Search Results (147)

Background: Mindray BC-6800 Plus ^TM (Mindray, Shenzhen, China) measures reticulocyte counts and provides the reticulocyte hemoglobin (RHe, reticulocyte Hb expression) and mean reticulocyte volume (MRV). We studied the performance of those reticulocyte-derived parameters for the detection of iron-restricted erythropoiesis in older patients, compared with standard laboratory tests. Methods: A total of 220 anemic patients, age > 65 years, were recruited in the context of routine health controls. Group differences were assessed using analysis of variance (ANOVA), with p values < 0.05 considered statistically significant. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic performance of RHe and MRV for detecting iron-restricted erythropoiesis. The reference standard for iron deficiency was sTfR > 52 nmol/L. A multivariable logistic regression model was constructed for iron-restricted erythropoiesis, including MRV, Ret-He and s-ferritin as independent covariates, and adjusted for inflammatory status and renal function. Results: Overall, 30.1% in the group had IDA and 29.0% had mixed IDA/ACD, so 59.1% had absolute or functional iron deficiency, while 40.9% had adequate iron supply. RHe and MRV values differed significantly between both groups (p = 0.0001). For s-ferritin, ROC analysis yielded an AUC of 0.685 (95% CI 0.606–0.767), with the best Youden index at a cut-off of 100 µg/L, corresponding to 72.5% sensitivity and 65.9% specificity. An MRV cut-off of 97.4 fL identified iron-restricted erythropoiesis with 88.2% sensitivity and 82.7% specificity (AUC 0.878, 95% CI 0.799–0.957); RHe AUC 0.860, 95% CI 0.777–0.947; cut-off 30.4 pg; sensitivity 82.4%, specificity 79.8%). In multivariable logistic regression adjusted for CRP and eGFR, s-ferritin was not an independent predictor of iron-restricted erythropoiesis, whereas MRV and RHe remained significant. The overall model demonstrated good discrimination, with an AUC 0.808 (95% CI 0.804–0.814). Conclusions: RHe and MRV are reliable parameters for assessing iron supply to erythropoiesis in older patients and can assist in distinguishing iron-restricted erythropoiesis in complex, inflammation-driven settings. Full article

This study presents a large-scale empirical comparison of operational efficiency metrics derived from the IMO Data Collection System (DCS) and the EU Monitoring, Reporting and Verification (MRV) framework. Paired non-parametric tests, effect size estimation, and agreement diagnostics were applied to a matched dataset of 15,755 dual-reported vessels and over 50,000 ship-year observations from 2019 to 2024 to assess consistency across monitoring systems. The results indicate that, although statistically significant differences are detected (p < 0.001), practical differences are negligible (Cohen’s d < 0.025), with MRV-based values averaging approximately 1.4% lower in Annual Efficiency Ratio (AER) and fuel intensity than DCS values. Distributional analysis confirms substantial overlap between the datasets, and temporal trends show progressive convergence following the implementation of the Carbon Intensity Indicator (CII) regulation. However, pronounced vessel-type heterogeneity is observed. Flexible cargo vessels exhibit consistent efficiency improvements in EU-related voyages, whereas container ships show minimal variation, and LNG carriers demonstrate indicator-dependent patterns. Overall, the findings indicate that the DCS and MRV frameworks provide broadly comparable representations of operational efficiency, with observed differences primarily reflecting vessel-type-specific operational characteristics rather than structural inconsistencies in the reporting systems. This study provides a scalable statistical validation framework for cross-regulatory monitoring assessment. Full article

The current research undertook a comprehensive examination of global research related to the use of measurement, reporting, and verification (MRV) techniques for quantifying and tracking greenhouse gas (GHG) emissions from agriculture and livestock farming. Data were collected using a bibliometric analysis of 5340 studies published in the period (1990–2025) and a systematic literature review of 100 studies published in the period (2020–2025). The insights from the findings showed that four MRV techniques were broadly adopted across different regions: (1) inventory techniques (IPCC Tiers, national systems), (2) accounting at the project/product level (LCA, carbon footprint protocols), (3) MRV based on measurement and models (chambers, remote sensing, farm models, AI/ML), and (4) frameworks for governance and standardization (UNFCCC, Paris ETF, PAS 2050, etc.). The findings further revealed the impact of the MRV techniques on agriculture and livestock farming, showing that they facilitated the uptake of low-carbon practices. In agriculture, the MRV techniques showed that lower emissions emerged from mixed cropping, while in livestock farming, the emissions varied based on the feeding stage and type of diet used. However, various challenges arose in the adoption of MRV techniques where there was limited data related to GHG emissions, thereby reducing generalizability. In future work, there is a need for scholars to consider integrating the different MRV techniques to develop an understanding of the problem area. Full article

Natural disasters disrupt maritime operations, yet their environmental consequences remain underexplored. This study quantifies CO₂ emission changes following the February 2023 İskenderun Bay earthquakes (7.6 Mwg and 7.5 Mwg) using AIS-derived port visit data and graph neural network modeling. Analyzing 25,837 port visits across a 36-month period (January 2022–December 2024), we compared emissions during baseline (pre-earthquake), acute disruption (February–June 2023), and recovery phases. Results revealed a statistically significant 35.9% increase in per-visit CO₂ emissions during the acute phase (t = 11.79, p < 0.001, Cohen’s d = 0.27), driven by extended port visit durations (from 77.87 to 105.82 h). Counterfactual analysis estimated 27,574 tonnes of excess CO₂ emissions directly attributable to earthquake disruption. Network analysis showed 23.8% reduction in edge density during the acute phase. The graph neural network (GNN) emission prediction model achieved R² = 0.985 (baseline) and R² = 0.997 (recovery) in predicting emission patterns, while acute phase showed predictability collapse (R² = −1.591). These findings demonstrate that seismic events generate sustainability-relevant externalities beyond immediate physical damage, and that quantifying disruption-driven excess emissions supports sustainability-oriented port resilience planning and more robust maritime emission accounting (e.g., under the EU MRV framework). Full article

Mammalian orthoreoviruses (MRVs) infect a wide range of animal hosts, yet epidemiological data from southern China remain limited. Here, we performed regional screening of diarrheic cattle in Guangxi, China, from 2023 to 2025. Using L1-targeted RT-PCR, MRV was detected in 8.4% (15/178) of fecal specimens collected across eight prefectures, with a higher detection rate during the cool (autumn–winter) season (October–March). We obtained two complete S1 segments, assigning one Guangxi strain to MRV1 and the other to MRV3. Phylogenetic analysis of L1 sequences indicated a single local lineage nested within a broader multi-host cluster, which was consistent with segment reassortment. σ1 protein alignment revealed a conserved central/C-terminal scaffold and a variable distal head; notably, the MRV3 σ1 sequence contained an extended ~360–390 aa region compared with MRV1. Overall, these findings provide an epidemiological baseline for Guangxi cattle, integrating detection rate, serotype context, and seasonality to support targeted, seasonally informed surveillance and MRV risk assessment. Full article

Mangrove ecosystems are recognized as highly efficient blue-carbon reservoirs, yet their monitoring requires scalable, transparent methods suitable for climate-finance and greenhouse-gas accounting applications. This study quantifies interannual carbon-stock dynamics and derives a carbon-market valuation indicator for Ecuador’s Churute Mangrove Ecological Reserve (2015–2021) using publicly available remote-sensing land-cover products. Annual activity data were derived from Copernicus Global Land Service LC100 (100 m, 2015–2019) and ESA WorldCover (10 m, 2020–2021), harmonized to a common reporting scheme, and combined with IPCC Tier 1 default coefficients for biomass and soil organic carbon in tropical wetlands. Total carbon stocks averaged 1.67 million t C across the period, remaining stable within the internally consistent LC100 phase (2015–2019), with trend statistics treated as descriptive given the short annual series, while a pronounced drop in 2020 primarily reflected methodological discontinuities between products rather than ecological change. Converted to CO₂e equivalents (mean 6.1 million t CO₂e), illustrative market values fluctuated between USD 18 and 123 million annually, driven predominantly by carbon-price variability. This remote-sensing-based, MRV-aligned approach provides a conservative baseline for protected-area blue-carbon accounting, highlighting the need for homogeneous high-resolution time series to distinguish real dynamics from classification artifacts in future assessments. Full article

Natural disasters disrupt maritime operations; yet, their environmental consequences remain underexplored. This study quantifies CO₂ emission changes following the February 2023 İskenderun Bay earthquakes (7.6 Mwg and 7.5 Mwg) using AIS-derived port visit data and graph neural network modeling. Analyzing 25,837 port visits across a 36-month period (January 2022–December 2024), we compared emissions during baseline (pre-earthquake), acute disruption (February–June 2023), and recovery phases. Results revealed a statistically significant 35.9% increase in per-visit CO₂ emissions during the acute phase (t = 11.79, p < 0.001, Cohen’s d = 0.27), driven by extended port visit durations (from 77.87 to 105.82 h). Counterfactual analysis estimated 27,574 tonnes of excess CO₂ emissions directly attributable to earthquake disruption. Network analysis showed a 23.8% reduction in edge density during the acute phase. The graph neural network (GNN) emission prediction model achieved R² = 0.985 (baseline) and R² = 0.997 (recovery) in predicting emission patterns, while the acute phase showed predictability collapse (R² = −1.591). These findings demonstrate that seismic events generate sustainability-relevant externalities beyond immediate physical damage, and that quantifying disruption-driven excess emissions supports sustainability-oriented port resilience planning and more robust maritime emission accounting (e.g., under the EU MRV framework). Full article

Measurement, Reporting and Verification (MRV) concepts have emerged as a means for reviewing and ensuring the effectiveness of energy efficiency measures (EEMs) in smart buildings. Nevertheless, high technological and regulatory demands imposed by the Energy Efficiency Directive, Article 8 (EED 8), result in limited adaptation, which makes the transition of the MRV concept into a practically applied framework a challenging endeavor. A significant concern lies in ensuring data integrity, accuracy and transparency throughout the entire adaptation and implementation process of the MRV concept. This study addresses these challenges by developing and evaluating a structured MRV framework tailored to smart building environments. The MRV framework design was tested in a real-world use case in Berlin, demonstrating its applicability for measuring, reporting and verifying energy efficiency data from smart buildings. The results confirmed the applicability of the approach, while also revealing persistent barriers related to data sovereignty, security and interoperability. Ensuring trust, transparency and long-term data accessibility requires robust governance structures and alignment with legal and ethical standards. Future work will focus on scaling the MRV framework to additional sectors and refining mechanisms for secure data sharing and automated verification. Full article

In the context of China’s “dual-carbon” strategy, the Beijing 2022 Winter Olympics provides a critical case for examining whether carbon-neutral commitments can be translated into measurable and lasting environmental outcomes through a closed-loop governance mechanism. This study develops an integrated analytical framework linking institutional design, policy tools, monitoring–reporting–verification (MRV), and environmental legacy, and evaluates full life-cycle carbon-neutral governance and post-event environmental performance using officially verified carbon accounting materials, governmental disclosures, and publicly available statistical data from 2016–2022. We synthesize the emission structure across preparation and Games-time phases, examine key mitigation and offset portfolios, and assess multi-dimensional environmental indicators in Beijing and Zhangjiakou, including atmospheric quality, energy structure transition, ecological restoration, and low-carbon transport systems. The results suggest that an MRV-centered governance chain strengthened accounting transparency and compliance-oriented implementation, while environmental indicators in the competition zones exhibited sustained improvement over the study period. To reduce over-attribution under concurrent national clean-air policies and macro-level environmental governance trends, we benchmarked host-zone indicators against external reference statistics and interpret the observed improvements as an “acceleration effect” under bounded inference rather than a strict net causal contribution. The findings highlight the importance of hotspot-oriented asset-chain governance (transport infrastructure and venue construction), robust MRV disclosure, and quality-controlled offsets in shaping credible environmental legacies, and provide policy implications for future mega-events seeking to balance carbon neutrality with long-term regional sustainability. Full article

Regenerative agriculture (RA) offers a critical pathway for climate change mitigation and adaptation, yet its implementation is often hindered by conceptual ambiguity and a lack of standardized assessment frameworks. This study employs a comparative systemic analysis, integrated with a Failure Mode and Effects Analysis (FMEA) framework, to evaluate the resilience of medium-sized RA farms (50–200 ha)—a segment representing the professional backbone of European agriculture—under varying infrastructural and policy conditions. By synthesizing recent standardized metrics from the global literature, the research constructs three operational contexts: Context A (Integrated High-Performance), characterized by robust support and digital monitoring; Context B (Transitional/Fragmented), reflecting partial adoption with limited resources; and Context C (Maladaptive), representing systemic barriers. The results reveal a significant “Resilience Gap” between theoretical potential and practical reality. Specifically, the analysis identifies that ecological practices alone (e.g., cover cropping, no-till) are insufficient to guarantee economic resilience without the support of Monitoring, Reporting, and Verification (MRV) systems. In transitional contexts, the inability to verify ecosystem services prevents farmers from accessing financial buffers, rendering the system vulnerable to climate shocks. This study concludes that enhancing RA resilience requires a paradigmatic shift from practice-based subsidies to outcome-based incentives, underpinned by accessible MRV technologies and standardized socio-economic indicators. Full article

In the context of the growing urgency of sustainable industrial transformation under global climate goals, this study examines how digitalization enables and amplifies industrial low-carbon transition through the synergistic interaction of policy tools, technological pathways, and financial innovation. Addressing the challenge of reconciling emissions reduction with industrial efficiency, the study employs a mixed-method approach that combines panel econometric analysis of manufacturing enterprises in China’s Yangtze River Delta with representative case studies. The empirical results demonstrate significant synergistic effects among policy, technology, and finance under digital enablement. Coordinated policy instruments, including emissions trading and green credit, reduce decarbonization costs by 18–23%, while digitally enabled mechanisms such as Zhejiang’s “Carbon Efficiency Code” lower carbon intensity by over 15% for nearly half of participating firms. Technological pathways exhibit sectoral heterogeneity: digital twin optimization reduces emissions by 12% in the steel industry, whereas IoT-based monitoring cuts energy consumption by 9.7% in textiles. Financial innovations further reinforce these outcomes by increasing green R&D intensity and enhancing firms’ climate risk resilience. From a sustainability perspective, the study shows that digitalization strengthens real-time carbon measurement, monitoring, and verification (MRV), thereby improving sustainability performance assessment and governance effectiveness. By integrating digital tools with policy and financial incentives, the findings provide actionable guidance for supporting sustainable industrial operations and designing more precise, scalable, and data-driven sustainability-oriented policy instruments. Full article

Soil amendments are widely applied to improve soil fertility and structure, yet their performance in cold regions is constrained by low accumulated temperatures, frequent freeze–thaw (FT) cycles, and permafrost sensitivity. In this review, ‘cold regions’ refers to high-latitude and high-altitude areas characterized by long winters and seasonally frozen soils and/or permafrost. We screened the peer-reviewed literature using keyword-based searches supplemented by backward/forward citation tracking; studies were included when they assessed amendment treatments in cold region soils and reported measurable changes in physical, chemical, biological, or environmental indicators. Across organic, inorganic, biological, synthetic, and composite amendments, the most consistent benefits are improved aggregation and nutrient retention, stronger pH buffering, and the reduced mobility of potentially toxic elements. However, effectiveness is often site-specific and may be short-lived, and unintended risks—including greenhouse gas emissions, contaminant accumulation, and thermal disturbances—can offset gains. Cold-specific constraints are dominated by limited thermal regimes, FT disturbance, and the trade-off between surface warming for production and permafrost protection. We therefore propose integrated countermeasures: prescription-based amendment portfolios tailored to soils and seasons; the prioritization and screening of local resources; coupling with engineering and land surface strategies; a minimal cold region MRV loop; and the explicit balancing of agronomic benefits with environmental safeguards. These insights provide actionable pathways for sustainable agriculture and ecological restoration in cold regions under climate change. Full article

Large-scale cultural events generate substantial greenhouse gas emissions, raising increasing concerns regarding carbon neutrality. In Taiwan, long-standing forest conservation policies have largely restricted commercial logging since the early 1990s, resulting in extensive secondary forests where active management options are limited. Within this policy context, improved forest management (IFM) provides a potential pathway to enhance carbon sequestration while maintaining conservation objectives. This study evaluates the feasibility of using afforestation combined with IFM to offset the carbon emissions of the Taipei Biennial 2020, estimated at approximately 390 t CO₂-e. Carbon sequestration was assessed using the Verified Carbon Standard (VCS) methodology (VM0005 v1.2) under the principles of Measurement, Reporting, and Verification (MRV). A total area of 52.70 ha was assessed, with 10.11 ha designated as the project activity area. Over a 25-year period, projected CO₂ sequestration across four baseline scenarios ranged from 3816 to 4523 tons, indicating that event-related emissions could be offset within 8–9 years. Uncertainty remains due to hypothetical management assumptions, highlighting the need for continuous monitoring and adaptive management. Full article

Carbon farming represents a strategic approach to enhancing agricultural sustainability while reducing greenhouse gas (GHG) emissions. In Türkiye, agriculture accounted for approximately 14.9% of national GHG emissions in 2023, dominated by methane (CH₄) and nitrous oxide (N₂O). By increasing carbon storage in soils and vegetation, carbon farming can improve soil health, water retention, and climate resilience, thereby contributing to mitigation efforts and sustainable rural development. This study reviews and synthesizes international and national evidence on carbon farming mechanisms, practices, payment models, and adoption enablers and barriers, situating these insights within Türkiye’s agroecological and institutional context. The analysis draws on a systematic review of peer-reviewed literature, institutional reports, and policy documents published between 2015 and 2025. The findings indicate substantial mitigation potential from soil-based practices and livestock- and manure-related measures, yet limited uptake due to low awareness, capacity constraints, financial and administrative barriers, and regulatory gaps, highlighting the need for region-specific approaches. To support implementation and scaling, the study proposes a policy-oriented, regionally differentiated and digitally enabled MRV framework and an associated implementation pathway designed to reduce transaction costs, enhance farmer participation, and enable integration with emerging carbon market mechanisms. Full article

Achieving sustainable development in the low-carbon transition requires securing critical raw materials (CRMs) while reducing environmental burdens and strengthening industrial resilience (SDGs 7, 9, 12, 13). This review synthesizes 2016–2025 evidence on how the European Union’s policy package—the Critical Raw Materials Act (CRMA), the Batteries Regulation, the Ecodesign for Sustainable Products Regulation (ESPR) with Digital Product Passports (DPPs), and the recast Waste Shipments Regulation (WSR)—shapes markets for secondary supply in battery-relevant metals such as lithium, cobalt, nickel, copper, aluminum, and rare earths. We apply a structured scoping review protocol to map the state of the art across policy instruments (EPR, ecodesign/DPP, recycled content mandates, recovery targets, shipment controls) and value chain stages (collection, preprocessing, refining, manufacturing). The analysis highlights benefits, including clearer investment signals, improved traceability, and emerging opportunities for industrial symbiosis, but also identifies drawbacks such as heterogeneous standards, compliance costs, and trade frictions. Evidence gaps remain, especially in causal ex post assessments, price pass-through, and interoperability of MRV/DPP systems. The paper contributes by (i) providing an integrative framework linking policy instruments, value chain stages, and investment signals for secondary CRM supply, and (ii) outlining a research agenda for rigorous ex post evaluation, improved MRV/DPP data architectures, and better alignment between EU trade rules, circularity, and a just energy transition. Full article