Search Results (44)

Carbon capture is pivotal for achieving carbon neutrality; however, its high energy consumption severely limits the operational flexibility of power plants and remains a key challenge. This study, targeting a full flue gas carbon capture scenario for a 1000 MW coal-fired power plant, identified the dual-element (“steam” and “power generation”) coupling convergence mechanism. Based on this mechanism, a comprehensive set of mathematical model equations for the “carbon–electricity–heat” coupling process is established. This model quantifies the dynamic relationship between key operational parameters (such as unit load, capture rate, and thermal consumption level) and system performance metrics (such as power output and specific power penalty). To address the challenge of flexible operation, this paper further proposes two innovative coupled modes: steam thermal storage and chemical solvent storage. Model-based quantitative analysis indicated the following: (1) The power generation impact rate under full THA conditions (25.7%) is lower than that under 30% THA conditions (27.7%), with the specific power penalty for carbon capture decreasing from 420.7 kW·h/tCO₂ to 366.7 kW·h/tCO₂. (2) Thermal consumption levels of the capture system are a critical influencing factor; each 0.1 GJ/tCO₂ increase in thermal consumption leads to an approximate 2.83% rise in unit electricity consumption. (3) Steam thermal storage mode effectively reduces peak-period capture energy consumption, while the chemical solvent storage mode almost fully eliminates the impact on peak power generation and provides optimal deep peak-shaving capability and operational safety. Furthermore, these modeling results provide a basis for decision-making in plant operations. Full article

Under the dual targets of carbon peaking and carbon neutrality, virtual power plants (VPPs) are expected to coordinate distributed energy resources in distribution networks to ensure low-carbon operation. This paper introduces a distribution-level dynamic carbon emission factor (DCEF), derived from nodal carbon potentials on an IEEE 33-bus distribution network, and uses it as a time-varying carbon signal to guide VPP scheduling. A bi-objective ε-constraint mixed-integer linear programming model is formulated to minimise daily operating costs and CO₂ emissions, with a demand response and battery storage being dispatched under network constraints. Four seasonal typical working days are constructed from measured load data and wind/PV profiles, and three strategies are compared: pure economic dispatch, dispatch with a static average carbon factor, and dispatch with the proposed spatiotemporal DCEF. Our results show that the DCEF-based strategy reduces daily CO₂ emissions by up to about 8–9% in the typical summer day compared with economic dispatch, while in spring, autumn, and winter, it achieves smaller but measurable reductions in the order of 0.1–0.3% of daily emissions. Across all seasons, the average and peak carbon potential are noticeably lowered, and renewable energy utilisation is improved, with limited impacts on costs. These findings indicate that feeder-level DCEFs provide a practical extension of existing carbon-aware demand response frameworks for low-carbon VPP dispatch in distribution networks. Full article

Under the dual pressures of global climate change and China’s “carbon peak and carbon neutrality” targets, traditional urban development models are insufficient to support sustainable transitions. Smart cities (SCs) have emerged as key platforms for achieving low-carbon urban transformation, yet the systemic causal mechanisms and dynamic transmission pathways of carbon emissions within these cities remain underexplored. This study develops an integrated DEMATEL–ISM–SD modeling framework to systematically identify key drivers, reveal causal structures, and simulate the dynamic evolution of carbon emissions in SCs. Eighteen influencing factors were identified through a comprehensive literature review. DEMATEL analysis evaluated the causal strength and centrality of factors, ISM constructed a five-level hierarchical structure, and a system dynamics model was established for scenario simulation, using Shenzhen as a case study. The results show that green technological innovation capacity exhibits the highest centrality, while energy structure demonstrates the strongest causal influence. SC policy intensity is positioned at the deepest level of the hierarchical structure, serving as a foundational driver that exerts influence on all other factors. Scenario simulations indicate that enhancing green innovation, optimizing industrial and energy structures, and developing smart transportation systems can significantly reduce carbon emissions over time. The research findings reveal the key drivers and transmission pathways of carbon emissions in SCs, providing a reference basis for policy formulation on urban low-carbon transformation and sustainable development. Full article

Since 2017, China’s carbon emissions have exceeded 10 billion tons. Hebei Province is one of the country’s major heavy-industrial regions, accounting for over 9 percent of the national total carbon emissions. Achieving carbon peaking and neutrality in Hebei is therefore vital to realizing China’s overall dual carbon goals. This study examines the spatiotemporal evolution of Hebei’s carbon emissions from four perspectives: general characteristics, energy structure, industrial structure, and urban emission patterns. Six key socioeconomic factors—population, GDP per capita, urbanization rate, share of secondary industry, installed capacity of thermal power generation, and energy intensity—were selected to project emission trends under baseline scenario, high-mitigation scenario, and low-mitigation scenario. The results show that Hebei’s carbon emissions are expected to peak in 2027 at 1.011 billion tons under the baseline scenario, in 2024 at 0.987 billion tons under the high-mitigation scenario, and in 2029 at 1.037 billion tons under the low-mitigation scenario, followed by a slight decline. Considering the province’s industrial composition and development trends, the baseline and low-mitigation pathways are more feasible. Controlling the expansion of energy-intensive industries, particularly ferrous-metal smelting and electricity and heat production, will be critical for achieving Hebei’s carbon-peaking target. Full article

To achieve carbon peak and neutrality goals and promote sustainable development, the power sector, as China’s largest source of carbon emissions, is the first industry to implement the national carbon emission trading scheme (ETS). A differences-in-differences model is employed on firm-level data to assess the causal impact of China’s national ETS, launched in 2017, on the sustainable technology progress of power generation enterprises. This study employs green patents and total factor productivity as measures for sustainable technology progress and then explores mechanisms and heterogeneity of the impact. Results show that: (1) The national ETS has a positive effect on green innovation capability and efficiency in the power industry, and the increasing causal effect is mainly achieved through research and development expenditure. (2) The national ETS exerts a more significant positive effect on power generation enterprises that are non-state-owned, have smaller asset scale, demonstrate superior environmental performance, and are located in the eastern region. However, there is no significant difference in total factor productivity across power enterprises. (3) Green innovations are predominantly concentrated in new energy and hybrid power generation enterprises. This study contributes to the literature by providing novel empirical evidence from China’s national ETS, highlighting its dual impact on innovation and productivity within a unified framework. The findings not only offer targeted recommendations for China’s power sector but also serve as an important reference for other high-emitting industries and other regions worldwide facing the same challenges in their pursuit of sustainable development. Full article

Accomplishing China’s national targets of carbon peaking and carbon neutrality necessitates proactive solutions, hinging critically on fundamentally transforming rural construction models. Current construction practices in rural areas are characterized by inefficiency, high resource consumption, and reliance on imported materials. These shortcomings not only jeopardize the attainment of climate objectives, but also hinder equitable development between urban and rural regions. Using the Digital Industrial Park in Yongtai County, Fuzhou City, as a case study, this study focuses on prefabricated public buildings in regions with extreme hot–humid climate, and innovatively integrates BIM (Building Information Modeling)-driven carbon modeling with the Gaussian Two-Step Floating Catchment Area (G2SFCA) method for spatial accessibility assessment to investigate the carbon emissions and economic benefits of prefabricated buildings during the embodied stage, and analyzes the spatial accessibility of prefabricated building material suppliers in Fuzhou City and identifies associated bottlenecks, seeking pathways to promote sustainable rural revitalization. Compared with traditional cast-in-situ buildings, embodied carbon emissions of prefabricated during their materialization phase significantly reduced. This dual-perspective approach ensures that the proposed solutions possess both technical rigor and logistical feasibility. Promoting this model across rural areas sharing similar climatic conditions would advance the construction industry’s progress towards the dual carbon goals. Full article

The global climate crisis has driven unprecedented agreements among nations on carbon mitigation. With China’s commitment to carbon peaking and carbon neutrality targets, the building sector has emerged as a critical focus for emission reduction, particularly because office buildings account for over 30% of building energy consumption. However, a systematic and regionally adaptive low-carbon technology evaluation framework is lacking. To address this gap, this study develops a multidimensional decision-making system to quantify and rank low-carbon technologies for office buildings in Beijing. The method includes four core components: (1) establishing three archetypal models—low-rise (H ≤ 24 m), mid-rise (24 m < H ≤ 50 m), and high-rise (50 m < H ≤ 100 m) office buildings—based on 99 office buildings in Beijing; (2) classifying 19 key technologies into three clusters—Envelope Structure Optimization, Equipment Efficiency Enhancement, and Renewable Energy Utilization—using bibliometric analysis and policy norm screening; (3) developing a four-dimensional evaluation framework encompassing Carbon Reduction Degree (CRD), Economic Viability Degree (EVD), Technical Applicability Degree (TAD), and Carbon Intensity Degree (CID); and (4) conducting a comprehensive quantitative evaluation using the AHP-entropy-TOPSIS algorithm. The results indicate distinct priority patterns across the building types: low-rise buildings prioritize roof-mounted photovoltaic (PV) systems, LED lighting, and thermal-break aluminum frames with low-E double-glazed laminated glass. Mid- and high-rise buildings emphasize integrated PV-LED-T8 lighting solutions and optimized building envelope structures. Ranking analysis further highlights LED lighting, T8 high-efficiency fluorescent lamps, and rooftop PV systems as the top-recommended technologies for Beijing. Additionally, four policy recommendations are proposed to facilitate the large-scale implementation of the program. This study presents a holistic technical integration strategy that simultaneously enhances the technological performance, economic viability, and carbon reduction outcomes of architectural design and renovation. It also establishes a replicable decision-support framework for decarbonizing office and public buildings in cities, thereby supporting China’s “dual carbon” goals and contributing to global carbon mitigation efforts in the building sector. Full article

As China commits to reaching peak carbon emissions and achieving carbon neutrality, accurately predicting the provincial carbon peak year is vital for designing effective, region-specific policies. This study proposes an integrated approach based on extended STIRPAT and GA-BiLSTM models to predict China’s provincial carbon peak year. First, based on panel data across 30 provinces in China from 2000 to 2023, we construct a multidimensional indicator system that encompasses socioeconomic factors, energy consumption dynamics, and technological innovation using the extended STIRPAT model, which explains 87.42% of the variation in carbon emissions. Second, to improve prediction accuracy, a hybrid model combining GA-optimized BiLSTM networks is proposed, capturing temporal dynamics and optimizing parameters to address issues like overfitting. The GA-BiLSTM model achieves an R² of 0.9415, significantly outperforming benchmark models with lower error metrics. Third, based on the model constructed above, the peak years are projected for baseline, low-carbon, and high-carbon scenarios. In the low-carbon scenario, 19 provinces are projected to peak before 2030, which is 8 more than in the baseline scenario. Meanwhile, under the high-carbon scenario, some provinces such as Jiangsu and Hebei may fail to peak by 2040. Finally, based on the predicted carbon peak year, provinces are categorized into four pathways—early, recent, later, and non-peaking—to provide targeted policy recommendations. This integrated framework significantly enhances prediction precision and captures regional disparities, enabling tailored decarbonization strategies that support China’s dual carbon goals of balancing economic growth with environmental protection. The approach provides critical insights for region-specific low-carbon transitions and advances sustainable climate policy modeling. Full article

To address energy shortages and achieve carbon peaking/neutrality, this study develops a distributed renewable-based integrated energy system (IES) for rural active zero-energy buildings (ZEBs). Energy consumption patterns of typical rural houses are analyzed, guiding the design of a resource-tailored IES that balances economy and sustainability. Key equipment capacities are optimized to achieve net-zero/zero energy consumption targets. For typical daily cooling/heating/power loads, equipment output is scheduled using a dual-objective optimization model minimizing operating costs and CO₂ emissions. Results demonstrate that: (1) Net-zero-energy IES outperforms separated production (SP) and full electrification systems (FES) in economic-environmental benefits; (2) Zero-energy IES significantly reduces rural building carbon emissions. The proposed system offers substantial practical value for China’s rural energy transition. Full article

Against the backdrop of intensifying global climate change and deepening sustainable development goals, the low-carbon transformation of agriculture, as a major greenhouse gas emission source, holds significant strategic importance for achieving China’s “carbon peaking and carbon neutrality” (referred to as the “dual carbon”) targets. To reveal the spatiotemporal evolution characteristics and complex driving mechanisms of agricultural carbon emissions (ACEs), this study constructs a comprehensive accounting framework for agricultural carbon emissions based on provincial panel data from China spanning 2000 to 2023. The framework encompasses three major carbon sources—cropland use, rice cultivation, and livestock farming—enabling precise quantification of total agricultural carbon emissions. Furthermore, spatial-temporal distribution patterns are characterized using methodologies including standard deviational ellipse (SDE) and spatial autocorrelation analysis. For driving mechanism identification, the Geodetector and Geographically and Temporally Weighted Regression (GTWR) models are employed. The former quantifies the spatial explanatory power and interaction effects of driving factors, while the latter enables dynamic estimation of factor influence intensities across temporal and spatial dimensions, jointly revealing significant spatiotemporal heterogeneity in driving mechanisms. Key findings: (1) temporally, total ACEs exhibit fluctuating growth, while emission intensity has significantly decreased, indicating the combined effects of policy regulation and technological advancements; (2) spatially, emissions display an “east-high, west-low” pattern, with an increasing number of hotspot areas and a continuous shift of the emission centroid toward the northwest; and (3) mechanistically, agricultural gross output value is the primary driving factor, with its influence fluctuating in response to economic and policy changes. The interactions among multiple factors evolve over time, transitioning from economy-driven to synergistic effects of technology and climate. The GTWR model further reveals the spatial and temporal variations in the impacts of each factor. This study recommends formulating differentiated low-carbon agricultural policies based on regional characteristics, optimizing industrial structures, enhancing modernization levels, strengthening regional collaborative governance, and promoting the synergistic development of climate and agriculture. These measures provide a scientific basis and policy reference for achieving the “dual carbon” goals. Full article

Under the “dual-carbon” targets, the coal power industry faces significant challenges in low-carbon transition, with carbon capture, utilization, and storage (CCUS) technologies as a key solution for emission reduction and energy security. Existing evaluation methods lack comprehensive assessments of technical, economic, and environmental synergies. This study proposes a dynamic three-dimensional framework integrating technical, economic, and emission indicators. By using Monte Carlo simulation and K-means clustering, the framework captures technology degradation and market fluctuations. Results show compression energy consumption averages of 0.37 ± 0.07 GJ/tCO₂, with capture rates above 94%, increasing the variability by 35%. Lifecycle costs can be reduced by 24% at carbon prices of 80–100 USD/tCO₂ with optimal subsidies. Emission costs peak alongside carbon prices above 430 USD/t, suggesting the need for tiered carbon pricing and CAPEX subsidies. A cluster analysis divides CCUS into high-capture-high-energy, balanced, and low-efficiency types, supporting differentiated policies such as tiered carbon pricing and phased subsidy withdrawal. This research offers actionable insights to balance economic viability and carbon neutrality goals. Full article

As the largest carbon emitter globally, China has formally adopted dual-carbon targets of achieving a carbon peak by 2030 and carbon neutrality by 2060. Urban renewal, as an essential approach to promoting sustainable urban development, plays a critical role in realizing dual-carbon targets. However, carbon emission reduction in urban renewal involves multiple stakeholders with divergent interests, significantly hindering the effective achievement of emission reduction goals. In this context, this paper innovatively selects the government, developers, and construction enterprises as game subjects and constructs an evolutionary game model of the three parties’ participation in carbon emission reduction from the perspective of carbon trading. Through simulation analysis, it explores the impacts of government subsidies, penalty mechanisms, additional benefits, and carbon trading on stakeholder decision-making. The findings indicate the following: (1) The emission reduction process in urban renewal follows an evolutionary pattern of the initial, growth, and mature stages. (2) Sensitivity analysis demonstrates that government subsidies and penalty mechanisms play important roles. (3) Additional benefits serve as intrinsic motivation for developers and construction enterprises to reduce emissions, while a well-developed carbon trading market provides additional incentives and benefit pathways for stakeholders. By integrating urban renewal with carbon trading for the first time, this study aims to enhance stakeholders’ engagement in emission reduction and provide practical reference suggestions, thereby contributing to sustainable urban development. Full article

Under the “dual-carbon goals” (carbon peaking and carbon neutrality), the accelerated global transition toward green and low-carbon development has become an irreversible trend. As a key carbon-emitting sector in China, the transportation industry accounts for approximately 10% of the nation’s total carbon emissions. Transportation decarbonization is therefore critical not only for addressing global climate change challenges and fulfilling international emission reduction commitments but also for driving the industry’s green transformation, optimizing energy structures, enhancing public livelihood and ecological environment quality, and, ultimately, achieving sustainable development. Taking Chengdu as a case study, systematically, this paper (1) objectively summarizes the current status and achievements of green development in Chengdu’s transportation sector; (2) identifies bottlenecks hindering its green transition; (3) calculates carbon emissions across various transport modes in recent years using the GHG Protocol framework to identify key influencing factors; and (4) proposes targeted strategies to establish Chengdu as a national pioneer in developing innovative “dual-carbon” pathways for transportation. The findings are intended to provide decision-making support for building a low-carbon transportation system that aligns with Chengdu’s megacity development goals. Full article

As the global ecological environment faces serious challenges and extreme climate change threatens the survival of humankind, the promotion of green development has become the focus for all countries in the world. As one of the world’s major greenhouse gas emitters, China has put forward the “twin goals” of achieving carbon peaking and carbon neutrality and is committed to promoting the green and low-carbon transformation of its cities. As the core of economic and social development, cities are the main source of carbon emissions. In response to the dual challenges of carbon emission control and traffic growth, it is particularly important to promote the development of green transportation. With the acceleration of urbanization, urban traffic pollution is becoming more and more serious. As a zero-emission transportation mode, electric vehicles have become a key way to achieve the carbon peak and carbon neutrality targets. In order to deeply analyze the research status of electric vehicles in the field of the green and low-carbon transformation of urban transportation in China and to explore the research hot spots, evolution trends, and their roles and strategies in the construction of green transportation networks, this paper uses the CiteSpace, VOSviewer, and Tableau analysis tools to review and analyze the 2460 articles and reviews in the Web of Science Core Collection (WOS) and 2650 articles and reviews in the China National Knowledge Infrastructure (CNKI), including the “publication volume and publication trend”, “subject citation path”, “countries cooperation and geographical distribution”, “author cooperation and institution cooperation”, “keyword co-occurrence and keywords clusters”, and the “evolution trend of research hot spots in timeline”. The results show that: (1) Since 2010, the research focus on electric vehicles has gradually increased, and especially in the past three years, the number of such publications has increased significantly. (2) China holds the lead in research output regarding electric vehicles and related fields, but its international cooperation needs to be strengthened. (3) In recent years, the research has focused on “energy transformation”, “energy-saving technology”, “carbon emissions”, “battery recycling”, and other relevant topics. The promotion and development of electric vehicles will continue to usher in new opportunities concerning technological innovation, policy support, and market expansion. Finally, based on the research hot spots and evolution trends of electric vehicles in the field of urban green transportation and low-carbon transportation in China, this paper discusses the key paths and strategies for electric vehicles to promote the transformation of urban transportation in China to green and low-carbon types and looks forward to future research directions. The research in this paper can provide theoretical support and practical guidance for China to promote electric vehicles, build low-carbon cities, and realize green transportation. It is expected to act as a useful reference for relevant policy formulation and academic research. Full article

Climate change is worsening across the region, exacerbating the energy crisis, while traditional centralized energy systems struggle to meet people’s needs. Globally, countries are actively responding to this dual challenge of climate change and energy demand. In September 2020, China introduced a dual carbon target of “Carbon peak and carbon neutrality”. Since then, it has consistently encouraged and supported innovative research on carbon reduction and energy conservation through its resource policies. Distributed energy systems (DESs) are gaining favor in various countries due to their promising applications in energy and environmental realms, particularly in light of current imperatives for energy conservation, emission reduction, and relevant policies. This paper provides a retrospective analysis of recent research and applications of DESs, conducts a systematic classification and statistical overview of DES implementations, and offers insightful recommendations and future prospects for the advancement of DESs. Full article