RADON IN A TOURIST CAVE: A ONE YEAR CONTINUOUS SURVEY OF THE CONCENTRATIONS OF ATTACHED AND UNATTACHED RADON PROGENY AND RADON

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1 Radon in the Living Environment, 062 RADON IN A TOURIST CAVE: A ONE YEAR CONTINUOUS SURVEY OF THE CONCENTRATIONS OF ATTACHED AND UNATTACHED RADON PROGENY AND RADON W. Zahorowski 1, S. Whittlestone 1, J. James 2 and S. Solomon 3 1 ANSTO, PMB 1, Menai, NSW 2234, Australia 2 Dept. of Chemistry, University of Sydney, NSW 2006, Australia 3 ARPANSA, Lower Plenty Rd, Yallambie, VIC 3085, Australia Radon, radon progeny and unattached radon progeny were measured in two chambers with different characteristics at the Jenolan Caves, New South Wales, Australia, in Meteorological parameters and condensation nucleus concentrations were measured in order to understand the processes governing the radon concentration and degree of disequilibrium with the progeny. One chamber was poorly ventilated, and rainfall proved to be the most important influence on radon concentration. The other was well ventilated, and most subject to strong convective flows driven by surface temperature. Under some conditions atmospheric pressure was an important factor. The radiation exposure was evaluated both from the radon using a constant conversion factor, and by the more rigorous method of using both the attached and unattached progeny as input to the Respiratory Tract Model recommended in ICRP-66. The size dependent conversion factors were determined for each chamber during a four day period in which activity-size distributions were measured using a wire screen diffusion battery. The size-weighted dose conversion factors were on average 1.7 times the conversion convention factor recommended in ICRP-65. Keywords: Radon, radon progeny, activity size distributions, unattached fractions, ICRP Respiratory Tract Model, dose conversion factors, show cave, diffusion battery, meteorology, seasonal variations. INTRODUCTION The cave environment is different from that of most dwellings because the ventilation and particle concentrations are often substantially lower (Solomon et al. (1992), Cheng et al. (1997)) These factors influence the equilibrium ratio and unattached fraction of the radon progeny in the cave. The dosimetric models (Birchall and James (1995), Porstendőrfer and Reineking (1999)) for inhalation of radon progeny predict that the factor for converting radon progeny exposure to effective dose would be different from the value recommended by the International Commission for Radiological Protection (ICRP) in its Publication 65 (ICRP, 1993). The Jenolan Caves, about 100 km west of Sydney, Australia, have been identified as having radon concentrations in excess of 1000 Bq m -3 (Solomon et al., 1996). This level has been adopted as an action level by the Australian National Health and Medical Research Council. Any workplace in which the average radon level exceeds 1000 Bq m -3 must institute measures to ensure that no worker receives more than 20 msv per year. Given the condition of low condensation nucleus (CN) concentrations, the ICRP-65 dose conversion convention was unlikely to be appropriate at the Jenolan Caves. An intensive study was made of the equilibrium ratio and unattached fraction of the radon progeny at two locations with markedly different ventilation. One, the Temple of Baal, is a large chamber almost a kilometre from the nearest known natural entrance. Passages leading to the chamber are at the bottom, so air exchange is slow, and temperature and humidity steady. The other chamber, Katie's Bower, is a 547

2 062 Radon in the Living Environment, small chamber, approximately 150 m from the nearest natural entrance. The chamber forms part of a series which exhibits a strong "chimney effect" (Wiggley and Brown, 1976) which results in changes in the intensity and direction of air flow in response to surface meteorological changes. Because it was known that there are strong seasonal changes which could influence the dose conversion factor the study was carried out for a full year. Meteorological data were also recorded to assess the influence of external conditions on the radon levels in the cave. Detailed analysis of the radon and meteorological data have yielded insights into the sources and transport of radon in cave systems. In particular rainfall is shown to have a strong influence on radon concentrations. Inter-annual variability of rainfall is the main factor in the wide difference in radon levels from year to year. The unattached fraction and equilibrium coefficient are not sufficient to fully determine the dose conversion factor, but the techniques necessary were not practicable for a full year deployment at two sites. The approach taken was to characterise the aerosols and the attached and unattached progeny at each site during a 4 day intensive experiment from 11 March Conditions were sufficiently similar during the rest of the year to those in this period, that the rigorously determined conversion factors could be applied to the data for the whole year. In an initial assessment of the first 6 months of observations at Jenolan Caves (Zahorowski et al., 1998), the radiation dose estimates for radon exposure to tour guides were derived using both the radon progeny conversion convention recommended by ICRP-65, as well as dose conversion factors derived using the Respiratory Tract Model recommended in ICRP Publication 66 (ICRP, 1994). For these latter estimates, the dose conversion factors were calculated from the measured values of f p, the unattached fraction of potential alpha energy concentration (PAEC), using a formula derived from measurement of radon progeny particle size distributions in house, mines and buildings, but not in caves (Solomon, 1997). An aim of this present work was to assess the appropriateness of this formula in the cave conditions and to compare the estimates of inhalation dose derived using the ICRP-65 conversion convention and with the updated dosimetric estimates. This comparison used additional measurements to characterise the radon progeny activity size distributions at the Temple of Baal and Katie's Bower sites in the Jenolan Caves. These measurements were made during the 4 day intensive experiment in March EXPERIMENTAL Radon and radon progeny concentrations The concentrations of radon were measured by 1 L scintillation cells, and radon progeny by counting alpha particle emissions from a filter (for total) or screen (for the unattached fraction) through which air was drawn continuously, at a flow rate of 0.8 L min -1. Unattached progeny were collected on a 20mm diameter 400 mesh stainless steel wire screen which had a 50% cut point of 4 nm. Correction for front-to-back ratio and screen loss was made using a factor of 1.24 calculated from the formula of Solomon and Ren (1992). The methods are described in detail by Zahorowski et al. (1998). Calibrations were performed at approximately two month intervals. Assessment of Radon Progeny Activity Size Distributions The PAEC, the unattached fraction of PAEC (f p ) and the PAEC activity size distributions were measured using a six-stage wire screen diffusion battery, which was operated with a continuous 548

3 Radon in the Living Environment, 062 sampling rate of 0.8 L min -1 per stage. The diffusion battery used in-situ alpha particle counting of radon progeny deposited on a collector (filter or screen) in each stage. The mode of operation of the diffusion battery has been described previously (Solomon and Wilks, 1994). The collection efficiencies for each stage were calculated using the fan-filtration penetration theory applied to wire screens by Cheng and Yeh (1980) and Cheng et al. (1980), with a semi-empirical diffusion coefficient equation in the molecular cluster size range (Ramamurthi and Hopke, 1989). The analysis of activity collected on the wire screen collector used the corrections for losses in the screens and for the front to total ratio from Solomon and Ren (1992). The wire screen parameters and calculated stage characteristics are summarised in Table 1. The collection and analysis of the diffusion battery data were all carried out by a purpose-written computer programme running on a PC based computer. For each 20 minute integration period, the set of six alpha activities were converted to PAEC and deconvoluted using both the Twomey (1975) and the Expectation Maximisation (EMax) algorithms (Maher and Laird, 1985 ) to derive two separate particle size distributions in 40 logarithmically spaced size intervals between 0.6 nm and 1500 nm. A size-weighted dose conversion factor was derived for each sample by combining the measured radon progeny size distribution with the particle-size dependent dose conversion factors, calculated using the ICRP-66 model, as implemented in the computer programme RADEP (Birchall and James, 1995). Dose conversion factors were calculated for an adult male using a breathing rate of 1.2 m 3 h - 1, assuming representative activity concentration ratios for 218 Po : 214 Pb : 214 Bi of 0.8 : 0.02 : 0.0 and 0.8 : 0.4 : 0.2, for particle sizes < 20 nm and >=20 nm, respectively. The resultant doses are relatively insensitive to the exact choice of values for the equilibrium ratios (Birchall and James, 1995). The ICRP-66 model-derived values have been adjusted by a factor of 0.3 to provide consistency with the epidemiologically-derived risk estimates in ICRP-65. RESULTS AND DISCUSSION Figure 1 shows weekly averages of radon concentrations with the standard deviations of each weekly distribution for both chambers. The radon scale is logarithmic, so the size of the bar indicates the percentage deviation. Data recovery was very good apart from a one month gap in spring caused by computer malfunction. For the Temple of Baal there are 3 periods evident in this graph. Weeks -2 to 8 have low to medium radon with high standard deviations, weeks 9 to 18 have high radon and high standard deviations, and weeks 19 to 45 have low radon and low standard deviations. In contrast, Katie's Bower exhibits a smooth seasonal variation correlating strongly to the mean weekly temperature, and high standard deviations throughout the year. Temple of Baal In an attempt to explain the gross features of the Temple of Baal radon concentrations, distributions of the meteorological data were examined for each of the three periods. As shown in Table 2, the high radon period had meteorological data median values intermediate between the data for the lower radon periods, with the exception of average rainfall, which is lower by a factor of 4 in the autumn high radon period compared to the other seasons. In the previous year, , Solomon et al. (1996) report an autumn minimum and spring maximum in their seasonal average radon concentrations (Table 3). The autumn rainfall in 1995 (2.4 mm, Table 3) was much higher than in autumn 1996 (0.5 mm). Also, in winter 1994, rainfall was lower than in winter 1996 (0.7 mm compared to 2.2 mm) and radon much higher. Clearly rainfall is the main factor governing radon concentration in the Temple of Baal. 549

4 062 Radon in the Living Environment, There are two ways in which rain can decrease radon concentrations. It can block air paths or it can flood areas of the sediment which is the source of radon. Evidence that blockage is a major factor comes from the very low variation of radon in the Temple of Baal during period 3. If simple suppression of flux were the cause, the variability would be expected to be similar to that of periods 1 and 2. It proved instructive to study the correlation of radon with other parameters within each period. In correlation analysis, long term trends can mask short term correlations, so the analysis was performed on de-trended data as well as unprocessed radon data. The procedure was to generate a trend by taking a 600 hour running mean of the radon hourly values. Then the concentrations were divided by the running mean to generate a normalised de-trended radon value. To remove short term fluctuations the data were smoothed by a 12 hour running mean. The effect was to give the same weight to an event in which, for example, a given change of pressure correlated with a change of radon of 10% when the radon was low, as an event in which the 10% radon change occurred when the radon was ten times higher, even though the absolute change in radon in the latter case was ten times bigger. As shown in Table 4, period 1 showed no significant correlations. Periods 2 and 3 on the other hand, both exhibited strong correlations with surface pressure (negative) and total rainfall in the 6 days prior to the radon measurement (positive). The negative correlation with pressure indicates that radon flux is suppressed by elevated pressure over time scales of tens of days, which is consistent with observations by Schery et al. (1984). It is obvious that there will be a lag between the change in flux and a change in radon concentration. The 17 hour lag during period 3 is consistent with the major radon source being close to or within the Temple of Baal. In period 2, the chamber must be connected to a more distant network of sources which take on average 72 hours to affect radon concentrations. The correlation with rainfall is particularly interesting because it is positive. Figure 2 reinforces the evidence that radon concentrations increase with rainfall within period 3. An increase in radon concentration with rainfall can only be caused by a reduction in ventilation rate. The apparent contradiction with the negative correlation previously noted is resolved by considering the time scales. The positive response occurs only for rain within the previous 6 days. Presumably this can reduce air flows from the surface through soil and fine cracks, whereas in the longer term, rain can fill passage ways deep under ground, blocking paths through which high levels of radon can reach The Temple of Baal. A comparison of correlations with hourly and de-trended data indicates that pressure varies on a much shorter time scale than the de-trending period, so the correlation is better with de-trended normalised radon. The effect of rainfall changed over a period comparable to the 600 hour detrending period, and so de-trending removed part of the effect, leading to a better correlation for the hourly rather than the de-trended data. Another feature of the radon in the Temple of Baal is the high variability and moderate radon values in summer. Solomon et al. (1996) show that chambers close to The Temple of Baal are well ventilated and exhibit strong summer maxima in radon concentrations. An explanation for increased variability in The Temple of Baal in summer is therefore that there is some transfer through the lower passages, which is a significant source only when the neighbouring chambers have high 550

5 Radon in the Living Environment, 062 concentrations. This is supported by the condensation nucleus (CN) concentrations (Table 2). CN concentrations are relatively high during the periods of high variability. Since there are no significant sources of CN inside the caves, the presence of CN implies mixing with surface air. The magnitude of the CN concentration proves that the mixing is slow. Compared to surface air, which has typical concentrations of several thousand per cubic centimetre at Jenolan, the higher values in the Temple of Baal, about 300 cm -3, are low, as would be expected if it took a few days for the air to reach the Temple of Baal. Katie's Bower Temperature is the main factor governing radon concentrations in Katie's Bower. Zahorowski et al. (1998) observed that there was a 3 hour lag between a temperature change and the response of radon. As a starting point for better understanding details of radon in Katie's Bower, radon was compared to the temperature 3 hours before the radon concentration. This is presented in Figure 3, where radon mean, minimum and maximum are plotted versus lagged temperature. An immediate question suggested by this graph is how can there be such high radon in Katie's Bower when the temperature is so low that there should be a strong convectively driven wind blowing through the cave? There are 155 hourly events where radon is above 4000 Bq m -3 and the temperature below 10 o C, well below the cave temperature of 13 o C. Equally interesting are events at high temperatures where the radon concentration is low. These two classes of events can be understood in terms of meteorological conditions. At low temperatures, high radon occurred only when three conditions were fulfilled: the rainfall in the preceding 6 days was less than 15mm; the wind direction was westerly; and the wind speed was between 1 and 3 m s -1 (Table 5). Our interpretation is that in drier periods, as in the Temple of Baal long term, more soil pores and cracks are open to permit transport of radon from the surrounding rock into the cave; wind from the west could counteract the convective flow; and the wind speed needed to inhibit ventilation had to fall into a fairly narrow range: too little and the convective flow would predominate; too much and the wind itself would create its own ventilation. The other parameter, atmospheric pressure, although not as strong a factor as the others, was negatively correlated with high radon as in the Temple of Baal. If the radon were above 4000 Bq m -3, 75% of the pressure readings were below 930 mbar, whereas for radon below 500 Bq m -3 46% of the pressure readings were above this value. For temperatures above 21 o C the special conditions required to obtain low radon concentrations are more limited. Table 6 compares conditions when radon is low with when it is high. Wind speed is a little higher, and there is some tendency for the wind direction to be easterly. Evidently, although wind can inhibit ventilation in some circumstances, it cannot overcome the stability created by high temperatures. Rainfall is low for both high and low radon levels, and does not affect radon concentrations simply because in the Jenolan climate rain does not fall when the temperature is high. It is pressure which seems to be the major factor governing radon concentrations at high temperatures. If the radon is low the pressure is high half of the time, and conversely, if radon is high the pressure is low. Dose Estimates Figure 4 shows typical radon progeny activity size distributions for each of the two measurement sites. The measured size distributions remained relatively stable across both measurement periods. The averages of the geometric means for the ultrafine (unattached) and accumulation (attached) modes in 551

6 062 Radon in the Living Environment, the size distributions were 0.9 ± 0.1 nm and 144 ± 11 nm, respectively for the Temple of Baal, and 0.6 ± 0.2 nm and 160 ± 5, respectively for the Katie's Bower site. The estimates of the size-weighted dose conversion factors from the diffusion battery measurements were matched to the respective measurement of unattached fraction at each site. The relationship between the dose conversion factors and unattached fraction is shown in Figure 5. The points were well fitted ( R = 0.996) by a linear regression of the form DCF(mSv/WLM) = * [%Unattached Fraction] (1) or DCF(mSv/(J.h.m-3) = 155 * [%Unattached Fraction] (2) Figure 6 shows the weekly averaged values for the unattached fraction of PAEC for the two measurement sites for the full year In general the measured values were lower at the Katie's Bower site than for the Temple of Baal. The Temple of Baal showed a significant seasonal variation. The inhalation dose to the tour guides at the two reference sites can be estimated from the yearly measurements of radon, radon progeny and/or unattached fraction by a number of methods: (1) ICRP-65 recommends the use of a single epidemiologically-based factor for converting radon progeny exposure to effective dose, namely 1425 msv/(j h m -3 ) or 5mSv/WLM. The inhalation dose (effective dose per hour) was calculated from the product of the measured PAEC and the conversion convention. (2) A second estimate of inhalation dose rate was derived using the radon concentration and the conversion convention, assuming a single equilibrium factor of 0.4 for the full year. This would be the typical approach to assessing occupational exposure based on measurements of passive radon dosimeters. (3) The third estimate used a dose conversion factor determined from the unattached fraction, using the equation 1. The inhalation dose was calculated from the product of the measured PAEC and the unattached fraction dependent dose factor. (4) A fourth estimate was based solely on a single dose conversion factor applied to the measured radon concentration. For the period of the diffusion battery measurements, the effective dose per hour per radon concentration was determined to be 5.5 µsv.h -1 per kbq m -3 radon. Table 7 summarises the inhalation dose rates for the two measurement sites for each season during the year 1996, based on each of the four methods outlined above. In general the dose estimates based on the conversion convention (Methods 1 and 2) are significantly lower that those estimates using sizeweighted dose conversion factors (Method 3). The distribution of the ratios of the estimates for Methods 1 and 3 are shown in Figure 7, for the full year This ratio corresponds to the so-called K-factor used for comparative dosimetry by the National Research Council (NRC, 1991). In contrast, the agreement shown in Figure 8 for the distribution of ratios for estimates using Method 4, relative to Method 3, is very good. For both sites the use of a single radon-based factor produces dose estimates that are in good agreement with the estimates based on PAEC and a size-weighted dose factor. In the study of the first 6 months of the dataset Zahorowski et al. (1998) recommended a correction factor of 1.5 to the ICRP-65 convention for doses estimated from integrated radon exposures. With refinement of the model and inclusion of the full year's data, the revised estimate of the correction factor is 1.7 for Katie's Bower and 2.2 for the Temple of Baal (Table 7) 552

7 Radon in the Living Environment, 062 CONCLUSIONS The major factors governing radon concentration in two very different caves have been identified. In the Temple of Baal, a large chamber with low air exchange rates, average rainfall over periods of several weeks was strongly negatively correlated with radon concentration because large amounts of water underground could block transport of radon to the chamber. Over shorter time scales, rainfall was positively correlated with radon because the reduction of air exchange with the surface led to reduced ventilation rates and consequent build up of radon concentration. During periods of low surface temperatures, pressure was an important factor. When the average surface temperature was high, and neighbouring chambers likely to have high radon concentrations, transport from these chambers appears to be the predominant source or radon to the Temple of Baal. In Katie's Bower, a well ventilated chamber, recent rainfall, wind speed and wind direction were important in understanding the more unusual concentrations. However, the main influence on radon concentration was dilution of radon by convective air flows when the ambient temperature dropped below that of the cave. At high ambient temperatures, when the ventilation was strongly inhibited, pressure became the predominant influence on radon concentration. Both test sites had very low CN concentrations throughout the year, typically less than 1000 CN cm -3. As a direct result, the measured unattached fractions were significantly higher than those found in houses and mines. This in turn results in a significant enhancement to the dosimetrically-derived radon progeny dose conversion factors, with the increase over the ICRP-65 convention for radon being a factor in the range 1.5 to 3.0, with an average of 1.7. Despite wide ranges of radon concentrations, this factor applies to all seasons, which simplifies evaluation of dose from integrating radon monitors. ACKNOWLEDGEMENTS We are grateful to the Jenolan Caves Reserve Trust for permission to carry out the work. Ernst Holland and Karen Jones of the trust assisted with maintenance of the equipment and provided meteorological data for Meteorological data for were supplied by the Commonwealth Bureau of Meteorology, Australia. Bryan Stenhouse and Michael Hyde of ANSTO contributed to construction and calibration of the instruments. REFERENCES [1] Birchall A, James AC. Uncertainty Analysis of the Effective Dose per Unit Exposure from Radon Progeny and Implications for ICRP Risk-Weighting Factors. Radiat. Protect. Dosim. 1995; 60(4): [2] Cheng YS, Yeh HC. Theory of screen type diffusion battery. J. Aerosol Sci. 1980; 11: [3] Cheng YS, Keating JA, Kanapilly GM. Theory and calibration of screen type diffusion battery. J. Aerosol Sci. 1980; 11: [4] Cheng YS, Chen TR, Wasiolek PT, Van-Engen A. Radon and radon progeny in the Carlsbad Caverns. Aerosol Science and Technology 1997; 26: [5] International Commission on Radiological Protection (ICRP) Protection against radon-222 at home and at work. ICRP Publication 65. Ann. ICRP 1993;23(2). 553

8 062 Radon in the Living Environment, [6] International Commission on Radiological Protection (ICRP) Human Respiratory Tract Model for Radiological Protection. ICRP Publication 66. Ann. ICRP 1994; 24(14). [7] Maher EF, Laird NM. Algorithm Reconstruction of Particle Size Distributions from Diffusion Battery Data. J. Aerosol Sci. 1985;16: [8] National Research Council (NRC). Comparative Dosimetry of Radon in homes and Mines. Panel on the Dosimetric Assumptions affecting the Application of Radon Risk Estimates. National Academy Press, Washington, DC, [9] Porstendőrfer J, Reineking A. Radon: characteristics in air and dose conversion factors. Health Phys. 1999; 76: [10] Ramamurthi M, Hopke PK. On improving the validity of wire screen "unattached" fraction Rn daughter measurements. Health Phys. 1989;56: [11] Schery SD, Gaeddert DH, Wilkening MH. Factors affecting exhalation of radon from a gravelly sandy loam. J Geophys Res 1984; 89: [12] Solomon SB. A Radon Progeny Sampler for the Determination of Effective Dose. Radiat. Protect. Dosim. 1997, 72: [13] Solomon SB, Ren T. Counting Efficiencies for Alpha Particle Emitted from Wire Screens. Aerosol Science and Technology 1992; 17: [14] Solomon SB, Wilks M. Characterisation of Airborne Radioactivity in an Australian Dwelling. Radiation Protect. Dosim. 1994; 56: [15] Solomon SB, Langroo R, Peggie JR. Occupational exposure to radon in Australian tourist caves. An Australia-wide study of radon levels. Australian Radiation Laboratory report ARL/TR119, ISSN , [16] Wiggley TML, Brown MC. The physics of Caves. In: Ford TD, Cullingford CHD, editors. The science of Speliology. Academic Press, London, 1976, pp [17] Twomey S. Comparison of Constrained Linear Inversion and an Iterative Algorithm [18] Applied to the Indirect Estimation of the Particle Size Distribution. J. Comp. Phys. 1975; 18: [19] Zahorowski W, Whittlestone S, James J. Continuous measurements of radon and radon progeny as a basis for management of radon as a hazard in a tourist cave. J Radioanal Nucl Chem 1998; 236:

9 Radon in the Living Environment, 062 Table 1: Summary of parameters for wire screens diffusion battery used by the Australian Radiation Laboratory. D p 50 values correspond to particle diameter for which there is 50% collection efficiency. Stage No. of Screens (mm) Mesh* Screen Diameter (cm) Collector Flow (L min -1 ) D p Filter ** Mesh Filter Filter Filter Filter * 105 Mesh wire screen : wire diameter 72 µm, screen thickness 148 µm, solid fraction 25% ** Stage 2 operates as an effective dosimeter and has a collection efficiency optimised to match the size dependency of the radon progeny dose conversion factor. Table 2: Summary of meteorological data for the three characteristic periods in the Temple of Baal Period in Summer (day -19 to 61) 2. Autumn (day 75 to 122) 3. Winter (day 150 to 250) Description Medium radon, high variability High radon, high variability Low radon, low variability Wind speed: median, 25 and 75 percentiles (km h -1 ) 2.3, 1.4, , 1.5, , 1.7, 4.7 Wind direction: %E %NW Surface temperature: median, , 12.5, , 8.9, , 3.9, 8.8 and 75 percentiles ( o C) Surface pressure: median 25 and , 922, , 927, , 924, 934 percentiles (mbar) CN concentrations: median 25 and 190, 145, , 260, , 24, percentiles (cm -3 ) Rain (average daily total mm) Radon concentrations: median, 25 and 75 percentiles (Bq m -3 ) 2280, 2025, , 4746, , 1784,

10 062 Radon in the Living Environment, Table 3: Average radon concentrations in the Temple of Baal (from Solomon et al. 1996) and rainfall in Period Winter 1994 Spring 1994 Summer 1995 Autumn 1995 Average radon (Bq m -3 ) Average daily rainfall (mm) Table 4: Correlations in the Temple of Baal between radon and meteorological parameters and lag in hours between parameter and radon reading in brackets. Correlations were made with de-trended and re-normalised radon concentrations (see text) and the lag applied to the variable to obtain the best correlation with radon Period 1. Summer (day -19 to 61) 2. Autumn (day 75 to 122) 3. Winter (day 150 to 250) Radon data hourly de-trended hourly de-trended hourly de-trended processing Wind speed -0.19(70) (72) 0.27(86) 0.33 (83) 0.34(28) 0.23 (25) Surface 0.41(55) 0.40 (58) <0.1 < (126) 0.32 (115) temperature s o C Surface pressure -0.24(39) -.27 (77) -0.6(70) (73) -0.6(18) (16) Rain in 6 days prior to radon measurement <0.1 < (60) 0.31 (76) 0.75 (0) 0.61 (6) Table 5: Characterisation of high radon events at low surface temperature ( greater than 3oC and less than 10oC) in Katie's Bower.The distribution of radon concentration for each parameter is summarised by the percentage of events within the specified range of the parameter Parameter Condition High radon Rn > 4000 Bq m -3 Wind Speed (m s -1 ) Wind Direction (deg) Pressure (mbar) Rain in preceding 6 days (mm) Low radon Rn <500 Bq m -3 Between 1 and Between 260 and Less than Less than

11 Radon in the Living Environment, 062 Table 6: Characterisation of low radon events at high ambient temperatures (greater than 21 oc) in Katie's Bower. The distribution of radon concentration for each parameter is summarised by the percentage of events within the specified range of the parameter Parameter Condition Low radon Rn < 3000 Bq m -3 High radon Rn >10000 Bq m -3 Wind Speed (m s -1 ) > Wind Direction Between 60 and (deg) Rain in preceding < days (mm) Pressure (mbar) > Table 7: Seasonal and annual averages of hourly inhalation dose rate (Sv.h-1) as determined by the four computational methods for the Katie's Bower and Temple of Baal test sites in the Jenolan Caves for the year ICRP-65 with radon progeny 2. ICRP-65 with radon gas 3. Lung model (f p and radon progeny) 4. Lung model (radon) Temple of Baal Summer Autumn Winter Spring Annual average Katie's Bower Summer Autumn Winter Spring Annual average

12 062 Radon in the Living Environment, a Temple of Baal Jenolan Caves 1996 Radon (Bq m -3 ) Week in b Katie's Bower Jenolan Caves 1996 Radon (Bq m -3 ) Week in 1996 Figure 1: Weekly average radon concentrations in Katie's Bower and the Temple of Baal. The bars show the standard deviations of the concentrations in each week. 558

13 Radon in the Living Environment, Radon (Bq m -3 ) Max Min 75% 25% Median Rain in 6 days prior to radon measurements (5mm bins) Figure 2: Radon concentration ranges in The Temple of Baal in winter versus rainfall in previous 6 days, divided into 5mm/6 day bins. 559

14 062 Radon in the Living Environment, Katie's Bower Radon (Bq m -3 ) Lagged surface temperature ( o C) Figure 3: Katie's Bower radon mean, minimum and maximum are plotted versus lagged temperature. 560

15 Radon in the Living Environment, Katie's Bower 14 March 1996 Relative Activity Particle Diameter (nm) Temple of Baal 12 March 1996 Relative Activity Particle Diameter (nm) Figure 4: Typical Radon Progeny Activity Size Distributions at the two test sites in the Jenolan Caves derived from diffusion battery measurements March

16 062 Radon in the Living Environment, Dose Conversion Factor (msv/ WLM) DCF(mSv/WLM) = %f p DCF (msv/(j.h.m -3 )) = 155 %f p Dose Conversion Factor (msv/ J.h.m -3 )) % Unattached Fraction PAEC Figure 5: DCF versus %unattached fraction (%f p ) for the two measurement sites March 11 14, Solid line shows fitted linear regression (R = ). 562

17 Radon in the Living Environment, a Temple of Baal Jenolan Caves 1996 Unattaached fraction b Week in 1996 Katie's Bower Jenolan Caves 1996 Unattaached fraction Week in 1996 Figure 6: Weekly averaged values of unattached fraction of PAEC at Katie's Bower and the Temple of Baal in the Jenolan Caves for year

18 062 Radon in the Living Environment, 300 Gaussian Fit Mea n SD 0.62 Temple of Baal Jenolan Katie's Bower Jenolan Gaussian Fit N umb er in R ange 100 Number in Range 200 Mean S D Dose Rate Ratio (Method #3/ Method #1) Dose Rate Ratio (Method#3 / Method #1) Figure 7: Distribution of values for the ratio of dosimetric model based dose estimates to conversion convention based estimates for two sites in the Jenolan Caves for the year

19 Radon in the Living Environment, Normal :48 Gaussian Fit Mean 1.18 Temple of Baal Jenolan Katie's Bower Jenolan 1996 SD 0.19 Gaussian Fit Nu m be r n Number in Range Mean SD Dose Rate Ratio (Method #3 / Method #4) Dose Rate Ratio (Method #3 / Method #4) Figure 8: Distribution of values for the ratio of dosimetric model based dose estimates using size weighted dose conversion factors to estimates based a single radon conversion factor (5.5 µsv h -1 per kbq m -3 ) for two sites in the Jenolan Caves for the year

20 062 Radon in the Living Environment, 566