Anthropogenic climate change, driven primarily by the intensification of greenhouse gas emissions since the Industrial Revolution, continues to pose significant environmental and socio-economic challenges. Among the most promising mitigation strategies is carbon capture, utilisation and storage (CCUS), which facilitates the reduction of carbon dioxide (CO₂) emissions by capturing CO₂ from large point sources and storing it in geological formations, such as depleted oil and gas reservoirs. In some configurations, CCUS has also been employed to enhance hydrocarbon recovery. While the technology is widely recognised for its potential to contribute to decarbonisation goals, particularly in fossil fuel-dependent economies, its large-scale deployment remains constrained by considerable economic and regulatory barriers. In Indonesia, a country with ambitious commitments to achieve net-zero emissions by 2060 but a continued reliance on fossil energy, CCUS is increasingly being considered a strategic pathway for transitioning the energy sector toward sustainability. This study undertakes a systematic review of existing and near-operational CCUS initiatives globally, with a focus on economic performance, cost structures, and policy frameworks. Evidence from the literature suggests that although CO₂-enhanced oil recovery (CO₂-EOR) can yield short-term productivity gains, the high capital and operational expenditures associated with CCUS systems often undermine their economic feasibility in the absence of supportive policy instruments or carbon pricing mechanisms. Furthermore, the lack of integrated regulatory frameworks and stakeholder coordination has been identified as a critical barrier to progress in Indonesia. It is therefore argued that a comprehensive national strategy is required—one that aligns with Article 6 of the Paris Agreement and incorporates targeted subsidies, regulatory clarity, and inter-sectoral collaboration among emitters and storage providers. The analysis underscores the necessity of embedding CCUS into Indonesia’s long-term decarbonisation roadmap through an approach that balances environmental obligations with economic pragmatism.
Wireless communication technology has transformed connectivity across industries, but its widespread adoption comes with significant challenges. The purpose of paper is to identify and analyze the most critical obstacles affecting the efficiency, reliability, and scalability of wireless communication systems. This research paper mainly demonstrates to determine the most effective challenges for wireless communication technology. In recent times, it is really very significant and demanding work of this technology-based society. Interference, security vulnerabilities, bandwidth limitations, signal attenuation, and latency concerns etc. are the basic factors of this challenging work. This study explores the application of multi-criteria decision making (MCDM) techniques using intuitionistic fuzzy numbers (IFNs) to evaluate this. We apply the weighted MCDM method, i.e., Entropy in this paper. The decisions of multiple decision makers (DMs) are considered into account when collecting this problem related data and IFNs are utilised as mathematical tools to handle uncertainty. In order to address the ambiguity and inconsistency of the system, we finally conclude to conduct the analysis here with final result.
The inadequate disclosure of environmental sustainability performance by polluting firms has led to significant information asymmetry between corporations and stakeholders, which in turn has contributed to investor apathy, diminished economic success, and increased community opposition. This study examines the effects of environmental sustainability performance disclosure on the profitability of firms, specifically focusing on the consumer goods manufacturing sector in Nigeria. The research is anchored in Stakeholder Theory and adopts a correlational research design. Data were obtained from the annual reports of thirteen listed consumer goods manufacturing companies over a period of thirteen years (2012-2024). Feasible Generalized Least Squares (FGLS) regression analysis was employed to test the hypotheses. The results indicate that the disclosure of greenhouse gas (GHG) emissions reduction is positively associated with profitability. Similarly, the disclosure of environmental waste management practices is significantly related to improved corporate profitability. However, the disclosure of water management practices revealed a significant negative relationship with profitability. The findings suggest that the disclosure of environmental sustainability practices, such as GHG emissions reduction, waste management, and water consumption reduction, plays a crucial role in enhancing both environmental sustainability and long-term financial performance. While GHG reduction was found to have a direct financial benefit, waste management strategies necessitate a shift from compliance-based approaches to innovation-driven practices. Water management, on the other hand, requires better alignment with industry-specific realities to effectively contribute to profitability and sustainable growth. These findings underscore the importance of transparent environmental performance disclosure as a driver of both ecological sustainability and financial success for firms operating in the consumer goods manufacturing sector.
Equipment failure in paper mills represents a critical barrier to operational efficiency and the adoption of Industry 4.0 principles. To address this, a systematic literature review was conducted to identify the multifactorial determinants of such failures. A novel hybrid methodology was proposed, integrating the Functional Analysis Systems Technique (FAST), enhanced by Lean 5S (Sort “Seiri”, Set in Order “Seiton”, Shine “Seiso”, Standardize “Seiketsu”, Sustain “Shitsuke”) principles, to structure the qualitative data collection. The analysis was performed using a Pugh matrix, followed by a Principal Component Analysis (PCA) to extract knowledge systematically. This approach facilitated the development of a conceptual model for downtime causation. The PCA results indicate that two principal components collectively explain 58.5% of the observed variance in failure data. The f irst component was strongly correlated with maintenance practices and operational errors, while the second was associated with intrinsic equipment characteristics and their operating conditions. This data-driven modeling elucidates underlying correlations between disparate factors, providing a robust foundation for prioritizing targeted maintenance optimization actions. This research contributes to the field of industrial intelligence by demonstrating an original methodology for transforming qualitative systematic review data into a quantifiable analytical framework. The application of PCA to this corpus enables the identification of multidimensional interactions that are frequently overlooked in conventional analyses, thereby enriching root-cause failure analysis and informing strategic decision making for predictive maintenance. The identified factors underscore the imperative of a balanced integration between technical data and human factors for the successful digital transformation of production systems.
In response to escalating urban traffic congestion, environmental degradation, and mobility inefficiencies, intelligent transportation systems (ITS) and sustainable mobility strategies have been increasingly recognised as vital components of smart city development. In this study, the city of Trabzon, Türkiye, was examined as a representative urban environment facing such challenges. Six major intersections exhibiting persistent traffic congestion were selected for conversion from conventional fixed-time signal control to adaptive, traffic-actuated signalisation systems. Detailed performance evaluations were conducted, incorporating microsimulation modelling and real-time traffic flow analysis. The implementation of adaptive signalisation was found to significantly reduce vehicular delay, queue lengths, and intersection-level emissions, while enhancing operational efficiency and traffic safety. A complementary analysis assessed the economic and environmental impacts of this intervention, revealing considerable annual savings in fuel consumption and marked reductions in carbon dioxide (CO$_2$) emissions, thereby underscoring the long-term sustainability and cost-effectiveness of the proposed system. In parallel, the integration of electric vehicles (EVs) and micromobility solutions—including electric buses, minibuses, passenger cars, bicycles, and scooters—was proposed to further promote sustainable urban mobility. Strategic placement of EV charging infrastructure was suggested, with spatial planning informed by expected demand distribution and intermodal connectivity. Economic modelling demonstrated a reduction in operational fuel expenditure, while environmental projections indicated a substantial decrease in transport-related greenhouse gas emissions. Furthermore, micromobility modes were proposed as critical for addressing first- and last-mile connectivity gaps, mitigating short-distance vehicular traffic, and alleviating urban parking demand. Policy recommendations emphasised the necessity of strong municipal leadership in facilitating infrastructure deployment, public adoption, and behavioural shifts towards low-emission transport alternatives. The findings position Trabzon as a viable model for medium-sized urban centres seeking to implement scalable and replicable smart mobility frameworks. By integrating adaptive traffic control with zero-emission mobility, this study provides actionable insights into the design of efficient, economically viable, and environmentally sustainable urban transportation ecosystems.
The risk of catastrophic flooding from sequential dam breaches in cascade reservoir systems has become increasingly critical under the influence of complex climate change and extreme geological events. In this study, a two-dimensional hydrodynamic dam-break model was developed to analyse flood propagation and inundation dynamics for the $RE1$, $RE2$, and $RE3$ cascade reservoirs in the lower Southwest China River Basin, considering various instantaneous full and partial collapse scenarios. Four distinct scenarios were simulated to evaluate breach characteristics and inundation impacts. Notably, Scenario 3-involving the simultaneous instantaneous full collapse of all three reservoirs-produced peak flow rates of 341,200 m$^3$/s, 1,157,900 m$^3$/s, and 340,100 m$^3$/s at $RE1$, $RE2$, and $RE3$, respectively. Under this worst-case scenario, maximum inundation depths at representative sites A, B, C, and D reached 69.51 m, 79.87 m, 77.16 m, and 48.38 m, with high-severity flooding areas extending over 0.95 km$^2$, 1.10 km$^2$, 1.21 km$^2$, and 1.73 km$^2$, respectively. In comparison, Scenarios 1 and 2 generated lower peak flow rates, smaller inundation areas, and less severe flooding, while Scenario 4-representing overtopping without structural breach-resulted in a substantial reduction of high-risk zones. The findings highlight the pronounced escalation of flood risk under simultaneous multi-reservoir collapse conditions and underscore the necessity for enhanced coordinated flood management and emergency response strategies in cascade reservoir systems. This study offers valuable insights into dam failure risk assessment, contributing to improved flood mitigation policies and emergency preparedness in regions vulnerable to extreme hydrological events.
Open Access
adi sutrisno 
, etty wahyuni , m. wahyu agang , tjahjo tri hartono , mas davino sayaza , dwi santoso , deny titing , erwan kusnadi , elida novita , rahmat pramulya , devi maulida rahmah |
Available online: 06-10-2025
Robusta coffee cultivation in Malinau Regency has been increasingly associated with forest land conversion, thereby intensifying the need for sustainable management practices that align with both environmental conservation and rural livelihood enhancement. To evaluate the sustainability of Robusta coffee farming systems, the sustainable livelihood framework was applied, focusing on five key livelihood capitals: natural, human, social, physical, and financial. A mixed-methods approach involving Multidimensional Scaling (MDS) and thematic analysis was employed to quantify sustainability levels and identify leverage points for strategic intervention. Results indicated that most capitals were classified as either “unsustainable” or “less sustainable.” Social capital demonstrated the lowest performance, with an index of 15.10, while financial capital followed at 20.88; both were categorized as “unsustainable.” Natural capital (26.13) and human capital (26.09) were deemed “less sustainable,” whereas physical capital showed relatively higher resilience with an index of 46.61, though still within the “less sustainable” threshold. Key constraints included insecure land tenure, underdeveloped infrastructure, limited social cohesion, and economic dependence on non-coffee income sources. Strategic interventions were proposed, including the certification of land ownership for 70% of coffee farmers within three years, the revitalization of farmer cooperatives to improve social capital, and the enhancement of rural infrastructure, particularly targeting 85% electricity coverage in coffee-producing areas by the second year. The integration of Geographical Indication (GI) certification with agroforestry-based production systems was identified as a pivotal strategy to reconcile ecological integrity with market competitiveness. By year four, price premiums of up to 40% in domestic markets and 60% in international markets were targeted through value addition and branding. These integrated measures are expected to reinforce livelihood resilience while promoting long-term socio-ecological sustainability in Malinau’s coffee landscapes.
Industrial parks represent one of the most significant contributors to carbon emissions, making their transition toward zero-carbon operations a critical priority. Achieving this goal requires scientific, phased evaluation tools capable of guiding differentiated emission reduction strategies. This study introduces an integrated assessment framework that combines interval-valued triangular fuzzy sets, an enhanced CRITIC weighting method, and matter-element extension theory to provide robust and diagnostic insights into carbon performance. Sensitivity and comparative analyses confirm the model's reliability and resilience. An empirical application involving five industrial parks in China’s Yangtze River Delta demonstrates the framework’s effectiveness. The results indicate that Park C has approached a near-zero-carbon status, while Parks D and E remain in high-emission stages. Notable disparities are observed among the parks: high-performing parks benefit from strong governance and energy synergy, whereas underperforming parks face bottlenecks due to weak carbon management and limited adoption of circular economy practices. The proposed model maintains stable ranking outcomes even under weight perturbations and aligns closely with alternative evaluation methods. These findings suggest that successful zero-carbon transformation depends on coordinated progress across multiple dimensions rather than isolated improvements in specific indicators. This research offers a scientific foundation for targeted, phase-based decarbonization strategies in industrial parks.
