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Aerosol simulations in chemistry transport models (CTMs) still suffer fromnumerous uncertainties, and diagnostic evaluations are required to point outmajor error sources. This paper presents an original approach to evaluateCTMs based on local and imported contributions in a large megacity ratherthan urban background concentrations. The study is applied to the CHIMEREmodel in the Paris region (France) and considers the fine particulate matter(PM2.5) and its main chemical constituents (elemental and organiccarbon, nitrate, sulfate and ammonium), for which daily measurements areavailable during a whole year at various stations (PARTICULES project).Back-trajectory data are used to locate the upwind station, from which theconcentration is identified as the import, the local production beingdeduced from the urban concentration by subtraction. Uncertainties on thesecontributions are quantified. Small biases in urban background PM2.5simulations (bias of +16%) hide significant error compensations betweenlocal and advected contributions, as well as in PM2.5 chemicalcompounds. In particular, winter time organic matter (OM) imports appear stronglyunderestimated while local OM and elemental carbon (EC) production is overestimated all alongthe year. Erroneous continental wood burning emissions and missing secondary organic aerosol (SOA)pathways may explain errors on advected OM, while the carbonaceous compounds is likely to be related to errors in emissions and dynamics.A statistically significant local formation of nitrate is also highlightedfrom observations, but missed by the model. Together with the overestimationof nitrate imports, it leads to a bias of +51% on the local PM2.5contribution. Such an evaluation finally gives more detailed insights onmajor gaps in current CTMs on which future efforts are needed

geoscientific model development

A novel model evaluation approach focusing on local and advected contributions to urban PM&amp;lt;sub&amp;gt;2.5&amp;lt;/sub&amp;gt; levels – application to Paris, France