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Environmental Restoration and Remediation

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Efficient remediation of different concentrations of Cr-contaminated soils by nano zero-valent iron modified with carboxymethyl cellulose and biochar.

Journal of environmental sciences (China)
Nano zero-valent iron (nZVI) is widely used in soil remediation due to its high reactivity. However, the easy agglomeration, poor antioxidant ability and passivation layer of Fe-Cr coprecipitates of nZVI have limited its application scale in Cr-conta...

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.

The Science of the total environment
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...

Phytobial remediation advances and application of omics and artificial intelligence: a review.

Environmental science and pollution research international
Industrialization and urbanization increased the use of chemicals in agriculture, vehicular emissions, etc., and spoiled all environmental sectors. It causes various problems among living beings at multiple levels and concentrations. Phytoremediation...

Machine learning-based exploration of biochar for environmental management and remediation.

Journal of environmental management
Biochar has a wide range of applications, including environmental management, such as preventing soil and water pollution, removing heavy metals from water sources, and reducing air pollution. However, there are several challenges associated with the...

Optimal biochar selection for cadmium pollution remediation in Chinese agricultural soils via optimized machine learning.

Journal of hazardous materials
Biochar is effective in mitigating heavy metal pollution, and cadmium (Cd) is the primary pollutant in agricultural fields. However, traditional trial-and-error methods for determining the optimal biochar remediation efficiency are time-consuming and...

Predicting Cd(II) adsorption capacity of biochar materials using typical machine learning models for effective remediation of aquatic environments.

The Science of the total environment
The screening and design of "green" biochar materials with high adsorption capacity play a pivotal role in promoting the sustainable treatment of Cd(II)-containing wastewater. In this study, six typical machine learning (ML) models, namely Linear Reg...

New strategy to optimize in-situ fenton oxidation for TPH contaminated soil remediation via artificial neural network approach.

Chemosphere
In-situ remediation of total petroleum hydrocarbon (TPH) contaminated soils via Fenton oxidation is a promising approach. However, determining the proper injection amount of HO and Fe source over the Fenton reaction in the complex geological conditio...

Innovations in plastic remediation: Catalytic degradation and machine learning for sustainable solutions.

Journal of contaminant hydrology
Plastic pollution is an extreme environmental threat, necessitating novel restoration solutions. The present investigation investigates the integration of machine learning (ML) techniques with catalytic degradation processes to improve plastic waste ...

Assessment of wetland ecological restoration effect based on fuzzy analytic hierarchy process: a case study of Tianjin Qilihai Wetland.

Environmental monitoring and assessment
Scientific evaluation of the effectiveness of ecological restoration could provide support for sustainable management and protection of wetlands. However, due to the multiple and difficult to quantify factors affecting wetlands, commonly used spatiot...