Table 2. am c a —_ Quantity of Pu Inhaled per Day to Result in 0.5 rems/yr after 70 Years (pCi) =z) “ ay oO OO Or <t ct OO CO WO OO MO more Soil and Smatl Particle Limits oO 8 Fr © No Sampling Depth at Me + Oe Nr OOO se Ke Fe Pe ~ — OO . 8 Oo 2 cm 1 — 5 sc o aa) aw _ wu at w mo o moioenm~ -_ 8 oOo 2 ~ wWwwnwMm ~~ mM . oo wo wm 8 oOo ww Ww 8 fo ri Small Particles Limit for Small Particles pci/g Limit for Total Soil p/Cig 1 10 30 1 75,000 7,500 2,500 15,000 750 750 750 150 30 500 150 10 1,500 150 *Air Conc. pg/m3 100 1,000 3,000 500 5,000 15,000 *During disturbance As can be seen, the limiting value in the soil changes with the amount of fines while the total soil value remains the same. This is the result of our assumption of a constant resuspension factor under al? conditions of the soil. mo ee 3 — N TM Oo MO . tt vidi mw oO erFnmren RK KN uw w ew fee vu a w al i >| tro Oo ’ woo —- mM —- * NSN © ot wom Ww WS OEY OO _ >|o oO : NI Ot ‘os : a — w 4 Ww In fact, the concentration in the air is a result of both the activity on the air-borne soil and the concentration of air-borne soil in the air. Data are not available to indicate whether the dust concentration in the air is a direct function of the fractions of small particles in the soil under different stimuli for resuspension. When one considers the extremes of this case, a clay bank of all small particles or a soil conststing of sand with only a few small particles, the hypothesis appears questionable. However, only detailed experimental data, not assumptions, will clarify the relationship. Let me finally give a few thoughts on models and modeling. The biggest problem in applying any model, particularly a complex one, is in obtain- Cc Oo nei nor . Dre KE O™~ WN NN mM FT CO se te Ww —__-4 ing estimates of the proper parameters. These cannot rely only on one set of experiments, even if done in an area of interest, but must include consideration of as much of the published data as possible. This jeads me to the conclusion that modeling is not a simple mathematical exercise in which others supply numbers for given phases of the problem. The modeter must be knowledgeable about the information he is using and apply it with full knowledge of its strengths and weaknesses. To me, a strict requirement in any modeling exercise should be a justification of any parameter or assumption in sufficient detail so that the reader can understand both the strengths and the weaknesses of each number. vo Table 1. —s > | 0 ayj;u; >p~ |---| oaghol Wi 7a _ eo, tT NSN o - » . oO a a << = « vle - Nw Ww soo valjalo09ognaqorenwnodc w nSw oe Ww dd WH In any modeling exercise, there are many unknowns or poorly-krowns, An important function of the exercise is to define these items and to identify those of critical] importance so that they may be investigated. Again the approach should be one of increased knowledge about the subject and not a simple search for a number. Such numbers are normally widely variable and the modeler can select one suitable to his purposes only on basis of complete knowledge of the information available and the field in which he is working. 219 218