The relationship between dissolved radon and other geochemical parameters in Campi Flegrei volcanic aquifer (Southern Italy): A follow-up study

地下水 含水层 火山 地质学 热液循环 地球化学 空间分布 环境科学 地球科学 水文学(农业) 地震学 量子力学 遥感 物理 岩土工程
作者
Pooria Ebrahimi,Annalise Guarino,Vincenzo Allocca,Antonello Cutolo,Domenico Cicchella,Stefano Albanese
出处
期刊:Applied Geochemistry [Elsevier BV]
卷期号:151: 105607-105607 被引量:2
标识
DOI:10.1016/j.apgeochem.2023.105607
摘要

Campi Flegrei is one of the most active volcanic areas in the world and assessing the potential proxies of volcanic-related phenomena is critical. Therefore, the spatial distribution of radon and carbon dioxide in groundwater and the statistical relationships between the dissolved gases and other variables deserve further attention. Compositional data analysis (CoDA) was proposed at the end of the last century and further developed in the last decades for reliable data mining, but its potential has not been fully explored for characterization of the groundwater aquifers affected by hydrothermal activity. Based on a prospecting campaign mainly aimed at the determination of both radon and carbon dioxide in Campi Flegrei groundwater, this article explores the spatial patterns of these gases in the local aquifer system and uses a CoDA approach to extract the relevant information and to determine the meaningful geochemical associations. The results show that the spatial distribution of both dissolved gases corresponds to the hydrothermal system. The logratio transformed CO2 (aq) distinguishes bicarbonate-rich groundwater better than the raw values. Principal component analysis reveals two associations: A1) Ca2+, Mg2+, K+, SO42−, HCO3− + CO2 and pH; and A2) Na+, Cl−, As, B, Li, Rn, TDS and T. It highlights that the groundwater composition is generally influenced by two main factors: (1) meteoric water, which is modified by CO2‒rich magmatic gases in some cases; and (2) hydrothermal fluid and/or seawater. The results are in agreement with the literature and application of CoDA is recommended in future investigations because the study area is highly populated and considering the compositional nature of geochemical data might help mitigate the volcanic hazard at Campi Flegrei.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
SunD完成签到,获得积分10
1秒前
科研通AI6.4应助ji采纳,获得10
1秒前
2秒前
灝男发布了新的文献求助30
2秒前
sheep完成签到,获得积分10
2秒前
alixy发布了新的文献求助10
3秒前
科研狗完成签到,获得积分10
4秒前
4秒前
zhangj696完成签到,获得积分10
4秒前
搜集达人应助圣晟胜采纳,获得10
6秒前
科研狗发布了新的文献求助10
6秒前
研友_8KX15L完成签到,获得积分10
8秒前
8秒前
正无穷完成签到,获得积分10
8秒前
研友_VZG7GZ应助科研通管家采纳,获得10
8秒前
Copyright应助科研通管家采纳,获得10
9秒前
打打应助科研通管家采纳,获得10
9秒前
单纯代萱发布了新的文献求助20
9秒前
NexusExplorer应助科研通管家采纳,获得10
9秒前
英俊的铭应助科研通管家采纳,获得10
9秒前
Hello应助科研通管家采纳,获得10
9秒前
CFD应助科研通管家采纳,获得10
9秒前
9秒前
小马甲应助五五采纳,获得10
9秒前
HXZR0924发布了新的文献求助10
9秒前
充电宝应助科研通管家采纳,获得10
9秒前
11秒前
少艾完成签到 ,获得积分10
11秒前
11秒前
12秒前
sheep发布了新的文献求助30
14秒前
蛋卷发布了新的文献求助10
14秒前
Hello应助coral_wei采纳,获得30
15秒前
123发布了新的文献求助20
15秒前
17秒前
18秒前
笨笨松发布了新的文献求助10
18秒前
顾矜应助wzhtnl采纳,获得10
18秒前
18秒前
高分求助中
Cronologia da história de Macau 5000
Matrix Methods in Data Mining and Pattern Recognition 510
Interactions of Vowel Quality and Prosody in East Slavic 500
Vander's Renal Physiology第10版 500
Forensic Science An Introduction to Scientific and Investigative Techniques 6th Edition 400
Virus-like particles empower RNAi for effective control of a Coleopteran pest 400
Materials Informatics Molecules, Crystals and Beyond A volume in Acta Materialia Book Series 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7098090
求助须知:如何正确求助?哪些是违规求助? 8754257
关于积分的说明 18515480
捐赠科研通 6654015
什么是DOI,文献DOI怎么找? 3138761
关于科研通互助平台的介绍 2248104
邀请新用户注册赠送积分活动 2113647