Search Results (305)

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

With global climate challenges intensifying, the cement industry, as a major CO₂ emitter, has attracted significant attention regarding its emission reduction potential and strategies. Advanced economies like the European Union use carbon pricing to spur innovation, while emerging countries focus on incremental solutions, such as fuel substitution. Combining LMDI decomposition and the LEAP model, this study examines Jiangsu Province as a test bed for China’s decarbonization strategy, a highly efficient region with carbon intensity 8% lower than the national average. Historical analysis identifies carbon intensity, energy mix, energy intensity, output scale, and economic effects as key drivers of emission changes. Specifically, the reduction in cement production, real estate contraction, lower housing construction, and reduced production capacity are the main factors curbing emissions. Under an integrated technology strategy—including energy efficiency, fuel and clinker substitution, and CCS—CO₂ emissions from Jiangsu’s cement sector are projected to decrease to 17.28 million tons and 10.9 million tons by 2060 under high- and low-demand scenarios, respectively. Clinker substitution is the most significant CO₂ reduction technology, contributing about 60%, while energy efficiency gains contribute only 3.4%. Despite the full deployment of existing reduction methods, Jiangsu’s cement industry is expected to face an emissions gap of approximately 10 million tons to achieve carbon neutrality by 2060, highlighting the need for innovative emission reduction technologies or carbon trading to meet carbon neutrality goals. Full article

Under the influence of water resource conservation policies, the annual water diversion volumes in irrigation areas have been steadily decreasing, leading to substantial changes in regional cropping systems. These shifts have profoundly impacted agricultural reactive nitrogen (Nr) emissions and surface water quality. This study focuses on the Yellow River Irrigation area of Ningxia, China, and employs a life cycle assessment method to quantitatively analyze fluctuations in the nitrogen footprint (NF) and gray water footprint (GWF) across three cropping systems—rice-maize intercropping, rice monoculture, and maize monoculture—during 2021–2023. The results indicate that rice monoculture exhibited significant variability in NF values (197.89–497.57 kg Neq·ha⁻¹), with NO₃⁻ leaching identified as the primary loss pathway (102.33–269.48 kg Neq·ha⁻¹). The GWF analysis revealed that in 2021, the region’s GWF peaked at 23.18 × 10⁴ m³·ha⁻¹, with water pollution predominantly concentrated in Pingluo County (8 × 10⁴ m³·ha⁻¹). LMDI analysis identified nitrogen fertilizer application as the main contributor to variations in NF, while surface water pollution was indirectly influenced by crop yield. Furthermore, gray correlation analysis highlighted a significant coupling relationship between NF and GWF, with nitrogen fertilizer application having the most pronounced impact on GWF. Therefore, in the face of the gradual tightening of water resources in the irrigation areas, the current situation of reduced water diversion should be adopted as early as possible, and initiatives such as the reduction of nitrogen fertilizer application and the adjustment of the planting area of dryland crops should be accelerated to cope with the problem of nitrogen pollution brought about by changes in the cropping system. Full article

As a significant source of greenhouse gas emissions, objectively understanding the quantity of emissions from the livestock industry and their spatiotemporal evolution is crucial for advancing low-carbon and green development in regional livestock industries. Therefore, based on the Life Cycle Assessment (LCA) method, this study estimated greenhouse gas emissions from the livestock industry across 11 municipal regions in Jiangxi Province from 2002 to 2022, revealing the spatiotemporal characteristics of these emissions. The study also employed the Logarithmic Mean Divisia Index (LMDI) model to analyze the influencing factors. The results showed that (1) between 2002 and 2022, total greenhouse gas emissions from Jiangxi Province’s livestock industry exhibited an upward trend, increasing from 13.52 million tons to 21.27 million tons, with an average annual growth rate of 2.36%. (2) During the study period, the spatial patterns of super-high-emission and light-emission zones remained relatively stable, while medium and heavy emission zones showed dynamic evolution. (3) Intensity effects, agricultural structural effects, and rural population size played a suppressive role in livestock greenhouse gas emissions, while regional development levels and urbanization levels were key drivers of increased emissions. Therefore, governments should accelerate the implementation of clean production models, enhance technological innovation, promote pollution reduction at the source, and develop differentiated livestock development strategies based on regional resource endowments and demographic–economic characteristics. Full article

Identifying the driving effects and differentiated characteristics of transportation carbon emissions is crucial for developing targeted and differentiated emission reduction strategies and providing a scientific basis for the Yangtze River Economic Belt. This study adopted a “top-down” approach to account for the transportation carbon emissions of the Yangtze River Economic Belt from 2000 to 2019 and constructed LMDI models and quantile regression models to estimate the driving effects and heterogeneity of influencing factors. The research results indicate the following: (1) The level of economic development is a key driving factor for transportation carbon emissions in the Yangtze River Economic Belt, with a cumulative effect of 160%. Upon inspection, the relationship between economic and transportation carbon emissions conforms to the environmental Kuznets curve. When the per capita transportation production value reaches CNY 7500, there is a “turning point” in transportation carbon emissions. (2) The population size has a driving effect on transportation carbon emissions, but as carbon emissions continue to increase, their marginal effects gradually diminish. (3) The energy structure and transportation structure have a significant inhibitory effect on transportation carbon emissions. The driving effect of the energy structure shows an “N” shape with quantile changes, while the transportation structure gradually converges. (4) Both energy intensity and transportation intensity show inhibitory effects, indicating that innovative energy substitution, optimization of transportation structure, and improvement of organizational efficiency are key ways to achieve carbon reduction in transportation. It is suggested that the Yangtze River Economic Belt should develop differentiated emission reduction paths in different regions, effectively balance economic development and carbon emission control, and promote the green and low-carbon transformation of the transportation system. Full article

The airline industry is currently navigating a pivotal period characterized by rapid development and increasing global pressure to reduce carbon emissions. Airlines, as the first to be significantly impacted, must actively manage their carbon footprints, adopt carbon abatement technologies, and address the inherent risks in this transformation. This paper examines the risk factors correlated with the technology transformation of carbon abatement and proposes effective abatement strategies. Using panel data of China Southern Airlines from 2009 to 2023 and applying the Logarithmic Mean Divisia Index (LMDI) method based on the Kaya identity, we analyze the differential impacts of various factors on unit carbon emissions. Multiple scenarios, derived from the influences of these factors, are constructed, and the Monte Carlo algorithm is employed to simulate the impact and volatility of correlated risks in the technology transformation for the abatement of carbon emissions. The findings are as follows: on the one hand, carbon emissions are strongly driven by energy consumption (0.99), flight volume (0.941), flight hours (0.931), transportation turnover (0.923), and take-off frequency (0.833). On the other hand, technology (56%) and scale (54.74%) significantly reduce unit carbon emissions, while take-off frequency negatively impacts emissions (−35.19%). Technology-related risks are controllable and relatively stable, whereas scale-related risks are highly uncertain. Additionally, operation-related risks can be partially hedged to ensure a certain level of risk controllability. Full article

The improvement of energy efficiency (EE) and growing consumption of renewable energy sources (RES) in the commercial and public services sector are playing important roles in seeking to pursue sustainable development in the Baltic States and contributing to the transition to a low-carbon economy. This paper provides findings from a detailed analysis of energy intensity trends in economic sectors from 2005 to 2022 in three countries, considering the role of transformations in the energy and climate framework of the European Union (EU). Based on the Fisher Ideal Index application, the different contributions from improving EE and structural changes are revealed. The dominant role of EE improvements in energy savings is identified in Estonia and Lithuania, and structural changes are dominant in Latvia. Changes in energy-related greenhouse gas (GHG) emissions in the commercial and public services sector and the main determinants of their reduction are examined. Based on applying the Kaya identity and the logarithmic mean Divisia index (LMDI) method, decreasing energy intensity is the most important determinant in all three countries. Due to the different extents of RES deployment, their role was very important in Estonia and Latia but was less effective in Lithuania. Reduction in emission intensity has the largest impact in Latvia. The GHG emissions decreased by 34.1% in Estonia, 17.5% in Latvia, and 16.7% in Lithuania. The results confirm the need for new policies, implementation of relevant EE measures, and the growing contribution from RES in Latvia and Lithuania. Full article

Carbon emissions (CE) from expanding construction land (CL), a vital territory for human production and habitation, have contributed to climate change worldwide. The Yellow River Basin (YRB), an essential economic region and energy supply base in China, is experiencing rapid urbanization, and the contradiction between economic development and ecological protection is increasingly acute. Consequently, a thorough examination of the spatial and temporal change features of carbon emissions from construction land (CECL) and its decoupling from economic growth (EG) is crucial for the maintaining development of the region. This study adopts the IPCC carbon emission coefficient approach for measuring the CECL in the YRB from 2010 to 2021. The temporal and spatial variation features of CECL in the YRB were revealed using ArcGIS software and the standard deviation ellipse (SDE) model. The decoupling effect between CECL and EG was analyzed using the Tapio decoupling model and innovatively combined with the Logarithmic Mean Divisia Index (LMDI) method to explore the influence of five main drivers on the decoupling effect. This study found that: (1) The CECL rose from 2.463 billion tons in 2010 to 3.329 billion tons in 2021. The spatial layout of CECL is “high in the east and low in the west”. (2) The SDE of CECL is distributed in the direction of “northeast to southwest”, and the gravity center’s moving path is “northwest to northeast to northwest”; (3) weak decoupling (WD) is the main decoupling state between CECL and EG; (4) the economic output effect and the construction land (CL) scale effect are the two main factors inhibiting the decoupling of CECL, while the energy intensity effect, the population density effect, and the energy structure effect are the main elements motivating the decoupling of CECL. This study provides specific references and bases for the YRB in China and other countries and regions with similar levels of development in promoting green and ecologically friendly initiatives and achieving low-carbon utilization of regional land and sustainable development. Full article

With rapid economic development, the amount of the municipal solid waste (MSW) generated has increased dramatically. To improve the socio-economic benefits and environmental impacts of the low-carbon management of MSW, it is crucial to identify the drivers of Greenhouse Gas (GHG) emissions from MSW treatment and assess their systematic and comprehensive benefits. The factor decomposition method is one of the most commonly used methods focused on identifying GHG emission-influencing factors, while the system dynamics (SD) method is commonly used to analyze the causal relationships between linear and nonlinear variables in complex dynamic systems. Unlike existing studies that account for and evaluate MSW from a static perspective, this paper innovatively combines the LMDI-SD model to identify and quantify the GHG emission drivers of MSW and evaluate the benefits of decarbonizing the MSW management in China from a comprehensive and systematic perspective. The results show that the dominant factor driving MSW GHG emissions from 2010 to 2022 is the economic development factor, ∆E_ED, while the intensity of MSW generation ∆E_GI and the structure of MSW treatment ∆E_TS play a stronger inhibiting role. Based on this, the SD model is constructed to simulate different scenarios, and the analysis shows that increasing the waste separation rate (S3) is the most effective measure to improve the socio-economic benefits and environmental impacts of the system. Compared with the base scenario, the socio-economic benefits and environmental impacts in 2050, for example, are increased by 82.8% and 43.4%, respectively. Improving the utilization rate of landfill gas (S1), reducing the per capita amount of MSW generated (S4) and increasing the incineration rate of MSW (S2) also have significant advantages for the improvement of benefits. Finally, some policy recommendations for the improvement of the comprehensive benefits of low-carbon MSW management systems are proposed to help policymakers make appropriate decisions. Full article

As new-energy vehicles (NEVs) gradually gain public attention, their carbon-reduction issues have become a focal point in academia. This study evaluates the carbon-reduction efficiency of NEVs in 21 Chinese provinces using an improved three-stage DEA model, analyzes spatial disparities with the Dagum Gini coefficient, and decomposes carbon-emission factors using the LMDI method. Results show that the overall carbon-reduction efficiency is low, with an average value of only 0.266. Significant differences exist in production- and consumption-stage efficiencies across regions. Shanxi Province performed the best, with efficiency scores of 1 in both stages, while the carbon-reduction stage showed the lowest efficiency, ranging between 0.2 and 0.3 in most regions. The central region exhibited the highest carbon-reduction efficiency, followed by the western and eastern regions, primarily influenced by intra-regional disparities. Energy intensity significantly suppresses carbon emissions, followed by energy structure, while economic development and population size positively contribute to carbon emissions. This study provides theoretical support for regional governments to formulate policies related to the NEV industry and offers practical guidance for its further development. Full article

Given the deficiencies in the definition of connotation, the construction of index systems, and the coordination of targets within the research on sustainable development in the manufacturing industry, an evaluation index system for sustainable development has been established. This system includes economic benefits, social benefits, resource management, and environmental goals and is built upon a clear definition of the concept’s connotation. The CRITIC–entropy–TOPSIS–CCDM approach is employed for the computation of the coordinated development level of the manufacturing industry. To identify the main factors influencing the coupling coordination degree (CCD) from a mechanistic and compositional point of view, a logarithmic mean divisia index (LMDI) is used. Furthermore, the obstacle degree model analyzes the factors that restrict subsystem development. The results show the following. (1) The coordinated development level of the Chinese manufacturing industry has been maintained at 0.6–0.7, while the CCD of Hainan, Qinghai, and Xinjiang remains to be enhanced. (2) The key factor affecting the CCD is the coupling degree. The evaluation value of the economy and employment system determines the trend of coordinated development in the regional manufacturing industry. (3) The economic and employment scenarios in most provinces (cities) led to a significant decrease in the CCD compared to the baseline scenario, with average growth rates of −10.55% and −12.69%. This suggests that policymakers’ priorities significantly influence the CCD. The research presents a theoretical framework for assessing the sustainability of the manufacturing industry, offering valuable insights to guide the industry towards more sustainable practices. Full article

Efficient allocation and utilization of water resources are critical for the sustainable development of agriculture in arid regions, particularly those heavily reliant on irrigation. Xinjiang, one of China’s major agricultural regions, faces significant challenges in managing water resources due to its arid climate and dependence on irrigation. This study investigates the spatial–temporal dynamics of crop water footprint (CWF) and its driving factors in Xinjiang. Unlike previous studies on Xinjiang that primarily focus on total water footprint, this research emphasizes the crop blue water footprint (CWFB) to provide a more precise assessment of agricultural water allocation and consumption. Using the CROPWAT 8.0 model, the CWF of 14 prefectures in Xinjiang were analyzed for the period 2000–2020. Focusing primarily on the crop blue water footprint (CWFB), the study employed the Logarithmic Mean Divisia Index (LMDI) model to identify key drivers and their mechanisms. Results reveal that Xinjiang’s average annual CWF is 179.02 Gm³, with CWFB contributing 90.22% and the crop green water footprint (CWFG) accounting for. 10.05%. The CWFB showed an initial increase followed by stabilization, with Southern Xinjiang being the largest contributor, trailed by Northern and Eastern Xinjiang. Among the 14 prefectures, the top seven accounted for 90.46% of CWFB. Cotton, wheat, and maize were the major crops, comprising 47.80%, 23.14%, and 21.45% of the total blue water footprint, respectively. This study identifies the dominant role of economic effect and water use efficiency effect in driving changes in CWFB through its analysis of the driving factors. Understanding the spatial–temporal changes and key drivers of blue water consumption helps regions adjust cropping structures and agricultural water resource allocation patterns to ensure sustainable agricultural development. The findings not only offer valuable implications for policymakers and stakeholders in Xinjiang but also provide references for other arid and semiarid regions facing similar challenges in agricultural water resource management. Full article

Policy synergy, the evidence-based coordination of public policies, can aid in more rapidly achieving air pollutant and carbon dioxide (CO₂) emission reduction targets. Using logarithmic mean Divisia index (LMDI) decomposition, coupling coordination degree (CCD), and geographically and temporally weighted regression (GTWR) models, we analyzed the emission characteristics, drivers, and reduction pathways of residential air pollution across 30 Chinese provinces from 2001 to 2020. The southern provinces produced more air pollution than the northern provinces, with the gap widening after 2015. In the residential sector, energy emission factors (LMDI decomposition result, 686,681.9) and population size (14,331) had greater impacts on air pollutant emissions than the energy structure, energy intensity, synergies, or GDP per capita. The GTWR analysis of the CCD mechanism indicated that hydroelectricity and urbanization enhanced coupling coordination in the southeast. Meanwhile, in the west, coupling coordination was improved by R&D investment, government spending on industrial pollution control, electricity consumption, per capita cropland, temperature, and urbanization. This analysis provides a valuable reference for optimizing emission reduction strategies. Full article

The waterway transportation industry, recognized for its high capacity, cost-effectiveness, and energy efficiency, plays a vital role in global freight transport and trade. In China, it serves as a key pillar supporting the national economy and foreign trade. However, its heavy dependence on fossil fuels has intensified carbon emission challenges, creating significant barriers to achieving sustainable development goals. This study employs Input-Output Analysis and the Logarithmic Mean Divisia Index model to examine the changes in carbon emissions and their driving factors in China’s waterway transportation industry from 2002 to 2020, while also exploring potential pathways for emission reduction. The findings reveal the following: (1) From 2002 to 2020, despite a substantial rise in total carbon emissions, the industry has been progressively transitioning towards a low-carbon trajectory through the adoption of clean energy technologies and optimization of its energy structure. (2) Economic scale effects have been the primary drivers of carbon emission growth, with population-scale effects playing a lesser role. Since 2011, the implementation of green technologies and low-carbon management strategies has effectively stabilized emission growth rates. (3) Improvements in energy carbon intensity and transportation energy intensity have significantly reduced carbon emissions. Moreover, the promotion of clean energy technologies and energy-saving measures has substantially lowered the industry’s carbon emission intensity. Full article

China’s transportation sector plays a significant role in reducing carbon dioxide (CO₂) and air pollution. Previous studies have predominantly utilized scenario analysis to forecast emissions for the next 30 to 50 years based on coefficients from a base year. To elucidate the current state of gas emissions in the transportation sector, this study employed panel data for 10 types of gas emissions from 2001 to 2020, analyzing their emission characteristics, tendencies, and synergistic effects. Utilizing the Kaya equation and the logarithmic mean division index (LMDI) decomposition method, we developed a model of pollutant emissions that considers the synergistic effects, pollution emission intensity, energy mix, energy consumption intensity, and population. The results show that all pollutants in the transportation sector decreased except for NH₃ and CO₂. There was a synergistic effect between air pollutants and CO₂ emissions, but the reduction was not significant. From 2013 to 2020, the transportation sector shifted from a high emission intensity with low synergy to a low emission intensity with high synergy. The results indicate that off-road mobile vehicles, on-road diesel vehicles, and motorcycles became the main source of emissions from transportation in certain provinces, and a key area requiring attention in policy development. Gasoline consumption was identified as the primary contributor to the significant increase in synergistic emission variability in the transportation sector. These results provide policymakers with practical ways to optimize emission reduction pathways. Full article