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Processes
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Environmental Protection and Remediation Processes
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Environmental Protection and Remediation Processes

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Environmental and Green Processes".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 2542

Special Issue Editors

Prof. Dr. Jemmyson Romário de Jesus

E-Mail Website
Guest Editor
Department of Chemistry, Federal University of Viçosa, Viçosa 36570-900, Brazil
Interests: sustainable materials; advanced analytical methods; sample preparation
Dr. Cícero Alves Lopes Junior

E-Mail Website
Guest Editor
Department of Chemistry, Federal University of Piauí, Teresina 64049550, Brazil
Interests: advanced analytical methods; sample preparation; green technologies

Special Issue Information

Dear Colleagues,

We are inviting submissions for this Special Issue, which aims to bring together innovative research in the field of environmental protection and remediation. The focus will be on new materials, processes and analytical methodologies that contribute to pollutant mitigation and contaminant monitoring in various environmental matrices. We encourage studies that explore everything from the development of sustainable materials and advanced technologies for pollutant removal to accurate analytical methods for the detection and quantification of toxic substances. Papers that present applicable solutions to environmental challenges, including but not limited to remediation of water, contaminated soils, control of atmospheric emissions, as well as innovative approaches to environmental monitoring are welcome.

Prof. Dr. Jemmyson Romário de Jesus
Dr. Cícero Alves Lopes Junior
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. Processes 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 2400 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

  • sustainable materials
  • pollutant monitoring
  • green technologies
  • environmental chemistry
  • advanced analytical methods
  • decontamination processes
  • environmental sensors
  • effluent treatment
  • sample preparation

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

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Research

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18 pages, 1063 KiB  
Article
Multi-Model and Variable Combination Approaches for Improved Prediction of Soil Heavy Metal Content
by Xiaolong Chen, Hongfeng Zhang, Cora Un In Wong and Zhengchun Song
Processes 2025, 13(7), 2008; https://doi.org/10.3390/pr13072008 - 25 Jun 2025
Viewed by 272
Abstract
Soil heavy metal contamination poses significant risks to ecosystems and human health, necessitating accurate prediction methods for effective monitoring and remediation. We propose a multi-model and variable combination framework to improve the prediction of soil heavy metal content by integrating diverse environmental and [...] Read more.
Soil heavy metal contamination poses significant risks to ecosystems and human health, necessitating accurate prediction methods for effective monitoring and remediation. We propose a multi-model and variable combination framework to improve the prediction of soil heavy metal content by integrating diverse environmental and spatial features. The methodology incorporates environmental variables (e.g., soil properties, remote sensing indices), spatial autocorrelation measures based on nearest-neighbor distances, and spatial regionalization variables derived from interpolation techniques such as ordinary kriging, inverse distance weighting, and trend surface analysis. These variables are systematically combined into six distinct sets to evaluate their predictive performance. Three advanced models—Partial Least Squares Regression, Random Forest, and a Deep Forest variant (DF21)—are employed to assess the robustness of the approach across different variable combinations. Experimental results demonstrate that the inclusion of spatial autocorrelation and regionalization variables consistently enhances prediction accuracy compared to using environmental variables alone. Furthermore, the proposed framework exhibits strong generalizability, as validated through subset analyses with reduced training data. The study highlights the importance of integrating spatial dependencies and multi-source data for reliable heavy metal prediction, offering practical insights for environmental management and policy-making. Compared to using environmental variables alone, the full framework incorporating spatial features achieved relative improvements of 18–23% in prediction accuracy (R2) across all models, with the Deep Forest variant (DF21) showing the most substantial enhancement. The findings advance the field by providing a flexible and scalable methodology adaptable to diverse geographical contexts and data availability scenarios. Full article
(This article belongs to the Special Issue Environmental Protection and Remediation Processes)
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22 pages, 1506 KiB  
Article
Potential of Sugarcane Biomass-Derived Biochars for the Controlled Release of Sulfentrazone in Soil Solutions
by Marcos R. F. da Silva, Maria Eliana L. R. Queiroz, Antônio A. Neves, Antônio A. da Silva, André F. de Oliveira, Liany D. L. Miranda, Ricardo A. R. Souza, Alessandra A. Z. Rodrigues and Janilson G. da Rocha
Processes 2025, 13(7), 1965; https://doi.org/10.3390/pr13071965 - 21 Jun 2025
Viewed by 889
Abstract
Sugarcane bagasse-derived biochars, produced at 350 °C (B350) and 600 °C (B600), were evaluated for their capacity to modify the sorption behavior of the herbicide sulfentrazone (SFZ) in Red–Yellow Latosol (RYL) and to serve as carriers for its controlled release. Batch sorption experiments [...] Read more.
Sugarcane bagasse-derived biochars, produced at 350 °C (B350) and 600 °C (B600), were evaluated for their capacity to modify the sorption behavior of the herbicide sulfentrazone (SFZ) in Red–Yellow Latosol (RYL) and to serve as carriers for its controlled release. Batch sorption experiments indicated that SFZ exhibits low affinity for soil and undergoes sorption–desorption hysteresis. Adding B350 biochar (up to 0.30%) did not significantly affect the herbicide sorption, whereas B600 enhanced its retention. Sequential desorption assays were conducted by incorporating SFZ either directly into the soil or into the biochars, which were subsequently blended into the soil (at 0.15% w/w). The SFZ desorbed more rapidly from the soil than from the biochars, suggesting that the pyrogenic material has potential for modulating herbicide release. Phytotoxicity assessments using Sorghum bicolor confirmed that only SFZ incorporated into B350 (at 0.15% w/w) retained herbicidal efficacy comparable to its direct application in soil. These findings underscore the potential of B350 biochar as a controlled-release carrier for SFZ without compromising its weed control effectiveness. Full article
(This article belongs to the Special Issue Environmental Protection and Remediation Processes)
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20 pages, 3713 KiB  
Article
Tertiary Treatment of Pulp Industry Effluents Using Activated Biochar Derived from Biological Sludge Within a Circular Economy Framework
by Antonio Machado Netto, Marília Christian Gomes Morais Nascimento, Leonardo Souza de Caux, Marcela de Oliveira Brahim Cortez, José Pedro Rodrigues Ferreira, Keivison Almeida Monteiro and Renata Pereira Lopes Moreira
Processes 2025, 13(6), 1647; https://doi.org/10.3390/pr13061647 - 23 May 2025
Viewed by 1105
Abstract
The application of circular economy principles to the sustainable management of waste from the pulp industry presents significant environmental challenges. In this context, using biological sludge as a raw material for producing activated biochar (BC) emerges as a promising and sustainable alternative. This [...] Read more.
The application of circular economy principles to the sustainable management of waste from the pulp industry presents significant environmental challenges. In this context, using biological sludge as a raw material for producing activated biochar (BC) emerges as a promising and sustainable alternative. This study evaluated the valorization of biological sludge through the synthesis of activated BC for the removal of color, chemical oxygen demand (COD), and conductivity from the industry’s effluent. BC was produced using chemical activation with phosphoric acid (H3PO4) and potassium hydroxide (KOH), followed by pyrolysis at 500 °C and 450 °C, respectively. A central composite rotational design (CCRD) was applied to optimize the process. The optimized BCs were characterized by proximate analysis, FTIR, BET surface area, higher heating value (HHV), and SEM. Adsorption assays showed that H3PO4-activated BC achieved removal efficiencies of 52.2% for color, 23.9% for COD, and 46.2% for conductivity at a dosage of 5 g L⁻1. Conversely, KOH-activated BC did not perform effectively. The results highlight the influence of activation and pyrolysis on BC properties and confirm the potential of this approach for the tertiary treatment of industrial effluents, contributing to waste valorization and environmental sustainability. Full article
(This article belongs to the Special Issue Environmental Protection and Remediation Processes)
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Review

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27 pages, 2217 KiB  
Review
From Detection to Solution: A Review of Machine Learning in PM2.5 Sensing and Sustainable Green Mitigation Approaches (2021–2025)
by Arpita Adhikari and Chaudhery Mustansar Hussain
Processes 2025, 13(7), 2207; https://doi.org/10.3390/pr13072207 - 10 Jul 2025
Abstract
Particulate matter 2.5 (PM2.5) pollution poses severe threats to public health, ecosystems, and urban sustainability. With increasing industrialization and urban sprawl, accurate pollutant monitoring and effective mitigation of PM2.5 have become global priorities. Recent advancements in machine learning (ML) have [...] Read more.
Particulate matter 2.5 (PM2.5) pollution poses severe threats to public health, ecosystems, and urban sustainability. With increasing industrialization and urban sprawl, accurate pollutant monitoring and effective mitigation of PM2.5 have become global priorities. Recent advancements in machine learning (ML) have revolutionized PM2.5 sensing by enabling high-accuracy predictions, and scalable solutions through data-driven approaches. Meanwhile, sustainable green technologies—such as urban greening, phytoremediation, and smart air purification systems—offer eco-friendly, long-term strategies to reduce PM2.5 levels. This review, covering research publications from 2021 to 2025, systematically explores the integration of ML models with conventional sensor networks to enhance pollution forecasting, pollutant source attribution, and intelligent pollutant monitoring. The paper also highlights the convergence of ML and green technologies, including nature-based solutions and AI-driven environmental planning, to support comprehensive air quality management. In addition, the study critically examines integrated policy frameworks and lifecycle-based assessments that enable equitable, sector-specific mitigation strategies across industrial, transportation, energy, and urban planning domains. By bridging the gap between cutting-edge technology and sustainable practices, this study provides a comprehensive roadmap for researchers to combat PM2.5 pollution. Full article
(This article belongs to the Special Issue Environmental Protection and Remediation Processes)
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