Climate change is reshaping risk worldwide, with many extreme events becoming more frequent and severe. Insurance plays a critical role in societal resilience by providing financial protection against climate-related losses. Climate indices translate climate information into actionable metrics that can support risk assessment, risk management, and resilience. Yet their diversity and broad scope make their application challenging. This paper reviews climate-related indices by grouping them into six categories and summarising their purpose and potential insurance applications. The review highlights how different types of indices can support actuarial functions across the insurance sector and emphasises the need for purpose-built indices that incorporate socio-economic characteristics alongside climate information to improve risk assessment and help address the climate protection gap.
The goal of this study was to replace the costly fishmeal (FM) with Tenebrio molitor larvae meal (TMLM) in diets for Nile tilapia (Oreochromis niloticus) juveniles. Six isonitrogenous diets were created in order to examine the viability of substituting FM protein with stepwise inclusion levels of TMLM protein, i.e., 0%, 15%, 30%, 45%, 60%, and 75% represented by TMLM0, TMLM15, TMLM30, TMLM45, TMLM60, and TMLM75, respectively. For 90 days, Nile tilapia juvenile (8.8-10.5 g) were fed on TMLM diets three times a day until apparent satiation. Nile tilapia fed on TMLM levels were found to significantly (p < 0.05) boosted their growth and feed efficiency indices by up to 45%, after which their performance declined. In comparison to other treatments, larger villi length/width and increased digestive enzymes activity were observed at this level (TMLM45). At TMLM45, there were no signs of inflammation in the liver tissues but feeding the fish on TMLM60 and TMLM75 showed more vacuolated hepatocytes and fewer hepatic sinusoids. Total protein, albumin, and globulin contents showed significant (p < 0.05) increases in response to TMLM levels in fish feeds; meanwhile no significant (p > 0.05) changes in blood glucose were observed compared to the control one (TMLM0). The values of alanine and aspartate aminotransferase, total cholesterol, and triglycerides decreased significantly (p < 0.05) as TMLM levels increased in fish feeds. In addition, significant (p < 0.05) increases in antioxidant and immunological variables were observed in fish fed with TMLM diets, in particular TMLM45. The current study concluded that the substitution of FM protein by 45% TMLM protein in diets administered to Nile tilapia juveniles significantly improved (p < 0.05) their growth, antioxidant, and immune response compared to the control diet (FM-based diet).
Urban drought pressure is increasing the operational risk and cost of maintaining municipal green infrastructure. Irrigation is still widely managed through fixed routines and fragmented information. To address this challenge, the study develops an integrated operational analysis by combining water consumption records, maintenance data and a GIS inventory for twenty municipal green spaces. System characterisation and performance screening were carried out using hourly meter readings to distinguish typical scheduled irrigation peaks from non-standard consumption patterns. To move from monitoring to control, irrigation needs were estimated using evapotranspiration (ET0) and a garden-coefficient logic adapted to urban planting conditions and compared with measured consumption. The comparison indicates a potential reduction of 29-61% through improved scheduling and system adjustment. Based on the diagnosis, technical intervention scenarios were defined and assessed using techno-economic metrics, including ground-cover redesign and Mediterranean-adapted planting strategies. To support implementation, options were organised into intervention priorities using a multicriteria tool that balances water savings, costs and feasibility under municipal operations. Coimbra, Portugal is used as a case study, and a pilot application in a city garden, supported by 797 user surveys, clarifies practical constraints for scaling beyond isolated pilots. Turf-free scenarios indicate a 53.4% reduction in water use and a 60.5% reduction in operational costs, with a payback period below three years. The results highlight the potential of data-driven irrigation management to support more resilient, cost-effective and water-efficient municipal green infrastructure across diverse urban contexts.
The Loskop Dam is a major reservoir on the upper Olifants River in South Africa. Many human activities in the upper river catchment are causing contamination in the river including heavy metals. Although several studies have investigated water pollution in the river system, limited information exists regarding the spatial distribution and ecological risks of heavy metals in the Loskop Dam and their ecological implications. Seasonal heavy metal concentrations and ecological risks associated with heavy metal contamination in the dam were assessed. Though most of the heavy metal concentrations were below detection levels in the water, the concentrations were substantially higher in the sediments, with higher concentrations mainly recorded during winter than summer. Chromium and nickel concentrations in the sediments exceeded the permissible guideline values. Furthermore, contamination factor, enrichment factor and geoaccumulation index were used to determine the extent of chemical pollution, and ecological risk index was used to assess the potential ecological risks. The contamination indices found the sediments to be moderately to highly contaminated by Cr, Pb and Zn. However, the ecological risk values were low, indicating a low ecological risk of contamination posed by heavy metals in the dam. During winter, Cd had the highest ecological risk and during summer, the ecological risk was dominated by Pb, but the values indicated a low contamination (ER <40) and the potential ecological risk index values were also low (RI < 150). Nonetheless, effective conservation strategies are needed to prevent further degradation of the river system. Furthermore, the study reinforces the importance of addressing metal pollution and conservation of freshwater ecosystems, which aligns with the United Nations Sustainable Development Goal (SDG) 6, particularly in enhancing water accessibility and responsible sanitation management.
The Wei River Basin (WRB) faces challenges including flood threats, ecological fragility, and uneven socio-economic development. However, existing ecosystem service supply-demand (ESSD) studies rarely incorporate flood-sediment transport as a core service, and systematic studies on revealing the multi-scale spatial heterogeneity and driving mechanism of ESSD coupling coordination remain insufficient. Therefore, this paper analyzed the ESSD across flood-sediment transport, eco-environmental, and socio-economic subsystems for the period 2005-2023 at three spatial scales (municipal, watershed, and county). A multi-scale comprehensive index of ESSD was constructed. Using the dynamic local and tele-coupling coordination degree (DLTCCD) model and spatial Markov model, we quantitatively assessed dynamic trade-offs and transition patterns of the DLTCCD in ESSD. The XGBoost-SHAP model and structural equation model were employed to explore the internal mechanisms through which key factors influence the DLTCCD. A zoning management mechanism was proposed by integrating the four-quadrant static model and DLTCCD change rate. The results showed the following: (1) ESSD exhibited a spatial pattern of "lower in the north and higher in the south," with imbalances more evident at the county scale. (2) The DLTCCD showed significant scale dependence, with "spatial club convergence" of high and low levels in the Ziwuling Mountain and Longdong Plain areas. (3) Based on both the XGBoost-SHAP model and the structural equation model, precipitation was identified as the fundamental driving force across scales, exerting influence through interactive effects and a dual mediating path. (4) Zoning identification revealed structural challenges for sustainable development, marked by coexistence of coordinated and uncoordinated development zones. This study identifies the northern Loess Plateau, Qinling northern foothills, and Guanzhong Plain as key zones, proposes a "zoning-based graded intervention" strategy, and provides scientific support for ESSD management in the WRB.
This study evaluates the scalability and sustainability impacts of integrating Napier grass cultivation with biofertilizer production and dairy systems in rural West Bengal. Field-level evidence indicates that biofertilizer application and irrigation optimization significantly enhance soil organic carbon (SOC), improving nutrient availability and enabling Napier yields of up to 500 tons/acre on fallow land. A technoeconomic model shows strong economies of scale, with production costs decreasing by 40% when area under cultivation is simulated from 1 acre to 100 acres. Statewide scaling scenarios demonstrate significant development potential. Under 10% adoption of fallow land by 2040, approximately 75 million tons of biomass can be grown annually, benefiting 3.75 million households, doubling under a 20% adoption scenario by 2050. The system enables a 2.5-4x increase in household income while delivering substantial climate co-benefits. Avoided emissions from manure management are estimated at similar to 40 Mt CO2 annually by 2040, increasing to similar to 80 Mt CO2 by 2050, alongside additional gains from soil carbon sequestration and reduced high-emission urea-use. Overall, the proposed circular model offers a scalable pathway for achieving multiple Sustainable Development Goals through integrated agricultural transformation.
Healthcare sustainability has become increasingly important due to the sector’s environmental footprint and the growing emphasis on environmental, social, and governance (ESG) criteria. This study examines ESG awareness, sustainability reporting readiness, and the association between sustainability-oriented leadership climate and employee green behavior in Greek healthcare organizations. A cross-sectional survey was conducted among 379 healthcare professionals employed in public hospitals and private clinics in Greece. Data were analyzed using descriptive statistics, exploratory factor analysis, correlation analysis, non-parametric group comparisons, and hierarchical regression. The findings indicate limited ESG awareness and weak institutionalization of sustainability reporting across the sampled organizations. The analysis also identified two distinct and reliable constructs, leadership climate for sustainability and employee green behavior. These constructs were positively associated, and leadership climate for sustainability remained a significant predictor of employee green behavior after controlling demographic and occupational characteristics, although the overall explained variance remained modest. The study contributes empirical evidence from the Greek healthcare sector by linking ESG awareness and sustainability reporting readiness with perceived leadership climate and employee green behavior, while identifying leadership climate for sustainability as one relevant organizational condition associated with employee-level green behavior.
In vitro methods rely on costly chemical inputs, such as synthetic nutrients, prompting us to search for sustainable alternatives. This study evaluated wastewater generated from the cigarette butt (CB) recycling process as a potential growth stimulant additive for in vitro plant cultivation. Seeds of Brachiaria ruziziensis Germain & Evrard were sown on agar media containing increasing CB wastewater concentrations from 0 to 25% v/v (CB0 to CB25, respectively) under controlled conditions. Germination was monitored over 10 days, and functional and physiological traits of shoot and root systems were assessed at the end. Responses were concentration-dependent and consistent with hormesis. Low concentrations, particularly CB2, enhanced germination (92.2% vs. similar to 67% in CB0), shoot elongation (similar to 6 vs. 3.4 cm), and total biomass (similar to 47 vs. similar to 33 mg fresh weight), while maintaining total chlorophyll and increasing carotenoids (147.8 vs. 103.3 mu g g(-1) FW) and chlorophyll a/b ratio (2.1 vs. 1.5). Contrarily, higher concentrations (>= CB10) reduced germination (47.6% at CB25), strongly inhibited root growth (0.5 cm at CB25), decreased total biomass (similar to 19 mg at CB25), led to growth disorders, and reduced pigment stability. These inhibitory effects were associated with the accumulation of CB-derived compounds, including high nicotine levels and unbalanced nutrients. At low concentrations, coordinated root aerenchyma formation and modulation of stomatal density indicated anatomical plasticity under mild stress conditions, although their physiological significance remains to be clarified. Overall, CB recycling-derived wastewater can act as an effective growth stimulant for B. ruziziensis in vitro when applied at low concentrations, offering a potential alternative for plant biotechnology while contributing to waste valorization.
Natural disasters such as floods and earthquakes cause severe physical, social, and economic losses, highlighting the critical need for timely and reliable early warning systems. Conventional water level and structural health monitoring technologies are often costly, limiting deployment to high-priority infrastructure only. This paper presents the development and validation of two low-cost Internet of Things (IoT) systems for multi-hazard disaster monitoring and early warning, explicitly supporting UN Sustainable Development Goals 9 (Industry, Innovation, and Infrastructure) and 11 (Sustainable Cities and Communities) by enabling equitable monitoring of rural or minor bridges. The proposed system achieves a significant cost reduction (approximately $300 compared to conventional systems typically exceeding $5000), highlighting its potential for scalable and sustainable deployment. The first system integrates a Raspberry Pi, Pi Camera, Lidar Lite V3, and ADXL355 accelerometer to simultaneously capture floodwater images, measure water levels, and record bridge vibrations, with distance measurements recorded at user-defined intervals and vibration data sampled up to 100 Hz. Laboratory repeatability and uncertainty analyses of the Lidar Lite V3 indicate a root mean square error of similar to 2.4 cm over a 0-25 cm range, demonstrating stable performance for flood monitoring and sufficient accuracy for early warning applications using low-cost sensing systems. The ADXL355 accelerometer is validated through harmonic excitation tests (0.1-2 Hz) and real earthquake recordings, confirming its suitability for low-frequency structural response monitoring. The second system combines a Raspberry Pi, an HX711 amplifier, and a CDP25 displacement transducer to measure bridge-bearing displacements up to 25 cm, with data acquisition at sampling rates of up to 80 Hz, with laboratory tests demonstrating consistent and repeatable measurements during both loading and unloading cycles. The IoT framework is resilient, incorporating solar power and local data storage to ensure operation during power or network outages. Unlike prior studies focusing on individual sensors, this work delivers a fully integrated multi-sensor platform with formalized early warning logic based on predefined thresholds. The results demonstrate the feasibility of scalable, real-time, low-cost monitoring for disaster risk reduction and infrastructure resilience, providing a sustainable solution for community-scale early warning applications.
Rechargeable magnesium batteries are promising candidates for next-generation energy storage systems due to their intrinsic safety, natural abundance, and high volumetric capacity. However, their practical application remains limited by sluggish Mg2+ transport, electrolyte instability, and low cathode utilization. In this work, a halogen-free electrolyte (HFE) based on Mg(NO3)(2) in an acetonitrile/tetraethylene glycol dimethyl ether (ACN/G4) solvent system is modified using the ionic liquid 1-ethyl-3-methylimidazolium acetate ([EMIM][OAc]) to form HFE_IL, with the aim of enhancing ionic transport and interfacial stability. In parallel, a sustainable sulfur cathode integrated with microalgae-derived hard carbon (S_C) is developed to improve electronic conductivity and suppress polysulfide shuttling. Structural and spectroscopic analyses confirm that the incorporation of the ionic liquid preserves the electrolyte framework while tuning the solvation environment. Electrochemical characterization (EIS, CV, LSV, GCD, and Mg stripping/plating measurements) reveals that HFE_IL exhibits reduced bulk and interfacial resistances, a significantly lower activation energy (0.0173 eV compared to 0.14 eV), and an increased Mg2+ transference number (similar to 0.8). Furthermore, enhanced Mg2+ diffusion (similar to 10(-13) cm(2) s(-1)) and improved charge-transfer kinetics are achieved compared to the pristine electrolyte. Symmetric Mg vertical bar vertical bar Mg cells demonstrate stable stripping/plating behavior with reduced polarization over 100 h. In full Mg vertical bar vertical bar electrolyte vertical bar vertical bar S_C cells, the HFE_IL system delivers a higher discharge capacity (similar to 575 mAh g(-1)) compared to the pristine electrolyte (similar to 437 mAh g(-1)), indicating improved reversibility and Mg2+ utilization. This study demonstrates that ionic-liquid modification of halogen-free electrolytes, combined with sustainable carbon-sulfur cathodes, provides an effective strategy to enhance Mg2+ transport, interfacial stability, and overall electrochemical performance in magnesium batteries.
Soil hydrophysical properties play a key role in processes such as water movement through soil and also affect the amount of water available to plants, thus influencing the sustainability of water management in lowland agricultural landscapes. This study investigated whether the application of calcium sulfate dihydrate (gypsum, CaSO4 center dot 2H(2)O) can improve selected hydrophysical properties of a heavy clay agricultural soil from the Eastern Slovak Lowland (Slovakia). In a controlled laboratory experiment, topsoil samples (0-15 cm depth) were treated with four rates of gypsum application (0.5, 1, 2.5 and 10 g core(-1); approximate to 2-40 t ha(-1) equivalents) and then repacked in 100 cm(3) cores. Gypsum caused a marked apparent shift from "clay" to "silt" in the particle-size analysis, consistent with flocculation and incomplete dispersion rather than a real textural change. Increasing the gypsum dose also led to a gradual increase in saturated hydraulic conductivity (from 0.68 +/- 0.21 to 2.00 +/- 0.66 cm d(-1)). Water retention near saturation changed little, but water content at the wilting point decreased at higher doses, increasing plant-available water (maximum similar to 59% at 2.5 g core(-1)). Under laboratory conditions, gypsum improved the hydraulic function of the soil, and, at selected doses, increased water availability related to drought, supporting its potential as a structural amendment for enhancing the sustainable management of heavy clay soils.
This research mapped mentoring typologies implemented by business incubators in Spain and examined the role of these typologies in fostering sustainable entrepreneurship. Using a quantitative multivariate approach, this study identified and classified mentoring models on the basis of 28 variables related to the mentoring process. The analysis drew on data from the Funcas 2025 survey of Spanish business incubators, which provided detailed information on mentoring practices across the participating incubators (initial responses: n = 100; final analytical sample after listwise deletion of missing values: n = 93). Principal component analysis was applied to extract the main latent dimensions underlying mentoring activities, and cluster analysis was subsequently used to group incubators into homogeneous mentoring typologies. The analysis identified three distinct mentoring profiles: (i) advanced mentoring, characterized by formalized programs with systematic evaluation, rigorous mentor selection, and continuous training; (ii) moderate mentoring, defined by partial integration into incubation services and the use of basic monitoring and evaluation mechanisms; and (iii) incipient mentoring, grounded ad hoc interactions, low formalization, and the absence of structured evaluation systems. Incubators with structured, continuous, and expert-driven mentoring systems were associated with higher entrepreneurial survival rates and stronger contributions to sustainable business development. From a public policy perspective, the findings highlighted mentoring as a strategic policy instrument for advancing Sustainable Development Goals related to Decent Work and Economic Growth (SDG 8), Industry, Innovation and Infrastructure (SDG 9), and Sustainable Cities and Communities (SDG 11). The proposed mentoring typology provided an evidence-based framework to support differentiated incubation policies, improve the targeting of public resources, and design stage-specific mentoring interventions. By moving beyond uniform policy approaches, public authorities can more effectively strengthen entrepreneurial ecosystems and promote resilient, innovative, and sustainable territorial development.
As climate change challenges intensify, the low-carbon transition has emerged as a fundamental structural transformation reshaping the global economic system and promoting sustainable development. In China, the “Dual Carbon” goals announced in September 2020 represent a landmark policy shift that imposes substantial environmental and regulatory pressure on high-carbon-emission enterprises. Against this backdrop, understanding how firms are adjusting their financial reporting practices to align with the low-carbon transition holds considerable significance for fostering their long-term sustainable development. Unlike previous studies that primarily attributed accounting conservatism to firm-specific risks or general economic uncertainty, this paper views the low-carbon transition as a structural institutional shock that reshapes firms’ external governance environment and information conditions, thereby offering a policy-driven explanation for accounting conservatism. Analysis using the Difference-in-differences method demonstrates that the low-carbon transition significantly enhances accounting conservatism among these enterprises (coefficient = 0.008, t = 4.13). Furthermore, mechanism analysis reveals that the low-carbon transition increases accounting conservatism through financing constraints and media attention. Heterogeneity analysis further indicates that the relationship between the low-carbon transition and accounting conservatism is more pronounced in non-state-owned enterprises, firms located in the eastern region, those facing intense industry competition, and companies with low levels of green innovation. Overall, the findings suggest that accounting conservatism is shaped not only by firm-level factors but also by large-scale institutional and policy transitions. By emphasizing that environmental regulation is a structural determinant of financial reporting behavior, this study extends the accounting conservatism literature. Furthermore, it demonstrates that improving financial reporting quality and risk identification capabilities enhances firms’ ability to address the challenges of the low-carbon transition, thereby fostering their long-term sustainable development.
Urban sustainability management increasingly relies on large volumes of heterogeneous environmental data generated by smart city infrastructures. While these data streams offer significant potential for evidence-informed policymaking, environmental governance, and public engagement, their effective use is often constrained by technical barriers and persistent data-skills gaps among non-specialist stakeholders. Using urban air quality as a policy-relevant and data-rich sustainability domain, this paper presents a proof-of-concept dashboard that investigates how large language model (LLM)-enabled natural language interfaces can lower barriers to querying, analysing, and visualising urban environmental data. The system translates natural language questions into executable database queries and automatically generates visualisations over air-quality datasets. A controlled comparative benchmark of proprietary and open-source LLMs is conducted to assess their suitability for text-to-SQL generation in this application context. In this benchmark, proprietary GPT-based models achieved the highest observed query accuracy and robustness among the evaluated models, highlighting practical trade-offs between performance, transparency, reproducibility, and long-term governance. This paper makes a twofold contribution: First, it demonstrates the technical feasibility of an LLM-enabled natural language access layer for smart-city environmental data. Second, it uses the implemented system as a concrete case through which to analyse the trust, transparency, inclusivity, vendor-dependency, and data-quality challenges that arise when such systems are incorporated into sustainability-oriented decision-support workflows. The study provides a transferable design contribution for urban sustainability data access by showing how natural language interfaces, model benchmarking, automated visualisation, and governance-aware system design can be combined to support more inclusive interaction with complex environmental datasets.
This study integrates geostatistical analysis, correlation analysis and pollution load assessment to investigate the spatial distribution characteristics and environmental impacts of rural domestic pollution emissions in the Yellow River Basin, laying a foundation for the sustainable development of rural areas and zoned and classified management of rural domestic sewage in the basin. Results show that: (1) The average rural domestic sewage discharge coefficient in the basin is 25.67 L/(person & centerdot;day), and the average pollutant generation coefficients are as follows: chemical oxygen demand (COD) 23.08 g/(person & centerdot;day), ammonia nitrogen (NH3-N) 0.71 g/(person & centerdot;day), total nitrogen (TN) 1.29 g/(person & centerdot;day) and total phosphorus (TP) 0.11 g/(person & centerdot;day); (2) Rural sewage discharge coefficients near urban areas are higher than other rural areas in the same jurisdiction, with downstream areas significantly exceeding upstream non-urban areas; (3) Youth population, illiterate population, average education years and annual precipitation are key influencing factors, showing significant negative correlations with the former two and positive correlations with the latter two; (4) The maximum equivalent load contribution of rural domestic pollution to the water quality objectives of the Yellow River's main streams and tributaries is merely 2.01%. Overall, rural per capita domestic sewage discharge in the basin is at a low level with obvious regional differences, mainly correlated with demographic, educational and climatic factors, and its impact on the basin's water quality objectives is negligible.
Carbon trading and green credit interest subsidies are two typical market-based environmental regulatory tools. Whether these two policies produce synergistic effects on regional carbon emissions reduction remains an important question. Using panel data from 274 prefecture-level cities in China, this study employs a difference-in-differences model to assess the impact of policy coordination on regional carbon emissions. The mechanisms are examined from two aspects: emission reduction and efficiency gains. The results show that policy synergy has a significant effect on regional carbon reduction. This effect is achieved by reducing energy intensity and improving green total factor productivity, which reflects structural and technical efficiency effects. The carbon-reduction effect of policy synergy is more significant in coastal cities, large and medium-sized cities, and administrative centres. However, a reverse effect is observed in non-administrative centres. These findings provide guidance and support for the coordinated implementation of carbon reduction policies.
This study is based on pollution assessment system and sustainability under a high geological background. The findings from atmospheric deposition research indicate that the exceedance rates for Cd, As, and Hg elements in black shale are 408%, 141%, and 220%, respectively. In atmospheric deposition, the concentrations of Cd, Hg, and Pb exceed the background values by 2.83, 3.29, and 4.08 times in dry conditions and by 3.6, 4.07, and 3.43 times in wet conditions. The difference between dry and wet deposition primarily reflects the concentration variations of Cd, Hg, and As. The distribution of Cd concentrations exceeding standards is widespread, covering over 71% of the total area, and shows a negative correlation with the enrichment patterns in weathered soils. Source analysis indicates that the contribution rates of PC1 for dry and wet deposition are 84.1% and 80.5%, respectively. This finding reveals that atmospheric deposition is significantly influenced by natural weathering processes, while anthropogenic factors exacerbate the overall pollution levels. The HI values for As, Hg, Pb, and Cr for both adults and children are all greater than 1, with the HI value for Pb in dry deposition reaching 13.5, indicating it poses the most severe health risk to children’s safety.
As a non-rivalrous, replicable, and non-consumable production factor, data offers conditions for resource-efficient value creation, and the conversion from scattered data resources into measurable data assets sits at the center of firm competitiveness and sustainable allocation of digital factors. How artificial intelligence supports this conversion, and how executive cognition shapes its strength, are taken up within a framework drawing on the resource-based view, dynamic capability, and upper-echelons theory. Using 24,251 firm-year observations from Chinese A-share listed firms over 2012-2022, panel fixed-effects estimation yields a positive association between AI and data asset formation, stable across instrumental-variable estimation, propensity score matching, Heckman correction, and alternative measures of both variables. AI deepens data mining capability through stronger research and development investment and widens data-carrying capacity through expanded digital infrastructure, with the two channels opening up the relationship. Cognitive flexibility improves the fit between AI and shifting business scenarios, while cognitive complexity supports balanced allocation of technological resources across competing constraints; both characteristics strengthen the main association. The pattern is more pronounced among state-owned enterprises and firms in eastern and central regions, with industry differences less clear-cut. The findings inform differentiated policy design for sustainable digital development in emerging-market settings.
Maritime transport remains a significant source of air pollution and greenhouse gas emissions, while existing vessels face increasing pressure to comply with both local pollutant limits and emerging carbon intensity constraints. This study presents a sustainability-oriented techno-economic assessment of alternative sulphur compliance strategies using real operational data from a 1998-built cruise vessel. Three scenarios were evaluated: a counterfactual heavy fuel oil baseline, heavy fuel oil operation with open-loop scrubbers, and full switching to marine diesel oil. Pollutant emissions were estimated using a Tier 3-oriented approach, while fuel-related Tank-to-Wake greenhouse gas intensity, prospective carbon cost exposure, total cost, break-even fuel price spread and sensitivity analyses were integrated into a decision support framework. Results show that scrubbers reduce SOx emissions by 96.9%, but increase fuel consumption, CO2 emissions and NOx emissions by approximately 3.6%. Marine diesel oil switching reduces SOx by more than 99%, particulate matter by 88.8% and CO2 by 4.6%, while also lowering prospective carbon cost exposure. However, under base case fuel price assumptions, heavy fuel oil operation with scrubbers remains the lower cost strategy, with a 2035 cost advantage of 4.03 to 5.30 million USD/year, depending on the carbon cost scenario. The findings show that the contribution of sulphur compliance strategies to sustainable maritime operation depends strongly on fuel price spreads, carbon cost exposure and remaining vessel lifetime under evolving regulatory conditions. By quantifying the trade-offs between local air pollution reduction, fuel-related carbon exposure and economic viability, this study contributes to sustainable maritime decision-making for aging vessels and supports compliance planning under regulatory uncertainty.
This study examines the impact of climate change on the performance of Egypt’s fish foreign trade during the period from 1995 to 2022. The analysis incorporates a set of climate indicators, including average surface air temperature, relative humidity, rainfall, carbon dioxide emissions, methane emissions, and nitrous oxide emissions, in addition to fish trade indicators represented by exports, imports, total trade volume, trade balance, and export-to-import coverage ratio. The study employs the Autoregressive Distributed Lag (ARDL) model to investigate both the short-run and long-run relationships between climate change variables and fish foreign trade performance in Egypt. Unit root tests confirmed that the variables were integrated at mixed orders I(0) and I(1), supporting the suitability of the ARDL methodology. The findings reveal the existence of a statistically significant long-run equilibrium relationship between climate change indicators and Egyptian fish exports. In particular, nitrous oxide emissions exerted a significant negative effect on fish exports in the long run, while rainfall showed a positive short-run effect. The results also indicate that approximately 57% of short-run disequilibria are corrected annually toward the long-run equilibrium. In contrast, no long-run cointegration relationship was found between climate variables and fish imports, total fish trade volume, or the fish trade balance, indicating that climate impacts on these indicators are mainly short-term in nature. The study concludes that climate change represents an important determinant of Egypt’s fish trade performance through its effects on productivity, environmental quality, and trade competitiveness. The findings highlight the need for integrated adaptation and mitigation policies to strengthen the sustainability and resilience of Egypt’s fisheries sector under changing climatic conditions.
