新疆环境保护2025，Vol.47Issue(4)：1-12,12.
基于响应面法与GA-BP神经网络优化ZSM-5热解修复石油污染土壤的研究
Research on the Pyrolysis Remediation of Petroleum-Contaminated Soil by ZSM-5 Based on Response Surface Method and GA-BP Neural Network Optimization
摘要
Abstract
In the remediation technology of oil-contaminated soil,low-temperature pyrolysis remediation is an efficient method.However,there are still problems of high energy consumption and low efficiency of pyrolysis.This study took the petroleum-contaminated soil in Xinjiang as the research object.ZSM-5 molecular sieve was used to enhance the pyrolysis of petroleum pollutants,and improvement effect of the removal rate of total petroleum hydrocarbons(TPH)under the control of pyrolysis temperature,residence time and molecular sieve addition amount was studied.RSM and GA-BP neural network models were established to optimize the pyrolysis conditions.The improvement effect of the removal rate of total petroleum hydrocarbons(TPH)under the control of pyrolysis temperature,residence time and molecular sieve addition amount was investigated.RSM and GA-BP neural network models were established to optimize the pyrolysis conditions.The results showed that both models could optimize the process conditions of ZSM-5 pyrolysis petroleum-contaminated soil.Considering the experimental conditions,the optimal pyrolysis conditions of the RSM model were 240℃,31 min,4.1 wt% ZSM-5;and the optimal pyrolysis conditions of the GA-BP neural network model were 240℃,35 min,4.1 wt% ZSM-5.The pyrolysis temperature,residence time and ZSM-5 dosage have significant effects on the improvement of TPH removal rate.The RSM model(R2=0.9946)could more accurately predict the pyrolysis process conditions,which provides a reference for the study of low-temperature pyrolysis remediation of oil-contaminated soil.关键词
石油污染土壤/响应曲面法/遗传算法/BP神经网络/ZSM-5分子筛Key words
petroleum contaminated soil/response surface methodology/genetic algorithm/BP neural network/ZSM-5 zeolite分类
资源环境引用本文复制引用
李吉群,加德拉·巴合提别克,许开豪,张程雪,夏梦..基于响应面法与GA-BP神经网络优化ZSM-5热解修复石油污染土壤的研究[J].新疆环境保护,2025,47(4):1-12,12.基金项目
国家自然科学基金项目(52200203) （52200203）
"天山英才"托举人才项目(2023TSYCQNTJ0011) （2023TSYCQNTJ0011）
中央引导地方科技发展资金项目(ZYYD2024ZY16) （ZYYD2024ZY16）
新疆自然科学基金项目(2022D01C74) （2022D01C74）
大学生创新训练计划资助项目(XJU-SRT-23087) （XJU-SRT-23087）
