Efficacy and Limitations of the Frontal Area Index: Empirical Validation and Necessary Modifications in the U.S. Midwest

The Frontal Area Index (FAI) is a commonly used, cost-effective preliminary screening tool for identifying the Least Cost Path (LCP) of urban ventilated corridors and mitigating the Urban Heat Island (UHI) effect, particularly in situations where data and budget availability are limited. Although its theoretical basis and simulation studies have been extensively examined, empirical validation through field measurements remains limited. This study assesses the FAI method’s applicability in two representative U.S. Midwest cities—St. Louis and Chicago—and proposes key modifications based on field-measurement validation. FAI simulations were conducted to identify optimal ventilation corridors, and the results were subsequently compared with in situ field measurements. Our findings indicated a strong correlation between FAI predictions and field data in St. Louis. In contrast, significant discrepancies were observed in Chicago, where simulated ventilation performance did not align with measured conditions, revealing the standard method’s limitations in complex urban topographies. To address these shortcomings, this study proposes four modifications to enhance the model’s accuracy for U.S. Midwest cities: (1) adjusting the model for varying urban morphologies, (2) limiting the calculation scope, (3) implementing a distinct approach for riverine areas, and (4) adopting a plot-based division for areas with large-scale buildings. This research verifies and refines the FAI method, creating a more reliable tool for diverse urban contexts. The optimized approach provides robust support for wind environment analysis, ventilation corridor planning, and UHI mitigation strategies.