Improving PM10 and PM2.5 concentration prediction using the Brazilian Regional Atmospheric Modeling 5.2 System in Lima, Peru

Sánchez-Ccoyllo O.R.; Alonso M. · Urban Climate (2024) · DOI: 10.1016/j.uclim.2024.101985

Resumen

Urban air pollution caused by atmospheric aerosols has far-reaching implications on human health, economy, and climate. Using chemical transport models (CTMs) as inputs to the existing vehicle emission inventory (VEI) data in the metropolitan area of Lima and Callao (MALC) results in lower simulated PM10 and PM2.5 concentrations than the measured concentrations in MALC. Thus, the model needs to be improved to increase the accuracy of simulations. Numerical air pollution modeling using CTMs has rarely been studied in Peru. This study aimed to improve PM10 and PM2.5 concentration simulations using CTMs in Peru by calculating a new VEI. Subsequently, PM10 and PM2.5 simulations were conducted using the Brazilian Regional Atmospheric Modeling System (BRAMS) 5.2, which employs both VEI from a previous study (referred to as numerical simulation 1, NS1, serving as the control simulation) and the new VEI (resulting in NS2, NS3, and NS4, representing the sensitivity simulations). The results indicated that the sensitivity simulations conducted using the BRAMS 5.2 model effectively captured PM10 and PM2.5 concentrations, aligning closely with the measured data. The study provides an in-depth understanding of air quality dynamics that can assist in implementing strong policies and environmental management efforts to mitigate air pollution.

Instituciones: Universidad Nacional Tecnológica de Lima Sur