Agricultural wastes from plant have continued to be a huge contributor to the global biomass generation and their utilization for biochar is growing. The goal of this research was to produce and characterize modified biochar of Vitex doniana (Black plum) seeds using chemical and thermal treatments. To achieve this, the vitex seed was carbonized for 2 hours at 400°C in a pyrolysis reactor. The resulting char was then impregnated for 24 hours with Phosphoric Acid (H₃PO₄) and potassium hydroxide (KOH) as chemical activating agents before being thermally activated at 400°C, 500°C, 600°C, and 700°C respectively. The purpose of the characterization was to see how the activators and activation temperature affected the adsorbents generated. The quality of absorbents produced was affected by the treatment of char with chemical agents and the activation temperature, according to the results. The samples had distinct functional groups on the surface, according to FTIR analysis, and SEM analysis via microscopy revealed the presence of pores on the surface. Iodine absorption testing reveals that materials activated with KOH had a higher absorption value, peaking at 950mg/g for KOH treated and 600°C activation temperature. The pore diameters and pore volume of KOH samples were determined using BET analysis. The results demonstrate that KOH activated at 600°C has larger pores and a higher pore volume, implying that KOH at 600°C has a higher adsorption capacity. The char sample was also subjected to TGA analysis in order to better understand its behavior in temperature settings.

In recent times, many investigators have delved into plastic waste (PW) research, both locally and internationally. Many of these studies have focused on problems related to land-based and marine-based PW management with its attendant impact on public health and the ecosystem. Hitherto, there have been little or no studies on forecasting PW quantities in developing countries (DCs). The key objective of this study is to provide a forecast on PW generation in the city of Johannesburg (CoJ), South Africa over the next three decades. The data used for the forecasting were historical data obtained from Statistics South Africa (StatsSA). For effective prediction and comparison, three-time series models were employed in this study. They include exponential smoothing (ETS), Artificial Neural Network (ANN), and the Gaussian Process Regression (GPR). The exponential kernel GPR model performed best on the overall plastic prediction with a determination coefficient (R²) of 0.96, however, on individual PW estimation, ANN was better with an overall R² of 0.93. From the result, it is predicted that between 2021 and 2050, the total PW generated in CoJ is forecasted to be around 6.7 megatonnes with an average of 0.22 megatonnes/year. In addition, the estimated plastic composition is 17,910 tonnes PS per year; 13,433 tonnes PP per year; 59,440 tonnes HDPE per year; 4478 tonnes PVC per year; 85,074 tonnes PET per year; 34,590 tonnes LDPE per year and 8955 tonnes other PWs per year.