IJERD – International Journal of Environmental and Rural Development (2012) 3-2

Research articleerd

The Diffusive Gradients in Thin Films Technique (DGT)
for Trace Metals versus Active Sampling
TATIANA KOMAROVA*
Queensland Health Forensic and Scientific Services (QHFSS), Inorganic Chemistry Division
E-mail: tatiana_komarova@health.qld.gov.au

HENRY OLSZOWYQueensland Health Forensic and Scientific Services (QHFSS), Australia

BARRY NOLLER
The University of Queensland, Centre for Mined Land Rehabilitation, Australia

GARY GOLDING
Queensland Health Forensic and Scientific Services (QHFSS), Australia
Received 19 December 2011

Accepted 18 April 2012(*: Corresponding Author)

Abstract The diffusive gradient in thin films (DGT) technique is an in situ passive sampling method that is designed to accumulate labile metal species in environmental systems.
DGTs were applied for the determination of time integrated concentrations of low level
dissolved metals in waters in areas of ecological concern. The data revealed heavy metal
contamination of waters and tracked the contamination to the source. A comparison of
DGT-derived water concentrations with water concentrations measured from grab samples
highlighted the effectiveness of passive water samplers for detecting ultra-trace levels ofmetals. Comparing active and passive sampling techniques showed that both methods produce similar results when used simultaneously at the same sites. The use of DGT technique along with traditional methods offers an extra cost effective method of independent
evaluation of environmental sites as well as more sensitive and inexpensive way of obtaining additional information about sites which would be very hard to obtain using active
sampling techniques.
Keywords passive sampling, ultra-trace levels, labile metal species, accumulation, time
integrated concentrations.

INTRODUCTION
In recent years, passive sampling techniques have been developed to measure dissolved organicand inorganic compounds in waters at sub-nanogram   per   litre   levels.   “Passive”   samplers   are  defined as human-made devices where sample collection occurs in a non-active, inert manner.
DGT technique is designed to accumulate labile species in environmental systems (Davisonand Zhang, 1994; Davison et al. 2000; Zhang and Davison, 1995; Zhang and Davison, 2000). The
currently available DGTs still require further method development and field validation (Warken etal., 2006).
The DGT technique employs an adsorbent (e.g. Chelex-100), usually immobilized in apolyacrylamide gel (the binding or resin gel), to adsorb analyte species from solution. Chelexbased resins can be used for simultaneous collection of many metals in water including silver (Ag),aluminium (Al), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), iron (Fe), manganese(Mn), nickel (Ni), lead (Pb) and zinc (Zn). The binding gel is separated from the bulk solution by apermeable polyacrylamide gel (the diffusive gel) and a solution diffusive boundary layer.
DGT devices are deployed in an environmental system for a time period ranging from days tomonths to accumulate analyte species of interest. Following deployment, the binding gel and theⒸISERD169

IJERD – International Journal of Environmental and Rural Development (2012) 3-2

diffusive gel are separated and the accumulated analyte is eluted from the binding gel. The
concentration of analyte in the eluant is then determined by an appropriate analytical technique,usually inductively-coupled plasma mass spectrometry (ICPMS). The time-averaged concentrationof a species in the bulk solution, C, is then calculated using the DGT Equation below, which isderived  from  Fick’s  first  law  of  diffusion (Zhang and Davison, 1995); M is the accumulated massof  analyte  on  the  binding  gel;;  Δg  is  the  thickness  of  the  diffusive  gel,  D  is  the  diffusion  coefficient  of analyte in the diffusive gel, t is the deployment time, and A is the surface area of the diffusive
gel exposed to the bulk solution.
C  =  M  Δg  /  D  t  A                                                                                                                                                                                                                          (1)The assessment of water quality for the protection of the aquatic ecosystem requires the use of
a combination of analytical methods based on the Australian ANZECC/ARMCANZ (2000)
decision tree process for assessing metal toxicity in water. An initial step is to calculate sitespecific trigger values for metals by using a correction for hardness, calculated from the calcium
plus magnesium concentrations expressed as mg/L CaCO3, to the default ANZECC/ARMCANZ(2000) guideline value. The aquatic toxicity decreases with increasing water hardness as soluble
metal is precipitated. The next step in the decision tree process uses the measurements of metals inlabile or bioavailable forms and metals and metalloids in particulate and insoluble colloidal
fractions that can be measured through filtration (<0.45µm) and ultra-filtration (<0.003µm) todetermine the bioavailable fractions of metals in waters. DGT samplers offer an alternative toconventional active sampling techniques.
The objective of the present study was to enhance and consolidate DGT applications formonitoring low levels of dissolved metals in water. The study seeks to address the following
research questions: (i) how will DGT and active sampling techniques compare in a real world studyof a contaminated water body in different environmental conditions; (ii) could the DGT technique
be incorporated into the trace metal monitoring programs in waters together with traditional
methods and replace them in the future; and (iii) will bioavailability results from DGT analysis add
more value to the current analysis by conventional sampling techniques?
MATERIAL AND METHODSDGT samplers were deployed for 2 days at the Woodcutter mine area in Northern Territory (Fig.1),
Australia and in the Tosno river area in St. Petersburg (Fig. 2), Russian Federation.
The major silver-lead-zinc deposits at Woodcutters were mined from 1985 (Noller et al. 2003)
to May 2000. Initial deployment of DGTs in Woodcutters Creek at the rehabilitated mine site wasundertaken in June 2010 and a further more extensive deployment took place in September 2010
(Noller et al. 2011).
To compare DGT and active sampling techniques in a real world study of contaminated waters
in different environmental conditions various experimental designs were established in a majorindustrial areas of the Russian Federation in January 2011 (Fig.2).
The diffusion coefficient of metals in the diffusive gel D (see Equation above) is dependent on
the temperature. Therefore the average temperature of the water at all sites during DGTdeployment was estimated. It ranged between 23.4-25.6 °C in the first round and 25.6-27.6 °C in
the second round of deployment in the Woodcutter Creek and between 0-1 °C in the Tosno river
deployment. At the completion of the deployment period, DGTs were delivered to the QHFSS
laboratory where they were kept below 4 °C until prepared for analysis. During the extraction
procedure the DGT device was opened, the binding gel and the diffusive gel were separated and thebinding gel was submersed in 1 mL nitric acid for over 24 hours to elute the accumulated metals.
Then 0.5 mL of extract was made up to 5 mL with nitric acid and water and analysed for metals byICPMS (ICPMS 7700X, Agilent). At the time of DGT deployment 1L water samples werecollected (active sampling) from all sites. Some water samples were filtered through 0.45 and 0.003µm filters and analysed for metals by ICPMS.
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IJERD – International Journal of Environmental and Rural Development (2012) 3-2

RESULTS AND DISCUSSION
Woodcutter mine site in Australia
Initially 5 sets of DGTs were deployed in Woodcutter Creek in the vicinity of Woodcutters minesite in June 2010 to identify the bioavailable fraction of metals in the creek water (Fig. 1A). The
DGTs collect the soluble or labile metal only and enable a comparison to be made with ecotoxicity
measurements previously undertaken on creek water.
The measured DGT concentrations were generally higher than some of the filtered fractions.
Table 1 shows the data for two major metals: lead and zinc. The grab water samples were collected
at the beginning of DGT deployment and therefore represent the concentration of lead and zinc at
this particular time. Concentrations of lead and zinc estimated from the DGT data represent theiraverage concentrations over the deployment period (i.e. time integrated concentrations and may
differ from spot sampling). Further experimental work performed at this site showed that the concentrations of lead and zinc in water may change significantly within 2-3 days (up to 5-10 times).
This can explain the difference between the data.

ABB

21 (old bore)

345

106

6.5
7

7.589Fig. 1 A Sampling sites at Woodcutter
Creek June 2010
1. upstream site
2. new polishing pond outflow
3. above Huandot crossing
4. seepage below former Tailings Dam 2 atHuandot crossing
5. Mine lease boundary

B. Shallow seepage sampling sites
at Woodcutters Creek
September 2010 Site 1 corresponds toJune 2010 Site 4

In the second DGT deployment undertaken at Woodcutters Creek in September 2010 (Fig. 1B)
grab water samples were collected before and after DGT deployment and the average
concentrations of lead and zinc were measured in filtered and unfiltered water. There wereinsignificant levels of lead present in water at all sites. Good agreement was found between theconcentrations of zinc in 0.003 µm filtered grab water fraction and zinc DGT concentrations (Table2). The minor difference in these values is attributed to the different approach applied with passiveand active sampling techniques; that is time integrated water concentration of dissolved metals vs.
“single  point  in  time”  concentrations.  The  overall  findings  from  September  2010  were  as  follows:  (i) increased zinc concentration was accompanied by increases in electrical conductivity and sulfate
in water; (ii) for an observed hardness range of 800-2200 mg/L CaCO3 the zinc filteredconcentration (<0.45µm) marginally exceeded the hardness-adjusted ANZECC/ARMCANZ (2000)
trigger value for 95% protection of aquatic species of 72 µg/L; (iii) the zinc DGT concentrationsⒸISERD171

IJERD – International Journal of Environmental and Rural Development (2012) 3-2

did not exceed the trigger value of 72 µg/L; and (iv) further investigation of actual ecotoxicity iswarranted to confirm this finding.
Tosno river in St Petersburg, Russian Federation
DGTs were deployed in Tosno River situated around one of the major industrial areas of St.
Petersburg (Fig.2). The deployment of DGTs in this area was aimed at the identification of thecontamination   source   which   was   suggested   to   be   downstream   of   site   фN1   (small   arrow,   Fig.   2).  
DGTs  were  deployed  at  four  different  sites  (фN1,  фN2,  фN3  and  фN4) following the direction ofthe river flow (large arrow, Fig. 2) for 2 days. At their deployment 5 L water samples were also
taken at the corresponding sites (active sampling).
Table 1 Metals in surface water at Woodcutters Creek (16 June 2010)
Site

Metal

123451
2
3
45

Pb
Pb
Pb
Pb
Pb
Zn
Zn
Zn
Zn
Zn

Active sampling (µg/L)
Total

0.45µm

0.003µm

Passive sampling(µg/L)
C from DGT0.450.4
10.3
2531
47
733

0.1
0.4
0.2
0.1
0.1
22740
5
22

000.1
0.1
0.1
20
425
6130.02
0.5
0.06
0.04
0.5
0.6
29
21
22

Table 2 Zinc in shallow seepage entering Woodcutters Creek andnearby groundwater (September 2010)
Site
WC1
WC2
WC3
WC4
WC5
WC6
WC7
WC8
WC9WC10

Sulfate(mg/L)
1200
701
789
1490
1920
1260
581
628
1590
509

Zinc (µg/L)
Total<0.45µm<0.003µm

from DGT

66
109
850
94
356
271
70
90
97
31252763
26
73
2432
25
47
9.6

9.1
1647235924
121229
8.9

7.5
13.1
16.6
18.3
47.6
15.9
10.5
10.3
25.1
3.7

After deployment and recovery the DGTs were delivered to QHFSS by air freight andanalysed for the following metals: aluminium, cadmium, cobalt, chromium, copper, iron,manganese, nickel, lead and zinc. Based on the obtained data the concentrations of these metals inwater at different sites of the river were estimated using Eq. (1). The results presented in Table 3
showed that a number of metals (aluminium, cadmium, cobalt, chromium and lead) on grab water
analysis were not at detectable levels. In contrast DGTs revealed their presence at all sites. Copper,
nickel and zinc were only  detected  in  grab  water  samples  collected  at  Sites  фN4  and  фN3  though  their presence at all sites was proven by the DGT data.
Only two metals, iron and manganese, were found above detectable levels at all sites for bothactive and passive sampling (Table 3). Despite the difference in the concentrations of these metals
found by the two methods, the change of the concentrations from site to site was similar. As theⒸISERD172

IJERD – International Journal of Environmental and Rural Development (2012) 3-2

grab water samples were not collected in a time integrated manner, the concentrations of metals
differed from the time averaged DGT-derived concentrations.
It is important to note that DGTs accumulate dissolved phase metals and the estimation of theconcentrations is based on diffusion through the gel followed by uptake of dissolved phase metals.
The DGT results are therefore more appropriate in terms of environmental risk since they represent
an immediately available fraction of the chemical or bioavailable fraction. The estimation of metal
concentrations by grab or active sampling is based on their total amounts in water including
particle associated and colloidal metals. This could also explain the difference in iron andmanganese concentrations found by comparing the two methods. The results obtained by two
independent methods (active and passive sampling) draw us to the same conclusion - the source of
the iron and manganese contamination of Tosno river is most likely situated somewhere between
Sites  фN1  and  фN2.
Table 3 Metal concentrations in water from grab samples and by DGTs
Passive sampling (µg/L) (DGT)
Site
фN1SiteфN2SiteфN3SiteфN4

Active sampling (µg/L) (grabwater)
Site
Site
Site
Site
фN1
фN2 фN3
фN4

95% Confidence interval ofmean ± t0.05 sea
Sites фN1  - фN4
Al
16.00
77.00
65.00
63.00
68±19n/dn/dn/dn/d
Cd
0.26
0.17
0.09
0.09
0.12±0.11
n/dn/dn/dn/dCo
0.09
0.18
0.17
0.18
0.18±0.01
n/dn/dn/dn/d
Cr0.62
0.41
0.10
0.10
0.20±0.44bn/dn/dn/dn/dCu
9.40
8.70
6.60
5.70
7±3.8bn/dn/dn/d
2.7Fe
51.00 216.00 253.00 245.00
238±481300 1900 1500 1800
Mn
1.20
89.00
85.00
84.00
86±6.6
150
290
220
210
Ni
11.00
3.80
0.81
1.40
2.0±3.9n/dn/d
3.4n/dPb
0.58
0.52
0.13
0.19
0.28±0.52bn/dn/dn/dn/dZn
0.62
65
48.00
45.00
53±27bn/dn/dn/d
7.5
Note: a. t0.05 = 4.303 from t-distribution table for degrees of freedom (n-1) =2 where n=number of results andstandard  error  (se)  =  s/√n;;  b.  not  significantly  different  from  фN1.

Fig. 2 Deployment sites on Tosno RiverThe  DGT  data  for  the  upstream  Site  фN1  was  compared  with  the  95%  confidence  interval  of  the mean of the   downstream   Sites   фN3   and   фN4   (Table   3).   This   comparison   showed   that,  compared   with   Site   фN1,   there   was   a   significant   increase   for   aluminium,   cobalt,   iron   and  manganese going downstream and a significant decrease for chromium, copper, lead and zincindicating their origin from another source upstream. Thus the DGT data in Table 3 showed that:(i) aluminium, cadmium, cobalt, chromium and lead were present in the water; (ii) aluminium andpossibly traces of cobalt were most likely released into the water along with iron and manganese by
the same source as their concentrations changed in a similar manner from site to site; and (iii) thesource of contamination of water with cadmium, chromium, copper, nickel, lead and zinc was mostlikely situated upstream of   Site   фN1   as   the   concentrations   of   the   metals   were   slowly   decreasing  ⒸISERD173

IJERD – International Journal of Environmental and Rural Development (2012) 3-2

from  Site  фN1  to  Sites  фN3  and  фN4.  The  use  of  DGTs  in  this  experimental  work  provided  a  more  complex picture of contamination of the river with heavy metals than could be achieved by using
any conventional active sampling techniques.
CONCLUSIONSThe results obtained in this study show the potential of the DGT technique to measure ultra-tracelevels of metals in water reliably at a range of temperature and environmental conditions.
Comparison of active and passive sampling techniques showed that both methods produce similar
results when used simultaneously. The use of DGT technique along with traditional methods offers
an extra cost effective method of independent evaluation of environmental sites as well as moresensitive and inexpensive way of obtaining some further information about sites which would bevery difficult to obtain using any conventional active sampling techniques.
This technique allows measurement of time integrated water concentration of dissolved
pollutants in contrast to grab sampling techniques which only represent single points in time. DGTs
require relatively inexpensive and simple materials for their preparation and there is no powersource or active sampling equipment (e.g. pump, flow meter etc) needed during their deployment.
The post deployment process of DGT extraction and clean up takes several minutes using minimal
consumables and chemicals and can be done in the field if necessary.
The DGT results represent an immediately available fraction of the chemical. DGTs mimic theaccumulation that occurs in aquatic biota allowing toxicologists to estimate the actual levels oftoxicities of different metals under the specific environmental conditions and their impact onenvironmental health and health of biological organisms including humans.
ACKNOWLEDGEMENTS
The authors thank Clinical and Statewide Services (CASS), Queensland (Australia) for thefinancial support of this work and staff of Inorganic Chemistry Division of QHFSS (Australia)
especially Michael Peters and Tetyana Krasnoff for assistance with sample analyses and datainterpretation, Prof. N. N. Bobrovitskaya, the Chief of Department of Monitoring surface water ofState Hydrological Institute (Russian Federation) for help with experimental work performed in St.
Petersburg, Drs. Mansour Edraki and Trang Huynh for assistance with the Woodcutters minestudies and Newmont Mining Asia Pacific for access to the Woodcutters site.
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