分析测试学报2025，Vol.44Issue(6)：1115-1122,8.DOI:10.12452/j.fxcsxb.241118533
激光诱导击穿光谱结合机器学习的土壤沉积物重金属元素定量分析方法研究
Research on Quantitative Analysis Method of Heavy Metal Elements in Soil Sediments Based on Laser Induced Breakdown Spectroscopy Combined with Machine Learning
摘要
Abstract
The issue of heavy metal contamination in soil sediment is becoming increasingly preva-lent.The development of on-site rapid detection methods for heavy metal elements represents the only viable approach to achieving effective pollution monitoring and environmental governance.According-ly,this study proposed a quantitative analysis method for heavy metal elements in soil sediments based on laser-induced breakdown spectroscopy combined with machine learning algorithms.Firstly,the spectral collection of soil sediment samples was completed using the constructed LIBS device,and the efficacy of various spectral preprocessing techniques on spectral data preprocessing was inves-tigated.Subsequently,feature variable selection was conducted on the preprocessed spectral data,based on the measurement of variable importance.The preprocessing method,variable importance threshold,and other parameters were optimized using cross-validation.A quantitative analysis mod-el for three heavy metal elements(Pb,Cu and Zn)in soil sediment samples was constructed based on optimized input variables.To further validate the performance of the model,a comparison was con-ducted with the performance of other calibration models.The results indicate that the VIM-RF cali-bration model proposed in this study exhibits the best predictive performance,with a R2p of 0.993 0 and a RMSEp of 0.029 8 mg/kg for Pb,a R2p of 0.981 0 and a RMSEp of 0.112 7 mg/kg for Cu,and a R2p of 0.992 0 and a RMSEp of 0.166 2 mg/kg for Zn.It can be seen that the method established by this research institute is expected to provide a theoretical reference for the rapid screening and treat-ment of heavy metal pollution in soil sediment environments.关键词
土壤沉积物/重金属/激光诱导击穿光谱/随机森林/特征选择Key words
soil sediment/heavy metals/laser induced breakdown spectroscopy/random forest/feature selection分类
化学化工引用本文复制引用
杏艳,李茂刚,念娟妮,王婷,周奎,张天龙,李华..激光诱导击穿光谱结合机器学习的土壤沉积物重金属元素定量分析方法研究[J].分析测试学报,2025,44(6):1115-1122,8.基金项目
国家自然科学基金(22173071) （22173071）
陕西省创新能力支撑计划-碳监测与评估创新团队项目(2024RS-CXTD-48) （2024RS-CXTD-48）
陕西省重点研发计划重点产业链项目(2024SF-ZDCYL-05-06) （2024SF-ZDCYL-05-06）
陕西省环境介质痕量污染物监测预警重点实验室开放基金项目(SHJKFJJ202303) （SHJKFJJ202303）
