Impact of randomly assigned "pay-as-you-go" liquefied petroleum gas prices on energy use for cooking: Experimental pilot evidence from rural Rwanda.

The disease burden related to air pollution from traditional solid-fuel cooking practices in low- and middle-income countries impacts millions of people globally. Although the use of liquefied petroleum gas (LPG) fuel for cooking can meaningfully reduce household air pollution concentrations, major barriers, including affordability and accessibility, have limited widespread adoption. Using a randomized controlled trial, our objective was to evaluate the association between the cost and use of LPG among 23 rural Rwandan households. We provided a 2-burner LPG stove with accessories and incorporated a "pay-as-you-go" (PAYG) LPG service model that included fuel delivery. PAYG services remove the large up-front cost of cylinder refills by integrating "smart meter" technology that allows participants to pay in incremental amounts, as needed. We assigned three randomized discounted prices for LPG to each household at ~4-week intervals over a 12-week period. We modeled the relationship between randomized PAYG LPG price and use (standardized to monthly periods), analyzing effect modification by relative household wealth. A 1000 Rwandan Franc (about 1 USD at the time of the study) increase in LPG price/kg was associated with a 4.1 kg/month decrease in use (95% confidence interval [CI]: -6.7, -1.6; n=69 observations). Wealth modified this association; we observed a 9.7 kg/month reduction (95% CI: -14.8, -4.5) among wealthier households and a 2.5 kg/month reduction (95% CI: -5.3, 0.3) among lower-wealth households (p-interaction=0.01). The difference in price sensitivity was driven by higher LPG use among wealthier households at more heavily discounted prices; from an 80% to 10% discount, wealthy households used 17.5 to 5.3 kg/month and less wealthy households used 6.2 to 3.1 kg/month. Our pilot-level experimental evidence of PAYG LPG in a rural low-resource setting suggests that further exploration of subsidized pricing varied by household wealth is needed to ensure future policy initiatives can achieve targets without exacerbating inequities.

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.

Large Particle Emissions from Human Vocalization and Playing of Wind Instruments.

Humans emit large salivary particles when talking, singing, and playing musical instruments, which have implications for respiratory disease transmission. Yet little work has been done to characterize the emission rates and size distributions of such particles. This work characterized large particle (dp > 35 µm in aerodynamic diameter) emissions from 70 volunteers of varying age and sex while vocalizing and playing wind instruments. Mitigation efficacies for face masks (while singing) and bell covers (while playing instruments) were also examined. Geometric mean particle count emission rates varied from 3.8 min-1 (geometric standard deviation [GSD] = 3.1) for brass instruments playing to 95.1 min-1 (GSD = 3.8) for talking. On average, talking produced the highest emission rates for large particles, in terms of both number and mass, followed by singing and then instrument playing. Neither age, sex, CO2 emissions, nor loudness (average dBA) were significant predictors of large particle emissions, contrary to previous findings for smaller particle sizes (i.e., for dp < 35 µm). Size distributions were similar between talking and singing (count median diameter = 53.0 µm, GSD = 1.69). Bell covers did not affect large particle emissions from most wind instruments, but face masks reduced large particle count emissions for singing by 92.5% (95% CI: 97.9%, 73.7%).

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 (PM2.5) 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 PM2.5 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.

Size-Resolved Field Performance of Low-Cost Sensors for Particulate Matter Air Pollution.

Particulate matter (PM) air pollution is a major health hazard. The health effects of PM are closely linked to particle size, which governs its deposition in (and penetration through) the respiratory tract. In recent years, low-cost sensors that report particle concentrations for multiple-sized fractions (PM1.0, PM2.5, PM10) have proliferated in everyday use and scientific research. However, knowledge of how well these sensors perform across the full range of reported particle size fractions is limited. Unfortunately, erroneous particle size data can lead to spurious conclusions about exposure, misguided interventions, and ineffectual policy decisions. We assessed the linearity, bias, and precision of three low-cost sensor models, as a function of PM size fraction, in an urban setting. Contrary to manufacturers' claims, sensors are only accurate for the smallest size fraction (PM1). The PM1.0-2.5 and PM2.5-10 size fractions had large bias, noise, and uncertainty. These results demonstrate that low-cost aerosol sensors (1) cannot discriminate particle size accurately and (2) only report linear and precise measures of aerosol concentration in the accumulation mode size range (i.e., between 0.1 and 1 µm). We recommend that crowdsourced air quality monitoring networks stop reporting coarse (PM2.5-10) mode and PM10 mass concentrations from these sensors.

In-Situ Elemental Composition Analysis of Large Inhalable Aerosol Using Laser Induced Breakdown Spectroscopy.

The ability to obtain information on the composition of airborne particles is a necessary part of identifying and controlling risks from exposure to potentially toxic materials, especially in the workplace. However, very few aerosol sampling instruments can characterize elemental composition in real time or measure large inhalable particles with aerodynamic diameter exceeding 20 µm. Here, we present the development and validation of a method for real time elemental composition analysis of large inhalable particles using laser-induced breakdown spectroscopy (LIBS). The prototype sensor uses a passive inlet and an optical triggering system to ablate falling particles with an LIBS plasma. Particle composition is quantified based on collected emission spectra using a real-time material classification algorithm. The approach was validated with a set of 1480 experimental spectra from four different aerosol test materials. We have studied effects of varying detection thresholds and find operating conditions with good agreement to truth values (F1 score ≥ 0.9). Details of the analysis method, including subtracting the spectral contribution from the air plasma and reasons for the infrequent misclassifications, are discussed. The LIBS elemental analysis can be combined with our previously demonstrated direct-reading particle sizer (DRPS) to provide a system capable of both counting, sizing, and elemental analysis of large inhalable particles.

Unequal airborne exposure to toxic metals associated with race, ethnicity, and segregation in the USA.

Persons of color have been exposed to a disproportionate burden of air pollution across the United States for decades. Yet, the inequality in exposure to known toxic elements of air pollution is unclear. Here, we find that populations living in racially segregated communities are exposed to a form of fine particulate matter with over three times higher mass proportions of known toxic and carcinogenic metals. While concentrations of total fine particulate matter are two times higher in racially segregated communities, concentrations of metals from anthropogenic sources are nearly ten times higher. Populations living in racially segregated communities have been disproportionately exposed to these environmental stressors throughout the past decade. We find evidence, however, that these disproportionate exposures may be abated though targeted regulatory action. For example, recent regulations on marine fuel oil not only reduced vanadium concentrations in coastal cities, but also sharply lessened differences in vanadium exposure by segregation.

Aerosol emissions from wind instruments: effects of performer age, sex, sound pressure level, and bell covers.

Aerosol emissions from wind instruments are a suspected route of transmission for airborne infectious diseases, such as SARS-CoV-2. We evaluated aerosol number emissions (from 0.25 to 35.15 µm) from 81 volunteer performers of both sexes and varied age (12 to 63 years) while playing wind instruments (bassoon, clarinet, flute, French horn, oboe, piccolo, saxophone, trombone, trumpet, and tuba) or singing. Measured emissions spanned more than two orders of magnitude, ranging in rate from < 8 to 1,815 particles s-1, with brass instruments, on average, producing 191% (95% CI 81-367%) more aerosol than woodwinds. Being male was associated with a 70% increase in emissions (vs. female; 95% CI 9-166%). Each 1 dBA increase in sound pressure level was associated with a 28% increase (95% CI 10-40%) in emissions from brass instruments; sound pressure level was not associated with woodwind emissions. Age was not a significant predictor of emissions. The use of bell covers reduced aerosol emissions from three brass instruments tested (trombone, tuba, and trumpet), with average reductions ranging from 53 to 73%, but not for the two woodwind instruments tested (oboe and clarinet). Results from this work can facilitate infectious disease risk management for the performing arts.

Household air pollution from wood-burning cookstoves and C-reactive protein among women in rural Honduras.

Household air pollution from solid fuel combustion was estimated to cause 2.31 million deaths worldwide in 2019; cardiovascular disease is a substantial contributor to the global burden. We evaluated the cross-sectional association between household air pollution (24-h gravimetric kitchen and personal particulate matter (PM2.5) and black carbon (BC)) and C-reactive protein (CRP) measured in dried blood spots among 107 women in rural Honduras using wood-burning traditional or Justa (an engineered combustion chamber) stoves. A suite of 6 additional markers of systemic injury and inflammation were considered in secondary analyses. We adjusted for potential confounders and assessed effect modification of several cardiovascular-disease risk factors. The median (25th, 75th percentiles) 24-h-average personal PM2.5 concentration was 115 µg/m3 (65,154 µg/m3) for traditional stove users and 52 µg/m3 (39, 81 µg/m3) for Justa stove users; kitchen PM2.5 and BC had similar patterns. Higher concentrations of PM2.5 and BC were associated with higher levels of CRP (e.g., a 25% increase in personal PM2.5 was associated with a 10.5% increase in CRP [95% CI: 1.2-20.6]). In secondary analyses, results were generally consistent with a null association. Evidence for effect modification between pollutant measures and four different cardiovascular risk factors (e.g., high blood pressure) was inconsistent. These results support the growing evidence linking household air pollution and cardiovascular disease.

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.

Acute differences in blood lipids and inflammatory biomarkers following controlled exposures to cookstove air pollution in the STOVES study.

Household air pollution is a leading risk factor for morbidity and premature mortality. Numerous cookstoves have been developed to reduce household air pollution, but it is unclear whether such cookstoves meaningfully improve health. In a controlled exposure study with a crossover design, we assessed the effect of pollution emitted from multiple cookstoves on acute differences in blood lipids and inflammatory biomarkers. Participants (n = 48) were assigned to treatment sequences of exposure to air pollution emitted from five cookstoves and a filtered-air control. Blood lipids and inflammatory biomarkers were measured before and 0, 3, and 24 hours after treatments. Many of the measured outcomes had inconsistent results. However, compared to control, intercellular adhesion molecule-1 was higher 3 hours after all treatments, and C-reactive protein and serum amyloid-A were higher 24 hours after the highest treatment. Our results suggest that short-term exposure to cookstove air pollution can increase inflammatory biomarkers within 24 hours.

Quantifying the Health Benefits of Face Masks and Respirators to Mitigate Exposure to Severe Air Pollution.

Familiarity with the use of face coverings to reduce the risk of respiratory disease has increased during the coronavirus pandemic; however, recommendations for their use outside of the pandemic remains limited. Here, we develop a modeling framework to quantify the potential health benefits of wearing a face covering or respirator to mitigate exposure to particulate air pollution. This framework accounts for the wide range of available face coverings and respirators, fit factors and efficacy, air pollution characteristics, and exposure-response data. Our modeling shows that N95 respirators offer robust protection against different sources of particulate matter, reducing exposure by more than a factor of 14 when worn with a leak rate of 5%. Synthetic-fiber masks offer less protection with a strong dependence on aerosol size distribution (protection factors ranging from 4.4 to 2.2), while natural-fiber and surgical masks offer reductions in the exposure of 1.9 and 1.7, respectively. To assess the ability of face coverings to provide population-level health benefits to wildfire smoke, we perform a case study for the 2012 Washington state fire season. Our models suggest that although natural-fiber masks offer minor reductions in respiratory hospitalizations attributable to smoke (2%-11%) due to limited filtration efficiency, N95 respirators and to a lesser extent surgical and synthetic-fiber masks may lead to notable reductions in smoke-attributable hospitalizations (22%-39%, 9%-24%, and 7%-18%, respectively). The filtration efficiency, bypass rate, and compliance rate (fraction of time and population wearing the device) are the key factors governing exposure reduction potential and health benefits during severe wildfire smoke events.

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.

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.

Short-term differences in cardiac function following controlled exposure to cookstove air pollution: The subclinical tests on volunteers exposed to smoke (STOVES) study.

BACKGROUND: Exposure to household air pollution from solid fuel combustion for cooking and heating is an important risk factor for premature death and disability worldwide. Current evidence supports an association of ambient air pollution with cardiovascular disease but is limited for household air pollution and for cardiac function. Controlled exposure studies can complement evidence provided by field studies. OBJECTIVES: To investigate effects of short-term, controlled exposures to emissions from five cookstoves on measures of cardiac function. METHODS: Forty-eight healthy adults (46% female; 20-36 years) participated in six, 2-h exposures ('treatments'), including emissions from five cookstoves and a filtered-air control. Target fine particulate matter (PM2.5) exposure-concentrations per treatment were: control, 0 µg/m3; liquefied petroleum gas, 10 µg/m3; gasifier, 35 µg/m3; fan rocket, 100 µg/m3; rocket elbow, 250 µg/m3; and three stone fire, 500 µg/m3. Participants were treated in a set (pre-randomized) sequence as groups of 4 to minimize order bias and time-varying confounders. Heart rate variability (HRV) and cardiac repolarization metrics were calculated as 5-min means immediately and at 3 h following treatment, for analysis in linear mixed-effects models comparing cookstove to control. RESULTS: Short-term differences in SDNN (standard deviation of duration of all NN intervals) and VLF (very-low frequency power) existed for several cookstoves compared to control. While all cookstoves compared to control followed a similar trend for SDNN, the greatest effect was seen immediately following three stone fire (ß = -0.13 ms {%}; 95% confidence interval = -0.22, -0.03%), which reversed in direction at 3 h (0.03%; -0.06, 0.13%). VLF results were similar in direction and timing to SDNN; however, other HRV or cardiac repolarization results were not similar to those for SDNN. DISCUSSION: We observed some evidence of short-term, effects on HRV immediately following cookstove treatments compared to control. Our results suggest that cookstoves with lower PM2.5 emissions are potentially capable of affecting cardiac function, similar to stoves emitting higher PM2.5 emissions.

A High-throughput, Robotic System for Analysis of Aerosol Sampling Filters.

The determination of accumulated mass on filter-based aerosol samples is the basis for many forms of scientific research and regulatory monitoring of air quality. However, gravimetric analysis of air sampling filters is tedious, time-intensive, and prone to human error. This work describes the development of an Automated Air Analysis Facility (AIRLIFT) for high-throughput gravimetric mass and optical black carbon measurements of filter-based aerosol samples. The AIRLIFT consists of a sealed environmental enclosure, a 6-axis articulating robotic arm, a programmable control system, a filter weighing apparatus, and an optical system for the determination of aerosol black carbon via light attenuation. The system actively monitors microbalance stability and chamber relative humidity. Digital imaging and QR code scanning support sample tracking and data logging. Performance metrics for temperature and humidity control and weight stability were found to meet or exceed minimum requirements set forth by the US Environmental Protection Agency. The AIRLIFT is capable of analyzing approximately 260 filters per day while reducing the required personnel time by a factor of ~4.

Acute changes in lung function following controlled exposure to cookstove air pollution in the subclinical tests of volunteers exposed to smoke (STOVES) study.

Background: Exposure to household air pollution generated as a result of cooking and heating is a leading contributor to global disease. The effects of cookstove-generated air pollution on adult lung function, however, remain uncertain.Objectives: We investigated acute responses in lung function following controlled exposures to cookstove-generated air pollution.Methods: We recruited 48 healthy adult volunteers to undergo six two-hour treatments: a filtered-air control and emissions from five different stoves with fine particulate matter (PM2.5) targets from 10 to 500 µg/m3. Spirometry was conducted prior to exposure and immediately, and three and 24 h post-exposure. Mixed-effect models were used to estimate differences in post-exposure lung function for stove treatments versus control.Results: Immediately post-exposure, lung function was lower compared to the control for the three highest PM2.5-level stoves. The largest differences were for the fan rocket stove (target 250 µg/m3; forced vital capacity (FVC): -60 mL, 95% confidence interval (95% CI) -135, 15; forced expiratory volume (FEV1): -51 mL, 95% CI -117, 16; mid-expiratory flow (FEF25-75): -116 mL/s, 95% CI -239, 8). At 3 h post-exposure, lung function was lower compared to the control for all stove treatments; effects were of similar magnitude for all stoves. At 24 h post-exposure, results were consistent with a null association for FVC and FEV1; FEF25-75 was lower relative to the control for the gasifier, fan rocket, and three stone fire.Conclusions: Patterns suggesting short-term decreases in lung function follow from exposure to cookstove air pollution even for stove exposures with low PM2.5 levels.

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.

Comparing regional stove-usage patterns and using those patterns to model indoor air quality impacts.

Monitoring improved cookstove adoption and usage in developing countries can help anticipate potential health and environmental benefits that may result from household energy interventions. This study explores stove-usage monitor (SUM)-derived usage data from field studies in China (52 stoves, 1422 monitoring days), Honduras (270 stoves, 630 monitoring days), India (19 stoves, 565 monitoring days), and Uganda (38 stoves, 1007 monitoring days). Traditional stove usage was found to be generally similar among four seemingly disparate countries in terms of cooking habits, with average usage of between 171 and 257 minutes per day for the most-used stoves. In Honduras, where survey-based usage data were also collected, there was only modest agreement between sensor data and self-reported user data. For Indian homes, we combined stove-usage data with a single-zone Monte Carlo box model to estimate kitchen-level PM2.5 and CO concentrations under various scenarios of cleaner cookstove adoption. We defined clean cookstove performance based on the International Standards Organization (ISO) voluntary guidelines. Model results showed that even with 75% displacement of traditional stoves with the cleanest available stove (ISO tier-5), World Health Organization 24 hours PM2.5 standards were exceeded in 96.4% of model runs, underscoring the importance of full displacement.

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.