Pedro Jiménez-Guerrero

An annual assessment of air quality with the CALIOPE modeling system over Spain.

The CALIOPE project, funded by the Spanish Ministry of the Environment, aims at establishing an air quality forecasting system for Spain. With this goal, CALIOPE modeling system was developed and applied with high resolution (4km×4km, 1h) using the HERMES emission model (including emissions of resuspended particles from paved roads) specifically built up for Spain. The present study provides an evaluation and the assessment of the modeling system, coupling WRF-ARW/HERMES/CMAQ/BSC-DREAM8b for a full-year simulation in 2004 over Spain. The evaluation focuses on the capability of the model to reproduce the temporal and spatial distribution of gas phase species (NO(2), O(3), and SO(2)) and particulate matter (PM10) against ground-based measurements from the Spanish air quality monitoring network. The evaluation of the modeling results on an hourly basis shows a strong dependency of the performance of the model on the type of environment (urban, suburban and rural) and the dominant emission sources (traffic, industrial, and background). The O(3) chemistry is best represented in summer, when mean hourly variability and high peaks are generally well reproduced. The mean normalized error and bias meet the recommendations proposed by the United States Environmental Protection Agency (US-EPA) and the European regulations. Modeled O(3) shows higher performance for urban than for rural stations, especially at traffic stations in large cities, since stations influenced by traffic emissions (i.e., high-NO(x) environments) are better characterized with a more pronounced daily variability. NO(x)/O(3) chemistry is better represented under non-limited-NO(2) regimes. SO(2) is mainly produced from isolated point sources (power generation and transformation industries) which generate large plumes of high SO(2) concentration affecting the air quality on a local to national scale where the meteorological pattern is crucial. The contribution of mineral dust from the Sahara desert through the BSC-DREAM8b model helps to satisfactorily reproduce episodic high PM10 concentration peaks at background stations. The model assessment indicates that one of the main air quality-related problems in Spain is the high level of O(3). A quarter of the Iberian Peninsula shows more than 30days exceeding the value 120μgm(-3) for the maximum 8-h O(3) concentration as a consequence of the transport of O(3) precursors downwind to/from the Madrid and Barcelona metropolitan areas, and industrial areas and cities in the Mediterranean coast.

A multi-physics ensemble of present-day climate regional simulations over the Iberian Peninsula

This work assesses the influence of the model physics in present-day regional climate simulations. It is based on a multi-phyiscs ensemble of 30-year long MM5 hindcasted simulations performed over a complex and climatically heterogeneous domain as the Iberian Peninsula. The ensemble consists of eight members that results from combining different parametrization schemes for modeling the Planetary Boundary Layer, the cumulus and the microphysics processes. The analysis is made at the seasonal time scale and focuses on mean values and interannual variability of temperature and precipitation. The objectives are (1) to evaluate and characterize differences among the simulations attributable to changes in the physical options of the regional model, and (2) to identify the most suitable parametrization schemes and understand the underlying mechanisms causing that some schemes perform better than others. The results confirm the paramount importance of the model physics, showing that the spread among the various simulations is of comparable magnitude to the spread obtained in similar multi-model ensembles. This suggests that most of the spread obtained in multi-model ensembles could be attributable to the different physical configurations employed in the various models. Second, we obtain that no single ensemble member outperforms the others in every situation. Nevertheless, some particular schemes display a better performance. On the one hand, the non-local MRF PBL scheme reduces the cold bias of the simulations throughout the year compared to the local Eta model. The reason is that the former simulates deeper mixing layers. On the other hand, the Grell parametrization scheme for cumulus produces smaller amount of precipitation in the summer season compared to the more complex Kain-Fritsch scheme by reducing the overestimation in the simulated frequency of the convective precipitation events. Consequently, the interannual variability of precipitation (temperature) diminishes (increases), which implies a better agreement with the observations in both cases. Although these features improve in general the accuracy of the simulations, controversial nuances are also highlighted.

The role of the land-surface model for climate change projections over the Iberian Peninsula

The importance of land-surface processes within Regional Climate Models for accurately reproducing the present-day climate is well known. However, their role when projecting future climate is still poorly reported. Hence, this work assesses the influence of the land-surface processes, particularly the contribution of soil moisture, when projecting future changes for temperature, precipitation and wind over a complex area as the Iberian Peninsula, which, in addition, shows great sensitivity to climate change. The main signals are found for the summer season, when the results indicate a strengthening in the increases projected for both mean temperature and temperature variability as a consequence of the future intensification of the positive soil moisture-temperature feedback. The more severe warming over the inner dry Iberian Peninsula further implies an intensification of the Iberian thermal low and, thus, of the cyclonic circulation. Furthermore, the land-atmosphere coupling leads to the projection of a wider future daily temperature range, since maximum temperatures are more affected than minima, a feature absent in non-coupled simulations. Regarding variability, the areas where the land-atmosphere coupling introduces larger changes are those where the reduction in the soil moisture content is more dramatic in future simulations, i.e., the so-called transitional zones. As regards precipitation, weaker positive signals for convective precipitation and more intense negative signals for non-convective precipitation are obtained as a result of the soil moisture-atmosphere interactions. These results highlight the crucial contribution of soil moisture to climate change projections and suggest its plausible key role for future projections of extreme events.

Temperature sensitivity to the land-surface model in MM5 climate simulations over the Iberian Peninsula

Three different Land Surface Models have been used in three high resolution climate simulations performed with the mesoscale model MM5 over the Iberian Peninsula. The main difference among them lies in the soil moisture treatment, which is dynamically modelled by only two of them (Noah and Pleim & Xiu models), while in the simplest model (Simple Five-Layers) it is fixed to climatological values. The simulated period covers 1958-2002, using the ERA40 reanalysis data as driving conditions. Focusing on near-surface air temperature, this work evaluates the skill of each simulation in reproducing mean values and temporal variability, by comparing the simulations with observed temperature series. When the simplest simulation was analyzed, the greatest discrepances were observed for the summer season, when both, the mean values and the temporal variability of the temperature series, were badly underestimated. These weaknesses are largely overcome in the other two simulations (performed by coupling a more advanced soil model to MM5), and there was greater concordance between the simulated and observed spatial patterns. The influence of a dynamic soil moisture parameterization and, therefore, a more realistic simulation of the latent and sensible heat fluxes between the land and the atmosphere, helps to explain these results.

Warming patterns in regional climate change projections over the Iberian Peninsula

A set of four regional climate change projections over the Iberian Peninsula has been performed. Simulations were driven by two General Circulation Models (consisting of two versions of the same atmospheric model coupled to two different ocean models) under two different SRES scenario. The XXI century has been simulated following a full-transient approach with a climate version of the mesoscale model MM5. An Empirical Orthogonal Function analysis (EOF) is applied to the monthly mean series of daily maximum and minimum 2-metre temperature to extract the warming signal. The first EOF is able to capture the spatial structure of the warming. The obtained warming patterns are fairly dependent on the month, but hardly change with the tested scenarios and GCM versions. Their shapes are related to geographical parameters, such as distance to the sea and orography. The main differences among simulations mostly concern the temporal evolution of the warming. The temperature trend is stronger for maximum temperatures and depends on the scenario and the driving GCM. This asymmetry, as well as the different warming rates in summer and winter, leads to a continentalization of the climate over the IP.

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.

A multi-physics ensemble of regional climate change projections over the Iberian Peninsula

This study illustrates the sensitivity of regional climate change projections to the model physics. A single-model (MM5) multi-physics ensemble of regional climate simulations over the Iberian Peninsula for present (1970–1999) and future (2070–2099 under the A2 scenario) periods is assessed. The ensemble comprises eight members resulting from the combination of two options of parameterization schemes for the planetary boundary layer, cumulus and microphysics. All the considered combinations were previously evaluated by comparing hindcasted simulations to observations, none of them providing clearly outlying climates. Thus, the differences among the various ensemble members (spread) in the future projections could be considered as a matter of uncertainty in the change signals (as similarly assumed in multi-model studies). The results highlight the great dependence of the spread on the synoptic conditions driving the regional model. In particular, the spread generally amplifies under the future scenario leading to a large spread accompanying the mean change signals, as large as the magnitude of the mean projected changes and analogous to the spread obtained in multi-model ensembles. Moreover, the sign of the projected change varies depending on the choice of the model physics in many cases. This, together with the fact that the key mechanisms identified for the simulation of the climatology of a given period (either present or future) and those introducing the largest spread in the projected changes differ significantly, make further claims for efforts to better understand and model the parameterized subgrid processes.

A seasonal study of the atmospheric dynamics over the Iberian Peninsula based on circulation types

A seasonal analysis of the atmospheric circulation over the Iberian Peninsula (IP) based on circulation types (CTs) obtained from sea level pressure and 500-hPa geopotential height is presented. The study covers the period of 1958–2008, when a high variability and important changes in winter and spring precipitation and temperature have been reported. Frequency, persistence, and the most probable transitions of the circulation types are analyzed. Among the clustering methods available in the literature, two of the most reliable classification methods have been tested, K-means and simulated annealing and diversified randomization. A comparison of both methods over the IP is presented for winter (DJF). The quality of the circulation types obtained through both methods as well as the better stability achieved by K-means suggest this method as more appropriated for our target area. Twelve CTs were obtained for each season and were analyzed. The patterns obtained were regrouped in five general situations: anticyclonic, cyclonic, zonal, summertime, and hybrid-mixed. The analysis of frequencies of these situations offers a similar characterization of the atmospheric circulation that others previously obtained by subjective methods. The analysis of the trends in frequency and persistence for each CT shows few significant trends, mainly in winter and spring with a general decrease of the cyclonic patterns and an increase of the anticyclonic situations. This can be related to the negative precipitation trends reported by other authors. Regarding the persistence, an interesting result is that there is a high interannual variability of the persistence in autumn and spring, when patterns can persist longer than in other seasons. An analysis of the most probable transitions between the CTs has been performed, revealing the existence of cyclic sequences in all seasons. These sequences are related to the high frequency of certain patterns such as the anticyclonic situations in winter. Finally, a clear seasonal dependence of the transitions between cyclonic situations associated with extratropical disturbances was found. This dependence suggests that the transitions of low-pressure systems towards the south of the IP are more likely in spring and autumn than in winter.

Organochlorine pesticides removal from wastewater by pine bark adsorption after activated sludge treatment

Pesticides have been responsible for strong environmental impacts, mainly due to their persistence in the environment. Removal technologies are usually combined, because degradation of organic matter is needed prior to a tertiary treatment to guarantee pesticides elimination to levels below legal limits (normally 0.1 µg L−1). Pine bark was studied as an alternative to activated carbon, for organochlorine pesticides removal. A combination of technologies based on biodegradation with activated sludge followed by pine bark adsorption treatment was used for lindane (LIN) and heptachlor (HEP) removal from contaminated waters. Pesticides were quantified throughout the process by GC‐ECD preceded by solid‐phase microextraction (SPME). An experimental set‐up was maintained for 4 months, by feeding a standard solution with pesticides concentration of 1 µg L−1 each and known organic matter (Chemical Oxygen Demand, COD, ∼563 mg O2 L−1) on a daily basis. COD suffered a reduction of about 81% in the biological step and no increase was detected in the subsequent adsorption treatment. Overall removal efficiency was 76.6% and above 77.7% for LIN and HEP, respectively.

High resolution modeling of the effects of alternative fuels use on urban air quality: introduction of natural gas vehicles in Barcelona and Madrid Greater Areas (Spain).

The mitigation of the effects of on-road traffic emissions on urban air pollution is currently an environmental challenge. Air quality modeling has become a powerful tool to design environment-related strategies. A wide range of options is being proposed; such as the introduction of natural gas vehicles (NGV), biofuels or hydrogen vehicles. The impacts on air quality of introducing specific NGV fleets in Barcelona and Madrid (Spain) are assessed by means of the WRF-ARW/HERMES/CMAQ modeling system with high spatial-temporal resolution (1 km(2), 1 h). Seven emissions scenarios are defined taking into account the year 2004 vehicle fleet composition of the study areas and groups of vehicles susceptible of change under a realistic perspective. O(3) average concentration rises up to 1.3% in Barcelona and up to 2.5% in Madrid when introducing the emissions scenarios, due to the NO(x) reduction in VOC-controlled areas. Nevertheless, NO(2), PM10 and SO(2) average concentrations decrease, up to 6.1%, 1.5% and 6.6% in Barcelona and up to 20.6%, 8.7% and 14.9% in Madrid, respectively. Concerning SO(2) and PM10 reductions the most effective single scenario is the introduction of 50% of NGV instead of the oldest commercial vehicles; it also reduces NO(2) concentrations in Barcelona, however in Madrid lower levels are attained when substituting 10% of the private cars. This work introduces the WRF-ARW/HERMES/CMAQ modeling system as a useful management tool and proves that the air quality improvement plans must be designed considering the local characteristics.