Search Results (161)

Faced with the dual challenges of intensifying global climate change and tightening food security, achieving a balance between food security and agricultural carbon sequestration and emissions reduction has become a focal point of academic inquiry. This study quantifies agricultural carbon intensity and food security levels in Hunan Province from 2002 to 2023. By employing the Tapio decoupling model, the Logarithmic Mean Divisa Index (LMDI) method, and spatial analysis techniques, it systematically examines the decoupling relationship and driving mechanisms between agricultural carbon intensity and food security in Hunan Province. The results indicate that agricultural carbon intensity exhibits a spatial pattern of “high in the east, low in the west,” while food security levels decline from the eastern plains to the western mountainous regions. The decoupling trajectory is broadly characterized by a transition from predominantly weak decoupling toward strong decoupling; since 2016, prefecture-level cities exhibiting strong decoupling have accounted for 92.9% of all cases, displaying spatial characteristics of “overall improvement, an uneven process, and regional asynchrony.” Agricultural energy intensity, energy structure, and rural labor force size serve as positive drivers of decoupling between agricultural carbon intensity and food security, whereas agricultural economic development and per capita cultivated area exert a restraining effect. Developing differentiated emissions reduction strategies to target these key factors is essential for advancing the coordinated development of low-carbon agriculture and food security. Full article

Anhui Province is a crucial industrial province in China, and its carbon emission reduction work is of overarching importance as a model for the upgrading of traditional industrial industries in other regions of China. The exploratory practice in Anhui Province offers other regions exemplary models and methodologies to emulate, facilitating the transition of conventional sectors in the country towards a low-carbon and environmentally sustainable paradigm. This paper examines the decoupling state of industrial economic growth from resources and the environment by quantifying carbon emissions across 14 major industrial sectors in Anhui Province from 2007 to 2021. The intensity and structure of these emissions are analyzed using the Tapio decoupling model and the LMDI model, which connect resources and the environment. It is concluded that the inhibitory effect of energy structure and energy intensity on industrial carbon emissions is intensifying, while the carbon–economy decoupling index for 14 major industrial sectors is on a downward trend, and the traditional high-energy-consuming industries, particularly iron, steel, and coal, upon which Anhui Province depends, have been decoupled from industrial economic growth due to enhancements in energy structure. This paper ultimately presents a series of specific recommendations for enhancing future carbon emission reduction across a range of diverse industrial sectors. Full article

Potassium is an essential nutrient for crop growth and plays a critical role in regulating water metabolism, facilitating photosynthate transport, and improving agricultural product quality. The precise management of potash fertilizer inputs is therefore vital for enhancing agricultural productivity and promoting sustainable resource use. Using panel data for 31 provinces in China from 2000 to 2024, obtained from the China Statistical Yearbook, this study integrates the Tapio decoupling model, stochastic frontier analysis (SFA), fixed-effects models, and an XGBoost–BiLSTM hybrid model to investigate the dynamic relationship, utilization efficiency, and driving mechanisms of potash fertilizer inputs and grain production. The results indicate that the relationship between potash fertilizer inputs and grain production has shifted from an expansive negative decoupling state—characterized by faster growth in fertilizer inputs than in output—to a strong decoupling state, where fertilizer inputs decline while grain production continues to increase. This transition exhibits a clear spatial gradient, with improvements from eastern to northeastern and central regions. Potassium use efficiency (KUE) shows a steady upward trend, with significant regional heterogeneity, characterized by higher efficiency in the south, lower efficiency in the north, and notable differentiation in western regions, largely driven by climatic and soil variations. Despite these improvements, substantial potential for reducing fertilizer inputs remains across provinces. Potash fertilizer inputs exert a significant positive effect on grain production, while the cultivation of potassium-intensive crops, such as sugar crops, tobacco, and fruits, is a key driver of regional demand. Model projections suggest that from 2025 to 2030, grain production will grow at an annual rate of 1.2–1.5%, while potash fertilizer inputs will decline by 2–4% annually, indicating a transition toward greener agricultural development. These findings highlight the need for region-specific fertilization strategies, optimized fertilizer structures, and improved soil nutrient monitoring systems to ensure food security and sustainability. Full article

This study constructs an integrated analytical framework combining a Tripartite Coupling Coordination Degree Model (TCCDM), the Tapio decoupling model, and the Generalized Divisia Index Method (GDIM) to investigate the dynamic interactions and driving mechanisms among urban transportation, economic growth, and carbon emissions in Shanghai from 2000 to 2023. The results indicate that the coordination degree among the three systems evolves through three distinct phases: initial imbalance, critical transition, and high-level coordination. A three-dimensional phase diagram further reveals a marked shift from a “low-development, high-emission” pattern toward a balanced, high-quality development trajectory. Decoupling analysis demonstrates that economic growth and carbon emissions, as well as transport development and carbon emissions, have achieved significant decoupling in recent years. However, an expansive negative decoupling between economic growth and transportation highlights emerging challenges in sustaining synergistic development. Decomposition via GDIM shows that the interaction between economic development and transportation has consistently contributed to emission reduction, often exceeding the independent effects of either system. These findings underscore the role of systemic synergy in driving the nonlinear low-carbon transition of megacities. Consequently, policy interventions should adopt an integrated approach that fosters deep collaboration between green transportation transformation and high-quality economic development to effectively achieve carbon neutrality goals. Full article

Carbon emissions from crop farming are a critical component of carbon emissions from land use. This study focuses on crop farming in the Yangtze River Economic Belt. The carbon emission coefficient method, the LMDI model, the Tapio decoupling model, and the GM(1,1) gray forecasting model were employed to systematically analyze the spatiotemporal evolution, driving mechanisms, decoupling effects, and future trends of carbon emissions from crop farming in the Yangtze River Economic Belt, based on panel data from 11 provinces (municipalities) covering the period 2013–2024. The results show that the total carbon emissions from crop farming in the Yangtze River Economic Belt exhibit an inverted “U”-shaped pattern, rising initially and then declining, while carbon emission intensity continues to decrease. In terms of emission sources, methane emissions from paddy fields account for the highest proportion, emissions from agricultural inputs show a steady decline, and emissions from soil use continue to rise. Regarding driving factors, crop farming efficiency is the most significant negative driver, while regional economic development serves as the primary positive driver; the decoupling pattern has gradually transitioned from “weak decoupling” to a predominantly “strong decoupling” pattern; projection results indicate that both carbon emissions and emission intensity from crop farming in the Yangtze River Economic Belt will generally decline in the future, though regional pressure for emission reductions remains significant; agricultural industrial structures should be optimized and adjusted, with efforts focused on promoting the standardized and scaled development of organic and ecological agriculture to facilitate the green and low-carbon transformation of agriculture. Full article

While critical to the global energy transition, China’s photovoltaic (PV) sector exemplifies the ‘green paradox’ of clean energy supply chains, where the rapid expansion of solar infrastructure generates significant upstream carbon emissions. This study provides a long-term (2000–2022) empirical examination of this tension, investigating the decoupling relationship between industrial growth and embodied carbon emissions. Employing a multi-regional input–output model, we quantify the evolving carbon footprint of China’s PV manufacturing. We then apply the Tapio decoupling framework—which measures whether emissions grow slower than, or decline relative to, economic output—and structural decomposition analysis to identify the key drivers of emission changes over two decades. Finally, we project future decarbonization pathways (2023–2030) under four policy scenarios using Monte Carlo simulations. Our findings reveal a fundamental transition: since 2015, technological progress has become the dominant force for emission reductions, contributing 78% to cumulative reductions and marking a shift from a ‘scale-driven’ to a ‘technology-driven’ growth model. However, rising global demand continues to push total emissions upward, resulting in ‘weak decoupling’ (emissions grow, but slower than output) rather than the ‘strong decoupling’ (absolute emissions decline) required for carbon neutrality. Scenario analysis indicates that strong decoupling is achievable by 2030 under ambitious policy and technology scenarios, with the Technological Breakthrough scenario projecting a 39% emission reduction alongside 103% output growth. Nevertheless, even under optimistic assumptions, approximately 29,000 tons of residual emissions remain due to the inherent energy intensity of upstream processes like polysilicon production. These findings support the development of differentiated policies that balance industrial competitiveness with carbon neutrality goals, highlighting that China’s PV sector—while enabling global decarbonization—must itself undergo a deep decarbonization transition. Full article

Against the backdrop of accelerating global carbon neutrality and the full implementation of China’s “Dual Carbon” strategy, the mining industry, as an energy-intensive sector that guarantees resource supply, plays a critical supporting role in the green transformation of the industry and achieving national carbon emission reduction targets. Based on panel data from 29 provinces in China from 2000 to 2021, this study combines the Tapio decoupling index and the LMDI decomposition method to systematically characterize the evolution of carbon emissions in China’s mining industry, to accurately identify the decoupling state between carbon emissions and economic growth, and to reveal the core driving mechanism, presenting quantifiable and interpretable empirical and technical results. The results show that carbon emissions and raw ore output in China’s mining industry generally followed an evolutionary trend of “first rising, then peaking, and continuously declining”. Carbon emissions peaked in 2013 and decreased steadily afterward, reflecting remarkable achievements in green development. The decoupling relationship has shifted from weak decoupling to stable strong decoupling in 2019 and has been maintained in this state ever since, indicating that the mining industry has entered a high-quality development stage featuring coordinated economic growth and carbon emission reductions. The decomposition results confirm that the output expansion effect is the main driver of the increase in carbon emissions, while the reduction in energy intensity, optimization of the energy structure, and improvement in output efficiency constitute the key forces driving the reduction in carbon emissions, with technological progress, industrial upgrading, and clean energy substitution as the core pathways. In summary, this study empirically verifies the feasibility and effectiveness of low-carbon transformation in China’s mining industry. The realization of a stable strong decoupling state shows that this paradigm can be replicated in the green development of other energy-intensive industries. In the future, precise policy incentives, energy structure upgrades, energy efficiency technological innovation, and standardized construction of green mines can further consolidate the decoupling effects and further encourage the comprehensive transition towards a low-carbon mining industry. The findings of this study can provide a solid theoretical basis and empirical support for the formulation of carbon emission reduction policies and the design of green development pathways in China’s mining industry, with important theoretical and practical value for ensuring national resource security and facilitating the realization of the “Dual Carbon” goals. Full article

Against the backdrop of China’s dual carbon goals, understanding how terrain complexity affects the decoupling linkage between infrastructure investment and carbon emissions is crucial for developing differentiated low-carbon strategies. This study focuses on Sichuan Province, a region characterized by significant topographical heterogeneity, to investigate how terrain constraints influence carbon emission decoupling. We construct a Terrain Constraint Index (TCI) using three indicators (Digital Elevation Model (DEM), Coefficient of Variation of elevation (CV), and Terrain Position Index (TPI)) weighted by a game theory-based combination of entropy and Criteria Importance Through Intercriteria Correlation (CRITIC) methods and employ the Tapio decoupling model combined with group comparison analysis to examine the correlation between terrain complexity and decoupling performance. The key findings are as follows. (1) The TCI exhibits a “high in the west, low in the east” spatial pattern, ranging from 0.151 (Zigong) to 0.591 (Ya’an), with five distinct terrain complexity levels identified. (2) During 2001–2021, good decoupling states (strong + weak decoupling) accounted for 76.8% of all observations, indicating overall improvement in carbon emission efficiency. (3) A monotonic negative association is observed between terrain complexity and decoupling performance: the good decoupling ratio decreases from 82.5% in Low TCI regions to 62.5% in Very High TCI regions, with Mann–Whitney tests showing suggestive differences (raw p < 0.05, though not significant after Bonferroni correction). (4) Average decoupling elasticity increases from 0.182 in Very Low TCI regions to 0.705 in Very High TCI regions, demonstrating that higher terrain complexity is associated with worse decoupling outcomes. (5) Geodetector analysis reveals that infrastructure investment has the highest explanatory power (q = 0.401, p < 0.01), and the interaction between terrain factors and investment shows significant nonlinear enhancement effects (q = 0.544–0.830). These findings suggest that terrain complexity is associated with worse carbon emission decoupling, plausibly through affecting infrastructure investment efficiency, and point to the need for differentiated low-carbon strategies for regions with varying topographical conditions. Full article

Water-scarce river basins face the dual challenge of sustaining development progress while maintaining water resources carrying capacity (WRCC), yet city-scale evidence remains limited on how New Quality Productive Force (NQPF)-driven high-quality development reshapes WRCC through coupled coordination and development–pressure decoupling processes. Using a balanced panel of 15 cities in the Weihe River Basin (WRB) during 2014–2023, an integrated analytical framework was implemented by combining composite index evaluation (WRCC and the high-quality development index (HQDI)), the Coupling Coordination Degree (CCD) model, Tapio decoupling diagnosis between HQDI and total water use (TWU), and logarithmic mean Divisia index (LMDI) decomposition. The results indicate that: (1) both the HQD index and WRCC exhibited sustained growth, with their CCD improving significantly from mild imbalance to primary coordination, while a distinct spatial pattern of “Guanzhong leading, northern Shaanxi improving, and eastern Gansu stabilizing” emerged; (2) the HQDI–WRCC linkage was further supported by pooled statistical tests and a two-way fixed effects specification with city-clustered robust standard errors, confirming a significant positive association (Pearson = 0.517, p < 0.01; Spearman = 0.183, p < 0.05) and a stable positive effect of HQDI on WRCC (β = 0.194, p = 0.0088); (3) Tapio results reveal an overall transition from earlier volatility toward a later-period regime dominated by Weak Decoupling (WD) and Strong Decoupling (SD), implying that development progress became less dependent on rising TWU, although pronounced inter-city heterogeneity persisted; (4) LMDI decomposition further identified water use intensity and industrial structure as primary inhibitors of water consumption, whereas the R&D scale effect increased nearly 60-fold, emerging as a major driver of water demand. This study provides a mechanistic basis for coordinating ecological protection and high-quality development under rigid water constraints in water-scarce basins. Full article

For less-developed, carbon-dependent regions, achieving carbon decoupling while pursuing economic catch-up presents a fundamental challenge. This study investigates this persistent dilemma through the case of Jiangxi Province, China, a typical coal-reliant inland region. Utilizing data from 2000 to 2022, we estimate carbon emissions following IPCC guidelines and employ the Generalized Divisia Index Method (GDIM) to decompose emission drivers, effectively overcoming the limitation of factor independence in conventional decomposition analyses. The results identify economic scale (cumulative contribution: 97.81%) and energy consumption (51%) as the primary drivers of emission growth, while carbon intensity of output (−47.38%) emerges as the strongest inhibiting factor. The application of the Tapio decoupling model reveals that weak decoupling is the dominant state, prevailing in 91% of the study period. This persistent pattern underscores only a partial and unstable separation between economic growth and emissions, highlighting the region’s entrenched carbon lock-in. Our findings demonstrate that transcending this weak decoupling dilemma necessitates a strategic shift beyond efficiency gains. We propose that the resolution lies in accelerating structural transitions within the energy system and fostering low-carbon industrial upgrading. This study not only elucidates the dynamics of the carbon decoupling challenge in catch-up regions but also offers actionable and context-specific pathways, providing a valuable reference for analogous regions, particularly in developing and transition economies. Full article

This research focuses on Henan, a key agricultural region, analyzing data from 2000 to 2022 on cropland use and agricultural input–output. It employs the Tapio decoupling model to examine the evolution and decoupling of cropland use intensity (CLUI) and cropland use carbon emissions (CUCE) in the province. The study reveals that from 2000 to 2022, CLUI in Henan Province fluctuated in a “high-low-high” pattern over time, creating a spatial distribution with high-intensity areas in the east and lower-intensity areas at the provincial boundaries. CUCE showed a “U” shaped trend, peaking around 2015 and then gradually declining. Spatially, emissions were consistently higher in the south and lower in the north. The relationship between CLUI and CUCE transitioned from a strong negative decoupling from 2000 to 2010, to a strong decoupling from 2015 to 2020, and to a recessive decoupling from 2020 to 2022. Spatially, it evolves from a state of negative decoupling across the entire region in the early stage to nearly full coverage of strong decoupling regions in the later stage. Based on these insights, the study suggests planning strategies focusing on regional management and policy alignment, providing scientific guidance for sustainable cropland use and optimized territorial planning in Henan Province. Full article

This study examines the relationship between energy consumption and energy-related CO₂ emissions for a sample of 79 reporting entities, grouped into seven regions, over the period 2013–2023. The methodology uses three empirical tools: (i) Tapio elasticity to classify types of decoupling; (ii) Kaya–LMDI decomposition to identify factors that determine emissions; and (iii) a log-difference panel model to separate year- and country-specific effects. The results indicate a reduction in carbon intensity in all regions, more pronounced in Europe and North America. According to the Tapio classification, Europe is in recessive decoupling, the Middle East is on the verge of expansive decoupling, North and South America are in strong expansive decoupling, and Asia Pacific, Africa, and CIS show only weak signals of expansive decoupling. The LMDI results show that, in regions with strong decoupling, the decrease in carbon intensity contributes to reducing emissions. In those with weak decoupling, the effects are partially canceled out by population growth and energy demand. Finally, the fixed-effects panel model does not identify any structural decoupling at the regional level. Overall, this study contributes to the literature by separating long-term structural effects from annual fluctuations. On this basis, we provide clear guidelines for designing regional energy policies. Full article

Agricultural non-point source pollution (ANPSP) represents a major threat to water quality, yet its spatiotemporal dynamics in arid and semi-arid regions remain poorly quantified. This study establishes an integrated assessment framework to analyze the spatiotemporal patterns and driving mechanisms of ANPSP in Inner Mongolia, China, from 2002 to 2023. Using a combination of inventory analysis, pollution load equivalence assessment, and the Tapio decoupling model, we systematically examined the evolution of four pollution sources—chemical fertilizers, livestock breeding, agricultural solid waste, and rural domestic discharge—across 12 administrative regions. These methods were sequentially applied to quantify loads, standardize impacts, and evaluate the economy–environment relationship, forming a coherent analytical chain. Key results indicate the following: (1) Pollutant loads increased consistently over the study period, with chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) rising by 24.21%, 31.67%, and 31.14%, respectively, largely driven by livestock sector expansion. (2) Spatial distribution was highly heterogeneous, with Tongliao, Chifeng, and Hulunbuir contributing 50.58–58.31% of total emissions, in contrast to minimal impacts in western regions. (3) Decoupling analysis indicated variable environment–economy relations, where fertilizer use and grain output reached strong decoupling in 2010–2011 and 2018–2019, whereas livestock pollution exhibited more unstable decoupling trajectories. A cluster-derived risk zoning scheme identified Bayannur as the only high-risk area and highlighted the need for tailored management approaches in medium- and low-risk zones. This study offers a scientific foundation for targeted ANPSP mitigation and sustainable agricultural strategy formulation in ecologically vulnerable areas. Full article

Achieving decoupling between economic growth and carbon emissions is imperative for global sustainable development. This study provides a comparative analysis of this decoupling process in the European Union (EU) and BRICS countries from 1996 to 2023, employing the Tapio decoupling model and Logarithmic Mean Divisia Index (LMDI) decomposition analysis. Our findings reveal a stark contrast: the EU has achieved an average annual carbon emission growth rate of −1%, predominantly characterized by strong decoupling, whereas the BRICS nations exhibit an average growth rate of 6.26%, mainly in a state of weak decoupling. The LMDI results indicate that the intensity effect is the primary driver of carbon reduction in the EU, while the income effect is the most significant factor promoting emissions growth in the BRICS bloc. A novel finding is the identification of a near-symmetrical relationship between the energy transition effect and the fossil energy structure effect in the cumulative decomposition charts, offering a new perspective for evaluating energy system changes. The study concludes that while the EU demonstrates a more advanced decoupling pathway, significant internal disparities persist. For BRICS countries, mitigating the pressure from economic and population growth through industrial upgrading, differentiated energy policies, and enhanced renewable infrastructure is crucial. These insights provide valuable policy implications for both developed and developing economies in navigating their low-carbon transitions. Full article

Land use change is a key driver of regional carbon emissions. Understanding the mechanisms through which regional land use changes influence carbon emissions, as well as their spatiotemporal evolution, is of great significance for the optimization of land use structure and the formulation of low-carbon policies. This study, based on land use data and socio-economic data from 2002 to 2022, combines decoupling analysis models with carbon carrying capacity assessment frameworks to systematically analyze the dynamic evolution of carbon emissions from land use in Jilin Province. The results show the following: (1) From 2002 to 2022, the cultivated land area in Jilin Province remained stable and accounted for the largest proportion; the areas of water bodies and construction land expanded, while forest, grassland, and unutilized land continued to decline. (2) Total carbon emissions exhibited a “growth-stabilization-slight decline” trend, with construction land contributing the most to emissions. Spatially, carbon emissions were concentrated in the central region with Changchun at its core. (3) The overall carbon ecological carrying capacity of Jilin Province showed a fluctuating upward trend, with notable differences in carbon ecological carrying capacity across cities. (4) Cultivated land showed the highest correlation with carbon emissions, followed by woodland. The decoupling relationship between carbon emissions and economic development exhibited phase fluctuations, evolving from weak decoupling to strong decoupling and then transitioning back to weak negative decoupling. Therefore, it is recommended that effective measures be adopted to curb the excessive expansion of construction land, enhance ecological carbon sink functions, and facilitate the transformation of cultivated land from a carbon source to a carbon sink. This will promote the efficient and green utilization of land resources, advance the synergistic progress of economic development and environmental protection, and achieve the goal of regional sustainable development. Full article