Suchergebnisse

Abstract

Background
Within the framework of the Convention on Long-range Transboundary Air Pollution atmospheric depositions of heavy metals and nitrogen as well as critical loads/levels exceedances are mapped yearly with a spatial resolution of 50 km by 50 km. The maps rely on emission data and are calculated by use of atmospheric modelling techniques. For validation, EMEP monitoring data collected at up to 70 sites across Europe are used. This spatially sparse coverage gave reason to test if the chemical and physical relations between atmospheric depositions and their accumulation in mosses collected at up to 7000 sites throughout Europe can be quantified in terms of statistical correlations which, if proven, could be used to calculate deposition maps with a higher spatial resolution. Indeed, combining EMEP maps on atmospheric depositions of cadmium, lead and nitrogen and the related maps of their concentrations in mosses by use of a Regression Kriging approach yielded deposition maps with a spatial resolution of 5 km by 5 km. Since spatial auto-correlation can make testing of statistical inference too liberal, the investigation at hand was to validate the 5 km by 5 km deposition maps by analysing if spatial auto-correlation of both EMEP deposition data and moss data impacted on the significance of their statistical correlation and, thus, the validity of the deposition maps. To this end, two hypotheses were tested: 1. The data on deposition and concentrations in mosses of heavy metals and nitrogen are not spatially auto-correlated significantly. 2. The correlations between the deposition and moss data lack statistical significance due to spatial autocorrelation.


Results
As already published, the regression models corroborated significant correlations between the concentrations of heavy metals and nitrogen in atmospheric depositions on the one hand and respective concentrations in mosses on the other hand. This investigation proved that atmospheric deposition and bioaccumulation data are spatially auto-correlated significantly in terms of Moran's I values and, thus, hypothesis 1 could be rejected. Accordingly, the degrees of freedom were reduced. Nevertheless, the results of the calculations regarding the reduced degrees of freedom indicate that the statistical relations between atmospheric depositions and bioaccumulations remained statistically significant so that hypothesis 2 could be rejected, too.


Conclusions
The positive auto-correlation in data on atmospheric deposition and bioaccumulation does not call for a revision of the 5 km by 5 km deposition maps published in recent papers. Therefore we can conclude that the European moss monitoring yields data that support the validation of modelling and mapping of atmospheric depositions of heavy metals and nitrogen at a high spatial resolution compared to the 50 km x 50 km EMEP maps.

Abstract

Background
In order to map exceedances of critical atmospheric deposition loads for nitrogen (N) surface data on the atmospheric deposition of N compounds to terrestrial ecosystems are needed. Across Europe such information is provided by the international European Monitoring and Evaluation Programme (EMEP) in a resolution of 50 km by 50 km, relying on both emission data and measurement data on atmospheric depositions. The objective of the article at hand is on the improvement of the spatial resolution of the EMEP maps by combining them with data on the N concentration in mosses provided by the International Cooperative Programme on Effects of Air Pollution on Natural Vegetation and Crops (ICP Vegetation) of the United Nations Economic Commission for Europe (UNECE) Long-range Transboundary Air Pollution (LTRAP) Convention.


Methods
The map on atmospheric depositions of total N as modelled by EMEP was intersected with geostatistical surface estimations on the N concentration in mosses at a resolution of 5 km by 5 km. The medians of the N estimations in mosses were then calculated for each 50 km by 50 km grid cell. Both medians of moss estimations and corresponding modelled deposition values were ln-transformed and their relationship investigated and modelled by linear regression analysis. The regression equations were applied on the moss kriging estimates of the N concentration in mosses. The respective residuals were projected onto the centres of the EMEP grid cells and were mapped using variogram analysis and kriging procedures. Finally, the residual and the regression map were summed up to the map of total N deposition in terrestrial ecosystems throughout Europe.


Results and discussion
The regression analysis of the estimated N concentrations in mosses and the modelled EMEP depositions 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. Regarding the German territory a nationwide mean of 18.1 kg/ha/a (standard deviation: 3.49 kg/ha/a) could be derived from the resulting map on total N deposition in a resolution of 5 km by 5 km. Recent updates of the modelled atmospheric deposition of N provided a similar estimate for Germany.


Conclusions
The linking of modelled EMEP data on the atmospheric depositions of total N and the accumulation of N in mosses allows to map the deposition of total N in a high resolution of 5 km by 5 km using empirical moss data. The mapping relies on the strong statistical relationship between both processes that are physically and chemically related to each other. The mapping approach thereby relies on available data that are both based on European wide harmonized methodologies. From an ecotoxicological point of view the linking of data on N depositions and those on N bioaccumulation can be considered a substantial progress.

Zusammenfassung

Hintergrund
Umweltbeobachtung ist zentraler Bestandteil internationaler Nachhaltigkeitsstrategien. Die langfristige Beobachtung der Anreicherung von Metallen in terrestrischen Ökosystemen erfolgte Zwischen 1990 und 2005 alle fünf Jahre europaweit in den europäischen Heavy Metals in Mosses Surveys. Seit 2005 wird auch die Stickstoffanreicherung bestimmt. Deutschland nahm an den Moosmonitoring-Kampagnen 1990 – 2005 teil. Der vorliegende Artikel ist Teil einer Serie, die Trends im Bundesgebiet und einzelnen Bundesländern beleuchtet. Gegenstand dieser Untersuchung ist die Kartierung der zeitlichen Entwicklung der Metallanreicherung in Nordrhein-Westfalen seit 1990, die Stickstoffanreicherung 2005, die räumliche Varianz der Metall-Bioakkumulation in Abhängigkeit von Eigenschaften der Moosbeprobungsstellen und ihrer Umgebung sowie erstmals auch die Verknüpfung der Stoffgehalte in den Moosen mit denen der flächendeckend modellierten Gesamtdeposition von Cadmium (Cd).


Methoden
In Nordrhein-Westfalen wurde die Bioakkumulation am häufigsten in Scleropodium purum bestimmt, gefolgt von Pleurozium schreberi und Hypnum cupressiforme. Die in diesen Moosen chemisch bestimmten Stoffe wurden mit den topografischen und ökologischen Beschreibungen der bis zu 88 Beprobungsorte und mit quantitativen Angaben über die Landnutzung in ihrer Umgebung in dem WebGIS MossMet zusammengeführt und ausgewertet: Aus den standort- und metallspezifischen Messdaten sowie den daraus geostatistisch berechneten Flächendaten über die Metallakkumulation wurde ein zusammenfassender Multi-Metall-Index (MMI1990-2005) für Arsen (As), Cd, Chrom (Cr), Kupfer (Cu), Eisen (Fe), Nickel (Ni), Blei (Pb), Titan (Ti), Vanadium (V) und Zink (Zn) berechnet und kartiert. Die Zusammenhänge zwischen den Schwermetall-Akkumulationen, Standortcharakteristika und Landnutzung wurden korrelations- und kontingenzanalytisch sowie am Beispiel von Cu multivariat-statistisch mit Classification and Regression Trees (Cart) quantifiziert. Die Cd-Gehalte in den Moosen wurden mit denen der im European Monitoring and Evaluation Programme (EMEP) europaweit flächendeckend modellierten Gesamtdepositionsdaten für Cd verknüpft und korrelationsstatistisch ausgewertet.


Ergebnisse und Diskussion
Während von 1990 bis 2005 bis auf Zn alle Metallgehalte in den Moosen sanken, stiegen von 2000 bis 2005 die Konzentrationen von As, Cr, Cu, Ni, Sb und Zn an, bei Cr und Zn statistisch signifikant. Eine Zunahme des MMI1990-2005 von 2000 nach 2005 erwies sich als statistisch nicht signifikant. Die Stickstoffgehalte (N) betragen zwischen 1.08 und 2,29%. Sie sind positiv mit dem Agrarflächenanteil im Umkreis der Beprobungsstellen und der Bestandeshöhe sowie negativ mit Waldflächenanteil, Entfernung zu Bäumen, Höhe über NN und Niederschlag korreliert (0.32 ≤ r

Spearman
≥0.49, p <0.01). Die Korrelationen zwischen Metallgehalten in den Moosen und der Landnutzung im Umkreis der Beprobungsorte rangieren zwischen r

S
 = 0.21 und r

S
 = 0.54 (0.01 <p <0.05). Moosart und –bewuchsform sind mit den Stoffkonzentrationen ähnlich stark assoziiert (Cramér´s V-Werte zwischen 0.27 und 0.56). Von den Standortmerkmalen weisen vor allem die Variablen Waldflächenanteil (insbesondere bei Cd, Cu, Pb, Zn, N), Flächenanteil urbaner Landnutzung (bei As, Cd, Cr, Cu, Fe, Ni, Ti, Zn), Niederschlagssumme im Akkumulationszeitraum (bei Cd, Ni, Pb, V, N), orografische Höhe (bei As, Cd, Cr, Cu, Fe, Ni, Ti, Zn, N) und Entfernung der Moos-Entnahmestelle von Straßen (bei Cr, Fe, Ni, Ti), Baumkronen oder Sträuchern (bei As, Cd, Cr, Cu, Fe, Ni, Zn) für die meisten Elemente signifikante Korrelationen zur Metallanreicherung auf. In der multivariat-statistischen Analyse mit CART werden der urbane Flächenanteil im Umkreis von 5 km um die Moossammelstelle sowie die dortige Geländehöhe und die Entfernung der Moossammelstelle von der Baumkrone als wichtigste Einflussgrößen für die Cu-Gehalte in den Moosen 2005 ermittelt. Die Cd-Gesamtdeposition (EMEP) und die Cd-Konzentrationen in Moosen Nordrhein-Westfalens sind positiv korreliert (0.57 ≤ r

S
≥0.71, p <0.01).
Anders als etwa in Baden-Württemberg stiegen die Metallanreicherungen in Moosen Nordrhein-Westfalens von 2000 bis 2005 an, Cr und Zn statistisch signifikant. Für Cd konnte in einer landesweit flächendeckenden GIS-gestützten Korrelationsanalyse gezeigt werden, dass die in den Moosen gemessenen Anreicherungen mit der modellierten Gesamtdeposition (EMEP) positiv verknüpft sind. Damit wurden punktuelle Korrelationen zwischen Depositions- und Mooskonzentrationen räumlich validiert. Im Vergleich zu zeitlich höher aufgelösten Depositionsmessungen erfasst das Moos-Monitoring europaweit mit mindestens einer Moosbeprobungsstelle pro 1000 km2 ein breites Stoffspektrum, das auch selten gemessene Stoffe mit humantoxikologischer Bedeutung (z. B. As, Al, Hg, Sb, V) umfasst. Damit bildet das Moos-Monitoring ein wichtiges Bindeglied zwischen der technischen Erfassung von Stoffeinträgen durch Deposition und der Anreicherung dieser Stoffe in biologischem Material. Die Untersuchung zeigt, dass die Stoffanreicherung in biologischem Material nicht nur von den Depositionen, sondern auch von topographischen und ökologischen Merkmalen der Messstellen und der Landnutzung ihrer Umgebung abhängt.


Schlussfolgerungen
Das Moos-Monitoring liefert wesentliche Beiträge zum Schwermetall- und zum Multi-Komponenten-Protokoll der CLRTAP. Es weist flächendeckend nach, wie sich Luftreinhaltepolitik auf die Anreicherung von atmosphärischen Stoffeinträgen in Schutzgütern wie der Vegetation auswirkt. Von besonderer umweltpolitischer Bedeutung ist, dass in keinem anderen Messprogramm räumlich so verdichtet Daten über ein breites, ökotoxikologisch und humanmedizinisch bedeutsames Stoffspektrum erhoben werden. Die räumliche Auflösung von Umweltinformationen ist ein wesentliches Kriterium für ihre Nutzbarkeit im Vollzug umweltpolitischer Maßnahmen auf Bundes- und Länderebene.
Das Moos-Monitoring sollte im bisherigen Umfang langfristig fortgesetzt werden. Es liefert als einziges Messnetz in Europa räumlich hinreichend differenzierte, flächendeckende Informationen über die Metall- und Stickstoffexposition naturnaher und agrarisch genutzter Ökosysteme, die auch für einzelne Staaten und deren administrative Untergliederungen räumlich aussagekräftig sind. Die in anderen Untersuchungen jüngst belegten europaweiten Korrelationen zwischen Stoffanreicherungen in Moosen und EMEP-Depositionsdaten wurden in anderen Arbeiten dazu genutzt, die Kartierung der Metall- und Stickstoffdepositionen räumlich höher aufzulösen.


Abstract
Every five years since 1990, the European moss surveys provide data on concentrations of heavy metals and since 2005 on nitrogen (N) in mosses. Germany participated in the monitoring campaigns 1990 – 2005. As part of a series reporting the trends for Germany and single federal states, this article is on North Rhine-Westphalia showing that the metal concentrations decreased from 1990 to 2000 for all elements but Zn. From 2000 to 2005 an increase can be stated for As, Cr, Cu, Ni, Sb, Zn and the Multi Metal Index MMI1990-2005. The N concentration reaches from 1.08 to 2,29% in dry mass showing significant correlations to the agriculture density (+), the height of the surrounding trees (+), the forests density (−), the distance to trees (−), altitude (−) and the precipitation sum for the accumulation period (−). The according correlation coefficients (Spearman) reach from r

s
0.32 to 0.49 (p <0.01). The correlation of the metal loads in the mosses and land use characteristics in the vicinity of the sampling sites lie between r

s
 = 0.21 and r

s
 = 0.54 (0.01 <p <0.05). The type of moss species and the moss growth patterns are associated to a similar degree (Cramér´s V-values between 0.27 and 0.56). Of all investigated site specific information on forest density (Cd, Cu, Pb, Zn, N), urban density precipitation (Cd, Ni, Pb, V, N), altitude (As, Cd, Cr, Cu, Fe, Ni, Ti, Zn, N) and the distance of the sampling site to roads (Cr, Fe, Ni, Ti), trees or bushes (As, Cd, Cr, Cu, Fe, Ni, Zn) are those showing significant correlations to the elements enumerated in brackets before. The urban land use density in a radius of 5 km around the sampling site as well as altitude and the distance of the sampling site to nearby trees are the statistically most significant factors for the Cu concentrations in mosses sampled in 2005. The total deposition of Cd (EMEP) and Cd concentrations in mosses are correlated significantly (0.57 ≤ r

s
≥0.71, p <0.01).

Abstract

Background
Every five 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 effectiveness 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 scientifically 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 quantified 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 in Germany were compared with background values derived from mosses sampled in north-eastern Greenland (Zackenberg Background Values). The differences between heavy metal concentrations in mosses in Germany and Greenland were calculated for the 16 federal states of Germany and mapped for Pb.


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 × 5 km and reflects the mesh size of the moss monitoring net. Even today, the bioaccumulation of several metals in Germany still exceeds the background values observed in Greenland. This is true especially for Cd, Cr, Cu, Mo, Pb, Sb, Sn and Zn. Comparing the results of this investigation with those from other methods it can be concluded that the mean values calculated for the total Cd and Pb deposition for Germany differ from such assessed by deposition measurements and models. The latter are used to calculate Critical Loads Exceedances, which complement the ecotoxicological endpoint 'accumulation'. The deposition measurements in Germany are mainly based on monitoring systems conducted by the federal states. When trying to use deposition measurements from the ICP Forests level II programme for the validation of the EMEP deposition modelling, problems arose due to a lack of methodical harmonization and the quality of the depositions measurements. That is why in this investigation the quality controlled and spatially high resolved moss data were used to empirically validate EMEP modelled deposition maps.


Conclusions
In Germany, the moss measurement data provide a valuable tool at a high spatial resolution for the validation of modelling and mapping of atmospheric heavy metal deposition and should as such be used for this purpose. The comparison of the metal concentrations in mosses in Germany with the values found in Greenland indicate that atmospheric deposition of heavy metals in Germany is still considerably higher than the natural background deposition.