Pollutant Source Contribution Study Using Chemistry Transport Models

Nowadays, environmental pollution has become one of the most urgent and critical global challenges. Adverse effects on human health, ecosystems, and climate require a thorough comprehension of the sources and magnitude of pollutants. In the last years, a lot of chemistry-transport models have been developed to better understand air pollution in cities. These models utilize pollutant emission fluxes as inputs to predict final pollutant concentrations. This study uses the CHIMERE model to investigate the impact of emission reductions on air quality in the city of Barcelona, focusing on key pollutants such as nitrogen dioxide (NO2), nitric oxide (NO), ozone (O3), and particulate matter (PM10). The primary objective is to identify and quantify the contributions of various sources to the final concentration of pollutants in the air. The study integrates global emission inventories (EMEP) with local data, enhanced by the emiSURF model, which generates precise emissions inputs for CHIMERE, ensuring reliable simulation results. A series of simulation scenarios were conducted to evaluate the impact of emission reductions across key sectors identified by the SNAP code, including production processes, solvent use, vehicular traffic, and other mobile sources. These scenarios were applied for two distinct periods, February and July 2022, representing different seasonal conditions. The results indicate that the transportation sector significantly impacts air quality, particularly regarding NO2 and NO concentrations. Emission reductions in this sector notably decreased these pollutants. Conversely, sectors such as production processes and solvent use had minimal impact on air quality unless substantial emission reductions were implemented. The study also revealed that O3 concentrations increased when NO2 emissions decreased, highlighting the complex interplay of atmospheric chemical reactions. In addition, the CHIMERE model has been demonstrated to be an effective tool for predicting the impact of air quality on human health and the environment and provides valuable insights for policymakers.