United States
    Environmental Protection
    Agency

    Research and Development
  Air and Energy Engineering
  Research  Laboratory
  Research Triangle Park, NC 27711
                                       EP/V600/SR-94/218
   Project Summary

   Soil  Radon  Potential  Mapping  of
   Twelve  Counties  in  North-Central
   Florida
  Kirk K. Nielson, Rodger B. Holt, and Vern C. Rogers
    This report describes the approach
  methods, and detailed data used to pre-
  pare soil radon potential maps of twelve
  counties in North-Central Florida. The
  maps were developed under the Florida
  Radon Research Program to provide a
  scientific  basis  for  implementing
  radon-protective building construction
  standards in areas of elevated risk and
  avoiding unnecessary regulations  in
  areas of low radon risk.
   Calculated soil radon potentials re-
  flect geographic variations by model-
  ing the potentials as the rate of radon
  entry  into a reference house that  Is
  successively modeled on the soils  in
  each radon map region. Individual soil
  profile properties are defined by hori-
 zon from county soil survey data  Ra-
 don source properties are defined from
 aeroradiometric data and from soil ra-
 dium and radon emanation measure-
 ments. Calculated rates of radon entry
 into the reference house are grouped
 into tiers for display on radon potential
 maps.  Comparison of the  calculated
 radon  entry rates with indoor radon
 data yields a geometric standard  de-
 viation of 2.1  and  indicates that  the
 reference house is consistent with the
 aggregate properties of the  Florida
 houses in the comparison.
  This Project Summary was developed
 by EPA's Air and Energy Engineering
 Research  Laboratory,  Research Tri-
 angle Park, NC, to announce key find-
 ings of the research project that is fully
 documented in a separate report of the
same title (see Project Report ordering
Information at back).
 Introduction
   Soil radon potential maps are being de-
 veloped for Alachua, Citrus, Clay, Duval
 Flagler, Lake, Levy,  Marion, Nassau'
 Putnam, St. Johns, and Volusia counties
 in Florida. They are designed to show
 from soil and geological features the ar-
 eas  that have  different levels of radon
 potential. The maps are being developed
 under the Florida Radon Research Pro-
 gram to provide a scientific basis for imple-
 menting radon-protective building construc-
 tion standards where they are needed and
 to avoid the cost of  unnecessary imple-
 mentation where they are not needed.
  Soil radon potentials are defined  for
 mapping purposes  as the  calculated
 annual-average  rate of radon entry from
 soils  into a  reference  house.  They are
 calculated to represent geographic radon
 sourcia distributions, minimizing the influ-
 ences of house  and occupant variations
temporal variations, and political and insti-
tutional boundaries (city, county, etc.). The
mapping approach consists of

     Definition  of radon map  polygons
     (geographic areas on a radon map)
     from existing soil and  geologic
     maps.

     Definition of the soil profiles asso-
     ciated with each radon map poly-
     gon and their associated radon gen-
     eration  and transport properties.
     Calculation of numeric soil radon
     potentials for individual soil profiles
     and an area-weighted average to
     represent each radon map polygon.
a.
b.
c.
                                                  Printed on Recycled Paper

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  d   Grouping map units with similar ra-
      don potentials and plotting the ra-
      don map polygons by color-coded
      radon potential tiers.
  Radon map polygons  ^redefined by
tho digital intersection of STATSGO soil
map units with digitized surface-geology
map units. The intersections to def.ne the
polygons were performed with a  geo-
maphic information system under Arclnfo
format at the University d Florida GeoPlan
Center. The STATSGO soil maps defined
29 units in Alachua County, 13 in Citrus
County, 14 in Clay and Duval counties, 13
in Flagler County, 16 in Lake County. 21
in Levy County,  20 in Marion County, 11
in Nassau County, 20 in Putnam County,
 18 in St. Johns County, and 21  in Volus.a
 County. The map units occurred in mul-
 tiple polygon areas in each county, rang-
 ing from about 40 to 120 polygons per
 county. When intersected by geology poly-
 gons, the number of map polygons was
  approximately doubled.
    Soil profiles in each polygon were de-
  fined from county soil sunwdate comi-
  piled at the University of Florida Soil and
  Water Science  Department for each hori-
  zon in each of several profiles. The data
  included horizon depth and thickness, den-
  sity, textural analyses and classifications,
  water drainage characteristics, high water
  table depths and  durations, and  related
  physical properties.
   Radon Entry Modeling
     Soil radon potentials were defined to
   eliminate house and  occupant  variables
   by using a hypothetical "reference house
   with invariant properties, including indoor
   pressure, ventilation rate, slab and foun-
   dation design  and attributes, and other
   reference conditions. The reference house
   was modeled as if it were located on each
   of the soil profiles that made up the  land
   areas of each  map polygon to reflect the
   average differences and variabilities in ra-
   don potential between and within the map
   polygons. The annual-average rates of ra-
   don  entry into the reference house  were
   modeled using complete, multiphase ra-
   don generation and transport  equations.
   They characterize indoor radon  entry by
   both diffusion (concentration-driven) and
   advection (with pressure-driven air flow).
      The  soil radon entry modeling for the
    reference house  utilized detailed soil pro-
    file  data defined by county soil survey
    analyses and surface geology data. The
    detailed soil profiles analyzed with the ref-
    erence house for each location included
    individual radon source and transport prop-
    erties of each soil horizon. The reference
    housa was defined with the approximate
characteristics of Florida  slab-on-grade
single-family dwellings. It consisted of an
8 6 x 16.5m rectangular structure with a
perimeter shrinkage  crack between the
floating floor slab and the stem walls. The
indoor pressure, house ventilation rate.
floor slab properties, and other house char-
acteristics were  based on typical values
measured in Florida houses. The radon
entry modeling represented soil moisture
profiles under the reference house by an
annualized  distribution that was  defined
from the reported high water table depths
 and durations.
   Since the map calculations  utilized a
 fixed set of house and foundation charac-
 teristics and considered only vertical varia-
 tions in radon source and transport prop-
 ertiesMhe 2-dimensionaURAdon-Emana--
 tion  and  TRansport  into  Dwellings
  (RAETRAD) model was used to develop
  a more efficient, 1-dimensional algorithm
  that gave equivalent results for the refer-
  ence house. The specialized radon poten-
  tial cartography algorithm  was named
  RnMAP and was shown to approximate
  the reference-house RAETRAD  analyses
  within about 5%. Most  of this difference
  resulted from  the finite-difference math-
  ematics in RAETRAD compared to ana-
  lytical radon calculations in RnMAP. The
  1 -dimensional  radon generation and trans-
  port calculations in RnMAP  define  the
  sub-slab radon concentration, from which
   radon entry rates are computed with em-
   pirical functions for radon diffusion through
   the intact floor slab and for diffusive and
   advective transport through floor cracks.
   The  empirical functions, fitted  to the
   sub-slab  soil  properties, also define the
   coupling  of the  soil  region to  the
   reference-house slab properties based on
   corresponding RAETRAD calculations.
   Radon Source and Transport
   Parameters                   ,
      Radon potentials of each map polygon
   were calculated from  the radon source
   and transport properties of the  soil pro-
   files comprising the polygon  region.  Ra-
   don source properties were estimated from
    National Uranium  Resource  Evaluation
    (NURE) aeroradiometric data for shallow
    horizons (0 to 2 or 2.5m). and from geo-
    logical classifications of the soils for deep
    horizons (to 5m depth). The NURE data
    were  averaged [to obtain  a geometric
    mean  and  geometric  standard  deviation
    (GSD)1 for  each polygon from data in an
    flight-line segments within the polygon, and
    were  converted from  equivalent uranium
    concentrations to corresponding radium
    concentrations for the model calcutalions.
     Polygons not intersected by NURE flight
lines were represented by the geometric
mean and GSD of all NURE data for their
geological classification in the county. The
NURE flight-line data were partitioned digi-
tally into map polygon segments with the
same geographic information system used
to define the map polygons.
   Radon amanation coefficients for each
of the NURE-based radium concentrations
were defined from a measured trend of
increasing emanation with radium concen-
tration. The   trend  had  the  form
 E » 0 15Ra + 0.20 for radium levels below
 23 pCi g-1 and  remained constant at
 0 50-0.55 for higher radium levels. The
 trend was based on emanation measure-
 ments  from over 200 samples from the
 twelve counties. Most of the samples were
 from University of Florida soil-survey ar,
 chives and corresponded to the soils used
 to develop the  STATSGO soil  maps The
 remainder were from U.S. Geological Sur-
 vey borings. To attain adequate precision
 at low radium  concentrations, the radon
 emanation measurements utilized a new
  effluent technique that  is described and
  validated  in the full report.
    Deep-soil  radium concentrations were
  defined from surface geology classifica-
  tions and radium measurements in a larger
  qroup of over 600 soil samples. These
  included the samples used for emanation
   measurements plus additional  samples
   from the same sources.
     Radon  transport properties were  esti-
   mated from soil profile physical data com-
   piled for  each STATSGO soil map unit.
   The radon transport properties (radon dif-
   fusion coefficients and air permeabilities)
   were calculated from empirical correlations
   with  soil  horizon water contents, porosi-
   ties,  and  particle sizes. Soil horizon water
   contents  were calculated from their height
   above the water table using soil water
   drainage data. Steady-state water balance
   calculations indicated that for water tabes -
    in the 5m or shallower range, sub-slab
    soil water contents were well-approximated
    by the soil drainage-curve moisture at a
    matric potential that was equal to the dis-
    tance above  the water table. Water drain-
    aqe data compiled for each soil horizon in
    each soil profile therefore  were directly
    interpolated from the horizon-to-water-tab e
    distance to estimate soil moistures  Field
    measurements of near-surface soil water
    matric potentials at 46 locations in Central
    Florida confirmed the range of matric po-
    tentials  being used.
     Calculation of Soil Radon
     Potentials
       Soil radon potentials were computed Dy
     mathematically  modeling the reference

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 house as  if it were located on each soil
 profile of  each  of the radon map poly-
 gons. The RnMAP calculations used the
 specific radon source and radon transport
 properties of  the horizons in  each  soil
 profile. The radon potentials were calcu-
 lated as the rate of radon entry  into the
 reference house in annual units (mCi y1)
 to emphasize the long-term average na-
 ture of the radon potential estimates.
   Radon  potentials were  calculated for
 each of several soil profiles in each poly-
 gon,  at each  of  two  or three seasonal
 water table depths. They then were aver-
 aged seasonally to obtain annual-average
 radon potentials, which in turn were aver-
 aged over the different profiles to repre-
 sent each polygon. Radon potentials also
 were  calculated  for both  low-  and
 high-radium geology,  and the applicable
 geologic classification was used afterward
 to select the appropriate values to repre-
 sent each polygon.
  Separate radon  potentials were calcu-
 lated for the estimated median of the dis-
tribution in  each polygon and also for ra-
don potentials corresponding to the 75,
90, and 95% confidence limits. The confi-
dence limits were based on the geometric
means and GSDs  of  radium  computed
from the NURE data distributions in each
polygon and also on the varied properties
 of the different soil profiles that comprised
 the polygon.

 Production and Interpretation
 of the Radon Maps
   The resulting radon potentials were par-
 titioned into seven tiers of similar numeri-
 cal values for display on the radon poten-
 tial maps. The tiers corresponded to the
 <0.4, 0.4-1, 1-2,  2-3, 3-6, 6-12.  and >12
 mCi y1 levels of  radon potential. This set
 of tiers provided suitable ranges for using
 a uniform tier scale on all  of the radon
 potential  maps. Map polygons were col-
 ored according to the appropriate tier clas-
 sification for intuitive visual interpretation.
 However  the numerical values of the ra-
 don potentials for each map polygon are
 presented in the report for more quantita-
 tive map interpretations. A radon potential
 of 3 mCi y1 corresponds to approximately
 3.9 pCi L1 in the  reference house.
  Separate maps were plotted for the me-
 dian, 75, 90, and 95% confidence limits of
 radon potentials to give a better perspec-
tive of radon potentials  in a given polygon
 (region).  Regions with  low potentials on
both the median and higher-confidence-limit
maps exhibit reasonable assurance of hav-
ing minimal indoor radon risk. Regions with
high radon potentials on the median and
higher-confidence-limit  maps conversely
have a relatively high  probability  of el-
 evated indoor radon levels. Regions with
 low median radon potentials but high pd-
 tentials  for higher confidence limits  are
 heterogeneous (low  median; high  GSD)
 arid may have generally low radon poten-
 tials but occasional to frequent anomalies
 with high radon potential. Special consid-
 erations  may be  needed  to define
 radon-protective building needs in  these
 areas.
   The calculated soil radon potentials ware
 compared with 804  indoor radon  mea-
 surements in the twelve counties from the
 state-wide land-based radon  survey. The
 comparison was consistent with the
 reference-house indoor radon accumula-
 tion rate of 1.3 pCi L1 per mCi y1 of soil
 radon  potential and with an ambient out-
 door radon concentration of approximately
 0.3 pCi L-'. The GSD between measured
 indoor radon levels and those predicted
 from the maps was  2.08, which  is the
 approximate level of precision associated
 with the  calculated soil  radon potentials.
 The total variation among measured in-
 door radon levels was partitioned to esti-
 mate a house variability of GSD=3.7, com-
 pared  to  soil variability on the order of
 GSD=2.2 to 2.4. Uncertainties are much
 higher  in predicting an indoor radon level
for a particular house than for predicting
the median level in the reference house
for a given polygon.

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K Wfe/son, R Holt, and V. Rogers are with Rogers and Associates Engineering
  ' Corp., Salt Lake City, UT 84110-0330.



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