Paolo Tuccella

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.

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.

Local Arctic air pollution: Sources and impacts

Local emissions of Arctic air pollutants and their impacts on climate, ecosystems and health are poorly understood. Future increases due to Arctic warming or economic drivers may put additional pressures on the fragile Arctic environment already affected by mid-latitude air pollution. Aircraft data were collected, for the first time, downwind of shipping and petroleum extraction facilities in the European Arctic. Data analysis reveals discrepancies compared to commonly used emission inventories, highlighting missing emissions (e.g. drilling rigs) and the intermittent nature of certain emissions (e.g. flaring, shipping). Present-day shipping/petroleum extraction emissions already appear to be impacting pollutant (ozone, aerosols) levels along the Norwegian coast and are estimated to cool and warm the Arctic climate, respectively. Future increases in shipping may lead to short-term (long-term) warming (cooling) due to reduced sulphur (CO2) emissions, and be detrimental to regional air quality (ozone). Further quantification of local Arctic emission impacts is needed.

Wildfires impact on surface nitrogen oxides and ozone in Central Italy

A summer campaign in Central Italy was carried out to study the impact of fire emissions on the mixing ratios of surface trace gases. Observations with a selective and sensitive instrument that uses the laser induced fluorescence technique for direct measurements of nitrogen dioxide (NO2), show a significant increase of NO2 mixing ratios, in the evening, when a fire plume reached the observations site. The increase of NO2 mixing ratios is well correlated (R=0.83) with that of particulate matter (PM), which is one of the primary product of forest and grassland fires. The tight correlation between NO2 and PM is used to improve the performance of a statistical regression model to simulate the observed O3, and to highlight the effect of fire emissions on the O3 mixing ratios. The statistical regression model of O3 improves in terms of performance (bias reduction of 77% and agreement enhancement of 10% for slope and correlation coefficient) when PM2.5 is included as additional input and proxy of the fire emissions among the usual input parameters (meteorological data and NO2 mixing ratios). A case study, comparing observed and modeled O3 in different days (with and without fire plume), suggests an impact of fire emissions on the O3 mixing ratios of about 10%.

On the Interplay Between Upper and Ground Levels Dynamics and Chemistry in Determining the Surface Aerosol Budget

We use the WRF/Chem model to interpret observations of the aerosol concentration and its chemical composition both at surface level and along vertical profiles performed during an intensive campaign in July 2007 in Milan urban area. The model is added with a new diagnostic for aerosol budget analysis, building on that available for gas species, in order to study the contribution of upper levels processes on the aerosol formation at ground level. The analysis illustrates a quite variegated evolution of budget terms, which we found to depend strongly on the hour of the day, the vertical level, the aerosol compound, and the aerosol size. Primary components are generally emitted near the ground and rapidly transported by turbulent motions to the upper levels, where they gradually disperse and age. For some secondary components, such as nitrate, we calculate a net chemical destruction in the bottom layers, as opposed to a net chemical production higher in the boundary layer, which supply new material to ground level aerosol through turbulent mixing.

Modeling of Aerosol Indirect Effects with WRF/Chem over Europe

WRF/Chem has been updated in order to simulate the aerosol indirect effects using a new parameterization for production of secondary organic aerosol. The model has been evaluated over North Sea among the ATR-42 aircraft measurements of aerosol and cloud issued in frame European Integrated project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI). WRF/Chem tends to overpredict the number of condensation nuclei. Simulated liquid water content shows a bias of +15 %. Predicted cloud droplet number concentration is overestimated and radius effective droplet is underestimated.

Toward a New Chemical Mechanism in WRF/Chem for Direct and Indirect Aerosol Effects: A Focus on the Carbonaceous Aerosols

An updated version of Weather Research and Forecasting/Chemistry model (WRF/Chem) with a new parameterization for the secondary organic aerosol (SOA) production based on the Volatility Basis Set (VBS) is evaluated over Europe in May–June 2003. Results are compared against surface observations issued from the EC/OC 2002–2003 campaign of European Monitoring and Evaluation Program (EMEP). WRF/Chem underestimates the elemental carbon (EC) and the organic aerosol mass (OA) by −7 and −38 %, respectively. The analysis of OA: EC ratio reveals that the under prediction may be mainly explained by a misrepresentation of anthropogenic emissions of carbonaceous aerosols due to the coarse resolution of the inventory. The modeled concentration of OA constituent is nearly constant during the day. The predicted SOA/OA ratio has a value of ∼80 %. The biogenic SOA (BSOA) are 30 % of the total OA mass. Dry deposition velocity of Volatile Organic Compounds (VOC) oxidation products is a source of uncertain in the SOA budget.

Aerosol Simulation with Fully Coupled “Online” Meteorology-Chemistry Model WRF/Chem over Europe: Preliminary Results

The new generation fully coupled “online” WRF/Chem model is implemented over Europe on a coarse grid and validated against ground-based observations of meteorological variables and atmospheric composition. Anthropogenic emissions are derived from the EMEP database. We studied its sensitivity to “Dudhia” and “Goddard” short waves radiation schemes. The model satisfactory reproduces the observed meteorological fields, particularly with the Goddard scheme. For chemical variable, they are not much difference between the two scheme. Ozone (O3) daily maximum is reproduced with a correlation of 0.81 and an root mean square error (RMSE) of 23 μg/m3. Nitrogen dioxide (NO2) is overestimated by a factor of 2, and reproduced with a correlation of 0.47. Particulate matter shows poor correlation with observations, however the model captures the magnitude of PM2.5 concentrations (bias −10%, RMSE 7 μg/m3). Simulated PM10 is affected by a too strong local dust source over dry areas.