Search Results (895)

Land cover, topography, precipitation, and socio-economic factors exert both direct and indirect influences on urban land surface temperatures. Within the broader context of global climate change, these influences are magnified by the escalating intensity of the urban heat island effect. However, the interplay and underlying mechanisms of natural and socio-economic determinants of land surface temperatures remain inadequately explored, particularly in the context of cold-region cities located in the northern temperate zone of China. This study focuses on Changchun City, employing multispectral remote sensing imagery to derive and spatially map the distribution of land surface temperatures and topographic attributes. Through comprehensive analysis, the research identifies the principal drivers of temperature variations and delineates their seasonal dynamics. The findings indicate that population density, night-time light intensity, land use, GDP (Gross Domestic Product), relief, and elevation exhibit positive correlations with land surface temperature, whereas slope demonstrates a negative correlation. Among natural factors, the correlations of slope, relief, and elevation with land surface temperature are comparatively weak, with determination coefficients (R²) consistently below 0.15. In contrast, socio-economic factors exert a more pronounced influence, ranked as follows: population density (R² = 0.4316) > GDP (R² = 0.2493) > night-time light intensity (R² = 0.1626). The overall hierarchy of the impact of individual factors on the temperature model, from strongest to weakest, is as follows: population, night-time light intensity, land use, GDP, slope, relief, and elevation. In examining Changchun and analogous cold-region cities within the northern temperate zone, the research underscores that socio-economic factors substantially outweigh natural determinants in shaping urban land surface temperatures. Notably, human activities catalyzed by population growth emerge as the most influential factor, profoundly reshaping the urban thermal landscape. These activities not only directly escalate anthropogenic heat emissions, but also alter land cover compositions, thereby undermining natural cooling mechanisms and exacerbating the urban heat island phenomenon. Full article

Measuring methane (CH₄) emissions from dairy systems is crucial for advancing sustainable agricultural practices aimed at mitigating climate change. However, current CH₄ measurement techniques are primarily designed for controlled research settings and are not readily scalable to diverse production environments. Thus, there is a need to develop accessible, production-level methods for estimating CH₄ emissions. This review examines the relationship between enteric CH₄ emissions and milk fatty acid (FA) composition, highlights key FA groups with potential as biomarkers for indirect CH₄ estimation, and outlines critical factors of predictive model development. Several milk FAs exhibit strong and consistent correlations to CH₄ emissions, supporting their utility as predictive biomarkers. Saturated and branched-chain FAs are generally positively associated with CH₄ emissions, while unsaturated FAs, including linolenic acid, conjugated linoleic acids, and odd-chain FAs, are typically negatively associated. Variability in the strength and direction of correlations across studies is often attributable to differences in diet or lactation stage. Similarly, differences in experimental design, data processing, and model development contribute to much of the variation observed in predictive equations across studies. Future research should aim to (1) identify milk FAs that consistently correlate with CH₄ emissions regardless of diet, (2) develop robust and standardized prediction models, and (3) prioritize the external validation of prediction models across herds and production systems. Full article

Cellulose nanocrystals (CNCs) have attracted growing interest in optics and electronics, extending beyond their traditional applications. They are considered key materials due to their fast computing, sensing adhesion, and emission of circularly polarized luminescence with high dissymmetry factors. This interest arises from their unique chemical structure, which gives rise to structural color, a chiral nematic phase, and high mechanical strength. In this perspective, we first introduce the definition, sources, and fundamental properties of CNCs to explain the basis for their unique and effective use in optics and electronics. Next, we review recent research on the application of CNCs in these fields. We then analyze the current limitations that hinder further advancement. Finally, we offer our own perspective on future directions for the CNC-enabled advanced optics and electronics. Full article

Marine biofouling significantly impacts the performance and longevity of polymer-based marine structures, particularly those designed for hydrodynamic applications such as Vortex-Induced Vibration suppression systems. Traditional antifouling solutions rely on copper-based multilayer coatings, which present challenges including mechanical vulnerability (e.g., chipping and scratching), high material and labor demands, and environmental concerns such as volatile organic compound emissions and copper leaching. Recent developments in material science have introduced an alternative system involving the direct incorporation of copper oxide (Cu₂O) into high-density polyethylene (HDPE) during the molding process. This study conducts a comparative life cycle assessment (LCA) of two antifouling integration methods—System 1 (traditional coating-based) and System 2 (Cu₂O-impregnated HDPE)—evaluating their environmental impact across production, application, use, and end-of-life stages. The functional unit used for this study was 1 square meter for a time period of five years. Using ISO 14040-compliant methodology and data from Ecoinvent and OpenLCA, three impact categories were assessed: global warming potential (GWP), cumulative energy demand (CED), and marine aquatic ecotoxicity Potential (MAETP). The results indicate that System 2 outperforms System 1 in GWP (4.42 vs. 5.65 kg CO₂-eq), CED (75.3 vs. 91.0 MJ-eq), and MAETP (327,002 vs. 469,929 kg 1,4-DCB-eq) per functional unit over a five-year lifespan, indicating a 21.8%, 17.3%, and 30.4% reduction in the key impact factors, respectively. These results suggest that direct Cu₂O incorporation offers a more environmentally sustainable and mechanically resilient antifouling strategy, supporting the potential of embedded antifouling systems to shift industry practices toward more sustainable marine infrastructure. Full article

The rice-wheat rotation is the main agricultural cropping system in Jiangsu Province, playing a vital role in ensuring food security and promoting economic development. However, current research on rice-wheat systems mainly focuses on in-situ controlled experiments at the point scale, with limited studies addressing carbon footprint (CF) and energy balance (EB) at the regional scale and long time series. Therefore, we analyzed the evolution patterns of the CF and EB of the rice-wheat system in Jiangsu Province from 1980 to 2022, as well as their influencing factors. The results showed that the sown area and total yield of rice and wheat exhibited an increasing–decreasing–increasing trend during 1980–2022, while the yield per unit area increased continuously. The CF of rice and wheat increased by 4172.27 kg CO₂ eq ha⁻¹ and 2729.18 kg CO₂ eq ha⁻¹, respectively, with the greenhouse gas emissions intensity (GHGI) showing a fluctuating upward trend. Furthermore, CH₄ emission, nitrogen (N) fertilizer, and irrigation were the main factors affecting the CF of rice, with proportions of 36%, 20.26%, and 17.34%, respectively. For wheat, N fertilizer, agricultural diesel, compound fertilizer, and total N₂O emission were the primary contributors, accounting for 42.39%, 22.54%, 13.65%, and 13.14%, respectively. Among energy balances, the net energy (NE) of rice exhibited an increasing and then fluctuating trend, while that of wheat remained relatively stable. The energy utilization efficiency (EUE), energy productivity (EPD), and energy profitability (EPF) of rice showed an increasing and then decreasing trend, while wheat decreased by 46.31%, 46.31%, and 60.62% during 43 years, respectively. Additionally, N fertilizer, agricultural diesel, and compound fertilizer accounted for 43.91–45.37%, 21.63–25.81%, and 12.46–20.37% of energy input for rice and wheat, respectively. Moreover, emission factors and energy coefficients may vary over time, which is an important consideration in the analysis of long-term time series. This study analyzes the ecological and environmental effects of the rice-wheat system in Jiangsu Province, which helps to promote the development of agriculture in a green, low-carbon, and high-efficiency direction. It also offers a theoretical basis for constructing a low-carbon sustainable agricultural production system. Full article

Developing accurate activity data on tree biomass using remote sensing tools such as LiDAR and drone-mounted sensors is essential for improving carbon accounting in the agricultural sector. However, direct biomass measurements of perennial fruit trees remain limited, especially for validating remote sensing estimates. This study evaluates the potential of terrestrial laser scanning (TLS) and drone-mounted RGB sensors (Drone_RGB) for estimating biomass in two major perennial crops in South Korea: apple (‘Fuji’/M.9) and citrus (‘Miyagawa-wase’). Trees of different ages were destructively sampled for biomass measurement, while volume, height, and crown area data were collected via TLS and Drone_RGB. Regression analyses were performed, and the model accuracy was assessed using R², RMSE, and bias. The TLS-derived volume showed strong predictive power for biomass (R² = 0.704 for apple, 0.865 for citrus), while the crown area obtained using both sensors showed poor fit (R² ≤ 0.7). Aboveground biomass was reasonably estimated (R² = 0.725–0.865), but belowground biomass showed very low predictability (R² < 0.02). Although limited in scale, this study provides empirical evidence to support the development of remote sensing-based biomass estimation methods and may contribute to improving national greenhouse gas inventories by refining emission/removal factors for perennial fruit crops. Full article

Our research explores the dynamic relationship between CO₂ emissions and four major influencing factors: foreign direct investment (FDI), economic growth (GDP), renewable energy consumption (REN) and population (POP) in the Association of Southeast Asian Nations (ASEAN) and three large Asian countries—China, India and Pakistan, collectively referred to as LACs (larger Asian countries), from 1990 to 2022. The study has three main objectives: (1) to assess the short-run and long-run effects of GDP, FDI, REN and POP on CO₂ emissions; (2) to compare the adjustment speeds and environmental policy responsiveness between ASEAN and LAC regions; and (3) to evaluate the role of renewable energy in mitigating environmental degradation. Against the backdrop of increasing environmental challenges and divergent development paths in Asia, this research contributes to the literature by applying a dynamic heterogeneous panel autoregressive distributed lag (panel ARDL) model. Unlike traditional static panel models, the panel ARDL model captures both long-run equilibrium relationships and short-run adjustments, allowing for country-specific dynamics. The results reveal a significant long-run cointegration among the variables. The error correction term (ECT) indicates a faster adjustment to equilibrium in LACs (−1.18) than ASEAN (−0.37), suggesting LACs respond more swiftly to long-run disequilibria in emissions-related dynamics. This may reflect more responsive policy mechanisms, stronger institutional capacities or more aggressive environmental interventions in LACs. In contrast, the slower adjustment in ASEAN highlights potential structural rigidities or delays in implementing effective policy responses, emphasizing the need for enhanced regulatory frameworks and targeted climate strategies to improve policy intervention efficiency. Results show that GDP and FDI increase emissions in both regions, while REN reduces them. POP is insignificant in ASEAN but increases emissions in LACs. These results provide insights into the relative effectiveness of policy instruments in accelerating the transition to a low-carbon economy, highlighting the need for differentiated strategies that align with each country’s institutional capacity, development stage and energy structure. Full article

The relationship between economic progress and environmental quality remains a central focus in global sustainability discourse. This study examines the link between per capita economic growth and CO₂ emissions across 128 countries from 1996 to 2022, controlling for energy consumption, trade volume, and foreign direct investment (FDI) inflows. It also evaluates the role of governance quality—measured by regulatory quality and its volatility—while considering the globalization index as a confounding factor influencing CO₂ emissions. We test the Environmental Kuznets Curve (EKC) hypothesis, which suggests that emissions initially rise with income but decline after reaching a certain economic threshold. Our findings confirm the global presence of the EKC. The analysis further shows that trade openness, governance, and globalization significantly influence FDI inflows, with FDI, in turn, reinforcing institutional quality through improved governance and globalization indicators. However, in countries with weaker governance and regulatory frameworks, FDI tends to promote pollution-intensive industrial growth, lending support to aspects of the Pollution Haven Hypothesis (PHH). We find a significant departure in EKC explained by post-COVID governance and globalization compromises, which induced the environment towards the PHH phenomenon. These results highlight the need for context-specific policy measures that align economic development with environmental constraints. Full article

Digitization and green low-carbon are the main directions of China’s economic development in the future. This paper aims to explore the relationship between improvements in the digital level of manufacturing industry segments and carbon emissions. It is found that the digitization level of China’s manufacturing industry segments is still at a low level, which needs to be further improved, and the digitization level of technology-intensive industries is higher than that of capital-intensive and labor-intensive industries. There is a serious misallocation of production factors and R&D factors among manufacturing industries, which is mainly caused by capital factors. Improvement in the digital level of manufacturing industry segmentation can significantly improve the double-layer factor allocation efficiency of the manufacturing industry, and can synchronously realize carbon emissions reduction through improvements in the double-layer factor allocation efficiency of the manufacturing industry; in other words, the improvement in the digital level of China’s manufacturing industry has the dual effects of improving factor allocation efficiency and carbon emissions reduction. Further analysis shows that this effect has significant heterogeneity of ownership. Therefore, China should focus on accelerating the digital transformation of the manufacturing industry, improve the allocation efficiency of traditional and R&D factors in the manufacturing industry through this digital transformation, and accelerate the realization of green and low-carbon development. Full article

Ambient PM concentrations are influenced by various emission sources and weather conditions such as temperature, wind speed, and direction. Measurements using optical sensors cannot directly link pollution levels to specific sources. Data from roadside monitoring often show that a significant portion of PM originates from non-traffic sources. Therefore, vehicle-related PM emissions are typically estimated using simulation models based on average emission factors. This study uses the COPERT (Computer Programme to Calculate Emissions from Road Transport) model to estimate emissions from road vehicles under current conditions and future scenarios. These include the introduction of Euro 7 standards and a shift from internal combustion engine (ICE) vehicles to battery electric vehicles (BEVs). The analysis considers exhaust and non-exhaust emissions, as well as indirect emissions from electricity generation for BEV charging. The conducted study showed, among other findings, that replacing internal combustion engine vehicles with electric ones could reduce PM2.5 emissions by approximately 6% (2% when including indirect emissions from electricity generation) and PM10 emissions by about 10% (5% with indirect emissions), compared to the Euro 7 scenario. Full article

Prefabricated buildings, known for their energy efficiency, environmental benefits, and industrial advantages, play a crucial role in urban renewal. Previous studies on the carbon emissions of prefabricated buildings mainly concentrate on the assessment and auditing of carbon emissions at the materialization and construction phase. Few of them have analyzed the carbon emissions at the operational phase or the influence mechanisms of prefabricated buildings on carbon emissions in urban renewal. Thus, this paper explored the factors and mechanisms that influence carbon emissions in prefabricated buildings in China’s urban renewal. Firstly, the factors that influence the carbon emissions of prefabricated buildings in China’s urban renewal were identified through meta-analysis. Secondly, the theoretical model was developed to illustrate the influence paths of prefabricated buildings on the carbon emissions of urban renewal. Finally, the structural equation model (SEM) was used to test the hypotheses in the theoretical model using data collected from questionnaires. The results show that the carbon emission reduction potential of prefabricated buildings is influenced by four aspects, namely, socioeconomic factors, policy regulations, building operation, and materialization. Policy regulations have the greatest impact on the carbon emissions of prefabricated buildings. They not only directly affect the carbon emissions of urban renewal but also influence carbon emissions indirectly through the social economy aspect. The direct impact of social economy on the carbon emissions of prefabricated buildings is insignificant, while it can indirectly affect the carbon emission reduction in prefabricated buildings by influencing building operations and the materialization stage. The findings could help provide strategies for prefabrication and enhance the reduction potential of urban renewal. Full article

Livestock farming is a vital component of global food security, yet it remains a major contributor to greenhouse gas (GHG) emissions, particularly methane (CH₄), which has a global warming potential 28 times greater than carbon dioxide (CO₂). This review provides a comprehensive synthesis of current knowledge surrounding the sources, biological mechanisms, and mitigation strategies related to CH₄ emissions from ruminant livestock. We first explore the process of methanogenesis within the rumen, detailing the role of methanogenic archaea and the environmental factors influencing CH₄ production. A thorough assessment of both direct and indirect methods used to quantify CH₄ emissions is presented, including in vitro techniques (e.g., syringe method, batch culture, RUSITEC), in vivo techniques (e.g., respiration chambers, Greenfeed, laser CH₄ detectors), and statistical modeling approaches. The advantages and limitations of each method are critically analyzed in terms of accuracy, cost, feasibility, and applicability to different farming systems. We then examine a wide range of mitigation strategies, organized into four core pillars: (1) animal and feed management (e.g., genetic selection, pasture quality improvement), (2) diet formulation (e.g., feed additives such as oils, tannins, saponins, and seaweed), (3) rumen manipulation (e.g., probiotics, ionophores, defaunation, vaccination), and (4) manure management practices and policy-level interventions. These strategies are evaluated not only for their environmental impact but also for their economic and practical viability in diverse livestock systems. By integrating technological innovations with sustainable agricultural practices, this review highlights pathways to reduce CH₄ emissions while maintaining animal productivity. It aims to support decision-makers, researchers, and livestock producers in the global effort to transition toward climate-smart, low-emission livestock farming. Full article

Driven by the environmental benefits associated with reduced greenhouse gas emissions, oil companies have intensified research efforts into reassessing the strategies used to meet the electrical demands of offshore production platforms. Among the various alternatives available, the deployment of onshore–offshore interconnections via High-Voltage Direct Current (HVDC) transmission systems has emerged as a promising solution, offering both economic and operational advantages. In addition to reliably meeting the electrical demand of offshore facilities, this approach enables enhanced operational flexibility due to the advanced control and regulation capabilities inherent to HVDC converter stations. Based on the use of interconnection through an HVDC link, aiming to evaluate the operation of the electrical system as a whole, this study focuses on evaluating dynamic events using the PSCAD software version 5.0.2 to analyze the direct online starting of a large induction motor and the sudden loss of a local synchronous generating unit. The simulation results are then analyzed to assess the effectiveness of both Grid-Following (GFL) and Grid-Forming (GFM) control strategies for the converters, while the synchronous generators are evaluated under both voltage regulation and constant power factor control operation, with a particular focus on system stability and restoration of normal operating conditions in the sequence of events. Full article

As a major contributor to energy consumption and carbon emissions, the low-carbon transformation of the construction industry is crucial for China to achieve its established carbon-emission reduction targets. Therefore, a systematic analysis of the spatial and temporal evolution trends and key drivers of carbon emissions in the construction industry is an important reference for the formulation of emission reduction policies in the industry and the promotion of green and low-carbon development. This study first estimated carbon emissions from direct and indirect energy consumption in China’s construction industry. Spatial and temporal variations in emissions were then analyzed using spatial autocorrelation and kernel density methods. Furthermore, an improved logarithmic mean Divisia index decomposition model, tailored to the characteristics of the construction industry, was applied to quantify the key driving factors. The results reveal that total carbon emissions follow an inverted U-shaped trend, with indirect carbon emissions—mainly from the production of cement and steel—being the dominant contributors. Emissions display a spatially uneven pattern: high in the east and south, low in the west and north, with the high-emission zone gradually expanding from the east to the central regions. Marked regional differences also exist in the evolution of emission intensity. Output intensity and energy intensity are identified as primary drivers of emissions, with their impact particularly prominent in the eastern region. These findings provide a quantitative basis and theoretical support for developing region-specific emission reduction policies, advancing the green and high-quality development of China’s construction industry. Full article

This article aims to assess the conditions and prospects for biomass utilization in the Visegrad Group (V4) countries. Additionally, the relationship between biomass energy production and greenhouse gas emissions was examined. A key component of the analysis involved identifying potential directions for the development of biomass utilization in the pursuit of the sustainable development of agricultural enterprises. In relation to these research objectives, a hypothesis was formulated regarding the causal relationship between biomass energy consumption and economic growth, the abundance of natural resources, and income in reference to the European Union economies. Both static and dynamic panel studies were applied. The conducted research revealed the complex nature of the conditions influencing biomass utilization. The study period covered the years 2004–2022. A negative correlation was found between the use of biomass and greenhouse gas emissions. At the same time, factors favoring biomass utilization included economic growth, the level of natural resource consumption per capita, and government policies aimed at increasing the share of renewable resources in the economy. Full article