Computational Assessment of the Phytoremediation Potential of Eco-Constructive Modules in a Semi-Arid Urban Climate: The EPI and Its Preliminary Validation

This study is devoted to a computational (in silico) assessment of the phytoremediation potential of eco-constructive modules—green facades, green roofs, and ground-based multifunctional systems—as applied to the urban environment of a semi-arid climate zone, using the city of Shymkent (Kazakhstan) as a case study. A computational model has been developed that combines gas and mass transfer equations (CO2 and SO2 absorption, O2 release, particulate matter retention, and thermohygric stabilization), parameterized using data from the TRY global plant trait database and the UFORE computational model, along with a qualimetric submodel of the Environmental Performance Index (EPI), whose weights were obtained using Saati’s hierarchical analysis method (Kendall’s coefficient of concordance W = 0.81, p < 0.001). The computational experiment covers a matrix of 24 virtual scenarios (12 eco-constructive modules and 12 paired baseline configurations of traditional planting) and is performed using the Monte Carlo method (n = 2000 simulations per scenario), followed by a global sensitivity analysis using Sobol indices. According to the results of ensemble calculations, integrating vegetation into building structures yields a statistically significant 48–84% increase in the health benefit compared to baseline scenarios, with the EPI reaching 0.87 for the best scenarios. The EPI regression model explains 89% of the ensemble variance (R2 = 0.89). Preliminary validation was performed by comparing the calculated values with independent published data for systems with similar designs (deviation of no more than ±8%); no field verification of the modeled configurations was conducted directly at the study site; this is the subject of a separate field research program. The results obtained from a reproducible computational basis for the comparative evaluation of design solutions at the pre-design stage and for planning subsequent field measurements.