Liquid scintillation counting (LSC)

The 99_{Tc activity of all DGT samples acquired from the secondary incubation, along with DGT} samples from deployment at day 262 through to day 549 inclusive in the primary incubation, was radiometrically determined through liquid scintillation counting (LSC) using a Packard Tri- Carb 3170 instrument. TEVA resin-gels plus the eluent (1 mL of 4 M HNO3) were analysed directly in 20 mL glass scintillation vials after the addition of 10 mL of cocktail (Meridian Gold Star LT2_{). Each vial was given a brief but vigorous shake to ensure that the gel and resin were} disaggregated. Background samples were prepared by eluting blank TEVA resin-gels in the same manner as for experimental samples. All samples were counted for 20 minutes on an open counting window (0-300 keV), with one background sample inserted per rack of 12 samples. The extent of quenching was monitored through the Transformed Spectral Index of the External Standard (tSIE) parameter. Quenching was consistent between analytical runs and no quench correction was deemed necessary.

The spectra derived from each analytical batch of samples were subjected to a post-count tuning procedure to minimise the contribution of background counts to the total integrated count rate. This process involved trimming the counting window to obtain the highest value for the figure of merit (FoM), where the FoM is calculated using Equation (2.2):

FoM = ( N N_total) 2 B (2.2)

where: N is equal to the number of counts over the selected counting window (e.g. 10-120 keV); Ntotal is the total number of counts over the entire energy window (0-150 keV); and B is the number of counts in the background sample over the selected counting window.

Figure 2.3 shows an example of a sample spectrum produced from an open counting window over the energy range 0-150 keV. The highest FoM value was obtained for the 6-65 keV energy window (highlighted by red dashed lines), so only counts produced in this window were used to calculate the total 99_{Tc count rate of the sample. This procedure was adopted for each} analytical run, resulting in the use of marginally different counting windows between the associated batches of samples. A net count rate for each sample (counts per minute) (CPM) was obtained after subtracting the mean count rate of all background samples from the same analytical run as the sample.

Figure 2.3. Sample spectrum produced from counting a sample containing 99_{Tc over an}

energy window of 0-150 keV. Red dashed lines indicate the portion of the spectrum (5-65 keV) that yields the highest figure of merit value.

The counting efficiency for the sample matrix (TEVA resin-gel disc, 1 mL 4 M HNO3 and 10 mL cocktail) was determined through a mass balance approach, whereby 1 mL aliquots of a 99_{Tc-spiked 0.01 M NaNO3 solution (10 mL) were taken before and after immersion of a TEVA} gel disc in the solution for ~24 hours. The difference in activity between the before and after

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aliquots was taken to represent the activity of 99_{Tc bound to the TEVA resin-gel. The ratio} between the count rate measured directly for eluted TEVA resin-gels and the activity determined through mass balance was taken to represent the counting efficiency. The counting efficiency of the 0.01 M NaNO3 matrix was in turn determined through directly spiking vials containing 1 mL of 0.01 M NaNO3 with a known activity of 99_{Tc. Background} samples with a matrix identical to both sample types (eluted TEVA gels and 0.01 M NaNO3) were also counted.

An overall mean counting efficiency of 0.72 (72%) was derived from the analysis of 8 resin- gels, with a standard deviation of 0.04 (% RSD = 5.71). This value was comparable to that obtained by French et al. (2005), who reported a counting a efficiency of 74.5 ± 2.0 %. Prior to the addition of cocktail, French et al. (2005) placed gel-bearing vials on an orbital shaker for ~24 hours to facilitate the separation of the resin beads from the gel. However, the figure presented here (72 ± 5.71 %) was derived without shaking the gels, so it can be concluded that shaking the resin-gels before counting does not yield a significant improvement in the counting efficiency. The counting efficiency was adjusted according to the counting window over which batches of DGT samples were counted. For example, where sample count rates from a particular run were tuned to an energy window of 10-80 keV, count rates for samples used to derive the counting efficiency were likewise tuned to the same counting window.

Surman (2014) reported that the TEVA resin-gel exhibited a 19.2 ± 1.5% uptake efficiency for 129_{I from a 0.01 M NaCl solution over 24 hours. Iodine-129 undergoes pure} - _{decay with an} Emax of 154 keV, compared to an Emax of 294 keV for 99_{Tc (Lehto and Hou, 2011). Since the soils} in the primary incubation were co-spiked with 129_{I (Section 2.1.3), there is the potential for} 129_I bound to the TEVA resin-gel to contribute to the observed count rate and produce an artificially elevated 99_{Tc activity. To assess the potential interference of} 129_{I, the spectra of}

primary incubation containing 129_{I and subsamples of their counterparts from the secondary} incubation that did not contain 129_{I. The comparison was made between samples acquired} from similarly-aged soils. Both spectra were subdivided into energy windows and the number of counts within each window was calculated as a proportion of the total number of counts over the entire spectrum to obtain a ‘count ratio’ (Figure 2.4). This method can be used because the endpoint of the 129_{I spectrum is lower than that for} 99_{Tc, so any contribution of} 129_{I counts to the} 99_{Tc spectrum will alter the count ratio. Figure 2.4 reveals that for all energy} windows of the spectra, the count ratios were within error of each other for all the soils tested. Based upon this finding, the uptake of 129_{I and resulting spectral interference was deemed} negligible.

Figure 2.4. A comparison of mean count ratios (energy window counts/total spectrum counts) for a batch (n = 6) of TEVA DGT resin-gels deployed in soil samples containing

iodine and those without iodine. 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 8-20 20-30 30-40 40-50 50-60

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