Mechanical impact evaluation of natural fibres with LDPE plastic composites : waste management in perspective

DATA AVAILABILITY : Data will be made available on request.There is increased enthusiasm towards the use of natural hair fibers for plastic reinforcement due to their toughness and light weight. In this research, low density polyethylene (LDPE) was reinforced using 0.25 ​M NaOH treated cow tail, human and sheep hair fibers at 2, 4, 6 and 8% concentration respectively prior to injection moulding. The average densities, diameters and lengths of hair fibres were assessed The results obtained from the analysis of reinforced LDPE composites indicated that cow tail hair gave the highest average density and diameter. Sheep hair had the highest length after grinding. The study also analyzed the ultimate tensile strength and modulus, flexural strength and modulus, elongation, impact and hardness test on the polymer and their composites as well as the morphology and statistical analysis of the composite. This study indicated that human hair LDPE composites achieved highest flexural strength, flexural modulus, ultimate tensile strength and tensile modulus at 8% fibre loading whereas elongation at break and hardness were at 4% fibre loading while impact strength was at 2%. The cow tail hair LDPE composite gave the best impact strength at 8% fibre loading and sheep hair at 6%. The SEM results showed no serious manufacturing defects on the composites. The analysis of variance indicated that only the means of the composites’ flexural properties were statistically significant. This study shows that short animal hair fibres could be effectively used to reinforced LDPE, and therefore suggest an alternative waste management strategy of these natural fibres that are currently viewed as environmental nuisance in the study area.https://www.sciencedirect.com/journal/current-research-in-green-and-sustainable-chemistryhj2023Future Afric

Geospatial-based analysis for soil erosion susceptibility evaluation : application of a hybrid decision model

DATA AVAILABILITY : Data will be made available on request.Erosion hazard is a major environmental change in developing countries and therefore necessitates investigations for effective erosion control measures. This study is hinged on the numerous advantages of a hybrid Multi-Criteria Decision Model (MCDM) to assess erosion vulnerability using remote-sensed data and the application of Geographical Information System (GIS). Nine risk factors of erosion were selected for this study and their thematic maps were utilized to produce a spatial distribution of erosion hazard in the state. An integrated IVFRN–DEMATEL–ANP model was used to investigate the interrelationships between the risk factors and also obtain their final weights. The assessment model identified Rainfall, Erosivity Index, Stream Power Index, Sediment Transport Index, Topographic Wetness Index, and Soil as the most influential factors of erosion in the study area. The weighted linear combination method was used to integrate the risk factors to produce the spatial distribution of erosion vulnerability model. The method was validated using Anambra State of Nigeria. The findings from the study revealed that Anambra State is vulnerable to erosion hazard with 45% of the state lying between Very High and Medium vulnerable zones. A good predictive model performance of 89.7% was obtained using the AUC-ROC method. The feasibility of integrating the IVFRN, DEMATEL, and ANP models as an assessment model for mapping erosion vulnerability has been determined in this study, and this is vital in managing the impact of erosion hazards globally. The model’s identification of hydrological and topographical factors as major causes of erosion hazard emphasizes the importance of critical analysis of risk factors as done in this study for effective management of erosion. This study is a veritable tool for implementation of erosion mitigation measures.https://link.springer.com/journal/40808hj2023Future Afric

Application of synthesized fish scale chito-protein (FSC) for the treatment of abattoir wastewater : coagulation-flocculation kinetics and equilibrium modeling

This work explores the use of chito-protein synthesized from fish scale as a bio-coagulant in Abattoir wastewater (AW) treatment. The effect of settling time, pH, adsorbent dosage, and temperature of coagulation on Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), turbidity, and Color from the AW sample were studied. The kinetic study was carried out using four process equilibrium models which are Langmuir, Freundlich, Frumkin, and Tempkin to investigate the mechanism of the reaction. SEM and FTIR spectral analyses were used to evaluate the surface morphology and chemical composition of the bio-coagulant. A low pH, 3 g of dosage in 250 mL vessel, settling period of 30 to 35 min, and temperatures of 323 K for all parameters resulted in the most efficient pollutant elimination. Turbidity, however, had an optimal temperature of 313 K. The result of the study shows that Langmuir model provided the best fit from the equilibrium models compared to Freundlich, Frumkin, and Temkin’s models. The experimental data suited the Elovich, Pseudo-first, and Second order kinetic models’ analysis and the high values of the regression coefficient of 0.90 supported the idea of perikinetic as the governing mechanism of coag-flocculation in the study. It can be inferred from this study that fish scale as a bio- coagulant provides a significant resource for abattoir wastewater treatment.http://www.elsevier.com/locate/sciafam2023Future Afric

Groundwater vulnerability to pollution assessment: an application of geospatial techniques and integrated IRN-DEMATEL-ANP decision model

This study evaluated the susceptibility to groundwater pollution using a modified DRASTIC model. A novel hybrid multi-criteria decision-making (MCDM) model integrating Interval Rough Numbers (IRN), Decision Making Trial and Evaluation Laboratory (DEMATEL), and Analytical Network Process (ANP) was used to investigate the interrelationships between critical hydrogeologic factors (and determine their relative weights) via a novel vulnerability index based on the DRASTIC model. The flexibility of GIS in handling spatial data was employed to delineate thematic map layers of the hydrogeologic factors and to improve the DRASTIC model. The hybrid MCDM model results show that Net Recharge (a key hydrogeologic factor) had the highest priority with a weight of 0.1986. In contrast, the Topography factor had the least priority, with a weight of 0.0497. A case study validated the hybrid model using Anambra State, Nigeria. The resultant vulnerability map shows that 12.98 % of the study area falls into a very high vulnerability class, 31.90 % falls into a high vulnerability, 23.52 % falls into the average vulnerability, 21.75 % falls into a low vulnerability, and 9.85 % falls into very low vulnerability classes, respectively. In addition, nitrate concentration was used to evaluate the degree of groundwater pollution. Based on observed nitrate concentration, the modified DRASTIC model was validated and compared to the traditional DRASTIC model; interestingly, the spatial model of the modified DRASTIC model performed better. This study is thus critical for environmental monitoring and implementing appropriate management interventions to protect groundwater resources against indiscriminate sources of pollution.</p

Supplementary information files for Groundwater vulnerability to pollution assessment: an application of geospatial techniques and integrated IRN-DEMATEL-ANP decision model

Supplementary files for article Groundwater vulnerability to pollution assessment: an application of geospatial techniques and integrated IRN-DEMATEL-ANP decision model This study evaluated the susceptibility to groundwater pollution using a modified DRASTIC model. A novel hybrid multi-criteria decision-making (MCDM) model integrating Interval Rough Numbers (IRN), Decision Making Trial and Evaluation Laboratory (DEMATEL), and Analytical Network Process (ANP) was used to investigate the interrelationships between critical hydrogeologic factors (and determine their relative weights) via a novel vulnerability index based on the DRASTIC model. The flexibility of GIS in handling spatial data was employed to delineate thematic map layers of the hydrogeologic factors and to improve the DRASTIC model. The hybrid MCDM model results show that Net Recharge (a key hydrogeologic factor) had the highest priority with a weight of 0.1986. In contrast, the Topography factor had the least priority, with a weight of 0.0497. A case study validated the hybrid model using Anambra State, Nigeria. The resultant vulnerability map shows that 12.98 % of the study area falls into a very high vulnerability class, 31.90 % falls into a high vulnerability, 23.52 % falls into the average vulnerability, 21.75 % falls into a low vulnerability, and 9.85 % falls into very low vulnerability classes, respectively. In addition, nitrate concentration was used to evaluate the degree of groundwater pollution. Based on observed nitrate concentration, the modified DRASTIC model was validated and compared to the traditional DRASTIC model; interestingly, the spatial model of the modified DRASTIC model performed better. This study is thus critical for environmental monitoring and implementing appropriate management interventions to protect groundwater resources against indiscriminate sources of pollution. </p

Groundwater vulnerability to pollution assessment: an application of geospatial techniques and integrated IRN-DEMATEL-ANP decision model

This study evaluated the susceptibility to groundwater pollution using a modified DRASTIC model. A novel hybrid multi-criteria decision-making (MCDM) model integrating Interval Rough Numbers (IRN), Decision Making Trial and Evaluation Laboratory (DEMATEL), and Analytical Network Process (ANP) was used to investigate the interrelationships between critical hydrogeologic factors (and determine their relative weights) via a novel vulnerability index based on the DRASTIC model. The flexibility of GIS in handling spatial data was employed to delineate thematic map layers of the hydrogeologic factors and to improve the DRASTIC model. The hybrid MCDM model results show that Net Recharge (a key hydrogeologic factor) had the highest priority with a weight of 0.1986. In contrast, the Topography factor had the least priority, with a weight of 0.0497. A case study validated the hybrid model using Anambra State, Nigeria. The resultant vulnerability map shows that 12.98 % of the study area falls into a very high vulnerability class, 31.90 % falls into a high vulnerability, 23.52 % falls into the average vulnerability, 21.75 % falls into a low vulnerability, and 9.85 % falls into very low vulnerability classes, respectively. In addition, nitrate concentration was used to evaluate the degree of groundwater pollution. Based on observed nitrate concentration, the modified DRASTIC model was validated and compared to the traditional DRASTIC model; interestingly, the spatial model of the modified DRASTIC model performed better. This study is thus critical for environmental monitoring and implementing appropriate management interventions to protect groundwater resources against indiscriminate sources of pollution.</p