Air Pollution Bark Monitoring -
A New Standardised Method for Biomonitoring the
Air Quality and Fingerprinting the Sources of Pollutants

F. Hofmann, G. Bracke, A. Giesemann, U. Siemers, W. Wosniok


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Fig. 1 & 2: Sample sites in Germany and in the area of Bremen

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Fig. 3: Typical sample site for standarised air polution bark monitoring

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Fig. 4: Removing the outer bark using the new sampler.

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Fig. 5: The fine coarsed bark sample in the PP-bag is ready for deep-freezing and transport to lab.

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Fig. 6 & 7: Air pollution gradients.

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Fig. 8: Isotopic pattern.

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Fig. 9: Pollution-Fingerprints.

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Fig. 10: Specific air pollution impacts.

For many purposes in environmental monitoring of industrial emitters it is necessary to evaluate the specific impact of an air pollution emitter in relation to the background and other sources. To do this in dense industrialised regions, where more than one emission source might be relevant, it is necessary to apply chemical fingerprinting e.g. to analyse the patterns of substances typically for the pollution sources. The usual sampling methods by technical instruments need measuring periods of several years, because air pollution measurements depend on meteorological conditions and show high temporal variation. For many applications in environmental control this is too long and furthermore too costly to be acceptable.
The biomonitor tree bark accumulates air pollutants over several years. The outer tree bark is dead. Compared to other bioaccumulators like needle and moss tree bark is free of annual growth cycles. Tree bark has been used widely in the literature and found to be an ideal bioaccumulator. Nevertheless there remained some severe difficulties in the sampling procedure, mainly because the pollutants are accumulated in the outermost layer of the bark with a steep gradient toward the inner parts.
With a new bark sampler, a standardisation of the bark monitoring became possible, thus the device allows now to remove the outer bark layer in particular thickness keeping pro-analysis conditions. Using this sampling method, the long term air pollution levels can be successfully determined within one single sampling for many elements, substances and isotopes at once.
In order to validate this approach, trees have been sampled from several sites across Germany, around industrial point sources and in areas affected by pollutants in various ways and to various extents. This should enable to test the method for gradients of air pollution and for the possibility of the fingerprinting approach.


Tree bark was sampled at 52 locations in Germany with the Hofmann bark sampler (fig. 1-5).
The sample sites were chosen around industrial emitters (steel plant, lead- and zinc smeltery, gas production, high traffic intensity) in the vicinity of Bremen according to existing data from dispersion models and results from pollution surveys in such a way, that the pollution gradients could be tested efficiently. Additionally several sites across Germany were sampled, too. The sites were located next to measuring places of national or regional pollution surveys and at so-called level-II sites of the national forest inventory, where secondary data were available. The standardised investigation was carried out on oak trees (Quercus spp.) under standardised site conditions (see fig. 3), comparable to the requirements for air pollution surveys with technical instruments (free standing, exposed trees, age over 60 yrs.).

The bark samples were analysed for (see fig. 8):

The data were statistically analysed, standardised and an Air Pollution Bark Monitoring Index was calculated, indicating the relative change of air pollution compared to the background pollution level for each substance in a comparable way. The results of the bark monitoring were related to the secondary data from the dispersion models and pollution surveys to test the gradients of air pollution. Fingerprints were calculated using discriminant functions and multiple regression analysis.


The results of the bark monitoring showed significant gradients for the elements and substances in relation to the tested pollution sources.
Around the steel factory we found major gradients for elements like Fe, Co, Cr, Mn, Nb, Ni, V, all of them typically for steel processing (see for example V in fig. 6). The gradients were of similar shape but showed differences in the extent according to the individual emission rates. The same applied for the lead- and zinc factory, where significant gradients of Pb, Sb, In, Cd, Cr, Zn were visible (see fig. 7 for Sb).
The sites of air pollution caused by traffic had common patterns by typical values of the isotopic ratios of Pb and some PAH, sulphur and its isotopic ratio d34S showed significant values for the sour gas field and the sites in saxony (see fig. 8 for the isotopic ratios of S and Pb).
The analysis of data gave distinct patterns of elements, isotopes and PAH in respect to the different air pollution sources (fig. 9).
This allowed to calculate fingerprints which could successfully be used to differentiate the specific impacts of the various pollution sources for each site (fig. 10).


With the new Hofmann bark sampler it became possible to sample the outer bark of trees in a comparable way, so that the bark could be analysed successfully for many substances. This allows a standardisation of biomonitoring air pollution by tree bark.
The results show that the method works well in reflecting the gradients of air pollution impacts related to industrial emission sources. Furthermore, the combined analysis of elements, isotopes and PAH allows a fingerprinting of the sources of pollutants. The analysis of the isotopic composition of S and Pb were found to be very useful in this approach.
The results indicate that the Air Pollution Bark Monitoring is especially valuable for screening purposes. The new method allows to gain information on air pollution deposition levels for many substances and many sampling points within one sampling and thus in acceptable time. Therefore the Air Pollution Bark Monitoring gives an ideal addition to technical based surveys and it could be of great value for many tasks in air pollution surveys and for controlling industrial emission sources.

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