Understanding the changes in a land use/land cover (LULC) is important for environmental assessment and land management. However, tracking the dynamic of LULC has proved difficult, especially in large-scale underground mining areas with extensive LULC heterogeneity and a history of multiple disturbances. Additional research related to the methods in this field is still needed. In this study, we tracked the LULC change in the Nanjiao mining area, Shanxi Province, China between 1987 and 2017 via random forest classifier and continuous Landsat imagery, where years of underground mining and reforestation projects have occurred. We applied a Savitzky–Golay filter and a normalized difference vegetation index (NDVI)-based approach to detect the temporal and spatial change, respectively. The accuracy assessment shows that the random forest classifier has a good performance in this heterogeneous area, with an accuracy ranging from 81.92% to 86.6%, which is also higher than that via support vector machine (SVM), neural network (NN), and maximum likelihood (ML) algorithm. LULC classification results reveal that cultivated forest in the mining area increased significantly after 2004, while the spatial extent of natural forest, buildings, and farmland decreased significantly after 2007. The areas where vegetation was significantly reduced were mainly because of the transformation from natural forest and shrubs into grasslands and bare lands, respectively, whereas the areas with an obvious increase in NDVI were mainly because of the conversion from grasslands and buildings into cultivated forest, especially when villages were abandoned after mining subsidence. A partial correlation analysis demonstrated that the extent of LULC change was significantly related to coal production and reforestation, which indicated the effects of underground mining and reforestation projects on LULC changes. This study suggests that continuous Landsat classification via random forest classifier could be effective in monitoring the long-term dynamics of LULC changes, and provide crucial information and data for the understanding of the driving forces of LULC change, environmental impact assessment, and ecological protection planning in large-scale mining areas.

Visible and near infrared spectroscopy is an effective method for monitoring the content of heavy metals in soil. However, due to the difference between polluted soil with phytoremediation and without phytoremediation, the common estimation model cannot meet accuracy requirements. To solve this problem, combined with an ecological restoration experiment for soil contamination using the plant Neyraudia reynaudiana, this study explored the feasibility of using a hyperspectral technology to estimate the heavy metal content (Cd, Cr, and Pb) of soil under phytoremediation. A total of 108 surface soil samples (from depths of 0–20 cm) were collected. Inversion models were established using partial least squares regression (PLSR) and the back propagation neural network optimized by a mind evolutionary algorithm (MEA-BPNN). The results revealed that: (1) modeling with derivative-transformed spectra can effectively enhance the correlation between soil spectral reflectance and heavy metal content. (2) Compared with the BP neural network model, the estimation accuracy (R²) was improved from 0.728, 0.737, and 0.675 to 0.873, 0.884, and 0.857 using the MEA-BP neural network model. The residual prediction deviation (RPD) values for the three heavy metals Cd, Cr, and Pb using the MEA-BPNN model were 2.114, 3.000, and 2.560, respectively. Among them, the estimated model of Cd was an excellent prediction. (3) Compared with PLSR, the model prediction results established by the MEA-BP neural network had higher estimation accuracy. In summary, the use of diffuse reflectance spectroscopy to predict heavy metal content provides a theoretical basis for further study of the large-scale monitoring of soil heavy-metal pollution and its remediation evaluation in the polluted area, which is of great significance.

The ecological rehabilitation of potential toxic metal-contaminated soils in sites disturbed by mining has been a great challenge in recent decades. Phytoremediation is one of the most widely promoted renovation methods due to its environmental friendliness and low cost. However, there is a lack of in situ investigation on the influence of vegetation pattern and spontaneous succession on the rehabilitation of potential toxic metal-polluted soil. To clarify how the vegetation pattern in the early stage of restoration and the spontaneous succession influence the remediation of the soil, we investigated a metal mining dump in Sichuan, China, by field investigation and laboratory analysis. We determined the plant growth, soil fertility, and the capacity of potential toxic metals (PTMs) in metal mining soil under different initial vegetation patterns for different years to understand the role of vegetation pattern and spontaneous succession in PTM pollution phytoremediation projects. The results show that: (1) Phytoremediation with a simple initial vegetation pattern (RP rehabilitative plant pattern) which involves two rehabilitation plants, Agave sisalana and Neyraudia reynaudiana, achieves a PTM pollution index that is 9.28% lower than that obtained with the complex vegetation pattern (RP&LP rehabilitation plants mixed with local plants pattern), 21.86% lower in the soil fertility index, and 73.69% lower in the biodiversity index; (2) The phytoremediation with the 10-year RP&LP pattern was associated with a PTM pollution index that was 4.04% higher than that for the 17-year RP&LP pattern, a soil fertility index that was 4.48% lower, and a biodiversity index that was 12.49% lower. During the process of vegetation succession, if accumulator plants face inhibition of growth or retreat, the reclamation rate will decrease. The vegetation patterns influence the effect of phytoremediation. Spontaneous vegetation succession will cause the phytoremediation process to deviate from the intended target. Therefore, according to the goal of vegetation restoration, choosing a suitable vegetation pattern is the main premise to ensure the effect of phytoremediation. The indispensable manipulation of succession is significant during the succession series, and more attention should be paid to the rehabilitative plants to ensure the stable effect of reclamation. The results obtained in this study could provide a guideline for the in situ remediation of PTM-polluted soil in China.

Lead (Pb), as one of the main pollution elements, has resulted in large-scale soil pollution around the world. Even if phytoremediation can solve this problem, the selection of restoration potential plants has always been a scientific problem. As a multifunctional repair plant, Neyraudia reynaudiana can rehabilitate both polluted soils and slopes. N. reynaudiana has been widely used in terrain restoration in southern China before. This study was the first to study the growth and Pb absorption and enrichment capacity of N. reynaudiana in Xuzhou, north of the Yangtze River. In this study, N. reynaudiana was planted in soils with different lead concentrations, and the change of lead content in roots, shoots, and soils, as well as the redox enzyme, was tested and analyzed during each growth stage. The results showed that the roots could absorb Pb and transfer 79.45% to the shoots at most. With the growth of the plant, the ability to accumulate and transfer gradually increased. Moreover, when the soil Pb concentration was above 800 mg kg⁻¹, the ability to accumulate by N. reynaudiana was significantly restrained. Furthermore, superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), and peroxidase (POD) first acted on the redox response in the initial phase, while increasing the pollutant concentration or the growth of N. reynaudiana in the later stage, and the glutathione reductase (GR) redox system continued to feed back on the lead stress. This study proved that N. reynaudiana is a kind remediation plant for lead pollution soil and could repair soil with a lead pollution concentration lower than 800 mg kg⁻¹. The results provide a theoretical reference for clarifying the action mechanism and threshold value of N. reynaudiana in rehabilitating soil lead pollution and provide practical guidance for the planting proportion of N. reynaudiana.

Air pollution in the developed regions of eastern China has been intensively investigated in the past decade. However, there is a relative dearth of air pollution studies on the northwest of inland China (e.g., Xinjiang). In this work, hourly measurement data of six criteria air pollutants (PM_2.5, PM₁₀, CO, NO₂, O₃, and SO₂) for the past five years (2018–2022) from Hami and Turpan cities of eastern Xinjiang were analyzed to reveal air pollution characteristics and the distribution of potential sources. Hami and Turpan had the highest AQI values in winter due to increased coal combustion for domestic heating and unfavorable meteorological conditions. The slight elevations of AQI values in spring were caused by frequent dust storms. PM₁₀ was the most frequent main pollutant in both Hami (63.1%) and Turpan (74.1%), followed by PM_2.5 and O₃. Except for O₃, PM_2.5, PM₁₀, SO₂, NO₂, and CO exhibited a generally decreasing pattern in annual average values. But the annual average concentrations of PM₁₀ in Hami (83.5 μg·m⁻³) and Turpan (139 μg·m⁻³) in 2022 were still higher than those in eastern China. Diurnal and monthly variations of the six criteria pollutants were influenced by a combination of emission sources and meteorological conditions. The air masses in eastern Xinjiang mainly originated from the west and north and were affected by both inter-regional and intra-regional transport. Analysis of the distribution of potential sources showed that local emissions strongly impacted particulate matter pollution in winter, while regional transport played a dominant role in other seasons. O₃ showed a broad distribution of potential sources across all four seasons. Considering that the trend that O₃ pollution increased year by year, eastern Xinjiang might face a similar pollution situation as eastern China, i.e., the combined pollution of particulate matter and O₃.

Hexavalent chromium Cr(VI) contamination poses a significant risk to soil ecosystems because of its high mobility and toxicity. Identifying plant species capable of surviving under Cr stress and translocating Cr to harvestable aboveground tissues is a key step in developing phytoremediation strategies. Chromium (Cr) contamination, particularly hexavalent chromium Cr(VI), poses a substantial risk to soil ecosystems. This study evaluated the tolerance, Cr distribution, and antioxidant responses of Neyraudia reynaudiana grown in soil amended with K₂Cr₂O₇. Seedlings were exposed to five nominal Cr treatments (200, 400, 600, 800, and 1000 mg kg⁻¹) and sampled at 30, 60, 90, 120, and 150 days. Total Cr concentrations were determined in soil, roots, and shoots; translocation factor (TF) and shoot bioconcentration factor (BCF) were calculated. The activities of superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), ascorbate peroxidase (APX), and glutathione reductase (GR) were also measured. N. reynaudiana remained viable throughout the 150 d exposure period, including under the highest nominal Cr treatment. At 150 d, TF exceeded 1.0 in the Cr400–Cr1000 treatments and reached a maximum of 1.50 in the Cr600 treatment, indicating substantial root-to-shoot Cr translocation under these conditions. In contrast, shoot BCF values remained below 0.30 (0.20–0.29 at 150 d), indicating limited concentration-based Cr enrichment in aboveground tissues. Soil total Cr concentrations declined during cultivation; however, biomass-based Cr mass balance is required to quantify net plant-associated Cr removal. The activities of SOD, POD, CAT, APX, and GR showed distinct Cr-concentration- and growth-stage-dependent responses, with the overall antioxidant response generally strongest at intermediate Cr concentrations and attenuated under the highest treatment. These findings indicate that N. reynaudiana has tolerance to Cr(VI) stress and the capacity for root-to-shoot Cr translocation in a controlled pot experiment. Its practical phytoremediation efficiency requires further evaluation using biomass-based Cr accumulation, Cr speciation, and field validation. By characterizing the Cr tolerance and translocation responses of a native slope-restoration species, this study provides a physiological basis for evaluating N. reynaudiana as a candidate plant for integrated stabilization and phytoextraction-oriented remediation strategies at Cr-contaminated sites. It also identifies the key evidence needed to translate pot-scale responses into reliable site-specific remediation assessments.