Predicting thermal desorption efficiency of PAHs in contaminated sites based on an optimized machine learning approach-Reference-Cited by-同舟云学术

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Predicting thermal desorption efficiency of PAHs in contaminated sites based on an optimized machine learning approach

Published:2024-04 Issue: Volume:346 Page:123667
ISSN:0269-7491
Container-title:Environmental Pollution
language:en
Short-container-title:Environmental Pollution

Author:

Zhang Shuai,Wang Shuyuan,Zhao Jiating,Zhu Lizhong

Funder

Chinese Academy of Engineering

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

Elsevier BV

Reference41 articles.

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2. Artificial neural network modeling in competitive adsorption of phenol and resorcinol from water environment using some carbonaceous adsorbents;Aghav;J. Hazard Mater.,2011

3. Bioremediation of PAHs and heavy metals co-contaminated soils: challenges and enhancement strategies;Ali;Environ. Pollut.,2022

4. Effects of biochar and organic substrates on biodegradation of polycyclic aromatic hydrocarbons and microbial community structure in PAHs-contaminated soils;Bao;J. Hazard Mater.,2020

5. Recent trends in polycyclic aromatic hydrocarbons pollution distribution and counteracting bio-remediation strategies;Barathi;Chemosphere,2023

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Prediction of BTEX volatilization in polluted soil based on the sorption potential energy theory;Environmental Pollution;2024-11

2. Predicting removal efficiency of organic pollutants by soil vapor extraction based on an optimized machine learning method;Science of The Total Environment;2024-06

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