Optimizing plant species selection for alleviating air pollution: Modified Anticipated Performance Index-based...

Urban green spaces are crucial in mitigating air pollution and enhancing environmental quality. The Anticipated Performance Index (API) screens plant species based on ecological, economic, and biochemical/Air Pollution Tolerance Index (APTI) parameters. However, it assigns equal weight to all components and excludes key biophysical traits affecting plant stress and pollution tolerance. This study evaluated 25 plant species (20 trees, 4 shrubs/small trees, and 1 herb) across eight urban parks and four vertical gardens in Delhi using weighted API and Modified Anticipated Performance Index (M-API). M-API was formulated by integrating five key biophysical traits-leaf weight, leaf area, specific leaf area, width/length ratio, and vein density. Results showed higher weighted API and M-API scores than the conventional API scores reported in literature. M-API scores classified none of the species as 'Poor' or 'Very Poor', with three shifting to 'Moderate,' one shifting from 'Best' to 'Excellent,' six from 'Very Good' to 'Excellent,' and five from 'Moderate' to 'Good'. Pearson correlation analysis showed a stronger correlation between dust load and M-API (0.31) than with API (0.21) or APTI (0.09), demonstrating M-API's effectiveness in capturing relevant plant traits. Among park species, Ficus benghalensis had the highest M-API score (7), whereas Syngonium podophyllum and Ficus benjamina scored highest (4) in vertical gardens. The study demonstrates M-API's better applicability in assessing plant potential under air pollution stress. By resolving API's limitations, M-API can help stakeholders choose optimal plant species for urban greening initiatives.