Development of an on-line source-tagged model for sulfate, nitrate and ammonium: A modeling study for highly polluted periods in Shanghai, China

- We develop an on-line source-tagged model which tracks spatial/temporal sources of sulfate, nitrate and ammonium in one run.
- A new dynamical temporal tagged method is introduced to mark the period when emissions are emitted to the air.
- The evaluation indicates that the source-tagged model system can track sources with reasonable accuracy.

An on-line source-tagged model coupled with an air quality model (Nested Air Quality Prediction Model System, NAQPMS) was applied to estimate source contributions of primary and secondary sulfate, nitrate and ammonium (SNA) during a representative winter period in Shanghai. This source-tagged model system could simultaneously track spatial and temporal sources of SNA, which were apportioned to their respective primary precursors in a simulation run. The results indicate that in the study period, local emissions in Shanghai accounted for over 20% of SNA contributions and that Jiangsu and Shandong were the two major non-local sources. In particular, non-local emissions had higher contributions during recorded pollution periods. This suggests that the transportation of pollutants plays a key role in air pollution in Shanghai. The temporal contributions show that the emissions from the “current day” (emission contribution from the current day during which the model was simulating) contributed 60%-70% of the sulfate and ammonium concentrations but only 10%-20% of the nitrate concentration, while the previous days' contributions increased during the recorded pollution periods. Emissions that were released within three days contributed over 85% averagely for SNA in January 2013. To evaluate the source-tagged model system, the results were compared by sensitivity analysis (emission perturbation of −30%) and backward trajectory analysis. The consistency of the comparison results indicated that the source-tagged model system can track sources of SNA with reasonable accuracy.