Digital transformation has become a strategic imperative across Europe, yet significant disparities persist between member states and within national economies. This study examines the determinants of digital maturity in Romanian enterprises using data from 199 firms assessed through the national Digital Maturity Assessment (DMA). By integrating regional, sectoral, and organizational characteristics with capability-based indicators, the analysis shows that Romania remains a developing digital ecosystem marked by low levels of automation and artificial intelligence (AI) adoption, persistent regional disparities, and sectoral fragmentation. Multiple regression results indicate that Human-Centric Digitalization, Automation AI readiness, and Green Digitalization are the capability domains most strongly associated with overall digital maturity, collectively explaining more than 91
This aim of the research is centred on the topic of the resilience of green and non-green cryptocurrencies during major systemic shocks: COVID-19, the Russia–Ukraine conflict, and the Israel–Gaza war, as platforms for digital innovation diffusion rather than speculative assets. This study conceptualizes cryptocurrencies as technology-bearing digital infrastructures and analyse the framework of sustainable and non-sustainable blockchain architectures function as channels of technology transfer during systemic crises. Using data covering the COVID-19 pandemic, the Russia–Ukraine war, and the Israel–Gaza conflict, the analysis applies Markov regime-switching models and spillover indices to assess volatility regimes, cross-market interconnectedness, and technological resilience. The findings indicate that volatility spillovers between cryptocurrencies and sustainability-linked financial instruments green bonds, carbon indices, and climate-focused ETFs intensify during crises and highlight the emerging hybrid transfer pathways, where digital financial technologies increasingly co-evolve with environmental and energy-related innovations and blockchain systems based on energy-efficient architectures demonstrate greater stability and stronger integration with sustainability-linked financial instruments during periods of disruption.
Carbon capture and storage (CCS) represents a critical technology for achieving climate neutrality targets, particularly for regions with significant industrial CO2 emissions. This study presents a comprehensive numerical simulation assessment of CO2 geological storage potential in the Sarmatian formations of the Getic Platform, Romania, located near the Turceni power plant—one of Europe’s largest thermal power facilities. Using ECLIPSE 300 compositional simulator with the CO2STORE option, we developed reservoir dynamic models incorporating geological properties, fluid characteristics, and pressure–volume–temperature (PVT) data specific to the Sarmatian aquifer system. Multiple injection scenarios were evaluated, including configurations with 3, 4, and 5 injection wells at varying inter-well distances (2000–10,000 m). The simulations covered a 20-year injection period followed by 300 years of monitoring. While previous assessments have provided static capacity estimates for Sarmatian formations, this study presents the first dynamic simulation-based evaluation of multi-well injection scenarios and long-term CO2 trapping behavior in this geological setting, directly linked to the Turceni Power Plant emissions profile. Results demonstrate that the study area (Zone V) can accommodate the target CO2 injection rate of 2.07 × 106 Sm3/day using five injection wells, with final reservoir pressure increasing only 7–9 bar above initial conditions, well below fracture pressure thresholds (~280 bar). Long-term simulations reveal favorable CO2 trapping behavior, with significant portions immobilized through residual and dissolution trapping mechanisms. The static storage capacity was estimated at 2.44 × 1014 kg CO2. These findings support the technical feasibility of large-scale CO2 storage in Romanian Sarmatian formations, providing quantitative evidence for CCS implementation strategies in the region.
In the context of intensifying global efforts to mitigate climate change, methane emissions from the oil and gas sector have emerged as a critical environmental and regulatory challenge, given methane’s high global warming potential over short timeframes. This study investigates methane emissions from representative extraction and production of oil and gas facilities in Romania, focusing on fugitive emissions from wells and associated processing infrastructure. The research is grounded in the implementation of a comprehensive Leak Detection and Repair (LDAR) program, aligned with OGMP 2.0 standards, and utilizes advanced detection technologies such as Flame Ionization Detectors (FID), Optical Gas Imaging (OGI), and Quantitative Optical Gas Imaging (QOGI). A systematic inventory and screening of thousands of components enabled the precise identification and quantification of methane leaks, providing actionable data for maintenance and emissions management. The findings highlight that, although the proportion of leaking components is relatively low, cumulative emissions are significant, with block valves, connectors, and compressor shaft seals identified as the most frequent sources of major leaks. The study underscores the importance of rigorous preventive and corrective maintenance, rapid leak remediation, and the adoption of modern detection and continuous monitoring technologies. The approach developed offers a robust framework for regulatory compliance and supports the transition from inventory-based to measurement-based emissions reporting, in line with recent European regulations. Ultimately, effective methane management not only fulfills environmental obligations but also delivers economic benefits by reducing product losses and enhancing operational efficiency, contributing to the decarbonization and sustainability objectives of the energy sector.
The present study investigates the optimization of the FDM parameters, that is, the height of the deposited layer in one pass (Lh) and the filling percentage (Id), for the manufacture of compression specimens from recycled ASA (rASA) in the context of transitioning to the circular economy. The Anycubic 4Max Pro 2.0 3D printer was utilized, where compression specimens were additively manufactured from rASA 45 using the following variable parameters: Lh = 0.10 mm, 0.15 mm, and 0.20 mm, and Id = 50%, 75%, and 100%. All compression specimens were tested on the Barrus White 20 kN universal testing machine. It was found that the Compressive strength (Cs) is influenced by the two considered variable parameters of the Fused Deposition Modeling (FDM), Lh and Id, but the overwhelmingly influencing parameter is Id. According to the results of the FDM parameter optimization for the manufacture of compression specimens from rASA, Lh = 0.10 mm and Id = 100%.
