Search Results (44)

In light of the persistent environmental degradation driven by fossil fuels, developing new energy sources is essential for achieving sustainability. The recent surge in electric vehicle adoption has underscored the significance of new energy batteries. However, the supply chains of new energy battery manufacturers face multiple sustainability risks, which impede sustainable practice adoption. To tackle these challenges, leanness philosophy is an effective tool, and Industry 5.0 enhances its efficacy significantly, further mitigating sustainability risks. This study integrates the supply chain, leanness philosophy, and Industry 5.0 by applying quality function deployment. A novel four-phase hybrid MCDM model integrating the fuzzy Delphi method, DEMATEL, AHP, and fuzzy VIKOR, identified five key sustainability risks five core leanness principles, and eight critical Industry 5.0 enablers. By examining a Chinese new energy battery manufacturer as a case study, the findings aim to assist managers and decision-makers in mitigating sustainability risks within their supply chains. Full article

Human activities at unprecedented levels have exacerbated the greenhouse effect and escalated the frequency of extreme weather. In response, the Chinese government has pledged to reach “carbon peak” by 2030 and achieve “carbon neutrality” by 2060. Leveraging the GOSAT L3 and L4B CO₂ datasets, this study investigated the spatiotemporal and vertical characteristics of atmospheric carbon dioxide (CO₂) concentration across China, alongside quantifying the relative importance of key influencing factors. The results show that there is a distinct regional disparity in CO₂ column concentration, with eastern China having a higher concentration level (406.85 × 10⁻⁶) than the western regions (400.92 × 10⁻⁶). Vertically, the concentration of CO₂ (390–420 × 10⁻⁶) reaches its peak at the near-surface layer (975 hPa) and then decreases with increasing altitude. High values of CO₂ levels in the mid-lower layer are concentrated in eastern China, while those in the upper layer are mainly located in southern China. In addition, CO₂ concentration shows seasonal variations, with the highest concentration occurring in spring (406.39 × 10⁻⁶) and the lowest in summer. Biospheric emissions and fossil fuel combustion emerge as the two most significant factors affecting CO₂ variation, with relative importance of 24% and 22%, respectively. Full article

Under the background of climate change, the risk spillover within the energy system is constantly intensifying. Clarifying the coupling relationship between entities within the energy system can help policymakers propose more reasonable policy measures and strengthen risk prevention. To estimate the risk spillover of energy-related systems, this paper constructs five subsystems: the fossil fuel subsystem, the electricity subsystem, the green bond subsystem, the renewable energy subsystem, and the carbon subsystem. Then, a quantitative risk analysis is conducted on two major energy consumption/carbon emission entities, China and Europe, based on the DCC-GARCH-CoVaR method. The result shows that (1) Markets of the same type often have more significant dynamic correlations. Of these, the average dynamic correlation coefficient of GBI-CABI (the Chinese green bond subsystem) and FR-DE (the European electricity subsystem) are the largest, by 0.8552 and 0.7347. (2) The high correlation between energy markets results in serious risk contagion, and the overall risk spillover effect within the European energy system is about 2.6 times that within the Chinese energy system. Of these, EUA and CABI are the main risk connectors of each energy system. Full article

This study investigates the annual carbon emission disparities between privately-owned electric vehicles (EVs) and internal combustion engine vehicles (ICEVs) by developing a usage-phase life cycle assessment (LCA) model, with a focus on the synergistic impacts of grid carbon intensity, driving intensity (e.g., annual mileage), and vehicle energy efficiency. Through scenario analyses and empirical case studies in four Chinese megacities, three key findings are obtained: (1) Grid carbon intensity is the primary factor affecting the emission advantages of EVs. EVs demonstrate significant carbon reduction benefits in regions with low-carbon power grids, even when the annual mileage is doubled. However, in coal-dependent grids under intensive usage scenarios, high-energy-consuming EVs may experience emission reversals, where their emissions exceed those of ICEVs. (2) Higher annual mileage among EV owners (1.5–2 times that of ICEV owners) accelerates carbon accumulation, particularly diminishing per-kilometer emission advantages in regions where electricity grids are heavily reliant on fossil fuels. (3) Vehicle energy efficiency heterogeneity plays a critical role: compact, low-energy EVs (e.g., A0-class sedans/SUVs) maintain emission advantages across all scenarios, while high-energy models (e.g., C-class sedans/SUVs) may exceed ICEV emissions even in regions with low-carbon power grids under specific conditions. The study proposes a differentiated policy framework that emphasizes the synergistic optimization of grid decarbonization, vehicle-class-specific management, and user behavior guidance to maximize the carbon reduction potential of EVs. These insights provide a scientific foundation for refining EV adoption strategies and achieving sustainable transportation transitions. Full article

Energy resources are a material basis for regional sustainable development and ecological security. However, this issue has not been adequately studied in Northwest China. Here, we consider the five northwestern provinces of China and break down the change in energy use intensity. Results show that the total energy intensity in the five northwestern provinces decreased from 2.389 tons/10⁴ Chinese yuan (CNY) in 2000 to 0.92 tons/10⁴ CNY in 2021. The main influencing factors for the decline in energy intensity are the industrial energy intensity followed by the industrial structure and the energy structure. There are eight industrial sub-sectors that contributed to the decrease in industrial energy intensity. Conversely, there are seven sub-sectors that increased industrial energy intensity. In addition, there are six sub-sectors with an energy intensity of more than 1 ton/10⁴ CNY. The convergence parameters demonstrate that the energy intensities of the five northwestern provinces did not converge to the same steady-state level, and their gap did not narrow in the short term. While the region’s overall energy intensity has shown a consistent downward trajectory, sectors heavily reliant on traditional fossil fuels—such as coal chemical processing, petroleum refining, and coking—have experienced a paradoxical upward trend in energy consumption. To address this, governments must implement targeted sector-specific measures, including upgrading technical capabilities through advanced coal gasification technologies, optimizing heat integration systems in petroleum refining processes, and streamlining intermediate production stages to minimize energy waste. Full article

Understanding the characteristics of biogas demand in rural areas is essential for on-demand biogas production and fossil fuel offsetting. However, the spatiotemporal features of rural household energy consumption are unclear. This paper developed a rural biogas demand forecasting model (RBDM) based on the hourly loads of different energy types in rural China. The model requires only a small amount of publicly available input data. The model was verified using household energy survey data collected from five Chinese provinces and one year’s data from a village-scale biogas plant. The results showed that the predicted and measured biogas consumption and dynamic load were consistent. The relative error of village biogas consumption was 11.45%, and the dynamic load showed seasonal fluctuations. Seasonal correction factors were incorporated to improve the model’s accuracy and practicality. The accuracy of the RBDM was 19.27% higher than that of a static energy prediction model. Future research should verify the model using additional cases to guide the design of accurate biogas production and distribution systems. Full article

Mitigating greenhouse gas emissions and reducing fossil fuel dependence have heightened interest in alternative fuels, particularly in agriculture, a key energy-intensive sector. This study investigates the use of the Technology Acceptance Model and the Theory of Planned Behavior to analyze Chinese farmers’ behavioral intentions to adopt alternative fuel machinery. In 2023, a total of 281 full-time farmers were sampled from Jiangsu, Sichuan, and Hebei provinces, followed by path analysis conducted using PLS-SEM. The results underline that perceived usefulness β = 0.369, p < 0.001, and social norms β = 0.185, p < 0.001 are strong drivers for the adoption of alternative fuel machinery, while perceived barriers to operate and infrastructure gaps act as inhibitors. Also, perceived benefits β = 0.235, p = 0.002, and perceived behavior control β = 0.157, p = 0.027 positively predict behavior intentions. This thus suggests that improvement in the technological infrastructure and increasing farmers’ awareness of the practical and economic benefits of alternative fuel machinery could result in a serious increase in adoption rates. This study does have weaknesses, as its focus on 50 mid-sized farms in the Midwest and utilization of self-reported data may limit the generalizability of its findings. This study, however, has major implications for policy and manufacturers to underscore the fact that targeted interventions through subsidies, training programs, and infrastructural development would be necessary to permit a transition toward sustainable energy in agriculture. Full article

The transition from fossil fuels to clean energy is a pivotal challenge in global climate efforts. China’s strategy emphasizes an orderly phase-out of fossil fuels, advocating for renewable energy as a sustainable alternative. This shift is integral to China’s “common prosperity” agenda, which seeks to harmonize economic growth with social equity and environmental sustainability. However, achieving this balance presents complex challenges, particularly in decoupling economic progress from traditional energy consumption patterns. This study addresses the critical need to evaluate how renewable energy contributes to common prosperity by developing a comprehensive indicator framework. By analyzing the dynamic evolution of prosperity levels across 30 Chinese provinces from 2008 to 2020, the research highlights regional disparities and identifies key areas for policy intervention. The findings underscore the importance of integrating renewable energy initiatives with social policies to enhance living standards and promote equitable economic growth. This paper provides valuable insights for policymakers and stakeholders aiming to advance sustainable development and achieve common prosperity in China, offering a foundation for more informed and effective energy and economic policies. Full article

With the global energy crisis and the decline of fossil fuel resources, biofuels are gaining attention as alternative energy sources. China, as a major developing country, has long depended on coal and is now looking to biofuels to diversify its energy structure and ensure sustainable development. However, due to its large population and limited arable land, it cannot widely use corn or sugarcane as raw materials for bioenergy. Instead, the Chinese government encourages the planting of non-food crops on marginal lands to safeguard food security and support the biofuel sector. The Southern China Karst Region, with its typical karst landscape and fragile ecological environment, offers a wealth of potential marginal land resources that are suitable for planting non-food energy crops. This area is also one of the most impoverished rural regions in China, confronting a variety of challenges, such as harsh natural conditions, scarcity of land, and ecological deterioration. Idesia polycarpa, as a fast-growing tree species that is drought-tolerant and can thrive in poor soil, is well adapted to the karst region and has important value for ecological restoration and biodiesel production. By integrating 19 bioclimatic variables and karst landform data, our analysis reveals that the Maximum Entropy (MaxEnt) model surpasses the Random Forest (RF) model in predictive accuracy for Idesia polycarpa’s distribution. The karst areas of Sichuan, Chongqing, Hubei, Hunan, and Guizhou provinces are identified as highly suitable for the species, aligning with regions of ecological vulnerability and poverty. This research provides critical insights into the strategic cultivation of Idesia polycarpa, contributing to ecological restoration, local economic development, and the advancement of China’s biofuel industry. Full article

This study investigates potential financing and management strategies that the Energy Corporation, a Chinese renewable energy company, could adopt in order to expand its green development projects. While China has made significant advancements in renewable energy, its heavy reliance on fossil fuels necessitates a shift towards a more sustainable energy system. To analyze the factors driving and impeding sustainability, this article provides an overview of China’s energy sector and policies. Through case studies of the Energy Corporation and other prominent renewable energy companies, the study showcases a range of demonstration projects, financing models, and management technologies that have the potential to accelerate the growth of sustainable initiatives. Recommendations from expert interviews are also provided, covering areas such as optimizing investment, monitoring distributed assets, and balancing social and environmental impacts. The results show that the Energy Corporation can effectively develop wind, solar, and energy efficiency projects nationwide by leveraging partnerships, utilizing green bonds, employing big data platforms, and engaging stakeholders, while also setting sustainability benchmarks. With a strategic approach, Energy Corporation aims to invest USD 1 billion over the next five years, targeting a renewable energy capacity of 5000 MW and a 20% reduction in CO₂ emissions. Achieving these goals would position Chinese companies as global leaders in the transition to renewable energy. The study also utilized an artificial neural network (ANN) to analyze the impact of increasing green jobs and renewable energy capacities on CO₂ emission reduction and economic growth. The results indicate that green jobs have a more significant effect on reducing CO₂ emissions compared to renewable energy capacities. When green jobs increased while energy capacities remained constant, substantial CO₂ reductions were observed, but the economic growth was only 1%. However, when there was a moderate increase in jobs alongside a four-fold increase in renewable energy capacities, economic growth reached 4%. The neural network’s prediction errors were deemed acceptable based on linear regression analysis and experimental results. Full article

Because of the pressure to meet carbon neutrality targets, carbon reduction has become a challenge for fossil fuel resource-based regions. Even though China has become the most active country in carbon reduction, its extensive energy supply and security demand make it difficult to turn away from its dependence on coal-based fossil energy. This paper analyzes the Chinese coal capital—Shanxi Province—to determine whether the green, low-carbon energy transition should be focused on coal resource areas. In these locations, the selection and effect of transition tools are key to ensuring that China meets its carbon reduction goal. Due to the time window of clean coal utilization, the pressure of local governments, and the survival demands of local high energy-consuming enterprises, Shanxi Province chose hydrogen as its important transition tool. A path for developing hydrogen resources has been established through lobbying and corporative influence on local and provincial governments. Based on such policy guidance, Shanxi has realized hydrogen applications in large-scale industrial parks, regional public transport, and the iron and steel industry. This paper distinguishes between the development strategies of gray and green hydrogen. It shows that hydrogen can be an effective development model for resource-based regions as it balances economic stability and energy transition. Full article

The Loess Plateau, with a large area of marginal land, holds the potential to produce 62–106 Tg per year of switchgrass biomass; however, the economic feasibility of producing bioenergy in the region is unclear. The farm-gate feedstock production (FGFP) cost of switchgrass was calculated in a spatially explicit way by taking the geographic variation in crop yield, soil properties, land quality, and input costs into consideration in order to evaluate the economic performance of bioenergy production. Cost–supply curves were constructed to explore the energy supply potential of switchgrass feedstock. The calculations were conducted using ArcGIS in a 1 km grid and all the evaluations were conducted under different agricultural management practice (AMP) scenarios in parallel. The FGFP costs showed significant spatial variation ranging from 95 to 7373 CNY (Chinese Yuan) per tonne⁻¹ and that the most economically desirable areas are scattered in the south and southeast region. The weighted average FGFP costs are 710, 1125, and 1596 CNY per tonne⁻¹ for small bale (SB), large bale (LB), and chipping (CP) harvest methods, respectively. The projected energy supply potential is 1927 PJ (Petajoules) per year⁻¹, of which 30–93% can be supplied below the market prices of different fossil fuels according to feedstock formats. Compared to current biomass residual pricing, 50–66 Tg (Teragrams) switchgrass feedstock is competitive. The results demonstrated that the Loess Plateau holds the potential to produce bioenergy that is economically feasible. This study provides a methodological framework for spatially explicit evaluation of the economic performance of perennial energy crops. Detailed information obtained from this study can be used to select the optimal locations and AMPs to produce feedstock production at minimum cost. Full article

Environmental pollution and climate warming have become global issues affecting human life, and the burning of fossil fuels is a major source of greenhouse gases. Ownership structure is related to energy efficiency and a change in ownership structure has a significant potential for energy saving. However, few papers have studied the impact of ownership structure on energy intensity from the perspective of technological innovation in the past. Based on panel data from 29 Chinese provinces from 2005 to 2020, we systematically investigate the impact of industrial department ownership structure on energy intensity and study the function of technological innovation in this relationship from the perspective of ownership heterogeneity by using empirical models including ordinary least squares, two-way fixed effects and random effects. The empirical results of this study reveal three findings. First, as the proportion of state-owned industrial enterprises increases by one unit, energy intensity increases by 0.803 units. However, as the proportion of Hong Kong, Macao and Taiwan-invested industrial enterprises, private industrial enterprises and foreign-invested industrial enterprises increases by one unit, energy intensity decreases by 0.847 units and 0.549 units. Second, R&D activities, FDI, capital intensity and exports can significantly reduce energy intensity, but imports can increase energy intensity. Third, the ownership structure can affect energy intensity by influencing R&D expenditure. The increase in the proportion of state-owned industrial enterprises can reduce R&D expenditure, but results in the opposite situation in private firms. Foreign-invested enterprises can reduce energy intensity by making more use of the parent company’s technology. Based on the above empirical results, we propose suggestions to reduce energy intensity, which can provide reference for government to formulate more effective energy policies and realize sustainable development. Full article

The burning of fossil fuels by humans emits large amounts of CO₂ into the atmosphere and strongly affects the Earth’s carbon balance, with grassland ecosystems changing from weak carbon sinks that were previously close to equilibrium to core carbon sinks. Chinese grasslands are located in typical arid–semi-arid and semi-arid climatic regions, and drought events in the soil and atmosphere can have strong and irreversible consequences on the function and structure of Chinese grassland ecosystems. Based on this, we investigated the response of the gross primary production (GPP) of Chinese grasslands to land–atmosphere moisture constraints, using GPP data simulated through four terrestrial ecosystem models and introduced copula functions and Bayesian equations. The main results were as follows: (1) Soil moisture trends were not significant, and changes were dominated by interannual variability. The detrended warm-season SM correlated with GPP at 0.48 and 0.63 for the historical and future periods, respectively; thus, soil moisture is the critical water stress that regulates interannual variability in Chinese grassland GPP. (2) The positive correlation between shallow SM (0–50 cm) and GPP was higher (r = 0.62). Shallow-soil moisture is the main soil layer that constrains GPP, and the soil moisture decrease in shallow layers is much more likely to cause GPP decline in Chinese grasslands than that in deep-soil water. (3) The probability of GPP decline in Chinese grasslands caused by drought in shallow soils of 0–20 and 20–50 cm is 32.49% and 27.64%, respectively, which is much higher than the probability of GPP decline in deeper soils. In particular, soil drought was more detrimental to grassland GPP in Xinjiang and the Loess Plateau. (4) The probability of soil drought causing GPP decline was higher than that of atmospheric drought during the historical period (1.78–8.19%), but the probability of an atmospheric drought-induced GPP deficit increases significantly in the future and becomes a key factor inhibiting GPP accumulation in some regions (e.g., the Loess Plateau). Our study highlighted the response of grassland ecosystems after the occurrence of soil drought, especially for the shallow-soil-water indicator, which provides important theoretical references for grassland drought disaster emergency prevention and policy formulation. Full article

Since the Industrial Revolution, fossil fuels have become the main energy source for economic development. However, fossil fuels have also been linked to serious environmental impacts. China has recently undergone rapid economic growth, but its development model demands large amounts of energy and causes severe pollution. Therefore, there has been a recent shift toward the development of coordinated strategies to achieve economic growth while minimizing energy consumption and preserving the environment. This study sought to explore the spatiotemporal evolution of the coordination degree between economic growth, energy consumption, and environmental conservation (i.e., the “3E” system) in China, thus establishing a basis to improve coordinated development and minimize regional differences. This study evaluated 30 Chinese provinces using mathematical models. Between 2000 and 2019, the coordinated development level of the components of the 3E system in China increased steadily but remained generally low. Clear spatial agglomeration was also identified at the provincial scale, with the highest values occurring on the east coast and lower values occurring in the west and middle provinces. Full article