Inmaculada Palomino

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.

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.

Application of the MELPUFF model to air quality assessment in the industrial area of Huelva (Spain)

The mesoscale Lagrangian puff dispersion model (MELPUFF) has been used in air quality assessment in the area of Huelva. The Huelva area is highly industrialised and it is located on the Atlantic coast of southern Spain. The MELPUFF model was applied to obtain monthly-averaged distributions of SO2 and number of probable exceedances per month of the EU air quality standards. The study period corresponds to one year from March 1999 to February 2000. Results of monthly averaged concentrations of pollutants computed by the model were compared with the measured data at the air quality network stations.

Power Plant Plume Dispersion Study in a Coastal Site with Complex Terrain

The city of Castellon (~ 00 02’ W; 39 59’ N) is located approximately 5 km inland from the East Spanish coast in the northern reaches of the Mijares River flood plain (Fig. 1). The Castellon power plant is located at the shoreline, SE of the city, within the industrial area. It is oil fired and has two 540 MW units each feeding a 150 m stack. The plant operates intermittently either for peak loading or backup purposes. Its environmental problems are associated with start-up or boiler purging operations when sub-millimetre size, acidic, particles are emitted. Except for the oil refinery, which borders it at the south, and the sea to the East, the plant is surrounded by orange groves where some fruit skin damages have been documented. One of the main objectives of this project is to develop a forecast procedure to enable the plant operator to proceed with purging operations when the flow at plume level is out to sea.

Modelling Arsenic, Lead, Cadmium and Nickel Ambient Air Concentrations in Spain

Ambient air levels of metals are included in the EC air quality standards due to their impact on human health and ecosystems. European directives 2008/50/CE and 2004/107/CE regulate lead, arsenic, cadmium, mercury and nickel ambient air levels. Air quality models constitute a powerful tool to understand tropospheric dynamics and to assign concentration values to areas where no measurement is available. For this reason models are currently being extensively applied in a variety of air quality applications. Metals have been more recently included in air quality models, and until now just studies showing results for some of them (mainly lead, cadmium and mercury) may be found in the literature. An attempt to simulate ambient air levels of arsenic, cadmium, lead and nickel in Spain has been done, by using the CHIMERE chemistry-transport model. An evaluation of model predictions was performed by comparing daily simulated values with observations in a set of monitoring sites for 2007. In overall, the model reproduces the temporal observed behavior, and it is able to simulate the high values measured in specific areas, such as those for lead and cadmium in Northern Spain. More refinement in emission database joined to higher-resolution simulations are required to better simulate this type of pollutants.

Combination of measured and modelling data in air quality assessment in Spain

This paper describes a methodology to combine measurements from air quality stations and estimates from the CHIMERE model for air quality assessment in Spain. The methodology consists of using linear regression and kriging interpolation to correct the model results, improving the fit to the observations. It was separately applied to rural and urban conditions, giving rise to maps for each case, which were then combined by taking into account the distribution of rural and urban areas in the domain. The results for several pollutants and the methodology’s application to air quality assessment in Spain are shown and discussed.

Evaluating the Impact of Resolution on the Predictions of an Air Quality Model over Madrid Area (Spain)

Modelling has become a very useful tool in air quality management. The accurate prediction of air quality using numerical models involves correctly simulating both the meteorology and chemical processes. Resolution plays an essential role in the quality of model predictions. Choosing an appropriate resolution is important to obtain good air quality forecasts. In this paper the influence of four different model resolutions on model predictions has been analyzed over the Madrid area for a summer period in 2004. The comparison between model results and observations using traditional evaluation statistics for some pollutants indicate that a significant improvement is found when comparing the coarsest domains, but it is much lower or inexistent for the finest domains. A spectral analysis of a topographic profile crossing the area and the evaluation of predicted meteorological parameters, such as wind speed and temperature, suggests that transitioning from 36-to 19-km grid spacing allows the definition of the major mesoscale topographic features and therefore, the atmospheric circulations. A better behaviour of pollutant predictions should be related to an improvement of meteorological predictions in terms of the parameterizations involved in the meteorological model and the input data, such as land use information. Also the use of more accurate emissions is needed to improve the traditional objective verification scores.