Search Results (750)

In the context of the urgent global transition toward sustainable materials, this study presents a comparative environmental life cycle assessment (LCA) of poly(3-hydroxybutyrate) (PHB), a biodegradable, bio-based polymer, against conventional petrochemical plastics (polystyrene—PS; polypropylene—PP) and another popular biopolymer, namely polylactic acid (PLA). The LCA was conducted using primary production data from a laboratory-scale PHB manufacturing process, integrating real-time energy consumption measurements across all production stages. Environmental indicators such as carbon footprint and energy demand were analyzed under cradle-to-gate and end-of-life scenarios. The results indicate that PHB, while offering biodegradability and renewable sourcing, currently exhibits a significantly higher carbon footprint than PP, PS, and PLA, primarily due to its energy-intensive downstream processing. However, the environmental impact of PHB can be markedly reduced—by over 67%—through partial integration of renewable energy. PLA demonstrated the lowest production-phase emissions, while PP showed the most favorable end-of-life outcomes under municipal waste management assumptions. The study highlights the critical influence of energy sourcing, production scale, and waste treatment infrastructure on the sustainability performance of biopolymers. These findings provide practical insights for industry and policymakers aiming to reduce the environmental burden of plastics and support a shift toward circular material systems. Full article

In response to the climate crisis, Colombia has committed to reducing greenhouse gas (GHG) emissions by 2030 through an energy transition strategy that promotes Non-Conventional Renewable Energy Sources (NCRES) and, increasingly, natural gas. Although natural gas is regarded as a transitional fuel with lower carbon intensity than other fossil fuels, existing reserves could be depleted by 2030 if no new discoveries are made. To assess this risk, a System Dynamics model was developed to project supply and demand under alternative transition pathways. The model integrates: (1) GDP, urban population growth, and adoption of clean energy, (2) the behavior of six major consumption sectors, and (3) the role of gas-fired thermal generation relative to NCRES output and hydroelectric availability, influenced by the El Niño river-flow variability. The novelty and contribution of this study lie in the integration of supply and demand within a unified System Dynamics framework, allowing for a holistic understanding of the Colombian natural gas market. The model explicitly incorporates feedback mechanisms such as urbanization, vehicle replacement, and hydropower variability, which are often overlooked in traditional analyses. Through the evaluation of twelve policy scenarios that combine hydrogen, wind, solar, and new gas reserves, the study provides a comprehensive view of potential energy transition pathways. A comparative analysis with official UPME projections highlights both consistencies and divergences in long-term forecasts. Furthermore, the quantification of demand coverage from 2026 to 2033 reveals that while current reserves can satisfy demand until 2026, the expansion of hydrogen, wind, and solar sources could extend full coverage until 2033; however, ensuring long-term sustainability ultimately depends on the discovery and development of new reserves, such as the Sirius-2 well. Full article

Background: Non-invasive diagnostic tools for the assessment of pulmonary arterial hypertension (PAH) are currently being intensively studied. Positron emission tomography (PET)/computed tomography (CT) with [18F]-fluorodeoxyglucose ([18F]-FDG) and [13N]-ammonia is the gold standard for assessing myocardial metabolism and perfusion. The relationship between right ventricle (RV) myocardial metabolism and perfusion and cardiopulmonary exercise testing (CPET) has not been studied. Objective: to evaluate correlations between the CPET parameters and RV perfusion and metabolism in IPAH patients. Methods: The study comprised 34 IPAH patients (34.2 ± 8.9 years, 4 males, 6 prevalent). Myocardial metabolism and perfusion were assessed using PET/CT with [18F]-FDG and [13N]-ammonia, respectively. CPET, cardiac MRI and invasive hemodynamics were also evaluated. Results: Significant negative correlations were registered between [18F]-FDG and [13N]-ammonia uptake by the RV (SUVmax _RV/LV) and the oxygen consumption, oxygen pulse and positive correlation with the ratio of minute ventilation to carbon dioxide production. The low-risk IPAH patients significantly differed from the intermediate-to-high-risk group in CPET indices and in SUVmax _RV/LV metabolism and SUVmax _RV/LV perfusion parameters. No reliable differences in CPET indices and [18F]-FDG and [13N]-ammonia uptake by the RV were registered between intermediate- and high-risk patients. Conclusions: CPET is a reliable non-invasive diagnostic tool that could distinguish low-risk young IPAH patients without comorbidities from those at intermediate-to-high risk. Significant correlations between CPET parameters and RV myocardial metabolism and perfusion indices, MRI, and invasive hemodynamics confirm the high diagnostic value for CPET. Full article

To achieve the carbon neutrality target, China has proposed “dual control” policies on provincial energy consumption. However, inter-provincial trade drives significant embodied energy flows beyond local demand. How do we identify key energy consumers driving through other provinces? And how does energy, especially from coal, flow to other provinces? Current studies analyzed regional and sectoral energy flow, which are always separated. And seldom was attention paid to coal flow. Intending to identify the critical energy-consuming province in China and investigate how energy and coal flow out from it, this study applied the EE-MRIO model to measure energy and coal embodied in provincial trades. The results suggest the following: (1) The energy embodied in provincial trade was mostly from energy-rich regions to provinces that lacked energy but had developed economies. Shanxi is a critical embodied-energy export province; (2) neighboring provinces and economically developed provinces drive the most embodied energy from Shanxi, and embodied energy mainly flows from the energy sectors and high-energy-intensity sectors; and (3) the provincial and sectoral coal flow in Shanxi presents consistent characteristics of embodied energy flow. We contributed to understanding the energy equity affected by embodied energy flow and propose energy consumption as a relieving measure. Full article

Using the Kaya identity and LMDI method, this study analyzes the influence of population, GDP per capita, energy intensity, and carbon intensity on Xinjiang’s carbon emissions, and compares the effects of industrial structure, energy intensity, and carbon intensity on the industrial sectors during the Eighth to Twelfth Five-Year Plan (FYP) periods. Key findings are as follows: (1) Xinjiang’s carbon emissions center on resource- and energy-intensive sectors, emissions from sectors such as extraction of petroleum and natural gas, fuel processing, chemicals, ceramics and cement, iron and steel, and non-ferrous and power generation accounted for 62% of carbon emissions in 2015; (2) after the Sixth FYP, GDP per capita effect turned into the core driver of carbon emission growth, while the population effect played an auxiliary role. Meanwhile, the energy intensity effect exerted a marked inhibitory impact on the increase in carbon emissions, yet the restraining effect of carbon intensity was comparatively limited; (3) during the Eighth to Twelfth FYPs, carbon emission growth was mainly attributed to industrial structure effects of the mining and washing of coal, extraction of petroleum and natural gas, fuel processing, chemicals, ceramics and cement, iron and steel, non-ferrous and power generation. Energy intensity and carbon intensity effects in various industries inhibited emission growth. Based on new trends in Xinjiang’s socioeconomic development, policy recommendations proposed including promoting the low-carbon transformation of industrial structure, profound restructuring of energy consumption, and improving energy efficiency by advancing energy-saving technology. Full article

This study aims to establish an energy assessment system and provide low-carbon design strategies for block-scale science and technology industrial parks in the Yangtze River Delta region of China. To investigate low-carbon design strategies for these parks, the impact of solar energy utilization potential and heat island effect on the energy consumption of buildings is taken as the entry point. Through an analysis of the spatial characteristics of twenty block-scale science and technology industrial parks in the Yangtze River Delta region of China, two types of idealized park models comprising a total of eighteen variations were established. The simulation process involved six key morphological parameters to describe the specific shape of the parks quantitatively. The Ladybug Tools 1.6.0, Radiance 5.4a, and URBANopt v0.9.2 software were used to simulate the potential for photovoltaic power generation and the energy consumption of the parks. Net Energy Use Intensity (NEUI) and Potential Utilization Ratio of Renewable Energy (PURRE) were selected as the final evaluation indexes to represent the integrated energy performance of the park. The results show that for the park with a circular layout, the optimal integrated energy performance is achieved when the building density is between 35% and 40%; the average building height is designed with lower values within the range of 20 m to 24 m, and the height-to-depth ratio is around 0.3. Finally, based on the results of the analysis, four major low-carbon design strategies were proposed: high-density development, courtyard layout, supporting-function centralized layout, and carbon sink enhancement. Full article

In the context of China’s “double carbon” goals, examining the spatial–temporal characteristics and influencing factors of the synergistic effect of pollution control and carbon reduction (SEPCR) in the Chengdu–Chongqing region (CCR) is crucial for advancing both air pollution (AP) control and carbon emissions (CE) mitigation. This study uses data on AP and CE from 2007 to 2022 and employs the coupling coordination degree (CCD) model, spatial autocorrelation analysis, and kernel density estimation to investigate the spatial–temporal distribution and dynamic evolution of the CCD between AP and CE in the CCR. Additionally, the Tobit regression model is applied to identify the key factors influencing this synergy. The results indicate that (1) during the study period, the air pollutant equivalents (APE) in the CCR showed a declining trend, while CE continued to increase; (2) the overall level of coupling coordination remained low, exhibiting an evolutionary pattern of initial increase, subsequent decrease, and then recovery, with synergistic effects showing slight improvement but significant fluctuations; (3) the SEPCR in the CCR was generally dispersed, exhibiting no significant spatial autocorrelation. A “core–periphery” structure emerged, with Chongqing and Chengdu as the core and peripheral cities forming low-value zones. Low–low clusters indicative of a “synergy poverty trap” also appeared; (4) economic development (PGDP), openness level (OP), and environmental regulation intensity (ER) are significant positive drivers, while urbanization rate (UR), industrial structure upgrading (IS), and energy consumption intensity (EI) exert significant negative impacts. Full article

Crude oil accounts for approximately 40% of global energy consumption, and the refining sector is a major contributor to greenhouse gas (GHG) emissions, particularly through the production of hard-to-abate fuels such as aviation fuel and fuel oil. This study disaggregates the refinery into its key process units to identify decarbonization opportunities along the entire production chain. Units are categorized into combustion-based processes—including crude and vacuum distillation, hydrogen production, coking, and fluid catalytic cracking—and non-combustion processes, which exhibit lower emission intensities. The analysis reveals that GHG emissions can be reduced by up to 60% with currently available technologies, without requiring major structural changes. Electrification, residual heat recovery, renewable hydrogen for desulfurization, and process optimization through digital twins are identified as priority measures, many of which are also economically viable in the short term. However, achieving full decarbonization and alignment with net-zero targets will require the deployment of carbon capture technologies. These results highlight the significant potential for emission reduction in refineries and reinforce their strategic role in enabling the transition toward low-carbon fuels. Full article

As global climate change intensifies with unprecedented urgency, nations worldwide have increasingly adopted market-based environmental regulatory instruments to advance carbon reduction objectives. In 2017, China launched energy rights trading pilots, thereby providing a crucial policy instrument for controlling total energy consumption at its source. However, the specific impacts and transmission pathways through which this system influences corporate carbon reduction behavior remain insufficiently explored through rigorous empirical investigation. Drawing upon panel data from heavy-polluting companies listed on the Shanghai and Shenzhen A-share markets, this study employs a difference-in-differences methodology to identify the causal effects of energy rights trading systems on corporate carbon reduction. Our findings reveal that energy rights trading systems significantly reduce corporate carbon emission intensity, generating pronounced emission reduction effects. Further mechanism analysis demonstrates that this system operates through two principal pathways: first, by promoting increased green investment among enterprises, whereby short-term emission reductions are achieved through procurement of energy-saving equipment and environmental protection facilities, and second, by stimulating corporate green technological innovation, whereby long-term sustainable emission reductions are realized through the development of energy-saving technologies and clean processes. Additionally, the research reveals that enterprises with lower financing constraints and stronger supply chain bargaining power respond more actively to policy implementation, with policy effects exhibiting significant heterogeneity. This study not only enriches the theoretical understanding of market-based environmental regulatory policy effects but also provides crucial empirical evidence for improving the energy rights trading system design and enhancing policy implementation effectiveness, thereby offering important policy insights for promoting corporate green transformation and achieving “dual carbon” objectives. Full article

This article presents an innovative and highly sustainable method for recycling photovoltaic (PV) panels laminated with very soft polydimethylsiloxane (PDMS) gels. This approach eliminates energy-intensive and environmentally harmful processes such as burning and chemical etching due to simple and clean mechanical delamination at room temperature via polyethylene wedges. This technology significantly contributes to environmental sustainability by facilitating the direct reuse of materials, reducing the amount of hazardous waste, and minimizing energy consumption during recycling. PDMS panels achieve extremely low annual degradation rates (0.15–0.22%) and excellent recycling efficiencies (95–98%) compared to conventional EVA/POE laminated panels, with up to 81% of the panel weight being directly reused. This has led to a drastic reduction in the overall carbon footprint and is in line with the principles of circular economy and sustainable development goals (SDGs). The synergistic combination of long service life and efficient end-of-life processing makes this technology a cornerstone of sustainability in the photovoltaic industry. It addresses pressing environmental and socioeconomic challenges by promoting resource efficiency, reducing photovoltaic waste by up to 114 times, and enabling policies and practices that support the global energy transition. Full article

Achieving synergistic effects in pollution reduction and carbon mitigation is of great significance for promoting the comprehensive green transformation of economic and social development. This study focuses on the textile industry in a specific city, aiming to (1) analyze the energy consumption and pollutant emission characteristics of the textile industry in a district of Suzhou from 2017 to 2021; (2) conduct carbon accounting for 18 typical textile enterprises using the emission factor method with extended accounting boundaries; and (3) explore targeted low-carbon collaborative control pathways for pollution and carbon reduction. The results show that from 2017 to 2021, the proportion of raw coal in the comprehensive energy consumption of the textile industry in the city decreased annually to 35.68%, while the proportion of natural gas increased to 13.96%. The adoption of natural gas significantly reduced carbon emissions. The industry’s total output value rose markedly, while energy consumption intensity declined noticeably. The production and emission of volatile organic compounds (VOCs) generally decreased, with the proportion of final combustion emissions of VOCs in carbon accounting being relatively low (0–19.79%). Based on the findings, this study provides strategic foundations for collaborative governance, including optimizing energy structures, substituting VOC-containing raw materials, and improving production processes. Full article

Dry ice, the solid form of carbon dioxide (CO₂), is widely used in cold chain logistics, industrial cleaning, and biomedical preservation. Its production, however, is closely linked to carbon capture, energy-intensive liquefaction, and solidification processes. This review critically evaluates and compares the existing methods of CO₂ capture, including chemical absorption, physical absorption, adsorption, and membrane-based separation as they pertain to dry ice production. This study further assesses liquefaction cycles using refrigerants such as ammonia and R744, highlighting thermodynamic and environmental trade-offs. Solidification techniques are examined in the context of energy consumption, process integration, and product quality. The comparative analysis is supported by extensive tabulated data on operating conditions, CO₂ purity, and sustainability metrics. This review identifies key technical and environmental challenges, such as solvent regeneration, CO₂ leakage, and energy recovery. Thus, it also explores emerging innovations, including hybrid cycles and renewable energy integration, to advance the sustainability of dry ice production. This, in turn, offers strategic insight for optimizing dry ice manufacturing in alignment with low-carbon industrial goals. Full article

Rising household carbon emissions (HCEs) substantially increase residential energy consumption. This review evaluates the four principal quantification methods: Emission Coefficient Method (ECM), Input–Output Analysis (IOA), Consumer Lifestyle Approach (CLA), and Life Cycle Assessment (LCA). The methods are compared according to data requirements, uncertainty levels, and scale suitability. The study synthesizes multidimensional determinants—including household income, household size, urbanization, energy intensity and composition, population aging, and household location—and translates these insights into behavior-informed mitigation pathways grounded in behavioral economics principles. Combining compact-city planning, targeted energy-efficiency incentives, and behavior-nudging measures can reduce HCEs without compromising living standards, providing local governments with an actionable roadmap to carbon neutrality. Full article

The transition of South Africa from coal-dependent energy systems to renewable energy alternatives presents economic and environmental trade-off complexities that require empirical investigation. This study employed threshold-switching dynamic models, NARDL analysis, and threshold Granger causality tests to investigate nonlinear relationships between renewable energy generation, economic growth, and carbon dioxide emissions in South Africa from 1980 to 2023. The threshold-switching dynamic models revealed critical structural breakpoints: a 56.4% renewable energy threshold for carbon dioxide emissions reduction, a 397.9% trade openness threshold for economic growth optimisation, and a 385.32% trade openness threshold for coal consumption transitions. The NARDL bounds test confirmed asymmetric effects in the carbon dioxide emissions and renewable energy relationship. The threshold Granger causality test established significant unidirectional causality from renewable energy to carbon dioxide emissions, economic growth to carbon dioxide emissions, and bidirectional causality between coal consumption and trade openness. However, renewable energy demonstrated no significant causal relationship with economic growth, contradicting traditional growth-led energy hypotheses. This study concluded that South Africa’s energy transition demonstrates distinct regime-dependent characteristics, with renewable energy deployment requiring critical mass thresholds to generate meaningful environmental benefits. The study recommended that optimal trade integration and renewable energy thresholds could fundamentally transform the economy’s carbon intensity while maintaining sustainable growth patterns. Full article

While the corporate adoption of artificial intelligence (AI) is accelerating, its environmental consequences remain insufficiently understood, particularly in absolute firm-level energy consumption. The main objective of this study is to empirically determine the causal impact of AI adoption on absolute firm-level energy consumption in Chinese publicly listed companies, with a particular focus on the mediating role of green innovation and the moderating role of digital capabilities. This study provides the first large-scale micro-level evidence on how AI adoption shapes corporate energy use, drawing on panel data from Chinese non-financial listed firms during 2011–2022. We construct a novel AI adoption index via Word2Vec-based textual analysis of annual reports and estimate its impact using firm fixed effects, instrumental variables, mediation models, and multiple robustness checks. Results show that AI adoption significantly reduces total energy consumption, with a 1% increase in AI intensity associated with an estimated 0.48% decrease in energy use. Green innovation emerges as a key mediating channel, while the energy-saving benefits are amplified in firms with advanced digital transformation and IT-oriented executive teams. Heterogeneity analyses indicate more substantial effects among large firms, private enterprises, non-energy-intensive sectors, and firms in digitally lagging regions, suggesting capability-driven and context-dependent dynamics. This study advances the literature on digital transformation and corporate sustainability by uncovering the mechanisms and boundary conditions of AI’s environmental impact and offers actionable insights for aligning AI investments with carbon reduction targets and industrial upgrading in emerging economies. Full article