Construction of fuzzy logic model for estimating environmental improvement index in industries of Bangladesh

Industrial activities significantly contribute to environmental degradation by presenting many obstacles to sustainable development, especially in developing countries like Bangladesh, where any major inconvenience can disrupt global market confidence and not much progress has been observed so far in terms of Sustainable Development Goals (SDGs). So, monitoring the environmental state of this country is a global concern for environmental management and policy-making purposes. Development of a model to evaluate the environmental status will help the industries to assess how close they are to these goals. While numerous studies have proposed methods to assess environmental performance, there remains a gap in dealing with qualitative data tailored to specific industrial fields that can accurately quantify the parameters of environmental improvements. This research introduces a novel fuzzy model designed to evaluate the Environmental Improvement Index (EII) for industrial sectors in Bangladesh. The model uniquely integrates four critical environmental parameters, wastewater treatment, solid waste management, hazardous waste handling, and air pollution reduction, each categorized into three qualitative levels (small, medium, large), resulting in 81 possible assessment conditions, which computes an index value reflecting the current state of environmental improvements in the country. A country’s policymakers can modify this model with their dataset and work on evaluating the EII that will help industries achieve a sustainable environmental state and keep environmental degradation under control globally. Verification and validation of the model demonstrate its reliability, making it a valuable resource for researchers, policymakers, and industry stakeholders globally committed to environmental sustainability.