Boundary Layer Influence on Aerosol pH at a High-Altitude Monitoring Station During the Chopin Campaign

Aerosols have a wide range of impacts on climate, clouds, ecosystems and public health. Much of the properties of aerosols that affect their impacts is related to their acidity levels. However, it remains understudied and only over the recent years ambient datasets become available to constrain it. One aspect that remains highly uncertain is the distribution of pH with height; given the large differences of semi-volatile concentration species affecting pH (like NH₃) as well as changes in relative humidity (that affect water content) and temperature (that affect the thermodynamic constants) we expect large changes of aerosol pH with altitude and airmass type.

High-altitude stations provide a unique opportunity to study these variations owing to their ability to sample airmasses that originate from the boundary layer close to ground, and airmasses that are in the free troposphere containing aerosol and gas-phase precursors from long-range transport. In this work, we estimate the aerosol pH at a high-altitude monitoring station during the CHOPIN (CleanCloud Helmos OrograPhic sIte experimeNt campaign, http://go.epfl.ch/chopin-campaign) and CALISHTO field campaigns at Mount Helmos, Greece. Our goal is to identify pH variations when the station is located in the free troposphere compared to periods below the boundary layer  and its variability over time-of-day and over time. Relative humidity, temperature, ammonia concentrations, and aerosol chemical composition observed were used to estimate aerosol pH using the ISORROPIA lite model.

We observed hourly pH variability at the site, with lower pH values between 7 am and 1 pm, before the boundary layer reached the site and after anthropogenic ammonia mixed into the atmosphere dispersed overnight. Higher pH values were observed in the afternoon when ammonia associated with anthropogenic emissions from nearby urban and agricultural activities reached the station. SHapley Additive exPlanations analysis (SHAP) was applied to identify the variables that contribute and influence the most to the observed pH, providing a more robust and reliable attribution than other models. It was found that during the free troposphere condition, SHAP values do not vary significantly with time; however, significant differences were observed when the station is below the boundary layer.

 

This work was supported by the CleanCloud project funded by the EC Horizon Europe Call “Improved knowledge in cloud-aerosol interaction” (HORIZON-CL5-2023-D1-01-04).