Potential energy production from organic waste and its environmental and economic impacts at a tertiary institution in Palestine

Municipal solid waste (MSW) is one of the most well-known biomass resources that can be utilized to produce renewable energy. Numerous countries are plagued by the proliferation of waste, particularly organic waste that can be utilized for energy recovery. Palestine suffers from inefficient solid waste management, and only recently have a few projects focused on bioenergy production been implemented. Throughout the years, the city of Tulkarm experiences power outages which cause a challenge to the Palestine Technical University-Kadoorie campus in Tulkarm. Thus, the possibility of energy recovery from the organic portion in Palestine Technical University-Kadoorie was evaluated. The analysis of an economic impact included discussions of a number of economic aspects, including Levelized cost of energy, internal rate of return, present worth, annual worth, and payback period. On the other hand, a carbon dioxide savings analysis and gas emission were evaluated. The outcomes of the energy optimization demonstrated that the suggested system could supply the institution with an average of roughly 7 MWh of electrical energy. According to the economic study, this project offers 0.25 million dollars in present value, 0.144 million dollars in annual value, a 13 percent internal rate of return, a payback period of 6 years, and a levelized cost of energy of 0.11 dollars for each kWh generated. Additionally, the environmental assessment revealed that this system might reduce CO₂ emissions by around 8,343,778 tons. For effective waste management, energy recovery, and emission reduction, it is advised to implement anaerobic digestion technology.     

Critical review for the quantification of leachate production: Evaluation example for the “Oum Azza” public landfill in Rabat city,Morocco

The estimation of leachate quantities produced in landfills is necessary to dimension the treatment plants allowing to reduce the polluting load of these effluents and consequently avoid their negative impacts on the environment. Different leachate quantification methods were used in this study to assess the leachate volume produced at the Oum Azza landfill. The water balance method give comparable estimations of leachate production to the Ouled Berjal landfill ratio. The first method showed average values between 487 and 495 m³/day for 2015, 2018, and 2019, and at the same time, the second method gave values between 470 and 477 m³/day for the same years. In contrast, the World Bank ratio showed high values that vary between 2260 and 2295 m³/day for 2015, 2018, and 2019. The on-site data and the statistical analysis showed us that the World Bank ratio is not adapted for the estimation of the leachates produced in Oum Azza landfill, while the water balance and the ratio of Ouled Berjal landfill allowed to give comparable results to reality.     

Effect of gervital in attenuating hepatotoxicity caused by methotrexate or azathioprine in adult albino rats

Environmental Science and Pollution Research - Methotrexate (MTX) and azathioprine (AZA) are chemotherapeutic, antimetabolic, and immunosuppressive agents with substantial risks such as oxidative...     

Property-performance relationship of core-shell structured black TiO2 photocatalyst for environmental remediation

● Properties and performance relationship of CSBT photocatalyst were investigated. ● Properties of CSBT were controlled by simply manipulating glycerol content. ● Performance was linked to semiconducting and physicochemical properties. ● CSBT (W:G ratio 9:1) had better performance with lower energy consumption. ● Phenols were reduced by 48.30% at a cost of $2.4127 per unit volume of effluent. Understanding the relationship between the properties and performance of black titanium dioxide with core-shell structure (CSBT) for environmental remediation is crucial for improving its prospects in practical applications. In this study, CSBT was synthesized using a glycerol-assisted sol-gel approach. The effect of different water-to-glycerol ratios (W:G = 1:0, 9:1, 2:1, and 1:1) on the semiconducting and physicochemical properties of CSBT was investigated. The effectiveness of CSBT in removing phenolic compounds (PHCs) from real agro-industrial wastewater was studied. The CSBT synthesized with a W:G ratio of 9:1 has optimized properties for enhanced removal of PHCs. It has a distinct core-shell structure and an appropriate amount of Ti³⁺ cations (11.18%), which play a crucial role in enhancing the performance of CSBT. When exposed to visible light, the CSBT performed better: 48.30% of PHCs were removed after 180 min, compared to only 21.95% for TiO₂ without core-shell structure. The CSBT consumed only 45.5235 kWh/m³ of electrical energy per order of magnitude and cost $2.4127 per unit volume of treated agro-industrial wastewater. Under the conditions tested, the CSBT demonstrated exceptional stability and reusability. The CSBT showed promising results in the treatment of phenols-containing agro-industrial wastewater.     

High degree of polyandry in Apis dorsata queens detected by DNA microsatellite variability

Workers of six colonies of the giant honeybee Apis dorsata from Sabah, Malaysia (five colonies) and Java (one colony) were genotyped using single locus DNA fingerprinting. The colonies from Sabah nested in colony aggregations of 5 and 28 nests respectively on two trees. Three DNA microsatellite loci (A14, A76, A88) with a total of 27 alleles provided sufficient genetic variability to classify the workers into distinct sub-families revealing the degree of polyandry of the queens. Queens mated on average with 30.17 ± 5.98 drones with a range from 19 to 53. The average effective number of matings per queen was 25.56 ± 11.63. In the total sample of 192 workers, 22 individuals were found that were not offspring of the colony's queen. Three of these were potentially drifted offspring workers from genotyped queens of colonies nesting on the same tree.     

Electrochemical degradation of the dye indigo carmine at boron-doped diamond anode for wastewaters remediation

Here we demonstrate that anodic oxidation with a boron-doped diamond (BDD) electrode can be applied to the remediation of wastewaters containing indigo carmine. This environmentally friendly method decontaminates completely acid and alkaline aqueous solutions of this dye. The degradation rate increases with increasing current and dye concentration. Indigo carmine is more rapidly removed in alkaline than in acid medium, but its kinetics does not follow a defined reaction order. Isatin 5-sulfonic acid is the main aromatic product formed. Oxalic and oxamic acids are generated as ultimate carboxylic acids. The nitrogen of the dye is converted into NH₄ ⁺ and NO₃ ⁻.     

The role of some feed additives in fish fed on diets contaminated with cadmium

The decline of cadmium pollution in fish farms is needed by any adequate method. The present study was designed to explore the effect of dietary cadmium contamination and its amelioration by using dietary clay, probiotic (Bactocell®), vitamin C, and vitamin E supplementation in Nile tilapia fish diet on growth rate, feed efficiency, blood components, and cadmium residues. Fish were separated into 15 groups, each group of fish was stocked into three aquaria and each contains 20 fishes. The fish of the first five groups were fed the basal diet, the second five groups were fed the basal diet contaminated with 25 mg cadmium/kg, and the third five groups were fed the same diet contaminated with 50 mg cadmium/kg. Within each dietary cadmium level, the first group was fed the diet without any supplementation, the second was fed the diet supplemented with natural clay (bentonite) at level 3%, the third group was fed the diet supplemented with 1 g Bactocell®/kg, the fourth group was fed the diet supplemented 50 mg vitamin E/kg, and the fifth group was fed the diet supplemented with 100 mg vitamin C/kg. Live body weight, daily body weight gain, and feed intake of Nile tilapia decreased significantly (P < 0.001) with increasing dietary cadmium level, while feed conversion was impaired. Fish group fed on diets contaminated with 50 mg cadmium/kg recorded the lowest live body weight and weight gain. Serum total protein and albumin concentration significantly (P < 0.001) decreased, while serum creatinine, AST, and ALT significantly (P < 0.001) increased with increasing cadmium level in fish diets. Blood hemoglobin and total erythrocyte (RBCs) significantly (P < 0.001 or 0.05) decreased with cadmium contamination in fish diets, while leukocytes were insignificantly affected. Body cadmium residues increased significantly (P < 0.001) by increasing cadmium level in fish diets. Live body weight, daily body weight gain, and feed intake of Nile tilapia increased significantly (P < 0.001) with feed additive supplementation in diets, also while feed conversion improved. Fish group fed on diets supplemented with probiotic Bactocell® or natural clay recorded higher body weight and gain rate than the other experimental groups. Serum total protein, blood hemoglobin, and total erythrocyte increased, while urea-N, creatinine, ALT, AST, and leukocytes decreased as affected with the feed additive supplementation. Feed additive supplementation in fish diets significantly (P < 0.001) decreased cadmium residues in fish bodies. Irrespective of dietary cadmium level, feed additive supplementation in fish diet improved the growth rate and decreased the concentrations of serum creatinine and ALT. The obtained results indicated that feed additive supplementation could modify the function of the kidney and liver in fish exposed to the cadmium toxicity.     

Extreme learning machines: a new approach for modeling dissolved oxygen (DO) concentration with and without water quality variables as predictors

In this paper, several extreme learning machine (ELM) models, including standard extreme learning machine with sigmoid activation function (S-ELM), extreme learning machine with radial basis activation function (R-ELM), online sequential extreme learning machine (OS-ELM), and optimally pruned extreme learning machine (OP-ELM), are newly applied for predicting dissolved oxygen concentration with and without water quality variables as predictors. Firstly, using data from eight United States Geological Survey (USGS) stations located in different rivers basins, USA, the S-ELM, R-ELM, OS-ELM, and OP-ELM were compared against the measured dissolved oxygen (DO) using four water quality variables, water temperature, specific conductance, turbidity, and pH, as predictors. For each station, we used data measured at an hourly time step for a period of 4 years. The dataset was divided into a training set (70%) and a validation set (30%). We selected several combinations of the water quality variables as inputs for each ELM model and six different scenarios were compared. Secondly, an attempt was made to predict DO concentration without water quality variables. To achieve this goal, we used the year numbers, 2008, 2009, etc., month numbers from (1) to (12), day numbers from (1) to (31) and hour numbers from (00:00) to (24:00) as predictors. Thirdly, the best ELM models were trained using validation dataset and tested with the training dataset. The performances of the four ELM models were evaluated using four statistical indices: the coefficient of correlation (R), the Nash-Sutcliffe efficiency (NSE), the root mean squared error (RMSE), and the mean absolute error (MAE). Results obtained from the eight stations indicated that: (i) the best results were obtained by the S-ELM, R-ELM, OS-ELM, and OP-ELM models having four water quality variables as predictors; (ii) out of eight stations, the OP-ELM performed better than the other three ELM models at seven stations while the R-ELM performed the best at one station. The OS-ELM models performed the worst and provided the lowest accuracy; (iii) for predicting DO without water quality variables, the R-ELM performed the best at seven stations followed by the S-ELM in the second place and the OP-ELM performed the worst with low accuracy; (iv) for the final application where training ELM models with validation dataset and testing with training dataset, the OP-ELM provided the best accuracy using water quality variables and the R-ELM performed the best at all eight stations without water quality variables. Fourthly, and finally, we compared the results obtained from different ELM models with those obtained using multiple linear regression (MLR) and multilayer perceptron neural network (MLPNN). Results obtained using MLPNN and MLR models reveal that: (i) using water quality variables as predictors, the MLR performed the worst and provided the lowest accuracy in all stations; (ii) MLPNN was ranked in the second place at two stations, in the third place at four stations, and finally, in the fourth place at two stations, (iii) for predicting DO without water quality variables, MLPNN is ranked in the second place at five stations, and ranked in the third, fourth, and fifth places in the remaining three stations, while MLR was ranked in the last place with very low accuracy at all stations. Overall, the results suggest that the ELM is more effective than the MLPNN and MLR for modelling DO concentration in river ecosystems.     

An analysis of spatial and temporal properties of daily sulfate, nitrate and chloride concentrations at UK urban and rural sites

Daily measurements of sulfate, nitrate and chloride in PM(10) have been made at three geographically separated UK sites over a three year period. Chloride shows a clear seasonal pattern with highest concentrations in winter, whilst sulfate and nitrate both show highest concentrations in the spring, apparently related to weather patterns. Spatial variability of both sulfate and nitrate is low in comparison to temporal variations, with high correlations of both species between all three sites, London (North Kensington), Harwell and Belfast, despite a geographic separation of 510 km. Both SO/SO(2) and NO/NO(x) ratios are considerably higher in summer than winter, reflecting a greater oxidising capacity of the atmosphere. SO(4)(2-)/NO(3)(-) ratios are higher in summer than winter, suggesting that aqueous phase oxidation of SO(2), expected to be most important in the winter months is not appreciably influencing production of sulfate aerosol, although greater dissociation of ammonium nitrate in summer may also play a role. Regression of concentrations at London, North Kensington with those from the proximate rural site of Harwell is interpreted as showing a similar effect of regional transport at the two sites and a small influence of local formation in the urban atmosphere or primary emissions, averaging 0.46 microg m(-3) of nitrate and 0.22 microg m(-3) of sulfate.