Co-located measurements of fine particulate matter (PM2.5) organic carbon (OC), elemental carbon, radiocarbon (14C), speciated volatile organic compounds (VOCs), and OH radicals during the CalNex field campaign provide a unique opportunity to evaluate the Community Multiscale Air Quality (CMAQ) model's representation of organic species from VOCs to particles. Episode average daily 23 h average 14C analysis indicates PM2.5 carbon at Pasadena and Bakersfield during the CalNex field campaign was evenly split between contemporary and fossil origins. CMAQ predicts a higher contemporary carbon fraction than indicated by the 14C analysis at both locations. The model underestimates measured PM2.5 organic carbon at both sites with very little (7% in Pasadena) of the modeled mass represented by secondary production, which contrasts with the ambient-based SOC / OC fraction of 63% at Pasadena. Measurements and predictions of gas-phase anthropogenic species, such as toluene and xylenes, are generally within a factor of 2, but the corresponding SOC tracer (2,3-dihydroxy-4-oxo-pentanoic acid) is systematically underpredicted by more than a factor of 2. Monoterpene VOCs and SOCs are underestimated at both sites. Isoprene is underestimated at Pasadena and overpredicted at Bakersfield and isoprene SOC mass is underestimated at both sites. Systematic model underestimates in SOC mass coupled with reasonable skill (typically within a factor of 2) in predicting hydroxyl radical and VOC gas-phase precursors suggest error(s) in the parameterization of semivolatile gases to form SOC. Yield values (α) applied to semivolatile partitioning species were increased by a factor of 4 in CMAQ for a sensitivity simulation, taking into account recent findings of underestimated yields in chamber experiments due to gas wall losses. This sensitivity resulted in improved model performance for PM2.5 organic carbon at both field study locations and at routine monitor network sites in California. Modeled percent secondary contribution (22% at Pasadena) becomes closer to ambient-based estimates but still contains a higher primary fraction than observed.
All Science Journal Classification (ASJC) codes
- Atmospheric Science