The transition to renewable energy sources (RES) for electricity generation has gained significant momentum due to environmental and sustainability concerns. However, the high initial costs associated with RES implementation remain a critical barrier, particularly for micro, small, and medium enterprises (MSMEs). To address this challenge, a cost-effective optimization framework for the hybrid renewable energy system (HRES) was proposed, integrating advanced decision-making methodologies. The study focused on a case study of an MSME in a rural village in Ludhiana, Punjab, where the feasibility of various HRES configurations was evaluated using HOMER Pro software. The optimization process aims to minimize key financial metrics, including net present cost (NPC), operation and maintenance (O&M) costs, and the levelized cost of energy (LCOE), while simultaneously reducing carbon emissions. Sensitivity analyses were conducted to assess the impact of critical parameters such as diesel prices, inflation rates, and system constraints. To rank the HRES configurations, a multi-criteria decision-making (MCDM) approach is employed, combining the Method based on the Removal Effects of Criteria (MEREC) for weight determination and the Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) for system ranking. The results demonstrate that the proposed framework effectively identifies the most cost-effective and environmentally sustainable HRES configuration, providing a robust decision-making tool for MSMEs. This study not only contributes to the growing body of knowledge on RES optimization but also offers practical insights for policymakers and stakeholders aiming to promote renewable energy adoption in small-scale industrial settings.

The adoption of electronic documents (e-documents) in logistics has emerged as a critical component for enhancing efficiency, reducing operational costs, and contributing to environmental sustainability. However, despite its numerous advantages, the transition from traditional paper-based systems to e-documents has been sluggish, hindered by a range of barriers including legal and regulatory constraints, lack of standardization, and insufficient system interoperability. This study aims to identify and analyze these barriers, propose relevant policy measures to mitigate them, and evaluate the most effective policy for promoting widespread adoption. Four primary policy strategies were proposed to address the challenges of e-documents in logistics. These policies were assessed using multi-criteria analysis, incorporating fuzzy Step-wise Weight Assessment Ratio Analysis (SWARA) and Axial-Distance-Based Aggregated Measurement (ADAM) methods, to rank their effectiveness in overcoming adoption barriers. The results indicate that the policy ensuring full compliance with regulatory and documentation requirements, through a harmonized approach, offers the most significant potential for driving the adoption of e-documents. This policy emphasizes standardization and mandates compliance, fostering a more robust and efficient transition to digital systems. The findings provide a comprehensive understanding of the policy measures that can most effectively support the expansion of e-documents in logistics, thereby contributing to the long-term sustainability and operational excellence of the sector.

Efficient management of railway infrastructure is recognized as a cornerstone for the sustainable development of the transport sector, as it plays a critical role in reducing congestion, mitigating environmental pollution, and enhancing mobility. The modernization and optimization of railway systems are essential for the optimal utilization of resources and the advancement of a more competitive and environmentally sustainable sector. Railway infrastructure managers (RIMs) are entrusted with the responsibility of ensuring efficient infrastructure management, maintenance, and modernization, thereby guaranteeing the safety, reliability, and sustainability of railway systems. In this study, a methodological framework was proposed for evaluating the efficiency of RIMs by integrating Pearson’s correlation and the Data Envelopment Analysis (DEA) method. The efficiency evaluation was conducted based on key performance indicators (KPIs) associated with railway infrastructure management. Pearson’s correlation was employed to analyze the relationships among 35 KPIs, while the DEA method was utilized to identify efficient managers. The developed framework offers a novel approach for creating analytical tools tailored to RIMs, providing regulatory bodies and decision-makers with a valuable toolset to implement best practices and enhance competitiveness. The findings of this study have practical implications, enabling performance comparisons, the development of management strategies, and the formulation of policies aimed at fostering a more sustainable and efficient railway industry.

The excessive application of agrochemicals has resulted in significant workplace exposure for agriculturists and environmental interaction for the general public, particularly in communities adjacent to agricultural zones. Such exposure is associated with detrimental health effects, including mutagenic and cytotoxic impacts. Agrochemical contamination frequently occurs through water, especially in rural villages where conventional water treatment systems are not designed to address these specific contaminants. The efficacy of activated carbon was investigated in this study as an adsorbent for the removal of 2,4-dichlorophenoxyacetic acid (2,4-D) from contaminated water. The concentration of 2,4-D in water samples was quantified using ultraviolet-visible (UV-Vis) spectroscopy at a wavelength of 283 nm. Preliminary adsorption experiments identified pH 2 as the optimal condition for 2,4-D uptake. The adsorption kinetics were best described by the Elovich model, with an equilibrium time of 480 minutes. Equilibrium studies revealed that three isotherm models—Redlich-Peterson, Temkin, and Toth—effectively represented the experimental data, with a maximum adsorption capacity of 252.8 mg/g. The findings underscore the potential of activated carbon as a cost-effective and straightforward treatment method for the removal of 2,4-D from drinking water, particularly in rural areas lacking access to advanced water treatment infrastructure.