An ensemble investigation of the causes for regional air-quality model critical load exceedances prediction variability in European and North American domains using diagnostics from Phase 4 of the Air Quality Model Evaluation International Initiative

We summarize tentative findings from multi air quality model ensembles for the years 2009 and 2010 in Europe (EU), and 2010 and 2016 in North America (NA), under AQMEII-4.  The model predictions of sulphur and nitrogen deposition were used to estimate exceedances of critical loads for acidification and eutrophication, to show the extent to which the ensemble members agree in the magnitude and the trend of ecologically meaningful impacts.  Model exceedance variability was analyzed using AQMEII-4 diagnostics.  Evaluation against concentration and wet deposition observations, coupled with these diagnostics, identified specific process representations as the causes for variability between model predictions and for reduced model performance. 

All models predicted reductions in ecosystem acidification impacts in North America between the years 2010 and 2016, in accord with SO₂ emissions reduction legislation which started in 2010 (SO₂ SIP) However, all models in EU and NA domains had net negative biases for wet deposition of sulphur and nitrogen relative to observations.  The wet S deposition average mean bias for the NA ensemble was -0.17 eq ha^-1 d^-1, and for the EU ensemble -1.15 eq ha^-1 d^-1.  The NA daily wet deposition average mean bias for NH₄⁺ was -0.37 eq ha^-1d^-1; EU -1.19 eq ha^-1 d^-1.  The daily NA wet NO₃^- deposition average mean bias was -0.24 eq ha^-1d^-1; EU -0.69 eq ha^-1 d^-1.  The members of the ensemble diverged (factor of 10) in their North American predictions for N_dep and consequently their eutrophication exceedances. The models with the highest eutrophication predictions also predicted the highest levels of gas-phase ammonia dry deposition (standard deviation of ammonia dry deposition flux across ensemble members was larger than the ensemble average).  These models also had negative biases of predicted ammonia concentrations; average mean biases of -0.63 (satellite NH₃) and -0.85 ppbv (surface NH₃) compared to ensemble averages of -0.30 and -0.34 ppbv.  Diagnostics showed that these differences resulted from the manner in which bidirectional ammonia fluxes were parameterized within these models.  The second largest source of NA eutrophication prediction variability were models with positive biases in particulate ammonium and nitrate concentrations, and higher particle nitrogen deposition levels ( particle ammonium concentration bias +0.35 ug m^-3; ensemble bias +0.15 ug m^-3).   We believe two factors may have led to these latter overestimates:  higher levels of fine mode particle nitrate formation compared to other models (due to the use of an inorganic heterogeneous chemistry algorithm which did not take base cation chemistry into account), and updates to particle dry deposition velocities carried out in the absence of concurrent updates to wet scavenging algorithms. 

The relative importance of dry gas, dry particulate, and wet deposition towards total sulphur and nitrogen deposition totals differed between EU and North American domains, though all models had negative biases in wet deposition as noted above.  Parallel and subsequent work suggests that multiphase hydrometeor scavenging may improve model wet deposition performance. 

An increased research focus is recommended for four model processes: multiphase hydrometeor scavenging, ammonia bidirectional fluxes, base cation chemistry and emissions, and particle dry deposition.