Mapping atmospheric depositions of cadmium and lead in Germany based on EMEP deposition data and the European Moss Survey 2005

Abstract

Background Every ve years since 1990, the European Heavy Metals in Mosses Survey provided data on atmospheric heavy metal bioaccumulations in mosses throughout Europe at a high spatial resolution. The moss data show the e ectiveness of air quality control policies: for Germany the metal bioaccumulations decreased between 1990 and 2000, whilst they increased from 2000 to 2005. This investigation is intended to show how the moss data could be used to map atmospheric depositions of Cd and Pb, which later on might serve for the calculation of Critical Loads Exceedances. In addition, we compared how much heavy metal concentrations in mosses in Germany deviate from background data observed in Greenland.Methods Mapping heavy metals with a high spatial resolution for the German territory was conducted according to the following methodology: EMEP deposition maps (50 km by 50 km spatial resolution) were intersected within a GIS with Kriging maps on Cd and Pb accumulations in mosses (EMEP (European Monitoring and Evaluation Programme) is a scienti cally based and politically driven programme under the Convention on Long-range Transboundary Air Pollution for international co-operation to solve transboundary air pollution problems). Subsequently, the statistical relations between the EMEP modelled depositions and the bioaccumulations in mosses were quanti ed by using regression analysis. The regression functions were used to transform the moss concentration maps into deposition maps. The resulting maps on Cd and Pb depositions have a spatial resolution of 5 km by 5 km and were added to the respective map on the residuals of the regression functions (Regression Kriging). Finally, the territory of Germany was extracted from the European maps on Cd and Pb depositions and the legends were adjusted accordingly in terms of n standard deviations from the German mean value. The concentrations of Al, As, Cd, Cr, Cu, Mo, Pb, Sb, Sn, and Zn in the mosses sampled in 1990, 1995, 2000 and 2005 Results and discussion The regression models corroborate that the Cd concentration in mosses is correlated with the EMEP modelled total Cd deposition across Europe (regression coefficient according to Pearson, r p = 0.67; regression coefficient according to Spearman, r s = 0.69). The coefficient of determination is r 2 = 0.44. The same is true for Pb with r p = 0.76 and r s = 0.77 and r 2 = 0.58. Based on the regression models and the respective residuals, maps on the total deposition of Cd and Pb were calculated for the year 2005. The German mean value of total Cd and Pb deposition was 0.342 g / ha / a (standard deviation 0.08 g / ha / a and 8.6 g / ha / a (standard deviation 2.1 g / ha / a) respectively. The maps depict the spatial patterns of the total Cd and Pb deposition in terms of n standard deviations from the respective German wide mean value. The spatial resolution of the maps is 5 km x 5 km and reflects the mesh size of the moss monitoring net. Even today, the bioaccumulation of several metals in Germany still exceeds the backgr...

Estimating atmospheric deposition of heavy metals in Germany using LOTOS-EUROS model calculations and data from biomonitoring programmes

“…Correlations based on geostatistical surface estimations were relatively strong compared to those based on the moss samplings. These results are in line with earlier Europe-wide studies, dealing with HM deposition values from EMEP model (Schröder et al, 2011). Correlations between moss data and LOTOS-EUROS were relatively high compared to EMEP.…”

“…numeric modelling and moss monitoring data, for computing deposition maps of Cd and Pb across Germany at a high spatial resolution. This approach for mapping atmospheric deposition by use of Regression-Kriging-Techniques (Hengl et al, 2004;Odeh et al, 1995) has proven successfully in similar cases (Schröder et al, 2011). The procedure encompasses following steps: (1) applying regression models (Formula 4.1 and 4.2) to available geostatistical surface estimations on HM concentration in moss (regression maps as result), (2) analyzing and interpolating residuals (regression model vs. LOTOS-EUROS) by use of geostatistical methods (residual maps as result) and (3) a nal summation of both (HM deposition maps as result).…”

“…All over Europe, up to 7000 sites are sampled (Harmens & Norris, 2008). In the last few years, these monitoring data were used for evaluating the EMEP model and can also be used for mapping deposition of heavy metals (Cd, Pb) at a relatively high spatial resolution of 3 km by 3 km (Schröder et al, 2011). Further data of HM accumulation in biota (i.e.…”

Does spatial auto-correlation call for a revision of latest heavy metal and nitrogen deposition maps?

“…The coefficient of determination is R 2 = 0.44. The same is true for Pb with r p = 0.76 and r s = 0.77 and R 2 = 0.58 [13]. The regression analysis of the estimated N concentrations in mosses and the modelled EMEP depositions, too, resulted in clear linear regression patterns with coefficients of determination of R 2 = 0.62 and Pearson correlations of r p = 0.79 and Spearman correlations of r s = 0.70, respectively [12].…”

“…The European moss monitoring produces datasets at high spatial resolution which was used to evaluate the performance of the EMEP model [11] and to calculate deposition maps with a spatial resolution of 5 km by 5 km through modelling the statistical relations between atmospheric deposition and bioaccumulation of of Cd, Pb and N by use of Regression Kriging [12,13]. The corresponding methodology and results can be summarised as follows: The EMEP deposition maps were intersected within a GIS with Kriging maps on N, Cd and Pb accumulations in mosses.…”