Heavy Metals, Metalloids & Organic Pollutants in Soil: Effects, Sources, and Remediation Techniques. The Use of Machine Learning Approaches for the Assessment of Soil Pollution

Dear Colleagues,

We are pleased to announce the Special Issue of Land on “Heavy Metals, Metalloids & Organic Pollutants in Soil: Effects, Sources, and Remediation Techniques. The Use of Machine Learning Approaches for the Assessment of Soil Pollution”.

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 Recently, the term heavy metals have often been replaced by the term Potentially Toxic Elements (PTEs) since some of the elements of this category can be toxic to plants, animals and humans in high concentrations.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. Dr. 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.

• Heavy Metal(oid)s & Organic Pollutants in Soil: Effects, Sources, and Remediation Techniques. Machine Learning Approaches for the Assessment of Soil Pollution in Land (8 articles)