@article {37889, title = {Assessment of the sensitivity of model responses to urban emission changes in support of emission reduction strategies}, journal = {Air Quality, Atmosphere \& Health}, year = {2023}, abstract = {

The sensitivity of air quality model responses to modifications in input data (e.g. emissions, meteorology and boundary conditions)
or model configurations is recognized as an important issue for air quality modelling applications in support of air quality
plans. In the framework of FAIRMODE (Forum of Air Quality Modelling in Europe, https:// fairm ode. jrc. ec. europa. eu/) a
dedicated air quality modelling exercise has been designed to address this issue. The main goal was to evaluate the magnitude
and variability of air quality model responses when studying emission scenarios/projections by assessing the changes of model
output in response to emission changes. This work is based on several air quality models that are used to support model users
and developers, and, consequently, policy makers. We present the FAIRMODE exercise and the participating models, and
provide an analysis of the variability of O3
and PM concentrations due to emission reduction scenarios. The key novel feature,
in comparison with other exercises, is that emission reduction strategies in the present work are applied and evaluated at urban
scale over a large number of cities using new indicators such as the absolute potential, the relative potential and the absolute
potency. The results show that there is a larger variability of concentration changes between models, when the emission reduction
scenarios are applied, than for their respective baseline absolute concentrations. For ozone, the variability between models
of absolute baseline concentrations is below 10\%, while the variability of concentration changes (when emissions are similarly
perturbed) exceeds, in some instances 100\% or higher during episodes. Combined emission reductions are usually more efficient
than the sum of single precursor emission reductions both for O3
and PM. In particular for ozone, model responses, in terms of
linearity and additivity, show a clear impact of non-linear chemistry processes. This analysis gives an insight into the impact of
model{\textquoteright} sensitivity to emission reductions that may be considered when designing air quality plans and paves the way of more
in-depth analysis to disentangle the role of emissions from model formulation for present and future air quality assessments.

}, url = {https://link.springer.com/article/10.1007/s11869-023-01469-z}, author = {Bessagnet, B.,, and Cuvelier, K. and De Meij, A. and Monteiro, A. and Pisoni, E. and Thunis, P. and Violaris, A. and Kushta, J. and Denby, B.R. and Mu, Q. and W{\ae}rsted, E.G. and Vivanco, M.G. and Theobald, M.R. and Gil, V. and Sokhi, R.S. and Momoh, K. and Alyuz, U. and VPM, R. and Kumar, S. and Bossioli, E. and Methymaki, G. and Brzoja, D. and Mili{\'c}, V. and A, Papi, and Pennel, R. and Mailler, S., and Menut, L., and Briganti, G., and Mircea, M., and Flandorfer, C., and Baumann-Stanzer, K., and Hutsem{\'e}kers, V., and Trimpeneers, E.} }