Bayesian multivariate receptor model and convolutional neural network to identify quantitative sources and spatial distributions of potentially toxic elements in soils: A case study in Qingzhou City, China

IF 2.9 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH

ACS Chemical Health & Safety Pub Date : 2024-07-01 DOI:10.1016/j.jhazmat.2024.135184

Xiangyi Kong, Yang Liu, Zongqi Duan, Jianshu Lv

引用次数: 0

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贝叶斯多元受体模型和卷积神经网络识别土壤中潜在有毒元素的定量来源和空间分布：中国青州市案例研究

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

ACS Chemical Health & Safety PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-

CiteScore

3.10

自引率

20.00%

发文量

期刊介绍： The Journal of Chemical Health and Safety focuses on news, information, and ideas relating to issues and advances in chemical health and safety. The Journal of Chemical Health and Safety covers up-to-the minute, in-depth views of safety issues ranging from OSHA and EPA regulations to the safe handling of hazardous waste, from the latest innovations in effective chemical hygiene practices to the courts'' most recent rulings on safety-related lawsuits. The Journal of Chemical Health and Safety presents real-world information that health, safety and environmental professionals and others responsible for the safety of their workplaces can put to use right away, identifying potential and developing safety concerns before they do real harm.