Mixing layer height as an indicator for urban air quality?
- 1Ludwig-Maximilians-Universität (LMU Munich), Meteorological Institute, Theresienstr. 37, 80333 Munich, Germany
- 2Institute for Advanced Sustainability Studies (IASS), Berliner Str. 130, 14467 Potsdam, Germany
- 3Karlsruhe Institute of Technology (KIT) – Institute of Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU), Kreuzeckbahnstr. 19, 82467 Garmisch-Partenkirchen, Germany
- 4Vaisala GmbH, Weather Instruments, Notkestr. 11, 22607 Hamburg, Germany
- 5Senate Department for the Environment, Transport and Climate Protection, Brückenstr. 6, 10179 Berlin, Germany
- anow at: ESA ESTEC, Keplerlaan 1, 2201AZ Noordwijk, the Netherlands
- bnow at: Albert-Ludwig-University, Institute for Forest Sciences, Georges-Köhler-Allee 53, 79110 Freiburg, Germany
Abstract. The mixing layer height (MLH) is a measure for the vertical turbulent exchange within the boundary layer, which is one of the controlling factors for the dilution of pollutants emitted near the ground. Based on continuous MLH measurements with a Vaisala CL51 ceilometer and measurements from an air quality network, the relationship between MLH and near-surface pollutant concentrations has been investigated. In this context the uncertainty of the MLH retrievals and the representativeness of ground-based in situ measurements are crucial. We have investigated this topic by using data from the BAERLIN2014 campaign in Berlin, Germany, conducted from June to August 2014. To derive the MLH, three versions of the proprietary software BL-VIEW and a novel approach COBOLT were compared. It was found that the overall agreement is reasonable if mean diurnal cycles are considered. The main advantage of COBOLT is the continuous detection of the MLH with a temporal resolution of 10 min and a lower number of cases when the residual layer is misinterpreted as mixing layer. We have calculated correlations between MLH as derived from the different retrievals and concentrations of pollutants (PM10, O3 and NOx) for different locations in the metropolitan area of Berlin. It was found that the correlations with PM10 are quite different for different sites without showing a clear pattern, whereas the correlation with NOx seems to depend on the vicinity of emission sources in main roads. In the case of ozone as a secondary pollutant, a clear correlation was found. We conclude that the effects of the heterogeneity of the emission sources, chemical processing and mixing during transport exceed the differences due to different MLH retrievals. Moreover, it seems to be unrealistic to find correlations between MLH and near-surface pollutant concentrations representative for a city like Berlin (flat terrain), in particular when traffic emissions are dominant. Nevertheless it is worthwhile to use advanced MLH retrievals for ceilometer data, for example as input to dispersion models and for the validation of chemical transport models.