EVALUATION OF MERIS AEROSOL PRODUCTS FOR NATIONAL AND REGIONAL AIR QUALITY IN AUSTRIA

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1 EVALUATION OF MERIS AEROSOL PRODUCTS FOR NATIONAL AND REGIONAL AIR QUALITY IN AUSTRIA Robert Höller (1),*, Christian Nagl (1), Herbert Haubold (1), Ludovic Bourg (2), Odile Fanton d Andon (2), and Philippe Garnesson (2) (1) Umweltbundesamt, Spittelauer Lände 5, 1090 Wien, Austria (2) ACRI-ST, 260, route du Pin Montard - B.P. 234,06904 Sophia Antipolis Cedex, France ABSTRACT/RESUME The Umweltbundesamt (Austrian Federal Environment Agency, FEA) is currently evaluating the potential of satellite data for assessing national and regional air quality. Within the framework of the GSE project PROMOTE, Service Level Agreements (SLA) were signed between the Umweltbundesamt and various data providers. In this paper, the ESA standard MERIS aerosol product, provided by ACRI-ST in near-real time, is evaluated. Data are also provided temporally aggregated for air quality reporting. In this paper, we present a first evaluation of ENVISAT/MERIS aerosol products during the period March to August 2005 and comparisons to data from the in-situ ground based monitoring network. 1 INTRODUCTION The situation of the air quality in Austria improved quite strongly in the last decades in Austria. Concentrations of most classic air pollutants were continuously reduced, and per capita emissions of SO 2 and NO x are among the lowest of all EU member states. Pollution levels are generally lower than the limit values for lead, benzene, and CO. SO 2 exceedances are rare and usually caused by transboundary air pollution. Nevertheless, limit values for PM10 concentrations (50 µg m -3 daily average not to be exceeded more than 35 times per year; 40 µg m -3 yearly average) are frequently exceeded in agglomerations (Figure 1), but exceedances are measured in nearly all regions of Austria, particularly in the north-eastern part of the country, Alpine valleys and basins. Statistical analyses of back trajectories showed that a considerable amount of the total PM10 levels in the eastern part of Austria is caused by long-range transport, but also local sources add substantially to PM10 levels. Due to its geographic situation Austria is, therefore, strongly affected by local, regional, and long-range air pollution. Therefore, the FEA supports further emission reduction strategies on a national and international level [1]. The legal framework for monitoring air quality in Austria are the Austrian air quality protection act, ozone act, clean air *Corresponding author. Tel.: , Fax.: ; robert.hoeller@umweltbundesamt.at

2 act for steam boilers, as well as international obligations, such as the EC Air Quality Framework Directive and DD, and the UNECE Convention of Long-Range Transboundary Air Pollution (CLRTAP) [2]. Figure 2 shows the air quality monitoring sites in Austria that are operated by the FEA. The total number of sites in Austria, including the sites operated by the Federal Provinces, already exceeded 90 in For an analysis of long-term trends, unfortunately only TSP measurements exist, monitoring of PM10 did not start until More recently, sites measuring PM2.5 are added to the monitoring network. Fig. 1. Number of days with daily average concentrations of PM10 higher than 50 µg m-3 [1]. Fig. 2. Air quality monitoring sites in Austria operated by the Umweltbundesamt [1].

3 For an analysis of the state of the atmosphere over Austria, besides the legally required monitoring and analysis methods, the FEA is currently also evaluation the potential of satellite remote sensing and modelling methods. Within the framework of the GEMS Service Element (GSE) project PROMOTE [3], several data products are evaluated and, if necessary and possible, optimized to the user s requirements. The mission of PROMOTE is to deliver the Atmosphere GMES Service Element by constructing and delivering a sustainable and reliable operational service to support informed decisions on atmospheric policy issues. The aim is an incremental enhancement of services during the lifetime of the project. 2 MERIS DATA MERIS aerosol data are delivered to FEA within a Service Level Agreement signed with ACRI-ST in the framework of PROMOTE [3]. The service lasts for the period of the project, with a continuous delivery of near real-time (NRT) aerosol products, that is, the aerosol optical thickness (AOT) and the Ångstöm exponent, as well as RGB images of the same area. The time delay between data acquisition by the satellite and the delivery of the aerosol product and the RGBs is presently about one day. Part of the SLA is also access to archive data (2003 and 2004), assistance to exploit the data products, and the production of monthly, seasonal, and yearly average maps. The resolution of the aerosol product is 1 km, with a latitude coverage of 44N - 50N, and a longitude coverage of 8E - 20E. A detailed description of the standard MERIS aerosol algorithm is given in Santer et al. [4] and the MERIS aerosol algorithm ATBD [5, 6]. 3 RESULTS Fig. 3. Example image of the aerosol optical thickness over Austria and surroundings on July 30, 2005.

4 Figure 3 shows an example of the aerosol optical thickness over Austria and surrounding on July 30, Typically, only for part of the area data is available, which is due to the coverage of the MERIS sensor. Also, the data only give a snapshot of the aerosol at the time of the overpass of the satellite. It can be well recognized in this image that the aerosol concentration is higher in valleys with lower altitude. A slightly higher AOT can also be recognized in the south-east of Austria. Cloudy areas are screened out, but it is clear that the cloud-screening algorithm still needs to be improved due to the high aerosol concentrations in the vicinity of clouds. Fig. 4. Monthly mean of the aerosol optical thickness during March Fig. 5. Monthly mean of the aerosol optical thickness during August 2005.

5 Figures 4 and 5 show average of the AOT during spring (March 2005) and summer (August 2005) over Austria and surroundings. In Figure 4 it can be seen that even in a monthly average image, no full coverage of the area can be achieved during spring. During winter (not shown here), the situation is even worse due to frequent cloud coverage and due to the fact that the dark-target method of the MERIS algorithm cannot retrieve data over highly reflecting surfaces such as snow and ice. It has to be mentioned that also for areas were data are available, only a small number of measurements (up to 8) are made for one pixel. Therefore, the monthly average value is calculated from a much smaller number of measurements than the values that are retrieved from ground in-situ stations, that measure the aerosol concentration every hour during the day and night time During summer, nearly full coverage of the area can be achieved, except for some high mountainous regions (Figure 5). For one pixel, up to 15 measurements per month are achieved with fewer measurements in areas with frequent cloud coverage. The clearly visible higher AOT in the southeastern part of Austria and over Slovenia might be an artefact due to cloud contamination, but could also be due to higher emissions in this area. Therefore, data for this period have to be investigated into more detail. Several groups already performed comparisons of AOT data from satellite measurements with ground-based PM data [7, 8, 9]. Here, for a comparison with ground-based data of PM10 measurements three background sites in Austria were chosen, that is, Pillersdorf, Illmitz, and Enzenkirchen. All of these sites are only slightly influenced by local air pollution. Figure 6 shows the PM10 concentrations (blue line) measured at Pillersdorf in the northeastern part of Austria, near to the Czech border (see Figure 2). Also shown are the retrieved AOT values from the MERIS aerosol product. The two datasets compare reasonable good, but the amount of data is still to small to make a more detailed assessment. It is planned to use archived data from the years 2003 and 2004 for a long-term comparison. Also, PM2.5 data will be used for sites where these are available. Pillersdorf 80 3 mass concentration (µg m-3) ,5 2 1,5 1 0,5 AOT Fig. 6. Comparison of PM10 concentrations and aerosol optical thickness values (AOT) for the site Pillersdorf between February and August 2005.

6 4 CONCLUSIONS From this preliminary evaluation of the ENVISAT/MERIS aerosol product, several lessons could be learnt. Disadvantages of MERIS aerosol data for air quality monitoring are missing data for cloudy pixels, and the low temporal frequency of data compared to ground-based data. Also, the dark-target approach of the MERIS aerosols algorithm does not provide aerosol information above high reflecting surfaces such as snow and ice, which limits the usefulness of data in the winter period, during which usually the highest PM10 levels are observed. Moreover, compared to ground-based measurements, the diurnal variability of the aerosol concentration is not covered. The advantage of satellite data compared to the operational in-situ monitoring network clearly is the wide spatial coverage of data. Especially in a country with a complex topography such as Austria, this could provide valuable additional information for areas where no ground-based monitoring stations exist. Satellite data can also give valuable information about long-range transport of pollution, and a synoptic view of the area of interest. One possible solution to the undersampling might be the future use of data from geostationary satellites, possible combined with data from data from sensors on LEO satellites to achieve higher accuracy. 5 ACKNOWLEDGEMENTS This work was financially supported by the ESA GSE Project PROMOTE. 6 REFERENCES 1. Schneider, J., et al. (Umweltbundesamt, Ed.), Schwebestaub in Österreich, pp. 410, 2005 (in German). 2. State of the Environment in Austria (Umweltbundesamt, Ed.), Vol. 7, pp. 472, PROMOTE webpage: 4. Santer, R., V. Carrere, P. Dubuisson, and J. C. Roger, Atmospheric corrections over land for MERIS, Int. J. of Rem. Sens., 20, , Santer, R, Carrere, V., Dessailly, D., Dubuisson, P., and J.-C. Roger, MERIS Algorithm theoretical basis document, ATBD 2.15, Atmospheric corrections over land. 6. Ramon, D., and R. Santer, MERIS Algorithm theoretical basis document, ATBD 2.19, Atmospheric corrections over land: correction of directional effects over DDV. 7. Chu, D. A., et al., Global monitoring of air pollution over land from the Earth Observing System Terra Moderate Resolution Imaging Spectroradiometer (MODIS), J. Geophys. Res., 108(D21), 4661, doi: /2002JD003179, Engel-Cox, J. A., R. A. Hoff, and A. D. J. Haymet, Recommendations on the use of satellite remote-sensing data for urban air quality, J. Air & Waste Manage. Assoc., 54, , Hutchison, K.D., Smith, S., and S. J. Faruqui, Correlating MODIS aerosol optical thickness data ground-based PM2.5 observations across Texas for use real-time air quality prediction system, Atmos. Environ., 39, , 2005.