Marta G. Vivanco

Multi-year assessment of photochemical air quality simulation over Spain

Ground-level ozone concentrations in the atmospheric boundary layer over Spain are still exceeding thresholds established in EU legislation to protect human health and prevent damage to ecosystems. The increasing role that air quality models play in air quality management requires comparison between model results and previous observations in order to determine the capacity of the model to reproduce past events. The CHIMERE chemistry-transport model has been used by several research groups to estimate air pollutant concentrations in different European countries. An evaluation of the model performance of the CHIMERE air quality model was carried out for the spring and summer periods of 2003-2005 in Spain, using EMEP emissions. This evaluation has demonstrated a fair agreement between observed and modelled ozone values for background stations, with a mean normalized absolute error below 15% for rural background air quality sites. This value lays inside the range proposed in EPAs guideline for an acceptable level of model performance. In spite of this acceptable model performance, further studies need to be carried out to explain some underestimation found over Madrid surroundings.

Modelling the influence of peri-urban trees in the air quality of Madrid region (Spain)

Tropospheric ozone (O(3)) is considered one of the most important air pollutants affecting human health. The role of peri-urban vegetation in modifying O(3) concentrations has been analyzed in the Madrid region (Spain) using the V200603par-rc1 version of the CHIMERE air quality model. The 3.7 version of the MM5 meteorological model was used to provide meteorological input data to the CHIMERE. The emissions were derived from the EMEP database for 2003. Land use data and the stomatal conductance model included in CHIMERE were modified according to the latest information available for the study area. Two cases were considered for the period April-September 2003: (1) actual land use and (2) a fictitious scenario where El Pardo peri-urban forest was converted to bare-soil. The results show that El Pardo forest constitutes a sink of O(3) since removing this green area increased O(3) levels over the modified area and over down-wind surrounding areas.

Nitrogen deposition alters nitrogen cycling and reduces soil carbon content in low-productivity semiarid Mediterranean ecosystems

Anthropogenic N deposition poses a threat to European Mediterranean ecosystems. We combined data from an extant N deposition gradient (4.3-7.3 kg N ha⁻¹ yr⁻¹) from semiarid areas of Spain and a field experiment in central Spain to evaluate N deposition effects on soil fertility, function and cyanobacteria community. Soil organic N did not increase along the extant gradient. Nitrogen fixation decreased along existing and experimental N deposition gradients, a result possibly related to compositional shifts in soil cyanobacteria community. Net ammonification and nitrification (which dominated N-mineralization) were reduced and increased, respectively, by N fertilization, suggesting alterations in the N cycle. Soil organic C content, C:N ratios and the activity of β-glucosidase decreased along the extant gradient in most locations. Our results suggest that semiarid soils in low-productivity sites are unable to store additional N inputs, and that are also unable to mitigate increasing C emissions when experiencing increased N deposition.

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.

Analysis of the spatial representativeness of rural background monitoring stations in Spain

The spatial representativeness of rural background air quality stations was estimated using the spatial distribution of air pollutants computed by the combinations of the results of annual WRF–CHIMERE model simulations and data measured at stations of the Iberian Peninsula in 2008, 2009 and 2010 for NO2, SO2, O3 and PM10. The advantage of using validated models combined with measurements is that effects of the emission sources distribution and atmospheric pollutant processes are both taken into account and that the model bias and errors are corrected. This methodology provides a considerably realistic spatial view of air pollutant concentration distribution around the rural background stations. The criteria for delimiting the representativeness area are based on the assumptions that: (1) concentration does not differ by more than a certain percentage from the concentration at the station; and (2) the air quality in the station and in the representativeness area should have the same status regarding the legal standard. The results showed that there is a large variability in the size and shape of the representativeness area of rural background stations in Spain, also depending on the pollutant and the limit or target value. In addition, the interannual variability of the representativeness areas, station redundancy and network coverage have been analyzed. A high interannual variability of spatial representativeness areas was found, except for daily and hourly SO2, hourly O3 and annual NO2. Roughly 50% of rural background stations measured O3 overlap with other stations in at least 80% of their spatial representativeness area, denoting a high percentage of station redundancy. Concerning network coverage, there are zones that are not covered by stations, the worst coverage being for PM10. The proposed methodology seems to be useful for determining the spatial representativeness of air quality stations.

Influence of Model Resolution on Ozone Predictions over Madrid Area (Spain)

Modeling has become a very useful tool in air quality management. The use of an air quality model requires comparison between model results and previous observations in order to determine the capacity of the model to reproduce air pollution episodes. In this paper the influence of three different model resolutions on model predictions has been analyzed over Madrid area for 2004. A lower mean normalized absolute error was found for the highest resolution domain, when comparing hourly-predicted ozone to 2004 observations. The improvement of model predictions is more clearly observed for NO 2 . When considering an episode occurred in July, 2004, this improvement in model performance is significantly reduced. For this episode, meteorological evaluation indicates that temperature and speed predictions for the coarsest domain present worse agreement to observations than those for the other two domains.

An Evaluation of the Performance of the CHIMERE Model over Spain Using Meteorology from MM5 and WRF Models

The presence of high pollution levels in the atmosphere can produce damages to human health and ecosystems. Because of this reason, the prediction of air pollutant concentration is important to prevent any potential damage. Chemistry-transport models constitute a useful tool to quantify the presence of pollutants in the atmosphere. Input information, such as meteorology and emissions, has a strong influence on model results. Many research activities are focused on trying to reduce errors affecting input information. In this paper we have applied the CHIMERE photochemical model to simulate ozone, NO2 and SO2 in Spain for two sets of meteorological fields obtained with the MM5 and WRF meteorological models. An evaluation of the performance of the CHIMERE model for both meteorological data sets is presented. Very similar air pollutant concentrations were found for the three pollutants and for the two sets of meteorological information.

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.

SO 2 effect on secondary organic aerosol from a mixture of anthropogenic VOCs: experimental and modelled results

The effect of SO 2 in the photooxidation of a mixture of anthropogenic precursors is studied. Four experiments are carried out in the EUPHORE outdoor chamber, adding different initial SO 2 concentrations in each experiment. The experimental secondary organic aerosol (SOA) obtained in the experiments is compared with the aerosol simulated by two air quality models (CMAQ and CHIMERE) under the same initial conditions. A simplified version of the models is designed in order to consider the closed system of the chamber, where only gas phase chemistry and aerosol formation take place. While the experimental results show a clear increase of the aerosol formed in the presence of increasing SO 2 concentrations, the models do not consider this enhancement in the simulations. The behaviour of the models points out the need of a way to implement this effect on anthropogenic secondary organic aerosol.

Secondary Organic Aerosol Formation from the Oxidation of a Mixture of Organic Gases in a Chamber

Particles suspended in the air can constitute a potential risk for human health and ecosystems (Pope and Dockery, 2006), specially the finest fraction. Although PM10 (particles with a maximum diameter of 10 m) have been included in European directives for a longer time (Directive 1999/30/EC) air quality objectives for finer particles have been just very recently established. For particles with a mean diameter lower than 2.5 m (PM2.5) the UE Directive 2008/50/EC has set a 25 m/m3 threshold for the annual mean concentration. Although the term aerosol includes the particles and the gas in which they are suspended, commonly both terms, particles and aerosols, refer to particles in the atmosphere. A variety of inorganic and organic chemical compounds can be present in the particulate phase. The organic fraction can account for a 20 90 % of the finest fraction, according to some authors, such as (Kanakidou et al., 2005) and, therefore, the knowledge of this fraction is important to prevent human health risks. Both inorganic and organic aerosols can be directly emitted (primary aerosols) or can be formed in the atmosphere as a consequence of multiple physical and chemical processes (secondary aerosols). The presence of secondary organic aerosols (SOA) is specially relevant in urban areas (Zhang et al., 2007). SOA is mainly produced from the oxidation of volatile organic compounds (VOCs), whose products present a sufficiently low volatility to partition into the particle phase according to the gas-particle partitioning theory (Odum et al., 1996) and then nucleate and grow to form organic particles. Presently, SOA is thought to be mainly constituted by polymers, formed through particle phase heterogeneous reactions (Kalberer et al., 2004). Other main components include organic nitrates, such as peroxynitrates and peroxyacylnitrates (Camredon et al., 2007; Kroll and Seinfeld, 2008), and carboxylic acids (Barsanti and Pankow, 2006). In spite of the fact that SOA formation has been the focus of many recent studies, some aspects continue to be not well understood. Simulation chambers represent an ideal vehicle to evaluate SOA formation potential by emitting selected VOCs in the presence of an oxidant under controlled conditions. Many studies in chambers have contributed to increase the knowledge of the oxidation processes of individual organic gases or simple mixes of them. VOCs related to anthropogenic emissions, such as substituted aromatics 12