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Aair quality issues and respiratory diseases have become issues of particular concern since the outbreak of the COVID-19 pandemic. The indoor air quality of crowded places such as underground metro stations has received growing attention from passengers and staff, thus requiring both qualitative and quantitative assessment. However, the traditional fuzzy comprehensive evaluation is ineffective in this respect. Therefore, this paper proposed the method of optimal combination weight and improved fuzzy comprehensive evaluation to assess the air quality. First, subjective weights were calculated with the multiple-input weighted precedence chart and analytic hierarchy process; objective weights were computed using the entropy weight and exceedance multiple methods. Second, the moment estimation theory was introduced for the optimal combination of these weights. Results show that the optimal combination weighting method achieves the minimum relative deviation. Moreover, in the traditional fuzzy comprehensive evaluation, the air quality is generally classified based on the maximum membership, and the evaluation is inapplicable when the validity (K0) is less than 0.5. Therefore, the concept of confidence was introduced herein for improvement. Finally, the optimal combination weight and improved fuzzy comprehensive evaluation is proved to be the most reasonable in comparison with the traditional fuzzy comprehensive evaluation and indoor air quality index. This study not only suggests a good method to assess the indoor air quality of metro stations but also provides references for decision makers. [ABSTRACT FROM AUTHOR]