Tracing carbonaceous aerosols through trace gas–aerosol relationships in urban pollution plumes

Understanding the composition of carbonaceous aerosols, black carbon (BC) and organic aerosols (OA), remains a major challenge in atmospheric science. Using data from two aircraft campaigns with identical instrumentation over Europe and East Asia, we analyze statistical relationships between concentrations of five trace gases (CO, NO 2 , HCHO, O 3 , and SO 2 ) with BC and OA in order to estimate carbonaceous aerosol in urban pollution plumes. We show that across both campaigns, CO is the best proxy for BC ( R 2 ≈ 0.6). In plumes, OA shows statistical links with NO 2 , O 3 , and CO, reflecting the combined influence of emissions, and secondary organic aerosol formation. Linear regressions based on trace gases remain limited, especially for OA, whereas the use of nonlinear machine-learning regression improves the quantification of BC and OA ( R 2 ≈ 0.9 for BC, R 2 ≈ 0.7 for OA). However, the number of flights is limited, the results should not be interpreted as applicable to flights in other regions and seasons. Our findings indicate that co-emitted and co-produced trace gases contain information for quantifying carbonaceous aerosol in urban pollution plumes. This potential is more robust for BC, whereas OA remains more complex to estimate because it depends on multiple predictors.