Assessing Environmental Pollution: Quality Control Using CRITIC-WASPAS Methodsunder Intuitionistic Fuzzy Z-Numbers

Abstract. Industrial pollution is still a major worldwide issue. Strong decision-making frameworks are required to evaluate and reduce its detrimental effects on the environment. An extensive case study assessing different industrial pollution produced by the energy industry, textile industry, chemical industry, manufacturing industry, agriculture industry, and construction industry and its environmental impact is presented in this paper. We present a structured evaluation of environmental degradation by analyzing key environmental criteria, including waste generation, noise pollution, soil contamination, air pollution, and water pollution. In order to accomplish a systematic and objective evaluation, we provide an advanced multi-criteria decision-making (MCDM) framework that combines the CRITIC-WASPAS and CRITIC-EDAS approaches with intuitionistic fuzzy Z-number (IFZN). This integration ensures a more reliable, flexible, and data-driven assessment of industrial pollution sources by addressing uncertainty, imprecision, and inconsistency in the data effectively. In order to determine the objective weights of environmental criteria , the CRITIC (Criteria Importance Through Intercriteria Correlation) method is applied here. These weights undergo additional processing using the WASPAS and EDAS approaches, which combine aggregated sum product weighting (WASPAS) and positive and negative distance based evaluation (EDAS) to check the ranking of given criteria. Additionally, sensitivity analysis is used to assess the robustness and dependability of the suggested fuzzy model by altering input parameters, including weights, membership values, and decision-maker preferences. Moreover, a comparison with earlier approaches is carried out to evaluate the consistency and accuracy of the proposed model’s ranking.