Using MIR and XRF spectroscopy to develop a heavy metal leaching potential model in Irish top soils

Rebecca L. Hall , Felipe Bachion de Santana , Victoria Lowe , Jim Hodgson , Karen Daly
{"title":"Using MIR and XRF spectroscopy to develop a heavy metal leaching potential model in Irish top soils","authors":"Rebecca L. Hall ,&nbsp;Felipe Bachion de Santana ,&nbsp;Victoria Lowe ,&nbsp;Jim Hodgson ,&nbsp;Karen Daly","doi":"10.1016/j.soisec.2024.100171","DOIUrl":null,"url":null,"abstract":"<div><div>The European Union aim to have all soils healthy by 2050. However, a major challenge to soil health monitoring is identifying key metrics for soil health indicators. Moreover, how to analyse numerous soil properties which are time-consuming, labour intensive and expensive. MIR spectroscopy is a rapid, non-destructive cheaper alternative to wet chemical methods. Here, we combined known soil properties that limit transport of heavy metals (i.e. drainage class, depth, organic matter, particle size/texture, bulk density and cation-exchange-capacity) to develop a topsoil (≤50 cm) leaching potential model (<em>n</em> = 3,515). The study area consisted of mostly grassland soils which had mainly high and moderately low leaching potential (43 and 36 %, respectively), with lower coverage of high and intermediate classes (10 and 11 %, respectively). However, known topsoil prediction models of 5–25 cm (<em>n</em> = 4759) were extrapolated to deeper samples 30–50 cm. As a result, 26 % of samples were identified as ‘out of control’ in peatland transition areas. For full spatial coverage for environmental modelling from spectral data, reference values are needed for the deeper samples in peatland transition areas.</div><div>Furthermore, this study used a geological survey of the northern half of Ireland at ≤4 km<sup>2</sup> resolution to map regions of naturally high levels of As, Cd, Cr, Cu, Ni and Pb by ICP and XRF spectroscopy. Geospatial clipping of heavy metal thresholds showed high coverage of As and Ni in Eastern regions, and Cd in the Midland regions of Ireland. Therefore, it would be useful to include fertiliser loadings, transport pathways or any source/recipient data to assess heavy metal movement throughout the soil profile, particularly in these regions.</div></div>","PeriodicalId":74839,"journal":{"name":"Soil security","volume":"17 ","pages":"Article 100171"},"PeriodicalIF":0.0000,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Soil security","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2667006224000455","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The European Union aim to have all soils healthy by 2050. However, a major challenge to soil health monitoring is identifying key metrics for soil health indicators. Moreover, how to analyse numerous soil properties which are time-consuming, labour intensive and expensive. MIR spectroscopy is a rapid, non-destructive cheaper alternative to wet chemical methods. Here, we combined known soil properties that limit transport of heavy metals (i.e. drainage class, depth, organic matter, particle size/texture, bulk density and cation-exchange-capacity) to develop a topsoil (≤50 cm) leaching potential model (n = 3,515). The study area consisted of mostly grassland soils which had mainly high and moderately low leaching potential (43 and 36 %, respectively), with lower coverage of high and intermediate classes (10 and 11 %, respectively). However, known topsoil prediction models of 5–25 cm (n = 4759) were extrapolated to deeper samples 30–50 cm. As a result, 26 % of samples were identified as ‘out of control’ in peatland transition areas. For full spatial coverage for environmental modelling from spectral data, reference values are needed for the deeper samples in peatland transition areas.
Furthermore, this study used a geological survey of the northern half of Ireland at ≤4 km2 resolution to map regions of naturally high levels of As, Cd, Cr, Cu, Ni and Pb by ICP and XRF spectroscopy. Geospatial clipping of heavy metal thresholds showed high coverage of As and Ni in Eastern regions, and Cd in the Midland regions of Ireland. Therefore, it would be useful to include fertiliser loadings, transport pathways or any source/recipient data to assess heavy metal movement throughout the soil profile, particularly in these regions.

Abstract Image

利用近红外光谱和 XRF 光谱建立爱尔兰表层土壤重金属沥滤潜力模型
欧盟的目标是到 2050 年实现所有土壤健康。然而,土壤健康监测面临的一大挑战是确定土壤健康指标的关键衡量标准。此外,如何分析众多耗时、耗力且昂贵的土壤特性也是一大挑战。相比湿化学方法,近红外光谱法是一种快速、非破坏性且成本更低的替代方法。在这里,我们将限制重金属迁移的已知土壤特性(即排水等级、深度、有机质、颗粒大小/质地、容重和阳离子交换容量)结合起来,建立了表层土壤(≤50 厘米)沥滤潜力模型(n = 3,515)。研究区域主要由草地土壤组成,这些土壤的沥滤潜力主要为高和中低水平(分别为 43% 和 36%),高水平和中等水平的覆盖率较低(分别为 10% 和 11%)。不过,已知的 5-25 厘米表层土预测模型(n = 4759)被推断为 30-50 厘米的深层样本。因此,泥炭地过渡区有 26% 的样本被认定为 "失控"。此外,本研究还利用分辨率≤4 平方公里的爱尔兰北半部地质调查,通过 ICP 和 XRF 光谱法绘制了 As、Cd、Cr、Cu、Ni 和 Pb 天然高含量区域图。重金属阈值的地理空间剪切显示,砷和镍在爱尔兰东部地区的覆盖率较高,镉在爱尔兰中部地区的覆盖率较高。因此,在评估重金属在整个土壤剖面中的移动情况时,特别是在这些地区,最好能包括肥料负荷、迁移路径或任何来源/受体数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Soil security
Soil security Soil Science
CiteScore
4.00
自引率
0.00%
发文量
0
审稿时长
90 days
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信