Search Results (228)

Mining activities in a quarry significantly interfere with the landscape, weaken its ecological functions, disrupt the continuity of habitats and change its natural character. The aim of this study is to present a robust, transparent, and participatory methodological framework centered on the Reclamation Quality Index, which enables a comprehensive and repeatable assessment of reclamation quality. At a time when the restoration of functional, ecologically stable and long-term sustainable landscapes is increasingly important, there is a need for reliable tools to assess the quality of restoration. This article presents an original methodology for the evaluation of quarry reclamation, which combines scientific precision with practical applicability. The proposed Reclamation Quality Index is built on multidisciplinary foundations and uses the Delphi methodology, through which expert knowledge and weighted preferences enter the evaluation process. A tool designed in this way makes it possible to quantify the quality of land restoration, identify the benefits of individual interventions, support effective planning, and strengthen the strategic management of post-mining transformation. At the same time, the Reclamation Quality Index creates space for the application of the principles of ecological stability and integration of the landscape as a living, dynamic system in the process of restoration. With its structure and philosophy, the methodology represents a prospective approach to the evaluation and planning of the post-extraction landscape. Its application goes beyond academia, as it can serve as a support for environmental policymaking, landscape planning, and assessing the quality of restoration in practice. Full article

In mining areas with high groundwater levels, intensive coal mining has led to the accumulation of substantial surface water and significant alterations in regional landscape patterns. Reconstructing the ecological security pattern (ESP) has emerged as a critical focus for ecological restoration in coal mining subsidence areas with high groundwater levels. This study employed the patch-generating land use simulation (PLUS) model to predict the landscape evolution trend of the study area in 2032 under three scenarios, combining environmental characteristics and disturbance features of coal mining subsidence areas with high groundwater levels. In order to determine the differences in ecological network changes within the study area under various development scenarios, morphological spatial pattern analysis (MSPA) and landscape connectivity analysis were employed to identify ecological source areas and establish ecological corridors using circuit theory. Based on the simulation results of the optimal development scenario, potential ecological pinch points and ecological barrier points were further identified. The findings indicate that: (1) land use changes predominantly occur in urban fringe areas and coal mining subsidence areas. In the land reclamation (LR) scenario, the reduction in cultivated land area is minimal, whereas in the economic development (ED) scenario, construction land exhibits a marked increasing trend. Under the natural development (ND) scenario, forest land and water expand most significantly, thereby maximizing ecological space. (2) Under the ND scenario, the number and distribution of ecological source areas and ecological corridors reach their peak, leading to an enhanced ecological network structure that positively contributes to corridor improvement. (3) By comparing the ESP in the ND scenario in 2032 with that in 2022, the number and area of ecological barrier points increase substantially while the number and area of ecological pinch points decrease. These areas should be prioritized for ecological protection and restoration. Based on the scenario simulation results, this study proposes a planning objective for a “one axis, four belts, and four zones” ESP, along with corresponding strategies for ecological protection and restoration. This research provides a crucial foundation for decision-making in enhancing territorial space planning in coal mining subsidence areas with high groundwater levels. Full article

The Eastern Huang–Huai region of China is a representative mining area with a high groundwater level. High-intensity underground mining activities have not only induced land cover and land use changes (LUCC) but also significantly changed the watershed hydrological behavior. This study integrated the land use prediction model PLUS and the hydrological simulation model MIKE 21. Taking the Bahe River Watershed in Huaibei City, China, as an example, it simulated the hydrological response trends of the watershed in 2037 under different land use scenarios. The results demonstrate the following: (1) The land use predictions for each scenario exhibit significant variation. In the maximum subsidence scenario, the expansion of water areas is most pronounced. In the planning scenario, the increase in construction land is notable. Across all scenarios, the area of cultivated land decreases. (2) In the maximum subsidence scenario, the area of high-intensity waterlogging is the greatest, accounting for 31.35% of the total area of the watershed; in the planning scenario, the proportion of high-intensity waterlogged is the least, at 19.10%. (3) In the maximum subsidence scenario, owing to the water storage effect of the subsidence depression, the flood peak is conspicuously delayed and attains the maximum value of 192.3 m³/s. In the planning scenario, the land reclamation rate and ecological restoration rate of subsidence area are the highest, while the regional water storage capacity is the lowest. As a result, the total cumulative runoff is the greatest, and the peak flood value is reduced. The influence of different degrees of subsidence on the watershed hydrological behavior varies, and the coal mining subsidence area has the potential to regulate and store runoff and perform hydrological regulation. The results reveal the mechanism through which different land use scenarios influence hydrological processes, which provides a scientific basis for the territorial space planning and sustainable development of coal mining subsidence areas. Full article

Macrophytes are important components of aquatic ecosystems performing essential ecological functions. Their species composition and density reflect the ecological status of water bodies. The optimal ratio of morphological types of macrophytes is an important condition for preventing eutrophication. The aim of the study is to analyse the species composition, distribution, and density of macrophytes in the Vyzhyvka River (Ukraine) in a seasonal aspect (2023–2024) under constant physical and chemical characteristics of water. To assess the seasonal dynamics of water quality, changes in indicators in three representative areas were analysed. The MIR method of environmental indexation of watercourses was used to assess the ecological state of the river. The water quality in the Vyzhyvka River at all test sites corresponds to the second class of the “good” category with the trophic status of “mesotrophic”. This is confirmed by the identified species diversity, which includes 64 species of higher aquatic and riparian plants. Among the various morphological types of macrophytes, submerged rooted forms account for only 10.56% of the total species composition. To ensure a functional balance between submerged and other forms of macrophytes, a scientifically based approach is proposed, which involves the use of mineral raw materials of local origin, in particular, mining and quarrying wastes rich in silicon, calcium and other mineral components. The results obtained are of practical value for water management, environmental protection, and ecological reclamation and can be used to develop effective measures to restore river ecosystems. Full article

Anthropogenic revegetation allows effective and timely soil development in mine restoration areas. The evaluation of soil quality is one of the most important criteria for measuring reclamation effectiveness, providing scientific reference for the subsequent management of ecological restoration projects. The aim of this research was to further investigate the influence of revegetation on mine-reclaimed soils in a semi-arid region. Thus, a coal-gangue dump within the afforestation chronosequence of 1 and 19 years in Shanxi Province, China, was selected as the study area. We assessed the physicochemical properties and nutrient stock of topsoils under four revegetation species, i.e., Pinus tabuliformis (PT), Medicago sativa (MS), Styphnolobium japonicum (SJ), and Robinia pseudoacacia ‘Idaho’ (RP). A two-way ANOVA revealed that reclamation age significantly affected SOC, TN, EC, moisture, and BD (p < 0.05), while the interaction effects of revegetation type and age were also significant for TN and moisture. In addition, SOC and TN stocks at 0–30 cm topsoil at the RP site performed the best among 19-year reclaimed sites, with an accumulation of 62.09 t ha⁻¹ and 4.23 t ha⁻¹, respectively. After one year of restoration, the MS site showed the highest level of SOC and TN accumulation, which increased by 186.8% and 88.5%, respectively, compared to bare soil in the 0–30 cm interval, but exhibited declining stocks during the 19-year restoration, possibly due to species invasion and water stress. In addition, an integrated soil quality index (ISQI) and the partial least squares structural equation model (PLS-SEM) were used to estimate comprehensive soil quality along with the interrelationship among influencing factors. The reclaimed sites with an ISQI value > 0 were 19-RP (3.906) and 19-SJ (0.165). In conclusion, the restoration effect of the PR site after 19 years of remediation was the most pronounced, with soil quality approaching that of the undisturbed site, especially in terms of soil carbon and nitrogen accumulation. These findings clearly revealed the soil dynamics after afforestation, further providing a scientific basis for choosing mining reclamation species in the semi-arid regions. Full article

Coal gangue, a primary byproduct of coal mining, causes significant environmental harm due to its improper utilization. This research proposes integrating microalgae with coal gangue-derived ecological products to improve soil conditions in ecologically vulnerable coal-mining regions. A field-scale experiment at the Jintong Coal Mine tested soils amended with varying proportions of a coal gangue ecological matrix (0%, 10%, 30%, and 50%), with and without microalgae inoculation. The results demonstrated that coal gangue addition caused undesirable soil pH decreases (11.30~42.20%) while increasing total dissolved solids (506.88~524.93%) and organic matter (8.51~46.81%). These effects were mitigated by the presence of microalgae. Microalgae play a role in regulating soil nutrient profiles, enhancing enzymatic activities, and modulating the microbial community structure. For example, they restored catalase activity under the stress imposed by coal gangue and stimulated urease activity at higher coal gangue proportions. Plant growth trials revealed that adding 30% coal gangue or combining coal gangue with microalgae significantly promoted the growth of Medicago sativa L. In summary, coupling the coal gangue ecological matrix with microalgae effectively enhances soil quality. Maintaining the coal gangue addition at 30% or less in conjunction with microalgae application represents an optimal approach for soil improvement in mining areas. Full article

An accurate forest soil organic carbon (SOC) assessment aids in the ecological restoration of forest mining areas, enabling dynamic monitoring of carbon sink accounting and informed land reclamation decisions. Digital soil mapping (DSM) has enhanced soil monitoring, with machine learning and environmental covariates becoming the keys to improving accuracy. This study utilized 32 environmental variables from multispectral, topographic, and soil data, along with 142 soil samples and six machine learning methods to construct a forest SOC model for the Huodong mining district. The performance of Boruta and SHAP (SHapley Additive exPlanations) in optimizing feature selection was evaluated. Ultimately, the optimal machine learning model and feature selection method were applied to map the SOC distribution, with variable contributions quantified using SHAP. The results showed that CatBoost performed best among the six algorithms in predicting the SOC content (R² = 0.70). Both Boruta and SHAP improved the prediction accuracy, with Boruta achieving the highest precision. Introducing the Boruta model increased R² by 8.57% (from 0.70 to 0.76) compared to models without feature selection. The spatial distribution mapping revealed higher SOC concentrations in the southern and northern regions and lower levels in the central area, indicating strong spatial heterogeneity. Key factors influencing the SOC distribution included pH, the nitrogen content, sand content, DEM, and B3 band. Full article

A study was conducted concerning the perceptions of a future reservoir (4.7–8.9 square kilometres, 42.2 million cubic metres) by residents, tourists, and visitors; the location in question was the former Kotlarnia sand pit in the catchment area of the Bierawka River (tributary of the Oder River in southern Poland). Divergent concepts for the reclamation and development of the former sand pit emerged; the construction of a reservoir was initially the dominant option but was eventually abandoned despite it having the greatest acceptance among the respondents (out of the 134 respondents, 43.3% favoured the creation of a water reservoir, 29.9% favoured introducing nature protection arrangements in the area to enable spontaneous nature regeneration, and 16.4% favoured reforestation). A clear discrepancy arose between the public’s expectations related to the reclamation and development of the former sand pit in order to create a reservoir and the official position of the land user and administrator of the potential reservoir, which indicated that it no longer intended to create such a reservoir. This study indicates that in the process of developing concepts related to the reclamation and development of former mineral workings, it is essential to obtain the results of public consultation based on a diagnostic survey conducted among representatives of the local community. This is an effective tool for predicting the optimal use of sites regenerated after the damage caused by open-pit mining provided that all technical considerations related to the planned project are taken into account in advance. Full article

Land reclamation is crucial for restoring ecosystems in mining areas, improving land use efficiency, and promoting sustainable regional development. Traditional single-indicator assessments fail to capture the full complexity of reclamation, highlighting the need for a more comprehensive evaluation approach. This study combines field-measured and remote sensing data to develop multiple evaluation indices, creating a comprehensive framework to assess reclamation effectiveness. A soil quality index based on the Minimum Data Set (SQI_MDS) was developed to analyze spatial variations in soil quality, efficiently capturing key soil attributes. Remote sensing data were used to calculate the Dump Reclamation Disturbance Index (DRDI) and the Enhanced Coal Dust Index (E_CDI) to evaluate vegetation recovery and ecological improvements. The Comprehensive Evaluation Quality Index (CEQI) was introduced, synthesizing soil, vegetation, and ecological conditions for a holistic assessment. Key findings include significant soil quality improvement over time, with MDS effectively capturing variations; vegetation recovery increased with reclamation duration, though regional disparities were observed; ecological conditions steadily improved, as evidenced by a decline in ECDI values and reduced contamination; and the CEQI reflected overall improvements in reclamation effectiveness. This study offers a practical framework for coal mining land reclamation, providing scientific support for decision-making and guiding effective reclamation strategies for ecological restoration and sustainable land management. Full article

Aiming at the remediation of soil in mining areas caused by mining activities, pot experiments were conducted using water jet-loom sludge (WJLS) and biochar as soil amendments to evaluate their potential for enhancing soil fertility and microbial communities of degraded mining soils. Six treatments with varying WJLS (0%, 5%, 15%) and biochar (0%, 3%) application rates were evaluated. Results showed that WJLS can significantly improve soil organic carbon (OC), total nitrogen (TN), total phosphorus (TP), and microbial biomass, while reducing soil pH and enhancing ryegrass biomass by 1.6–4.1 times. However, a 3% biochar addition may increase the soil sodium absorption ratio (SAR). Moreover, the role of biochar was mainly reflected in the microbiological properties. The combining of WJLS and biochar increased the soil microbial biomass and obviously improved the diversity and abundance of bacteria and fungi in the soil (p < 0.05) after the amendment, especially in the biochar addition groups. At the phylum level, the relative abundance of Proteobacteria, Firmicutes, and Actinobacteriota accounted for 72.4%~84.2% of soil bacteria in all treatments, while the fungi were dominated by Ascomycota (58.30%~95.36%) and Fungi_unclassified (1.26%~38.97%), all of which were significantly related to enhanced soil properties especially OC, TN, TP, and cation exchange capacity (CEC). Overall, WJLS and biochar demonstrate strong potential as sustainable amendments for improving soil fertility and biological quality in the reclamation of mining-affected lands. Full article

Atmospheric pollution due to an increased particulate matter (PM) concentration imposes a threat for human health. This is particularly true for regions with intensive industrial activity and nature-based solutions, such as tree plantations, are adopted to mitigate the phenomenon. Here, we report on the case of the lignite complex of western Macedonia (LCWM), the largest in Greece, where extensive Robinia pseudoacacia L. plantations have been established during the last 40 years for post-mining reclamation, but their PM retention capacity and the controlling parameters have not been assessed to date. Thus, during the 2021 growth season (May to October), we determined the PM10 capture by leaves sampled twice per month, across four 10-m long transects, each consisting of five trees, and at three different heights along the tree canopy. During the same period, we also measured the leaf area index (LAI) of the plantations and collected climatic data, as well as data on PM10 production by the belt conveyors system, the main polluting source at the site. We estimated that the plantations’ foliage captures on average c. 42.85 μg cm⁻² PM10 and we developed a robust linear model that describes PM10 retention on a leaf area basis, as a function of PM10 production, LAI (a proxy of seasonal changes in leaf area), distance from the emitting source, and wind speed and foliage height within the crown. The accuracy of the estimates and the performance of the model were tested with the bootstrap cross-validate resampling technique. PM10 retention increased in spring and early summer following the increase in LAI, but its peak in August and October was controlled by the highest PM10 production, due to elevated energy demands. Moreover, PM10 retention was facilitated by wind speed, and it was higher at the lower part of the trees’ canopy. On the contrary, the PM10 load on the trees’ foliage decreased with an increasing distance from the conveyor belt system and the frontline of the plantations. Our findings support the positive role of R. pseudoacacia plantations for PM10 retention at heavily polluted areas, such as the lignite mines in Greece, and provide a model for the estimation of PM10 retention by their foliage based on basic environmental drivers and characteristics of the plantations, which could be helpful for planning their future management. Full article

Post-industrial and post-mining areas are an important element of cities historically associated with industrial activity. The transformation of degraded areas is a challenge for spatial policy, which is characterized by a substantial impact on the cultural heritage of mining and industry. The case of Piekary Śląskie shows the consequences of deindustrialization, which leads to the degradation of urban space and requires innovative revitalization strategies considering the principles of sustainable development and the concept of blue–green infrastructure. Archived topographic maps and current interactive maps of the study city were used in a spatial data analysis. The aim was to determine the directions of the spatial development of post-industrial and post-mining areas using the example of a medium-sized city located in the core of the Katowice conurbation, while considering the role of blue–green infrastructure in the revitalization process. Integrating blue–green infrastructure into the city’s planning documents may serve as a model for other urban areas, highlighting the synergy benefits between urban development and environmental protection. Such solutions support the development of a green economy to improve residents’ living conditions and increase the city’s competitiveness in the region. The specific examples of the revitalization of the areas in the Andaluzja and Julian mines and the reclamation of the brickyard in the area of Kozłowa Góra in Piekary Śląskie show that a multifunctional approach to revitalization contributes to the harmonious development of urban spaces. Full article

The rehabilitation of post-mining sites is crucial due to the severe environmental impacts of mining, including land degradation, heavy metal pollution, and loss of biodiversity. Effective reclamation strategies are essential to reverse these impacts and enable sustainable land use. This study presents the possibility of the rehabilitation of a post-mining area in Velenje, Slovenia, using artificial soils made from combustion by-products amended with lignite and organic compost, and explores the potential of lignite mine water for irrigation. This approach introduces an innovative solution that differs from the traditional methods of rehabilitating degraded areas. Physicochemical and phytotoxicity tests were conducted to determine the quality of the soil substitutes. The analysis revealed that the pH, salinity, and chemical composition of soils positively impacted Sinapis alba growth as a test plant, with the most promising compositions containing 20–30% of lignite by weight as a replacement for organic compost. Irrigation water quality parameters, such as electrical conductivity (0.87 dS/m), the sodium absorption ratio (2.09 meq/L), and boron content (0.05 mg/L), indicated a low soil dispersion risk, while the residual sodium carbonate (3.02 meq/L) suggested a medium risk. Although, the concentration of toxic elements did not exceed the threshold limits; the long-term irrigation with mine water requires the monitoring of the molybdenum levels. These results suggest the potential for using artificial soils and mine water in post-mining land reclamation but highlight the need for the monitoring of their quality. Full article

The initial variations in soil bacteria at the very beginning of reclamation still remains unclear. This study investigates the impact on bacterial communities of eight different treatments, including uncultivated land, unfertilized cultivation, chemical fertilizer, chemical fertilizer + bacterial fertilizer, manure, manure + bacterial fertilizer, manure + chemical fertilizer, and manure + chemical fertilizer + bacterial fertilizer, during the short-term reclamation of coal-mining soils. The results showed that total nitrogen, available phosphorus, soil organic carbon, microbial biomass carbon, and alkaline phosphatase activity were significantly increased in all fertilization treatments compared to uncultivated land (p < 0.05). All fertilization treatments other than chemical fertilizer harbored significantly higher activities of urease, catalase, and invertase than unfertilized cultivation (p < 0.05). The bacterial communities structures in manure-amended treatments significantly differed in uncultivated land and unfertilized cultivation and were phylotypically shifted from oligotrophic to Actinobacteria-dominant copiotrophic traits, accompanied with phenotypic succession of the enriching characteristics of Gram-positive, biofilms formation, and stress tolerance. The co-occurrence network in manure-amended treatments harbored a simple co-occurrence network, indicating more productive soils than in no-manure treatments. Manure amendment, total nitrogen, microbial biomass carbon, invertase, catalase, and soil moisture were the key driving factors. Our study underscores the bacterial initialization characteristics promoted by manure at the very beginning of coal-mining reclamation. Full article

Observing coal mining and reclamation activities using remote sensing avoids the need for physical site visits, which is important for environmental and land management. This study utilizes deep learning techniques with a U-Net and ResNet architecture to analyze Sentinel imagery in order to track changes in coal mining and reclamation over time in Tapin Regency, Kalimantan, Indonesia. After gathering Sentinel 1 and 2 satellite imagery of Kalimantan Island, manually label coal mining areas are used to train a deep learning model. These labelled areas included open cuts, tailings dams, waste rock dumps, and water ponds associated with coal mining. Applying the deep learning model to multitemporal Sentinel 1 and 2 imagery allowed us to track the annual changes in coal mining areas from 2016 to 2021, while identifying reclamation sites where former coal mines had been restored to non-coal-mining use. An accuracy assessment resulted in an overall accuracy of 97.4%, with a Kappa value of 0.91, through a confusion matrix analysis. The results indicate that the reclamation effort increased more than twice in 2020 compared with previous years’ reclamation. This phenomenon was mainly affected by the massive increase in coal mining areas by over 40% in 2019. The proposed method provides a practical solution for detecting and monitoring open-pit coal mines while leveraging freely available data for consistent long-term observation. The primary limitation of this approach lies in the use of medium-resolution satellite imagery, which may result in lower precision compared to direct field measurements; however, the ability to integrate historical data with consistent temporal coverage makes it a viable alternative for large-scale and long-term monitoring. Full article