Prediction of the Concentration and Source Contributions of PM_2.5 and Gas-Phase Pollutants in an Urban Area with the SmartAQ Forecasting System

Abstract

The SmartAQ (Smart Air Quality) forecasting system produces high-resolution (1 × 1 km2) air quality predictions in an urban area for the next three days using advanced chemical transport modeling. In this study, we evaluated the SmartAQ performance for the urban area of Patras, Greece, for four months (July 2021, September 2021, December 2021, and March 2022), covering all seasons. In this work, we assess the system’s ability to forecast PM2.5 levels and the major gas-phase pollutants during periods with different meteorological conditions and local emissions, but also in areas of the city with different characteristics (urban, suburban, and background sites). We take advantage of this SmartAQ application to also quantify the main sources of the pollutants at each site. During the summertime, PM2.5 model performance was excellent (Fbias −3, ME = 2.5 μg m−3) the overall measured PM2.5 behavior and the high nighttime peaks due to cooking activity, as well as the transported PM pollution in the suburbs. During the fall, the SmartAQ PM2.5 performance was good (Fbias −3) for the suburbs because the model overpredicted the long-range transport of pollution. For wintertime, the system reproduced well (MB = −2 μg m−3, ME = 6.5 μg m−3) the PM2.5 concentration in the high-biomass-burning emission area with an excellent model performance (Fbias = −4%, Ferror = 33%) and reproduced well (MB −3, ME −3) the background PM2.5 levels. SmartAQ reproduced well the PM2.5 concentrations in the urban and suburban core during the spring (Fbias −3, ME −3), while it tended to slightly overestimate the regional pollution. The main local source of fine PM during summer and autumn was cooking, but most of the PM was transported to the city. Residential biomass burning was the dominant particle source of pollution during winter and early spring. For gas-phase pollutants, the system reproduced well the daily nitrogen oxides (NOx) concentrations during the summertime. Predicted NOx concentrations during the winter were consistent with measurements at night but underestimated the observations during the rest of the day. SmartAQ achieved the US EPA modeling goals for hourly O3 concentrations indicating good model performance.

Keywords

• air quality predictions
• pollutant sources
• PM_2.5
• NO_x
• O₃
• evaluation metrics