The stakes could hardly be higher. Roughly 2.4 billion people worldwide lack access to electricity and depend on biomass for their daily energy needs, and in sub-Saharan Africa as much as 90 to 98 percent of energy comes from fuelwood. Ethiopia is among the most biomass-dependent countries on Earth: traditional fuels supply approximately 92 percent of the energy used for lighting and cooking. More than half of all wood harvested globally is burned as fuel, and about a third of that harvest is unsustainable, driving deforestation, soil degradation and rising greenhouse gas emissions. In Girar Jarso, a mountainous district of about 49,435 hectares located 112 kilometers from Addis Ababa, the pressure is visible in degraded natural forests and in the daily scramble of women who compete for dung fuel on grazing lands because firewood has become scarce and expensive.

Biogas technology offers an elegant alternative. Anaerobic digesters ferment animal, human or municipal organic waste in an oxygen-free environment, producing a combustible gas that is typically 60 to 70 percent methane and 30 to 40 percent carbon dioxide, with small amounts of hydrogen, nitrogen and hydrogen sulfide. The methane can be burned directly for cooking and lighting, while the leftover slurry serves as fertilizer. The concept is not new; the first biogas system, used for street lighting, was installed in Exeter, England, in 1895. Ethiopia’s national biogas program introduced the technology roughly four decades ago, and organizations such as the African Biogas Partnership Program and the Netherlands Development Organization have since promoted it across Uganda, Kenya, Rwanda and Ethiopia. Yet adoption across Africa remains patchy, hampered by high upfront costs, maintenance challenges and uneven policy support.

To measure what biogas actually delivers in this specific context, the researchers surveyed 345 households in three purposefully selected kebeles: Goticho Safane, Wertu and Torban Ashe. The sample included 50 biogas adopters and 295 non-adopters, drawn using Yamane’s formula from a population of 2,493 households, and was supplemented by 15 key informant interviews, 6 focus group discussions and field observations. The centerpiece of the study was the Kitchen Performance Test, a standardized method for weighing the fuel a household actually consumes. Thirty-six households, half of them adopters and half non-adopters, had their daily fuelwood use weighed over periods of three to seven days, with consumption normalized by the number of adult equivalents each household served.

The numbers are striking. Households cooking with biogas consumed an average of 1.04 kilograms of fuelwood per capita per day, compared with 2.46 kilograms for households using traditional open three-stone fires. At the household level, adopters burned 4.6 kilograms of wood daily against 7.7 kilograms for non-adopters, while per capita consumption was 0.93 kilograms versus 1.53 kilograms. Scaled across a year, the researchers calculated that each biogas plant saves 1,131.5 kilograms of fuelwood annually, a statistically significant difference. That figure is lower than savings reported in southern Ethiopia, where earlier work recorded daily consumption of 4.95 and 8.34 kilograms for adopters and non-adopters respectively, and well below the 2,534.4 kilograms of annual savings documented in northern Ethiopia, differences the authors attribute to regional practices, biomass availability and household energy needs.

The carbon accounting is equally consequential. Using the saved fuelwood as a starting point, the team applied a standard emission reduction formula that incorporates the net calorific value of wet fuelwood, set at 15 megajoules per kilogram, a fuelwood emission factor of 112 tons of carbon dioxide per terajoule, and the fraction of non-renewable biomass, estimated at 88 percent because wood in the district is harvested faster than forests can regenerate. The result: each biogas plant avoids approximately 1.6 tons of carbon dioxide equivalent per year. That is modest compared with some earlier estimates, including one study that credited biogas plants with around 4 tons of annual reductions, but it reflects the realities of small digesters, wet wood and local cooking habits. There are health dividends as well: traditional firewood stoves can emit 20 to 30 grams of particulate matter per kilogram of wood burned, while biogas stoves emit less than one gram per kilogram of fuel, promising cleaner indoor air and better respiratory outcomes.

Who adopts biogas, and why? A binary logistic regression identified five significant predictors among seven tested variables. The strongest was livestock ownership: households with more cattle were significantly more likely to install digesters, because manure is the primary feedstock and cattle-rich families have a ready supply. Household size also mattered positively, since larger families generate both the labor needed for daily digester operation and the organic waste to feed it. Annual income showed a strong positive correlation, confirming that high investment costs remain the dominant barrier for poorer families, a pattern consistent with studies from Kenya and elsewhere in Ethiopia. Access to adequate water emerged as another decisive factor, because anaerobic digestion requires a consistent water supply to mix with feedstock. Notably, the age and gender of the household head showed no significant effect, suggesting that female-headed and male-headed households are equally capable adopters when resources allow.

The study also sheds light on the fuelwood economy of the district itself. The most commonly used species is Eucalyptus globulus, known locally as Bahrzaf, favored by 69.5 percent of respondents because it grows quickly, burns fast and produces relatively little smoke. Its dominance reflects a landscape in which natural forests are partially disturbed and heavily degraded, indigenous trees survive mainly near church compounds, and plantations of fast-growing eucalypts fill the gap. In an area where 52 percent of the land is highland and terrain ranges from moderate slopes to deep gorges, hauling firewood is labor-intensive, and scarcity pushes the poorest households toward burning dung that would otherwise fertilize fields, a cascade of consequences that biogas adoption can interrupt.

The authors are careful about the limits of their findings. The study covers a single district, which may not represent all of North Shoa or Ethiopia, and while the sample was statistically robust, larger observations would strengthen generalizations. Still, the implications for policy are clear. Financial support mechanisms and educational programs could extend biogas adoption to less advantaged households, and ensuring reliable water access is essential for digester operation. Further research, the team suggests, should explore the welfare effects of adoption across different regions. With Ethiopia’s forests under relentless pressure and global climate targets demanding rapid emission cuts, the message from Girar Jarso is that a digester fed with manure in a highland farmhouse is not just a cooking convenience. It is a measurable intervention, saving more than a ton of wood and 1.6 tons of carbon dioxide equivalent per plant every year, that links household kitchens to the fate of forests and the climate.

Subject of Research: Adoption of household biogas technology and its fuelwood-saving and carbon emission reduction potential in rural Ethiopia

Article Title: Biogas technology adoption and its potential for fuelwood saving and carbon emission reduction in North Shoa, Ethiopia

Article References: Jima, T. T., Deressa, M. T., & Chemeda, B. A. (2025). Biogas technology adoption and its potential for fuelwood saving and carbon emission reduction in North Shoa, Ethiopia. Discover Biotechnology, 2(1), Article 22. https://doi.org/10.1007/s44340-025-00020-3

Image Credits: AI Generated

DOI: 10.1007/s44340-025-00020-3

Keywords: biogas, Ethiopia, fuelwood, carbon emissions, renewable energy, anaerobic digestion, deforestation, clean cooking, kitchen performance test, rural households, climate mitigation, North Shoa

Researchers Seyed Mohammad Javad Sobhani, Maryam Karimi Malek-Abadi and Morteza Taki surveyed 231 forest-dwelling households across 31 villages in Khuzestan Province, using multi-stage stratified random sampling drawn from a population of roughly 3,200 households. Their instrument measured eight latent constructs on a five-point Likert scale, from perceived usefulness and ease of use to cost burden, institutional trust, environmental awareness, subjective norms, behavioral intention and usage continuity. Data were collected face-to-face by trained local enumerators between June 2025 and February 2026, achieving a 93.1 percent effective response rate after quality screening.

The study’s central theoretical move is the introduction of an extended Socio-Ecological Technology Acceptance Model, or SETAM, which fuses the classic Technology Acceptance Model with the tripartite Social Acceptance Framework distinguishing socio-political, market and community acceptance. The authors argue that established frameworks such as TAM2, TAM3, UTAUT and UTAUT2 were built for stable institutional environments with formal credit systems and accessible after-sales markets, and therefore translate poorly to informal economies where upfront solar investment is psychologically weighed against immediate subsistence needs rather than long-term amortization.

SETAM departs from its predecessors in four ways. It folds maintenance literacy and post-installation support networks into perceived ease of use, recognizing that rural servicing logistics matter as much as technical complexity. It situates cost perception within irregular income streams. It treats institutional trust as a gatekeeper capable of amplifying or suppressing every other adoption driver. And it elevates subjective norms in tightly knit communities from a transient social influence to a structural determinant of whether a technology is seen as legitimate at all.

Empirically, the team combined Partial Least Squares Structural Equation Modeling with an artificial neural network to capture both linear causal pathways and non-linear thresholds. The model explained 58.3 percent of the variance in behavioral intention, with predictive relevance confirmed through blindfolding and PLSpredict procedures. The single-hidden-layer neural network, trained with Levenberg-Marquardt backpropagation and validated through Monte Carlo cross-validation, achieved a mean test RMSE of 0.178 against a training RMSE of 0.117, indicating robust generalization without overfitting.

The results are unambiguous about what drives adoption. Subjective norms emerged as the strongest predictor, with a standardized path coefficient of 0.33 and the highest normalized importance in the neural network at 100 percent. In collectivist settings, solar panels become socially legitimate only when neighbors endorse them and local leaders approve. Perceived cost and maintenance burden ranked second as the most formidable barrier, with a negative coefficient of 0.31. Institutional trust followed at 0.26, while perceived usefulness registered 0.28. Environmental awareness influenced intention primarily indirectly, mediated through perceived usefulness, accounting for 56 percent of its total effect—a finding that challenges awareness-centric campaigning.

Perhaps the most policy-relevant discovery comes from the neural network’s partial dependence analysis: adoption intention rises sharply only once perceived cost falls below a Likert-scale tipping point of 2.8. Cost perception, the authors conclude, does not behave linearly. Households operating under tight budget constraints experience a psychological threshold, below which marginal reductions in perceived financial burden yield disproportionate gains in willingness to adopt. Uniform subsidies, they argue, are inefficient because they ignore this tipping point; tiered, income-sensitive financing aimed at the households with the highest perceived burden would deliver far greater leverage per unit of public spending.

Multi-group analysis added a further nuance: first-time adopters are significantly more sensitive to cost and maintenance concerns than experienced solar users, with path coefficients of negative 0.423 versus negative 0.194 and a significant group difference at p equals 0.018. Institutional trust, by contrast, operated as a universal enabler with no significant difference between users and non-users, suggesting that credible subsidies, transparent warranty frameworks and consistent government communication reduce perceived risk for everyone. Robustness checks, including Gaussian copula tests for endogeneity and measurement invariance testing, confirmed that these estimates withstand omitted-variable bias and hold across education levels.

The authors translate their findings into four evidence-informed policy pathways for fossil-rich developing economies. First, replace uniform subsidies with tiered, income-sensitive co-payment structures that build financial literacy alongside ownership. Second, institutionalize community-based maintenance cooperatives—training local technicians, establishing spare-part supply chains and creating peer-support networks—to convert post-installation anxiety into sustained usage. Third, shift from top-down hardware deployment to participatory governance in which local leaders, forest authorities and energy agencies co-design subsidy timelines and guarantees. Fourth, exploit the power of social diffusion through visible demonstration installations and testimonial-based outreach, which the data suggest may be more cost-effective than traditional awareness campaigns, especially when reinforced by institutional credibility.

The stakes extend well beyond household convenience. The study frames solar adoption as a dual-purpose intervention advancing both SDG 7 on affordable clean energy and SDG 13 on climate action: every household that swaps firewood for photovoltaics eases deforestation pressure, reduces indoor air pollution and cuts carbon emissions from biomass combustion. By positioning social acceptance as a structural driver rather than an implementation afterthought, the Zagros research offers a transferable diagnostic framework for biomass-dependent communities across Sub-Saharan Africa, South Asia and Latin America. Its core message is deceptively simple: the energy transition will be won not on rooftops alone, but in the trust between governments and communities, and in the quiet consensus of neighbors watching a neighbor’s panels work.

Subject of Research: Socio-behavioral drivers and institutional enablers of household solar energy adoption among forest-dwelling communities in the Zagros Mountains of Iran.

Article Title: From fuelwood to photovoltaics: Socio-behavioral drivers and institutional enablers of household solar energy adoption in fossil-rich developing contexts

Article References: From fuelwood to photovoltaics: Socio-behavioral drivers and institutional enablers of household solar energy adoption in fossil-rich developing contexts. (n.d.). https://doi.org/10.1016/j.indic.2026.101515

Image Credits: AI Generated

DOI: 10.1016/j.indic.2026.101515

Keywords: solar energy adoption, Zagros Mountains, technology acceptance, institutional trust, subjective norms, energy poverty, PLS-SEM, artificial neural network, renewable energy policy, fuelwood, SDG 7, just energy transition