With Stefania Rennaand Lara Aleluia Reis
This study performs a data-driven investigation of the impact of agriculture on air pollution in Lombardy, Italy, focusing on secondary inorganic particulate matter (PM) formation resulting from ammonia (NH3) emissions. Leveraging on the predictive power of machine learning models and exploiting the reduction in non-agricultural emissions during the 2020 COVID-19 lockdown, we analyze the complex relationship between NH3, nitrogen dioxide (NO2), and secondary inorganic aerosols (SIA). We find that even substantially large reduction in precursor emissions may not deliver large drops in secondary inorganic PM. While NO2 plays a significant role in urban environments, in rural areas where NH3 levels are high, both NO2 and NH3 contribute to SIA formation. This emphasizes the importance of considering both NH3 and NO2 emissions in policies controlling secondary inorganic PM, as reductions in both precursors may be necessary for significant improvements. The study provides insights into the interplay between agricultural practices and air pollution, more specifically the NH3–NO2 regime and its implications for effective air pollution control strategies in Lombardy.