Optimierung des Moosmonitoring-Messnetzes in Deutschland

Pesch, Roland; Schröder, Winfried; Dieffenbach-Fries, Helga; Genßler, Lutz

doi:10.1065/uwsf2007.03.166

Cited by 12 publications

(6 citation statements)

References 21 publications

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“…Die dabei gewählte räumliche Auflösung orientiert sich an der Standardabweichung der Distanzen zwischen je zwei Beprobungspunkten in Deutschland und beträgt dementsprechend 5 km mal 5 km. Schließlich wurden die Gehalte von Al, As, Cd, Cr, Cu, Mo, Pb, Sb, Sn und Zn der 1990Zn der , 1995Zn der , 2000 [20].…”

Section: Hintergrundunclassified

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

et al. 2011

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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...

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Section: Hintergrundunclassified

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

et al. 2011

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“…The number of sampling sites in five GMS ( Fig. 1) was reduced from 1026 (1995) and 1028 (2000), respectively, to 726 (2005) and, further on, to 400 (2015) according to a transparent and statistically sound methodology [34,45,46,59]. In addition to Cd, Hg, Pb and N, aluminium (Al), arsenic (As), chromium (Cr), copper (Cu), nickel (Ni), vanadium (V) and zinc (Zn) were determined in the moss specimens collected in 2015.…”

Section: Introductionmentioning

confidence: 99%

Spatial structures of heavy metals and nitrogen accumulation in moss specimens sampled between 1990 and 2015 throughout Germany

Schröder

Nickel

2019

Environ Sci Eur

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Background: The collection of atmospheric deposition by technical samplers and validated deposition modelling using chemical transport models is spatially complemented by using mosses as bioindicator: since 1990, the European moss survey has been providing data on element concentrations in moss every 5 years at up to 7300 sampling sites. In the moss specimens, heavy metals (since 1990), nitrogen (since 2005) and persistent organic pollutants (since 2010) were determined. Germany participated in all surveys with the exception of that in 2010. In this study, the spatial structures of element concentrations in moss collected in Germany between 1990 and 2015 were comparatively investigated by using Moran's I statistics and Variogram analysis and mapped by use of Kriging interpolation. This is the precondition to spatially join the moss survey data with data collected at other locations within different environmental networks and to validate spatial patterns of atmospheric deposition as derived by technical sampling and modelling. Results: The calculated maps reveal a clear and statistically significant decrease of most heavy metals, but not of nitrogen, in moss. Due to decreasing element concentrations and the unchanged application of the element concentration classification for the mapping, the heavy metal maps for the survey 2015 do no longer depict much spatial variation. Conclusions: Therefore, in an upcoming study, this analysis needs to be complemented for the heavy metals by calculating maps that depict the spatial structure of survey-specific percentile statistics

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“…Furthermore, the moss technique enables achieving a high spatial resolution compared to technical deposition samplers. Since 1990, so-called 'moss surveys' were therefore carried out every 5 years in at least 21 European countries at about 7,000 sites [8][9][10]. These surveys enabled mapping the spatial and temporal trends of metal accumulation in Europe [11,12].…”

Section: Introductionmentioning

confidence: 99%

Accounting for canopy drip effects of spatiotemporal trends of the concentrations of N in mosses, atmospheric N depositions and critical load exceedances: a case study from North-Western Germany

et al. 2013

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Background: Atmospheric nitrogen (N) deposition into terrestrial ecosystems is frequently considered as a threat to phyto-diversity. In previous investigations, the atmospheric N inputs enriched in mosses were recorded in 2004 as part of a regional investigation at 54 locations in north-west Germany and in 2005 at 726 locations across the whole country. This article deals with a study conducted in 2012 comparing N concentrations in mosses sampled within 30 forest stands and in 26 adjacent open fields in north-west Germany. The N concentration in mosses were determined and, by the use of a regression model, converted to N atmospheric deposition values. These deposition estimations enabled to calculate N critical load exceedances.

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Optimierung des Moosmonitoring-Messnetzes in Deutschland

Cited by 12 publications

References 21 publications

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

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

Spatial structures of heavy metals and nitrogen accumulation in moss specimens sampled between 1990 and 2015 throughout Germany

Accounting for canopy drip effects of spatiotemporal trends of the concentrations of N in mosses, atmospheric N depositions and critical load exceedances: a case study from North-Western Germany

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