The utilization of renewable energy (RE) is a meaningful way to realize the low-carbon transformation of energy systems. However, due to the imbalance of resources, economy, technology, society, and environment among regions, the coordinated development of regional RE may be restricted by different factors, which brings challenges to the formulation of relevant development policies. This paper focuses on the development of RE in 30 provinces in China from 2011 to 2019. It uses the AHP-EM integrated evaluation model to evaluate the constructed multilayer indicator system for the comprehensive development of RE. The characteristics of the coupling and coordination relationship between indicators are explored, and the critical driving factors affecting the coordinated development and change in RE in different regions are quantitatively identified through the logarithmic mean Divisia index method. The results show that the comprehensive development level of RE in each province is relatively low, and the relatively high-level areas gradually move eastward in terms of spatial distribution. The degree of coupling and coordination between indicators is still in a low-level coupling stage, and RE in each region has not achieved coordinated development. In addition, the comprehensive development of regional RE is consistent with the spatial evolution characteristics of the degree of coordination among indicators, emphasizing the importance of coordinated development among indicators for RE. These findings will provide broader insights for improving the comprehensive development level of regional RE and formulating differentiated policies.

The medium and long-term demand prediction for water resources is critical to the country’s macro-allocation of water resources and the formulation of a long-term regional economic development strategy. However, the official prediction report of China’s water resources was created ten years ago, and its results are far from accurate in practice making it difficult to direct China’s water resource planning in the coming ten years. By introducing the demand forecasting method for the first time, this study built a mathematical prediction model that integrates “data constraint + mathematical prediction + actuarial prediction”. The conclusions are as follows: (1) The new method developed in this research is more accurate than previous prediction methods and has a higher degree of matching with actual data. Despite the problem of trend extrapolation, this model can accurately understand the long-term trend. However, the amount of data must be calculated. (2) China’s consumption of total water, agricultural water, industrial water, domestic water, and ecological water will predict to be 552.9 billion m³, 319.1 billion m³, 95.7 billion m³, 95.5 billion m³ and 42.6 billion m³ in 2030, respectively, as well as 504.7 billion m³, 281.1 billion m³, 61.4 billion m³, 101.4 billion m³, and 60.8 billion m³ in 2050, respectively, indicating obvious structural changes. (3) China’s industrial structure evolves frequently; therefore, water resource forecasting must account for changes in industrial structure as well as geographical variances. In North China, agricultural water demand will fall, but ecological water investment will rise. The planning and distribution of the nation’s water resources will significantly be influenced theoretically and practically by the development of this methodology study. This method is universal and can be used for long-term prediction of future water demand in other countries.

This study investigates the heterogeneity and driving factors of carbon emission reduction in developed countries, providing insights for formulating carbon neutrality strategies and plans in China. Firstly, typical developed countries worldwide are categorized into four modes: high energy consumption–high emissions, high energy consumption–low emissions, low energy consumption–low emissions and low energy consumption–high emissions, based on the “per capita energy consumption–emission intensity” classification method. Secondly, the LMDI decomposition model is employed to calculate the carbon emission-reduction driving effects of each mode, thereby analyzing the evolution path of carbon emissions. Finally, carbon emission-reduction policy recommendations are proposed based on the current situation of provincial carbon emissions in China. The research findings are as follows: (1) Carbon emissions in developed countries follow the Environmental Kuznets Curve (EKC) law, exhibiting an inverted U-shaped trajectory. In the per capita GDP range of USD 12,000–20,000, carbon emissions in most countries have reached or are close to their peak, with per capita carbon emissions in different modes decreasing and tending towards a level of 4000 kg/person. (2) There is heterogeneity in the EKC of carbon emissions in developed countries, which can be divided into technological, structural, comprehensive and clean types based on differences in emission-reduction factors. The trajectories of carbon emissions in most developed countries follow a clean path, while those in newly developed countries are constrained by environmental pressures and are expected to be between mixed and structural types before the emission peak, and tend towards a clean type after the peak. (3) Energy clean-up is the most direct and efficient method for carbon emission reduction, which can significantly and efficiently achieve carbon emission reduction. Industrial restructuring and technological progress play a significant role in suppressing carbon emissions. Policy recommendations are proposed as follows: first, reduce the proportion of fossil energy and increase energy cleanliness; second, promote industrial restructuring to reduce energy dependence; third, enhance production technology and improve energy-utilization efficiency; fourth, increase technological breakthroughs to support low-carbon transformation; fifth, correctly recognize the differences among provinces in China and formulate differentiated carbon emission-reduction policies.

Workover operations significantly impact the service life and gas production capacity of coalbed methane (CBM) wells and are crucial for optimizing resource exploitation. To investigate workover operations’ impact on coal seam reservoirs, the authors designed a series of experiments and obtained the following results: (1) The workover operation induced a phase transition in the solid-liquid composition produced by the CBM well, indicating changes in the coal reservoir’s internal structure. (2) During the stable production stage before and after the workover, the proportion of Na⁺, Cl⁻, Ca²⁺, and Total Dissolved Solids (TDS) in the water samples showed a downward trend as a whole, while the HCO₃⁻; after the workover, the Na⁺, Cl⁻, Ca²⁺, and TDS all increased suddenly, while the HCO₃⁻ decreased. (3) While inorganic minerals predominated in the precipitation material during the stable production stage pre-workover, their proportion decreased post-workover, with a noticeable shift in their qualitative composition. (4) It is an indisputable fact that workover operations cause physical and chemical damage to coal seam reservoirs. During workover operation, how to avoid damage and conduct benign reconstruction to the reservoir will be the direction of our future efforts. The experimental results provide valuable insights that can guide the optimization of CBM workover operations and inform the strategic planning of subsequent drainage activities.

The ecological consequences of hydraulic engineering on riverine environments have intensified the need for scientifically grounded ecological flow regimes. To ensure habitat suitability during critical fish spawning periods, this study developed habitat preference curves by correlating physiological parameters with key hydro-environmental drivers. A habitat suitability index (HSI) model was established using fuzzy logic, integrated with a genetic algorithm (GA) to simultaneously optimize fuzzy membership functions and inference rules. This model was applied to simulate the relationship between the weighted usable area (WUA) and discharge for various fish egg types in the reach downstream of the Fengman Dam, ultimately facilitating the determination of an optimized ecological pulse flow hydrograph. The results reveal distinct hydro-environmental preference variations among species. Specifically, drifting eggs require specific hatching cycles supported by higher flow magnitudes and velocities. Conversely, adhesive eggs experience a significant reduction in suitable habitat area under high-flow and high-velocity conditions. These findings suggest that reservoir water resource allocation must be tailored to the life-history requirements of target species to maximize spawning success. This study provides a robust scientific framework for eco-friendly reservoir scheduling and the conservation of regulated river ecosystems.