Search Results (170)

Understanding how energy use and economic activity shape carbon emissions is pivotal for achieving global climate targets. This study quantifies the dynamic nexus between disaggregated energy consumption, economic growth, and CO₂ emissions in India and China—two economies that together account for more than one-third of global emissions. Using annual data from 1990 to 2021, we implement Long Short-Term Memory (LSTM) neural networks, which outperform traditional linear models in capturing nonlinearities and lagged effects. The dataset is split into training (1990–2013) and testing (2014–2021) intervals to ensure rigorous out-of-sample validation. Results reveal stark national differences. For India, coal, natural gas consumption, and economic growth are the strongest positive drivers of emissions, whereas renewable energy exerts a significant mitigating effect, and nuclear energy is negligible. In China, emissions are dominated by coal and petroleum use and by economic growth, while renewable and nuclear sources show weak, inconsistent impacts. We recommend retrofitting India’s coal- and gas-plants with carbon capture and storage, doubling clean-tech subsidies, and tripling annual solar-plus-storage auctions to displace fossil baseload. For China, priorities include ultra-supercritical upgrades with carbon capture, utilisation, and storage, green-bond-financed solar–wind buildouts, grid-scale storage deployments, and hydrogen-electric freight corridors. These data-driven pathways simultaneously cut flagship emitters, decouple GDP from carbon, provide replicable models for global net-zero research, and advance climate-resilient economic growth worldwide. 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

The mitigation and reduction of carbon footprint is nowadays one of the most pressing challenges covering the most diverse fields of civil activity and industrial production, to meet the climate neutrality targets of the Paris protocol by 2050. However, the intermittency of renewable sources necessitates diverse technical solutions for energy storage. An attractive peculiarity of NH₃ as an energy vector stems in its double possibility of being used both as a source of H₂ and directly as a green fuel. Intriguingly, an aspect common to most scientific publications on the subject is the limited attention to safety and risk problems connected with the use of NH₃. This paper intended to fill a gap pertaining to the emerging risks associated with the use of ammonia as an energy vector and to provide experimental and theoretical investigations on liquid spray curtains as an effective mitigation technique for accidental releases of ammonia in air. Full article

This study is one of the first empirical attempts to quantify the social benefit of virtual power plants (VPPs) in South Korea using the contingent valuation method (CVM). As Korea pursues its ambitious carbon neutrality goal by 2050, VPPs have emerged as a critical technology for managing the intermittency of renewable energy sources and ensuring grid stability. Despite their recognized technical potential, the social and economic value of VPPs remains largely unexplored. Through a nationwide survey of 1105 households, we employed a double-bounded dichotomous choice spike model to estimate willingness to pay (WTP) for government-led VPP implementation. The analysis revealed two distinct dimensions influencing VPP valuation: electricity bill perceptions and electricity generation mix preferences. Results indicated that Korean households exhibited significant but heterogeneous WTP for VPP implementation, with unconditional mean annual WTP ranging from KRW 23,474 to KRW 26,545 per household. Notably, support for renewable energy transition showed stronger positive effects on WTP compared to nuclear expansion preferences, suggesting VPPs are primarily valued as renewable energy enablers. The substantial spike probability (32–34%) indicated that approximately one-third of the population has zero WTP, highlighting challenges in introducing novel energy technologies. Key determinants of positive WTP included perceived fairness of electricity pricing, support for market-based mechanisms, and preferences for transitioning from coal and nuclear to renewables. These findings provide critical policy insights for VPP deployment strategies, suggesting the need for phased implementation, targeted communication emphasizing renewable integration benefits, and coordination with broader electricity market reforms. The study contributes to energy transition economics literature by demonstrating how public preferences for emerging grid technologies are shaped by both economic considerations and environmental values. Full article

Bone marrow-derived macrophages (BMMs) exhibit dynamic behavior and functional capabilities in response to specific microenvironmental stimuli. Recent investigations have proved that BMMs play crucial roles in promoting necrotic lesion resolution. Despite substantial advancements in understanding their activation and interaction with injured livers, researchers face challenges to develop effective treatments based on manipulating BMMs function. Caveolin-1 (Cav-1) is the major structural protein on the plasma membrane. We previously reported that Cav-1 knockout (KO) mice exhibited less functional damage and necrosis in carbon tetrachloride (CCl₄)-induced liver injury. We hypothesize that the activation and recruitment of BMMs are involved in the resolution of necrotic lesions in Cav-1 KO mice. Wild-type (WT) and Cav-1 KO mice were injected with CCl₄ (10% v/v) to induce acute liver injury model. Blood samples and hepatic tissues were harvested for serum alanine transaminase (ALT) activity assessment, histopathological examination through hematoxylin–eosin (H&E) staining, and BMMs subpopulation analysis via flow cytometry. Then, primary BMMs were isolated and cultured to investigate the effect of Cav-1 on BMMs polarization, migration, and activation of STAT3 signal pathway. Validation of hepatic macrophage depletion was induced by administrating clodronate liposomes (CLs), and BMMs reconstitution was evaluated by EGFP labelled BMMs. Following this, hepatic macrophages were depleted by CLs, BMMs were isolated from Cav-1 KO, and WT mice were cultured and administrated to evaluate the protective role of Cav-1-deleted BMMs on the resolution of hepatocellular necrosis and apoptosis in acute liver injury. The BMMs ratio significantly increased from 2.12% (1D), 4.38% (1W), and 5.38% (2W) in oil control mice to 7.17%, 14.90%, and 19.30% in CCl₄-treated mice (p < 0.01 or p < 0.001). Concurrently, Cav-1 positive BMMs exhibited a marked elevation from 6.41% at 1D to 24.90% by 2W (p = 0.0228). Cav-1 KO exerted protective effects by reducing serum ALT by 26% (p = 0.0265) and necrotic areas by 28% (p = 0.0220) and enhancing BMMs infiltration by 60% (p = 0.0059). In vitro, Cav-1 KO BMMs showed a decrease in CD206 fluorescence intensity (p < 0.001), a time-dependent upregulation of arginase-1 mRNA (p < 0.05 or p < 0.01), a 1.22-fold increase in phosphorylated STAT3 (p = 0.0036), and impaired wound healing from 12 to 24 h (p < 0.001). The macrophage-depleting action in livers by CL injection persists for a minimum of 48 h. Administrated EGFP⁺ BMMs emerged as the predominant population following CL injection for a duration of 48 h. Following clodronate liposome-mediated hepatic macrophage depletion, the adoptive transfer of Cav-1 KO BMMs demonstrated therapeutic efficacy in CCl₄-induced acute liver injury. In CCl₄-induced acute liver injury, the adoptive transfer of Cav-1 KO BMMs reduced necrosis by 12.8% (p = 0.0105), apoptosis by 25.2% (p = 0.0127), doubled macrophages infiltration (p = 0.0269), and suppressed CXCL9/10 mRNA expression (p = 0.0044 or p = 0.0385). BMMs play a key role in the resolution of liver necrotic lesions in CCl₄-induced acute liver injury. Cav-1 depletion attenuates hepatocellular necrosis and apoptosis by accelerating BMMs recruitment and M2 polarization. Cav-1 in macrophages may represent a potential therapeutic target for acute liver injury. Full article

Reducing agricultural carbon emissions is key to promoting the sustainable development of agriculture. Carbon sources play a significant role in the carbon emissions of China’s planting industry. Researching the principles of evolutionary trends of carbon sources regarding carbon emissions in China’s planting industry helps formulate scientific policies to control such emissions in the industry. This paper adopted an emission factor approach from the IPCC to estimate the CO₂ emissions of all kinds of carbon sources in China’s planting industry from 1997 to 2017. On the basis of the data, the principles of dynamic evolution in China’s planting industry and six carbon sources were analyzed by the kernel density estimation approach. Notably, the study discovered that carbon emissions peaked in 2015. In terms of the contributions of various carbon sources to the carbon emissions of the planting industry, sorted by chemical fertilizers, agricultural diesel oil, agricultural films, pesticides, agricultural irrigation, and seeding, their contribution rates were 60.82%, 13.95%, 12.88%, 9.83%, 1.88%, and 0.64%. At the same time, the kernel density results show that there was an increasing trend in carbon emissions across the whole of China’s planting industry and six kinds of carbon sources nationwide, with apparent “multipolarization”. From the perspective of various regions, the carbon emissions of chemical fertilizers, diesel oil, films, and pesticides in China’s planting industry had an evolutionary trend of multipolarization in central regions, while there was an evolutionary trend of monopolarization in eastern and western regions. The carbon emissions of seeding and irrigation had a similarly evolutionary trend in eastern, central, and western regions. Basically, they all had a double increase pattern in carbon emissions and regional differences. Therefore, China’s government needs a target to set up long-term mechanisms to ensure a stable and orderly reduction in carbon emissions in the planting industry, leading its development from the traditional planting industry to a climate-smart planting industry. Full article

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by a gradual decline in cognitive function. Currently, there are no effective treatments for this condition. Medicine food homology plants have gained increasing attention as potential natural treatments for AD because of their nutritional value and therapeutic benefits. In this work, we aimed to provide a deeper understanding of how medicine food homology plants may help alleviate or potentially treat AD by identifying key targets, pathways, and small molecule compounds from 10 medicine food homology plants that play an important role in this process. Using network pharmacology, we identified 623 common targets between AD and the compounds from the selected 10 plants, including crucial proteins such as STAT3, IL6, TNF, and IL1B. Additionally, the small molecules from the selected plants were grouped into four clusters using hierarchical clustering. The ConPlex algorithm was then applied to predict the binding capabilities of these small molecules to the key protein targets. Cluster 3 showed superior predicted binding capabilities to STAT3, TNF, and IL1B, which was further validated by molecular docking. Scaffold analysis of small molecules in Cluster 3 revealed that those with a steroid-like core—comprising three fused six-membered rings and one five-membered ring with a carbon–carbon double bond—exhibited better predicted binding affinities and were potential triple-target inhibitors. Among them, MOL005439, MOL000953, and MOL005438 were identified as the top-performing compounds. This study highlights the potential of medicine food homology plants as a source of active compounds that could be developed into new drugs for AD treatment. However, further pharmacokinetic studies are essential to assess their efficacy and minimize side effects. Full article

Forests mitigate greenhouse gas (GHG) emissions by capturing CO₂ and storing it as carbon in various forms, including living biomass, dead wood, soil, and forest litter. Importantly, when trees are harvested, a portion of the above-ground biomass is converted into harvested wood products (HWPs), which can retain carbon for decades. With approximately 7 million hectares of forest (30% of its land area), Romania significantly contributes to the country’s carbon budget through the HWP pool. Using country-specific data from 1961 to 2022 and an IPCC method, we tracked HWP carbon storage and projected future scenarios to evaluate the category’s significance in achieving the 2050 climate target. During this period, the carbon stored in Romanian HWPs more than doubled from 28.20 TgC to 60.76 TgC, with sawnwood products as major contributors. Fluctuations were influenced by domestic policies, market dynamics, and industry changes, notably after the 1990s. Annual carbon inflow dipped to 0.65 TgC in 1994 and peaked at 2.54 TgC in 2013. By analyzing the scenarios, we demonstrated that a moderate growth trajectory in carbon inflow, combined with a focus on producing long-lived wood products, could double carbon stock changes by 2050 to 4.4 TgC—roughly 4% of the country’s current total emissions excluding the LULUCF sector. Additionally, based on sustainable forest management practices in Romania, this approach would significantly enhance the carbon pool and its importance in achieving the country’s climate policies. Full article

Glioblastoma (GBM), the most prevalent primary malignant brain tumor, remains challenging to treat due to extensive inter- and intra-tumor heterogeneity. This variability demands combination treatments to improve therapeutic outcomes. A significant obstacle in treating GBM is the expression of O⁶-methylguanine-DNA methyltransferase, a DNA repair enzyme that reduces the efficacy of the standard alkylating agent, temozolomide, in about 50% of patients. This underscores the need for novel, more targeted therapies. Our study investigates the metabolic–epigenetic impact of combining SN-38, a novel topoisomerase inhibitor inducing DNA double-strand breaks, with rabusertib, a checkpoint kinase 1 inhibitor. We identified this synergistic combination through high-throughput drug screening across a panel of GBM cell lines using a cancer drug library combined with SN-38. A secondary metabolic screening with the PEDS algorithm demonstrated a synergistic modulation of purine, one-carbon, and redox metabolism. Furthermore, the combined treatment led to the significant depletion of epigenetically relevant metabolites such as 5-methyl-cytosine, acetyl-lysine, and trimethyl-lysine. Reduced intermediates of the glutathione cycle indicated increased cellular stress following combinatorial treatment. Overall, the combination of SN-38 and rabusertib synergistically disrupts metabolites associated with epigenetic adaptations, leading to cytotoxicity independent of O⁶-methylguanine-DNA methyltransferase status, thereby underpinning this combination as a promising candidate for combinatorial therapy in GBM. Full article

The increasing challenges posed by plant viral diseases demand innovative and sustainable management strategies to minimize agricultural losses. Exogenous double-stranded RNA (dsRNA)-mediated RNA interference (RNAi) represents a transformative approach to combat plant viral pathogens without the need for genetic transformation. This review explores the mechanisms underlying dsRNA-induced RNAi, highlighting its ability to silence specific viral genes through small interfering RNAs (siRNAs). Key advancements in dsRNA production, including cost-effective microbial synthesis and in vitro methods, are examined alongside delivery techniques such as spray-induced gene silencing (SIGS) and nanocarrier-based systems. Strategies for enhancing dsRNA stability, including the use of nanomaterials like layered double hydroxide nanosheets and carbon dots, are discussed to address environmental degradation challenges. Practical applications of this technology against various plant viruses and its potential to ensure food security are emphasized. The review also delves into regulatory considerations, risk assessments, and the challenges associated with off-target effects and pathogen resistance. By evaluating both opportunities and limitations, this review underscores the role of exogenous dsRNA as a sustainable solution for achieving viral disease resistance in plants. Full article

Peroxynitrite (ONOO⁻) plays an important role in many physiological and pathological processes. Excessive ONOO⁻ in cells leads to oxidative stress and inflammation. However, precise monitoring of ONOO⁻ levels in specific organelles (e.g., mitochondria) is still lacking and urgently needed. Herein, we rationally designed a mitochondria-targeted ratiometric fluorescent probe, MOBDP-I, for imaging of ONOO⁻ in the mitochondria of inflammatory cells and model mice. This probe, MOBDP-I, was synthesized by conjugating a BODIPY fluorophore to a mitochondria-targeting moiety–indole-salt group by a carbon–carbon double bond (C=C). In the presence of ONOO⁻, the C=C bond between the BODIPY backbone and the indole-salt group was oxidized and broken, leading to an 18-fold enhancement of fluorescence at 510 nm, along with a significant fluorescence decrease at 596 nm. The ratiometric response property bestowed the probe with advantages in the precise quantification of ONOO⁻ in cells, thus allowing estimation of the extent of inflammation in living cells and mouse models of rheumatoid arthritis, peritonitis, and brain inflammation. MOBDP-I could act as an effective molecular tool to study the relationship between ONOO⁻ and the occurrence and development of inflammatory diseases. Full article

The Middle Permian Maokou Formation carbonate rocks in the southern Sichuan Basin are import targets for hydrocarbon exploration, with numerous gas fields discovered in structural traps. However, as exploration extends into slope and syncline zones, the limestone reservoirs become denser, and fluid distribution becomes increasingly complex, limiting efficient exploration and development. Identifying the key factors controlling natural gas accumulation is therefore critical. This study is the first to apply deep learning techniques to fault detection in the southern Sichuan Basin, identifying previously undetected WE-trending subtle strike-slip faults (vertical displacement < 20 m). By integrating well logging, seismic, and production data, we highlight the primary factors influencing natural gas accumulation in the Maokou Formation. The results demonstrate that 80% of production comes from less than 30% of the well, and that high-yield wells are strongly associated with faults, particularly in slope and syncline zones where such wells are located within 200 m of fault zones. The faults can increase the drilling leakage of the Maokou wells by (7–10) times, raise the reservoir thickness to 30 m, and more than double the production. Furthermore, 73% of high-yield wells are concentrated in areas of fault intersection with high vertical continuity. Based on these insights, we propose four hydrocarbon enrichment models for anticline and syncline zones. Key factors controlling gas accumulation and high production include fault intersections, high vertical fault continuity, and local structural highs. This research demonstrates the effectiveness of deep learning for fault detection in complex geological settings and enhances our understanding of fault systems and carbonate gas reservoir exploration. Full article

Double photoionization (DPI) allows for a sensitive and direct probe of electron correlation, which governs the structure of all matter. For atoms, much of the work in theory and experiment that informs our fullest understanding of this process has been conducted on helium, and efforts continue to explore many-electron targets with the same level of detail to understand the angular distributions of the ejected electrons in full dimensionality. Expanding on previous results, we consider here the double photoionization of two $2p$ valence electrons of atomic carbon and neon and explore the possible continuum states that are connected by dipole selection rules to the coupling of the outgoing electrons in ³P, ¹D, and ¹S initial states of the target atoms. Carbon and neon share these possible symmetries for the coupling of their valence electrons. Results are presented for the energy-sharing single differential cross section (SDCS) and triple differential cross section (TDCS), further elucidating the impact of the initial state symmetry in determining the angular distributions that are impacted by the correlation that drives the DPI process. Full article

Carbon emissions trading pilots are an essential environmental regulation tool for incentivizing companies to reduce carbon emissions and a critical initiative for achieving “dual carbon” targets. This study, based on 2366 observations of 169 high-carbon listed companies on the Shanghai and Shenzhen stock exchanges from 2009 to 2022, uses double machine learning analysis to examine the impact and mechanisms of pilot policy on the low-carbon competitiveness of high-carbon industry-listed companies. The empirical results show that, first, pilot policy significantly enhances the low-carbon competitiveness of high-carbon industry-listed companies, and this conclusion holds after considering a series of robustness checks. Second, mechanism analysis indicates that alleviating green financing constraints and enhancing total factor productivity are pathways through which pilot policy influences low-carbon competitiveness. Heterogeneity analysis shows that the policy effects are stronger for state-owned enterprises, small- and medium-sized enterprises, and companies in eastern regions. Further analysis reveals that pilot policy enhances low-carbon competitiveness and increase enterprise value. Based on the study’s conclusions, the government should ensure the incentivizing effect of pilot policy, promote expansion of the carbon emissions trading market, assist enterprises in overcoming green financing constraints, improve total factor productivity, and formulate tailored policies according to the development levels and resource endowments of regions and companies. Full article

This paper presents the results of a study on the characteristics of semiconductor sensors based on thin SnO₂ films modified with antimony, dysprosium, and silver impurities and dispersed double Pt/Pd catalysts deposited on the surface to detect carbon monoxide (CO). An original technology was developed, and ceramic targets were made from powders of Sn-Sb-O, Sn–Sb-Dy–O, and Sn–Sb-Dy-Ag–O systems synthesized by the sol–gel method. Films of complex composition were obtained by RF magnetron sputtering of the corresponding targets, followed by technological annealing at various temperatures. The morphology of the films, the elemental and chemical composition, and the electrical and gas-sensitive properties were studied. Special attention was paid to the effect of the film composition on the stability of sensor parameters during long-term tests under the influence of CO. It was found that different combinations of concentrations of antimony, dysprosium, and silver had a significant effect on the size and distribution of nanocrystallites, the porosity, and the defects of films. The mechanisms of degradation under prolonged exposure to CO were examined. It was established that Pt/Pd/SnO₂:0.5 at.% Sb film with optimal crystallite sizes and reduced porosity provided increased stability of carbon monoxide sensor parameters, and the response to the action of 100 ppm carbon monoxide was G₁/G₀ = 2–2.5. Full article