Comparative role of charcoal, biochar, hydrochar and modified biochar on bioavailability of heavy metal(loid)s and machine learning regression analysis in alkaline polluted soil.

Autor: Lahori AH; Department of Environmental Sciences, Sindh Madressatul Islam University, Karachi 74000, Pakistan. Electronic address: ahlahori@yahoo.com., Ahmed SR; Department of English, Sindh Madressatul Islam University, Karachi 74000, Pakistan., Mierzwa-Hersztek M; Department of Agricultural and Environmental Chemistry, University of Agriculture in Krakow, al. Mickiewicza 21, 31-120 Krakow, Poland. Electronic address: monika6_mierzwa@wp.pl., Afzal M; Department of Environmental Sciences, Sindh Madressatul Islam University, Karachi 74000, Pakistan., Afzal A; National Institute of Maritime Affairs, Bahria University Karachi Campus, 75260, Pakistan., Bano S; Department of Geology, University of Karachi, Pakistan., Muhammad MT; Department of Chemistry, Jinnah University for women; 74600, Pakistan., Aqsa A; Department of Computer Science, Sindh Madressatul Islam University Karachi, Pakistan., Vambol V; Department of Environmental Engineering and Geodesy, University of Life Sciences in Lublin, Lublin, Poland; Department of Applied Ecology and Environmental Sciences, National University «Yuri Kondratyuk Poltava Polytechnic», Poltava, Ukraine., Vambol S; Department of 'Labour & Environment Protection', National Technical University 'Kharkiv Polytechnic Institute', Kharkiv, Ukraine.
Jazyk: angličtina
Zdroj: The Science of the total environment [Sci Total Environ] 2024 Jun 20; Vol. 930, pp. 172810. Date of Electronic Publication: 2024 Apr 26.
DOI: 10.1016/j.scitotenv.2024.172810
Abstrakt: Pot experiment was performed aimed to assess the comparative role of charcoal, biochar, hydrochar and thiourea-vegetable modified biochar at 1 and 2 % doses, and <1 mm particle size on the bioavailability of Cd, Pb, As, Ni, Cu and Zn, and enhance NPK, and mustard growth in a slightly alkaline polluted soil. Furthermore, machine learning method was used to examine the systematic evaluation of the impact of feature selection based on Pearson's correlation on the performance of the linear regression model. The results revealed that maximum fresh and dry biomass of mustard was observed by 26.38 and 38.18 % with hydrochar 1 %, whereas lemon biochar at 2 % reduced fresh and dry biomass up to 34.0 and 53.0 % than control. The immobilization of Cd and Pb was observed by 83.70 and 71.15 % with thiourea-vegetable modified biochar at 2 %, As 71.62 % with hydrochar 2 %, Ni 80.84 % with thiourea-vegetable modified biochar 2 %, Cu 66.32 % with and Zn 36.30 % with thiourea-vegetable modified biochar at 2 % than control. However, the maximum mobilization of Cu in soil was observed by 30.3 % with lemon biochar 2 %, similarly for Zn 37.36 % with hydrochar 2 % as compared with other treatments. The phyto-availability of Cd, Pb, As and Cu in the mustard shoot and root biomass was reduced except Ni and Zn in soil than control. It was observed that using the machine learning regression analysis approach, variability in treatments effectiveness is evident across different feature correlation thresholds. This study clearly shows that the beneficial role of studied amendments on mustard growth and reduced bioavailability of heavy metal(loid)s and enhance primary macronutrients in alkaline polluted soil. It is suggested that future studies may be conducted on combined application of studies amendments on plant growth, immobilization of heavy metal(loid)s in multi-metal polluted soil under different field conditions.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024. Published by Elsevier B.V.)
Databáze: MEDLINE
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