The second phase of the Air Quality Model Evaluation International Initiative (AQMEII) brought together seventeen modeling groups from Europe and North America, running eight operational online-coupled air quality models over Europe and North America using common emissions and boundary conditions. The simulated annual, seasonal, continental and sub-regional particulate matter (PM) surface concentrations for the year 2010 have been evaluated against a large observational database from different measurement networks operating in Europe and North America. The results show a systematic underestimation for all models in almost all seasons and sub-regions, with the largest underestimations for the Mediterranean region. The rural PM10 concentrations over Europe are underestimated by all models by up to 66% while the underestimations are much larger for the urban PM10 concentrations (up to 75%). On the other hand, there are overestimations in PM2.5 levels suggesting that the large underestimations in the PM10 levels can be attributed to the natural dust emissions. Over North America, there is a general underestimation in PM10 in all seasons and sub-regions by up to ∼90% due mainly to the underpredictions in soil dust. SO42− levels over EU are underestimated by majority of the models while NO3− levels are largely overestimated, particularly in east and south Europe. NH4+ levels are also underestimated largely in south Europe. SO4 levels over North America are particularly overestimated over the western US that is characterized by large anthropogenic emissions while the eastern USA is characterized by underestimated SO4 levels by the majority of the models. Daytime AOD levels at 555 nm is simulated within the 50% error range over both continents with differences attributed to differences in concentrations of the relevant species as well as in approaches in estimating the AOD. Results show that the simulated dry deposition can lead to substantial differences among the models. Overall, the results show that representation of dust and sea-salt emissions can largely impact the simulated PM concentrations and that there are still major challenges and uncertainties in simulating the PM levels.