Investigation and Optimization of Air Pollution Risk by a Multi-criteria Decision Making Method Using Fuzzy TOPSIS: A Case Study of Construction Workers

The study identifies a significant concern for the health and safety of workers in occupational settings, with a special focus on the air pollution risks construction workers face. To better understand and address these risks, the study employs a specialized approach that combines Multi-Objective Decision-Making (MODM) with fuzzy TOPSIS. The study aims to improve health and safety for construction workers by determining and emphasizing the most important risk factors. In the research model, the author uses risk behavior and safety, efficiency and optimally, risk comprehension, and the level of risk involved to develop comparison matrices and apply the Phillips-Perron test. The study reveals that “risk comprehension” and “safety efficiency” are

the most influential factors in worker health. Additionally, among risk factors, “worker knowledge,” “manager awareness,” “manager’s logistical specialization,” “contemporary infrastructure,” and “advanced technology” are found to be the most effective. This research also includes selecting and estimating the parameters of both linear and non-linear models via F values, creating a comprehensive approach for identifying and correcting risk in construction environments. This methodology serves as a framework to design specific programs to promote occupational health and safety.

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