The transition to sustainable energy in China is closely intertwined with environmental, social, and governance (ESG) risks within the water–energy–land–food (WELF) nexus. This study examines the complex interdependencies among these resources and evaluates the ESG challenges that may hinder or accelerate the energy transition. By integrating policy analysis and quantitative risk assessment, this research identifies key ESG risks, such as water scarcity, land-use conflicts, food security concerns, and social equity issues. The findings highlight the need for holistic governance frameworks and cross-sectoral strategies to mitigate ESG risks while ensuring a resilient and just energy transition. This study provides policy recommendations for aligning energy development with sustainable resource management, contributing to China’s long-term climate and economic goals.

Social aging significantly impacts household energy consumption patterns and demand, particularly in megacities like Shanghai. This study addresses the gap in understanding high-frequency impacts of aging on energy use by employing advanced machine learning techniques. Using Gaussian Mixture Models (GMM) and Finite Mixture Models (FMM), we analyze high-frequency hourly energy consumption data from 14,000 households in Shanghai (2016–2023) to identify distinct consumption patterns and their relationship with household characteristics. The study also simulates future scenarios incorporating demographic aging and income growth. The results reveal that an aging society not only increases overall energy demand but also significantly alters hourly consumption patterns, amplifying disparities between peak and non-peak hours. These shifts, compounded by income growth, highlight the need for tailored energy policies addressing demographic transitions. This research contributes to sustainable energy planning by providing actionable insights into the intersection of aging demographics, economic development, and urban energy consumption. The findings align with the United Nations Sustainable Development Goals (SDGs) by promoting efficient and inclusive energy strategies.

Carbon emissions and land use intensity serve as crucial indicators of land management. This paper proposes a methodological framework to elucidate the sustainability of carbon emissions in rural areas via a coordination model, scrutinizes the correlation with land use intensity, and investigates the significance of influential factors. The study focuses on village-level units within Ningde City, and finds the pronounced spatial heterogeneity characterizing the distribution of carbon emissions across different villages: (1) Villages exhibiting high levels of carbon emissions are predominantly concentrated in the southeast region, whereas those with low carbon emission levels are primarily clustered in the northwest region. The majority of the villages serve as net carbon emission sources. (2) Spatial disparities exist in the impact of land use intensity on economic benefits from carbon sources, ecological benefits from carbon sinks, and carbon emission sustainability. (3) Significant variations exist in the influence of factors affecting land use intensity, economic benefits of carbon sources, ecological benefits of carbon sinks, and the sustainability of carbon emissions in rural areas. These findings could guide governments in implementing distinct land use control policies and provide a framework for assessing carbon emission sustainability within land management strategies.

This study investigates the intricate interplay between urbanization, environmental regulation, gross domestic product (GDP), and their collective impact on agricultural land use efficiency, with a specific focus on the potential implications for a just transition. As the world grapples with growing environmental concerns and the need for sustainable development, understanding how these factors influence agricultural practices is paramount. The research employs a multi-dimensional approach, utilizing a comprehensive dataset of agricultural, economic, and environmental indicators from various regions. Through a combination of statistical analysis, econometric modeling, and case studies, the study unveils the complex relationships between urbanization, environmental regulation stringency, GDP growth, and agricultural land use efficiency. The findings highlight that the dynamic signifies China's agricultural land use efficiency initially ascending and later descending. The progressive improvement in average agricultural land use efficiency, from 1.0196 in 2005 to 1.0891 in 2021, underscores a positive trend in China's agricultural practices. It also shows that as one region enhances its agricultural land use efficiency, there is a corresponding improvement in the agricultural land use efficiency of the surrounding areas. Evidently, within all three regions, environmental regulations and GDP exert a direct influence on agricultural land use efficiency. However, it is noteworthy that the significance of urbanization is more pronounced in the eastern and middle regions, while the western region places greater emphasis on the pivotal role played by agricultural machinery total power and fiscal expenditure. This differentiation underscores the distinct drivers and dynamics shaping agricultural land use efficiency in each of these regions.

This paper examines the coal reliance of all 31 provinces in China and assesses the potential for a just energy transition towards cleaner energy sources. The authors calculate a coal reliance index (CRI) for each province based on China statistical data. The CRI takes into account factors such as coal production, consumption, and import/export, as well as GDP, population, and gender differences in mining employment. The authors highlight the importance of considering the varying degrees of coal reliance among provinces in developing effective policies for a just energy transition. The findings suggest the provincial CRI has generally been decreasing across most provinces over the past 16 years. When looking at regional CRI rankings, the northwest region has the highest average CRI compared to other regions, while the northeast region has the lowest CRI, followed by the north, east, south central, and southwest regions. The gender CRI indicates that women in China are not benefiting as much as men from economic growth and development. The paper provides insights for policymakers seeking to achieve a more sustainable and just energy system in China.

This study takes Xincun Village (to protect the privacy of the village, the name we are using is not the real name of the village) in the Golden Triangle of China's coal industry to conduct research focused on the frequent occurrence of anomic social actions by villagers after sudden wealth. Based on 160 days of structured and semistructured interviews, the results show that the anomic actions of suddenly wealthy groups mainly include self, other and socially oriented actions. The implication is that appropriate governance measures can weaken or prevent the occurrence of anomie and its devastating consequences.

Hydrological uncertainties are the main components of a sustainable framework in agricultural water management. Prediction of drought as a meteorological phenomenon should be considered to define the groundwater exploitation strategies. This study was conducted to develop a multiobjective-bivariate structure for reducing the soil moisture deficit and groundwater withdrawal in the Qazvin Irrigation District, Qazvin province, Iran. Therefore, non-dominated sorting theory, self-organizing particle swarm optimization and bivariate copula functions were incorporated under fuzzy uncertainty analysis. The results showed that the generalized extreme values and log-normal distribution functions had the best fitness on the drought peak and severity with Kolmogorov Smirnov amounts of 0.08 and 0.17, respectively. Furthermore, the goodness-of-fit tests were indicated the Joe joint function (MLE = 11) is the appropriate function for estimating the probabilistic values of drought characteristics. Proposed plans were to increase the water use efficiency for improving the expected yield production by an average of 20%. Furthermore, the standardized groundwater index was decreased from 1.1 to –4.3 for winter crops.

In recent years, major public safety incidents occur frequently in smoke-free cities. Under the complex and severe situation, the emergency preparedness capacity of smoke-free cities in China needs to be improved. In this paper, 50 fire emergency plans in smoke-free City F are taken as samples, and the qualitative comparative analysis method of clear set (csqca) is applied to explore the improvement path of emergency preparedness ability. Three influence paths are obtained to improve the emergency preparedness ability, which are information resource integration mode, business collaboration pre control mode and system route mode. The results provide reference for improving the effectiveness of pre disaster prevention, enhance the emergency preparedness capacity of smoke-free cities and improving the effect of emergency management.

The utilization of nature-inspired algorithms for logistic domains and its potential to manage uncertainty evolve solutions and conduct optimization leftovers to be an antecedent research domain. The present article has considered primary bio-inspired processes to solve the logistics problem systematically until Feb 2020. We have opted 36 articles to summarize and review. The significant algorithm has been ranked into five primary categories: ant colony optimization, particle swarm optimization, memetic algorithm, genetic algorithm, and artificial bee colony. It is evident from the outcomes that within the past 10 years, bio-inspired procedures have experienced fast progress. They have prosperously been applied for optimization and design of particularly intricate systems like logistics distribution systems. It can be deducted from the outcomes that the other algorithms in the logistics distribution’s optimization have to be enhanced, leading to the elevation of the effectiveness of logistics enterprises. Also, the policy assistance for the logistics organization has been empowered to boost the efficient and healthy progress of it. We can observe that the genetic algorithm and its hybrids have indicated the best efficiency until now. So, it is essential to investigate the logistics distribution route optimization by recent nature-inspired algorithms for optimizing the logistics and selecting a rational distribution scheme.