Features

Applying biological monitors and neutronactivation analysis in studies ofheavy-metal air pollutionMoss, tree bark, lichens and other materials can yield importantinformation about environmental pollution and its likely sources

by M. de Bruin

Trowing concerns about current and future levels ofenvironmental pollution have led to an increased demandfor experimental methods to study the environment.Although still under development, the application of bio-logical monitors, or indicators, may provide importantinformation on the levels, availability, and pathways ofa variety of pollutants in the environment.

In such applications, relevant information is com-monly deduced from studying an organism used formonitoring (the monitor organism). One approach in-volves analysis of changes in the organism's behaviour,such as abundance, diversity, ecological performance,or morphology. A second approach entails analysis ofconcentrations of specific substances that may accumu-late in the organism's tissue. Typical examples of thefirst approach are the use of species-distributions oflichens as indicators for. ambient sulphur dioxide levelsand the behaviour of selected fish species in relation towater quality.

The second approach includes procedures in whichthe concentrations of trace substances in an organism areused as a measure of the concentrations or availability ofthese substances in certain parts of the environment.This approach will be discussed in more detail in thisarticle. Attention will be focussed on the "biomonitor-ing" of heavy-metal air pollution and the role ofinstrumental neutron activation analysis (INAA) in suchprocedures. To illustrate the value of the combination ofbiomonitoring and INAA in air pollution studies, someresults will be given that were obtained in a recent studyin the Netherlands.

Prof, de Bruin is Director, Interfaculty Reactor Institute, Delft Univer-sity of Technology, 2629 JB Delft, Netherlands. The author would liketo thank J.E. Sloof and H.Th. Wolterbeek for the fruitful discussions.Full technical references to this article are available from the author.

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Biomonitoring of air pollution

The use of biological materials for monitoring heavy-metal air pollution was introduced about 30 years ago.Since then, a variety of materials and organisms hasbeen proposed for biomonitoring purposes. Theseinclude mosses, lichens, tree bark, tree rings, pineneedles, leaves, grass, ferns, or animal tissues such asfeathers, hair, and liver.

A detailed comparison of the most commonly usedmaterials leads to the conclusion that mosses and lichens

Figure 1. Concentrations of cadmium in Parme-lia sulcata in the Netherlands, 1986-87.

Source: Cl. J.E. Sloof and H.Th. Wolterbeek, 1990.

IAEA BULLETIN, 4/1990

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and, to a lesser extent, tree bark are the most suitablemonitors of heavy metals in the atmosphere. However,for all biomonitors used, the mechanisms of metaluptake and retention are still not sufficiently known.Consequently, the quantitative relationships between theelement's concentration in the monitor's tissue and itsconcentration in a relevant compartment of the atmo-sphere are not predictable. Therefore, without extensivecalibration under all relevant conditions, the use of evenone of the most suitable organisms will yield onlyqualitative information on atmospheric levels as a func-tion of time or place. Probably for this reason, most pub-lications on biomonitonng of air pollution refer toobserved relationships between element concentrationsin the biological monitor and the known levels orsources of heavy materials. Only in a few cases havebiological monitors for air pollution been applied inrealistic environmental situations, rather than in a prioriknown situations.

Biomonitoring programme in the Netherlands

In 1986 in the Netherlands, a biomonitoring pro-gramme was started using the epiphytic lichen Parmeliasulcuta as monitor for heavy-metal air pollution. Fulldetails and results of the study, which followed anearlier programme in 1982, are being published.

Samples were collected at 250 sampling sites thatcovered the whole country Lichen samples were sepa-rated from the bark substratum, washed, dried, andhomogenized. Ahquots of 30-100 milligrams dry weightwere analysed using the Interfaculty Research Institute(IRI) system for routine INAA. A standard protocol wasused comprising an irradiation of 30 seconds followedby a measurement after 15 minutes, and a second irradi-ation of 4 hours followed by two measurements after5 days and 20 days, respectively. The irradiations werecarried out in the institute's 2 megawatt research reac-tor In a separate sample aliquot, lead was determined bygraphite-furnace atomic absorption spectroscopy, afteracid destruction.

For the interpretation of the data, two methods wereapplied. In a straightforward approach, concentrationsof the individual trace element were plotted geographi-cally (See Figure 1 for an example.) Such plots givedirect insight into regional variations of the heavy-metalair pollution Moreover, combining these plots withinformation on prevailing wind direction may provideinformation on the geographical positions of individualsources of air pollution But, as can be expected, thismethod of source appointment yields adequate resultsonly in uncomplicated situations with only a fewdominant sources. Both the 1986 study and the earlier1982 study show that this approach alone is not success-ful in the Dutch situation, which is characterized bynumerous sources of pollution inside and outside thecountry.

In another approach, additional information wasderived from correlations existing between the concen-

trations of different elements For most sources, theemissions are not limited to only one element Theycomprise a mixture of toxic and non-toxic elements witha concentration pattern characteristic of specificsources. Therefore, the observed correlations and ratiosbetween concentrations of different elements may pro-vide significant information on the nature of the con-tributing sources

The relevant information can be deduced from theanalytical data by a specific multi-variate statistical pro-cedure known as "Target Transformation Factor Ana-lysis" (TTFA) From the concentration patternsobserved in the set of samples, sets of correlated ele-ments and associated concentration profiles (factors) arededuced. These can be regarded as (hypothetical) emis-sions from pollution sources On the basis of the natureof the constituting elements and their ratios, thehypothetical emissions can often be identified asmaterials from specific realistic sources. The identifica-tion can further be improved by plotting geographicallythe calculated contributions from the different hypotheti-cal emissons for each sampling point. (See Figure 2 foran example of such a plot) This combination of elementconcentration patterns and geographical distributionsallows for the unambiguous identification of pollutionsources even in a very complex environment.

Figure 2. Calculated contribution from zinc-smelters to the cadmium concentrations in theNetherlands.

Source: Cf. J.E. Sloof and H.Th. Wolterbeek. 1990.

This computer generated map of the Netherlands shows thegeographical distribution of the calculated contribution to the totalconcentration in Parmelia su/cata of assumed cadmium emissionsfrom zinc smetters and/or the electronics industry. The observedmaxima nicely coincide with known concentrations of non-ferrousmetal industries in the southeastern part of the country.

IAEA BULLETIN, 4/1990 23

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Analysis of samples in biomonitoring

Analysis of collected samples constitutes alarge part of the total effort required in biomonitor-ing programmes. A number of analysis techniquescurrently are used for studying heavy-metal air pol-lution. These techniques include induction coupledplasma emission spectroscopy (ICPES); atomicabsorption spectroscopy (AAS); X-ray fluore-scence analysis (XRF); charged particle inducedX-ray emission analysis (PIXE); and instrumentalneutron activation analysis (INAA).

The success of the biomonitoring programmeas a whole fully depends on the quality of theanalytical data. When selecting the proper ana-lysis method, a number of aspects has to be takeninto account. Particularly relevant are multi-element capability; sensitivity; accuracy and preci-sion; analysis costs; sample characteristics; andavailability.

Multi-element capability. It is clear that inheavy-metal air pollution studies the analysisprocedure applied to the monitor material will befocussed primarily on the concentrations of theseheavy-metal elements. The spectrum of elementsshould be as broad as possible to minimize thechance of overlooking any unexpected pollutant.When possible, the analysis procedure should alsoprovide information on accompanying non-toxicelements. The concentration patterns of theseadditional elements may provide information onthe nature and origin of certain pollutants, and fordiscriminating between individual natural andanthropogenic sources.

Sensitivity. The detection limits for heavymetals must be low enough to enable study ofthese elements in very early stages of pollution. Inaddition, a broad spectrum of non-toxic trace ele-ments should be detectable in the majority of thesamples if trace element concentration patternsare to be used in source appointment procedures.The required sensitivities can be deduced fromdata of the concentrations of 34 elements deter-mined by INAA in Dutch lichens. (See Table 2.)

Accuracy and precision. Results of environ-mental monitoring programmes may establish thebasis for often very expensive measures for envi-ronmental protection. Therefore, high demandsare made on the accuracy of the analytical tech-niques employed. However, when using biologicalmonitors, the precision of the whole procedure islimited by biological variations in the response ofthe monitor organism. For the analytical proce-dure, no extreme precision is required.

Analysis costs. Biomonitoring programmesgenerally comprise several hundreds to severalthousands of samples. Therefore, the analysismethod should be applicable on a routine scaleand the costs of the analysis should be acceptablewhen compared to the total costs of the monitoringprogramme. The high costs associated with col-lecting and preparing samples, coupled with theadministrative procedures and data interpretation,make it worthwhile to apply an analytical proce-dure that provides maximum information fromthe samples. Economizing too much on the analy-sis procedure easily becomes a matter of "penny-wise and pound-foolish".

Sample characteristics. Some materials com-monly used for biomonitoring air pollution can beeasily digested (or dissolved) prior to analysis. Asa result, they can be analysed by techniques thatrequire solid samples just as well as by techniquesthat are only suitable for solutions. For plantmaterials, however, a careful and time-consumingprocedure is required to assure the sample's com-plete destruction. Moreover, lichens usually con-tain mineral particles, which further complicatesthe destruction procedure. Therefore, for plantmaterials, a method of non-destructive analysishas to be preferred.

Availability. The analytical method to be em-ployed in a biomonitoring programme should bewell developed and mature, so that the analyticalactivities can be properly planned in advancetogether with other project activities. The availableanalysis capacity should be sufficient to absorbthe significant workload associated with a moni-toring programme. Moreover, contact is requiredbetween field workers who collect the samples andthe analyst, to assure proper sampling and samplepreparation procedures.

Comparison of analytical techniques

There are many pitfalls associated with makinga comparison between analytical techniques.Moreover, local conditions, such as availability oreasy access to a certain facility, will strongly deter-mine the choice of a proper analytical method. Thecomparison presented here (see Table 1) shouldbe regarded as a personal view; it does not pre-tend to give a detailed, absolute, or generally validrating of techniques.

For this comparison, ICPES seems to be themethod of choice, provided the matrix can easily

24 IAEA BULLETIN, 4/1990

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be dissolved. But INAA is preferred for difficultmaterials, such as lichens, that require laboriousdestruction procedures with the associated conse-quences for costs and accuracy. AAS is basicallya single-element method and therefore onlyapplicable in well-established situations where themonitoring programme can be focussed on only

one or two elements. If information on a largernumber of elements is needed, consecutive ana-lyses have to be carried out which will easily leadto prohibitive costs per sample. The major limi-tation of XRF is its limited sensitivity. PIXE isprimarily a micro-beam technique and less suitedfor accurate bulk analysis.

Table 1. Applicability of analytical techniques in biomonitoring heavy-metal air pollution

Technique

ICPESAASXRFPIXEINAA

Aspect

Multi-elementcapability

_ ... .. Accuracy and _ . Sample . ., ..,.Sensitivity . . Costs . . . . . Avai abi hty

precision characteristics '

ICPES = Induction Coupled Plasma Emission Spectroscopy.AAS = Atomic Absorption Spectroscopy.XRF = X-ray Fluorescence Analysis.PIXE = Charged Particle Induced X-ray Emission Analysis.INAA = Instrumental Neutron Activation Analysis.

Studies of air pollution sources and pathways are increasingly being done in many countries.

IAEA BULLETIN, 4/1990 25

Features

Selected results

In the 1986 Dutch study, 34 elements were com-monly observed in the lichen samples. (See Table 2.)The statistical procedure (TTFA) was applied to the con-centration data of 15 selected elements and it yielded10 "factors" of hypothetical emissions. (See Table 3.)On the basis of the element concentration patterns, mostof these hypothetical emissions can be assigned tospecific sources:

• Factor 1: crustal material;• Factor 2: zinc smelters and/or electronic industry;• Factor 3: oil processing or combustion;• Factor 4: waste incineration or non-ferrous metal

industry;• Factor 5: probably coal combustion;

Factor 6: unknown;Factor 7: probably waste incineration;Factor 8: traffic;Factor 9: unknown;Factor 10: unknown.

Geographical distributions also were done of the con-tributions from the (assumed) emissions from specificsources.

Only a small part of the study's results have beenreferred to in this article. Nonetheless, they clearly showthe power of the application of lichens as biologicalmonitors, when combined with IN A A as a multi-elementanalysis procedure and with TTFA techniques to inter-pret observed trace element patterns for purposes ofestablishing and identifying sources of heavy-metal airpollution.

Table 2. Trace elements in the lichen Parmelia sulcata in the Netherlands, determined by INAA (1986)

Element

AluminumArsenicBromineCalciumCadmiumCobaltChromiumCaesiumCopperIronGalliumHafniumMercuryIodinePotassiumLanthanumLutetiumMagnesiumManganeseSodiumNickel(Lead)RubidiumAntimonyScandiumSeleniumStrontiumThoriumThalliumUraniumVanadiumTungstenYtterbiumZinc

Mean

58005.7

564700

2.82.0

260.8

335800

471.40.5

155200

6.20.071

1800110

100016

(150)133.31.11.8

501.2

4900.57

320.90.4

210

Concentrationin mg/kg

Range

2300.5

151100

0.60.204.00.21.4

7202.30.090.15.3

13000.80.009

49016

2601.9

(3.11.80.30.160.48.50.14

780.0895.70.10.078

61

-2100017

- 170-21000

216.3

- 2705

- 120- 30000- 180

83632

- 1600064

0.46- 3800- 400- 5400

51- 370)

62125.27.5

- 4008.9

- 20002.7

99103

- 1100

INAA detectionlimit

1000.10.1

30010.110.3

1030

30.10.1

3100

1

0.01100

113

0.30.10.31

300.1

1000.310.30.031

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Future directions

Biological monitors, combined with an analyticaltechnique that provides information on concentrations ofa broad pattern of elements, have proved to be a power-ful tool for detecting and identifying sources of heavy-metal pollution. If lichens are used as monitor organ-isms, INAA is the analytical method of choice. It pro-vides accurate data on a broad range of elements. As nolabourious sample preparation or destructive steps arerequired, INAA can be economically competitive withother multi-element analysis techniques.

Application of INAA on a large scale, as relevant inenvironmental monitoring programmes, requires certainmeasures to assure or improve its practical usefulness orapplicability. Research reactor facilities should be will-ing to carry out a large number of routine analyses and

to take the necessary infrastructural measures to avoidunwanted interference between routine analysis andscientific research. Moreover, quality assurance proce-dures have to be developed so that the intrinsic accuracyof INAA is indeed reflected in the quality of the resultsof large-scale routine analysis.

For obvious reasons, INAA requires direct access toa research reactor. At present, the potential use of acti-vation analysis is already very strongly limited, sinceonly a small number of such reactors is presently inoperation. Further reduction of this number will gradu-ally lead to the end of the many important applicationsof activation analysis in environmental research.

Table 3. Results of the Target Transformation Factor Analysis

Element

Aluminium

Arsenic

Bromine

Cadmium

Cobalt

Chromium

Caesium

Iron

Mercury

Lanthanum

Manganese

Nickel

Lead

Antimony

Scandium

Selenium

Thorium

Vanadium

Tungsten

Zinc

F1

420 000

2 300

72

380 000

100

140

F2

1.8

0.36

15

1.1

0.35

100

Normalized factor compositions

F3 F4

2.3

100

6.6

0.28

100

22

150

F5 F6 F7

12 000

100

5.8

0.26

3 200 29 000

100

100

4.0 34

43

13

0.44

9.4

F8 F9 F10

370 98 000

11

9.8 100

100

4.3 380

100

Note: Concentrations are normalized to a concentration equalling 100 for the element regarded as characteristic of each factor.

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