Spatial distribution prediction of soil heavy metals based on sparse sampling and multi-source environmental data.

Predicting the precise spatial distribution of heavy metals in soil is crucial, especially in the fields of environmental management and remediation. However, achieving accurate spatial predictions of soil heavy metals becomes quite challenging when the number of soil sampling points is relatively limited. To address this challenge, this study proposes a hybrid approach, namely, Light Gradient Boosting Machine plus Ordinary Kriging (LGBK), for predicting the spatial distribution of soil heavy metals. A total of 137 soil samples were collected from the Shengli Coal-mine Base in Inner Mongolia, China, and their heavy metal concentrations were measured. Leveraging environmental covariates and soil heavy metal data, we constructed the predictive model. Experimental results demonstrate that, in comparison to traditional models, LGBK exhibits superior predictive performance. For copper (Cu), zinc (Zn), chromium (Cr), and arsenic (As), the coefficients of determination (R²) from the cross-validation results are 0.65, 0.52, 0.57, and 0.63, respectively. Moreover, the LGBK model excels in capturing intricate spatial features in heavy metal distribution. It accurately forecasts trends in heavy metal distribution that closely align with actual measurements. ENVIRONMENTAL IMPLICATION: This study introduces a novel method, LGBK, for predicting the spatial distribution of soil heavy metals. This method yields higher-precision predictions even with a limited number of sampling points. Furthermore, the study analyzes the spatial distribution characteristics of Cu, Zn, Cr, and As in the grassland coal-mine base, along with the key environmental factors influencing their spatial distribution. This research holds significant importance for the environmental regulation and remediation of heavy metal pollution.

Spatial Distribution and Migration Characteristics of Heavy Metals in Grassland Open-Pit Coal Mine Dump Soil Interface.

The open-pit coal mine dump in the study area contains many low-concentration heavy metal pollutants, which may cause pollution to the soil interface. Firstly, statistical analysis and geostatistical spatial interpolation methods described heavy metal pollution's spatial distribution. The mine dump heavy metal pollution distribution is strongly random due to disorderly piles, but it is closely related to slope soil erosion. Furthermore, the soil deposition area is where pollutants accumulate. For example, all heavy metal elements converge at the bottom of the dump. Usually, the pollution in the lower part is higher than that in the upper part; the pollution in the lower step is higher than the upper step; the pollution in the soil deposition locations such as flat plate and slope bottom is higher than the soil erosion locations such as slope tip and middle slope. Finally, the hyperspectral remote sensing method described heavy metals pollution's migration characteristics, that the pollutants could affect the soil interface by at least 1 km. This study provides a basis for preventing and controlling critical parts of mine dump heavy metal pollution and pollution path control.

Effects of Ground Subsidence on Vegetation Chlorophyll Content in Semi-Arid Mining Area: From Leaf Scale to Canopy Scale.

Ground subsidence is the main cause of vegetation degradation in mining areas. It is of great significance to study the effects of ground subsidence on vegetation. At present, few studies have analyzed the effects of ground subsidence on vegetation from different scales. However, the conclusions on different scales may differ. In this experiment, chlorophyll content was used as an indicator of vegetation degradation. We conducted a long-term field survey in the Lijiahao coalfield in China. Based on field survey data and remote sensing images, we analyzed the effects of ground subsidence on chlorophyll content from two scales (leaf scale and canopy scale) and summarized the similarities and differences. We found that, regardless of leaf scale or canopy scale, the effects of subsidence on chlorophyll content have the following three characteristics: (1) mining had the least effect on chlorophyll content in the neutral area, followed by the compression area, and the greatest effect on chlorophyll content in the extension area; (2) subsidence had a slight effect on chlorophyll content of Caragana korshins, but a serious effect on chlorophyll content of Stipa baicalensis; (3) chlorophyll content was not immediately affected when the ground sank. It was the cumulative subsidence that affects chlorophyll content. The difference between leaf scale and canopy scale was that the chlorophyll content at canopy scale is more affected by mining. This means that when assessing vegetation degradation, the results obtained by remote sensing were more severe than those measured in the field. We believe that this is because the canopy chlorophyll content obtained by remote sensing is also affected by the plant canopy structure. We recommend that mining and ecological restoration should be carried out concurrently, and that ground fissures should be taken as the focus of ecological restoration. In addition, Caragana korshins ought to be widely planted. Most importantly, managers should assess the effects of ground subsidence on vegetation on different scales. However, managers need to be aware of differences at different scales.

Analysis of Plant and Soil Restoration Process and Degree of Refuse Dumps in Open-Pit Coal Mining Areas.

Vegetation and soil restoration are the key to ecological reconstruction in the damaged areas of open-pit coal mining areas. Ecological stability is an important indicator of the degree of ecological restoration. In this study, the ecological stability and the process of plant and soil restoration were investigated at different refuse dumps in three coal mines, namely, the Wulanhada (WLHD) coal mine, the Liulingou (LLG) coal mine, and the Jinzhengtai (JZT) coal mine, in Jungar Banner. Results show that organic matter, total N, available N, and available K increased with the increase in restoration age at the two coal mines of WLHD and LLG. In the JZT coal mine, organic matter, total N, and available K firstly increased, and then slightly decreased with the increase in restoration age. The redundancy analysis indicates that most reclaimed mine soil properties (including soil moisture content, organic matter, total N, and available K) are positively correlated with plant species diversity in the three coal mines, while soil pH and soil bulk density showed a negative correlation with plant species diversity. Plant parameters increased with the years since revegetation, except the Pielou index for the WLHD coal mine, and the Pielou and Margalef indexes for the JZT coal mine. The Euclidean distance between the restoration areas and the natural reference areas decreased with the increase in restoration age. Our findings suggest that, in the three coal mines, the change law of ecological stability conformed to the logistic succession model. The same degree of ecological stability in different refuse dumps may correspond to different degrees of vegetation and soil development. This study emphasizes that ecological restoration in mining areas could benefit the structure of the plant community and the recovery of soil properties, which would eventually improve the ecological stability of coal mining areas.

Geographic distribution of heavy metals and identification of their sources in soils near large, open-pit coal mines using positive matrix factorization.

Mining activities are considered the most important factor causing heavy metal accumulation in surface soil and it is important to understand the spatial distribution and source of heavy metals in typical steppes. In this study, the contents, spatial distribution, and sources of heavy metals were determined using geostatistical analyses, multivariate statistical analyses, and a positive matrix factorization (PMF) model using 152 soil samples collected from a grassland near the Sheng-Li coal base. The results shows that the mean concentration of heavy metals is low and does not threaten the quality of the local soil. However, the concentrations of eight heavy metals (Cu 15.04 mg kg-1, Zn 49.30 mg kg-1, Cd 0.11 mg kg-1, Pb 20.00 mg kg-1, Se 0.12 mg kg-1, Ge 1.45 mg kg-1, As 9.06 mg kg-1, and Sn 2.52 mg kg-1) are higher than their mean background values in soil in Inner Mongolia. High coefficients of variation for the heavy metals, especially Ge (1.03), and As (0.56), indicate that the concentrations of the elements are affected by the presence of the open-pit mines. Multivariate statistical and geo-statistical analyses show that Ge and As are highly correlated (R2 = 0.67, P < 0.01), suggesting that they have the same source. Using geostatistical and PMF models, we identified five potential pollution sources in the study area: 1) Industrial pollution (21.2 %), which includes smelting activity and open-pit coal mines, as suggested by elevated levels of Zn, Cd, Ge, and Cu; 2) Germanium mining (7.6 %), as indicated by higher levels of Ge and As; 3) Natural sources (37.2 %), as indicated by higher levels of Mn and Ni; 4) Coal mining activity (8.5 %), as indicated by higher levels of Sn and Cr; 5) Coal conveyor belts and high vehicular traffic, as indicated by elevated levels of Pb and Se. Taken together, the results of this study indicate that the coal base has a significant effect on the heavy metal concentration in the grassland. Therefore, the identification of the spatial distribution of heavy metals in the area may be key to controlling the pollution in the grassland. The results of this study can help to reduce pollution sources, cut down on pollution transport. So that zonal pollution control and ecological protection in the typical steppe region is achieved.

Assessment of Landscape Ecological Health: A CaseStudy of a Mining City in a Semi-Arid Steppe.

The ecological status of the semi-arid steppes in China is fragile. Under the long-term and high-intensity development of mining, the ecological integrity and biodiversity of steppe landscapes have been destroyed, causing soil pollution, grassland degradation, landscape function defect, and so on. Previous studies have mainly focused on ecosystem health assessment in mining areas. Landscape ecological health (LEH) pays more attention to the interactions between different ecosystems. Therefore, the ecological assessment of mining cities is more suitable on a landscape scale. Meanwhile, the existing LEH assessment index systems are not applicable in ecologically fragile areas with sparse population, underdeveloped economy, and in relatively small research areas. The purpose of this study was to construct a LEH assessment index system and evaluate the LEH of a mining city located in a semi-arid steppe. Xilinhot is a typical semi-arid steppe mining city in China. The contradictions between the human, land and ecological environment are serious. A new model Condition, Vigor, Organization, Resilience, and Ecosystem (CVORE) model was constructed that integrated five subsystems (services) from the perspectives of ecology, landscape ecology, mining science, and geography. This study used the CVORE model to systematically evaluate the LEH in Xilinhot city in terms of five LEH levels, including very healthy, healthy, sub-healthy, unhealthy and morbid landscape. Research results show that the areas of the very healthy, healthy, sub-healthy, unhealthy and morbid landscapes are 13.23, 736.35, 184.5, 66.76 and 20.63 km², respectively. The healthy landscapes area accounts for 72.08% and most grasslands are healthy. The sub-healthy landscapes are mainly located around areas with higher disturbances due to human activities. The morbid or unhealthy landscapes are concentrated in the mining areas. The proposed CVORE model can enrich the foundations for the quantitative assessment of Landscape Ecological Health of Mining Cities in Semi-arid Steppe (LEHMCSS). This study provided a new LEH assessment approach (CVORE model), which can support landscape ecological restoration, ecological environmental protection and urban planning of the semi-arid steppe mining cities.

The challenges of reusing mining and mineral-processing wastes.

Mining and mineral-processing wastes are one of the world's largest chronic waste concerns. Their reuse should be included in future sustainable development plans, but the potential impacts on a number of environmental processes are highly variable and must be thoroughly assessed. The chemical composition and geotechnical properties of the source rock determine which uses are most appropriate and whether reuse is economically feasible. If properly evaluated, mining waste can be reused to reextract minerals, provide additional fuel for power plants, supply construction materials, and repair surface and subsurface land structures altered by mining activities themselves.