International Journal of Science, Engineering and TechnologyAuthors: S. Aityk, B. Alibi
Abstract: Regions experiencing cold climates, such as Kazakhstan, experience seasonal water shortages; however, these areas have abundant, albeit typically polluted, amounts of frozen precipitation. Approximately 90 percent of river run-off in Kazakhstan occurs during the springtime when snow melts, however much of this run-off evaporates or is un-treated and thus many rural communities are left without adequate access to clean water during the most critical time of year due to low precipitation. The paper presents new technology called SENIMSU which is a cost effective, decentralized technology that utilizes passive solar melting combined with multi-layered biochar filtration and an Arduino based sensor network with machine learning (ML) capabilities for assessing the quality of the treated water in real-time. Biochar is a type of charcoal produced by heating organic materials in the absence of oxygen at high temperatures. The biochar utilized in this study was generated by pyrolyzing agricultural waste at a temperature range of 450° – 500° C. The surface area and pH of the generated biochar were determined. Optimization of filtration parameters including particle size (0.5–2 mm), depth (15–30 cm), and flow rate (1–2.5 L/h) was achieved via Response Surface Methodology with a Box-Behnken experimental design. Simulated polluted snowmelt experiments utilizing the optimized filtration parameters resulted in significant reductions in turbidity (>85–>90%) (NTU of 30 to <5 NTU), TDS (>45–>55%) (ppm of 250 to <120 ppm), and pH stabilization (pH range of 6.4–7.2 to 7.0–7.2) and therefore meet WHO drinking water standards. Additionally, machine learning regression models (R² > 0.85) enabled accurate prediction of filtration efficiencies allowing for real-time optimizations. The estimated cost of the SENIMSU system per household unit will be $45 compared to the $200+ estimated cost for commercial technologies and the use of locally generated biochar will eliminate the need to replace filters. SENIMSU is the first ML-integrated snow treatment system designed specifically for the climate conditions found in Central Asia and directly addresses SDG 6.1 (universal access to safe drinking water) and 6.3 (water quality improvement). Each unit has the capability to produce between 20 and 60 liters of clean water per day for a family of four to six people during the most critical time of the year when they require it (snow-melt period). Preliminary field testing conducted in the rural Akmola region of Kazakhstan reported that 92% of users accepted the use of SENIMSU systems and successfully operated them in temperatures below -15°C. FTIR analysis verified the adsorption mechanisms, whereas the decentralized nature of SENIMSU enables its replication across the 2.5 million rural Kazakhs who currently lack dependable access to clean water. This provides a scalable and locally sustainable means for communities located in cold climates around the world to address similar water security issues.
DOI: https://doi.org/10.5281/zenodo.19511933
