Critical load exceedances for North America and Europe using an ensemble of models and an investigation of causes of environmental impact estimate variability: an AQMEII4 study

Abstract. Exceedances of critical loads for deposition of sulfur (S) and nitrogen (N) in different ecosystems were estimated using European and North American ensembles of air quality models, under the Air Quality Model Evaluation International Initiative Phase 4 (AQMEII4), to identify where the risk of ecosystem harm is expected to occur based on model deposition estimates. The ensembles were driven by common emissions and lateral boundary condition inputs. Model output was regridded to common North American and European 0.125° resolution domains, which were then used to calculate critical load exceedances. Targeted deposition diagnostics implemented in AQMEII4 allowed for an unprecedented level of post-simulation analysis to be carried out and facilitated the identification of specific causes of model-to-model variability in critical load exceedance estimates. Datasets for North American critical loads for acidity for forest soil water and aquatic ecosystems were created for this analysis. These were combined with the ensemble deposition predictions to show a substantial decrease in the area and number of locations in exceedance between 2010 and 2016 (forest soils: 13.2 % to 6.1 %; aquatic ecosystems: 21.2 % to 11.4 %). All models agreed regarding the direction of the ensemble exceedance change between 2010 and 2016. The North American ensemble also predicted a decrease in both the severity and total area in exceedance between the years 2010 and 2016 for eutrophication-impacted ecosystems in the USA (sensitive epiphytic lichen: 81.5 % to 75.8 %). The exceedances for herbaceous-community richness also decreased between 2010 and 2016, from 13.9 % to 3.9 %. The uncertainty associated with the North American eutrophication results is high; there were sharp differences between the models in predictions of both total N deposition and the change in N deposition and hence in the predicted eutrophication exceedances between the 2 years. The European ensemble was used to predict relatively static exceedances of critical loads with respect to acidification (4.48 % to 4.32 % from 2009 to 2010), while eutrophication exceedance increased slightly (60.2 % to 62.2 %). While most models showed the same changes in critical load exceedances as the ensemble between the 2 years, the spatial extent and magnitude of exceedances varied significantly between the models. The reasons for this variation were examined in detail by first ranking the relative contribution of different sources of sulfur and nitrogen deposition in terms of deposited mass and model-to-model variability in that deposited mass, followed by their analysis using AQMEII4 diagnostics, along with evaluation of the most recent literature. All models in both the North American and European ensembles had net annual negative biases with respect to the observed wet deposition of sulfate, nitrate, and ammonium. Diagnostics and recent literature suggest that this bias may stem from insufficient cloud scavenging of aerosols and gases and may be improved through the incorporation of multiphase hydrometeor scavenging within the modelling frameworks. The inability of North American models to predict the timing of the seasonal peak in wet ammonium ion deposition (observed maximum was in April, while all models predicted a June maximum) may also relate to the need for multiphase hydrometeor scavenging (absence of snow scavenging in all models employed here). High variability in the relative importance of particulate sulfate, nitrate, and ammonium deposition fluxes between models was linked to the use of updated particle dry-deposition parameterizations in some models. However, recent literature and the further development of some of the models within the ensemble suggest these particulate biases may also be ameliorated via the incorporation of multiphase hydrometeor scavenging. Annual sulfur and nitrogen deposition prediction variability was linked to SO2 and HNO3 dry-deposition parameterizations, and diagnostic analysis showed that the cuticle and soil deposition pathways dominate the deposition mass flux of these species. Further work improving parameterizations for these deposition pathways should reduce variability in model acidifying-gas deposition estimates. The absence of base cation chemistry in some models was shown to be a major factor in positive biases in fine-mode particulate ammonium and particle nitrate concentrations. Models employing ammonia bidirectional fluxes had both the largest- and the smallest-magnitude biases, depending on the model and bidirectional flux algorithm employed. A careful analysis of bidirectional flux models suggests that those with poor NH3 performance may underestimate the extent of NH3 emission fluxes from forested areas. Model–measurement fusion in the form of a simple bias correction was applied to the 2016 critical loads. This generally reduced variability between models. However, the bias correction exercise illustrated the need for observations which close the sulfur and nitrogen budgets in carrying out model–measurement fusion. Chemical transformations between different forms of sulfur and nitrogen in the atmosphere sometimes result in compensating biases in the resulting total sulfur and nitrogen deposition flux fields. If model–measurement fusion is only applied to some but not all of the fields contributing to the total deposition of sulfur or nitrogen, the corrections may result in greater variability between models or less accurate results for an ensemble of models, for those cases where an unobserved or unused observed component contributes significantly to predicted total deposition. Based on these results, an increased process-research focus is therefore recommended for the following model processes and for observations which may assist in model evaluation and improvement: multiphase hydrometeor scavenging combined with updated particle dry-deposition, cuticle, and soil deposition pathway algorithms for acidifying gases, base cation chemistry and emissions, and NH3 bidirectional fluxes. Comparisons with satellite observations suggest that oceanic NH3 emission sources should be included in regional chemical transport models. The choice of a land use database employed within any given model was shown to significantly influence deposition totals in several instances, and employing a common land use database across chemical transport models and critical load calculations is recommended for future work.