Principal Investigator Maggie L. Clark, Ph.D. Last update posted July 12, 2018.

Measuring personal exposure to fine particulate matter (PM2.5) among rural Honduran women: A field evaluation of the Ultrasonic Personal Aerosol Sampler (UPAS)

We measured 24-hour average personal exposure to fine particulate matter (PM_2.5) among rural Honduran women using a lightweight, gravimetric monitor - the Ultrasonic Personal Aerosol Sampler (UPAS). Performance of the UPAS was compared with a commonly used gravimetric pump, cyclone, and filter sampling system. We observed strong agreement and correlation (Spearman ρ = 0.91; PM_2.5 concentration range: 19-120 μg/m³) between 43 paired measures, supporting the use of the UPAS as a personal exposure monitor for household air pollution studies.

Personal Exposure to PM2.5 Black Carbon and Aerosol Oxidative Potential using an Automated Microenvironmental Aerosol Sampler (AMAS)

Traditional methods for measuring personal exposure to fine particulate matter (PM2.5) are cumbersome and lack spatiotemporal resolution; methods that are time-resolved are limited to a single species/component of PM. To address these limitations, we developed an automated microenvironmental aerosol sampler (AMAS), capable of resolving personal exposure by microenvironment. The AMAS is a wearable device that uses a GPS sensor algorithm in conjunction with a custom valve manifold to sample PM2.5 onto distinct filter channels to evaluate home, school, and other (e.g., outdoors, in transit, etc.) exposures. Pilot testing was conducted in Fresno, CA where 25 high-school participants ( n = 37 sampling events) wore an AMAS for 48-h periods in November 2016. Data from 20 (54%) of the 48-h samples collected by participants were deemed valid and the filters were analyzed for PM2.5 black carbon (BC) using light transmissometry and aerosol oxidative potential (OP) using the dithiothreitol (DTT) assay. The amount of inhaled PM2.5 was calculated for each microenvironment to evaluate the health risks associated with exposure. On average, the estimated amount of inhaled PM2.5 BC (μg day-1) and OP [(μM min-1) day-1] was greatest at home, owing to the proportion of time spent within that microenvironment. Validation of the AMAS demonstrated good relative precision (8.7% among collocated instruments) and a mean absolute error of 22% for BC and 33% for OP when compared to a traditional personal sampling instrument. This work demonstrates the feasibility of new technology designed to quantify personal exposure to PM2.5 species within distinct microenvironments.

Evaluation of micro-well collector for capture and analysis of aerosolized Bacillus subtilis spores

Bioaerosol sampling and identification are vital for the assessment and control of airborne pathogens, allergens, and toxins. In-situ analysis of chemical and biological particulate matter can significantly reduce the costs associated with sample preservation, transport, and analysis. The analysis of conventional filters is challenging, due to dilute samples in large collection regions. A low-cost cartridge for collection and analysis of aerosols is developed for use in epidemiological studies and personal exposure assessments. The cartridge collects aerosol samples in a micro-well which reduces particles losses due to the bounce and does not require any coating. The confined particle collection area (dwell~1.4 mm) allows reducing the elution volume for subsequent analysis. The performance of the cartridge is validated in laboratory studies using aerosolized bacterial spores (Bacillus subtilis). Colony forming unit analysis is used for bacterial spore enumeration. Cartridge collection efficiency is evaluated by comparison with the reference filters and found to be consistent with tested flow rates. Sample recovery for the pipette elution is ~80%. Due to the high density of the collected sample, the cartridge is compatible with in-situ spectroscopic analysis and sample elution into the 10-20 μl liquid volume providing a significant increase in sample concentration for subsequent analysis.

Characterizing exposure to household air pollution within the Prospective Urban Rural Epidemiology (PURE) study

BACKGROUND

Household air pollution (HAP) from combustion of solid fuels is an important contributor to disease burden in low- and middle-income countries (LIC, and MIC). However, current HAP disease burden estimates are based on integrated exposure response curves that are not currently informed by quantitative HAP studies in LIC and MIC. While there is adequate evidence supporting causal relationships between HAP and respiratory disease, large cohort studies specifically examining relationships between quantitative measures of HAP exposure with cardiovascular disease are lacking.

OBJECTIVE

We aim to improve upon exposure proxies based on fuel type, and to reduce exposure misclassification by quantitatively measuring exposure across varying cooking fuel types and conditions in diverse geographies and socioeconomic settings. We leverage technology advancements to estimate household and personal PM2.5 (particles below 2.5 μm in aerodynamic diameter) exposure within the large (N~250,000) multi-country (N~26) Prospective Urban and Rural Epidemiological (PURE) cohort study. Here, we detail the study protocol and the innovative methodologies being used to characterize HAP exposures, and their application in epidemiologic analyses.

METHODS/DESIGN

This study characterizes HAP PM2.5 exposures for participants in rural communities in ten PURE countries with >10% solid fuel use at baseline (Bangladesh, Brazil, Chile, China, Colombia, India, Pakistan, South Africa, Tanzania, and Zimbabwe). PM2.5 monitoring includes 48-h cooking area measurements in 4500 households and simultaneous personal monitoring of male and female pairs from 20% of the selected households. Repeat measurements occur in 20% of households to assess impacts of seasonality. Monitoring began in 2017, and will continue through 2019. The Ultrasonic Personal Aerosol Sampler (UPAS), a novel, robust, and inexpensive filter based monitor that is programmable through a dedicated mobile phone application is used for sampling. Pilot study field evaluation of cooking area measurements indicated high correlation between the UPAS and reference Harvard Impactors (r = 0.91; 95% CI: 0.84, 0.95; slope = 0.95). To facilitate tracking and to minimize contamination and analytical error, the samplers utilize barcoded filters and filter cartridges that are weighed pre- and post-sampling using a fully automated weighing system. Pump flow and pressure measurements, temperature and RH, GPS coordinates and semi-quantitative continuous particle mass concentrations based on filter differential pressure are uploaded to a central server automatically whenever the mobile phone is connected to the internet, with sampled data automatically screened for quality control parameters. A short survey is administered during the 48-h monitoring period. Post-weighed filters are further analyzed to estimate black carbon concentrations through a semi-automated, rapid, cost-effective image analysis approach. The measured PM2.5 data will then be combined with PURE survey information on household characteristics and behaviours collected at baseline and during follow-up to develop quantitative HAP models for PM2.5 exposures for all rural PURE participants (~50,000) and across different cooking fuel types within the 10 index countries. Both the measured (in the subset) and the modelled exposures will be used in separate longitudinal epidemiologic analyses to assess associations with cardiopulmonary mortality, and disease incidence.

DISCUSSION

The collected data and resulting characterization of cooking area and personal PM2.5 exposures in multiple rural communities from 10 countries will better inform exposure assessment as well as future epidemiologic analyses assessing the relationships between quantitative estimates of chronic HAP exposure with adult mortality and incident cardiovascular and respiratory disease. This will provide refined and more accurate exposure estimates in global CVD related exposure-response analyses.