**Gamma-Ray Spectrometry and the Investigation of Environmental and Food Samples**

Markus R. Zehringer

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/67099

#### **Abstract**

Gamma radiation consists of high‐energy photons and penetrates matter. This is an advantage for the detection of gamma rays, as gamma spectrometry does not need the elimination of the matrix. The disadvantage is the need of shielding to protect against this radiation. Gamma rays are everywhere: in the atmosphere; gamma nuclides are produced by radiation of the sun; in the Earth, the primordial radioactive nuclides thorium and uranium are sources for gamma and other radiation. The technical enrichment and use of radioisotopes led to the unscrupulously use of radioactive material and to the Cold War, with over 900 bomb tests from 1945 to 1990, combined with global fallout over the northern hemisphere. The friendly use of radiation in medicine and for the production of energy at nuclear power plants (NPPs) has caused further expositions with ionising radiation. This chapter describes in a practical manner the instrumentation for the detection of gamma radiation and some results of the use of these techniques in environmental and food investigations.

**Keywords:** gamma‐ray spectrometry, neutron activation analysis, radioactive contamination, radiocaesium, radiostrontium

#### **1. Gamma spectrometric equipment for the control of food and environmental samples**

#### **1.1. Theory of gamma spectrometry**

Gamma rays are electromagnetic radiation and are part of photon radiation. They are produced when transitions between excited nuclear levels of a nucleus occur. Delayed gamma rays are emitted during the decay of the parent nucleus and often follow a Beta decay. There can be many transitions between energy levels of a nucleus, resulting in many gamma‐ray lines. The typical wavelength is 10-7 to 10‐13 m, corresponding to an energy range of 0.01–10 MeV.

Gamma rays can be detected through their interaction with matter. There are three main processes: photoelectric absorption, Compton scattering and pair production. The photoelectric effect occurs when a gamma ray interacts with an electron of an inner shell of an atom and a photoelectron is emitted. This is the most important effect for the detection of gamma rays with semiconductor detectors. The effect of Compton scattering describes the interaction of a gamma ray with matter when some of its energy is transferred to the recoil electron. The energy transmitted is a function of the scattering angle. Therefore, the Compton effect results in a broad range of gamma‐ray energies, which gives a continuous background in the gamma spectrum. Pair production is the third effect when a gamma ray is absorbed by matter and loses energy to produce an electron/positron pair. This effect only occurs when gamma rays have more than 1.02 MeV energy, twice the rest mass energy of an electron (0.551 MeV) [1–4].

#### **1.2. Semiconductor detectors**

Until the mid‐1970s, no germanium could be produced of the desired purity. The purity required for large‐volume detectors could only be produced by doping germanium crystals with n‐type impurities, such as lithium (Ge(Li)‐detectors). Later on, pure germanium crystals became available in n‐type or p‐type form and of closed‐end coaxial or planar geometry and as bore‐hole crystals. n‐type detectors cover an energy range from about 10 keV to 3 MeV, while p‐type detectors range from 40 keV to 3 MeV. p‐type detectors with a carbon fibre or beryllium window instead of the aluminium end cap are best to detect energies below 100 keV.

#### **1.3. Requirements for proper gamma spectrometry**

The minimum detectable activity (MDA) of a Ge‐detector depends on its energy resolution, the efficiency of the crystal, peak/Compton‐factor, background, measuring time, sample geometry, self‐absorption and the emission probabilities of the gamma emission lines of the radionuclide. Information can be obtained from the homepages of the providers, such as Ortec, Canberra and others [5–7].

#### *1.3.1. Detector calibration*

Ge‐detectors are calibrated for the energy response of the multi‐channel analyser, peak resolution and counting efficiency. Normally, gamma spectroscopists use commercially available calibration sources containing a mix of gamma‐nuclides, which cover the whole energy range. Such nuclides are 210Pb or 241Am, 109Cd, 139Ce, 57Co and 60Co, 134Cs or 137Cs, 88Y, 85Sr. Such mixes cover an energy range from 46 keV (210Pb) to 1836 keV (<sup>88</sup>Y). The disadvantage is that some of the nuclides have short half lives (e.g. 85Sr has a half‐life of 65 days) and therefore such calibration mixes only can be used for a year. Sometimes it might be better to use a mix of a low‐ energy nuclide (e.g. 241Am) and 152Eu, which disintegrates slowly (half‐life of 13.5 years) and shows a multiplicity of emission lines from 122 to 1528 keV. The disadvantage is the summing effects of 152Eu, which require correction (e.g. using software based on Monte Carlo simulations). Furthermore, the calibration of peak resolution and efficiency of the sample geometry is necessary; this is performed with the same calibration sources. We use calibration sources with 241Am/152Eu of different sample geometries. They are solidified by gelation and have a density of 1.0 g/mL. Such sources are available, e.g. at Czech Metrology Institute at Prague [7]. Peak resolution should be tested on a regular basis together with the energy calibration. The peak shape is close to a Poisson distribution. For more counts, the distribution is closer to a Gaussian shape. The peak resolution is given by the quotient of FWTM (full width at tenth maximum) versus FWHM (full width at half maximum). Ge‐detectors show resolutions of typically 1–2.5 keV. The software for the recording and analysis of pulse high spectra is available from Canberra, Ortec products, Oxford instruments, etc. Interwinner software from ITEC is a commonly used software in Germany and Switzerland [8].

#### *1.3.2. Background*

Gamma rays can be detected through their interaction with matter. There are three main processes: photoelectric absorption, Compton scattering and pair production. The photoelectric effect occurs when a gamma ray interacts with an electron of an inner shell of an atom and a photoelectron is emitted. This is the most important effect for the detection of gamma rays with semiconductor detectors. The effect of Compton scattering describes the interaction of a gamma ray with matter when some of its energy is transferred to the recoil electron. The energy transmitted is a function of the scattering angle. Therefore, the Compton effect results in a broad range of gamma‐ray energies, which gives a continuous background in the gamma spectrum. Pair production is the third effect when a gamma ray is absorbed by matter and loses energy to produce an electron/positron pair. This effect only occurs when gamma rays have more than 1.02 MeV energy, twice the rest mass energy of an electron (0.551 MeV) [1–4].

Until the mid‐1970s, no germanium could be produced of the desired purity. The purity required for large‐volume detectors could only be produced by doping germanium crystals with n‐type impurities, such as lithium (Ge(Li)‐detectors). Later on, pure germanium crystals became available in n‐type or p‐type form and of closed‐end coaxial or planar geometry and as bore‐hole crystals. n‐type detectors cover an energy range from about 10 keV to 3 MeV, while p‐type detectors range from 40 keV to 3 MeV. p‐type detectors with a carbon fibre or beryllium window instead of the aluminium end cap are best to detect energies below 100 keV.

The minimum detectable activity (MDA) of a Ge‐detector depends on its energy resolution, the efficiency of the crystal, peak/Compton‐factor, background, measuring time, sample geometry, self‐absorption and the emission probabilities of the gamma emission lines of the radionuclide. Information can be obtained from the homepages of the providers, such as

Ge‐detectors are calibrated for the energy response of the multi‐channel analyser, peak resolution and counting efficiency. Normally, gamma spectroscopists use commercially available calibration sources containing a mix of gamma‐nuclides, which cover the whole energy range. Such nuclides are 210Pb or 241Am, 109Cd, 139Ce, 57Co and 60Co, 134Cs or 137Cs, 88Y, 85Sr. Such mixes cover an energy range from 46 keV (210Pb) to 1836 keV (<sup>88</sup>Y). The disadvantage is that some of the nuclides have short half lives (e.g. 85Sr has a half‐life of 65 days) and therefore such calibration mixes only can be used for a year. Sometimes it might be better to use a mix of a low‐ energy nuclide (e.g. 241Am) and 152Eu, which disintegrates slowly (half‐life of 13.5 years) and shows a multiplicity of emission lines from 122 to 1528 keV. The disadvantage is the summing effects of 152Eu, which require correction (e.g. using software based on Monte Carlo simulations). Furthermore, the calibration of peak resolution and efficiency of the sample geometry is necessary; this is performed with the same calibration sources. We use calibration sources with 241Am/152Eu of different sample geometries. They are solidified by gelation and have a

**1.2. Semiconductor detectors**

4 New Insights on Gamma Rays

Ortec, Canberra and others [5–7].

*1.3.1. Detector calibration*

**1.3. Requirements for proper gamma spectrometry**

It is absolutely necessary to know the background of the Ge‐detector system. This depends on the shielding of the detector and the background of the laboratory. We use shielding with 10 cm of lead and an inner layer of copper 5‐mm thick. Before our laboratory was built, radiation‐poor materials for the construction of the walls, soil and ceiling were sought. We analysed different components, such as gravel, sand, white cement and additives from different producers. Our choice for gravel and sand was a local producer in the Swiss Alps. The cement was from Dyckerhoff in Denmark. With this effort, we could reduce the background of our counting laboratory from 70 to 20 nSv/h. Nevertheless, background is still present. Incoming cosmic muons are not suppressed. They can be reduced by building an anticoincidence chamber over the detector. Vojtyla et al. could reduce the background by a factor of 2.2 [9]. Another approach is described by Seo et al., using Marinelli beakers of aluminium and purging the surrounding air of the detector reduced the background [10]. The background has to be measured periodically for each geometry to this end; a sample container with deionised water is placed on the detector and counted over a weekend. The background depends on the counting geometry and the matrix.

#### *1.3.3. Attenuation effects*

Photons may be absorbed by the sample matrix and therefore do not reach the detector. This effect depends on the elemental composition of the sample and its density. The photon attenuation effect is not negligible for photons with lower energies and for high‐volume sample geometries. It has to be taken into account with the Gamma spectrometry software or software based on Monte Carlo simulations.

#### *1.3.4. Coincidence summing effect*

This effect occurs for all radionuclides emitting at least two photons in sequence and is a function of the source‐detector distance and the detector efficiency. With a 50% Ge‐detector, more coincidence summing is recorded than with a 20% detector. To avoid this effect, the samples may be counted a certain distance away from the detector.

#### *1.3.5. Dead time*

Samples of high activities may lead to a loss of peak counts. This effect occurs when the pulse processing electronics are slower than the frequency of the incoming photons. This leads to a dead time of the detector. Normally, environmental and food samples do not show such high activities that result in dead times of the detector. Dead time can be avoided by counting the sample at a well defined distance from the detector. Such constellations can be important when the samples have to be analysed for an emergency case.

#### **1.4. Best sample geometries for gamma‐ray analyses**

MDA is a function of the detector efficiency and the sample weight. The best gamma‐ray efficiencies are achieved with Marinelli beakers of 1 or 2 L, as the gamma rays of the sample interfere on top and on the sides with the Ge‐crystal, gaining more efficiency. This geometry is best when large sample amounts of water, soil, vegetation, food, etc. are available. Marinelli geometries have to be calibrated carefully and coincidence summing has to be corrected. For small sample amounts, dishes with volumes of 32 and 77 mL (12 or 24 mm height and 6.5 cm in diameter) might be used. In small sample devices, the attenuation of gamma rays by the sample matrix is remarkably decreased. The disadvantage is the small sample load of 30–80 g. Other geometries commonly used are beakers of 250 and 500 mL volume. To enhance the sensitivity of the gamma‐ray spectrometry, samples containing water may be freeze‐dried. For milk samples, a concentration factor of eight can be achieved by freeze‐drying. Soil, vegetation and food samples should also be dried (e.g. at 120°C). Soil samples are ground and sieved to eliminate large particles, such as stones or root parts. Further practical advice is given in other sources [11, 12].

#### **1.5. Interpretation of gamma spectrometry data of natural radionuclides**

Dose‐relevant radionuclides of the natural decay series of 238U, 232Th and 235U are nuclides from uranium, radium, thorium, actinium, lead and polonium. Relevant criteria are the half‐ life and the dose coefficients of these radionuclides. With a few exceptions, these radionuclides can be detected via the gamma emissions of their daughter nuclides. The exceptions are 7 Be, 40K, 223Ra, 210Pb, 231Pa. The detection of 226Ra and 224Ra needs a secular equilibrium between the mother nuclide and its daughters. This can be reached when the sample is packed gas tight for at least the sevenfold half‐life of the corresponding radon nuclide prior to the gamma analysis. This equates to 20 days in the case of 226Ra, or 7 min for 224Ra.

 <sup>226</sup> Ra⟶-*<sup>α</sup>* 222R <sup>n</sup>⟶-*<sup>α</sup>* 218P <sup>o</sup>⟶-*<sup>α</sup>* 214P <sup>b</sup>⟶-*<sup>α</sup>* 214B <sup>i</sup>⟶-<sup>β</sup> 214P <sup>o</sup> <sup>224</sup> <sup>R</sup>a⟶-*<sup>α</sup>* 220R <sup>n</sup>⟶-*<sup>α</sup>* 216P <sup>o</sup>⟶-*<sup>α</sup>* 212P <sup>b</sup>⟶-<sup>β</sup> 212B <sup>i</sup>⟶-<sup>β</sup> 208T <sup>l</sup>⟶-<sup>β</sup> 208P <sup>b</sup> (1)

After reaching secular equilibrium, the activities of the daughters of 222Rn and 226Ra can be set equal to the activities of 214Pb and 214Bi. Often, the direct determination of 226Ra is not possible due to the major interference with the gamma line of 235U around 186 keV. Therefore, this is the best method to detect radium using gamma‐ray spectrometry. The same applies for the system 228Th/224Ra and their daughters 212Pb and 212Bi. Here, equilibrium is reached within minutes due to the very short half‐life of 220Rn.

Other mother‐daughter systems can be used for the determination of 232Th, 228Ra (a pure β‐ emitter), 227Ac and 238U.

$$\text{^{2227}\text{Th} \rightarrow \text{^{228}\text{Ac} + a \rightarrow \text{^{228}\text{Ac} + \beta \; \_{2}\text{T} \text{Ac} \rightarrow \text{^{227}\text{Th} + \beta \; \_{2}\text{Th} \rightarrow \text{^{234}\text{Th} + a \rightarrow \text{^{24m}\text{Pa} + \beta \; \_{2}\text{T} \text{Ac} + \beta \; \_{2}\text{T} \text{Ac}}} \text{(2)}$$

Due to the very short half‐lives of the daughters, these radionuclides are already at equilibrium. **Table 1** shows the adequate choice of gamma emission lines for relevant natural radionuclides. In natural uranium, the activity ratio of 238U/235U is 21.7.

high activities that result in dead times of the detector. Dead time can be avoided by counting the sample at a well defined distance from the detector. Such constellations can be important

MDA is a function of the detector efficiency and the sample weight. The best gamma‐ray efficiencies are achieved with Marinelli beakers of 1 or 2 L, as the gamma rays of the sample interfere on top and on the sides with the Ge‐crystal, gaining more efficiency. This geometry is best when large sample amounts of water, soil, vegetation, food, etc. are available. Marinelli geometries have to be calibrated carefully and coincidence summing has to be corrected. For small sample amounts, dishes with volumes of 32 and 77 mL (12 or 24 mm height and 6.5 cm in diameter) might be used. In small sample devices, the attenuation of gamma rays by the sample matrix is remarkably decreased. The disadvantage is the small sample load of 30–80 g. Other geometries commonly used are beakers of 250 and 500 mL volume. To enhance the sensitivity of the gamma‐ray spectrometry, samples containing water may be freeze‐dried. For milk samples, a concentration factor of eight can be achieved by freeze‐drying. Soil, vegetation and food samples should also be dried (e.g. at 120°C). Soil samples are ground and sieved to eliminate large particles, such as stones or root parts. Further practical advice is given in

Dose‐relevant radionuclides of the natural decay series of 238U, 232Th and 235U are nuclides from uranium, radium, thorium, actinium, lead and polonium. Relevant criteria are the half‐ life and the dose coefficients of these radionuclides. With a few exceptions, these radionuclides can be detected via the gamma emissions of their daughter nuclides. The exceptions are

Be, 40K, 223Ra, 210Pb, 231Pa. The detection of 226Ra and 224Ra needs a secular equilibrium between the mother nuclide and its daughters. This can be reached when the sample is packed gas tight for at least the sevenfold half‐life of the corresponding radon nuclide prior to the gamma

<sup>224</sup> <sup>R</sup>a⟶-*<sup>α</sup>* 220R <sup>n</sup>⟶-*<sup>α</sup>* 216P <sup>o</sup>⟶-*<sup>α</sup>* 212P <sup>b</sup>⟶-<sup>β</sup> 212B <sup>i</sup>⟶-<sup>β</sup> 208T <sup>l</sup>⟶-<sup>β</sup> 208P <sup>b</sup>

After reaching secular equilibrium, the activities of the daughters of 222Rn and 226Ra can be set equal to the activities of 214Pb and 214Bi. Often, the direct determination of 226Ra is not possible due to the major interference with the gamma line of 235U around 186 keV. Therefore, this is the best method to detect radium using gamma‐ray spectrometry. The same applies for the system 228Th/224Ra and their daughters 212Pb and 212Bi. Here, equilibrium is reached within

Other mother‐daughter systems can be used for the determination of 232Th, 228Ra (a pure β‐

(1)

when the samples have to be analysed for an emergency case.

**1.5. Interpretation of gamma spectrometry data of natural radionuclides**

analysis. This equates to 20 days in the case of 226Ra, or 7 min for 224Ra.

minutes due to the very short half‐life of 220Rn.

emitter), 227Ac and 238U.

<sup>226</sup> Ra⟶-*<sup>α</sup>* 222R <sup>n</sup>⟶-*<sup>α</sup>* 218P <sup>o</sup>⟶-*<sup>α</sup>* 214P <sup>b</sup>⟶-*<sup>α</sup>* 214B <sup>i</sup>⟶-<sup>β</sup> 214P <sup>o</sup>

**1.4. Best sample geometries for gamma‐ray analyses**

other sources [11, 12].

6 New Insights on Gamma Rays

7


**Table 1.** Common used emission lines for the detection of natural radionuclides with gamma‐ray spectrometry. Emission probabilities are mean values from different sources [13–17].

When analysing for natural radionuclides, it is very important to know and to reconsider the background of the gamma system. Prominent radionuclides in the background are radon and its daughter nuclides from underground radiation. The background has to be determined for each geometry and has to be subtracted from the sample. We determine the background radiation using gamma spectrometry with sample containers containing deionised water, to take into account that the sample matrix also absorbs a part of the background radiation.

#### **2. Instrumental neutron activation analysis**

#### **2.1. Principle**

Instrumental neutron activation analysis (INAA) is based on the production of short‐lived radionuclides by nuclear reactions. Most frequently, reactor neutrons (i.e. thermal neutrons) are used to activate many nuclides to produce radioactive nuclides. The efficiency of the irradiation process depends on the flux density of the neutrons and the cross section of the nuclear reaction of the irradiated nucleus. Typically, the thermal neutrons required for INAA are generated in a nuclear reactor [18, 19]. For our experiments, we used the reactor at the University of Basel (AGN‐211‐P), which is a light water‐moderated swimming pool reactor. The compact core contained 2.2 kg of highly enriched uranium and a graphite reflector around the core. This uranium gave a thermal neutron flux of 3.8 × 1010 n/cm2 /s at a power of 2 kW. The insertion of samples into the core was possible over a cannula (brown cylinder above the reactor in **Figure 1**) through the so‐called glory hole. The glory hole consists of an air‐filled pipe of a diameter of 1" (2.5 cm), which goes from above the pool down and through the centre of the reactor.

**Figure 1.** Equipment for NAA. Swimming pool reactor (left) gamma‐ray spectrometer with lead shielding (middle) gamma‐ray spectrum (above right) curry sample and sample device for the irradiation [4].

#### **2.2. Operational procedure**

When analysing for natural radionuclides, it is very important to know and to reconsider the background of the gamma system. Prominent radionuclides in the background are radon and its daughter nuclides from underground radiation. The background has to be determined for each geometry and has to be subtracted from the sample. We determine the background radiation using gamma spectrometry with sample containers containing deionised water, to take into account that the sample matrix also absorbs a part of the background radiation.

Instrumental neutron activation analysis (INAA) is based on the production of short‐lived radionuclides by nuclear reactions. Most frequently, reactor neutrons (i.e. thermal neutrons) are used to activate many nuclides to produce radioactive nuclides. The efficiency of the irradiation process depends on the flux density of the neutrons and the cross section of the nuclear reaction of the irradiated nucleus. Typically, the thermal neutrons required for INAA are generated in a nuclear reactor [18, 19]. For our experiments, we used the reactor at the University of Basel (AGN‐211‐P), which is a light water‐moderated swimming pool reactor. The compact core contained 2.2 kg of highly enriched uranium and a graphite reflector

of 2 kW. The insertion of samples into the core was possible over a cannula (brown cylinder above the reactor in **Figure 1**) through the so‐called glory hole. The glory hole consists of an air‐filled pipe of a diameter of 1" (2.5 cm), which goes from above the pool down and through

**Figure 1.** Equipment for NAA. Swimming pool reactor (left) gamma‐ray spectrometer with lead shielding (middle)

gamma‐ray spectrum (above right) curry sample and sample device for the irradiation [4].

/s at a power

around the core. This uranium gave a thermal neutron flux of 3.8 × 1010 n/cm2

**2. Instrumental neutron activation analysis**

**2.1. Principle**

8 New Insights on Gamma Rays

the centre of the reactor.

The detection limit of gamma spectrometry is given by the half‐life of the activated nuclides and the underlying Compton background from highly activated nuclides, such as sodium or chloride. Gold foils are used as the internal standard for each sample and are set on top of each sample. A sample series of 12 samples each of 1–2 g material was irradiated for 30 min at a power of 2 kW. Each irradiation place in the neutron field of the reactor was calibrated with coagulated salt solutions containing a known amount of the analyte and a corresponding gold foil. The response factors of each analyte to its gold foil for each place in the neutron field were then calculated (comparator method).

#### **2.3. Common applications of INAA**

#### *2.3.1. Determination of total bromine content in food samples*

The total bromine content of food, such as tea, coffee, dried mushrooms, vegetables and spices, gives information about the use of methyl bromide, a fumigant. The application of methyl bromide results in residues of bromide. This bromide can be activated to the gamma‐active compound 82Br (half‐life of 35 h) by neutrons and analysed with gamma spectrometry. After irradiation of 30 min, the samples have to be cooled down for several hours (for the disintegration of activated sodium and chloride nuclides). The gamma analysis takes 15 min.

$$\text{Activation process}: \text{ } \text{``Br} + \text{\*\*} \to \text{\*2Br} \qquad \text{Decay process}: \text{\*2Br} \to \text{\*2Kr} + \text{\#} \text{ } \text{\*} \text{---} \qquad \text{(3)}$$

According to **Table 2**, many objections had to be executed for spices and dried mushrooms, which were treated with methyl bromide. Our last investigation of tea resulted in one objection. Since some years, the use of methyl bromide as a fumigant has been rare. Other fumigants, such as sulfuryl fluoride, hydrogen cyanide and phosphines, have become more important [20].

#### *2.3.2. Determination of total iodine content in food*

Algae and other food samples rich in iodine were irradiated to determinate the total content of iodine. Iodine is essential for the production of thyroid hormones and prevents goitre. In most European countries, people suffer from an iodine deficiency. The iodine level can be increased by the consumption of iodine‐enriched food and dietary supplements. However, high levels of iodine (i.e. over 500 µg/kg) can result in hyperthyreosis. Therefore, the range of tolerance for iodine is narrow and it is important to declare the correct iodine content for food.

About 1 g of sample can be activated with reactor neutrons (30 min, 2 kW). The radioactive product 128I is analysed directly using a gamma spectrometer

$$\text{Activation process}: \text{ } ^{127}I \vdash n \rightarrow ^{128}I \qquad \text{Decay process}: \text{ } ^{128}I \rightarrow ^{128}Xe + \beta + \gamma. \tag{4}$$

The half‐life of 128I is only 25 min; therefore, the samples had to be counted immediately after the activation. This is unfavourable regarding the background of other activated ions and results in higher detection limits. The total iodine content of fish, seafood, algae and dietary supplements can be analysed [22, 23].


Objections, which prove a use of the fumigant methyl bromide, show a bromine content over the limit. Limit values are 50 mg/kg (coffee, tea) and 100 mg/kg (spices mushrooms) according to the Swiss Ordinance on contaminants and constituents in Food [21]. The number of investigated samples is given in brackets.

**Table 2.** INAA analyses of food samples for total bromine content.

#### *2.3.3. Determination of flame‐retarding agents in plastics*

INAA can be used as a screening analysis for flame‐retarding agents in plastic materials, such as decabromo‐bis‐phenylether or tetrabromo‐bisphenol A. The activation and decay process are the same as for the bromine analysis in food samples. The INAA gives information about the total content of brominated flame‐retarding agents. We used INAA as a screening analysis and samples containing a high amount of bromine were detected and then analysed with gas chromatography to determine the amount of different flame‐retarding compounds [24–26].

#### *2.3.4. Determination of U and Th in suspended matter, sediment and soil samples*

About 1 g samples of dried and ground material (e.g. freeze‐dried suspended matter) were irradiated for 30 min at a power of 2 kW. After a cooling period of 2 h, the samples were analysed with a gamleast 30 min [27]

$$\begin{aligned} \text{In general case we have } \{\square\} \\\\ \text{Activation process: } \text{:} \quad & 2^{28}\text{U} + \text{:} \to \text{:} \quad \not\to +\gamma \quad \text{and} \quad & 2^{23}\text{Th} + \text{:} \to \text{:} \quad \not\to +\infty \\\\ \text{Decay processes: } \text{:} \quad & 2^{29}\text{U} \to \, ^{238}\text{Np} + \beta + \gamma \to \, ^{239}\text{Pu} + \beta + \gamma \\\\ \text{and } \, ^{233}\text{Th} \to \, ^{233}\text{Pa} + \beta + \gamma \to \, ^{233}\text{U} + \beta + \gamma \end{aligned} \tag{5}$$

#### **3. Gamma‐ray sources in the environment**

Materials that emit radioactive rays are called radioactive sources. We distinguish between naturally occurring radioactive material (NORM) and technologically enriched naturally occurring radioactive material (TENORM) on the one hand and artificially produced radioactive sources on the other. Radionuclides may emit different rays, such as alpha, beta and gamma rays. Most α‐ and β‐decays are accompanied by γ‐rays. There are only a few important exceptions, such as 210Po, 63Ni, or 90Sr, which are pure α‐ or β‐emitters. Therefore, many important β ‐nuclides can be detected with gamma spectrometry.

#### **3.1. First use of natural radioactivity**

Soon after the discovery of radioactivity by Henry Becquerel, Pierre and Marie Curie and others, when radium became available, the production and the commercial use of TENORM began. Radium and thorium were used as remedies to cure many diseases. Underwear and wool, soap, lipstick, hair shampoo, toothpaste, suppositories, soda drinks, butter, etc. were spiked with NORM or TENORM. The negative effects of TENORM went visible only decades later. Quacks, such as William Bailey, earned their money by dealing with radioactive sources as medicinal drugs. It was therapy with radithor (a mixture of 226Ra and 228Ra) that led to the tragic death of Eben McBurney Byers [28]. Another tragedy was the "radium girls" from New Jersey. Many young women became ill or died from painting watch dials with radium. These and many more cases became public and led to the decline of the popularity of radioactivity [29]. Today, radon therapy in radon water, inhalation of radon air in tunnels or drinking of radon water remain the few existing applications of NORM for health cures against chronic diseases, rheumatic diseases and Morbus Bechterew. The health effects of radon are well described, but are not fully understood [30]. Such dubious items of the past are sometimes still present in households (see Section 3.3).

#### **3.2. Natural radioactivity in food**

*2.3.3. Determination of flame‐retarding agents in plastics*

**Table 2.** INAA analyses of food samples for total bromine content.

constituents in Food [21]. The number of investigated samples is given in brackets.

ing compounds [24–26].

1988 10 (172)

10 New Insights on Gamma Rays

1995 0 (33)

2001 1 (26)

1989 4 (34) 7 (48)

1996 1 (33) 1998 0 (15)

lysed with a gamleast 30 min [27]

*Activation processes* :

*Decay processes* :

INAA can be used as a screening analysis for flame‐retarding agents in plastic materials, such as decabromo‐bis‐phenylether or tetrabromo‐bisphenol A. The activation and decay process are the same as for the bromine analysis in food samples. The INAA gives information about the total content of brominated flame‐retarding agents. We used INAA as a screening analysis and samples containing a high amount of bromine were detected and then analysed with gas chromatography to determine the amount of different flame‐retard-

Objections, which prove a use of the fumigant methyl bromide, show a bromine content over the limit. Limit values are 50 mg/kg (coffee, tea) and 100 mg/kg (spices mushrooms) according to the Swiss Ordinance on contaminants and

**Year/food Spices Dried mushrooms Tea Coffee Chocolate Rice**

1994 0 (30) 0 (24)

1990 0 (30)

1991 5 (28) 0 (27)

2002 2 (33) 2006 0 (17) 2009 1 (40)

1992 2 (57) 0 (5)

About 1 g samples of dried and ground material (e.g. freeze‐dried suspended matter) were irradiated for 30 min at a power of 2 kW. After a cooling period of 2 h, the samples were ana-

*U* + *β* + *γ and* <sup>232</sup>

*Pu* <sup>+</sup> *<sup>β</sup>* <sup>+</sup> *<sup>γ</sup> and* <sup>233</sup> Th <sup>→</sup> <sup>233</sup> Pa <sup>+</sup> <sup>β</sup> <sup>+</sup> *<sup>γ</sup>* <sup>→</sup> <sup>233</sup> <sup>U</sup> <sup>+</sup> <sup>β</sup> <sup>+</sup> *<sup>γ</sup>* (5)

*Th* + *n* →<sup>233</sup>

*Th*

*2.3.4. Determination of U and Th in suspended matter, sediment and soil samples*

*U* + *n* →<sup>239</sup>

*Np* + *β* + *γ* →<sup>239</sup>

238

 239 *U* →<sup>239</sup> Some natural radionuclides from the natural decay series of uranium and thorium enter the food chain. The alpha nuclide polonium‐210 (210Po), a product of the decay series of uranium‐238 (238U), is enriched in the intestinal tract of mussels and fish. Lead‐210 (210Pb), radium and thorium nuclides are present in cereals. In addition, spices and salt may contain elevated levels of radium and potassium‐40 (40K). Generally, potassium‐rich food is also rich in 40K (e.g. tea, vegetables). A special case is Brazil nuts, which are enriched in radium from soil. This is well described in [31]. Tap water may contain uranium, radium and their daughter nuclides depending on the local geological situation [32].

#### **3.3. Radioactive sources in consumer products**

Remnants from the application of natural radionuclides in the past century may be present in households even today. Our laboratory maintains a collection of radioactive objects that people brought in for investigation or disposal.

The use of thorium in flame detectors is widespread: for instance, in dials with radium in watches or on dial‐plates for military use, coloured glass pearls or drinking glasses containing uranium oxides, wall tiles with uranium oxides, etc (**Table 3**). The finders of such items are encouraged to bring them to a specialised laboratory or to a collecting point for radioactive materials. The included radioactive material may be harmful.


**Table 3.** Consumer products containing radioactive materials (modified after Ref. [37]).

Incandescent gas mantles are in use without the knowledge of any possible danger. They contain 232Th‐oxides used to produce a bright light, which may be inhaled when the gas mantle disintegrates. In Germany and Switzerland, these gas mantles have been banned from the market. Attention has to be given to imports of products from the Far East. They may still contain thorium oxides.

A special case is the "Radium Drinkkur" (radium drinking device). It was used at the start of the twentieth century. The "Drinkkur" contained a small piece of pitch blend as a radium source (e.g. 100 MBq). The idea was to enrich drinking water with radon by emanation. Radon is said to be a remedy against rheumatics. Our own experiments have shown that a 2 month application of such a drinking therapy gave a yearly dose of 34 mSv, only from the radon. Unfortunately, radium was also released when the source was immersed into the water. Therefore, an even higher dose with additionally washed‐out radium could be incorporated [33].

**Figure 2.** (1) Wall tiles; (2) pitch‐blend source for radium drinking device (3); (4) watch, compass, glass pearls; (5) gas mantle and static eliminator; (6) bowl with paintings.

In the 1960s, radioactive wall tiles were discovered in Swiss households. They were produced with uranium oxide to obtain a brilliant red colour. Radiation from the walls of kitchens and toilets was of minor concern (low gamma energies), but a certain risk existed when the tiles were removed. The unavoidable dust contained uranium oxides; its inhalation had to be avoided. The Federal Office of Public Health regulated the professional drawbacks and disposal of the radioactive tiles [34] (**Figure 2**).

#### **4. Gamma nuclides in the environment**

Radioactive fallout is the main source for artificial radionuclides in the environment. In the following section, the application of gamma‐ray spectrometry in Swiss environmental monitoring programs will be presented with examples [38].

#### **4.1. Swiss monitoring programme**

The use of thorium in flame detectors is widespread: for instance, in dials with radium in watches or on dial‐plates for military use, coloured glass pearls or drinking glasses containing uranium oxides, wall tiles with uranium oxides, etc (**Table 3**). The finders of such items are encouraged to bring them to a specialised laboratory or to a collecting point for radioactive

**Consumer product Radionuclide(s) Radionuclide content range**

H 147Pm 226Ra

H 226Ra

H 147Pm

Static eliminators 210Po 1–19 MBq Dental products natU up to 4 Bq Gas mantles 232Th 1–2 kBq Welding rods 232Th 0.2–1.2 kBq

Glassware: vaseline glass, canary flint glass natU 100 kBq Lamp starters <sup>85</sup>Kr 0.6 kBq Smoke detectors 241Am 37 kBq Electron capture detectors 63Ni 370 kBq Drinking devices "Radium Drinkkur" 226Ra, (222Rn) 100 MBq Wall tiles, ceramics natUO<sup>3</sup> 50–500 kBq Granitic surfaces natU 5–10 kBq/kg Cardiac pacemaker [36] 239Pu 113 GBq

**Table 3.** Consumer products containing radioactive materials (modified after Ref. [37]).

4–930 MBq 0.4–4 MBq 0.07–170 kBq

28 MBq 15 kBq

10 kBq 300 kBq

232Th 5–75 Bq

Incandescent gas mantles are in use without the knowledge of any possible danger. They contain 232Th‐oxides used to produce a bright light, which may be inhaled when the gas mantle disintegrates. In Germany and Switzerland, these gas mantles have been banned from the market. Attention has to be given to imports of products from the Far East. They may still

A special case is the "Radium Drinkkur" (radium drinking device). It was used at the start of the twentieth century. The "Drinkkur" contained a small piece of pitch blend as a radium source (e.g. 100 MBq). The idea was to enrich drinking water with radon by emanation. Radon is said to be a remedy against rheumatics. Our own experiments have shown that a 2 month application of such a drinking therapy gave a yearly dose of 34 mSv, only from the radon. Unfortunately,

contain thorium oxides.

Optical glasses Ophthalmic lenses [35]

12 New Insights on Gamma Rays

materials. The included radioactive material may be harmful.

Radio luminous timepieces <sup>3</sup>

Marine compass <sup>3</sup>

Aircraft luminous safety devices <sup>3</sup>

The Federal Office of Public Health (BAG) publishes a yearly report on the radioactivity in the environment and on radiation doses of the Swiss public. Several institutions, such as Labor Spiez (LS), Institut de Radiophysique Appliqué (IRA), Paul Scherrer Institut of ETH Zurich (PSI), the Swiss Federal Institute of Aquatic Science and Technology (EAWAG), the National Emergency Operations Centre (NAZ), the Swiss Accident Insurance Fund (SUVA), the Swiss Federal Nuclear Safety Inspectorate (ENSI), the BAG, the European Organization for Nuclear Research (CERN), laboratories of the NPPs and some of the state laboratories of Switzerland, analyse different compartments with different techniques [39]. The main content of the reports lies in the supervision of emissions from NPPs and other industry using and producing radionuclides, the emissions from wastewater treatment plants and waste incineration plants. The report shows the results of the yearly survey of a grid of environmental sampling points, such as farms, sampling points in the vicinity of NPPs, water and air monitoring stations. Data from monitoring stations are collected and interpreted. These are the NADAM‐net of the NAZ (66 automatic radiation dose meters [40]), the MADUK‐ net, operated by the ENSI (radiation dose meters [41]), RADAIR (air monitoring stations) and URANET (Automatic River monitoring detectors) both operated by BAG [42, 43]. These results are completed with the investigation of human tissues, such as the investigation of teeth and bones by the IRA or whole‐body counting at the university hospital in Geneva and investigation of special radionuclides, e.g. 14C in tree leaf samples in the vicinity of NPP's and chemical industries by the University of Berne. Based on these results, the radiation exposure of the public is estimated annually.

From the beginning, the state laboratory of Basel‐City took part. The Office of Public Health chose for us three sampling points (farms) in Ticino, one farm in Basel‐Country and a milk processing centre in the Canton of Jura for the yearly analysis of soil (upper 5‐cm layer), grass and milk. Milk from milk distribution centres and other sites are analysed for radiostrontium as a supplement. Also, the survey of suspended matter of the River Rhine in Basel was delegated to our laboratory. Our laboratory also controls the local emissions of radioactivity. These are the wastewater of the local hospitals, the waste water treatment plant (WWTP) of Basel, ProRheno, and the incineration Plant of Basel, KVA Basel. Monitoring was started in 1993.

#### *4.1.1. Environmental monitoring*

In 1986, the southern parts of Switzerland were the most heavily affected by the fallout from Chernobyl. This can clearly be demonstrated by the time series of the investigated soil, grass and milk samples. There and also in elevated sampling points, such as in the Jura mountains, a remarkable increase in the radio‐strontium and radio‐caesium levels from global fallout was observed from 1986 to 1988. Other sampling points, such as Grangeneuve, the vicinity of the NPP's of Gösgen and Mühleberg and Leibstadt showed the normal decreasing trend of the global fallout with only slight additional fallout from Chernobyl [44]. For radiostrontium, they did not observe an increase in the contamination. Corcho et al. [45] recently published trend curves for three alpine investigated sites and two sampling sites in Swiss Mittelland. They analysed radioactive data of soil, grass and milk samples from 1994 to 2013. The effective half‐lives did not depend on the altitude of the site. Radiostrontium showed quite a shorter half‐life than the physical half‐life. This can be explained by its migration to deeper soil layers and therefore less being available for plants. On the contrary, the effective half‐life

of radiocaesium is similar to its physical half‐life. This is because it is fixed on clay particles in the soil and moves only slowly into the deeper soil layers [45].

**Figure 3.** Activity trends of radiocaesium in soil, vegetation and cow's milk on a farm in Basel‐Country. We calculated the effective half‐live to 12.9 years (soil), 11.6 years (grass) and 12.0 years (cow's milk).

One of our regular sampling points is a farm in Basel‐Country (450 m altitude). Data from 1986 until today are available. The data analysis of 137Cs shows the following trends (**Figure 3**). The effective half‐life of radiocaesium is lower than the physical one. We explain this fact by movement of the radionuclide into deeper soil layers. Therefore, the radiocaesium becomes progressively less available for the grass roots.

Such calculations are of interest when trends in the behaviour of radionuclides for food and feed are sought. They provide important information about the contamination of the food chain. The Chernobyl impact resulted in an increase in the contamination in cow's milk for about 6 years.

#### *4.1.2. Monitoring of local emissions of radionuclides*

Labor Spiez (LS), Institut de Radiophysique Appliqué (IRA), Paul Scherrer Institut of ETH Zurich (PSI), the Swiss Federal Institute of Aquatic Science and Technology (EAWAG), the National Emergency Operations Centre (NAZ), the Swiss Accident Insurance Fund (SUVA), the Swiss Federal Nuclear Safety Inspectorate (ENSI), the BAG, the European Organization for Nuclear Research (CERN), laboratories of the NPPs and some of the state laboratories of Switzerland, analyse different compartments with different techniques [39]. The main content of the reports lies in the supervision of emissions from NPPs and other industry using and producing radionuclides, the emissions from wastewater treatment plants and waste incineration plants. The report shows the results of the yearly survey of a grid of environmental sampling points, such as farms, sampling points in the vicinity of NPPs, water and air monitoring stations. Data from monitoring stations are collected and interpreted. These are the NADAM‐net of the NAZ (66 automatic radiation dose meters [40]), the MADUK‐ net, operated by the ENSI (radiation dose meters [41]), RADAIR (air monitoring stations) and URANET (Automatic River monitoring detectors) both operated by BAG [42, 43]. These results are completed with the investigation of human tissues, such as the investigation of teeth and bones by the IRA or whole‐body counting at the university hospital in Geneva and investigation of special radionuclides, e.g. 14C in tree leaf samples in the vicinity of NPP's and chemical industries by the University of Berne. Based on these results, the radiation exposure

From the beginning, the state laboratory of Basel‐City took part. The Office of Public Health chose for us three sampling points (farms) in Ticino, one farm in Basel‐Country and a milk processing centre in the Canton of Jura for the yearly analysis of soil (upper 5‐cm layer), grass and milk. Milk from milk distribution centres and other sites are analysed for radiostrontium as a supplement. Also, the survey of suspended matter of the River Rhine in Basel was delegated to our laboratory. Our laboratory also controls the local emissions of radioactivity. These are the wastewater of the local hospitals, the waste water treatment plant (WWTP) of Basel, ProRheno, and the incineration Plant of Basel, KVA Basel. Monitoring was started in 1993.

In 1986, the southern parts of Switzerland were the most heavily affected by the fallout from Chernobyl. This can clearly be demonstrated by the time series of the investigated soil, grass and milk samples. There and also in elevated sampling points, such as in the Jura mountains, a remarkable increase in the radio‐strontium and radio‐caesium levels from global fallout was observed from 1986 to 1988. Other sampling points, such as Grangeneuve, the vicinity of the NPP's of Gösgen and Mühleberg and Leibstadt showed the normal decreasing trend of the global fallout with only slight additional fallout from Chernobyl [44]. For radiostrontium, they did not observe an increase in the contamination. Corcho et al. [45] recently published trend curves for three alpine investigated sites and two sampling sites in Swiss Mittelland. They analysed radioactive data of soil, grass and milk samples from 1994 to 2013. The effective half‐lives did not depend on the altitude of the site. Radiostrontium showed quite a shorter half‐life than the physical half‐life. This can be explained by its migration to deeper soil layers and therefore less being available for plants. On the contrary, the effective half‐life

of the public is estimated annually.

14 New Insights on Gamma Rays

*4.1.1. Environmental monitoring*

In Basel, the main emission sources of radioactive material are the chemical/pharmaceutical industry, hospitals and some minor industries using radioactive sources. Emissions from these sources are deposited in the environment via wastewater and the air. The waste water is cleaned at the local WWTP ProRheno and two waste incineration plants, the city's incineration plant, KVA Basel and an incineration plant of the chemical industry for hazardous wastes, RSMVA of Valorec.

An important task of the state laboratory is the monitoring of the local wastewater effluents. These monitoring programmes started in 1988 and included the parameters 3 H (mainly used by the local chemical/pharmaceutical industries) and short‐lived radionuclides used in hospitals, such as 131I, 99mTc, 90Y, 111In, 177Lu, 186Re, 153Sm, 67Ga and others. The university hospital of Basel is specialised towards DOTATOC therapies, where mainly 90Y and 177Lu are used. Wastewater from the patients is collected in cool‐down tanks for some weeks before being discharged to the wastewater treatment plant. Monitoring results are published yearly [46].

Tritium emissions are regularly detected in the washing water of the air filters of KVA Basel. Several times during the last 25 years, tritium was above the permitted emission limits of 6000 Bq/L and 60,000 Bq/month. However, these emissions contribute very little to the 3 H‐ level of the River Rhine. Here, the main 3 H sources are the NPPs and tritium producing industry in Switzerland upstream [47].

The main contamination factor of air is radiocarbon, which are used mainly by the chemical/ pharmaceutical industries. In Basel, radiocarbon is emitted when waste is burned at RSMVA. Incineration takes place mainly in the night, to lower the uptake of radiocarbon in plants by photosynthesis. These emissions are controlled annually by the University of Berne. The monitoring programme of the University of Berne includes other emission sources in Switzerland, such as incineration plants, ZWILAG and NPPs [39].

#### *4.1.3. Behaviour of radionuclides in a WWTP*

In 2014, the influents and effluents of the WWTP ProRheno were investigated, to obtain a balance of short‐lived radionuclides for medical use. The main fraction of 131I was dissolved in wastewater and over 90% of the input was emitted with the treated wastewater into the River Rhine. Only a small amount was emitted via air when the sewage sludge is incinerated. For 177Lu, we observed that about 60% of the incoming activity was eliminated in the WWTP, mainly by adsorption on the sewage sludge. Finally, it remained in the sludge ash, which is deposited on a nearby landfill disposal site. It disintegrates there rapidly. About 40% of the activity is emitted with the treated wastewater to the River Rhine and deposited on suspended matter and river sediment [48, 49]. The investigation of sewer sludge in the local sewage water system of Basel clearly shows that a part of the activities found at the influent of the WWTP originates from patients treated in ambulances [50].

Some of the waste from the hospitals is burnt at the incineration plant. This is proven by the activities found in the washing water of the air filters. While 131I is found permanently in the low Becquerel level, other nuclides only are found sporadically. The main contamination factor at KVA Basel is 3 H. The sources of these emissions are not known. The Swiss Accident Insurance Fund, SUVA, supposes the source to be the accidental burning of 3 H‐containing watches with the daily‐delivered waste from households and industry.

#### *4.1.4. Suspended matter of the River Rhine*

Many contaminants, such as organics, metals and radionuclides, adsorb onto clay particles and are transported in a river as suspended matter. After quite a long distance or sections where the river water stands still, e.g. behind dams, the suspended particles settle onto the river sediment. Radionuclides released from NPPs are monitored by EAWAG and our  laboratory at defined sampling points downstream. Suspended matter is collected either continuously by a special particle‐settling chamber, or by the use of a centrifuge (i.e. non‐continuous monitoring). At the river monitoring station Weil, downstream of Basel, suspended matter is collected monthly with a centrifuge. The freeze‐dried and ground material is then analysed with a Ge‐detector. Beside NPP‐specific radionuclides, such as 60Co, 54Mn or 65Zn, radionuclides from medicinal applications (131I, 177Lu and others), natural radionuclides from the decay series of U and Th and from fallout (137Cs) can be detected [39, 51].

#### **4.2. Special applications/projects**

by the local chemical/pharmaceutical industries) and short‐lived radionuclides used in hospitals, such as 131I, 99mTc, 90Y, 111In, 177Lu, 186Re, 153Sm, 67Ga and others. The university hospital of Basel is specialised towards DOTATOC therapies, where mainly 90Y and 177Lu are used. Wastewater from the patients is collected in cool‐down tanks for some weeks before being discharged to the wastewater treatment plant. Monitoring results are published yearly [46].

Tritium emissions are regularly detected in the washing water of the air filters of KVA Basel. Several times during the last 25 years, tritium was above the permitted emission limits of 6000 Bq/L and 60,000 Bq/month. However, these emissions contribute very little to the 3

The main contamination factor of air is radiocarbon, which are used mainly by the chemical/ pharmaceutical industries. In Basel, radiocarbon is emitted when waste is burned at RSMVA. Incineration takes place mainly in the night, to lower the uptake of radiocarbon in plants by photosynthesis. These emissions are controlled annually by the University of Berne. The monitoring programme of the University of Berne includes other emission sources in Switzerland,

In 2014, the influents and effluents of the WWTP ProRheno were investigated, to obtain a balance of short‐lived radionuclides for medical use. The main fraction of 131I was dissolved in wastewater and over 90% of the input was emitted with the treated wastewater into the River Rhine. Only a small amount was emitted via air when the sewage sludge is incinerated. For 177Lu, we observed that about 60% of the incoming activity was eliminated in the WWTP, mainly by adsorption on the sewage sludge. Finally, it remained in the sludge ash, which is deposited on a nearby landfill disposal site. It disintegrates there rapidly. About 40% of the activity is emitted with the treated wastewater to the River Rhine and deposited on suspended matter and river sediment [48, 49]. The investigation of sewer sludge in the local sewage water system of Basel clearly shows that a part of the activities found at the influent of the WWTP originates from patients treated in

Some of the waste from the hospitals is burnt at the incineration plant. This is proven by the activities found in the washing water of the air filters. While 131I is found permanently in the low Becquerel level, other nuclides only are found sporadically. The main contamination

Many contaminants, such as organics, metals and radionuclides, adsorb onto clay particles and are transported in a river as suspended matter. After quite a long distance or sections where the river water stands still, e.g. behind dams, the suspended particles settle onto the river sediment. Radionuclides released from NPPs are monitored by EAWAG and our

Insurance Fund, SUVA, supposes the source to be the accidental burning of 3

watches with the daily‐delivered waste from households and industry.

H. The sources of these emissions are not known. The Swiss Accident

H sources are the NPPs and tritium producing indus-

level of the River Rhine. Here, the main 3

such as incineration plants, ZWILAG and NPPs [39].

*4.1.3. Behaviour of radionuclides in a WWTP*

ambulances [50].

factor at KVA Basel is 3

*4.1.4. Suspended matter of the River Rhine*

try in Switzerland upstream [47].

16 New Insights on Gamma Rays

H‐

H‐containing

We now describe our own investigations to find representative organisms for radioactivity monitoring of the environment. Therefore, we analysed possible sample types, such as mosses, soil, grass, dust, water and wood.

#### *4.2.1. Behaviour of radionuclides in soil filters of local drinking water production*

The filtration of river water through forest soils is the most important step of drinking water production in Basel. In the context of an emergency concept for drinking water production, the question arose as to how the radioactive contaminants behave when entering the soil filter. Is there a danger of contamination of the drinking water after a nuclear accident? We analysed soil cores in one of the filtering fields for global fallout. As described in the literature, radiocaesium and plutonium remain in the upper soil layer. Radiostrontium moved deeper into the soil. For radiocaesium, we estimate two main sources: global fallout and fallout from Chernobyl. We estimated that in 1986, only about 65% of the total caesium reached the infiltration site with the infiltrated river water. The rest was bound to the suspended matter and removed by sand filtration before the infiltration step. Plutonium and perhaps radiostrontium, only originates from global fallout. We suppose that radionuclides are retained in the soil even at higher charges. For radiostrontium, the retention was lower and could have reached the groundwater. Further investigations are necessary (**Figure 4**) [52].

**Figure 4.** Soil profiles from a soil filtration site of the drinking water producer of Basel. Bars in grey are cores from the filtration site compared to a reference site outside (bars in white). From Ref. [52].

#### *4.2.2. Fallout monitoring at Basel and vicinity*

During the annual emergency exercises for an A‐impact, soil samples were collected (the upper 5‐cm layer) over 50 different sampling points in the city of Basel and surroundings at different altitudes (250–360 m). The analysis of over 200 soil samples with gamma‐ray spectrometry resulted in an overall range of 10.6 ± 6.4 Bq/kg of 137Cs.

A second project was focused on the analysis of mosses. Mosses were analysed with beta and gamma spectrometry. The analysis with gamma‐ray spectrometry resulted in an overall range 2.2 ± 2.6 Bq/kg for 134Cs (n = 3) and 24 ± 42 Bq/kg (n = 87) for 137Cs with a maximum of over 300 Bq/kg. Radiostrontium was found in 67 samples: 5.2 ± 4.5 Bq/kg of 90Sr [53].

Recently, our focus was on tree bark monitoring. The gamma‐ray analysis of the tree bark of 26 different trees gave a mean of 6.7 ± 18 Bq/kg 137Cs.

Compared to the undisturbed situation on a country site, variability in soil and vegetation in a city and surroundings is quite dominant. Nonetheless, we think that tree bark monitoring is comparable with soil monitoring and can give relevant contamination data for emergency cases. The uptake mechanism for radionuclides in mosses is quite different to that of trees and of the deposition on soils. Mosses do not have roots; they incorporate contamination mainly through the air. Contamination is deposited on tree leaves. Trees accumulate contamination through their roots and also later by the deposited leaves (litter‐fall) [54].

Despite their great variability in moss species and the difficulties in the determination of age, mosses can be monitoring plants for radioactive fallout, when carefully normalised (**Figure 5**). In Basel, radiocaesium and radioiodine (131I) were detectable in the first rainfall in April 2011, after the catastrophe at Fukushima‐Dai‐ichi. Here, over 9500 km away from Japan, the fallout could also be detected in moss, grass and soil and even in cow's milk [55].

**Figure 5.** Correlations of radiocaesium between moss, tree bark and the corresponding soil activity.

#### **5. Gamma nuclides in food**

*4.2.2. Fallout monitoring at Basel and vicinity*

18 New Insights on Gamma Rays

trometry resulted in an overall range of 10.6 ± 6.4 Bq/kg of 137Cs.

26 different trees gave a mean of 6.7 ± 18 Bq/kg 137Cs.

(litter‐fall) [54].

[55].

During the annual emergency exercises for an A‐impact, soil samples were collected (the upper 5‐cm layer) over 50 different sampling points in the city of Basel and surroundings at different altitudes (250–360 m). The analysis of over 200 soil samples with gamma‐ray spec-

A second project was focused on the analysis of mosses. Mosses were analysed with beta and gamma spectrometry. The analysis with gamma‐ray spectrometry resulted in an overall range 2.2 ± 2.6 Bq/kg for 134Cs (n = 3) and 24 ± 42 Bq/kg (n = 87) for 137Cs with a maximum of

Recently, our focus was on tree bark monitoring. The gamma‐ray analysis of the tree bark of

Compared to the undisturbed situation on a country site, variability in soil and vegetation in a city and surroundings is quite dominant. Nonetheless, we think that tree bark monitoring is comparable with soil monitoring and can give relevant contamination data for emergency cases. The uptake mechanism for radionuclides in mosses is quite different to that of trees and of the deposition on soils. Mosses do not have roots; they incorporate contamination mainly through the air. Contamination is deposited on tree leaves. Trees accumulate contamination through their roots and also later by the deposited leaves

Despite their great variability in moss species and the difficulties in the determination of age, mosses can be monitoring plants for radioactive fallout, when carefully normalised (**Figure 5**). In Basel, radiocaesium and radioiodine (131I) were detectable in the first rainfall in April 2011, after the catastrophe at Fukushima‐Dai‐ichi. Here, over 9500 km away from Japan, the fallout could also be detected in moss, grass and soil and even in cow's milk

**Figure 5.** Correlations of radiocaesium between moss, tree bark and the corresponding soil activity.

over 300 Bq/kg. Radiostrontium was found in 67 samples: 5.2 ± 4.5 Bq/kg of 90Sr [53].

#### **5.1. Radio contamination of food**

Whereas food can be contaminated just after its release with fallout of short‐lived radionuclides for a short period, contamination with long‐lived radionuclides from global fallout and the Chernobyl catastrophe remain. The contamination of food by the Chernobyl fallout was reduced within 2 years concerning the short‐lived radionuclides, such as 131I, 132I, 134Cs, whereas long‐lived radionuclides still persist (see **Figure 3**) in the soil and are transferred to crops and grass (feed for cows). The typical tracer food for this is milk. We recently published a review of radioactivity monitoring in Switzerland over the last 35 years [56]. We compared the contamination level of food categories with artificial radionuclides. In the time span 1990–2015, some moderate contamination of some food categories was noted. Special cases were hazelnuts and tea from Turkey. As some regions of that country were affected by the fallout from Chernobyl, food imports may contain higher levels of Radiocaesium (0.1–30 Bq/kg). Tea contained up to 100 Bq/kg radiocaesium and 2–40 Bq/kg of radiostrontium. The latter may also originate from global fallout. Until the present, most affected food from the fallout of Chernobyl concerns wild grown mushrooms, wild grown berries and game (especially wild boars). Even today, violations are noted for wild boars from Bavaria, Southern Germany and Southern Switzerland [57] (**Table 4**).


1 Including blue berries and chest nuts.

2 Fish and Japanese tea contains also 134Cs from local fallout of the Fukushima‐Daiji accidents.

n.a.: not analysed.

**Table 4.** Some food categories which are still contaminated with global fallout and/or fallout from NPP's accidents in Chernobyl and Fukushima.

The Office of Public Health estimates the total ingested dose to about 0.3–0.4 mSv/year. The main contribution comes from potassium‐40 (40K; 0.2 mSv/year) and from natural radionuclides of the uranium and thorium decay series. The remaining contamination from bomb fallout is less than 0.1 mSv/year [39].

#### **5.2. Healing earths**

Siliceous earths are widely used in the food industries as a food supplement. They incorporate foreign atoms in the crystal lattice, such as radionuclides of the natural decay series of uranium and thorium.

In 2008, siliceous earth products on the Swiss market were analysed with γ‐spectrometry. In two products, the threshold value for natural radionuclides of group 21 was exceeded (>50 Bq/kg). Furthermore, by regular consumption of one product from California, USA, the annual dose would reach half of the permitted yearly dose of 1 mSv. Consequently, this product was withdrawn from the Swiss market. In 2010, the reinspection of healing earths showed that two products from one producer in Germany slightly exceeded the limit value according to higher levels of 226Ra and 228Ra. The annual dose from the consumption of these products would lead to 0.1 mSv/year. Therefore, healing earths and silica‐based chemicals used in food industry and in chemical laboratories remain a source of natural radionuclides [59].

#### **6. Gamma spectrometry as an important analytical tool for emergency cases with ionising radiation**

The instrumentation of an emergency A‐Laboratory depends on the required detection devices for the analysis of the fallout from nuclear bombs or from nuclear power plants. **Table 5** gives a short survey of some expected fission and activation products. In used reactor fuel, more than 200 radionuclides are present [60] (**Figure 6**). The Institut de Radiophysique Appliqué (IRA) prepared simulated gamma spectra 2 and 11 days after release from an NPP. After 2 days, the gamma analysis was very complex and contained more than 270 gamma emission lines. At day 11 after the release, the number of gamma lines was reduced remarkably. Not all expected radionuclides were detectable due to low activity. For mother/daughter nuclide pairs, attention has to be paid to when the half‐life of the daughter is shorter than that of the mother. After seven half‐lives of the daughter, the two nuclides are in equilibrium, so one has to calculate the activity of the daughter using the half‐life of the mother nuclide (e.g. 132Te (77.5 h) and daughter 132I (2.3 h)) [61].

As we see, gamma spectrometry is the most important instrumentation for an emergency case with ionising radiation. Only for a few radionuclides α‐spectrometry (Pu‐isotopes) and β‐spectrometry (3 H, 14C, 89Sr, 90Sr) have to be available.

The main task is to analyse environmental samples, such as soil, vegetation, fallout, air and food samples, such as vegetables and fruit grown outdoors. The pathways are air/fallout, rain/washout and water (rivers, lakes). Later on, collection and analysis of sediment, grass and soil samples will follow. The most important/affected food is milk and milk products, baby food, outdoor‐ grown vegetables, meat and game, fruit (including hazelnuts) and cereals. According to our experience in 1986, vegetables were the most affected (by radioiodine and radiocaesium). Special focus should be set on baby food and human milk (including analysis for radiostrontium) [55].

<sup>1</sup> Ordinance on Contaminants and Constituents in Food: natural radionuclides group 2: the sum of activities of 226Ra, 228Ra, 230Th, 232Th and 231Pa.


**1** Analysis has to be performed with β‐spectrometry.

**5.2. Healing earths**

20 New Insights on Gamma Rays

uranium and thorium.

**cases with ionising radiation**

β‐spectrometry (3

228Ra, 230Th, 232Th and 231Pa.

1

Siliceous earths are widely used in the food industries as a food supplement. They incorporate foreign atoms in the crystal lattice, such as radionuclides of the natural decay series of

In 2008, siliceous earth products on the Swiss market were analysed with γ‐spectrometry. In two

Furthermore, by regular consumption of one product from California, USA, the annual dose would reach half of the permitted yearly dose of 1 mSv. Consequently, this product was withdrawn from the Swiss market. In 2010, the reinspection of healing earths showed that two products from one producer in Germany slightly exceeded the limit value according to higher levels of 226Ra and 228Ra. The annual dose from the consumption of these products would lead to 0.1 mSv/year. Therefore, healing earths and silica‐based chemicals used in food industry and

**6. Gamma spectrometry as an important analytical tool for emergency** 

The instrumentation of an emergency A‐Laboratory depends on the required detection devices for the analysis of the fallout from nuclear bombs or from nuclear power plants. **Table 5** gives a short survey of some expected fission and activation products. In used reactor fuel, more than 200 radionuclides are present [60] (**Figure 6**). The Institut de Radiophysique Appliqué (IRA) prepared simulated gamma spectra 2 and 11 days after release from an NPP. After 2 days, the gamma analysis was very complex and contained more than 270 gamma emission lines. At day 11 after the release, the number of gamma lines was reduced remarkably. Not all expected radionuclides were detectable due to low activity. For mother/daughter nuclide pairs, attention has to be paid to when the half‐life of the daughter is shorter than that of the mother. After seven half‐lives of the daughter, the two nuclides are in equilibrium, so one has to calculate the activity of the daughter using the half‐life of the mother nuclide (e.g. 132Te (77.5 h) and daughter 132I (2.3 h)) [61]. As we see, gamma spectrometry is the most important instrumentation for an emergency case with ionising radiation. Only for a few radionuclides α‐spectrometry (Pu‐isotopes) and

The main task is to analyse environmental samples, such as soil, vegetation, fallout, air and food samples, such as vegetables and fruit grown outdoors. The pathways are air/fallout, rain/washout and water (rivers, lakes). Later on, collection and analysis of sediment, grass and soil samples will follow. The most important/affected food is milk and milk products, baby food, outdoor‐ grown vegetables, meat and game, fruit (including hazelnuts) and cereals. According to our experience in 1986, vegetables were the most affected (by radioiodine and radiocaesium). Special focus should be set on baby food and human milk (including analysis for radiostrontium) [55].

Ordinance on Contaminants and Constituents in Food: natural radionuclides group 2: the sum of activities of 226Ra,

was exceeded (>50 Bq/kg).

products, the threshold value for natural radionuclides of group 21

in chemical laboratories remain a source of natural radionuclides [59].

H, 14C, 89Sr, 90Sr) have to be available.

**Table 5.** Extract of possible fission and activation products released at an NPP accident or from a bomb.

**Figure 6.** Process of a release of radioactive material to the environment by an accident or bomb (after Ref. [64]).

In Switzerland, the National Emergency Operations Centre (NEOC) coordinates these emergency investigations. They give the order to collect samples for the estimation of the contamination/radiation level outdoor and for controlling the level of the contamination of food. The local authorities then take action (e.g. banning severely contaminated food categories). An initial focus is set on the drinking water quality. In Basel, drinking water is produced from groundwater, which is enriched with river water by soil filtration. It is important to prevent the entry of contaminated river water into this filtration system. After an earthquake, when the drinking water production site is no longer operable, there exist plans for emergency supply of the public with pumped water from the ground and from rivers. This requires efficient and rapid analysis systems. With a gamma analysis of a 1 L water sample in a Marinelli‐beaker, it is possible to restrict the analysis time to 15 min for the examination of threshold values. 3 H and 90Sr have to be analysed by β‐spectrometry. With an extraction/ scintillation‐method, we are able to obtain results for both radionuclides within 2 hours [63].

#### **Acknowledgements**

My special thanks go to my former collaborator, Matthias Stöckli. I benefited greatly from his great expertise in radiation detection, especially in Neutron Activation Analysis. Furthermore, I express my thanks to my collaborators Franziska Kammerer and Michael Wagmann for their permanent support. Finally, I wish to thank Major Franz Näf from the civil protection of Basel City for his engagement during the annual emergency exercises that are mentioned in Section 6.

#### **Author details**

Markus R. Zehringer

Address all correspondence to: markus.zehringer@bs.ch

Head of Radiation Laboratory, State‐Laboratory of Basel‐City, Basel, Switzerland

#### **References**

In Switzerland, the National Emergency Operations Centre (NEOC) coordinates these emergency investigations. They give the order to collect samples for the estimation of the contamination/radiation level outdoor and for controlling the level of the contamination of food. The local authorities then take action (e.g. banning severely contaminated food categories). An initial focus is set on the drinking water quality. In Basel, drinking water is produced from groundwater, which is enriched with river water by soil filtration. It is important to prevent the entry of contaminated river water into this filtration system. After an earthquake, when the drinking water production site is no longer operable, there exist plans for emergency supply of the public with pumped water from the ground and from rivers. This requires efficient and rapid analysis systems. With a gamma analysis of a 1 L water sample in a Marinelli‐beaker, it is possible to restrict the analysis time to 15 min for the examination

**Figure 6.** Process of a release of radioactive material to the environment by an accident or bomb (after Ref. [64]).

scintillation‐method, we are able to obtain results for both radionuclides within 2 hours [63].

My special thanks go to my former collaborator, Matthias Stöckli. I benefited greatly from his great expertise in radiation detection, especially in Neutron Activation Analysis. Furthermore, I express my thanks to my collaborators Franziska Kammerer and Michael Wagmann for their permanent support. Finally, I wish to thank Major Franz Näf from the civil protection of Basel City for his engagement during the annual emergency exercises that are mentioned in Section 6.

H and 90Sr have to be analysed by β‐spectrometry. With an extraction/

of threshold values. 3

22 New Insights on Gamma Rays

**Acknowledgements**

**Author details**

Markus R. Zehringer

Address all correspondence to: markus.zehringer@bs.ch

Head of Radiation Laboratory, State‐Laboratory of Basel‐City, Basel, Switzerland


[33] Zehringer M. Radiological investigation of a radium drinking device. In: annual report of the state‐laboratory Basel‐City. Basel; 2006. p. 173–175.

[16] Firestone R, Shirley V. Table of Isotopes. 8th ed. New York: Wiley & Sons; 1999. ISBN:

[17] Legrand J, Perolat J, Lagourtine F, Le Gallic Y. Table of Radionuclides. Atomic Energy

[18] Amiel S (Ed.). Nondestructive Activation Analysis, Amsterdam: Elsevier; 1981. ISBN:

[19] Parry S. Handbook of Neutron Activation Analysis. Woking: Viridian Publishing; 2003.

[20] Zehringer M, Stöckli M. Determination of total bromine residue in food and non‐food

[21] The Federal Department of Home Affairs. Ordinance on Contaminants and Constituents

[22] Zehringer M, Testa G, Jourdan J. Determination of total Iodine content of food with means of Neutron Activation Analysis (NAA). Proceedings of the Swiss Food Science

[23] Bhagat P et al. Estimation of iodine in food, food products and salt using ENAA. Food

[24] Frey T. Detection and quantification of brominated flame retarding agents in plastic

[25] Kuhn E, Frey T, Arnet R, Känzig A. Brominated flame retarding agents in plastic products on the Swiss market. In: Federal Office of Environment (Ed.) Umweltmaterialien;

[26] Wegmann L, Werfeli M, Bachmann R, Tremp J, Figueiredo V. Brominated flame retarding agents in plastics. A tentative investigation on the Swiss Market, Amt für Umweltschutz

[27] Zehringer M et al. Neutron Activation Analysis (NAA)—another approach to uranium

[28] Mahaffey J. Atomic Accidents. A History of Nuclear Meltdowns and Disasters. New

[29] Valerius‐Mahler C. Radiation—the two faces of radioactivity. Pharmazie‐Historisches

[30] Pratzel H, Deetjen P. Radon Application at Sanitariums. Geretsried: I.S.M.H Verlag; 1997. [31] Pöschl M, Nollet L, editors. Radionuclide Concentrations in Food and the Environment.

[32] Bünger T et al. Radioactivity in water—an actual overview. Strahlenschutzpraxis. 2014;**1**:

and thorium analysis in environmental samples. Chimia 2013; **67**:828.

York: Pegasus Books; 2014. ISBN: 978‐1‐60598‐680‐7.

New York: CRC Taylor & Francis; 2007. ISBN: 0‐8493‐3594‐9.

Museum der Universität Basel; 2014, 67–87.

978‐0‐471‐35633‐2

24 New Insights on Gamma Rays

0‐444‐41942‐X.

in Food; 1995.

2004:**189**.

3–28.

ISBN: 0‐9544891‐1‐X.

samples. Chimia 2004;**59**:112.

Chem. 2009; **115**: 706–710.

und Energie. Liestal; 1999.

Meeting (SFSM '13); 2013; Neuchatel.

materials. [Master's thesis]. Aarau; 1999.

Agency, Gif‐sur‐Yvettes, France 1957.


[63] Zehringer M, Abraham J, Kammerer F, Syla V, Wagmann M. Fast survey of Radiostrontium after an Emergency Incident involving Ionizing Radiation. Chimia 2016;**70**: 816.

[49] Kammer F, Rumpel N, Wagmann M, Zehringer M. Monitoring of Radionuclides for medical use in Basel. Proceedings of the GDCH‐Wissenschaftsforum, Dresden; 2015. [50] Rumpel N, Kammerer F, Wagmann M, Zehringer M. Gamma ray spectrometry of sewer sludge—a useful tool for the identification of emissions sources in a city. Chimia 2015;**69**:

[51] Zehringer M. Radioactivity monitoring of the river Rhine. In: Annual Report of the State‐

[52] Abraham J. Study of the behavior of radionuclides at an infiltration site for drinking

[53] Meyer J. Monitoring of moss in Basel‐City for the investigation of radioactive fallout

[54] Agapkina G et al. Dynamics of Chernobyl‐fallout radionuclides in soil solutions of forest

[55] Zehringer M. Radioactivity in food and other objects from Japan. In: Annual Report of

[56] Zehringer M. Radioactivity in Food: Experiences of the Food Control Authority of Basel since the Chernobyl Accident. In: Monteiro W. editor. Radiation Effects in Materials.

[57] Palacios M, Estier S, Ferreri G. On the trace of 137Cs in wild boars in Ticino In: Federal Office of Public Health, editor. Environmental Radioactivity and Radiation Doses in

[58] Swiss wild boar meat: radioactivity and heavy metal content. In: Annual Report of the

[59] Zehringer M. Radionuclides in siliceous and healing earths. In: Annual Report of the

[60] Choppin G, Rydberg J. Nuclear Chemistry—Theory and Applications. New York:

[61] Buchillier T, Baillat C, Laedermann J, Leupin A. Rapport sur l'exercice d'analyse de spectre de centrale nucléaire 2013; Rapport interne de l'Institut de Radiophysique Appliqué,

[62] Demongeot S et al. A practical guide for laboratories measuring radionuclides at post‐ accidental situations. IRSN (Institut de Radioprotection et de Sureté Nucléaire), Rapport

water production. Basel: State‐Laboratory Basel‐City. Basel; 2016.

[scholarly paper]. Oberwil: State Grammar School Oberwil; 2014.

Laboratory Basel‐City. Basel; 2015. p. 134–138.

ecosystems. Chemosphere 1998;**36**: 1125–1130.

InTech Open. 2016. ISBN: 978‐953‐51‐2438‐2.

Switzerland. Bern: BAG; 2013. p. 100–101.

Lausanne, Switzerland, 2015.

No 2011‐02, 2011.

State‐Laboratory of Zurich. Zurich; 2014. p. 71–72.

State‐Laboratory Basel‐City. Basel; 2008. p. 79–82.

Pergamon Press; 1980. ISBN: 0‐08‐023826‐2. p.593 Apendix H.

the State‐Laboratory Basel‐City. Basel; 2011. p. 29–31.

301.

26 New Insights on Gamma Rays

[64] Federal Commission for ABC‐protection. Concept for emergency protection in the vincinity of NPPs, KomABC 2006‐03‐D; Berne: 2006.

All references concerning the reports of the State Laboratory Basel City are on the internet, available at: http://www.kantonslabor.bs.ch/berichte.html.

## **Dead Time in the Gamma‐Ray Spectrometry**

Salih Mustafa Karabıdak

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/67083

#### Abstract

A review of studies of the dead time correction on gamma-ray spectroscopy is presented. Compensate for counting losses due to system dead time is a vital step for quantitative and qualitative analysis. The gamma-ray spectroscopy system consisting of electronic devices are used for detection of radiation due to gamma rays. The dead time of the spectroscopy system is based on time limitations of these electronic devices. Firstly, a new model for determination of this electronic dead time is proposed. Secondly, two alternative methods suggested for the correction of this electronic dead-time losse.

Keywords: gamma rays, gamma-rays detectors, semiconductor detectors, dead time, counting rate, peaking time

#### 1. Introduction

Development of a gamma spectrometer for each energy region of the electromagnetic radiation has progressed in parallel with the development of experimental tools. The first and rough detectors often just used to determine the presence of radiation. The secondgeneration radiation detectors used to determine the radiation intensity, but with only a very small part of information on its energy. The last types of radiation detectors measure the intensity as a function of the photon energy in addition to the determination of the presence of radiation.

After the first observation of the gamma rays with photographic plates, advances related to measuring in this field began with the development of various types of gas-filled counters at the beginning of 1908 [1]. The counters that are compared to the photographic detection process allowed the experimenter to obtain a more accurate quantitative measure of the

radiation as well as determining the presence of the radiation. The proportional counters did allow one to obtain energy spectra for gamma rays whose energies were low enough to interact primarily by the photoelectric effect and where the secondary electrons produced by these interactions could be completely stopped in the gas volume. However, generally these detectors are only used in determining the number of events that occur in the counter and not to measure directly the energy of the incoming photons [2].

The main improvement in determining the quantity measurement of gamma rays began with the development of NaI (Tl) detectors in about 1948. These detectors can supply energy spectra over a wide energy range. After a certain period of development, detectors consist of crystals with sufficiently large size to allow high absorption rates even above 1 MeV photons energy were produced. The main advantages of these detectors include their relatively fine resolution, the good physical and chemical stability of the crystal material used and their high relative yield. As these detectors have a good resolution, photon energies are well separated and it allows the observation of different energy photon peaks [2].

In 1962, semiconductor Ge (Li) detectors were manufactured [3]. As these detectors can be made from many different semiconductor materials, these are used as photon detectors as well as nuclear-charged particles detectors. To collect the secondary charges efficiently, these detectors need to be made of single crystals of a pure material. Due to difficulties in producing single crystals other than germanium, Ge (Li) detectors have, so far, been successfully used as high-resolution photon detectors of significant size. These detectors have a high resolution. The most serious drawback of semiconductor detectors is the need to keep them cold, generally at liquid nitrogen temperature.

In the coming years, there have been numerous studies on similar detectors of high atomic number. Mayer [4] proposed several detectors made from bicomponent material. Sakai [5] had worked on semiconductor detectors made from bicomponent material such as GaAs, CdTe and HgI2 to make measurements at room temperature. However, there is not much use of these detectors up to now because of the relatively low yield due to their small surface area, low resolution and expensive production methods and techniques.

Characteristics of an ideal detector for gamma spectrometer can be expressed as follows [6]:


#### 2. General characteristics of photon detectors

radiation as well as determining the presence of the radiation. The proportional counters did allow one to obtain energy spectra for gamma rays whose energies were low enough to interact primarily by the photoelectric effect and where the secondary electrons produced by these interactions could be completely stopped in the gas volume. However, generally these detectors are only used in determining the number of events that occur in the counter and not

The main improvement in determining the quantity measurement of gamma rays began with the development of NaI (Tl) detectors in about 1948. These detectors can supply energy spectra over a wide energy range. After a certain period of development, detectors consist of crystals with sufficiently large size to allow high absorption rates even above 1 MeV photons energy were produced. The main advantages of these detectors include their relatively fine resolution, the good physical and chemical stability of the crystal material used and their high relative yield. As these detectors have a good resolution, photon energies are well separated and it allows the observation of different energy photon peaks

In 1962, semiconductor Ge (Li) detectors were manufactured [3]. As these detectors can be made from many different semiconductor materials, these are used as photon detectors as well as nuclear-charged particles detectors. To collect the secondary charges efficiently, these detectors need to be made of single crystals of a pure material. Due to difficulties in producing single crystals other than germanium, Ge (Li) detectors have, so far, been successfully used as high-resolution photon detectors of significant size. These detectors have a high resolution. The most serious drawback of semiconductor detectors is the need to keep them cold, gener-

In the coming years, there have been numerous studies on similar detectors of high atomic number. Mayer [4] proposed several detectors made from bicomponent material. Sakai [5] had worked on semiconductor detectors made from bicomponent material such as GaAs, CdTe and HgI2 to make measurements at room temperature. However, there is not much use of these detectors up to now because of the relatively low yield due to their small

Characteristics of an ideal detector for gamma spectrometer can be expressed as follows

surface area, low resolution and expensive production methods and techniques.

2. It should have a good efficiency (that should be a high absorption coefficient).

5. It should have good stability over time, temperature and operating parameters.

1. Output pulse number should be proportional to the gamma-ray energy.

3. To collect the detector signals, it should have an easy mechanism.

to measure directly the energy of the incoming photons [2].

[2].

30 New Insights on Gamma Rays

[6]:

ally at liquid nitrogen temperature.

4. It should have good energy resolution.

7. It should have a reasonable size.

6. It should be conferred at a reasonable cost.

Modern photon detectors used in determining the radiation and in measuring the quantity of radiation run based on a series of joint steps. These steps are the same in almost all species and types of detectors. In this section, characteristics of gas detectors and of semiconductor detectors commonly used in the determination of radiation and in the measurement of the quantity of radiation are discussed. These detectors are used to count electrons, heavy charged particles and photons. We will only focus on their use as a photon detector. A photon detector operates over the following principles [2]:


A photon spectrum released by a source is usually consists of monoenergetic photons group. The detector converts such a line spectrum into a combination of lines and continuous components. Detectors can be used to determine the energies and intensities of the original photon as long as these lines are observable. However, if the lines are lost in the associated continuity it is usually not possible to determine these quantities. The ability of the detector to produce peaks and lines for monoenergetic photons is characterized by the peak efficiency and peak width. The peak width in the gamma-ray spectrometer is usually expressed as the full width at half maximum (FWHM) in terms of keV. In addition, FWHM referred to as the resolving power of the detector. The peak efficiency of the detector is the ratio of the number counts in the peak corresponding to the absorption of all the photon energy (so in the full energy peak) to the number of photons of that energy emitted by the source. Both the peak and the peak efficiency are functions of the photon energy [2].

#### 3. Gamma-ray spectrometry system components

The magnitude of the pulses from the gamma ray is equal to the magnitude of electrical charge, which is proportional to the amount of absorbed gamma-ray energy by gamma-ray detectors. The function of the electronic system is to collect these electrical charges, to measure the amount of electrical charge and to store these information. The electronic system for a gamma-ray detector spectrometer is shown schematically in Figure 1.

The gamma-ray detector system consists of a detector bias supply, preamplifier, amplifier, analog-to-digital converter (ADC), multichannel analyzer (MCA), a data storage device (computer and spectrum analysis program), a pulse generator and oscilloscope if desired. Pulse generator is used in the spectroscopy system, which does not contain an electronic circuit with functions such as a base line restorer or a pileup rejector. Detector bias supply generates

Figure 1. General appearance of the gamma-ray spectrometry system.

electric field, this produced electric field sweeps the electron-hole pairs toward detector contacts. These swept electron-hole pairs are collected by preamplifier. The collected electron-hole pairs in the preamplifier are converted to a voltage pulse with a field effect transistor (FET). The amplifier changes the shape of the voltage pulse. This shape of the pulse increases linearly with the size of the incoming pulse. The analog-to-digital converter converts from the analog structure to the digital structure. The multichannel analyzer (MCA) shorts the pulses according to pulse height in addition; MCA counts the number of pulses in the individual pulse height ranges. Computers are used to check the measurements and to record the spectrum in modern gamma-ray spectrometers. The advantage of such systems is providing great convenience to users in fulfilling their various data-analysis calculations during and after measurement. During the measurement, the location and area of the peak of interest via a program used can be determined on screen, therefore, the collection rate of counting and the identity of radionuclide can be determined.

#### 4. The dead-time detection methods

The main reason for the counting and pileup losses is the dead time of the gamma spectrometry system. In order to fulfill the necessary corrections primarily related to these losses, it is to be first determined the dead time of the gamma-rays spectrometry. The dead time is associated with limited time features known as constant separation time of electronic circuits of the gamma-ray spectrometry. It has been generally accepted that the direct measurement of the dead time because of the pulse processing conditions in the gamma-ray spectrometry may change or not is accurately known. Traditional dead-time measurement techniques are based on the fact that the observed count rate varies nonlinearly with the true counting rate. Therefore, by assuming that one of the specific models is applicable and by measuring the observed rate for at least two different true counting rates that differ by a known ratio, the dead time can be calculated [7].

#### 4.1. Two sources method

This method is based on the observation of the counting rate from two individual sources and in combination of these two sources. Because of the counting losses are nonlinear, the observed counting rate resulting from the two sources combined is less than the sum of the observed counting rates resulting from each individual source counting. Thus, the dead time can be calculated from this mismatch [7]. Considering two sources, such as A and B, Prussin [8] gave this relationship:

$$
\mathfrak{n}\_A + \mathfrak{n}\_B = \mathfrak{n}\_{AB} + \mathfrak{n}\_{\text{BG}} \tag{1}
$$

Where nA, nB, nAB and nBG show the observed counting rate of A, B, A + B (A plus B) source and background, respectively. Considering the counting rate correction in the case of nonparalyazable and zero background, general solution to this statement is as follows:

$$T\_D = \frac{n\_A n\_B - \left[n\_A n\_B (n\_{AB} - n\_A)(n\_{AB} - n\_B)\right]^{1/2}}{n\_A n\_B n\_{AB}} \tag{2}$$

#### 4.2. Decaying source method

electric field, this produced electric field sweeps the electron-hole pairs toward detector contacts. These swept electron-hole pairs are collected by preamplifier. The collected electron-hole pairs in the preamplifier are converted to a voltage pulse with a field effect transistor (FET). The amplifier changes the shape of the voltage pulse. This shape of the pulse increases linearly with the size of the incoming pulse. The analog-to-digital converter converts from the analog structure to the digital structure. The multichannel analyzer (MCA) shorts the pulses according to pulse height in addition; MCA counts the number of pulses in the individual pulse height ranges. Computers are used to check the measurements and to record the spectrum in modern gamma-ray spectrometers. The advantage of such systems is providing great convenience to users in fulfilling their various data-analysis calculations during and after measurement. During the measurement, the location and area of the peak of interest via a program used can be determined on screen, therefore, the collection rate of counting and the

The main reason for the counting and pileup losses is the dead time of the gamma spectrometry system. In order to fulfill the necessary corrections primarily related to these losses, it is to be first determined the dead time of the gamma-rays spectrometry. The dead time is associated with limited time features known as constant separation time of electronic circuits of the

identity of radionuclide can be determined.

Figure 1. General appearance of the gamma-ray spectrometry system.

32 New Insights on Gamma Rays

4. The dead-time detection methods

This method can be applied if the source is a short-lived radioisotope. In this method, the decay constant of the radioactive source must be known. The dead time due to the observed count rate resulting from exponential decay of the source is determined. A graph is plotted using the observed counting rate and the decay constant of the source and dead time can be determined with the help of this graph [7]. A general approach to obtain accurate count rates in this method is that: first, the net count rate versus time is plotted on the semilogarithmic graph paper, to obtain a linear curve. This curve is fitted linearly by the least square method. The resulting fit equation is as follows [7, 8]:

$$m(t) = n\_0 e^{-\lambda t} + n\_{\text{BG}} \tag{3}$$

where n<sup>0</sup> is the true rate at the beginning of the measurement and λ is the decay constant of the particular isotope used for the measurement. If the paralyzable model used for this case, the solution can be given as follows:

$$
\lambda t + \mathbf{l}\mathbf{n}\mathbf{u} = -n\_0 \tau e^{-\lambda t} + \mathbf{l}\mathbf{n}u\_0 \tag{4}
$$

#### 4.3. The electronic dead time

In this recently proposed method, the dead time is a result of the electronic components of the gamma-ray spectrometry [9]. Charged particles that are generated by incident radiation within the detector crystal are transported by an electric field to the detector electrodes [9]. The production and collection of the charged particle are subjected to random statistical variations, which depend on the incident energy and the detector medium. An intrinsic resolution limitation exists in the process of converting the incident radiation to an electrical signal [9, 10]. The output signal undergoes various processing steps in order to be correctly acquired and analyzed in semiconductor X or gamma-ray detectors. The time required to collect the charged particles produced by the incident radiation is important in many applications. If the collection time is not sufficiently short compared with the peaking time of the amplifier, a loss in the recovered signal amplitude occurs [9, 11]. The charge collection time depends on the detector geometry, medium, electric field and location of the interaction within the detector active volume [9].

An optimized spectrometer system provides the best energy resolution obtainable within a given set of experimental constraints. System optimization requires the proper selection of equipment and knowledge of the compromise of resolution and count rate performance in any system [9]. The detector and preamplifier combination is the most critical component of the system electronics. The best amplifier cannot compensate for poor signal-to-noise or count rate limitations caused by improper selection of the system front end. Selection of the proper amplifier will enhance the performance of the good detector and preamplifier combination. The source and detector interaction, detector and preamplifier combination, pulse processor shaping and the system count rate determine the system resolution [9, 10].

#### 4.3.1. Determination of the electric dead time

The relationship between the minimum resolving time, peaking time and overall pulse width is given by the following equation [9, 10]:

$$T\_R \geq \frac{T\_W}{T\_P} - 1\tag{5}$$

where TR is minimum resolving time, TW is overall pulse width and TP is peaking time of the amplifier. Overall pulse widths in response to possible peaking times of the amplifier can be measurement using the oscilloscope. A graph is plotted using the measurement overall pulse widths and the possible peaking time of the amplifier (see Figure 2). The relationship between overall pulse width and peaking time can be determined with the help of this graph. The fitting equation of data in Figure 2 is,

$$T\_W = B\_3 T\_P^3 + B\_2 T\_P^2 + B\_1 T\_P + A \tag{6}$$

where A, B1, B<sup>2</sup> and B<sup>3</sup> are coefficients of the equation fitted [9]. The minimum resolving times in response to possible peaking times of the amplifier were calculated using Eq. (5) and the minimum resolving time versus peaking time is plotted in Figure 3 [9].

The fitting equation of the data in Figure 3 is [9],

Figure 2. Change in the overall pulse width with peaking time [9].

4.3. The electronic dead time

34 New Insights on Gamma Rays

In this recently proposed method, the dead time is a result of the electronic components of the gamma-ray spectrometry [9]. Charged particles that are generated by incident radiation within the detector crystal are transported by an electric field to the detector electrodes [9]. The production and collection of the charged particle are subjected to random statistical variations, which depend on the incident energy and the detector medium. An intrinsic resolution limitation exists in the process of converting the incident radiation to an electrical signal [9, 10]. The output signal undergoes various processing steps in order to be correctly acquired and analyzed in semiconductor X or gamma-ray detectors. The time required to collect the charged particles produced by the incident radiation is important in many applications. If the collection time is not sufficiently short compared with the peaking time of the amplifier, a loss in the recovered signal amplitude occurs [9, 11]. The charge collection time depends on the detector geometry, medium, electric

An optimized spectrometer system provides the best energy resolution obtainable within a given set of experimental constraints. System optimization requires the proper selection of equipment and knowledge of the compromise of resolution and count rate performance in any system [9]. The detector and preamplifier combination is the most critical component of the system electronics. The best amplifier cannot compensate for poor signal-to-noise or count rate limitations caused by improper selection of the system front end. Selection of the proper amplifier will enhance the performance of the good detector and preamplifier combination. The source and detector interaction, detector and preamplifier combination, pulse processor

The relationship between the minimum resolving time, peaking time and overall pulse width

where TR is minimum resolving time, TW is overall pulse width and TP is peaking time of the amplifier. Overall pulse widths in response to possible peaking times of the amplifier can be measurement using the oscilloscope. A graph is plotted using the measurement overall pulse widths and the possible peaking time of the amplifier (see Figure 2). The relationship between overall pulse width and peaking time can be determined with the help of this graph. The

<sup>P</sup> <sup>þ</sup> <sup>B</sup>2T<sup>2</sup>

where A, B1, B<sup>2</sup> and B<sup>3</sup> are coefficients of the equation fitted [9]. The minimum resolving times in response to possible peaking times of the amplifier were calculated using Eq. (5) and the

−1 (5)

<sup>P</sup> þ B1TP þ A (6)

TR≥ TW TP

field and location of the interaction within the detector active volume [9].

shaping and the system count rate determine the system resolution [9, 10].

TW <sup>¼</sup> <sup>B</sup>3T<sup>3</sup>

minimum resolving time versus peaking time is plotted in Figure 3 [9].

4.3.1. Determination of the electric dead time

is given by the following equation [9, 10]:

fitting equation of data in Figure 2 is,

The fitting equation of the data in Figure 3 is [9],

Figure 3. Minimum resolving time versus peaking time [9].

$$T\_R = B\_2 T\_P^2 + B\_1 T\_P + A \tag{7}$$

The TD effective system dead time can fall into one of the following categories [9]:

$$T\_R > 1.5 \mu \text{s} + T\_\odot \tag{8}$$

or

$$T\_R < 1.5\mu\text{s} + T\_\odot \tag{9}$$

where TC is conversion time of the analog-to-digital converter (ADC). If the minimum resolving time of the pileup rejector is greater than 1.5 μs + TC, then the system dead time is simply [9]

$$T\_D = T\_P + T\_R \tag{10}$$

Otherwise, the system dead time is

$$T\_D = T\_P + 1.5\mu\text{s} + T\_{\odot} \tag{11}$$

The ADC conversion time for the relevant energy lines can be calculated [12] by using,

$$T\_{\mathbb{C}} = \frac{E}{\Delta E} T\_{\text{Clock}} \tag{12}$$

where E is energy line, ΔE is energy per channel and TClock is the amplifier operation frequency. Considering Eqs. (7) and (10)–(12), the system dead time can be written as [9]:

$$T\_D = B\_2 T\_p^2 + (B\_1 + 1) T\_P + A \tag{13}$$

or

$$T\_D = T\_P + 1.5\mu s + \frac{E}{\Delta E} T\_{\text{Clock}}\tag{14}$$

#### 5. Some models for the dead-time correction

Illustration of the effect on the counting rate of the dead time can be done with the detector; a pulse-forming network consists of a square wave output with constant τ length (amplifier and analog-to-digital converter (ADC) and a counter (multichannel analyzer (MCA)). This time τ is variable due to caused dead time of the ADC.

#### 5.1. Paralyzable (extended) model

One model of dead time behavior of gamma-ray spectroscopy system is paralyzable (extended) response. This model has come into common usage. The model represents idealized behavior. True events that occur during the dead time are lost and assumed to have no effect, whatsoever on the behavior of the detector. True events that occur during the dead time, however, although still not recorded as counts, are assumed to extend the dead time by another period τ following the lost events. This method can be expressed as follows [7]:

$$m = n e^{-n\tau} \tag{15}$$

where m is the recorded count rate, n is the true count rate and τ is the system dead time.

For the so-called paralyzable (extendable) systems, the dead time is extended by starting from the last arrival time. Pulse pileup can also be interpreted as a kind of pulse loss of the paralyzable type [13]. Consecutive pulses falling within a time interval peaking time, TP, are treated as pileup and excluded from the spectrum, as a pileup rejector (PUR) [14]. To generate second output pulse without a time interval of at least s between two consecutive true events is not possible in the paralyzable model. In this model, the recovery of the electronic device is further extended during the respond time s to an initial event for an additional time s by some additional true events, which occur before the full recovery has taken place [15].

#### 5.2. Non-paralyzable (nonextended) model

TR > 1:5μs þ TC (8)

TR < 1:5μs þ TC (9)

TD ¼ TP þ TR (10)

TD ¼ TP þ 1:5μs þ TC (11)

<sup>Δ</sup><sup>E</sup> <sup>T</sup>Clock (12)

<sup>P</sup> þ ðB<sup>1</sup> þ 1ÞTP þ A (13)

<sup>Δ</sup><sup>E</sup> TClock (14)

where TC is conversion time of the analog-to-digital converter (ADC). If the minimum resolving time of the pileup rejector is greater than 1.5 μs + TC, then the system dead time is simply

The ADC conversion time for the relevant energy lines can be calculated [12] by using,

TC <sup>¼</sup> <sup>E</sup>

quency. Considering Eqs. (7) and (10)–(12), the system dead time can be written as [9]:

TD ¼ TP þ 1:5μs þ

TD <sup>¼</sup> <sup>B</sup>2T<sup>2</sup>

5. Some models for the dead-time correction

variable due to caused dead time of the ADC.

5.1. Paralyzable (extended) model

where E is energy line, ΔE is energy per channel and TClock is the amplifier operation fre-

Illustration of the effect on the counting rate of the dead time can be done with the detector; a pulse-forming network consists of a square wave output with constant τ length (amplifier and analog-to-digital converter (ADC) and a counter (multichannel analyzer (MCA)). This time τ is

One model of dead time behavior of gamma-ray spectroscopy system is paralyzable (extended) response. This model has come into common usage. The model represents idealized behavior. True events that occur during the dead time are lost and assumed to have no effect, whatsoever on the behavior of the detector. True events that occur during the dead time, however, although still not recorded as counts, are assumed to extend the dead time by another period τ following the lost events. This method can be expressed as follows [7]:

E

or

36 New Insights on Gamma Rays

[9]

or

Otherwise, the system dead time is

Another model of dead-time behavior of gamma-ray spectroscopy system is nonparalyzable (nonextended) response. This model has come into common usage. The model represents idealized behavior. A fixed time τ is assumed to follow each true event that occurs during the live time of the detector. True events that occur during the dead time are lost and assumed to have no effect, whatsoever on the behavior of the detector. True events that occur during the dead time, however, although still not recorded as counts, are assumed to not-extend the dead time by another period τ following the lost event. This method can be expressed as follows [7]:

$$m = \frac{m}{1 - m\tau} \tag{16}$$

where m is the recorded count rate, n is the true count rate and τ represents the system dead time.

In nuclear spectrometry measurements, the pulse loss is traditionally related to the nonparalyzable (nonextendable) dead time per incoming pulse caused by an ADC during pulse processing. Nonparalyzable means that the dead time period is not prolonged by a new pulse arriving during that time [14]. In the nonparalyzable model, recovery period of electronic device is not affected by events that have come into being during the s dead time [16].

#### 5.3. Live-time correction model

On the assumption that all the MCA dead-time losses are manifested through the input rate, the accumulated live time takes as the proper counting time of the measurement should be both necessary and sufficient. The live time is the actual time during which the system is open and available for collecting counts. Thus, the counts within a spectral peak must be divided by live time (Tlive, in seconds) to obtain the counts per second. This model is well in low count rate situations [6].

#### 5.4. Gedcke-hale model

This model is a development of the previous one, which also compensates for losses due to leading edge pileup in the amplifier and is favored by EG&G Ortec. It predicts a correction based on Poisson statistics. This method can be roughly expressed as follows [6]:

$$\text{Counts to memory } = \text{ input pulses to amplifier} \frac{T\_{\text{Live}}}{T\_{\text{Real}}} \tag{17}$$

Where Tlive is the live time and Treal is the real time of the counting system.

#### 5.5. Pulser Model

In this model, the pulser generates constant amplitude pulses that are similar to the pulses output from the detector. These pulses are sent to preamplifier. Through the electronic components of the gamma-ray spectrometry, the produced pulses are transported and stored in the memory as a pulser peak. It is a fair assumption that the fractional losses sustained by the pulser counts are the same as those sustained by the gamma-ray derived counts. Thus, deadtime losses in the gamma spectrometry may be allowed for by multiplying the gamma peak areas by the following simple ratio [6]:

$$\frac{\text{pulses produced by pulse}}{\text{Pulse counts in pulse peak}}\tag{18}$$

#### 5.6. Loss-free counting model

There is a number of methods can be grouped under this general heading. All of them make use of a subsidiary circuit to monitor the instantaneous count rate and based on that generate a weighting factor, n. Thus, the high instantaneous count rate is reflected by a high count in a channel in the spectrum that is appropriate at that time [6].

The Harms procedure was a pioneering effort. It counts those pulses that are presented for processing but which are rejected because the system is busy. The number of discarded pulses in such a scale is read and used to weight the next real event. However, the ADC processing time is not necessarily the major problem at high count rates as losses due to pulse pileup can dominate [6].

#### 5.7. Zero dead-time counting model

Changing the dead time problems of gamma-ray spectrometry is a source of a well-known error. The dead-time correction under such conditions may be true if changing the dead time dominantly affected measured radioisotopes [17, 18]. Zero dead-time losses correction is almost the same as the loss-free counting. The difference between them is completely quantified of zero dead-time correction.

#### 5.8. Integral dead-time correction model

5.4. Gedcke-hale model

38 New Insights on Gamma Rays

5.5. Pulser Model

areas by the following simple ratio [6]:

channel in the spectrum that is appropriate at that time [6].

5.6. Loss-free counting model

5.7. Zero dead-time counting model

fied of zero dead-time correction.

dominate [6].

This model is a development of the previous one, which also compensates for losses due to leading edge pileup in the amplifier and is favored by EG&G Ortec. It predicts a correction

Counts to memory <sup>¼</sup> input pulses to amplifier <sup>T</sup>Live

In this model, the pulser generates constant amplitude pulses that are similar to the pulses output from the detector. These pulses are sent to preamplifier. Through the electronic components of the gamma-ray spectrometry, the produced pulses are transported and stored in the memory as a pulser peak. It is a fair assumption that the fractional losses sustained by the pulser counts are the same as those sustained by the gamma-ray derived counts. Thus, deadtime losses in the gamma spectrometry may be allowed for by multiplying the gamma peak

pulses produced by pulser

There is a number of methods can be grouped under this general heading. All of them make use of a subsidiary circuit to monitor the instantaneous count rate and based on that generate a weighting factor, n. Thus, the high instantaneous count rate is reflected by a high count in a

The Harms procedure was a pioneering effort. It counts those pulses that are presented for processing but which are rejected because the system is busy. The number of discarded pulses in such a scale is read and used to weight the next real event. However, the ADC processing time is not necessarily the major problem at high count rates as losses due to pulse pileup can

Changing the dead time problems of gamma-ray spectrometry is a source of a well-known error. The dead-time correction under such conditions may be true if changing the dead time dominantly affected measured radioisotopes [17, 18]. Zero dead-time losses correction is almost the same as the loss-free counting. The difference between them is completely quanti-

Pulser counts in pulser peak (18)

TReal

(17)

based on Poisson statistics. This method can be roughly expressed as follows [6]:

Where Tlive is the live time and Treal is the real time of the counting system.

The major constraint in the gamma-ray spectrometers is both the time required to collect the charge produced by ionizing radiation in the active detector volume and subsequently the pulse processing by the electronics [14, 19]. In this major constraint of all gamma-ray spectrometers, there is a minimum amount of time called dead time of the spectrometer system. During this dead time, the system cannot respond to other incoming photons and these events cannot be counted and thus can be lost [14]. One of the major problems confronting the user of gamma-ray spectrometer is to correct the results for counts lost due to the spectrometer dead time. This problem can be solved automatically by carrying out all counting runs for a known or measured total instrument live time rather than for real time [14, 20].

When count rate is kept nearly constant, counting losses due to dead time can be corrected by a simple formulae for both types of nonextendable and extendable dead times [14, 21]. However, when the count rate changes or fluctuates significantly, the correction based upon mathematical means becomes difficult and complex. In order to overcome this problem, a method was demonstrated by Kawada [14, 22], which allows compensating the dead time effects automatically at every moment during the counting experiment. In this method, pulses whose number is equivalent to the dead-time losses were generated as random coincidence pulses using a gating technique in a first-order approximation and added to the output pulse train after delay [14, 23].

The problem of varying dead time is a well-known source of error in nuclear spectrometry measurement. In this case, dead-time corrections can only be accurate if the varying dead time is dominantly caused by a radiation source. Solutions have been offered in several forms: dead time stabilization [14, 24–26] solves the problem at the cost of a fixed, perhaps unnecessary, dead time and resulting loss of counting efficiency [17]. However, results of the other deadtime correction models have not been forthcoming for counting losses due to the system dead time. It is a reliable estimation of the original count rate or of the number of original events for the interval of time considered. To do this, we need either an accurate value for the average loss per dead time or a method that allows us to arrive at individual corrections. An analytic correction method was developed instead of using a pulser or a radioactive source. This proposed model by Karabıdak et al. [14] is based on a measuring principle on the total live time.

#### 5.8.1. Background of the integral dead-time correction model

In Galushka's study [14, 27], a method is described for restoring dead-time losses in real time so that at the output of a counter, constructed according to this new scheme, one obtains directly by the number of events expected in the absence of dead time. This is accomplished by inserting additional pulses into actual series of registered events. In such a situation, let the observed sequences of events be characterized by the arrival times T0, T1, T<sup>2</sup> … [14, 28]. Consecutive arrivals are separated at least by the peaking time, TP, applied. If we put T<sup>0</sup> = 0, then pulse number, k, occurs at the instant [14]:

$$\begin{array}{l} T\_k = T\_1 + T\_2 + \dots + T\_k \\ = (\tau + \delta\_1) + (\tau + \delta\_2) + \dots + (\tau + \delta\_k) \\ = k\tau + \sum\_{j=1}^k \delta\_j for \, k \ge 1 \end{array} \tag{19}$$

where δj is the width of each pulse, which is separated from each other by steady dead time arising from peaking time of the amplifier. However, peaking time is important for calculations of counting losses due to the dead time of the system. Therefore, the dead time of the system is determined by adding the peaking time to the ADC converting time. To determine the dead time of the system, minimum resolving time should be ascertained first [14].

For counting losses due to systems dead time, both approaches are possible. Traditional correction formulae were used for the first method: they are based on the observed count rate and are applied at the end of a measurement period [14]. On the contrary, methods of a second type work in a different way by instantly correcting or compensating for losses, apparently without requiring knowledge of the measurement or calculate count rate. In the second method, it is possible to estimate the probability of losing a specific number k of counts in a dead time of length TD. Since we deal with a Poisson process, this probability is given by Refs. [14, 23, 28]:

$$P\_k = \frac{\left(nT\_D\right)^k}{k!}e^{-nT\_D} \tag{20}$$

where n is the count rate in each channel. The expected counting losses due to each dead time are given as follows [14]:

$$L = \sum\_{k=1}^{\bullet} kP\_k = e^{-nT\_D} \sum\_{k} \frac{(nT\_D)^k}{(k-1)!} = nT\_D \tag{21}$$

Thus, correction counting is given by Ref. [14]:

$$\mathsf{C}\_{\mathsf{C}} = \mathsf{Count} + L \tag{22}$$

#### 5.9. Differential dead-time correction model

Recording two pulses apart as two different events at almost all detectors systems requires to be separated from another pulse. This situation needs the minimum time interval [15]. The minimum time interval based on electronic devices using the counting system is usually called the dead time of the counting system. This is generally determined by pileup reject time, paralyzable or nonparalyzable system dead time or a combination of these mechanisms [13]. The photons arriving to the detector at the dead time period are not being counted. Thus, count rate, which is expressed as the count of per unit time, decreases [15].

The paralyzable and nonparalyzable models are assumed to express the idealized behavior. Every true event came into being during live time of detector was assumed to occur in a stable s dead time at every two models [7, 15]. However, this situation is only valid in the dead time depending on peaking time of amplifier. Nevertheless, a counting system can be containing analog-to-digital converter (ADC) which determines the energy value of pulse. The dead time of such a counting system is variable with ADC conversion time [14]. Therefore, fulfilled corrections, which are taken into account for a fixed dead time, cannot be realistic. In addition, modern counting systems consist of electronic devices, which contain paralyzable (amplifier), nonparalyzable (ADC) and pileup reject (amplifier) [15, 29]. The paralyzable and nonparalyzable models predict the same first-order losses and differ only when true event rates are high. These models have two extreme idealized system behaviors and real counting systems often display a behavior that is intermediate between these extremes. The detailed behavior of a specific counting system may depend on physical processes taking place in the detector, delay introduced by the pulse processing and recording electronics [15].

Tk ¼ T<sup>1</sup> þ T<sup>2</sup> þ … þ Tk

δ<sup>j</sup> f or k≥1

¼ kτ þ ∑ k j¼1

first [14].

40 New Insights on Gamma Rays

[14, 23, 28]:

are given as follows [14]:

time, decreases [15].

¼ ðτ þ δ1Þþðτ þ δ2Þ þ … þ ðτ þ δkÞ

where δj is the width of each pulse, which is separated from each other by steady dead time arising from peaking time of the amplifier. However, peaking time is important for calculations of counting losses due to the dead time of the system. Therefore, the dead time of the system is determined by adding the peaking time to the ADC converting time. To determine the dead time of the system, minimum resolving time should be ascertained

For counting losses due to systems dead time, both approaches are possible. Traditional correction formulae were used for the first method: they are based on the observed count rate and are applied at the end of a measurement period [14]. On the contrary, methods of a second type work in a different way by instantly correcting or compensating for losses, apparently without requiring knowledge of the measurement or calculate count rate. In the second method, it is possible to estimate the probability of losing a specific number k of counts in a dead time of length TD. Since we deal with a Poisson process, this probability is given by Refs.

Pk <sup>¼</sup> <sup>ð</sup>nTD<sup>Þ</sup>

L ¼ ∑ ∞ k¼1

Thus, correction counting is given by Ref. [14]:

5.9. Differential dead-time correction model

kPk ¼ e

where n is the count rate in each channel. The expected counting losses due to each dead time

<sup>−</sup>nTD ∑ k

Recording two pulses apart as two different events at almost all detectors systems requires to be separated from another pulse. This situation needs the minimum time interval [15]. The minimum time interval based on electronic devices using the counting system is usually called the dead time of the counting system. This is generally determined by pileup reject time, paralyzable or nonparalyzable system dead time or a combination of these mechanisms [13]. The photons arriving to the detector at the dead time period are not being counted. Thus, count rate, which is expressed as the count of per unit

ðnTDÞ k

k <sup>k</sup>! <sup>e</sup>

<sup>−</sup>nTD (20)

<sup>ð</sup>k−1Þ! <sup>¼</sup> nTD (21)

CC ¼ Count þ L (22)

(19)

In medium and high-count rate events, both of the two models are not applicable. The corrections, which are done by these models, are problematic because of the limitations expressed below. The troubling aspect of nonparalyzable model is the singularity at mτ – 1 and the fact that a maximum observed counting rate of 1/τ is approached in the limit as n approaches infinity. In the paralyzable model, the observed counting rate becomes zero at high-count rate. In addition, it should be noted that this model could not be explicitly solved for n0. Nevertheless, this model solves a transcendental equation to obtain the true counting rate. In addition, the observed counting rate is either double valued or does not exist above a maximum value given by exp (−1/τ) [14, 30].

This model can be applied to the counting systems at which the system dead time is not predominant on count rates. That is, this method adequately corrects counting lost at steady counting rate. In addition, the dead-time or count-rate corrections based on live time can be ideal in the count rates which are not predominate at the system dead time [15]. In addition, on a mathematical essence, the principle of the live time is an integral mathematics. The integral mathematics is correct if applied only to stationary Poisson processes (invariable in time). It should be noted that time-invariant Poisson processes are valid in experimental studies with radionuclides having long half-lives. The current study includes count-rate corrections based on differential mathematics and the proposed model in this study is ideal in the count systems at which the system dead time is predominant on count rates. Differential mathematics is also correctly applicable to Poisson process changing in time [15].

#### 5.9.1. Background of the differential dead-time correction model

Kurbatov et al. [15, 31] proposed a correction method that included to a statistical approach for Geiger—Muller counter. All of photons emitted from source are assumed to be caught by the detector and transmitted to counting system without loss. Let P(t) be the probability that a photon is emitted from a source in the interval (t−τ, t). Let a(t)dt be the probability that a photon is caught by detector and transmitted to counting system during the interval (t, t + dt). The fact that P(t) is a continuous function of t is used here. In order that a photon can be caught by the detector and sent to counting system, it is necessary and sufficient that; (i) a photon is sent counting system from detector in the time interval (t, t + dt) and (ii) no counting take place in the time interval (t − τ, t). Since these are independent events, the realization probability of one counting in the time dt becomes. Then, since only one counting can occur in the interval (t − τ, t), the probability of one counting in that interval is [15, 31]:

$$P(t) = \int\_{t-\tau}^{t} [1 - P(\mathbf{x})] a(\mathbf{x}) d\mathbf{x} \tag{23}$$

When 1−QðxÞ ¼ PðxÞ conversion is taken into consideration, the following equation can be written as:

$$Q(t) = 1 - \int\_{t-\tau}^{t} Q(\mathbf{x}) a(\mathbf{x}) d\mathbf{x} \tag{24}$$

If t is too large of τ, a(t) is independent of t. For a preparation whose decay constant is λ, containing N<sup>0</sup> atoms at time zero, f approaches to while N<sup>0</sup> increases [15, 32, 33]. Then, the expected number of photons reaching the detector in t time without dead time (the P(x) probability equal zero) is given by Ref. [15]:

$$\mathbf{C}(t) = \bigwedge\_{0}^{t} \mathbf{N}\_{0} \lambda e^{-\lambda t} dt = \mathbf{N}\_{0} (1 - e^{-\lambda t}) \tag{25}$$

Considering these inferences, the differential correction model can be created in the following way: λ on Eq. (17) is known as "decay constant" and is defined as the number of decay particles per second. In addition, unit of λ is 1/second. On the other hand, the number of particles counted per second by the detector defines counting rate. Therefore, unit of the counting rate is 1/second. Decay constant and counting rate are equivalent from the perspective of analogical. Therefore, the counting system consisting of only amplifier or ADC or both amplifier and ADC can be considered as a decaying source. In that case, n<sup>0</sup> maximum number of counting rate of the amplifier or the ADC or both the amplifier and ADC can be compared with N0, the number of particles at t = 0 in a radioactive source. Thus, Eq. (25) may be rearranged when n<sup>0</sup> instead of N<sup>0</sup> and λ [15]:

$$n(t) = \int\_0 n\_0 n\_0 e^{-n\_0 t} dt = n\_0 (1 - e^{-n\_0 t}) \tag{26}$$

Where n(t) is the count rate recorded by the counting system which consists of a detector, an amplifier and ADC.

For a compound system, observed counting rate in each channel of X or gamma-ray spectrum is given by Karabıdak et al. [14]. Karabıdak and Çevik [15] calculated the dead time for amplifier, ADC, or both amplifier and ADC. Thus, for a compound system, counting rate correction, (or true counting rate) corresponding to each channel can be satisfied by:

#### Dead Time in the Gamma‐Ray Spectrometry http://dx.doi.org/10.5772/67083 43

$$m\_0 = \frac{1}{T\_D} \ln \left( \frac{1}{1 - m \cdot T\_D} \right) \tag{27}$$

In this case, corrected count in each channel at a counting period in a spectrum is given by Ref. [15]:

$$\mathcal{C}\_{\mathbb{C}} = n\_0 T\_{\text{Real}} \tag{28}$$

where TReal is the real time of the counting system.

#### 6. Conclusion

can be caught by the detector and sent to counting system, it is necessary and sufficient that; (i) a photon is sent counting system from detector in the time interval (t, t + dt) and (ii) no counting take place in the time interval (t − τ, t). Since these are independent events, the realization probability of one counting in the time dt becomes. Then, since only one counting can occur in the interval (t − τ, t), the probability of one counting in that interval

When 1−QðxÞ ¼ PðxÞ conversion is taken into consideration, the following equation can be

t t−τ

If t is too large of τ, a(t) is independent of t. For a preparation whose decay constant is λ, containing N<sup>0</sup> atoms at time zero, f approaches to while N<sup>0</sup> increases [15, 32, 33]. Then, the expected number of photons reaching the detector in t time without dead time (the P(x)

Considering these inferences, the differential correction model can be created in the following way: λ on Eq. (17) is known as "decay constant" and is defined as the number of decay particles per second. In addition, unit of λ is 1/second. On the other hand, the number of particles counted per second by the detector defines counting rate. Therefore, unit of the counting rate is 1/second. Decay constant and counting rate are equivalent from the perspective of analogical. Therefore, the counting system consisting of only amplifier or ADC or both amplifier and ADC can be considered as a decaying source. In that case, n<sup>0</sup> maximum number of counting rate of the amplifier or the ADC or both the amplifier and ADC can be compared with N0, the number of particles at t = 0 in a radioactive source. Thus, Eq. (25) may be

dt ¼ N0ð1−e

dt ¼ n0ð1−e

Where n(t) is the count rate recorded by the counting system which consists of a detector, an

For a compound system, observed counting rate in each channel of X or gamma-ray spectrum is given by Karabıdak et al. [14]. Karabıdak and Çevik [15] calculated the dead time for amplifier, ADC, or both amplifier and ADC. Thus, for a compound system, counting rate correction, (or true counting rate) corresponding to each channel can be

−n0t

−λt

½1−PðxÞ�aðxÞdx (23)

QðxÞaðxÞdx (24)

Þ (25)

Þ (26)

PðtÞ ¼ ∫ t t−τ

QðtÞ ¼ 1− ∫

CðtÞ ¼ ∫ t 0 N0λe −λt

nðtÞ ¼ ∫ t 0 n0n0e −n0t

is [15, 31]:

42 New Insights on Gamma Rays

written as:

probability equal zero) is given by Ref. [15]:

rearranged when n<sup>0</sup> instead of N<sup>0</sup> and λ [15]:

amplifier and ADC.

satisfied by:

A practical method to determine the dead time is proposed by Karabıdak and colleagues [9]. In other methods to determine the dead time, the dead time due to the amplifier and ADC is determined separately. In addition, to compensate for the counting losses kept constant dead time is fulfilled by considering a fixed dead time. Wherein, the dead time in this method is obtained at the same time for both the amplifier and ADC. An effective way of decreasing counting losses is by decreasing the system dead time in quantitative and qualitative analysis. Thus, the dead time is that variables in the counting process are fulfilled and the counting losses for a unified system are easily compensated. Because the system dead time is linked to the amplifier peaking time, the amplifier peaking time can be set to lower and optimum values.

The integral dead-time correction is effective both for low count rates and for medium count rates. It is possible to observe the dead time contributions due to ADC conversion time and peaking time in this model. Thus, counting losses correction arising from system dead time can be made for demanded situation (nonparalyzable or paralyzable or both). The dead time of the counting system was determined with an analytic formula. Counting losses occurring during this dead time were compensated for by considering uncorrected spectra obeying the Poisson behavior. This new method adequately corrects counting loss at steady counting rate [14].

The differential dead-time correction is effective both for medium count rates and for high-count rates. Output count rates of the only ADC and both the amplifier and ADC are the same. In addition, output-counting rates of the only amplifier are higher than others output counting rates. Moreover, increasing peaking time of the amplifier increases both the dead time and the counting losses. In addition, this model easily determined the relationship between the output counting rates and input counting rates. According to the dead time of the counting system, the amplifier or ADC or both the amplifier and ADC may be taken into account up to a certain limit value. This limit value of such electronic devices represents a saturation point. This saturation point is determined by the size of the dead time of the counting system. This is a result of Poisson statistics. Since the dead time is a function of the peaking time of the amplifier and photon energy, this saturation point is directly related to them. Therefore, while low peaking time determines low dead time, low dead time determines the high saturation point (or counting rate) [15].

The dead time increases as long as the counting rate increases. This increase in dead time becomes stable at around 1 s after a certain point. This fixed point corresponds to the counting rate at saturation point of the electronic system at which the detector is not considered to be receiving the photons [15].

#### Author details

Salih Mustafa Karabıdak

Address all correspondence to: smkarabidak@gumushane.edu.tr

Department of Physics Engineering, Faculty of Engineering and Natural Sciences, Gümüşhane University, Gümüşhane, Turkey

#### References


[12] Spieler H. Introduction to radiation detectors and electronics [Internet]. 2009. Available from: http://www-physics.lbl.gov/~spieler/physics\_198\_notes\_1999/index.html [Accessed: 14-02-2009]

rate at saturation point of the electronic system at which the detector is not considered to be

Department of Physics Engineering, Faculty of Engineering and Natural Sciences, Gümüşhane

[1] Rutherford E, Geiger, H. An electrical method of counting the number of α-particles from

[2] Debertin K, Helmer RG. Gamma and x-ray spectrometry with semiconductor detectors.

[3] Pell EM. Effect of Li-B ion pairing on Li+ ion drift in Si. J. Appl. Phys. 1960;31:1675–1680.

[4] Mayer JW. Semiconductor detectors for nuclear spectrometry II. Nucl. Instr. Meth.

[5] Sakai E. Present status of room temperature semiconductor detectors. Nucl. Instr. Meth.

[6] Gilmore G, Hemingway JD. Practical gamma-ray spectrometry. 2nd ed. Chichester: John

[7] Knoll GF. Radiation detection and measurement. 3rd ed. New York: Jhon Wiley and Sons

[8] Prussin SG. Prospects for near State-of-the art analysis of complex semiconductor spectra in the small laboratory. Nucl. Instr. Meth. 1982;193:121–128. DOI: 10.1016/0029-554X(82)

[9] Karabıdak SM, Kaya S, Çevik U, Çelik A. Determination of proper peaking time for Ultra-LEGe detector. Radiat. Measur. 2011;46:446–450. DOI: 10.1016/j.radmeas.2011.01.023 [10] Tennelec Instruction Manual TC 244 Amplifier. Oxford Instruments Inc. Analytical Sys-

[11] Gerardi G, Abbene L, Manna AL, Fauci F, Raso G. Digital filtering and analysis for a semiconductor x-ray detector data acquisition. Nucl. Instr. Meth. A 2006;571:378–380.

Address all correspondence to: smkarabidak@gumushane.edu.tr

radio-active substances. Proc. R. Soc. Lond. A 1908;81:141–161.

1966;43:55–64. DOI: 10.1016/0029-554X(66)90532-5

1982;196:121–130. DOI: 10.1016/0029-554X(82)90626-7

tems Division. Nuclear Measurements Group. USA, 1986.

receiving the photons [15].

Salih Mustafa Karabıdak

University, Gümüşhane, Turkey

Amsterdam: Elsevier; 1988. 402 p.

Wiley and Sons Inc.; 2008. 390 p.

DOI: 10.1016/j.nima.2006.10.113

Inc.; 2000. 796 p.

90685-1

DOI: 10.1063/1.1735914

Author details

44 New Insights on Gamma Rays

References

