Peter Builtjes

The LOTOS?EUROS model: description, validation and latest developments

In this paper, we present a validation study for oxidants and secondary inorganic aerosols using the new regional Chemistry Transport Model (CTM) Long Term Ozone Simulation (LOTOS) European Operational Smog (EUROS). The model is the product of the integration of the Netherlands Organisation for Applied Scientific Research (TNO) LOTOS model and the National Institute for Public Health and the Environment (RIVM) EUROS model. In addition to a model description, we present an overview of a validation of the model. The new model is able to capture the variability of ozone well, especially in summer. However, the exchange between the mixing layer and the free troposphere was assessed to be too low resulting in too high ozone levels at days with low ozone. Sulphate levels are underestimated, whereas the concentrations of nitrate and ammonium are in line with measured data. The performance of LOTOS-EUROS is similar to other regional models in Europe. Examples of new applications of the model are presented. These include the modelling of sea salt and heavy metals.

Data assimilation of ozone in the atmospheric transport chemistry model LOTOS

Modelled ozone concentrations often differ from measured concentrations quite substantially, partly due to measurement errors, but mainly due to uncertainties in the model. Modelling studies would therefore benefit highly from more reliable model simulations. One way to achieve this is the application of data assimilation, a technique that uses measurement information within the model simulation in a way that is consistent with the model itself. This aim of this paper is to show that this is indeed one way to go with atmospheric transport chemistry models (ATCMs) by presenting results of data assimilation simulations of ozone with the model LOTOS. The assimilation technique used in this study is the Ensemble Kalman Filter. A simulation for a period of 4 weeks has been performed in which ground-level ozone measurements have been assimilated. The necessary noise input consisted of uncertainties in the emissions of NOx, SOx, VOC and CO in 17 groups of countries. The main conclusion is that it is possible to improve ATCM simulations of ozone by data assimilation, but that noise inputs other than emissions only are essential for the reduction of the differences between measured and modelled concentrations to acceptable margins.

Is regional air quality model diversity representative of uncertainty for ozone simulation

We examine whether seven state-of-the-art European regional air quality models provide daily ensembles of predicted ozone maxima that encompass observations. Using tools borrowed from the evaluation of ensemble weather forecasting, we analyze statistics of simulated ensembles of ozone daily maxima over an entire summer season. Although the model ensemble overestimates ozone, the distribution of simulated concentrations is representative of the uncertainty. The spread of simulations is due to random fluctuations resulting from differences in model formulations and input data, but also to the spread between individual model systematic biases. The ensemble average skill increases as the spread decreases. The skill of the ensemble in giving probabilistic predictions of threshold exceedances is also demonstrated. These results allow for optimism about the ability of this ensemble to simulate the uncertainty of the impact of emission control scenarios.

The Added Value of a Proposed Satellite Imager for Ground Level Particulate Matter Analyses and Forecasts

Monitoring aerosols over wide areas is important for the assessment of the populations exposure to health relevant particulate matter (PM). Satellite observations of aerosol optical depth (AOD) can contribute to the improvement of highly needed analyzed and forecasted distributions of PM when combined with a model and ground-based observations. In this paper, we evaluate the contribution of column AOD observations from a future imager on a geostationary satellite by performing an Observing System Simulation Experiment (OSSE). In the OSSE simulated imager, AOD observations and ground-based PM observations are assimilated in the chemistry transport model LOTOS-EUROS to assess the added value of the satellite observations relative to the value of ground-based observations. Results show that in highly polluted situations, the imager AOD observations improve analyzed and forecasted PM2.5 concentrations even in the vicinity of simultaneously incorporated ground-based PM observations. The added value of the proposed imager is small when considering monthly averaged PM distributions. This is attributed to relatively large errors in the imager AODs in case of background aerosol loads coupled to the fact that the imager AODs are column values and an indirect estimate of PM. In the future, model improvements and optimization of the assimilation system should be achieved for better handling of situations with aerosol plumes above the boundary layer and satellite observations containing aerosol profile information. With the suggested improvements, the developed OSSE will form a powerful tool for determining the added value of future missions and defining requirements for planned satellite observations.

An Observing System Simulation Experiment (OSSE) for Aerosol Optical Depth from Satellites

Monitoring aerosols over wide areas is a scientific challenge with important applications for human health and the understanding of climate. Aerosol optical depth (AOD) measurements from satellites can improve the highly needed analyzed and forecasted distributions of ground-level aerosols in combination with models and ground-based measurements. To assess the benefit of future satellite AOD measurements, an observing system simulation experiment (OSSE) is developed. In this pilot study, the OSSE is applied to total AOD measurements from a flexible combined imager (FCI) proposed to fly on a geostationary satellite. OSSEs are widely used in the meteorological research community, but their use for air quality applications and specifically for aerosols is new. In this paper, the functionality and potential of the developed OSSE for evaluation of aerosol data from future satellite missions are demonstrated. The results show a positive impact of adding AOD observations next to in situ observations for the analysis of PM2.5 (particles smaller than 2.5 μm in median diameter) distributions. However, the development of an OSSE for aerosols presents a number of further challenges, as discussed in this paper, which prohibits a detailed quantitative analysis of the results of this pilot study.

Einrichtung einer Umweltzone und ihre Wirksamkeit auf die PM10-Feinstaubkonzentration — eine Pilotanalyse am Beispiel München

ZusammenfassungSeit Einführung der Umweltzonen in Deutschland im Jahr 2008 stellt sich die Frage nach ihrer Effizienz zur Feinstaubreduktion. In dieser Pilotstudie wurden Messdaten vor und nach Einführung der Umweltzone in München (Oktober 2007 bis Januar 2008 vs. Oktober 2008 bis Januar 2009) mithilfe gematchter Messwerte-Quadrupel analysiert. Basierend auf einer publizierten Methodik (Morfeld et al. 2011) wurden kontinuierliche Halbstundenmessungen von PM10-Staubkonzentrationen zeitgleich ermittelt an innerhalb der Umweltzone gelegenen Indexstationen und außerhalb positionierten Referenzstationen (Hintergrundbelastung). Diese jeweils gematchten Messwertequadrupel wurden vergleichend ausgewertet mit Hilfe der Differenzwertmethode im Zwei-Perioden-Fall. Zusätzlich wurden meteorologische Größen (Mischungsschichthöhe, Niederschlagsmenge, Luftgeschwindigkeit) sowie Basisdaten an Index- und Referenzstationen regressionstechnisch berücksichtigt. Die Auswertemethodik wurde mittels einer Analyse von Simulationsdaten vorab erfolgreich geprüft.Insgesamt konnten 26438 Quadrupel für den Auswertezeitraum zusammengestellt werden. Als PM10-Mittelwerte ergaben sich an 5 Indexstationen vor bzw. nach Einführung der Umweltzone 33.9 μg/m3 bzw. 39.0 μg/m3 und 24.6 μg/m3 bzw. 30.5 μg/m3 an einer Referenzstation außerhalb der Münchener Umweltzone. Ein additives Modell ermittelte unter Berücksichtigung von Kovariablen eine durchschnittliche PM10-Staubkonzentrationsänderung von +0.017 μg/m3 (0.95-CI: −0.33 μg/m3, +0.37 μg/m3), ein multiplikatives Modell schätzte den relativen Effekt durch die Einführung der Umweltzone auf −0.5 % (0.95-CI: −0.12 %, +0.30 %).Die mit diesem methodischen Auswerteansatz erzielten Ergebnisse unterscheiden sich relevant von den Befunden einer früheren Analyse auf der Basis derselben Messdaten der Münchner Umweltzone von Cyrys et al. (2009). Aufgrund der hier erzielten Ergebnisse lassen sich die Befunde von Cyrys et al. (2009) nicht als Beweis für eine Effektivität der Umweltzone heranziehen. Vielmehr ist der methodische Ansatz für eine wissenschaftlich belastbare Bewertung der Wirksamkeit von Umweltzonen entscheidend. Eine sorgfältige Datenauswahl und stringente Auswerteregeln müssen beachtet werden, um Fehlschlüsse hinsichtlich der PM10-Konzentrationsänderungen zu vermeiden.AbstractSince the introduction of low emission zones in Germany in 2008 the question of their efficiency has been debated. In this pilot study, measurement data collected before and after the introduction of the low emission zone in Munich (October 2007 until January 2008 vs. October 2008 until Januar 2009) were analysed on the basis of matched quadruples. Applying previously described methods (Morfeld et al. 2011), continuously measured half-hour fine dust concentration data (PM10) — simultaneously determined at an index station situated inside the low emission zone and a reference station outside of the zone — were contrasted and analysed (difference score method in the two-period case). Meteorological parameters (height of the inversion base, amount of precipitation, wind velocity) as well as baseline data of index and reference stations were taken into account as covariates in regression analyses. The statistical approach was successfully validated in an analysis of simulated data.26438 quadrupels could be matched for analysis. Averages of PM10 concentration values before (after) introducing the low emission zone were 33.9 μg/m3 (39.0 μg/m3) at 5 index stations and 24.6 μg/m3 (30.5 μg/m3) at 2 reference stations. Taking covariates into account, an additive model estimated the change in concentration associated to the introduction of the low emission zone as +0.017 μg/m3 (0.95-CI: −0.33 μg/m3, +0.37 μg/m3), multiplicative model estimated the relative effect as −0.5% (0.95-CI: −0.12%, +0.30%).The results of this study differ relevantly from the findings of an earlier investigation by Cyrys et al. (2009) who analyzed the same data. This analysis does not prove the effectiveness of Munich’s low emission zone. This study also points out that the methodological approach is crucial for a scientifically reliable evaluation of the efficacy of low emission zones. Strict rules need to be followed in order to prevent from misinterpretations.

Evaluation of the Performance of a Photochemical Dispersion Model in Practical Applications

A photochemical dispersion model has been used to calculate concentrationlevels for an area covering the Netherlands and its surroundings during a given episode. The agreement between measured and calculated concentrations of O3, and to a somewhat less extent of NO2, showed to be remarkably good. With this model the influence of traffic emissions, the emissions from industry and the inflow of emissions from outside the area during the episode considered on the existing concentration levels of O3, NO2 and NO has been determined. The emissions from outside the area showed to have a large influence on the O3-concentrations. The influence of industry on O3- and NO2-levels is larger than that of traffic.

Application of a Photochemical Dispersion Model to the Netherlands and its Surroundings

The investigation deals with the application of a grid-based Eulerian photochemical dispersion model developed by Systems Application Inc., U.S.A. The model calculates concentrations of O3, PAN, NO, NO2, SO2, etc. with emissions, meteorological parameters and initial and boundary values as input data.

Curriculum vitae of the LOTOS–EUROS (v2.0) chemistry transport model

The development and application of chemistry transport models has a long tradition. Within the Netherlands the LOTOS–EUROS model has been developed by a consortium of institutes, after combining its independently developed predecessors in 2005. Recently, version 2.0 of the model was released as an open-source version. This paper presents the curriculum vitae of the model system, describing the model’s history, model philosophy, basic features and a validation with EMEP stations for the new benchmark year 2012, and presents cases with the model’s most recent and key developments. By setting the model developments in context and providing an outlook for directions for further development, the paper goes beyond the common model description. With an origin in ozone and sulfur modelling for the models LOTOS and EUROS, the application areas were gradually extended with persistent organic pollutants, reactive nitrogen, and primary and secondary particulate matter. After the combination of the models to LOTOS–EUROS in 2005, the model was further developed to include new source parametrizations (e.g. road resuspension, desert dust, wildfires), applied for operational smog forecasts in the Netherlands and Europe, and has been used for emission scenarios, source apportionment, and long-term hindcast and climate change scenarios. LOTOS–EUROS has been a front-runner in data assimilation of ground-based and satellite observations and has participated in many model intercomparison studies. The model is no longer confined to applications over Europe but is also applied to other regions of the world, e.g. China. The increasing interaction with emission experts has also contributed to the improvement of the model’s performance. The philosophy for model development has always been to use knowledge that is state of the art and proven, to keep a good balance in the level of detail of process description and accuracy of input and output, and to keep a good record on the effect of model changes using benchmarking and validation. The performance of v2.0 with respect to EMEP observations is good, with spatial correlations around 0.8 or higher for concentrations and wet deposition. Temporal correlations are around 0.5 or higher. Recent innovative applications include source apportionment and data assimilation, particle number modelling, and energy transition scenarios including corresponding land use changes as well as Saharan dust forecasting. Future developments would enable more flexibility with respect to model horizontal and vertical resolution and further detailing of model input data. Published by Copernicus Publications on behalf of the European Geosciences Union. 4146 A. M. M. Manders et al.: Curriculum vitae of the LOTOS–EUROS (v2.0) chemistry transport model This includes the use of different sources of land use characterization (roughness length and vegetation), detailing of emissions in space and time, and efficient coupling to meteorology from different meteorological models.

Progress in the determination of the sea spray source function using satellite data

Sea spray aerosol influences climate considerably through both direct and indirect aerosol effects. Climate models contain a sea spray source function, i.e. the emission rate of sea spray aerosol droplets per unit area of the sea surface, currently parameterised in terms of wind speed and sea surface temperature (SST). The uncertainty between different formulations of the sea spray source function, and thus associated with the calculated emission fluxes for sea spray aerosol, is more than a factor of 2. In addition, the fraction of organic material in sub-micrometer sea spray droplets is highly uncertain. It is expected that improved estimates can be obtained by inclusion of factors, such as wave conditions, whitecap fraction, improved SST, salinity, and chlorophyll concentration. We aim to incorporate these factors in a new sea spray emission model constrained by the use of satellite observations. Here, we present a methodology for estimating the global primary marine sub-micron organic matter emission. As a first estimate we found an annual global emission of about 20 TgC.