CASA: An InnovativeTool for Near-Real-Time SourceApportionment of Atmospheric Organic Aerosols

Since organic aerosols (OA) account for a significant fraction of PM worldwide, source apportionment is essential for effective air quality mitigation and policymaking. In the present study, we developed a novel method based on a chemical mass balance and an elastic net regressor (EN-CMB), using positive matrix factorization (PMF) as prior knowledge for near real-time source apportionment of OA. EN-CMB has been integrated into a so-called continuous aerosol source apportionment (CASA) software package, which has been evaluated against state-of-the-art rolling-PMF data at three contrasted urban sites in Europe. CASA exhibits very satisfactory performance for primary OA components, with, at all sites, R2 values of 0.87–0.97 and mean bias error (MBE) of between −0.15 and 0.14 μg/m3. Secondary OA (SOA) fractions showed similar R2 values (0.81–0.97), but slightly higher MBE values (ranging from −0.71 to 0.04 μg/m3), which can be related to the complex nature of SOA and is still acceptable regarding bulk trends. CASA allows near real-time operation and, as it is open source, represents a promising example of timely and efficient air pollution management with applications in real-time air quality monitoring. The next steps will enable community-driven initiatives to improve and expand the application of such open-source methodologies across diverse regions and emission sources.