Background: Groundwater is the principal source of freshwater for many communities in the Niger Delta, where intensive petroleum exploration and production have raised increasing concerns regarding groundwater contamination. Although numerous hydrogeochemical investigations have been conducted within the region, most have focused on onshore environments, leaving offshore groundwater systems largely unexplored. Moreover, the combined application of complementary hydrogeochemical, statistical, index-based, and spatial analytical approaches remains limited, restricting comprehensive evaluation of groundwater quality and contamination patterns. Objectives: This study aimed to comprehensively assess groundwater quality and hydrogeochemical characteristics in an offshore petroleum-producing field of the Niger Delta and to identify the dominant natural hydrogeochemical processes and petroleum-related anthropogenic influences governing groundwater chemistry and contamination patterns. Methods: Groundwater samples were collected from ten monitoring wells during the dry season of 2024. Physicochemical properties, major ions, heavy metals, and total hydrocarbon content were determined following APHA standard methods with comprehensive QA/QC procedures. Hydrogeochemical facies were evaluated using Piper, Durov, and Stiff diagrams. Pearson correlation, Principal Component Analysis (PCA), and Hierarchical Cluster Analysis (HCA) were applied to identify relationships among hydrochemical variables and classify groundwater samples. Groundwater quality was assessed using the Metal Index (MI) and Water Quality Index (WQI), while Geographic Information System (GIS)-based inverse distance weighting (IDW) interpolation was employed to evaluate the spatial distribution of key groundwater quality indicators. Results: Groundwater was consistently characterized by a magnesium-sulphate (Mg–SO₄) hydrochemical facies across all sampling locations. Electrical conductivity (852–1,842 μS/cm), total dissolved solids (1,082–2,338 mg/L), magnesium (98–210 mg/L), sulphate (210–620 mg/L), and iron (2.84–12.45 mg/L) exceeded recommended guideline values in most samples. Principal Component Analysis extracted three components explaining 83.1% of the total variance, representing groundwater mineralisation, salinity-related processes, and sulphate-phosphate enrichment. Hierarchical Cluster Analysis classified the ten wells into four hydrochemically distinct groups with contamination severity increasing near petroleum infrastructure. Metal Index values ranged from 0.94 to 4.82 (Classes II–V), while Water Quality Index values ranged from 105 to 284, classifying all groundwater samples as unsuitable for drinking without treatment. Geospatial analysis identified contamination hotspots within approximately 500 m of petroleum facilities. Conclusion: The findings suggest that groundwater quality in Offshore Field X is governed by the combined influence of natural hydrogeochemical processes and petroleum-related activities. The integrated framework, incorporating hydrogeochemical facies analysis, multivariate statistics, water quality indices, and geospatial mapping, provides complementary lines of evidence for identifying contamination patterns and the processes influencing groundwater chemistry, thereby supporting more informed groundwater assessment and environmental management in petroleum-producing sedimentary environments.
Background: Temperature and rainfall are among the most important indicators of climate change because they directly influence water resources, agricultural productivity, ecosystem functioning, and human well-being. Although numerous studies have investigated historical climatic trends in Nigeria, comparative long-term forecasting across major ecological zones remains limited. Consequently, knowledge of how future climatic trajectories may differ among contrasting environmental regions remains incomplete, constraining evidence-based climate adaptation and environmental management planning. Objectives: This study evaluated long-term temperature and rainfall dynamics across three contrasting ecological zones of Nigeria and assessed the capability of ARIMA models to forecast future climatic conditions. The study further examined spatial differences in projected climate responses and tested hypotheses regarding regional climate variability and model suitability. Methods: Observed temperature and rainfall records from the Nigerian Meteorological Agency covering the period 1985–2023 were obtained for Sokoto (Sahel savanna zone), Abuja (Guinea savanna zone), and Port Harcourt (coastal rainforest zone). Following quality control and pre-processing, annual temperature and rainfall series were developed and analysed using the Box–Jenkins ARIMA framework. Model identification was performed using autocorrelation and partial autocorrelation diagnostics, and ARIMA (1,1,3) was selected as the optimal forecasting model. Model adequacy was evaluated using stationary R², Mean Absolute Percentage Error (MAPE), residual diagnostics, and significance testing. Forecasts were generated for 2024–2050, while long-term monotonic trends were assessed using Kendall's tau-b correlation analysis. Results: The forecasts revealed statistically significant warming trends across all three ecological zones through 2050. Temperature exhibited strong positive temporal associations at Sokoto station (τ_b = 0.884), Abuja station (τ_b = 0.539), and Port Harcourt station (τ_b = 0.914) (p < 0.001). Rainfall projections demonstrated substantial spatial variability. Increasing rainfall trends were observed at Sokoto station (τ_b = 0.572, p < 0.001) and Port Harcourt station (τ_b = 0.673, p < 0.001), whereas Abuja station showed a significant decreasing rainfall trend (τ_b = −0.519, p < 0.001). Model performance statistics indicated acceptable predictive capability, with low temperature forecasting errors and satisfactory diagnostic results. The findings reveal spatially heterogeneous climate-change responses among Nigeria's major ecological zones and confirm the operational usefulness of ARIMA forecasting under data-limited conditions. Conclusion: The study confirmed significant future warming across all investigated ecological zones, while rainfall trajectories varied considerably among regions. All proposed hypotheses were supported. The findings fill an important gap in comparative climate forecasting across Nigeria's major ecological systems and provide evidence that regional climate adaptation strategies should account for substantial spatial differences in future climatic change.
Background: Land degradation represents a major environmental and development challenge in Sub-Saharan Africa, where agricultural systems remain highly dependent on natural soil fertility and rain-fed production. Soil erosion and declining land quality reduce ecosystem services and threaten food security, rural livelihoods, and economic stability. Burkina Faso is particularly affected due to high exposure to climatic variability and intensive land use pressure. Objectives: This study aims to assess the impact of land degradation on agricultural productivity in Burkina Faso and to evaluate its economy-wide consequences using an integrated biophysical and computable general equilibrium modelling framework. Methods: The study combines the Revised Universal Soil Loss Equation (RUSLE) model with a recursive dynamic computable general equilibrium (CGE) model. The RUSLE model is used to estimate spatial soil erosion and derive land productivity loss coefficients across agricultural regions. These coefficients are then introduced as exogenous productivity shocks into the CGE model calibrated on the 2016 Social Accounting Matrix of Burkina Faso. The CGE framework captures interactions among production sectors, households, government, and external trade. It allows assessment of direct and indirect effects of land degradation on agricultural production, income distribution, and macroeconomic performance under different scenarios. Results: The RUSLE results indicate that approximately 28% of agricultural land in Burkina Faso is affected by degradation, corresponding to an estimated economic loss of 321.34 billion CFA francs. Crop-specific results show that staple crops such as maize, millet, sorghum, and groundnuts are the most affected. CGE simulations demonstrate that land productivity losses lead to significant declines in agricultural output, reduced household income, and contraction in macroeconomic indicators. Under the baseline scenario, GDP declines by approximately 27%, while pessimistic conditions lead to even larger reductions. Rural households are disproportionately affected due to their dependence on agriculture. Results also show strong heterogeneity across crop types and regions, reflecting spatial variation in land degradation intensity. Conclusion: Land degradation significantly constrains agricultural productivity and economic performance in Burkina Faso. Integrated biophysical and CGE modelling highlights the importance of sustainable land management policies to mitigate soil erosion impacts and improve agricultural resilience, food security, and rural welfare.
Background: Occupational exposure in automotive coatings manufacturing remains a major industrial health concern due to volatile organic compounds (VOCs), isocyanates, and mixed solvent aerosols generated during spraying, mixing, curing, and cleaning operations. Exposure conditions are particularly variable in small and medium-sized enterprises (SMEs), where limited engineering controls, insufficient ventilation performance, and inconsistent occupational hygiene implementation contribute to unstable indoor environmental conditions and elevated worker health risks across different regulatory systems. Objectives: This review aims to develop an integrated systems-based interpretation of occupational exposure in automotive coatings SMEs by comparatively evaluating exposure pathways, engineering control effectiveness, and occupational risk governance across the European Union, the United States, and Ukraine. Methods: A narrative critical review was conducted using peer-reviewed literature, occupational hygiene studies, environmental exposure investigations, and regulatory documents retrieved from Scopus, Web of Science, EU-OSHA, OSHA, and Ukrainian legislative and technical sources published between 2000 and 2025. The review focused on occupational exposure to VOCs and isocyanates in automotive coatings environments, with SMEs serving as the primary analytical context due to their known limitations in exposure monitoring and engineering control implementation. A structured comparative synthesis was applied to examine relationships between exposure dynamics, ventilation and engineering control performance, and regulatory implementation capacity across jurisdictions. The analysis integrated evidence from exposure science, indoor environmental engineering, and occupational risk governance to identify system-level determinants of exposure variability and implementation gaps in SME-dominated industrial settings. Results: The analysis demonstrates that occupational exposure in automotive coatings facilities is governed not only by chemical hazard properties, but by the interaction between regulatory implementation, engineering control effectiveness, ventilation stability, and organizational capacity within SMEs. Across all examined jurisdictions, measured exposure conditions frequently diverged from formal occupational exposure limits, particularly during high-emission operations such as spray-painting, solvent mixing, and cleaning processes. The review identifies SMEs as structural amplifiers of exposure variability due to insufficient local exhaust ventilation, inconsistent maintenance of engineering systems, and limited occupational hygiene infrastructure. A novel typology of SME exposure-control environments was developed, consisting of controlled-stable, compliance-driven, fragmented-control, and reactive SMEs. Comparative synthesis further identified three distinct occupational exposure governance paradigms: preventive and engineering-oriented (EU), compliance-oriented (USA), and transitional hybrid (Ukraine). The findings additionally indicate that conventional time-weighted exposure metrics insufficiently capture episodic peak exposures relevant to respiratory sensitization risks associated with isocyanates. Conclusion: This review proposes a systems-oriented conceptual framework for interpreting occupational exposure variability in automotive coatings SMEs by integrating regulatory governance, engineering controls, and indoor environmental dynamics. The findings demonstrate that effective occupational risk reduction depends more strongly on implementation capacity and ventilation performance than on formal regulatory compliance alone.
Background: Urban water systems face increasing pressure from climate-driven droughts, population growth, and infrastructural limitations. In Cape Town, prolonged droughts have highlighted inequalities in household water access and consumption patterns. Understanding how socio-economic disparities and behavioural responses interact with municipal water management is essential to inform equitable, efficient, and sustainable water governance. Objectives: This study investigates how household socio-economic status, local infrastructure, and smart water metering influence water consumption patterns, identifies unaccounted-for water, and assesses strategies to improve demand-side management during droughts in rapidly urbanising cities. Methods: A multi-component, spatially grounded methodology was applied across six Cape Town suburbs representing three income tiers. Secondary data, including monthly billing records, water meter readings, and socio-economic indicators, were analysed using descriptive statistics, trend analyses, and unaccounted-for water assessment. Stratified random sampling ensured proportional representation of households across income categories. Geographic Information Systems (GIS) were used to map consumption patterns and detect spatial disparities. Comparative analyses quantified variations in water demand, billing anomalies, and behavioural responses, while scenario-based evaluation examined the effectiveness of smart metering and demand-side interventions under differing drought conditions. Results: Findings reveal substantial heterogeneity in water consumption and billing across income tiers, with high variability driven by socio-economic disparities, household size, and settlement patterns. Negative consumption and unaccounted-for water indicate operational inefficiencies and potential socio-economic stress. Smart metering enabled improved detection of leaks and anomalous usage, but its effectiveness was moderated by affordability and compliance. Demand-side interventions, including tiered tariffs, volumetric restrictions, and public awareness campaigns, demonstrated potential to reduce consumption, particularly in higher-income households. Proactive and reactive strategies combined improved resilience and demonstrated the importance of equity-centred governance. Results showed that technical solutions alone are insufficient without concurrent socio-economic and behavioural considerations. Conclusion: Urban water resilience under drought requires integrated, equity-focused strategies combining technical, economic, and behavioural interventions. Smart metering and demand management are most effective when measures are taken to reduce socio-economic inequalities. The study' s novelty lies in combining municipal water billing records, socio-economic classifications, and GIS-based demographic mapping to examine disparities in urban water allocation and unaccounted-for water during drought conditions. This work advances knowledge by demonstrating how GIS-supported demographic analysis can contextualize patterns of water allocation, billing irregularities, and unaccounted-for water across socio-economic areas.
