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Insight into the Adsorption of Nutrients from Water by Pyrogenic Carbonaceous Adsorbents Using a Bootstrap Method and Machine Learning
https://orcid.org/0000-0001-9675-0655
Herein, findings from 98 research papers [52 biochar (BC) and 46 activated carbon (AC) papers] were analyzed using a bootstrap method and a 95% confidence interval (CI) to provide insights into nutrient adsorption. The results indicated the solution temperature, pore volume, specific surface area, and pyrolysis temperature were correlated significantly to the maximum adsorption capacity (Q m), achieving r values of 0.37, 0.23, 0.16, and 0.14, respectively. A statistically significant difference was witnessed for nitrate Q m between AC and BC with median values of 17.64 and 0.51 mg/g, respectively, and CIs of 11.01–27.56 and 0.39–0.82 mg/g, respectively. In contrast, the difference in Q m between AC and BC for phosphate and ammonium contained a high probability of chance. On average, engineered biochar achieved higher Q m values of ammonium and phosphate (12.13 and 24.73 mg/g, respectively) in comparison with that of the original biochar. However, there is a good probability of no difference in nitrate between the two, albeit greater nitrate adsorption on the modified biochar with a mean Q m of 3.03 mg/g. The tuned Cubist estimated equilibrium adsorption capacity with an R 2 of ∼0.90–0.91. The median and bootstrap 95% CI can be used as an average standard for designing adsorbate–adsorbent systems.
This work provides insights into the nutrient adsorption on pyrogenic carbonaceous adsorbents and an average standard for designing adsorbate−adsorbent systems using a bootstrap method and machine learning.
Insight into the Adsorption of Nutrients from Water by Pyrogenic Carbonaceous Adsorbents Using a Bootstrap Method and Machine Learning
https://orcid.org/0000-0001-9675-0655
Herein, findings from 98 research papers [52 biochar (BC) and 46 activated carbon (AC) papers] were analyzed using a bootstrap method and a 95% confidence interval (CI) to provide insights into nutrient adsorption. The results indicated the solution temperature, pore volume, specific surface area, and pyrolysis temperature were correlated significantly to the maximum adsorption capacity (Q m), achieving r values of 0.37, 0.23, 0.16, and 0.14, respectively. A statistically significant difference was witnessed for nitrate Q m between AC and BC with median values of 17.64 and 0.51 mg/g, respectively, and CIs of 11.01–27.56 and 0.39–0.82 mg/g, respectively. In contrast, the difference in Q m between AC and BC for phosphate and ammonium contained a high probability of chance. On average, engineered biochar achieved higher Q m values of ammonium and phosphate (12.13 and 24.73 mg/g, respectively) in comparison with that of the original biochar. However, there is a good probability of no difference in nitrate between the two, albeit greater nitrate adsorption on the modified biochar with a mean Q m of 3.03 mg/g. The tuned Cubist estimated equilibrium adsorption capacity with an R 2 of ∼0.90–0.91. The median and bootstrap 95% CI can be used as an average standard for designing adsorbate–adsorbent systems.
This work provides insights into the nutrient adsorption on pyrogenic carbonaceous adsorbents and an average standard for designing adsorbate−adsorbent systems using a bootstrap method and machine learning.
Insight into the Adsorption of Nutrients from Water by Pyrogenic Carbonaceous Adsorbents Using a Bootstrap Method and Machine Learning
https://orcid.org/0000-0001-9675-0655
Herein, findings from 98 research papers [52 biochar (BC) and 46 activated carbon (AC) papers] were analyzed using a bootstrap method and a 95% confidence interval (CI) to provide insights into nutrient adsorption. The results indicated the solution temperature, pore volume, specific surface area, and pyrolysis temperature were correlated significantly to the maximum adsorption capacity (Q m), achieving r values of 0.37, 0.23, 0.16, and 0.14, respectively. A statistically significant difference was witnessed for nitrate Q m between AC and BC with median values of 17.64 and 0.51 mg/g, respectively, and CIs of 11.01–27.56 and 0.39–0.82 mg/g, respectively. In contrast, the difference in Q m between AC and BC for phosphate and ammonium contained a high probability of chance. On average, engineered biochar achieved higher Q m values of ammonium and phosphate (12.13 and 24.73 mg/g, respectively) in comparison with that of the original biochar. However, there is a good probability of no difference in nitrate between the two, albeit greater nitrate adsorption on the modified biochar with a mean Q m of 3.03 mg/g. The tuned Cubist estimated equilibrium adsorption capacity with an R 2 of ∼0.90–0.91. The median and bootstrap 95% CI can be used as an average standard for designing adsorbate–adsorbent systems.
This work provides insights into the nutrient adsorption on pyrogenic carbonaceous adsorbents and an average standard for designing adsorbate−adsorbent systems using a bootstrap method and machine learning.
Insight into the Adsorption of Nutrients from Water by Pyrogenic Carbonaceous Adsorbents Using a Bootstrap Method and Machine Learning
Nguyen, Xuan Cuong (author) / Nguyen, Thi Thanh Huyen (author) / Hang, Nguyen Thi Thuy (author) / Thai, Van Nam (author) / Doan, Thi Oanh (author) / Duong, Thi Thuy (author) / Duong, Thanh Nghi (author) / Hwang, Yuhoon (author) / Lam, Vinh Son (author) / Ly, Quang Viet (author)
ACS ES&T Water ; 4 ; 869-879
2024-03-08
Article (Journal)
Electronic Resource
English
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