Noha Said

This study investigates the environmental and energy performance of rice straw-based energy pathways in Egypt, combining life cycle assessment (LCA) with supply chain optimization to improve system efficiency. The analysis covers thirteen governorates producing over 4.45 million tons of rice straw annually. It examines the whole supply chain from paddy farming, straw collection, and transport to electricity generation and ash disposal. Total energy consumption was 11,287 TJ, dominated by farming (5673 TJ) and transport (5490 TJ). Greenhouse gas (GHG) emissions were estimated at 12,007.5 million kg CO₂-eq, with significant contributions from farming (5158 million), combustion (3630 million), and natural gas use (3039 million). Gross electricity output was 5525 GWh, yielding a net of 4973 GWh, equivalent to 1116.5 kWh per ton of straw. Scenario analysis highlighted that the optimized multi-hub system, prioritizing Cluster 1 in the Nile Delta, which contributes over 92% of straw production and 4607 GWh of net electricity, achieved a reduction of more than 25% in transport distances and an 18% decrease in diesel consumption and related emissions. Sensitivity analysis further indicated that delivered electricity and GHG intensity are more sensitive to conversion efficiency and transmission and distribution losses than to moderate changes in transport assumptions. In addition to environmental improvements, the optimized scenario indicates potential social co-benefits, including rural employment generation, additional income opportunities for farmers, and improved air quality associated with reduced open-field burning. These outcomes are presented as indicative qualitative insights. Findings confirm rice straw as a strategic, scalable, and sustainable energy resource aligned with Egypt’s Vision 2030 and the UN Sustainable Development Goals (SDGs).

An integrated CaO–Fenton waste-to-resource strategy was evaluated for converting anaerobic sewage digestate into a microbiologically safe and nutritionally functional solution for hydroponic lettuce (Lactuca sativa L.) cultivation. Lime stabilization at dosages up to 35% achieved near-complete pathogen inactivation. Beside substantial decreases in total solids (TS), total volatile solids (TVS), chemical oxygen demand (COD), NH₄⁺ ions, and heavy metals. Subsequent Fenton oxidation using hydrogen peroxide (H2O2) and Fe²⁺ ensured complete microbial sterilization and further improved effluent quality, achieving additional reductions in TS (87.7%), TVS (100%), COD (52.5%), and BOD (52.4%). When applied in a deep-water culture (DWC) hydroponic system, CaO–Fenton-TD supported plant growth with moderate biomass reductions but significantly increased the accumulation of bioactive compounds with potential nutritional value, including ascorbic acid, total carotenoids, total phenolics, and total flavonoids, relative to the control. One-way ANOVA followed by Tukey’s HSD confirmed that both CaO stabilization and Fenton oxidation had significant effects (P ≤ 0.05) on the physicochemical and microbial properties of the digestate. Overall, the results demonstrated the feasibility of using CaO–Fenton-treated anaerobic digestate in hydroponic systems. The proposed approach supports circular economy by promoting nutrient recovery and beneficial reuse of digestate, thereby reducing waste-disposal burdens and dependence on conventional mineral fertilizers.

Despite extensive research on anaerobic digestion (AD), the combined effects of intermittent stirring energy demand and substrate co-digestion on overall energy performance have remained insufficiently explored. This study evaluated the effects of intermittent stirring duration and the AD performance of cattle dung (CD), poultry droppings (PD), rabbit droppings (RD), and their mixtures on methane production and net energy recovery. Experiments were conducted in 30 L laboratory-scale mechanically stirred batch anaerobic digesters operated under mesophilic conditions and intermittent stirring durations of 1, 2, and 3 h/day. Co-digestion clearly outperformed mono-digestion, achieving higher methane yields (up to 223 L/kg VS), improved biodegradability (>90%), methane-rich biogas, and shorter digestion times (18 days). Intermittent stirring duration significantly influenced performance; moderate stirring (2 h/day) was optimal for most binary mixtures, while higher stirring (3 h/day) enhanced methane yield in balanced ternary systems. Optimized co-digestion could reach up to 7.96 MJ/kg VS despite increased mixing energy use. The statistical analyses revealed strong interrelationships among process variables, identifying stirring duration and digestion time as key drivers of methane yield and net energy production. Artificial neural network (ANN) modeling successfully predicted methane production and net energy based on C/N ratio, stirring rate, and waste composition. The optimal ANN showed high accuracy (R=0.99).

This study evaluates the quality and irrigation suitability of drainage water in the Al-Jouf Region, Saudi Arabia, where water scarcity necessitates the reuse of nonconventional resources. Eighteen drainage water samples were analyzed for physicochemical parameters and irrigation indices, including electrical conductivity (EC), sodium percentage (Na⁺%), sodium adsorption ratio (SAR), magnesium hazard (MH), Kelly’s ratio (KR), permeability index (PS), and irrigation water quality index (IWQI). Multivariate statistical tools were applied to identify dominant hydrogeochemical processes. Inverse Distance Weighting (IDW) interpolation in ArcGIS Desktop 10.8 was employed to map significant physicochemical data and irrigation indicators. Results revealed that while EC values indicated low to moderate salinity (0.74–25.2 μS/cm), most samples showed high Na⁺%, SAR, and KR, classifying them as doubtful to unsuitable for irrigation. The IWQI ranged from 84.47 to 1617.87, indicating poor to inferior quality due to evaporation, fertilizer leaching, and sodium accumulation. Furthermore, the results highlight the importance of precise geographic modeling in determining whether drainage water is suitable for long-term agricultural use in arid regions such as Al-Jouf. Sustainable reuse of such drainage water requires freshwater blending, gypsum application, and the cultivation of salt-tolerant crops, aligning with Saudi Vision 2030 objectives for sustainable water management in arid regions.

Anaerobic digestion is an effective technology for converting organic waste into biogas while reducing environmental pollution. This study investigates the impact of co-digesting waste-activated sludge (WAS) with wheat straw, rice straw, and bokashi on biogas production. Nine anaerobic batch reactors were operated under mesophilic conditions (35 °C), incorporating different proportions of bokashi (1% and 2%) along with rice and wheat straw (4%). The results revealed that reactors supplemented with wheat and rice straw exhibited higher biogas production than the control reactor (sludge only). Wheat straw outperformed rice straw in improving biogas yield, total solids (TS) reduction, total volatile solids (TVS) degradation, and chemical oxygen demand (COD) removal. The addition of bokashi enhanced biogas production, confirming its role in accelerating organic matter breakdown. The maximum biogas yield was observed in the reactor containing sludge co-digested with wheat straw and 2% bokashi, which generated three times more biogas than the control. This reactor also exhibited the highest degradation rates of TS (57.83%), TVS (66.37%), and COD (71.53%). Furthermore, pH remained stable within the optimal range across all reactors, ensuring a balanced digestion process. Statistical analysis revealed significant correlations between organic matter degradation (COD, TS, TVS reduction) and biogas production, demonstrating that effective substrate decomposition improves biogas yield. The recurrent neural network (RNN) model was applied to experimental data to predict biogas production. With an exceptionally low root mean square error (RMSE) of 0.0041, R² close to 1, and MAE 0.0117, the model exhibited excellent accuracy and reliability in generating precise predictions.

This study investigates the combined effect of wheat straw particle size and mixing ratio on the anaerobic co-digestion (ACD) of waste activated sludge under mesophilic conditions. Ten batch digesters were tested with varying straw-to-sludge ratios (0–1.5%) and particle sizes (5 cm, 1 cm, and 2 close to 1. These results confirm the potential of integrating agricultural residues into wastewater treatment for renewable energy recovery and emission reduction. This study uniquely integrates mechanical pretreatment of wheat straw with RNN-based modeling to enhance biogas generation and predictive accuracy. It establishes a dual-experimental AI framework for optimizing sludge–straw co-digestion systems. This approach provides a scalable, data-driven solution for sustainable waste-to-energy applications.

This study analyses the potential electricity output from different bio wastes using various energy conversion technologies to enhance the share of renewable energy. Furthermore, it evaluates the carbon emissions mitigated by replacing fossil fuels with bioenergy, contributing to efforts to reduce environmental pollution. The findings reveal that Egypt’s annual biomass waste (BW) could total approximately 80 million tons, with the most significant contributions from agricultural crop residues and municipal solid waste (MSW). MSW incineration and crop residue combustion were found to have the highest power generation compared to other techniques. Additionally, the anaerobic digestion of various biomass types offers the benefits of lower greenhouse gas emissions while still generating significant energy. The electricity generation from different BW sources is approximately 49.14 TWh/year. This energy can be predominantly generated through direct combustion of agricultural crop residues (66%), incineration of MSW (29%), anaerobic digestion of sewage sludge (3%), and animal waste (2%). Furthermore, the reduction in carbon emissions from substituting fossil fuels with bioenergy is estimated at up to 30.47 million tons of CO₂ annually, supporting efforts to mitigate climate change and combat global warming.

Heavy metals, extensively used in various industrial applications, are among the most significant environmental pollutants due to their hazardous effects on human health and other living organisms. Removing these pollutants from the environment is essential. In this study, activated carbon (AC) (Carbon C) was employed to eliminate Pb(II) from water. The optimal removal conditions were determined as follows: a 50 mg dose of activated carbon, an initial Pb(II) concentration of 100 mg/L, pH 4, a temperature of 30 °C, and a contact time of 60 min Under these conditions, activated carbon achieved a Pb(II) removal efficiency of approximately 97.86%. The adsorption data for Pb(II) closely aligned with the 2nd-order kinetic model, and the equilibrium data were effectively described by the Langmuir isotherm equation. The maximum adsorption capacity of Pb(II), as determined by the Langmuir model, was 48.75 mg/g. These methods were successfully applied to remove Pb(II) from various environmental and industrial wastewater samples. To accurately predict the percentage of Pb(II) removal based on parameters such as pollutant type, carbon dosage, pH, initial concentration, temperature, and treatment duration, feed-forward neural networks (FFNNs) were utilized. The FFNN model demonstrated outstanding predictive accuracy, achieving a root mean square error (RMSE) of 0.03 and an R² value of 0.996.

The use of wheat straw as a renewable energy source is essential from both energy production and environmental points of view. It has a great energy potential that can be generated either by combustion or anaerobic digestion. However, there are some limitations during its conversion to energy in both techniques. Therefore, the current study investigated the effect of physical and chemical treatments on the characteristics of wheat straw as fuel for energy applications. Water washing of wheat straw and mixing with KOH solution were applied for physical and chemical treatments. Physical, chemical, and thermal characteristics of wheat straw were investigated before and after the treatments. It was found that the wheat straw has high carbon (44.8%) and volatile contents (87.1%), making it an excellent source for energy production. The physical treatment showed a positive impact on reducing the ash content (by 14.9%) and undesirable compounds, such as K and Cl, which were reduced by 46.4% and 57.0%, respectively. Moreover, it reduced sintering formation through combustion. In contrast, the chemical treatment resulted in 9.3% lignin removal and destroyed the complex lignocellulosic structure, thereby increasing the cellulose accessibility and enhancing the anaerobic digestion process. Therefore, the applied treatments showed attractive options to solve problems related to straw energy generation.