Molecular markers in ambient organic aerosol (OA) provide highly specific source information. Their traditional quantification is based on offline analysis of filter samples, and the coarse time resolution and labor-intensive nature hugely limit the utility of the tracer data. In this study, hourly organic molecular markers in fine particulate matter were measured using a recently commercialized thermal desorption aerosol gas chromatography− mass spectrometry (TAG) technique at an urban location in Shanghai, China during a three-week campaign from 9 November to 3 December, 2018. Selected primary OA molecular markers, including anhydrosugars, fatty acids, aromatic acids, and polycyclic aromatic hydrocarbons (PAHs), were examined in detail. Their diurnal variations showed characteristic features representing the corresponding emission source activities. For example, stearic acid showed a clear peak around 7 pm, in accordance with the enhanced cooking activities during mealtime. Diagnostic ratios of related makers of different reactivities provided unique information in uncovering the source information and tracking evolution of the OA in the atmosphere, for example, ratios of levoglucosan to its isomers and K + identified crop residue burning as the major form of biomass burning (BB). Ratios of unsaturated and saturated fatty acids gave unambiguous indication of atmospheric degradation of unsaturated fatty acids after emissions. Oleic acid to stearic acid ratios in ambient data (0.83 ± 0.54) were lower than those in the source profiles (1.2−6.5). Furthermore, the oleic acid to stearic acid ratio was found to be highly correlated with O/C ratios (R p : −0.66), suggesting the possible utility of oleic acid as a model compound to examine the heterogeneous reaction of cooking-related OA. PAH ratio−ratio plots helped identify varying influences of major combustion sources associated with air masses of different origins, revealing that BB and coal combustion were dominant under the influence of long-range transport air mass, while vehicle emissions were dominant under local/median-range air mass influence. This study demonstrated the utility of high time-resolution organic markers in capturing the dynamic change of source emissions and atmospheric aging, providing observational evidence to support their use in source apportionment.

This study evaluates the impact of atmospheric observations from the Tropospheric Airborne Meteorological Data Reporting (TAMDAR) observing system on numerical weather prediction of hurricane Ike (2008) using three-dimensional data assimilation system for the Weather Research and Forecast (WRF) model (WRF 3D-Var). The TAMDAR data assimilation capability is added to WRF 3D-Var by incorporating the TAMDAR observation operator and corresponding observation processing procedure. Two 6-h cycling data assimilation and forecast experiments are conducted. Track and intensity forecasts are verified against the best track data from the National Hurricane Center.The results show that, on average, assimilating TAMDAR observations has a positive impact on the forecasts of hurricane Ike. The TAMDAR data assimilation reduces the track errors by about 30 km for 72-h forecasts. Improvements in intensity forecasts are also seen after four 6-h data assimilation cycles. Diagnostics show that assimilation of TAMDAR data improves subtropical ridge and steering flow in regions along Ike's track, resulting in better forecasts.