Environmental Remediation doi: 10.3390/environremediat1020006

Authors: Polina Lemenkova

Soil pollution constitutes a critical global environmental challenge driven by industrialization, intensive agriculture, urban expansion, mining, and the application of synthetic agrochemicals. This article presents seven annotated Python-based Machine Learning (ML) workflows for soil pollution assessment, structured around five contaminant groups: heavy metals, pesticides, microplastics, per- and polyfluoroalkyl substances (PFAS), and excess macronutrients. The contribution has three distinct components. First, a literature synthesis drawing on more than 100 peer-reviewed studies contextualizes each contaminant group within current spectroscopic, geochemical, and ML-based detection frameworks. Second, a conceptual six-step workflow links field sampling, ML-based analysis, and scenario-based risk modelling to soil ecosystem service (SES) assessment. Third, seven executable Python scripts—implementing Random Forest regression, XGBoost with SHAP explainability, 1-D Convolutional Neural Networks, LSTM time-series forecasting, PCA-based dimensionality reduction, Monte Carlo uncertainty propagation, and GeoPandas geospatial mapping—serve as illustrative demonstrations using a benchmark dataset. All reported performance metrics are derived from synthetic data and represent workflow demonstrations, not validated field results. Radionuclides are acknowledged as an important contaminant class but fall outside the defined scope of this study. The scripts are provided as reproducible templates for adaptation to real contaminated-site datasets.

Environmental Remediation doi: 10.3390/environremediat1010005

Authors: Kuok Ho Daniel Tang

Microplastic contamination in soils is an emerging environmental challenge requiring effective and scalable remediation strategies. This review synthesizes advances in physical, chemical, biological, and hybrid approaches, focusing on mechanisms, performance, and practical applicability. Physical methods, particularly adsorption using biochar, achieve removal efficiencies exceeding 86% for 1 μm polystyrene microplastics and maintain > 85% efficiency after multiple reuse cycles, demonstrating strong durability. Filtration and aggregation systems, such as permeable reactive barriers, reach up to 81.55% removal but are less effective in co-contaminated conditions. Chemical strategies exhibit the highest efficiencies. Dielectric barrier discharge plasma achieves 96.5–98.7% degradation within 30–60 min, while electrochemical coagulation reaches ~98% removal via flocculation. Thermal treatments, including pyrolysis, enable near-complete microplastic removal (~100%) at ≥400 °C, although high energy demands limit in situ application. Chemical amendments also improve soil quality, increasing organic matter by ~7.35% and enhancing nutrient availability. Biological approaches offer sustainable but slower remediation. Microbial degradation achieves up to ~60% breakdown within 21 days, while enzyme–microbe systems reach ~21.4% over 60 days. Earthworm activity enhances fragmentation and nutrient cycling (up to 36.1%), whereas phytoremediation alone shows minimal direct degradation (<1% over 12 months). Hybrid strategies, particularly biochar-based systems, provide the most practical solutions by combining adsorption, microbial stimulation, and soil restoration, but their effectiveness in degrading microplastics needs further verification. These systems enhance microbial biomass (up to 57.67%), nutrient availability (up to 66.02%), and crop yield (up to 81.41%). Overall, physicochemical methods ensure rapid removal (>90%), biological approaches support long-term degradation, and hybrid systems offer scalable, sustainable remediation for field applications.

Environmental Remediation doi: 10.3390/environremediat1010004

Authors: Naira Ibrahim Utsab Basnet Zavier Smith Christian Sutton Vaughn Reed

Communities in Mississippi located near petrochemical refining facilities face ongoing risks from heavy metal contamination in soils, threatening environmental quality, food safety, and public health. This pilot study evaluated the phytoremediation potential of Nerium oleander and cabbage (Brassica oleracea) in a residential fence-line community within the Cherokee Forest subdivision of East Pascagoula, Mississippi, impacted by long-term petrochemical and shipyard activities. Plants were grown directly in contaminated garden soils under natural field conditions. Soil and plant tissue concentrations of lead (Pb), cadmium (Cd), zinc (Zn), and nickel (Ni) were measured using Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES) (PerkinElmer, Waltham, MA, USA). Phytoremediation effectiveness was assessed through removal efficiency, translocation factor, and bioaccumulation factor. Results showed significant reductions (p < 0.01) in all soil metals, with cadmium removal exceeding 97%. Nerium oleander exhibited substantially higher metal uptake and translocation capacity than cabbage, achieving a maximum cadmium translocation factor of 9.99 and bioaccumulation factors up to 5.67. In contrast, cabbage showed lower translocation efficiency, suggesting that limited remediation potential but suitability as a food crop after soil treatment. These findings highlight Nerium oleander as an effective, sustainable, and community-acceptable phytoremediation solution.

Environmental Remediation doi: 10.3390/environremediat1010003

Authors: Yannick Useni Sikuzani John Kikuni Tchowa Médard Mpanda Mukenza Jan Bogaert

The rapid expansion of mining activities in the Katangese Copperbelt has led to the accumulation of large volumes of mine waste, which are increasingly shaping extractive landscapes. However, their spatial dynamics and morphological evolution remain insufficiently documented. This study analyses the spatio-temporal evolution of mine waste dumps in Lualaba Province (Democratic Republic of the Congo) between 2009 and 2025 to characterise their growth patterns, morphological changes, and spatial organisation. Mine waste dumps were mapped through multi-temporal interpretation of high-resolution imagery in Google Earth Pro and analysed using GIS-based spatial metrics and statistical approaches. Results reveal a strong increase in dump area from approximately 1900 ha in 2009 to more than 6400 ha in 2025. The dynamics shift from a phase dominated by the proliferation of dumps between 2015 and 2020 to one characterised by the expansion and consolidation of existing deposits after 2020. Mutshatsha territory emerges as the main hotspot of mining intensification, while Lubudi territory displays more irregular dynamics and greater morphological changes. Spatial metrics indicate a clustered distribution of dumps around active mining areas, followed by a partial spatial expansion toward new zones after 2020. Although most dumps occur relatively close to the road network, statistical analyses show that transport accessibility has only a limited influence on their size or emergence. Overall, these results highlight the importance of morpho-spatial monitoring of mine waste dumps for understanding mining landscape transformations and for supporting the spatial prioritisation of ecological remediation strategies.

Environmental Remediation doi: 10.3390/environremediat1010002

Authors: Xuanyu Peng Kun Zhang Yao Li Kai Jiang Yongfeng Liu Yuxi Chai Lisha Duan Jian Long Hongbo Hou Peiqin Peng

The release of heavy metals into the environment due to human activities is increasing, and this has led to concern about heavy-metal contamination on farmland. Prior studies have primarily focused on short-term investigations or specific pollution sources, lacking systematic monitoring of cadmium’s long-term input-output fluxes and their mass balance at the scale of a complete farmland ecosystem. This study clarified the cadmium (Cd) pollution trends for a typical paddy system in southern China. A six-year long-term monitoring study (2019–2024 inclusive) of a Cd-contaminated paddy system in Ningxiang City, Hunan Province, China, was conducted. The Cd flux dynamics for three input pathways (atmospheric deposition, irrigation water, and fertilizer) and three output pathways (crop harvesting, surface runoff, and subsurface infiltration) were investigated. The results showed that atmospheric deposition is the primary source of Cd input, accounting for 76% of total inputs, and leads to persistent net accumulation of soil Cd. Straw removal serves as the dominant output mechanism, facilitating substantial Cd removal, representing 77% of total Cd exports, while straw retention significantly reduces export fluxes. The study found that the net Cd fluxes from 2019 to 2024 were 1.994, 2.624, 8.984, 11.299, 9.944, and 20.162 g·(hm2·a)−1, straw removal was primarily adopted during the period. A net flux analysis showed that progressive soil Cd accumulation had occurred over the study period. The results suggest that science-based straw management is critical when attempting to mitigate soil Cd pollution and enhance safe land utilization. These findings can be used to improve region-specific pollutant source control strategies and soil management policies.

Environmental Remediation doi: 10.3390/environremediat1010001

Authors: Chenxi Wu

Environmental remediation plays a pivotal role in cleaning up polluted sites, reducing future pollution, and restoring ecosystem health, creating a cleaner, safer environment for both humans and wildlife [...]