Adnan Ahmed

Heavy metals in agricultural soils pose risks to ecosystems and public health, influenced by industrial emissions, atmospheric deposition, and agricultural practices. This study assesses contamination in reforested farmlands following unauthorized development removal in conservation areas of Baoqizhai and Dayangyu (Jiaodai Town, Lantian County, Xi’an City, northern Qinling foothills, China). Spatial distributions of chromium (Cr), arsenic (As), nickel (Ni), cadmium (Cd), lead (Pb), copper (Cu), and zinc (Zn) were quantified using inductively coupled plasma optical emission spectrometry (ICP-OES). Pollution levels were evaluated with the geo-accumulation index (Igeo) and potential ecological risk index (PERI). Mean concentrations were 65.4 mg/kg (Cr), 12.1 (As), 29.8 (Ni), 0.36 (Cd), 32.7 (Pb), 42.5 (Cu), and 110.3 mg/kg (Zn), generally below China’s Grade II standards except for Cd, which approached limits and contributed the highest risk. I _geo values indicated unpolluted to moderately polluted conditions (maximum Cd I _geo = 0.28), while PERI showed low to moderate overall risk ( RI = 62.02), primarily from Cd ( Er = 36.0). Atmospheric deposition, sewage irrigation, and industrial/agricultural activities were identified as the main sources through correlation and principal component analysis. The study evaluates reforestation’s effects on legacy pollution and recommends ongoing Cd monitoring and phytoremediation to protect soil health and biodiversity in this ecologically sensitive region.

In arid open-pit mines, rainfall-triggered slope instability presents significant risks, but quantitative thresholds are poorly defined due to limited integration of transient seepage and stability in low-permeability soils. This study fills this gap by using GeoStudio’s SEEP/W and SLOPE/W modules to simulate rainfall effects on a moderately steep-slope (51° average) limestone mine slope in Ningxia’s Kazimiao Mining Area (annual precipitation: 181.1 mm). The novelty lies in identifying a 12 h saturation window under intense rainfall (≥100 mm h⁻¹), during which pore water pressure stabilizes as soil reaches saturation, creating an “infiltration buffering effect” driven by arid soil properties (hydraulic conductivity: 2.12 × 10⁻⁴ cm s⁻¹). Results show that the factor of safety (FOS) drops sharply within 12 h (e.g., from 1.614 naturally to 1.010 at 200 mm h⁻¹) and then stabilizes, with FOS remaining >1.05 (basically stable) under rainfall intensities ≤ 50 mm h⁻¹, but drops into the less-stable range (1.00–1.05) at 100–200 mm h⁻¹, reaching marginal stability (FOS ≈ 0.98–1.02) after 24 h of extreme events, according to GB/T 32864-2016. Slope protection measures increase FOS (e.g., 2.518 naturally). These findings quantify higher instability thresholds in arid compared to humid regions, supporting regional guidelines and informing early-warning systems amid climate-related extremes. This framework enhances sustainable slope management for mines worldwide in arid–semi-arid zones.

Heavy metal contamination poses significant environmental and health risks, necessitating cost-effective and sustainable remediation strategies. Biochar, a carbon-rich material derived from the pyrolysis of biomass, has emerged as a promising solution for mitigating heavy metal pollution. This review explores the underlying mechanisms of biochar-mediated heavy metal remediation, including adsorption, precipitation, ion exchange, and complexation. It highlights critical factors, such as feedstock selection, pyrolysis conditions, and the physicochemical properties of biochar, that influence its efficacy. Additionally, the review identifies challenges, including variability in biochar properties and long-term environmental impacts, while discussing advanced modification techniques to enhance the performance of biochar. By synthesising current research, this study highlights the importance of biochar as a sustainable and economically viable tool for soil remediation. The findings provide valuable insights for developing targeted biochar applications to mitigate heavy metal contamination, thereby contributing to enhanced environmental quality and agricultural sustainability. Moreover, emerging technologies, such as magnetic or electric field-responsive biochars, nano-engineered composites, and machine learning-guided design, offer promising avenues for creating intelligent remediation materials and accelerating field deployment.

Ecosystem service value (ESV) represents the benefits that people obtain directly or indirectly from ecosystems. Based on the land use/land cover (LULC) data of Qinghai Province in 2000, 2010, and 2018, combined with the equivalent factor method, land use dynamic degree, land use transition matrix, and coefficient of sensitivity (CS), the ESV of Qinghai Province is calculated. This study found that ESV in Qinghai Province exhibited significant variations. It has increased from CNY 750.77 billion to CNY 772.4 billion from 2000 to 2018. The results show that grassland and unused land are the main land use types, with a total coverage of more than 88% in the study area. The land use dynamic degree result demonstrates that the dynamic degree of built-up land is the highest. The CS analysis found that the CSs of the ESV of each land use type in Qinghai Province were less than 1 during 3 periods, 2000–2010, 2010–2018, and 2000–2018, indicating that the ESV in the area lacks elasticity and the result is reliable. This study can provide scientific support for the sustainable development of ecosystems and land use planning in Qinghai Province under global climate change.

The Qinling region in central China, known as the ‘Dragon Vein of China’, is a vital ecological barrier facing significant soil erosion challenges. This study aims to enhance soil erosion management and analyse the spatiotemporal changes of soil erosion in the northern foothills of the Qinling Mountains. We collected data on precipitation, terrain, land use types, and soil in the designated region. Using GIS technology and the Revised Universal Soil Loss Equation (RUSLE) model, we created a detailed soil erosion map and analysed its evolution from 2018 to 2022. Results show a significant reduction in soil erosion in 2020–2021 despite a general upward trend in other years. Innovation includes integrating remote sensing with RUSLE for high-precision mapping and introducing a hierarchical approach for erosion risk assessment. The study found erosion peaks in summer and autumn, with higher levels in the southern parts compared to the northern parts. Influential factors include climate variables, human activities, soil, and vegetation types. The average soil erosion modulus in 2023 is 233.515 t/(km²·a), with total soil erosion of 85,233.046 t/a, mainly concentrated in the valley and mountain basin areas. This research provides a theoretical basis for improving the natural environment and implementing comprehensive soil and water conservation measures in the Qinling region, offering a model for similar ecological regions globally.

Global climate change has intensified extreme rainfall events, significantly increasing flood risks. This study assesses flood disaster risks in the Northern foothills of Qingling Mountain, a crucial area for ecological and economic stability within the Yellow River Basin, utilising data from the Coupled Model Intercomparison Project Phase 6 (CMIP6). We analysed future daily rainfall data from 2024-2100 across four selected models, employing multi-model ensemble averaging, hyperbolic interpolation, and Delta downscaling methods. Six extreme rainfall indices, including RX1day and RX5day, were used to evaluate spatial and temporal variations. An innovative flood disaster risk assessment model was developed, integrating the game combination weighting method, entropy weight method, and Analytic Hierarchy Process (AHP). This model incorporated population density, elevation, GDP, and land use to assess flood risk and vulnerability under two scenarios (SSPs245 and SSPs585) for 2040-2060 and 2070-2090. Key findings reveal that the maximum one-day precipitation (RX1day) is projected to increase by up to 15% under the SSPs585 scenario for 2070-2090, while the maximum five-day precipitation (RX5day) could rise by 12%. The flood risk assessment highlighted that areas with higher population density and economic activity are increasingly vulnerable, with risk levels projected to rise by 20% under SSPs585 compared to SSPs245 by the end of the century. This study’s innovative approach and comprehensive risk assessment framework significantly enhance our understanding of future flood risks in the Northern foothills of Qingling Mountain. The insights provided are essential for improving flood control infrastructure and disaster management strategies, ensuring the region’s ecological and economic resilience amidst escalating climate change impacts.