Agricultural drainage water sodium removal by biochar

Document Type : Research/Original/Regular Article

Authors

1 Ph.D. Student, Department of Water Engineering, Faculty of Agriculture, Lorestan University, KhoramAbad, Iran

2 Associate Professor, Department of Water Engineering, Faculty of Agriculture, Lorestan University, KhoramAbad, Iran

3 Associate Professor, Department of Water Engineering, Faculty of Agriculture, Shahrekord University, Shahrekord, Iran

4 Assistant Professor, Department of Water Engineering, Faculty of Agriculture, Lorestan University, KhoramAbad, Iran

Abstract

 Introduction
The increased fresh-water demand due to the population growth will cause the pressure on water resources to increase in the future causing the water supply through saline and unconventional water to become a serious issue, especially in areas facing water scarcity. As reuse of the agricultural wastewater reduces the pressure on water resources and improves environmental conditions, and some field wastewater is rich in sodium, this research has studied the sodium removability by sugarcane bagasse sorbents. agriculture is the greatest water consumer in the world where saline water not only reduces the products but also destroys the soil structure and damages the environment. Wastewater desalination and its reuse is a relatively new approach in the water industry that solves saline-water problems through various methods, but it is uneconomical due to high equipment costs and energy consumption, especially in agriculture where water consumption and costs are much higher. Therefore, inexpensive primary saline-water modification methods can reduce desalination costs. To remove pollutants, various studies have used different adsorbents such as biochar, activated carbon, zeolite, and resin among which biochar can effectively remove pollutants from aquatic environments because it is an effective, inexpensive, polar, high-porosity adsorbent.
 
Materials and Methods
To produce biochar, this study utilized sugarcane bagasse as the primary biomass. The process involved several steps: 1. Washing and drying: the bagasse was washed multiple times with both ordinary and distilled water, then air-dried to eliminate residual salts. 2. Crushing and drying: it was crushed using an industrial mill and then placed in an oven at 60°C for 24 h to remove excess moisture. 3. Grinding: the dried bagasse was further ground using a small mill. 4. Sieving: the ground bagasse was passed through 60 and 100 mesh sieves in two stages to ensure uniformity. 5. Storage: the processed bagasse was stored in closed containers. The biomass was then converted to biochar using a heat-programmable electric furnace, with the temperature increased at a rate of 5°C.min-1 for even heat distribution. The bagasse was placed in a steel reactor, and nitrogen gas was injected at a constant flow rate to prevent oxidation. The biomass was maintained at 600°C for 2 h, after which the furnace was turned off, and the temperature was gradually reduced to room temperature while continuing the nitrogen gas flow. Each batch consisted of 20 g of biomass, yielding approximately five grams of biochar, resulting in a production efficiency of about 25%. Nano biochar (N-BC) was produced using a planetary ball mill with ceramic cups and bullets, maintaining a bullet-to-biochar weight ratio of 15:1.
 
Results and Discussion
In all treatments, increasing the initial sodium concentration enhances removability, with activated nano biochar showing higher removability under similar conditions compared to non-nano adsorbent. The greatest difference between the two is 179.5% in the treatment with 200 W microwave power for an initial sodium concentration of two g/l. Magnetic-activated nano biochar's removability is 18.8% less than that of activated biochar. The highest reductions are 40.3% and 68% for initial concentrations of four g/l and two g/l in activated non-nano adsorbent, while the lowest are 24.9% and 46.9% for similar concentrations in activated nano adsorbent. This indicates that sodium removability by activated nano adsorbent is less affected by reductions in initial sodium concentration, performing better at low sodium concentrations than the other two adsorbents. The highest reductions are 25.5% and 15.5% at 200W and 700 W powers for activated non-nano adsorbent, and the lowest are 12.9% and 5.8% at similar powers for activated nano adsorbent. This shows that activated nano adsorbent is less affected by non-optimal microwave power. The highest cavities that removed 99.9% of methylene blue were at 900W and 20 minutes. Average correlation coefficients are 0.994 and 0.886 for Langmuir and Freundlich models, respectively, with the former being more consistent with the measured data. The nf parameter is greater than one for all three adsorbents, indicating that the sodium adsorption process is mostly physical. According to the results, Langmuir and Freundlich linear models better match the real values, with the Langmuir model providing more accurate estimates than the Freundlich model.
 
Conclusion
Wastewater desalination and its reuse is a relatively new approach in the water industry that solves saline-water problems through various methods, but it is uneconomical due to high equipment costs and energy consumption, especially in agriculture where water consumption and costs are much higher. Irrigation water salinity is a very serious problem in different parts of the world, especially in arid and semi-arid regions. The present research showed that increasing the initial sodium concentration enhanced sodium removal, with activated nano biochar. In addition, magnetizing nano-adsorbents reduced sodium removal. The highest sodium removal for all three adsorbents (activated non-nano, activated nano, and magnetically activated nano) in the 200 and 400 W treatments was observed at an activator-to-biochar ratio of three. The average correlation coefficients for the Langmuir and Freundlich models were 0.994 and 0.886, respectively, indicating that the Langmuir isothermal model better matched the measured data than the Freundlich model.

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