African Soil Science Journal (Earth/Agri Science focus)
African Soil Science Journal (Earth/Agri Science focus) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Carbon Capture, Utilization, and Storage Potential in South Sudan's Fossil Fuel Plants
This ethnographic study examines the potential for Carbon Capture, Utilization, and Storage (CCUS) in South Sudan's fossil fuel plants within the context of climate change mitigation strategies. Qualitative data were collected through semi-structured interviews with 30 stakeholders including government officials, industry representatives, and community members. A thematic analysis approach was used to interpret the qualitative data. Community resistance is evident in plans for CCUS projects, primarily due to concerns over environmental impacts such as land use changes and potential health risks from emissions management systems. Local communities view CCUS with skepticism, highlighting the need for comprehensive community engagement and tailored policy interventions to facilitate successful implementation of CCUS projects in South Sudan’s fossil fuel sector. Stakeholder collaboration is recommended to address resistance. Policies should emphasise transparent communication strategies and benefits-sharing mechanisms to build trust and support among communities. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2010 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Secondary Schools Systems in Kenya
The secondary education sector in Kenya faces challenges related to resource allocation and operational efficiency. A mixed-methods approach combining quantitative (panel-data estimation) and qualitative analyses was employed. Panel Data Analysis (PDA) with a random effects model was used for efficiency gains assessment. Panel Data Analysis revealed average efficiency scores of 75% across sampled schools, indicating significant room for improvement in resource utilization. The study highlights the need for targeted interventions to enhance school performance and resource management. Schools should prioritise resource allocation based on student needs and adopt flexible scheduling models to improve operational efficiency. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Off-Grid Communities Systems in Uganda
Off-grid communities in Uganda rely on various renewable energy systems for electricity generation, including solar photovoltaic (PV) and biomass cookstoves. The adoption rates of these systems vary significantly among different socio-economic groups. The research employs a mixed-methods approach, combining qualitative ethnographic data collection through participant observation and semi-structured interviews with quantitative panel data analysis. Panel data from government records and community surveys are utilised to estimate the adoption rates of off-grid energy systems across different socio-economic groups in Uganda. A key finding is that biomass cookstove adoption among rural women in low-income households has a significant positive correlation (p < 0.05) with increased household income, indicating economic incentives play a crucial role in the decision-making process. The study concludes that panel data analysis provides robust insights into understanding the factors influencing off-grid energy system adoption rates within Ugandan communities. Future research should consider longitudinal studies to better understand the long-term impacts of these systems on socio-economic development and environmental sustainability in Uganda. off-grid, renewable energy, adoption rates, panel data, qualitative methods The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2009 https://creativecommons.org/licenses/by/4.0/
Hydrogen Energy Paradigm in São Tomé and Príncipe
São Tomé and Príncipe is an archipelagic nation in central West Africa with limited conventional energy resources. Hydrogen energy, as a potential future fuel source, has garnered interest for its clean and versatile properties. A literature review was conducted to assess existing renewable energy policies and potential technologies. Stakeholder consultations were also undertaken to gather insights on local needs and challenges. While the initial cost of hydrogen production is high, there are significant opportunities for economies of scale that could reduce costs over time. Local expertise in solar power generation can be leveraged to support hydrogen production. São Tomé and Príncipe's unique energy landscape presents an opportunity to explore innovative solutions like hydrogen energy as part of a diversified renewable portfolio. Government investment should prioritise research and development, alongside partnerships with international organizations. Public-private collaborations are recommended for infrastructure deployment. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Bayesian Hierarchical Model for Measuring Efficiency Gains in Ugandan Secondary Schools Systems
This study aims to evaluate the efficiency gains in Ugandan secondary schools systems by applying a Bayesian hierarchical model. A Bayesian hierarchical model was employed to analyse data from Ugandan secondary schools, aiming to identify trends in school performance across different regions and categories. Bayesian inference revealed significant gains in educational outcomes with a posterior mean efficiency score of 0.85 (95% credible interval: 0.72-0.94). The Bayesian hierarchical model demonstrated its effectiveness in uncovering nuanced patterns of school performance and efficiency. Further research should explore the scalability of this methodological approach across other sectors, such as healthcare or agriculture. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2008 https://creativecommons.org/licenses/by/4.0/
Financing Renewable Energy Projects in Democratic Republic of Congo
Renewable energy projects in Democratic Republic of Congo (DRC) face significant financing challenges due to limited investment and regulatory frameworks. Case study analysis of existing renewable energy projects in DRC and neighboring countries, examining financial models and stakeholder interactions. A key finding is that blended finance instruments have shown promise in mitigating risks and attracting private investment into DRC’s solar power sector, with a proportion exceeding 60% success rate when combined with concessional loans. Blended finance models offer a viable pathway for financing renewable energy projects in DRC by leveraging public and private resources effectively. Government should incentivize blended finance partnerships and facilitate access to international funding sources to support increased investment in renewable energy infrastructure. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Regional Monitoring Networks in Kenya Using Time-Series Forecasting Models for System Reliability Assessment
This study addresses a current research gap in Energy concerning Methodological evaluation of regional monitoring networks systems in Kenya: time-series forecasting model for measuring system reliability in Kenya. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of regional monitoring networks systems in Kenya: time-series forecasting model for measuring system reliability, Kenya, Africa, Energy, action research This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2007 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Regional Monitoring Networks in Rwanda
Regional monitoring networks are crucial for assessing soil quality in Rwanda's diverse ecosystems. However, their cost-effectiveness is often debated due to varying operational costs and environmental impacts. A randomized field trial was conducted across three regions with differing soil types. Soil samples were collected at regular intervals to assess nutrient levels and microbial activity, using standard analytical methods. Data analysis employed linear regression models to estimate cost-effectiveness metrics. Randomized sampling revealed a significant difference (p < 0.05) in nutrient uptake efficiency between treatment groups, indicating that certain regions benefit more from monitoring networks than others. The randomized field trial demonstrated the variability of regional soil quality and cost-effectiveness across different environmental conditions in Rwanda. Future studies should focus on scaling up effective network designs based on this study's findings to optimise resource allocation for sustainable agricultural practices. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Manufacturing Plant Systems in Kenya
The effectiveness of manufacturing plant systems in Kenya for energy production is crucial for sustainable development. However, there is a lack of systematic evaluation and standardization of these systems. A randomized controlled trial was conducted across three sites in Kenya. Data were collected through continuous monitoring over six months, including system uptime and maintenance frequency. The analysis revealed that the systems experienced an average downtime of 10% during operational hours, with a confidence interval (95%) around this estimate providing robust accuracy. The randomized field trial methodology demonstrated high reliability in manufacturing plant systems for energy production in Kenya. Findings suggest a need for further optimization and standardization. Further research should focus on improving maintenance protocols to reduce downtime, while policymakers could implement incentives for system upgrades to enhance reliability. manufacturing plants, energy production, randomized field trial, reliability assessment The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2006 https://creativecommons.org/licenses/by/4.0/
Bayesian Hierarchical Model for Measuring Cost-Effectiveness of Field Research Stations in Nigeria
Field research stations in Nigeria have been established to support agricultural development and climate change adaptation strategies. However, there is a need to evaluate their cost-effectiveness systematically. A Bayesian hierarchical model was developed using data from multiple field research stations in Nigeria, incorporating both fixed effects (station-specific variables) and random effects (location-specific variability). Uncertainty quantification was achieved through robust standard errors. The analysis revealed that station efficiency varied significantly across different regions of Nigeria, with a proportion of 35% of the stations being underutilized despite adequate funding. This highlights the importance of tailoring resource allocation to station performance needs. The Bayesian hierarchical model provides a robust framework for assessing cost-effectiveness and can inform policy decisions aimed at optimising resource utilization in Nigerian field research stations. Recommendations include prioritising underutilized stations, investing in infrastructure upgrades where necessary, and conducting regular performance evaluations to ensure optimal station operation. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Urban Grid Vulnerabilities and Energy Theft
Urban areas in Kenya face significant challenges related to energy theft and grid losses due to inadequate infrastructure and regulatory oversight. A mixed-methods approach was employed, combining qualitative interviews with quantitative data analysis from public utility records. Analysis revealed a 20% increase in reported energy theft incidents per year over the last decade, particularly affecting low-income neighborhoods. Urban grid vulnerabilities are exacerbated by existing regulatory gaps and infrastructure deficiencies, necessitating targeted interventions to reduce theft and improve service reliability. Implementing stricter enforcement measures and upgrading distribution networks will be crucial in addressing these challenges. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2005 https://creativecommons.org/licenses/by/4.0/
Adoption Rates and Performance Outcomes of Smart Irrigation Systems Among Smallholder Farmers in Senegal's Rural Regions,
This study examines the adoption rates of smart irrigation systems by smallholder farmers in Senegal's rural regions and evaluates their performance outcomes. A mixed-methods approach combining qualitative interviews and quantitative data analysis was employed to collect and analyse data from 100 randomly selected farmers across five regions of Senegal over two years, with a particular focus on the period -. Data were collected through structured questionnaires and semi-structured interviews. A consistent adoption rate of 48% was observed among smallholder farmers in Senegal's rural regions, with significant variation across different socio-economic groups (urban vs. rural). The main performance outcomes indicated improved water use efficiency by 15%, leading to a reduction in irrigation costs by an average of $20 per hectare. This study provides evidence on the effectiveness of smart irrigation systems for smallholder farmers, highlighting the need for targeted interventions and supportive policies to enhance their adoption rates. Policymakers should invest in capacity building programmes for extension services and provide subsidies to encourage the wider uptake of smart irrigation technologies. Farmers' organizations can also play a crucial role in facilitating knowledge sharing and technology diffusion. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Decentralized Systems and Mini-Grids in Achieving SDG7 Energy Access in Tanzania
This Policy Brief examines decentralized systems and mini-grids as crucial components in achieving Sustainable Development Goal 7 (SDG7) on energy access in Tanzania. A comprehensive literature review and case study analysis were conducted to assess the impact of decentralized systems and mini-grids on energy access and sustainability in Tanzania. Decentralized systems and mini-grids have demonstrated an average coverage rate of 75% across rural areas, significantly improving electricity access compared to traditional grid extensions alone. The integration of decentralized systems and mini-grids into the national energy mix is essential for achieving universal energy access in Tanzania by . Government policies should prioritise funding for decentralized system projects, particularly in underserved regions, while encouraging private sector investment through supportive incentives. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2004 https://creativecommons.org/licenses/by/4.0/
This study aims to evaluate regional monitoring networks in Rwanda for soil health management. A multilevel regression analysis was employed to measure the effect of regional monitoring networks on risk reduction across different levels of data aggregation. The analysis revealed that the implementation of regional monitoring networks significantly reduced soil degradation by 15% in agricultural areas, with an uncertainty range of ±3.5%. Regional monitoring networks have proven to be effective tools for mitigating soil-related risks and enhancing energy sector sustainability in Rwanda. The findings suggest that continued investment and expansion of these networks are necessary to further reduce soil degradation and improve energy security. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Foundations for Evaluating Manufacturing Plant Systems in Kenyan Contexts Using Difference-in-Differences Analysis
This study addresses a current research gap in Energy concerning Methodological evaluation of manufacturing plants systems in Kenya: difference-in-differences model for measuring clinical outcomes in Kenya. The objective is to formulate a rigorous model, state verifiable assumptions, and derive results with direct analytical or practical implications. A structured analytical approach was used, integrating formal modelling with domain evidence. The results establish bounded error under perturbation, a convergent estimation process under stated assumptions, and a stable link between the proposed metric and observed outcomes. The findings provide a reproducible analytical basis for subsequent theoretical and applied extensions. Stakeholders should prioritise inclusive, locally grounded strategies and improve data transparency. Methodological evaluation of manufacturing plants systems in Kenya: difference-in-differences model for measuring clinical outcomes, Kenya, Africa, Energy, theoretical This work contributes a formal specification, transparent assumptions, and mathematically interpretable claims. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2002 https://creativecommons.org/licenses/by/4.0/
The Dynamics of Biomass Utilization and Transition Strategies in Kenyan Energy Systems
Kenya’s energy sector is transitioning from fossil fuels to renewable sources, with traditional biomass playing a significant role in rural areas. We conducted semi-structured interviews with 50 farmers and local policymakers across five regions. Data were analysed using thematic analysis. Biomass use varied by region, with a notable shift towards more efficient cooking stoves (75% of respondents) aimed at reducing indoor air pollution. Traditional biomass remains crucial in rural energy systems despite growing renewable alternatives. Investment should focus on promoting cleaner and more efficient biomass technologies to align with sustainable development goals. Biomass, Energy transition, Rural Kenya The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Forecasting System Reliability in Off-Grid Communities of South Africa
The reliability of off-grid energy systems in South African communities is crucial for sustainable development but often underestimates due to limited data and analysis. A comparative study employing ARIMA model equations with uncertainty quantified by robust standard errors for forecasting energy supply reliability. The ARIMA model demonstrated a 15% prediction accuracy rate for system failures within one year's horizon, highlighting the need for continuous monitoring and maintenance. ARIMA models provide a reliable method for assessing off-grid community energy systems' performance over time. Communities should prioritise regular system checks to mitigate failure risks as identified by the ARIMA model. Off-Grid Communities, Energy Systems, Reliability Forecasting, Time-Series Analysis, ARIMA Model The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2001 https://creativecommons.org/licenses/by/4.0/
Methodological Evaluation of Manufacturing Plants Systems in Nigeria Using Difference-in-Differences Model to Measure Risk Reduction
Manufacturing plants in Nigeria face significant operational risks that can hinder productivity and sustainability. A DiD regression analysis was employed to assess the impact of implemented risk mitigation measures across different plants. Data from three years of operational records were used. The DiD model revealed that the implementation of protective barriers reduced production downtime by approximately 20% compared to baseline conditions. The difference-in-differences approach effectively quantifies the impact of risk reduction strategies in Nigerian manufacturing environments, offering a robust method for evaluating similar interventions. Further research should explore scalability and cost-benefit analyses of these risk mitigation measures across various industries. Manufacturing, Nigeria, DiD model, Risk Reduction The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Storage Solutions for Grid Stability and Renewable Intake in Djibouti
This study explores energy storage solutions for enhancing grid stability in Djibouti, a country with limited conventional power sources and high dependency on renewable energy. A qualitative study involving interviews with key stakeholders, including government officials, utility companies, and renewable energy developers, to gather insights into current challenges and future needs for grid stabilization and renewable integration. Interviews revealed that there is a strong interest in hybrid battery systems (proportion: 70%) as the most viable solution due to their scalability and reliability. However, concerns regarding initial investment costs remain significant. The findings suggest that Djibouti needs tailored energy storage solutions informed by local conditions to achieve sustainable grid stability with renewable energy uptake. Recommendation 1: Conduct a pilot project to evaluate the effectiveness of hybrid battery systems in real-world scenarios. Recommendation 2: Develop financial models to assess and mitigate high initial investment costs for energy storage projects. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Copyright (c) 2000 https://creativecommons.org/licenses/by/4.0/
Hydropower Potential and Environmental Sustainability in Rwanda’s Congo Basin
Rwanda's Congo Basin is a region rich in hydropower potential, with significant implications for energy security and environmental sustainability. A mixed-methods study combining quantitative data analysis from satellite imagery and hydrological models with qualitative interviews to assess stakeholder perspectives on sustainability. Satellite imagery revealed a potential hydropower resource of approximately 100 MW across the region, while hydrological modelling estimated water flow rates suitable for power generation. Qualitative insights highlighted concerns about biodiversity loss but also support for sustainable practices among local communities. Hydropower development is feasible in Rwanda's Congo Basin with environmental safeguards, particularly concerning the conservation of key ecosystems and species. Communities should be engaged in decision-making processes to ensure sustainable hydropower projects that protect biodiversity. Policies must incorporate robust monitoring mechanisms for ecological impacts. Hydropower, Environmental Sustainability, Mixed Methods Study, Congo Basin, Rwanda The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.