Global household energy model: a multivariate hierarchical approach to estimating trends in the use of polluting and clean fuels for cooking

Spatial variation and determinants of solid fuel use in Ethiopia; Mixed effect and spatial analysis using 2019 Ethiopia Mini Demographic and Health Survey dataset

BACKGROUND

According to UNSD, World Bank, and WHO, a 2020 joint report, 3 billion people who used solid fuel were found in low and middle-income countries. The burning of such type of fuel emits a variety of pollutants such as PM2.5, PM10, CO, NO2, organic compounds, and other substances which a had wide range of public health problems The evidence from the WHO report, indoor air pollution was attributed to around 3.2 million deaths each year in 2020, and more than 237 000 deaths of children under the age of five. This study aims to investigate solid fuel prevalence, predictors, and spatial variation in Ethiopia.

METHOD

This study was conducted in Ethiopia based on the fifth Ethiopian Demographic and Health Surveys 2019 dataset. 8,663 households were successfully interviewed at a response rate of 99%. Weighted by sampling weight was done to do a reliable statistical analysis. Fuel type was used as the outcome variable whereas sex of household head (male or female), wealth index (poor, middle, and rich), educational status (no education, primary, secondary, higher), having television and radio, a separate room used as a kitchen, were individual predictor variables and community level education(lower/higher), residence(urban/rural), community level media exposure (exposed/unexposed), region (pastoralist, semi-pastoralist, Agrarian, and City administration) were community level variables. All the above analyses were conducted using Excel Microsoft 2016, STATA 14, ArcGIS 10.7, and SaTScan 10.1 software.

RESULTS

The majority (72.62%) of household heads were males. The overall national level of solid fuel use was 87.13% (95% CI (86.4%-87.82%)). From this 87.13% of solid fuel use, 18.60% accounts for urban and 68.53% for rural parts of the country. Educational status, having television, accessing electricity, and wealth index were individual-level variables community-level education, type of residence, and region were community-level variables significantly associated factors towards solid fuel use in our study. Global (z-score = 33.109144, P-value <0.0001), local (hot spot, cluster, and outlier), and Spatial Scan statistical analyses revealed that there was a major geographical variation in solid fuel use across Ethiopia.

CONCLUSION

Based on this finding, the prevalence of solid fuel use was higher in Ethiopia. Educational status, having television, accessing electricity, and wealth index were individual-level variables and community-level education, type of residence, and region were community-level variables statistically significant factors in determining fuel choice for cooking. There was significant spatial variation in the prevalence of solid-fuel use across the country. In order to addressing such heavily dependent on solid fuel use, responsible bodies like health policy makers, national and international organizations, and public health researchers should work on showing health problems of solid fuel use and the means of increasing clean fuel use. Substantial policy modifications are desirable to reach access to clean fuels and technologies (SDG 7.1.2) by 2030 to address health inequities.

Economic Growth Facilitates Household Fuel Use Transition to Reduce PM2.5-Related Deaths in China

Exposure to ambient and indoor particle matter (PM2.5) leads to millions of premature deaths in China. In recent years, indoor air pollution and premature deaths associated with polluting fuel cooking demonstrate an abrupt decline. However, the driving forces behind the mortality change are still unclear due to the uncertainty in household fuel use prediction. Here, we propose an integrated approach to estimate the fuel use fractions and PM2.5-related deaths from outdoor and indoor sources during 2000-2020 across China. Our model estimated 1.67 and 1.21 million premature deaths attributable to PM2.5 exposure in 2000 and 2020, respectively. We find that the residential energy transition is associated with a substantial reduction in premature deaths from indoor sources, with 100,000 (95% CI: 76,000-122,000) for urban and 265,000 (228,000-300,000) for rural populations during 2000-2020. Economic growth is the dominant driver of fuel use transition and avoids 21% related deaths (357,000, 315,000-402,000) from polluting fuel cooking since 2000, which offsets the adverse impact of ambient emissions contributed by economic growth. Our findings give an insight into the coupled impact of socioeconomic factors in reshaping health burden in exposure pathways.

Accurate intercensal estimates of energy access to track Sustainable Development Goal 7

Intercensal estimates of access to electricity and clean cooking fuels at policy planning microregions in a country are essential for understanding their evolution and tracking progress towards Sustainable Development Goals (SDG) 7. Surveys are prohibitively expensive to get such intercensal microestimates. Existing works, mainly, focus on electrification rates, make predictions at the coarse spatial granularity, and generalize poorly to intercensal periods. Limited works focus on estimating clean cooking fuel access, which is one of the crucial indicators for measuring progress towards SDG 7. We propose a novel spatio-temporal multi-target Bayesian regression model that provides accurate intercensal microestimates for household electrification and clean cooking fuel access by combining multiple types of earth-observation data, census, and surveys. Our model's estimates are produced for Senegal for 2020 at policy planning microregions, and they explain 77% and 86% of variation in regional aggregates for electrification and clean fuels, respectively, when validated against the most recent survey. The diagnostic nature of our microestimates reveals a slow evolution and significant lack of clean cooking fuel access in both urban and rural areas in Senegal. It underscores the challenge of expanding energy access even in urban areas owing to their rapid population growth. Owing to the timeliness and accuracy of our microestimates, they can help plan interventions by local governments or track the attainment of SDGs when no ground-truth data are available.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1140/epjds/s13688-022-00371-5.

Household clean energy consumption and health: Theoretical and empirical analysis

The impact of energy consumption on health has become a widely debated topic around the world. However, much of the current research on this topic lacks a theoretical basis. As a result, this paper employs both theoretical and empirical analysis to investigate the impact of household clean energy consumption on residents' health. First, based on the theories of health economics and energy economics, this paper believes that the usage of clean energy can improve the health of residents. Then, the sample for this study is comprised of data from the 2018 China Health and Retirement Longitudinal Study, and the Order Probit Model is applied for the empirical analysis. The outcomes of basic regression, robustness testing, and the treatment of endogenous factors reveal that the usage of clean energy has greatly benefited the health of residents. Furthermore, the heterogeneity analysis shows that long-term use of clean energy greatly improved the health of non-religious people and had a more pronounced impact on the health of women and low-income residents. In addition, the mechanistic analysis indicates that subjective happiness and air quality played a partial mediating role in the impact of cleaner energy consumption on health. Finally, cleaner household energy reduced the prevalence of hypertension, hyperlipidemia, lung disease, asthma, and depression. The conclusion of this paper supports the view of some existing literature, and several policy recommendations are made based on the research findings.

Household cooking fuel estimates at global and country level for 1990 to 2030

Household air pollution generated from the use of polluting cooking fuels and technologies is a major source of disease and environmental degradation in low- and middle-income countries. Using a novel modelling approach, we provide detailed global, regional and country estimates of the percentages and populations mainly using 6 fuel categories (electricity, gaseous fuels, kerosene, biomass, charcoal, coal) and overall polluting/clean fuel use – from 1990-2020 and with urban/rural disaggregation. Here we show that 53% of the global population mainly used polluting cooking fuels in 1990, dropping to 36% in 2020. In urban areas, gaseous fuels currently dominate, with a growing reliance on electricity; in rural populations, high levels of biomass use persist alongside increasing use of gaseous fuels. Future projections of observed trends suggest 31% will still mainly use polluting fuels in 2030, including over 1 billion people in Sub-Saharan African by 2025.

Household air pollution derived from cooking fuels is a major source of health and environmental problems. Here, the authors provide detailed global, regional and country estimates of cooking fuel usage from 1990 to 2030 and project that 31% of people will still be mainly using polluting fuels in 2030.