Manganese is mostly used in the iron and steel industry and serves as an important metal mineral in the national economy. It is difficult to substantially increase the output of China’s manganese ore because it is of low grade and high impurity content. However, as a large consumer in the world, it is very important to ensure the long-term stable supply of this mineral. Collecting historical data on manganese ore in China over the past 20 years, we identified and evaluated risks during the whole process of production, supply, consumption, reserves, and trade of resources using the Volkswagen and German Federal Institute for Geosciences and Natural Resources (VW-BGR) method by selecting nine indicators: current market equilibrium, market price volatility, Reserve/production ratio, import dependence, import concentration, country risks, country concentration and future supply and demand trend. Furthermore, we assessed its economic importance by calculating the contribution of manganese ore involved in different value chains. It shows the same downward trend both in manganese ore consumption and economic importance, and the future demand of manganese ore will slow down, and the global supply will exceed demand. Based on the comprehensive evaluation of supply and demand trends in the past and future, it was concluded that the current market balance, import dependence and country concentration risks are the main driving factors for the supply risk of manganese ore in China, showing higher supply risk than that of the other factors; the resource and geostrategic risks are moderate, and may significantly reduce the supply risk if effective measures are implemented. As per the aforementioned analysis, to address the risk of supply interruption, this study provides some suggestions and measures, such as strengthening resource reserves and low-grade manganese ore utilization at home, actively exploring foreign markets, exploiting overseas resources, expanding import channels, extending the industrial chain, and adopting equity mergers and acquisitions abroad.

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Empirical models have been found to be inadequate in both accounting for breakthrough behaviors and reflecting the performance of fixed-bed systems, primarily due to their lack of a robust theoretical foundation. This limitation severely restricts their practical application. To address this difficulty, the adjustable parameters of six empirical models were first determined using the Levenberg–Marquardt iteration algorithm. The fitting quality of these models was subsequently evaluated by several error statistics, including the reduced chi-square (χ²), adjusted coefficient of determination (Adj. R²), residual sum of squares (RSS) and root of mean squared error (RMSE). In addition, the Akaike information criterion (AIC) and Bayesian information criterion (BIC) were employed to further compare these empirical models with the different parameters. The equilibrium loading, breakthrough capacity and saturation capacity were then solved by the int command of MATLAB 2023b software. Meanwhile, the breakthrough time and saturation time were determined by its fzero command. Regardless of whether empirical or mechanistic models were used, the model with the asymmetric S-shaped curve could well describe the measured breakthrough curves. Based on the parallel sigmoidal model, the predicted equilibrium loadings were 101.11, 116.69 and 129.50 mg g⁻¹, respectively, at adsorbent masses of 0.1, 0.3 and 0.5 g. This study aimed to conveniently obtain the critical process parameters through MATLAB software using empirical breakthrough models, thereby providing reliable information for the design and optimization of fixed-bed adsorbers.

Sustainable tourism is increasingly threatened by compound climate extremes, but how these hazards propagate through destination networks is poorly understood. This study quantifies the direct and cross-boundary spillover effects of compound climate extremes on tourism demand in Sichuan Province, China, by integrating 75 years of high-resolution ERA5 reanalysis data with an 11-year municipal panel dataset (2014–2024, N = 21). Employing a gravity center migration model and a two-way fixed-effects spatial econometric model, we find that prolonged droughts impose a significant direct local damage on tourism, while wet-hot compound events generate a substantial positive spatial spillover, indicating that tourists spatially substitute toward cooler neighboring destinations rather than cancelling travel. By contrast, drought and dry-hot events produce negative spillovers consistent with regional brand contagion. These contrasting propagation mechanisms (spatial substitution versus contagion) depend fundamentally on event type and are invisible to conventional non-spatial models. Our findings directly inform global sustainable development objectives related to climate action and economic growth, offering an evidence base for spatially coordinated, event-specific climate adaptation strategies in mountain tourism networks facing accelerating climate risks.