Prediction of the Impact of Land Use and Soil Type on Concentrations of Heavy Metals and Phthalates in Soil Based on Model Simulation

Author:

Stojić Nataša1ORCID,Pezo Lato2ORCID,Lončar Biljana3ORCID,Pucarević Mira1ORCID,Filipović Vladimir3ORCID,Prokić Dunja1ORCID,Ćurčić Ljiljana1ORCID,Štrbac Snežana4ORCID

Affiliation:

1. Faculty of Environmental Protection, Educons University, 21208 Sremska Kamenica, Serbia

2. Institute of General and Physical Chemistry, University of Belgrade, 11000 Belgrade, Serbia

3. Faculty of Technology Novi Sad, University of Novi Sad, 21000 Novi Sad, Serbia

4. Institute of Chemistry, Technology and Metallurgy, University of Belgrade, 11000 Belgrade, Serbia

Abstract

The main objective of this study is to determine the possibility of predicting the impact of land use and soil type on concentrations of heavy metals (HMs) and phthalates (PAEs) in soil based on an artificial neural network model (ANN). Qualitative analysis of HMs was performed with inductively coupled plasma–optical emission spectrometry (ICP/OES) and Direct Mercury Analyzer. Determination of PAEs was performed with gas chromatography (GC) coupled with a single quadrupole mass spectrometry (MS). An ANN, based on the Broyden–Fletcher–Goldfarb–Shanno (BFGS) iterative algorithm, for the prediction of HM and PAE concentrations, based on land use and soil type parameters, showed good prediction capabilities (the coefficient of determination (r2) values during the training cycle for HM concentration variables were 0.895, 0.927, 0.885, 0.813, 0.883, 0.917, 0.931, and 0.883, respectively, and for PAEs, the concentration variables were 0.950, 0.974, 0.958, 0.974, and 0.943, respectively). The results of this study indicate that HM and PAE concentrations, based on land use and soil type, can be predicted using ANN.

Funder

European Union’s Horizon Europe Project GREENLand—Twinning Microplastic-free Environment

Provincial Secretariat for Urbanism and Environmental Protection

Ministry of Science Technological Development and Innovations of the Republic of Serbia

Publisher

MDPI AG

Subject

Chemical Health and Safety,Health, Toxicology and Mutagenesis,Toxicology

Cited by 3 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

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3