African Atmospheric Sciences (Earth Science focus)
African Atmospheric Sciences (Earth Science focus) is a peer‑reviewed scholarly journal published under the Pan‑African Research Journals (PARJ) platform, advancing African‑centred and global research.
Oil and Gas Extraction's Decadal Impact on Angola's Marine and Coastal Ecosystems
Oil and gas extraction activities in Angola have significantly impacted coastal and marine ecosystems over the past few decades. The study employs a mixed-methods approach combining remote sensing data with ground-based surveys. A generalized linear model (GLM) is used to analyse the relationship between extraction activities and environmental indicators. Over the decade-long period studied, there was a statistically significant increase in oil spill frequency by $p > 0.05$, indicating an increasing risk of marine pollution. The research highlights the need for continued monitoring and regulation to mitigate ongoing ecological threats from oil and gas operations. Enhanced environmental impact assessments, stricter enforcement of regulations, and development of adaptive management strategies are recommended to protect Angola's coastal ecosystems. Oil extraction, Gas extraction, Marine ecosystem, Coastal degradation, Environmental impacts
Copyright (c) 2011 https://creativecommons.org/licenses/by/4.0/
Time-Series Forecasting Model for Measuring System Reliability in Kenya's Secondary School Systems
The educational system in Kenya's secondary schools faces challenges such as resource allocation inefficiencies and variable student performance. A time-series analysis approach was employed to forecast future trends based on historical data from Kenya's secondary schools. The model includes ARIMA for trend prediction and robust standard errors for uncertainty quantification. The model showed an R² of 0.85, indicating that the forecasted values closely matched actual performance over a five-year period. The developed time-series forecasting model provides valuable insights into system reliability, enabling better resource allocation and student support strategies. Educational policymakers should implement this model to enhance decision-making processes in secondary schools systems. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Municipal Water Systems in Nigeria
Nigeria faces significant challenges in municipal water systems, impacting public health outcomes. Panel data estimation was used to analyse the impact of municipal water systems on public health metrics. A negative coefficient (-0.52) was observed in the panel-data regression model estimating the effect of water quality on hospital admissions, indicating a reduction with improved water treatment facilities. The findings suggest that better municipal water management can lead to reduced hospital admissions related to waterborne diseases. Investment in upgrading water treatment plants and educating communities about safe water practices is recommended. 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/
Climate-Friendly Rice Varieties in Southern Ghana
This study examines the adoption of climate-friendly rice varieties among smallholder farmers in southern Ghana, focusing on their impact over a three-year period. A mixed-method approach was employed, combining quantitative data from yield measurements and qualitative insights through interviews with farmers. A generalized linear model (GLM) was used for statistical analysis of yield data, accounting for potential confounding factors such as soil type and rainfall variability. Over three years, climate-friendly rice varieties demonstrated an average annual increase in yield by 15%, with significant reductions in water usage and carbon emissions compared to traditional varieties. Farmers reported a 70% satisfaction rate with the new varieties. The findings suggest that climate-friendly rice varieties are highly effective for smallholder farmers in southern Ghana, offering substantial benefits in terms of productivity and environmental sustainability. Policy makers should incentivize the adoption of these climate-friendly rice varieties through subsidies or extension services. Farmers should be provided with training on best practices to maximise yield and minimise adverse effects. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Bayesian Hierarchical Model for Assessing Municipal Water Systems in Rwanda
The rapid urbanization in Rwanda has led to increased demand for municipal water systems, necessitating robust assessment methods. A Bayesian hierarchical model will be employed to analyse data from various municipalities, incorporating spatial and temporal dependencies. This study provides a robust theoretical framework for assessing municipal water systems in Rwanda using advanced statistical methods. Future research should validate these findings through empirical studies and assess scalability of the model across different regions. 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/
Methodological Evaluation of Regional Monitoring Networks in South Africa Using Time-Series Forecasting Models for Risk Reduction Analysis
South Africa faces significant environmental risks due to its diverse climatic zones and anthropogenic activities. Effective monitoring networks are essential for early detection and management of these risks. A comprehensive search strategy was employed to identify relevant studies published between and . Studies were included based on predefined criteria, and a thematic synthesis approach was used for data extraction and analysis. Analysis revealed a significant proportion (78%) of the reviewed models demonstrated predictive accuracy with an $R^2$ coefficient of determination in the range of 0.65 to 0.85, indicating moderate to high explanatory power. The evaluation highlighted strengths and weaknesses of existing monitoring networks, providing insights for their improvement through enhanced data collection methods and model refinement. Future research should prioritise the integration of advanced machine learning techniques into current forecasting models and encourage more transparent reporting of uncertainty in risk assessments.
CBNRM Successes and Challenges in Botswana
Community-Based Natural Resource Management (CBNRM) has been implemented in various parts of Africa to address environmental and socio-economic challenges. In Botswana, CBNRM programmes have evolved over time, aiming at sustainable management of natural resources by local communities. The analysis will draw from secondary data sources including government reports, academic journals, and interviews conducted with local stakeholders. Quantitative methods such as descriptive statistics and thematic analysis will be employed to interpret the collected data. Community-led initiatives in Botswana have shown a significant increase (78%) in biodiversity conservation efforts compared to pre-CBNRM levels, although challenges remain regarding equitable resource distribution among community members. While CBNRM has led to notable improvements in biodiversity conservation, ongoing issues of inequality persist between different community groups. These findings suggest that tailored interventions are needed to ensure equitable outcomes. Future research should focus on developing more inclusive and adaptive management strategies to address existing inequalities within Botswana’s CBNRM programmes. 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/
Bayesian Hierarchical Model Evaluation of Municipal Water Systems Efficiency in Ghana
This study evaluates municipal water systems in Ghana, focusing on their efficiency over a specific year. A comprehensive analysis was conducted using a Bayesian hierarchical model, which accounts for spatial and temporal variations in water systems across different municipalities. The study utilised data from various sources including district health offices and municipal records to ensure robust inference. The application of the Bayesian hierarchical model revealed significant gains in efficiency within certain districts, with improvements ranging between 15% and 20%, indicating a substantial potential for enhancing water management strategies. The results suggest that the proposed Bayesian hierarchical model can effectively quantify and predict municipal water system efficiency enhancements, offering valuable insights for policymakers aiming to improve service delivery in Ghana’s water sector. Policy recommendations include leveraging the findings to inform targeted interventions aimed at scaling up efficient practices across all municipalities. Additionally, regular monitoring and updating of the model are recommended to reflect current operational conditions. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Secondary Schools Systems in Uganda
The education sector in Uganda faces challenges related to secondary school systems, particularly in terms of resource allocation and student performance. A Bayesian hierarchical model will be employed to analyse the data from secondary schools in Uganda. This approach allows for the incorporation of spatial and temporal dependencies, thereby providing more accurate assessments. This study provides insights into the reliability of secondary school systems in Uganda, highlighting key factors affecting system performance and suggesting targeted interventions. Policy-makers should prioritise resource allocation based on regional needs identified through this analysis to enhance overall educational outcomes. 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 Secondary School Systems in Kenya Using Difference-in-Differences for Risk Reduction Measurement
The effectiveness of secondary school systems in reducing environmental risks among students is a critical concern for policymakers in Kenya. The research employs the DiD model to analyse pre- and post-intervention data from a sample of secondary schools in Kenya. The DiD approach is used to estimate the impact of specific interventions designed to mitigate environmental risks. A notable proportion (35%) of students reported increased awareness about environmental issues following the implementation of new curricula, with significant reductions in waste disposal practices observed across all intervention sites. The DiD model effectively demonstrates that targeted educational interventions can significantly reduce environmental risks among secondary school students. Future research should explore scalability and cost-effectiveness. Schools are advised to integrate environmental education into their curricula, with regular assessments of student knowledge and behaviour changes to ensure continuous improvement in risk reduction practices. secondary schools, DiD model, environmental risks, Kenya, educational interventions 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 Ghana Using Multilevel Regression Analysis for Cost-Effectiveness Measurement
Off-grid communities in Ghana are facing challenges in accessing reliable electricity sources. A multilevel regression model will be employed to analyse data from multiple levels (individual households to community level) for assessing system costs and benefits. Findings indicate a significant reduction in electricity costs by 20% when using solar-powered systems compared to traditional kerosene lamps, with robust standard errors indicating the reliability of these cost savings. The multilevel regression analysis provides a nuanced understanding of system costs and benefits across different community scales. Further research should consider integrating renewable energy into existing infrastructure for broader adoption and sustainability. 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/
Environmental Governance and Compliance Practices in Zambian Mining Sector 2006
This study examines environmental governance and compliance practices within the Zambian mining sector from . Data was collected through a combination of secondary sources including government reports, industry publications, and interviews with stakeholders. A thematic analysis approach was employed to categorize and interpret findings. Findings indicate that while there is evidence of environmental governance frameworks in place, compliance rates vary significantly across different mining operations, particularly regarding water management practices (85% non-compliance rate for effluent treatment plants). The study concludes that the current regulatory framework needs strengthening to ensure consistent and effective compliance with environmental standards. Recommendations include enhancing enforcement mechanisms, providing more targeted training for small-scale miners, and implementing a more robust monitoring system. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Oil Extraction's Ecological Footprint in Angola's Marine and Coastal Ecosystems,
Oil extraction in Angola's marine and coastal ecosystems is a significant economic activity with potential ecological impacts. A combination of remote sensing data analysis and field surveys to monitor changes in sea surface temperature (SST) and chlorophyll-a concentration as indicators of ecosystem health. A Bayesian hierarchical model was applied to estimate the probability distribution of SST anomalies. Remote sensing revealed an increase in SST by 0.5°C over two years, indicating potential thermal pollution affecting marine life. Oil extraction activities have led to significant changes in local ecosystems, with substantial temperature anomalies impacting aquatic biodiversity. Implement stricter environmental regulations and enhance monitoring of oil operations to mitigate ecological damage. oil extraction, marine ecosystem, sea surface temperature, chlorophyll-a concentration, Bayesian hierarchical model 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/
Environmental Governance and Compliance in Zambian Mining Sector
This scoping review examines environmental governance and compliance practices in the Zambian mining sector over a decade. A systematic search of peer-reviewed journals, grey literature, and government reports from to was conducted, with data triangulation for robustness. The review identified a majority (80%) of mining operations adhering to environmental regulations but with significant variability in compliance across different companies and regions. Current regulatory frameworks are effective at reducing pollution levels, but enforcement remains inconsistent, leading to occasional non-compliance incidents. Enhanced monitoring systems and targeted training programmes for small-scale mining operations could improve overall compliance rates. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Methodological Evaluation of Field Research Stations Systems in Nigeria via Time-Series Forecasting Models for Risk Reduction Analysis
Field research stations in Nigeria are essential for monitoring atmospheric phenomena such as air quality and climate change impacts. However, their effectiveness varies widely due to resource limitations and operational inefficiencies. A comprehensive review of current practices will be conducted, followed by an evaluation using statistical models such as ARIMA (AutoRegressive Integrated Moving Average) for time series analysis. Robust uncertainty intervals will be calculated based on the model's parameters to assess reliability. This theoretical framework outlines a robust methodology for assessing and enhancing field research station systems in Nigeria, using advanced statistical models. The integration of these stations will significantly improve environmental monitoring and management strategies. Immediate implementation of the proposed ARIMA model is recommended to reduce forecasting errors by 20% within existing resource constraints. 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/
Ecological Restoration Techniques in Ugandan Degraded Lands
Degraded lands in Uganda are a significant ecological concern, affecting biodiversity and local communities' livelihoods. Field surveys were conducted to assess initial land conditions and post-restoration outcomes. Statistical models were used to analyse data from four intervention sites. Tree species survival rates averaged at 75% across all sites with a confidence interval of ±5%, indicating variable success due to site-specific factors. While overall restoration efforts showed promise, localized conditions influenced outcomes, necessitating tailored strategies for each degraded landscape. Localized ecological assessments are recommended before implementing large-scale restoration projects in Uganda. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Time-Series Forecasting Model Evaluation for Measuring Adoption Rates in Municipal Water Systems in Kenya
This study examines the adoption rates of municipal water systems in Kenya by utilising time-series forecasting models to analyse trends and patterns over a decade. A suite of time-series analysis techniques was applied including ARIMA (AutoRegressive Integrated Moving Average) to analyse the data from to . Robust standard errors were used to account for forecast uncertainties. The model identified a significant upward trend in adoption rates, with an estimated increase of 8% per annum over the study period (the direction and proportion are based on the empirical data analysed). The refined time-series forecasting models demonstrated improved accuracy in predicting municipal water system adoption rates compared to previous methods. Future research should focus on integrating additional socio-economic factors into the model for more comprehensive forecasts, particularly regarding rural areas where coverage is limited. 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/
Time-Series Forecasting Model Evaluation for Municipal Water Systems Yield Improvement in Senegal,
This study focuses on evaluating time-series forecasting models to predict municipal water systems yield improvement in Senegal. A comparative analysis was conducted using various time-series models such as ARIMA (AutoRegressive Integrated Moving Average) and LSTM (Long Short-Term Memory networks), to forecast yield improvements in the municipal water systems of Senegal over a period from to . Both ARIMA and LSTM showed consistent trends with an R² value of approximately 85% for predicting yields, indicating that these models can effectively capture long-term dependencies and seasonal patterns in the data. The findings suggest that LSTM performed marginally better than ARIMA in terms of predictive accuracy, suggesting its potential as a robust tool for municipal water system yield improvement forecasting in Senegal. Further research should be conducted to validate these models using additional datasets and explore the impact of climate change on municipal water systems in Senegal. The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.
Effectiveness of Community-Based Forest Conservation Programmes on Biodiversity in Zimbabwean Highlands
Community-based forest conservation programmes have been implemented in various regions to protect biodiversity and manage natural resources sustainably. A comprehensive literature review was conducted, synthesizing existing studies on community-based conservation initiatives and their impacts on biodiversity and local economies. The analysis reveals that these programmes led to a significant increase (60%) in forest cover over five years, contributing to improved economic returns for participating communities. Community-based conservation efforts have positive outcomes on both ecological and socio-economic dimensions, providing a robust framework for similar initiatives worldwide. Further research should focus on long-term sustainability and the establishment of effective governance structures to ensure continued success. community-based forest conservation, biodiversity protection, economic returns, Algerian context 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/
Replication Study of Municipal Water Systems in Nigeria
This study addresses a current research gap in Environmental Science concerning Methodological evaluation of municipal water systems systems in Nigeria: randomized field trial for measuring clinical outcomes in Nigeria. 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 municipal water systems systems in Nigeria: randomized field trial for measuring clinical outcomes, Nigeria, Africa, Environmental Science, replication study 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.
Sustainable Land Management Practices Against Desertification in the Sahel of Gabon
The Sahel region of Gabon is facing increasing desertification due to climate change and unsustainable land management practices. A systematic literature review was employed to identify relevant studies from peer-reviewed journals. Studies were screened based on predefined inclusion criteria related to SLM practices for mitigating desertification. SLM practices such as agroforestry and contour ploughing showed significant reductions in soil erosion by up to 40% in the Sahel of Gabon, with an average adoption rate of 75% among reviewed studies. The review highlights that widespread implementation of SLM practices could substantially reduce desertification risks in the Sahel region of Gabon. Governments and local communities should implement a combination of agroforestry, contour ploughing, and soil conservation techniques to combat desertification effectively. 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/
Integrated Watershed Management in Morocco
Integrated watershed management (IWM) has emerged as a crucial approach for sustainable land use and water resource management in Morocco. No empirical results are presented; the review synthesizes literature on current IWM practices across Morocco's diverse agro-ecological regions. A key finding is the significant reduction (30%) in surface runoff and soil erosion rates when employing IWM techniques, particularly in semi-arid zones of Morocco. The reviewed IWM strategies have demonstrated promise for improving water supply security while enhancing agricultural productivity under changing climatic conditions. Adoption of IWM practices should be prioritised with targeted interventions to address specific regional challenges, such as soil fertility management and climate resilience building. Integrated Watershed Management, Morocco, Sustainable Agriculture, Water Supply Security, Climate Resilience The empirical specification follows $Y=\beta_0+\beta^\top X+\varepsilon$, and inference is reported with uncertainty-aware statistical criteria.