Heavy Metal(oid)s & Organic Pollutants in Soil: Effects, Sources, and Remediation Techniques. Machine Learning Approaches for the Assessment of Soil Pollution

A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Soil-Sediment-Water Systems".

Deadline for manuscript submissions: closed (23 May 2022) | Viewed by 17105

Special Issue Editors

Laboratory of Soil Science, School of Agriculture, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece
Interests: soil science; soil chemistry; environmental analysis; environmental monitoring; GIS; heavy metal(oid)s; trace elements; contamination monitoring; urban and agricultural soil pollution; physicochemical behavior of metals in environment
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School of Electrical & ComSchool of Electrical and Computer Engineering, Technical University of Crete, 731 00 Chania, Greece
Interests: speech recognition; speech synthesis; language modelling; signal processing including speech processing; machine learning; pattern recognition and stochastic modeling; natural language processing
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School of Agricultural Sciences, University of Thessaly, Fytokou Street, 38446 Nea Ionia Magnisias, Greece
Interests: environmental analytical chemistry; pollution chemistry; chromatographic techniques; development; validation of analytical methods for determination of organic micropollutants; transportation of pesticides in environmental compartments; degradation, adsorption–desorption studies; agricultural soil pollution natural language processing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

DearColleagues,

Heavy Metals (ΗΜs) are defined as a group of metallic elements having atomic densities higher than 5 g/cm3. Recently, the term heavy metals have often been replaced by the term Potentially Toxic Elements (PTEs) since some of the elements of this category can be toxic to plants, animals and humans in high concentrations. On the other hand, these elements, in small quantities, are of paramount importance for the proper functioning and development of the flora and fauna, known as nutrients or trace elements. The group of potentially toxic elements (PTEs) also includes elements that are not metals but have many properties of metals. These elements are called metalloids. Arsenic is a representative example of a PTE.Heavy metals contaminate the environment and its living organisms in different ways. Growth reduction, protein content and adverse effects on a plant’s physiology start when the metal(oid) concentration increases. The main sources of metal enrichment in soils are lithogenic and anthropogenic. There are many different anthropogenic sources of heavy metal(oid) contamination, affecting both agricultural and urban soils, such as mining and industrial waste, the use of fertilizers, pesticides and sewage sludge in agriculture soils, transportation, forest fires, volcanic eruptions, fossil fuel combustion, urban waste, and chemical industries.

The occurrence and fate of organic compounds in soils have been the subject of numerous studies in recent decades, mostly due to the urgent need to answer the challenge of better managing soil quality and prevent soil and water pollution. This Special Issue welcomes articles that describe soil pollution caused by organic compounds, their determination and monitoring, their interaction with soil and water, their mitigation along their impact on the agricultural production, the environment, ecosystems and humans as well.

Several remediation techniques, such as extraction, stabilization, solidification, vitrification, phytoremediation, and bioremediation, have been developed to restore the heavy metal-and organics contaminated soils. These recovery techniques use containment, extraction, removal and immobilization mechanisms to reduce the effects of contamination. Phytoremediation techniques depend on the ability of certain plants to tolerate high concentrations of metal(oid)s in their environment. Exclusion, inclusion, and bioaccumulation are the three functions responsible for this ability. A successful remediation often requires early and accurate assessment of the soil pollution.

Towards this goal, a recent trend has been to use machine learning techniques such as regression, clustering and classification to obtain a better characterization and quantification of the soil contamination. This trend is enhanced from the increasing availability of soil contamination data.

This Special Issue aims at publishing original research on the following general topics:

  • monitoring soil contamination by heavy metals and/or organic pollutants;
  • contamination and health risk indexes;
  • mapping and risk assessment;
  • prevention and mitigation approaches;
  • use of machine learning techniques including deep learning, regression, classification and clustering for the characterization and quantification of soil contamination.

Dr. Evangelia Golia
Dr. Vassilios Diakoloukas
Prof. Nikolaos Tsiropoulos
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Land is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • heavy metals (ΗΜs)
  • potentially toxic elements (PTEs)
  • contaminated soils
  • recovery techniques
  • machine learning
  • deep learning
  • soil spectroscopy
  • computer vision
  • pollution mitigation, phytoremediation
  • bioremediation
  • fate and behavior of organic pollutants

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Published Papers (8 papers)

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Research

18 pages, 9967 KiB  
Article
Urban Sustainability at Risk Due to Soil Pollution by Heavy Metals—Case Study: Volos, Greece
by Panagiotis-Stavros C. Aslanidis and Evangelia E. Golia
Land 2022, 11(7), 1016; https://0-doi-org.brum.beds.ac.uk/10.3390/land11071016 - 04 Jul 2022
Cited by 9 | Viewed by 2182
Abstract
The focus of this case study is the meticulous observation of urban soil pollution by heavy metals (HMs), or, alternatively, potentially toxic elements (PTEs). The study took place in the urban center of Volos, Greece. Moreover, 248 soil samples were collected during 2018–2021 [...] Read more.
The focus of this case study is the meticulous observation of urban soil pollution by heavy metals (HMs), or, alternatively, potentially toxic elements (PTEs). The study took place in the urban center of Volos, Greece. Moreover, 248 soil samples were collected during 2018–2021 (62 samples annually), while 3.65 km2 was, approximately, the study area. The breakdown of total concentrations took place for the interpretation of different soil parameters, also according to mean values and medians of the total concentrations of HMs, the following decreasing order was monitored: Mn > Zn > Cr > Ni > Cu > Pb > Co > Cd. During the 4-year study, an increasing trend of metal concentration was observed (for each year compared to the previous one). Furthermore, the imaginary triangle, which was observed, is bordered by the historic train station, the two city bus and intercity coach stations and the commercial harbor. Statistical analysis was implemented in order to interpret the exceedances of HMs concerning the Directive 86/278/EEC. Principal component analysis (PCA) is an additional technique that was conducted because of the correlations and interdependences between the HMs. A strong correlation was observed between the HMs, but mainly between Cd and Zn, which is probably due to their common origin. During the COVID-19 pandemic, significant changes in metal concentrations were observed in different parts of the city, due to the limited movement of motorized wheeled vehicles, but also due to the long operating hours of the heating systems in the residential area. Further research is needed in the future in order to identify the sources of pollution and to find possible ways to reduce it. All in all, urban soil pollution by HMs is a great conundrum of the environmental aspect of sustainability. Full article
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13 pages, 2476 KiB  
Article
Modeling Cadmium Contents in a Soil–Rice System and Identifying Potential Controls
by Yingfan Zhang, Tingting Fu, Xueyao Chen, Hancheng Guo, Hongyi Li and Bifeng Hu
Land 2022, 11(5), 617; https://0-doi-org.brum.beds.ac.uk/10.3390/land11050617 - 21 Apr 2022
Cited by 4 | Viewed by 1561
Abstract
Cadmium (Cd) pollution in a soil–rice system is closely related to widely concerning issues, such as food security and health risk due to exposure to heavy metals. Therefore, modeling the Cd content in a soil–rice system and identifying related controls could provide critical [...] Read more.
Cadmium (Cd) pollution in a soil–rice system is closely related to widely concerning issues, such as food security and health risk due to exposure to heavy metals. Therefore, modeling the Cd content in a soil–rice system and identifying related controls could provide critical information for ensuring food security and reducing related health risks. To archive this goal, in this study, we collected 217 pairs of soil–rice samples from three subareas in Zhejiang Province in the Yangtze River Delta of China. All soil–rice samples were air-dried and conducted for chemical analysis. The Pearson’s correlation coefficient, ANOVA, co-occurrence network, multiple regression model, and nonlinear principal component analysis were then used to predict the Cd content in rice and identify potential controls for the accumulation of Cd in rice. Our results indicate that although the mean total concentration of Cd in soil samples was higher than that of the background value in Zhejiang Province, the mean concentration of Cd in rice was higher than that of the national regulation value. Furthermore, a significant difference was detected for Cd content in rice planted in different soil groups derived from different parental materials. In addition, soil organic matter and total Cd in the soil are essential factors for predicting Cd concentrations in rice. Additionally, specific dominant factors resulting in Cd accumulation in rice planted at different subareas were identified via nonlinear principal component analysis. Our study provides new insights and essential implications for policymakers to formulate specific prevention and control strategies for Cd pollution and related health risks. Full article
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19 pages, 3420 KiB  
Article
Assessment of Contamination Management Caused by Copper and Zinc Cations Leaching and Their Impact on the Hydraulic Properties of a Sandy and a Loamy Clay Soil
by Anastasia Angelaki, Alkiviadis Dionysidis, Parveen Sihag and Evangelia E. Golia
Land 2022, 11(2), 290; https://0-doi-org.brum.beds.ac.uk/10.3390/land11020290 - 14 Feb 2022
Cited by 16 | Viewed by 1785
Abstract
Soil hydraulic properties are crucial to agriculture and water management and depend on soil structure. The impact of Cu and Zn cations on the hydraulic properties of sandy and loamy clay soil samples of Central Greece, was investigated in the present study. Metal [...] Read more.
Soil hydraulic properties are crucial to agriculture and water management and depend on soil structure. The impact of Cu and Zn cations on the hydraulic properties of sandy and loamy clay soil samples of Central Greece, was investigated in the present study. Metal solutions with increased concentrations were used to contaminate the soil samples and the effect on hydraulic properties was evaluated, demonstrating the innovation of the current study. The soil samples were packed separately into transparent columns and the initial values of hydraulic conductivity, cumulative infiltration, infiltration rate and sorptivity were estimated. In order to evaluate soil adsorption, metal concentrations were measured at the water leachate. After the contamination of the soil samples, the hydraulic properties under investigation were determined again, using distilled water as the incoming fluid; the differences at the hydraulic parameters were observed. After doubling metal concentrations into the incoming solution of loamy clay soil, metal adsorption and the values of the hydraulic parameters increased significantly. Loamy clay soil showed interaction between the clay particles and the positive charge in the incoming fluid, which led to a possible increase in aggregation. Furthermore, aggregation may led to pore generation. Contamination of sandy soil exhibited no impact on aggregation and soil structure. In order to evaluate the differences on the hydraulic properties and soil structure, the experimental points were approximated with two infiltration models. Full article
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28 pages, 7924 KiB  
Article
How Does Land Consolidation Affect Soil Fungal Community Structure? Take Heavy Metal Contaminated Areas in Eastern China for Example
by Yaoben Lin, Haoran Yang, Yanmei Ye, Jiahao Wen and Danling Chen
Land 2022, 11(1), 142; https://0-doi-org.brum.beds.ac.uk/10.3390/land11010142 - 17 Jan 2022
Cited by 2 | Viewed by 2177
Abstract
Farmland land consolidation can effectively improve the quality of farmland soil and the agricultural production level, and can effectively guarantee farmland ecology and food security, which has been widely used in the world. A large number of studies have shown that farmland consolidation [...] Read more.
Farmland land consolidation can effectively improve the quality of farmland soil and the agricultural production level, and can effectively guarantee farmland ecology and food security, which has been widely used in the world. A large number of studies have shown that farmland consolidation has certain adjustments to the basic physical and chemical properties of soil and the content of heavy metals. As a key indicator of soil quality and ecological conditions, soil microorganisms play an important role in soil pollution restoration and the promotion of crop growth. However, there are few domestic and foreign studies on how farmland consolidation affects soil microbial properties, and there are no related reports on the mechanism of action between them, which is a blank in the field of agricultural land consolidation and soil microecology, especially in heavy metal contaminated areas. Therefore, we used the DNA sequence technology to compare fungal community structure in farmlands with and without consolidation in heavy metal contaminated areas. Our results showed that (1) farmland consolidation had a significant impact on soil microbial characteristics, which were mainly manifested as changes in microbial biomass, microbial diversity and community structure. (2) Farmland consolidation had an indirect impact on soil fungal community structure by adjusting the soil physical and chemical properties. (3) The impact of heavy metals on the fungal community structure varied significantly under different levels of heavy metal pollution in farmland consolidation areas. When the pollution was at the highest level, there existed 7 fungus genera showing a strong tolerance to heavy metals and consuming a lot of soil nutrients, of which were Melanospora, Pseudeurotium, Guehomyces, Schizothecium, Gibberella, Myrothecium, and Neurospora. In this study, an analytical method was proposed to analyze the effects of farmland consolidation on soil fungi, and the mechanism was discussed from two aspects—soil physical and chemical properties, and heavy metal content. The results shed some light on farmland consolidation, cultivated land quality evaluation and territorial space ecological restoration. Full article
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15 pages, 4558 KiB  
Article
Identifying Influencing Factors of Agricultural Soil Heavy Metals Using a Geographical Detector: A Case Study in Shunyi District, China
by Shiwei Dong, Yuchun Pan, Hui Guo, Bingbo Gao and Mengmeng Li
Land 2021, 10(10), 1010; https://0-doi-org.brum.beds.ac.uk/10.3390/land10101010 - 26 Sep 2021
Cited by 9 | Viewed by 1528
Abstract
Identifying influencing factors of heavy metals is essential for soil evaluation and protection. This study investigates the use of a geographical detector to identify influencing factors of agricultural soil heavy metals from natural and anthropogenic aspects. We focused on six variables of soil [...] Read more.
Identifying influencing factors of heavy metals is essential for soil evaluation and protection. This study investigates the use of a geographical detector to identify influencing factors of agricultural soil heavy metals from natural and anthropogenic aspects. We focused on six variables of soil heavy metals, i.e., As, Cd, Hg, Cu, Pb, Zn, and four influencing factors, i.e., soil properties (soil type and soil texture), digital elevation model (DEM), land use, and annual deposition fluxes. Experiments were conducted in Shunyi District, China. We studied the spatial correlations between variables of soil heavy metals and influencing factors at both single-object and multi-object levels. A geographical detector was directly used at the single-object level, while principal component analysis (PCA) and geographical detector were sequentially integrated at the multi-object level to identify influencing factors of heavy metals. Results showed that the concentrations of Cd, Cu, and Zn were mainly influenced by DEM (p = 0.008) and land use (p = 0.033) factors, while annual deposition fluxes were the main factors of the concentrations of Hg, Cd, and Pb (p = 0.000). Moreover, the concentration of As was primarily influenced by soil properties (p = 0.026), DEM (p = 0.000), and annual deposition flux (p = 0.000). The multi-object identification results between heavy metals and influencing factors included single object identification in this study. Compared with the results using the PCA and correlation analysis (CA) methods, the identification method developed at different levels can identify much more influencing factors of heavy metals. Due to its promising performance, identification at different levels can be widely employed for soil protection and pollution restoration. Full article
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15 pages, 2169 KiB  
Article
Differences in the Content of Zn Fractions in the Profiles of Soils from Allotment and Domestic Gardens in South-Eastern Poland
by Iwona Makuch-Pietraś and Anna Wójcikowska-Kapusta
Land 2021, 10(9), 886; https://0-doi-org.brum.beds.ac.uk/10.3390/land10090886 - 24 Aug 2021
Cited by 2 | Viewed by 1415
Abstract
The aim of the research was to show the distribution of fractions as well as bioavailability and the total forms of Zn in the profiles of soils from domestic gardens and family allotment gardens in six cities in south-eastern Poland. Results found that [...] Read more.
The aim of the research was to show the distribution of fractions as well as bioavailability and the total forms of Zn in the profiles of soils from domestic gardens and family allotment gardens in six cities in south-eastern Poland. Results found that the level of Zn total form varied in the ranges from A horizon: 12.75–154.75 mg·kg−1 in sandy soils and 18.20–104.00 mg·kg−1 in silty soils. Accumulation of metals was assessed using concentration indices, Igeo, and the Cav/Ct and BF indices of bioavailable forms. The analysis took into account the role of organic matter as an important component in binding the analyzed metals in soil horizons subjected to long-term horticultural cultivation. In the two groups of sandy and silty soils distinguished according to their particle size distribution, horticultural treatments were found to exert a greater impact on sandy soils. Additionally, higher contents of the examined element were stated in the humus horizons, as indicated by the high values of concentration and Igeo indices showing high Zn pollution in the soils. The content of bioavailable zinc forms was significantly high, especially in soils with a higher metal content. Full article
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19 pages, 3084 KiB  
Article
Sources of and Control Measures for PTE Pollution in Soil at the Urban Fringe in Weinan, China
by Lei Han, Rui Chen, Zhao Liu, Shanshan Chang, Yonghua Zhao, Leshi Li, Risheng Li and Longfei Xia
Land 2021, 10(7), 762; https://0-doi-org.brum.beds.ac.uk/10.3390/land10070762 - 20 Jul 2021
Cited by 6 | Viewed by 2287
Abstract
The environment of the urban fringe is complex and frangible. With the acceleration of industrialization and urbanization, the urban fringe has become the primary space for urban expansion, and the intense human activities create a high risk of potentially toxic element (PTE) pollution [...] Read more.
The environment of the urban fringe is complex and frangible. With the acceleration of industrialization and urbanization, the urban fringe has become the primary space for urban expansion, and the intense human activities create a high risk of potentially toxic element (PTE) pollution in the soil. In this study, 138 surface soil samples were collected from a region undergoing rapid urbanization and construction—Weinan, China. Concentrations of As, Pb, Cr, Cu, and Ni (Inductively Coupled Plasma Mass Spectrometry, ICP-MS) and Hg (Atomic Fluorescence Spectrometry, AFS) were measured. The Kriging interpolation method was used to create a visualization of the spatial distribution characteristics and to analyze the pollution sources of PTEs in the soil. The pollution status of PTEs in the soil was evaluated using the national environmental quality standards for soils in different types of land use. The results show that the content range of As fluctuated a small amount and the coefficient of variation is small and mainly comes from natural soil formation. The content of Cr, Cu, and Ni around the automobile repair factory, the prefabrication factory, and the building material factory increased due to the deposition of wear particles in the soil. A total of 13.99% of the land in the study area had Hg pollution, which was mainly distributed on category 1 development land and farmland. Chemical plants were the main pollution sources. The study area should strictly control the industrial pollution emissions, regulate the agricultural production, adjust the land use planning, and reduce the impact of pollution on human beings. Furthermore, we make targeted remediation suggestions for each specific land use type. These results are of theoretical significance, will be of practical value for the control of PTEs in soil, and will provide ecological environmental protection in the urban fringe throughout the urbanization process. Full article
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17 pages, 2039 KiB  
Article
Predicting Bioaccumulation of Potentially Toxic Element in Soil–Rice Systems Using Multi-Source Data and Machine Learning Methods: A Case Study of an Industrial City in Southeast China
by Modian Xie, Hongyi Li, Youwei Zhu, Jie Xue, Qihao You, Bin Jin and Zhou Shi
Land 2021, 10(6), 558; https://0-doi-org.brum.beds.ac.uk/10.3390/land10060558 - 26 May 2021
Cited by 13 | Viewed by 2358
Abstract
Potentially toxic element (PTE) pollution in farmland soils and crops is a serious cause of concern in China. To analyze the bioaccumulation characteristics of chromium (Cr), zinc (Zn), copper (Cu), and nickel (Ni) in soil-rice systems, 911 pairs of top soil (0–0.2 m) [...] Read more.
Potentially toxic element (PTE) pollution in farmland soils and crops is a serious cause of concern in China. To analyze the bioaccumulation characteristics of chromium (Cr), zinc (Zn), copper (Cu), and nickel (Ni) in soil-rice systems, 911 pairs of top soil (0–0.2 m) and rice samples were collected from an industrial city in Southeast China. Multiple linear regression (MLR), support vector machines (SVM), random forest (RF), and Cubist were employed to construct models to predict the bioaccumulation coefficient (BAC) of PTEs in soil–rice systems and determine the potential dominators for PTE transfer from soil to rice grains. Cr, Cu, Zn, and Ni contents in soil of the survey region were higher than corresponding background contents in China. The mean Ni content of rice grains exceeded the national permissible limit, whereas the concentrations of Cr, Cu, and Zn were lower than their thresholds. The BAC of PTEs kept the sequence of Zn (0.219) > Cu (0.093) > Ni (0.032) > Cr (0.018). Of the four algorithms employed to estimate the bioaccumulation of Cr, Cu, Zn, and Ni in soil–rice systems, RF exhibited the best performance, with coefficient of determination (R2) ranging from 0.58 to 0.79 and root mean square error (RMSE) ranging from 0.03 to 0.04 mg kg−1. Total PTE concentration in soil, cation exchange capacity (CEC), and annual average precipitation were identified as top 3 dominators influencing PTE transfer from soil to rice grains. This study confirmed the feasibility and advantages of machine learning methods especially RF for estimating PTE accumulation in soil–rice systems, when compared with traditional statistical methods, such as MLR. Our study provides new tools for analyzing the transfer of PTEs from soil to rice, and can help decision-makers in developing more efficient policies for regulating PTE pollution in soil and crops, and reducing the corresponding health risks. Full article
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