Muhammad Rasool Al-Kilani

The growing imperative for water conservation contrasts with a paucity of farm‑level data on the concomitant carbon implications of available management options. This work presents such insights from an agricultural compound with 30 operational plots in Mafraq, Jordan using sensor measurements, rainfall data, water use, and energy consumption information. The annual water consumption was 20,000m3 at a carbon footprint of 3.47 kg eCO2/m3. Smart irrigation corresponded to seasonal water savings of 30m3 per single plot of 100m2, based on how often irrigation exceeded soil field capacity. This scales to a net reduction of 5475.6 Kg eCO2 of the water carbon footprint across all plots, accounting also for imbodied carbon (0.09 Kg eCO2/m3) from the electronic and electrical components needed in smart irrigation. Water harvesting showed the least water saving potential (260.6 m3) due to the arid nature of the region, but also the lowest carbon footprint (0.03 Kg eCO2/m3) resulting from transportation to irrigation area. The feasibility of treated wastewater reuse at the site was constrained by the requisite ancillary infrastructure and the embedded carbon footprint of the treatment phase, rendering it less competitive relative to other available strategies. The results demonstrate how on-site techniques can have carbon-viable water savings, but managing crop water demand, like reduced evaporation, could result in much larger water-carbon reductions.

Electrocoagulation (EC) can reduce the organic load of greywater, but increasing treatment intensity may shift environmental burdens toward electricity use and sacrificial-electrode production. This study integrated bench-scale experiments with a screening life-cycle carbon assessment to evaluate aluminum (Al) and iron (Fe) electrodes at applied currents of 0.1, 0.2, and 0.3 A. COD removal, electrolysis energy consumption, and theoretical electrode consumption were evaluated, with climate-change impacts expressed per cubic meter of treated greywater and per kilogram of COD removed. Applied current significantly affected COD removal (p < 0.001), whereas the overall effect of electrode material was not significant. Mean COD removal increased from 68.0 to 95.8% for Al and from 62.0 to 96.2% for Fe between 0.1 and 0.3 A, while specific energy consumption increased from 0.45 to 3.00 and 3.15 kWh/m³, respectively. Under the reference life-cycle scenario, total global warming potential increased from 0.46 to 2.16 kg CO₂e/m³ for Al and from 0.33 to 1.83 kg CO₂e/m³ for Fe. Lower-current operation also produced the lowest impact per kilogram of COD removed. Contribution analysis revealed a shift in environmental hotspots: primary-Al production dominated at 0.1 A, whereas electricity dominated Al at higher currents and Fe under all tested currents. Electricity-carbon-intensity and electrode-production-route scenarios showed that decarbonized electricity substantially reduced impacts at high current, while low-carbon Al and scrap-based steel became increasingly important as electricity-related impacts declined. The results demonstrate that the climate performance of greywater EC depends jointly on treatment target, applied current, electricity supply, and electrode production pathway. The assessment provides early-stage decision support for lower-carbon and more circular EC design but should be validated through pilot-scale operation and an expanded multi-impact life-cycle inventory.

This study investigated a full-scale iron-anode electrocoagulation (EC) system for treating hard-plating wastewater containing manganese (Mn) and fluoride (F–), focusing on performance, scalability, and economic feasibility. This study integrates laboratory optimisation, pilot-scale trials, and industrial processes. The EC system showed removal performance compared to conventional chemical coagulation over a 6-month monitoring period. Energy demand decreased from approximately 3.0 kWh/m³ at laboratory scale to 2.1 kWh/m³ under full-scale conditions, while Mn removal efficiency improved from approximately 88% to over 95%. Fluoride removal increased from 38% to 72%, with effluent concentrations of 1 to 4 mg/L, and Mn was maintained below 1.5 mg/L (over 90% removal), highlighting the importance of pH and Fe(OH)₃ floc availability. Replacing chemical coagulation with EC resulted in cost savings exceeding 50%, mainly through reductions in manpower (50%), sludge production (30–50%), and chemical use (>90%). Monthly sludge volume decreased from over 27,000 kg to approximately 15,000 kg, and chemical consumption from approximately 7,000 kg to less than 500 kg. RSM analysis showed statistically significant models (p < 0.05) for fluoride removal, with R² 84.15%, and manganese removal, with R² 74.07%. These results show Fe anode EC is a robust, scalable, economical alternative for industrial wastewater treatment, reducing chemical use, sludge, and operational costs. Mn removal includes cathode reactions, precipitation due to high pH, and sweep co-precipitation. For F–, the process is adsorption rather than precipitation. Passivation remains a factor for large-scale EC applications.

This study presents an integrated optimization framework for enhancing biogas and methane production through anaerobic digestion, addressing the challenge of identifying optimal operating conditions across multiple interacting parameters. Biochemical methane potential tests were conducted to evaluate the individual effects of four critical operational parameters: temperature, mixing regime, inoculum-to-substrate (I-S) ratio, and chemical oxygen demand load (COD-L). Experimental findings confirmed that thermophilic conditions, mixing once a day, I-S ratio of 1:2, and moderate COD loading consistently delivered the most favorable biogas and methane yields. Kinetic modeling, including the Modified Gompertz and Logistic models, showed strong predictive agreement with experimental data (R² > 0.90), reliably capturing production dynamics across all tested conditions. Polynomial response surface methodology further identified COD-L as the dominant driver of methane yield, with optimal operating conditions falling within moderate temperature and COD-L ranges. This revealed significant nonlinear interactions between parameters. Building on these findings, the Crayfish Optimization algorithm successfully determined global optimal conditions, achieving a maximum biogas production of 0.371 Nm³/kg.VS. These results highlight how combining experimental investigation with predictive modeling and metaheuristic optimization creates a powerful decision-support framework for improving the efficiency and stability of anaerobic digestion systems.

Wastewater treatment by electrocoagulation (EC) using waste‐derived electrodes is a promising solution, but its viability in irrigation reuse remains unclear. This work presents a quantitative framework integrating agrometeorological analysis (FAO‐56 method) and waste information into energy and electrochemical models (Faraday's laws of dissolution) for viability assessment. The circular reuse framework was evaluated at a study site comprising a large institution surrounded by irrigated trees. Onsite experiments showed that electrochemical dosages as low as 20 g/m ³ of aluminum (Al) scrap, or 60 g/m ³ for iron (Fe) scrap, achieved significant removals (75%–94%) of COD, BOD, TSS, and turbidity. Onsite metal waste generation (593 kg/month) could accommodate ~98,000 m ² of surrounding irrigated lands. Crop production capacities of scrap metals (food per scrap) were estimated to reach 23.3 kg/kg using Al scrap. Based on crop water dynamics, theoretical fixed energy demand for renewable energy integration was calculated to be 0.58 kWh/m ³ . Validation of model components revealed that modeling scrap electrode consumption comprised minimal uncertainty compared with other components like crop water demand. The reuse framework shows promising potential as a WEFE nexus application but raised some socioeconomic concerns such as impacts on scrap scavengers' livelihoods. Prior to wider adoption, qualitative assessments are necessary to address heavy metals removal, soil contamination, nutrient content, and microbial indicators. Pilot‐scale experiments are also encouraged to gain improved insights.

Smart irrigation is increasingly promoted for water conservation in agriculture, the largest consumer of freshwater resources. Yet, documentation of how farmers utilize technology for decision support remains limited. This study explored this aspect across 45 farms in different arid regions within Jordan through field visits and interviews. Results showed that technology was mostly obtained through grant funding (69%). Farmers' interest began for various reasons, including COVID-19 curfews and refugee farmers' challenges adapting to the local climate and water scarcity, but water conservation was the primary adoption driver. Different techniques were observed, including soil sensors, meteorological stations, flow meters, water level sensors, and leaf temperature. Meteorological stations were the most common technology (51%), predominantly among grant-funded farms. Self-investing farmers favored irrigation control systems and soil moisture sensors. Only 4.4% of farms had identified decision parameters needed for scientifically informed irrigation scheduling, such as field capacity (FC) and crop coefficients (Kc). The remaining farmers relied on their own heuristic approach and trial and error, slightly increasing or decreasing irrigation based on variables like temperature ranges. Lack of sufficient agronomic knowledge across different stakeholders limited technology utilization to its full potential. National soil and agricultural services did not provide technical support to identify relevant parameters such as FC and Kc. These issues highlight a problematic perception of 'smart irrigation' focused mainly on hardware acquisition. Farmers' persistence in solving technology issues and the availability of funding are significant positive factors. These can be complemented by minor framework revisions in funding, implementation, and extension service structures.