Corrigendum to "A novel model evaluation approach focusing on local and advected contributions to urban PM<sub>2.5</sub> levels – application to Paris, France" published in Geosci. Model Dev., 7, 1483–1505, 2014

Abstract

Due to an oversight in the production process, an essential word (overestimation) was left out of the abstract. The correct version of the abstract can be seen below. Abstract. Aerosol simulations in chemistry transport mod- els (CTMs) still suffer from numerous uncertainties, and di- agnostic evaluations are required to point out major error sources. This paper presents an original approach to evaluate CTMs based on local and imported contributions in a large megacity rather than urban background concentrations. The study is applied to the CHIMERE model in the Paris region (France) and considers the fine particulate matter (PM 2.5) and its main chemical constituents (elemental and organic carbon, nitrate, sulfate and ammonium), for which daily mea- surements are available during a whole year at various sta- tions (PARTICULES project). Back-trajectory data are used to locate the upwind station, from which the concentration is identified as the import, the local production being de- duced from the urban concentration by subtraction. Uncer- tainties on these contributions are quantified. Small biases in urban background PM2.5 simulations (bias of +16 %) hide significant error compensations between local and advected contributions, as well as in PM2.5 chemical compounds. In particular, winter time organic matter (OM) imports appear strongly underestimated while local OM and elemental car- bon (EC) production is overestimated all along the year. Er- roneous continental wood burning emissions and missing secondary organic aerosol (SOA) pathways may explain er- rors on advected OM, while the carbonaceous compounds overestimation is likely to be related to errors in emissions and dynamics. A statistically significant local formation of nitrate is also highlighted from observations, but missed by the model. Together with the overestimation of nitrate im- ports, it leads to a bias of +51 % on the local PM2.5 contribu- tion. Such an evaluation finally gives more detailed insights on major gaps in current CTMs on which future efforts are needed.