The article aims at multi-criteria decision making analysis using the fuzzy set theory to evaluate different policy options to reduce CO₂ emissions from road transport in case of India. The fuzzy set theory has been applied to investigate different possible measures which the government can adopt to reduce CO₂ emissions and improve air quality. Ordered weighted average operator of linguistic fuzzy set theory is used to rank different policy options. Findings show that the use of low emissions vehicles and the adoption of sustainability-oriented behaviour are considered the most preferred options, which can effectively reduce the CO₂ emissions from road transport. The research shows that fuzzy set theory may be an effective tool in analyzing environmental uncertainties. Analyzing the optimal policy measure and prospects of it in different scenarios would help policymakers in designing and focusing on effective policy measures in order to reduce CO₂ emissions from road transport in a country like India. The study implies ways to assess policy options for environment management and dealing with climate change. This study also fills the gap between the theoretical fuzzy model and its practical implication in policy decision-making, especially in a sustainability area that is more uncertain.

本文旨在使用模糊集理论进行多准则决策分析，以评估不同的政策选择，以减少印度道路交通产生的CO ₂排放。模糊集理论已被用于研究政府可能采取的减少CO ₂排放和改善空气质量的各种可能措施。语言模糊集理论的有序加权平均算子用于对不同的策略选项进行排序。结果表明，使用低排放车辆和采取以可持续发展为导向的行为被认为是最可取的选择，它们可以有效地减少CO ₂排放。公路运输产生的排放。研究表明，模糊集理论可能是分析环境不确定性的有效工具。分析最佳政策措施及其在不同情况下的前景，将有助于政策制定者设计和关注有效的政策措施，以减少像印度这样的国家的公路运输产生的CO ₂排放。该研究暗示了评估环境管理和应对气候变化的政策选择的方法。这项研究还填补了理论模糊模型及其在政策决策中的实际含义之间的空白，特别是在更具不确定性的可持续性领域。