Modern methods for determining heavy metals in soil DOI

Nikolay I. Klimakov,

Dmitry E. Kucher

Vestnik of the Russian agricultural science, Год журнала: 2024, Номер 4, С. 84 - 89

Опубликована: Сен. 2, 2024

This article discusses the problem of heavy metal detection in soil and its impact on vegetation. Based experience foreign domestic research, this global fundamental problems challenges, modern methods detection, as well prospects for further research new challenges facing scientific community. The aim study is to identify established metals soil, such spectral analysis reflectance spectra plant parts. review summarizes results experimental studies confirming effectiveness combined sampling spectrometry method estimating concentration feasibility using measure pollution. World confirms expediency approaches determine analyze their have practical application field ecology, agriculture nature protection, allow effectively controlling level pollution taking measures elimination.

Язык: Английский

Health for the future: spatiotemporal CA-MC modeling and spatial pattern prediction via dendrochronological approach for nickel and lead deposition DOI
Öznur Işınkaralar, Kaan Işınkaralar, Hakan Sevık

и другие.

Air Quality Atmosphere & Health, Год журнала: 2025, Номер unknown

Опубликована: Янв. 28, 2025

Язык: Английский

Процитировано

3

Potentially toxic elements in the agricultural soils of northwestern Bosnia and Herzegovina: spatial and vertical distribution, origin and ecological risk DOI
Dijana Mihajlović, S. Srdić, Pavel Benka

и другие.

Environmental Monitoring and Assessment, Год журнала: 2025, Номер 197(3)

Опубликована: Фев. 14, 2025

Язык: Английский

Процитировано

1

Source analysis and distribution prediction of soil heavy metals in a typical area of the Qinghai-Tibet Plateau DOI Creative Commons
Xinjie Zha, Liyuan Deng, Wei Jiang

и другие.

Ecological Indicators, Год журнала: 2024, Номер 166, С. 112460 - 112460

Опубликована: Авг. 8, 2024

The excessive presence of heavy metals (HMs) in soil poses a significant threat to both ecosystems and human health. Consequently, there is compelling need for quantitative analysis HMs concentration the prediction potential contamination. In this study, 58 surface samples were systematically collected from 11 different townships Luolong County. Using ArcGIS 10.7, fishing net interpolation resampling was performed obtain model data. GeoDetector employed determine key driving factors their interrelationships affecting composition. Subsequently, influential with higher explanatory power Random Forest (RF) generate contamination map. results revealed that arsenic (As), cadmium (Cd) lead (Pb) exceeded risk screening values by 8.62%, 10.34%, respectively. identified such as elevation, annual average precipitation, distance nearest river, geomorphic type natural sources, geological roads, proximity mining sites, per capita income inhabitants, total potassium content organic matter anthropogenic sources significantly influencing spatial distribution soil. interactions among primary increased capacity. By using RF predict main HMs, it found areas high probability As mainly concentrated northern, central southeast regions Regions Cd exceeding value primarily east, northeast few northern County, while likelihood Pb southwestern This study integrates stratified heterogeneity random forest mitigate overfitting HM contamination, common issue traditional machine learning methods. approach essential elucidating environmental drivers pollution, predicting high-risk complex conditions limited data, ensuring safety stability agricultural production well well-being local residents.

Язык: Английский

Процитировано

6

Tracking the impact of heavy metals on human health and ecological environments in complex coastal aquifers using improved machine learning optimization DOI
Abdulhayat M. Jibrin, Sani I. Abba, Jamilu Usman

и другие.

Environmental Science and Pollution Research, Год журнала: 2024, Номер 31(40), С. 53219 - 53236

Опубликована: Авг. 24, 2024

Язык: Английский

Процитировано

5

Long-Term Trends and Ecological Risks of Heavy Metal Accumulation in Cultivated Land of Songnen Plain, China DOI Creative Commons

Zonglai Liu,

Jinying Li, Yanan Chen

и другие.

Toxics, Год журнала: 2025, Номер 13(1), С. 59 - 59

Опубликована: Янв. 15, 2025

Heavy metal pollution in agricultural soils poses a serious threat to food security. Therefore, it is crucial conduct risk assessments and issue early warnings about high levels of contamination for the sustained prosperity agriculture. To assess risks, identify sources, quantify amounts, determine extent from seven heavy metals, as well provide warnings, 78 soil samples were collected farmed lands Songnen Plain Jilin Province. The average concentrations Zn, Cu, Mn, Pb, Cd, Ni, As found be 2.05, 1.5, 0.2, 1.09, 2.68, 1.53, 1.17 times higher than background values Chinese soils, respectively. Source analysis indicated that toxic Pb originates vehicle exhaust emission, while Ni are attributed industrial activities. Zn likely associated with practices, Mn predominantly stems natural environmental sources. geo-accumulation index suggests relatively high, accumulation Pb. Meanwhile, single-factor indicates elevated Cd. Potential ecological assessment reveals certain areas within Changchun Baicheng cities exhibit risks. Notably, Cd has highest potential (RI) metals warrants special attention. By analyzing annual pollutant accumulations, predictions can made content four Plain, enabling issuance regarding findings suggest without proactive measures mitigate Songyuan will reach severe by 2031 2029,

Язык: Английский

Процитировано

0

A data-driven framework to identify influencing factors for soil heavy metal contaminations using random forest and bivariate local Moran's I: A case study DOI
Rui Zhou, Jian Chen,

Shiwen Cui

и другие.

Journal of Environmental Management, Год журнала: 2025, Номер 375, С. 124172 - 124172

Опубликована: Янв. 21, 2025

Язык: Английский

Процитировано

0

Anthropogenic metal storage in wetland soils across the conterminous United States DOI Creative Commons
Matthew Dietrich, Michael Dumelle, Amanda M. Nahlik

и другие.

Research Square (Research Square), Год журнала: 2025, Номер unknown

Опубликована: Янв. 31, 2025

Abstract Wetlands provide many ecosystem services, such as mitigating pollution, attenuating flooding and drought extremes, providing habitat for species. However, studies quantifying potential wetland sequestration of heavy metals an service, particularly across large spatial extents, are sparse. We utilized data from the United States Environmental Protection Agency’s National Wetland Condition Assessment to estimate anthropogenic metal (Pb, Cu, Cr) storage in upper 40 centimeters soils conterminous (CONUS). Large amounts Cu Cr stored soil CONUS, at 299.5 ± 73.2 (95% confidence interval) 483.4 132.1 thousand metric tons (MT), respectively. Anthropogenic Pb totaled 394.3 265.2 MT, amount roughly equivalent 7% lead-based gasoline additives used U.S. between 1927–1994, largest widespread source landscape. Between 15–22% Cr, mass within cm CONUS is anthropogenic. also estimated loading normalize by area. related complex interaction landscape features. national-scale variations obscure which features dominant retention processes. In most cases, redox state, tidal influence, hydrologic regime, geographical region do not substantially impact estimates soils. More detailed regional research may help disentangle these relationships further support management.

Язык: Английский

Процитировано

0

Deciphering Heavy Metal Adsorption Capacity of Soil Based on its Physicochemical Properties and Adsorption Reaction Time Using Machine Learning DOI

Jianle Wang,

Xueming Liu, Weijie Li

и другие.

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Applications of machine learning and artificial intelligence in soil science DOI
Sérgio Henrique Godinho Silva, Marcelo Mancini, Anita Fernanda dos Santos Teixeira

и другие.

Elsevier eBooks, Год журнала: 2025, Номер unknown, С. 155 - 179

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Assessing the Sources and Risks of Heavy Metals in Agricultural Soils: A Comprehensive Review DOI

Freslyn Mae Camata,

Ryna Mae Capurcos,

Eula Marie Delino

и другие.

Опубликована: Апрель 8, 2025

Heavy metals in agricultural soils pose a significant environmental and health risk, impacting both soil quality food safety. These contaminants primarily originate from anthropogenic sources, such as industrial activities, improper waste disposal, the excessive use of pesticides fertilizers. Natural including mineral weathering, also contribute to accumulation heavy soil. Influencing factors, pH, organic matter content, climate conditions, can affect mobility bioavailability these metals, exacerbating risks. The primary concern include lead (Pb), arsenic (As), cadmium (Cd), mercury (Hg), chromium (Cr) (di pa sure mga metals), which accumulate chain through crop uptake. Understanding distribution, influencing factors is crucial for mitigating risks associated with their presence soils. Effective management strategies, remediation, controlled fertilizers, monitoring programs, are essential reducing exposure humans ecosystems toxic metals.

Язык: Английский

Процитировано

0