The development and application of chemistry transport models has a long
tradition. Within the Netherlands the LOTOS–EUROS model has been developed by
a consortium of institutes, after combining its independently developed
predecessors in 2005. Recently, version 2.0 of the model was released as an
open-source version. This paper presents the curriculum vitae of the model
system, describing the model's history, model philosophy, basic features and a
validation with EMEP stations for the new benchmark year 2012, and presents
cases with the model's most recent and key developments. By setting the model
developments in context and providing an outlook for directions for further
development, the paper goes beyond the common model description. With an
origin in ozone and sulfur modelling for the models LOTOS and EUROS, the
application areas were gradually extended with persistent organic pollutants,
reactive nitrogen, and primary and secondary particulate matter. After the
combination of the models to LOTOS–EUROS in 2005, the model was further
developed to include new source parametrizations (e.g. road resuspension,
desert dust, wildfires), applied for operational smog forecasts in the
Netherlands and Europe, and has been used for emission scenarios, source
apportionment, and long-term hindcast and climate change scenarios.
LOTOS–EUROS has been a front-runner in data assimilation of ground-based and
satellite observations and has participated in many model intercomparison
studies. The model is no longer confined to applications over Europe but is
also applied to other regions of the world, e.g. China. The increasing
interaction with emission experts has also contributed to the improvement of
the model's performance. The philosophy for model development has always been
to use knowledge that is state of the art and proven, to keep a good balance
in the level of detail of process description and accuracy of input and
output, and to keep a good record on the effect of model changes using
benchmarking and validation. The performance of v2.0 with respect to EMEP
observations is good, with spatial correlations around 0.8 or higher for
concentrations and wet deposition. Temporal correlations are around 0.5 or
higher. Recent innovative applications include source apportionment and data
assimilation, particle number modelling, and energy transition scenarios
including corresponding land use changes as well as Saharan dust forecasting.
Future developments would enable more flexibility with respect to model
horizontal and vertical resolution and further detailing of model input data.
This includes the use of different sources of land use characterization
(roughness length and vegetation), detailing of emissions in space and time,
and efficient coupling to meteorology from different meteorological models