Biosynthesis, Characterization and Biological Applications of Silver Nanoparticles using Celosia trigyna and Solanum nigrum Extracts: Neglected Vegetables in Nigeria

Plant-mediated synthesis is gaining acceptance in many fields i.e. biology and pharmaceutical fields. This aim of this study is synthesizing Ag nanoparticles using air-dried leaves of two (2) neglected vegetables i.e.  Celosia trigyna and Solanum nigrum.  Ultraviolet–visible spectroscopy, fourier transform infrared spectroscopy (FT-IR) and scanning electron microscopy (SEM) were used to characterize the formation of silver nanoparticles (AgNPs). The anti-inflammatory properties of these AgNPs were evaluated using Cell Stabilization Membrane (CSM) and lipoxidase assays, their antioxidant activity were established on DPPH and ABTS+ assays. The positive control employed are indomethacin and ascorbic acid for these activities. Nanoparticles synthesized were labelled for Celosia trigyna (CT-AgNPs) and Solanum nigrum (SN-AgNPs) were noticed through visual color change. The UV–Vis spectra of the synthesized nanoparticles displayed absorption bands at around 360-440 nm, which is a characteristic band for Ag and FTIR displayed possible functional groups responsible for Ag nanoparticles synthesized by these plants.  The SEM image of the AgNPs formed displayed were spherical in morphology. CT-AgNPs exhibited the most significant inhibitory activity against HRBC (IC50: 32.2 µg/ml) while SN-AgNPs displayed the most significant inhibitory activity against lipoxygenases (IC50: 32.8 µg/ml) when compared to the positive control used indomethacin (IC50: 28.1 µg/ml). SN-AgNPs exhibited the most significant antioxidant effect against ABTS (IC50: 11.4 µg/ml) while CT-AgNPs displayed the most significant antioxidant activity against DPPH (IC50: 4.6 µg/ml) when compared to the positive control used ascorbic acid (IC50: 4.7 µg/ml). This work showed that the synthesized AgNPs from non-cultivated vegetable can find relevance and application in health, drugs, food and environmental science

Application of Boruta algorithms as a robust methodology for performance evaluation of CMIP6 general circulation models for hydro- climatic studies

Regional climate models are essential for climate change projections and hydrologic modelling studies, especially in watersheds that are overly sensitive to changes in climate. Accurate hydrologic model development is a daunting task in data-sparse regions where climate change’s impact on hydrologic and water quality processes is necessary for a well-informed policy decision on adaptation and hazard mitigation strategies. Novel approaches have been evolving that evaluated GCMs with the objective of improved parameterization to limit uncertainty and improve hydrologic model development. However, conclusions drawn should be purpose-driven based on intended usage. This study provides an overview of the state-of-the-art Boruta random forest as a robust methodology in the performance evaluation of GCMs models for hydroclimatic study. Highlights from the assessment indicate that: (1) there is consistency in replicating the three observed climate variables of daily precipitation, maximum and minimum temperature respectively, (2) better temporal correlation (R2 = 0.95) in annual precipitation with a mean bias of 0.638mm/yr.; when compared to symmetrical uncertainty (SU) (R2 = 0.82), and all models ensembles (AME) (R2 = 0.88) with associated biases of 68.19mm/yr. and 10.57mm/yr. respectively. Evaluation of the multi-year climate extreme indices, trends and magnitude reveal that there is a fair representation of basin-scale observed climate extreme events. However, the Boruta random forest approach exhibited a better statistical trend and magnitude of the extreme event in the basin. The findings of the study revealed enhanced GCM dataset evaluation and present a simple and efficient methodology to examine the limitations associated with the selected GCM ensemble for impact study in hydrology

Agricultural wastewater treatment using oil palm waste activated hydrochar for reuse in plant irrigation : synthesis, characterization, and process optimization

The best possible use of natural resources and the large amounts of trash produced by industrial and human activity is necessary for sustainable development. Due to the threat of global climate change and other environmental challenges, waste management systems are changing, leading to more instances of water resource management. The waste generated must be controlled from a sustainability point of view. Typically, the conventional disposal of Agricultural Wastewater (AW) and biomass can be achieved by recycling, reusing, and converting them into a variety of green products. To improve the AW quality for the purposes of environmental sustainability, Sustainable Development Goals (SDGs) 6 and 14, dealing with clean water, sanitation, and life below water, are very important goals. Therefore, the present investigation evaluates the effectiveness of a Bench-scale Activated Sludge Reactor (BASR) system for AW treatment. The BASR was designed to focus on getting the maximum possible utilization out of a biosorbent derived from oil palm waste activated hydrochar (OPAH). This is in accordance with SDG 9, which targets inorganic and organic waste utilization for added value. An experiment was developed using the Response Surface Methodology (RSM). A Hydraulic Retention Time (HRT) of 1–3 days was used in the bioreactor’s setup and operation, and Mixed Liquor Suspended Solids (MLSS) concentrations of 4000–6000 mg/L were used. BASR was fed with AW with initial mean concentrations of 4486 ± 5.63 mg/L and 6649 ± 3.48 for the five-day Biochemical Oxygen Demand (BOD5) and Chemical Oxygen Demand (COD) experiments, respectively. The results obtained showed that maximum reductions of 84.66% and 72.07% were recorded for BOD5 and COD, respectively. Through RSM optimization, the greatest reductions in the amounts of organic materials were achieved with a 2-day HRT and an MLSS dosage of 5000 mg/L. Substrate elimination thresholds were assessed using the first-order, the Grau second-order, and the modified Stover–Kincannon models. The reported observations were found to be perfectly fit by the modified Stover–Kincannon model, with high R2 values of 0.9908 and 0.9931 for BOD5 and COD, respectively. As a result, the model may be used to design the BASR system and forecast how the reactor would behave. The findings from this study suggest that the developed OPAH has promising potential to be applied as eco-friendly material for the removal of BOD5 and COD from AW. Consequently, the study findings additionally possess the ability to address SDGs 6, 9, and 14, in order to fulfil the United Nations (UN) goals through 2030

Evaluation of the physical, chemical, bacteriological and trace metals concentrations in different brands of packaged drinking water

—Human survival largely depends on potable water quality. This study used current analytical procedures and compared with the National Agency for Food and Drug Administration Control (NAFDAC) drinking water specification to evaluate the physio-chemical and microbiological characteristics of fifteen packaged water brands that are available locally. Atomic absorption spectroscopy was used to determine trace metals while instrumental techniques determined the physical and chemical parameters. The evaluation focused on the pH, colour, total dissolved solids, turbidity, dissolved oxygen, fluoride, chloride, iron, zinc, magnesium, calcium, potassium, and sodium. In all the samples examined, chromium, manganese, cadmium, and copper were not detected. However, total bacterial counts were discovered in samples (S1, S2, S3, B1 and B2) with values of 2, 3, 5, 3 and 1 cfu/100 ml, respectively. Packaged water containing these type and quantity of bacteria are not fit for consumption by human beings. It requires the most appropriate techniques for processing

Synthesis, characterization, and performance evaluation of hybrid waste sludge biochar for cod and color removal from agro-industrial effluent

Agro-waste management processes are evolving through the development of novel experimental approaches to understand the mechanisms in reducing their pollution levels efficiently and economically from industrial effluents. Agro-industrial effluent (AIE) from biorefineries that contain high concentrations of COD and color are discharged into the ecosystem. Thus, the AIE from these biorefineries requires treatment prior to discharge. Therefore, the effectiveness of a continuous flow bioreactor system (CFBS) in the treatment of AIE using hybrid waste sludge biochar (HWSB) was investigated. The use of a bioreactor with hydraulic retention time (HRT) of 1–3 days and AIE concentrations of 10–50% was used in experiments based on a statistical design. AIE concentration and HRT were optimized using response surface methodology (RSM) as the process variables. The performance of CFBS was analyzed in terms of COD and color removal. Findings indicated 76.52% and 66.97% reduction in COD and color, respectively. During biokinetic studies, the modified Stover models were found to be perfectly suited for the observed measurements with R2 values 0.9741 attained for COD. Maximum contaminants elimination was attained at 30% AIE and 2-day HRT. Thus, this study proves that the HWSB made from biomass waste can potentially help preserve nonrenewable resources and promote zero-waste attainment and principles of circular economy

Comparative analysis of the use of organic and inorganic fertilizers among yam farmers in Shiroro local government area of Niger state, Nigeria

The broad objective of the study is to comparatively analyse the use of organic and inorganic fertilizers among yam farmers. The specific objectives are to determine farmers preference for the use of organic and inorganic fertilizers , their average yam yields per hectare and the annual income realized from the sales of yam. It also include the examination of various factors militating against the use of both organic and inorganic fertilizers .To achieve this, the study was conducted in Shiroro Local Government Area of Niger State, Nigeria.The methodology involved a stepwise random sampling of 10 wards, 19 villages and purposive sampling of 131 yam farmers. Primary data were collected with the aid of Interview Schedule that was validated by experts and tested for reliability using Test- retest method ( r = 0.83). Descriptive and Inferential statistics were used to analyse data collected for the study. Hypotheses were tested at 5% significant level. Results showed that 40.5% and 59.5% of the farmers preferred the use of organic and inorganic fertilizers respectively. Findings also indicated that there was no significant difference between annual yam yields per hectare, using organic and inorganic fertilizers. However, the study confirmed a significant difference between the income realized from sales of yam by the farmers. This might be connected to different marketing strategies being adopted by individual farmer. It is recommended that Extension Agents (EAs) should encourage farmers to adopt the use of organic fertilizers with a view to complementing the use of inorganic fertilizers which were considered very expensive and not readily available by the yam farmers.Key words: Organic fertilizer, Inorganic fertilizer, Yield, Income, Soil nutrients and Ya

Integrated framework for hydrologic modelling in data-sparse watersheds and climate change impact on projected green and blue water sustainability

Climate and hydrologic hazards threaten the distribution of watersheds’ water resources in time and space, necessitating planning for sustainable resilience and adaptation. Hydrologic modelling has emerged as a potential solution for understanding watershed responses to projected climate change and a prediction model that can deliver actionable information is necessary, although it requires basin-scale observations to calibrate the model to reliably predict basin-scale water resources hazards. Such luxury is not always tenable in watersheds with inadequate ground-based observation. However, the availability of satellite-based data of hydrologic fluxes and states, coupled with a machine learning feature selection and data refinement process has made integrated water balance modelling widely regarded as a viable alternative for improving the performance and capability of watershed modelling processes in data-sparse regions. This study develops a convincing framework by integrating machine learning-based feature selection and a process-based hydrologic model to calibrate sufficiently, accurate behavioural solutions for all model responses using satellite evapotranspiration data. The framework was applied to four subbasins that form the larger Lake Chad basin with distinct morphological features. The model results were used to assess the dynamic changes in projected blue and green water resource sustainability in response to climate change in one of the subbasins. Study findings indicate that hydrologic fluxes can be simulated accurately with varying degrees of acceptability, irrespective of the watershed morphological properties although there are significant trade-offs in parameter sensitivity. While green water is the dominant freshwater component across the basin relative to blue water, climate change may be a significant factor in the spatial and temporal changes of projected green water sustainability status. However, the combination of socioeconomic drivers and climate change may significantly impact the projected blue water sustainability status across the basin. Projected changes in green and blue water sustainability status have shown that more than 50% of the watershed will be ecologically fragile and identified freshwater geographic sustainability hotspots may be beyond restoration without adequate long-term river basin water resources plans

Application andUniversiti Teknologi PETRONAS circular economy prospects of palm oil waste for eco-friendly asphalt pavement industry: A review

Summary: During the production of palm oil, a significant amount of waste is generated. However, because of inefficient handling and utilization, these wastes are becoming a larger issue. As a result, one initiative is to use these wastes in the pavement industry as sustainable materials. However, there is still a lack of understanding about the wider incorporation of palm oil waste in asphalt pavement and its performance. This study examines existing literature on the use of various wastes in the pavement industry, including palm oil clinker (POC), palm oil fibre (POF), palm kernel shell (PKS), and palm oil fuel ash (POFA). As a result, this paper presents a systematic review and scientometric investigation of related study publications on many uses of palm oil waste in the asphalt pavement industry and its performance from 2009 to 2022. The VOSviewer application was used to conduct the scientometric study analysis. The relationship between interactions detected in co-authored country studies cited sources of co-citation, and the keyword of the co-occurrence and publication source enabled the identification of the research gap. According to the systematic literature review, 40%–60% POC can be used to fine aggregate for optimal performance, while 0–100% PKS can be used to replace coarse aggregate. In addition, 50%–80% POFA or POC fine (POCF) can be used as a filler replacement, 5%–8% POCF or POFA as a bitumen modifier, and 0.3% POF as a stabilizing additive. Furthermore, the study demonstrates that the safety of utilizing wastes with more than 50% CO2 emissions can be curtailed with minimal heavy metal leaching and radioactivity levels. The scientometric analysis may encourage researchers to seek out gaps in the literature that will aid in the long-term, multifaceted use of palm oil wastes in the asphalt pavement industry. Furthermore, the study recommends employing and researching the enormous potential of using palm oil waste in the pavement sectors because they are more sustainable and have better performance. However, there are some barriers to using palm oil waste in the asphalt pavement industry, such as a lack of design standards and guidelines, inefficient raw material processing conversion facilities, and large-scale production equipment

Modeling and optimization of asphalt content, waste palm oil clinker powder and waste rice straw ash for sustainable asphalt paving employing response surface methodology: A pilot study

Waste management is becoming increasingly important around the world, and incorporating agro-waste into the pavement industry represents a promising strategy for achieving sustainability while improving mixture properties. In this study, we optimize and determine the optimum asphalt binder content of asphalt concrete mixtures modified with waste palm oil clinker powder (WPOCP) and waste rice straw ash (WRSA) to improve their engineering properties. To optimize the interactions between three independent variables (asphalt binder, WPOCP, and WRSA content) on mixture bulk unit weight (BUW), void in the total mix (VTM), Marshall stability, and flow values, the Marshall mix design approach and response surface methodology (RSM) with a Box-Behnken design were used. WPOCP samples containing 2%, 4%, 6%, and 8% by weight of asphalt mixtures were prepared, as were WRSA samples containing 25%, 50%, 75%, and 100% by weight of filler, with asphalt binder content ranging from 4 to 6% by weight of the mix. The statistical model results show that all responses were significant, with high coefficients of correlation (R2) of 0.9840, 0.9971, 0.9920, and 0.9891 for the BUW, VTM, Marshall stability, and flow, respectively. Individual effects of the input variables and synergistic interactions between the three variables were observed to influence all of the responses. Numerical optimization produced optimum WPOCP, WRSA, and asphalt content values of 8%, 74%, and 5%, respectively. The mean error for all responses was less than 5%, indicating that predicted values agree well with experimental data and that generated models accurately reflect experimental results. Based on the findings of the study, it can be concluded that RSM is an effective method for determining the optimal asphalt binder and modifier content in asphalt mixtures. It enables the identification of the most important variables influencing the response of the asphalt mixture and enables mixture optimization for improved performance. Furthermore, incorporating WPOCP and WRSA into asphalt mixtures was found to improve both volumetric and Marshall properties, resulting in a more sustainable approach in the pavement industry