In this work, crash precipitation technique was employed to synthesize a visible light-responsive tungsten trioxide (WO₃) photocatalyst using ammonium paratungstate as tungsten precursor. The spray-dried (120 °C) and calcined (600 °C) WO₃ powder was characterized by analyzing methods of XRD, PSD, BET and BJH, Raman, FESEM/EDX, FTIR, UV–vis DRS and XPS spectroscopy. X-ray diffraction (XRD) and Raman studies confirm the well crystalline monoclinic crystal structure. Scanning electron microscopy (SEM) images showed micron-sized spherical bulks of WO₃ particles with needle-like morphology. A normal distribution with a d₅₀ (median diameter) value of 6.0 μm was observed with particle size analysis. Much enhanced BET surface area of 102 g/m² with wide pore size 1.8 nm is measured compared to commercially available WO₃ that results in increased pollutants surface adsorption. Fourier transform infrared spectroscopy (FTIR) study demonstrated that the calcined sample surface is enriched with bonded hydroxyl groups, beneficial for powder particles activity. Photocatalyst band gap was calculated by considering the absorbance measurements recorded on UV–vis diffuse reflectance spectroscopy (DRS). The energy value of 2.6 eV was calculated which lies in the visible light region while X-ray photoelectron spectroscopy (XPS) analysis showed 6 + oxidation state for tungsten. Bulk WO₃ sphere photocatalytic activity was evaluated through the exertion of synthetic textile methylene blue (MB) dye and sulfamethoxazole (SMX) pharmaceutical antibiotic. The obtained activity results showed 85% and 100% degradation for MB and SMX under 100 min visible light irradiation. We expect that our work may provide a new sample for energy production (H₂) through water photolysis, gas sensing and soft matter research.

Urban stormwater is known to cause a myriad of problems, ranging from flooding to water quality degradations. This paper provides an extensive review of analytical probabilistic model (APMs) used in the design of urban runoff control systems. APMs are closed-form mathematical expressions representing a long-term system’s output performance derived from the probability distribution of the system’s input variables. Once derived, the APMs are easy to handle, allow for sensitive analysis, and can be co-opted into optimization frameworks. The implementation of APM in the planning and design of runoff control systems will not only help address the runoff quantity and quality problems of urban stormwater, but will also go a long way in optimizing the benefits derived from the systems. This paper reviews studies that document the negative impacts of urbanization on runoff quantity and quality, and the best management practices (BMPs) used to mitigate the impacts. Three design methodologies used in urban stormwater control systems were reviewed. A detailed review of research on the development and use of APMs in urban stormwater management in various runoff control systems is presented, and recommendations are proffered.

Groundwater resource management in drylands, characterized by climate variability and population growth, is difficult. Exploration and exploitation of groundwater, due to inadequate surface water is very costly. This study employed the analytic hierarchy process (AHP) and GIS to identify groundwater potential (GWP) areas in a semi-arid region of Nigeria. Land-use-land-cover, drainage density, slope, rainfall, static water level, soil, lithology, and aquifer were selected for GWP analysis. Parameter weights were determined using AHP and ranked based on their contribution to GWP by experts. The parameters were then integrated using the weighted overlay tool in ArcGIS 10.5 to produce a GWP map of the study area. Borehole yield data from 245 wells were collected to determine the model accuracy and model validation. Results classified the study area into very high GWP (1.9%), high GWP (8.8%), moderate GWP (62%), low GWP (20.70%) and very low GWP (6.6%). Areas with better GWP include Gurun, Dugol, Zago, Kumbo, Dukku, Doguwa, Riruwai, Dambazau, etc. Moderate GWP areas are widely spread across the state while areas with poor GWP include Sharawa, Kadewa, Koya, Dagar, Jigilawa, Galwanga, Yanganau, Kunchi, Tofa, Tsanyawa, etc. Validation of the AHP model with borehole yield data shows a correlation coefficient of 71.3% giving a good prediction. AHP and GIS can be used to successfully map GWP areas which could serve as an exploration guide for sustainable management of groundwater resources in semi-arid areas.

Climate change is projected to have adverse impacts on environmental sustainability. This research combines statistical analysis and Bayesian modeling for climate change detection and attribution in Kaduna, Northern Nigeria. The study combines the Bayesian estimation of abrupt change, seasonality, and trend model (BEAST) with the Mann–Kendall (M–K) trend test for detection and correlation analysis with optimum fingerprinting for attribution. The study used 122 years of climate data (1901–2022), focusing on average annual rainfall and average annual surface temperature for climate change detection, alongside a 30-year analysis of greenhouse gas (GHG) emissions (1990–2020) for climate change attribution. The result of the M–K test reveals a significant increasing trend in temperature (approximately 0.004 °C/year) and a decreasing trend in rainfall (approximately 0.756 mm/year), indicating a warming climate and potential drought conditions. The Bayesian approach further identified multiple changepoints in temperature data, highlighting years of significant climatic shifts. Correlation analysis demonstrated a weak positive relationship between temperature increases and GHG emissions with a correlation coefficient of 0.27. Optimum fingerprinting results show a non-statistically significant relationship between the variables with an R2 value of 0.071, indicating that only 7.1% of the variability in temperature can be explained by the model.

Soil loss is aggravated by uncontrolled deforestation, indiscriminate land clearing for agricultural activities, overgrazing, and urban development that leads to severe soil erosion over the land surface. The main objective of this research is to apply the Revised Universal Soil Loss Equation (RUSLE), in conjunction with remote sensing and GIS, to determine the temporal variation of soil loss from the Gubi watershed in the years 2000 and 2017 and to estimate the sediment delivery into the Gubi reservoir in Northern Nigeria. Datasets of rainfall, soil type, topography, cover management, and support practice were utilized to determine the five RUSLE factors. The research identified five levels of erosion ranging from severe to very low-risk areas. The spatial distribution of erosion hotspots in the catchment area was highlighted. Results revealed increasing levels of erosion from 14,244.31 tons/year in 2000 to 16,792.33 tons/year in 2017. Consequently, the catchment's sediment yield was 6903.65 tons/year and 9172.71 tons/year corresponding to sediment delivery ratios of 48.46 % and 54.62 % in 2000 and 2017 respectively. The sediment inflow into Gubi reservoir was 747.38 tons/year and 950.76 tons/year corresponding to 10.83 % and 10.37 % of the total sediment yield in 2000 and 2017 respectively. Soil erosion vulnerability index maps were produced and the erosion is expected to increase with time as agricultural activities and deforestation continue to occur. The sediment deposits have the potential to reduce the designed life of the reservoir. Best management practices, such as tree planting, mulching, and contour ridging are recommended for soil conservation. There is a need to assess the reservoir sediment deposits so that measures can be taken to maintain the reservoir operations properly.

Rainfall-runoff modelling was carried out to determine HydrologicEngineering Center’s Hydrologic Modeling System model parametersfor catchments in Johor, Malaysia.