Search Results (2,063)

To clarify the composition and origin of the suspected solid bitumen, which is found in the fractures of the Jixian System in Tongcheng outcrops, the suspected solid bitumen samples, as well as dolomite samples, were collected from the Jixian System in Tongcheng and Qishan outcrops for various tests. The results show that the suspected solid bitumen samples are mainly composed of clay minerals. No solid bitumen was found in the pores and microcracks of the dolomite samples by microscope and Raman spectroscopy. The total organic carbon content of the solid bitumen ranges from 0.59% to 1.15%, revealing that the suspected solid bitumen is dark mudstone powder, rather than solid bitumen. The R_b values range from 2.59% to 2.77%, and the Ts/(Ts + Tm) values mostly approach 0.5, indicating that the organic matter in the suspected solid bitumen is in the mature to over-mature stage. The V/(V + Ni), Sr/Cu, and Sr/Ba values of the suspected solid bitumen indicate that it was deposited in a warm, humid, anoxic sedimentary environment. The slightly right-inclined rare earth element pattern of the suspected solid bitumen samples implies the sedimentation rate was slow or they were affected by weathering and leaching processes. Through a comparison of trace elements and hierarchical clustering analysis of rare earth elements, the suspected solid bitumen manifests the closest correlation with the mudstone source rocks of the Cambrian Zhangxia Formation. Early Devonian period, the Cambrian mudstone source rocks in the Tongcheng area were uplifted; then weathered, leached, and fragmented into powder; and then filled the fractures of the underlying Mesoproterozoic Jixian System. Of course, another geological scenario has not been ruled out: that some of the fractures in the Jixian System may be filled with solid bitumen, which may be the result of the destroyed paleo-oil reservoirs near the ancient uplift in the Tongcheng area. Full article

Against the backdrop of global climate change and carbon neutrality strategies, land use carbon emissions have become a prominent topic amid regional efforts toward low-carbon transformation. However, existing studies on land-use carbon emissions have predominantly focused on humid and economically developed regions, while the unique carbon metabolism pathways of arid oasis–desert ecosystems, which are characterized by extremely low environmental carrying capacity and high sensitivity to land-use disturbance, remain largely unexplored. This study takes the oasis urban cluster in the Tarim Basin in southern Xinjiang Uygur Autonomous Region as the research object. This region belongs to a typical oasis–desert composite ecosystem, with a simple structure and low environmental carrying capacity (reflected by sparse vegetation cover <20%, annual precipitation <100 mm, extremely limited water resources, and high sensitivity to land disturbance). Its carbon metabolism pathway (i.e., the dynamic balance between carbon sources and sinks induced by land-use change) is fundamentally different from that in humid areas, and thus merits dedicated investigation. This study selects the period from 2000 to 2020 as the research period, which completely covers the acceleration period of urbanization and agricultural expansion in the Tarim Basin oasis urban cluster since the advancement of China’s Western Development Initiative. The data have a temporal resolution of 5 years (samples in 2000, 2005, 2010, 2015, 2020) and a spatial resolution of 30 m for land use and prefecture level for socio-economic indicators. Based on this, to fill the above-mentioned research gap, a research framework integrating the carbon emission coefficient accounting method, landscape pattern index, spatial autocorrelation analysis and geographic detector is adopted. Specifically, this study aims to systematically quantify the spatio-temporal evolution of land use carbon emissions and identify the most robust driving factors in the Tarim Basin oasis urban cluster by integrating multiple models, an approach that has not been previously applied to arid oasis regions. The research results show: (1) Based on the carbon emission coefficient method, total carbon emissions increased from 1.4455 million tons to 22.364 million tons, following a ‘slow-then-fast’ trajectory. In terms of temporal evolution, the study period can be further divided into three sub-stages: 2000–2005 (slow diffusion, with emission center skewed toward the northern energy-intensive zone), 2005–2015 (rapid restructuring, characterized by a ‘unipolar surge’ in Aksu and spread to the central oasis belt), and 2015–2020 (high-intensity stabilization, forming a cross-regional emission belt). Meanwhile, the land use structure has undergone a significant transformation. Construction land and cultivated land have continued to expand, while ecological land has significantly shrunk, resulting in a complex transformation pattern of oasis–desert ecotone. (2) The overall landscape became increasingly fragmented and diversified, the integrity of ecological space was damaged, and the regional carbon sink function was weakened. (3) The spatial autocorrelation analysis indicates that the spatial distribution of carbon emissions shows a heterogeneous pattern, forming a high-emission concentration area centered around Aksu-Bayingol. However, the global Moran’s I index is negative (such as −0.171 in 2020, p > 0.05), suggesting that carbon emissions have not formed a significant spatial clustering. (4) Carbon emissions are dominated by human and economic factors, and the interaction of factors is significant. The geographic detector identifies population density (average q value 0.904) and the proportion of construction land (average q value 0.858) as the key determinants of spatial variation in carbon emissions, reflecting the sensitive response of the human-nature system of arid zones to the urbanization process. These findings not only clarify the spatio-temporal features and driving forces of land use carbon emissions in the Tarim Basin oasis urban cluster, but also provide a replicable analytical framework for carbon-emission research in other arid and semi-arid regions worldwide. Based on these findings, we discuss the unique driving mechanisms of carbon emissions in arid regions, conclude that construction land expansion and population density are the dominant factors, and recommend a three-tier zoning governance system (carbon source control zone, carbon sink enhancement zone, coordinated development zone) for low-carbon spatial planning in arid areas. Full article

Rapid urban expansion has increasingly reshaped the carbon budgets of urban agglomerations through land use change. However, the role of functional heterogeneity within construction land remains insufficiently considered when examining the spatial differentiation of construction expansion-related carbon increases. Using the Pearl River Delta Urban Agglomeration in China as the study area, this research traced the spatiotemporal changes in land use carbon budgets between 2000 and 2024, evaluated how the expansion of construction land contributed to the growth of regional carbon emissions, and further examined the spatial associations between six construction land functional categories and expansion-related carbon increases over the period of 2010–2024. The results show the following. (1) During 2000–2024, approximately 15,200 km² of land experienced use transitions, representing 28.2% of the regional land area. These transitions generated an accumulated increase of 15.46 million t in net carbon emissions, largely driven by the conversion of cultivated land, forest land, and other non-construction land into construction land. (2) Approximately 96.2% of the carbon increase from land use transitions was attributed to the conversion of other land use types into construction land, confirming construction land expansion as the dominant pathway of regional carbon increases. (3) From 2010 to 2024, expansion-related carbon increases showed significant spatial clustering, with high-value clusters mainly concentrated in the Guangzhou–Foshan–Dongguan–Shenzhen corridor and low-value clusters in peripheral areas. (4) Functional space variables were further associated with the spatial differentiation of carbon increases. Industrial and transportation spaces showed the strongest spatial associations, and their interaction showed the strongest explanatory effect, while GWR results revealed stronger local associations in peripheral areas and weaker associations in core areas. These findings provide empirical support for carbon-focused land use governance, functional optimization of construction land, and differentiated territorial spatial regulation in rapidly urbanizing urban agglomerations. Full article

Against the backdrop of China’s “Dual Carbon” strategy—the national strategic goal of achieving carbon peaking by 2030 and carbon neutrality by 2060—and the accelerated improvement of the solid waste governance system specified in the 15th Five-Year Plan, the low-carbon recycling of construction waste has become a core research topic for the sustainable development of the construction industry. To systematically reveal the evolutionary laws, research hotspots and frontier trends regarding the life-cycle carbon emissions of recycled concrete (this study defines its accounting scope clearly for the first time, covering three parts: ① direct carbon emissions generated in the stages of recycled aggregate recovery, processing, transportation and concrete mixing; ② indirect carbon emissions reduced by replacing the exploitation of natural aggregates with recycled aggregates; ③ potential carbon sequestration benefits brought by carbonation curing during the service phase of recycled concrete), the literature published from 2015 to 2025 retrieved from the CNKI and Web of Science Core Collection databases was selected as the research sample. Standardized data preprocessing was carried out: intra-database duplicate literatures were removed based on titles, authors and publication years, cross-database duplicate records were manually eliminated, and non-academic documents including news, editorial notes and conference abstracts were screened out. A total of 1340 valid publications were finally obtained to form the analysis dataset. Bibliometric tools CiteSpace and VOSviewer were adopted to quantitatively analyze the annual publication trends, national and institutional distribution, keyword co-occurrence clustering and temporal evolution characteristics in this research field. The results show that the annual publication volume concerning the life-cycle carbon emissions of recycled concrete presents a continuous upward trend, and the research development can be divided into three stages: initial exploration, rapid expansion and steady growth. China, the United States and Australia act as the core research forces in this field. Current research hotspots mainly focus on recycled aggregate modification, life-cycle assessment, carbon emission accounting, durability performance optimization and low-carbon preparation technologies, while research frontiers are gradually shifting toward multi-source data fusion, machine learning-based carbon emission prediction and low-carbon path optimization. Based on the quantitative bibliometric results, this study puts forward targeted priorities for future research: establishing a unified localized specification system for life-cycle carbon accounting, developing data-driven optimization models for the low-carbon mix proportion design of recycled concrete, and promoting the large-scale engineering demonstration and application of high-value resource utilization technologies, to facilitate the full life-cycle low-carbon transformation of construction waste recycling. Full article

Accurate discrimination of multiple heavy metal ions is essential for environmental monitoring. This study developed a simple fluorescent sensing array utilizing carbon dots derived from black plum peels (PCDs) for the precise identification of metal ions in environmental waters. Three structurally distinct PCDs were hydrothermally synthesized using phenylenediamine isomers as nitrogen dopants, exhibiting distinct fluorescence response patterns to target ions. Pattern recognition was performed using linear discriminant analysis (LDA) and hierarchical clustering analysis (HCA). The optimized system (pH 5–7) achieved high discrimination accuracy for eight metal ions (Sn²⁺, Ag⁺, Hg²⁺, Fe³⁺, Cr³⁺, Pb²⁺, Sb³⁺, and Cu²⁺) at 5–400 μM concentrations. The array effectively identified the binary and ternary mixtures of Hg²⁺/Cu²⁺/Cr³⁺ and successfully detected target ions in river water samples. This cost-effective and scalable approach demonstrates strong potential for applications in water quality monitoring and food safety. Full article

Carbon dioxide (CO₂) corrosion affects the integrity of energy and process infrastructure, yet the field has lacked a quantitative description of its own structure and evolution. This study presents a scientometric analysis of CO₂ corrosion research published between 2005 and 2025, based on 8671 documents retrieved from Scopus and Web of Science and processed in VOSviewer for co-authorship, co-citation, and keyword co-occurrence mapping. Annual output rose from low and irregular levels in the early period to sustained growth from approximately 2013 onward, and more than 80% of cumulative citations were recorded after 2016, indicating that the recently published literature constitutes the field’s actively cited base. Ranked by publication volume, China and the United States are the leading contributors across both databases, followed by a stable group of European and other national communities; at the institutional level, energy-focused organizations predominate, and Corrosion Science is the most frequently occurring and most strongly connected source in the co-citation network. Keyword co-occurrence mapping resolves the literature into four thematic clusters: physic-chemical context, degradation quantification, electrochemical and surface-analytical methods, and industrial application. The analysis also indicates that broad CO₂-based queries retrieve substantial adjacent-field literature; corrosion-specific search terms are therefore suggested for delimiting this domain in future bibliometric studies. Full article

Bioinspired superhydrophobic surfaces (SHS) have been proven to afford high corrosion inhibition to the underlying metal. Targeting brass metal, this paper presents a biomimetic mineralization route for obtaining SHS. Calcium carbonate is first synthesized in an ethanol solution containing an organic curing agent through CO₂ gas introduction, resulting in colloidal material. Subsequent modification with stearic acid yields the SHS. Electrochemical impedance spectroscopy (EIS) experiments reveal that the biomimetic calcium carbonate cluster coating significantly improves the corrosion inhibition performance. After the coverage of the CaCO₃ SHS, the low-frequency impedance modulus value increases to 4.6 × 10⁵ Ω cm², which is enhanced compared with the bare brass with 3.2 × 10³ Ω cm². Meanwhile, the corrosion current density value decreases substantially from 2.31 × 10⁻⁶ mA/cm² for bare metal to 1.30 × 10⁻⁸ mA/cm² for the SHS surface. This demonstrates its high anti-corrosion properties. Acid-base corrosion tests further confirm the good resistance of the coating to an alkaline environment. Moreover, the coating exhibits anti-freezing adhesion and self-cleaning properties, surpassing the bare brass. The combined characteristics of the biomimetic calcium carbonate SHS coating highlight the promising potential in corrosion protection applications. Full article

Cement slurry is a staple grouting agent, yet its properties can weaken when exposed to heat. Studying grouting materials for use in high-temperature tunnels is therefore a matter of considerable importance. To enhance the applicability of cement-based slurry in high-temperature tunnels, multi-walled carbon nanotubes (MWCNTs), polycarboxylate ether superplasticizer (PCE), and hydroxypropyl methylcellulose (HPMC) were added to improve their performance at elevated temperatures. Various experimental methods were employed to investigate the properties of the modified slurry at different temperatures, including flowability, setting time, compressive strength, and dynamic water retention ratio. Additionally, X-ray diffraction (XRD), thermogravimetric analysis (TG), and scanning electron microscopy (SEM) were used to study the effects of temperature on hardened slurry. Experimental results indicate that the optimal MWCNTs content is 0.32%. At this content, the compressive strength of the hardened slurry after 28 days of curing at 80 °C increases by approximately 20%, reaching 26.4 MPa. PCE improves the fluidity of the slurry, while HPMC enhances its water dynamic water retention ratio. The optimal proportion was found to be 0.3% PCE and 0.2% HPMC. At this ratio, the fluidity of the slurry increased by about 8%, reaching approximately 17.7 cm; the dynamic water retention ratios of 0.8 m/s and 1.0 m/s improved by approximately 22% and 38%, respectively, achieving 35.8% and 18.1%. Furthermore, multi-walled carbon nanotubes significantly enhance the compressive strength of the hardened slurry primarily by suppressing the formation of ettringite during the later stages of hydration, as well as by providing nucleation sites, encapsulating hydration products, and bridging hydration product clusters within the microstructure. This investigation lays a theoretical groundwork for formulating and choosing grouting materials suited to high-temperature tunnel environments. Full article

This study investigates nitrogen-fixing rhizobia associated with Pisum sativum, a member of the tribe Vicieae (Fabaceae), whose species establish symbioses with bacteria belonging predominantly to the symbiovar viciae within the Rhizobium leguminosarum complex (Rlc). Based on a comprehensive taxonomic revision of the F-clade within this complex, we report the identification and characterization of a novel rhizobial subspecies, Rhizobium laguerreae subsp. mediterraneum subsp. nov., isolated from pea nodules in Tunisia. Phylogenetic analyses based on 16S rRNA and multilocus sequence analysis (recA, atpD, dnaK, and glnII) placed strains 25PS6 and 10PS4 within the Rlc, while whole-genome phylogenomics using 2960 single-copy orthologues supported their assignment to a distinct monophyletic clade (Q-II). Subspecies-level clustering consistency was maximized using an optimized ANIm criterion of 97.40%, corresponding to 76.65% dDDH. Both strains belong to symbiovar viciae and exhibited improved symbiotic performance on pea plants compared to the reference strain, indicating strong symbiotic performance and potential relevance for biological nitrogen fixation. Cluster-specific SNP analysis identified 63 exclusive non-synonymous mutations with putative functional effects predicted in silico. These results suggest that cluster-specific nsSNPs may contribute to genomic differentiation within the Q-II lineage. Phenotypic and chemotaxonomic analyses further distinguished the novel subspecies based on carbon utilization, enzymatic activity, antibiotic resistance, and fatty acid profiles. Together, these findings highlight the genomic diversity within nitrogen-fixing rhizobia associated with legumes and identify a novel subspecies with potential agronomic relevance for improving symbiotic nitrogen fixation in pea cultivation. The proposed subspecies, Rhizobium laguerreae subsp. mediterraneum, is represented by strains 10PS4 and 25PS6, with strain 25PS6^T (=DSM 116212^T = LMG 33205^T) designated as the type strain. Full article

Deforestation remains a crucial Anthropocene challenge, driving biodiversity loss, carbon emissions, and socio-ecological disruption. Despite extensive study, the long-term structure, thematic evolution, and collaborative patterns of deforestation research remain insufficiently synthesized. This bibliometric analysis examines 5091 publications from WoS and Scopus (1974–2025), using RStudio (version 4.5.2 (31 October 2025)), VOSViewer (version 1.6.20), and Excel to analyze publication trends, citation patterns, thematic clusters, and collaboration networks. Results show rapid growth after 2000, with citation peaks in 2010 and 2020. Major thematic clusters include deforestation, climate change, agriculture, governance, REDD+, and remote sensing. Environmental Research Letters is the most influential journal; Fearnside, P., is the leading author, and the UC system is a top institution. The USA and Brazil lead nationally, with the Amazon, Congo Basin, and Southeast Asia as primary geographic foci, reflecting persistent North–South collaboration dynamics. Limitations include reliance on English-language publications and title-only search criteria, which may underrepresent non-Anglophone research. Future research should expand to multiple languages, incorporate gray literature, and examine the policy impacts of deforestation-free supply chain regulations, such as the EUDR. This review underscores deforestation science as a growing, multidisciplinary field that requires the integration of social and ecological sciences, AI, and geospatial tools, alongside stronger research-policy linkages and enhanced capacity in forest-affected regions. Full article

With the widespread application of park integrated energy systems (PIESs), challenges of multi-energy coupling, high investment costs, and multi-type uncertainties have become increasingly prominent. Existing research often employs typical scenario generation or robust optimization for short-term uncertainties but struggles with long-term load growth uncertainties and fails to fully utilize the flexibility of demand-side resources during the planning phase. This paper proposes a robust planning method for PIESs considering dynamic demand response and multi-timescale uncertainties. First, an energy flow framework encompassing cooling, heating, electricity, gas, and hydrogen is constructed. To overcome the limitations of traditional fixed-boundary DR, a dynamic elastic DR mechanism featuring transferable, substitutable, and curtailable types is established. Transferable demand boundaries are defined by a price–demand elasticity matrix, and actual responses are dynamically adjusted in synergy with system power balance conditions for optimal configuration. Second, multivariate dynamic time warping and hierarchical clustering algorithms derive typical daily scenarios accounting for short-term uncertainties. Finally, information gap decision theory characterizes long-term load growth uncertainty, constructing a robust planning model addressing both timescales. Case studies show that flexible resources and demand response reduce lifecycle cost by 55.24% and carbon emissions by 47.75%. The proposed demand response method further cuts costs by 153,800 yuan and emissions by 11.36%. The robust planning method synergistically addresses multi-timescale uncertainties, ensuring economy while maximizing resilience to uncertain fluctuations. Full article

The post-COVID-19 tourism recovery exposes a structural divergence between economic resilience and environmental sustainability. Traditional tourism planning metrics consistently fail to diagnose how macroeconomic growth dynamics decouple from environmental pressures, leaving policymakers without empirical tools to identify structural vulnerabilities or prevent carbon-intensive recoupling during post-crisis transitions. This study integrates macroeconomic, environmental, and digital data across a global panel to map actionable pathways for sustainable tourism transitions. Employing a multi-stage methodology, the analysis first utilizes K-Means clustering (n = 80) to isolate the structural fixed effects of baseline destination archetypes driving a K-shaped recovery. Second, using a synchronized environmental panel (n = 41), a Decoupling Index evaluates eco-efficiency elasticity to test the alignment between tourism value recovery and aviation-induced CO₂ emissions. Third, regression analysis of an elite digital cohort (n = 18) measures dynamic exogenous catalysts, revealing that digital attractiveness, proxied by the global digital nomad market share, is a significantly stronger accelerator of recovery (β = 55.59, p = 0.019) than traditional physical air connectivity (β = −46.48, p = 0.036). Synthesizing these insights, a 2 × 2 Strategic Decision Matrix (n = 41) classifies destinations into Sustainable Leaders, Mass-Market Traps, Value Pivoters, and Vulnerable Laggards. The empirical results demonstrate that pre-pandemic structures do not deterministically dictate recovery (p > 0.05, Partial η² ≤ 0.077), yet rapid financial recovery often masks deep atmospheric vulnerabilities, with specific absolute decoupling leaders achieving exceptional value expansion alongside strict carbon contraction (e.g., Saudi Arabia, DE = −0.35; El Salvador, DE = −0.26). This framework provides a data-driven roadmap for policymakers to utilize “soft” digital infrastructure to transition from carbon-intensive, volume-dependent models toward value-optimized, low-emission ecosystems. Full article

The accurate detection of soil organic carbon (SOC) is essential due to its role in nutrient availability for plants and its contribution to sustainable agricultural practices that benefit the environment. However, detecting SOC in computed tomography (CT) images poses challenges, as this component is small, and its gray intensity resembles that of pores. This study developed a novel methodology that characterizes two soil samples accurately by detecting spaces such as pores/macropores, gravel, solids, and especially candidate SOC regions (cSOCRs). The approach includes 3D representation for analyzing the distribution, density, and connectivity of macropores/pores and candidate SOC regions. We proposed a dual segmentation method: first, identifying pores/macropores and non-pores (gravel, solids, and cSOCRs) using standard algorithms; second, sub-segmenting to detect solid and gravel regions, highlighting atypical sub-regions. One of these atypical regions in the gravel space corresponds to cSOCRs. Quality was assessed through a homogeneity measure, assuring consistency in the detected regions. The results confirm the effectiveness of dual segmentation in accurately detecting and characterizing cSOCRs in soil samples. The detected cSOCR content ranged from 2% to 9% in Sample I and from 5% to 10% in Sample II, demonstrating the method’s ability to capture variations in organic carbon distribution. This approach stands out as a promising and reliable alternative for soil characterization studies. The findings contribute to precision agriculture by enabling informed decision-making, reducing unnecessary tillage in areas with a high cSOCR content, and optimizing the application of fertilizers and compost in regions with low cSOCR levels. Full article

Against the background of the dual carbon goals and the high proportion of distributed energy access, the distribution network presents the characteristics of source–network–load–storage two-way interaction. Traditional centralized control struggles to cope with voltage fluctuation, new-energy consumption difficulties and control dimension explosion. This paper focuses on the study of flexible resource aggregation modeling and cloud-side collaborative control, constructs the control constraint model of distributed Photovoltaic, energy storage, electric vehicle and flexible load constraints, proposes a resource aggregation method based on weight-improved K-means clustering, and includes voltage sensitivity to achieve accurate evaluation of adjustable capacity. A cloud–edge–end three-level collaborative control framework is built, and a two-layer scheduling model is established with the goal of peak shaving and valley filling so as to realize global optimization and local rapid response. The simulation results based on the improved IEEE 33-node distribution network show that the proposed method can effectively cluster flexible resources and quantify the adjustable potential. The cloud–edge coordination strategy can effectively reduce the load peak–valley difference, improve new-energy consumption rate and voltage stability, and provide a feasible technical path for the efficient regulation of the active distribution network. Full article

The Milano Cortina 2026 Winter Olympic Games represent a significant departure from traditional mega-event models due to their markedly polycentric territorial structure. This study investigates the sustainability of this “decentralized” model by analyzing the environmental impact of mobility flows across a vast geographic area. Adopting a methodological approach, the research integrates historical attendance data from previous Winter Games with official projections and travel time simulations to model the event’s carbon footprint. Specifically, the framework quantifies gas emissions by categorizing mobility flows into external international travel and internal inter-cluster transit. The analysis highlights a significant discrepancy between the stated sustainability objectives and the actual implementation of the infrastructural plan. Findings reveal that the total carbon debt is heavily driven by international travel, yet the localized impact on Alpine clusters remains critical due to a persistent reliance on road infrastructure over rail systems. The results suggest a “paradox of decentralized sustainability”, where the benefits of reusing existing sporting venues are offset by the environmental costs of connecting geographically fragmented sites. We conclude that without a robust and efficient public transport network, territorial dispersion acts as a catalyst for widespread anthropogenic pressure on fragile mountain ecosystems, challenging the long-term ecological legacy of the event. By empirically exposing these dynamics, this study offers a novel evaluative framework for assessing the true sustainability of distributed governance in future mega-events. Full article