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

Household Air Pollution and High Blood Pressure: A Secondary Analysis of the 2016 Albania Demographic Health and Survey Dataset

Background: Hypertension is a significant public health problem in low- and middle-income countries (LMICs). This study aimed to examine the association between household air pollution (HAP) and blood pressure using data from the 2016 Albania Demographic Health and Survey (DHS). Methods: We computed the odds ratio (OR) for the prevalence of hypertension between respondents exposed to clean fuels (e.g., electricity, liquid petroleum gas, natural gas, and biogas) and respondents exposed to polluting fuel (e.g., kerosene, coal/lignite, charcoal, wood, straw/shrubs/grass, and animal dung). Result: The results show that participants exposed to household polluting fuels in Albania were 17% more likely to develop hypertension than those not exposed to household air pollution (OR = 1.17, 95% CI 1.10 to 1.24). Subgroup analysis revealed that the odds of hypertension were more significant among women (OR = 1.22, 95% CI 1.13 to 1.31), rural residents (OR = 1.12, 95% CI 1.04 to 1.22), and participants aged >24 years (OR = 1.35, 95% CI 1.12 to 1.62) who were exposed to household polluting fuels compared to their counterparts who were not exposed. In summary, the results of the study show significant associations between household air pollution and hypertension risk overall, especially among women, rural dwellers, and people aged >24 years in Albania. Conclusion: In this study, an association between household air pollution and the risk of hypertension was found, particularly among low-income households, those with no education, women, and those who live in rural areas.

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

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

Pay-as-you-go liquefied petroleum gas supports sustainable clean cooking in Kenyan informal urban settlement during COVID-19 lockdown

Approximately 2.8 billion people rely on polluting fuels (e.g. wood, kerosene) for cooking. With affordability being a key access barrier to clean cooking fuels, such as liquefied petroleum gas (LPG), pay-as-you-go (PAYG) LPG smart meter technology may help resource-poor households adopt LPG by allowing incremental fuel payments. To understand the potential for PAYG LPG to facilitate clean cooking, objective evaluations of customers' cooking and spending patterns are needed. This study uses novel smart meter data collected between January 2018-June 2020, spanning COVID-19 lockdown, from 426 PAYG LPG customers living in an informal settlement in Nairobi, Kenya to evaluate stove usage (e.g. cooking events/day, cooking event length). Seven semi-structured interviews were conducted in August 2020 to provide context for potential changes in cooking behaviours during lockdown. Using stove monitoring data, objective comparisons of cooking patterns are made with households using purchased 6 kg cylinder LPG in peri-urban Eldoret, Kenya. In Nairobi, 95% of study households continued using PAYG LPG during COVID-19 lockdown, with consumption increasing from 0.97 to 1.22 kg/capita/month. Daily cooking event frequency also increased by 60% (1.07 to 1.72 events/day). In contrast, average days/month using LPG declined by 75% during lockdown (17 to four days) among seven households purchasing 6 kg cylinder LPG in Eldoret. Interviewed customers reported benefits of PAYG LPG beyond fuel affordability, including safety, time savings and cylinder delivery. In the first study assessing PAYG LPG cooking patterns, LPG use was sustained despite a COVID-19 lockdown, illustrating how PAYG smart meter technology may help foster clean cooking access.

In-use emissions from biomass and LPG stoves measured during a large, multi-year cookstove intervention study in rural India

We conducted an emission measurement campaign as a part of a multiyear cookstove intervention trial in two rural locations in northern and southern India. 253 uncontrolled cooking tests measured emissions in control and intervention households during three ~3-month-long measurement periods in each location. We measured pollutants including fine particulate matter (PM_2.5), organic and elemental carbon (OC, EC), black carbon (BC) and carbon monoxide (CO) from stoves ranging from traditional solid fuel (TSF) to improved biomass stoves (rocket, gasifier) to liquefied petroleum gas (LPG) models. TSF stoves showed substantial variability in pollutant emission factors (EFs; g kg^-1 wood) and optical properties across measurement periods. Multilinear regression modeling found that measurement period, fuel properties, relative humidity, and cooking duration are significant predictors of TSF EFs. A rocket stove showed moderate reductions relative to TSF. LPG stoves had the lowest pollutant EFs, with mean PM_2.5 and CO EFs (g MJ_delivered^-1) >90% lower than biomass stoves. However, in-home EFs of LPG were substantially higher than lab EFs, likely influenced by non-ideal combustion performance, emissions from food and possible influence from other combustion sources. In-home emission measurements may depict the actual exposure benefits associated with dissemination of LPG stoves in real world interventions.