Search Results (1,464)

Industrial structure upgrading serves as an important driving force for the sustained and healthy development of the economy, and it has a positive effect on reducing carbon emission intensity. This study uses provincial panel data from China from 2004 to 2019, starting from the dual perspectives of green total factor productivity and labor misallocation, and employs a four-stage mediation regression model to estimate the mechanism of industrial structure upgrading on carbon emission intensity. The research findings show that: for every 1% increase in industrial structure upgrading, carbon emission intensity will decrease by 0.296%; the central region shows the most significant effect, followed by the western region, while the eastern region shows no significant effect. From the view of the influencing mechanism, industrial structure upgrading will promote green total factor productivity and labor misallocation. When each of the two mediating variables increase by 1%, carbon emission intensity will decrease by 0.12% and 0.054%, respectively. Under the influence of industrial structure upgrading, the inhibitory effects of green total factor productivity and labor misallocation on carbon emission intensity have weakened, and the two factors have made it difficult to form a mediating superposition effect within the sample period. The research conclusion provides the policy implications for China to continuously adhere to industrial structure upgrading, pay attention to improving green total factor productivity, and enhance the low-carbon technical level of workers to achieve the “dual carbon” goals. Full article

Excessive use of antibiotics can lead to antibiotic resistance, posing a significant threat to human health and the environment. Chloramphenicol (CAP), once widely used, has been banned in many regions for over 20 years due to its toxicity. Detecting CAP residues in food products is crucial for regulating safe use and preventing unnecessary antibiotic exposure. Electrochemical sensors are low-cost, sensitive, and easily detect CAP. This paper reviews recent research on electrochemical sensors for CAP detection, with a focus on the materials and fabrication techniques employed. The sensors are evaluated based on key performance parameters, including limit of detection, sensitivity, linear range, selectivity, and the ability to perform simultaneous detection. Specifically, we highlight the use of metal and carbon-based electrode modifications, including gold nanoparticles (AuNPs), nickel–cobalt (Ni-Co) hollow nano boxes, platinum–palladium (Pt-Pd), graphene (Gr), and covalent organic frameworks (COFs), as well as molecularly imprinted polymers (MIPs) such as polyaniline (PANI) and poly(o-phenylenediamine) (P(o-PD)). The mechanisms by which these modifications enhance CAP detection are discussed, including improved conductivity, increased surface-to-volume ratio, and enhanced binding site availability. The reviewed sensors demonstrated promising results, with some exhibiting high selectivity and sensitivity, and the effective detection of CAP in complex sample matrices. This review aims to support the development of next-generation sensors for antibiotic monitoring and contribute to global efforts to combat antibiotic resistance. Full article

With increasing global pressure to decarbonize electricity systems, particularly in regions outside international carbon trading frameworks, it is essential to develop adaptive optimization tools that account for regulatory policies and system-level uncertainty. An emission-constrained power dispatch strategy based on an Adaptive Grouped Fish Migration Optimization (AGFMO) algorithm is proposed. The algorithm incorporates dynamic population grouping, a perturbation-assisted escape strategy from local optima, and a performance-feedback-driven position update rule. These enhancements improve the algorithm’s convergence reliability and global search capacity in complex constrained environments. The proposed method is implemented in Taiwan’s 345 kV transmission system, covering a decadal planning horizon (2023–2033) with scenarios involving varying load demands, wind power integration levels, and carbon tax schemes. Simulation results show that the AGFMO approach achieves greater reductions in total dispatch cost and CO₂ emissions compared with conventional swarm-based techniques, including PSO, GACO, and FMO. Embedding policy parameters directly into the optimization framework enables robustness in real-world grid settings and flexibility for future carbon taxation regimes. The model serves as decision-support tool for emission-sensitive operational planning in power markets with limited access to global carbon trading, contributing to the advanced modeling of control and optimization processes in low-carbon energy systems. Full article

Achieving carbon reduction is essential in advancing China’s dual carbon goals and promoting a green transformation in the transportation sector. Changes in energy structure and intensity constitute key drivers for sustainable and low-carbon development in this field. To explore the spatial spillover effects of the energy structure and intensity on the green transition of transportation, this study constructs a panel dataset of 30 Chinese provinces from 2007 to 2020. It employs a super-efficiency SBM model, non-parametric kernel density estimation, and a spatial Markov chain to verify and quantify the spatial spillover effects of green total factor productivity (GTFP) in the transportation sector. A dynamic spatial Durbin model is then used for empirical estimation. The main findings are as follows: (1) GTFP in China’s transportation sector exhibits a distinct spatial pattern of “high in the east, low in the west”, with an evident path dependence and structural divergence in its evolution; (2) GTFP displays spatial clustering characteristics, with “high–high” and “low–low” agglomeration patterns, and the spatial Markov chain confirms that the GTFP levels of neighboring regions significantly influence local transitions; (3) the optimization of the energy structure significantly promotes both local and neighboring GTFP in the short term, although the effect weakens over the long term; (4) a reduction in energy intensity also exerts a significant positive effect on GTFP, but with clear regional heterogeneity: the effects are more pronounced in the eastern and central regions, whereas the western and northeastern regions face risks of negative spillovers. Drawing on the empirical findings, several policy recommendations are proposed, including implementing regionally differentiated strategies for energy structure adjustment, enhancing transportation’s energy efficiency, strengthening cross-regional policy coordination, and establishing green development incentive mechanisms, with the aim of supporting the green and low-carbon transformation of the transportation sector both theoretically and practically. Full article

Urban carbon reduction is instrumental in enabling cities to realize their developmental sustainability objectives. However, regional disparities in economic development pose significant challenges to low-carbon transitions. This study utilizes panel data from 282 cities in China spanning 2006–2021, considering the energy saving and emission reduction (ESER) fiscal policy as an external shock. Using a multi-period difference-in-differences approach, we assess how ESER impacts urban carbon emissions. Our findings indicate that ESER significantly reduces municipal carbon emissions by an average of 23.3% compared to non-pilot cities. Mechanism analyses suggest that this effect operates through reduced energy consumption, improved industrial structure, and enhanced green innovation. ESER’s impact exhibits heterogeneity across cities with different levels of economic development, population size, innovation capacity, and industrial composition. Moreover, we find evidence of spatial spillover effects, as ESER benefits extend to neighboring regions. These results confirm the effectiveness of ESER in promoting low-carbon development and offer practical implications for enhancing environmental governance through green fiscal instruments. Full article

This study investigates the perceptions of economics students from Romania’s Central Region regarding the global phenomena of globalization, localization, and slowbalization (GLS), analyzed through the lens of environmental, economic, and educational sustainability. The research highlights a high level of awareness and understanding of globalization and localization, while the concept of slowbalization remains relatively unfamiliar and often perceived with uncertainty or neutrality. Most respondents view globalization as the most sustainable model for long-term economic development, emphasizing its contributions to international trade, market expansion, investment flows, and access to global education and research. At the same time, localization is recognized for its role in preserving cultural identity, strengthening local economies, and addressing pressing environmental issues through low-carbon solutions. Regarding educational sustainability, students support a hybrid model that balances global exposure with the appreciation of local knowledge and traditions—a glocal approach particularly endorsed by master’s students. The study also reveals statistically significant differences between undergraduate and graduate respondents, indicating more mature perspectives among those in advanced studies. The paper could help in course design and lesson engagement and concludes by recommending curricular reforms in economic education and proposing future interdisciplinary, comparative, and qualitative research to deepen understanding of GLS dynamics, particularly in the context of emerging global trends and technological transformations. Full article

With increasing energy demand and advancing carbon neutrality goals, arid regions—key areas for centralized photovoltaic (PV) station development in China—urgently require efficient and accurate remote sensing techniques to support spatial distribution monitoring and ecological impact assessment. Although numerous studies have focused on PV station extraction, challenges remain in arid regions with complex surface features to develop extraction frameworks that balance efficiency and accuracy at a regional scale. This study focuses on the Inner Mongolia Yellow River Basin and develops a PV extraction framework on the Google Earth Engine platform by integrating spectral bands, spectral indices, and topographic features, systematically comparing the classification performance of support vector machine, classification and regression tree, and random forest (RF) classifiers. The results show that the RF classifier achieved a high Kappa coefficient (0.94) and F1 score (0.96 for PV areas) in PV extraction. Feature importance analysis revealed that the Normalized Difference Tillage Index, near-infrared band, and Land Surface Water Index made significant contributions to PV classification, accounting for 10.517%, 6.816%, and 6.625%, respectively. PV stations are mainly concentrated in the northern and southwestern parts of the study area, characterized by flat terrain and low vegetation cover, exhibiting a spatial pattern of “overall dispersion with local clustering”. Landscape pattern indices further reveal significant differences in patch size, patch density, and aggregation level of PV stations across different regions. This study employs Sentinel-2 imagery for regional-scale PV station extraction, providing scientific support for energy planning, land use optimization, and ecological management in the study area, with potential for application in other global arid regions. Full article

Land use change significantly affects regional carbon emissions and ecosystem service value (ESV). Under China’s Dual Carbon Goals, this study takes Beijing-Tianjin-Hebei, experiencing rapid land use change, as the study area and counties as the study unit. This study employs a combination of methods, including carbon emission coefficients, equivalent-factor methods, bivariate spatial autocorrelation, and a multinomial logit model. These were used to explore the spatial relationship between land use carbon emissions and ESV, and to identify their key driving factors. These insights are essential for promoting sustainable regional development. Results indicate the following: (1) Total land use carbon emissions increased from 2000 to 2015, then declined until 2020; emissions were high in municipal centers; carbon sinks were in northwestern ecological zones. Construction land was the primary contributor. (2) ESV declined from 2000 to 2010 but increased from 2010 to 2020, driven by forest land and water bodies. High-ESV clusters appeared in northwestern and eastern coastal zones. (3) A significant negative spatial correlation was found between carbon emissions and ESV, with dominant Low-High clustering in the north and Low-Low clustering in central and southern regions. Over time, clustering dispersed, suggesting improved spatial balance. (4) Population density and cultivated land reclamation rate were core drivers of carbon–ESV clustering patterns, while average precipitation, average temperature, NDVI, and per capita GDP showed varied effects. To promote low-carbon and ecological development, this study puts forward several policy recommendations. These include implementing differentiated land use governance and enhancing regional compensation mechanisms. In addition, optimizing demographic and industrial structures is essential to reduce emissions and improve ESV across the study area. Full article

The Eastern Kazakhstan Gold Belt is a major black-shale-hosted gold province in Central Asia where the main types of deposits comprise mineralized zones with auriferous sulfides (micro- and nano-inclusions of gold and refractory gold) and quartz veins with visible gold. The quartz vein deposits are economically less important but may potentially represent the upper parts of bigger ore systems concealed at depth. In this work, the mineralogy of the quartz vein deposits and related wall rock alteration zones was studied using microscopy and SEM-EDS analysis, and the geochemical dispersion of the ore elements in primary alteration haloes was documented utilizing spatial distribution maps and statistical treatment methods. The studied auriferous quartz veins are classified as epizonal black-shale-hosted orogenic gold deposits. The veins generally have linear shapes with an average width of ca. 1 m and length up to 150 m and contain high-grade native gold with minor amounts of sulfides. In supergene oxidation zones, the native gold is closely associated with Fe-hydroxide minerals cementing brecciated zones within the veins. The auriferous quartz veins are usually enclosed by the wall rock alteration envelopes, where two types of alteration are distinguished. Proximal phyllic alteration (sericite-albite-pyrite ± chlorite, Fe-Mg-Ca carbonates, arsenopyrite, and pyrrhotite) develops as localized alteration envelopes, and pervasive carbonation accompanied by chlorite ± sericite and albite is the dominant process in the distal alteration zones. The rocks within the alteration zones are enriched in Au and chalcophile elements, and three groups of chemical elements showing significant positive mutual correlation have been identified: (1) an early geochemical assemblage includes V, P, and Co (±Ni), which are the chemical elements characteristic for black shale formations, (2) association of Au, As, and other chalcophile elements is distinctly overprinting, and manifests the main stage of sulfide-hosted Au mineralization, and (3) association of Bi and Hg (±Sb and U) includes the chemical elements that are mobile at low temperatures, and can be explained by activity of the late-stage hydrothermal or supergene fluids. The chalcophile elements show negative slopes from proximal to distal alteration zones and form overlapping positive anomalies on spatial distribution mono-elemental maps. Thus, the geochemical methods can provide useful tools to delineate the ore elemental associations and to outline reproducible anomalies for subsequent regional gold prospecting. Full article

While technologies like renewable energy and low-carbon transportation are known to mitigate carbon emissions from urban expansion, achieving carbon neutrality during this process remains a critical unresolved challenge. This issue is particularly pressing for developing countries striving to balance urbanization with carbon reduction. Taking Qionglai City as a case study, this study simulated the territorial spatial functional patterns (TSFPs) and carbon emission distribution for 2025 and 2030. Based on the key drivers of carbon emissions from urban expansion identified through the Geographical and Temporal Weighted Regression (GTWR) model, carbon-neutral pathways were designed for two scenarios: urban expansion scenarios under historical evolution patterns (Scenario I) and urban expansion scenarios optimized under carbon neutrality targets (Scenario II). The results indicate that (1) urban space is projected to expand from 6094.73 hm² in 2020 to 6249.77 hm² in 2025 and 6385.75 hm² in 2030; (2) total carbon emissions are forecasted to reach 1.25 × 10⁶ t (metric tons) and 1.40 × 10⁶ t in 2025 and 2030, respectively, exhibiting a spatial pattern of “high in the central-eastern regions, low in the west”; (3) GDP, Net Primary Productivity (NPP), and the number of fuel vehicles are the dominant drivers of carbon emissions from urban expansion; and (4) a four-pronged strategy, optimizing urban green space vegetation types, replacing fuel vehicles with new energy vehicles, controlling carbon emissions per GDP, and purchasing carbon credits, proves effective. Scenario II presents the optimal pathway: carbon neutrality in the expansion zone can be achieved by 2025 using the first three measures (e.g., optimizing 66.73 hm² of green space, replacing 800 fuel vehicles, and maintaining emissions at 0.21 t/10⁴ CNY per GDP). By 2030, carbon neutrality can be achieved by implementing all four measures (e.g., optimizing 67.57 hm² of green space, replacing 1470 fuel vehicles, and achieving 0.15 t/10⁴ CNY per GDP). This study provides a methodological basis for local governments to promote low-carbon urban development and offers practical insights for developing nations to reconcile urban expansion with carbon neutrality goals. Full article

To advance global climate governance, this study investigates the carbon emission efficiency (CEE) of 110 Chinese resource-based cities (RBCs) using a super-efficiency SBM-GML model combined with kernel density estimation and spatial analysis (2006–2022). Spatial Durbin model (SDM) and geographically and temporally weighted regression (GTWR) further elucidate the driving mechanisms. The results show that (1) RBCs achieved modest CEE growth (3.8% annual average), driven primarily by regenerative cities (4.8% growth). Regional disparities persisted due to decoupling between technological efficiency and technological progress, causing fluctuating growth rates; (2) CEE exhibited high-value clustering in the northeastern and eastern regions, contrasting with low-value continuity in the central and western areas. Regional convergence emerged through technology diffusion, narrowing spatial disparities; (3) energy intensity and government intervention directly hinder CEE improvement, while rigid industrial structures and expanded production cause negative spatial spillovers, increasing regional carbon lock-in risks. Conversely, trade openness and innovation level promote cross-regional emission reductions; (4) the influencing factors exhibit strong spatiotemporal heterogeneity, with varying magnitudes and directions across regions and development stages. The findings provide a spatial governance framework to facilitate improvements in CEE in RBCs, emphasizing industrial structure optimization, inter-regional technological alliances, and policy coordination to accelerate low-carbon transitions. Full article

Tourism ecological efficiency (TEE) is a significant indicator of the development level of green and intensive tourism. However, conventional directional and radial TEE measurement approaches overlook critical factors such as intermediate process influences and input–output slack variables, potentially leading to biased estimates. Urban areas are key to coordinating tourism across provinces, so accurately assessing the TEE is vital for sustainable regional tourism. This study uses an improved TEE measurement model to measure the TEE of the Guangdong–Fujian–Zhejiang (GFZ) coastal city clusters from 2010 to 2021. The improved TEE measurement model is a three-stage super-efficiency SBM approach. It then uses standard deviation ellipses and geographic detectors to analyze the TEE’s spatiotemporal characteristics and influencing factors. The findings indicate the following: (1) The three-stage super-efficiency SBM approach improves the accuracy and validity of measurement results by removing external environmental variables. (2) During the study period, the TEE values of the GFZ coastal city clusters were above average (except for Meizhou, where the efficiency improved). Temporally, the TEE values of 75% of the cities showed an increasing trend; spatially, the high-value areas increased significantly, the middle- and low-value areas decreased, and the center of gravity shifted to the north and south. (3) The years 2016–2021 saw an increase in external development factors and the use of external resources. The study’s findings can serve as scientific benchmarks for TEE measurement, as well as the low-carbon and environmentally friendly growth of tourism in urban agglomerations. Full article

Investigating the microbial community structure and stress-tolerance mechanisms in the rhizospheres of salt-adapted plants along saline lakes is critical for understanding plant–microbe interactions in extreme environments and developing effective strategies for saline–alkaline soil remediation. This study explored the rhizosphere microbiomes of four salt-adapted species (Suaeda glauca, Artemisia carvifolia, Chloris virgata, and Limonium bicolor) from the Yuncheng Salt Lake region in China using high-throughput sequencing. Cultivable salt-tolerant plant growth-promoting rhizobacteria (PGPR) were isolated and characterized to identify functional genes related to stress resistance. Results revealed that plant identity and soil physicochemical properties jointly shaped the microbial community composition, with total organic carbon being a dominant driver explaining 17.6% of the variation. Cyanobacteria dominated low-salinity environments, while Firmicutes thrived in high-salinity niches. Isolated PGPR strains exhibited tolerance up to 15% salinity and harbored genes associated with heat (htpX), osmotic stress (otsA), oxidative stress (katE), and UV radiation (uvrA). Notably, Peribacillus and Isoptericola strains demonstrated broad functional versatility and robust halotolerance. Our findings highlight that TOC (total organic carbon) plays a pivotal role in microbial assembly under extreme salinity, surpassing host genetic influences. The identified PGPR strains, with their stress-resistance traits and functional gene repertoires, hold significant promise for biotechnological applications in saline–alkaline soil remediation and sustainable agriculture. Full article

Achieving decoupling between tourism economic growth and tourism carbon emissions is of paramount importance. This study innovatively integrates the geographically weighted regression (GWR) model—a tool for analyzing spatial heterogeneity—into the Tapio decoupling framework to examine the dynamic decoupling relationship between tourism growth and carbon emissions. It further investigates the driving factors behind decoupling evolution, their interactions, and precisely characterizes the mechanisms, directions, pathways, and intensities of these drivers. Key findings reveal an M-shaped fluctuation trend in tourism carbon emissions within the study area, with significant variations in emission shares across different tourism sectors and transportation modes. Spatially, carbon emissions exhibit heterogeneity and negative autocorrelation, where inter-regional disparities diminish while intra-regional disparities intensify. The tourism economic system in the Yangtze River Economic Belt (YREB) transitioned through weak decoupling, expansive negative decoupling, and strong decoupling states, eventually stabilizing at weak decoupling. Regional decoupling states varied markedly, suggesting that some areas require exploration of new low-carbon development paradigms. For sustainable tourism development, policy-makers should prioritize the decoupling relationship between tourism emissions and economic growth. Region-specific policies must be formulated to facilitate low-carbon transitions, promote industrial upgrading, and enhance inter-regional collaboration—ultimately advancing sustainable tourism under carbon neutrality goals. Full article

This study focuses on buildings in the Chinese–Baroque Historic Shopping District in Harbin. In view of global climate change and high carbon emissions from the construction industry, this study aims to quantify carbon emissions during the decoration process and explore low-carbon decoration strategies that suit the local characteristics. This research adopts a four-stage framework of “data collection–quantitative analysis–strategy design–verification and optimization” and integrates Life Cycle Assessment (LCA) and multi-objective optimization theory. Data are collected through questionnaires and field investigations, and simulations and analyses are carried out using Grasshopper and Honeybee. The results show that there are differences in carbon emissions between different decoration schemes. The chosen scheme of raw concrete and paint results in relatively low carbon emissions over the 10.12-year usage cycle. Based on this, design strategies such as extending the service life of decorations, rationally renovating windows, and preferentially selecting local low-carbon materials are proposed and applied to practical projects. This study not only fills a gap in the research on the low-carbon renovation of historical commercial blocks from the perspective of LCA but also provides practical solutions for the sustainable development of historical shopping blocks in Harbin and similar regions, promoting the low-carbon transformation of cities. Full article