Efisio Solazzo

Technical note: Coordination and harmonization of the multi-scale, multi-model activities HTAP2, AQMEII3, and MICS-Asia3: simulations, emission inventories, boundary conditions, and model output formats

We present an overview of the coordinated global numerical modelling experiments performed during 2012–2016 by the Task Force on Hemispheric Transport of Air Pollution (TF HTAP), the regional experiments by the Air Quality Model Evaluation International Initiative (AQMEII) over Europe and North America, and the Model Intercomparison Study for Asia (MICS-Asia). To improve model estimates of the impacts of intercontinental transport of air pollution on climate, ecosystems, and human health and to answer a set of policy-relevant questions, these three initiatives performed emission perturbation modelling experiments consistent across the global, hemispheric, and continental/regional scales. In all three initiatives, model results are extensively compared against monitoring data for a range of variables (meteorological, trace gas concentrations, and aerosol mass and composition) from different measurement platforms (ground measurements, vertical profiles, airborne measurements) collected from a number of sources. Approximately 10 to 25 modelling groups have contributed to each initiative, and model results have been managed centrally through three data hubs maintained by each initiative. Given the organizational complexity of bringing together these three initiatives to address a common set of policy-relevant questions, this publication provides the motivation for the modelling activity, the rationale for specific choices made in the model experiments, and an overview of the organizational structures for both the modelling and the measurements used and analysed in a number of modelling studies in this special issue.

Evaluation and error apportionment of an ensemble of atmospheric chemistry transport modeling systems : Multivariable temporal and spatial breakdown

Through the comparison of several regional-scale chemistry transport modeling systems that simulate meteorology and air quality over the European and North American continents, this study aims at (i) apportioning error to the responsible processes using timescale analysis, (ii) helping to detect causes of model error, and (iii) identifying the processes and temporal scales most urgently requiring dedicated investigations. The analysis is conducted within the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII) and tackles model performance gauging through measurement-to-model comparison, error decomposition, and time series analysis of the models biases for several fields (ozone, CO, SO2, NO, NO2, PM10, PM2.5, wind speed, and temperature). The operational metrics (magnitude of the error, sign of the bias, associativity) provide an overallsense of model strengths and deficiencies, while apportioning the error to its constituent parts (bias, variance, and covariance) can help assess the nature and quality of the error. Each of the error components is analyzed independently and apportioned to specific processes based on the corresponding timescale (long scale, synoptic, diurnal, and intraday) using the error apportionment technique devised in the former phases of AQMEII. The application of the error apportionment method to the AQMEII Phase 3 simulations provides several key insights. In addition to reaffirming the strong impact of model inputs (emission and boundary conditions) and poor representation of the stable boundary layer on model bias, results also highlighted the high interdependencies among meteorological and chemical variables, as well as among their errors. This indicates that the evaluation of air quality model performance for individual pollutants needs to be supported by complementary analysis of meteorological fields and chemical precursors to provide results that are more insightful from a model development perspective. This will require evaluaion methods that are able to frame the impact on error of processes, conditions, and fluxes at the surface. For example, error due to emission and boundary conditions is dominant for primary species (CO, particulate matter (PM)), while errors due to meteorology and chemistry are most relevant to secondary species, such as ozone. Some further aspects emerged whose interpretation requires additional consideration, such as the uniformity of the synoptic error being region- and model-independent, observed for several pollutants; the source of unexplained variance for the diurnal component; and the type of error caused by deposition and at which scale.

The Fukushima-137Cs deposition case study: properties of the multi-model ensemble

In this paper we analyse the properties of an eighteen-member ensemble generated by the combination of five atmospheric dispersion modelling systems and six meteorological data sets. The models have been applied to the total deposition of (137)Cs, following the nuclear accident of the Fukushima power plant in March 2011. Analysis is carried out with the scope of determining whether the ensemble is reliable, sufficiently diverse and if its accuracy and precision can be improved. Although ensemble practice is becoming more and more popular in many geophysical applications, good practice guidelines are missing as to how models should be combined for the ensembles to offer an improvement over single model realisations. We show that the ensemble of models share large portions of bias and variance and make use of several techniques to further show that subsets of models can explain the same amount of variance as the full ensemble mean with the advantage of being poorly correlated, allowing to save computational resources and reduce noise (and thus improving accuracy). We further propose and discuss two methods for selecting subsets of skilful and diverse members, and prove that, in the contingency of the present analysis, their mean outscores the full ensemble mean in terms of both accuracy (error) and precision (variance).

Assessment and economic valuation of air pollution impacts on human health over Europe and the United States as calculated by a multi-model ensemble in the framework of AQMEII3

The impact of air pollution on human health and the associated external costs in Europe and the United States (US) for the year 2010 are modeled by a multi-model ensemble of regional models in the frame of the third phase of the Air Quality Modelling Evaluation International Initiative (AQMEII3). The modeled surface concentrations of O3, CO, SO2 and PM2.5 are used as input to the Economic Valuation of Air Pollution (EVA) system to calculate the resulting health impacts and the associated external costs from each individual model. Along with a base case simulation, additional runs were performed introducing 20 % anthropogenic emission reductions both globally and regionally in Europe, North America and east Asia, as defined by the second phase of the Task Force on Hemispheric Transport of Air Pollution (TF-HTAP2). Health impacts estimated by using concentration inputs from different chemistry–transport models (CTMs) to the EVA system can vary up to a factor of 3 in Europe (12 models) and the United States (3 models). In Europe, the multi-model mean total number of premature deaths (acute and chronic) is calculated to be 414 000, while in the US, it is estimated to be 160 000, in agreement with previous global and regional studies. The economic valuation of these health impacts is calculated to be EUR 300 billion and 145 billion in Europe and the US, respectively. A subset of models that produce the smallest error compared to the surface observations at each time step against an all-model mean ensemble results in increase of health impacts by up to 30 % in Europe, while in the US, the optimal ensemble mean led to a decrease in the calculated health impacts by ~ 11 %. A total of 54 000 and 27 500 premature deaths can be avoided by a 20 % reduction of global anthropogenic emissions in Europe and the US, respectively. A 20 % reduction of North American anthropogenic emissions avoids a total of ~ 1000 premature deaths in Europe and 25 000 total premature deaths in the US. A 20 % decrease of anthropogenic emissions within the European source region avoids a total of 47 000 premature deaths in Europe. Reducing the east Asian anthropogenic emissions by 20 % avoids ~ 2000 total premature deaths in the US. These results show that the domestic anthropogenic emissions make the largest impacts on premature deaths on a continental scale, while foreign sources make a minor contribution to adverse impacts of air pollution.

Evaluation and uncertainty estimation of the impact of air quality modelling on crop yields and premature deaths using a multi-model ensemble

This study promotes the critical use of air pollution modelling results for health and agriculture impacts, with the primary goal of providing more reliable estimates to decision makers. To date, the accuracy of air quality (AQ) models and the effects of model-to-model result variability (which we will refer to as model uncertainty) on impact assessment studies have been often ignored, thus undermining the robustness of the information used in the decision making process and the confidence in the results obtained. A suite of twelve PM2.5 and ozone concentration fields produced by regional-scale chemistry transport Air Quality (AQ) models during the third phase of the Air Quality Model Evaluation International Initiative (AQMEII) has been used to calculate the impact of air pollution on premature deaths and crop yields. An innovative technique is applied to bias-adjust the models to available observations. The model results for ozone and PM2.5 are combined in a multi-model (MM) ensemble, which is used to estimate the damage and economic cost to human health and crop yields, as well as the associated uncertainties. The MM ensemble quantifies directly the uncertainty introduced by AQ models into the air pollution impact assessment chain, while the indirect use of experimental information through a bias adjustment, reduces the uncertainty in the ozone and PM2.5 fields and subsequently the uncertainty of the final impact assessment and cost valuation. The analysis over the European countries analysed in this study shows a mean number of premature deaths due to exposure to PM2.5 and ozone of approximately 370,000 (inter-quantile range between 260,000 and 415,000) and a relative yield loss of approximately 7% to 9% (depending on the exposure metrics used, for wheat and maize together). Furthermore, the results indicate that a reduction in the uncertainty of the modelled ozone by 61% and by 80% (depending on the aggregation metric used) and by 46% for PM2.5, produces a reduction in the uncertainty in premature mortality and crop loss of >60%, and of an equivalent percentage in the final uncertainty of cost valuation, providing decision makers with more accurate estimations for more targeted interventions.

AQMEII 1, 2 and 3: Direct and Indirect Benefits of Community Model Evaluation Exercises

Now that the third model evaluation exercise has been launched, a critical review of the activities performed under the Air Quality Model Evaluation International Initiative (AQMEII) is presented. Attention will be focused on the scientific results obtained by individual modeling groups and by the overall community activity. In particular, we critically review the contributions of AQMEII to operational, diagnostic, dynamic, and probabilistic model evaluation. In addition, the role of community collaborations around coordinated modeling activities will be analyzed. Aspects considered in this analysis are the coverage of multiple topics and research interests, the distribution of the workload among several players, the exploitation of web technology for data exchange, the rationalization of the organization of information, and the exploitation of existing data from emission inventory to niche ad hoc and operational monitoring data. Finally, we discuss the channeling of efforts towards the collaboration with other international activities such as the LTRAP Task Force on Hemispheric Transport of Air Pollutant (TF-HTAP) thus multiplying the benefits for the community.

Air Quality Model Evaluation International Initiative (AQMEII): A Two-Continent Effort for the Evaluation of Regional Air Quality Models

With the endorsement and support from the U.S. Environmental Protection Agency, European Commission, and Environment Canada, a project entitled Air Quality Model Evaluation International Initiative (AQMEII) was launched in 2009 by bringing together scientists from Europe and North America (Rao ST, Galmarini S, Puckett K, Bull Am Meteorol Soc 92:23–30, 2011). Several regional-scale numerical photochemical models were applied over the North American and European domains with 2006 emissions inventory. Several papers resulting from this international collaborative effort were accepted for publication in the AQMEII special issue of Atmospheric Environment. Also, a large 4-D database, assembled by EU Joint Research Centre for the AQMEII project, is now available to all scientists interested in developing innovative model evaluation techniques (Galmarini S, Rao ST, Atmos Environ 45(14):2464, 2011). Having successfully completed the first phase of AQMEII, Phase 2 of AQMEII was launched at the 2011 AQMEII workshop in Chapel Hill, NC, USA to focus on the interactions of air quality and climate change. In Phase 2, coupled meteorology-atmospheric chemistry models will be exercised over the two continents with a common emissions database to assess how well the current generation of coupled regional-scale air quality models can simulate the spatio-temporal variability in the optical and radiative characteristics of atmospheric aerosols and associated feedbacks among aerosols, radiations, clouds, and precipitation. The results from AQMEII Phase 2 would be useful to policy makers for developing effective policies to deal with air pollution and climate change.

Model Evaluation for Surface Concentration of Particulate Matter in Europe and North America in the Context of AQMEII

Ten state-of-the-science regional air quality (AQ) modeling systems have been applied to continental-scale domains in North America and Europe for full-year simulations of 2006 for the Air Quality Model Evaluation International Initiative (AQMEII), whose main goals are model inter-comparison and model evaluation. Model simulations are inter-compared and evaluated with a large set of observations for ground-level particulate matter (PM10 and PM2.5) and its chemical components. Analyses of PM10 time series show a large model underestimation throughout the year. Moreover, a large variability among models in predictions of emissions, deposition, and concentration of PM and its precursors has been found.

Ensemble Modelling of Surface-Level Ozone in Europe and North America for AQMEII

Eleven state-of-the-science regional air quality (AQ) models, exercised by 20 independent groups in Europe and North America, have been assembled for the Air Quality Model Evaluation International Initiative (AQMEII). The modelled ground-level ozone mixing ratios are collectively examined from the ensemble perspective and evaluated against observations from both continents. We aim at creating optimized ensembles in order to capture the data variability while keeping the error low. It is shown that the most commonly used ensemble approach, namely the average over all available members, can be outperformed by subsets of members optimally selected in terms of bias, error, and correlation, independent of the skill of the individual members. A clustering methodology is applied to discriminate among members and to build a skilful ensemble based on model association and data clustering.

The sustainable development of Heathrow Airport: model inter-comparison study

Air quality modelling near airports has received attention due to the impact of emissions from aircrafts near ground level. This work is part of the model inter-comparison study undertaken for the Department of Transport in connection with air quality near Heathrow Airport. Results formed part of a submission to the UK government in July 2006. The Emissions and Dispersion Modelling System (EDMS) was used. Our contribution required the setting up and running of EDMS for Heathrow Airport and its surroundings to simulate the year 2002. NOX, NO2 and PM10 were chosen for the study; these being of particular concern.